Namibia - Demographic and Health Survey - 2014

Publication date: 2014

Namibia 2013Demographic and Health Survey N am ibia 2013 D em ographic and H ealth Survey REPUBLIC OF NAMIBIA Namibia Demographic and Health Survey 2013 Ministry of Health and Social Services Windhoek, Namibia Namibia Statistics Agency Windhoek, Namibia September 2014 This report summarizes the findings of the 2013 Nambia Demographic and Health Survey (NDHS) implemented by the Ministry of Health and Social Services (MoHSS) in collaboration with the Namibia Statistics Agency (NSA) and the National Institute of Pathology (NIP). Technical support was provided by ICF International with financial support from the Government of Namibia, the United States Agency for International Development (USAID), and the Global Fund (GFATM). Information about the 2013 NDHS may be obtained from the Ministry of Health and Social Services (MoHSS), Private Bag 13198, Windhoek, Namibia; Telephone: (264-61) 203-2500/2; Fax: (264-61) 222-558; Email: pro@mhss.gov.na; Internet: www.mhss.gov.na. Information about The DHS Program may be obtained from ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850-5971, USA; Telephone: +1-301-407-6500; Fax: +1-301-407-6501; Email: reports@DHSprogram.com; Internet: www.DHSprogram.com. Cover photo: “Sunset behind a baobab.” ©2006 Ian Beatty [www.flickr.com/photos/ibeatty/351180675/in/set- 72157594468704452]. Used under Creative Commons license. Suggested citation: The Nambia Ministry of Health and Social Services (MoHSS) and ICF International. 2014. The Namibia Demographic and Health Survey 2013. Windhoek, Namibia, and Rockville, Maryland, USA: MoHSS and ICF International. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xvii MILLENNIUM DEVELOPMENT GOAL INDICATORS . xix MAP OF NAMIBIA . xx 1 INTRODUCTION . 1 1.1 Geography, History, and Economy . 1 1.1.1 Geography . 1 1.1.2 History . 1 1.1.3 Economy . 2 1.2 Population . 2 1.3 Health Services and Programmes . 3 1.4 Survey Objectives . 4 1.5 Organisation of the Survey . 4 1.6 Survey Implementation. 4 1.6.1 Sample Design . 4 1.6.2 Questionnaires . 5 1.6.3 Anaemia and HIV Testing . 6 1.6.4 Blood Glucose and Blood Pressure Testing . 7 1.6.5 Pretest. 8 1.6.6 Household Listing . 8 1.6.7 Training of Field Staff . 8 1.6.8 Data Collection . 8 1.6.9 Data Processing . 9 1.7 Response Rates . 9 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 11 2.1 Household Characteristics . 11 2.1.1 Drinking Water . 11 2.1.2 Sanitation Facilities and Waste Disposal . 13 2.1.3 Housing Characteristics . 14 2.1.4 Household Possessions . 15 2.2 Household Wealth . 16 2.3 Hand Washing . 17 2.4 Household Population by Age, Sex, and Residence . 18 2.5 Household Composition . 20 2.6 Birth Registration . 20 2.7 Children’s Living Arrangements and Parental Survival . 21 2.8 Education of the Household Population . 22 2.8.1 Educational Attainment . 22 2.8.2 School Attendance Ratios . 24 2.9 Utilisation of Health Services and Out-of-Pocket Expenditure for Health Care . 26 3 CHARACTERISTICS OF SURVEY RESPONDENTS . 29 3.1 Characteristics of Survey Respondents . 29 3.2 Educational Attainment by Background Characteristics . 31 3.3 Literacy . 33 iv • Contents 3.4 Exposure to Mass Media . 35 3.5 Employment . 37 3.5.1 Employment Status . 37 3.5.2 Occupation . 40 3.5.3 Earnings, Employers, and Continuity of Employment for Women . 42 4 MARRIAGE AND SEXUAL ACTIVITY . 45 4.1 Marital Status . 45 4.2 Polygyny . 46 4.3 Age at First Marriage . 48 4.4 Age at First Sexual Intercourse . 49 4.5 Recent Sexual Activity . 51 5 FERTILITY . 55 5.1 Current Fertility . 55 5.2 Fertility by Background Characteristics . 56 5.3 Fertility Trends . 57 5.4 Children Ever Born and Living . 58 5.5 Birth Intervals . 59 5.6 Postpartum Amenorrhoea, Abstinence, and Insusceptibility . 60 5.7 Median Duration of Postpartum Insusceptibility by Background Characteristics . 61 5.8 Menopause . 62 5.9 Age at First Birth . 62 5.10 Median Age at First Birth by Background Characteristics . 63 5.11 Teenage Pregnancy and Motherhood . 63 6 FERTILITY PREFERENCES . 65 6.1 Fertility Preferences by Number of Living Children . 65 6.2 Desire to Limit Childbearing by Background Characteristics . 66 6.3 Ideal Number of Children . 67 6.4 Mean Ideal Number of Children by Background Characteristics . 69 6.5 Fertility Planning Status . 69 6.6 Wanted Fertility Rates . 70 7 FAMILY PLANNING . 71 7.1 Knowledge of Contraceptive Methods . 71 7.2 Current Use of Contraception . 72 7.3 Current Use of Contraception by Background Characteristics . 74 7.4 Source of Modern Contraceptive Methods . 76 7.5 Informed Choice . 77 7.6 Rates of Discontinuing Contraceptive Methods . 78 7.7 Reasons for Discontinuing Contraceptive Methods . 79 7.8 Knowledge of the Fertile Period . 80 7.9 Need and Demand for Family Planning . 80 7.10 Future Use of Contraception . 82 7.11 Exposure to Family Planning Messages in the Media . 82 7.12 Contact of Nonusers with Family Planning Providers . 83 8 INFANT AND CHILD MORTALITY . 85 8.1 Background and Assessment of Data Quality . 85 8.2 Infant and Child Mortality Levels and Trends . 87 8.3 Socioeconomic Differentials in Early Childhood Mortality . 88 8.4 Demographic Differentials in Early Childhood Mortality . 89 Contents • v 8.5 Perinatal Mortality . 90 8.6 High-Risk Fertility Behaviour . 91 9 ADULT AND MATERNAL MORTALITY . 93 9.1 Assessment of Data Quality . 94 9.2 Estimates of Adult Mortality . 95 9.3 Estimates of Maternal Mortality . 95 10 MATERNAL HEALTH CARE . 99 10.1 Antenatal Care . 100 10.2 Number and Timing of Antenatal Care Visits . 101 10.3 Components of Antenatal care . 102 10.4 Tetanus Toxoid . 104 10.5 Place of Delivery . 104 10.6 Assistance during Delivery . 106 10.7 Postnatal Care . 108 10.7.1 Postnatal Checkup for the Mother . 108 10.7.2 Postnatal Care for the Newborn . 111 10.8 Problems in Accessing Health Care . 113 11 CHILD HEALTH . 115 11.1 Child’s Weight and Size at Birth . 115 11.2 Vaccination of Children . 117 11.2.1 Sources of Information . 117 11.2.2 Vaccination Coverage . 117 11.2.3 Trends in Vaccination Coverage . 119 11.3 Prevalence and Treatment of Acute Respiratory Infection . 120 11.4 Prevalence and Treatment of Fever . 120 11.5 Diarrhoeal Disease . 122 11.5.1 Prevalence of Diarrhoea . 122 11.5.2 Treatment of Diarrhoea . 122 11.5.3 Feeding Practices during Diarrhoea . 124 11.6 Knowledge of ORS Packets . 124 11.7 Disposal of Children’s Stools . 126 12 NUTRITION OF CHILDREN AND ADULTS . 129 12.1 Nutritional Status of Children . 130 12.1.1 Measurement of Nutritional Status among Young Children . 130 12.1.2 Data Collection . 131 12.1.3 Levels of Child Malnutrition . 131 12.1.4 Trends in Child Malnutrition . 133 12.2 Initiation of Breastfeeding . 134 12.3 Breastfeeding Status by Age . 135 12.4 Duration of Breastfeeding . 138 12.5 Types of Complementary Foods . 138 12.6 Infant and Young Child Feeding Practices . 139 12.7 Prevalence of Anaemia in Children . 142 12.8 Micronutrient Intake and Supplementation among Children . 143 12.9 Presence of Iodised Salt in Households . 146 12.10 Adult Nutritional Status . 146 12.10.1 Nutritional Status of Women . 146 12.10.2 Nutritional Status of Men . 148 12.10.3 Anaemia in Women . 149 12.10.4 Anaemia in Men . 150 12.11 Micronutrient Intake among Mothers . 150 vi • Contents 13 MALARIA . 153 13.1 Ownership of Mosquito Nets . 153 13.2 Indoor Residual Spraying . 156 13.3 Access to an Insecticide-Treated Net . 157 13.4 Use of Mosquito Nets . 158 13.4.1 Use of Mosquito Nets by Persons in the Household . 158 13.4.2 Use of Existing Mosquito Nets . 160 13.4.3 Use of Mosquito Nets by Children under Age 5 . 160 13.4.4 Use of Mosquito Nets by Pregnant Women . 161 13.5 Use of Intermittent Preventive Treatment of Malaria During Pregnancy . 163 13.6 Prevalence, Diagnosis, and Prompt Treatment of Children with Fever . 163 13.7 Prevalence of Low Haemoglobin in Children . 166 14 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 169 14.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 170 14.1.1 Knowledge of AIDS . 170 14.1.2 Knowledge of HIV Prevention . 171 14.1.3 Comprehensive Knowledge about HIV/AIDS . 173 14.2 Knowledge about Mother-to-Child Transmission . 176 14.3 Attitudes toward People Living with HIV/AIDS . 178 14.4 Attitudes toward Negotiating Safer Sexual Relations with Husbands . 180 14.5 Attitudes toward Condom Education for Young People . 182 14.6 Higher-Risk Sex . 183 14.6.1 Multiple Sexual Partners . 183 14.6.2 Point Prevalence and Cumulative Prevalence of Concurrent Sexual Partners . 186 14.7 Paid Sex . 187 14.8 Male Circumcision . 189 14.9 Self-Reporting of Sexually Transmitted Infections . 192 14.10 Injections . 193 14.11 HIV/AIDS-Related Knowledge and Behaviour among Young People . 195 14.11.1 Knowledge about HIV/AIDS and Source for Condoms . 195 14.11.2 First Sex . 196 14.11.3 Premarital Sex . 198 14.11.4 Multiple Sexual Partners among Youth . 199 14.11.5 Age Mixing in Sexual Relationships . 201 15 HIV PREVALENCE . 203 15.1 Participation Rates for HIV Testing . 204 15.2 HIV Prevalence . 208 15.2.1 HIV Prevalence by Age . 208 15.2.2 HIV Prevalence by Socioeconomic Characteristics . 209 15.2.3 HIV Prevalence by Demographic and Health Characteristics . 211 15.2.4 HIV Prevalence by Sexual Risk Behaviour . 213 15.3 HIV Prevalence among Young People . 216 15.4 HIV Prevalence by Other Characteristics Related to HIV Risk . 217 15.5 HIV Prevalence among Couples . 219 16 SELF-REPORTED PRIOR HIV TESTING AND TREATMENT . 221 16.1 Coverage of HIV Testing Services . 221 16.2 HIV Testing among Youth . 224 16.3 Couple Counselling and Testing . 225 16.4 Place of Last HIV Test . 229 16.5 HIV Prevalence by Prior HIV Test Results . 229 Contents • vii 16.6 Self-Reported Use of Antiretroviral Medications (ARVs) . 232 16.7 HIV Testing during Pregnancy . 233 16.8 Early Infant Diagnosis . 235 17 BLOOD PRESSURE AND BLOOD GLUCOSE . 237 17.1 Coverage Rates for Blood Pressure and Blood Glucose Measurement . 237 17.2 High Blood Pressure . 238 17.2.1 History and Treatment of High Blood Pressure . 239 17.2.2 Prevalence of High Blood Pressure . 241 17.3 Diabetes . 247 17.3.1 History of Diabetes . 248 17.3.2 Prevalence and Treatment of Diabetes . 250 18 OTHER HEALTH ISSUES. 253 18.1 Knowledge of and Attitudes toward Tuberculosis . 253 18.2 Cancer Screening . 255 18.2.1 Breast Cancer and Cervical Cancer Screening . 255 18.2.2 Prostate Cancer Screening . 257 18.3 Use of Tobacco . 258 18.4 Alcohol Consumption . 261 18.5 Use of Seatbelts . 264 18.6 Physical Activity . 266 18.7 Consumption of Water, Fruits, and Vegetables . 269 18.8 Mental Health . 271 18.9 Health Insurance . 274 19 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 277 19.1 Women’s and Men’s Employment . 277 19.2 Women’s Control over Their Own Earnings and Relative Magnitude of Women’s Earnings . 278 19.3 Women’s Ownership of Assets . 282 19.4 Women’s and Men’s Participation in Decision Making . 284 19.5 Attitudes toward Wife Beating . 288 19.6 Women’s Empowerment Indicators . 291 19.7 Current Use of Contraception by Women’s Empowerment . 291 19.8 Ideal Family Size and Unmet Need by Women’s Empowerment . 292 19.9 Women’s Empowerment and Reproductive Health Care . 293 20 DOMESTIC VIOLENCE . 295 20.1 Valid Measures of Domestic Violence . 295 20.1.1 Use of Valid Measures of Violence . 295 20.1.2 Ethical Considerations for the Domestic Violence Module in the 2013 NDHS . 296 20.1.3 Subsample for the Violence Module . 297 20.2 Experience of Physical Violence . 297 20.3 Perpetrators of Physical Violence . 299 20.4 Experience of Sexual Violence . 299 20.5 Perpetrators of Sexual Violence . 301 20.6 Experience of Different Forms of Violence . 301 20.7 Violence during Pregnancy . 302 20.8 Marital Control by Husband . 303 20.9 Forms of Spousal Violence . 305 20.10 Spousal Violence by Background Characteristics . 306 viii • Contents 20.11 Violence by Spousal Characteristics and Women’s Empowerment Indicators . 308 20.12 Recent Spousal Violence . 310 20.13 Onset of Spousal Violence . 310 20.14 Physical Consequences of Spousal Violence . 311 20.15 Women’s Violence Against Their Husbands . 312 20.16 Help-Seeking Behaviour by Women Who Experience Violence . 315 20.17 Sources of Help to Stop Violence . 316 REFERENCES . 317 APPENDIX A SAMPLE SELECTION . 323 A.1 Introduction . 323 A.2 Sampling Frame . 323 A.3 Sampling Procedure and Sample Allocation . 324 A.4 Sampling Probabilities . 326 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 335 APPENDIX C DATA QUALITY TABLES . 355 APPENDIX D PARTICIPANTS IN THE 2013 NAMIBIA DEMOGRAPHIC AND HEALTH SURVEY . 361 APPENDIX E QUESTIONNAIRES . 367 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION . 1 Table 1.1 Basic demographic indicators, Namibia 1991, 2001, and 2011 . 2 Table 1.2 Results of the household and individual interviews . 9 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 11 Table 2.1 Household drinking water . 12 Table 2.2 Household sanitation facilities . 13 Table 2.3 Household characteristics . 14 Table 2.4 Household possessions . 15 Table 2.5 Wealth quintiles . 17 Table 2.6 Hand washing . 18 Table 2.7 Household population by age, sex, and residence . 19 Table 2.8 Household composition . 20 Table 2.9 Birth registration of children under age 5 . 21 Table 2.10 Children’s living arrangements and orphanhood . 22 Table 2.11.1 Educational attainment of the female household population . 23 Table 2.11.2 Educational attainment of the male household population . 24 Table 2.12 School attendance ratios . 25 Table 2.13.1 Health expenditure: Inpatient visits . 27 Table 2.13.2 Health expenditure: Outpatient visits . 28 Figure 2.1 Population pyramid . 19 Figure 2.2 Age-specific attendance rates . 26 3 CHARACTERISTICS OF SURVEY RESPONDENTS . 29 Table 3.1 Background characteristics of respondents . 30 Table 3.2.1 Educational attainment: Women . 32 Table 3.2.2 Educational attainment: Men . 33 Table 3.3.1 Literacy: Women . 34 Table 3.3.2 Literacy: Men . 35 Table 3.4.1 Exposure to mass media: Women . 36 Table 3.4.2 Exposure to mass media: Men . 37 Table 3.5.1 Employment status: Women . 38 Table 3.5.2 Employment status: Men . 39 Table 3.6.1 Occupation: Women . 41 Table 3.6.2 Occupation: Men . 42 Table 3.7 Type of employment . 43 Figure 3.1 Women’s employment status in the past 12 months . 40 4 MARRIAGE AND SEXUAL ACTIVITY . 45 Table 4.1 Current marital status . 46 Table 4.2.1 Number of women’s co-wives . 47 Table 4.2.2 Number of men’s wives . 48 Table 4.3 Age at first marriage . 49 Table 4.4 Age at first sexual intercourse . 50 Table 4.5 Median age at first sexual intercourse by background characteristics . 50 x • Tables and Figures Table 4.6.1 Recent sexual activity: Women . 51 Table 4.6.2 Recent sexual activity: Men . 53 5 FERTILITY . 55 Table 5.1 Current fertility . 55 Table 5.2 Fertility by background characteristics . 56 Table 5.3.1 Trends in age-specific fertility rates . 57 Table 5.3.2 Trends in fertility . 57 Table 5.4 Children ever born and living . 58 Table 5.5 Birth intervals . 59 Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility . 60 Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 61 Table 5.8 Menopause . 62 Table 5.9 Age at first birth . 62 Table 5.10 Median age at first birth . 63 Table 5.11 Teenage pregnancy and motherhood . 64 Figure 5.1 Trends in fertility . 58 6 FERTILITY PREFERENCES . 65 Table 6.1 Fertility preferences by number of living children . 66 Table 6.2 Desire to limit childbearing: Women . 67 Table 6.3 Ideal number of children by number of living children . 68 Table 6.4 Mean ideal number of children . 69 Table 6.5 Fertility planning status . 70 Table 6.6 Wanted fertility rates . 70 7 FAMILY PLANNING . 71 Table 7.1 Knowledge of contraceptive methods . 72 Table 7.2.1 Current use of contraception by age . 73 Table 7.2.2 Current use of contraception by background characteristics . 75 Table 7.3 Trends in contraceptive use . 76 Table 7.4 Source of modern contraception methods . 77 Table 7.5 Informed choice . 78 Table 7.6 Twelve-month contraceptive discontinuation rates . 79 Table 7.7 Reasons for discontinuation . 79 Table 7.8 Need and demand for family planning for all women . 81 Table 7.9 Future use of contraception . 82 Table 7.10 Exposure to family planning messages . 83 Table 7.11 Contact of nonusers with family planning providers . 84 Figure 7.1 Trends in contraceptive use among all women age 15-49, Namibia 1992-2013 . 76 8 INFANT AND CHILD MORTALITY . 85 Table 8.1 Early childhood mortality rates . 87 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 88 Table 8.3 Early childhood mortality rates by demographic characteristics . 89 Table 8.4 Perinatal mortality . 91 Table 8.5 High-risk fertility behaviour . 92 Figure 8.1 Trends in childhood mortality, 1987-2012 . 88 Tables and Figures • xi 9 ADULT AND MATERNAL MORTALITY . 93 Table 9.1 Adult mortality rates . 95 Table 9.2 Adult mortality probabilities . 95 Table 9.3 Maternal mortality . 96 Figure 9.1 Maternal mortality ratios with confidence intervals for the 10 years preceding the 1992, 2000, 2006-07, and 2013 NDHS surveys (per 100,000 live births) . 97 10 MATERNAL HEALTH CARE . 99 Table 10.1 Antenatal care . 101 Table 10.2 Number of antenatal care visits and timing of first visit . 102 Table 10.3 Components of antenatal care . 103 Table 10.4 Tetanus toxoid injections . 104 Table 10.5 Place of delivery . 105 Table 10.6 Reasons for not delivering in a health facility . 106 Table 10.7 Assistance during delivery . 107 Table 10.8 Timing of first postnatal checkup . 109 Table 10.9 Type of provider of first postnatal checkup for the mother . 110 Table 10.10 Timing of first postnatal checkup for the newborn . 112 Table 10.11 Type of provider of first postnatal checkup for the newborn . 113 Table 10.12 Problems in accessing health care . 114 Figure 10.1 Mother’s duration of stay in the health facility after giving birth . 111 11 CHILD HEALTH . 115 Table 11.1 Child’s size and weight at birth. 116 Table 11.2 Vaccinations by source of information . 117 Table 11.3 Vaccinations by background characteristics . 118 Table 11.4 Vaccinations in first year of life . 119 Table 11.5 Prevalence and treatment of symptoms of ARI . 120 Table 11.6 Prevalence and treatment of fever . 121 Table 11.7 Prevalence of diarrhoea . 122 Table 11.8 Diarrhoea treatment . 123 Table 11.9 Feeding practices during diarrhoea . 125 Table 11.10 Disposal of children’s stools . 126 Figure 11.1 Trends in vaccination coverage during the first year of life among children age 12-23 months . 119 12 NUTRITION OF CHILDREN AND ADULTS . 129 Table 12.1 Nutritional status of children . 132 Table 12.2 Initial breastfeeding . 135 Table 12.3 Breastfeeding status by age . 136 Table 12.4 Median duration of breastfeeding . 138 Table 12.5 Foods and liquids consumed by children in the day or night preceding the interview . 139 Table 12.6 Infant and young child feeding (IYCF) practices . 141 Table 12.7 Prevalence of anaemia in children . 143 Table 12.8 Micronutrient intake among children . 145 Table 12.9 Presence of iodised salt in household . 146 Table 12.10.1 Nutritional status of women . 147 Table 12.10.2 Nutritional status of men . 148 xii • Tables and Figures Table 12.11.1 Prevalence of anaemia in women . 149 Table 12.11.2 Prevalence of anaemia in men . 150 Table 12.12 Micronutrient intake among mothers . 151 Figure 12.1 Nutritional status of children by age . 133 Figure 12.2 Trends in nutritional status of children under age 5 by period . 134 Figure 12.3 Infant feeding practices by age . 137 Figure 12.4 IYCF indicators on breastfeeding status . 137 Figure 12.5 IYCF indicators on minimum acceptable diet . 142 13 MALARIA . 153 Table 13.1 Household possession of mosquito nets . 155 Table 13.2 Indoor residual spraying against mosquitoes . 156 Table 13.3 Access to an insecticide-treated net (ITN) . 157 Table 13.4 Use of mosquito nets by persons in the household . 159 Table 13.5 Use of existing ITNs . 160 Table 13.6 Use of mosquito nets by children . 161 Table 13.7 Use of mosquito nets by pregnant women . 162 Table 13.8 Use of Intermittent Preventive Treatment (IPTp) by women during pregnancy . 163 Table 13.9 Prevalence, diagnosis, and prompt treatment of children with fever . 165 Table 13.10 Source of advice or treatment for children with fever . 166 Table 13.11 Haemoglobin <8.0 g/dl in children . 167 Figure 13.1 Percentage of the de facto population with access to an ITN in the household . 158 Figure 13.2 Ownership, access, and use of ITNs . 160 14 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 169 Table 14.1 Knowledge of AIDS . 171 Table 14.2 Knowledge of HIV prevention methods . 172 Table 14.3.1 Comprehensive knowledge about AIDS: Women . 174 Table 14.3.2 Comprehensive knowledge about AIDS: Men . 175 Table 14.4 Knowledge of prevention of mother-to-child transmission of HIV . 177 Table 14.5.1 Accepting attitudes toward those living with HIV/AIDS: Women . 179 Table 14.5.2 Accepting attitudes toward those living with HIV/AIDS: Men . 180 Table 14.6 Attitudes toward negotiating safer sexual relations with husband . 181 Table 14.7 Adult support of education about condom use to prevent AIDS . 182 Table 14.8.1 Multiple sexual partners: Women . 184 Table 14.8.2 Multiple sexual partners: Men . 185 Table 14.9 Point prevalence and cumulative prevalence of concurrent sexual partners . 187 Table 14.10 Payment for sexual intercourse and condom use at last paid sexual intercourse . 188 Table 14.11 Male circumcision . 189 Table 14.12 Provider and place of circumcision . 189 Table 14.13 Attitudes toward male circumcision . 190 Table 14.14 Benefits of male circumcision . 191 Table 14.15 Specific benefits of male circumcision . 191 Table 14.16 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms . 192 Table 14.17 Prevalence of medical injections . 194 Table 14.18 Comprehensive knowledge about AIDS and of a source of condoms among youth . 196 Tables and Figures • xiii Table 14.19 Age at first sexual intercourse among young people . 197 Table 14.20 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 199 Table 14.21.1 Multiple sexual partners in the past 12 months among young people: Women . 200 Table 14.21.2 Multiple sexual partners in the past 12 months among young people: Men . 201 Table 14.22 Age mixing in sexual relationships among women and men age 15-19 . 202 Figure 14.1 Women and men seeking advice for treatment of STIs . 193 Figure 14.2 Trends in age at first sexual intercourse . 198 15 HIV PREVALENCE . 203 Table 15.1.1 Coverage of HIV testing by background characteristics: Respondents age 15-49 . 205 Table 15.1.2 Coverage of HIV testing by background characteristics: Respondents age 50-64 . 207 Table 15.2 HIV prevalence by age . 209 Table 15.3.1 HIV prevalence by socioeconomic characteristics: Respondents age 15-49 . 210 Table 15.3.2 HIV prevalence by socioeconomic characteristics: Respondents age 50-64 . 211 Table 15.4.1 HIV prevalence by demographic characteristics: Respondents age 15-49 . 212 Table 15.4.2 HIV prevalence by demographic characteristics: Respondents age 50-64 . 213 Table 15.5.1 HIV prevalence by sexual behaviour: Respondents age 15-49 . 214 Table 15.5.2 HIV prevalence by sexual behaviour: Respondents age 50-64 . 215 Table 15.6 HIV prevalence among young people by background characteristics . 216 Table 15.7 HIV prevalence among young people by sexual behaviour . 217 Table 15.8 HIV prevalence by other characteristics: Respondents age 15-64 . 218 Table 15.9 HIV prevalence by male circumcision . 219 Table 15.10 HIV prevalence among couples . 220 16 SELF-REPORTED PRIOR HIV TESTING AND TREATMENT . 221 Table 16.1.1 Coverage of prior HIV testing: Women . 223 Table 16.1.2 Coverage of prior HIV testing: Men . 224 Table 16.2 Recent HIV tests among youth . 225 Table 16.3.1 Couple counselling and testing . 227 Table 16.3.2 Consideration of couple counselling and testing in the future . 228 Table 16.4 Place of last HIV test . 229 Table 16.5.1 HIV prevalence by self-reported prior HIV testing: Respondents 15-49 . 230 Table 16.5.2 HIV prevalence by self-reported prior HIV testing: Respondents age 50-64 . 230 Table 16.6.1 Prior HIV testing by current HIV status: Respondents 15-49 . 231 Table 16.6.2 Prior HIV testing by current HIV status: Respondents 50-64 . 231 Table 16.7 Self-reported HIV status and ARV use: Women . 232 Table 16.8 Pregnant women counselled and tested for HIV . 234 Table 16.9 Early infant diagnosis . 235 Figure 16.1 Self-reported ARV use and HIV status among HIV-positive women age 15-64 . 233 17 BLOOD PRESSURE AND BLOOD GLUCOSE . 237 Table 17.1 Coverage of testing for blood pressure and fasting blood glucose measurement among women and men age 35-64 . 238 Table 17.2 History of hypertension . 240 Table 17.3 Actions taken or advice received to lower blood pressure . 241 xiv • Tables and Figures Table 17.4.1 Blood pressure status: Women . 243 Table 17.4.2 Blood pressure status: Men . 245 Table 17.5 History of diabetes . 249 Table 17.6 Actions taken or advice received to lower high blood glucose or diabetes . 250 Table 17.7.1 Prevalence of diabetes by background characteristics: Women . 251 Table 17.7.2 Prevalence of diabetes by socioeconomic characteristics: Men . 252 Figure 17.1 Awareness of high blood pressure and treatment status among women and men age 35-64 with high blood pressure. 247 18 OTHER HEALTH ISSUES. 253 Table 18.1.1 Knowledge of and attitudes concerning tuberculosis: Women . 254 Table 18.1.2 Knowledge of and attitudes concerning tuberculosis: Men . 255 Table 18.2 Breast cancer examination and cervical cancer examination or test . 257 Table 18.3 Knowledge of and testing for prostate cancer . 258 Table 18.4.1 Use of tobacco: Women . 259 Table 18.4.2 Use of tobacco: Men . 260 Table 18.5.1 Use of alcohol: Women . 262 Table 18.5.2 Use of alcohol: Men . 263 Table 18.6 Use of seatbelts . 265 Table 18.7.1 Physical activity: Women . 267 Table 18.7.2 Physical activity: Men . 268 Table 18.8.1 Consumption of water, fruits, and vegetables: Women . 270 Table 18.8.2 Consumption of water, fruits, and vegetables: Men . 271 Table 18.9.1 Mental health: Women . 272 Table 18.9.2 Mental health: Men . 273 Table 18.10.1 Health insurance coverage: Women . 275 Table 18.10.2 Health insurance coverage: Men . 276 19 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES . 277 Table 19.1 Employment and cash earnings of currently married women and men . 278 Table 19.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 279 Table 19.2.2 Control over men’s cash earnings . 281 Table 19.3 Women’s control over their own earnings and over those of their husbands . 282 Table 19.4.1 Ownership of assets: Women . 283 Table 19.4.2 Ownership of assets: Men . 284 Table 19.5 Participation in decision making . 285 Table 19.6.1 Women’s participation in decision making by background characteristics . 286 Table 19.6.2 Men’s participation in decision making by background characteristics . 288 Table 19.7.1 Attitude toward wife beating: Women . 289 Table 19.7.2 Attitude toward wife beating: Men . 290 Table 19.8 Indicators of women’s empowerment . 291 Table 19.9 Current use of contraception by women’s empowerment . 292 Table 19.10 Ideal number of children and unmet need for family planning by women’s empowerment . 293 Table 19.11 Reproductive health care by women’s empowerment . 293 Figure 19.1 Number of decisions in which currently married women participate, Namibia 2013 . 287 Tables and Figures • xv 20 DOMESTIC VIOLENCE . 295 Table 20.1 Experience of physical violence . 298 Table 20.2 Persons committing physical violence . 299 Table 20.3 Experience of sexual violence. 300 Table 20.4 Persons committing sexual violence . 301 Table 20.5 Experience of different forms of violence . 301 Table 20.6 Experience of violence during pregnancy . 302 Table 20.7 Marital control exercised by husbands . 304 Table 20.8 Forms of spousal violence . 305 Table 20.9 Spousal violence by background characteristics . 307 Table 20.10 Spousal violence by husband’s characteristics and empowerment indicators . 309 Table 20.11 Physical or sexual violence in the past 12 months by any husband/partner . 310 Table 20.12 Experience of spousal violence by duration of marriage . 311 Table 20.13 Injuries to women due to spousal violence . 311 Table 20.14 Women’s violence against their spouse . 313 Table 20.15 Women’s violence against their spouse by husband’s characteristics and empowerment indicators . 314 Table 20.16 Help seeking to stop violence . 315 Table 20.17 Sources of help to stop the violence . 316 APPENDIX A SAMPLE SELECTION . 323 Table A.1 Enumeration areas (EAs) and average EA size in the sampling frame . 324 Table A.2 Distribution of households in the sampling frame . 324 Table A.3 Sample allocation of clusters and households . 325 Table A.4 Sample allocation of expected number of interviews with women and men . 325 Table A.5 Sample implementation: Women . 328 Table A.6 Sample implementation: Men . 329 Table A.7 Coverage of HIV testing by social and demographic characteristics: Women . 330 Table A.8 Coverage of HIV testing by social and demographic characteristics: Men . 331 Table A.9 Coverage of HIV testing by sexual behaviour characteristics: Women . 332 Table A.10 Coverage of HIV testing by sexual behaviour characteristics: Men . 333 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 335 Table B.1 List of selected variables for sampling errors, Namibia 2013 . 337 Table B.2 Sampling errors: Total sample, Namibia 2013 . 338 Table B.3 Sampling errors: Urban sample, Namibia 2013 . 339 Table B.4 Sampling errors: Rural sample, Namibia 2013 . 340 Table B.5 Sampling errors: Zambezi sample, Namibia 2013 . 341 Table B.6 Sampling errors: Erongo sample, Namibia 2013 . 342 Table B.7 Sampling errors: Hardap sample, Namibia 2013 . 343 Table B.8 Sampling errors: //Karas sample, Namibia 2013 . 344 Table B.9 Sampling errors: Kavango sample, Namibia 2013 . 345 Table B.10 Sampling errors: Khomas sample, Namibia 2013 . 346 Table B.11 Sampling errors: Kunene sample, Namibia 2013 . 347 Table B.12 Sampling errors: Ohangwena sample, Namibia 2013 . 348 Table B.13 Sampling errors: Omaheke sample, Namibia 2013 . 349 Table B.14 Sampling errors: Omusati sample, Namibia 2013 . 350 Table B.15 Sampling errors: Oshana sample, Namibia 2013 . 351 Table B.16 Sampling errors: Oshikoto sample, Namibia 2013 . 352 Table B.17 Sampling errors: Otjozondjupa sample, Namibia 2013 . 353 Table B.18 Sampling errors for adult and maternal mortality rates, Namibia 2013 . 354 xvi • Tables and Figures APPENDIX C DATA QUALITY TABLES . 355 Table C.1 Household age distribution . 355 Table C.2.1 Age distribution of eligible and interviewed women . 356 Table C.2.2 Age distribution of eligible and interviewed men . 356 Table C.3 Completeness of reporting . 357 Table C.4 Births by calendar years . 357 Table C.5 Reporting of age at death in days . 358 Table C.6 Reporting of age at death in months . 358 Table C.7 Nutritional status of children based on the NCHS/CDC/WHO International Reference Population . 359 Table C.8 Completeness of information on siblings . 360 Table C.9 Sibship size and sex ratio of siblings . 360 Foreword • xvii FOREWORD he 2013 Namibia Demographic and Health Survey (NDHS) serves as a periodic update of the demographic and health situation in Namibia. This is the fourth comprehensive, national-level population and health survey conducted in Namibia as part of the global Demographic and Health Surveys (DHS) programme. The 2013 NDHS was implemented by the Ministry of Health and Social Services (MoHSS) in collaboration with the Namibia Statistics Agency (NSA) and the National Institute of Pathology (NIP). Technical support was provided by ICF International, with financial support from the Government of Namibia, the United States Agency for International Development (USAID), and the Global Fund. The study was initiated in April 2012, and data collection was carried out from May to September 2013. The overall objective of the survey was to provide demographic, socioeconomic, and health data necessary for policymaking, planning, monitoring, and evaluation at both the national and regional levels. The survey was designed to generate recent and reliable information on fertility, family planning, infant and child mortality, maternal and child health, nutrition, domestic violence, and knowledge and prevalence of HIV/AIDS and other noncommunicable diseases, which allows monitoring progress through time with respect to these issues. In addition, the survey measured the prevalence of anaemia, high blood pressure, and high blood glucose among adult women and men and the prevalence of anaemia among children age 6-59 months; it also collected anthropometric data to assess the nutritional status of women, men, and children. The information provided in this report will aid in assessments of current health- and population- related policies and programmes. It will also be useful in formulating new population and health policies and programmes. A long-term objective of the survey is to strengthen the technical capacity of local organisations to plan, conduct, process, and analyse data from complex national population and health surveys. Moreover, the 2013 NDHS is comparable to similar surveys conducted in other developing countries and therefore affords a national and international comparison. The 2013 NDHS adds to the vast and growing international database on demographic and health-related variables. The Ministry of Health and Social Services would like to extend its appreciation to all development partners for their input to the survey, to ICF International for providing technical support, and, most importantly, to the respondents who provided the information on which this report is based. ANDREW NDISHISHI PERMANENT SECRETARY T Millennium Development Goal Indicators • xix MILLENNIUM DEVELOPMENT GOAL INDICATORS Millennium Development Goal Indicators Namibia 2013 Sex Total Indicator Male Female 1. Eradicate extreme poverty and hunger 1.8 Prevalence of underweight children under age 5 15.3 11.4 13.3 2. Achieve universal primary education 2.1 Net attendance ratio in primary education1 89.5 90.8 90.1 2.3 Literacy rate of 15 to 24-year-olds2 92.8a 95.9 94.4b 3. Promote gender equality and empower women 3.1 Ratio of girls to boys in primary, secondary ,and tertiary education 3.1a Ratio of girls to boys in primary education3 na na 1.0 3.1b Ratio of girls to boys in secondary education3 na na 1.2 3.1c Ratio of girls to boys in tertiary education3 na na 1.5 4. Reduce child mortality 4.1 Under-5 mortality rate4 64 54 54 4.2 Infant mortality rate4 44 37 39 4.3 Proportion of 1-year-old children immunized against measles 91.4 87.8 89.5 5. Improve maternal health 5.1 Maternal mortality ratio5 na na 385 5.2 Percentage of births attended by skilled health personnel6 na na 88.2 5.3 Contraceptive prevalence rate7 na 56.1 na 5.4 Adolescent birth rate8 na 82.3 na 5.5a Antenatal care coverage: at least one visit9 na 73.6 na 5.5b Antenatal care coverage: four or more visits10 na 62.5 na 5.6 Unmet need for family planning na 17.5 na 6. Combat HIV/AIDS, malaria, and other diseases 6.2 Condom use at last high-risk sex11 82.0 67.5 74.7 6.3 Percentage of the population age 15-24 with comprehensive correct knowledge of HIV/AIDS12 51.1 61.6 56.3 6.4 Ratio of school attendance of orphans to school attendance of non-orphans age 10-14 1.02 1.01 1.02 6.7 Percentage of children under 5 sleeping under insecticide-treated bed nets 5.9 5.2 5.6 6.8 Percentage of children under 5 with fever who are treated with appropriate antimalarial drugs13 8.8 8.1 8.4 Urban Rural Total 7. Ensure environmental sustainability 7.8 Percentage of population using an improved drinking water source14 97.8 71.9 84.0 7.9 Percentage of population with access to improved sanitation15 53.2 16.7 33.8 na = Not applicable 1 The ratio is based on reported attendance, not enrollment, in primary education among primary school age children age 6-10. The rate also includes children of primary school age enrolled in secondary education. This is a proxy for MDG indicator 2.1, Net enrollment ratio. 2 Refers to respondents who attended secondary school or higher or who could read a whole sentence or part of a sentence 3 Based on reported net attendance, not gross enrollment, among 6-12-year-olds for primary, 13-17-year-olds for secondary, and 18-22-year- olds for tertiary education 4 Expressed in terms of deaths per 1,000 live births. Mortality by sex refers to a 10-year reference period preceding the survey. Mortality rates for males and females combined refer to the five-year period preceding the survey. 5 Expressed in terms of maternal deaths per 100,000 live births in the seven-year period preceding the survey 6 Among births in the five years preceding the survey 7 Percentage of currently married women age 15-49 using any method of contraception 8 Equivalent to the age-specific fertility rate for women age 15-19 for the three years preceding the survey, expressed in terms of births per 1,000 women age 15-19 9 With a skilled provider 10 With any health care provider 11 High-risk sex refers to sexual intercourse with a non-marital, non-cohabitating partner. Expressed as a percentage of men and women age 15- 24 who had higher-risk sex in the past 12 months. 12 Comprehensive knowledge means knowing that consistent use of a condom during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about transmission or prevention of the AIDS virus. 13 Measured as the percentage of children age 0-59 months who were ill with a fever in the two weeks preceding the interview and who received any antimalarial drug 14 Percentage of de jure population whose main source of drinking water is a household connection (piped), public tap or standpipe, tubewell or borehole, protected dug well, protected spring, rainwater collection, or bottled water. 15 Percentage of de jure population whose household has a flush toilet, ventilated improved pit latrine, pit latrine with a slab, or composting toilet and does not share its facility with other households a Restricted to men in a subsample of households selected for the male interview b The total calculated as the simple arithmetic mean of the percentages in the columns for male and females xx • Map of Namibia Introduction • 1 INTRODUCTION 1 1.1 GEOGRAPHY, HISTORY, AND ECONOMY 1.1.1 Geography amibia is a country in south-western Africa that covers approximately 824,000 square kilometres. It is bordered by the Atlantic Ocean in the west, Angola and Zambia in the north, Botswana in the east, and South Africa in the south and east. It lies mostly between 17° and 29° south latitude (a small area is north of 17°) and 11° and 26° east longitude. The name of the country is derived from the Namib Desert, one of the oldest deserts in the world. Its sand dunes, created by the strong onshore winds, are the highest in the world. There is often extremely dense fog in the Namib Desert as a result of its location, where the Atlantic’s cold waters reach Africa. The Namib Desert stretches along the entire west coast of the country, and the Kalahari Desert runs along the south-eastern border with Botswana. The Namibia consists of five geographical areas: the Central Plateau, the Namib Desert, the Great Escarpment, the Bushveld, and the Kalahari Desert. The central, southern, and coastal areas constitute some of the most arid landscapes south of the Sahara. Because of its location between the Namib and Kalahari deserts, Namibia has the least rainfall in sub-Saharan Africa. The climate in Namibia ranges from arid and semi-arid to subtropical, with temperatures between 5°C and 20°C. Fog sometimes occurs along the temperate desert coast. The hottest months of the year are January and February, with average daytime temperatures ranging between 9°C and 30°C. During the winter months, May to September, temperatures can fluctuate from between -6°C and 10°C at night to 20°C in the day. Although frost occurs over large areas of the country during the winter, in general winter days are clear, cloudless, and sunny. Overall, Namibia is a summer rainfall area, with limited showers beginning in October and continuing until April. 1.1.2 History Namibia gained independence from South Africa on March 21, 1990, following the Namibian War of Independence. Independence followed almost a century of colonial rule by Germany and then by South Africa. Namibia became a German Imperial protectorate in 1884 and remained a German colony until the end of World War I. South Africa occupied the colony in 1915, and the League of Nations mandated Namibia to South Africa in 1919. In 1978 the United Nations (UN) Security Council passed UN Resolution 435, which planned the transition toward independence for Namibia. However, it was only in 1985, after internal violence and uprisings, that South Africa established an interim administration in Namibia. Namibia obtained full independence in 1990 with the exception of Walvis Bay and the Penguin Islands, which remained under South African control until 1994. The country has a multi-party system and holds general elections every five years. A bicameral legislature consists of the National Council (two members chosen from each regional council) and the National Assembly. Namibia is a member state of the UN, the Southern African Development Community, the African Union, and the Commonwealth of Nations. Administratively, the country is divided into 13 regions: Zambezi, Kavango, Kunene, Ohangwena, Omusati, Oshana, and Oshikoto in the north; Omaheke, Otjozondjupa, Erongo, and Khomas in central Namibia; and Hardap and //Karas in the south. The capital is Windhoek, located in the Khomas region. N 2 • Introduction 1.1.3 Economy Agriculture, herding, tourism, and the mining industry, including mining for gem diamonds, uranium, gold, silver, and base metals, are the basis of the economy in Namibia. The growth rate of the domestic economy is expected to increase from 4.7 percent in 2013 to 5.0 percent in 2014 (Bank of Namibia, 2013). This economic growth is attributed to the agricultural sector, which recorded a tremendous growth of 42 percent despite the drought experienced in 2013. The drought led to a decrease in the local production of crop farming and, hence, the need to import food items to feed the country’s population. Sectors that have recently performed well include meat processing; manufacturing of other food products, textiles, clothing apparel, and non-metallic mineral products; publishing and printing. The fishing sector declined by 12 percent in 2013, attributed to the ongoing economic crisis in Europe, especially in Spain, which is the largest export market for the Namibian fishing industry. The mining sector also recorded a reduction of 10 percent due to a decline in the value of diamonds (National Planning Commission [NPC], 2013). Namibia is ranked as a middle-income country but has one of the most skewed distributions of income per capita in the world. The disparities in per capita income among the population are the result of the unbalanced development that characterised the Namibian economy in the past. The annual unemployment rate increased from 27 percent in 2012 to 29 percent in 2013 (Namibia Statistics Agency [NSA], 2013a). 1.2 POPULATION Decennial population censuses have been carried out in Namibia since 1991. Table 1.1 provides a summary of the basic demographic indicators for Namibia from 1991, 2001, and 2011census data. According to the 2011 Population and Housing Census, the country’s population stands at 2,113,077, with an increase of 1.5 percent in the last 10 years. Given the presence of the arid Namib Desert, Namibia is one of the least densely populated countries in the world; the population density is estimated to be 2.6 persons per square kilometre. Regional population densities vary substantially, with almost two-thirds of the population living in the four northern regions and less than one-tenth living in the south. Despite rapid urbanisation, Namibia is still mostly rural, with about four in ten people living in urban areas. The percentage of the population residing in urban areas has increased steadily over the last two decades, from 28 percent in 1991 to 43 percent in 2011. Table 1.1 Basic demographic indicators, Namibia 1991, 2001, and 2011 Indicator Census year 19911 20012 20113 Population 1,409,920 1,830,330 2,113,077 Intercensal growth rate (percentage) 3.1 2.9 1.5 Density (population/km2) 1.7 2.1 2.6 Percentage urban 28 33 43 Life expectancy at birth (years)4 Male 59 48 53 Female 63 50 61 1 Central Bureau of Statistics (CBS), 1992 2 CBS, 2003 3 NSA, 2013b 4 NSA, 2013c English is the country’s official language, but there are more than 11 indigenous languages in Namibia. People commonly speak two or three languages, and close to 50 percent of the population speaks Oshiwambo (NSA, 2013b). Introduction • 3 1.3 HEALTH SERVICES AND PROGRAMMES The government of Namibia recognizes that health is a fundamental human right, and it is committed to achieving health for all Namibians. The mandate of the Ministry of Health and Social Services (MoHSS) is derived from Article 95 of the Namibian Constitution, whereby the government is required to support the health and well-being of all people by putting in place legislation that helps provide health care for all and social assistance to the country’s most vulnerable groups (MoHSS, 2012a). Upon gaining independence in 1990, Namibia inherited a health service delivery structure that was segregated along racial lines and based entirely on curative health services. Since then, the MoHSS has adopted a primary health care (PHC) approach for the delivery of health services to the Namibian population. The core functions of the PHC directorate within the MoHSS are organized around four pillars: health promotion, disease prevention, curative services, and rehabilitation services. The PHC programmes were established to reflect the eight core elements of PHC: • Promotion of proper nutrition and an adequate supply of safe water • Maternal and child care, including family spacing • Immunisation of children against the major infectious diseases • Basic housing and sanitation • Prevention and control of locally endemic diseases • Education, awareness, and training on prevention and control of prevailing community health problems • Appropriate treatment for common diseases and injuries • Community participation in health and social matters To implement the national health strategy, the MoHSS has established the following directorates at the national and regional levels (MoHSS, 2007): • Primary Health Care • Special Programmes • Developmental Social Welfare Services • Tertiary Health Care and Clinical Support Services • Policy, Planning and Human Resource Development • Human Resource Management and General Services • Finance and Logistics • 13 Regional Health Directorates The 13 Regional Health Directorates oversee service delivery in 34 health districts. The role of each district is to ensure efficient and effective implementation of regionally directed programmes and projects. Public health services are provided through 30 public district hospitals, 44 health centres, and 269 clinics. Because of the vastness of the country, the sparse distribution of the population, and the lack of access to permanent health facilities in some communities, outreach (mobile clinic) services are provided at about 1,150 outreach points across the country. Three intermediate hospitals (Oshakati Hospital in Oshana, Rundu Hospital in Kavango, and Katutura Hospital in Khomas) and the national referral hospital (Windhoek Central Hospital) provide support to the district hospitals. Intersectoral collaboration has been recognised as an important aspect of health and social care delivery in Namibia, with a number of partners and stakeholders playing a role. Although the government is the main health care and service provider, private and faith-based facilities make an important contribution. The private sector is mainly urban, providing health care through medium-sized hospitals as well as through private pharmacies, doctors’ surgery offices, and nursing homes. Faith-based services are entirely subsidised by the government. 4 • Introduction 1.4 SURVEY OBJECTIVES The 2013 NDHS is part of the worldwide Demographic and Health Surveys (DHS) programme funded by the United States Agency for International Development (USAID). DHS surveys are designed to collect data on fertility, family planning, and maternal and child health; assist countries in monitoring changes in population, health, and nutrition; and provide an international database that can be used by researchers investigating topics related to population, health, and nutrition. The overall objective of the survey is to provide demographic, socioeconomic, and health data necessary for policymaking, planning, monitoring, and evaluation of national health and population programmes. In addition, the survey measured the prevalence of anaemia, HIV, high blood glucose, and high blood pressure among adult women and men; assessed the prevalence of anaemia among children age 6-59 months; and collected anthropometric measurements to assess the nutritional status of women, men, and children. A long-term objective of the survey is to strengthen the technical capacity of local organizations to plan, conduct, and process and analyse data from complex national population and health surveys. At the global level, the 2013 NDHS data are comparable with those from a number of DHS surveys conducted in other developing countries. The 2013 NDHS adds to the vast and growing international database on demographic and health-related variables. 1.5 ORGANISATION OF THE SURVEY The 2013Namibia Demographic and Health Survey is the fourth nationally representative, comprehensive DHS survey conducted in Namibia. The 2013 NDHS was implemented by the Ministry of Health and Social Services in collaboration with the Namibia Statistics Agency and the National Institute of Pathology (NIP). Technical support was provided by ICF International, with financial support from the government of Namibia, the United States Agency for International Development, and the Global Fund. 1.6 SURVEY IMPLEMENTATION 1.6.1 Sample Design The primary focus of the 2013 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas. In addition, the sample was designed to provide estimates of most key variables for the 13 administrative regions. Each of the administrative regions is subdivided into a number of constituencies (with an overall total of 107 constituencies). Each constituency is further subdivided into lower level administrative units. An enumeration area (EA) is the smallest identifiable entity without administrative specification, numbered sequentially within each constituency. Each EA is classified as urban or rural. The sampling frame used for the 2013 NDHS was the preliminary frame of the 2011 Namibia Population and Housing Census (NSA, 2013a). The sampling frame was a complete list of all EAs covering the whole country. Each EA is a geographical area covering an adequate number of households to serve as a counting unit for the population census. In rural areas, an EA is a natural village, part of a large village, or a group of small villages; in urban areas, an EA is usually a city block. The 2011 population census also produced a digitised map for each of the EAs that served as the means of identifying these areas. The sample for the 2013 NDHS was a stratified sample selected in two stages. In the first stage, 554 EAs—269 in urban areas and 285 in rural areas—were selected with a stratified probability proportional to size selection from the sampling frame. The size of an EA is defined according to the Introduction • 5 number of households residing in the EA, as recorded in the 2011 Population and Housing Census. Stratification was achieved by separating every region into urban and rural areas. Therefore, the 13 regions were stratified into 26 sampling strata (13 rural strata and 13 urban strata). Samples were selected independently in every stratum, with a predetermined number of EAs selected. A complete household listing and mapping operation was carried out in all selected clusters. In the second stage, a fixed number of 20 households were selected in every urban and rural cluster according to equal probability systematic sampling. Due to the non-proportional allocation of the sample to the different regions and the possible differences in response rates, sampling weights are required for any analysis using the 2013 NDHS data to ensure the representativeness of the survey results at the national as well as the regional level. Since the 2013 NDHS sample was a two-stage stratified cluster sample, sampling probabilities were calculated separately for each sampling stage and for each cluster. 1.6.2 Questionnaires Three questionnaires were administered in the 2013 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from the standard DHS6 core questionnaires to reflect the population and health issues relevant to Namibia at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organisations, and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organised by the MoHSS from September 25-28, 2012, in Windhoek. The questionnaires were then translated from English into the six main local languages—Afrikaans, Rukwangali, Oshiwambo, Damara/Nama, Otjiherero, and Silozi—and back translated into English. The questionnaires were finalised after the pretest, which took place from February 11-25, 2013. The Household Questionnaire was used to list all usual household members as well as visitors in the selected households. 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, parents’ survival status was determined. In addition, the Household Questionnaire included questions on knowledge of malaria and use of mosquito nets by household members, along with questions regarding health expenditures. The Household Questionnaire was used to identify women and men who were eligible for the individual interview and the interview on domestic violence. The questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various durable goods. The results of tests assessing iodine levels were recorded as well. In half of the survey households (the same households selected for the male survey), the Household Questionnaire was also used to record information on anthropometry and biomarker data collected from eligible respondents, as follows: • All eligible women and men age 15-64 were measured, weighed, and tested for anaemia and HIV. • All eligible women and men age 35-64 had their blood pressure and blood glucose measured. • All children age 0 to 59 months were measured and weighed. • All children age 6 to 59 months were tested for anaemia. The Woman’s Questionnaire was used to collect information from women age 15-49. Women were asked questions on the following topics: • Background characteristics (e.g., education, residential history, media exposure) • Birth history and childhood mortality • Knowledge and use of family planning methods 6 • Introduction • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Women’s work and husbands’ background characteristics • Awareness and behaviour regarding AIDS and other sexually transmitted infections (STIs) • Other health issues (e.g., knowledge of tuberculosis; tobacco use; alcohol consumption; use of seat belts while seated in a vehicle; physical activity; consumption of water, fruits, and vegetables; knowledge of and testing for breast cancer and cervical cancer; and mental health) • Maternal mortality • Domestic violence The Woman’s Questionnaire was also used to collect information from women age 50-64 living in half of the selected survey households on background characteristics, marriage and sexual activity, women’s work and husbands’ background characteristics, awareness and behaviour regarding AIDS and other STIs, and other health issues. The Man’s Questionnaire was administered to all men age 15-64 living in half of the selected survey households. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition. In addition to the questionnaires, other technical documents were prepared by the MoHSS in collaboration with DHS programme staff at ICF International, including interviewer and supervisor training manuals and assignment sheets for fieldwork control. 1.6.3 Anaemia and HIV Testing In half of the survey households (the same households selected for the male survey), haemoglobin testing to assess the prevalence of anaemia was conducted on women and men age 15-64 who voluntarily consented to the testing and on children 6-59 months for whom consent was obtained from their parents or the adult responsible for the children. To carry out the testing, a drop of blood was obtained from a finger prick (or a heel prick in the case of children less than 12 months old or young children with thin fingers) and collected in a microcuvette. Haemoglobin analysis was performed on-site using a battery-operated portable HemoCue analyser. Results were given to the adults and to the parents or adults responsible for the children, verbally and in writing. Parents of children with a haemoglobin level under 7 g/dl (considered to be severely anaemic) were instructed to take the child to a health facility for follow-up care. Likewise, non-pregnant women and men were referred for follow-up care if their haemoglobin level was below 7 g/dl. Pregnant women were referred to a health facility for follow-up care if their haemoglobin level was below 9 g/dl. In the same households selected for anaemia (half of the survey households), blood specimens were also collected in the field from men and women age 15-64 for HIV testing in the laboratory. Verbal consent for HIV testing was requested from each respondent following completion of the individual interview. The HIV testing protocol was approved by the MoHSS Biomedical Research Committee, the Institutional Review Board of ICF International, and the U.S. Centers for Disease Control and Prevention. Health technicians collected blood specimens from all women and men who consented. The protocol for blood specimen collection and analysis was based on the anonymous linked protocol developed by the DHS programme. This protocol allows for the merging of HIV test results with socio- Introduction • 7 demographic data collected in the individual questionnaires after all information that can potentially identify an individual has been destroyed. Health technicians explained the procedure, the confidentiality of the data, and the fact that the test results would not be made available to the respondent. If a respondent consented to HIV testing, three to five blood spots from a finger prick were collected on a filter paper card to which a barcode label unique to the respondent was affixed. Respondents were asked whether they would consent to having the laboratory store their blood sample for future unspecified testing. If they did not consent to additional testing using their sample, this was indicated on the Household Questionnaire, and the words “no additional testing” were written on the filter paper card. Each respondent, whether providing consent or not, was given an informational brochure on HIV/AIDS and a list of nearby sites providing voluntary counselling and testing services. A barcode label identical to that placed on the filter paper card was attached to the Household Questionnaire. A third copy of the same barcode was affixed to the dried blood spot (DBS) transmittal form to track the blood samples from the field to the laboratory. Blood samples were dried overnight and packaged for storage the following morning. Samples were periodically collected from the field, along with the completed questionnaires, and transported to be logged in and checked at the MoHSS; the samples were then delivered to the NIP, where HIV testing took place. At the NIP, each blood sample was logged into the CSPro HIV Test Tracking System database, given a laboratory number, and stored at -20˚C. The HIV testing protocol stipulates that testing of blood can be conducted only after questionnaire data entry is completed, verified, and cleaned; all paper questionnaires are destroyed; and all unique identifiers are removed from the questionnaire data file except the anonymous barcode number. The HIV testing algorithm followed in the 2013 NDHS was as follows. First, all samples were screened using the Vironostika® Ag/Ab combination assay (Biomérieux), a highly sensitive fourth- generation enzyme-linked immunoassay (ELISA). A negative result was recorded as negative. All samples that tested positive on the first ELISA and 10 percent of the samples that tested negative were retested with a second highly specific fourth-generation ELISA, the Enzygnost® HIV Integral II assay (Siemens). Positive samples on both tests were recorded as positive. If the results of the first and second ELISAs were discordant, the two ELISAs were repeated. If the results remained discordant, the samples were tested using a third confirmatory test, the Inno-Lia HIV I/II Score line immunoassay (Innogenetics), to resolve the discordance. The final result was recorded as positive if the line immunoassay confirmed it to be positive and negative if the line immunoassay confirmed it to be negative. If the line immunoassay results were indeterminate, the sample result was recorded as indeterminate. The line immunoassay was also used to determine the HIV type of all positive samples. Following laboratory testing, the HIV test results were entered into a spreadsheet with a barcode as the unique identifier. The barcode linked the HIV test results with the data from the individual interviews. 1.6.4 Blood Glucose and Blood Pressure Testing In the 2013 NDHS, blood glucose testing was conducted to estimate the prevalence of diabetes mellitus type 2 among women and men age 35-64. After an overnight fast, a blood sample was obtained from respondents by a finger prick, and the blood was tested using the HemoCue Glucose 201 RT system (HemoCue Ab, Angelholm, Sweden) to determine the blood glucose level. Blood glucose levels were recorded as millimoles per litre (mmol/L) and compared with the World Health Organization’s cutoffs to classify the prevalence of diabetes among adult women and men. Elevated blood pressure, commonly referred to as high blood pressure, is a known risk factor for death from stroke and coronary heart disease. In the 2013 NDHS, blood pressure measurements (systolic 8 • Introduction and diastolic) were carried out among women and men age 35-64 to assess the prevalence of high blood pressure among adults. The measurements were not used for diagnostic purposes. Rather, respondents who had an abnormal measurement were informed of their blood pressure level and advised to visit a health facility for evaluation. Blood pressure was measured using the Life Source UA-767 Plus digital device with automatic upper-arm inflation and automatic pressure release. Interviewers were trained in the use of this device according to the manufacturer’s recommended protocol. Three blood pressure measurements were taken, and the first measurement was discarded. The average of the last two measurements was reported as the blood pressure reading in millimetres of mercury (mmHg). 1.6.5 Pretest Pretest training was held at the Khomas Regional Council Office and the National Training Center in Windhoek. There were 35 trainees, 16 men and 19 women. Trainees included eight individuals who had participated in previous NDHS surveys. The survey instruments were piloted from February 11 to February 24, 2013. The questionnaires were pretested in both urban and rural clusters. About 150 women and 150 men were interviewed during the pilot survey, and the results were used to modify the survey instruments as necessary. 1.6.6 Household Listing Prior to the main survey, a complete listing of households in the selected primary sampling units (PSUs) was carried out. This provided a sampling frame from which 20 households in each PSU were selected for the survey. The listing exercise was carried out by the MoHSS in collaboration with the NSA. 1.6.7 Training of Field Staff The main training for the 2013 NDHS was conducted from April 22 to May 18, 2013. A total of 250 participants were recruited, including 31 nurses who served as health technicians. The interviewers were split into five classrooms. The first three weeks primarily covered classroom instruction, expert presentations on selected topics, mock interviews and quizzes. At the end of the classroom training, all of the interviewers completed a final exam and a structured, scored mock interview; they were also judged according to their performance during field practice. In addition to training on the basic content of the questionnaires, a separate training session was conducted for health technicians from May 6-22 on height and weight measurements, blood pressure and blood glucose measurements, anaemia and HIV testing, and DBS preparation. Also, separate training sessions were held for regional supervisors, team supervisors, and editors on their roles and responsibilities, emphasizing the importance of field editing and data quality. 1.6.8 Data Collection Data collection was carried out by 28 teams, each consisting of a supervisor, a field editor, three female interviewers, one male interviewer, and a health technician. Fieldwork started on May 26, 2013, with all teams initially deployed to complete one selected cluster each in Windhoek to enable intense supervision and technical backstopping. After satisfactory completion of these clusters, the teams were deployed to their respective regions to continue fieldwork. Fieldwork was completed on September 30, 2013. Quality assurance was maintained by national and regional supervisors through close supervision and monitoring during fieldwork. The questionnaires were edited by the field editors in the field and verified by the team supervisor before being transported to the MoHSS central office. In addition, national and regional supervisors ensured quality control through editing of questionnaires and observation of interviewers. Common mistakes and practical solutions were communicated through written notes and discussed with all team members. Introduction • 9 Close contact between the MoHSS central office and the teams was maintained through field visits by senior staff, ICF International staff and representatives of USAID/Namibia. Regular communication was maintained through cell phones. A publicity campaign was implemented during May and June 2013 to provide information to communities about the survey and its objectives. The campaign enlightened the public about survey processes, including interviews, anthropometric measurements and collection of blood samples. Information about the survey was announced in the print media and on television, including the official launch of the survey by the MoHSS. T-shirts and leaflets were also prepared for this purpose. 1.6.9 Data Processing CSPro—a Windows-based integrated census and survey processing system that combines and replaces the ISSA and IMPS packages—was used for entry, editing, and tabulation of the NDHS data. Prior to data entry, a practical training session was provided by ICF International to all data entry staff. A total of 28 data processing personnel, including 17 data entry operators, one questionnaire administrator, two office editors, three secondary editors, two network technicians, two data processing supervisors, and one coordinator, were recruited and trained on administration of questionnaires and coding, data entry and verification, correction of questionnaires and provision of feedback, and secondary editing. NDHS data processing was formally launched during the week of June 22, 2013, at the National Statistics Agency Data Processing Centre in Windhoek. The data entry and editing phase of the survey was completed in January 2014. 1.7 RESPONSE RATES Table 1.2 shows household and indi- vidual response rates for the 2013 NDHS. A total of 11,004 households were selected for the sample, of which 10,165 were found to be oc- cupied during data collection. Of the occupied households, 9,849 were successfully inter- viewed, yielding a household response rate of 97 percent. In these households, 9,940 women age 15-49 were identified as eligible for the individ- ual interview. Interviews were completed with 9,176 women, yielding a response rate of 92 percent. In addition, in half of these households, 842 women age 50-64 were successfully inter- viewed; in this group of women, the response rate was 91 percent. Of the 5,271 eligible men identified in the selected subsample of households, 4,481 (85 percent) were successfully interviewed. Response rates were higher in rural than in urban areas, with the rural-urban difference more marked among men than among women. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Namibia 2013 Result Residence Total Urban Rural Household interviews Households selected 5,343 5,661 11,004 Households occupied 4,975 5,190 10,165 Households interviewed 4,766 5,083 9,849 Household response rate1 95.8 97.9 96.9 Interviews with women age 15-49 Number of eligible women 5,327 4,613 9,940 Number of eligible women interviewed 4,843 4,333 9,176 Eligible women response rate2 90.9 93.9 92.3 Interviews with women age 50-643 Number of eligible women 359 562 921 Number of eligible women interviewed 320 522 842 Eligible women response rate2 89.1 92.9 91.4 Interviews with men age 15-643 Number of eligible men 2,722 2,549 5,271 Number of eligible men interviewed 2,224 2,257 4,481 Eligible men response rate2 81.7 88.5 85.0 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents 3 In 50 percent of selected households Housing Characteristics and Household Population • 11 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 his chapter presents information on the demographic and socioeconomic characteristics of the household population, including age, sex, education, and place of residence. These descriptive data provide a context for the interpretation of demographic and health indices and can offer an approximate indication of the representativeness of the survey. In the 2013 NDHS, a household was defined as a person or group of related and unrelated persons who lived together in the same dwelling unit(s), who acknowledged one adult male or female as the head of the household, who shared the same housekeeping arrangements, and who were considered a single unit. Information was collected from all of the usual residents of each selected household and visitors who had stayed in the selected household the night before the interview. Those persons who stayed in the selected household the night before the interview (whether usual residents or visitors) represent the de facto population; usual residents alone constitute the de jure population. To maintain comparability with other surveys, all tables in this report refer to the de facto population unless otherwise specified. 2.1 HOUSEHOLD CHARACTERISTICS The physical characteristics of households and the availability and accessibility of basic household facilities are important in assessing the general welfare and socioeconomic condition of the population. The 2013 NDHS collected information on a range of housing characteristics, including source of drinking water, time taken to fetch water, type of sanitation facility, access to electricity, type of flooring, and number of rooms used for sleeping. Questions were asked about sources of energy for cooking fuel and lighting, household effects, hand washing, school attendance, and educational attainment as well as health insurance and health expenditures. These data are presented for households and are further disaggregated by residence (rural and urban) and region. 2.1.1 Drinking Water The source of drinking water is an indicator of its suitability for drinking. Sources that are more likely to provide water suitable for drinking are identified in Table 2.1 as improved sources. These include T Key Findings • Eighty-seven percent of Namibian households use an improved source of drinking water. • Only 34 percent of households in Namibia use improved toilet facilities that are not shared with other households; 46 percent of households have no toilet facility at all. • Forty-seven percent of households have access to electricity. • Fifty-three percent of households use solid fuel for cooking. • Ownership of mobile phones has risen dramatically; 89 percent of households reported owning a mobile phone in the current survey, as compared with 52 percent in the 2006-07 NDHS. • Eighty-seven percent of children under age 5 have been registered with civil authorities and 63 percent have a birth certificate. • Approximately 14 percent of children under age 18 are orphaned (that is, one or both parents are not living). • Twelve percent of females and 14 percent of males age 6 and older have never attended school. 12 • Housing Characteristics and Household Population a piped source within the dwelling, yard, or plot; a public tap, tube well, or borehole; a hand pump/protected well or protected spring; and rainwater or bottled water.1 Lack of ready access to a water source may limit the quantity of suitable drinking water that is available to a household. Even if the water is obtained from an improved source, it may be contaminated during transportation or storage if it is fetched from a source that is not immediately accessible to the household. Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Namibia 2013 Characteristic Households Population Urban Rural Total Urban Rural Total Source of drinking water Improved source 97.5 75.5 86.9 97.8 71.9 84.0 Piped into dwelling 52.8 19.4 36.8 54.9 18.5 35.5 Piped to yard/plot 14.6 13.6 14.2 15.5 12.5 13.9 Public tap/standpipe 28.7 23.3 26.1 26.3 22.8 24.4 Tube well or borehole 0.3 15.3 7.5 0.4 13.9 7.6 Protected well 0.0 3.0 1.5 0.0 3.4 1.8 Protected spring 0.0 0.6 0.3 0.0 0.6 0.3 Rainwater 0.0 0.1 0.1 0.0 0.1 0.1 Bottled water 1.1 0.1 0.6 0.7 0.0 0.4 Non-improved source 0.3 13.2 6.5 0.3 15.5 8.4 Unprotected well 0.2 11.2 5.5 0.3 13.6 7.4 Unprotected spring 0.0 0.8 0.4 0.0 0.7 0.4 Tanker truck/cart with drum 0.0 1.1 0.6 0.1 1.3 0.7 Other 2.1 3.0 2.6 1.7 2.4 2.1 Missing 0.1 8.3 4.0 0.1 10.1 5.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 68.0 37.3 53.3 70.9 34.9 51.7 Less than 30 minutes 26.2 35.5 30.7 23.3 34.9 29.5 30 minutes or longer 4.9 25.5 14.8 5.1 28.6 17.6 Don’t know/missing 0.8 1.7 1.2 0.8 1.6 1.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 9.1 2.3 5.9 9.4 2.3 5.6 Bleach/chlorine added 0.3 4.2 2.2 0.3 5.1 2.9 Strained through cloth 0.0 0.3 0.2 0.0 0.3 0.2 Ceramic, sand, or other filter 1.5 0.2 0.9 1.5 0.2 0.8 Other 0.6 0.6 0.6 0.5 0.5 0.5 No treatment 88.5 92.6 90.5 88.4 92.0 90.3 Percentage using an appropriate treatment method2 10.7 6.4 8.7 11.0 7.3 9.0 Number 5,121 4,728 9,849 19,458 22,207 41,665 1 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100 percent. 2 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. Source of drinking water is important because waterborne diseases such as diarrhoea are prevalent in Namibia. Sources of water expected to be relatively free of the agents responsible for these diseases are piped water, hand pumps/protected wells, protected springs, rainwater, and bottled water. Other sources such as unprotected wells, unprotected springs, and tanker trucks/carts with drums are more likely to carry disease-causing agents. Table 2.1 indicates that a majority of Namibian households (87 percent) have access to improved water sources: 37 percent from piped water into the dwelling, 14 percent from water piped to the yard, and 26 percent from a public tap. Households in urban areas (98 percent) are more likely than those in rural areas (76 percent) to have access to an improved source of water. In the 2006-07 NDHS, 97 percent of urban households and 80 percent of rural households were reported to use improved sources of water. 1 The categorisation into improved and non-improved categories follows that proposed by the WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation (WHO and UNICEF, 2012a). Housing Characteristics and Household Population • 13 The table further shows that 53 percent of households in Namibia have a source of drinking water on their premises, with a large difference between urban and rural households (68 percent and 37 percent, respectively). A comparison with the findings from the 2006-07 NDHS shows that there has been a significant drop in the proportion of urban households with water on the premises (from 81 percent to 68 percent), while the percentage of rural households with water on the premises has increased slightly from 32 percent to 37 percent . Thirty-one percent of households take less than 30 minutes to obtain drinking water, while 15 percent take 30 minutes or longer. Nine percent of households treat their drinking water. Six percent boil their water and 2 percent use bleach/chlorine prior to drinking. Ninety-three percent of rural households and 89 percent of urban households do not treat their drinking water. 2.1.2 Sanitation Facilities and Waste Disposal A household is classified as having an improved toilet if the toilet is used only by members of one household (i.e., it is not shared) and if the facility used by the household separates waste from human contact (WHO and UNICEF, 2012b). The types of facilities considered improved are toilets that flush or pour flush into a piped sewer system, septic tank, or pit latrine; ventilated improved pit (VIP) latrines; and pit latrines with a slab. Table 2.2 shows that only 34 percent of households in Namibia use improved toilet facilities that are not shared with other households, and 15 percent use facilities that would be considered improved if they were not shared. Forty-nine percent of households in urban areas have improved toilet facilities that are not shared, as compared with 17 percent of households in rural areas. Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Namibia 2013 Type of toilet/latrine facility Households Population Urban Rural Total Urban Rural Total Improved, not shared facility Flush/pour flush to piped sewer system 44.0 7.4 26.4 48.0 5.2 25.2 Flush/pour flush to septic tank 0.9 0.8 0.9 0.9 0.6 0.8 Flush/pour flush to pit latrine 1.3 1.5 1.4 1.7 1.4 1.5 Ventilated improved pit (VIP) latrine 1.9 5.4 3.6 2.2 7.0 4.8 Pit latrine with slab 0.3 1.9 1.0 0.4 2.2 1.3 Composting toilet 0.1 0.2 0.1 0.1 0.2 0.1 Total 48.5 17.2 33.5 53.2 16.7 33.8 Shared facility1 Flush/pour flush to piped sewer system 19.0 2.0 10.9 15.4 0.9 7.7 Flush/pour flush to septic tank 0.2 0.4 0.3 0.1 0.2 0.2 Flush/pour flush to pit latrine 1.9 0.5 1.3 1.5 0.2 0.8 Ventilated improved pit (VIP) latrine 3.2 2.1 2.6 2.8 1.7 2.2 Pit latrine with slab 0.2 0.5 0.4 0.2 0.3 0.2 Composting toilet 0.0 0.1 0.0 0.0 0.1 0.0 Total 24.6 5.5 15.4 20.1 3.3 11.2 Non-improved facility Flush/pour flush not to sewer/septic tank/pit latrine 1.8 0.7 1.2 1.7 0.4 1.0 Pit latrine without slab/open pit 2.7 2.3 2.5 3.4 2.7 3.0 Bucket 0.6 0.6 0.6 0.6 0.4 0.5 Hanging toilet/hanging latrine 0.1 0.1 0.1 0.1 0.1 0.1 No facility/bush/field 21.1 73.6 46.3 20.0 76.4 50.0 Other 0.5 0.0 0.3 0.7 0.0 0.3 Missing 0.1 0.1 0.1 0.1 0.1 0.1 Total 26.9 77.3 51.1 26.7 80.0 55.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 5,121 4,728 9,849 19,458 22,207 41,665 1 Facilities that would be considered improved if they were not shared by 2 or more households More than half of Namibian households (51 percent) have non-improved toilet facilities. Forty-six percent of households have no toilet facility at all, as compared with 49 percent in the 2006-07 NDHS 14 • Housing Characteristics and Household Population survey. Twenty-one percent of households in urban areas and 74 percent of households in rural areas lack any toilet facility. The proportion of urban households without a toilet facility increased by 6 percentage points over the last six years from 15 percent to 21 percent. On the other hand, the proportion of rural households with no toilet facility decreased by 4 percentage points over the same period (78 percent versus 74 percent). 2.1.3 Housing Characteristics Table 2.3 presents information on the characteristics of household dwellings. In addition to reflecting the household’s socioeconomic situation, these character- istics show the environmental conditions in which the household lives. Access to electricity usually goes hand in hand with improved housing structures and a better standard of living. In Namibia, only 47 percent of households have electricity. There is a large difference in access to electricity between urban and rural households (72 percent and 21 percent, respectively). The percentage of households with electricity has risen since the 2006-07 NDHS survey, when only 44 percent of households had electricity. This gain, however, has been in rural households only, in which the percentage of households with electricity rose from 15 percent to 21 percent. Access to electricity in urban households however, declined from 78 percent to 72 percent over the same period. The type of material used for flooring is also an indicator of socio- economic status and, to some extent, deter- mines the household’s vulnerability to disease-causing agents. Forty percent of Namibian households have earthen floors (made of earth/sand, dung, or mud/clay), while 34 percent have cement floors. One in five households have ceramic floors. Differences exist between rural and urban households; earth/sand flooring is most common in rural areas (44 percent), while cement and ceramic tiles are most common in urban areas (35 percent and 33 percent, respectively). Overall, 31 percent of Namibian households use one room for sleeping, 26 percent use two rooms, and 43 percent use three or more rooms. Table 2.3 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Namibia 2013 Housing characteristic Residence Total Urban Rural Electricity Yes 72.2 20.5 47.4 No 27.8 79.5 52.6 Total 100.0 100.0 100.0 Flooring material Earth/sand 17.7 44.1 30.4 Dung 0.5 2.7 1.6 Mud/clay 1.9 13.8 7.6 Wood planks 0.4 0.1 0.3 Palm/bamboo 0.2 0.0 0.1 Parquet or polished wood 0.6 0.1 0.4 Vinyl or asphalt strips 1.4 0.3 0.9 Ceramic tiles 33.4 3.7 19.1 Cement 34.5 33.7 34.1 Carpet 8.3 1.3 4.9 Other 0.8 0.1 0.5 Missing 0.3 0.1 0.2 Total 100.0 100.0 100.0 Rooms used for sleeping One 35.3 26.0 30.8 Two 29.3 21.8 25.7 Three or more 35.0 51.7 43.0 Missing 0.5 0.5 0.5 Total 100.0 100.0 100.0 Place for cooking In the house 77.5 52.8 65.6 In a separate building 5.8 10.8 8.2 Outdoors 16.2 36.2 25.8 No food cooked in household 0.4 0.1 0.3 Other 0.1 0.1 0.1 Total 100.0 100.0 100.0 Cooking fuel Electricity 58.0 7.4 33.7 LPG/natural gas/biogas 16.3 3.4 10.1 Kerosene 5.0 0.1 2.6 Charcoal 0.2 0.4 0.3 Wood 19.9 87.4 52.3 Animal dung 0.0 1.0 0.5 Other 0.1 0.0 0.1 No food cooked in household 0.4 0.1 0.3 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 20.1 88.9 53.1 Frequency of smoking in the home Daily 19.5 22.4 20.9 Weekly 2.2 2.4 2.3 Monthly 0.4 0.2 0.3 Less than monthly 0.5 0.6 0.5 Never 77.3 74.4 75.9 Missing 0.1 0.0 0.1 Total 100.0 100.0 100.0 Number 5,121 4,728 9,849 LPG = Liquid petroleum gas 1 Includes charcoal, wood, and animal dung Housing Characteristics and Household Population • 15 The potential for exposure to harmful effects of smoke from using solid fuels for cooking increases if cooking occurs within the house itself rather than outdoors or in a separate building. Sixty-six percent of households in Namibia cook in the house, 8 percent cook in a separate building, and 26 percent cook outdoors. Seventy-eight percent of urban households cook in the house, as compared with 53 percent of rural households. Cooking and heating with solid fuels can lead to high levels of indoor smoke, a complex mix of health-damaging pollutants that can increase the risk of contracting diseases (WHO, 2011). Solid fuels include charcoal, wood, and animal dung. In the 2013 NDHS, households were asked about their primary source of fuel for cooking. The results show that 52 percent of households use wood for cooking, while only 34 percent use electricity. There are large differences in use of fuel for cooking between urban and rural areas. Eighty-seven percent of households in rural areas use wood as their primary source of fuel for cooking, while 58 percent of urban households use electricity as their main source of cooking fuel. Information on frequency of smoking inside the home was obtained to assess the percentage of households in which there is exposure to secondhand smoke, which causes health risks in children and adults who do not smoke. Pregnant women who are exposed to secondhand smoke have a higher risk of delivering a low birth weight baby (Windham et al., 1999), and children exposed to secondhand smoke are at increased risk for respiratory and ear infections and poor lung development (U.S. Department of Health and Human Services, 2006). Twenty-one percent of Namibian households reported that someone smokes in the home daily. In 76 percent of households, smoking never occurs in the home. 2.1.4 Household Possessions Possession of durable goods is an indicator of a household’s socioeconomic status. Moreover, each particular item has specific benefits. For instance, having access to a radio or a television exposes household members to innovative ideas, a refrigerator prolongs the wholesomeness of foods, and a means of transport allows greater access to services away from the local area. Table 2.4 shows data on ownership of selected household possessions by residence. The most commonly owned items by households are mobile telephones (89 percent), radios (68 percent), televisions (44 percent), and refrigerators (42 percent). With the exception of the radio, all of these proportions are higher than those recorded in the 2006-07 NDHS. Most notably, household ownership of mobile phones has risen from 52 percent to 89 percent, a 71 percent increase. Urban households are more likely than rural households to own each of these items. With regard to a means of transportation, 14 percent of households own a bicycle, while 27 percent own a car or truck. Urban households are twice as likely to own a car or truck as rural households. Farming of agricultural land and ownership of farm animals are common in Namibia, with about 48 percent of households owning farm animals. Not surprisingly, the proportions of households in rural areas that own agricultural land (70 percent) and farm animals (75 percent) are much higher than the corresponding proportions of urban households (20 percent and 22 percent, respectively). Table 2.4 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Namibia 2013 Possession Residence Total Urban Rural Household effects Radio 73.3 63.0 68.4 Television 66.6 18.5 43.6 Mobile telephone 95.0 81.4 88.5 Non-mobile telephone 15.0 2.6 9.0 Refrigerator 64.9 16.7 41.8 Means of transport Bicycle 15.2 11.8 13.5 Animal-drawn cart 2.0 12.4 7.0 Motorcycle/scooter 2.5 1.1 1.8 Car/truck 35.0 17.6 26.7 Boat with a motor 0.8 0.2 0.5 Ownership of agricultural land 19.7 70.3 44.0 Ownership of farm animals1 22.3 74.8 47.5 Number 5,121 4,728 9,849 1 Cattle, cows, bulls, horses, donkeys, goats, sheep, or chickens 16 • Housing Characteristics and Household Population 2.2 HOUSEHOLD WEALTH Information on household assets was used to create an index that is used throughout this report to represent the wealth of the households interviewed in the 2013 NDHS. This method for calculating a country-specific wealth index was developed and tested in a large number of countries in relation to inequalities in household income, use of health services, and health outcomes (Rutstein and Johnson, 2004). It has been shown to be consistent with expenditure and income measures. The wealth index is constructed using household asset data, including ownership of consumer items ranging from a television to a bicycle or car, as well as dwelling characteristics, such as source of drinking water, sanitation facilities, and type of flooring material. In its current form, which takes account of urban-rural differences in these items and characteristics, the wealth index is created in three steps. In the first step, a subset of indicators common to urban and rural areas is used to create wealth scores for households in both areas. For purposes of creating scores, categorical variables are transformed into separate dichotomous (0-1) indicators. These indicators and those that are continuous are then examined using a principal components analysis to produce a common factor score for each household. In the second step, separate factor scores are produced for households in urban and rural areas using area-specific indicators (Rutstein, 2008). The third step combines the separate area-specific factor scores to produce a nationally applicable combined wealth index by adjusting area-specific scores through a regression on the common factor scores. The resulting combined wealth index has a mean of zero and a standard deviation of one. Once the index is computed, national-level wealth quintiles (from lowest to highest) are formed by assigning the household score to each de jure household member, ranking each person in the population by that score, and then dividing the ranking into five equal categories, each comprising 20 percent of the population. Thus, throughout this report, wealth quintiles are expressed in terms of quintiles of individuals in the overall population rather than quintiles of individuals at risk for any one health or population indicator. For example, quintile rates for infant mortality refer to 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. Table 2.5 presents wealth quintiles by residence and region. Also included in the table is the Gini coefficient, which indicates the level of concentration of wealth (0 being an equal distribution and 1 a totally unequal distribution). The table shows that wealth in Namibia is unevenly distributed by residence and region. Forty percent of the urban population is in the highest wealth quintile, as compared with 2 percent of the rural population. In contrast, 36 percent of the rural population is in the lowest wealth quintile, compared with 2 percent of the urban population. The distribution of the population by wealth quintile among regions shows large variations. In Khomas and Erongo, half of the population is in the highest wealth quintile (50 percent and 48 percent, respectively). In Ohangwena and Kavango, on the other hand, half of the population is in the lowest wealth quintile. The overall Gini coefficient in Namibia is 0.42. It is higher in rural (0.45) than in urban (0.24) areas, indicating a more unequal distribution of wealth in the rural population than in the urban population. The lowest Gini coefficient is seen in Erongo (0.18), where nearly one in two persons are in the highest wealth quintile. The highest Gini coefficient—that is, the least equitable distribution of wealth—is observed in Kavango (0.51). Housing Characteristics and Household Population • 17 Table 2.5 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and region, Namibia 2013 Residence/region Wealth quintile Total Number of persons Gini coefficient Lowest Second Middle Fourth Highest Residence Urban 1.7 11.0 17.5 29.5 40.3 100.0 19,458 0.24 Rural 36.1 27.8 22.3 11.6 2.2 100.0 22,207 0.45 Region Zambezi 36.3 23.8 19.7 11.4 8.8 100.0 2,181 0.44 Erongo 0.5 8.0 12.1 31.3 48.1 100.0 3,083 0.18 Hardap 3.4 11.3 19.0 34.9 31.3 100.0 1,451 0.30 //Karas 3.8 10.7 22.5 31.9 31.0 100.0 1,482 0.28 Kavango 48.9 22.0 15.6 10.5 3.1 100.0 4,308 0.51 Khomas 0.5 10.4 14.9 23.7 50.4 100.0 7,697 0.21 Kunene 17.7 28.3 22.3 19.3 12.5 100.0 1,288 0.41 Ohangwena 49.2 26.2 13.6 8.7 2.2 100.0 4,861 0.47 Omaheke 10.6 27.1 30.2 21.4 10.7 100.0 1,144 0.44 Omusati 23.1 30.5 32.8 10.8 2.8 100.0 4,829 0.37 Oshana 10.6 24.3 29.2 22.7 13.2 100.0 3,306 0.38 Oshikoto 26.8 26.6 20.9 17.2 8.5 100.0 3,483 0.48 Otjozondjupa 5.5 13.2 21.1 41.9 18.3 100.0 2,553 0.30 Total 20.0 20.0 20.0 20.0 20.0 100.0 41,665 0.42 2.3 HAND WASHING To obtain hand washing information, interviewers asked to see the place where members of the household most often washed their hands. Information on the availability of water, cleansing agents, or both was recorded only for households where a hand washing place was observed. Interviewers observed a place for hand washing in 87 percent of households (Table 2.6). Among households where a place for washing hands was observed, 54 percent had soap and water, 21 percent had only water, and 21 percent had no water, soap, or any other cleansing agent. Not surprisingly, households in urban areas were much more likely to have soap and water for hand washing. Three in four households in Otjozondjupa and //Karas (76 percent and 74 percent, respectively) had soap and water for hand washing. On the other hand, four in ten households in Omusati (43 percent) had no water, no soap, and no cleansing agent for washing hands. The percentage of households with soap and water for hand washing increases with increasing wealth, from 22 percent among the poorest households to 85 percent among the wealthiest households. 18 • Housing Characteristics and Household Population Table 2.6 Hand washing Percentage of households in which the place most often used for washing hands was observed, and among households in which the place for hand washing was observed, percent distribution by availability of water, soap, and other cleansing agents, Namibia 2013 Background characteristic Percentage of households where place for washing hands was observed Number of households Among households where place for hand washing was observed, percentage with: Number of households with place for hand washing observed Soap and water1 Water and cleansing agent2 other than soap only Water only Soap but no water3 Cleansing agent other than soap only2 No water, no soap, no other cleansing agent Missing Total Residence Urban 89.1 5,121 68.3 0.0 14.9 4.6 0.0 12.1 0.1 100.0 4,561 Rural 84.0 4,728 37.4 0.4 28.0 3.5 0.2 30.4 0.0 100.0 3,970 Region Zambezi 79.6 541 42.2 0.8 37.9 1.1 0.0 18.0 0.0 100.0 431 Erongo 89.4 930 63.0 0.1 16.3 4.2 0.0 16.4 0.0 100.0 832 Hardap 91.5 381 60.2 0.0 20.6 0.8 0.0 18.4 0.0 100.0 349 //Karas 63.3 406 73.8 0.2 14.8 2.5 0.0 8.5 0.2 100.0 257 Kavango 58.9 737 36.7 0.0 35.1 5.7 0.2 22.4 0.0 100.0 435 Khomas 89.7 2,015 68.0 0.0 18.4 3.2 0.0 10.1 0.3 100.0 1,807 Kunene 87.5 354 69.4 2.5 15.5 1.7 0.0 10.9 0.0 100.0 310 Ohangwena 83.7 900 25.1 0.0 28.5 4.7 0.9 40.9 0.0 100.0 754 Omaheke 80.7 335 66.7 0.0 21.0 0.8 0.2 11.2 0.0 100.0 270 Omusati 90.0 949 27.2 0.0 26.5 3.6 0.0 42.7 0.0 100.0 855 Oshana 99.2 831 58.2 0.1 7.0 11.2 0.0 23.4 0.1 100.0 824 Oshikoto 97.2 817 43.3 0.1 25.7 2.2 0.0 28.6 0.0 100.0 794 Otjozondjupa 94.1 652 75.6 0.7 14.4 5.8 0.0 3.5 0.0 100.0 614 Wealth quintile Lowest 77.0 1,737 21.6 0.5 35.2 3.3 0.3 39.1 0.1 100.0 1,338 Second 84.8 1,910 38.2 0.4 25.8 3.6 0.2 31.8 0.0 100.0 1,620 Middle 88.4 1,954 46.1 0.1 22.9 5.6 0.1 25.1 0.1 100.0 1,728 Fourth 90.2 2,136 65.6 0.1 18.5 4.8 0.0 10.9 0.0 100.0 1,927 Highest 90.8 2,111 84.9 0.0 7.8 3.1 0.0 4.0 0.2 100.0 1,918 Total 86.6 9,849 53.9 0.2 21.0 4.1 0.1 20.6 0.1 100.0 8,530 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand. 3 Includes households with soap only as well as those with soap and another cleansing agent 2.4 HOUSEHOLD POPULATION BY AGE, SEX, AND RESIDENCE Age and sex are important demographic variables and are the primary basis for demographic classifications in vital statistics, censuses, and surveys. They are also important variables in the study of mortality, fertility, and marriage. The distribution of the de facto household population in the 2013 NDHS is shown in Table 2.7 by five-year age groups, according to sex and residence. A total of 41,396 individuals resided in the 9,849 households successfully interviewed; 21,774 were female, and 19,621 were male. The age-sex structure of the population is shown in the population pyramid in Figure 2.1. The broad base of the pyramid indicates that Namibia’s population is mostly young. The proportion of persons under age 15 was 38 percent in 2013, while the proportion of individuals age 65 and older was 5 percent. After a steady decline from 16 percent in the 1992 NDHS to 14 percent in the 2000 NDHS and 13 percent in the 2006–07 NDHS, the proportion of the population less than age 5 increased slightly to 14 percent in the current survey. Housing Characteristics and Household Population • 19 Table 2.7 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Namibia 2013 Age Urban Rural Male Female Total Male Female Total Male Female Total <5 11.7 11.5 11.6 16.4 15.1 15.7 14.2 13.4 13.8 5-9 10.6 10.5 10.5 15.6 13.5 14.5 13.3 12.1 12.7 10-14 9.8 9.1 9.4 14.6 13.4 14.0 12.4 11.4 11.9 15-19 8.8 9.8 9.4 12.4 9.9 11.1 10.8 9.9 10.3 20-24 11.8 12.5 12.2 7.8 6.7 7.2 9.6 9.4 9.5 25-29 10.3 10.4 10.4 5.5 5.7 5.6 7.8 7.9 7.9 30-34 9.0 8.6 8.8 4.9 5.0 4.9 6.8 6.7 6.7 35-39 7.4 7.3 7.4 4.6 4.8 4.7 5.9 6.0 5.9 40-44 6.5 5.9 6.2 3.2 3.9 3.6 4.8 4.8 4.8 45-49 5.0 4.0 4.5 2.7 3.5 3.2 3.8 3.8 3.8 50-54 3.2 3.6 3.4 2.4 3.9 3.2 2.7 3.8 3.3 55-59 2.0 2.3 2.1 1.8 2.7 2.2 1.9 2.5 2.2 60-64 1.4 1.5 1.5 1.9 2.8 2.4 1.7 2.2 2.0 65-69 1.0 1.1 1.0 1.9 2.3 2.1 1.5 1.7 1.6 70-74 0.7 0.7 0.7 1.6 2.0 1.8 1.2 1.4 1.3 75-79 0.3 0.5 0.4 0.9 1.3 1.1 0.6 0.9 0.8 80+ 0.2 0.5 0.4 1.6 3.4 2.5 1.0 2.0 1.5 Don’t know/missing 0.1 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 9,116 10,174 19,291 10,505 11,599 22,106 19,621 21,774 41,396 Figure 2.1 Population pyramid 8 6 4 2 0 2 4 6 8 <5 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80+ Percent Age Male Female NDHS 2013 8 6 4 2 20 • Housing Characteristics and Household Population 2.5 HOUSEHOLD COMPOSITION Information on the composition of households, including the sex of the head of the household and the size of the household, is presented in Table 2.8. These characteristics are important because they are associated with the welfare of the household. In larger households, economic resources are often more limited. Moreover, when the household size is large, crowding can lead to health problems. Table 2.8 shows that 44 percent of the households in Namibia are headed by women. Households with one and two members constitute 17 percent and 16 percent of all households, respectively. The average household size is 4.2 persons, as compared with 4.5 in the 2006-07 NDHS survey. On average, rural households are larger (4.7 persons) than urban households (3.8 persons). Information was also collected on the living arrangements of all children under age 18 residing in the sample households and on the survival status of their parents. This information can be used to assess the extent to which households face a need to care for orphaned or foster children. Orphans include children whose mother or father has died (single orphans) as well as children who have lost both parents (double orphans). In the case of foster children, both parents are alive but the children are living in a household where neither their natural mother nor their natural father resides. Overall, 35 percent of households in Namibia are caring for foster and/or orphaned children. 2.6 BIRTH REGISTRATION Birth registration is the inscription of the facts of each birth into an official log kept at the registrar’s office. A birth certificate is issued as proof of the registration of the birth. Birth registration is basic to ensuring a child’s legal status and, thus, fundamental rights and services (UNICEF, 2006; United Nations General Assembly, 2002). Information on registration of births was collected in the household interview. Respondents were asked whether children under age 5 residing in the household had a birth certificate. Table 2.9 shows the percentage of de jure children under age 5 whose births are registered with the civil authorities. Eighty-seven percent of children under five are registered with the civil authorities—63 percent have a birth certificate, 23 percent have a hospital card and less than 1 percent are registered but do not have a birth certificate. Children less than age 2 are less likely to have a birth certificate (56 percent) than children age 2-4 (68 percent Male children are slightly more likely to have a birth certificate than female children (65 percent versus 62 percent). Children in urban households are more likely to have a birth certificate than children in rural households (77 percent and 54 percent, respectively). By region, the proportion of children with birth certificates is highest in //Karas (89 percent) and lowest in Kavango (47 percent). The percentage of children with birth certificates correlates positively with wealth, ranging from 42 percent among children in the lowest wealth quintile to 90 percent among children in the highest quintile. Table 2.8 Household composition Percent distribution of households by sex of head of household and by household size, mean size of household, and percentage of households with orphans and foster children under age 18, according to residence, Namibia 2013 Characteristic Residence Total Urban Rural Household headship Male 59.5 52.3 56.1 Female 40.5 47.7 43.9 Total 100.0 100.0 100.0 Number of usual members 0 0.2 0.2 0.2 1 18.6 16.1 17.4 2 18.1 13.4 15.8 3 15.2 12.6 13.9 4 15.7 11.7 13.8 5 11.5 12.0 11.7 6 8.3 9.3 8.8 7 4.8 7.4 6.0 8 2.7 5.0 3.8 9+ 5.1 12.2 8.5 Total 100.0 100.0 100.0 Mean size of households 3.8 4.7 4.2 Percentage of households with orphans and foster children under age 18 Foster children1 18.4 46.4 31.9 Double orphans 2.0 3.5 2.7 Single orphans2 9.5 19.9 14.5 Foster and/or orphan children 22.1 49.6 35.3 Number of households 5,121 4,728 9,849 Note: Table is based on de jure household members (i.e., usual residents). 1 Foster children are those under age 18 living in households with neither their mother nor their father present. 2 Includes children with one dead parent and an unknown survival status of the other parent Housing Characteristics and Household Population • 21 Table 2.9 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Namibia 2013 Background characteristic Children whose births are registered Number of children Percentage with a birth certificate Percentage without a birth certificate Percentage with only a hospital card Percentage registered Age <2 55.5 0.4 29.3 85.3 2,288 2-4 68.4 0.9 19.1 88.4 3,390 Sex Male 64.7 0.7 22.2 87.6 2,776 Female 61.8 0.7 24.2 86.7 2,900 Residence Urban 77.2 0.8 10.9 88.9 2,214 Rural 54.3 0.6 31.0 86.0 3,464 Region Zambezi 49.1 1.1 41.9 92.1 352 Erongo 79.7 0.5 10.6 90.8 310 Hardap 84.7 0.0 7.8 92.5 195 //Karas 88.8 3.0 5.1 97.0 175 Kavango 46.5 0.4 23.4 70.2 688 Khomas 78.1 0.6 10.6 89.3 769 Kunene 52.2 3.4 20.9 76.4 221 Ohangwena 54.4 0.3 36.5 91.2 836 Omaheke 60.4 1.4 22.9 84.6 180 Omusati 64.3 0.1 24.8 89.2 672 Oshana 63.2 1.1 17.3 81.6 398 Oshikoto 59.1 0.2 37.6 96.9 504 Otjozondjupa 70.7 1.0 14.2 86.0 379 Wealth quintile Lowest 42.2 0.6 40.2 83.1 1,420 Second 55.6 0.6 28.2 84.5 1,306 Middle 68.2 0.8 19.4 88.4 1,181 Fourth 76.1 1.1 12.8 90.1 1,009 Highest 90.4 0.4 2.5 93.3 762 Total 63.2 0.7 23.2 87.1 5,678 Note: Total includes 1 child with missing information on sex. 2.7 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Information was collected on the living arrangements and parental survival status of all children under age 18 residing in the sample households to assess the potential burden on households in terms of the need to provide for orphaned or foster children. The information was also used to assess the situation from the perspective of the children themselves. Table 2.10 presents the proportion of children under age 18 who are not living with one or both parents, either because the parent(s) died or for other reasons. Two percent of Namibian children under age 18 have lost both parents. Eight percent are not living with either parent. Twenty-eight percent of children are not living with either parent although both are alive. Fourteen percent of children under age 18 are orphaned (that is, one or both parents are dead). The percentage of orphaned children increases rapidly with age, from 4 percent among children under age 5 to 27 percent among children age 15-17. Rural children are more likely to be orphaned than urban children (15 percent and 12 percent, respectively). Otjozondjupa and Erongo (9 percent each) have the lowest proportion of orphaned children, and Oshana has the highest (18 percent). The percentage of children with one or both parents dead varies little by wealth. Thirty-seven percent of children are not living with their biological parents. Twenty-one percent of children from households in the highest wealth quintile are not living with a biological parent, and 43 and 44 percent of children from households in the second and middle wealth quintiles, respectively, are not living with a biological parent. The vast majority (97) percent) of children with no parents are attending school, while 95 percent of children with at least one living parent are attending school (data not shown). 22 • Housing Characteristics and Household Population Table 2.10 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Namibia 2013 Background characteristic Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biolo- gical parent Percent- age with one or both parents dead1 Number of children Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing infor- mation on father/ mother Age 0-4 29.8 40.6 2.1 2.3 0.1 22.6 0.5 0.8 0.4 0.9 100.0 24.3 4.0 5,678 <2 31.9 53.4 2.2 0.6 0.0 10.7 0.3 0.1 0.2 0.7 100.0 11.3 2.8 2,288 2-4 28.4 32.0 2.0 3.4 0.2 30.5 0.7 1.3 0.6 1.0 100.0 33.1 4.8 3,390 5-9 25.2 25.2 3.6 4.7 0.4 33.7 1.8 2.9 1.2 1.3 100.0 39.6 10.0 5,267 10-14 20.8 21.3 6.4 4.4 0.9 30.0 4.4 6.6 3.3 1.9 100.0 44.3 21.9 4,919 15-17 20.3 17.3 8.5 3.7 1.2 26.7 5.9 6.5 4.2 5.7 100.0 43.2 26.8 2,528 Sex Male 24.8 27.4 4.6 4.2 0.6 28.4 2.5 3.6 2.0 2.0 100.0 36.5 13.5 9,148 Female 24.7 28.3 4.5 3.3 0.5 28.3 2.8 3.9 1.9 1.9 100.0 36.8 13.8 9,243 Residence Urban 34.9 30.5 4.8 5.0 0.8 15.9 1.8 2.1 2.1 2.1 100.0 22.0 11.8 7,087 Rural 18.4 26.2 4.4 2.9 0.4 36.1 3.2 4.8 1.8 1.8 100.0 45.8 14.8 11,305 Region Zambezi 34.1 27.2 5.9 3.1 1.2 17.3 2.8 3.3 3.5 1.7 100.0 26.8 16.7 987 Erongo 38.4 28.5 3.7 5.3 0.6 17.3 2.7 1.5 0.2 1.9 100.0 21.7 9.0 1,053 Hardap 33.1 30.8 3.0 3.8 0.5 20.0 2.2 1.9 3.3 1.4 100.0 27.4 11.1 581 //Karas 31.6 29.5 6.9 5.8 0.9 15.5 2.0 1.6 4.0 2.3 100.0 23.0 15.8 574 Kavango 29.5 29.6 4.7 3.1 0.3 22.8 2.7 3.2 1.9 2.2 100.0 30.7 12.9 2,268 Khomas 39.1 30.4 5.6 5.8 1.0 11.5 1.3 1.8 1.9 1.8 100.0 16.5 11.7 2,482 Kunene 23.6 29.2 4.3 4.2 0.2 29.9 1.3 2.2 1.2 3.9 100.0 34.7 9.5 568 Ohangwena 13.4 25.5 3.7 3.8 0.4 42.5 3.3 5.2 1.2 1.0 100.0 52.2 14.1 2,755 Omaheke 32.2 23.9 5.5 3.3 1.2 25.8 2.2 1.4 2.5 2.1 100.0 31.9 12.7 465 Omusati 12.6 26.4 4.8 2.5 0.4 40.0 3.1 5.7 2.4 2.1 100.0 51.2 16.6 2,498 Oshana 14.3 27.0 4.9 3.5 0.1 34.6 4.0 6.3 2.5 2.8 100.0 47.4 18.1 1,426 Oshikoto 16.6 27.7 3.5 2.4 0.4 37.3 3.8 5.4 1.3 1.5 100.0 47.8 14.8 1,637 Otjozondjupa 32.4 27.1 3.8 3.5 0.6 25.6 1.1 1.4 1.9 2.6 100.0 30.0 8.9 1,098 Wealth quintile Lowest 22.6 28.6 5.5 2.5 0.4 30.5 2.7 3.9 1.9 1.5 100.0 39.0 14.5 4,520 Second 19.7 28.2 4.1 2.9 0.4 32.8 3.4 4.8 1.9 1.9 100.0 42.8 14.7 3,967 Middle 20.1 25.5 4.3 4.2 0.6 34.6 2.7 4.5 1.7 1.9 100.0 43.5 14.1 3,677 Fourth 23.2 33.0 4.3 3.9 0.8 24.1 2.8 3.1 2.3 2.5 100.0 32.4 13.7 3,347 Highest 42.9 23.2 4.4 6.1 0.5 15.6 1.4 1.8 1.9 2.1 100.0 20.7 10.2 2,882 Total <15 25.5 29.5 3.9 3.7 0.4 28.6 2.2 3.3 1.6 1.3 100.0 35.6 11.6 15,864 Total <18 24.8 27.8 4.6 3.7 0.5 28.3 2.7 3.7 1.9 1.9 100.0 36.6 13.6 18,392 Note: Table is based on de jure household members (i.e., usual residents). Total includes 1 child with missing information on sex. 1 Includes children with father dead, mother dead, both dead, and one parent dead but missing information on the survival status of the other parent 2.8 EDUCATION OF THE HOUSEHOLD POPULATION The educational level of household members is among the most important characteristics of a household because it is associated with many factors that have a significant impact on health-seeking behaviours, reproductive behaviours, use of contraception, and the health of children. Results from the 2013 NDHS can be used to look at educational attainment among household members and school attendance as well as dropout rates among youth. 2.8.1 Educational Attainment Tables 2.11.1 and 2.11.2 show the distribution of female and male household members age 6 and above by the highest level of schooling ever attended (even if they did not complete that level) and the median number of years of education completed according to age, residence, region, and wealth quintile. A comparison of the two tables reveals that there is a gap in educational attainment between females and males. Although the majority of the household population age 6 and older has some education, 12 percent of females have never attended school, as compared with 14 percent of males. Females have completed a median of 6.6 years of schooling, which is 0.6 years more than the median for males (6.0 years). Housing Characteristics and Household Population • 23 Table 2.11.1 Educational attainment of the female household population Percent distribution of the de facto female household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Namibia 2013 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 31.9 67.0 0.0 0.0 0.0 0.0 1.1 100.0 2,111 0.0 10-14 2.2 83.0 5.7 8.5 0.1 0.0 0.5 100.0 2,481 3.8 15-19 2.0 15.5 10.9 60.7 7.4 3.5 0.1 100.0 2,148 7.7 20-24 3.2 6.8 4.2 48.5 22.6 14.4 0.3 100.0 2,052 9.7 25-29 4.6 9.0 5.2 49.0 21.0 10.7 0.4 100.0 1,725 9.4 30-34 6.0 11.6 6.2 45.5 20.0 10.4 0.2 100.0 1,454 9.3 35-39 6.9 16.1 5.2 41.3 20.7 9.0 0.9 100.0 1,298 9.2 40-44 7.0 19.2 5.5 37.4 19.7 10.5 0.6 100.0 1,055 9.2 45-49 12.3 24.5 7.0 29.8 12.9 12.3 1.2 100.0 820 7.8 50-54 14.8 33.6 7.2 23.0 9.2 10.8 1.4 100.0 825 6.1 55-59 23.3 33.5 8.3 20.7 5.0 8.8 0.3 100.0 545 4.9 60-64 28.8 35.7 5.9 16.6 5.4 6.4 1.3 100.0 475 3.8 65+ 43.3 36.5 4.6 7.9 2.3 3.2 2.1 100.0 1,331 1.0 Residence Urban 7.1 24.1 4.4 34.5 17.9 11.5 0.6 100.0 8,805 8.9 Rural 16.9 40.8 6.7 27.7 4.7 2.5 0.8 100.0 9,528 4.8 Region Zambezi 13.3 31.5 4.4 36.2 9.5 4.6 0.6 100.0 911 6.7 Erongo 5.2 25.8 3.6 39.1 18.5 7.5 0.3 100.0 1,311 8.9 Hardap 7.5 34.4 5.8 35.5 12.0 4.6 0.3 100.0 633 7.1 //Karas 7.5 29.7 6.9 38.3 12.9 4.5 0.3 100.0 646 7.5 Kavango 18.7 44.6 8.1 21.3 4.2 1.8 1.3 100.0 1,848 4.1 Khomas 4.5 19.4 3.8 31.4 21.7 18.4 0.8 100.0 3,561 9.6 Kunene 31.7 29.3 2.7 25.7 6.2 3.5 0.9 100.0 522 3.5 Ohangwena 18.7 41.2 5.3 28.1 4.1 2.0 0.5 100.0 2,119 4.5 Omaheke 25.8 29.3 7.0 26.8 6.1 4.2 0.8 100.0 440 4.6 Omusati 14.3 41.4 7.6 29.6 3.6 2.9 0.6 100.0 2,268 5.2 Oshana 6.6 33.1 3.0 35.7 13.5 7.5 0.6 100.0 1,527 7.5 Oshikoto 11.4 35.9 7.1 31.6 9.4 3.9 0.7 100.0 1,501 6.3 Otjozondjupa 16.6 30.2 8.0 29.8 10.2 3.8 1.3 100.0 1,048 6.3 Wealth quintile Lowest 23.0 45.2 7.9 21.1 1.8 0.1 1.0 100.0 3,560 3.4 Second 17.1 40.0 6.4 31.3 4.0 0.7 0.6 100.0 3,459 5.0 Middle 11.9 34.4 5.8 36.2 8.6 2.2 0.9 100.0 3,523 6.4 Fourth 7.3 27.4 5.4 35.9 15.5 8.0 0.5 100.0 3,784 8.2 Highest 3.2 19.0 2.8 30.2 23.3 20.9 0.7 100.0 4,007 9.9 Total 12.2 32.7 5.6 31.0 11.0 6.8 0.7 100.0 18,333 6.6 Note: Total includes 13 children with missing information on age. 1 Completed 7 grades at the primary level 2 Completed 5 grades at the secondary level The percentage of females who have no education decreases from 43 percent among those age 65 and over to 2 percent among those age 10-19. Similarly, the percentage of males who have never been to school decreases from 39 percent in the oldest age group to 3 percent among those age 10-19, indicating that there has been a gradual improvement in the level of education in Namibia over the last few decades. Educational attainment also differs markedly among regions. For example, the largest proportion of the female and male household population over age 6 that has never been to school is found in Kunene (32 percent and 35 percent, respectively). The region with the lowest proportion of household members who have never attended school is Khomas and Erongo for females (5 percent each) and Khomas for males (7 percent). The percentage of males and females who have no education decreases steadily with increasing wealth. 24 • Housing Characteristics and Household Population Table 2.11.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Namibia 2013 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Don’t know/ missing Total Number Median years completed Age 6-9 34.0 64.9 0.0 0.1 0.0 0.0 0.9 100.0 2,035 0.0 10-14 3.4 88.0 3.7 4.4 0.0 0.0 0.5 100.0 2,426 3.4 15-19 3.1 27.3 10.9 53.0 3.6 1.6 0.5 100.0 2,111 7.0 20-24 6.6 12.5 5.8 44.5 20.0 10.1 0.5 100.0 1,892 9.2 25-29 9.7 12.5 5.2 40.4 19.1 12.6 0.5 100.0 1,525 9.3 30-34 9.9 14.8 5.9 35.8 20.6 11.5 1.4 100.0 1,340 9.2 35-39 10.1 17.7 7.1 34.2 18.4 11.5 1.1 100.0 1,160 9.1 40-44 14.0 21.3 5.6 28.9 17.0 12.2 1.1 100.0 933 8.4 45-49 14.7 20.3 7.6 24.5 17.7 13.5 1.7 100.0 747 8.0 50-54 17.2 25.4 7.4 24.3 10.4 14.1 1.2 100.0 538 6.9 55-59 22.1 29.3 4.5 21.9 10.3 11.1 0.8 100.0 364 5.6 60-64 27.6 31.5 5.6 19.1 5.6 8.5 2.2 100.0 334 4.3 65+ 39.4 35.0 2.8 10.2 5.7 4.8 2.1 100.0 834 1.5 Residence Urban 8.7 26.0 4.4 32.0 16.6 11.5 0.9 100.0 7,840 8.5 Rural 18.1 45.4 6.4 22.3 4.6 2.4 1.0 100.0 8,414 4.0 Region Zambezi 8.5 37.3 4.5 30.5 13.5 4.8 0.9 100.0 846 6.6 Erongo 7.6 25.7 4.2 35.8 17.5 8.6 0.5 100.0 1,333 8.4 Hardap 11.4 34.6 6.3 29.9 13.5 3.6 0.6 100.0 587 6.5 //Karas 10.1 29.6 8.3 33.0 12.1 6.5 0.3 100.0 610 7.2 Kavango 19.4 44.3 6.2 20.6 5.1 2.8 1.5 100.0 1,595 3.5 Khomas 6.9 21.6 4.3 30.4 18.7 16.9 1.3 100.0 3,183 9.3 Kunene 34.7 31.0 3.1 21.2 5.2 4.2 0.6 100.0 477 2.8 Ohangwena 19.0 49.3 4.2 21.3 3.0 1.9 1.3 100.0 1,725 3.5 Omaheke 27.0 33.2 6.0 21.8 7.5 3.8 0.8 100.0 493 3.9 Omusati 14.0 49.7 7.8 21.7 3.4 3.0 0.5 100.0 1,757 4.4 Oshana 7.5 39.8 4.1 29.4 11.1 7.9 0.2 100.0 1,311 6.3 Oshikoto 14.5 41.5 7.5 25.4 6.5 3.9 0.9 100.0 1,364 5.0 Otjozondjupa 20.6 30.6 5.2 29.0 10.3 2.8 1.6 100.0 972 5.6 Wealth quintile Lowest 23.8 48.7 6.0 17.6 2.1 0.3 1.4 100.0 3,011 2.8 Second 18.8 43.9 6.0 25.1 4.7 0.8 0.8 100.0 3,257 4.1 Middle 13.4 38.0 6.6 30.4 7.9 2.5 1.2 100.0 3,374 5.7 Fourth 8.7 31.7 5.5 32.4 14.0 7.1 0.6 100.0 3,246 7.4 Highest 4.2 19.3 2.9 28.3 22.2 22.4 0.7 100.0 3,367 9.9 Total 13.5 36.0 5.4 26.9 10.4 6.8 0.9 100.0 16,254 6.0 Note: Total includes 16 children with missing information on age. 1 Completed 7 grades at the primary level 2 Completed 5 grades at the secondary level 2.8.2 School Attendance Ratios The net attendance ratio (NAR) indicates participation in primary schooling for the population age 6-12 and secondary schooling for the population age 13-17. The gross attendance ratio (GAR) measures participation at each level of schooling among those of any age from 5 to 24 years. The GAR is almost always higher than the NAR for the same level because the GAR includes participation by those who may be older or younger than the official age range for that level. An NAR of 100 percent would indicate that all of those in the official age range for a given level are attending at that level. The GAR can exceed 100 percent if there is significant overage or underage participation at a given level of schooling. Table 2.12 provides data on net attendance ratios and gross attendance ratios by sex and level of schooling, according to residence, region, and wealth quintile. The NAR is 90 percent at the primary level and 50 percent at the secondary level. The rural primary school NAR is 88 percent, as compared with 93 percent in urban areas. The NAR is highest in Erongo (96 percent). In general, the NAR at the primary level increases with increasing wealth, from 85 percent in the lowest wealth quintile to 94-95 percent in the highest two quintiles. There have been only very small changes in the NAR and GAR since 2006-07. Housing Characteristics and Household Population • 25 Table 2.12 School attendance ratios Net attendance ratios (NARs) and gross attendance ratios (GARs) for the de facto household population by sex and level of schooling, and the gender parity index (GPI), according to background characteristics, Namibia 2013 Background characteristic Net attendance ratio1 Gross attendance ratio2 Male Female Total Gender parity index3 Male Female Total Gender parity index3 PRIMARY SCHOOL Residence Urban 92.7 93.8 93.3 1.01 128.9 124.5 126.6 0.97 Rural 87.7 88.8 88.2 1.01 135.7 126.9 131.4 0.94 Region Zambezi 94.7 94.2 94.4 0.99 144.2 137.0 140.8 0.95 Erongo 94.7 97.7 96.3 1.03 130.5 124.1 127.2 0.95 Hardap 92.8 96.1 94.5 1.04 124.2 117.7 120.9 0.95 //Karas 92.3 92.0 92.1 1.00 127.5 114.8 120.7 0.90 Kavango 86.0 89.6 87.8 1.04 135.8 135.1 135.4 0.99 Khomas 93.4 94.4 93.9 1.01 123.5 127.3 125.4 1.03 Kunene 66.2 77.6 71.9 1.17 99.9 105.0 102.4 1.05 Ohangwena 87.4 88.6 88.0 1.01 135.4 128.0 131.9 0.95 Omaheke 83.1 83.9 83.5 1.01 111.8 115.4 113.3 1.03 Omusati 90.9 88.1 89.4 0.97 143.1 121.5 131.9 0.85 Oshana 96.4 92.5 94.4 0.96 153.4 122.3 137.5 0.80 Oshikoto 88.4 91.9 90.2 1.04 136.5 135.1 135.8 0.99 Otjozondjupa 84.0 87.9 86.0 1.05 109.6 117.9 114.0 1.08 Wealth quintile Lowest 83.0 87.1 85.0 1.05 132.2 131.3 131.8 0.99 Second 88.5 88.0 88.3 0.99 138.2 124.7 131.7 0.90 Middle 90.5 91.3 90.9 1.01 136.7 124.1 130.4 0.91 Fourth 95.6 94.4 95.0 0.99 133.1 126.1 129.5 0.95 Highest 93.3 94.8 94.1 1.02 123.4 122.1 122.7 0.99 Total 89.5 90.8 90.1 1.01 133.2 126.0 129.6 0.95 SECONDARY SCHOOL Residence Urban 55.3 56.0 55.7 1.01 66.6 67.0 66.8 1.01 Rural 40.2 51.5 45.6 1.28 51.5 61.6 56.4 1.20 Region Zambezi 45.0 55.7 50.7 1.24 70.2 71.6 71.0 1.02 Erongo 51.4 60.1 55.9 1.17 58.0 67.5 62.9 1.16 Hardap 44.2 47.0 45.6 1.06 44.9 50.6 47.7 1.13 //Karas 56.1 63.6 59.5 1.14 66.7 77.8 71.7 1.17 Kavango 33.8 31.9 32.8 0.94 50.0 40.5 45.0 0.81 Khomas 62.6 58.5 60.3 0.93 75.1 70.5 72.5 0.94 Kunene 22.5 38.1 30.0 1.69 33.0 41.2 37.0 1.25 Ohangwena 40.6 49.9 45.1 1.23 52.2 62.7 57.3 1.20 Omaheke 37.9 30.6 34.2 0.81 40.4 31.9 36.2 0.79 Omusati 45.4 62.4 53.5 1.37 57.3 74.4 65.5 1.30 Oshana 50.2 61.4 55.3 1.22 59.3 75.6 66.8 1.28 Oshikoto 41.6 57.5 49.7 1.38 52.8 66.3 59.6 1.26 Otjozondjupa 46.1 49.8 48.2 1.08 49.7 53.5 51.8 1.08 Wealth quintile Lowest 30.9 41.5 36.3 1.34 44.0 49.8 46.9 1.13 Second 36.2 44.9 40.3 1.24 44.9 60.2 52.0 1.34 Middle 47.2 56.0 51.3 1.19 60.0 65.0 62.3 1.08 Fourth 53.5 53.7 53.6 1.00 63.9 65.0 64.5 1.02 Highest 69.0 70.6 69.9 1.02 80.8 79.6 80.1 0.99 Total 45.8 53.4 49.6 1.17 57.1 63.9 60.5 1.12 1 The NAR for primary school is the percentage of the primary school age (A-B years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary school age (C-D 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. The GAR at the primary school level is 130 percent. This figure exceeds the primary school NAR (90 percent) by 40 percentage points, indicating that a large number of children outside the official school age population are attending primary school. At the secondary level, the GAR (61 percent) is somewhat closer to the NAR (50 percent), indicating that fewer youth outside of the official school age population are attending secondary school than is the case for primary school. 26 • Housing Characteristics and Household Population At the primary school level, the GPI is more than 1 for the NAR and 0.95 for the GAR, but both are more than 1 at the secondary school level. This means that there is a greater gender disparity in favour of females in secondary school than in primary school. This parity difference is especially pronounced between urban and rural areas. The GPI associated with the secondary school NAR in rural areas is 1.28, as compared with 1.01 in urban areas; the GPI associated with the secondary school GAR is 1.20 and 1.01 in rural areas and urban areas, respectively. Large differences in GPI are also observed by region. The difference in the GPI for both the NAR and GAR by wealth quintile is more pronounced at the secondary level. Age-specific attendance rates (ASARs) for the population age 5 to 24—that is, the percentage of a given age cohort that attends school, regardless of the level attended (primary, secondary, or higher)—are shown in Figure 2.2. Up to age 14, a higher percentage of females than males attend school. From age 15- 20, a higher percentage of males than females attend school. Beyond age 20, females are more likely to be in school than males. Figure 2.2 Age-specific attendance rates 2.9 UTILISATION OF HEALTH SERVICES AND OUT-OF-POCKET EXPENDITURE FOR HEALTH CARE The 2013 NDHS collected data in the Household Questionnaire on utilisation of health services by household members. Information on inpatient visits was collected for each household from just a single member who was admitted for an overnight stay at a health facility in the six months preceding the survey. This information included place of admission, the cost of treatment and services received during the most recent visit (including the cost of laboratory tests, drugs, and other items), the main reason for seeking care, and the total number of times the individual stayed overnight at a health facility in the preceding six months. Information on outpatient visits was also collected from a single household member who consulted a health care facility, provider, pharmacy, or traditional healer for health care in the four weeks preceding the survey without staying overnight. Information on outpatient care included the place where care was most recently received, the cost of treatment and services received (including the cost of consulting fees and expenses, as well as other items such as drugs and tests), the main reason for seeking care, and the number of times the individual received care in the last four weeks without staying overnight. 0 10 20 30 40 50 60 70 80 90 100 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Percent Age (years) Male Female NDHS 2013 Housing Characteristics and Household Population • 27 Caution should be exercised when interpreting the data collected on inpatient and outpatient health care visits since this information refers to only one person from each household who was not selected at random, but rather selected on the basis of the most recent visit during the reference period (six months for inpatient care and four weeks for outpatient care). These data cannot be extrapolated to provide information on the number of annual outpatient visits per capita among women and men in Namibia, nor can they provide the annual number of inpatient admissions. The information is meant to simply provide insight into the general level of out-of-pocket expenditure on inpatient and outpatient visits. Table 2.13.1 shows that 14 percent of households had a member who stayed overnight at a health facility in the past six months. Inpatient visits were most common in households in Kavango (20 percent) and least common in Omaheke (10 percent). The average expenditure for the most recent visit was 798 Namibian dollars (NAD) (about US$75) for men and 817 NAD (about US$77) for women. Men had an average of 3.6 inpatient stays, as compared with women’s average of 2.9 inpatient stays. Not surprisingly, men and women in urban areas and in the highest wealth quintile paid much more on average for inpatient visits than men and women in rural areas or in the other wealth quintiles. Table 2.13.1 Health expenditure: Inpatient visits Percentage of households with a member who was admitted to stay overnight at a health facility in the last six months, average cost of health care (in Namibia dollars) during the most recent overnight stay, and average number of inpatient visits for this particular household member (unweighted), Namibia 2013 Background characteristic Percentage of households with a member who stayed overnight in a health facility in the past 6 months Number of households Men Women Average health expenditure for the most recent visit Average number of inpatient visits Number of households Average health expenditure for the most recent visit Average number of inpatient visits Number of households Age <5 na 211 291 3.3 120 185 3.4 91 5-14 na 84 (827) (2.0) 52 (258) (3.6) 32 15-24 na 185 (651) (3.5) 37 85 2.0 148 25-34 na 301 820 4.9 82 1,460 2.1 218 35-44 na 203 361 4.4 77 299 2.1 126 45-54 na 122 (1,730) (2.8) 45 2,670 4.1 77 55-64 na 96 (1,154) (2.6) 41 1,021 6.2 54 65+ na 149 1,290 3.6 81 149 3.4 67 Residence Urban 13.6 5,121 1,424 2.7 249 1,076 2.7 447 Rural 14.0 4,728 259 4.3 289 501 3.0 366 Region Zambezi 15.4 541 (57) (1.8) 31 51 1.3 51 Erongo 13.0 930 (1,294) (2.1) 39 971 1.5 81 Hardap 12.4 381 * * 12 1,315 2.9 35 //Karas 13.0 406 (1,943) (2.2) 22 1,648 3.4 30 Kavango 20.2 737 252 7.6 62 53 5.4 80 Khomas 12.3 2,015 (1,975) (3.7) 91 1,843 2.0 156 Kunene 12.5 354 (92) (4.5) 16 148 2.1 28 Ohangwena 13.7 900 (33) (5.9) 55 (54) (4.0) 68 Omaheke 9.5 335 (529) (1.5) 16 (111) (1.4) 15 Omusati 15.3 949 181 2.9 75 664 3.5 70 Oshana 12.8 831 (1,848) (2.2) 34 833 2.0 72 Oshikoto 13.1 817 (292) (2.0) 38 527 2.8 69 Otjozondjupa 15.4 652 790 2.3 45 765 4.5 56 Wealth quintile Lowest 14.7 1,737 82 4.3 126 42 4.2 124 Second 14.2 1,910 209 4.6 108 75 2.7 161 Middle 12.7 1,954 195 3.6 86 51 2.5 161 Fourth 14.7 2,136 476 2.8 116 431 3.0 196 Highest 12.9 2,111 3,180 2.5 102 3,258 2.2 170 Total 13.8 9,849 798 3.6 538 817 2.9 813 Note: Total includes 1 man with missing information on age. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable Table 2.13.2 shows that 36 percent of households reported a member who had sought care from a health provider, pharmacy, or traditional healer without staying overnight in the four weeks preceding the survey. Outpatient visits are more common in rural (39 percent) than urban areas (33 percent) and most common in Omusati (51 percent). Differences by wealth quintile are small. Outpatient visits are less 28 • Housing Characteristics and Household Population expensive than inpatient visits. Men paid an average of 99 NAD (about US$10) and women an average of 161 NAD (about US$15) for an outpatient visit. There is only a minimal difference in the average number of outpatient visits by men (1.6) and women (1.5). Both men and women incurred costs for an average of 1.2 outpatient visits. Outpatient visits were most expensive for men in Hardap and least expensive for men in Omusati. On the other hand, women in Otjozondjupa paid the most for an outpatient visit and women in Ohangwena paid the least. Among both men and women, outpatient visits were much more expensive in urban than rural areas and for households in the highest wealth quintile. Table 2.13.2 Health expenditure: Outpatient visits Percentage of households with a member who received care from a health provider, a pharmacy, or a traditional healer without staying overnight in the last four weeks, average cost of health care (in Namibia dollars) during the most recent visit, average number of outpatient visits for this particular household member, and average number of outpatient visits for which money was spent (unweighted), Namibia 2013 Background characteristic Percentage of households with a member who had an outpatient visit in the past 4 weeks Number of households Men Women Average health expenditure for the most recent visit Average number of outpatient visits Average number of outpatient visits for which money was spent Number of households Average health expenditure for the most recent visit Average number of outpatient visits Average number of outpatient visits for which money was spent Number of households Age <5 na 594 39 1.4 1.2 316 44 1.5 1.3 278 5-14 na 312 42 1.6 1.2 143 46 1.3 1.1 169 15-24 na 402 79 1.4 1.2 167 63 1.7 1.4 235 25-34 na 527 50 1.7 1.2 196 65 1.5 1.2 331 35-44 na 498 148 1.7 1.4 207 467 1.4 1.2 291 45-54 na 422 184 1.7 1.3 156 365 1.7 1.5 266 55-64 na 296 158 1.6 1.3 126 42 1.5 1.1 170 65+ na 457 156 1.4 0.9 156 107 1.5 0.9 300 Residence Urban 32.5 5,121 149 1.6 1.3 715 284 1.6 1.3 945 Rural 39.1 4,728 51 1.5 1.1 751 55 1.5 1.2 1,099 Region Zambezi 42.8 541 31 1.8 1.4 106 84 1.9 1.4 126 Erongo 31.2 930 112 1.5 1.3 146 67 1.5 1.2 145 Hardap 24.6 381 538 1.3 0.9 37 65 1.1 0.8 57 //Karas 35.8 406 95 1.5 1.0 62 80 1.4 1.2 82 Kavango 37.5 737 26 1.7 1.3 110 22 1.6 1.2 166 Khomas 28.9 2,015 241 1.8 1.5 229 447 1.6 1.3 348 Kunene 20.9 354 97 1.2 1.1 26 129 1.4 1.2 48 Ohangwena 45.0 900 12 1.4 1.0 164 11 1.4 0.9 241 Omaheke 34.0 335 160 1.5 1.4 57 210 1.5 1.1 56 Omusati 50.5 949 7 1.5 1.1 171 15 1.5 1.3 308 Oshana 36.3 831 59 1.4 1.2 137 68 1.5 1.4 163 Oshikoto 37.5 817 32 1.7 1.1 122 113 1.2 1.1 185 Otjozondjupa 33.3 652 148 1.3 1.1 99 689 1.9 1.4 118 Wealth quintile Lowest 37.4 1,737 12 1.6 1.2 256 8 1.5 1.1 394 Second 34.5 1,910 21 1.7 1.2 278 305 1.5 1.1 381 Middle 36.5 1,954 16 1.6 1.2 308 70 1.5 1.2 406 Fourth 33.1 2,136 92 1.6 1.4 296 86 1.6 1.3 409 Highest 37.3 2,111 316 1.4 1.1 328 322 1.5 1.3 454 Total 35.7 9,849 99 1.6 1.2 1,466 161 1.5 1.2 2,044 Note. Total includes 3 women with missing information on age. na = Not applicable Characteristics of Survey Respondents • 29 CHARACTERISTICS OF SURVEY RESPONDENTS 3 his chapter presents information on key demographic and socioeconomic characteristics of the survey respondents, including age, religion, marital status, residence, education, literacy, and media access. The chapter also explores adult employment status, occupation, and earnings. The information contained in this chapter provides a useful context within which the demographic and health indices discussed in the remainder of the report should be understood. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 shows the background characteristics of the 9,176 women and 3,950 men age 15-49 interviewed in the 2013 NDHS. In addition, as explained in Chapter 1, interviews on selected sections of the questionnaires were conducted with 842 women and 531 men age 50-64 in a subsample of half of the households selected for the male survey. Overall, 57 percent of women and 59 percent of men are below the age of 30. The highest proportions of respondents however, fall in the 15-19 age group with 21 percent of women and 23 percent of men falling within this age group. These percentages decrease steadily to reach 8 percent and 7 percent, respectively, in the 45-49 age group. The Namibian population is predominantly Christian. The majority (44 percent of women and 43 percent of men) belong to the Evangelical Lutheran Church in Namibia (ELCIN). Twenty percent of women and 26 percent of men reported being Roman Catholic while 21 percent of women and 13 percent of men reported being Protestant or Anglican. A large majority of respondents age 15-49 (60 percent of women and 68 percent of men) have never been married. Thirty-four percent of women and 29 percent of men are currently married or living together with a partner as if married, while 7 percent and 3 percent, respectively, are divorced, separated, or widowed. T Key Findings • A total of 9,176 women and 3,950 men age 15-49 were interviewed as part of the 2013 NDHS. • In half of the households selected for the male survey, partial interviews were conducted with 842 women and 531 men age 50-64. • Five percent of women and 8 percent of men age 15-49 have no education. The majority of respondents (76 percent of women and 69 percent of men) have a secondary education or higher. • Literacy rates are high in Namibia: 93 percent of women and 91 percent of men are literate. • Forty-three percent of women and 56 percent of men age 15-49 are currently employed. • Among women who were employed in the past 12 months, the majority work in sales and services (58 percent). Men are most likely to be employed in skilled manual work (33 percent) and sales and services (30 percent). • Three percent of women and 9 percent of men work in agriculture. • Thirty-six percent of women who work in agriculture are not paid for their work. 30 • Characteristics of Respondents Fifty-seven percent of the respondents reside in urban areas, while 43 percent reside in rural areas. By region, Khomas (where Windhoek, the capital city, is located) had the highest proportion of both female and male respondents (24 percent and 25 percent, respectively), whereas Kunene, Omaheke, Hardap, and //Karas had the lowest proportions of respondents (3-4 percent). Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Namibia 2013 Background characteristic Women Men Weighted percent Weighted number Unweighted number Weighted percent Weighted number Unweighted number Age 15-19 20.8 1,906 1,857 22.9 922 883 20-24 19.5 1,786 1,720 20.1 808 771 25-29 16.2 1,489 1,495 16.4 658 613 30-34 13.7 1,260 1,262 12.9 520 516 35-39 12.1 1,110 1,146 11.1 448 454 40-44 10.0 917 942 9.3 376 404 45-49 7.7 708 754 7.2 289 309 Religion Roman Catholic 19.6 1,802 1,892 25.9 1,041 1,031 Protestant/Anglican 21.2 1,947 2,049 12.7 511 511 ELCIN 44.0 4,035 3,783 43.4 1,745 1,571 Seventh-Day Adventist 4.8 436 522 4.0 161 192 No religion 1.1 105 129 1.8 72 100 Other 9.0 827 779 12.0 483 537 Missing 0.3 23 22 0.2 9 8 Marital status Never married 59.5 5,458 5,188 68.3 2,745 2,577 Married 17.9 1,644 1,779 15.1 609 657 Living together 16.1 1,476 1,587 13.7 551 587 Divorced/separated 4.4 408 429 2.6 106 118 Widowed 2.1 189 193 0.2 10 11 Residence Urban 56.6 5,190 4,843 56.8 2,282 1,998 Rural 43.4 3,986 4,333 43.2 1,739 1,952 Region Zambezi 5.0 457 647 5.4 218 291 Erongo 8.4 771 858 9.3 372 421 Hardap 3.3 304 595 3.8 152 299 //Karas 3.7 343 782 3.8 151 333 Kavango 9.1 835 743 7.9 316 281 Khomas 24.0 2,202 986 25.4 1,023 415 Kunene 2.8 258 584 2.6 104 252 Ohangwena 9.7 894 695 8.2 328 255 Omaheke 2.5 225 535 2.6 103 256 Omusati 9.6 884 725 8.5 342 262 Oshana 8.2 755 671 8.3 335 274 Oshikoto 7.7 707 656 8.3 335 302 Otjozondjupa 5.9 540 699 6.0 241 309 Education No education 4.6 419 551 7.7 310 379 Primary 19.6 1,798 1,914 23.5 944 978 Secondary 65.7 6,029 6,019 59.7 2,400 2,307 More than secondary 10.1 930 692 9.1 368 286 Wealth quintile Lowest 15.6 1,429 1,461 14.8 594 605 Second 17.7 1,625 1,661 19.1 769 768 Middle 19.6 1,795 1,903 22.0 886 897 Fourth 23.1 2,116 2,162 22.8 917 913 Highest 24.1 2,211 1,989 21.3 855 767 Total 15-49 100.0 9,176 9,176 100.0 4,021 3,950 50-64 0.0 797 842 0.0 460 531 Total 15-64 0.0 9,973 10,018 0.0 4,481 4,481 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. ELCIN = Evangelical Lutheran Church in Namibia Education is an important determinant of the other demographic and health characteristics of individuals and the societies to which they belong. The proportion of respondents with no education is low (5 percent of women and 8 percent of men). The majority of respondents (76 percent of women and 69 percent of men) have a secondary education or higher. Characteristics of Survey Respondents • 31 3.2 EDUCATIONAL ATTAINMENT BY BACKGROUND CHARACTERISTICS Tables 3.2.1 and 3.2.2 show the educational attainment of women and men age 15-49, respectively, by background characteristics. As mentioned above, the level of education in Namibia is high, with only 5 percent of women and 8 percent of men having no formal education. As expected, the proportion of respondents with no education increases with age, from 2 percent among women and men age 15-19 to 12 percent among women age 45-49 and 13 percent among men age 40-44. Respondents in rural areas are less likely to be educated than their urban counterparts; 7 percent of women and 11 percent of men in rural areas have no education, as compared with 3 percent and 5 percent, respectively, of women and men in urban areas. The proportion of women and men with no education is highest in Kunene (22 percent and 30 percent, respectively) and lowest in Erongo and Oshana among women (1 percent each) and Oshana among men (2 percent). The percentage of women and men with no education decreases with increasing wealth. Ten percent of women and 15 percent of men in the lowest wealth quintile have no education, as compared with less than 1 percent each among respondents in the highest wealth quintile. Women are more likely to reach higher levels of education than men. For example, 48 percent of women have some secondary education, compared with 44 percent of men. Tables 3.2.1 and 3.2.2 further show that women have a median of 9.1 years of schooling while men have a median of 8.7 years of schooling. Median number of years of schooling is higher among women and men age 20-29, those residing in urban areas and in Khomas, and those in the wealthiest quintile than among their counterparts in the other groups. Overall, the results show that there have been improvements in educational attainment since the 2006-07 NDHS. For example, median number of years of schooling completed has increased from 8.5 to 9.1 among women and from 7.2 to 8.7 among men. 32 • Characteristics of Respondents Table 3.2.1 Educational attainment: Women Percent distribution of women age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Namibia 2013 Background characteristic Highest level of schooling Total Median years completed Number of women No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 1.8 10.5 6.8 55.5 15.5 10.0 100.0 8.9 3,691 15-19 1.6 14.3 9.1 62.4 8.0 4.6 100.0 8.1 1,906 20-24 2.0 6.5 4.2 48.2 23.4 15.7 100.0 9.7 1,786 25-29 4.2 10.3 4.7 48.2 21.8 10.9 100.0 9.4 1,489 30-34 5.9 11.6 6.2 46.4 20.0 9.9 100.0 9.3 1,260 35-39 6.1 16.3 5.8 42.9 19.9 9.1 100.0 9.1 1,110 40-44 7.2 19.8 5.3 38.3 19.6 9.8 100.0 9.1 917 45-49 11.6 26.2 7.4 30.5 12.3 12.0 100.0 7.8 708 Residence Urban 3.1 8.3 4.3 44.7 24.4 15.2 100.0 9.7 5,190 Rural 6.5 20.2 8.5 52.1 9.3 3.5 100.0 8.0 3,986 Region Zambezi 5.0 12.6 4.6 57.8 15.0 5.0 100.0 8.7 457 Erongo 1.0 9.1 4.2 51.7 24.6 9.4 100.0 9.6 771 Hardap 3.2 12.8 7.1 54.8 16.9 5.2 100.0 9.0 304 //Karas 1.7 12.1 6.6 55.0 18.1 6.6 100.0 9.1 343 Kavango 6.6 31.4 10.8 36.0 12.5 2.7 100.0 7.1 835 Khomas 2.0 5.4 3.3 37.6 27.2 24.4 100.0 11.1 2,202 Kunene 21.9 18.1 4.1 42.7 9.3 3.9 100.0 7.6 258 Ohangwena 4.8 21.6 7.7 54.2 8.3 3.3 100.0 7.9 894 Omaheke 17.2 16.0 7.8 45.2 9.7 4.1 100.0 7.8 225 Omusati 4.4 14.7 9.8 59.2 7.9 3.9 100.0 8.2 884 Oshana 0.9 8.9 2.7 53.8 22.8 10.9 100.0 9.5 755 Oshikoto 5.2 12.8 7.5 52.3 15.9 6.3 100.0 8.7 707 Otjozondjupa 9.5 15.1 8.3 46.5 15.6 4.9 100.0 8.6 540 Wealth quintile Lowest 10.3 30.0 11.3 43.8 4.3 0.2 100.0 6.7 1,429 Second 7.5 20.3 9.1 55.2 7.1 0.9 100.0 7.8 1,625 Middle 4.7 13.4 6.5 56.3 15.3 3.9 100.0 8.8 1,795 Fourth 2.5 8.3 4.7 49.9 25.0 9.6 100.0 9.6 2,116 Highest 0.5 2.8 1.8 36.3 29.6 29.0 100.0 11.3 2,211 Total 4.6 13.5 6.1 47.9 17.8 10.1 100.0 9.1 9,176 1 Completed 7th grade at the primary level 2 Completed 5th grade at the secondary level Characteristics of Survey Respondents • 33 Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Namibia 2013 Background characteristic Highest level of schooling Total Median years completed Number of men No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Age 15-24 3.6 16.2 7.4 53.5 13.5 5.8 100.0 8.3 1,730 15-19 1.8 21.5 9.0 58.9 6.9 1.9 100.0 7.5 922 20-24 5.7 10.1 5.7 47.3 21.0 10.2 100.0 9.3 808 25-29 9.6 11.4 5.5 42.4 19.2 11.8 100.0 9.3 658 30-34 10.3 15.9 6.4 36.4 19.4 11.5 100.0 9.2 520 35-39 10.3 18.6 5.7 36.9 18.5 9.9 100.0 9.1 448 40-44 13.2 21.1 5.8 30.2 15.9 13.9 100.0 8.5 376 45-49 12.0 22.5 11.3 28.1 14.6 11.4 100.0 7.5 289 Residence Urban 4.9 9.8 4.5 45.7 22.1 13.1 100.0 9.5 2,282 Rural 11.4 25.4 10.1 40.9 8.2 4.0 100.0 7.0 1,739 Region Zambezi 4.5 19.7 4.6 40.7 24.8 5.7 100.0 9.2 218 Erongo 4.8 9.4 5.7 48.6 21.4 10.0 100.0 9.4 372 Hardap 5.4 18.8 6.8 48.4 17.1 3.5 100.0 9.0 152 //Karas 3.0 13.9 7.8 49.3 18.2 7.7 100.0 9.0 151 Kavango 12.1 21.5 8.0 42.8 9.7 5.9 100.0 7.3 316 Khomas 4.1 8.5 4.7 40.7 24.5 17.5 100.0 9.8 1,023 Kunene 30.2 17.8 7.4 30.0 8.7 5.9 100.0 6.2 104 Ohangwena 13.6 24.3 5.4 47.7 5.6 3.5 100.0 6.8 328 Omaheke 19.2 24.6 7.3 34.6 8.9 5.5 100.0 6.8 103 Omusati 3.5 25.2 16.2 44.4 6.1 4.7 100.0 7.2 342 Oshana 2.1 17.2 6.6 47.2 15.4 11.5 100.0 9.1 335 Oshikoto 13.7 25.6 7.9 39.7 7.5 5.6 100.0 7.1 335 Otjozondjupa 11.7 12.8 5.9 49.1 17.7 2.7 100.0 8.6 241 Wealth quintile Lowest 15.3 32.2 10.7 35.8 6.0 0.0 100.0 6.2 594 Second 13.1 24.8 9.1 43.8 8.1 1.1 100.0 7.0 769 Middle 8.9 19.7 9.2 47.8 9.7 4.7 100.0 7.9 886 Fourth 3.5 9.6 5.4 49.6 20.5 11.4 100.0 9.4 917 Highest 0.8 2.4 1.6 38.2 32.0 24.9 100.0 11.2 855 Total 15-49 7.7 16.5 6.9 43.6 16.1 9.1 100.0 8.7 4,021 1 Completed 7th grade at the primary level 2 Completed 5th grade at the secondary level 3.3 LITERACY The ability to read and write is an important personal asset, enhancing people’s ability to access information and connect with opportunities for enhancing their socioeconomic well-being. In addition, knowledge of the literacy level of the population can help health and development workers determine how to package and communicate their messages. In the 2013 NDHS, the literacy status of respondents who had not attended school or had attended only primary school was determined by assessing their ability to read all or part of a sentence. Respondents with a secondary education or higher were assumed to be literate. Tables 3.3.1 and 3.3.2 show the percent distributions of women and men, respectively, by level of schooling attended and level of literacy, as well as the percentage of respondents who are literate, according to background characteristics. The literacy rate in Namibia is generally high, with more than nine in ten respondents being literate (93 percent of women and 91 percent of men). Literacy level tends to decrease with age, especially among women. Ninety-six percent of women age 15-24 are literate, as compared with 86 percent of women age 45-49. Women and men in urban areas (96 percent and 95 percent, respectively) are more likely to be literate than those in rural areas (90 percent and 85 percent, respectively). Variations also exist by region. The literacy rate among women ranges from 77 percent in Kunene and Omaheke to 98 percent in Erongo and Oshana. Among men, literacy rate is highest in Khomas (97 percent) and lowest in Kunene and Omaheke (71 percent each). Literacy increases with increasing wealth among both women and men. For 34 • Characteristics of Respondents example, 86 percent of women in the lowest wealth quintile are literate, as compared with 99 percent of those in the highest wealth quintile. The corresponding percentages for men are 79 percent and 99 percent, respectively. Table 3.3.1 Literacy: Women Percent distribution of women age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Namibia 2013 Background characteristic Secondary school or higher No schooling or primary school Percent- age literate1 Number of women Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/visually impaired Total Age 15-24 80.9 11.7 3.3 3.0 0.7 0.0 100.0 95.9 3,691 15-19 75.0 17.2 3.6 2.9 1.1 0.1 100.0 95.7 1,906 20-24 87.3 5.9 2.9 3.1 0.3 0.0 100.0 96.2 1,786 25-29 80.8 9.0 4.1 5.0 0.7 0.0 100.0 93.9 1,489 30-34 76.3 12.9 3.7 6.0 0.6 0.1 100.0 92.9 1,260 35-39 71.9 14.7 4.4 7.5 0.9 0.0 100.0 91.0 1,110 40-44 67.7 17.0 7.0 5.4 2.4 0.0 100.0 91.7 917 45-49 54.8 22.8 8.6 11.4 1.8 0.3 100.0 86.2 708 Residence Urban 84.3 8.8 2.9 3.1 0.5 0.0 100.0 95.9 5,190 Rural 64.8 19.0 6.4 7.9 1.5 0.1 100.0 90.2 3,986 Region Zambezi 77.8 8.2 6.0 7.7 0.2 0.0 100.0 92.1 457 Erongo 85.7 9.3 2.5 2.1 0.0 0.0 100.0 97.6 771 Hardap 76.9 12.7 5.9 4.1 0.1 0.0 100.0 95.4 304 //Karas 79.6 11.2 5.1 2.0 1.6 0.1 100.0 95.9 343 Kavango 51.1 23.1 16.0 8.9 0.5 0.1 100.0 90.3 835 Khomas 89.2 5.4 1.8 2.4 0.6 0.0 100.0 96.5 2,202 Kunene 55.9 15.5 5.1 22.5 0.4 0.0 100.0 76.5 258 Ohangwena 65.9 21.5 4.2 3.2 4.8 0.2 100.0 91.6 894 Omaheke 59.0 10.3 7.9 20.9 1.5 0.0 100.0 77.2 225 Omusati 71.0 19.9 2.9 5.5 0.0 0.0 100.0 93.9 884 Oshana 87.5 10.1 0.4 1.9 0.0 0.0 100.0 98.0 755 Oshikoto 74.5 17.4 3.0 4.7 0.2 0.0 100.0 94.9 707 Otjozondjupa 67.0 14.9 5.4 9.3 2.8 0.2 100.0 87.3 540 Wealth quintile Lowest 48.4 26.0 11.2 11.5 2.4 0.2 100.0 85.6 1,429 Second 63.2 19.4 6.4 9.1 1.4 0.0 100.0 89.0 1,625 Middle 75.5 14.0 3.8 5.5 0.9 0.0 100.0 93.2 1,795 Fourth 84.5 9.3 2.5 2.7 0.4 0.0 100.0 96.3 2,116 Highest 94.9 3.4 0.9 0.5 0.3 0.0 100.0 99.2 2,211 Total 75.8 13.2 4.4 5.2 1.0 0.0 100.0 93.4 9,176 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence Characteristics of Survey Respondents • 35 Table 3.3.2 Literacy: Men Percent distribution of men age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Namibia 2013 Background characteristic Secondary school or higher No schooling or primary school Percentage literate1 Number of men Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Total Age 15-24 72.8 14.8 5.3 5.9 0.7 0.0 100.0 92.8 1,730 15-19 67.7 21.5 4.7 4.7 0.8 0.0 100.0 93.9 922 20-24 78.5 7.1 6.0 7.3 0.7 0.0 100.0 91.6 808 25-29 73.5 7.3 9.2 9.8 0.3 0.0 100.0 89.9 658 30-34 67.4 11.9 8.4 11.4 0.3 0.0 100.0 87.7 520 35-39 65.4 10.0 14.7 8.3 0.9 0.0 100.0 90.2 448 40-44 59.9 13.8 12.4 12.5 0.6 0.5 100.0 86.1 376 45-49 54.2 21.4 13.5 10.3 0.5 0.2 100.0 89.0 289 Residence Urban 80.8 7.8 6.1 4.3 0.5 0.0 100.0 94.7 2,282 Rural 53.1 19.9 12.0 13.9 0.7 0.1 100.0 84.9 1,739 Region Zambezi 71.2 9.1 8.0 9.6 0.5 0.0 100.0 88.3 218 Erongo 80.1 9.6 5.8 3.5 0.6 0.0 100.0 95.4 372 Hardap 69.0 10.6 11.0 6.8 2.1 0.4 100.0 90.6 152 //Karas 75.3 15.0 3.4 3.9 0.7 0.3 100.0 93.7 151 Kavango 58.4 12.2 11.3 14.1 2.5 0.4 100.0 82.0 316 Khomas 82.7 6.4 7.5 2.9 0.4 0.0 100.0 96.6 1,023 Kunene 44.6 11.8 14.7 27.9 0.4 0.1 100.0 71.2 104 Ohangwena 56.8 16.7 9.1 17.4 0.0 0.0 100.0 82.6 328 Omaheke 48.9 5.0 17.2 26.3 2.1 0.0 100.0 71.1 103 Omusati 55.2 25.5 13.9 5.4 0.0 0.0 100.0 94.6 342 Oshana 74.1 21.4 0.3 3.5 0.0 0.0 100.0 95.8 335 Oshikoto 52.8 19.5 13.5 13.9 0.3 0.0 100.0 85.8 335 Otjozondjupa 69.6 11.7 7.3 10.3 0.2 0.0 100.0 88.6 241 Wealth quintile Lowest 41.8 22.1 14.7 19.3 1.6 0.2 100.0 78.6 594 Second 53.0 18.7 12.4 14.3 0.8 0.0 100.0 84.1 769 Middle 62.2 16.3 11.1 9.3 0.8 0.0 100.0 89.6 886 Fourth 81.4 8.8 6.0 2.9 0.1 0.1 100.0 96.3 917 Highest 95.2 2.7 1.3 0.7 0.0 0.0 100.0 99.2 855 Total 15-49 68.8 13.0 8.6 8.4 0.6 0.1 100.0 90.5 4,021 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence 3.4 EXPOSURE TO MASS MEDIA The 2013 NDHS collected information on respondents’ exposure to common print and electronic media. Respondents were asked how often they read a newspaper,1 listened to the radio, or watched television. The mass media in Namibia serve as an important channel for conveying messages on family planning, malaria, HIV/AIDS awareness, and other health-related issues. Tables 3.4.1 and 3.4.2 show the percentages of women and men, respectively, who were exposed to the different types of mass media by age, residence, region, level of education, and wealth quintile. Radio is the most commonly used type of mass media among both men and women, with 58 percent and 60 percent, respectively, listening to the radio at least once a week. More than four in ten women and men (42 percent and 44 percent, respectively) watch television at least once a week. Thirty-nine percent of women read a newspaper at least once a week. Overall, 21 percent of women have access to all three media (radio, television, and newspaper) at least once per week. Urban women are substantially more likely to be exposed to all three media (33 percent) than rural women (6 percent). There exist wide regional variations with respect to media exposure. About four in ten women in Khomas (41 percent), Hardap (40 percent), and Erongo (38 percent) 1 Data for men who read a newspaper at least once a week are not shown due to a problem in the data entry programme. The responses from men with a secondary education or higher were not entered, resulting in a gross underestimate of men’s exposure to this type of media. 36 • Characteristics of Respondents are exposed to all three media, as compared with only 2 percent of women in Omusati and 5 percent of those in Kavango. Women’s exposure to all three media increases notably with increasing education and wealth. Among men, 34 percent have access to both media (radio and television) at least once per week (as noted, data for men who read a newspaper at least once a week are not shown). Similar to women, urban men (51 percent) are much more likely to be exposed to both of these types of media than rural men (11 percent). Access to the two specified media ranges from 8 percent among men in Omusati to 74 percent among those in Erongo. Men’s exposure to both radio and television increases steadily as their education and wealth increase. Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Namibia 2013 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15-19 36.0 40.2 52.5 17.9 30.6 1,906 20-24 43.7 47.0 56.9 24.1 24.4 1,786 25-29 40.8 45.8 57.3 21.8 25.6 1,489 30-34 40.1 40.6 59.7 21.2 25.6 1,260 35-39 35.6 38.1 60.7 21.4 28.4 1,110 40-44 38.7 37.8 60.7 21.7 26.5 917 45-49 35.4 36.8 62.3 21.8 29.0 708 Residence Urban 55.4 61.9 63.9 33.2 15.0 5,190 Rural 17.7 15.5 49.6 5.8 42.8 3,986 Region Zambezi 17.9 36.2 58.4 10.6 30.7 457 Erongo 60.4 65.3 66.4 38.4 11.5 771 Hardap 56.5 68.7 73.4 39.5 11.7 304 //Karas 34.0 51.8 53.4 17.5 23.7 343 Kavango 10.3 21.6 33.8 4.8 54.8 835 Khomas 69.8 67.2 67.3 40.9 8.6 2,202 Kunene 23.2 42.7 58.3 13.4 31.5 258 Ohangwena 15.7 15.4 58.4 5.6 35.6 894 Omaheke 22.3 33.9 66.4 10.7 23.9 225 Omusati 15.2 6.1 36.6 2.2 55.8 884 Oshana 41.3 33.4 61.4 19.8 27.2 755 Oshikoto 33.1 29.0 60.9 12.5 26.4 707 Otjozondjupa 35.5 51.7 56.4 22.8 28.3 540 Education No education 2.1 15.5 44.0 0.9 51.3 419 Primary 13.8 18.0 46.8 5.7 45.3 1,798 Secondary 43.4 45.1 61.0 23.3 23.0 6,029 More than secondary 76.0 77.8 63.3 47.5 7.2 930 Wealth quintile Lowest 9.9 4.0 40.5 1.4 55.4 1,429 Second 18.3 8.3 49.2 4.0 45.0 1,625 Middle 31.7 23.4 59.6 8.8 28.7 1,795 Fourth 48.1 65.8 63.5 30.0 14.5 2,116 Highest 70.4 82.6 68.0 48.6 6.4 2,211 Total 39.0 41.8 57.7 21.3 27.1 9,176 Characteristics of Survey Respondents • 37 Table 3.4.2 Exposure to mass media: Men Percentage of men age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Namibia 2013 Background characteristic Watches television at least once a week Listens to the radio at least once a week Accesses both media at least once a week Accesses neither of the two media at least once a week Number of men Age 15-19 41.0 54.0 29.8 34.8 922 20-24 42.3 55.9 30.0 31.7 808 25-29 43.7 64.1 34.1 26.2 658 30-34 47.4 63.0 36.7 26.3 520 35-39 44.1 66.1 35.9 25.6 448 40-44 45.8 59.8 39.4 33.8 376 45-49 48.5 72.6 44.3 23.2 289 Residence Urban 63.9 68.3 51.3 19.1 2,282 Rural 17.7 50.1 11.4 43.7 1,739 Region Zambezi 29.2 49.1 19.7 41.4 218 Erongo 80.7 85.8 74.1 7.6 372 Hardap 52.2 49.1 27.4 26.1 152 //Karas 64.4 71.3 51.3 15.6 151 Kavango 22.9 40.6 14.3 50.8 316 Khomas 68.9 74.4 55.9 12.6 1,023 Kunene 38.2 54.5 28.9 36.3 104 Ohangwena 17.6 56.1 11.4 37.7 328 Omaheke 22.8 57.3 18.1 38.0 103 Omusati 15.1 41.1 7.8 51.6 342 Oshana 24.2 38.0 11.7 49.4 335 Oshikoto 20.0 63.7 14.6 30.9 335 Otjozondjupa 52.1 62.2 46.7 32.4 241 Education No education 13.7 51.1 12.8 48.1 310 Primary 25.0 52.4 18.6 41.2 944 Secondary 50.2 63.8 39.2 25.2 2,400 More than secondary 76.4 66.8 57.9 14.7 368 Wealth quintile Lowest 7.2 40.7 3.9 56.0 594 Second 14.7 57.5 10.9 38.8 769 Middle 27.7 55.7 20.2 36.8 886 Fourth 70.4 68.1 55.7 17.2 917 Highest 84.0 73.5 66.9 9.4 855 Total 15-49 43.9 60.4 34.0 29.7 4,021 Note: Data on men who read a newspaper at least once a week are not shown due to a problem in the data entry programme. The responses from men with a secondary education or higher were not entered, resulting in a gross underestimate of men’s exposure to this type of media. 3.5 EMPLOYMENT 3.5.1 Employment Status The 2013 NDHS asked respondents a number of questions regarding their employment status, including whether they were working in the seven days preceding the survey and, if not, whether they had worked in the 12 months preceding the survey. The results for women and men are presented in Tables 3.5.1 and 3.5.2, respectively. At the time of the survey, 43 percent of women were employed and 3 percent were not employed but had worked sometime during the past 12 months (Table 3.5.1 and Figure 3.1). Fifty-six percent of men were employed at the time of the survey, and 6 percent were employed at some point during the 12 months before the survey (Table 3.5.2). The proportion of currently employed respondents is considerably lower among younger women and men, especially those age 15-19 (8 percent of women and 14 percent of men), probably because many are still in school. Also, never-married women and men are less likely to be working than those currently or formerly married. For example, 36 percent of women who have never been married are employed, as compared with 52 percent of those who are married or cohabiting and 57 percent of those who are divorced, separated, or widowed. Women and men with no children are less likely to be employed than respondents who have children. 38 • Characteristics of Respondents The proportion of women and men who are employed is higher in urban areas (53 percent and 66 percent, respectively) than in rural areas (30 percent and 43 percent, respectively). By region, employment among women ranges from 25 percent in Zambezi to 56 percent each in Erongo and //Karas. Among men, employment is lowest in Omusati (28 percent) and highest in Hardap (73 percent). In the case of women, there is a linear inverse relationship between level of education and unemployment. Three in ten women with no education (30 percent) are employed, as compared with more than six in ten (62 percent) women with more than a secondary education. Among men, those with more than a secondary education (77 percent) are more likely to be employed than men with less education or no education (53-59 percent). However, the patterns by education are not linear. Employment increases steadily with increasing wealth among both women and men. Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Namibia 2013 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of women Currently employed1 Not currently employed Age 15-19 8.3 1.7 90.0 100.0 1,906 20-24 31.0 5.7 63.3 100.0 1,786 25-29 54.2 3.2 42.6 100.0 1,489 30-34 61.2 2.6 36.0 100.0 1,260 35-39 58.0 2.8 39.0 100.0 1,110 40-44 62.7 1.8 35.5 100.0 917 45-49 58.1 1.2 40.8 100.0 708 Marital status Never married 36.0 3.2 60.8 100.0 5,458 Married or living together 51.7 2.2 46.0 100.0 3,121 Divorced/separated/widowed 57.0 4.9 38.0 100.0 597 Number of living children 0 24.1 2.9 73.0 100.0 3,034 1-2 52.7 3.7 43.6 100.0 3,606 3-4 55.5 1.6 42.7 100.0 1,750 5+ 39.8 2.8 57.3 100.0 785 Residence Urban 52.8 3.8 43.2 100.0 5,190 Rural 29.5 1.8 68.7 100.0 3,986 Region Zambezi 25.0 1.0 74.1 100.0 457 Erongo 56.3 3.5 40.1 100.0 771 Hardap 44.3 1.9 53.8 100.0 304 //Karas 56.1 6.5 37.4 100.0 343 Kavango 28.0 1.0 71.0 100.0 835 Khomas 54.2 4.5 41.2 100.0 2,202 Kunene 33.9 0.9 65.2 100.0 258 Ohangwena 34.9 1.5 63.6 100.0 894 Omaheke 35.5 4.8 59.7 100.0 225 Omusati 25.8 0.0 74.0 100.0 884 Oshana 44.8 1.6 53.6 100.0 755 Oshikoto 47.0 6.0 47.0 100.0 707 Otjozondjupa 44.1 4.2 51.6 100.0 540 Education No education 29.5 3.4 66.8 100.0 419 Primary 31.8 2.0 66.2 100.0 1,798 Secondary 43.9 3.2 52.8 100.0 6,029 More than secondary 62.0 2.8 35.0 100.0 930 Wealth quintile Lowest 21.8 1.7 76.5 100.0 1,429 Second 32.2 2.7 65.0 100.0 1,625 Middle 42.9 2.6 54.4 100.0 1,795 Fourth 52.0 3.8 44.2 100.0 2,116 Highest 54.8 3.5 41.6 100.0 2,211 Total 42.7 3.0 54.3 100.0 9,176 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Survey Respondents • 39 Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Namibia 2013 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Total Number of men Background characteristic Currently employed1 Not currently employed Age 15-19 14.3 5.6 80.1 100.0 922 20-24 56.0 5.6 38.4 100.0 808 25-29 70.1 7.7 21.9 100.0 658 30-34 72.8 5.9 21.2 100.0 520 35-39 77.5 4.3 18.1 100.0 448 40-44 72.4 3.9 23.7 100.0 376 45-49 70.8 3.9 25.2 100.0 289 Marital status Never married 44.9 6.5 48.5 100.0 2,745 Married or living together 80.3 3.2 16.5 100.0 1,160 Divorced/separated/widowed 72.7 7.3 20.1 100.0 116 Number of living children 0 38.5 6.2 55.3 100.0 2,094 1-2 73.7 5.5 20.6 100.0 1,077 3-4 79.9 3.8 16.3 100.0 544 5+ 70.0 4.1 25.8 100.0 305 Residence Urban 65.5 4.9 29.6 100.0 2,282 Rural 43.3 6.5 50.1 100.0 1,739 Region Zambezi 52.6 5.6 41.8 100.0 218 Erongo 71.7 3.3 25.0 100.0 372 Hardap 72.6 2.6 24.7 100.0 152 //Karas 69.5 4.4 25.8 100.0 151 Kavango 46.3 7.6 46.0 100.0 316 Khomas 69.3 5.9 24.8 100.0 1,023 Kunene 58.3 1.3 40.4 100.0 104 Ohangwena 28.6 9.7 61.3 100.0 328 Omaheke 67.1 4.2 28.7 100.0 103 Omusati 28.1 4.4 67.6 100.0 342 Oshana 54.2 6.4 39.5 100.0 335 Oshikoto 47.8 8.7 43.5 100.0 335 Otjozondjupa 56.1 0.3 43.6 100.0 241 Education No education 58.8 3.2 38.0 100.0 310 Primary 52.5 5.3 42.2 100.0 944 Secondary 53.7 6.1 40.1 100.0 2,400 More than secondary 76.9 4.4 18.8 100.0 368 Wealth quintile Lowest 40.9 7.0 52.0 100.0 594 Second 50.6 5.9 43.6 100.0 769 Middle 57.1 5.0 37.9 100.0 886 Fourth 61.7 4.3 34.0 100.0 917 Highest 63.9 6.2 29.9 100.0 855 Total 15-49 55.9 5.6 38.5 100.0 4,021 1 “Currently employed” is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 40 • Characteristics of Respondents Figure 3.1 Women’s employment status in the past 12 months 3.5.2 Occupation Respondents who are employed or had worked in the 12 months preceding the survey were asked to specify their occupation. The results for women and men are presented in Table 3.6.1 and Table 3.6.2, respectively, according to background characteristics. In Namibia, women are most likely to be employed in sales and services (58 percent), followed by professional, technical, or managerial jobs (19 percent) and clerical jobs (12 percent). By contrast, men are most likely to be employed in skilled manual work (33 percent), followed closely by sales and services (30 percent). Sixteen percent of men are engaged in professional, technical, or managerial jobs. Three percent of women and 9 percent of men work in agriculture. Urban-rural residence influences the type of work that men do but does not have a notable effect on women’s occupations. Men who live in urban areas are most likely to be employed in skilled manual labour (39 percent), followed by sales and services (25 percent) and professional, technical, or managerial jobs (20 percent). Among rural men, the leading occupations are sales and services (38 percent), skilled manual labour (23 percent), and agriculture (21 percent). There are no major variations by region. Women and men with more than a secondary education are more likely to be employed in professional, technical, or managerial occupations, while those with no education or a primary education are more likely to be employed in sales and services. Currently employed 43% Not currently employed but worked in last 12 months 3% Did not work in last 12 months 54% NDHS 2013 Characteristics of Survey Respondents • 41 Table 3.6.1 Occupation: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Namibia 2013 Background characteristic Professional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Number of women Age 15-19 8.6 9.5 68.7 1.7 2.3 7.0 2.2 100.0 190 20-24 13.8 17.5 59.7 2.0 3.0 3.2 0.8 100.0 655 25-29 18.4 13.1 57.4 5.1 3.2 2.2 0.6 100.0 855 30-34 20.2 11.7 59.3 3.0 2.6 2.8 0.5 100.0 804 35-39 20.5 8.1 57.1 5.7 4.1 3.7 0.7 100.0 675 40-44 21.1 11.4 55.4 5.1 3.0 3.9 0.1 100.0 591 45-49 29.2 7.9 49.1 5.8 3.5 2.8 1.8 100.0 420 Marital status Never married 14.2 12.4 62.4 4.1 3.3 2.9 0.8 100.0 2,138 Married or living together 25.9 11.6 50.5 4.4 3.2 3.8 0.6 100.0 1,681 Divorced/separated/widowed 19.6 9.2 61.0 4.4 2.2 2.5 1.1 100.0 370 Number of living children 0 22.2 18.2 48.8 3.8 2.7 3.0 1.3 100.0 820 1-2 20.9 13.1 56.2 3.6 3.5 2.4 0.4 100.0 2,034 3-4 17.8 7.1 63.0 5.1 3.2 2.9 0.8 100.0 1,001 5+ 7.9 2.4 70.0 6.3 1.8 10.0 1.7 100.0 335 Residence Urban 21.9 14.8 53.4 4.3 3.6 1.3 0.7 100.0 2,941 Rural 13.4 4.7 67.1 4.0 2.0 7.9 0.9 100.0 1,248 Region Zambezi 14.6 8.3 60.7 6.7 4.2 4.9 0.6 100.0 118 Erongo 14.8 14.2 53.4 4.6 10.9 1.4 0.6 100.0 461 Hardap 18.7 18.4 56.5 2.5 1.4 2.4 0.0 100.0 140 //Karas 13.7 14.8 45.4 3.0 12.4 9.8 0.9 100.0 215 Kavango 14.3 5.8 64.9 3.1 0.5 9.8 1.6 100.0 242 Khomas 29.2 14.4 49.3 4.1 1.9 0.4 0.6 100.0 1,292 Kunene 20.0 9.3 57.8 6.9 2.3 3.3 0.5 100.0 90 Ohangwena 12.3 5.6 72.1 6.3 1.3 1.4 0.9 100.0 326 Omaheke 14.8 12.2 63.2 6.9 0.3 2.6 0.0 100.0 91 Omusati 18.8 3.0 71.4 5.2 0.0 1.6 0.0 100.0 228 Oshana 16.7 11.9 65.0 4.3 0.6 0.7 0.8 100.0 351 Oshikoto 11.9 11.1 60.4 2.2 1.6 11.0 1.8 100.0 374 Otjozondjupa 15.3 13.1 60.4 3.5 2.6 4.4 0.6 100.0 261 Education No education 1.5 0.0 83.3 3.4 3.6 6.1 2.1 100.0 138 Primary 2.4 0.7 84.0 3.6 2.1 6.9 0.3 100.0 607 Secondary 13.8 14.3 59.6 4.8 3.8 2.8 0.8 100.0 2,842 More than secondary 66.9 14.0 14.7 2.2 1.1 0.7 0.6 100.0 602 Wealth quintile Lowest 5.6 0.8 72.6 5.9 2.0 11.2 1.9 100.0 336 Second 5.2 4.4 76.6 3.4 2.2 7.2 1.1 100.0 567 Middle 9.0 7.8 70.7 5.7 2.9 3.6 0.4 100.0 817 Fourth 16.1 13.1 59.1 4.8 4.9 1.6 0.5 100.0 1,181 Highest 38.8 19.3 35.2 2.7 2.5 0.7 0.8 100.0 1,289 Total 19.4 11.8 57.5 4.2 3.2 3.2 0.8 100.0 4,189 42 • Characteristics of Respondents Table 3.6.2 Occupation: Men Percent distribution of men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Namibia 2013 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Number of men Age 15-19 6.9 4.8 33.1 31.2 13.0 10.1 0.9 100.0 184 20-24 11.6 5.5 32.0 33.6 8.7 8.4 0.3 100.0 498 25-29 16.8 3.1 32.2 33.3 7.5 6.9 0.3 100.0 512 30-34 16.4 3.9 27.9 34.4 7.0 9.4 1.0 100.0 410 35-39 19.6 2.3 25.9 35.8 7.6 8.0 0.8 100.0 367 40-44 20.3 3.4 28.1 29.0 7.8 10.7 0.7 100.0 287 45-49 22.7 2.1 27.5 32.4 5.0 9.9 0.3 100.0 216 Marital status Never married 13.6 4.2 31.3 34.9 7.8 7.6 0.6 100.0 1,411 Married or living together 19.3 3.2 27.2 31.1 8.4 10.3 0.5 100.0 968 Divorced/separated/ widowed 26.1 0.6 31.0 28.2 4.6 8.8 0.6 100.0 93 Number of living children 0 15.5 4.5 31.7 30.5 9.0 8.3 0.5 100.0 937 1-2 17.5 3.7 27.7 35.0 7.1 8.4 0.6 100.0 854 3-4 17.9 2.9 29.7 30.6 8.2 10.2 0.6 100.0 456 5+ 11.9 2.0 28.7 42.4 6.0 8.4 0.7 100.0 226 Residence Urban 20.3 5.2 25.0 38.9 8.0 2.0 0.5 100.0 1,607 Rural 8.8 0.9 38.3 22.5 7.7 21.1 0.7 100.0 866 Region Zambezi 12.0 1.5 44.0 25.6 10.2 6.3 0.4 100.0 127 Erongo 18.7 3.3 18.8 42.0 10.9 4.7 1.6 100.0 279 Hardap 12.7 3.8 18.8 25.2 5.0 33.1 1.4 100.0 115 //Karas 13.6 2.4 23.1 25.1 19.6 16.0 0.3 100.0 112 Kavango 7.7 1.3 50.5 22.6 8.3 8.3 1.3 100.0 171 Khomas 22.8 6.4 21.6 41.7 5.5 1.9 0.1 100.0 769 Kunene 11.7 2.4 26.2 19.7 9.8 29.3 1.1 100.0 62 Ohangwena 10.1 1.8 38.5 34.3 13.6 1.7 0.0 100.0 126 Omaheke 7.4 1.7 27.8 19.6 9.8 33.0 0.8 100.0 74 Omusati 13.0 0.0 38.3 34.0 7.2 6.3 1.1 100.0 111 Oshana 20.2 3.3 31.0 40.2 3.3 2.0 0.0 100.0 203 Oshikoto 11.8 3.5 46.2 19.5 5.8 13.2 0.0 100.0 189 Otjozondjupa 10.0 2.0 35.6 21.1 8.8 20.7 1.8 100.0 136 Education No education 1.4 0.0 40.6 21.2 11.3 24.9 0.7 100.0 192 Primary 3.7 0.6 35.7 35.7 7.0 16.7 0.6 100.0 545 Secondary 13.3 4.9 29.3 37.9 9.2 4.9 0.5 100.0 1,437 More than secondary 63.4 5.5 13.8 13.5 1.3 1.9 0.6 100.0 299 Wealth quintile Lowest 1.6 1.2 53.0 23.8 6.1 14.3 0.0 100.0 284 Second 6.3 0.1 36.3 30.9 8.6 16.8 0.9 100.0 434 Middle 9.5 1.5 25.6 40.7 11.8 10.4 0.5 100.0 550 Fourth 17.9 6.1 25.9 35.6 8.8 5.1 0.6 100.0 605 Highest 35.2 7.0 21.4 29.8 3.8 2.1 0.7 100.0 599 Total 16.3 3.7 29.7 33.2 7.9 8.7 0.6 100.0 2,472 3.5.3 Earnings, Employers, and Continuity of Employment for Women Table 3.7 shows the percent distribution of women employed in the 12 months preceding the survey by type of earnings, type of employer, continuity of employment, and type of employment (agricultural or nonagricultural). The financial sector in Namibia is well developed by African standards, and the economy is largely monetised. Fifty-four percent of women engaged in agricultural work are paid in cash only, while 9 percent are paid in-kind. More than one-third (36 percent) of women who work in agriculture are not paid at all for their work. By contrast, 89 percent of women engaged in nonagricultural work are paid in cash, and only 7 percent are not paid at all. Characteristics of Survey Respondents • 43 Fifty-three percent of women who work in agriculture are employed by non-family members, 32 percent are employed by family members, and 16 percent are self-employed. Among women engaged in nonagricultural work, 70 percent are employed by non-family members, 23 percent are self-employed, and 7 percent are employed by family members. With regard to continuity of employment, 77 percent of employed women work all year, 14 percent are seasonal workers, and 9 percent are considered occasional workers. Seventy-eight percent of women who work in the nonagricultural sector are employed all year, as compared with 43 percent of those who work in agriculture. On the other hand, 51 percent of women who work in agriculture are seasonal workers, compared with only 12 percent of those who do nonagricultural work. Table 3.7 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 nonagricultural), Namibia 2013 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 53.9 89.3 88.0 Cash and in-kind 9.0 3.2 3.4 In-kind only 1.6 0.7 0.7 Not paid 35.5 6.6 7.6 Total 100.0 100.0 100.0 Type of employer Employed by family member 31.6 7.4 8.3 Employed by non-family member 52.9 69.7 68.9 Self-employed 15.5 22.6 22.4 Total 100.0 100.0 100.0 Continuity of employment All year 42.7 78.4 77.1 Seasonal 51.2 12.3 13.6 Occasional 6.1 9.2 9.1 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 135 4,023 4,189 Note: Total includes women with missing information on type of employment who are not shown separately. Marriage and Sexual Activity • 45 MARRIAGE AND SEXUAL ACTIVITY 4 arriage is a primary indication of the exposure of women to the risk of pregnancy and, therefore, is important for an understanding of fertility. Populations in which women marry at a young age tend to initiate childbearing early and have high fertility. More direct measures of the beginning of exposure to pregnancy are age at first sexual intercourse and frequency of sexual intercourse. Fertility is more closely linked to age at first sexual intercourse than to age at marriage in countries such as Namibia, where sexual initiation often occurs before marriage. This chapter addresses the principal factors, other than contraception, that affect a woman’s risk of becoming pregnant. These factors include marriage, polygyny, and sexual activity. 4.1 MARITAL STATUS Table 4.1 presents data on the current marital status of women and men age 15-49 interviewed in the survey. In this table, the term “married” is intended to mean legal, traditional, or formal marriage, while “living together” describes persons who live together in an informal union as husband and wife. Thirty-four percent of women of childbearing age are in a union; that is, they are either married or living with a man as if married. Sixty percent of women of childbearing age have never been married. The proportion of women who have never been married declines with age, from 94 percent among those age 15-19 to 24 percent among those age 45-49. Seven percent of women of childbearing age are divorced, separated, or widowed. The proportion of formerly married women increases with age. As expected, the proportion of women who are widowed is highest in the oldest age group 45-49 (12 percent). Men tend to marry at a later age than women. Overall, 29 percent of men are either married or living with a woman as if married. Sixty-eight percent of men have never married. The proportion of men who have never married (or lived with a woman) declines with age, from 99 percent among those age 15-19 to 19 percent among those age 45-49. Three percent of men are divorced, separated, or widowed. As with women, the proportion of formerly married men increases with age. M Key Findings • Thirty-four percent of women age 15-49 and 29 percent of men age 15-49 are either married or living together with a partner. • Six percent of currently married women age 15-49 report being married to men who are in a polygynous union, while 2 percent of currently married men age 15-49 report having two or more wives. • The median age at first sexual intercourse is 19 years among women and 18 years among men age 25-49. • About four in ten women and men age 15-49 reported having had sexual intercourse in the past four weeks. 46 • Marriage and Sexual Activity Table 4.1 Current marital status Percent distribution of women and men age 15-49 by current marital status, according to age, Namibia 2013 Marital status Total Percentage of respondents currently in union Number of respondents Age Never married Married Living together Divorced Separated Widowed WOMEN 15-19 94.1 0.6 4.8 0.0 0.5 0.0 100.0 5.4 1,906 20-24 77.9 5.0 14.6 0.1 2.3 0.1 100.0 19.5 1,786 25-29 57.8 13.8 23.7 0.3 4.1 0.4 100.0 37.5 1,489 30-34 44.2 27.1 23.3 0.9 3.9 0.7 100.0 50.3 1,260 35-39 36.5 32.1 21.3 1.8 5.5 2.8 100.0 53.4 1,110 40-44 30.6 38.1 16.2 3.2 5.9 6.0 100.0 54.2 917 45-49 24.1 41.4 13.1 3.5 5.6 12.3 100.0 54.5 708 Total 15-49 59.5 17.9 16.1 1.0 3.4 2.1 100.0 34.0 9,176 MEN 15-19 99.3 0.0 0.7 0.0 0.0 0.0 100.0 0.7 922 20-24 90.0 1.2 8.2 0.0 0.6 0.0 100.0 9.4 808 25-29 72.1 8.1 16.9 0.3 2.6 0.0 100.0 25.0 658 30-34 53.4 17.6 25.6 0.6 2.8 0.0 100.0 43.2 520 35-39 40.9 30.6 24.0 0.8 3.1 0.6 100.0 54.6 448 40-44 30.2 45.0 18.4 1.7 3.7 1.1 100.0 63.4 376 45-49 18.6 51.2 19.8 6.1 3.2 1.1 100.0 71.0 289 Total 15-49 68.3 15.1 13.7 0.8 1.8 0.2 100.0 28.8 4,021 4.2 POLYGYNY Polygyny (the practice of having more than one wife) has implications for frequency of exposure to sexual activity and, therefore, fertility. The extent of polygyny in Namibia was measured by asking all women currently married or living with a man the following question: “Does your husband/partner have other wives, or does he live with other women as if married?” If the answer was yes, the woman was asked “Including yourself, in total, how many wives or live-in partners does he have?” Currently married men or men living with a woman were asked “Do you have other wives, or do you live with other women as if married?” If the answer was yes, the man was asked “Altogether, how many wives or live-in partners do you have?” Table 4.2.1 shows the distribution of currently married women by number of co-wives, according to selected background characteristics. Seventy-six percent of married women report that their husband or partner has no other wife, a decrease from the figure reported in the 2006-07 NDHS (81 percent). Six percent of women report that their husbands have more than one wife. Rural women are more likely to live in a polygynous union than urban women (9 percent versus 4 percent). Ten percent or more of women in Zambezi, Kunene, Kavango, and Ohangwena are in a polygynous union, as compared with less than 1 percent of women in Hardap. The proportion of women in a polygynous relationship declines with increasing education and, in general, with increasing household wealth. Marriage and Sexual Activity • 47 Table 4.2.1 Number of women’s co-wives Percent distribution of currently married women age 15-49 by number of co-wives, according to background characteristics, Namibia 2013 Number of co-wives Total Number of women Background characteristic 0 1 2+ Don’t know/ missing Age 15-19 78.0 2.0 0.0 20.0 100.0 103 20-24 81.9 2.8 0.3 15.0 100.0 349 25-29 77.3 4.1 1.0 17.7 100.0 558 30-34 76.3 4.2 0.3 19.1 100.0 634 35-39 76.4 5.3 1.2 17.0 100.0 593 40-44 73.1 6.1 2.2 18.6 100.0 497 45-49 73.6 6.5 1.9 18.0 100.0 386 Residence Urban 74.0 2.8 0.9 22.3 100.0 1,819 Rural 79.6 7.4 1.4 11.6 100.0 1,301 Region Zambezi 85.1 10.0 1.3 3.5 100.0 204 Erongo 73.3 3.6 1.3 21.8 100.0 305 Hardap 91.9 0.9 0.0 7.2 100.0 131 //Karas 82.5 1.9 0.7 14.9 100.0 133 Kavango 85.5 9.5 0.6 4.4 100.0 429 Khomas 67.3 1.8 0.9 30.0 100.0 727 Kunene 78.6 7.2 3.4 10.8 100.0 108 Ohangwena 84.6 9.8 0.0 5.6 100.0 184 Omaheke 77.8 3.7 1.3 17.1 100.0 110 Omusati 67.3 7.0 1.2 24.5 100.0 187 Oshana 76.5 4.3 0.7 18.6 100.0 164 Oshikoto 79.8 2.0 3.4 14.7 100.0 208 Otjozondjupa 67.3 2.1 0.8 29.8 100.0 231 Education No education 75.5 7.6 1.8 15.1 100.0 233 Primary 77.8 7.8 1.7 12.8 100.0 718 Secondary 75.8 4.0 0.8 19.4 100.0 1,808 More than secondary 76.9 0.8 0.8 21.5 100.0 362 Wealth quintile Lowest 80.9 10.0 1.3 7.8 100.0 558 Second 77.8 5.4 2.2 14.6 100.0 539 Middle 71.7 5.8 1.4 21.1 100.0 598 Fourth 75.1 2.5 0.7 21.7 100.0 623 Highest 76.5 1.6 0.4 21.5 100.0 802 Total 15-49 76.3 4.8 1.1 17.8 100.0 3,121 Table 4.2.2 presents the distribution of currently married men age 15-49 by number of wives, according to background characteristics. The vast majority of men (98 percent) report having only one wife. Two percent of married men report having two or more wives, as compared with 6 percent of women who reported having co-wives. Men in Kunene (8 percent), those with no education (4 percent), and men living in households in the second and fourth wealth quintiles (4 percent each) are most likely to report having more than one wife. 48 • Marriage and Sexual Activity Table 4.2.2 Number of men’s wives Percent distribution of currently married men age 15-49 by number of wives, according to background characteristics, Namibia 2013 Background characteristic Number of wives Total Number of men 1 2+ Age 15-19 * * 100.0 7 20-24 98.9 1.1 100.0 76 25-29 97.8 2.2 100.0 165 30-34 96.4 3.6 100.0 225 35-39 96.8 3.2 100.0 245 40-44 99.3 0.7 100.0 238 45-49 98.4 1.6 100.0 205 Residence Urban 98.2 1.8 100.0 745 Rural 97.1 2.9 100.0 415 Region Zambezi 95.4 4.6 100.0 78 Erongo 98.4 1.6 100.0 137 Hardap 100.0 0.0 100.0 63 //Karas 97.3 2.7 100.0 53 Kavango 99.0 1.0 100.0 126 Khomas 97.9 2.1 100.0 307 Kunene 92.5 7.5 100.0 39 Ohangwena (97.0) (3.0) 100.0 42 Omaheke 100.0 0.0 100.0 37 Omusati (96.8) (3.2) 100.0 45 Oshana (100.0) (0.0) 100.0 50 Oshikoto 98.2 1.8 100.0 66 Otjozondjupa 96.8 3.2 100.0 117 Education No education 95.6 4.4 100.0 122 Primary 98.0 2.0 100.0 252 Secondary 97.9 2.1 100.0 635 More than secondary 98.8 1.2 100.0 151 Wealth quintile Lowest 98.0 2.0 100.0 175 Second 96.3 3.7 100.0 196 Middle 99.1 0.9 100.0 226 Fourth 96.5 3.5 100.0 285 Highest 99.1 0.9 100.0 277 Total 15-49 97.8 2.2 100.0 1,160 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that an estimate is based on fewer than 25 unweighted cases and has been suppressed. 4.3 AGE AT FIRST MARRIAGE Age at first marriage has a major effect on childbearing. Women who marry early will, on average, have longer exposure to pregnancy and a greater number of lifetime births. Information on age at first marriage was obtained by asking all ever-married respondents the month and year they started living together with their first spouse. Table 4.3 presents the percentages of both women and men age 15-49 who first married by specific exact ages. Fourteen percent of women age 25-49 married by age 20, as compared with 17 percent in the 2006-07 NDHS. Among men, 5 percent were married by age 20, same as the figure reported in the 2006-07 NDHS survey. The median age at first marriage among women and men age 20-49 or 25-49 cannot be calculated since less than 50 percent of women and men began living with their spouses or partners for the first time before reaching the beginning of the age group. Similarly, median age at first marriage by background characteristics is not shown separately because, for most subgroups of women and men, less than 50 percent began living with their spouses or partners for the first time before reaching the beginning of the age group. Marriage and Sexual Activity • 49 Table 4.3 Age at first marriage Percentage of women and men age 15-49 who were first married by specific exact ages and median age at first marriage, according to current age, Namibia 2013 Percentage first married by exact age: Percentage never married Number Median age at first marriage Current age 15 18 20 22 25 WOMEN 15-19 0.9 na na na na 94.1 1,906 a 20-24 1.6 6.9 13.0 na na 77.9 1,786 a 25-29 2.0 7.8 14.3 21.6 33.0 57.8 1,489 a 30-34 1.2 7.3 12.6 18.3 28.7 44.2 1,260 a 35-39 2.2 8.6 15.3 20.7 30.9 36.5 1,110 30.4 40-44 1.9 8.7 13.9 20.7 31.3 30.6 917 30.7 45-49 2.2 8.9 16.6 25.8 39.1 24.1 708 28.9 20-49 1.8 7.8 14.0 na na 50.4 7,270 a 25-49 1.8 8.1 14.3 21.1 32.1 41.5 5,485 a MEN 15-19 0.0 na na na na 99.3 922 a 20-24 0.0 1.4 3.9 na na 90.0 808 a 25-29 0.0 2.4 5.5 10.5 20.4 72.1 658 a 30-34 0.0 1.7 4.6 10.1 19.6 53.4 520 a 35-39 0.0 2.6 5.0 9.8 19.8 40.9 448 34.1 40-44 0.0 2.3 5.5 9.3 19.5 30.2 376 33.5 45-49 0.0 3.0 5.7 9.4 19.1 18.6 289 34.7 20-49 0.0 2.1 4.9 na na 59.0 3,099 a 25-49 0.0 2.4 5.2 9.9 19.8 48.1 2,291 a Note: The age at first marriage is defined as the age at which the respondent began living with her/his first spouse/partner. na = Not applicable due to censoring a = Omitted because less than 50 percent of women or men began living with their spouse or partner for the first time before reaching the beginning of the age group 4.4 AGE AT FIRST SEXUAL INTERCOURSE Age at first marriage can be used as a proxy for the beginning of exposure to the risk of pregnancy. However, because some women are sexually active before marriage, the age at which women initiate sexual intercourse more precisely marks the beginning of their exposure to reproductive risks. The 2013 NDHS asked women and men how old they were when they first had sexual intercourse. Table 4.4 presents the percentages of women and men who had sexual intercourse by specific exact ages and the median ages at first sexual intercourse. The results show that men initiate sex at an earlier age than women. The median age at first intercourse is 19.0 years among women age 25-49 and 18.2 years among men the same age. Five percent of women and 10 percent of men age 25-49 reported that they had sexual intercourse by age 15. The majority of women and men age 25-49 (62 percent and 74 percent, respectively) reported having had sexual intercourse by age 20. Table 4.5 presents the median age at first sexual intercourse among women and men by background characteristics. Among women age 25-49, median age at first sexual intercourse ranges from a low of 17.0 years in Kavango to a high of 20.3 years in Omusati. Median age at first sexual intercourse increases with increasing education and wealth. For example, the median age is more than three years lower among women with no education than among women with more than a secondary education. There are smaller differences among men by residence, education, and wealth. However, there are noteworthy differences by region, with median age at first sexual intercourse ranging from 16.6 years in Kunene to 18.4 years in Omusati. 50 • Marriage and Sexual Activity Table 4.4 Age at first sexual intercourse Percentage of women and men age 15-49 who had first sexual intercourse by specific exact ages, percentage who never had sexual intercourse, and median age at first sexual intercourse, according to current age, Namibia 2013 Percentage who had first sexual intercourse by exact age: Percentage who never had intercourse Number Median age at first intercourse Current age 15 18 20 22 25 WOMEN 15-19 6.8 na na na na 54.9 1,906 a 20-24 3.9 39.7 72.5 na na 9.2 1,786 18.6 25-29 6.1 36.8 63.7 79.3 88.5 1.8 1,489 18.8 30-34 5.2 39.3 63.2 77.7 86.1 1.1 1,260 18.7 35-39 4.5 34.6 59.1 74.3 82.2 0.8 1,110 19.2 40-44 4.1 30.6 52.3 68.6 79.1 1.1 917 19.7 45-49 4.2 28.5 50.2 65.3 77.4 0.8 708 20.0 20-49 4.7 36.0 62.3 na na 3.2 7,270 a 25-49 5.0 34.8 59.0 na na 1.2 5,485 19.0 15-24 5.4 na na na na 32.8 3,691 19.0 MEN 15-19 13.4 na na na na 56.6 922 a 20-24 12.7 55.2 82.6 na na 7.6 808 17.7 25-29 13.9 53.0 77.6 92.1 95.9 2.3 658 17.7 30-34 8.5 46.2 73.5 88.4 92.2 0.3 520 18.2 35-39 10.8 48.6 69.9 85.5 89.3 1.3 448 18.1 40-44 6.1 36.3 63.6 79.8 86.5 1.3 376 18.6 45-49 8.0 38.1 65.8 82.4 90.4 0.4 289 18.6 20-49 10.7 48.4 74.3 na na 2.9 3,099 a 25-49 10.1 46.0 71.4 na na 1.2 2,291 18.2 15-24 13.1 na na na na 33.7 1,730 18.3 na = Not applicable due to censoring a = Omitted because less than 50 percent of respondents had sexual intercourse for the first time before reaching the beginning of the age group Table 4.5 Median age at first sexual intercourse by background characteristics Median age at first sexual intercourse among women and men age 25-49, according to background characteristics, Namibia 2013 Background characteristic Women age 25-49 Men age 25-49 Residence Urban 19.1 18.3 Rural 18.6 18.2 Region Zambezi 18.1 18.1 Erongo 18.9 18.2 Hardap 19.1 18.4 //Karas 19.0 18.1 Kavango 17.0 18.1 Khomas 19.5 18.2 Kunene 17.8 16.8 Ohangwena 18.6 18.1 Omaheke 18.2 18.1 Omusati 20.3 18.4 Oshana 19.9 18.3 Oshikoto 19.5 18.4 Otjozondjupa 18.5 18.4 Education No education 17.3 18.4 Primary 17.9 18.4 Secondary 19.2 18.1 More than secondary 20.7 18.1 Wealth quintile Lowest 17.9 18.3 Second 18.6 18.2 Middle 18.9 18.2 Fourth 19.1 18.2 Highest 19.8 18.3 Total 19.0 18.2 Marriage and Sexual Activity • 51 4.5 RECENT SEXUAL ACTIVITY In the absence of effective contraception, the probability of pregnancy depends highly upon the frequency of intercourse. Information on sexual activity, therefore, can be used to refine measures of exposure to pregnancy. All women and men were asked how long ago they most recently had sexual intercourse. Tables 4.6.1 and 4.6.2 present the distribution of women and men by recent sexual activity, according to background characteristics. Table 4.6.1 Recent sexual activity: Women Percent distribution of women age 15-49 by timing of last sexual intercourse, according to background characteristics, Namibia 2013 Timing of last sexual intercourse Never had sexual intercourse Total Number of women Background characteristic Within the past 4 weeks Within 1 year1 One or more years Missing Age 15-19 13.7 24.0 7.0 0.4 54.9 100.0 1,906 20-24 36.6 41.9 11.6 0.8 9.2 100.0 1,786 25-29 49.8 36.8 10.6 1.1 1.8 100.0 1,489 30-34 54.5 32.3 11.4 0.5 1.1 100.0 1,260 35-39 53.2 29.1 15.8 1.1 0.8 100.0 1,110 40-44 52.5 26.8 18.5 1.1 1.1 100.0 917 45-49 46.2 23.5 27.5 2.1 0.8 100.0 708 Marital status Never married 23.5 37.4 15.0 0.7 23.4 100.0 5,458 Married or living together 74.0 21.4 3.3 1.3 0.0 100.0 3,121 Divorced/separated/ widowed 24.7 31.8 43.1 0.4 0.0 100.0 597 Marital duration2 0-4 years 74.6 22.0 2.2 1.2 0.0 100.0 958 5-9 years 75.6 20.7 2.8 1.0 0.0 100.0 679 10-14 years 70.4 23.9 4.5 1.3 0.0 100.0 464 15-19 years 73.1 20.5 4.0 2.4 0.0 100.0 310 20-24 years 74.9 19.6 4.8 0.7 0.0 100.0 224 25+ years 73.5 18.5 6.0 2.0 0.0 100.0 131 Married more than once 74.8 20.6 3.6 1.0 0.0 100.0 354 Residence Urban 45.4 29.6 11.4 1.3 12.4 100.0 5,190 Rural 34.8 34.2 14.8 0.3 15.9 100.0 3,986 Region Zambezi 45.7 33.9 12.6 1.0 6.8 100.0 457 Erongo 48.3 27.7 11.3 1.1 11.7 100.0 771 Hardap 47.1 23.6 15.2 1.2 12.9 100.0 304 //Karas 46.2 31.1 10.2 1.2 11.3 100.0 343 Kavango 40.3 29.8 22.4 0.3 7.2 100.0 835 Khomas 47.0 29.1 9.2 1.8 12.9 100.0 2,202 Kunene 49.1 35.8 11.1 0.0 4.1 100.0 258 Ohangwena 27.9 36.4 15.5 0.3 19.9 100.0 894 Omaheke 51.5 28.9 11.4 0.7 7.5 100.0 225 Omusati 30.2 33.1 12.4 0.4 23.9 100.0 884 Oshana 29.9 40.6 13.0 0.1 16.4 100.0 755 Oshikoto 34.2 35.0 13.1 0.2 17.5 100.0 707 Otjozondjupa 48.4 24.0 13.3 1.8 12.5 100.0 540 Education No education 54.8 26.4 15.5 0.2 3.1 100.0 419 Primary 40.7 28.3 16.7 0.4 14.0 100.0 1,798 Secondary 38.6 33.0 12.5 0.8 15.2 100.0 6,029 More than secondary 48.7 30.9 6.9 3.1 10.5 100.0 930 Wealth quintile Lowest 36.7 34.2 14.8 0.3 13.9 100.0 1,429 Second 38.5 33.6 14.7 0.2 13.0 100.0 1,625 Middle 41.6 32.6 13.2 0.5 12.0 100.0 1,795 Fourth 41.9 32.3 12.9 0.6 12.3 100.0 2,116 Highest 43.3 26.8 10.0 2.3 17.6 100.0 2,211 Total 15-49 40.8 31.6 12.9 0.9 13.9 100.0 9,176 1 Excludes women who had sexual intercourse within the last 4 weeks 2 Excludes women who are not currently married Table 4.6.1 shows that 41 percent of women age 15-49 were sexually active within the four weeks preceding the survey, 32 percent were sexually active within the past year, and 13 percent were sexually active one or more years prior to the survey. Fourteen percent of women reported never having had sexual intercourse. The proportion of women who were sexually active in the past four weeks increases with age, 52 • Marriage and Sexual Activity from 14 percent at age 15-19 to 55 percent at age 30-34, before decreasing gradually to reach 46 percent at age 45-49. Women who are married or living together with a partner are most likely to have recently engaged in sexual intercourse (74 percent), while women who are divorced, separated, or widowed are only slightly more likely to be sexually active than those who have never been married (25 percent versus 24 percent). Among married women, those married for 10-14 years are least likely than other women to have recently engaged in sexual intercourse (70 percent). Recent sexual activity is relatively lower among women in rural areas (35 percent) than among women in urban areas (45 percent). More than half of the women in Omaheke (52 percent) were sexually active in the last four weeks, compared with 28 percent in Ohangwena. Women with no education and those with more than a secondary education are more likely to have recently engaged in sexual intercourse than women with a primary or secondary education. The percentage of women who have recently been sexually active increases with increasing wealth. Table 4.6.2 indicates that a slightly higher proportion of men than women age 15-49 have recently engaged in sexual intercourse (44 percent versus 41 percent). Thirty percent of men have been sexually active within the past year and 10 percent within one or more years. There has been a small increase in recent sexual activity over the last six years, with the 2006-07 NDHS reporting that 40 percent of men and 38 percent of women had recently been sexually active. Fifteen percent of men reported that they have never had sex. Men who are married or living together with a partner are more likely to be sexually active (76 percent) than men who have never been married (31 percent) and men who are divorced, separated, or widowed (40 percent). Men who have been married more than once are most sexually active (80 percent). As with women, men in urban areas (50 percent) are more likely to have engaged in recent sexual activity than men in rural areas (37 percent). About half of men in Zambezi, Erongo, Hardap, Kavango, Khomas, Kunene, and Omaheke have recently been sexually active. Recent sexual activity is highest among men with more than a secondary education (61 percent) and those in the highest wealth quintile (55 percent). Marriage and Sexual Activity • 53 Table 4.6.2 Recent sexual activity: Men Percent distribution of men age 15-49 by timing of last sexual intercourse, according to background characteristics, Namibia 2013 Timing of last sexual intercourse Never had sexual intercourse Total Number of men Background characteristic Within the past 4 weeks Within 1 year1 One or more years Missing Age 15-19 11.6 21.4 10.2 0.2 56.6 100.0 922 20-24 40.1 38.9 13.1 0.3 7.6 100.0 808 25-29 52.4 35.5 8.4 1.5 2.3 100.0 658 30-34 61.5 27.5 10.5 0.2 0.3 100.0 520 35-39 56.7 32.1 8.8 1.1 1.3 100.0 448 40-44 60.7 28.2 7.5 2.3 1.3 100.0 376 45-49 67.0 19.8 10.3 2.5 0.4 100.0 289 Marital status Never married 30.8 33.4 13.3 0.4 22.3 100.0 2,745 Married or living together 75.9 20.2 1.9 2.0 0.0 100.0 1,160 Divorced/separated/ widowed 39.7 38.7 19.2 2.4 0.0 100.0 116 Marital duration2 0-4 years 76.8 21.0 1.5 0.7 0.0 100.0 362 5-9 years 74.1 21.1 2.2 2.6 0.0 100.0 250 10-14 years 77.5 17.7 1.2 3.5 0.0 100.0 202 15-19 years 71.9 22.3 2.5 3.2 0.0 100.0 124 20-24 years 73.4 18.8 5.3 2.4 0.0 100.0 76 25+ years (79.4) (20.6) (0.0) (0.0) (0.0) 100.0 27 Married more than once 79.6 19.0 0.7 0.6 0.0 100.0 118 Residence Urban 49.5 28.2 9.8 1.5 10.9 100.0 2,282 Rural 36.8 31.7 10.5 0.1 20.8 100.0 1,739 Region Zambezi 56.4 26.4 11.2 0.0 5.9 100.0 218 Erongo 53.2 25.7 8.5 0.3 12.3 100.0 372 Hardap 49.9 28.1 6.0 1.3 14.8 100.0 152 //Karas 39.9 28.4 11.3 1.1 19.3 100.0 151 Kavango 50.8 30.0 6.6 1.1 11.5 100.0 316 Khomas 50.6 27.4 11.9 1.6 8.5 100.0 1,023 Kunene 51.4 27.0 12.3 0.4 8.8 100.0 104 Ohangwena 30.4 37.0 8.3 0.0 24.4 100.0 328 Omaheke 49.0 32.4 9.0 0.0 9.6 100.0 103 Omusati 29.5 25.5 7.3 0.0 37.8 100.0 342 Oshana 30.8 39.3 8.2 1.5 20.2 100.0 335 Oshikoto 35.0 34.0 16.5 0.2 14.3 100.0 335 Otjozondjupa 46.2 27.1 10.4 2.3 13.9 100.0 241 Education No education 47.6 36.6 10.3 0.1 5.4 100.0 310 Primary 37.1 29.3 11.8 0.3 21.4 100.0 944 Secondary 43.7 29.6 10.1 1.0 15.7 100.0 2,400 More than secondary 61.4 25.7 6.0 2.5 4.4 100.0 368 Wealth quintile Lowest 38.0 32.9 11.9 0.4 16.9 100.0 594 Second 37.0 31.0 12.8 0.5 18.8 100.0 769 Middle 41.6 32.4 11.0 0.1 14.9 100.0 886 Fourth 46.6 31.0 7.6 0.7 14.2 100.0 917 Highest 54.5 22.3 8.4 2.8 12.2 100.0 855 Total 15-49 44.0 29.7 10.1 0.9 15.2 100.0 4,021 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Excludes men who had sexual intercourse within the last 4 weeks 2 Excludes men who are not currently married Fertility • 55 FERTILITY 5 Fertility is one of the three principal components of population dynamics that determine the size, structure, and composition of the population in any country. This chapter focuses on a number of fertility indicators including levels, patterns, and trends in both current and cumulative fertility; the length of birth intervals; and the age at which women begin childbearing. Birth intervals are important because short intervals are associated with high childhood mortality. The age at which childbearing begins can also have a major impact on the health and well-being of both the mother and the child. Measures of several proximate determinants of fertility that influence exposure to the risk of pregnancy are presented as well, including duration of postpartum amenorrhoea, postpartum abstinence, and menopause. The fertility indicators presented in this chapter are based on reports of reproductive histories provided by women age 15-49. As in the previous NDHS surveys, each woman was asked to provide information on the total number of sons and daughters to whom she had given birth and who were living with her, the number living elsewhere, and the number who had died, in order to obtain the total number of live births. In the birth history, women reported the details of each live birth separately, including such information as name, month and year of birth, sex, and survival status. For children who had died, age at death was recorded. 5.1 CURRENT FERTILITY Measures of current fertility are presented in Table 5.1 for the three-year period preceding the survey, corresponding to the calendar period 2011-2013. A three-year period was chosen for calculating these rates to provide the most current information while also allowing the rates to be calculated for a sufficient number of cases so Table 5.1 Current fertility Age-specific and total fertility rates, the general fertility rate, and the crude birth rate for the three years preceding the survey, by residence, Namibia 2013 Residence Total Age group Urban Rural 15-19 66 101 82 20-24 134 226 168 25-29 144 207 168 30-34 122 187 149 35-39 84 144 110 40-44 29 59 42 45-49 8 12 10 TFR (15-49) 2.9 4.7 3.6 GFR 103 156 125 CBR 30.0 29.3 29.5 Note: Age-specific fertility rates are per 1,000 women. Rates for the 45-49 age group may be slightly biased due to truncation. Rates are for the period 1-36 months prior to the interview. TFR: Total fertility rate, expressed per woman GFR: General fertility rate, expressed per 1,000 women age 15-44 CBR: Crude birth rate, expressed per 1,000 population Key Findings • The total fertility rate for Namibia is 3.6 children per woman. Overall, the TFR declined by 1.8 children per woman between the 1992 and 2006-07 NDHS surveys, from 5.4 to 3.6, with no change in fertility over the last six years. • Fertility is considerably lower among urban women (2.9 children per woman) than among rural women (4.7 children per woman). Fertility ranges from 2.6 births per woman in Khomas to 5.3 among women in Ohangwena. • The median birth interval in Namibia is 45.1 months. About 14 percent of children are born less than 24 months after a previous birth. • The median age at first birth among women age 25-49 is 21.6 years. • Overall, 19 percent of young women age 15-19 have begun childbearing, an increase from 15 percent in the 2006-07 NDHS survey. • Teenage pregnancy is more than three times higher among young women in the lowest wealth quintile than among those in the highest wealth quintile. 56 • Fertility as not to compromise the statistical precision of the estimates. Age-specific fertility rates (ASFRs) are useful in understanding the age pattern of fertility. Numerators for the ASFRs are calculated by identifying live births that occurred in the period 1 to 36 months preceding the survey (determined from the date of the interview and the date of birth of the child); they are then classified by the age of the mother (in five-year groups) at the time of the child’s birth. The denominators for these rates are the number of woman-years lived by the survey respondents in each of the five-year age groups during the specified period. The total fertility rate (TFR) is a common measure of current fertility and is defined as the number of children a woman would have by the end of her childbearing years if she were to pass through those years bearing children at the current age-specific fertility rates. The general fertility rate (GFR) represents the number of live births per 1,000 women of reproductive age. The crude birth rate (CBR) is the number of live births per 1,000 population. The latter two measures are based on the birth history data for the three-year period before the survey and the age-sex distribution of the household population. Table 5.1 shows the age-specific and aggregate fertility measures at the national level and by urban-rural residence. The TFR in Namibia is 3.6 children per woman, the same as in the 2006-07 NDHS. Fertility is considerably lower among urban women (2.9 children per woman) than among rural women (4.7 children per woman). The urban-rural difference in fertility is most pronounced among women in the 20-24 age group (134 births per 1,000 women in urban areas versus 226 births per 1,000 women in rural areas). As the ASFRs show, the pattern of higher rural fertility is prevalent in all age groups. The overall age pattern of fertility, as reflected in the ASFRs, indicates that childbearing begins early. Fertility is low among adolescents, increases to a peak of 168 births per 1,000 among women age 20-29, and declines thereafter, with a sharp decline after age 39. 5.2 FERTILITY BY BACKGROUND CHARACTERISTICS Table 5.2 shows differentials in fertility by residence, region, education, and wealth quintile. The TFR varies between regions, ranging from 2.6 children per woman in Khomas to 5.3 children per woman in Ohangwena. Education and wealth are closely linked to a woman’s fertility. The TFR declines as women’s education rises, from 5.3 children per woman among those with no education to 2.2 children per woman among those with more than a secondary education. Similarly, the TFR declines with increasing household wealth, from 5.5 children per woman in the lowest wealth quintile to 2.3 children per woman in the highest quintile. There are no significant differences from the rates reported in the 2006-07 NDHS. Table 5.2 also allows for a general assessment of differential trends in fertility over time among population subgroups. The mean number of children ever born to women age 40-49 is a measure of past fertility. The mean number of children ever born to older women who are nearing the end of their reproductive period is an indicator of average completed fertility of women who began childbearing during the three decades preceding the survey. If fertility were to remain constant over time, and the reported data on children ever born and births during the three years preceding the survey were reasonably accurate, the TFR and the mean number of children ever born to women age Table 5.2 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of women age 15-49 currently pregnant, and mean number of children ever born to women age 40-49, by background characteristics, Namibia 2013 Background characteristic Total fertility rate Percentage of women age 15-49 currently pregnant Mean number of children ever born to women age 40-49 Residence Urban 2.9 6.7 3.2 Rural 4.7 6.3 4.4 Region Zambezi 4.2 4.5 4.4 Erongo 2.9 6.1 3.3 Hardap 3.7 3.8 3.4 //Karas 3.4 6.4 3.4 Kavango 4.6 6.8 5.4 Khomas 2.6 6.4 2.7 Kunene 4.5 8.5 4.6 Ohangwena 5.3 9.8 5.2 Omaheke 4.6 8.6 4.2 Omusati 4.2 6.3 3.6 Oshana 2.7 6.2 3.1 Oshikoto 4.2 5.7 4.0 Otjozondjupa 4.1 5.4 4.0 Education No education 5.3 10.3 5.3 Primary 4.8 6.4 5.0 Secondary 3.5 6.3 3.0 More than secondary 2.2 6.8 2.5 Wealth quintile Lowest 5.5 6.8 5.3 Second 4.4 7.3 4.4 Middle 3.9 6.7 3.7 Fourth 3.1 7.1 3.3 Highest 2.3 5.2 2.8 Total 3.6 6.5 3.7 Note: Total fertility rates are for the period 1-36 months prior to the interview. Fertility • 57 40-49 would be similar. If fertility levels have fallen, the TFR will be substantially lower than the mean number of children ever born. Overall, a comparison of past (completed) and current (TFR) fertility indicators suggests a very small difference. Current fertility is higher than past fertility in rural areas. A similar trend is seen in Hardap, Omaheke, and Omusati, with smaller increases in Ohangwena, Oshikoto, and Otjozondjupa. Current fertility is also higher than past fertility among women with a secondary education and among those in the lowest and middle wealth quintiles. At the time of the survey, 7 percent of interviewed women reported that they were pregnant. This percentage is likely to be an underestimate because women in the early stages of pregnancy may be unaware that they are pregnant, and some may not want to declare that they are pregnant. Current pregnancy varies among regions, with the highest percentage in Ohangwena (10 percent) and the lowest in Hardap (4 percent). Women with no education were more likely to be pregnant at the time of the survey than women with some education. The percentage of women who were pregnant was lowest among those in the highest wealth quintile. 5.3 FERTILITY TRENDS The data in Table 5.3.1 provide evidence of fluctuations in fertility in Namibia over the past 20 years. The table uses information from the retrospective birth histories obtained from the 2013 NDHS respondents to examine trends in age-specific fertility rates for successive five-year periods before the survey. To calculate these rates, births were classified according to the period of time in which the birth occurred and the mother’s age at the time of the birth. Because women age 50 and above were not interviewed in the survey, the rates are successively truncated for periods more distant from the survey date. For example, rates cannot be calculated for women age 35-39 for the period 15 to 19 years before the survey because these women would have been over age 50 at the time of the survey and thus would not have been interviewed. Fertility has fallen among women in all age groups over the past two decades. With the exception of the 20-24 and 30-34 age groups, there has been a gradual decline in fertility over the last 20 years. The decline in fertility is steepest among women age 25-29. Table 5.3.2 and Figure 5.1 show trends in current fertility rates based on successive NDHS surveys from 1992 to 2013. Overall, the TFR declined by 1.8 births per woman between the 1992 and the 2006-07 NDHS surveys, from 5.4 births to 3.6 births per woman. There has been no change in fertility over the last six years. Table 5.3.2 Trends in fertility Age-specific and total fertility rates (TFR), Namibia 1992, 2000, 2006-07 and 2013 Mother’s age at birth NDHS 1992 (1990-1992) NDHS 2000 (1998-2000) NDHS 2006-07 (2004/5-2006/7) NDHS 2013 (2011-2013) 15-19 109 88 78 82 20-24 207 166 169 168 25-29 241 176 159 168 30-34 208 160 145 149 35-39 166 137 110 110 40-44 105 71 44 42 45-49 37 38 8 10 TFR 5.4 4.2 3.6 3.6 Note: Age-specific fertility rates are per 1,000 women. Table 5.3.1 Trends in age-specific fertility rates Age-specific fertility rates for five-year periods preceding the survey, by mother’s age at the time of the birth, Namibia 2013 Number of years preceding survey Mother’s age at birth 0-4 5-9 10-14 15-19 15-19 78 81 85 87 20-24 166 162 165 173 25-29 165 172 171 177 30-34 149 143 151 [190] 35-39 105 108 [124] 40-44 45 [62] 45-49 [9] Note: Age-specific fertility rates are per 1,000 women. Estimates in brackets are truncated. Rates exclude the month of the interview. 58 • Fertility Figure 5.1 Trends in fertility 5.4 CHILDREN EVER BORN AND LIVING Data on the number of children ever born reflect the accumulation of births over the past 30 years and therefore have limited relevance to current fertility levels, particularly when the country has experienced a decline in fertility. Moreover, the data are subject to recall error, which is typically greater for older than younger women. Nevertheless, information on children ever born (or parity) is useful in looking at a number of issues. For example, parity data show how average family size varies across age groups. Also, the percentage of currently married women in their 40s who have never had children provides an indicator of level of primary infertility or inability to bear children. Comparisons of differences in the mean number of children ever born and the mean number surviving reflect the cumulative effects of mortality levels during the childbearing period. Table 5.4 shows the percent distribution of all women and currently married women by number of children ever born, along with the mean number of children ever born and the mean number of living children. Eighty-six percent of women age 15-19 have never given birth. This proportion declines to Table 5.4 Children ever born and living Percent distribution of all women and currently married women age 15-49 by number of children ever born, mean number of children ever born, and mean number of living children, according to age group, Namibia 2013 Number of children ever born Total Number of women Mean number of children ever born Mean number of living children Age 0 1 2 3 4 5 6 7 8 9 10+ ALL WOMEN 15-19 86.2 12.4 1.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 1,906 0.15 0.15 20-24 43.9 38.4 14.5 2.7 0.5 0.1 0.0 0.0 0.0 0.0 0.0 100.0 1,786 0.78 0.74 25-29 17.3 29.3 30.8 14.6 5.9 1.5 0.5 0.1 0.0 0.0 0.0 100.0 1,489 1.70 1.61 30-34 9.1 19.2 27.7 21.7 12.2 5.3 3.1 1.2 0.5 0.1 0.0 100.0 1,260 2.46 2.31 35-39 4.9 11.8 21.7 23.0 16.3 10.8 6.0 2.8 1.7 0.3 0.7 100.0 1,110 3.23 3.01 40-44 7.4 10.8 18.7 21.8 13.9 10.2 7.6 3.9 3.5 1.3 1.0 100.0 917 3.43 3.20 45-49 4.6 5.8 14.6 20.7 15.2 12.4 9.3 7.2 6.6 1.3 2.2 100.0 708 4.14 3.79 Total 32.2 20.4 17.5 12.4 7.3 4.3 2.7 1.5 1.1 0.3 0.4 100.0 9,176 1.85 1.73 CURRENTLY MARRIED WOMEN 15-19 35.2 54.5 9.9 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 103 0.76 0.74 20-24 15.4 45.9 29.7 7.1 1.8 0.1 0.0 0.0 0.0 0.0 0.0 100.0 349 1.34 1.26 25-29 8.9 24.9 34.9 18.9 8.8 2.6 0.6 0.4 0.0 0.0 0.0 100.0 558 2.06 1.96 30-34 6.9 15.8 27.1 22.1 15.5 6.4 3.8 1.8 0.7 0.0 0.0 100.0 634 2.71 2.55 35-39 2.5 9.5 19.0 24.1 16.9 13.0 7.3 3.6 2.4 0.3 1.4 100.0 593 3.59 3.36 40-44 4.4 4.4 17.8 24.5 14.7 11.9 8.4 5.5 4.8 1.9 1.7 100.0 497 3.94 3.72 45-49 2.6 3.8 11.4 22.6 15.1 13.6 9.4 8.0 9.9 1.4 2.3 100.0 386 4.51 4.16 Total 7.4 17.6 23.3 19.9 12.3 7.8 4.8 3.0 2.6 0.5 0.8 100.0 3,121 2.96 2.78 0 50 100 150 200 250 300 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Rate (per 1,000 women) Mother's age at birth NDHS 1992 (1990-1992) NDHS 2000 (1998-2000) NDHS 2006-07 (2004/5-2006/7) NDHS 2013 (2011-2013) Fertility • 59 17 percent among women age 25-29 and to 9 percent or less among women age 30 and above, indicating that childbearing among Namibian women is nearly universal. On average, women approaching the end of their reproductive years have attained a parity of 4.1 children. This is 0.5 children more than the total fertility rate. The same pattern is seen for currently married women, except that the mean number of children ever born is higher in this group (3.0 children) than among all women (1.9 children). Results at younger ages differ between currently married women and all women because of the large number of unmarried women in the latter group, who exhibit lower fertility. Differences at older ages generally reflect the impact of marital dissolution (either divorce or widowhood). Three percent of currently married women age 45-49 have never had a child. If the desire for children is universal in Namibia, this percentage represents a rough measure of primary infertility or inability to bear children. Of the 4.1 children ever born to women age 45-49, 3.8 survived to the time of the survey. 5.5 BIRTH INTERVALS Information on the length of birth intervals provides insight into birth spacing patterns, which affect fertility as well as infant and child mortality. Research has shown that children born too soon after a previous birth are at increased risk of poor health, particularly when the interval is less than 24 months. Table 5.5 shows the distribution of births in the five years before the survey by the interval since the preceding birth, according to various background and demographic characteristics. Table 5.5 Birth intervals Percent distribution of non-first births in the five years preceding the survey by number of months since preceding birth, and median number of months since preceding birth, according to background characteristics, Namibia 2013 Background characteristic Months since preceding birth Total Number of non-first births Median number of months since preceding birth 7-17 18-23 24-35 36-47 48-59 60+ Age 15-19 (19.2) (26.5) (36.7) (11.6) (6.0) (0.0) 100.0 25 (24.6) 20-29 6.0 11.2 29.0 17.6 15.1 21.2 100.0 1,225 38.1 30-39 3.9 7.5 20.0 16.0 12.6 40.1 100.0 1,492 49.8 40-49 2.8 6.2 23.3 7.4 13.8 46.6 100.0 415 56.4 Sex of preceding birth Male 4.7 9.6 24.9 15.4 12.3 33.1 100.0 1,570 43.0 Female 4.7 8.2 23.2 15.4 15.1 33.5 100.0 1,587 46.6 Survival of preceding birth Living 4.0 8.4 24.1 15.7 13.8 34.0 100.0 2,970 45.9 Dead 14.9 17.1 23.4 11.2 11.0 22.4 100.0 186 32.9 Birth order 2-3 4.4 7.9 21.8 14.7 13.8 37.3 100.0 1,962 48.9 4-6 4.8 9.1 25.8 17.0 13.9 29.4 100.0 963 42.4 7+ 6.4 16.3 35.4 14.9 11.5 15.5 100.0 232 32.0 Residence Urban 5.2 7.1 19.8 14.5 14.2 39.1 100.0 1,435 50.6 Rural 4.2 10.4 27.6 16.2 13.2 28.4 100.0 1,722 40.9 Region Zambezi 4.2 5.3 20.9 16.8 17.7 35.3 100.0 199 49.3 Erongo 7.5 7.0 15.2 12.7 14.2 43.4 100.0 210 53.8 Hardap 7.8 11.0 22.6 12.8 11.5 34.2 100.0 109 43.7 //Karas 7.2 6.9 17.1 16.8 15.3 36.7 100.0 110 49.0 Kavango 6.3 7.6 26.8 18.7 14.4 26.2 100.0 394 41.0 Khomas 4.1 6.0 19.8 17.9 12.2 40.0 100.0 499 50.6 Kunene 6.4 14.5 26.0 14.0 13.1 26.1 100.0 130 37.6 Ohangwena 4.7 11.7 31.9 14.9 12.1 24.7 100.0 413 37.5 Omaheke 5.0 17.1 21.5 21.8 8.8 25.8 100.0 115 38.6 Omusati 0.8 11.8 28.2 15.0 12.8 31.3 100.0 306 43.4 Oshana 1.8 5.4 24.2 12.1 16.2 40.3 100.0 202 49.7 Oshikoto 4.1 9.0 29.3 12.5 14.4 30.6 100.0 253 41.2 Otjozondjupa 5.5 9.0 17.7 11.1 15.7 41.1 100.0 217 52.1 Education No education 2.8 11.7 30.2 18.3 12.4 24.5 100.0 264 38.8 Primary 5.2 8.6 27.8 16.8 15.5 26.2 100.0 872 40.9 Secondary 4.8 8.8 22.0 14.5 13.0 37.0 100.0 1,867 48.0 More than secondary 4.1 7.6 17.1 14.4 13.7 43.0 100.0 154 54.0 Wealth quintile Lowest 4.7 11.5 32.9 16.5 12.8 21.7 100.0 791 36.4 Second 4.7 9.7 25.4 17.3 12.8 30.1 100.0 698 42.1 Middle 4.5 7.9 20.1 12.2 13.9 41.4 100.0 674 52.5 Fourth 4.7 7.9 17.7 14.7 16.6 38.3 100.0 604 51.5 Highest 5.0 5.3 20.3 16.5 12.1 40.7 100.0 390 51.0 Total 4.7 8.9 24.0 15.4 13.7 33.3 100.0 3,157 45.1 Note: First-order births are excluded. The interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. Figures in parentheses are based on 25-49 unweighted cases. 60 • Fertility The median birth interval in Namibia is 45.1 months. About 14 percent of all children are born after too short an interval (less than 24 months). The median interval is shorter among births to women under age 30 than among births to older mothers. The median birth interval in urban areas (50.6 months) is substantially higher than the interval in rural areas (40.9 months). Among the regions, the median birth interval ranges from 37.5 months in Ohangwena to 53.8 months in Erongo. Birth interval increases with increasing education, from 38.8 months among women with no education to 54 months among women with more than a secondary education. In addition, median birth interval increases from 36.4 months among women in the lowest wealth quintile to 51 or more months among women in the third through fifth quintiles. 5.6 POSTPARTUM AMENORRHOEA, ABSTINENCE, AND INSUSCEPTIBILITY Postpartum amenorrhoea refers to the interval between childbirth and the return of menstruation. During this period, the risk of pregnancy is greatly reduced. The duration of this protection from conception after childbirth depends on the duration and intensity of breastfeeding and the length of time before the resumption of sexual intercourse. Women who gave birth during the three years prior to the survey were asked about their breastfeeding practices, the duration of amenorrhoea, and sexual abstinence. Women are considered insusceptible to pregnancy if they are not exposed to the risk of pregnancy either because they are amenorrhoeic or because they are still abstaining from sex after a birth. The results are shown in Table 5.6. Table 5.6 Postpartum amenorrhoea, abstinence, and insusceptibility Percentage of births in the three years preceding the survey for which mothers are postpartum amenorrhoeic, abstaining, and insusceptible, by number of months since birth, and median and mean durations, Namibia 2013 Months since birth Percentage of births for which the mother is: Number of births Amenorrhoeic Abstaining Insusceptible1 <2 80.5 96.4 99.3 133 2-3 61.5 70.7 86.8 190 4-5 51.4 62.7 78.1 189 6-7 49.3 43.7 64.6 185 8-9 39.8 39.0 58.0 176 10-11 29.6 31.2 50.5 164 12-13 26.9 29.9 47.7 160 14-15 24.2 30.2 42.0 173 16-17 18.2 25.8 36.5 168 18-19 20.2 25.4 35.5 136 20-21 10.1 16.6 24.6 162 22-23 11.6 12.9 21.9 145 24-25 4.6 14.1 16.4 194 26-27 7.2 15.9 20.8 155 28-29 4.1 12.7 16.2 153 30-31 7.4 11.4 14.4 150 32-33 7.0 9.3 14.9 167 34-35 1.2 10.6 10.8 147 Total 25.7 31.4 41.7 2,947 Median 5.7 6.3 11.3 na Mean 9.4 11.4 15.0 na Note: Estimates are based on status at the time of the survey. na = Not applicable 1 Includes births for which mothers are either still amenorrhoeic or still abstaining (or both) following birth The period of postpartum abstinence is longer than the period of postpartum amenorrhoea, suggesting that the former is a stronger determinant of the length of postpartum insusceptibility in Namibia. The median duration of amenorrhoea is 5.7 months, women abstain for a median of 6.3 months, and they are insusceptible to pregnancy for a median of 11.3 months. Almost all women are virtually insusceptible to pregnancy during the first two months after a birth, and both amenorrhoea and abstinence are important factors in their insusceptibility. However, abstinence declines more slowly over time than amenorrhoea, with the percentage of abstaining mothers higher than the percentage of amenorrhoeic mothers at almost all time intervals evaluated. Fertility • 61 5.7 MEDIAN DURATION OF POSTPARTUM INSUSCEPTIBILITY BY BACKGROUND CHARACTERISTICS In the absence of contraception, variations in postpartum amenorrhoea and abstinence are the most important determinants of the interval between births and ultimately the completion of fertility. Table 5.7 shows the median durations of postpartum amenorrhoea, abstinence, and insusceptibility by selected background characteristics. Although the median duration of postpartum amenorrhoea among women age 30-49 and 15-29 is nearly the same (5.9 months and 5.5 months, respectively), the median duration of postpartum abstinence is much longer among women age 15-29 (7.3 months) than among women age 30- 49 (4.4 months), resulting in a 3.4-month difference in the median duration of postpartum insusceptibility between younger women (12.4) and older women (9.0). Women in rural areas have a longer median duration of amenorrhoea than women in urban areas (7.9 versus 3.6 months), and they differ from women in urban areas in median duration of postpartum abstinence by more than two months (7.5 versus 5.3 months). Median duration of postpartum insusceptibility is substantially longer among women in rural areas (14.1 months) than women in urban areas (8.1 months). Postpartum insusceptibility is three months longer among women with a primary education than among women with a secondary education. The median duration of postpartum insusceptibility is more than twice as long among women in the poorest households as among women in the richest households. Table 5.7 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility Median number of months of postpartum amenorrhoea, postpartum abstinence, and postpartum insusceptibility following births in the three years preceding the survey, by background characteristics, Namibia 2013 Background characteristic Postpartum amenorrhoea Postpartum abstinence Postpartum insusceptibility1 Mother’s age 15-29 5.5 7.3 12.4 30-49 5.9 4.4 9.0 Residence Urban 3.6 5.3 8.1 Rural 7.9 7.5 14.1 Region Zambezi (6.4) (7.7) (14.8) Erongo (1.7) (4.2) (4.7) Hardap (2.8) (6.3) (11.5) //Karas * (6.9) (11.4) Kavango 5.5 3.8 (15.0) Khomas (6.0) (4.6) (8.6) Kunene 3.8 5.7 (7.2) Ohangwena (9.5) (8.0) 12.6 Omaheke (7.7) (4.6) (11.3) Omusati (7.5) (9.7) (19.0) Oshana (3.4) (6.7) (10.9) Oshikoto (7.7) (7.3) (9.4) Otjozondjupa 3.3 6.1 (11.4) Education No education (9.4) (7.4) (11.4) Primary 8.6 5.8 13.9 Secondary 5.0 6.6 10.8 More than secondary (1.4) (2.8) * Wealth quintile Lowest 9.4 6.7 13.4 Second 5.8 7.3 11.4 Middle 5.5 5.2 14.6 Fourth 2.7 7.1 11.1 Highest 2.9 4.2 6.3 Total 5.7 6.3 11.3 Note: Medians are based on status at the time of the survey (current status). Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that an estimate is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes births for which mothers are either still amenorrhoeic or still abstaining (or both) following birth 62 • Fertility 5.8 MENOPAUSE Fecundity refers to the ability to have children. The risk of pregnancy declines with age as increasing proportions of women become infecund. Although the onset of infecundity is difficult to determine for an individual woman, there are ways of estimating it for a population. Table 5.8 presents data on menopause, an indicator of decreasing exposure to the risk of pregnancy among women age 30 and older. The percentage of women who have reached menopause refers to the population of women who are neither pregnant nor postpartum amenorrhoeic and have not had a menstrual period in the six months preceding the survey, as well as women who report being menopausal. Table 5.8 shows that, overall, 11 percent of women age 30-49 are menopausal. The proportion of menopausal women increases with age, from 6 percent among those age 30-39 to 34 percent among those age 48-49. 5.9 AGE AT FIRST BIRTH The age at which childbearing begins has an impact on the health and welfare of a mother and her children. In many countries, postponement of first births has contributed to an overall fertility decline. Table 5.9 shows the distribution of women by age at first birth, according to their current age. The median age at first birth among women age 25-49 is 21.6 years, slightly higher than the figure reported in the 2006-07 NDHS (21.4 years). However, a more detailed analysis of trends in age at first birth reveals a slight increase in early childbearing. For example, whereas 14 percent of women age 45-49 gave birth by age 18, 15 percent of women age 20-24 had their first birth by age 18. Table 5.9 Age at first birth Percentage of women age 15-49 who gave birth by exact ages, percentage who have never given birth, and median age at first birth, according to current age, Namibia 2013 Percentage who gave birth by exact age Percentage who have never given birth Number of women Median age at first birth Current age 15 18 20 22 25 15-19 0.9 na na na na 86.2 1,906 a 20-24 1.1 14.9 34.6 na na 43.9 1,786 a 25-29 2.4 17.5 36.0 53.5 73.1 17.3 1,489 21.5 30-34 1.6 18.7 38.4 53.8 73.1 9.1 1,260 21.5 35-39 2.1 18.6 37.5 56.2 74.7 4.9 1,110 21.3 40-44 1.4 13.3 29.9 50.5 71.2 7.4 917 21.9 45-49 2.5 13.6 31.3 50.9 72.6 4.6 708 21.9 20-49 1.7 16.3 35.1 na na 18.0 7,270 a 25-49 2.0 16.8 35.2 53.3 73.0 9.6 5,485 21.6 na = Not applicable due to censoring a = Omitted because less than 50 percent of women had a birth before reaching the beginning of the age group Table 5.8 Menopause Percentage of women age 30-49 who are menopausal, by age, Namibia 2013 Age Percentage menopausal1 Number of women 30-34 5.6 1,260 35-39 5.9 1,110 40-41 13.6 391 42-43 10.0 348 44-45 19.9 323 46-47 24.2 283 48-49 33.6 280 Total 11.3 3,995 1 Percentage of all women who are not pregnant and not postpartum amenorrhoeic whose last menstrual period occurred 6 or more months preceding the survey Fertility • 63 5.10 MEDIAN AGE AT FIRST BIRTH BY BACKGROUND CHARACTERISTICS Table 5.10 shows the median age at first birth for different age cohorts across residential, regional, educational, and wealth status subgroups. Among women age 25-49, median age at first birth is slightly higher in urban areas than in rural areas (22.1 versus 21.0 years). By region, median age at first birth ranges from 19.3 years in Kavango to 23.1 years in Khomas. Age at first birth increases slightly with increasing levels of education and wealth. Women with no education or a primary education have their first birth about two and a half years earlier than women with a secondary education (19.5 versus 22.1 years). Women in the lowest wealth quintile have their first birth four years earlier than women in the highest quintile (19.9 versus 23.9 years). 5.11 TEENAGE PREGNANCY AND MOTHERHOOD The issue of adolescent fertility is important for both health and social reasons. Children born to very young mothers are at increased risk of sickness and death. Teenage mothers are more likely to experience adverse pregnancy outcomes and are more constrained in their ability to pursue educational opportunities than young women who delay childbearing. Table 5.11 shows the percentage of women age 15-19 who have given birth or were pregnant with their first child at the time of the survey, according to selected background characteristics. Overall, 19 percent of women age 15-19 have begun childbearing (14 percent have had a live birth, and 5 percent are currently pregnant). This represents a 4 percentage point increase in teenage pregnancies in Namibia since the 2006-07 NDHS (15 percent). The proportion of teenagers who have had a live birth rises rapidly with age, increasing from 3 percent at age 15 to 27 percent at age 19. Rural teenagers and those with a primary education tend to start childbearing earlier than their urban and better educated peers. Kunene has the highest proportion of teenage pregnancy in Namibia (39 percent), followed by Omaheke (36 percent). Oshana has the lowest proportion of teenage pregnancy (9 percent). Teenage pregnancy is more than three times higher among young women in the lowest wealth quintile than among those in the highest wealth quintile. Table 5.10 Median age at first birth Median age at first birth among women age 25-49, according to background characteristics, Namibia 2013 Background characteristic Women age 25-49 Residence Urban 22.1 Rural 21.0 Region Zambezi 20.4 Erongo 21.7 Hardap 21.4 //Karas 21.0 Kavango 19.3 Khomas 23.1 Kunene 20.0 Ohangwena 21.0 Omaheke 20.5 Omusati 22.6 Oshana 22.4 Oshikoto 22.0 Otjozondjupa 21.2 Education No education 19.5 Primary 19.5 Secondary 22.1 Wealth quintile Lowest 19.9 Second 20.9 Middle 21.2 Fourth 21.9 Highest 23.9 Total 21.6 64 • Fertility Table 5.11 Teenage pregnancy and motherhood Percentage of women age 15-19 who have had a live birth or who are pregnant with their first child, and percentage who have begun childbearing, by background characteristics, Namibia 2013 Percentage of women age 15-19 who: Percentage who have begun childbearing Number of women Background characteristic Have had a live birth Are pregnant with first child Age 15 2.5 1.2 3.6 362 16 5.9 3.6 9.5 367 17 11.8 5.8 17.5 347 18 19.7 5.8 25.5 404 19 26.5 7.1 33.6 426 Residence Urban 11.6 5.2 16.7 901 Rural 15.8 4.4 20.3 1,005 Region Zambezi 22.7 5.4 28.1 95 Erongo 12.2 3.1 15.2 119 Hardap 15.8 3.4 19.3 52 //Karas 13.1 4.5 17.6 53 Kavango 27.0 7.4 34.4 201 Khomas 8.6 3.7 12.3 375 Kunene 28.8 10.1 38.9 40 Ohangwena 14.5 8.3 22.7 245 Omaheke 24.8 11.5 36.3 40 Omusati 9.7 1.4 11.1 252 Oshana 5.4 3.6 9.0 154 Oshikoto 9.7 3.5 13.2 177 Otjozondjupa 18.5 5.1 23.6 103 Education No education (22.0) (23.1) (45.1) 31 Primary 21.2 4.5 25.7 446 Secondary 12.1 4.8 16.8 1,341 More than secondary 0.0 0.0 0.0 87 Wealth quintile Lowest 21.0 7.0 28.0 359 Second 19.6 6.1 25.6 354 Middle 13.4 4.2 17.6 360 Fourth 10.5 6.1 16.6 384 Highest 6.8 1.3 8.1 449 Total 13.8 4.8 18.6 1,906 Note: Figures in parentheses are based on 25-49 unweighted cases. Fertility Preferences • 65 FERTILITY PREFERENCES 6 nformation on fertility preferences is of considerable importance to family planning programmes because it allows planners to assess the need for contraception, whether for spacing or limiting births, and the extent of unwanted and mistimed pregnancies. Data on fertility preferences can also be useful as an indicator of the direction that future fertility patterns may take. In the 2013 NDHS, respondents were asked whether they wanted more children and, if so, how long they would prefer to wait before the next child. They were also asked, if they could start afresh, how many children they would want. 6.1 FERTILITY PREFERENCES BY NUMBER OF LIVING CHILDREN Information about the desire for more children is important for understanding future reproductive behaviour. The provision of adequate and accessible family planning services depends on the availability of such information. In the 2013 NDHS, currently married women (whether pregnant or not) and men were asked about their intentions to have another child and, if they had such intentions, how soon they wanted the child. The question was phrased differently for pregnant women and for men whose wife or wives (girlfriend or girlfriends) were pregnant at the time of the interview to ensure the wantedness of subsequent children after completion of the current pregnancy. Sterilised women and men were considered to want no more children, and therefore they were not asked questions about their desire for more children. Table 6.1 presents fertility preferences among currently married women and men by number of living children. Sixteen percent of currently married women and 18 percent of currently married men age 15-49 would like to have another child soon (within the next two years). Twenty percent of women and 18 percent of men would prefer to wait two or more years before having their next child. More than four in ten currently married respondents (45 percent of women and 41 percent of men) report that they want no more children; an additional 7 percent of women and 1 percent of men have been sterilised. Thus, about seven in ten women (72 percent) and six in ten men (59 percent) want to either delay their next birth for two or more years or end childbearing altogether. The percentage of currently married women who want no more children or are sterilised has decreased from 60 percent in the 2006-07 NDHS to 52 percent in the 2013 NDHS. I Key Findings • Fifty-two percent of currently married women and 42 percent of currently married men want no more children or have been sterilised. • The percentage of women who want to stop childbearing among currently married women has decreased from 60 percent in the 2006-07 NDHS to 52 percent in the 2013 NDHS. • Women report an ideal family size of 3.2 children, and men report an ideal family size of 3.9 children. • Overall, 49 percent of all births were wanted at the time of conception, 41 percent were reported as mistimed (wanted later), and 10 percent were unwanted. • The total wanted fertility rate is 2.9 children per woman, as compared with the actual fertility rate of 3.6 children per woman. 66 • Fertility Preferences As expected, women’s and men’s desire to have children decreases as number of living children increases. For example, 52 percent of currently married women who have no children want to have a child soon, as compared with only 4 percent of women who have six or more children. On the other hand, the proportion of women who do not want more children increases from 8 percent among those with no children to 77 percent among those with six or more children. Similar patterns are observed among currently married men. Table 6.1 Fertility preferences by number of living children Percent distribution of currently married women and currently married men age 15-49 by desire for children, according to number of living children, Namibia 2013 Number of living children Total 15-49 Desire for children 0 1 2 3 4 5 6+ WOMEN1 Have another soon2 51.7 28.3 14.8 11.1 6.3 6.1 3.9 16.1 Have another later3 17.8 36.7 24.7 16.6 15.6 6.7 5.0 20.3 Have another, undecided when 12.8 7.2 3.4 3.4 1.7 0.4 0.5 4.0 Undecided 2.4 3.2 4.1 4.9 4.6 5.5 7.4 4.5 Want no more 7.7 21.6 43.1 48.6 60.2 67.6 76.6 45.3 Sterilised4 0.6 0.5 6.5 12.2 9.6 10.1 4.8 6.7 Declared infecund 6.6 1.9 2.6 2.2 1.4 1.9 1.2 2.3 Missing 0.5 0.6 0.8 1.1 0.7 1.7 0.6 0.8 Total 15-49 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 207 562 775 633 407 214 321 3,121 MEN5 Have another soon2 37.7 33.7 12.3 11.8 11.7 14.8 10.6 17.6 Have another later3 20.0 23.4 27.2 14.9 15.3 5.7 8.1 17.7 Have another, undecided when 10.8 8.2 6.8 3.7 6.0 4.9 5.2 6.3 Undecided 14.1 17.5 10.6 11.2 16.0 20.2 12.9 14.0 Want no more 12.9 14.0 38.7 53.3 49.1 50.6 60.1 40.7 Sterilised4 0.0 1.1 2.1 0.5 0.0 0.6 0.6 0.9 Declared infecund 0.5 0.1 0.0 0.0 0.5 0.7 0.0 0.2 Missing 4.0 2.0 2.3 4.6 1.4 2.5 2.5 2.7 Total 15-49 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of men 80 205 246 222 150 98 160 1,160 1 The number of living children includes the current pregnancy. 2 Wants next birth within 2 years 3 Wants to delay next birth for 2 or more years 4 Includes both female and male sterilisation 5 The number of living children includes one additional child if the respondent’s wife is pregnant (or if any wife is pregnant for men with more than one current wife). 6.2 DESIRE TO LIMIT CHILDBEARING BY BACKGROUND CHARACTERISTICS Table 6.2 presents the percentages of currently married women and men age 15-49 who want no more children, by number of living children and selected background characteristics. Overall, there is no substantial difference in the desire to limit childbearing between urban and rural women (52 percent and 53 percent, respectively). However, among women with two or more children, those in urban areas are more likely to want to limit childbearing than those in rural areas. The reverse is true among women with one child. At the regional level, Omaheke has the highest percentage of women who want to limit childbearing (66 percent), and Zambezi has the lowest (34 percent). There is an inverse association between education and desire to limit childbearing. For example, 60 percent of women with no education want to limit childbearing, as compared with 47 percent of those with a secondary education or higher. There is no clear pattern by wealth. Overall, 42 percent of currently married men age 15-49 want to limit childbearing or have been sterilised. There are too few cases to allow meaningful comparisons of men’s desire to limit childbearing by various background characteristics or number of living children. Fertility Preferences • 67 Table 6.2 Desire to limit childbearing: Women Percentage of currently married women age 15-49 who want no more children, by number of living children, according to background characteristics, Namibia 2013 Background characteristic Number of living children1 Total 0 1 2 3 4 5 6+ Residence Urban 8.8 19.8 52.8 67.7 79.0 82.1 84.1 51.5 Rural 7.4 27.0 42.2 50.4 60.3 74.4 80.4 52.7 Region Zambezi * 15.2 22.0 41.5 (43.9) (55.9) (77.9) 34.4 Erongo (10.9) 19.6 53.2 66.3 (88.2) * * 52.1 Hardap * (31.4) 61.2 89.3 (88.5) * * 64.8 //Karas * (38.7) 52.1 62.9 (90.1) * * 61.0 Kavango * 25.1 33.3 47.7 (45.2) * 76.4 42.5 Khomas (6.9) 16.2 61.1 63.5 (76.8) * * 48.0 Kunene * (42.4) (49.2) (74.6) (77.6) (73.8) (65.0) 61.3 Ohangwena * * (41.4) * * * (82.9) 56.8 Omaheke * (35.0) 66.7 77.4 (86.7) (83.3) * 66.4 Omusati * * (36.6) (44.3) * * (84.3) 52.8 Oshana * * (56.5) (59.1) * * * 55.7 Oshikoto * (22.7) (52.4) (64.5) (79.3) * (80.7) 59.6 Otjozondjupa * (31.8) 46.8 74.0 (77.9) (97.3) (84.9) 60.1 Education No education * (32.7) (53.5) 62.8 58.6 (77.9) 75.5 60.0 Primary (21.7) 27.5 44.9 55.9 60.7 73.4 79.4 57.6 Secondary 3.5 23.1 47.3 61.0 75.2 80.8 88.5 49.8 More than secondary (12.8) 10.1 62.2 66.6 * * * 46.8 Wealth quintile Lowest (1.5) 32.8 33.8 36.0 45.5 66.9 75.6 48.2 Second (19.7) 29.4 37.5 65.2 65.8 81.9 88.2 55.9 Middle (9.3) 24.0 46.2 56.0 73.2 (77.6) 80.1 51.0 Fourth 2.8 16.3 48.4 64.2 79.7 87.2 (85.6) 49.7 Highest 10.2 15.1 61.7 72.8 89.1 (79.6) * 54.6 Total 15-49 8.3 22.1 49.6 60.8 69.8 77.7 81.4 52.0 Note: Women who have been sterilised are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The number of living children includes the current pregnancy. 6.3 IDEAL NUMBER OF CHILDREN Women and men, regardless of marital status, were asked what number of children they would choose to have if they could start afresh. Respondents who had no children were asked “If you could choose exactly the number of children to have in your whole life, how many would that be?” For respondents who had children, the question was rephrased as follows: “If you could go back to the time when you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be?” Women’s and men’s responses to these questions are summarised in Table 6.3. Table 6.3 shows that the mean ideal number of children is 3.2 for all women and 3.9 for all men, as compared with 3.7 children for currently married women and 4.6 for currently married men. Overall, more than seven in ten women (73 percent) and more than six in ten men (64 percent) ideally would want between two and four children. The ideal number of children among currently married women is similar to the figure reported in the 2006-07 NDHS. When interpreting the findings in Table 6.3, it is important to remember that the actual and stated ideal number of children tend to be related. There are several reasons for this. First, to the extent that women are able to fulfil their fertility desires, those who want large families will achieve large families. Second, because women with large families are, on average, older women, they may prefer a greater number of children because of the attitudes toward childbearing to which they were exposed during the early stages of their reproductive lives. Finally, some women may have difficulty admitting that they would prefer fewer 68 • Fertility Preferences children than they currently have if they could begin childbearing again. Such women are likely to report their actual number as their preferred number. Indeed, women who have fewer children do report a smaller ideal number of children than women with more children. The mean ideal number of children among all women with no children is 2.6, as compared with 5.4 among all women with six or more children. Similarly, the ideal number of children among men with no children is almost five fewer than the number among men with six or more children (3.2 children versus 8.1 children). Table 6.3 Ideal number of children by number of living children Percent distribution of women and men age 15-49 by ideal number of children, and mean ideal number of children for all respondents and for currently married respondents, according to number of living children, Namibia 2013 Number of living children Total Ideal number of children 0 1 2 3 4 5 6+ WOMEN1 0 6.3 2.9 2.9 3.8 6.2 4.2 5.6 4.5 1 6.4 9.1 4.1 4.7 4.1 2.0 1.9 5.8 2 40.9 31.7 30.2 13.7 12.6 13.3 7.5 28.7 3 26.0 31.2 21.0 25.7 6.4 9.9 9.2 23.3 4 12.8 16.2 29.1 29.0 32.6 17.9 19.7 20.6 5 3.5 4.6 6.6 11.2 13.6 20.2 6.9 6.9 6+ 2.2 3.6 5.9 10.4 22.6 31.3 44.5 9.0 Non-numeric responses 1.8 0.6 0.3 1.6 1.9 1.2 4.8 1.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 2,819 2,032 1,695 1,136 686 360 449 9,176 Mean ideal number of children for:2 All women 2.6 2.8 3.2 3.6 4.2 4.8 5.4 3.2 Number of women 2,768 2,019 1,690 1,118 673 355 427 9,050 Currently married women 2.7 2.9 3.2 3.7 4.2 4.9 5.4 3.7 Number of currently married women 207 562 773 628 400 212 308 3,089 MEN3 0 6.3 2.0 2.3 3.2 2.9 3.4 1.8 4.4 1 5.0 6.3 2.7 2.6 0.7 0.6 2.3 4.3 2 28.0 22.0 29.5 10.5 11.0 8.6 6.1 23.2 3 23.7 27.2 14.5 19.7 5.8 5.9 5.8 20.6 4 19.8 22.1 23.1 22.1 26.6 14.1 7.7 20.3 5 9.3 9.0 12.6 19.8 18.9 23.2 9.2 11.5 6+ 7.2 10.2 14.3 20.7 32.7 42.6 64.8 14.8 Non-numeric responses 0.7 1.2 1.1 1.4 1.4 1.6 2.2 1.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 2,065 638 449 337 219 126 187 4,021 Mean ideal number of children for:2 All men 3.2 3.7 3.9 4.5 5.3 5.7 8.1 3.9 Number of men 2,051 631 444 332 216 124 183 3,980 Currently married men 2.6 3.5 3.6 4.3 5.5 5.3 7.6 4.6 Number of currently married men 80 205 245 219 148 97 156 1,148 1 The number of living children includes the current pregnancy. 2 Means are calculated excluding respondents who gave non-numeric responses. 3 The number of living children includes one additional child if the respondent’s wife is pregnant (or if any wife is pregnant for men with more than one current wife). Fertility Preferences • 69 6.4 MEAN IDEAL NUMBER OF CHILDREN BY BACKGROUND CHARACTERISTICS Table 6.4 shows the mean ideal number of children among all women age 15-49 by background characteristics. Mean ideal number of children increases consistently with age, from 2.4 among women age 15-19 to 4.4 among women age 45-49. Women in rural areas have a larger ideal family size than those in urban areas (3.5 children and 3.0 children, respectively). Among regions, women in Hardap have the lowest desired family size (2.4 children) and women in Ohangwena have the highest (4.1 children). The mean ideal number of children decreases steadily with increasing education, from a high of 4.2 children among women with no education to a low of 2.9 children among women with a secondary education or higher. Mean ideal number of children also decreases with increasing wealth, from 3.9 children among women in the lowest quintile to 2.8 among those in the highest quintile. 6.5 FERTILITY PLANNING STATUS Information collected in the 2013 NDHS can also be used to estimate levels of unwanted fertility. This information provides insight into the degree to which couples are able to control fertility. Women age 15-49 were asked a series of questions about each child born to them in the preceding five years, as well as any current pregnancy, to determine whether the birth or pregnancy was wanted then (planned), wanted later (mistimed), or not wanted at all (unplanned) at the time of conception. In assessing these results, it is important to recognise that women may declare a previously unwanted birth or current pregnancy as wanted, and this rationalisation would result in an underestimate of the true extent of unwanted births. Table 6.5 shows the distribution of births in the five years before the survey by the planning status of the birth. Overall, 49 percent of births were wanted at the time of conception, 41 percent were reported as mistimed (wanted later), and 10 percent were unwanted. In general, the percentage of mistimed births decreases with increasing birth order, from 53 percent for first births to 32-34 percent for births of order three or higher. On the other hand, the proportion of unwanted births increases with birth order, from 5 percent for first births to 19 percent for births of order four or higher. A much larger proportion of births to older women than younger women are unwanted. For example, only 6 percent of births to women who gave birth at age 20-24 are unwanted, as compared with 27 percent of births to women who gave birth at age 40-44. The percentage of wanted pregnancies increases with age and peaks at 60 percent among women age 30-34, after which it decreases steadily. The percentage of mistimed births decreases steadily with age, from 60 percent among women who gave birth before age 20 to 22 percent among women who gave birth at age 40-44. Table 6.4 Mean ideal number of children Mean ideal number of children for all women age 15-49 by background characteristics, Namibia 2013 Background characteristic Mean Number of women1 Age 15-19 2.4 1,861 20-24 2.8 1,780 25-29 3.1 1,481 30-34 3.5 1,251 35-39 3.9 1,090 40-44 3.9 901 45-49 4.4 686 Residence Urban 3.0 5,151 Rural 3.5 3,899 Region Zambezi 3.7 450 Erongo 3.1 766 Hardap 2.4 303 //Karas 2.9 343 Kavango 3.3 829 Khomas 3.0 2,190 Kunene 3.5 254 Ohangwena 4.1 851 Omaheke 3.1 224 Omusati 3.3 873 Oshana 3.2 752 Oshikoto 3.2 683 Otjozondjupa 3.1 534 Education No education 4.2 404 Primary 3.7 1,746 Secondary 3.1 5,973 More than secondary 2.9 927 Wealth quintile Lowest 3.9 1,380 Second 3.5 1,594 Middle 3.3 1,778 Fourth 2.9 2,097 Highest 2.8 2,201 Total 3.2 9,050 1 Number of women who gave a numeric response 70 • Fertility Preferences Table 6.5 Fertility planning status Percent distribution of births to women age 15-49 in the five years preceding the survey (including current pregnancies), by planning status of the birth, according to birth order and mother’s age at birth, Namibia 2013 Planning status of birth Total Number of births Birth order and mother’s age at birth Wanted then Wanted later Wanted no more Missing Birth order 1 41.8 52.5 5.0 0.7 100.0 1,858 2 53.9 37.1 8.6 0.4 100.0 1,355 3 56.5 31.9 11.5 0.1 100.0 853 4+ 47.2 33.5 19.0 0.3 100.0 1,337 Mother’s age at birth <20 30.2 60.2 8.5 1.1 100.0 860 20-24 44.3 49.1 6.2 0.4 100.0 1,481 25-29 51.8 39.2 8.7 0.2 100.0 1,254 30-34 59.9 27.1 12.6 0.4 100.0 987 35-39 58.6 24.2 16.7 0.4 100.0 597 40-44 50.0 22.4 27.4 0.2 100.0 208 45-49 * * * * 100.0 17 Total 48.5 40.7 10.4 0.5 100.0 5,404 Note: Women who have been sterilised are considered to want no more children. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 6.6 WANTED FERTILITY RATES Responses to the question on ideal number of children are used to calculate the total “wanted” fertility rate. This measure is calculated in the same manner as the conventional total fertility rate, except that unwanted births are excluded from the numerator. A birth is considered wanted if the number of living children at the time of conception is less than the ideal number of children reported by the respondent. Wanted fertility rates express the level of fertility that theoretically would result if all unwanted births were prevented. Comparison of the actual fertility rate with the wanted rate indicates the potential demographic impact of eliminating unwanted births. Table 6.6 shows that the wanted fertility rate is 2.9 children, as compared with the actual fertility rate of 3.6 children (rates were calculated over the three years prior to the survey). In other words, Namibian women are currently having an average of 0.7 children more than they actually want. The table also shows that regardless of place of residence, level of education, and wealth quintile, the wanted fertility rate is lower than the actual total fertility rate. Women in rural areas have a larger gap between their actual and wanted fertility (1.2) than women in urban areas (0.5). Among regions, the largest difference between actual and wanted fertility is in Omaheke (1.5 children), and the narrowest gap is in Khomas and Oshana (0.3 children each). Women with no education and those in the lowest wealth quintile have the largest gap between wanted and actual fertility rates (1.6 children each). Table 6.6 Wanted fertility rates Total wanted fertility rates and total fertility rates for the three years preceding the survey, by background characteristics, Namibia 2013 Background characteristic Total wanted fertility rate Total fertility rate Residence Urban 2.4 2.9 Rural 3.5 4.7 Region Zambezi 3.7 4.2 Erongo 2.4 2.9 Hardap 2.3 3.7 //Karas 2.6 3.4 Kavango 3.2 4.6 Khomas 2.3 2.6 Kunene 3.1 4.5 Ohangwena 4.2 5.3 Omaheke 3.1 4.6 Omusati 3.2 4.2 Oshana 2.4 2.7 Oshikoto 3.1 4.2 Otjozondjupa 3.4 4.1 Education No education 3.7 5.3 Primary 3.4 4.8 Secondary 2.8 3.5 More than secondary 2.1 2.2 Wealth quintile Lowest 3.9 5.5 Second 3.4 4.4 Middle 3.0 3.9 Fourth 2.5 3.1 Highest 2.0 2.3 Total 2.9 3.6 Note: Rates are calculated based on births to women age 15-49 in the period 1-36 months preceding the survey. The total fertility rates are the same as those presented in Table 5.2. Family Planning • 71 FAMILY PLANNING 7 amily planning refers to a conscious effort to limit or space the number of children they want to have through the use of contraceptives. This chapter presents results from the 2013 NDHS on a number of aspects of contraception: knowledge of specific contraceptive methods, attitudes and behaviours regarding contraceptive use, current use, and sources of current contraceptive methods. The chapter focuses on women who are sexually active because these women have the greatest risk of exposure to pregnancy and therefore the greatest need for regulating their fertility. However, the results of interviews with men are presented along with those of women because men play an equally important role in making decisions about sexual reproductive health and family planning. 7.1 KNOWLEDGE OF CONTRACEPTIVE METHODS Information about contraceptive methods was collected by asking respondents if they had heard of various methods that can be used to delay or avoid a pregnancy. Specifically, the interviewer named a method, described it, and then asked whether the respondent had heard of it. In all, the interviewer asked about thirteen different contraceptive methods. Provision was also made in the questionnaire to record any additional methods the respondent had heard of but was not asked about by the interviewer. Contraceptive methods are classified into two broad categories, modern methods and traditional methods. Modern methods include female sterilisation, male sterilisation, the pill, the intrauterine contraceptive device (IUCD), injectables, implants, male condoms, female condoms, the lactational amenorrhoea method (LAM), the contraceptive patch, and emergency contraception. Traditional methods include fertility awareness methods such as rhythm (periodic abstinence), withdrawal, and various folk methods such as use of strings and herbs. F Key Findings • Knowledge of contraception is universal in Namibia: nearly all women and men have heard of at least one method. • One in two (50 percent) women age 15-49 use a method of contraception. Injectables are the most commonly used method (21 percent). • Use of a modern method is 53 percent among women in the highest wealth quintile versus 39 percent among women in the lowest wealth quintile. • The majority of modern contraceptive users obtain their method from the public sector (73 percent). • Fifty-seven percent of modern contraceptive users were informed of side effects or health problems associated with the method they used; 51 percent knew what to do if they experienced side effects, and 65 percent had been told of other methods available. • Twelve percent of all women have an unmet need for family planning services (8 percent for spacing and 4 percent for limiting births). Eight in ten women’s demand for family planning has been satisfied. • Eighty-five percent of nonusers who had contact with a fieldworker or health facility in the 12 months preceding the survey did not use the opportunity to discuss family planning. 72 • Family Planning Table 7.1 shows that knowledge of contraceptive methods is universal in Namibia, with nearly all women and men age 15-49 aware of at least one method of contraception. Modern methods are more widely known than traditional methods; almost all women know of a modern method, while 67 percent know of a traditional method. Male condoms (99 percent), injectables (96 percent), the pill (95 percent), and female condoms (94 percent) are the most commonly known modern methods among women, with relatively smaller percentages mentioning the other modern methods. The extent of and patterns in knowledge of a modern method of family planning are similar among currently married and sexually active unmarried women and men. Because knowledge of at least one method of contraception is universal, there are few differences in knowledge by background characteristics (data not shown). Table 7.1 Knowledge of contraceptive methods Percentage of all respondents, currently married respondents, and sexually active unmarried respondents age 15-49 who know any contraceptive method, by specific method, Namibia 2013 Women Men Method All women Currently married women Sexually active unmarried women1 All men Currently married men Sexually active unmarried men1 Any method 99.6 99.8 99.8 99.7 100.0 100.0 Any modern method 99.6 99.8 99.8 99.7 100.0 100.0 Female sterilisation 69.8 75.3 72.2 66.9 74.8 73.1 Male sterilisation 42.6 44.6 43.5 52.9 57.1 58.7 Pill 94.5 97.1 96.2 89.0 94.1 93.3 Contraceptive patch 31.9 33.9 36.1 27.9 31.0 31.5 IUD 51.4 54.8 55.2 34.8 39.5 39.9 Injectables 95.8 98.3 97.4 88.3 93.0 93.7 Implants 28.4 32.4 30.0 30.1 36.0 35.4 Male condom 98.7 98.4 99.5 99.1 99.7 99.9 Female condom 94.2 94.1 95.7 92.5 93.0 97.0 Lactational amenorrhoea (LAM) 18.3 23.2 18.3 12.7 16.2 14.6 Emergency contraception 43.3 44.1 47.0 46.1 51.9 53.6 Any traditional method 67.3 70.7 74.0 73.2 77.5 83.8 Rhythm 48.5 50.9 54.0 47.5 50.8 55.7 Withdrawal 57.0 61.1 63.9 68.0 73.8 79.0 Other 4.2 5.5 3.4 4.1 4.4 5.1 Mean number of methods known by respondents age 15-49 7.8 8.1 8.1 7.6 8.2 8.3 Number of respondents 9,176 3,121 1,437 4,021 1,160 896 Mean number of methods known by respondents age 15-64 na na na 6.8 6.2 8.1 Number of respondents na na na 4,481.0 1,526.5 914.3 na = Not applicable 1 Had last sexual intercourse within 30 days preceding the survey With respect to traditional methods, withdrawal and the rhythm method are known by 49 percent and 57 percent of all women, respectively. Women know 7.8 contraceptive methods on average, while men know 7.6 methods. This is an increase from an average of 6.1 contraceptive methods known by both women and men in the 2006-07 NDHS. 7.2 CURRENT USE OF CONTRACEPTION The prevalence of contraceptive use among women in Namibia at the time of the survey is one of the principal determinants of fertility. Changes in prevalence that have occurred over time can indicate the overall success of family planning programmes. Percentages of contraceptive use among all women, currently married women, and sexually active unmarried women age 15-49 are presented in Table 7.2.1. The results show that 50 percent of all women in Namibia are using a modern contraceptive method. This represents a very small increase from the figure reported in the 2006-07 NDHS (47 percent). Fa m ily P la nn in g • 7 3 Ta bl e 7. 2. 1 C ur re nt u se o f c on tra ce pt io n by a ge P er ce nt d is tri bu tio n of a ll w om en , c ur re nt ly m ar rie d w om en , a nd s ex ua lly a ct iv e un m ar rie d w om en a ge 1 5- 49 b y co nt ra ce pt iv e m et ho d cu rre nt ly u se d, a cc or di ng to a ge , N am ib ia 2 01 3 A ny m et ho d A ny m od er n m et ho d M od er n m et ho d A ny tra di - tio na l m et ho d Tr ad iti on al m et ho d N ot cu rr en t- ly u si ng To ta l N um be r of w om en A ge Fe m al e st er ili - sa tio n M al e st er ili - sa tio n P ill IU D C on tra - ce pt iv e pa tc h In je ct - ab le s Im - pl an ts M al e co nd om Fe m al e co nd om D ia - ph ra gm LA M O th er R hy th m W ith - dr aw al O th er A LL W O M E N 15 -1 9 24 .5 24 .1 0. 0 0. 0 1. 1 0. 0 0. 0 9. 2 0. 0 13 .3 0. 4 0. 0 0. 0 0. 0 0. 3 0. 0 0. 0 0. 3 75 .5 10 0. 0 1, 90 6 20 -2 4 56 .4 55 .9 0. 1 0. 0 3. 9 0. 3 0. 7 24 .3 0. 1 25 .7 0. 8 0. 0 0. 0 0. 0 0. 5 0. 2 0. 0 0. 3 43 .6 10 0. 0 1, 78 6 25 -2 9 62 .7 62 .4 0. 2 0. 0 6. 0 0. 3 0. 8 31 .4 0. 3 23 .0 0. 2 0. 0 0. 1 0. 2 0. 3 0. 2 0. 0 0. 1 37 .3 10 0. 0 1, 48 9 30 -3 4 59 .1 58 .4 2. 1 0. 1 7. 3 1. 1 1. 0 28 .4 0. 2 17 .8 0. 2 0. 0 0. 2 0. 1 0. 7 0. 2 0. 5 0. 0 40 .9 10 0. 0 1, 26 0 35 -3 9 55 .9 55 .7 5. 4 0. 2 6. 4 0. 9 0. 5 23 .3 0. 1 18 .3 0. 4 0. 0 0. 1 0. 0 0. 3 0. 0 0. 1 0. 2 44 .1 10 0. 0 1, 11 0 40 -4 4 54 .9 54 .6 7. 9 0. 4 5. 1 0. 9 0. 4 20 .1 0. 1 18 .7 0. 7 0. 0 0. 1 0. 1 0. 3 0. 2 0. 0 0. 1 45 .1 10 0. 0 91 7 45 -4 9 46 .1 45 .2 13 .8 0. 1 3. 9 1. 5 0. 4 8. 8 0. 1 15 .6 0. 8 0. 2 0. 0 0. 1 0. 9 0. 2 0. 5 0. 3 53 .9 10 0. 0 70 8 To ta l 50 .2 49 .7 2. 8 0. 1 4. 5 0. 6 0. 5 21 .2 0. 1 19 .2 0. 5 0. 0 0. 1 0. 1 0. 5 0. 1 0. 1 0. 2 49 .8 10 0. 0 9, 17 6 C U R R EN TL Y M AR R IE D W O M EN 15 -1 9 37 .2 32 .2 0. 0 0. 0 3. 1 0. 0 0. 0 23 .3 0. 0 5. 8 0. 0 0. 0 0. 0 0. 0 5. 0 0. 0 0. 0 5. 0 62 .8 10 0. 0 10 3 20 -2 4 53 .7 53 .2 0. 0 0. 0 4. 7 1. 0 1. 7 35 .5 0. 0 10 .3 0. 0 0. 0 0. 0 0. 0 0. 5 0. 5 0. 0 0. 0 46 .3 10 0. 0 34 9 25 -2 9 58 .5 58 .0 0. 2 0. 1 7. 6 0. 5 1. 3 35 .8 0. 2 11 .9 0. 0 0. 0 0. 0 0. 4 0. 5 0. 0 0. 1 0. 4 41 .5 10 0. 0 55 8 30 -3 4 58 .4 57 .6 3. 4 0. 1 9. 3 2. 0 1. 0 30 .0 0. 2 11 .2 0. 0 0. 0 0. 3 0. 2 0. 8 0. 3 0. 6 0. 0 41 .6 10 0. 0 63 4 35 -3 9 57 .3 56 .9 8. 4 0. 4 7. 3 1. 0 0. 3 24 .5 0. 2 14 .3 0. 4 0. 0 0. 1 0. 0 0. 4 0. 0 0. 1 0. 3 42 .7 10 0. 0 59 3 40 -4 4 57 .5 56 .9 11 .3 0. 7 6. 1 1. 1 0. 7 24 .2 0. 2 12 .1 0. 3 0. 0 0. 1 0. 1 0. 5 0. 3 0. 0 0. 2 42 .5 10 0. 0 49 7 45 -4 9 52 .6 50 .9 18 .4 0. 2 5. 7 2. 0 0. 5 8. 8 0. 1 13 .5 1. 2 0. 3 0. 0 0. 1 1. 7 0. 3 0. 9 0. 5 47 .4 10 0. 0 38 6 To ta l 56 .1 55 .3 6. 4 0. 3 7. 0 1. 2 0. 9 26 .8 0. 2 12 .0 0. 3 0. 0 0. 1 0. 1 0. 8 0. 2 0. 3 0. 4 43 .9 10 0. 0 3, 12 1 S EX U A LL Y A C TI VE U N M A R R IE D W O M E N 1 15 -1 9 72 .5 72 .3 0. 0 0. 0 1. 9 0. 0 0. 0 17 .2 0. 0 51 .1 2. 1 0. 0 0. 0 0. 0 0. 2 0. 2 0. 0 0. 0 27 .5 10 0. 0 19 5 20 -2 4 77 .7 77 .7 0. 0 0. 0 5. 9 0. 1 1. 2 25 .8 0. 6 42 .5 1. 5 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 22 .3 10 0. 0 39 0 25 -2 9 82 .2 82 .2 0. 3 0. 0 6. 5 0. 3 1. 1 30 .8 0. 7 41 .1 1. 0 0. 0 0. 0 0. 4 0. 0 0. 0 0. 0 0. 0 17 .8 10 0. 0 33 4 30 -3 4 75 .6 74 .4 0. 9 0. 0 7. 6 0. 0 3. 0 35 .9 0. 4 25 .9 0. 4 0. 0 0. 0 0. 3 1. 2 0. 0 1. 2 0. 0 24 .4 10 0. 0 20 8 35 -3 9 79 .2 78 .9 3. 3 0. 0 9. 9 0. 2 1. 6 26 .0 0. 0 37 .2 0. 7 0. 0 0. 0 0. 0 0. 3 0. 0 0. 0 0. 3 20 .8 10 0. 0 15 7 40 -4 4 78 .0 78 .0 1. 4 0. 0 6. 0 0. 8 0. 0 25 .4 0. 0 43 .4 1. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 22 .0 10 0. 0 10 3 45 -4 9 74 .1 74 .1 8. 3 0. 0 5. 5 0. 8 1. 4 22 .5 0. 0 35 .6 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 25 .9 10 0. 0 50 To ta l 77 .8 77 .6 0. 9 0. 0 6. 2 0. 2 1. 2 27 .1 0. 4 40 .2 1. 1 0. 0 0. 0 0. 1 0. 2 0. 0 0. 2 0. 0 22 .2 10 0. 0 1, 43 7 N ot e: If m or e th an o ne m et ho d is u se d, o nl y th e m os t e ffe ct iv e m et ho d is c on si de re d in th is ta bu la tio n. LA M = L ac ta tio na l a m en or rh oe a m et ho d 1 W om en w ho h ad s ex ua l i nt er co ur se w ith in 3 0 da ys p re ce di ng th e su rv ey Family Planning • 73 74 • Family Planning Among all women, the contraceptive methods most commonly used are injectables (21 percent) and male condoms (19 percent). Five percent of all women use the pill and 3 percent use female sterilisation, while a total of 2 percent use the IUCD, contraceptive patch, female condom, male sterilisation, implants, LAM, diaphragm, or other modern methods. The use of modern contraceptive methods among all women increases with age, from 24 percent among those age 15-19 to 62 percent among those age 25-29, before gradually falling to a low of 45 percent among women age 45-49. A similar pattern emerges in the use of injectables. 7.3 CURRENT USE OF CONTRACEPTION BY BACKGROUND CHARACTERISTICS Table 7.2.2 presents information on current use of contraceptives among all women age 15-49. Current use of any method of contraception varies by number of living children, residence, region, education, and wealth quintile. One in three women without children uses a contraceptive method (33 percent). The use of any contraceptive method increases from 59 percent among women with one to two children to 62 percent among women with three to four children before falling to 49 percent among women with five or more children. Women in rural areas are less likely to use contraceptive methods than their counterparts in urban areas (43 percent versus 56 percent). Among regions, use of contraceptive methods is highest in //Karas (60 percent) and lowest in Omusati (37 percent). Contraceptive use is positively associated with women’s level of education and wealth. For example, 34 percent of women with no education use contraceptives, as compared with 58 percent of those with more than a secondary education. Similarly, only 40 percent of women in the lowest wealth quintile use contraceptives, compared with 54 percent of women in the highest wealth quintile. Fa m ily P la nn in g • 7 5 Ta bl e 7. 2. 2 C ur re nt u se o f c on tra ce pt io n by b ac kg ro un d ch ar ac te ris tic s P er ce nt d is tri bu tio n of a ll w om en a ge 1 5- 49 b y co nt ra ce pt iv e m et ho d cu rr en tly u se d, a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, N am ib ia 2 01 3 A ny m et ho d A ny m od er n m et ho d M od er n m et ho d A ny tra di - tio na l m et ho d Tr ad iti on al m et ho d N ot cu rr en t- ly u si ng To ta l N um be r of w om en B ac kg ro un d ch ar ac te ris tic Fe m al e st er ili - sa tio n M al e st er ili - sa tio n Pi ll IU C D C on tra - ce pt iv e pa tc h In je ct - ab le s Im - pl an ts M al e co nd om Fe m al e co nd om D ia - ph ra gm LA M O th er R hy th m W ith - dr aw al O th er N um be r o f l iv in g ch ild re n 0 33 .1 32 .7 0. 1 0. 0 2. 0 0. 1 0. 4 5. 8 0. 0 23 .4 0. 8 0. 0 0. 0 0. 0 0. 4 0. 2 0. 0 0. 1 66 .9 10 0. 0 3, 03 4 1- 2 59 .0 58 .6 1. 6 0. 2 6. 2 0. 7 0. 7 29 .3 0. 3 19 .1 0. 2 0. 0 0. 1 0. 2 0. 4 0. 0 0. 1 0. 2 41 .0 10 0. 0 3, 60 6 3- 4 62 .0 61 .3 8. 4 0. 0 6. 2 1. 1 0. 4 29 .4 0. 1 14 .9 0. 6 0. 1 0. 1 0. 0 0. 7 0. 2 0. 3 0. 2 38 .0 10 0. 0 1, 75 0 5+ 49 .3 48 .6 7. 0 0. 0 3. 1 0. 5 0. 2 24 .4 0. 1 13 .1 0. 3 0. 0 0. 0 0. 0 0. 7 0. 1 0. 2 0. 4 50 .7 10 0. 0 78 5 R es id en ce U rb an 55 .5 55 .1 3. 8 0. 1 5. 5 0. 8 0. 9 21 .2 0. 2 22 .0 0. 5 0. 0 0. 1 0. 1 0. 4 0. 2 0. 1 0. 1 44 .5 10 0. 0 5, 19 0 R ur al 43 .2 42 .7 1. 6 0. 0 3. 3 0. 3 0. 0 21 .1 0. 0 15 .7 0. 5 0. 0 0. 0 0. 1 0. 5 0. 1 0. 1 0. 3 56 .8 10 0. 0 3, 98 6 R eg io n Za m be zi 49 .8 49 .5 0. 2 0. 0 3. 8 0. 0 0. 3 39 .8 0. 0 5. 3 0. 2 0. 0 0. 0 0. 0 0. 2 0. 2 0. 0 0. 0 50 .2 10 0. 0 45 7 E ro ng o 56 .5 55 .9 4. 3 0. 3 5. 4 0. 7 0. 2 22 .8 0. 4 21 .3 0. 2 0. 0 0. 2 0. 0 0. 5 0. 2 0. 3 0. 1 43 .5 10 0. 0 77 1 H ar da p 49 .8 49 .8 9. 0 0. 2 7. 3 0. 3 0. 2 24 .4 0. 3 8. 1 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 0. 0 50 .2 10 0. 0 30 4 //K ar as 59 .5 58 .8 6. 8 0. 2 6. 2 0. 7 0. 2 29 .1 0. 0 15 .1 0. 1 0. 0 0. 1 0. 3 0. 7 0. 2 0. 1 0. 4 40 .5 10 0. 0 34 3 K av an go 40 .8 39 .3 0. 8 0. 0 3. 3 0. 2 0. 0 29 .3 0. 0 5. 7 0. 0 0. 0 0. 0 0. 1 1. 5 0. 0 0. 0 1. 5 59 .2 10 0. 0 83 5 K ho m as 56 .3 55 .7 3. 4 0. 1 5. 2 1. 3 1. 7 18 .1 0. 2 25 .2 0. 5 0. 0 0. 0 0. 0 0. 6 0. 2 0. 3 0. 1 43 .7 10 0. 0 2, 20 2 K un en e 52 .2 52 .1 0. 6 0. 2 5. 2 0. 4 0. 2 25 .2 0. 0 20 .3 0. 0 0. 0 0. 0 0. 0 0. 2 0. 0 0. 2 0. 0 47 .8 10 0. 0 25 8 O ha ng w en a 39 .4 39 .2 1. 7 0. 0 2. 4 0. 1 0. 0 15 .0 0. 0 19 .6 0. 2 0. 0 0. 0 0. 2 0. 1 0. 1 0. 0 0. 0 60 .6 10 0. 0 89 4 O m ah ek e 55 .4 55 .2 6. 6 0. 3 5. 3 0. 5 0. 5 26 .0 0. 5 15 .2 0. 0 0. 0 0. 1 0. 2 0. 2 0. 2 0. 0 0. 0 44 .6 10 0. 0 22 5 O m us at i 37 .2 37 .1 0. 9 0. 0 2. 7 0. 4 0. 0 14 .6 0. 0 17 .7 0. 5 0. 1 0. 0 0. 0 0. 1 0. 1 0. 0 0. 0 62 .8 10 0. 0 88 4 O sh an a 57 .9 57 .5 2. 9 0. 0 4. 2 0. 1 0. 3 15 .3 0. 2 32 .6 1. 9 0. 0 0. 0 0. 0 0. 4 0. 1 0. 0 0. 3 42 .1 10 0. 0 75 5 O sh ik ot o 49 .3 49 .3 1. 9 0. 0 5. 2 0. 6 0. 4 18 .5 0. 0 21 .4 1. 1 0. 0 0. 1 0. 1 0. 0 0. 0 0. 0 0. 0 50 .7 10 0. 0 70 7 O tjo zo nd ju pa 51 .6 51 .1 3. 7 0. 1 6. 1 0. 1 0. 1 24 .5 0. 1 15 .2 0. 3 0. 0 0. 5 0. 3 0. 5 0. 1 0. 4 0. 0 48 .4 10 0. 0 54 0 Ed uc at io n N o ed uc at io n 33 .7 32 .7 2. 4 0. 0 2. 6 0. 0 0. 0 16 .2 0. 0 10 .8 0. 2 0. 0 0. 4 0. 0 1. 0 0. 0 0. 4 0. 6 66 .3 10 0. 0 41 9 P rim ar y 42 .8 42 .4 3. 2 0. 0 2. 9 0. 1 0. 0 23 .7 0. 0 12 .4 0. 1 0. 0 0. 0 0. 0 0. 4 0. 0 0. 0 0. 4 57 .2 10 0. 0 1, 79 8 S ec on da ry 52 .3 52 .0 2. 4 0. 1 4. 4 0. 6 0. 4 22 .7 0. 1 20 .5 0. 7 0. 0 0. 0 0. 1 0. 3 0. 1 0. 1 0. 1 47 .7 10 0. 0 6, 02 9 M or e th an s ec on da ry 58 .0 56 .9 5. 4 0. 5 9. 2 1. 6 2. 9 8. 1 0. 3 27 .9 0. 3 0. 1 0. 2 0. 4 1. 1 0. 5 0. 4 0. 2 42 .0 10 0. 0 93 0 W ea lth q ui nt ile Lo w es t 39 .6 38 .9 1. 2 0. 0 2. 5 0. 0 0. 0 21 .6 0. 0 13 .2 0. 3 0. 0 0. 0 0. 0 0. 8 0. 1 0. 0 0. 7 60 .4 10 0. 0 1, 42 9 S ec on d 48 .7 48 .5 1. 8 0. 0 3. 7 0. 1 0. 0 25 .0 0. 0 17 .2 0. 6 0. 0 0. 1 0. 0 0. 2 0. 0 0. 1 0. 1 51 .3 10 0. 0 1, 62 5 M id dl e 52 .9 52 .4 1. 9 0. 0 4. 0 0. 4 0. 0 24 .4 0. 1 21 .2 0. 3 0. 0 0. 1 0. 0 0. 5 0. 1 0. 1 0. 2 47 .1 10 0. 0 1, 79 5 Fo ur th 52 .5 52 .1 2. 5 0. 0 4. 5 0. 2 0. 5 22 .3 0. 1 21 .1 0. 7 0. 1 0. 0 0. 1 0. 3 0. 1 0. 1 0. 2 47 .5 10 0. 0 2, 11 6 H ig he st 53 .7 53 .1 5. 8 0. 3 6. 9 1. 8 1. 7 14 .2 0. 3 21 .3 0. 4 0. 0 0. 1 0. 2 0. 5 0. 3 0. 2 0. 0 46 .3 10 0. 0 2, 21 1 To ta l 50 .2 49 .7 2. 8 0. 1 4. 5 0. 6 0. 5 21 .2 0. 1 19 .2 0. 5 0. 0 0. 1 0. 1 0. 5 0. 1 0. 1 0. 2 49 .8 10 0. 0 9, 17 6 N ot e: If m or e th an o ne m et ho d is u se d, o nl y th e m os t e ffe ct iv e m et ho d is c on si de re d in th is ta bu la tio n. LA M = L ac ta tio na l a m en or rh oe a m et ho d Family Planning • 75 76 • Family Planning Table 7.3 and Figure 7.1 show trends in contraceptive use among all women over the past 21 years, as measured by the 1992, 2000, 2006-07, and 2013 NDHS surveys. Over this time period, use of contraception has risen from 23 percent to 50 percent. Table 7.3 Trends in contraceptive use Percentage of all women who are currently using contraception, by specific method, Namibia 1992, 2000, 2006-07, and 2013 Method 1992 NDHS 2000 NDHS 2006-07 NDHS 2013 NDHS Any method 23.3 37.8 46.6 50.2 Any modern method 21.4 37.1 45.7 49.7 Female sterilisation 3.8 4.3 5.0 2.8 Male sterilisation 0.1 0.3 0.2 0.1 Pill 7.1 5.7 5.4 4.5 IUD 1.3 0.7 0.6 0.6 Injectables 8.6 17.0 17.1 21.2 Implants u u 0.1 0.1 Male condom 0.5 8.9 17.0 19.2 Female condom u u 0.3 0.5 Contraceptive patch u u u 0.5 Any traditional method 1.8 0.7 0.9 0.5 Rhythm/periodic abstinence 0.6 0.1 0.3 0.1 Withdrawal 0.2 0.1 0.1 0.1 Other traditional methods 1.0 0.5 0.5 0.2 Number of women 5,421 6,755 9,804 9,176 u = Unknown Figure 7.1 Trends in contraceptive use among all women age 15-49, Namibia 1992-2013 7.4 SOURCE OF MODERN CONTRACEPTIVE METHODS Information on where women obtain the contraceptive methods they use is useful for family planning programme managers and others who plan the distribution of contraceptives. In the 2013 NDHS, all women who reported that they were currently using any modern contraceptive method at the time of the survey were asked where they obtained the method the last time they used it. Sometimes women may know the name of the facility but not know whether it is a public or private sector source. In such cases, interviewers were instructed to note the full name of the source or facility. Supervisors were trained to 23 38 47 50 21 37 46 50 1992 NDHS 2000 NDHS 2006-07 NDHS 2013 NDHS Percent Any method Any modern method Family Planning • 77 verify the name and type of source to maintain consistency and improve the accuracy of the information collected. Table 7.4 shows that the majority of users obtain their contraceptives from public sector sources (73 percent). Government primary health care clinics and government hospitals are the most common public sources of contraceptives (48 percent and 22 percent, respectively). Twelve percent of users obtain their contraceptives from private sources and 11 percent from other sources. Table 7.4 Source of modern contraception methods Percent distribution of users of modern contraceptive methods age 15-49 by most recent source of method, according to method, Namibia 2013 Source Female sterilisation Pill Injectables Male condom Total Public 64.9 71.8 95.4 53.4 73.0 Government hospital 64.5 11.3 17.1 22.6 21.6 Government health centre 0.4 1.4 3.5 0.8 2.0 Government primary health care clinic 0.0 57.6 73.8 27.7 47.9 Outreach point 0.0 0.6 0.2 0.7 0.4 Mobile clinic 0.0 0.9 0.5 0.7 0.6 Other public 0.0 0.0 0.3 0.9 0.5 Private 34.9 26.0 3.6 10.5 12.1 Private hospital 31.6 3.0 0.8 0.4 3.0 Private clinic 2.6 0.8 1.0 0.3 0.9 Pharmacy 0.0 10.7 0.2 9.6 5.3 Private doctor 0.7 11.4 1.6 0.1 2.8 Other source 0.0 0.1 0.2 27.9 11.1 Shop 0.0 0.1 0.0 24.7 9.7 Friend/relative 0.0 0.0 0.1 2.5 1.1 School 0.0 0.0 0.0 0.7 0.3 Other 0.0 0.7 0.2 6.4 2.8 Total 99.8 98.5 99.3 98.2 98.9 Number of women 261 417 1,941 1,765 4,549 Note: Total includes 8 users of male sterilisation, 51 users of the IUCD, 49 users of the contraceptive patch, 12 users of implants, 44 users of the female condom, and 1 user of the diaphragm who are not shown separately but excludes lactational amenorrhoea method (LAM). The public sector is the primary source of injectables, supplying the vast majority of users (95 percent), with government primary health care clinics supplying 74 percent of users. More than one in two (53 percent) users of male condoms obtained their method from the public sector, with primary health care clinics the main supplier. Government health centres (23 percent) and shops (25 percent) are also an important source of male condoms, supplying about one in four users. Seventy-two percent of pill users obtained their method from the public sector, the majority (58 percent) from primary health care clinics. Not surprisingly, the public sector is also the main source of female sterilisation, with government hospitals most often providing this service (65 percent). The proportional distribution of contraceptive methods by public and private sector sources has not changed substantially over the last six years. 7.5 INFORMED CHOICE Women age 15-49 who were currently using a modern contraceptive method and who started the last episode of use within five years of the survey were asked whether they had been informed about possible side effects or problems associated with their chosen method, what to do if they experienced side effects, and other methods that they could also use. Their responses offer a measure of the quality of family planning service provision. Table 7.5 shows the results by method and source. Fifty-seven percent of users of modern contraceptives were informed about side effects or health problems associated with the method they used, 51 percent were informed about what to do if they experienced side effects, and 65 percent were told of other methods available. Women using the pill were most likely to be informed of side effects, what to do if they experienced side effects, and other methods they could use. Women who obtained their contraceptive from the private sector, typically a private doctor or a private hospital, were more likely than those who obtained their contraceptive from another source to be informed of side effects, what to do if they experienced side effects, and other methods they could use. 78 • Family Planning Table 7.5 Informed choice Among current users of modern methods age 15-49 who started the last episode of use within the five years preceding the survey, the percentage who were informed about possible side effects or problems of that method, the percentage who were informed about what to do if they experienced side effects, and the percentage who were informed about other methods they could use, by method and initial source, Namibia 2013 Among women who started last episode of modern contraceptive method within five years preceding the survey: Method/source Percentage who were informed about side effects or problems of method used Percentage who were informed about what to do if experienced side effects Percentage who were informed by a health or family planning worker of other methods that could be used Number of women Method Female sterilisation 51.1 45.3 59.1 94 Pill 61.1 55.9 68.9 328 IUD (76.7) (74.9) (84.9) 38 Injectables 55.9 49.5 63.7 1,705 Implants * * * 9 Initial source of method1 Public 56.4 50.5 65.1 1,941 Government hospital 62.1 57.9 69.9 483 Government health centre 64.8 54.9 71.4 83 Government primary health care clinic 53.7 47.7 63.0 1,353 Outreach point * * * 9 Field worker/community health care provider * * * 5 Other public * * * 8 Private 69.0 60.2 70.7 198 Private hospital 63.0 55.4 69.0 76 Private clinic * * * 17 Pharmacy * * * 23 Private doctor 78.0 67.7 74.0 81 Other private medical * * * 1 Other source * * * 10 Friend/relative * * * 2 School * * * 8 Other * * * 0 Total 56.8 50.7 64.8 2,174 Note: Table includes users of only the methods listed individually. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that an estimate is based on fewer than 25 unweighted cases and has been suppressed. 1 Source at start of current episode of use 7.6 RATES OF DISCONTINUING CONTRACEPTIVE METHODS Reproductive goals can only be realised when reliable methods of contraception methods are used consistently. Of particular concern for family planning programmes is the rate at which users discontinue contraceptive methods and the reasons for such discontinuation. Armed with this information, family planning providers are able to better advise potential users of the advantages and disadvantages of each contraceptive method, allowing women to make a more informed decision about the method that best suits their needs. The calendar section of the Woman’s Questionnaire records all segments of contraceptive use from 3-59 months prior to the survey. The month of the interview and the two months prior to the survey are ignored in order to avoid bias that may be introduced by unrecognised pregnancies. One-year contraceptive discontinuation rates based on the calendar data are presented in Table 7.6. Overall, 19 percent of episodes of contraceptive use were discontinued within 12 months of their initiation. Six percent of discontinuations occurred due to fear of side effects or health concerns. Discontinuation rates vary by method. The rate is highest for pills (9 percent), followed by injectables and male condoms (4 percent each). Family Planning • 79 Table 7.6 Twelve-month contraceptive discontinuation rates Among women age 15-49 who started an episode of contraceptive use within the five years preceding the survey, the percentage of episodes discontinued within 12 months, by reason for discontinuation and specific method, Namibia 2013 Method Method failure Desire to become pregnant Other fertility- related reasons1 Side effects/ health concerns Wanted more effective method Other method- related reasons2 Other reasons Any reason3 Switched to another method4 Number of episodes of use5 Pill 2.7 3.7 1.7 9.5 3.2 3.5 3.7 28.0 8.8 585 Injectables 0.2 2.1 1.0 9.9 0.2 2.5 3.7 19.7 3.6 2,491 Male condom 3.4 1.8 2.5 0.6 2.2 0.5 5.5 16.4 3.5 1,889 All methods 1.8 2.2 1.7 6.0 1.3 2.0 4.3 19.2 4.1 5,314 Note: Figures are based on life table calculations using information on episodes of use that began 3-62 months preceding the survey. 1 Includes infrequent sex/husband away, difficult to get pregnant/menopausal, and marital dissolution/separation 2 Includes lack of access/too far, costs too much, and inconvenient to use 3 Reasons for discontinuation are mutually exclusive and add to the total given in this column. 4 The episodes of use included in this column are a subset of the discontinued episodes included in the discontinuation rate. A woman is considered to have switched to another method if she used a different method in the month following discontinuation or if she gave “wanted a more effective method” as the reason for discontinuation and started another method within two months of discontinuation. 5 Number of episodes of use includes both episodes of use that were discontinued during the period of observation and episodes of use that were not discontinued during the period of observation. 7.7 REASONS FOR DISCONTINUING CONTRACEPTIVE METHODS Table 7.7 shows the percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason stated for the discontinuation, according to specific method. In total, 3,455 discontinuations occurred within this time period. Overall, across all contraceptive methods, the most common reason for discontinuation was side effects or health concerns (26 percent), followed by a desire to become pregnant (22 percent) and becoming pregnant while using the method (14 percent). Table 7.7 Reasons for discontinuation Percent distribution of discontinuations of contraceptive methods in the five years preceding the survey by main reason stated for discontinuation, according to specific method, Namibia 2013 Reason Pill Injection Male condom All methods Became pregnant while using 13.2 3.5 28.4 14.1 Wanted to become pregnant 29.2 20.9 20.1 22.2 Husband disapproved 1.1 2.3 7.9 4.1 Wanted a more effective method 5.0 0.8 10.9 5.3 Side effects/health concerns 23.9 43.7 3.9 25.5 Lack of access/too far 4.8 7.2 0.8 4.4 Cost too much 0.1 0.0 0.0 0.1 Inconvenient to use 5.6 2.4 1.7 2.7 Up to God/fatalistic 0.0 0.2 0.2 0.2 Difficult to get pregnant/menopausal 0.3 0.2 0.1 0.2 Infrequent sex/husband away 4.8 3.5 7.5 5.1 Marital dissolution/separation 0.9 1.4 0.8 1.1 Other 4.3 5.5 2.7 4.3 Don’t know 0.0 0.0 0.2 0.1 Missing 6.8 8.5 14.8 10.6 Total 100.0 100.0 100.0 100.0 Number of discontinuations 493 1,614 1,225 3,455 Note: Total includes 124 cases in which women reported discontinuation while using male sterilisation, IUCD, contraceptive patch, implants, female condom, lactational amenorrhoea method (LAM), rhythm, withdrawal, and other methods. There were variations in reasons for discontinuation across specific contraceptive methods. For example, among pill users, 29 percent of discontinuations occurred because women wanted to become pregnant, 24 percent were due to side effects or health concerns, and 13 percent occurred because of method failure (i.e., the woman became pregnant while using the method). Among users of injectables, side effects or health concerns were the most common reason for discontinuations (44 percent), followed by a desire to become pregnant (21 percent); method failure resulted in only 4 percent of discontinuations. Method failure was the most common reason for discontinuations among male condom users (28 percent), followed by a desire to become pregnant (20 percent); 11 percent of discontinuations were due to the need for a more effective method. 80 • Family Planning 7.8 KNOWLEDGE OF THE FERTILE PERIOD The fertile period refers to the time when a woman can become pregnant. Such knowledge is particularly critical in the use of fertility awareness methods. The 2013 NDHS included a question designed to obtain information on the respondent’s understanding of when a woman is most likely to become pregnant during the menstrual cycle. Respondents were asked, “From one menstrual period to the next, are there certain days when a woman is more likely to get pregnant if she has sexual relations?” If the reply was yes, the respondent was further asked whether that time was just before a woman’s period begins, during her period, right after her period has ended, or halfway between two periods. The results show that only 16 percent of women know that they are most fertile midway between two menstrual periods. Due to small group numbers, breakdowns by perceived fertile period are not shown separately. 7.9 NEED AND DEMAND FOR FAMILY PLANNING The proportion of women who want to stop childbearing or who want to space their next birth is a crude measure of the extent of the need for family planning, given that not all of these women are exposed to the risk of pregnancy and some may already be using contraception. This section discusses the extent of need and the potential demand for family planning services. Women who want to postpone their next birth for two or more years or who want to stop childbearing altogether but are not using a contraceptive method are said to have an unmet need for family planning. Pregnant women are considered to have an unmet need for spacing or limiting if their pregnancy was mistimed or unwanted. Similarly, amenorrhoeic women are categorised as having an unmet need if their last birth was mistimed or unwanted. Women who are currently using a family planning method are said to have a met need for family planning. Total demand for family planning services comprises those who fall in the met need and unmet need categories. Table 7.8 presents data on unmet need, met need, and total demand for family planning among all women. These indicators help to evaluate the extent to which family planning programmes in Namibia meet the demand for services. The definition of unmet need for family planning has been revised to make levels of unmet need comparable over time and across surveys. Twelve percent of all women have an unmet need for family planning (8 percent for spacing and 4 percent for limiting births). Fifty percent of women are currently using a contraceptive method (28 percent for spacing and 22 percent for limiting). More than six in ten women (62 percent) have a demand for family planning. At present, 81 percent of the potential demand for family planning is being met. Thus, if all women who said they want to space or limit their children were to use family planning methods, the contraceptive prevalence rate would increase from 50 percent to 62 percent. Unmet need for spacing is highest among women age 20-24 (12 percent), while unmet need for limiting childbearing is highest among women age 45-49 (8 percent). Unmet need is much higher in rural than urban areas (15 percent and 9 percent, respectively) and it ranges from a low of 7 percent in Erongo to a high of 18 percent in Kunene. Unmet need varies substantially by education; women with no education are most likely to have an unmet need for family planning (24 percent), while women with more than a secondary education have the lowest unmet need (7 percent). Unmet need is inversely associated with a woman’s wealth status. Eighteen percent of women in the lowest wealth quintile have an unmet need, as compared with 7 percent of those in the highest quintile. Family Planning • 81 Recalculation of unmet need among women age 15-49 using the new definition shows an increase from 9 percent in the 2006-07 to 12 percent in the 2013 NDHS survey.1 Table 7.8 Need and demand for family planning for all women Percentage of all women age 15-49 with unmet need for family planning, percentage with met need for family planning, the total demand for family planning, and the percentage of the demand for contraception that is satisfied, by background characteristics, Namibia 2013 Background characteristic Unmet need for family planning Met need for family planning (currently using) Total demand for family planning1 Percentage of demand satisfied2 Percentage of demand satisfied by modern methods3 Number of women For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Age 15-19 7.8 1.2 9.0 19.3 5.2 24.5 27.0 6.4 33.5 73.1 72.1 1,906 20-24 12.0 1.8 13.8 44.6 11.8 56.4 56.5 13.7 70.2 80.3 79.6 1,786 25-29 9.6 3.8 13.5 42.3 20.4 62.7 51.9 24.3 76.2 82.3 81.9 1,489 30-34 8.2 4.5 12.6 32.2 26.9 59.1 40.4 31.4 71.8 82.4 81.4 1,260 35-39 6.3 5.8 12.1 22.1 33.9 55.9 28.4 39.7 68.1 82.2 81.8 1,110 40-44 3.9 7.1 11.1 13.1 41.8 54.9 17.1 49.0 66.0 83.2 82.8 917 45-49 0.6 7.6 8.2 4.1 42.1 46.1 4.7 49.7 54.4 84.8 83.1 708 Residence Urban 6.3 3.1 9.4 32.3 23.2 55.5 38.6 26.3 65.0 85.5 84.8 5,190 Rural 9.8 4.8 14.6 23.0 20.2 43.2 32.8 25.0 57.8 74.7 73.9 3,986 Region Zambezi 7.1 4.2 11.3 32.8 16.9 49.8 40.0 21.1 61.1 81.5 81.1 457 Erongo 4.3 2.8 7.2 31.9 24.6 56.5 36.2 27.4 63.6 88.7 87.9 771 Hardap 7.1 7.1 14.1 18.1 31.7 49.8 25.1 38.8 63.9 77.9 77.9 304 //Karas 5.3 3.5 8.8 25.5 34.0 59.5 30.8 37.4 68.3 87.2 86.1 343 Kavango 10.8 5.5 16.3 21.0 19.9 40.8 31.7 25.4 57.1 71.5 68.8 835 Khomas 6.2 2.7 8.9 34.7 21.5 56.3 40.9 24.2 65.1 86.4 85.5 2,202 Kunene 11.2 7.1 18.3 26.1 26.1 52.2 37.4 33.2 70.5 74.0 73.8 258 Ohangwena 12.4 3.8 16.1 22.5 16.9 39.4 34.9 20.7 55.5 70.9 70.7 894 Omaheke 9.5 6.7 16.3 19.4 36.0 55.4 28.9 42.8 71.7 77.3 77.0 225 Omusati 9.2 3.3 12.5 23.3 13.9 37.2 32.6 17.1 49.7 74.9 74.6 884 Oshana 5.9 1.9 7.8 38.1 19.8 57.9 44.0 21.7 65.7 88.1 87.5 755 Oshikoto 8.4 5.3 13.7 26.7 22.6 49.3 35.2 27.9 63.0 78.3 78.3 707 Otjozondjupa 7.4 4.9 12.3 22.1 29.5 51.6 29.5 34.4 63.9 80.8 80.0 540 Education No education 14.1 10.1 24.2 12.7 21.0 33.7 26.8 31.1 57.9 58.2 56.5 419 Primary 9.2 6.0 15.2 16.5 26.3 42.8 25.7 32.3 58.0 73.8 73.1 1,798 Secondary 7.3 3.1 10.4 31.0 21.3 52.3 38.3 24.4 62.7 83.4 82.8 6,029 More than secondary 5.9 1.4 7.4 40.0 18.0 58.0 45.9 19.4 65.4 88.8 87.1 930 Wealth quintile Lowest 12.0 5.8 17.8 20.1 19.5 39.6 32.1 25.3 57.4 69.0 67.7 1,429 Second 9.1 4.2 13.3 23.9 24.8 48.7 33.0 29.0 62.0 78.5 78.2 1,625 Middle 8.6 4.1 12.7 31.4 21.5 52.9 40.1 25.6 65.6 80.6 79.9 1,795 Fourth 7.0 3.8 10.8 31.3 21.2 52.5 38.3 25.0 63.3 82.9 82.4 2,116 Highest 4.4 2.2 6.5 31.3 22.4 53.7 35.6 24.6 60.2 89.1 88.2 2,211 Total 7.8 3.9 11.7 28.3 21.9 50.2 36.1 25.8 61.9 81.1 80.4 9,176 Currently married women 9.1 8.4 17.5 23.5 32.6 56.1 32.6 41.0 73.6 76.2 75.0 3,121 Sexually active unmarried women4 10.7 3.7 14.4 54.1 23.7 77.8 64.8 27.4 92.2 84.4 84.1 1,437 Note: Numbers in this table correspond to the revised definition of unmet need described in Bradley et al., 2012. 1 Total demand is the sum of unmet need and met need. 2 Percentage of demand satisfied is met need divided by total demand. 3 Modern methods include female sterilisation, male sterilisation, pill, IUD, injectables, implants, male condom, female condom, and lactational amenorrhoea method (LAM). 4 Women who had sexual intercourse within 30 days preceding the survey 1 There was an error in the 2006-07 Namibia DHS Final Report in the percentage of women age 15-49 with an unmet need for family planning. The percentage of all women age 15-49 with an unmet need for family planning was actually 9 percent, with unmet need for spacing at 4 percent and unmet need for limiting at 5 percent. Corresponding figures for currently married women were 21 percent, 9 percent, and 12 percent, and corresponding figures for women who were not currently married were 3.2 percent, 1.7 percent, and 1.5 percent. Data on unmet need on the DHS Programme website (http://dhsprogramme.com) compare unmet need among currently married women calculated according to the new definition and the previous definition. The two percentages are very similar (20.5 percent and 20.6 percent, respectively). 82 • Family Planning 7.10 FUTURE USE OF CONTRACEPTION An important indicator of the changing demand for family planning is the extent to which nonusers plan to use contraceptive methods in the future, as this is a forecast of potential demand for services. Women age 15-49 who were not using contraceptives at the time of the survey were asked about their intention to use family planning in the future. Table 7.9 shows that 64 percent of nonusers indicated that they intend to use family planning methods in the future, while 28 percent said that they do not intend to use a method in the future. The proportion of women who intend to use a method is highest among those with one child and lowest among those with four or more children. Table 7.9 Future use of contraception Percent distribution of all women age 15-49 who are not using a contraceptive method by intention to use in the future, according to number of living children, Namibia 2013 Number of living children1 Total Intention 0 1 2 3 4+ Intends to use 63.9 70.3 67.7 60.7 54.7 64.0 Unsure 11.1 3.6 3.0 3.5 4.2 6.6 Does not intend to use 24.3 24.3 26.0 32.0 39.7 27.7 Missing 0.7 1.9 3.3 3.8 1.3 1.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number of women 1,814 893 706 430 729 4,572 1 Includes current pregnancy 7.11 EXPOSURE TO FAMILY PLANNING MESSAGES IN THE MEDIA Radio, television, and newspapers and/or magazines are the major media sources of information about family planning in Namibia. Information on the level of public exposure to a particular type of media allows policymakers to ensure the use of the most effective media for various target groups. To assess the effectiveness of such media in disseminating family planning information, women and men in the 2013 NDHS were asked whether they had heard messages about family planning on the radio or seen them on television or in newspapers/magazines during the last few months preceding the survey (Table 7.10). Overall, 39 percent of women reported that they had recently heard a family planning message on the radio, 31 percent had seen a message in newspapers or magazines, and 28 percent saw messages on television. Nearly one in two women (49 percent) had no exposure to any of the three media. Non- exposure to any of the three media sources was highest among women age 15-19, women living in rural areas and in Ohangwena, women with no education, and those in the lowest wealth quintile. In general, the pattern of exposure to family planning messages among men was similar to that among women. However, men in Hardap were most likely to have had no exposure to media messages on family planning. Family Planning • 83 Table 7.10 Exposure to family planning messages Percentage of women and men age 15-49 who heard or saw a family planning message on radio, on television, or in a newspaper or magazine in the past few months, according to background characteristics, Namibia 2013 Women Men Background characteristic Radio Television Newspaper/ magazine None of these three media sources Number of women Radio Television Newspaper/ magazine None of these three media sources Number of men Age 15-19 29.4 22.7 25.7 56.5 1,906 26.6 20.3 24.0 58.3 922 20-24 42.0 32.4 37.0 43.2 1,786 36.9 22.9 31.7 46.1 808 25-29 39.2 28.6 32.1 48.3 1,489 42.4 28.7 32.2 46.3 658 30-34 42.3 27.6 30.8 46.7 1,260 42.5 28.8 36.0 43.8 520 35-39 40.2 25.8 29.4 49.6 1,110 45.2 27.1 34.8 43.8 448 40-44 42.1 26.1 30.7 47.1 917 44.5 30.4 31.6 47.2 376 45-49 44.3 30.0 29.6 47.0 708 50.3 29.3 35.0 42.2 289 Residence Urban 45.6 40.4 43.0 36.8 5,190 43.2 37.2 40.5 40.0 2,282 Rural 30.3 10.7 15.1 64.3 3,986 32.9 10.5 18.8 59.0 1,739 Region Zambezi 38.0 18.5 17.3 55.9 457 40.3 21.9 24.3 52.3 218 Erongo 46.1 43.7 43.3 36.3 771 55.0 48.0 50.7 31.0 372 Hardap 48.6 44.8 37.9 36.2 304 21.9 14.0 8.4 71.2 152 //Karas 45.7 40.1 42.5 35.7 343 41.5 35.0 35.0 40.5 151 Kavango 43.2 17.1 18.0 52.5 835 33.7 15.9 19.1 59.5 316 Khomas 43.7 42.1 47.0 35.0 2,202 42.2 38.1 40.6 41.1 1,023 Kunene 24.2 22.0 17.5 66.6 258 40.3 23.1 22.0 56.0 104 Ohangwena 22.3 7.3 11.3 74.1 894 30.7 10.0 21.2 58.2 328 Omaheke 48.2 22.0 25.2 43.7 225 37.9 10.9 12.2 59.7 103 Omusati 23.0 7.4 14.6 72.4 884 24.5 7.2 17.2 64.7 342 Oshana 36.9 18.2 28.5 53.3 755 35.9 18.0 35.3 44.0 335 Oshikoto 36.7 16.2 25.3 51.8 707 37.4 13.6 23.8 49.9 335 Otjozondjupa 56.6 49.6 46.1 28.6 540 49.7 38.2 44.1 35.2 241 Education No education 24.5 4.7 1.5 73.9 419 26.3 8.3 5.8 71.8 310 Primary 29.2 11.0 9.5 66.3 1,798 32.0 11.3 13.7 62.1 944 Secondary 42.2 30.5 34.9 44.9 6,029 41.9 29.6 37.1 42.8 2,400 More than secondary 43.3 49.9 59.8 28.2 930 45.9 50.8 57.8 28.1 368 Wealth quintile Lowest 24.3 2.5 7.4 73.2 1,429 30.2 7.3 15.3 64.1 594 Second 30.5 7.1 14.8 65.5 1,625 32.8 10.4 18.3 59.4 769 Middle 40.1 18.7 25.0 51.9 1,795 38.0 14.4 24.1 52.5 886 Fourth 48.9 43.1 40.8 35.9 2,116 45.3 38.9 40.4 38.4 917 Highest 44.2 50.8 53.1 30.4 2,211 43.7 49.5 51.0 33.3 855 Total 15-49 39.0 27.5 30.9 48.7 9,176 38.7 25.6 31.1 48.2 4,021 7.12 CONTACT OF NONUSERS WITH FAMILY PLANNING PROVIDERS In the 2013 NDHS, women who were not using any contraceptive method were asked whether a fieldworker had talked with them about family planning in the 12 months preceding the survey. This information is especially useful for determining whether family planning outreach programmes reach nonusers. Nonusers were also asked if they had visited a health facility in the preceding 12 months for any reason and, if so, whether any staff member at the facility had spoken to them about family planning. These questions help to assess the extent of missed opportunities to inform women about contraception. The results shown in Table 7.11 indicate that 7 percent of nonusers reported discussing family planning when a fieldworker visited them. Eleven percent of nonusers visited a health facility and discussed family planning, while 37 percent visited a facility but did not discuss family planning. 84 • Family Planning Table 7.11 Contact of nonusers with family planning providers Among women age 15-49 who are not using contraception, the percentage who during the past 12 months were visited by a fieldworker who discussed family planning, the percentage who visited a health facility and discussed family planning, the percentage who visited a health facility but did not discuss family planning, and the percentage who did not discuss family planning either with a fieldworker or at a health facility, by background characteristics, Namibia 2013 Percentage of women who were visited by fieldworker who discussed family planning Percentage of women who visited a health facility in the past 12 months and who: Percentage of women who did not discuss family planning either with fieldworker or at a health facility Number of women Background characteristic Discussed family planning Did not discuss family planning Age 15-19 5.0 3.9 29.6 91.7 1,439 20-24 7.3 16.1 35.9 80.5 779 25-29 9.1 17.9 37.6 77.8 555 30-34 7.2 14.9 46.8 81.7 515 35-39 6.1 12.5 43.0 85.1 489 40-44 6.9 14.2 38.7 82.5 413 45-49 5.8 9.3 42.7 86.9 381 Residence Urban 6.1 11.0 37.1 85.4 2,308 Rural 6.9 11.4 36.8 84.7 2,264 Region Zambezi 8.2 10.2 49.7 84.2 229 Erongo 5.4 15.5 36.9 81.3 336 Hardap 4.5 7.1 14.3 89.7 153 //Karas 4.2 10.8 34.1 86.0 139 Kavango 9.5 17.3 35.0 77.9 494 Khomas 5.3 9.2 38.1 87.9 963 Kunene 8.8 8.7 18.0 86.3 123 Ohangwena 8.8 9.2 37.1 85.5 542 Omaheke 10.8 20.0 17.3 74.2 100 Omusati 1.3 8.7 45.5 90.9 555 Oshana 8.5 13.2 43.1 81.8 318 Oshikoto 7.0 11.8 41.0 84.5 358 Otjozondjupa 7.7 9.0 24.9 85.2 261 Education No education 6.8 8.7 32.7 87.5 278 Primary 6.1 8.9 34.6 87.3 1,028 Secondary 6.8 12.5 37.2 83.7 2,876 More than secondary 5.2 9.5 44.1 87.1 390 Wealth quintile Lowest 8.3 11.6 34.8 83.5 863 Second 5.2 10.9 39.5 86.6 834 Middle 8.5 14.3 37.9 81.2 845 Fourth 5.8 11.8 35.4 85.2 1,006 Highest 5.1 8.0 37.4 88.0 1,024 Total 6.5 11.2 36.9 85.0 4,572 Overall, 85 percent of nonusers did not discuss family planning with a fieldworker or a staff member at a health facility. This indicates a missed opportunity for potential users of family planning who could be targeted for family planning information and counselling. Outreach services provided by health extension workers could be practical in reaching these women. Variations in the percentages of nonusers who did not discuss family planning either with a fieldworker or at a health facility were relatively small across the different background characteristics. Infant and Child Mortality • 85 INFANT AND CHILD MORTALITY 8 eonatal, infant, and child mortality are important indicators of a country’s socioeconomic development and quality of life, as well as health status. Measures of childhood mortality also contribute to a better understanding of the progress of population and health programmes and policies and are useful for population projections. Disaggregation of mortality measures by socioeconomic and demographic characteristics helps to identify differentials in population subgroups and target high-risk groups for effective programmes. This chapter describes levels of and trends and differentials in early childhood mortality and high-risk fertility behaviour in Namibia. 8.1 BACKGROUND AND ASSESSMENT OF DATA QUALITY Childhood mortality rates presented in this chapter are defined as follows: Neonatal mortality (NN): the probability of dying within the first month of life Postneonatal mortality (PNN): the arithmetic difference between infant and neonatal mortality Infant mortality (1q0): the probability of dying between birth and the first birthday Child mortality (4q1): the probability of dying between the first and the fifth birthday Under-5 mortality (5q0): the probability of dying between birth and the fifth birthday All rates are expressed as deaths per 1,000 live births, except in the case of child mortality, which is expressed as deaths per 1,000 children surviving to their first birthday. Information on childhood mortality was obtained from the birth history section of the Woman’s Questionnaire. Respondents were first asked a series of questions about their childbearing experience. In particular, they were asked to report the number of sons and daughters living with them, the number living elsewhere, and the number who have died. For each live birth reported in the birth history, information was collected on sex, month and year of birth, survivorship status, and current age or, if the child has died, age at death. N Key Findings • Infant and under-5 mortality rates in the past five years are 39 and 54 deaths per 1,000 live births, respectively. At these mortality levels, one in every 26 Namibian children die before reaching age 1, and one in every 19 do not survive to their fifth birthday. • Data from the 2013 NDHS show that infant mortality has declined by 19 percent over the last 15 years, while under-5 mortality has declined by 18 percent over the same period. A comparison of childhood mortality rates across all NDHS surveys shows a decline between 1992 and 2013. However, this decline is more pronounced between 1992 and 2000. Since then there have not been any substantial declines. • The neonatal mortality rate in the past five years is 20 deaths per 1,000 live births, similar to the postneonatal mortality rate (19). The perinatal mortality rate is 24 per 1,000 pregnancies. • Infant mortality is more than twice as high in the lowest wealth quintile (51 per 1,000 live births) as in the highest wealth quintile (22 per 1,000 live births). A similar picture emerges for all other mortality rates. 86 • Infant and Child Mortality The accuracy of mortality estimates depends on the sampling variability of the estimates and on nonsampling errors. Sampling variability and sampling errors are discussed in detail in Appendix B. Nonsampling errors depend on the extent to which date of birth and age at death are accurately reported and recorded and the completeness with which child deaths are reported. Omission of births and deaths affects mortality estimates, displacement of birth and death dates impacts mortality trends, and misreporting of age at death may distort the age pattern of mortality. Typically, the most serious source of nonsampling errors in a survey that collects retrospective information on births and deaths is the underreporting of births and deaths of children who were dead at the time of the survey. The possible occurrence of these data problems in the 2013 NDHS is discussed with reference to the data quality tables in Appendix C. Underreporting of births and deaths is generally more severe the further back in time an event occurred. An unusual pattern in the distribution of births by calendar years is an indication of omission of children or age displacement. In the 2013 NDHS, the cutoff for asking health questions was January 2008. Table C.4 shows that the overall percentage of births for which a month and year of birth were reported is almost 100 percent for both children who have died and children who are alive. Table C.4 also shows some age displacement across this boundary for both living and dead children. The distribution of living children and the total number of children show a deficit in 2008 in relation to 2007 and 2009, as denoted by the calendar year ratios. However, this transference is proportionately higher for living children than dead children. The excess in 2007 could have resulted from interviewers knowingly recording a birth as occurring after the cutoff year to cut down on their overall workload, because live births occurring during the five years preceding the interview were the subject of a lengthy set of additional questions. The transference of children, especially deceased children, out of the five-year period preceding the survey is likely to underestimate the true level of childhood mortality for that period, but this does not appear to be the case in Namibia, where the transference is much higher for living than deceased children. Underreporting of deaths is usually assumed to be higher for deaths that occur very early in infancy. Omission of deaths or misclassification of deaths as stillbirths may also be more common among women who have had several children or in cases where a death took place in the distant past. Two indicators are used to assess the impact of omission on measures of child mortality: the percentage of deaths that occurred in the first seven days to the number that occurred in the first month; and, the percentage of neonatal deaths to infant deaths. It is hypothesised that omission will be more prevalent among those who died immediately after birth than among those who lived longer and that it will be more serious for events that took place in the distant past than for those that occurred in the more recent past. Table C.5 shows data on age at death for early infant deaths. Selective underreporting of early neonatal deaths would result in an abnormally low ratio of deaths within the first seven days of life to all neonatal deaths. Early infant deaths were not severely underreported in the 2013 NDHS, as suggested by the high ratio of deaths in the first seven days of life to all neonatal deaths (82 percent in the five years preceding the survey). Heaping of age at death on certain digits is another problem that is inherent in most retrospective surveys. Misreporting of age at death biases age pattern estimates of mortality if the net result is transference of deaths between age segments for which the rates are calculated; for example, child mortality may be overestimated relative to infant mortality if children who died in the first year of life are reported as having died at age 1 or older. In an effort to minimise misreporting of age at death, interviewers were instructed to record deaths under one month in days and deaths under two years in months. In addition, they were trained to probe deaths reported at exactly one year or 12 months to ensure that they had actually occurred at 12 months. The distribution of deaths under two years during the 20 years prior to the survey by month of death shows that there is heaping at age 12 months, with corresponding deficits in adjacent months (Table C.6). This is likely to underestimate infant mortality and overestimate child mortality. Infant and Child Mortality • 87 8.2 INFANT AND CHILD MORTALITY LEVELS AND TRENDS Table 8.1 presents neonatal, postneonatal, infant, child, and under-5 mortality rates for three five- year periods preceding the 2013 NDHS. Neonatal mortality in the most recent period is 20 deaths per 1,000 live births. This rate is similar to the postneonatal rate (19 deaths per 1,000 live births) during the same period. The infant mortality rate in the five years preceding the survey is 39 deaths per 1,000 live births, and the under-5 mortality rate is 54 deaths per 1,000 live births. This means that one in every 26 Namibian children die before reaching age 1, while one in every 19 do not survive to their fifth birthday. Neonatal mortality represents 51 percent of infant mortality. Thus, half of the deaths taking place before the first birthday occur during the first month of life. Table 8.1 Early childhood mortality rates Neonatal, postneonatal, infant, child, and under-5 mortality rates for five-year periods preceding the survey, Namibia 2013 Years preceding the survey Approximate calendar years Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) 0-4 2008-2012 20 19 39 16 54 5-9 2003-2007 17 25 42 23 64 10-14 1998-2002 25 23 48 18 66 1 Computed as the difference between the infant and neonatal mortality rates Mortality trends can be examined in two ways: by comparing mortality rates for three five-year periods preceding a single survey and by comparing mortality estimates obtained from various DHS surveys. However, comparisons between surveys should be interpreted with caution because of variations in quality of data, time references, and sample coverage. In particular, sampling errors associated with mortality estimates are large and should be taken into account when examining trends between surveys. Data from the 2013 NDHS show that neonatal mortality declined by 20 percent over the 15-year period preceding the survey, from 25 to 20 deaths per 1,000 live births. The corresponding declines in postneonatal, infant, and under-5 mortality over the 15-year period were 17 percent, 19 percent, and 18 percent. Mortality trends can also be observed by comparing data from the 2013 NDHS with data from the 1992, 2000, and 2006-07 NDHS surveys (Figure 8.1). Infant and under-5 mortality rates in the five years preceding the four surveys confirm a declining trend in mortality. Infant mortality has declined by 32 percent over the last 25 years, from 57 deaths per 1,000 live births in 1987-1991 to 39 deaths per 1,000 live births in 2008-2012. Under-5 mortality declined by 35 percent over the same period, from 83 deaths per 1,000 live births to 54 deaths per 1,000 live births. The data also show 38 percent and 24 percent declines in neonatal and postneonatal mortality, respectively. However, the data show that there has not been a significant decline in neonatal and infant mortality since 2000. Neonatal mortality remained at 20 deaths per 1,000 live births during 1995-1999 and 2008-2012. Similarly, infant mortality was 38 deaths per 1,000 live births in 1995-1999 and 39 deaths per 1,000 live births in 2008-2012. On the other hand, under-5 mortality declined from 62 to 54 deaths per 1,000 live births during the same time period. 88 • Infant and Child Mortality Figure 8.1 Trends in childhood mortality, 1987-2012 8.3 SOCIOECONOMIC DIFFERENTIALS IN EARLY CHILDHOOD MORTALITY Table 8.2 shows differentials in infant and child mortality by residence, region, mother’s education, and wealth quintile. Mortality estimates are calculated for the 10-year period before the survey so that the rates are based on a sufficient number of cases in each category to ensure statistically reliable estimates. Table 8.2 Early childhood mortality rates by socioeconomic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, by background characteristics, Namibia 2013 Background characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Residence Urban 16 19 35 20 54 Rural 22 25 46 18 64 Region Zambezi 23 30 53 (21) (73) Erongo 19 18 37 16 53 Hardap 11 18 29 (9) (38) //Karas 17 19 36 9 44 Kavango 27 35 62 38 97 Khomas 12 15 27 15 41 Kunene 25 14 39 6 45 Ohangwena 22 31 53 28 79 Omaheke 30 12 41 5 46 Omusati 11 20 30 15 45 Oshana 13 (24) (37) (10) (46) Oshikoto 27 20 47 22 68 Otjozondjupa 15 14 30 22 51 Mother’s education No education 26 30 56 22 76 Primary 20 29 50 23 71 Secondary 18 20 38 17 55 More than secondary (10) (0) (10) (14) (24) Wealth quintile Lowest 23 28 51 17 67 Second 19 26 45 24 68 Middle 19 23 41 25 66 Fourth 19 19 37 19 56 Highest 11 11 22 8 31 Note: Figures in parentheses are based on 250 to 499 children exposed to the risk of mortality. 1 Computed as the difference between the infant and neonatal mortality rates 32 25 57 38 83 20 18 38 25 62 24 22 46 24 69 20 19 39 16 54 Neonatal mortality Postneonatal mortality Infant mortality Child mortality Under-5 mortality Percent 1992 NDHS 2000 NDHS 2006-07 NDHS 2013 NDHS Infant and Child Mortality • 89 Infant and under-5 mortality are higher in rural areas than in urban areas. For example, infant mortality in rural areas is 46 deaths per 1,000 live births, as compared with 35 deaths per 1,000 live births in urban areas. Rural-urban differences are also noticeable in the case of neonatal and postneonatal mortality rates. However, child mortality is slightly lower in rural areas than in urban areas. There are wide differentials in infant and under-5 mortality by region. For example, under-5 mortality ranges from 41 deaths per 1,000 live births in Khomas to 97 deaths per 1,000 live births in Kavango. Mother’s education and household wealth also directly affect the survival of young children. For example, under-5 mortality decreases from 76 deaths per 1,000 live births among children of mothers with no education to 55 deaths among children of mothers with a secondary education. Similarly, under-5 mortality is 67 deaths per 1,000 live births among children in the poorest households, as compared with 31 deaths per 1,000 live births among children in the wealthiest households. Thus, under-5 mortality is more than twice as high in the lowest wealth quintile as in the highest quintile. A similar pattern is observed for all other mortality rates. These findings point to the potential for mortality reduction that could result from successful efforts to target the most vulnerable populations, such as the poorly educated and socioeconomically disadvantaged groups of women. 8.4 DEMOGRAPHIC DIFFERENTIALS IN EARLY CHILDHOOD MORTALITY The relationship between early childhood mortality and various demographic variables is examined in Table 8.3. With the exception of postneonatal mortality, childhood mortality is higher for male than female children. The largest difference is in the under-5 mortality rate (54 deaths per 1,000 live births among girls and 64 deaths per 1,000 live births among boys). Table 8.3 Early childhood mortality rates by demographic characteristics Neonatal, postneonatal, infant, child, and under-5 mortality rates for the 10-year period preceding the survey, by demographic characteristics, Namibia 2013 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality (PNN)1 Infant mortality (1q0) Child mortality (4q1) Under-5 mortality (5q0) Child’s sex Male 23 21 44 21 64 Female 14 23 37 18 54 Mother’s age at birth <20 19 23 42 15 56 20-29 18 20 38 20 58 30-39 19 26 45 17 62 40-49 (20) (13) (33) * * Birth order 1 19 18 37 18 55 2-3 18 22 41 17 57 4-6 17 25 42 24 65 7+ (26) (34) (59) (23) (81) Previous birth interval2 <2 years 35 38 73 24 96 2 years 18 23 41 16 56 3 years 18 15 33 10 43 4+ years 14 22 36 24 59 Birth size3 Small/very small 43 30 73 * * Average or larger 11 16 28 na na Note: Figures in parentheses are based on 250 to 499 unweighted children exposed to the risk of mortality. An asterisk indicates that an estimate is based on fewer than 250 unweighted children and has been suppressed. na = Not available 1 Computed as the difference between the infant and neonatal mortality rates 2 Excludes first-order births 3 Rates for the five-year period before the survey 90 • Infant and Child Mortality The relationship between maternal age at birth and neonatal, postneonatal, and infant mortality is U-shaped, with rates being relatively higher among children born to mothers under age 20 and over age 30 than among children born to mothers in the 20-29 age group. However, under-5 mortality increases with mother’s age at birth. There is an inverted U-shaped relationship between child mortality and mother’s age. With the exception of neonatal mortality, childhood mortality generally increases with increasing birth order. For example, under-5 mortality rises from 55 deaths per 1,000 live births among first births to 65 deaths among births of order four to six. Studies have shown that a longer birth interval seems to increase a child’s chance of survival. Data from the 2013 NDHS support this observation. For example, under-5 mortality decreases from 96 deaths per 1,000 live births among children born less than two years after a preceding sibling to 43-59 deaths per 1,000 live births among children born two years or longer after a preceding sibling. Child, infant, postneonatal, and neonatal mortality rates also generally decline as the interval between births increases. These findings point to the potential for mortality reduction that could result from successful efforts to promote birth spacing in Namibia. A child’s size at birth is an indicator of the risk of dying during infancy, particularly during the first month of life. In the 2013 NDHS, in addition to recording the actual birth weight, interviewers asked mothers whether their children born in the last five years were very small, small, average in size, large, or very large at birth. This type of subjective assessment has been shown to correlate closely with actual birth weight. Survey results indicate that newborns perceived by their mothers to be very small or small were more likely to die in their first year than those perceived as average or larger in size; the differential was especially great with respect to infant mortality. 8.5 PERINATAL MORTALITY Pregnancy losses occurring after seven completed months of gestation (stillbirths) and deaths of live births within the first seven days of life (early neonatal deaths) are defined as perinatal deaths. The distinction between a stillbirth and an early neonatal death is recognised as a fine one, often depending on observing and then remembering sometimes faint signs of life after delivery. Furthermore, the causes of stillbirths and early neonatal deaths are closely linked, and examining just one or the other can understate the true level of mortality around the time of delivery. For this reason, deaths around the time of delivery are combined to provide the perinatal mortality rate. Information on stillbirths is available for the five years preceding the survey and was collected using the calendar section of the Woman’s Questionnaire. Table 8.4 indicates that the perinatal mortality rate for the country as a whole is 24 deaths per 1,000 pregnancies of seven or more months in duration. Differentials in perinatal mortality across selected maternal background characteristics vary widely. For example, perinatal mortality is particularly high in Zambezi and Kunene (34 deaths and 32 deaths per 1,000 pregnancies, respectively) compared with 11 deaths and 12 deaths per 1,000 pregnancies in Omusati and Otjozondjupa, respectively. Perinatal mortality is higher among mothers age 30-39 than among mothers in the other age groups and slightly higher in urban than rural areas. In addition, it is highest for pregnancies with a previous pregnancy interval of 27 to 38 months. There is no consistent relationship between perinatal mortality and mother’s education or wealth quintile. Infant and Child Mortality • 91 Table 8.4 Perinatal mortality Number of stillbirths and early neonatal deaths, and the perinatal mortality rate for the five-year period preceding the survey, by background characteristics, Namibia 2013 Background characteristic Number of stillbirths1 Number of early neonatal deaths2 Perinatal mortality rate3 Number of pregnancies of 7+ months’ duration Mother’s age at birth <20 3 12 20 768 20-29 11 38 20 2,458 30-39 23 25 33 1,418 40-49 2 3 25 198 Previous pregnancy interval in months4 First pregnancy 11 22 20 1,614 <15 0 7 17 425 15-26 5 11 25 659 27-38 5 11 32 509 39+ 19 25 26 1,635 Residence Urban 21 37 25 2,367 Rural 18 39 23 2,476 Region Zambezi 3 7 34 299 Erongo 1 6 21 336 Hardap 1 2 18 174 //Karas 1 3 19 166 Kavango 5 12 30 583 Khomas 12 13 28 899 Kunene 2 4 32 181 Ohangwena 3 8 19 602 Omaheke 1 3 27 151 Omusati 2 3 11 456 Oshana 5 4 30 315 Oshikoto 3 8 29 375 Otjozondjupa 0 4 12 308 Mother’s education No education 1 6 23 299 Primary 9 20 25 1,134 Secondary 27 46 23 3,100 More than secondary 3 5 26 310 Wealth quintile Lowest 10 16 24 1,057 Second 5 18 21 1,058 Middle 11 17 28 1,008 Fourth 6 19 26 1,006 Highest 7 7 20 714 Total 39 77 24 4,843 1 Stillbirths are foetal deaths in pregnancies lasting 7 or more months. 2 Early neonatal deaths are deaths at age 0-6 days among live-born children. 3 The sum of the number of stillbirths and early neonatal deaths divided by the number of pregnancies of 7 or more months’ duration, expressed per 1,000 4 Categories correspond to birth intervals of <24 months, 24-35 months, 36-47 months, and 48+ months. 8.6 HIGH-RISK FERTILITY BEHAVIOUR Typically, infants and young children have a higher risk of dying if they are born to very young mothers or older mothers, if they are born after a short birth interval, or if their mothers have already had many children. In this analysis, mothers are classified as at risk if they are younger than age 18 or older than age 34 at the time of childbirth. A short birth interval is defined as less than 24 months, and a high- order birth is defined as occurring after three or more previous births (i.e., birth order three or higher). A child may be at an elevated risk of dying due to a combination of factors. The first column of Table 8.5 shows the percentage of births in the five years before the survey classified by various risk categories. Overall, 40 percent of births involved at least one avoidable risk factor, with about 27 percent involving a single risk factor and about 14 percent involving multiple risk factors. 92 • Infant and Child Mortality Table 8.5 High-risk fertility behaviour Percent distribution of children born in the five years preceding the survey by category of elevated risk of mortality and the risk ratio, and percent distribution of currently married women by category of risk if they were to conceive a child at the time of the survey, Namibia 2013 Births in the 5 years preceding the survey Percentage of currently married women1 Risk category Percentage of births Risk ratio Not in any high risk category 31.7 1.00 34.3a Unavoidable risk category First-order births between age 18 and 34 28.1 0.79 4.9 Single high-risk category Mother’s age <18 5.9 1.26 0.3 Mother’s age >34 4.4 0.29 11.9 Birth interval <24 months 4.6 0.98 5.4 Birth order >3 11.7 1.08 7.6 Subtotal 26.6 0.97 25.2 Multiple high-risk category Age <18 and birth interval <24 months2 0.3 * 0.3 Age >34 and birth interval <24 months 0.1 * 0.4 Age >34 and birth order >3 9.3 1.15 26.9 Age >34 and birth interval <24 months and birth order >3 1.2 2.28 3.7 Birth interval <24 months and birth order >3 2.7 1.10 4.4 Subtotal 13.6 1.24 35.6 In any avoidable high-risk category 40.2 1.06 60.8 Total 100.0 na 100.0 Number of births/women 4,804 na 3,121 Note: Risk ratio is the ratio of the proportion dead among births in a specific high-risk category to the proportion dead among births not in any high-risk category. An asterisk indicates that an estimate is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Women are assigned to risk categories according to the status they would have at the birth of a child if they were to conceive at the time of the survey: current age less than 17 years and 3 months or older than 34 years and 2 months, latest birth less than 15 months ago, or latest birth being of order 3 or higher. 2 Includes the category age <18 and birth order >3 a Includes sterilised women The second column in Table 8.5 presents risk ratios, which represent the increased risk of mortality among births in various high-risk categories relative to births not having any high-risk characteristics. Young mothers whose age at birth is less than 18 (risk ratio of 1.26) and birth order higher than three (risk ratio of 1.08) are the single factors most associated with an increased risk of under-5 mortality in Namibia. Overall, the risk ratio for births involving a single risk factor was 0.97. Multiple risk factor births were generally associated with higher risk ratios than single risk factor births, with an overall risk ratio of 1.24. The most vulnerable births are those to women older than age 34 with a birth interval of less than 24 months and a birth order higher than three. This group of children is more than twice as likely to die as children not in any high-risk category. However, only 1 percent of births fall in this category. The third column of Table 8.5 shows the distribution of currently married women by the risk category into which a birth conceived at the time of the survey would fall. The data show that 34 percent of women are not in any high-risk category, and only 5 percent are at risk of having their first birth between age 18 and age 34, which is considered to be an unavoidable risk. Sixty-one percent of currently married women have at least one avoidable risk factor, with 25 percent having a single risk factor and 36 percent having multiple risk factors. Adult and Maternal Mortality • 93 ADULT AND MATERNAL MORTALITY 9 ollowing the launch of the Safe Motherhood Initiative in 1987, attention to reproductive health has increased worldwide, as has the need for reliable countrywide estimates of maternal deaths. The estimate of maternal mortality that is most commonly used in developing countries (pregnancy- related mortality) is based only on the timing of death relative to pregnancy. Pregnancy-related deaths are any deaths among women during pregnancy or within two months following the termination of a pregnancy, including deaths from accidental or incidental causes. Discussions of pregnancy-related deaths generally include four measures. The pregnancy-related mortality ratio, which is the most common measure, is defined as the number of pregnancy-related deaths during a given time period per 100,000 live births during the same time period. The pregnancy-related mortality rate refers to the number of pregnancy-related deaths in a given time period per 1,000 woman-years of exposure during the same period. The probability of dying from a pregnancy-related cause during a woman’s reproductive life is the adult lifetime risk of pregnancy-related death. The final measure is the proportion of all deaths among women that are pregnancy related (proportion of pregnancy-related deaths). The Maternal Mortality Estimation Inter-agency Group (WHO et al., 2014) estimated that, from 1990 to 2013, the global maternal mortality ratio declined by 45 percent, from 380 deaths to 210 deaths per 100,000 live births. This translates to an average annual rate of reduction of 2.6 percent. While impressive, this is less than half of the 5.5 percent rate needed to achieve the three-quarters reduction in maternal mortality targeted for 2015 in Millennium Development Goal 5. The number of women and girls who died each year from complications of pregnancy and childbirth declined from 523,000 in 1990 to 289,000 in 2013. Almost all of these deaths (99 percent) occur in developing countries. The risks of dying during pregnancy and childbirth are increased by women’s lack of empowerment, education, and access to economic resources, as well as poor nutrition and a heavy physical workload during pregnancy. Most maternal deaths could be prevented by ensuring good-quality maternal health services, such as antenatal and postnatal care, and skilled assistance during childbirth, including emergency obstetric care. Prevention of unwanted pregnancies and provision of safe abortion services, as allowed by law, could reduce maternal deaths and injuries caused by unsafe abortions. High-quality family planning services, counselling, and information could further reduce maternal deaths and injuries. F Key Findings • Direct estimates of mortality show that the level of adult mortality is higher among men than among women (7.3 deaths and 5.2 deaths per 1,000 population, respectively). • Nineteen percent of women and 27 percent of men are likely to die between exact ages 15 and 50. Comparisons with previous NDHS surveys do not show a consistent trend in these probabilities over time. • Maternal deaths account for 9 percent of all deaths among women age 15-49. The maternal mortality rate for the 10-year period preceding the survey was 0.44 maternal deaths per 1,000 woman-years of exposure. • The maternal mortality ratio was 385 maternal deaths per 100,000 live births during the 10 years preceding the survey. The 2013 estimate of the MMR is lower than the MMR in the 2006-07 NDHS (449) but higher than in 2000 and 1992 (271 and 249, respectively). However, this difference between the 2013 NDHS and the three previous surveys is not statistically significant. 94 • Adult and Maternal Mortality This chapter includes results based on sibling history data collected in the sibling survival module (commonly referred to as the maternal mortality module) of the 2013 NDHS Woman’s Questionnaire. In addition to adult mortality rates for five-year age groups, a summary measure (35q15) is included that represents the probability of dying between exact ages 15 and 50. Also, data collected in the 1992, 2000, 2006-07, and 2013 NDHS surveys are used to examine trends in adult mortality probabilities. The term maternal mortality used in this chapter (and in previous NDHS surveys) corresponds to the term pregnancy-related mortality as defined by WHO. In keeping with this definition, the sibling survival module used in the DHS surveys measures only the timing of deaths and not the cause. The data collected in the NDHS questionnaire are based on information about deaths during the two months following a birth. 9.1 ASSESSMENT OF DATA QUALITY To obtain a sibling history, the 2013 NDHS first asked each female respondent to list all children born to her biological mother, starting with the firstborn. The respondent was then asked whether each of these siblings was still alive. For living siblings, the interviewer asked the current age of each sibling. For deceased siblings, the age at death and the number of years since death were recorded. When a respondent could not provide precise information on age at death or years since death, approximate but quantitative answers were accepted. For sisters who died at age 12 or older, three questions were asked to determine whether the death was maternity-related: “Was [NAME OF SISTER] pregnant when she died?” and, if the response was negative, “Did she die during childbirth?” and, if not, “Did she die within two months after the end of a pregnancy or childbirth?” A brief discussion of data quality is warranted here. This discussion refers to tables in Appendix C. One measure of the quality of the data collected is the completeness of information on siblings. Table C.8 in Appendix C shows that, in the 2013 NDHS, a total of 44,805 siblings were recorded in the sibling histories. The survival status was not reported for 40 siblings (0.1 percent). Among surviving siblings current age was not reported for 1,197 siblings (3 percent). For more than 87 percent of deceased siblings, both age at death (AD) and years since death (YSD) were reported. In 8 percent of cases, both AD and YSD were missing. Rather than excluding siblings with missing information from the analysis, the information on the birth order of siblings in conjunction with other information is used to impute the missing data.1 In addition, the 2013 NDHS data show that deaths among 11 percent of sisters could not be classified as maternal or non-maternal (data not shown separately). Another crude measure of data quality is the mean number of siblings, or mean sibship size (Table C.9). Sibship size is expected to decline as fertility declines over time. The data show that there has been a general decline in sibship size from the oldest to the youngest age group in line with the long-term decline in fertility observed in Namibia. The sex ratio of the enumerated siblings (the ratio of brothers to sisters multiplied by 100) is 100.5 (Table C.9), which is higher than the sex ratio of 94 that was reported in the 2011 Population and Housing Census (NSA, 2012) but closer to the internationally accepted ratio of 103- 105. 1 The imputation procedure is based on the assumption that the reported birth order of the siblings in the birth history is correct. The first step is to calculate birth dates. For each living sibling with a reported age and for each dead sibling with complete information on both age at death and year of death, the birth date is calculated. For a sibling missing these data, a birth date is imputed within the range defined by the birth dates of the bracketing siblings. In the case of living siblings, an age is calculated from the imputed birth date. In the case of dead siblings, if either age at death or year of death is reported, that information is combined with the birth date to produce missing information. If both pieces of information are missing, the age at death is imputed. This imputation is based on the distribution of the ages at death for those whose year of death is unreported but whose age at death is reported. Adult and Maternal Mortality • 95 9.2 ESTIMATES OF ADULT MORTALITY Yet another way to assess the quality of data used to estimate maternal mortality is to evaluate the plausibility and stability of overall adult mortality estimates. If the estimated rates of overall adult mortality are implausible, rates based on a subset of deaths—maternal mortality in particular—are likely to have serious problems. The direct estimation of adult mortality uses the reported ages at death and years since death of the respondents’ brothers and sisters. Mortality rates are calculated by dividing the number of deaths in each age group of women and men by the total person- years of exposure to the risk of dying in that age group during a specified period prior to the survey. To have a sufficiently large number of adult deaths to generate a robust estimate, the rates are calculated for the 10- year period preceding the survey (roughly mid-2004 to mid-2013). Nevertheless, age-specific mortality rates obtained in this manner are subject to considerable sampling variation. Table 9.1 shows age-specific mortality rates for women and men age 15-49 for the 10 years preceding the survey. Overall, the level of adult mortality is much higher among men (7.3 deaths per 1,000 population) than among women (5.2 deaths per 1,000 population). Age-specific mortality rates are higher for men than for women in most age groups, but none of the differences are statistically significant. In general, age-specific mortality rates show the expected increases with increasing age among both men and women. The confidence intervals for these rates can be found in Appendix Table B.18. Confidence intervals for many of the five-year mortality rates overlap. Table 9.2 shows a summary measure of the risk of dying between exact ages 15 and 50 (35q15). Based on the 2013 NDHS results, 19 percent of women and 27 percent of men are likely to die between age 15 and age 50. Ten-year 35q15 estimates based on data from the 1992, 2000, and 2006-07 NDHS surveys show that men and women had a higher probability of dying between exact ages 15 and 50 in 2006-07 than in 2013, with the rates for the former survey year much higher than the latter. However, data from the 1992 and 2000 surveys show that the probabilities of dying for both men and women were lower than in 2013. In the two decades between the 1992 and 2013 NDHS surveys, the probability of dying between exact ages 15 and 50 increased among both women (from 12 percent to 19 percent) and men (from 22 percent to 27 percent). Confidence intervals for the 35q15 estimates can be found in Appendix Table B.18. 9.3 ESTIMATES OF MATERNAL MORTALITY It should be kept in mind that maternal mortality is difficult to measure because large sample sizes are required to calculate accurate estimates. The maternal mortality estimates presented here are subject to large sampling errors because cost and time considerations make it impossible to draw a sample large Table 9.1 Adult mortality rates Direct estimates of female and male mortality rates for the 10 years preceding the survey, by five-year age groups, Namibia 2013 Age Deaths Exposure years Mortality rate1 FEMALE 15-19 52 28,264 1.84 20-24 82 30,457 2.70 25-29 143 28,315 5.04 30-34 197 23,790 8.30 35-39 144 17,203 8.39 40-44 84 11,350 7.37 45-49 54 7,182 7.46 15-49 756 146,562 5.19a MALE 15-19 50 27,279 1.84 20-24 96 29,577 3.26 25-29 171 28,095 6.09 30-34 212 23,906 8.87 35-39 212 17,334 12.25 40-44 152 10,735 14.12 45-49 98 6,241 15.73 15-49 992 143,166 7.33a 1 Expressed per 1,000 population a Age-adjusted rate Table 9.2 Adult mortality probabilities The probability of dying between the ages of 15 and 50 among women and men for the 10 years preceding the survey, Namibia 2013 Female Male Survey 35q151 35q151 2013 NDHS 186 267 2006-07 NDHS 294 374 2000 NDHS 155 238 1992 NDHS 115 216 1 The probability of dying between exact ages 15 and 50 expressed per 1,000 person-years of exposure 96 • Adult and Maternal Mortality enough to keep sampling errors reasonably small. Thus, caution should be exercised when interpreting maternal mortality data collected in any survey, and especially when comparing two or more previously conducted surveys. Definite conclusions should be based on the confidence intervals associated with maternal mortality data. Changes can be reported as significantly different only when confidence intervals do not overlap. When confidence intervals overlap, one cannot conclusively state that there has been any change in rates or ratios over the periods being compared. Table 9.3 presents direct estimates of maternal mortality for the 10-year period preceding the survey. The maternal mortality rate among women age 15-49 is 0.44 maternal deaths per 1,000 woman- years of exposure, a rate 15 percent lower than that reported in the 2006-07 NDHS. However, the rate is 7 percent higher than that reported in 1992 and 16 percent higher than that reported in 2000. By five-year age groups, the maternal mortality rate is highest among women age 35-39 (0.83). The confidence intervals for maternal mortality rates can be found in Appendix Table B.18. In the 2013 NDHS, maternal deaths represent 9 percent of all deaths among women age 15-49, as compared with 6 percent in 2006-07, 10 percent in 2000, and 13 percent in 1992. The percentage of female deaths that are maternal varies by age, rising from 8 percent among women age 15-19 to a peak of 13 percent among women age 20-24 and then declining to 6 percent among women age 45-49. The sharp decline in the 25-29 and 30-34 age groups is anomalous to the pattern of a gradual decline at older ages. Table 9.3 Maternal mortality Direct estimates of maternal mortality rates for the 10 years preceding the survey, by five-year age groups, Namibia 2013 Age Percentage of female deaths that are maternal Maternal deaths Exposure years Maternal mortality rate1 15-19 8.4 4 28,264 0.15 20-24 12.7 10 30,457 0.34 25-29 6.8 10 28,315 0.34 30-34 8.8 17 23,790 0.73 35-39 9.9 14 17,203 0.83 40-44 6.7 6 11,350 0.50 45-49 6.2 3 7,182 0.46 15-49 8.6 65 146,562 0.44 General fertility rate (GFR)2 115 Lifetime risk of maternal death3 0.014a Confidence Intervals 2013 NDHS maternal mortality ratio (MMR)4 385 259 511 2006-07 NDHS maternal mortality ratio (MMR)4 449 325 572 2000 NDHS maternal mortality ratio (MMR)4 271 174 367 1992 NDHS maternal mortality ratio (MMR)4 249 159 339 1 Expressed per 1,000 woman-years of exposure 2 Expressed per 1,000 women age 15-49 3 Calculated as 1-(1-MMR)TFR, where TFR represents the total fertility rate for the 10 years preceding the survey 4 Expressed per 100,000 live births; calculated as the age-adjusted maternal mortality rate multiplied by 100 and divided by the age-adjusted general fertility rate a Age-adjusted rate The maternal mortality rate can be converted to a maternal mortality ratio (expressed as deaths per 100,000 live births) by dividing the rate by the general fertility rate (GFR) of 115 that prevailed during the same time period and multiplying the result by 100,000. This procedure produces a maternal mortality ratio (MMR) of 385 deaths per 100,000 live births during the 10-year period preceding the survey (Table 9.3). In other words, for every 1,000 live births in Namibia during the 10 years preceding the 2013 NDHS, about four women died during pregnancy, during childbirth, or within two months of childbirth. The lifetime risk of maternal death (0.014) indicates that about 1 percent of women die during pregnancy, during childbirth, or within two months of childbirth. Table 9.3 also shows a comparison of maternal mortality ratios for all four NDHS surveys with their respective confidence intervals. The estimated maternal mortality ratio calculated for the 10 years preceding the survey is lower in the 2013 NDHS than in the 2006-07 NDHS (449) but higher than in 2000 and 1992 (271 and 249, respectively). However, as shown in Figure 9.1, the confidence intervals Adult and Maternal Mortality • 97 surrounding the maternal mortality ratios calculated for all four surveys overlap. Because it is still possible for a difference to be statistically significant even if the confidence intervals overlap, a statistical test of significance was conducted. The test concluded that there is no significant difference between the 2013 NDHS estimate of the MMR and all the previous survey estimates. Therefore, any change in the MMR estimates from the most recent NDHS and the three previous surveys was not large enough to be statistically significant. Figure 9.1 Maternal mortality ratios with confidence intervals for the 10 years preceding the 1992, 2000, 2006-07, and 2013 NDHS surveys (per 100,000 live births) 159 174 325 259249 271 449 385 339 367 572 511 0 100 200 300 400 500 600 700 Ten years preceding the 1992 NDHS (1983-1992) Ten years preceding the 2000 NDHS (1991-2000) Ten years preceding the 2006-07 NDHS (1997/98- 2006/07) Ten years preceding the 2013 NDHS (2004-2013) Maternal Health Care • 99 MATERNAL HEALTH CARE 10 he health care services that a woman receives during pregnancy, childbirth, and the immediate postnatal period are important for the survival and well-being of both mother and infant. The 2013 NDHS obtained information on the extent to which women in Namibia receive care during each of these stages. These results are important to those who design policies and implement programmes to improve maternal and child health care services. Pregnancy and childbirth are normal and healthy events that most women, couples, and families aspire to at some point in their lives. However, this normal, life-affirming process might carry serious life- threatening risks of death and disability. Even though maternal mortality ratios and child mortality rates worldwide have declined over the past two decades, more than 289,000 women still die each year (World Health Organization [WHO] et al., 2014), and about 7 million children do not see their fifth birthday (WHO, 2014). Yet most of these deaths could be avoided if preventive measures were taken and adequate care accessed when needed. The tragedies of maternal mortality are well documented, and children’s lives are also affected when mothers die. Maternal and child mortality are litmus tests of the status of women, their access to health care, and the adequacy of the health care system to respond to their needs. Access to emergency obstetric care is unevenly distributed. The human resources for health at the lower levels of the health care delivery system are not adequately equipped with life-saving skills to provide emergency obstetric and neonatal care services. In addition to the above-mentioned constraints, access to health services is another challenge in Namibia because of long distances to the nearest health provider and the vastness of the country. About 21 percent of the country’s residents live more than 10 km from a health facility and must travel long distances to access basic and comprehensive emergency obstetric care services (Ministry of Health and Social Services [MoHSS], 2013b). T Key Findings • Ninety-seven percent of women age 15-49 who gave birth in the five years preceding the survey received antenatal care from a skilled provider during the pregnancy for their most recent birth. Forty-three percent of women received antenatal care during their first trimester. • The percentage of pregnant women with four or more antenatal care visits declined from 70 percent in 2006-07 to 63 percent in 2013. • Thirty-six percent of women who gave birth in the five years preceding the survey received two or more tetanus toxoid injections during pregnancy, ensuring that their most recent live birth was protected against neonatal tetanus. • Eighty-seven percent of live births in the five years preceding the survey took place in a health facility, and 88 percent were delivered by a skilled provider. However, only 73 percent of births to women in the lowest wealth quintile were delivered by a skilled provider, in contrast to 98 percent of births to women in the highest quintile. • Among women who gave birth in the two years preceding the survey, 69 percent received a postnatal checkup within the first two days after birth, and 68 percent received the checkup from a skilled provider. • Twenty-eight percent of women report that getting money for treatment is a serious problem in accessing health care when they are sick; 31 percent indicate that distance to a health facility is a serious problem. 100 • Maternal Health Care Namibia is committed to reducing maternal mortality. This is evident in the multisectoral institutional structures the country has put in place, along with training of personnel in emergency obstetric and neonatal care, routine maternal death reviews, an enhanced referral system, construction of new health facilities and maternity waiting homes (and renovations of existing facilities), procurement of medical equipment and essential medicines, strengthening of adolescents’ sexual and reproductive health and rights, and improved efforts to prevent mother-to-child transmission of HIV. Other health interventions undertaken to improve maternal health include enhanced antenatal, delivery, and postnatal care services; preventive treatment of malaria during pregnancy; and tetanus toxoid immunisation. Namibia has developed a road map to expedite the achievement of maternal health targets. The Ministry of Health and Social Services is building the capacity of reproductive health service providers at all levels to ensure the availability and maintenance of essential medicines and equipment, as well as designing clinics to cater to all relevant health needs. The aim is to reduce maternal and neonatal mortality by focusing on community sensitisation and mobilisation, aided by the country’s newly created cadre of health extension workers. 10.1 ANTENATAL CARE Antenatal care from a skilled provider is important to monitor the pregnancy and reduce the risks for both mother and child during pregnancy, at delivery, and during the postnatal period. Antenatal care enables (1) screening and/or early detection of complications and prompt treatment (e.g., of sexually transmitted infections or anaemia), (2) prevention of diseases through immunisation and micronutrient supplementation, (3) birth preparedness and complication readiness, (4) health promotion and disease prevention through health messages, and (5) counselling of pregnant women (e.g., on prevention of mother-to-child transmission of HIV) and referral of mothers with complications. Collecting information on antenatal care is relevant for identifying subgroups of women who do not use such services and is useful in planning improvements in the services provided. In the 2013 NDHS, women who had given birth in the five years preceding the survey were asked whether they had received antenatal care for their last live birth. If the respondent had received antenatal care for her last birth, she was then asked a series of questions about the care she received, such as the type of provider, number of visits made, stage of pregnancy at the time of the first visit, and services and information provided during visits. For women with two or more live births during the five-year period preceding the survey, data refer to the most recent birth. Table 10.1 presents information about the type of provider from whom antenatal care services were received for the most recent birth, according to background characteristics. In the case of women who reported more than one source of prenatal services, only data for the provider with the highest qualifications are presented in the table. Ninety-seven percent of women age 15-49 who had a live birth in the five years preceding the survey received antenatal care from a skilled provider (doctor or nurse/midwife) during their last pregnancy. This figure is higher than that reported in the 2006-07 NDHS (95 percent). Seventeen percent of women received care from a doctor and 79 percent from a nurse/midwife. Three percent of women received no antenatal care, as compared with 4 percent in the 2006-07 NDHS. Due to the very high percentage of women receiving antenatal care from a skilled provider, there are only marginal overall differences by background characteristics. However, there are notable differences in receipt of skilled care from a doctor. Women in Khomas (41 percent) are much more likely than women in the other regions to receive care from a doctor. In addition, women in urban areas are more than three times as likely as those in rural areas to receive antenatal care from a doctor (26 percent versus 8 percent). Furthermore, women age 35-39, those who have 1-3 children, women with more than a secondary education, and those in the highest wealth quintile are most likely to receive ANC from a doctor. Overall, antenatal care coverage by a skilled provider is relatively lower in Omaheke (89 percent) and Otjozondjupa (92 percent) than in the other regions (95 percent and higher). Maternal Health Care • 101 Table 10.1 Antenatal care Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by antenatal care (ANC) provider during pregnancy for the most recent birth and the percentage receiving antenatal care from a skilled provider for the most recent birth, according to background characteristics, Namibia 2013 Antenatal care provider No ANC Total Percentage receiving antenatal care from a skilled provider1 Number of women Background characteristic Doctor Nurse/ midwife Community health worker Traditional birth attendant Other Missing Mother's age at birth <20 10.1 85.2 0.0 0.0 0.0 0.6 4.2 100.0 95.2 592 20-34 17.8 79.4 0.0 0.0 0.1 0.3 2.5 100.0 97.1 2,619 35-49 21.7 74.2 0.0 0.0 0.0 0.3 3.8 100.0 95.9 630 Birth order 1 19.5 77.6 0.0 0.0 0.2 0.4 2.2 100.0 97.2 1,288 2-3 18.7 78.8 0.0 0.0 0.0 0.2 2.2 100.0 97.5 1,603 4-5 13.6 81.1 0.1 0.0 0.0 0.4 4.7 100.0 94.8 605 6+ 8.0 85.7 0.0 0.0 0.2 0.1 5.9 100.0 93.8 346 Residence Urban 26.1 70.6 0.0 0.0 0.1 0.4 2.8 100.0 96.7 1,970 Rural 7.9 88.7 0.0 0.0 0.0 0.3 3.2 100.0 96.5 1,871 Region Zambezi 5.2 91.9 0.2 0.0 0.0 0.0 2.7 100.0 97.1 239 Erongo 20.7 77.9 0.0 0.0 0.0 0.5 0.9 100.0 98.6 285 Hardap 12.5 84.3 0.0 0.0 0.0 0.0 3.2 100.0 96.8 133 //Karas 21.8 75.3 0.0 0.0 0.0 0.4 2.5 100.0 97.1 136 Kavango 3.6 92.7 0.0 0.0 0.0 0.0 3.7 100.0 96.3 448 Khomas 41.0 54.7 0.0 0.0 0.3 0.5 3.5 100.0 95.7 771 Kunene 8.4 86.8 0.0 0.1 0.0 0.3 4.5 100.0 95.2 133 Ohangwena 8.5 89.6 0.0 0.0 0.0 0.3 1.6 100.0 98.1 440 Omaheke 16.3 72.6 0.0 0.0 0.5 0.2 10.4 100.0 88.8 107 Omusati 5.4 93.9 0.0 0.0 0.0 0.0 0.8 100.0 99.2 350 Oshana 17.3 81.4 0.0 0.0 0.0 0.8 0.6 100.0 98.7 261 Oshikoto 17.4 80.0 0.0 0.0 0.0 0.0 2.6 100.0 97.4 290 Otjozondjupa 12.4 79.3 0.0 0.0 0.0 0.9 7.4 100.0 91.7 248 Education No education 5.4 82.2 0.0 0.0 0.3 0.5 11.6 100.0 87.7 218 Primary 8.0 87.2 0.0 0.0 0.0 0.3 4.6 100.0 95.2 836 Secondary 16.1 81.7 0.0 0.0 0.0 0.3 1.9 100.0 97.8 2,517 More than secondary 65.9 31.5 0.0 0.0 0.9 0.9 0.8 100.0 97.4 271 Wealth quintile Lowest 5.7 89.8 0.0 0.0 0.1 0.1 4.3 100.0 95.5 756 Second 7.5 88.4 0.0 0.0 0.0 0.3 3.7 100.0 95.9 819 Middle 10.4 87.0 0.1 0.0 0.0 0.2 2.3 100.0 97.5 807 Fourth 20.0 77.6 0.0 0.0 0.0 0.0 2.4 100.0 97.6 846 Highest 49.5 47.1 0.0 0.0 0.4 1.1 2.0 100.0 96.6 614 Total 17.2 79.4 0.0 0.0 0.1 0.3 3.0 100.0 96.6 3,842 Note: If more than one source of ANC was mentioned, only the provider with the highest qualifications is considered in this tabulation. 1 Skilled provider includes doctor, nurse, and midwife. 10.2 NUMBER AND TIMING OF ANTENATAL CARE VISITS Antenatal care is more effective in preventing adverse pregnancy outcomes when it is sought early in the pregnancy and continued through to delivery. The goal-directed antenatal care strategy implemented in Namibia is designed to address the prevention, early detection, and management of conditions that affect pregnancy outcomes for both the mother and the newborn. WHO recommends that a woman without complications have at least four comprehensive antenatal care visits. WHO further recommends that the first prenatal visit occur within the initial 12 weeks of the pregnancy and the second visit between weeks 12 and 18, followed by visits every four weeks until week 28 and every 1-2 weeks thereafter. The government of Namibia recommends a slightly different schedule. The first visit is recommended at less than 16 weeks, the second between weeks 20 and 24, the third between weeks 28 and 32, and the fourth at 36 weeks (MoHSS, 2013c). Each of these visits should consist of a well-defined set of activities related to screening for conditions likely to increase adverse outcomes, provision of therapeutic interventions known to be beneficial, education of pregnant women about planning for a safe birth, and provision of information on emergencies during pregnancy and how to deal with them. Women with complications, special needs, or conditions beyond the scope of basic care will require additional visits. 102 • Maternal Health Care In the 2013 NDHS, respondents were asked how many antenatal care visits they made during the pregnancy for their last birth in the five years preceding the survey and how many months pregnant they were at the time of the first visit. Table 10.2 shows that 63 percent of women with a live birth in the five years preceding the survey had four or more antenatal care visits, 10 percent had two to three visits, and 1 percent had one visit only. Urban women were more likely to have had at least four visits (64 percent) than rural women (61 percent). The percentage of pregnant women with four or more antenatal care visits has declined from 70 percent in the 2006-07 NDHS survey. Table 10.2 also shows that 43 percent of women had their first visit before their fourth month of pregnancy, as recommended. The median duration of pregnancy at the first visit was 4.2 months, down from 4.7 months in the 2006-07 NDHS. 10.3 COMPONENTS OF ANTENATAL CARE The content of antenatal care is an essential component of the quality of services. Apart from receiving basic care, every pregnant woman should be monitored for complications. Ensuring that pregnant women receive information and undergo screening for complications should be a routine part of all antenatal care visits. To assess antenatal care services, respondents were asked whether they had been advised of complications or received certain screening tests during at least one of their antenatal care visits. Table 10.3 presents information on the percentages of women who took iron supplements, took medicine for intestinal parasites, were informed of the signs of pregnancy complications, and received selected routine services during antenatal care visits for their most recent birth in the past five years. Overall, 88 percent of women took iron tablets during the pregnancy of their last birth. Variations by background characteristics are generally minor. As a component of antenatal care, administration of medicine to treat intestinal worms is much less common than administration of iron supplements. Overall, only 7 percent of women took medicine to treat intestinal worms during their last pregnancy. Mothers are most likely to take medicines for intestinal parasites for births of order 2-3. By region, intake of medicines for intestinal parasites ranged from 1 percent in Omusati to17 percent in Kavango. Women with a primary education and those in the lowest wealth quintile (11 percent each) were more likely than their peers to have taken medicine for intestinal parasites. Table 10.2 Number of antenatal care visits and timing of first visit Percent distribution of women age 15-49 who had a live birth in the five years preceding the survey by number of antenatal care (ANC) visits for the most recent live birth and by the timing of the first visit, and among women with ANC, median months pregnant at first visit, according to residence, Namibia 2013 Residence Total Number and timing of ANC visits Urban Rural Number of ANC visits None 3.1 3.2 3.2 1 0.5 1.3 0.9 2-3 9.0 11.5 10.2 4+ 63.9 61.1 62.5 Don’t know/missing 23.6 22.9 23.2 Total 100.0 100.0 100.0 Number of months pregnant at time of first ANC visit No antenatal care 3.1 3.2 3.2 <4 43.9 41.1 42.5 4-5 36.8 40.0 38.4 6-7 13.8 13.6 13.7 8+ 1.7 1.3 1.5 Don’t know/missing 0.7 0.8 0.7 Total 100.0 100.0 100.0 Number of women 1,970 1,871 3,842 Median months pregnant at first visit (for those with ANC) 4.2 4.3 4.2 Number of women with ANC 1,909 1,811 3,721 Maternal Health Care • 103 Table 10.3 Components of antenatal care Among women age 15-49 with a live birth in the five years preceding the survey, the percentage who took iron tablets and drugs for intestinal parasites during the pregnancy of the most recent birth, and among women receiving antenatal care (ANC) for the most recent live birth in the five years preceding the survey, the percentage receiving specific antenatal services, according to background characteristics, Namibia 2013 Among women with a live birth in the past five years, the percentage who during the pregnancy of their last birth: Among women who received antenatal care for their most recent birth in the past five years, the percentage with selected services Background characteristic Took iron tablets Took intestinal parasite drugs Number of women with a live birth in the past five years Informed of signs of pregnancy complications Blood pressure measured Urine sample taken Blood sample taken Number of women with ANC for their most recent birth Mother’s age at birth <20 88.2 6.8 592 71.9 94.1 91.7 98.4 564 20-34 87.5 6.8 2,619 73.9 97.8 96.4 98.6 2,551 35-49 86.8 6.9 630 72.6 98.3 97.4 98.8 606 Birth order 1 88.5 6.6 1,288 73.6 96.0 94.7 98.4 1,254 2-3 87.6 7.5 1,603 76.1 97.9 96.3 98.5 1,565 4-5 85.8 5.1 605 68.3 99.1 97.0 98.7 576 6+ 86.2 8.1 346 68.1 96.6 96.3 99.2 325 Residence Urban 86.6 6.1 1,970 74.9 98.1 97.8 98.8 1,909 Rural 88.4 7.6 1,871 71.7 96.5 93.8 98.4 1,811 Region Zambezi 89.0 5.6 239 84.9 94.0 94.3 98.3 232 Erongo 90.2 5.1 285 79.6 99.4 98.7 99.4 281 Hardap 90.9 7.0 133 73.5 99.6 100.0 100.0 129 //Karas 88.8 7.3 136 68.5 99.7 96.7 98.1 132 Kavango 94.4 17.3 448 84.3 90.7 92.8 97.3 432 Khomas 79.5 5.4 771 71.7 97.7 98.6 98.2 740 Kunene 92.4 3.7 133 74.9 99.4 98.2 98.3 127 Ohangwena 90.6 5.7 440 53.9 98.6 92.3 100.0 433 Omaheke 89.6 6.3 107 55.0 98.6 99.0 99.9 96 Omusati 77.2 1.1 350 88.1 98.1 92.8 97.7 347 Oshana 90.9 8.3 261 73.1 98.9 94.8 99.2 259 Oshikoto 94.5 5.8 290 67.2 97.8 96.0 98.1 283 Otjozondjupa 86.4 7.4 248 70.7 99.1 98.2 99.1 229 Education No education 80.4 5.0 218 67.4 96.2 94.8 96.1 192 Primary 86.1 10.6 836 69.4 95.9 94.4 98.4 795 Secondary 89.0 5.7 2,517 74.5 97.7 96.4 98.9 2,467 More than secondary 83.9 7.0 271 78.9 98.3 95.8 98.1 266 Wealth quintile Lowest 88.4 10.9 756 70.5 94.9 92.5 98.1 723 Second 85.7 6.4 819 71.9 97.2 95.4 98.9 788 Middle 88.4 6.6 807 75.5 98.2 95.9 98.3 788 Fourth 88.7 4.6 846 72.2 97.7 98.1 98.5 826 Highest 86.0 5.8 614 77.4 98.6 97.5 99.2 596 Total 87.5 6.9 3,842 73.4 97.3 95.9 98.6 3,721 Seventy-three percent of women who received antenatal care for their most recent live birth in the five years preceding the survey were informed of the signs of pregnancy complications. Women in Omusati (88 percent) were most likely to receive information and women in Ohangwena least likely (54 percent). Education and wealth have a positive impact on quality of care. The percentage of women informed of signs of pregnancy complications rises from 67 percent among those with no education to 79 percent among those with more than a secondary education. Similarly, 71 percent of women in the poorest households are informed of signs of pregnancy complications, as compared with 77 percent of women in the wealthiest households. Overall, 97 percent of women who received antenatal care had their blood pressure measured, 96 percent had a urine sample taken, and 99 percent had a blood sample taken. Differences by background characteristics are small due to the large percentages of women receiving each of these services. 104 • Maternal Health Care 10.4 TETANUS TOXOID Tetanus toxoid injections are given during pregnancy to prevent neonatal tetanus, a leading cause of early infant death in many developing countries that is often due to poor hygiene during delivery. For full protection of her newborn baby, a pregnant woman should receive at least two injections of the vaccine during pregnancy. If a woman has been vaccinated during a previous pregnancy, however, she may require only one or no doses for the current pregnancy. Five doses are considered to provide lifetime protection. Table 10.4 presents the percentage of women age 15-49 with a birth in the five years preceding the survey whose last birth was protected against neonatal tetanus. Thirty-six percent of women received two or more tetanus toxoid injections during the pregnancy for their last live birth. This represents a small increase from the figure reported in the 2006-07 NDHS (33 percent). By region, Zambezi has the highest proportion of women who received two or more tetanus toxoid injections during their last pregnancy (51 percent), while Ohangwena and Erongo have the lowest proportion (24 percent each). The percentage of women who received two or more tetanus toxoid injections during their last pregnancy declines with increasing education, from 41 percent among those with no education to 19 percent among those with more than a secondary education. A similar pattern is seen in the case of wealth quintile, but with smaller differences. Overall, 66 percent of women reported that their last births were protected against neonatal tetanus. Differences by background characteristics follow patterns similar to those observed among women who received two or more tetanus toxoid injections during their last pregnancy. The proportion of births protected against neonatal tetanus has increased since 2006-07, when 57 percent of births were protected. 10.5 PLACE OF DELIVERY Increasing the proportion of women who deliver in health facilities is an important factor in reducing health risks to the mother and the newborn. Proper medical attention and hygienic conditions during delivery can reduce the risks of complications and infections. Table 10.5 presents the percent distribution of live births in the five years preceding the survey by place of delivery, according to background characteristics. Table 10.4 Tetanus toxoid injections Among mothers age 15-49 with a live birth in the five years preceding the survey, the percentage receiving two or more tetanus toxoid injections during the pregnancy for the last live birth and the percentage whose last live birth was protected against neonatal tetanus, according to background characteristics, Namibia 2013 Background characteristic Percentage receiving two or more injections during last pregnancy Percentage whose last birth was protected against neonatal tetanus1 Number of mothers Mother’s age at birth <20 47.5 70.2 592 20-34 35.3 65.9 2,619 35-49 29.0 61.7 630 Birth order 1 42.2 68.1 1,288 2-3 34.4 65.2 1,603 4-5 29.6 64.7 605 6+ 33.1 62.7 346 Residence Urban 35.4 65.5 1,970 Rural 36.9 66.3 1,871 Region Zambezi 50.7 83.4 239 Erongo 24.4 57.5 285 Hardap 45.9 80.7 133 //Karas 37.7 77.6 136 Kavango 44.7 61.2 448 Khomas 38.1 62.2 771 Kunene 38.3 77.0 133 Ohangwena 24.1 60.3 440 Omaheke 43.9 74.1 107 Omusati 34.2 64.0 350 Oshana 27.8 57.1 261 Oshikoto 33.7 69.8 290 Otjozondjupa 39.1 71.8 248 Education No education 41.1 61.2 218 Primary 38.8 63.8 836 Secondary 36.7 68.9 2,517 More than secondary 19.0 48.4 271 Wealth quintile Lowest 39.6 66.4 756 Second 38.2 64.4 819 Middle 39.0 70.9 807 Fourth 34.3 70.0 846 Highest 28.1 55.0 614 Total 36.1 65.9 3,842 1 Includes mothers with two injections during the pregnancy of her last birth, or two or more injections (the last within 3 years of the last live birth), or three or more injections (the last within 5 years of the last birth), or four or more injections (the last within 10 years of the last live birth), or five or more injections at any time prior to the last birth. Maternal Health Care • 105 Table 10.5 Place of delivery Percent distribution of live births in the five years preceding the survey by place of delivery and percentage delivered in a health facility, according to background characteristics, Namibia 2013 Health facility Home Other Missing Total Percentage delivered in a health facility Number of births Background characteristic Public sector Private sector Mother’s age at birth <20 85.6 1.3 12.0 0.2 0.9 100.0 86.9 765 20-34 83.5 5.5 10.2 0.5 0.3 100.0 89.0 3,317 35-49 72.5 7.7 19.0 0.3 0.5 100.0 80.2 722 Birth order 1 87.9 5.4 5.6 0.2 0.8 100.0 93.3 1,647 2-3 82.6 7.0 9.7 0.6 0.1 100.0 89.7 1,962 4-5 79.4 2.7 17.4 0.3 0.2 100.0 82.1 755 6+ 63.4 0.3 34.9 0.6 0.8 100.0 63.7 440 Antenatal care visits1 None 49.3 2.8 42.9 0.7 4.3 100.0 52.1 121 1-3 75.4 1.5 22.2 1.0 0.0 100.0 76.8 426 4+ 84.3 7.1 8.2 0.3 0.1 100.0 91.4 2,402 Don’t know/missing 89.5 3.4 6.7 0.4 0.0 100.0 92.9 892 Residence Urban 85.5 9.2 4.2 0.5 0.6 100.0 94.7 2,347 Rural 79.0 1.3 19.0 0.4 0.2 100.0 80.4 2,457 Region Zambezi 84.8 0.4 14.1 0.0 0.7 100.0 85.2 297 Erongo 85.4 12.2 1.3 0.5 0.5 100.0 97.6 334 Hardap 88.6 5.4 5.0 1.0 0.0 100.0 94.0 173 //Karas 84.8 6.9 7.9 0.0 0.4 100.0 91.8 165 Kavango 71.0 1.9 26.6 0.2 0.4 100.0 72.8 577 Khomas 81.3 13.9 3.2 0.6 0.9 100.0 95.2 887 Kunene 71.0 1.3 25.8 1.2 0.6 100.0 72.4 179 Ohangwena 85.1 0.8 13.7 0.2 0.2 100.0 85.9 598 Omaheke 73.9 1.7 23.8 0.4 0.1 100.0 75.6 149 Omusati 84.6 1.3 13.8 0.3 0.0 100.0 85.8 454 Oshana 90.8 3.7 5.5 0.0 0.0 100.0 94.5 310 Oshikoto 85.5 4.2 9.5 0.8 0.0 100.0 89.8 373 Otjozondjupa 83.2 2.8 12.7 0.7 0.6 100.0 86.0 308 Mother’s education No education 58.0 0.0 40.0 1.3 0.7 100.0 58.0 298 Primary 73.6 0.2 25.2 0.4 0.6 100.0 73.8 1,125 Secondary 89.4 4.7 5.3 0.4 0.3 100.0 94.0 3,073 More than secondary 65.2 33.3 0.0 0.6 0.8 100.0 98.5 307 Wealth quintile Lowest 70.6 0.6 28.3 0.3 0.2 100.0 71.2 1,047 Second 86.5 0.6 11.8 0.7 0.5 100.0 87.0 1,053 Middle 88.9 0.2 9.9 0.3 0.6 100.0 89.1 997 Fourth 92.8 2.8 4.0 0.4 0.1 100.0 95.5 1,000 Highest 68.5 29.2 1.2 0.5 0.7 100.0 97.7 707 Total 82.2 5.2 11.8 0.4 0.4 100.0 87.4 4,804 1 Includes only the most recent birth in the 5 years preceding the survey The 2013 NDHS data show that 87 percent of births occurred in health facilities, as compared with 81 percent in the 2006-07 NDHS. Eighty-two percent of births took place in public health facilities and 5 percent in private facilities. Twelve percent of live births in the five years preceding the survey occurred at home, compared with 19 percent in 2006-07. Women age 20-34 are slightly more likely to deliver in a health facility (89 percent) than women less than age 20 (87 percent) or age 35-49 (80 percent). There is a strong relationship between receipt of antenatal care and place of delivery. Only 52 percent of live births among women who received no antenatal care took place in a health facility, as compared with 91 percent among women with four or more antenatal care visits. Place of delivery differs greatly by residence; 95 percent of births in urban areas were delivered in a health facility, compared with 80 percent of births in rural areas. The percentage of births that occurred in 106 • Maternal Health Care a health facility was highest in Erongo and lowest in Kunene (98 percent versus 72 percent). Home deliveries are most common in Kavango (27 percent) and least common in Erongo (1 percent). Education and household wealth correlate strongly with place of delivery. Births to mothers with more than a secondary education are much more likely to take place in a health facility than births to mothers with no education (99 percent versus 58 percent). Likewise, births to women in the highest wealth quintile are most likely to take place in a health facility, and births to women in the lowest wealth quintile are least likely (98 percent and 71 percent, respectively). Women who delivered at home were asked why they chose not to deliver in a health facility (Table 10.6). The vast majority of women (72 percent) who delivered at home reported that they did so because a health facility was too far away or they had no transportation to the facility. Six percent of women did not think it was necessary to deliver in a health facility, 5 percent stated that facility deliveries cost too much, 2 percent said that their husband or family did not allow them to go to a facility, and 1 percent said that they did not trust the facility or believed that it offered poor quality service. Rural women were much more likely than urban women to cite distance/lack of transportation and cost as reasons for not delivering in a facility. Urban women, however, were more likely than rural women to state that facility deliveries are not necessary and that their husband or family did not allow them to go to a facility to deliver. Overall, the percentage of women who mentioned distance or lack of transportation as a reason for not delivering in a health facility decreases with increasing education and household wealth. Table 10.6 Reasons for not delivering in a health facility Among last live births delivered at home, percentage whose mothers cite specific reasons for not delivering in a facility, according to background characteristics, Namibia 2013 Background characteristic Cost too much Facility not open Too far/ no transpor- tation Don’t trust facility/ poor quality service Husband/ family did not allow Not necessary Not customary Other Total number of births Residence Urban 3.9 0.0 60.0 0.6 5.1 11.9 0.0 16.4 74 Rural 5.5 0.4 74.5 0.9 0.9 4.8 0.7 16.9 330 Mother’s education No education 6.4 0.6 75.0 2.2 2.5 13.5 1.6 7.2 82 Primary 4.8 0.5 73.1 0.7 1.1 5.1 0.4 16.3 198 Secondary 5.0 0.0 67.6 0.4 1.9 2.9 0.0 24.2 124 Wealth quintile Lowest 6.8 0.6 73.7 0.4 1.9 4.9 0.9 16.7 198 Second 2.9 0.0 75.4 1.5 0.3 7.9 0.5 14.2 91 Middle 6.2 0.3 66.2 0.6 3.3 5.8 0.0 16.2 78 Fourth (0.8) (0.0) (62.2) (3.1) (0.0) (10.4) (0.0) (25.8) 31 Highest * * * * * * * * 6 Total 5.2 0.4 71.8 0.9 1.6 6.1 0.5 16.8 404 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. 10.6 ASSISTANCE DURING DELIVERY Obstetric care from a skilled provider (doctor or nurse/midwife) during delivery is recognised as a critical element in reducing maternal and neonatal mortality. Births taking place at home are usually more likely to be delivered without assistance from a skilled provider, whereas births delivered at a health facility are more likely to be delivered by a trained health professional. Table 10.7 shows the percent distribution of live births in the five years preceding the survey by the person providing assistance at delivery and the percentage of births delivered via caesarean section (C-section), according to background characteristics. Maternal Health Care • 107 Table 10.7 Assistance during delivery Percent distribution of live births in the five years preceding the survey by person providing assistance during delivery, percentage of births assisted by a skilled provider and the percentage delivered by caesarean-section, according to background characteristics, Namibia 2013 Person providing assistance during delivery Percentage delivered by a skilled provider1 Percentage delivered by C-section Number of births Background characteristic Doctor Nurse/ midwife Traditional birth attendant Relative/ other No one Don’t know/ missing Total Mother’s age at birth <20 12.9 74.5 3.2 8.2 0.2 1.1 100.0 87.3 9.8 765 20-34 20.2 69.7 4.0 5.0 0.8 0.3 100.0 89.9 15.4 3,317 35-49 22.4 58.7 7.3 9.4 1.7 0.5 100.0 81.1 14.9 722 Birth order 1 22.8 70.9 1.6 3.6 0.2 0.9 100.0 93.7 18.6 1,647 2-3 20.8 69.7 3.3 5.5 0.8 0.1 100.0 90.4 15.0 1,962 4-5 14.5 69.1 7.9 7.1 1.3 0.2 100.0 83.6 9.9 755 6+ 8.5 56.8 13.6 17.2 3.1 0.8 100.0 65.4 4.4 440 Antenatal care visits2 None 10.3 42.2 13.4 23.4 6.4 4.3 100.0 52.5 13.9 121 1-3 13.5 64.6 12.2 7.4 2.3 0.0 100.0 78.2 7.7 426 4+ 23.7 68.4 3.0 4.3 0.5 0.1 100.0 92.1 16.8 2,402 Don’t know/missing 17.2 76.6 1.5 4.5 0.2 0.0 100.0 93.8 15.8 892 Place of delivery Health facility 22.1 77.6 0.1 0.2 0.0 0.0 100.0 99.7 16.5 4,196 Elsewhere 0.6 8.2 35.4 48.9 6.7 0.2 100.0 8.8 0.0 588 Residence Urban 29.2 65.7 1.5 2.7 0.3 0.6 100.0 94.9 20.7 2,347 Rural 9.9 71.8 7.1 9.5 1.4 0.3 100.0 81.7 8.5 2,457 Region Zambezi 6.3 79.8 5.3 7.0 0.9 0.7 100.0 86.1 8.3 297 Erongo 28.0 69.9 0.4 1.1 0.0 0.5 100.0 97.9 19.3 334 Hardap 27.4 67.9 1.2 3.0 0.5 0.0 100.0 95.3 24.0 173 //Karas 28.1 65.3 1.2 4.9 0.2 0.4 100.0 93.3 18.8 165 Kavango 8.8 66.2 13.4 9.2 2.2 0.2 100.0 75.0 6.1 577 Khomas 39.4 56.8 0.9 1.9 0.0 0.9 100.0 96.2 26.2 887 Kunene 13.2 60.8 11.4 13.9 0.2 0.6 100.0 74.0 9.3 179 Ohangwena 7.8 78.1 6.8 6.4 0.7 0.2 100.0 85.9 8.7 598 Omaheke 16.8 59.3 4.6 16.8 2.2 0.1 100.0 76.2 9.3 149 Omusati 9.5 77.5 3.3 8.6 0.5 0.6 100.0 87.0 10.4 454 Oshana 24.7 70.1 1.3 3.9 0.0 0.0 100.0 94.8 13.1 310 Oshikoto 15.5 74.2 2.2 6.7 1.4 0.0 100.0 89.7 10.3 373 Otjozondjupa 16.3 69.8 2.7 7.8 2.8 0.6 100.0 86.1 18.3 308 Mother’s education No education 7.8 51.7 11.0 25.9 3.0 0.7 100.0 59.4 5.9 298 Primary 10.2 65.3 10.2 11.4 2.1 0.8 100.0 75.4 6.2 1,125 Secondary 19.6 75.0 2.0 2.9 0.3 0.2 100.0 94.5 15.6 3,073 More than secondary 62.1 37.1 0.0 0.0 0.0 0.8 100.0 99.2 41.2 307 Wealth quintile Lowest 6.2 66.5 11.3 13.5 2.2 0.3 100.0 72.7 5.4 1,047 Second 12.2 76.0 4.5 5.9 0.9 0.4 100.0 88.3 9.6 1,053 Middle 15.6 74.1 3.7 5.3 0.5 0.8 100.0 89.7 13.2 997 Fourth 22.0 73.6 0.6 3.3 0.3 0.1 100.0 95.6 16.5 1,000 Highest 51.0 47.3 0.2 0.8 0.0 0.7 100.0 98.3 34.0 707 Total 19.3 68.8 4.4 6.2 0.8 0.4 100.0 88.2 14.4 4,804 Note: Total includes 13 women with missing information on place of delivery. If the respondent mentioned more than one person attending during delivery, only the most qualified person is considered in this tabulation. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Skilled provider includes doctor, nurse, or midwife. 2 Includes only the most recent birth in the five years preceding the survey Eighty-eight percent of live births in the five years preceding the survey were delivered by a skilled provider, with 19 percent of deliveries assisted by a doctor and 69 percent by a nurse/midwife. Four percent of deliveries were assisted by a traditional birth attendant and 6 percent by relatives or others. The percentage of live births delivered by a skilled provider has increased from the figure reported in the 2006- 07 NDHS (81 percent). The percentage of live births delivered by a skilled provider does not differ greatly by mother’s age at birth. In contrast, large variations occur by birth order, number of antenatal care visits, place of delivery, residence, region, education, and wealth quintile. Assistance during delivery from a skilled provider decreases from 94 percent for first-order births to 65 percent for births of order six and higher. 108 • Maternal Health Care Births to mothers with four or more antenatal care visits (92 percent) are much more likely than births to mothers with fewer visits (78 percent) or no antenatal care (53 percent) to be delivered by a skilled provider. Almost all births taking place in a health facility are delivered by a skilled provider, as compared with 9 percent of births occurring elsewhere. Among births occurring outside a health facility, 35 percent are assisted by a traditional birth attendant and 49 percent by relatives or others. In urban areas, 95 percent of births are assisted by a skilled provider, as compared with 82 percent in rural areas. The percentage of births delivered by skilled providers ranges from 74 percent in Kunene to 98 percent in Erongo. Kavango has the highest percentage of deliveries by traditional birth attendants (13 percent) and Erongo the lowest (less than 1 percent). Mother’s education is strongly related to type of assistance at delivery. Births to women with a secondary and more than a secondary education (95 percent and 99 percent, respectively) are much more likely to receive assistance from a skilled provider than births to women with no education (59 percent) or those with a primary education (75 percent). Eleven percent of births to women with no education and 10 percent of births to women with a primary education are assisted by a traditional birth attendant, as compared with 2 percent or less of births to women with a secondary or higher education. In addition, 26 percent of births to women with no education are assisted by a relative or friend, compared with 3 percent or less of births to women with a secondary or more than a secondary education. As with education, wealth quintile is strongly associated with type of assistance at delivery. Births to women in the highest wealth quintile are more likely to be assisted by a skilled provider (98 percent) than births to women in the lowest wealth quintile (73 percent). Furthermore, births to women in the highest wealth quintile are more than eight times as likely as births to women in the lowest quintile to be assisted by a doctor (51 percent and 6 percent, respectively). Overall, 14 percent of births are delivered via caesarean section, a figure only 1 percent higher than that reported in the 2006-07 NDHS survey. C-sections are most common among first births (19 percent), births in urban areas (21 percent), births in Khomas (26 percent), births to women with more than a secondary education (41 percent), and births to women in the highest wealth quintile (34 percent). 10.7 POSTNATAL CARE Postnatal care refers to the care and follow-up given to a mother and her newborn immediately following delivery, during the postpartum period (the period beginning immediately after birth and extending up to six weeks). This is the period after birth in which the mother’s body, including hormone levels and uterus size, returns to pre-pregnancy levels. In 2013, the Ministry of Health and Social Services introduced a revised postnatal visit plan designed to improve the health and survival of the mother and the baby. Lack of care during this period may result in death or disability as well as missed opportunities to promote healthy behaviours affecting women, newborns, and children. Both the woman and her newborn are at the highest risk of death during the postpartum period. Many countries in Africa, including Namibia, have adopted the 1998 WHO model of care, which recommends postnatal care within six hours as well as three to six days, six weeks, and six months after birth (WHO, 2014). 10.7.1 Postnatal Checkup for the Mother A large proportion of maternal and neonatal deaths occur during the first 48 hours after delivery. Thus, prompt postnatal care for both the mother and the child is important to treat any complications arising from the delivery, as well as to provide the mother with important information on how to care for herself and her child. Safe motherhood programmes recommend that all women receive a check of their health within two days after delivery. Women who deliver at home should visit a health facility for postnatal care services within 24 hours, and subsequent visits (including those by women who deliver in a Maternal Health Care • 109 health facility) should be made at six days, six weeks, and six months after delivery. It is also recommended that women who have a normal, uneventful vaginal delivery without any complications at a health facility be observed for 24 hours before discharge. Women who have undergone a caesarean section should ideally be observed in the health facility for a period of at least three days (or longer depending on their clinical status) before discharge (MoHSS, 2013c). Table 10.8 shows that in the two years preceding the survey, 69 percent of women received postnatal care for their last birth within the critical first two days following delivery. This is a small improvement from 2006-07, when 65 percent of women received care in the first two days after delivery. About one in three (34 percent) women received postnatal care within 4 hours of delivery, 14 percent received care within 4-23 hours, and 21 percent were seen 1-2 days following delivery. Differences by mother’s age, birth order, place of delivery, residence, and education are pronounced and are similar to the differences discussed for delivery care. Postnatal care within the first two days following delivery is lowest in Kavango (48 percent), followed closely by Kunene (50 percent). Table 10.8 Timing of first postnatal checkup Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution of the mother’s first postnatal checkup for the last live birth by time after delivery, and the percentage of women with a live birth in the two years preceding the survey who received a postnatal checkup in the first two days after giving birth, according to background characteristics, Namibia 2013 Time after delivery of mother’s first postnatal checkup No postnatal checkup1 Total Percentage of women with a postnatal checkup in the first two days after birth Number of women Background characteristic Less than 4 hours 4-23 hours 1-2 days 3-6 days 7-41 days Don’t know/ missing Mother’s age at birth <20 31.3 11.0 20.1 1.4 7.9 6.4 21.9 100.0 62.4 294 20-34 34.1 15.1 21.1 2.0 6.4 6.1 15.3 100.0 70.3 1,349 35-49 36.7 11.8 20.3 1.5 6.7 3.3 19.7 100.0 68.8 304 Birth order 1 38.6 12.3 20.2 1.8 8.0 5.3 13.8 100.0 71.2 628 2-3 32.4 15.8 21.2 2.1 6.6 6.7 15.2 100.0 69.3 829 4-5 29.7 14.4 22.4 0.6 5.6 4.8 22.5 100.0 66.5 332 6+ 34.3 9.7 17.8 2.5 4.6 3.7 27.3 100.0 61.9 159 Place of delivery Health facility 36.9 14.2 21.5 1.5 7.2 6.2 12.4 100.0 72.6 1,715 Elsewhere 12.9 11.9 15.8 3.9 3.1 1.7 50.7 100.0 40.7 232 Residence Urban 35.0 13.5 20.5 1.9 8.9 5.3 14.9 100.0 69.0 925 Rural 33.2 14.4 21.1 1.7 4.7 6.0 18.8 100.0 68.7 1,022 Region Zambezi 42.5 18.5 11.6 1.2 4.2 4.8 17.2 100.0 72.6 112 Erongo 35.6 6.9 19.8 1.4 12.1 10.6 13.6 100.0 62.4 136 Hardap 31.0 25.1 12.7 2.3 4.4 2.2 22.4 100.0 68.7 73 //Karas 42.2 9.6 20.2 2.6 4.9 6.6 14.0 100.0 72.0 61 Kavango 14.0 9.1 24.6 0.8 2.5 9.9 39.2 100.0 47.7 231 Khomas 37.2 12.3 20.3 1.6 11.8 4.3 12.6 100.0 69.7 344 Kunene 16.6 19.4 14.2 4.0 18.1 5.2 22.5 100.0 50.2 69 Ohangwena 36.3 12.0 25.4 2.1 5.0 3.4 15.9 100.0 73.7 254 Omaheke 29.7 9.8 21.4 1.1 12.4 6.8 18.7 100.0 61.0 59 Omusati 51.5 18.7 5.9 0.0 3.7 9.1 11.2 100.0 76.0 189 Oshana 42.7 21.9 24.1 1.5 2.4 1.4 6.1 100.0 88.6 127 Oshikoto 32.5 17.3 34.0 4.5 1.1 2.5 8.2 100.0 83.7 154 Otjozondjupa 26.2 10.7 26.1 2.8 9.4 6.4 18.4 100.0 63.0 137 Education No education 17.7 8.2 21.6 1.7 2.5 8.3 40.1 100.0 47.5 110 Primary 26.3 13.2 19.2 1.4 5.4 6.8 27.7 100.0 58.7 438 Secondary 37.5 14.1 21.2 2.1 7.2 5.4 12.5 100.0 72.8 1,295 More than secondary 41.2 21.9 21.3 0.0 10.4 1.5 3.7 100.0 84.4 105 Wealth quintile Lowest 29.4 12.7 18.5 2.4 2.9 6.6 27.6 100.0 60.5 415 Second 36.5 13.0 24.6 1.6 5.7 6.0 12.6 100.0 74.1 439 Middle 37.8 13.8 21.4 1.0 6.1 5.1 14.8 100.0 73.0 423 Fourth 31.3 16.5 21.3 2.3 7.7 4.8 16.0 100.0 69.1 389 Highest 35.6 14.1 16.6 1.7 13.5 6.0 12.6 100.0 66.2 281 Total 34.1 14.0 20.8 1.8 6.7 5.7 17.0 100.0 68.8 1,947 1 Includes women who received a checkup after 41 days 110 • Maternal Health Care Table 10.9 shows that, in the majority of cases, mothers received postnatal care from a health professional (68 percent). Less than 1 percent of mothers received a postnatal checkup from a community health worker or a traditional birth attendant. Differences by background characteristics are similar to those discussed in reference to timing of the first postnatal checkup. Table 10.9 Type of provider of first postnatal checkup for the mother Among women age 15-49 giving birth in the two years preceding the survey, the percent distribution by type of provider of the mother’s first postnatal health check in the two days after the last live birth, according to background characteristics, Namibia 2013 Type of health provider of mother’s first postnatal checkup No postnatal checkup in the first two days after birth1 Total Number of women Background characteristic Doctor/nurse/ midwife Community health worker Traditional birth attendant Mother’s age at birth <20 61.0 0.4 1.0 37.6 100.0 294 20-34 69.7 0.1 0.5 29.7 100.0 1,349 35-49 67.3 0.0 1.5 31.2 100.0 304 Birth order 1 70.2 0.2 0.8 28.8 100.0 628 2-3 68.8 0.1 0.4 30.7 100.0 829 4-5 65.9 0.0 0.5 33.5 100.0 332 6+ 59.2 0.0 2.7 38.1 100.0 159 Place of delivery Health facility 72.4 0.0 0.1 27.4 100.0 1,715 Elsewhere 35.0 0.5 5.2 59.3 100.0 232 Residence Urban 68.6 0.0 0.4 31.0 100.0 925 Rural 67.5 0.2 1.1 31.3 100.0 1,022 Region Zambezi 71.4 0.7 0.5 27.4 100.0 112 Erongo 62.4 0.0 0.0 37.6 100.0 136 Hardap 68.7 0.0 0.0 31.3 100.0 73 //Karas 70.3 0.0 1.6 28.0 100.0 61 Kavango 46.4 0.0 1.3 52.3 100.0 231 Khomas 69.7 0.0 0.0 30.3 100.0 344 Kunene 47.4 0.0 2.8 49.8 100.0 69 Ohangwena 72.3 0.4 0.9 26.3 100.0 254 Omaheke 60.1 0.0 0.9 39.0 100.0 59 Omusati 74.2 0.0 1.8 24.0 100.0 189 Oshana 88.6 0.0 0.0 11.4 100.0 127 Oshikoto 83.1 0.0 0.6 16.3 100.0 154 Otjozondjupa 62.5 0.0 0.5 37.0 100.0 137 Education No education 46.5 0.0 1.0 52.5 100.0 110 Primary 57.4 0.0 1.3 41.3 100.0 438 Secondary 72.1 0.1 0.6 27.2 100.0 1,295 More than secondary 84.4 0.0 0.0 15.6 100.0 105 Wealth quintile Lowest 59.3 0.3 0.9 39.5 100.0 415 Second 73.4 0.2 0.5 25.9 100.0 439 Middle 71.1 0.0 2.0 27.0 100.0 423 Fourth 69.1 0.0 0.0 30.9 100.0 389 Highest 66.2 0.0 0.0 33.8 100.0 281 Total 68.0 0.1 0.7 31.2 100.0 1,947 1 Includes women who received a checkup after 41 days Figure 10.1 shows the percent distribution of mothers with a birth in the five years preceding the survey who delivered their last birth in a health facility, by duration of stay and type of delivery. As expected, the large majority of women with a vaginal birth stayed at a health facility for 1-2 days (67 percent). In contrast, the large majority of women with a C-section stayed at a health facility for 3 or more days (78 percent). Maternal Health Care • 111 Figure 10.1 Mother’s duration of stay in the health facility after giving birth 10.7.2 Postnatal Care for the Newborn As mentioned, a significant proportion of neonatal deaths occur during the first 48 hours after delivery. Thus, postnatal care services should be provided as soon as possible after the child is born. The timing of the postnatal checkup for the newborn is similar to that of the mother in that it should occur within six days after birth. Table 10.10 shows that 20 percent of infants born in the two years preceding the survey received a postnatal checkup. Three percent received a postnatal checkup less than 1 hour after birth, 9 percent within 1 to 3 hours, 3 percent within 4 to 23 hours, 4 percent within 1 to 2 days, and less than 1 percent within 3 to 6 days. Over three-quarters of newborns (77 percent) did not receive a postnatal checkup. Timing of a newborn’s first postnatal checkup varies slightly by place of delivery and urban-rural residence. For instance, 20 percent of newborns whose mothers delivered in a health facility received a postnatal checkup within two days, as compared with 18 percent of newborns whose mothers delivered elsewhere. Twenty-one percent of newborns whose mothers reside in urban areas had a postnatal check-up within two days after birth, compared with 19 percent of newborns whose mothers live in rural areas. However, there are more pronounced variations by region, education, and wealth. One in three newborns in Ohangwena had a postnatal checkup within two days after birth (33 percent), while only 3 percent of newborns in Kavango had a checkup. Newborns whose mothers had more than a secondary education were more likely to have a postnatal checkup than newborns whose mothers had no education (31 percent and 12 percent, respectively). Similarly, newborns whose mothers were in the highest wealth quintile were more likely to have a checkup within two days after birth than newborns whose mothers were in the second wealth quintile (24 percent and 17 percent, respectively). 4 <13 <12 <1 67 20 24 78 <1 <1 Vaginal birth Caesarean section Percentage < 6 hours 6-11 hours 12-23 hours 1-2 days 3+ days Missing NDHS 2013 112 • Maternal Health Care Table 10.10 Timing of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by time after birth of first postnatal checkup, and the percentage of births with a postnatal checkup in the first two days after birth, according to background characteristics, Namibia 2013 Time after birth of newborn’s first postnatal checkup No postnatal checkup1 Total Percentage of births with a postnatal checkup in the first two days after birth Number of births Background characteristic Less than 1 hour 1-3 hours 4-23 hours 1-2 days 3-6 days Don’t know/ missing Mother’s age at birth <20 1.3 8.4 1.9 3.7 0.6 1.9 82.2 100.0 15.3 294 20-34 2.7 9.8 3.8 4.7 0.8 2.5 75.7 100.0 21.0 1,349 35-49 4.7 7.6 2.1 3.6 0.6 3.4 78.0 100.0 17.9 304 Birth order 1 1.7 11.6 2.3 3.9 0.7 2.7 77.1 100.0 19.5 628 2-3 4.0 7.5 4.2 4.4 0.6 2.5 76.7 100.0 20.1 829 4-5 1.1 9.7 2.5 4.5 0.9 1.9 79.5 100.0 17.8 332 6+ 4.3 8.2 3.7 5.5 1.2 4.0 73.2 100.0 21.7 159 Place of delivery Health facility 2.9 10.1 3.2 3.7 0.7 2.7 76.7 100.0 19.9 1,715 Elsewhere 1.6 3.1 3.7 9.6 1.3 1.3 79.5 100.0 18.0 232 Residence Urban 2.8 10.2 3.9 4.0 0.6 1.8 76.7 100.0 20.9 925 Rural 2.8 8.4 2.7 4.7 0.9 3.3 77.3 100.0 18.6 1,022 Region Zambezi 4.6 7.4 5.1 6.8 0.6 0.4 75.1 100.0 23.9 112 Erongo 2.2 18.9 1.4 1.9 0.0 2.8 72.9 100.0 24.4 136 Hardap 2.1 8.9 4.3 5.0 1.2 1.2 77.3 100.0 20.3 73 //Karas 2.5 15.3 5.1 8.3 3.6 2.6 62.5 100.0 31.2 61 Kavango 0.4 0.5 0.0 2.2 0.9 1.2 94.7 100.0 3.2 231 Khomas 3.3 8.9 3.6 3.9 0.6 0.8 78.9 100.0 19.7 344 Kunene 0.9 3.6 2.1 2.9 1.1 0.0 89.4 100.0 9.5 69 Ohangwena 7.2 17.8 3.2 5.0 0.4 4.5 62.0 100.0 33.2 254 Omaheke 0.9 7.4 6.0 7.5 0.4 1.3 76.6 100.0 21.6 59 Omusati 0.2 7.8 2.8 3.3 0.6 7.4 77.9 100.0 14.1 189 Oshana 0.0 2.7 5.1 3.4 0.0 1.7 87.2 100.0 11.2 127 Oshikoto 3.8 11.2 2.9 5.6 1.5 4.4 70.5 100.0 23.6 154 Otjozondjupa 3.8 8.1 5.7 6.7 0.7 1.9 73.1 100.0 24.3 137 Mother’s education No education 1.4 4.1 3.8 2.7 0.5 3.1 84.4 100.0 12.0 110 Primary 1.9 7.9 4.4 3.8 0.9 2.9 78.2 100.0 18.0 438 Secondary 2.7 9.6 2.7 5.0 0.8 2.3 77.0 100.0 20.0 1,295 More than secondary 8.3 16.8 5.1 0.4 0.0 4.2 65.2 100.0 30.6 105 Wealth quintile Lowest 3.3 6.9 2.8 5.5 1.1 2.4 78.0 100.0 18.5 415 Second 1.4 8.4 2.9 4.3 0.8 3.9 78.5 100.0 16.9 439 Middle 2.6 10.1 3.5 4.4 0.7 2.8 75.8 100.0 20.6 423 Fourth 3.3 8.5 4.3 3.5 0.2 1.7 78.5 100.0 19.6 389 Highest 3.9 13.9 2.8 3.9 0.9 1.7 73.0 100.0 24.4 281 Total 2.8 9.3 3.3 4.4 0.7 2.6 77.0 100.0 19.7 1,947 1 Includes newborns who received a checkup after the first week Table 10.11 shows the type of provider of the newborn’s first postnatal checkup. Nineteen percent of newborns received a postnatal checkup from a skilled provider, while less than 1 percent received a checkup from a traditional birth attendant. Eighty percent of newborns did not receive a postnatal checkup within the first two days after birth. Differences by background characteristics are similar to those observed for timing of the newborn’s first postnatal checkup. Maternal Health Care • 113 Table 10.11 Type of provider of first postnatal checkup for the newborn Percent distribution of last births in the two years preceding the survey by type of provider of the newborn’s first postnatal health check during the two days after the last live birth, according to background characteristics, Namibia 2013 Type of health provider of newborn’s first postnatal checkup No postnatal checkup in the first two days after birth Total Number of births Background characteristic Doctor/nurse/ midwife Traditional birth attendant Mother’s age at birth <20 15.0 0.3 84.7 100.0 294 20-34 20.6 0.3 79.0 100.0 1,349 35-49 17.5 0.4 82.1 100.0 304 Birth order 1 19.2 0.3 80.5 100.0 628 2-3 19.8 0.3 79.9 100.0 829 4-5 17.1 0.7 82.2 100.0 332 6+ 21.7 0.0 78.3 100.0 159 Place of delivery Health facility 19.7 0.1 80.1 100.0 1,715 Elsewhere 16.2 1.8 82.0 100.0 232 Residence Urban 20.8 0.1 79.1 100.0 925 Rural 17.9 0.5 81.4 100.0 1,022 Region Zambezi 23.2 0.0 76.1 100.0 112 Erongo 24.4 0.0 75.6 100.0 136 Hardap 20.3 0.0 79.7 100.0 73 //Karas 30.6 0.6 68.8 100.0 61 Kavango 2.3 0.9 96.8 100.0 231 Khomas 19.7 0.0 80.3 100.0 344 Kunene 8.3 1.2 90.5 100.0 69 Ohangwena 32.3 0.9 66.8 100.0 254 Omaheke 20.8 0.9 78.4 100.0 59 Omusati 14.1 0.0 85.9 100.0 189 Oshana 11.2 0.0 88.8 100.0 127 Oshikoto 23.6 0.0 76.4 100.0 154 Otjozondjupa 23.8 0.5 75.7 100.0 137 Mother’s education No education 11.6 0.4 88.0 100.0 110 Primary 17.4 0.6 82.0 100.0 438 Secondary 19.7 0.3 80.0 100.0 1,295 More than secondary 30.6 0.0 69.4 100.0 105 Wealth quintile Lowest 17.9 0.6 81.5 100.0 415 Second 16.7 0.0 83.1 100.0 439 Middle 19.7 0.9 79.4 100.0 423 Fourth 19.6 0.0 80.4 100.0 389 Highest 24.3 0.1 75.6 100.0 281 Total 19.3 0.3 80.3 100.0 1,947 10.8 PROBLEMS IN ACCESSING HEALTH CARE Many factors can prevent women from obtaining medical advice or treatment for themselves when they are sick. Information on such factors is particularly important in understanding and addressing the barriers women may face when seeking care during pregnancy, delivery, and the postnatal period. In the 2013 NDHS, women were asked whether each of the following factors would be an impediment (or not) in seeking medical care: getting permission to go for treatment, getting money for treatment, distance to a health facility, and not wanting to go alone. Table 10.12 shows that 43 percent of women reported at least one of these concerns as a hindrance to accessing health care. 114 • Maternal Health Care Table 10.12 Problems in accessing health care Percentage of women age 15-49 who reported that they have serious problems in accessing health care for themselves when they are sick, by type of problem, according to background characteristics, Namibia 2013 Problems in accessing health care Background characteristic Getting permission to go for treatment Getting money for treatment Distance to health facility Not wanting to go alone At least one problem accessing health care Number of women Age 15-19 6.9 26.8 29.4 18.6 45.1 1,906 20-34 6.4 27.0 29.3 13.5 42.1 4,535 35-49 5.7 29.1 33.3 13.9 44.1 2,735 Number of living children 0 5.0 21.6 24.5 15.8 38.4 3,034 1-2 6.8 26.3 29.5 12.4 41.8 3,606 3-4 6.3 32.6 34.5 14.9 46.3 1,750 5+ 8.4 45.1 49.8 20.4 62.4 785 Marital status Never married 5.4 25.8 28.8 14.7 41.9 5,458 Married or living together 7.5 29.0 32.1 14.3 43.7 3,121 Divorced/separated/widowed 8.1 36.3 38.4 16.3 53.7 597 Employed in last 12 months Not employed 6.8 33.5 35.7 16.9 49.7 4,987 Employed for cash 5.7 19.3 23.1 11.2 34.4 3,826 Employed not for cash 4.9 32.6 38.1 20.4 50.0 351 Residence Urban 5.2 20.0 18.6 10.3 32.7 5,190 Rural 7.6 37.4 46.0 20.3 57.2 3,986 Region Zambezi 7.9 49.2 36.6 21.3 57.5 457 Erongo 8.2 19.7 13.7 9.5 29.5 771 Hardap 5.6 21.3 30.6 6.3 37.4 304 //Karas 4.0 20.5 22.7 9.8 36.4 343 Kavango 14.5 65.5 54.7 25.7 77.0 835 Khomas 4.1 15.9 17.9 9.7 29.0 2,202 Kunene 2.1 32.2 38.3 6.0 46.5 258 Ohangwena 4.2 30.1 48.2 26.5 57.6 894 Omaheke 9.6 37.4 43.6 15.7 56.0 225 Omusati 5.4 25.3 35.2 16.3 42.7 884 Oshana 3.9 20.3 23.1 9.7 33.2 755 Oshikoto 7.7 20.6 31.3 16.4 44.3 707 Otjozondjupa 6.9 30.0 31.8 13.5 48.2 540 Education No education 10.9 54.0 57.8 25.1 72.2 419 Primary 9.6 46.5 48.3 22.5 63.9 1,798 Secondary 5.5 22.7 26.2 12.7 38.5 6,029 More than secondary 2.7 10.7 12.3 8.0 21.6 930 Wealth quintile Lowest 9.0 55.8 61.6 28.2 74.4 1,429 Second 8.7 38.4 44.5 19.2 58.9 1,625 Middle 6.8 26.0 32.0 13.8 44.6 1,795 Fourth 5.1 19.1 19.6 10.4 33.3 2,116 Highest 3.4 10.8 9.5 7.4 20.3 2,211 Total 6.3 27.6 30.5 14.7 43.3 9,176 Note: Total includes 12 women with missing information on employment. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. The most common factor impeding women from accessing health care for themselves is distance to a health facility (31 percent), followed closely by getting money to pay for treatment (28 percent). Six percent of women reported getting permission to go as a problem in accessing health care, and 15 percent reported not wanting to go alone. Women with five or more children, formerly married women, unemployed women, women who are employed but not for cash, rural women, and women in Kavango were more likely than their counterparts to cite having at least one of these problems in seeking health care for themselves, as were women with no education and those from the poorest households. The percentage of women who reported each of these factors as a problem in seeking medical care generally decreased with increasing educational attainment and wealth. As expected, women residing in rural areas were more likely than those in urban areas to report distance as a problem (46 percent versus 19 percent). Child Health • 115 CHILD HEALTH 11 his chapter presents findings on child health and survival, including neonatal characteristics (birth weight and size), the vaccination status of young children, and treatment practices—particularly contact with health services—among children suffering from three childhood illnesses: acute respiratory infection (ARI), fever, and diarrhoea. Because appropriate sanitary practices can help prevent and reduce the severity of diarrhoeal disease, information is also provided on disposal of children’s faecal matter. These results can assist policymakers and programme managers as they formulate appropriate strategies and interventions to improve the health of children in Namibia. In particular, the results will be used to assess coverage of current strategies such as integrated management of childhood illness, which seeks to prevent deaths from pneumonia, malaria, and diarrhoea, and to plan for improvements in these initiatives. 11.1 CHILD’S WEIGHT AND SIZE AT BIRTH Birth weight is an important indicator when assessing a child’s health in terms of early exposure to childhood morbidity and mortality. Children who weigh less than 2.5 kilograms at birth, or children reported to be “very small” or “smaller than average,” are considered to have a higher than average risk of early childhood death. In the 2013 NDHS, for births in the five years preceding the survey, birth weight was recorded in the Woman’s Questionnaire based on either a written record or the mother’s report. The mother’s estimate of the infant’s size at birth was also obtained because birth weight may be unknown for many infants. Although the mother’s estimate of size is subjective, it can be a useful proxy for the child’s weight. Table 11.1 includes information on mothers’ estimates of their infant’s size at birth. Seven percent of births are reported as very small, 13 percent as smaller than average, and 79 percent as average or larger than average. Children of mothers less than age 20 are more likely to be reported as very small than children of mothers age 20 or older. Mothers who smoke cigarettes or tobacco are more likely to report very small babies at birth than mothers who do not smoke. Kavango has the highest percentage of infants T Key Findings • Nineteen percent of infants born in the five years preceding the survey were very small or smaller than average at birth. Among infants with a reported birth weight, 13 percent weighed less than 2.5 kg. • Sixty-eight percent of children age 12-23 months were fully vaccinated at the time of the survey; 63 percent of children in this age group had received all basic vaccinations by age 12 months. • Six percent of children under age 5 experienced symptoms of acute respiratory infection (ARI) in the two weeks preceding the survey. • Twenty-four percent of children under age 5 had a fever within the two weeks preceding the survey. Among those with a fever, 59 percent were taken to a health facility or provider for advice or treatment, 8 percent received antimalarial medicines, and 45 percent received antibiotics. • Seventeen percent of children under age 5 had diarrhoea in the two weeks preceding the survey. Sixty-four percent of these children were taken to a health facility or provider, and 79 percent were treated with oral rehydration therapy (ORT) or increased fluids. Twelve percent of children with diarrhoea did not receive any type of treatment. 116 • Child Health reported as very small at birth, and Zambezi has the lowest percentage. Children of mothers with more than a secondary education are less likely to be reported as very small than children of mothers with no education (7 percent and 11 percent, respectively). Mothers in the fourth wealth quintile are less likely to report very small babies than mothers in the lowest and highest wealth quintiles. Table 11.1 Child’s size and weight at birth Percent distribution of live births in the five years preceding the survey by mother’s estimate of baby’s size at birth, percentage of live births in the five years preceding the survey that have a reported birth weight, and among live births in the five years preceding the survey with a reported birth weight, percentage less than 2.5 kg, according to background characteristics, Namibia 2013 Percent distribution of all live births by size of child at birth Percentage of all births that have a reported birth weight1 Number of births Births with a reported birth weight1 Background characteristic Very small Smaller than average Average or larger Don’t know/ missing Total Percentage less than 2.5 kg Number of births Mother’s age at birth <20 9.0 13.9 73.8 3.3 100.0 80.0 765 15.8 612 20-34 6.1 12.3 80.0 1.6 100.0 86.8 3,317 12.6 2,880 35-49 5.9 13.3 79.1 1.7 100.0 84.2 722 12.1 608 Birth order 1 7.4 13.4 76.8 2.4 100.0 88.5 1,647 15.2 1,457 2-3 5.7 12.0 80.9 1.4 100.0 88.1 1,962 12.2 1,728 4-5 6.5 12.3 79.8 1.4 100.0 81.7 755 12.0 617 6+ 6.4 14.5 76.3 2.8 100.0 67.5 440 9.3 297 Mother’s smoking status Smokes cigarettes/ tobacco 8.8 18.1 70.4 2.7 100.0 79.2 241 18.3 191 Does not smoke 6.4 12.5 79.4 1.8 100.0 85.7 4,559 12.8 3,907 Residence Urban 6.8 11.6 79.8 1.8 100.0 90.8 2,347 12.9 2,130 Rural 6.2 13.8 78.0 1.9 100.0 80.1 2,457 13.1 1,969 Region Zambezi 2.6 18.3 77.6 1.6 100.0 86.6 297 10.1 257 Erongo 5.2 10.0 82.2 2.6 100.0 93.7 334 11.8 313 Hardap 4.0 14.3 79.3 2.4 100.0 91.4 173 13.5 158 //Karas 4.2 15.5 80.0 0.4 100.0 91.3 165 14.3 151 Kavango 9.8 24.0 65.1 1.0 100.0 75.8 577 13.0 438 Khomas 8.4 9.8 80.0 1.8 100.0 91.3 887 13.8 810 Kunene 7.0 11.4 78.9 2.7 100.0 65.6 179 15.1 117 Ohangwena 4.3 7.7 87.0 0.9 100.0 76.2 598 11.6 456 Omaheke 9.4 17.4 71.9 1.3 100.0 74.0 149 15.2 110 Omusati 5.4 10.3 80.1 4.3 100.0 89.3 454 12.6 405 Oshana 5.1 7.6 85.5 1.8 100.0 95.0 310 15.8 294 Oshikoto 8.0 13.6 77.1 1.4 100.0 87.4 373 14.1 325 Otjozondjupa 6.6 11.2 79.8 2.4 100.0 86.2 308 10.5 266 Mother’s education No education 10.7 14.9 67.2 7.1 100.0 51.6 298 13.8 154 Primary 7.6 13.0 76.6 2.8 100.0 72.3 1,125 11.9 814 Secondary 5.7 12.9 80.3 1.1 100.0 92.3 3,073 13.3 2,835 More than secondary 6.5 8.0 84.2 1.3 100.0 96.6 307 12.5 297 Wealth quintile Lowest 7.7 14.9 75.4 2.0 100.0 71.6 1,047 13.8 750 Second 5.9 14.0 77.9 2.3 100.0 84.1 1,053 15.6 885 Middle 6.2 12.3 79.5 2.1 100.0 87.8 997 12.2 875 Fourth 5.4 10.2 83.2 1.2 100.0 91.5 1,000 11.8 915 Highest 7.8 11.9 78.6 1.7 100.0 95.3 707 11.5 674 Total 6.5 12.7 78.9 1.9 100.0 85.3 4,804 13.0 4,100 Note: Total includes 4 births with missing information on mother’s smoking status. 1 Based on either a written record or the mother’s recall Table 11.1 also shows that birth weight is reported for 85 percent of the live births that occurred in the five years preceding the survey; 13 percent of these infants had low birth weights (less than 2.5 kg). Children of mothers less than age 20 and first births are more likely to be of low birth weight than their counterparts in the other categories. Smoking has an adverse impact on birth weight. The percentage of children of low birth weight ranges from a low of 10 percent in Zambezi to a high of 16 percent in Oshana. Child Health • 117 11.2 VACCINATION OF CHILDREN According to the World Health Organization, a child is considered fully immunised if he or she has received a BCG vaccination against tuberculosis; three doses of the DPT vaccine to prevent diphtheria, pertussis, and tetanus; at least three doses of the polio vaccine; and one dose of the measles vaccine. These vaccinations should be received during the first year of life. The 2013 NDHS collected information on the coverage of these vaccinations among all children under age 5, including receipt of three doses of the pentavalent vaccination (in place of the DPT vaccine), introduced in Namibia in September 2009. The pentavalent vaccine is a combination of five vaccines: diphtheria, tetanus, pertussis (whooping cough), hepatitis B, and Haemophilus influenzae type b (the bacteria that causes meningitis, pneumonia, and otitis). Since the reference period for childhood vaccination coverage includes both the stand-alone DPT and the pentavalent vaccine, we refer to this vaccination as DPT/pentavalent in the text and tables. BCG should be given shortly after birth. The DPT/pentavalent and polio vaccines are given at approximately age 6, 10, and 14 weeks, and the measles vaccine should be given at or soon after age 9 months. 11.2.1 Sources of Information In the 2013 NDHS, information on immunisation coverage was collected in two ways: from immunisation cards shown to the interviewer and from mothers’ verbal reports. If the cards were available, the interviewer copied the immunisation dates directly onto the questionnaire. When there was no immunisation card, or if a vaccine had not been recorded on the card as being administered, the respondent was asked to recall the specific vaccines given to her child. The results presented here are based on both health card information and, for children without a card, information provided by the mother. 11.2.2 Vaccination Coverage Table 11.2 shows vaccination coverage among children age 12-23 months by source of information. Overall, 68 percent of children age 12-23 months were fully vaccinated at the time of the survey. Ninety-four percent had received the BCG vaccination at any time before the survey. In the case of the DPT/pentavalent vaccine, 93 percent had received the first dose, 89 percent had received the second dose, and 84 percent had received the third dose. Ninety-three percent had received the first dose of the polio vaccine, 88 percent had received the second dose, and 74 percent had received the third dose. Coverage of measles was 90 percent. Four percent of children age 12-23 months had not received any vaccinations, as compared with 2 percent in the 2006-07 NDHS. Table 11.2 also shows the percentage of children vaccinated by age 12 months. This is the youngest cohort of children who have reached the age by which they should be fully immunised. Overall, 63 percent of children are fully immunised by 12 months. Table 11.2 Vaccinations by source of information Percentage of children age 12-23 months who received specific vaccines at any time before the survey, by source of information (vaccination card or mother’s report), and percentage vaccinated by 12 months of age, Namibia 2013 Source of information BCG DPT/Pentavalent1 Polio Measles All basic vaccina- tions3 No vaccina- tions Number of children 1 2 3 02 1 2 3 Vaccinated at any time before survey Vaccination card 69.4 68.7 68.3 67.1 69.1 69.5 69.2 67.8 66.2 64.7 0.0 652 Mother’s report 24.8 24.0 20.8 16.5 20.8 23.1 18.4 6.5 23.3 3.7 4.4 286 Either source 94.2 92.7 89.0 83.5 89.9 92.6 87.6 74.3 89.5 68.4 4.4 938 Vaccinated by 12 months of age4 94.2 92.3 88.8 82.4 89.9 92.2 87.4 73.2 82.9 62.6 4.6 938 1 Pentavalent vaccinations include DPT, Hepatitis B (HepB) and Haemophilus influenza type B (HiB) 2 Polio 0 is the polio vaccination given at birth. 3 BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) 4 For children whose information is based on the mother’s report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccination. 118 • Child Health Table 11.3 presents information on vaccination coverage among children age 12-23 months (from either vaccination cards or mothers’ reports) by background characteristics. Table 11.3 Vaccinations by background characteristics Percentage of children age 12-23 months who received specific vaccines at any time before the survey (according to a vaccination card or the mother’s report), and percentage with a vaccination card, by background characteristics, Namibia 2013 Background characteristic BCG DPT/pentavalent1 Polio Measles All basic vaccina- tions3 No vaccina- tions Percentage with a vaccination card seen Number of children 1 2 3 02 1 2 3 Sex Male 95.1 94.4 91.4 85.9 91.2 93.5 88.7 74.5 91.4 69.0 3.1 69.6 440 Female 93.4 91.1 87.0 81.4 88.8 91.8 86.7 74.2 87.8 67.9 5.6 69.5 498 Birth order 1 93.0 90.6 86.7 80.3 87.2 90.9 85.0 64.5 90.7 60.2 5.7 61.3 306 2-3 94.9 93.7 88.8 84.6 91.7 93.2 88.0 78.3 87.5 70.5 3.1 72.2 389 4-5 94.2 92.6 91.7 83.8 88.8 93.4 91.1 79.6 91.2 73.4 5.7 74.4 163 6+ 95.7 95.7 93.9 89.9 93.8 94.9 89.0 81.6 91.2 79.2 3.7 78.5 80 Residence Urban 91.8 89.1 84.0 78.3 87.0 89.6 83.8 66.4 85.7 58.1 6.4 59.5 467 Rural 96.5 96.2 94.0 88.6 92.8 95.6 91.4 82.1 93.2 78.6 2.5 79.4 471 Region Zambezi 100.0 98.3 95.9 88.8 92.4 98.9 89.3 81.7 91.7 78.3 0.0 74.1 57 Erongo 91.6 91.1 87.1 80.4 90.3 94.0 93.0 71.9 93.3 65.7 6.0 60.9 70 Hardap 98.7 97.5 97.5 97.5 96.7 97.1 97.1 87.8 97.5 87.8 1.3 82.8 35 //Karas 97.2 97.7 94.1 81.4 96.0 95.5 87.3 68.7 91.8 65.0 1.3 66.4 33 Kavango 94.7 94.7 89.4 80.6 90.9 91.8 88.3 78.0 89.0 73.4 5.3 77.8 108 Khomas 83.4 77.3 72.0 64.4 76.8 81.6 73.3 52.6 75.1 39.6 13.9 46.6 165 Kunene 91.6 91.9 89.3 78.7 85.2 94.2 88.1 60.7 88.2 56.0 3.5 52.9 32 Ohangwena 97.0 99.0 95.0 92.6 95.6 95.7 93.5 79.1 95.7 74.7 1.0 74.1 123 Omaheke 94.4 93.5 92.6 87.9 91.1 93.5 88.9 78.2 87.3 73.8 4.7 69.3 27 Omusati 98.8 97.4 95.8 93.0 94.5 98.8 96.0 91.8 91.7 84.7 1.2 90.4 89 Oshana 94.2 89.1 85.5 80.9 85.7 87.9 79.3 66.5 89.8 62.2 4.3 63.3 60 Oshikoto 98.7 98.7 95.4 90.8 97.5 95.8 89.5 83.8 98.7 82.5 0.0 81.3 78 Otjozondjupa 99.1 97.8 94.5 93.5 92.0 96.4 93.2 83.5 90.9 77.6 0.9 76.9 63 Mother’s education No education 92.3 93.4 88.6 72.8 83.4 93.7 87.1 70.4 83.8 59.0 5.0 69.6 55 Primary 94.9 92.9 92.0 85.9 90.4 92.0 90.0 79.6 89.2 74.6 5.1 76.2 211 Secondary 94.7 94.1 89.6 85.7 91.2 93.4 87.6 73.9 91.3 68.7 3.5 68.2 621 More than secondary (87.4) (73.0) (70.6) (58.4) (79.3) (84.1) (79.6) (61.5) (75.2) (49.3) (12.6) (57.6) 50 Wealth quintile Lowest 96.3 97.4 93.8 86.9 93.0 95.4 90.4 79.1 93.3 74.6 2.5 76.5 195 Second 95.2 93.0 89.9 82.9 89.9 93.0 89.6 77.4 90.2 70.3 3.5 76.2 194 Middle 93.8 93.2 90.0 87.2 90.0 92.2 86.7 75.7 88.9 72.5 5.7 72.6 203 Fourth 92.4 91.2 88.7 86.1 88.5 91.7 86.5 72.9 88.8 69.4 6.4 64.0 198 Highest 93.1 87.3 80.7 71.3 87.7 90.1 84.3 63.8 85.2 50.7 3.9 54.7 147 Total 94.2 92.7 89.0 83.5 89.9 92.6 87.6 74.3 89.5 68.4 4.4 69.5 938 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Pentavalent vaccinations include DPT, Hepatitis B (HepB) and Haemophilus influenza type B (HiB). 2 Polio 0 is the polio vaccination given at birth. 3 BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) There are only slight variations in vaccination coverage by gender. Full vaccination coverage increases steadily with increasing birth order. Children in urban areas are much less likely to be fully immunised than children in rural areas (58 percent versus 79 percent). Full immunisation coverage is lowest in Khomas (40 percent), the most urban region, and highest in Hardap (88 percent). Coverage is highest (75 percent) among children of mothers with a primary education. Children in the lowest wealth quintile are more likely to be fully vaccinated than those in the highest quintile (75 percent and 51 percent, respectively). Table 11.3 also shows that an immunisation card was seen for 70 percent of children age 12-23 months. Cards were most likely to have been seen for children of birth order six and higher (79 percent), children living in rural areas (79 percent), children living in Omusati (90 percent), children of mothers with a primary education (76 percent), and children of mothers in the lowest wealth quintile (77 percent). Child Health • 119 11.2.3 Trends in Vaccination Coverage Figure 11.1 compares vaccination coverage from the 2006-07 and 2013 NDHS surveys for the first year of life among children age 12-23 months. Full immunisation coverage has decreased slightly in the last six years from 64 percent in 2006-07 to 63 percent in 2013. Differences in coverage between the two surveys by specific vaccines are small with the exception of measles (which increased from 78 percent to 83 percent) and polio 3 (which decreased from 77 percent to 73 percent). Figure 11.1 Trends in vaccination coverage during the first year of life among children age 12-23 months Table 11.4 shows the percentage of children age 12-59 months who received specific vaccinations during the first year of life, according to age cohort. The data indicate that the proportion of children fully vaccinated by age 12 months has increased noticeably only among the youngest two cohorts, from 48 percent among children age 24-35 months to 63 percent among children age 12-23 months. Table 11.4 Vaccinations in first year of life Percentage of children age 12-59 months at the time of the survey who received specific vaccines by 12 months of age, and percentage with a vaccination card, by current age of child, Namibia 2013 BCG DPT/Pentavalent1 Polio Measles All basic vaccina- tions3 No vaccina- tions Percent- age with a vaccination card seen Number of children Age in months 1 2 3 02 1 2 3 12-23 94.2 92.3 88.8 82.4 89.9 92.2 87.4 73.2 82.9 62.6 4.6 69.5 938 24-35 92.8 92.1 84.0 72.4 86.6 91.3 84.5 64.7 74.2 47.8 4.1 53.9 926 36-47 93.2 90.9 80.6 70.7 83.7 89.7 81.2 57.9 76.7 44.5 4.7 44.4 883 48-59 92.4 89.8 83.2 72.2 82.9 91.1 83.0 60.0 75.1 44.2 5.2 39.2 830 Total 93.2 91.3 84.3 74.7 85.9 91.1 84.1 64.3 78.1 50.3 4.6 52.3 3,577 Note: Information was obtained from the vaccination card or if there was no written record, from the mother. For children whose information is based on the mother’s report, the proportion of vaccinations given during the first year of life is assumed to be the same as for children with a written record of vaccinations. 1 Pentavalent vaccinations include DPT, Hepatitis B (HepB) and Haemophilus influenza type b (HiB) 2 Polio 0 is the polio vaccination given at birth. 3 BCG, measles and three doses each of DPT and polio vaccine (excluding polio vaccine given at birth) 63 94 82 89 92 73 87 92 90 83 64 95 81 88 93 77 88 94 91 78 All BCG DPT 3 DPT 2 DPT 1 Polio 3 Polio 2 Polio 1 Polio 0 Measles Percentage 2007 2013 NDHS 2013 120 • Child Health 11.3 PREVALENCE AND TREATMENT OF ACUTE RESPIRATORY INFECTION Acute respiratory infections (ARIs) are a leading cause of childhood morbidity and mortality throughout the developing world. Early diagnosis and treatment with antibiotics can reduce the number of deaths caused by ARIs, particularly deaths resulting from pneumonia. In the 2013 NDHS, the prevalence of ARI symptoms was estimated by asking mothers whether, in the two weeks preceding the survey, their children under age 5 had been ill with a cough accompanied by short, rapid breathing and difficulty breathing as a result of a chest-related problem. These symptoms are consistent with conditions leading to pneumonia. It should be noted that the data collected on ARI symptoms are subjective because they are based on a mother’s perception of illness without validation by medical personnel. Table 11.5 shows that 6 percent of children under age 5 exhibited symptoms of ARI in the two weeks preceding the survey. The prevalence of ARI symptoms varied by the age of the child. Children age 6-11 months were more likely to have symptoms of ARI (8 percent) than children in the other age groups. Male children were more likely than female children to exhibit symptoms of ARI (7 percent versus 5 percent). ARI symptoms were also more likely to be reported among children of mothers who do not smoke, rural children, and children in Zambezi than among children in the other categories. Children of mothers with a primary education and those living in the poorest households were most likely to exhibit ARI symptoms. Two-thirds (68 percent) of children with symptoms of ARI were taken to a health facility or health provider. More than one in two children (53 percent) with ARI symptoms received antibiotics. Due to the small number of cases, these data are not shown separately by background characteristics. 11.4 PREVALENCE AND TREATMENT OF FEVER Fever is a symptom of malaria, but it may also accompany other illnesses including pneumonia, common colds, and influenza. Because malaria is a major cause of death in infancy and childhood in many developing countries, prior to 2010 presumptive treatment of fever with antimalarial medication was advocated in many countries where malaria is endemic (WHO, 2010a). In Namibia, ideally all suspected malaria cases should be confirmed diagnostically before treatment; however, when parasitological diagnosis is not accessible, treatment may be based on clinical diagnosis (Ministry of Health and Social Services [MoHSS], 2005). Information relating to the prevention and treatment of malaria is discussed in detail in Chapter 12. In the 2013 NDHS, fever prevalence was estimated by asking mothers whether their children under age 5 had been ill with a fever in the two weeks preceding the survey. For children with a fever, Table 11.5 Prevalence and treatment of symptoms of ARI Among children under age five, the percentage who had symptoms of acute respiratory infection (ARI) in the two weeks preceding the survey, according to background characteristics, Namibia 2013 Among children under age five: Background characteristic Percentage with symptoms of ARI1 Number of children Age in months <6 3.8 500 6-11 7.9 512 12-23 6.5 938 24-35 7.6 926 36-47 4.7 883 48-59 3.7 830 Sex Male 6.6 2,237 Female 4.9 2,351 Mother’s smoking status Smokes cigarettes/tobacco 4.8 227 Does not smoke 5.8 4,357 Cooking fuel Electricity or gas 5.2 1,653 Kerosene 2.1 115 Wood/straw2 6.2 2,793 Residence Urban 5.4 2,249 Rural 6.1 2,340 Region Zambezi 12.1 279 Erongo 7.4 320 Hardap 2.2 166 //Karas 3.9 160 Kavango 5.5 541 Khomas 5.2 858 Kunene 2.9 170 Ohangwena 4.0 561 Omaheke 3.8 143 Omusati 6.9 440 Oshana 4.9 300 Oshikoto 7.6 353 Otjozondjupa 5.7 298 Mother’s education No education 4.6 281 Primary 6.6 1,061 Secondary 5.6 2,948 More than secondary 5.6 300 Wealth quintile Lowest 6.6 988 Second 6.2 1,009 Middle 5.7 952 Fourth 4.5 954 Highest 5.7 686 Total 5.7 4,588 Note: Total includes 4 children with missing information on mother’s smoking status; 24 children living in households using coal/lignite, charcoal, animal dung, and other fuel; 1 child living in a household where no food is cooked; and 2 children missing information on cooking status who are not shown separately. 1 Symptoms of ARI (cough accompanied by short, rapid breathing that is chest-related and/or by difficult breathing that is chest-related) are considered a proxy for pneumonia. 2 Includes grass, shrubs, and crop residues Child Health • 121 mothers were also asked about treatment actions they took, including whether or not the child had been given any medicine to treat the fever and, if so, what medicine the child was given. Table 11.6 shows that about one in four children under age 5 (24 percent) had a fever during the two weeks preceding the survey. The prevalence of fever varies with children’s ages. Children age 6-11 months were more likely to have had a fever (38 percent) than children in other age groups. Among regions, the prevalence of fever in the two weeks preceding the survey ranged from a high of 50 percent in Zambezi to a low of 13 percent in Kunene. Children of mothers with some education were more likely to have had a fever in the two weeks preceding the survey than children of mothers with no education. Advice or treatment was sought from a health facility or provider for 59 percent of children with fever. Children were more likely to have received an antibiotic medicine than an antimalarial medicine during an episode of fever (45 percent versus 8 percent). Children age 12-23 months, male children, those living in rural areas, children of mothers with more than a secondary education, and those in the middle wealth quintile were more likely than their counterparts in the other categories to have been taken to a facility or provider for advice or treatment of fever. Table 11.6 Prevalence and treatment of fever Among children under age five, the percentage who had a fever in the two weeks preceding the survey; and among children with fever, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage who took antimalarial medicines, and the percentage who received antibiotics as treatment, by background characteristics, Namibia 2013 Among children under age five: Among children under age five with fever: Background characteristic Percentage with fever Number of children Percentage for whom advice or treatment was sought from a health facility or provider1 Percentage who took antimalarial medicines Percentage who took antibiotic medicines Number of children Age in months <6 23.1 500 57.1 6.3 33.3 116 6-11 38.0 512 61.1 8.1 47.6 194 12-23 27.7 938 70.1 10.7 47.8 260 24-35 24.1 926 49.5 7.4 41.2 223 36-47 21.0 883 57.3 12.0 44.5 186 48-59 15.4 830 51.0 2.9 52.5 128 Sex Male 25.0 2,237 59.5 8.8 46.8 559 Female 23.3 2,351 57.7 8.1 43.0 547 Residence Urban 25.2 2,249 56.6 7.9 45.3 567 Rural 23.0 2,340 60.8 9.0 44.4 538 Region Zambezi 50.2 279 62.5 1.5 46.7 140 Erongo 22.6 320 62.3 15.2 40.9 72 Hardap 15.8 166 (51.1) (1.5) (69.8) 26 //Karas 20.8 160 55.5 6.6 46.7 33 Kavango 36.3 541 62.8 19.9 19.5 196 Khomas 26.3 858 43.6 7.7 54.3 225 Kunene 13.4 170 50.5 1.8 35.3 23 Ohangwena 18.8 561 66.1 4.5 47.3 105 Omaheke 23.4 143 57.5 0.9 33.6 33 Omusati 14.4 440 78.7 14.7 64.7 64 Oshana 17.5 300 (76.4) (1.7) (38.6) 53 Oshikoto 24.1 353 57.2 5.7 61.1 85 Otjozondjupa 16.7 298 47.2 1.6 49.5 50 Mother’s education No education 15.6 281 44.3 6.9 37.6 44 Primary 26.4 1,061 55.0 14.2 35.2 280 Secondary 24.0 2,948 60.6 6.2 48.2 707 More than secondary 24.9 300 62.1 9.4 53.8 75 Wealth quintile Lowest 25.0 988 57.0 12.0 34.1 247 Second 23.2 1,009 56.2 4.9 43.0 234 Middle 24.8 952 65.6 10.4 45.1 236 Fourth 22.2 954 57.1 9.5 52.5 212 Highest 25.8 686 56.8 4.4 53.0 177 Total 24.1 4,588 58.6 8.4 44.9 1,106 Note: Figures in parentheses are based on 25-49 unweighted cases 1 Excludes pharmacy, shop, market, and traditional practitioner 122 • Child Health 11.5 DIARRHOEAL DISEASE Dehydration caused by severe diarrhoea is a major cause of morbidity and mortality among young children. Exposure to diarrhoea-causing agents is often related to the use of contaminated water and to unhygienic practices in food preparation and disposal of excreta. The 2013 NDHS obtained information on the prevalence of diarrhoea among young children by asking mothers whether their children under age 5 had had diarrhoea during the two weeks preceding the survey. When a child was identified as having had diarrhoea, information was collected on treatment and feeding practices during the diarrhoeal episode. The mother was also asked whether there was blood in the child’s stools, which indicates an infection that needs to be treated differently than diarrhoea without blood. 11.5.1 Prevalence of Diarrhoea Table 11.7 shows that 17 percent of children under age 5 had diarrhoea in the two weeks preceding the survey, and 2 percent had blood in their stool. The prevalence of diarrhoea is much higher among children age 6-35 months than among children in the other age groups. Male children are slightly more likely than female children to have had diarrhoea (19 percent versus 16 percent). Diarrhoea is somewhat more prevalent among children in households without an improved source of drinking water (20 percent) than among children from households that do have an improved source of water (17 percent). Similarly, the prevalence of diarrhoea is higher among children whose households do not have an improved toilet facility (20 percent) or share a facility with other households (16 percent) than among children whose households have an improved, unshared toilet facility (13 percent). Rural children are more likely to have had diarrhoea than urban children (20 percent versus 15 percent). The prevalence of diarrhoea varies at the regional level: it is highest in Zambezi and Kavango (32 percent each) and lowest in Hardap (8 percent). The prevalence of diarrhoea with blood by background characteristics follows a pattern similar to that observed for diarrhoea in general. 11.5.2 Treatment of Diarrhoea Table 11.8 shows that 64 percent of children with diarrhoea were taken to a health facility or provider for advice or treatment. Children age 6-23 months, male children, children with bloody diarrhoea, and children from Kavango were more likely than their counterparts to be taken to a health facility or Table 11.7 Prevalence of diarrhoea Percentage of children under age five who had diarrhoea in the two weeks preceding the survey, by background characteristics, Namibia 2013 Diarrhoea in the two weeks preceding the survey Number of children Background characteristic All diarrhoea Diarrhoea with blood Age in months <6 12.2 0.2 500 6-11 30.2 4.6 512 12-23 28.1 3.8 938 24-35 20.5 2.6 926 36-47 9.2 1.1 883 48-59 6.1 0.9 830 Sex Male 18.9 2.3 2,237 Female 16.1 2.2 2,351 Source of drinking water1 Improved 16.7 2.1 3,833 Not improved 20.4 2.5 719 Other/missing (37.4) (11.2) 36 Toilet facility2 Improved, not shared 13.0 1.3 1,241 Shared3 16.2 1.2 633 Non-improved 19.8 2.9 2,709 Residence Urban 14.7 1.6 2,249 Rural 20.1 2.9 2,340 Region Zambezi 32.3 3.0 279 Erongo 10.1 0.4 320 Hardap 7.5 0.3 166 //Karas 9.6 0.7 160 Kavango 31.8 6.0 541 Khomas 16.4 1.3 858 Kunene 12.4 2.8 170 Ohangwena 15.0 2.0 561 Omaheke 14.7 2.3 143 Omusati 19.2 2.8 440 Oshana 10.2 1.5 300 Oshikoto 14.7 1.9 353 Otjozondjupa 14.9 1.6 298 Mother’s education No education 14.3 1.7 281 Primary 22.7 3.3 1,061 Secondary 16.4 2.1 2,948 More than secondary 11.7 0.4 300 Wealth quintile Lowest 23.0 3.8 988 Second 18.9 2.8 1,009 Middle 18.5 1.5 952 Fourth 13.8 1.5 954 Highest 10.9 1.2 686 Total 17.4 2.2 4,588 Note: Total includes 5 children with missing information on toilet facility. Figures in parentheses are based on 25-49 unweighted cases. 1 See Table 2.1 for definition of categories 2 See Table 2.2 for definition of categories 3 Facilities that would be considered improved if they were not shared by two or more households Child Health • 123 provider for treatment, as were children of mothers with a primary education and children from households in the fourth wealth quintile. A simple and effective response to dehydration caused by diarrhoea is oral rehydration therapy (ORT). Oral rehydration salt (ORS) packets are one source of rehydration therapy available in Namibia. Seventy-two percent of children were treated with ORS, 18 percent were given recommended home fluids (RHF), 78 percent were given oral rehydration therapy (that is, either ORS or RHF), 12 percent were given increased fluids, and 79 percent were given ORT or increased fluids. Table 11.8 Diarrhoea treatment Among children under age five who had diarrhoea in the two weeks preceding the survey, the percentage for whom advice or treatment was sought from a health facility or provider, the percentage given oral rehydration therapy (ORT), the percentage given increased fluids, the percentage given ORT or increased fluids, and the percentage given other treatments, by background characteristics, Namibia 2013 Percentage of children with diarrhoea for whom advice or treatment was sought from a health facility or provider1 Oral rehydration therapy (ORT) Increased fluids ORT or increased fluids Other treatments No treatment Number of children with diarrhoea Background characteristic Fluid from ORS packets or pre- packaged ORS fluid Recom- mended home fluids (RHF) Either ORS or RHF Antibiotic medicines Home remedy/ other Age in months <6 61.8 49.4 4.0 49.4 6.7 52.6 19.0 19.8 27.8 61 6-11 65.5 68.5 19.1 79.5 8.8 80.3 20.1 28.1 11.1 155 12-23 65.8 75.8 15.2 79.9 11.6 81.8 22.2 19.3 9.8 263 24-35 60.2 75.9 19.9 82.2 14.0 83.0 17.2 18.6 11.4 190 36-47 63.5 73.4 21.9 77.0 11.7 78.2 13.5 19.5 12.5 81 48-59 63.1 67.3 33.6 75.7 16.6 83.2 20.0 29.2 6.0 51 Sex Male 66.6 71.5 18.4 78.6 13.4 80.6 19.3 22.8 11.3 422 Female 60.5 71.7 17.7 76.2 9.5 77.8 19.3 20.1 12.4 378 Type of diarrhoea Non-bloody 62.6 72.0 18.1 78.4 11.8 80.5 20.4 19.8 11.6 684 Bloody 73.4 73.1 20.3 76.3 9.4 76.5 13.4 32.9 12.3 102 Residence Urban 63.8 75.4 20.0 82.0 14.0 83.7 21.7 18.1 9.4 330 Rural 63.7 69.0 16.7 74.3 9.9 76.3 17.7 23.9 13.6 471 Region Zambezi 63.4 69.7 25.4 80.3 12.6 80.3 16.7 10.3 13.2 90 Erongo (63.5) (69.3) (33.1) (84.4) (15.0) (84.4) (18.5) (29.4) (7.5) 32 Hardap * * * * * * * * * 12 //Karas (55.9) (75.9) (16.3) (75.9) (12.5) (77.2) (20.0) (20.0) (7.4) 15 Kavango 72.0 78.3 21.5 81.2 1.6 81.2 6.2 21.0 12.1 172 Khomas 56.5 75.5 16.1 83.6 15.2 86.3 24.0 14.5 11.7 141 Kunene 53.1 59.4 9.5 65.6 3.8 65.6 12.2 42.7 18.0 21 Ohangwena 67.7 66.5 8.9 66.5 22.0 70.7 18.2 32.3 15.1 84 Omaheke 53.4 82.3 30.3 86.8 7.8 86.8 23.0 17.2 11.3 21 Omusati 70.2 67.1 21.0 76.8 4.3 76.8 35.8 27.7 11.3 85 Oshana (64.0) (78.3) (12.8) (78.3) (13.7) (78.3) (31.7) (30.4) (10.8) 31 Oshikoto (56.7) (64.4) (11.8) (72.4) (23.2) (79.8) (15.4) (21.9) (7.5) 52 Otjozondjupa 57.6 62.7 9.1 64.9 10.3 69.6 27.5 18.2 12.9 44 Mother’s education No education 53.1 61.6 12.3 68.4 5.5 68.4 12.7 22.8 13.7 40 Primary 67.6 70.8 17.8 75.6 8.3 76.9 15.1 21.2 13.9 241 Secondary 63.1 73.7 19.6 80.1 12.8 81.6 22.1 21.1 10.3 485 More than secondary * * * * * * * * * 35 Wealth quintile Lowest 62.4 64.2 18.6 70.2 9.0 72.6 12.5 20.4 18.6 227 Second 62.0 75.4 16.9 82.4 8.8 82.4 16.8 23.0 8.7 191 Middle 64.8 73.2 21.4 79.5 12.1 80.7 21.6 22.3 7.7 177 Fourth 68.7 77.9 18.8 83.7 12.9 84.9 29.6 19.3 8.9 131 Highest 61.3 69.7 10.5 71.4 23.1 78.8 23.2 23.3 14.5 75 Total 63.7 71.6 18.1 77.5 11.6 79.3 19.3 21.5 11.9 800 Note: ORT includes fluid prepared from oral rehydration salt (ORS) packets, pre-packaged ORS fluid, and recommended home fluids (RHF). Total includes 15 children with missing information on type of diarrhoea. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Excludes pharmacy, shop, and traditional practitioner 124 • Child Health Nineteen percent of children with diarrhoea were given antibiotic medicines, and 22 percent were given home remedies or other unspecified drugs. However, about one in ten (12 percent) children with diarrhoea did not receive any treatment at all. 11.5.3 Feeding Practices during Diarrhoea When a child has diarrhoea, mothers are encouraged to continue feeding the child the same amount of food as they would if the child did not have diarrhoea, and they are also encouraged to increase the child’s fluid intake. These practices help to reduce dehydration and minimise the adverse consequences of diarrhoea for the child’s nutritional status. In the 2013 NDHS, mothers were asked whether they gave their child with diarrhoea less, the same amount of, or more fluids and food than usual. Table 11.9 shows the percent distribution of children under age 5 who had diarrhoea in the two weeks preceding the survey by feeding practices, according to background characteristics. Forty-five percent of children with diarrhoea were given the same amount of liquids as usual, and 12 percent were given more. Eighteen percent of children were given somewhat less and 21 percent were given much less to drink than usual. Forty percent of children were given the same amount of food as usual, 4 percent were given more food, 22 percent were given somewhat less food, and 23 percent were given much less food. Five percent of children were not given any food during the diarrhoea episode. Overall, only 8 percent of children had increased fluid intake and continued feeding. Fifty-two percent of children continued feeding and were given ORT and/or increased fluids. 11.6 KNOWLEDGE OF ORS PACKETS To ascertain respondents’ knowledge of ORS in Namibia, women were asked whether they knew about ORS packets. Knowledge was nearly universal, with 96 percent of women knowing about ORS packets or ORS pre-packaged liquids; there was little variation in knowledge by background characteristics (data not shown separately). C hi ld H ea lth • 1 25 Ta bl e 11 .9 F ee di ng p ra ct ic es d ur in g di ar rh oe a P er ce nt d is tri bu tio n of c hi ld re n un de r ag e 5 w ho h ad d ia rr ho ea in th e tw o w ee ks p re ce di ng th e su rv ey b y am ou nt o f l iq ui ds a nd fo od o ffe re d co m pa re d w ith n or m al p ra ct ic e, th e pe rc en ta ge o f c hi ld re n gi ve n in cr ea se d flu id s an d co nt in ue d fe ed in g du rin g th e di ar rh oe a ep is od e, a nd th e pe rc en ta ge o f c hi ld re n w ho c on tin ue d fe ed in g an d w er e gi ve n O R T an d/ or in cr ea se d flu id s du rin g th e ep is od e of d ia rr ho ea , b y ba ck gr ou nd c ha ra ct er is tic s, N am ib ia 2 01 3 A m ou nt o f l iq ui ds g iv en A m ou nt o f f oo d gi ve n P er ce nt ag e gi ve n in cr ea se d flu id s an d co nt in ue d fe ed in g1 P er ce nt ag e w ho co nt in ue d fe ed in g an d w er e gi ve n O R T an d/ or in cr ea se d flu id s1 N um be r of c hi ld re n w ith di ar rh oe a B ac kg ro un d ch ar ac te ris tic M or e S am e as us ua l S om e- w ha t l es s M uc h le ss N on e D on ’t kn ow / m is si ng To ta l M or e S am e as us ua l S om e- w ha t l es s M uc h le ss N on e N ev er ga ve fo od D on ’t kn ow / m is si ng To ta l A ge in m on th s <6 6. 7 65 .5 15 .9 6. 1 5. 8 0. 0 10 0. 0 0. 0 37 .6 17 .3 9. 1 0. 0 35 .9 0. 0 10 0. 0 0. 0 21 .2 61 6- 11 8. 8 39 .1 20 .0 24 .7 6. 7 0. 7 10 0. 0 3. 7 38 .8 20 .9 23 .7 6. 8 5. 6 0. 5 10 0. 0 5. 9 51 .1 15 5 12 -2 3 11 .6 41 .8 18 .5 26 .3 1. 2 0. 5 10 0. 0 3. 6 40 .9 22 .6 23 .6 6. 2 2. 9 0. 2 10 0. 0 9. 3 55 .6 26 3 24 -3 5 14 .0 44 .2 15 .9 22 .8 1. 7 1. 3 10 0. 0 5. 0 40 .5 18 .4 28 .3 5. 7 0. 8 1. 3 10 0. 0 8. 4 52 .1 19 0 36 -4 7 11 .7 49 .3 17 .1 12 .2 6. 1 3. 6 10 0. 0 2. 7 35 .3 32 .7 21 .4 3. 0 2. 5 2. 5 10 0. 0 9. 3 55 .2 81 48 -5 9 16 .6 47 .1 25 .6 8. 4 0. 0 2. 4 10 0. 0 1. 4 51 .3 28 .8 16 .1 0. 0 0. 0 2. 4 10 0. 0 9. 1 67 .4 51 Se x M al e 13 .4 41 .4 19 .5 21 .7 3. 1 0. 9 10 0. 0 4. 1 38 .3 23 .4 23 .9 4. 8 5. 1 0. 4 10 0. 0 8. 3 53 .8 42 2 Fe m al e 9. 5 48 .5 17 .0 20 .3 3. 2 1. 4 10 0. 0 2. 8 42 .4 21 .1 21 .8 5. 2 5. 4 1. 4 10 0. 0 7. 0 49 .9 37 8 Ty pe o f d ia rr ho ea N on -b lo od y 11 .8 46 .1 18 .3 20 .6 2. 7 0. 5 10 0. 0 3. 5 40 .7 22 .9 22 .5 4. 6 5. 5 0. 3 10 0. 0 7. 9 53 .2 68 4 B lo od y 9. 4 39 .2 16 .7 27 .1 6. 6 1. 0 10 0. 0 4. 0 38 .1 19 .7 26 .9 7. 0 4. 4 0. 0 10 0. 0 6. 8 47 .0 10 2 R es id en ce U rb an 14 .0 40 .2 15 .2 26 .7 3. 4 0. 5 10 0. 0 3. 2 40 .2 19 .6 25 .9 5. 9 4. 7 0. 4 10 0. 0 9. 1 52 .0 33 0 R ur al 9. 9 47 .9 20 .5 17 .1 3. 0 1. 6 10 0. 0 3. 6 40 .3 24 .2 20 .8 4. 3 5. 6 1. 2 10 0. 0 6. 7 52 .0 47 1 R eg io n Za m be zi 12 .6 46 .0 20 .9 18 .7 1. 8 0. 0 10 0. 0 4. 4 34 .4 30 .1 22 .0 1. 3 7. 6 0. 0 10 0. 0 10 .9 54 .6 90 E ro ng o (1 5. 0) (3 7. 1) (2 .3 ) (3 9. 9) (5 .7 ) (0 .0 ) 10 0. 0 (9 .5 ) (3 3. 3) (7 .8 ) (3 5. 7) (6 .1 ) (7 .7 ) (0 .0 ) 10 0. 0 (1 0. 7) (4 2. 9) 32 H ar da p * * * * * * 10 0. 0 * * * * * * * 10 0. 0 * * 12 //K ar as (1 2. 5) (4 3. 4) (6 .5 ) (1 9. 7) (7 .3 ) (1 0. 7) 10 0. 0 (2 .6 ) (4 1. 1) (1 9. 4) (2 0. 8) (2 .8 ) (2 .6 ) (1 0. 7) 10 0. 0 (9 .8 ) (5 0. 8) 15 K av an go 1. 6 54 .3 27 .7 14 .3 0. 9 1. 2 10 0. 0 0. 7 48 .7 27 .4 12 .4 1. 5 8. 0 1. 2 10 0. 0 0. 6 61 .2 17 2 K ho m as 15 .2 36 .9 15 .0 28 .7 4. 1 0. 0 10 0. 0 4. 0 36 .5 19 .0 31 .0 6. 5 2. 9 0. 0 10 0. 0 9. 4 49 .5 14 1 K un en e 3. 8 54 .7 14 .6 26 .9 0. 0 0. 0 10 0. 0 1. 6 50 .0 14 .9 23 .3 5. 0 5. 2 0. 0 10 0. 0 1. 6 45 .9 21 O ha ng w en a 22 .0 40 .5 10 .1 24 .3 1. 6 1. 4 10 0. 0 5. 3 35 .8 16 .8 37 .3 1. 6 1. 6 1. 4 10 0. 0 16 .4 38 .8 84 O m ah ek e 7. 8 44 .5 21 .0 21 .2 4. 5 1. 0 10 0. 0 3. 2 43 .7 19 .6 22 .3 8. 9 2. 3 0. 0 10 0. 0 7. 8 55 .1 21 O m us at i 4. 3 41 .5 27 .6 14 .5 10 .7 1. 4 10 0. 0 0. 0 35 .9 27 .8 16 .2 14 .5 4. 2 1. 4 10 0. 0 0. 0 50 .9 85 O sh an a (1 3. 7) (3 2. 0) (6 .6 ) (4 4. 2) (3 .5 ) (0 .0 ) 10 0. 0 (3 .4 ) (2 7. 4) (2 3. 8) (3 5. 7) (3 .5 ) (6 .3 ) (0 .0 ) 10 0. 0 (1 0. 5) (4 4. 1) 31 O sh ik ot o (2 3. 2) (4 0. 3) (2 1. 1) (8 .3 ) (1 .9 ) (5 .3 ) 10 0. 0 (2 .8 ) (3 7. 6) (2 4. 6) (1 9. 5) (8 .3 ) (5 .7 ) (1 .6 ) 10 0. 0 (9 .9 ) (5 4. 5) 52 O tjo zo nd ju pa 10 .3 60 .4 9. 6 19 .6 0. 0 0. 0 10 0. 0 1. 8 58 .3 14 .4 14 .2 5. 7 5. 7 0. 0 10 0. 0 9. 1 53 .9 44 M ot he r’s e du ca tio n N o ed uc at io n 5. 5 65 .2 11 .7 15 .2 0. 0 2. 4 10 0. 0 4. 6 50 .0 13 .4 22 .8 2. 8 6. 4 0. 0 10 0. 0 0. 0 45 .8 40 P rim ar y 8. 3 46 .0 24 .3 16 .6 3. 4 1. 5 10 0. 0 2. 2 38 .3 29 .3 20 .1 4. 9 3. 8 1. 4 10 0. 0 5. 0 51 .9 24 1 S ec on da r y 12 .8 43 .0 16 .7 23 .0 3. 4 0. 9 10 0. 0 4. 3 40 .9 19 .6 23 .1 5. 4 6. 0 0. 7 10 0. 0 9. 3 53 .3 48 5 M or e th an s ec on da ry * * * * * * 10 0. 0 * * * * * * * 10 0. 0 * * 35 W ea lth q ui nt ile Lo w es t 9. 0 46 .9 23 .1 18 .6 1. 6 0. 7 10 0. 0 4. 7 37 .7 25 .5 23 .5 2. 7 5. 2 0. 7 10 0. 0 5. 8 50 .3 22 7 S ec on d 8. 8 48 .5 20 .3 17 .6 3. 0 1. 9 10 0. 0 2. 3 47 .7 18 .4 19 .5 6. 4 4. 5 1. 3 10 0. 0 5. 4 54 .4 19 1 M id dl e 12 .1 44 .1 14 .7 22 .6 5. 4 1. 2 10 0. 0 2. 7 35 .6 24 .6 23 .3 6. 2 6. 4 1. 2 10 0. 0 8. 0 50 .4 17 7 Fo ur th 12 .9 42 .5 17 .4 24 .0 2. 5 0. 7 10 0. 0 5. 1 43 .3 18 .5 22 .2 7. 0 3. 9 0. 0 10 0. 0 10 .3 57 .0 13 1 H i g he st 23 .1 34 .2 8. 6 28 .8 4. 2 1. 1 10 0. 0 1. 7 34 .7 23 .6 30 .2 2. 0 6. 6 1. 1 10 0. 0 13 .8 45 .7 75 To ta l 11 .6 44 .8 18 .3 21 .1 3. 2 1. 1 10 0. 0 3. 5 40 .2 22 .3 22 .9 5. 0 5. 2 0. 9 10 0. 0 7. 7 52 .0 80 0 N ot e: I t is r ec om m en de d th at c hi ld re n be g iv en m or e liq ui ds t o dr in k du rin g di ar rh oe a an d th at f oo d no t be r ed uc ed . To ta l i nc lu de s 15 c hi ld re n w ith m is si ng in fo rm at io n on t yp e of d ia rr ho ea . Fi gu re s in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 1 C on tin ue d fe ed in g pr ac tic es in cl ud es c hi ld re n w ho w er e gi ve n m or e, th e sa m e as u su al , o r s om ew ha t l es s fo od d ur in g th e di ar rh oe a ep is od e. Child Health • 125 126 • Child Health 11.7 DISPOSAL OF CHILDREN’S STOOLS The proper disposal of children’s faeces is important in preventing the spread of disease. If faeces are left uncontained, disease may spread by direct contact or through animal contact. Children’s stools are considered to be safely disposed of if the child uses a toilet or latrine, the child’s stool is put or rinsed into a toilet or latrine, or the stool is buried. Table 11.10 presents information on disposal of children’s stools, according to background characteristics. Overall, 51 percent of children had their last stool disposed of safely. Stools for 5 percent of children are put or rinsed into a drain or ditch, 26 percent are thrown into the garbage, and 12 percent are left in the open. Children in rural areas were more likely than those in urban areas to have had their last stool safely disposed of (54 percent and 48 percent, respectively). Table 11.10 Disposal of children’s stools Percent distribution of youngest children under age five living with their mother by the manner of disposal of the child’s last faecal matter, and percentage of children whose stools are disposed of safely, according to background characteristics, Namibia 2013 Manner of disposal of children’s stools Total Percentage of children whose stools are disposed of safely1 Number of children Background characteristic Child used toilet or latrine Put/rinsed into toilet or latrine Buried Put/rinsed into drain or ditch Thrown into garbage Left in the open Other Missing Age in months <6 3.0 9.3 25.7 11.3 40.2 2.5 7.5 0.5 100.0 38.0 487 6-11 3.0 8.5 35.8 7.1 33.4 5.5 6.2 0.6 100.0 47.3 481 12-23 5.2 7.4 37.3 4.7 31.2 11.3 2.3 0.4 100.0 49.9 753 24-35 11.8 11.6 32.2 2.4 19.2 16.1 5.0 1.7 100.0 55.6 585 36-47 20.3 12.6 25.2 1.3 14.4 20.8 3.9 1.5 100.0 58.1 407 48-59 29.8 11.9 20.1 0.8 10.5 21.1 5.3 0.5 100.0 61.8 329 Toilet facility2 Improved, not shared 23.3 21.0 9.7 4.0 35.0 3.6 2.3 1.1 100.0 54.0 853 Shared3 16.7 16.5 12.6 5.1 38.5 4.5 5.3 0.7 100.0 45.9 373 Non-improved or shared 3.1 3.2 44.5 5.1 19.5 17.8 5.9 0.8 100.0 50.8 1,812 Residence Urban 17.9 16.4 13.4 4.9 36.1 7.1 3.3 0.9 100.0 47.7 1,445 Rural 3.7 4.0 46.5 4.8 17.2 16.9 6.2 0.8 100.0 54.2 1,596 Region Zambezi 2.2 5.7 38.6 7.3 27.9 14.4 3.3 0.6 100.0 46.5 206 Erongo 25.3 19.8 3.0 0.7 42.9 6.9 0.6 0.8 100.0 48.0 199 Hardap 11.9 8.9 4.9 13.1 41.5 17.5 2.2 0.0 100.0 25.7 119 //Karas 22.5 12.1 6.9 13.6 36.3 5.9 1.7 0.9 100.0 41.6 102 Kavango 1.1 3.0 55.3 3.3 19.8 9.8 7.2 0.5 100.0 59.4 400 Khomas 20.8 17.2 5.6 2.8 41.1 5.4 6.2 0.9 100.0 43.7 544 Kunene 7.8 5.8 34.6 4.7 31.7 13.8 1.0 0.6 100.0 48.2 106 Ohangwena 7.3 1.6 48.6 6.3 14.3 12.3 9.2 0.4 100.0 57.6 349 Omaheke 6.3 17.1 40.8 6.4 13.8 9.2 1.4 5.2 100.0 64.1 89 Omusati 6.3 2.6 48.3 3.2 15.9 20.5 2.0 1.3 100.0 57.2 295 Oshana 10.6 12.0 26.6 3.3 18.3 27.1 1.1 1.0 100.0 49.2 193 Oshikoto 4.4 8.7 43.4 6.0 13.1 15.1 8.9 0.4 100.0 56.4 241 Otjozondjupa 9.6 21.0 22.2 5.0 27.8 9.2 4.0 1.2 100.0 52.8 200 Mother’s education No education 3.1 5.8 49.0 2.7 14.3 15.6 7.4 2.0 100.0 58.0 193 Primary 4.2 4.7 42.9 4.6 21.8 15.3 5.2 1.3 100.0 51.8 687 Secondary 11.4 10.4 27.6 5.6 28.2 11.8 4.4 0.6 100.0 49.5 1,945 More than secondary 28.1 24.9 4.1 0.8 32.8 3.2 5.0 1.2 100.0 57.0 217 Wealth quintile Lowest 2.3 1.6 51.0 3.9 16.4 15.8 8.4 0.6 100.0 54.9 676 Second 1.6 4.1 42.2 5.5 21.2 19.7 4.7 1.0 100.0 47.9 681 Middle 6.4 8.7 34.6 5.7 24.1 15.0 4.9 0.5 100.0 49.8 618 Fourth 16.9 19.3 14.1 5.4 34.4 5.8 3.1 1.1 100.0 50.3 598 Highest 32.2 19.7 1.0 3.3 40.0 0.7 1.9 1.2 100.0 52.9 468 Total 10.5 9.9 30.7 4.8 26.2 12.2 4.8 0.9 100.0 51.1 3,042 Note: Total includes 4 children with missing information on toilet facility. 1 Children’s stools are considered to be disposed of safely if the child used a toilet or latrine, if the faecal matter was put/rinsed into a toilet or latrine, or if it was buried. 2 See Table 2.2 for definition of categories. 3 Facilities that would be considered improved if they were not shared by 2 or more households Child Health • 127 At the regional level, there are wide variations in the proportion of children whose last stool was disposed of properly. For example, 64 percent of children in Omaheke had their stools disposed of safely, as compared with only 26 percent of children from Hardap. There are no substantial differences by mother’s education or wealth quintile in safe disposal of children’s stools. Nutrition of Children and Adults • 129 NUTRITION OF CHILDREN AND ADULTS 12 his chapter presents findings on the nutritional status of adults and children in Namibia. A specific focus is infant and young child feeding practices, including early initiation of breastfeeding, exclusive breastfeeding during the first six months of life, continued breastfeeding until at least age 2, timely introduction of complementary foods at age 6 months (with increasing frequency of feeding solid and semisolid foods), and diet diversity. Data on nutritional status, diversity of foods consumed, micronutrient intake, and vitamin A supplementation are presented for women and for children under age 5, along with the results of household testing of salt for adequate levels of iodine. A summary indicator that describes the quality of infant and young child feeding (IYCF) practices for infants age 6-23 months is included. Findings on the prevalence of anaemia among children age 6-59 months and women and men age 15-49 are also presented. Good nutrition is a basic building block of human capital and, as such, contributes to economic development. Adequate nutrition is critical to child development, with the period from birth to age 2, referred to as the critical window of opportunity, being important for optimal growth, health, and development. Unfortunately, this period is often marked by growth faltering, micronutrient deficiencies, and common childhood illnesses such as malaria, diarrhoea, and acute respiratory infections. A woman’s nutritional status has important implications for her health as well as the health of her children. Malnutrition in women results in reduced productivity, an increased susceptibility to infections, slow recovery from illness, and heightened risks of adverse pregnancy outcomes. For example, a woman who has poor nutritional status, as indicated by a low body mass index (BMI), short stature, anaemia, or other micronutrient deficiencies, has a greater risk of obstructed labour, of having a baby with a low birth T Key Findings • Among Namibian children under age 5 at the time of the survey, 24 percent were stunted (short for their age), 6 percent were wasted (thin for their height), and 13 percent were underweight (thin for their age). Only 3 percent of children were overweight (heavy for their height). • Almost all children (96 percent) are breastfed at some point in their life. Forty-nine percent of children under age 6 months are exclusively breastfed. Sixty-two percent of children age 6-9 months are breastfeeding and consuming complementary foods. • The median duration of breastfeeding is 14.7 months. • Only 13 percent of children age 6-23 months are fed in accordance with the three core infant and young child feeding (IYCF) practices. • Eighty-four percent of Namibian children age 6-59 months received vitamin A supplements in the six months prior to the survey, 43 percent received deworming medication in the preceding six months, and 76 percent live in households with iodised salt. • Overall, 55 percent of women and 65 percent of men have a body mass index (BMI) in the normal range. Three in ten women and one in ten men are overweight or obese. • Among women age 15-49 with a child born in the past five years, 58 percent received a vitamin A dose postpartum; during the pregnancy of their last birth, 39 percent of women took iron tablets for the recommended period of time, while only 7 percent took deworming medication. 130 • Nutrition of Children and Adults weight, of producing lower quality breast milk, of mortality due to postpartum haemorrhage, and of morbidity for both herself and her baby. 12.1 NUTRITIONAL STATUS OF CHILDREN The anthropometric data on height and weight collected in the 2013 NDHS permit the measurement and evaluation of the nutritional status of young children in Namibia. This evaluation allows identification of subgroups of the child population that are at increased risk of growth faltering, diseases, impaired mental development, and death. Marked differences, especially with regard to height-for-age, weight-for-height, and weight-for-age, are often seen among different subgroups of children within the country. 12.1.1 Measurement of Nutritional Status among Young Children The 2013 NDHS collected data on the nutritional status of children by measuring the height and weight of all children under age 5. Data were collected with the aim of calculating three indices—namely, weight-for-age, height-for-age, and weight-for-height—all of which take age and sex into consideration. Weight measurements were obtained using lightweight, bathroom-type scales with a digital screen designed and manufactured under the guidance of UNICEF. Height measurements were carried out using a measuring board. Children younger than age 24 months were measured lying down (recumbent length) on the board, while standing height was measured for older children. For this report, indicators of the nutritional status of children were calculated using growth standards published by WHO in 2006. These growth standards were generated through data collected in the WHO Multicentre Growth Reference Study (WHO, 2006a). That study, whose sample included 8,440 children in six countries, was designed to provide a description of how children should grow under optimal conditions. The WHO child growth standards can therefore be used to assess children all over the world, regardless of ethnicity, social and economic influences, and feeding practices. The three nutritional status indicators described below are expressed in standard deviation units from the median of the Multicentre Growth Reference Study sample. Each of these indices provides different information about growth and body composition. The height-for-age index is an indicator of linear growth retardation and cumulative growth deficits. Children whose height-for-age Z-score is below minus two standard deviations (-2 SD) from the median of the WHO reference population are considered short for their age (stunted) and are chronically malnourished. Children who are below minus three standard deviations (-3 SD) from the reference median are considered severely stunted. Stunting reflects failure to receive adequate nutrition over a long period of time and is affected by recurrent and chronic illness. Height-for-age, therefore, represents the long-term effects of malnutrition in a population and is not sensitive to recent, short-term changes in dietary intake. The weight-for-height index measures body mass in relation to height or length and describes current nutritional status. Children whose Z-scores are below minus two standard deviations (-2 SD) from the reference median are considered thin (wasted) and are acutely malnourished. Wasting represents the failure to receive adequate nutrition in the period immediately preceding the survey and may be the result of inadequate food intake or a recent episode of illness causing loss of weight and the onset of malnutrition. Children whose weight-for-height is below minus three standard deviations (-3 SD) from the reference median are considered severely wasted. Overweight and obesity are becoming problems for some children in developing countries. Children who are more than two standard deviations (+2 SD) above the median for weight-for-height are considered overweight or obese. Weight-for-age is a composite index of height-for-age and weight-for-height. It takes into account both acute and chronic malnutrition. Children whose weight-for-age is below minus two standard deviations (-2 SD) from the reference median are classified as underweight. Children whose weight-for- Nutrition of Children and Adults • 131 age is below minus three standard deviations (-3 SD) from the reference median are considered severely underweight. 12.1.2 Data Collection Height and weight measurements were obtained for 2,287 children under age 5 who were present in the households selected for the NDHS at the time of the survey. The following analysis focuses on children for whom complete and credible anthropometric data and valid age data were collected. Although data were collected for all children under age 6, for purposes of comparability, the analysis is limited to children under age 5. Height and weight measurements were obtained for 80 percent of the 2,856 eligible children (unweighted). Height and weight were missing for 7 percent of children, the data for 12 percent were flagged (out-of-range), and 1 percent had incomplete information on age in months. 12.1.3 Levels of Child Malnutrition Table 12.1 and Figure 12.1 show the percentage of children under age 5 classified as malnourished according to the three anthropometric indices of nutritional status (height-for-age, weight- for-height, and weight-for-age), by background characteristics. Nationally, 24 percent of children under age 5 are stunted, and 8 percent are severely stunted. The percentage of children who are stunted initially increases with age, from 1 percent among children age 6-8 months to 35 percent among those age 24-35 months, before declining steadily to reach 21 percent among children age 48-59 months. Severe stunting shows a similar trend, with children age 24-35 months most likely (14 percent) and those below 9 months least likely (2 percent) to be severely stunted. Twenty-seven percent of male children are stunted, as compared with 21 percent of female children. Children with a preceding birth interval of 48 months or more have a lower prevalence of stunting (19 percent) than children with shorter preceding birth intervals (23-26 percent). As expected, children whose size at birth was reported as very small by their mothers are most likely to be stunted (40 percent). The mother’s body mass index has an inverse relationship with stunting levels. For example, 28 percent of children of mothers who are thin (BMI less than 18.5) are stunted, as compared with 15 percent of children whose mothers are overweight or obese (BMI of 25 or above). Children in rural areas are much more likely than those in urban areas to be stunted (28 percent and 17 percent, respectively). By region, Ohangwena (37 percent) has the highest proportion of stunted children, while Khomas has the lowest (13 percent). Mother’s level of education has an inverse relationship with stunting. For example, children of mothers with more than a secondary education are least likely to be stunted (9 percent), whereas children whose mothers have no education are most likely to be stunted (34 percent). A similar inverse relationship is observed between household wealth and stunting, with children living in households in the poorest wealth quintile having the highest prevalence of stunting (31 percent). Variations in severe stunting among children under age 5 by background characteristics follow the same patterns as those for moderate stunting. 132 • Nutrition of Children and Adults Table 12.1 Nutritional status of children Percentage of children under age 5 classified as malnourished according to three anthropometric indices of nutritional status: height-for-age, weight-for-height, and weight-for-age, by background characteristics, Namibia 2013 Height-for-age1 Weight-for-height Weight-for-age Number of children Background characteristic Percent- age below -3 SD Percent- age below -2 SD2 Mean Z-score (SD) Percent- age below -3 SD Percent- age below -2 SD2 Percent- age above +2 SD Mean Z-score (SD) Percent- age below -3 SD Percent- age below -2 SD2 Percent- age above +2 SD Mean Z-score (SD) Age in months <6 (0.0) (0.0) (-0.9) (8.2) (17.3) (3.2) (0.9) (0.0) (3.4) (4.9) (-0.1) 37 6-8 0.0 1.3 0.4 2.5 11.7 0.0 -0.6 0.0 5.5 1.4 -0.2 120 9-11 2.1 5.4 0.0 8.6 18.7 3.9 -0.8 2.5 12.3 1.9 -0.5 122 12-17 5.2 19.8 -0.9 3.8 9.7 3.0 -0.4 3.1 12.7 2.4 -0.6 248 18-23 11.8 29.9 -1.2 2.7 11.8 3.1 -0.5 2.7 13.0 0.8 -0.8 248 24-35 13.5 34.7 -1.5 1.4 3.4 5.1 0.1 3.3 15.0 0.0 -0.8 566 36-47 8.6 25.1 -1.3 0.7 2.4 3.7 0.0 2.7 13.0 1.0 -0.9 474 48-59 5.3 20.5 -1.2 0.5 3.1 2.1 -0.2 2.3 15.4 0.2 -1.0 472 Sex Male 9.0 26.6 -1.2 3.1 8.6 3.1 -0.2 2.9 15.3 0.9 -0.8 1,140 Female 7.3 21.0 -1.0 0.9 3.9 3.7 -0.2 2.3 11.4 0.9 -0.7 1,147 Birth interval in months3 First birth4 7.5 21.8 -0.9 1.3 4.1 3.6 -0.1 1.3 9.9 1.1 -0.6 460 <24 8.4 22.8 -1.2 2.1 10.5 3.5 -0.3 3.3 17.6 0.5 -0.9 150 24-47 9.2 26.0 -1.2 3.1 9.6 3.5 -0.4 4.2 16.7 1.1 -1.0 400 48+ 6.1 19.1 -0.9 2.3 8.7 3.3 -0.3 2.9 13.5 0.7 -0.7 511 Size at birth3 Very small 21.6 40.4 -1.7 4.3 17.1 1.5 -0.5 10.3 34.7 0.0 -1.4 93 Small 10.2 30.1 -1.3 3.1 13.8 2.3 -0.6 4.9 20.3 0.0 -1.2 207 Average or larger 5.9 19.3 -0.9 1.9 6.0 3.9 -0.2 1.9 10.8 1.1 -0.6 1,201 Mother's interview status Interviewed 7.6 22.1 -1.0 2.2 7.7 3.5 -0.3 2.8 13.7 0.9 -0.8 1,521 Not interviewed but in household 4.4 16.8 -0.9 2.1 2.1 1.3 0.0 0.0 6.3 0.0 -0.6 105 Not interviewed and not in the household5 10.2 28.8 -1.3 1.6 3.5 3.6 -0.1 2.5 13.8 0.9 -0.9 660 Mother's nutritional status6 Thin (BMI <18.5) 10.9 28.0 -1.2 2.0 9.8 0.3 -0.6 6.3 17.5 0.3 -1.1 158 Normal (BMI 18.5-24.9) 8.0 24.5 -1.1 2.7 8.6 2.9 -0.4 2.7 15.8 0.4 -0.9 795 Overweight/obese (BMI ≥25) 4.8 14.6 -0.8 0.9 5.0 4.5 0.1 1.6 9.4 1.4 -0.4 413 Residence Urban 5.2 16.7 -0.8 1.6 5.0 4.1 0.0 1.4 9.1 1.5 -0.5 836 Rural 9.9 27.8 -1.2 2.2 6.9 3.0 -0.3 3.3 15.8 0.5 -0.9 1,451 Region Zambezi 5.4 18.6 -1.0 2.1 5.7 2.0 -0.1 0.9 10.5 1.3 -0.7 150 Erongo 4.5 15.2 -0.7 4.6 8.1 6.5 0.1 0.9 9.9 2.0 -0.3 119 Hardap 10.8 29.1 -1.1 2.6 8.2 3.7 -0.2 5.7 17.8 0.8 -0.8 85 //Karas 9.8 27.0 -1.1 1.4 5.6 3.2 -0.1 1.5 12.1 1.5 -0.7 69 Kavango 8.9 23.9 -1.1 1.4 8.5 1.7 -0.4 2.3 15.0 0.4 -0.9 259 Khomas 5.2 12.8 -0.8 0.7 3.5 3.6 0.0 1.1 9.1 0.9 -0.5 265 Kunene 5.1 19.4 -0.9 1.0 6.1 4.2 -0.3 2.4 11.9 2.9 -0.7 93 Ohangwena 13.9 36.5 -1.5 1.8 5.4 2.3 -0.3 4.3 16.3 0.0 -1.1 371 Omaheke 7.7 26.9 -1.2 3.3 10.4 5.3 -0.3 5.2 18.1 1.6 -0.9 73 Omusati 8.8 24.2 -1.3 2.4 6.0 2.4 -0.4 1.9 14.6 0.5 -1.0 283 Oshana 5.6 19.8 -0.9 2.1 4.5 7.4 0.0 1.3 8.2 1.1 -0.5 169 Oshikoto 7.6 26.3 -1.1 3.8 8.5 1.7 -0.6 5.2 20.7 0.6 -1.1 204 Otjozondjupa 6.2 20.1 -0.9 0.5 4.3 5.7 0.2 1.5 6.5 1.7 -0.4 147 Mother's education7 No education 9.0 33.8 -1.4 6.9 14.8 1.6 -0.6 6.1 22.7 1.4 -1.2 121 Primary 11.2 29.0 -1.3 2.6 7.9 2.8 -0.4 4.9 18.3 0.3 -1.1 383 Secondary 6.0 18.8 -0.9 1.6 6.9 3.4 -0.2 1.6 10.9 1.0 -0.6 1,030 More than secondary 4.1 8.5 -0.5 0.4 0.4 6.5 0.3 0.6 5.6 0.7 -0.1 91 Wealth quintile Lowest 11.6 31.3 -1.4 3.6 9.2 2.2 -0.5 4.3 18.9 0.5 -1.1 587 Second 10.8 28.8 -1.3 1.8 5.6 2.0 -0.2 2.9 15.1 0.1 -0.9 510 Middle 8.0 24.2 -1.1 1.3 7.0 3.9 -0.2 2.5 13.6 0.7 -0.8 466 Fourth 4.3 16.8 -0.8 1.7 3.7 5.5 0.0 1.6 9.0 0.9 -0.5 468 Highest 2.5 8.7 -0.4 0.9 3.9 4.3 0.2 0.3 4.9 3.7 -0.1 256 Total 8.2 23.8 -1.1 2.0 6.2 3.4 -0.2 2.6 13.4 0.9 -0.8 2,287 Note: Table is based on children who stayed in the household on the night before the interview. Each of the indices is expressed in standard deviation units (SD) from the median of the WHO child growth standards adopted in 2006. The indices in this table are NOT comparable to those based on the previously used NCHS/CDC/WHO reference. Table is based on children with valid dates of birth (month and year) and valid measurement of both height and weight. Total includes 20 children with missing information on size at birth and 2 children with missing information on mother’s education. Figures in parentheses are based on 25-49 unweighted cases. 1 Recumbent length is measured for children under age 2 and in the few cases when the age of the child is unknown and the child is less than 85 cm; standing height is measured for all other children. 2 Includes children who are below -3 standard deviations (SD) from the WHO Child Growth standards population median 3 Excludes children whose mothers were not interviewed 4 First-born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval 5 Includes children whose mothers are deceased 6 Excludes children whose mothers were not weighed and measured, children whose mothers were not interviewed, and children whose mothers are pregnant or gave birth within the preceding 2 months. Mother's nutritional status in terms of BMI (body mass index) is presented in Table 12.10.1. 7 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. Nutrition of Children and Adults • 133 Figure 12.1 Nutritional status of children by age Table 12.1 also shows the nutritional status of children under age 5 as measured by wasting (low weight-for-height). Overall, 6 percent of children are wasted and 2 percent are severely wasted. Children age 9-11 months (19 percent), male children (9 percent), those with a preceding birth interval of less than 24 months (11 percent), those with a very small size at birth (17 percent), and those living in Omaheke (10 percent) have the highest levels of wasting. The prevalence of wasting decreases with increasing mother’s education, from 15 percent among children whose mothers have no education to less than 1 percent among children whose mothers have more than a secondary education. The data further show that children living in the poorest households have the highest prevalence of wasting (9 percent). Finally, 13 percent of children under age 5 are underweight (low weight-for-age) and 3 percent are severely underweight (Table 12.1). The proportion of underweight children increases substantially with age, from 6 percent among children age 6-8 months to 12-15 percent among older children, which might be explained by the fact that with the transition to complementary foods older children may not be getting the recommended types of food or the minimum meal frequency. Older children are also more exposed to the environment, thus increasing their exposure to infections and susceptibility to illness. Male children (15 percent) are slightly more likely to be underweight than female children (11 percent). The percentage of underweight children decreases as the preceding birth interval lengthens. Eighteen percent of children whose mothers are thin (BMI less than 18.5) are underweight, as compared with 9 percent of those whose mothers are overweight or obese (BMI of 25 or above). Rural children are more likely to be underweight (16 percent) than urban children (9 percent). Oshikoto has the highest proportion of underweight children (21 percent), while Otjozondjupa has the lowest proportion (7 percent). The proportion of underweight children is inversely associated with mother’s level of education and household wealth. 12.1.4 Trends in Child Malnutrition Figure 12.2 presents trends in the nutritional status of children under age 5 in Namibia over the last six years. The results show that the proportions of children who are stunted, wasted, and underweight decreased between the 2006-07 NDHS and 2013 NDHS surveys. 134 • Nutrition of Children and Adults Figure 12.2 Trends in nutritional status of children under age 5 by period 12.2 INITIATION OF BREASTFEEDING Early breastfeeding practices determine the successful establishment and duration of breastfeeding. Moreover, during the first three days after delivery, colostrum, an important source of nutrition and protection for the newborn, is produced and should be given to the newborn while awaiting the let-down of regular/mature breast milk. Thus, it is recommended that children be put to the breast immediately or within one hour after birth and that prelacteal feeding (i.e., feeding newborns anything other than breast milk before breast milk is initiated) be discouraged. Table 12.2 shows the percentage of children born in the two years before the survey by breastfeeding status and the timing of initial breastfeeding, according to background characteristics. The results indicate that 96 percent of children are breastfed at some point. Differences by background characteristics are small. Seventy-one percent of children are breastfed within one hour of birth and 89 percent within one day after delivery. The proportion of children breastfed within one hour of birth is lower among those delivered in a health facility (71 percent) than among those born at home (77 percent). The likelihood of an infant breastfeeding within one hour of birth varies markedly by region from 59 percent in Oshana to 80 percent in Zambezi. The practice of giving prelacteal feeds limits the frequency of suckling by the infant and exposes the baby to the risk of infection. Table 12.2 shows that 10 percent of children who had ever been breastfed received prelacteal feeds. Prelacteal feeding is most common among children whose delivery was assisted by a traditional birth attendant (20 percent), those born at home (15 percent), and those living in urban areas (11 percent). By region, Omusati has the lowest percentage of children who received a prelacteal feed (2 percent), and Kavango has the highest percentage (19 percent). The proportion of children who receive a prelacteal feed does not have a clear correlation with mother’s education. Prelacteal feeding is least common among children whose mothers have no education (5 percent) and most common among children whose mothers have more than a secondary education (19 percent). The proportion of children who receive a prelacteal feed is highest among those in the wealthiest households (16 percent). 29 8 17 24 6 13 Stunting Wasting Underweight Percentage 2006-07 NDHS 2013 NDHS Note: Stunting reflects chronic malnutrition; wasting reflects acute malnutrition; underweight reflects chronic or acute malnutrition or a combination of both. Nutrition of Children and Adults • 135 Table 12.2 Initial breastfeeding Among last-born children who were born in the two years preceding the survey, the percentage who were ever breastfed and the percentages who started breastfeeding within one hour and within one day of birth, and among last-born children born in the two years preceding the survey who were ever breastfed, the percentage who received a prelacteal feed, by background characteristics, Namibia 2013 Among last-born children born in the past two years: Among last-born children born in the past two years who were ever breastfed: Background characteristic Percentage ever breastfed Percentage who started breastfeeding within 1 hour of birth Percentage who started breastfeeding within 1 day of birth1 Number of last-born children Percentage who received a prelacteal feed2 Number of last-born children ever breastfed Sex Male 95.4 72.2 88.4 941 9.8 898 Female 96.0 70.3 89.7 1,006 10.6 966 Assistance at delivery Health professional3 95.4 70.9 89.0 1,732 9.6 1,653 Traditional birth attendant 98.7 72.5 84.1 81 20.4 80 Other 97.6 74.6 92.6 115 13.3 113 No one * * * 18 * 17 Place of delivery Health facility 95.4 70.6 88.9 1,715 9.6 1,637 At home 97.8 76.9 89.7 226 14.5 221 Other * * * 5 * 5 Residence Urban 94.4 69.6 87.9 925 10.9 874 Rural 96.9 72.6 90.1 1,022 9.6 990 Region Zambezi 91.6 79.5 89.9 112 12.5 103 Erongo 91.2 67.0 83.9 136 15.0 124 Hardap 95.4 76.5 90.0 73 3.9 70 //Karas 93.6 75.9 90.3 61 18.0 58 Kavango 96.9 77.6 82.9 231 19.4 224 Khomas 95.6 68.6 88.1 344 10.4 329 Kunene 95.7 74.6 84.7 69 12.8 66 Ohangwena 97.1 65.4 93.0 254 2.9 246 Omaheke 96.7 69.7 90.8 59 14.8 57 Omusati 96.1 75.9 93.9 189 2.3 181 Oshana 96.6 59.1 87.4 127 12.6 123 Oshikoto 96.5 69.0 89.5 154 11.0 149 Otjozondjupa 97.7 76.5 93.6 137 6.1 133 Mother's education No education 93.2 73.7 87.3 110 5.4 102 Primary 96.8 74.5 90.7 438 10.8 424 Secondary 95.7 70.9 88.8 1,295 9.7 1,240 More than secondary 93.7 59.1 87.5 105 19.3 98 Wealth quintile Lowest 96.7 73.7 88.6 415 12.7 402 Second 96.7 70.8 90.1 439 6.4 425 Middle 95.9 75.5 91.3 423 8.3 406 Fourth 95.3 68.7 88.9 389 9.9 370 Highest 93.1 65.4 85.0 281 15.9 261 Total 95.7 71.2 89.1 1,947 10.2 1,864 Note: Table is based on last-born children born in the 2 years preceding the survey regardless of whether the children were living or dead at the time of the interview. Total includes 1 child with missing information on assistance at delivery. 1 Includes children who started breastfeeding within 1 hour of birth 2 Children given something other than breast milk during the first 3 days of life 3 Doctor or nurse/midwife 12.3 BREASTFEEDING STATUS BY AGE UNICEF and WHO recommend that children be exclusively breastfed during the first six months of life and that they be given age-appropriate solid or semisolid complementary food in addition to continued breastfeeding from age 6 months to at least age 24 months. Exclusive breastfeeding is recommended because breast milk is uncontaminated and contains all of the nutrients necessary for children in the first few months of life. In addition, the mother’s antibodies in breast milk provide immunity to diseases or infections. Early supplementation is discouraged for several reasons. First, it exposes infants to pathogens and increases their risk of infection. Second, it decreases infants’ intake of breast milk and therefore suckling, which reduces breast milk production. Third, in low-resource settings, supplementary food is often nutritionally inferior. 136 • Nutrition of Children and Adults Information on complementary feeding was obtained by asking mothers about the current breastfeeding status of all children under age 5 and, for the youngest child born in the three-year period before the survey and living with the mother, the foods and liquids given to the child the day and night before the survey. Table 12.3 shows breastfeeding practices by child’s age. Only 49 percent of infants under age 6 months are exclusively breastfed. Contrary to the recommendation that children under age 6 months be exclusively breastfed, 16 percent of infants consume plain water in addition to breast milk, 4 percent consume non-milk liquids, 11 percent consume other milk, and 13 percent consume complementary foods in addition to breast milk. Sixty-three percent of children age 6-8 months receive timely complementary foods, and 70 percent of children age 18-23 months have been weaned. Feeding children using a bottle with a nipple is discouraged but remains a relatively common practice in Namibia, with more than one-fourth (26 percent) of children below age 6 months using a bottle with a nipple. The prevalence of bottle-feeding is highest among children age 6-11 months (49-50 percent). Table 12.3 Breastfeeding status by age Percent distribution of youngest children under age 2 who are living with their mother by breastfeeding status and the percentage currently breastfeeding, and the percentage of all children under age 2 using a bottle with a nipple, according to age in months, Namibia 2013 Age in months Not breast- feeding Breastfeeding status Total Percentage currently breast- feeding Number of youngest child under age 2 living with their mother Percentage using a bottle with a nipple Number of all children under age 2 Exclusively breastfed Breast- feeding and consuming plain water only Breast- feeding and consuming non-milk liquids1 Breast- feeding and consuming other milk Breast- feeding and consuming comple- mentary foods 0-1 2.3 72.0 12.5 1.7 10.7 0.7 100.0 97.7 128 15.4 132 2-3 5.9 52.7 17.3 5.2 11.2 7.6 100.0 94.1 184 22.9 190 4-5 14.4 26.8 16.7 3.8 10.2 28.1 100.0 85.6 175 37.0 179 6-8 19.6 2.4 8.8 3.9 2.8 62.5 100.0 80.4 267 49.3 279 9-11 25.4 1.8 2.6 0.0 3.0 67.2 100.0 74.6 214 50.0 232 12-17 40.7 0.8 1.7 1.3 0.0 55.5 100.0 59.3 429 34.8 496 18-23 70.2 0.5 1.3 0.3 0.4 27.3 100.0 29.8 324 26.3 442 0-3 4.4 60.6 15.3 3.8 11.0 4.8 100.0 95.6 312 19.9 321 0-5 8.0 48.5 15.8 3.8 10.7 13.2 100.0 92.0 487 26.0 500 6-9 21.6 2.4 7.2 3.1 3.3 62.4 100.0 78.4 341 49.8 357 12-15 35.6 1.2 2.2 1.5 0.0 59.6 100.0 64.4 293 36.4 329 12-23 53.4 0.7 1.6 0.9 0.2 43.4 100.0 46.6 753 30.8 938 20-23 79.0 0.2 1.7 0.4 0.0 18.6 100.0 21.0 216 22.6 304 Note: Breastfeeding status refers to a “24-hour” period (yesterday and last night). Children who are classified as breastfeeding and consuming plain water only consumed no liquid or solid supplements. The categories of not breastfeeding, exclusively breastfed, and breastfeeding and consuming plain water, non-milk liquids, other milk, and complementary foods (solids and semisolids) are hierarchical and mutually exclusive, and their percentages sum to 100 percent. Thus, children who receive breast milk and non-milk liquids and who do not receive other milk and who do not receive complementary foods are classified in the non- milk liquid category even though they may also get plain water. Any children who get complementary food are classified in that category as long as they are breastfeeding as well. 1 Non-milk liquids include juice, juice drinks, clear broth, or other liquids. Figure 12.3 depicts the transition of feeding practices among children up to age 2. The rapid drop in exclusive breastfeeding from 72 percent among children under age 2 months to 27 percent among those age 4-5 months is noteworthy. Nutrition of Children and Adults • 137 Figure 12.3 Infant feeding practices by age Figure 12.4 presents the 2013 NDHS results on infant and young child feeding (IYCF) indicators related to breastfeeding status. Detailed descriptions of these indicators can be found in various WHO publications (WHO, 2008; WHO, 2010a). As noted above, 49 percent of children under age 6 months are exclusively breastfed. Twenty-seven percent of children 4-5 months are exclusively breastfed and 28 percent are breastfeeding and consuming complementary foods. Eight in ten children age 6-8 months (both breastfed and nonbreastfed) are introduced to complementary foods at an appropriate time. Sixty-four percent of all children are still breastfeeding at age 1, and 21 percent are still breastfeeding at age 2. Fifty- one percent of children age 0-23 months are breastfed appropriately for their age. This includes exclusive breastfeeding for children age 0-5 months and continued breastfeeding along with complementary foods for children age 6-23 months. Almost seven in ten children under age 6 months (68 percent) are predominantly breastfed. This percentage includes children who are exclusively breastfed and those who receive breast milk and only plain water or non-milk liquids such as juice. Finally, 35 percent of children under age 2 are bottle fed. Figure 12.4 IYCF indicators on breastfeeding status 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% <2 2-3 4-5 6-7 8-9 10-11 12-13 14-15 16-17 18-19 20-21 22-23 Percentage Age group in months Exclusively breastfed Plain water only Non-milk liquids/juice Other milk Complementary foods Not breastfeeding NDHS 2013 49 27 64 80 21 51 68 35 Exclusive breastfeeding under age 6 months Exclusive breastfeeding at age 4-5 months Continued breastfeeding at 1 year Introduction of solid, semisolid, or soft foods (6-8 months) Continued breastfeeding at 2 years Age-appropriate breastfeeding (0-23 months) Predominant breastfeeding (0-5 months) Bottle feeding (0-23 months) Percentage of children NDHS 2013 138 • Nutrition of Children and Adults 12.4 DURATION OF BREASTFEEDING Table 12.4 shows the median duration of breastfeeding (i.e., the length of time in months for which half of children are breastfed) by selected background characteristics. Estimates of median and mean durations of breastfeeding are based on current status data, that is, the proportion of children born in the three years preceding the survey who were being breastfed at the time of the survey. Overall, the median duration of any breastfeeding among children in Namibia is 15 months, which is slightly shorter than the duration reported in the 2006-07 NDHS (17 months). Children are breastfed five months longer on average in rural areas (17 months) than in urban areas (12 months). Comparisons of duration of exclusive breastfeeding by background characteristics should be regarded with caution due to the small number of children in several categories. The median duration of exclusive breastfeeding is 2 months, with a mean duration of 4 months. 12.5 TYPES OF COMPLEMENTARY FOODS Appropriate nutrition includes feeding children a variety of foods to ensure that nutrient requirements are met. Fruits and vegetables rich in vitamin A should be consumed daily. Although eating a range of fruits and vegetables, especially those rich in vitamin A, is important, studies have shown that plant-based complementary foods by themselves are insufficient to meet the needs for certain micronutrients. Therefore, it has been recommended that meat, poultry, fish, or eggs be eaten daily or as often as possible (WHO, 1998). Table 12.5 is based on information from mothers about the foods and liquids consumed during the day or night preceding the interview by their youngest child under age 2.1 Dietary data on children are subject to recall errors on the mother’s part. Furthermore, the mother may not be able to report fully on the child’s intake of food and liquids if the child was fed by other individuals during the period. Despite these problems, the information collected in the 2013 NDHS on the types of foods and liquids consumed by young children is useful in assessing the diversity of children’s diets. The data show that, as expected, the proportions of children consuming foods or liquids included in the various food groups generally increase with age. Children who are currently breastfed are less likely than children who are not being breastfed to consume other types of liquids and solid/semisolid foods. For example, 70 percent of nonbreastfeeding children age 6-23 months consumed foods made from grains the day or night preceding the interview, compared with 48 percent of breastfeeding children in that age group. Similarly, 49 percent of nonbreastfeeding children age 6-23 1 In the earlier NDHS surveys, this information was collected for the youngest children under age 3 who were living with their mother at the time of the survey. Table 12.4 Median duration of breastfeeding Median duration of any breastfeeding, exclusive breastfeeding, and predominant breastfeeding among children born in the three years preceding the survey, by background characteristics, Namibia 2013 Background characteristic Median duration (months) of breastfeeding among children born in the past three years1 Any breast- feeding Exclusive breast- feeding Predominant breast- feeding2 Sex Male 14.3 2.0 3.9 Female 15.1 2.4 4.0 Residence Urban 11.6 2.0 2.8 Rural 17.4 2.4 4.8 Region Zambezi (17.5) * (4.8) Erongo (5.7) * * Hardap (17.0) (3.6) (5.1) //Karas (12.9) * * Kavango 19.6 * 3.8 Khomas (9.8) * (2.9) Kunene (11.3) * 5.9 Ohangwena (14.4) 4.6 6.0 Omaheke (11.3) * (2.8) Omusati (18.1) * (3.8) Oshana (11.8) (3.8) (4.7) Oshikoto (17.6) (2.6) (4.6) Otjozondjupa (15.6) * (4.5) Mother’s education No education (19.2) * (5.0) Primary 17.0 (2.3) 4.4 Secondary 13.0 2.2 3.8 More than secondary (5.5) * * Wealth quintile Lowest 17.3 2.9 5.3 Second 16.5 2.5 4.5 Middle 17.0 (2.1) 3.4 Fourth 11.1 (1.4) 2.7 Highest 5.6 * * Total 14.7 2.2 3.9 Mean for all children 14.8 3.5 5.2 Note: Median and mean durations are based on the distributions at the time of the survey of the proportion of births by months since birth. Includes children living and deceased at the time of the survey. 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 It is assumed that non-last-born children and last-born children not currently living with their mother are not currently breastfeeding. 2 Either exclusively breastfed or received breast milk and plain water and/or non-milk liquids only Nutrition of Children and Adults • 139 months consumed foods rich in vitamin A, compared with 32 percent of breastfeeding children in the same age group. Seven in ten nonbreastfeeding children and more than half (55 percent) of breastfeeding children age 6-23 months consumed meat, fish, and poultry. Table 12.5 Foods and liquids consumed by children in the day or night preceding the interview Percentage of youngest children under age 2 who are living with their mother by type of foods consumed in the day or night preceding the interview, according to breastfeeding status and age, Namibia 2013 Liquids Solid or semisolid foods Any solid or semi- solid food Number of children Age in months Infant formula Other milk1 Other liquids2 Fortified baby foods Food made from grains3 Fruits and vegetable s rich in vitamin A4 Other fruits and vege- tables Food made from roots and tubers Food made from legumes and nuts Meat, fish, poultry Eggs Cheese, yogurt, other milk products BREASTFEEDING CHILDREN 0-1 11.4 8.5 1.8 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 125 2-3 10.8 10.5 9.4 0.7 1.8 1.3 0.7 1.0 0.0 0.7 0.6 2.5 8.1 173 4-5 11.3 10.7 16.1 4.1 6.4 9.6 6.8 5.6 0.8 9.8 2.6 2.1 32.9 150 6-8 11.5 12.9 47.0 18.6 29.3 26.5 14.4 18.0 2.8 32.5 13.2 17.1 77.7 215 9-11 7.7 13.9 56.6 14.8 50.8 25.4 18.9 22.8 11.9 59.4 27.1 19.2 90.0 160 12-17 4.8 7.4 60.5 10.1 58.2 38.0 26.7 21.1 10.2 63.2 17.7 16.9 93.6 254 18-23 7.7 9.0 59.9 10.5 59.8 41.3 30.3 24.5 15.6 75.3 26.0 19.7 91.4 97 6-23 7.8 10.7 55.6 13.7 48.2 32.3 21.9 21.0 9.1 54.9 19.5 17.9 87.8 725 Total 9.1 10.4 38.0 9.2 30.9 21.4 14.5 13.9 5.7 35.3 12.5 11.7 59.8 1,173 NONBREASTFEEDING CHILDREN 0-1 * * * * * * * * * * * * * 3 2-3 * * * * * * * * * * * * * 11 4-5 (67.9) (52.6) (23.5) (28.6) (18.6) (15.5) (5.6) (6.6) (3.1) (3.1) (3.1) (19.2) (45.8) 25 6-8 71.7 53.9 65.5 45.9 43.7 27.9 17.5 35.7 8.8 27.0 19.8 35.2 87.4 52 9-11 25.3 38.3 56.0 31.5 69.0 53.7 35.2 38.5 3.5 48.9 13.1 17.0 95.5 54 12-17 15.6 24.8 70.3 15.2 72.0 51.9 41.8 31.1 11.1 75.3 29.6 35.6 98.4 174 18-23 3.9 19.0 71.0 8.0 73.7 50.7 39.3 29.4 17.9 81.0 27.2 28.2 97.6 227 6-23 17.2 26.7 68.6 16.9 69.5 49.1 37.5 31.6 13.1 70.1 25.8 30.2 96.6 508 Total 20.8 27.5 64.8 17.0 65.4 46.3 35.1 29.7 12.3 65.2 24.1 29.0 91.8 547 Note: Breastfeeding status and food consumed refer to a “24-hour” period (yesterday and last night). 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 milk includes fresh, tinned, and powdered cow or other animal milk. 2 Does not include plain water 3 Includes fortified baby food 4 Includes pumpkin, carrots, squash or red sweet potatoes, dark green leafy vegetables, ripe mangoes, papayas, and other locally grown fruits and vegetables that are rich in vitamin A 12.6 INFANT AND YOUNG CHILD FEEDING PRACTICES Appropriate IYCF practices include breastfeeding through age 2, introduction of solid and semisolid foods at age 6 months, and gradual increases in the amount of food given and frequency of feeding as the child gets older. The minimum frequencies for feeding children in developing countries are based on the energy output of complementary foods. The energy needs of children are based on age- specific total daily energy requirements plus two standard deviations (to cover almost all children), minus the average energy intake from breast milk. Infants with low breast milk intake need to be fed more frequently than those with high breast milk intake. However, care should be taken that feeding frequencies do not exceed the recommended input from complementary foods because excessive feeding can result in displacement of breast milk (PAHO/WHO, 2003). According to recommendations, breastfed children age 6-23 months should receive animal-source foods and vitamin A-rich fruits and vegetables daily (PAHO/WHO, 2003). Because first foods almost always include a grain- or tuber-based staple, it is unlikely that young children who eat food from less than three groups will receive both an animal-source food and a vitamin A-rich fruit or vegetable. Therefore, three food groups are considered the minimum number appropriate for breastfed children (Arimond and Ruel, 2004). Breastfed infants age 6-8 months should receive complementary foods two to three times a day with one or two snacks; breastfed children age 9-23 months should receive meals three to four times a day with one or two snacks (PAHO/WHO, 2003; WHO, 2008; WHO, 2010a). 140 • Nutrition of Children and Adults The National Guidelines on Infant and Young Child Feeding recommend that complementary feeding be introduced at six months and that the frequency of feedings gradually increase. According to these guidelines, children age 6-8 months should eat 2 to 3 times a day, and children age 9-14 months should eat 3 to 4 times a day. Children in all age groups should also eat 1-2 snacks a day. The Ministry of Health and Social Services (MoHSS) recommends that breastfeeding continue until age 2 or older (MoHSS, 2011). WHO recommends that nonbreastfed children age 6-23 months receive milk or milk products two or more times a day to ensure that their calcium needs are met. In addition, they need animal- source foods and vitamin A-rich fruits and vegetables. Four food groups are considered the minimum number appropriate for nonbreastfed young children. Nonbreastfed children age 12-23 months should be fed meals four to five times each day, with one or two snacks (WHO, 2005; WHO, 2008; and WHO, 2010a). Table 12.6 presents summary indicators of IYCF practices by background characteristics. The indicators take into account the percentages of children for whom feeding practices meet minimum standards with respect to food diversity (i.e., the number of food groups consumed) and feeding frequency (i.e., the number of times the child was fed), as well as consumption of breast milk or other milks or milk products. Breastfed children are considered as being fed in accordance with the minimum standards if they consume at least four food groups and receive foods other than breast milk at least twice per day in the case of infants age 6-8 months and at least three times per day in the case of children age 9-23 months. Nonbreastfed children are considered to be fed in accordance with the minimum standards if they consume milk or milk products, consume food from four or more food groups (including milk products), and are fed at least four times per day. Only 13 percent of children age 6-23 months are fed in accordance with all IYCF practices (Table 12.6 and Figure 12.5). Although 72 percent of children receive either breast milk or other milk products, only 41 percent are fed the minimum number of times, and 31 percent are fed from the required number of food groups. Nonbreastfed children are much more likely to consume a diverse diet (42 percent) than breastfed children (24 percent). By contrast, breastfed children seem to be more likely than nonbreastfed children to consume solid or semisolid foods the recommended number of times. An analysis by background characteristics indicates differences in feeding practices by place of residence and mother’s education. Children residing in urban areas are notably more likely to be fed according to the three IYCF practices (21 percent) than rural children (6 percent). By region, the proportion of children who are fed according to the IYCF recommendations is lowest in Omusati and Kavango (3 percent) and highest in //Karas (31 percent). The percentage of children who are fed according to the recommended practices increases with increasing mother’s education and wealth. For example, only 3 percent of children in the lowest wealth quintile are fed according to all three IYCF practices, as compared with 32 percent of children in the richest quintile. Nutrition of Children and Adults • 141 Table 12.6 Infant and young child feeding (IYCF) practices Percentage of youngest children age 6-23 months living with their mother who are fed according to three IYCF feeding practices based on breastfeeding status, number of food groups, and times they are fed during the day or night preceding the survey, by background characteristics, Namibia 2013 Background characteristic Among breastfed children 6-23 months, percentage fed: Number of breastfed children 6-23 months Among nonbreastfed children 6-23 months, percentage fed: Number of non- breastfed children 6- 23 months Among all children 6-23 months, percentage fed: Number of all children 6-23 months 4+ food groups1 Minimum meal frequency2 Both 4+ food groups and minimum meal frequency Milk or milk products3 4+ food groups1 Minimum meal frequency4 With 3 IYCF practices5 Breast milk, milk, or milk products6 4+ food groups1 Minimum meal frequency7 With 3 IYCF practices Age in months 6-8 15.1 47.4 9.9 215 73.6 25.6 75.8 7.1 52 94.8 17.2 53.0 9.4 267 9-11 27.3 25.1 9.4 160 47.1 35.7 59.8 16.6 54 86.6 29.4 34.0 11.2 214 12-17 24.6 35.4 13.5 254 33.3 46.1 51.2 17.8 174 72.9 33.3 41.8 15.3 429 18-23 34.2 33.1 15.6 97 19.2 43.5 35.7 11.0 227 43.3 40.7 35.0 12.4 324 Sex Male 23.7 38.5 12.7 339 29.5 38.8 45.5 8.8 251 70.0 30.1 41.5 11.1 589 Female 23.6 34.5 11.1 387 35.7 44.6 49.9 18.1 257 74.3 32.0 40.7 13.9 644 Residence Urban 39.9 41.0 21.1 280 46.7 56.8 59.8 20.2 288 73.0 48.5 50.6 20.6 568 Rural 13.4 33.5 6.1 446 14.2 22.0 32.0 4.8 221 71.6 16.3 33.0 5.7 666 Region Zambezi 20.4 24.2 7.4 43 (17.5) (35.8) (35.4) (8.2) 27 67.9 26.4 28.6 7.7 70 Erongo (45.4) (38.5) (25.6) 43 (50.2) (62.7) (55.7) (23.6) 41 75.8 53.8 46.9 24.6 84 Hardap 23.5 25.8 9.7 29 (43.7) (38.7) (51.1) (11.3) 20 77.2 29.6 36.0 10.3 49 //Karas (52.4) (38.1) (30.7) 21 (61.9) (63.4) (66.3) (31.1) 17 82.8 57.4 50.8 30.9 38 Kavango 22.3 22.2 3.6 117 (15.5) (51.1) (14.0) (2.5) 42 77.8 29.9 20.0 3.3 159 Khomas (53.1) (45.5) (28.8) 88 54.8 61.4 73.0 23.8 115 74.4 57.8 61.1 26.0 202 Kunene 15.1 47.2 13.6 24 (17.5) (29.2) (53.2) (1.3) 17 65.0 21.1 49.7 8.4 41 Ohangwena 7.9 41.8 6.5 89 (11.8) (20.4) (32.3) (5.3) 57 65.3 12.9 38.0 6.1 146 Omaheke (17.2) (50.1) (14.2) 20 (45.2) (30.7) (46.3) (8.6) 15 76.7 22.9 48.5 11.8 35 Omusati 6.3 40.8 5.0 88 (7.5) (10.2) (41.2) (0.0) 49 67.1 7.7 40.9 3.2 137 Oshana (12.0) (23.5) (0.0) 37 (31.0) (40.9) (47.3) (19.7) 42 63.4 27.3 36.1 10.4 78 Oshikoto 24.0 48.1 14.0 74 (20.2) (31.0) (32.6) (12.4) 34 75.0 26.2 43.2 13.5 108 Otjozondjupa 20.7 32.3 11.9 54 (36.4) (37.6) (41.7) (12.2) 34 75.6 27.2 35.9 12.0 87 Mother’s education No education 12.6 33.0 6.8 49 (16.5) (7.4) (24.5) (0.0) 24 72.5 10.9 30.2 4.5 72 Primary 15.8 30.3 6.0 201 17.0 27.4 30.1 3.8 97 72.9 19.6 30.2 5.3 299 Secondary 26.4 39.1 13.9 453 34.3 44.5 50.9 14.1 348 71.4 34.3 44.2 14.0 801 More than secondary * * * 23 (67.3) (73.5) (78.0) (41.4) 39 (79.4) (69.7) (65.0) (38.2) 61 Wealth quintile Lowest 10.8 28.3 3.7 186 8.7 15.4 20.2 0.5 88 70.6 12.3 25.7 2.7 274 Second 18.3 42.8 9.9 191 14.3 19.3 36.5 0.3 102 70.1 18.7 40.6 6.6 293 Middle 23.9 35.5 12.5 178 24.7 41.6 50.6 8.1 89 74.8 29.8 40.5 11.0 268 Fourth 38.7 39.7 20.9 109 36.0 52.3 44.9 17.5 117 66.9 45.7 42.4 19.1 226 Highest 51.7 37.5 24.3 61 71.2 72.1 80.7 36.3 111 81.4 64.8 65.4 32.0 172 Total 23.7 36.4 11.8 725 32.6 41.7 47.7 13.5 508 72.2 31.1 41.1 12.5 1,234 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 Food groups: a. infant formula, milk other than breast milk, cheese or yogurt or other milk products; b. foods made from grains, roots, and tubers, including porridge and fortified baby food from grains; c. vitamin A-rich fruits and vegetables; d. other fruits and vegetables; e. eggs; f. meat, poultry, fish, and shellfish and organ meats; g. legumes and nuts. 2 For breastfed children, minimum meal frequency is receiving solid or semisolid food at least twice a day for infants age 6-8 months and at least 3 times a day for children age 9- 23 months. 3 Includes 2 or more feedings of commercial infant formula; fresh, tinned, and powdered animal milk; and yogurt 4 For nonbreastfed children age 6-23 months, minimum meal frequency is receiving solid or semisolid food or milk feeds at least 4 times a day. 5 Nonbreastfed children age 6-23 months are considered to be fed with a minimum standard of 3 IYCF practices if they receive other milk or milk products at least twice a day, receive the minimum meal frequency, and receive solid or semisolid foods from at least 4 food groups not including the milk or milk products food group. 6 Breastfeeding, or not breastfeeding and receiving 2 or more feedings of commercial infant formula; fresh, tinned, and powdered animal milk; and yogurt 7 Children are fed the minimum recommended number of times per day according to their age and breastfeeding status as described in notes 2 and 4. 142 • Nutrition of Children and Adults Figure 12.5 IYCF indicators on minimum acceptable diet 12.7 PREVALENCE OF ANAEMIA IN CHILDREN Anaemia is characterised by a decreased concentration of haemoglobin in the blood. It may be an underlying cause of maternal mortality, spontaneous abortions, premature births, and low birth weight. The most common cause of anaemia is inadequate dietary intake of nutrients necessary for synthesis of haemoglobin, such as iron, folic acid, and vitamin B12. Anaemia also results from sickle cell disease, malaria, and parasitic infections. A number of interventions have been put in place to address anaemia in children. These include expanded distribution of multi-micronutrient powders; deworming of children age 1 to 5 every six months, along with vitamin A distribution; and promotion of the use of insecticide-treated mosquito nets for children under age 5 in malaria-endemic areas. In the 2013 NDHS, the HemoCue rapid testing methodology was used to determine anaemia levels among children age 6-59 months and among women and men age 15-64. To measure the level of haemoglobin, capillary blood was taken in the field from a finger using sterile, one-time-use lancets that allowed a relatively painless puncture. The concentration of haemoglobin in the blood was measured using the HemoCue system. Each team had a health technician who was specifically trained to conduct this procedure. Each respondent (and, in the case of unmarried minors, their parent or guardian) was asked for her or his consent to participate in the anaemia testing. Levels of anaemia were classified as severe, moderate, or mild according to criteria developed by the World Health Organization (DeMaeyer et.al., 1989). Table 12.7 presents anaemia levels among children age 6-59 months by background characteristics. The results are based on children who stayed in the household the night before the interview. Haemoglobin was measured in 2,303 children. Unadjusted (i.e., measured) haemoglobin values were obtained using the HemoCue instrument. Given that haemoglobin requirements differ substantially depending on altitude, an adjustment to sea-level equivalents was made using CDC formulas before classifying children according to level of anaemia (CDC, 1998). Overall, 48 percent of children age 6-59 months are anaemic. The majority of children who suffer from anaemia are classified as having mild or moderate anaemia (25 percent and 22 percent, respectively), while less than 1 percent are severely anaemic. Anaemia is highest among children age 12-17 months (70 percent) and is slightly higher among male than female children (50 percent versus 46 percent). Across regions, children from Kavango (63 percent) are most likely to be anaemic and those in Ohangwena (35 percent) are least likely. The prevalence of anaemia is lowest among children whose mother has more than a secondary education (38 percent) and those in the richest households (41 percent). 24 36 12 42 48 14 31 41 13 IYCF 5: Minimum dietary diversity IYCF 6: Minimum meal frequency IYCF 7: Minimum acceptable diet Percentage Breastfed Nonbreastfed All children 6-23 months NDHS 2013 Nutrition of Children and Adults • 143 Table 12.7 Prevalence of anaemia in children Percentage of children age 6-59 months classified as having anaemia, by background characteristics, Namibia 2013 Anaemia status by haemoglobin level Number of children Background characteristic Any anaemia (<11.0 g/dl) Mild anaemia (10.0-10.9 g/dl) Moderate anaemia (7.0-9.9 g/dl) Severe anaemia (<7.0 g/dl) Age in months 6-8 60.3 25.4 34.0 0.9 135 9-11 63.8 23.9 36.9 2.9 126 12-17 69.7 27.0 41.9 0.8 253 18-23 58.3 29.8 27.2 1.3 245 24-35 48.8 25.0 23.3 0.5 561 36-47 37.1 23.5 13.3 0.3 492 48-59 31.8 22.8 8.2 0.8 491 Sex Male 49.5 26.5 22.1 1.0 1,139 Female 45.5 23.3 21.5 0.6 1,164 Mother’s interview status Interviewed 49.3 24.4 24.2 0.8 1,494 Not interviewed but in household 48.0 28.7 17.3 2.0 104 Not interviewed and not in the household1 43.5 25.5 17.4 0.6 705 Residence Urban 46.6 22.6 23.2 0.8 836 Rural 47.9 26.2 21.0 0.8 1,467 Region Zambezi 56.6 29.1 27.4 0.0 150 Erongo 46.1 26.6 17.2 2.4 115 Hardap 39.4 17.0 21.3 1.1 88 //Karas 57.4 28.4 29.0 0.0 72 Kavango 62.9 33.1 27.2 2.6 248 Khomas 42.7 20.0 21.9 0.8 267 Kunene 61.3 28.2 31.7 1.5 90 Ohangwena 35.1 20.0 14.8 0.3 362 Omaheke 37.7 20.4 17.3 0.0 79 Omusati 46.7 27.5 19.2 0.0 299 Oshana 42.1 24.1 18.0 0.0 164 Oshikoto 49.1 26.4 22.2 0.5 210 Otjozondjupa 53.8 23.5 29.0 1.3 160 Mother’s education2 No education 48.3 26.8 19.7 1.8 113 Primary 52.0 25.4 24.7 1.9 383 Secondary 49.3 24.9 24.1 0.4 1,015 More than secondary 38.2 16.3 21.0 0.9 85 Wealth quintile Lowest 49.3 26.7 21.3 1.3 591 Second 50.6 28.4 21.6 0.7 504 Middle 48.3 25.7 21.9 0.7 486 Fourth 44.5 20.0 23.8 0.7 464 Highest 40.8 21.4 19.4 0.0 258 Total 47.5 24.9 21.8 0.8 2,303 Note: Table is based on children who stayed in the household on the night before the interview and who were tested for anaemia. Prevalence of anaemia, based on haemoglobin levels, is adjusted for altitude using formulas in CDC, 1998. Haemoglobin is in grams per decilitre (g/dl). Total includes 2 children with missing information on mother’s education. 1 Includes children whose mothers are deceased 2 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. 12.8 MICRONUTRIENT INTAKE AND SUPPLEMENTATION AMONG CHILDREN Micronutrient deficiency is a major contributor to childhood morbidity and mortality. Micro- nutrients are available in foods and can also be provided through direct supplementation. Breastfeeding children benefit from supplements given to their mother. Iron deficiency is one of the primary causes of anaemia, which has serious health consequences for both women and children. Vitamin A is an essential micronutrient for the immune system and plays an important role in maintaining the epithelial tissue in the body. Severe vitamin A deficiency (VAD) can cause eye damage and is the leading cause of childhood blindness. VAD also increases the severity of infections, such as measles and diarrheal disease in children, and slows recovery from illness. VAD is 144 • Nutrition of Children and Adults common in dry environments where fresh fruits and vegetables are not readily available. Vitamin A supplementation is an important tool in preventing VAD among young children. Information was collected on food consumption during the day and night preceding the interview among the youngest children under age 2 living with their mothers; these data are useful in assessing the extent to which children are consuming from food groups rich in two key micronutrients—vitamin A and iron—in their daily diet. In addition, the NDHS included questions designed to ascertain whether young children had received vitamin A supplements or deworming medication in the six months preceding the survey. Table 12.8 presents data on intake of key micronutrients among children by background characteristics. The table shows the percentage of youngest children age 6-23 months living with their mother who consumed foods rich in vitamin A and iron in the day or night preceding the survey, the percentage of all children age 6-59 months who were given vitamin A supplements in the six months preceding the survey and who were given iron supplements in the past seven days, the percentage of children age 12-59 months who were given deworming medication in the six months preceding the survey, and, among all children age 6-59 months living in households that were tested for the presence of iodised salt, the percentage who lived in households with iodised salt. Seventy-one percent of children age 6-23 months consumed foods rich in vitamin A the day or night preceding the survey. There is no difference in the consumption of vitamin A-rich foods between boys and girls, but consumption of such foods is considerably higher among nonbreastfeeding (80 percent) than breastfeeding (66 percent) children. Children living in urban areas are more likely than children in rural areas to consume foods rich in vitamin A (75 percent versus 68 percent). By region, children in Zambezi (85 percent) are most likely to consume vitamin A-rich foods, and those in Kunene are least likely to do so (49 percent). Education and wealth are positively associated with the percentage of children who consume vitamin A-rich foods. Sixty-four percent of children age 6-23 months consumed iron-rich foods in the day and night preceding the survey. Consumption of iron-rich foods is slightly higher among girls (65 percent) than boys (63 percent), and it is substantially higher among nonbreastfeeding than breastfeeding children (73 percent versus 58 percent). Urban children (68 percent) are more likely than rural children (61 percent) to consume iron-rich foods. Children in Omaheke (74 percent) are most likely to consume iron-rich foods, and children in Kunene (42 percent) are least likely to do so. The percentage of children who consume iron-rich foods increases with increasing mother’s education and wealth. For example, 57 percent of children in the lowest wealth quintile consume iron-rich foods, as compared with 77 percent of those in the highest quintile. The 2013 NDHS also collected data on vitamin A supplementation and iron supplementation among children under age 5. According to Table 12.8, 84 percent of children age 6-59 months were given vitamin A supplements in the six months before the survey. The proportion of children receiving vitamin A supplementation is highest among those age 12-17 months (92 percent). Children who are still breastfeeding (86 percent) are more likely to receive vitamin A supplements than those who are not breastfeeding (83 percent). A lower percentage of children living in urban (80 percent) than rural (87 percent) areas received vitamin A supplements in the last six months. By region, the proportion of children receiving vitamin A supplements is highest in Oshana (95 percent) and lowest in Khomas and Erongo (74 percent each). Certain types of intestinal parasites can cause anaemia. Periodic deworming for organisms such as helminthes and schistosomiasis (bilharzia) can improve children’s micronutrient status. Table 12.8 shows that more than four in ten children age 6-59 months (43 percent) received deworming medication in the six months before the survey. Older children, female children, children living in rural areas and in Kavango, children of mothers with no education or a primary education, and children living in the poorest households are more likely than other children to have been given deworming medication. The proportion of children who received micronutrient supplements or deworming medication has increased since the 2006-07 NDHS. For example, the percentage of children who received vitamin A supplementation in the last six months increased from 52 percent to 84 percent, and the percentage who received deworming medication increased from 9 percent to 43 percent. Nutrition of Children and Adults • 145 Inadequate amounts of iodine in the diet are related to serious health risks for young children. The 2013 NDHS tested for the presence of iodine in household salt. The results show that, among children age 6-59 months in households tested for salt, 76 percent live in households that use iodised salt. Table 12.8 Micronutrient intake among children Among youngest children age 6-23 months who are living with their mother, the percentages who consumed vitamin A-rich and iron-rich foods in the day or night preceding the survey; among all children age 6-59 months, the percentages who were given vitamin A supplements in the six months preceding the survey, who were given iron supplements in the past seven days, and who were given deworming medication in the six months preceding the survey; and among all children age 6-59 months who live in households that were tested for iodised salt, the percentage who live in households with iodised salt, by background characteristics, Namibia 2013 Among youngest children age 6-23 months living with their mother: Among all children age 6-59 months: Among children age 6-59 months living in households tested for iodised salt Background characteristic Percentage who consumed foods rich in vitamin A in last 24 hours1 Percentage who consumed foods rich in iron in last 24 hours2 Number of children Percentage given vitamin A supplements in last 6 months Percentage given deworming medication in last 6 months3 Number of children Percentage living in households with iodised salt4 Number of children Age in months 6-8 46.3 36.4 267 73.8 31.3 279 71.4 270 9-11 67.6 60.2 214 88.1 30.8 232 73.2 216 12-17 77.8 70.7 429 91.9 41.6 496 75.1 473 18-23 85.9 81.2 324 86.4 49.2 442 73.8 419 24-35 na na na 83.9 45.2 926 76.2 883 36-47 na na na 82.7 44.9 883 76.8 832 48-59 na na na 79.7 43.5 830 77.6 783 Sex Male 70.7 63.3 589 82.7 40.6 1,997 75.4 1,896 Female 71.9 65.0 644 84.5 45.3 2,092 76.0 1,980 Breastfeeding status Breastfeeding 65.5 57.9 725 85.7 42.1 794 69.2 751 Not breastfeeding 79.7 73.3 508 83.2 43.3 3,271 77.4 3,102 Mother’s age at birth 15-19 71.8 60.8 115 74.3 45.0 206 70.1 193 20-29 73.0 66.9 635 83.3 43.2 2,088 76.6 1,982 30-39 69.5 61.7 402 84.3 42.2 1,417 76.0 1,345 40-49 67.2 60.0 81 87.2 43.8 377 72.9 355 Residence Urban 75.4 68.4 568 79.8 38.7 2,043 89.8 1,952 Rural 67.9 60.7 666 87.3 47.4 2,046 61.5 1,924 Region Zambezi 84.9 71.2 70 88.9 41.6 246 95.8 220 Erongo 77.2 68.3 84 73.6 26.0 292 94.6 274 Hardap 66.5 61.6 49 82.5 35.7 146 75.6 135 //Karas 78.3 69.3 38 91.1 50.8 143 87.4 137 Kavango 79.0 66.9 159 93.0 90.3 479 78.6 443 Khomas 78.0 70.5 202 74.1 29.6 787 93.0 762 Kunene 48.9 42.1 41 78.0 35.1 151 71.5 132 Ohangwena 63.8 58.3 146 87.2 36.6 480 61.4 470 Omaheke 74.4 74.4 35 84.0 41.9 127 59.7 114 Omusati 62.1 55.7 137 79.7 23.3 397 57.2 382 Oshana 63.9 60.6 78 95.0 64.6 265 67.4 264 Oshikoto 76.4 70.8 108 89.1 40.3 316 56.9 308 Otjozondjupa 62.2 59.0 87 81.3 45.1 260 69.7 235 Mother’s education No education 47.8 38.6 72 77.7 45.1 253 59.8 224 Primary 67.9 57.9 299 84.7 47.1 956 67.9 887 Secondary 73.7 67.6 801 84.6 41.4 2,615 77.8 2,512 More than secondary (85.5) (81.0) 61 74.7 41.8 265 96.4 253 Wealth quintile Lowest 66.2 57.0 274 86.6 49.6 868 62.4 800 Second 66.2 60.2 293 86.6 45.0 889 66.1 843 Middle 68.6 62.0 268 86.9 43.0 849 68.7 816 Fourth 77.0 71.4 226 81.9 40.0 857 89.1 823 Highest 85.1 76.5 172 72.8 35.4 625 98.3 595 Total 71.3 64.2 1,234 83.6 43.0 4,088 75.7 3,875 Note: Information on vitamin A is based on both mother’s recall and the immunisation card (where available). Information on iron supplements and deworming medication is based on mother’s recall. Total includes 23 children with missing information on breastfeeding status. Figures in parentheses are based on 25- 49 unweighted cases. na = Not applicable 1 Includes meat (and organ meat), fish, poultry, eggs, pumpkin, squash, carrots, red sweet potatoes, dark green leafy vegetables, ripe mango, papaya, and other locally grown fruits and vegetables that are rich in vitamin A 2 Includes meat (and organ meat), fish, poultry, and eggs 3 Deworming for intestinal parasites is commonly done for helminthes and for schistosomiasis. 4 Excludes children in households in which salt was not tested 146 • Nutrition of Children and Adults 12.9 PRESENCE OF IODISED SALT IN HOUSEHOLDS Salt is used for several purposes in a household. It plays a role in cooking and food preservation. In line with food and drug regulations, household salt should be fortified with iodine sufficient to ensure a concentration of at least 15 parts per million (ppm) when consumed. Iodine is an essential micronutrient, and iodised salt prevents goitre among children and adults. As mentioned above, the 2013 NDHS tested for the presence of iodine in household salt. Salt was tested in 94 percent of households (Table 12.9). It should be noted that household salt was tested for the presence or absence of iodine only; the iodine level in the salt was not measured. Among households in which salt was tested, 76 percent were consuming iodised salt. The percentages of households with iodised salt vary somewhat by residence, region, and wealth. Notably, 90 percent of households in urban areas have iodised salt, as compared with only 61 percent in rural areas. Zambezi has the highest percentage of households with iodised salt (96 percent), followed by Erongo and Khomas (93 percent each); Omusati has the lowest percentage (55 percent). The percentage of households with iodised salt increases steadily with increasing wealth. Table 12.9 Presence of iodised salt in household Among all households, the percentage with salt tested for iodine content and the percentage with no salt in the household, and among households with salt tested, the percentage with iodised salt, according to background characteristics, Namibia 2013 Among all households, the percentage: Among households with tested salt: Background characteristic With salt tested With no salt in the household Number of households Percentage with iodised salt Number of households Residence Urban 93.4 6.6 2,554 89.9 2,386 Rural 93.8 6.2 2,363 61.4 2,217 Region Zambezi 87.7 12.3 270 96.1 237 Erongo 92.8 7.2 460 93.4 427 Hardap 91.0 9.0 199 76.7 181 //Karas 93.3 6.7 200 89.8 186 Kavango 94.4 5.6 368 76.4 347 Khomas 93.4 6.6 1,007 92.6 940 Kunene 88.5 11.5 177 75.7 157 Ohangwena 98.4 1.6 443 59.1 435 Omaheke 89.3 10.7 168 62.0 150 Omusati 95.3 4.7 473 55.2 451 Oshana 97.5 2.5 415 68.2 404 Oshikoto 95.6 4.4 411 57.9 393 Otjozondjupa 89.8 10.2 328 73.5 295 Wealth quintile Lowest 92.9 7.1 872 55.1 810 Second 92.1 7.9 936 65.3 862 Middle 94.2 5.8 952 72.1 897 Fourth 94.6 5.4 1,120 87.0 1,059 Highest 94.0 6.0 1,037 95.3 975 Total 93.6 6.4 4,917 76.2 4,603 12.10 ADULT NUTRITIONAL STATUS 12.10.1 Nutritional Status of Women Anthropometric data on height and weight were collected for women age 15-64 interviewed in the survey. In this report, two indicators of nutritional status based on these data are presented: body mass index (BMI) and the percentage of women of very short stature (less than 145 cm). The body mass index, or the Quetelet index, is used to measure thinness or obesity. BMI is expressed as weight in kilograms divided by height squared in metres (kg/m2). A cutoff point of 18.5 is used to define thinness or acute undernutrition, and a BMI of 25.0 or above usually indicates overweight or obesity. The height of a woman is associated with past socioeconomic status and nutrition during childhood and adolescence. Low pre-pregnancy BMI and short stature are risk factors for poor birth outcomes and obstetric complications. In developing countries, maternal underweight is a leading risk factor for preventable death and diseases. Nutrition of Children and Adults • 147 Table 12.10.1 shows the nutritional status of women by background characteristics. Respondents for whom there was no information on height and/or weight and for whom a BMI could not be estimated were excluded from this analysis. Overall, less than 1 percent of women fall below the 145-cm cutoff point for height. The mean BMI for women age 15-49 is 23.7. At the national level, 55 percent of women age 15-49 have a BMI in the normal range, 14 percent of women are thin (BMI below 18.5), and 32 percent are overweight or obese. Hence, among women of reproductive age in Namibia, being overweight or obese is more of a public health concern than being underweight. Table 12.10.1 Nutritional status of women Among women age 15-49, the percentage with height under 145 cm, mean body mass index (BMI), and the percentage with specific BMI levels, by background characteristics, Namibia 2013 Height Body mass index1 Mean BMI Normal Thin Overweight/obese Number of women Background characteristic Percentage below 145 cm Number of women 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (moderately and severely thin) ≥25.0 (total over- weight or obese) 25.0-29.9 (over- weight) ≥30.0 (obese) Age 15-19 0.5 878 20.5 65.9 26.7 14.7 12.0 7.4 5.4 2.0 816 20-29 0.7 1,538 22.8 62.6 12.4 8.7 3.7 25.0 17.5 7.6 1,371 30-39 0.3 1,136 25.2 46.8 8.7 5.4 3.4 44.4 24.9 19.5 1,014 40-49 0.6 736 26.6 37.0 9.7 6.4 3.3 53.3 25.4 27.9 721 Residence Urban 0.6 2,341 24.7 49.6 10.6 7.1 3.5 39.8 21.9 18.0 2,133 Rural 0.4 1,947 22.4 60.4 17.8 10.5 7.4 21.7 14.1 7.6 1,788 Region Zambezi 0.0 220 23.3 63.9 10.9 5.7 5.2 25.2 13.5 11.8 208 Erongo 1.5 354 25.5 48.9 7.2 5.6 1.7 43.8 21.4 22.4 326 Hardap 1.2 160 25.2 41.1 14.5 7.4 7.1 44.4 21.8 22.7 149 //Karas 1.5 167 25.4 45.9 8.2 4.4 3.7 46.0 26.0 19.9 158 Kavango 0.3 381 22.0 65.2 17.6 11.3 6.3 17.2 12.2 5.0 339 Khomas 0.0 921 24.8 49.6 9.7 6.9 2.8 40.8 22.6 18.1 838 Kunene 0.5 123 25.5 41.9 12.0 6.5 5.5 46.1 24.9 21.2 109 Ohangwena 0.3 468 21.4 61.9 23.6 14.5 9.1 14.5 10.1 4.4 414 Omaheke 2.1 115 24.7 47.1 13.7 9.3 4.3 39.3 22.0 17.2 103 Omusati 0.3 414 21.8 62.8 18.6 9.6 8.9 18.6 13.4 5.2 386 Oshana 1.2 380 23.3 57.0 14.5 8.6 5.9 28.5 18.4 10.1 349 Oshikoto 0.0 334 23.0 58.3 14.6 10.7 4.0 27.1 18.0 9.1 309 Otjozondjupa 0.8 250 24.8 44.4 13.3 7.4 5.9 42.3 23.1 19.3 233 Education No education 2.2 208 23.9 52.6 13.1 6.9 6.2 34.3 18.9 15.4 184 Primary 1.3 855 22.5 54.6 20.6 11.6 9.0 24.8 16.2 8.6 786 Secondary 0.2 2,843 23.8 55.2 12.8 8.3 4.4 32.1 18.4 13.6 2,598 More than secondary 0.0 383 25.3 50.4 7.8 5.1 2.8 41.7 22.2 19.5 353 Wealth quintile Lowest 0.4 690 21.1 64.4 22.9 12.1 10.8 12.7 10.4 2.3 624 Second 1.0 777 22.3 63.3 16.7 11.2 5.5 20.0 13.9 6.1 705 Middle 0.8 819 23.3 55.9 14.2 9.3 4.9 29.8 18.2 11.6 754 Fourth 0.4 1,034 24.8 46.3 10.9 6.6 4.3 42.8 24.6 18.3 943 Highest 0.2 968 25.7 48.2 8.3 5.7 2.6 43.5 21.0 22.6 895 Total 0.5 4,288 23.7 54.5 13.9 8.6 5.3 31.6 18.3 13.2 3,922 Note: Body mass index is expressed as the ratio of weight in kilograms to the square of height in metres (kg/m2). 1 Excludes pregnant women and women with a birth in the preceding 2 months In general, the percentage of women who are thin decreases with age, while the percentage of women who are overweight increases with age. For example, women age 15-19 (27 percent) are much more likely to be thin than women age 30-49 (9-10 percent). Women living in rural areas are more likely to be thin (18 percent) than those living in urban areas (11 percent), while urban women are more likely to be overweight or obese (40 percent versus 22 percent). At the regional level, the proportion of thin women is highest in Ohangwena (24 percent) and lowest in Erongo (7 percent). The proportion of women who are overweight or obese is highest in //Karas and Kunene (46 percent each) and lowest in Ohangwena (15 percent). The percentage of women who are thin tends to decrease with increasing wealth. As one would expect, overweight and obesity increases with wealth. 148 • Nutrition of Children and Adults 12.10.2 Nutritional Status of Men For the first time in an NDHS, anthropometric data on height and weight were collected among men age 15-64. Overall, this information was successfully gathered for 99 percent of the men interviewed during the survey. These data are useful in BMI calculations, which can be used as a measure of chronic energy deficiency among men (BMI calculations and cutoff points are the same for men and women). In addition, BMI can be used to measure overweight and obesity, risk factors for nutrition-related chronic diseases such as diabetes mellitus and cardiovascular disease. Table 12.10.2 shows the nutritional status of men by background characteristics. Overall, 65 percent of men age 15-49 have a BMI in the normal range, 23 percent are thin, and 12 percent are overweight or obese. These findings show that men are more likely than women to be thin and less likely to be overweight or obese. Table 12.10.2 Nutritional status of men Among men age 15-49, mean body mass index (BMI) and the percentage with specific BMI levels, by background characteristics, Namibia 2013 Body mass index Mean BMI Normal Thin Overweight/obese Number of men Background characteristic 18.5-24.9 (total normal) <18.5 (total thin) 17.0-18.4 (mildly thin) <17 (moderately and severely thin) ≥25.0 (total over- weight or obese) 25.0-29.9 (overweight) ≥30.0 (obese) Age 15-19 18.8 47.8 50.3 27.0 23.2 2.0 1.4 0.6 844 20-29 21.1 77.6 14.0 11.6 2.4 8.3 6.9 1.5 1,322 30-39 22.0 67.9 14.8 10.2 4.6 17.3 12.7 4.5 857 40-49 22.7 58.1 17.3 11.6 5.6 24.6 14.3 10.3 553 Residence Urban 21.8 65.5 17.4 12.7 4.7 17.2 11.7 5.4 1,936 Rural 20.1 65.0 30.2 17.5 12.7 4.8 3.9 0.9 1,639 Region Zambezi 21.0 77.0 15.1 12.6 2.6 7.9 6.5 1.4 193 Erongo 22.7 64.3 12.4 9.1 3.2 23.3 14.4 9.0 329 Hardap 21.8 59.1 23.4 15.4 7.9 17.5 10.2 7.3 142 //Karas 21.9 56.0 22.8 14.5 8.3 21.2 16.2 4.9 142 Kavango 20.0 70.9 26.1 18.1 8.0 3.0 3.0 0.0 298 Khomas 21.8 68.5 14.6 11.2 3.5 16.9 12.4 4.5 805 Kunene 21.5 74.2 13.6 11.4 2.3 12.1 7.9 4.3 97 Ohangwena 19.7 62.1 35.2 18.6 16.6 2.7 2.4 0.4 307 Omaheke 21.2 66.9 21.0 16.4 4.6 12.1 9.0 3.1 99 Omusati 19.1 55.3 43.1 20.4 22.7 1.6 1.2 0.4 326 Oshana 20.4 66.4 26.8 17.8 8.9 6.8 5.4 1.4 299 Oshikoto 20.4 65.5 26.8 16.9 9.9 7.7 6.3 1.4 312 Otjozondjupa 21.7 59.4 24.0 15.8 8.2 16.6 9.0 7.5 225 Education No education 21.0 79.0 14.4 10.5 3.9 6.5 5.0 1.5 289 Primary 20.0 61.8 33.4 18.2 15.2 4.8 4.1 0.7 864 Secondary 21.1 64.7 22.6 15.5 7.1 12.7 9.0 3.7 2,123 More than secondary 23.2 66.1 7.3 5.9 1.4 26.6 16.6 10.1 300 Wealth quintile Lowest 19.7 63.3 34.1 18.9 15.1 2.6 2.3 0.3 556 Second 20.0 70.4 26.5 15.6 10.8 3.1 3.1 0.1 719 Middle 20.6 68.7 25.3 16.8 8.4 6.0 4.9 1.1 804 Fourth 21.1 65.3 22.2 15.8 6.4 12.5 9.3 3.2 821 Highest 23.6 57.1 10.0 7.5 2.5 32.9 20.6 12.3 676 Total 15-49 21.0 65.2 23.3 14.9 8.3 11.5 8.1 3.4 3,575 Note: Body mass index is expressed as the ratio of weight in kilograms to the square of height in metres (kg/m2). Similar to women, men age 15-19 (50 percent) are more likely to be thin than older men (age 40-49) (17 percent), while older men are much more likely to be overweight or obese than those in the 15-19 age group (25 percent versus 2 percent). Rural men are more likely to be thin than urban men (30 percent versus 17 percent), while urban men are more likely to be overweight or obese (17 percent versus 5 percent). The percentage of men who are thin ranges from 12 percent in Erongo to 43 percent in Omusati. By contrast, the percentage of men who are overweight or obese is highest among those in Erongo (23 percent) and lowest among those in Omusati (2 percent). The percentage of men who are thin decreases steadily with increasing wealth, from 34 percent among those in the lowest wealth quintile to 10 percent among those in the highest quintile. Overall, there are substantial increases in the percentage of overweight and obese men with increasing education and wealth. Nutrition of Children and Adults • 149 12.10.3 Anaemia in Women Table 12.11.1 presents anaemia levels for women age 15-49. Overall, 21 percent of women are anaemic. The majority of women who suffer from anaemia are mildly or moderately anaemic (17 percent and 4 percent, respectively), while less than 1 percent are severely anaemic. Women age 40-49 are more likely to be anaemic (28 percent) than those age 15-29 (17-19 percent). Women who have given birth to six or more children are more likely to be anaemic (30 percent) than those with fewer children (19-22 percent). Pregnant women have a higher prevalence of anaemia (26 percent) than nonpregnant or breastfeeding women (20-22 percent). Anaemia among women is slightly higher in rural than urban areas. Across regions, women from Kavango (33 percent) are most likely to be anaemic, and those in Hardap (15 percent) are least likely. Anaemia prevalence is lowest among those with more than a secondary education (17 percent) and the wealthiest women (18 percent). Table 12.11.1 Prevalence of anaemia in women Percentage of women age 15-49 with anaemia, by background characteristics, Namibia 2013 Anaemia status by haemoglobin level Number of women Background characteristic Any Mild Moderate Severe Not pregnant <12.0 g/dl 10.0-11.9 g/dl 7.0-9.9 g/dl <7.0 g/dl Pregnant <11.0 g/dl 10.0-10.9 g/dl 7.0-9.9 g/dl <7.0 g/dl Age 15-19 19.1 15.4 3.2 0.5 870 20-29 17.3 14.5 2.7 0.1 1,514 30-39 21.8 16.8 4.5 0.5 1,127 40-49 27.8 22.2 4.4 1.2 731 Number of children ever born 0 19.4 15.7 3.1 0.5 1,343 1 19.1 16.0 3.0 0.1 868 2-3 20.7 17.0 3.4 0.3 1,261 4-5 22.0 16.2 5.2 0.6 510 6+ 29.7 22.1 5.6 1.9 260 Maternity status Pregnant 25.6 18.7 6.5 0.4 288 Breastfeeding 21.9 18.5 3.0 0.4 585 Neither 20.0 16.1 3.4 0.5 3,369 Using IUD Yes * * * * 21 No 20.7 16.6 3.6 0.5 4,221 Smoking status Smokes cigarettes/ tobacco 15.9 13.8 1.9 0.2 204 Does not smoke 20.9 16.7 3.7 0.5 4,036 Missing * * * * 2 Residence Urban 19.2 15.7 3.0 0.6 2,303 Rural 22.4 17.7 4.3 0.4 1,938 Region Zambezi 26.3 19.9 6.2 0.3 219 Erongo 21.1 15.6 5.1 0.4 356 Hardap 14.6 13.3 1.1 0.2 159 //Karas 20.9 17.3 3.4 0.2 167 Kavango 32.9 23.2 7.8 1.8 377 Khomas 15.8 13.7 1.7 0.4 889 Kunene 15.8 13.1 2.7 0.0 120 Ohangwena 16.5 12.8 3.4 0.2 469 Omaheke 20.6 17.7 2.5 0.4 114 Omusati 25.4 21.6 3.8 0.0 409 Oshana 20.8 17.1 2.7 1.0 382 Oshikoto 21.2 17.4 3.3 0.5 330 Otjozondjupa 19.1 15.6 3.6 0.0 249 Education No education 26.8 21.3 5.2 0.2 204 Primary 24.0 18.2 5.0 0.9 857 Secondary 19.7 16.1 3.3 0.3 2,821 More than secondary 16.9 14.4 1.8 0.6 361 Wealth quintile Lowest 24.0 18.0 5.3 0.7 686 Second 19.7 16.6 2.7 0.4 781 Middle 20.4 15.7 4.3 0.4 813 Fourth 21.9 17.6 3.7 0.6 1,023 Highest 17.9 15.3 2.2 0.4 939 Total 20.7 16.6 3.6 0.5 4,242 Note: Prevalence is adjusted for altitude and for smoking status if known using formulas in CDC, 1998. Total includes 2 women with missing information on smoking status. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 150 • Nutrition of Children and Adults 12.10.4 Anaemia in Men Table 12.11.2 presents anaemia levels for men age 15- 49. Overall, 12 percent of men are anaemic. Men age 15-19 are more likely to be anaemic (18 percent) than older men. The prevalence of anaemia is higher among men in rural (16 percent) than in urban (8 percent) areas. Across regions, men from Kavango (23 percent) have the highest anaemia prevalence, while men in Kunene have the lowest prevalence (5 percent). The prevalence of anaemia among men decreases with increasing wealth and education. 12.11 MICRONUTRIENT INTAKE AMONG MOTHERS Adequate micronutrient intake has important benefits for both women and their children. Breastfeeding children benefit from micronutrient supplementation that mothers receive, especially vitamin A. Iron supplementation of women during pregnancy protects the mother and infant against anaemia, which is considered a major cause of perinatal and maternal mortality. Anaemia also results in an increased risk of premature delivery and low birth weight. Finally, iodine deficiency is related to a number of adverse pregnancy outcomes including abortion, foetal brain damage and congenital malformation, stillbirth, and prenatal death. The 2013 NDHS collected data on consumption of vitamin A and iron-folic acid supplements among women age 15-49 with a child born in the past five years, use of deworming medication during the last pregnancy, and the percentage of women living in households with iodised salt. A single dose of vitamin A is typically given to women within 45 days of childbirth, aimed at increasing the mother’s vitamin A level and the content of the vitamin in her breast milk for the benefit of her child. Because of the risk of teratogenesis (abnormal development of the foetus) resulting from high doses of vitamin A during pregnancy, the dose should not be given to pregnant women. Table 12.12 shows that 58 percent of women with a child born in the five years before the survey received a vitamin A dose in the first two months after the birth of their last child. Vitamin A supplementation rates are highest among rural women (58 percent), women living in Otjozondjupa (69 percent), women with at least a secondary education (59-60 percent), and women in the middle wealth quintile (61 percent). With regard to iron supplementation during pregnancy, 39 percent of women reported taking iron tablets or syrup for 90 or more days during the pregnancy of their most recent birth, as recommended. Only 12 percent did not take any iron supplements during pregnancy. Women living in Ohangwena were least likely to have taken iron tablets during their last pregnancy for the recommended period of time (25 percent), while women in Kunene were most likely to have done so (67 percent). Seven percent of women took deworming medication during the pregnancy of their most recent birth. Women residing in Kavango (17 percent), those with a primary education (11 percent), and those in the lowest quintile (11 percent) were most likely to take deworming medicine. Table 12.11.2 Prevalence of anaemia in men Percentage of men age 15-49 with anaemia, by background characteristics, Namibia 2013 Anaemia status by haemoglobin level Background characteristic Any anaemia <13.0 g/dl Number of men Age 15-19 18.4 830 20-29 6.1 1,275 30-39 10.5 840 40-49 15.7 548 Smoking status Smokes cigarettes/ tobacco 9.8 694 Does not smoke 12.0 2,798 Residence Urban 7.5 1,883 Rural 16.3 1,609 Region Zambezi 11.1 187 Erongo 8.9 327 Hardap 10.0 138 //Karas 7.7 139 Kavango 22.9 283 Khomas 6.6 774 Kunene 5.4 93 Ohangwena 13.2 307 Omaheke 7.1 97 Omusati 16.5 323 Oshana 10.5 301 Oshikoto 18.8 301 Otjozondjupa 9.1 222 Education No education 13.5 285 Primary 17.8 861 Secondary 9.9 2,073 More than secondary 2.4 273 Wealth quintile Lowest 21.7 550 Second 12.8 708 Middle 10.5 789 Fourth 10.6 796 Highest 4.1 649 Total 15-49 11.6 3,492 Note: Prevalence is adjusted for altitude and for smoking status, if known, using formulas in CDC, 1998. Nutrition of Children and Adults • 151 Seventy-six percent of women with a child born in the last five years live in households with iodised salt. The percentage of women who live in households with iodised salt is higher in urban areas (90 percent) than in rural areas (62 percent). Omusati and Oshikoto (56 percent each) have the lowest proportion of women living in households with iodised salt. The percentage of women living in households with iodised salt increases with increasing education and household wealth. Table 12.12 Micronutrient intake among mothers Among women age 15-49 with a child born in the past five years, the percentage who received a vitamin A dose in the first two months after the birth of the last child, the percent distribution by number of days they took iron tablets or syrup during the pregnancy of the last child, and the percentage who took deworming medication during the pregnancy of the last child, and among women age 15-49 with a child born in the past five years and who live in households that were tested for iodised salt, the percentage who live in households with iodised salt, by background characteristics, Namibia 2013 Percentage who received vitamin A dose postpartum1 Among women with a child born in the past five years: Among women with a child born in the last five years who live in households that were tested for iodised salt: Number of days women took iron tablets during pregnancy of last birth Percentage of women who took deworming medication during pregnancy of last birth Number of women Background characteristic None <60 60-89 90+ Don’t know/ missing Total Percentage living in households with iodised salt2 Number of women Age 15-19 50.4 11.1 24.0 5.7 34.3 24.9 100.0 7.1 263 70.5 249 20-29 57.1 11.2 19.0 6.4 37.1 26.3 100.0 6.9 1,910 77.1 1,813 30-39 60.0 12.8 14.8 5.4 40.7 26.3 100.0 6.9 1,308 76.8 1,239 40-49 57.1 11.5 14.7 3.8 41.7 28.3 100.0 6.0 360 73.7 341 Residence Urban 57.3 12.3 15.2 4.3 45.2 23.0 100.0 6.1 1,970 89.6 1,879 Rural 58.0 11.2 20.1 7.2 31.5 30.0 100.0 7.6 1,871 61.9 1,763 Region Zambezi 56.5 10.5 23.2 4.5 35.7 26.1 100.0 5.6 239 96.4 215 Erongo 56.1 9.2 8.4 6.1 63.0 13.4 100.0 5.1 285 93.5 268 Hardap 60.3 7.9 18.6 5.7 51.3 16.5 100.0 7.0 133 77.6 124 //Karas 65.4 10.2 19.8 9.4 43.7 16.8 100.0 7.3 136 86.8 130 Kavango 55.2 5.6 39.4 4.6 35.1 15.3 100.0 17.3 448 79.4 415 Khomas 53.4 18.8 14.9 2.5 40.1 23.7 100.0 5.4 771 92.7 742 Kunene 47.2 7.3 5.8 8.3 66.7 11.9 100.0 3.7 133 71.5 117 Ohangwena 59.4 9.1 13.7 5.0 25.0 47.2 100.0 5.7 440 63.4 429 Omaheke 50.5 10.2 10.0 9.2 39.8 30.9 100.0 6.3 107 60.6 98 Omusati 67.4 21.7 11.6 11.5 26.4 28.8 100.0 1.1 350 55.7 338 Oshana 58.4 8.1 26.9 4.1 25.8 35.1 100.0 8.3 261 67.0 260 Oshikoto 52.4 5.5 13.7 9.7 42.0 29.1 100.0 5.8 290 56.1 281 Otjozondjupa 69.4 13.2 8.8 4.3 39.8 33.9 100.0 7.4 248 69.7 226 Education No education 44.8 19.4 14.8 6.2 30.1 29.4 100.0 5.0 218 60.4 194 Primary 54.1 13.3 21.3 7.3 29.6 28.4 100.0 10.6 836 67.2 772 Secondary 59.8 10.4 16.5 5.6 41.7 25.8 100.0 5.7 2,517 78.2 2,417 More than secondary 58.6 13.2 17.6 2.4 43.5 23.3 100.0 7.0 271 96.5 259 Wealth quintile Lowest 52.9 11.4 23.7 6.2 27.3 31.5 100.0 10.9 756 63.4 695 Second 60.3 13.3 19.3 7.1 30.9 29.4 100.0 6.4 819 65.2 775 Middle 61.0 11.5 15.8 7.5 40.7 24.5 100.0 6.6 807 69.5 776 Fourth 58.3 10.4 16.2 4.5 44.9 24.0 100.0 4.6 846 88.4 810 Highest 54.5 12.4 11.8 2.8 51.1 21.9 100.0 5.8 614 98.1 586 Total 57.6 11.8 17.5 5.8 38.5 26.4 100.0 6.9 3,842 76.2 3,642 1 In the first 2 months after delivery of last birth 2 Excludes women in households where salt was not tested Malaria • 153 MALARIA 13 alaria is one of the leading causes of death in sub-Saharan Africa. Although preventable and curable, the disease remains a public health problem in Namibia. Malaria is endemic in several regions, including Zambezi, Kavango, Ohangwena, Omusati, Oshana, Kunene, Oshikoto and parts of the Otjozondjupa and Omaheke. This chapter presents data that are useful for assessing the implementation of malaria control strategies, including indoor residual spraying of dwellings with insecticides, the availability and use of mosquito nets, the prophylactic and therapeutic use of antimalarial medicines, and the collection for diagnostic test for children with fever. 13.1 OWNERSHIP OF MOSQUITO NETS The use of ITNs is a primary health intervention designed to reduce malaria transmission in Namibia. An ITN is a factory-treated net that does not require any further treatment or a net that has been soaked with insecticide within the past 12 months. Long-lasting insecticidal nets (LLINs) are factory- treated mosquito nets made with netting material that has insecticide incorporated within or bound around the fibres. The current generation of LLINs lasts three to five years, after which the net should be replaced. The use of long-lasting nets is highly recommended as they greatly reduce the cost and the operational difficulties associated with retreatment of nets (MoHSS, 2005). In Namibia, most of the mosquito nets are provided free of charge by the Ministry of Health and Social services (MoHSS). All households in the 2013 NDHS were asked whether they owned mosquito nets and, if so, how many. Table 13.1 shows household ownership of nets by type (any type, ITN, or LLIN) and average number of nets per household, by background characteristics. Overall, 35 percent of households in Namibia own at least one net, regardless of type. Twenty-four percent of households own at least one net that meets one of the ITN criteria (i.e., a factory-treated net that does not require retreatment, a pretreated net obtained within the previous 12 months, or a net soaked in insecticide at some time within the 12 M Key Findings • Thirty-five percent of households have at least one mosquito net; 24 percent have at least one insecticide-treated mosquito net (ITN), the majority of which are long-lasting insecticidal nets (23 percent). • Sixteen percent of households reported that they had received indoor residual spraying during the past 12 months. • On the night before the survey, only 6 percent of children under age 5 slept under an ITN. Among households with at least one ITN, 18 percent of children under age 5 slept under an ITN. • Overall, 4 percent of pregnant women slept under an ITN the night before the survey. Among pregnant women living in households that possess an ITN, 14 percent slept under an ITN the night before the survey. • Five percent of women who had their last birth in the two years preceding the survey received intermittent preventive treatment during their pregnancy; that is, they took two or more doses of sulfadoxine and pyrimethamine (SP)/Fansidar and received at least one during an antenatal care visit. • Three percent of children age 6-59 months had a low haemoglobin level (less than 8.0 g/dl), indicating possible malarial infection. 154 • Malaria months prior to the survey). The majority of these ITNs are long-lasting insecticidal nets; 23 percent of households own at least one LLIN. There has been an increase in the household ownership of any nets over the last six years from 25 percent in the 2006-07 NDHS to 35 percent in the 2013 NDHS. Ownership of ITNs is higher in rural households than in urban households (34 percent and 15 percent, respectively). Among regions, Erongo and //Karas have the lowest percentage of households that own an ITN (4 percent), while Zambezi has the highest percentage (59 percent each). ITN ownership decreases as household wealth increases from 33 percent of households in the lowest wealth quintile to 13 percent in the highest wealth quintile. Although mosquito net ownership is a key indicator of the success of malaria control measures, it is also important to determine if a household has a sufficient number of nets for those sleeping within the home. Households in Namibia own, on average, about one ITN. Universal net coverage within the population can be measured by assuming that each net is shared by two people in the household. Table 13.1 also shows the percentage of households with at least one mosquito net for every two persons who stayed in the household the night before the interview. Eighteen percent of households in Namibia had at least one mosquito net of any type for every two persons who stayed in the household the night before the survey; 12 percent had at least one ITN for every two people. M al ar ia • 1 55 Ta bl e 13 .1 H ou se ho ld p os se ss io n of m os qu ito n et s P er ce nt ag e of h ou se ho ld s w ith a t l ea st o ne m os qu ito n et (t re at ed o r u nt re at ed ), in se ct ic id e- tre at ed n et (I TN ), an d lo ng -la st in g in se ct ic id al n et (L LI N ); av er ag e nu m be r o f n et s, IT N s, a nd L LI N s pe r h ou se ho ld ; a nd pe rc en ta ge o f h ou se ho ld s w ith a t l ea st o ne n et , I TN , a nd L LI N p er tw o pe rs on s w ho s ta ye d in th e ho us eh ol d la st n ig ht , b y ba ck gr ou nd c ha ra ct er is tic s, N am ib ia 2 01 3 P er ce nt ag e of h ou se ho ld s w ith a t l ea st o ne m os qu ito n et A ve ra ge n um be r o f n et s pe r h ou se ho ld N um be r o f ho us eh ol ds P er ce nt ag e of h ou se ho ld s w ith a t l ea st o ne n et fo r e ve ry tw o pe rs on s w ho s ta ye d in th e ho us eh ol d la st n ig ht 1 N um be r o f ho us eh ol ds w ith at le as t o ne pe rs on w ho st ay ed in th e ho us eh ol d la st ni gh t B ac kg ro un d ch ar ac te ris tic A ny m os qu ito ne t In se ct ic id e- tre at ed m os qu ito n et (IT N )2 Lo ng -la st in g in se ct ic id al n et (L LI N ) A ny m os qu ito ne t In se ct ic id e- tre at ed m os qu ito n et (IT N )2 Lo ng -la st in g in se ct ic id al n et (L LI N ) A ny m os qu ito ne t In se ct ic id e- tre at ed m os qu ito n et (IT N )2 Lo ng -la st in g in se ct ic id al n et (L LI N ) R es id en ce U rb an 25 .0 15 .2 13 .9 0. 4 0. 2 0. 2 5, 12 1 13 .9 8. 1 7. 4 5, 08 8 R ur al 45 .1 34 .3 32 .3 0. 9 0. 7 0. 7 4, 72 8 22 .4 16 .3 15 .2 4, 70 6 R eg io n Za m be zi 75 .5 58 .8 53 .8 1. 5 1. 2 1. 1 54 1 46 .5 35 .7 32 .2 54 1 E ro ng o 6. 1 4. 1 4. 0 0. 1 0. 1 0. 1 93 0 3. 2 2. 5 2. 4 92 2 H ar da p 19 .0 12 .0 10 .4 0. 3 0. 2 0. 1 38 1 7. 2 4. 8 4. 1 37 9 //K ar as 11 .0 4. 1 3. 3 0. 1 0. 1 0. 0 40 6 5. 2 2. 2 1. 7 40 1 K av an go 43 .4 40 .6 39 .5 0. 9 0. 9 0. 8 73 7 18 .9 17 .6 17 .0 73 4 K ho m as 17 .4 6. 7 4. 7 0. 3 0. 1 0. 1 2, 01 5 9. 0 2. 9 2. 1 2, 00 3 K un en e 28 .2 24 .2 23 .7 0. 4 0. 4 0. 3 35 4 14 .4 12 .2 11 .8 35 4 O ha ng w en a 56 .1 37 .0 32 .9 1. 3 0. 9 0. 8 90 0 29 .7 19 .1 17 .1 89 5 O m ah ek e 30 .8 20 .4 19 .5 0. 5 0. 3 0. 3 33 5 14 .6 7. 6 7. 1 33 2 O m us at i 42 .2 31 .6 31 .0 0. 8 0. 6 0. 6 94 9 18 .3 12 .6 12 .4 94 8 O sh an a 52 .5 41 .8 41 .6 0. 9 0. 7 0. 7 83 1 29 .5 22 .3 22 .2 83 1 O sh ik ot o 52 .0 38 .7 36 .5 1. 1 0. 7 0. 7 81 7 29 .1 20 .1 18 .5 80 9 O tjo zo nd ju pa 29 .3 15 .2 13 .6 0. 5 0. 2 0. 2 65 2 14 .8 6. 1 5. 3 64 5 W ea lth q ui nt ile Lo w es t 42 .5 32 .7 30 .8 0. 8 0. 6 0. 6 1, 73 7 19 .8 14 .9 13 .9 1, 73 3 S ec on d 38 .8 29 .5 27 .9 0. 7 0. 6 0. 5 1, 91 0 20 .3 14 .0 13 .5 1, 89 5 M id dl e 40 .6 28 .7 26 .7 0. 7 0. 5 0. 5 1, 95 4 21 .3 14 .3 13 .0 1, 94 5 Fo ur th 30 .3 20 .6 19 .0 0. 6 0. 4 0. 4 2, 13 6 16 .3 10 .9 9. 9 2, 11 6 H ig he st 23 .3 12 .7 11 .6 0. 5 0. 2 0. 2 2, 11 1 13 .1 6. 8 6. 2 2, 10 4 To ta l 34 .7 24 .4 22 .7 0. 7 0. 5 0. 4 9, 84 9 18 .0 12 .0 11 .1 9, 79 3 1 D e fa ct o ho us eh ol d m em be rs 2 A n in se ct ic id e- tre at ed n et ( IT N ) is ( 1) a fa ct or y- tre at ed n et th at d oe s no t r eq ui re a ny fu rth er tr ea tm en t ( LL IN ), (2 ) a pr et re at ed n et o bt ai ne d w ith in th e pa st 1 2 m on th s, o r (3 ) a ne t t ha t h as b ee n so ak ed w ith in se ct ic id e w ith in th e pa st 1 2 m on th s. Malaria • 155 156 • Malaria 13.2 INDOOR RESIDUAL SPRAYING In Namibia, indoor residual spraying (IRS) is part of the integrated vector management strategy, which is a key component of malaria prevention. IRS has a significant impact on the mosquito population and, therefore, can lead to rapid reductions in malaria transmission and subsequent mortality. IRS involves spraying of the interior walls with insecticide with the goal of killing mosquitoes when they rest on the sprayed wall. IRS reduces the mosquito population and, in turn, human-vector contact. The country has adopted selective households residual spraying with the goal to maintain 80 percent or more coverage. The appropriate period for indoor spraying of houses is between the months of October to January, just after the peak rainy season. The MoHSS is responsible for spraying rural areas outside of municipal boundaries; while in urban areas, this responsibility falls under the respective local authority (MoHSS, 2005). To obtain information on the prevalence of indoor residual spraying, all households interviewed in the 2013 NDHS were asked whether the interior walls of their dwelling had been sprayed to protect against mosquitoes during the 12-month period before the survey and, if so, who had sprayed the dwelling. Table 13.2 shows that 16 percent of households had been sprayed in the past 12 months. There is a dramatic difference in IRS by residence, with rural households nearly 10 times as likely as urban households to report receiving IRS (29 percent versus 3 percent). By region, 2 percent or less of households in Erongo, Table 13.2 Indoor residual spraying against mosquitoes Percentage of households in which someone has come into the dwelling to spray the interior walls against mosquitoes (IRS) in the past 12 months, the percentage of households with at least one ITN and/or IRS in the past 12 months, and the percentage of households with at least one ITN for every two persons and/or IRS in the past 12 months, by background characteristics, Namibia 2013 Background characteristic Percentage of households with IRS1 in the past 12 months Percentage of households with at least one ITN2 and/or IRS in the past 12 months Percentage of households with at least one ITN2 for every two persons and/or IRS in the past 12 months Number of households Residence Urban 3.0 17.0 10.6 5,121 Rural 29.0 49.7 38.8 4,728 Region Zambezi 35.0 67.7 54.9 541 Erongo 0.3 4.3 2.7 930 Hardap 0.4 12.4 5.2 381 //Karas 1.3 5.0 3.2 406 Kavango 45.9 64.9 55.4 737 Khomas 0.6 7.2 3.5 2,015 Kunene 32.5 43.6 38.1 354 Ohangwena 22.3 50.3 37.5 900 Omaheke 2.1 21.9 9.2 335 Omusati 13.8 40.2 24.5 949 Oshana 22.7 53.6 40.8 831 Oshikoto 32.3 56.8 45.0 817 Otjozondjupa 10.7 22.9 15.4 652 Wealth quintile Lowest 31.2 51.0 40.5 1,737 Second 21.7 40.3 30.7 1,910 Middle 15.5 36.2 25.9 1,954 Fourth 9.6 25.6 18.1 2,136 Highest 3.0 14.5 9.1 2,111 Total 15.5 32.7 24.1 9,849 1 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non-governmental organisation 2 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), (2) a pretreated net obtained within the past 12 months, or (3) a net that has been soaked with insecticide within the past 12 months Malaria • 157 Hardap, //Karas, Khomas, and Omaheke reported having been sprayed, compared with 32-46 percent in malaria-endemic regions such as Zambezi, Kavango, Kunene, or Oshikoto. Wealthier households are much less likely to have been sprayed when compared with households in the lower quintiles. For example, only 3 percent of households in the highest wealth quintile have been sprayed, as compared with 31 percent of households in the lowest quintile. The combination of IRS and use of an ITN offers the greatest protection against malaria. Overall, 33 percent of households are protected because they own at least one ITN and/or they have been sprayed in the past 12 months. However, ITNs must be available in sufficient quantities for use by household members. About one-fourth (24 percent) of all households have at least one ITN for every two persons and/or have been sprayed in the past 12 months. Differences by residence, region, and wealth are similar to those observed for IRS. Ninety percent of household are sprayed by government workers, local government or municipal authorities, and only 1 percent are sprayed by private sector companies (data not shown). 13.3 ACCESS TO AN INSECTICIDE-TREATED NET The 2013 NDHS gathered data on the proportion of the population that could sleep under an ITN if each ITN in the household were used by up to two people. This population is referred to as having access to an ITN. Coupled with mosquito net usage, ITN access can provide useful information on the magnitude of the gap between ITN ownership and use (in other words, the population with access to an ITN but not using it). If the difference between these indicators is substantial, the programme may need to focus on behaviour change and how to identify the main drivers of and barriers to ITN use in order to design an appropriate intervention. Such an analysis would help ITN programmes determine whether they need to achieve higher ITN coverage, promote ITN use, or both. Table 13.3 shows the percent distribution of the de facto household population by the number of ITNs owned by the household, according to the number of persons who stayed in the household the night before the survey. Nationally, 18 percent of the population in Namibia has access to an ITN. Access to ITNs fluctuates only slightly with the household size. It is lowest among households with eight or more persons (16 percent). Table 13.3 Access to an insecticide-treated net (ITN) Percent distribution of the de facto household population by number of ITNs the household owns, according to number of persons who stayed in the household the night before the survey, Namibia 2013 Number of persons who stayed in the household the night before the survey Total Number of ITNs 1 2 3 4 5 6 7 8+ 0 82.0 81.1 77.2 75.9 72.4 69.7 69.2 67.7 72.4 1 15.1 11.8 12.0 9.5 10.7 11.3 11.7 7.6 10.2 2 1.9 5.5 7.1 7.9 8.6 9.2 8.5 7.9 7.7 3 0.8 1.4 3.4 5.7 7.5 8.1 8.2 12.2 7.7 4 0.0 0.0 0.2 0.4 0.3 1.1 1.2 1.7 0.9 5 0.1 0.1 0.1 0.2 0.1 0.2 0.6 1.5 0.6 6 0.0 0.0 0.0 0.3 0.2 0.1 0.3 0.7 0.3 7+ 0.0 0.0 0.0 0.0 0.2 0.2 0.2 0.8 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,718 3,102 4,308 5,224 5,582 5,227 4,070 12,164 41,396 Percent with access to an ITN1 18.0 18.9 18.8 19.3 19.5 19.7 17.6 16.2 18.1 1 Percentage of the de facto household population who could sleep under an ITN if each ITN in the household were used by up to two people Figure 13.1 shows the percentage of the household population with access to an ITN, by selected background characteristics. A lower percentage of urban households than rural households have access to an ITN (25 percent and 11 percent, respectively). By region, the percentage of the population with access to an ITN is highest in Zambezi (46 percent) and lowest in //Karas (2 percent). The percentage of the household population with access to an ITN decreases as wealth increases, from 23 percent of the population in the lowest quintile to 10 percent in the highest quintile. 158 • Malaria Figure 13.1 Percentage of the de facto population with access to an ITN in the household 13.4 USE OF MOSQUITO NETS Community-level protection against malaria helps reduce the spread of the disease and offers an additional level of protection for those most vulnerable: children under age 5 and pregnant women. This section describes use of mosquito nets among all persons in the household, among children under age 5, and among pregnant women. 13.4.1 Use of Mosquito Nets by Persons in the Household Mosquito net coverage of the entire population is necessary to accomplish large reductions in the malaria burden. Although vulnerable groups (e.g., children under age 5 and pregnant women) should still be prioritised, the communal benefits of wide-scale ITN use by older children and adults should be promoted and evaluated by national malaria control programmes (Killeen et al., 2007). Table 13.4 shows that, overall, only 5 percent of the household population slept under a net the night before the survey; 4 percent slept under ITNs, nearly all of which are LLINs. Children under age 5 are most likely to use ITNs (6 percent). Substantial differences are observed by region, with Zambezi having the highest percentage of household members who slept under an ITN the night before the survey (19 percent), followed by Kavango (10 percent), compared with 7 percent or less of the population in the other regions. The percentage of the population sleeping under an ITN decreases with wealth. Twenty-three percent of the household population slept under an ITN the night before the survey or in a dwelling that was sprayed during the 12 months preceding the survey. Differences in the percentage of the household population protected in this way by background characteristics are similar to those observed for the percentage of household members who slept under an ITN the night before the survey. In households that own at least one ITN, 14 percent of household members slept under an ITN the night before the survey. Those most likely to sleep under an ITN were children under age 5 (18 percent), household members living in urban areas (16 percent), those living in Zambezi (32 percent), and the population living in the poorest households (18 percent). 11 25 46 3 7 2 26 4 16 28 15 20 31 28 10 23 22 21 16 10 18 Residence Urban Rural Region Zambezi Erongo Hardap //Karas Kavango Khomas Kunene Ohangwena Omaheke Omusati Oshana Oshikoto Otjozondjupa Wealth quintile Lowest Second Middle Fourth Highest Total Percent NDHS 2013 Malaria • 159 Table 13.4 Use of mosquito nets by persons in the household Percentage of the de facto household population who slept the night before the survey under a mosquito net (treated or untreated), under an insecticide-treated net (ITN), under a long-lasting insecticidal net (LLIN), and under an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among the de facto household population in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Namibia 2013 Household population Household population in households with at least one ITN1 Background characteristic Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number Percentage who slept under an ITN1 last night Number Age <5 7.7 5.6 5.1 26.4 5,711 17.8 1,778 5-14 3.9 3.1 2.9 27.0 10,153 10.1 3,135 15-34 4.6 3.5 3.3 19.5 14,226 13.9 3,551 35-39 5.4 3.9 3.6 17.9 6,032 16.6 1,436 50+ 6.3 4.9 4.8 26.2 5,245 16.8 1,536 Sex Male 4.9 3.6 3.4 22.8 19,621 13.5 5,311 Female 5.4 4.2 3.9 23.0 21,774 14.8 6,134 Residence Urban 3.9 2.7 2.4 6.6 19,291 16.4 3,140 Rural 6.3 5.0 4.8 37.2 22,106 13.4 8,304 Region Zambezi 24.3 19.0 17.4 48.6 2,165 31.8 1,294 Erongo 0.2 0.1 0.1 0.5 3,016 2.6 156 Hardap 0.9 0.3 0.3 0.6 1,455 2.3 182 //Karas 1.4 0.8 0.6 2.1 1,473 17.9 63 Kavango 10.4 9.9 9.6 55.5 4,252 24.8 1,699 Khomas 1.3 0.7 0.4 1.3 7,693 10.8 486 Kunene 3.4 2.7 2.5 39.2 1,266 10.3 332 Ohangwena 7.1 4.6 4.1 30.7 4,857 11.8 1,907 Omaheke 1.1 0.7 0.7 2.6 1,152 2.4 320 Omusati 3.1 2.3 2.3 18.0 4,823 6.9 1,598 Oshana 8.0 6.8 6.8 39.0 3,324 15.0 1,508 Oshikoto 4.7 2.8 2.5 40.8 3,462 6.7 1,462 Otjozondjupa 1.6 0.7 0.7 13.0 2,459 4.1 437 Wealth quintile Lowest 6.9 6.0 5.6 39.2 8,260 17.5 2,820 Second 6.7 5.6 5.3 33.5 8,257 16.9 2,732 Middle 5.5 3.5 3.3 23.1 8,288 10.8 2,714 Fourth 4.3 3.1 2.9 14.6 8,286 12.6 2,061 Highest 2.4 1.4 1.2 4.2 8,304 10.3 1,117 Total 5.2 3.9 3.7 22.9 41,396 14.2 11,445 Note: Total includes 29 cases for which information on age is missing and 2 cases for which information on sex is missing. 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), (2) a pretreated net obtained within the past 12 months, or (3) a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non-governmental organisation. Figure 13.2 presents data on ownership, access, and use of ITNs in Namibia. About one-fourth of households (24 percent) own at least one ITN. However, only 12 percent of households have enough ITNs to cover their entire household population (assuming that one ITN is used by two persons). Eighteen percent of household members have access to an ITN, and 4 percent slept under an ITN the night before the survey. A comparison of the first two columns indicates that households in Namibia do not have a sufficient number of ITNs to cover the population sleeping in the household, and a comparison of the second two columns suggest that ITN use is much lower than ITN access. 160 • Malaria Figure 13.2 Ownership, access, and use of ITNs 13.4.2 Use of Existing Mosquito Nets Table 13.5 presents data on use of existing ITNs. Overall, 21 percent of ITNs were used by someone in the household the night before the survey. Twenty-four percent of ITNs were used in urban areas, as compared with 20 percent in rural areas. Zambezi (37 percent) had the highest levels of ITN usage, while Erongo had the lowest (4 percent). 13.4.3 Use of Mosquito Nets by Children under Age 5 Malaria is endemic in some regions of Namibia. Those living in areas of high malaria transmission acquire immunity to the disease over time (Doolan et al., 2009). Acquired immunity is not the same as sterile immunity; that is, acquired immunity does not prevent infection but rather protects against severe disease and death. Age is an important factor in determining levels of acquired immunity to malaria. For about six months following birth, antibodies acquired from the mother during pregnancy protect children born in areas of endemic malaria. This immunity gradually disappears, and children start to develop their own immunity. The pace at which immunity develops depends on the level of exposure to malarial infection; in highly malaria-endemic areas, children are thought to attain a high level of immunity by their fifth birthday. Such children may experience episodes of illness but usually do not suffer from severe, life- threatening malaria. Immunity in areas of low malaria transmission is acquired more slowly. Malaria affects all age groups of the population. 24 12 18 4 Percent of households with at least one ITN Percent of households with at least one ITN for every two persons who stayed in the household last night Percent of the household population with access to an ITN within their household Percent of the household population who slept under an ITN Percent NDHS 2013 Table 13.5 Use of existing ITNs Percentage of insecticide-treated nets (ITNs) that were used by anyone the night before the survey, by background characteristics, Namibia 2013 Background characteristic Percentage of existing ITNs1 used last night Number of ITNs1 Residence Urban 24.0 1,263 Rural 20.0 3,264 Region Zambezi 37.2 631 Erongo 4.3 57 Hardap 5.7 65 //Karas (26.7) (21) Kavango 37.3 630 Khomas 17.1 174 Kunene 18.5 126 Ohangwena 16.6 819 Omaheke 5.0 97 Omusati 10.2 558 Oshana 23.0 610 Oshikoto 12.0 594 Otjozondjupa 8.7 143 Wealth quintile Lowest 26.1 1,093 Second 24.9 1,060 Middle 17.4 1,033 Fourth 18.8 834 Highest 13.9 506 Total 21.1 4,527 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), (2) a pretreated net obtained within the past 12 months, or (3) a net that has been soaked with insecticide within the past 12 months. Malaria • 161 Table 13.6 shows the use of mosquito nets by children under age 5. Only 8 percent of children slept under a mosquito net the night before the survey; 6 percent slept under an ITN, nearly all of which are LLIN. Additionally, 26 percent of children either slept under an ITN the night before the survey or slept within a dwelling that had been sprayed in the past 12 months. Among households with at least one ITN, 18 percent of children under age 5 slept under an ITN the night before the survey. The percentage of children under age 5 in all the households who slept under an ITN the night before the survey decreases with age and somewhat with wealth, and it is slightly higher in rural areas than urban. The largest variation is by region, with Zambezi having the highest percentage of children under age 5 who slept under an ITN (24 percent) compared with 1 percent or less in several regions. Table 13.6 Use of mosquito nets by children Percentage of children under 5 years of age who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide- treated net (ITN), under a long-lasting insecticidal net (LLIN), and under either an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among children under 5 years of age in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Namibia 2013 Children under age 5 in all households Children under age 5 in households with at least one ITN1 Background characteristic Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of children Percentage who slept under an ITN1 last night Number of children Age (in months) <12 10.5 7.3 6.5 27.3 1,172 26.2 326 12-23 8.6 6.5 6.1 26.3 1,136 20.4 363 24-35 6.8 5.1 4.8 26.6 1,188 16.8 364 36-47 6.2 4.6 4.3 25.9 1,134 13.6 382 48-59 6.1 4.1 4.0 25.9 1,082 12.8 344 Sex Male 8.3 5.9 5.5 26.7 2,786 18.4 893 Female 7.1 5.2 4.8 26.2 2,923 17.3 886 Residence Urban 6.9 4.5 3.8 8.8 2,237 22.5 444 Rural 8.1 6.2 6.0 37.8 3,474 16.3 1,335 Region Zambezi 31.0 23.5 21.2 50.7 355 38.9 214 Erongo 0.7 0.3 0.0 0.8 308 * 20 Hardap 2.4 0.5 0.5 0.8 205 3.4 31 //Karas 3.0 1.5 1.0 2.3 176 * 9 Kavango 13.1 12.3 11.9 55.5 683 32.5 258 Khomas 1.9 1.1 0.6 1.9 792 (15.1) 56 Kunene 2.7 1.7 1.3 36.7 224 5.9 63 Ohangwena 9.4 5.8 5.2 30.3 845 14.7 333 Omaheke 1.5 0.5 0.5 3.5 182 1.4 57 Omusati 4.9 3.3 3.3 18.5 667 10.0 220 Oshana 9.7 8.5 8.5 42.8 399 16.8 203 Oshikoto 7.8 4.8 4.5 44.5 501 10.1 238 Otjozondjupa 3.0 0.9 0.9 17.5 373 4.4 76 Wealth quintile Lowest 8.6 7.2 6.8 39.1 1,417 20.3 502 Second 8.3 6.6 6.2 34.2 1,307 19.0 454 Middle 7.4 4.4 4.1 24.8 1,179 13.2 395 Fourth 6.8 4.8 4.4 16.5 1,025 16.8 291 Highest 6.4 3.5 2.9 6.0 783 20.2 136 Total 7.7 5.6 5.1 26.4 5,711 17.8 1,778 Note: Table is based on children who stayed in the household the night before the interview. Total includes 1 case for whom information on age is missing. 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 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), (2) a pretreated net obtained within the past 12 months, or (3) a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non-governmental organisation. 13.4.4 Use of Mosquito Nets by Pregnant Women In malaria-endemic areas, adults usually have acquired some degree of immunity to severe, life- threatening malaria. However, pregnancy leads to suppression of the immune system; thus, pregnant 162 • Malaria women, especially those in their first pregnancy, have a higher risk of malarial infection. Moreover, malaria among pregnant women may be asymptomatic. Malaria during pregnancy is a major contributor to low birth weight, maternal anaemia, infant mortality, spontaneous abortion, and stillbirth. Pregnant women can reduce the risk of these adverse effects of malaria by sleeping under insecticide-treated mosquito nets. Table 13.7 shows the use of mosquito nets by pregnant women, according to background characteristics. Overall, only 4 percent of pregnant women age 15-49 slept under any net the night before the survey (4 percent slept under an ITN and 3 percent slept under an LLIN). About one in five (19 percent) of pregnant women either slept under an ITN the night before the survey or slept in a dwelling that had been sprayed during the 12 months preceding the survey. Among households with at least one ITN, 14 percent of pregnant women slept under an ITN the night before the survey. ITN use by pregnant women is higher in rural than urban areas (7 percent versus 1 percent) and it is higher for women in the lowest two wealth quintiles (6-7 percent) than in the middle, fourth and highest wealth quintiles. The number of cases is too small to make meaningful comparisons by region. Table 13.7 Use of mosquito nets by pregnant women Percentages of pregnant women age 15-49 who, the night before the survey, slept under a mosquito net (treated or untreated), under an insecticide- treated net (ITN), under a long-lasting insecticidal net (LLIN), and under either an ITN or in a dwelling in which the interior walls have been sprayed against mosquitoes (IRS) in the past 12 months; and among pregnant women age 15-49 in households with at least one ITN, the percentage who slept under an ITN the night before the survey, by background characteristics, Namibia 2013 Among pregnant women age 15-49 in all households Among pregnant women age 15-49 in households with at least one ITN1 Background characteristic Percentage who slept under any net last night Percentage who slept under an ITN1 last night Percentage who slept under an LLIN last night Percentage who slept under an ITN1 last night or in a dwelling sprayed with IRS2 in the past 12 months Number of women Percentage who slept under an ITN1 last night Number of women Residence Urban 1.6 1.1 1.1 4.7 363 6.2 62 Rural 8.2 6.9 6.5 37.9 276 18.7 101 Region Zambezi (38.7) (32.2) (29.2) (44.8) 22 * 13 Erongo 0.0 0.0 0.0 0.0 50 * 6 Hardap * * * * 12 * 1 //Karas (2.1) (2.1) (0.0) (4.2) 24 * 1 Kavango 7.4 7.4 7.4 48.4 60 * 25 Khomas 0.0 0.0 0.0 0.0 140 * 10 Kunene (0.0) (0.0) (0.0) (36.6) 24 * 5 Ohangwena 4.0 2.7 2.7 25.5 97 (6.2) 42 Omaheke (0.0) (0.0) (0.0) (0.0) 22 * 6 Omusati (7.0) (7.0) (7.0) (19.1) 62 * 15 Oshana (8.1) (5.3) (5.3) (31.1) 51 * 19 Oshikoto (5.9) (2.4) (2.4) (41.5) 43 * 14 Otjozondjupa (0.0) (0.0) (0.0) (7.4) 31 * 6 Education No education 4.0 4.0 4.0 21.8 49 * 15 Primary 3.5 3.5 3.1 21.9 125 (11.4) 38 Secondary 5.5 4.1 3.9 19.8 401 15.9 104 More than secondary (0.0) (0.0) (0.0) (5.6) 64 * 6 Wealth quintile Lowest 6.8 5.7 5.7 37.6 107 (17.0) 36 Second 7.6 6.9 6.4 29.7 129 (22.6) 39 Middle 3.7 2.1 1.7 13.8 128 (9.1) 30 Fourth 4.0 3.0 3.0 15.5 157 (10.3) 46 Highest 0.3 0.3 0.3 0.9 118 * 12 Total 4.4 3.6 3.4 19.0 639 14.0 163 Note: Table is based on women who stayed in the household the night before the interview. Total includes 1 case for which information on education is missing. 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 An insecticide-treated net (ITN) is (1) a factory-treated net that does not require any further treatment (LLIN), (2) a pretreated net obtained within the past 12 months, or (3) a net that has been soaked with insecticide within the past 12 months. 2 Indoor residual spraying (IRS) is limited to spraying conducted by a government, private, or non-governmental organisation. Malaria • 163 13.5 USE OF INTERMITTENT PREVENTIVE TREATMENT OF MALARIA DURING PREGNANCY In line with the Namibia National Malaria Policy, chemoprophylaxis is only recommended for persons who are at risk of contracting malaria; non-immune travelers; and individuals living in malaria- endemic areas for a short time, such as labour force, police, and army. The risk of severe or fatal malaria is greatest in areas of unstable transmission and can cause maternal death, abortion, still birth, premature delivery, and low birth weight in infants. Sulphadoxine/pryrimethamine/Fansidar (SP/Fansidar) is recommended for intermittent preventive treatment during the first and second pregnancies. This regimen is beneficial in low- and high-transmission areas. Chemoprophylaxis is not recommended for third and subsequent pregnancies, as it does not confer additional protection against malaria. In areas where the prevalence of HIV is documented to be greater than 10 percent, a third dose of SP is given four weeks after the second dose (MoHSS, 2005). During antenatal care (ANC) visits, pregnant women are given the required dose of SP/Fansidar and urged to consume it immediately. Women in the 2013 NDHS who had a live birth in the two years preceding the survey were asked whether they took any antimalarial medications during the pregnancy leading to their most recent birth and, if so, which ones. Women were also asked whether the medicines they took were received during an antenatal care visit. It should be noted that obtaining information about medicines can be difficult because some respondents may not know or remember the name or the type of medicine that they received. Eight percent of pregnant women with a live birth in the two years preceding the survey reported taking at least one dose of SP/Fansidar during an ANC visit, and 5 percent reported taking two or more doses, at least one of which was received during an ANC visit (Table 13.8). The highest proportion of pregnant women who took two or more doses of SP/Fansidar and received at least one dose during an ANC visit is among women living in Oshana (13 percent), among those with more than secondary education (8 percent), and women in the middle wealth quintile (7 percent). 13.6 PREVALENCE, DIAGNOSIS, AND PROMPT TREATMENT OF CHILDREN WITH FEVER The diagnosis of malaria in Namibia is based on detection of parasites in the blood using a malaria rapid diagnostic test (MRDT), widely available at all public health facilities, and microscopy available at all the district hospitals, provided by National Institute of Pathology (NIP). Prompt and effective malaria treatment is essential to prevent the disease from becoming severe. Fever is a major manifestation of malaria in young children, although it also accompanies other illnesses. In malaria areas, it is important that children experiencing fever receive prompt testing for malaria parasites, either by rapid diagnostic test Table 13.8 Use of Intermittent Preventive Treatment (IPTp) by women during pregnancy Percentage of women age 15-49 with a live birth in the two years preceding the survey who, during the pregnancy preceding the last birth, received any SP/Fansidar during an ANC visit and who took at least two doses of SP/Fansidar and received at least one dose during an ANC visit, by background characteristics, Namibia 2013 Background characteristic Percentage who received any SP/Fansidar during an ANC visit Percentage who took 2+ doses of SP/Fansidar and received at least one during ANC visit Number of women with a live birth in the two years preceding the survey Residence Urban 7.2 5.1 925 Rural 7.7 4.8 1,022 Region Zambezi 6.3 1.7 112 Erongo 4.7 4.3 136 Hardap 0.9 0.9 73 //Karas 1.7 1.7 61 Kavango 13.1 8.9 231 Khomas 4.5 3.9 344 Kunene 4.4 0.8 69 Ohangwena 5.9 3.2 254 Omaheke 3.4 2.1 59 Omusati 7.2 5.3 189 Oshana 15.9 12.6 127 Oshikoto 12.7 7.9 154 Otjozondjupa 8.0 3.2 137 Education No education 3.5 1.6 110 Primary 7.6 5.0 438 Secondary 7.6 4.9 1,295 More than secondary 9.4 7.8 105 Wealth quintile Lowest 8.1 5.0 415 Second 6.3 4.4 439 Middle 9.2 6.8 423 Fourth 8.4 5.0 389 Highest 4.3 2.8 281 Total 7.5 4.9 1,947 164 • Malaria or by microscopy. The first-line treatment of choice in Namibia is artemether lumefantrine, one of the artemisinin-based combination therapies recommended for the treatment of uncomplicated malaria in all age groups except children under the age of 1 year and pregnant women in their first trimester who are treated with quinine as their first line of defense against malaria (MoHSS, 2005). Fever is a primary manifestation of malaria. Although fever occurs year round, malaria is most prevalent during the rainy season. Therefore, temporal factors must be taken into consideration when interpreting the occurrence of fever as an indicator of malaria prevalence. The Namibia Malaria Strategic Plan (2010-2016) envisioned that by 2013, 90 percent of all people with fever seek treatment within 24 hours of the onset of symptoms (MoHSS, 2010b). Malaria case management, one of the most fundamental strategic areas of malaria control, is the identification, diagnosis, and prompt treatment of all malaria cases with appropriate and effective antimalarial medicines. As almost all treatment of malarial fevers occurs at home, caregivers are often trained in providing prompt and effective management to prevent the fever from becoming severe, thus preventing severe malaria-related morbidity and mortality. In the 2013 NDHS, mothers were asked if their children under age 5 had experienced an episode of fever in the two weeks preceding the survey and, if so, whether treatment and advice were sought. Information was also collected on the type and timing of the treatment given. Table 13.9 shows the percentage of children under age 5 who had a fever in the two weeks preceding the survey and, among those with a fever, the percentage for whom advice or treatment was sought from a health facility, provider, or pharmacy; the percentage who had a drop of blood taken from a finger or heel (presumably for a malaria test); the percentage who took artemisinin-based combination therapy (ACT) or any antimalarial medicines; and the percentage who took malaria medicines on the same or next day. Twenty-four percent of children under age 5 had a fever during the two weeks preceding the survey. The prevalence of fever is highest among children under 12 months (31 percent) and children in Zambezi (50 percent). Children whose mothers have no education are the least likely to have had fever in the preceding two weeks (16 percent) when compared with children of mothers with any education (24-26 percent). There is no clear pattern in the relationship between fever prevalence and wealth. Advice or treatment was sought for 63 percent of children with a fever, and 22 percent had blood taken from a finger or heel for testing. Four percent of children who had a fever took ACT, and 3 percent took ACT the same or the next day. Seven percent of children with a fever took antimalarial medicines the same or next day. The differentials in treatment patterns in Table 13.9 must be interpreted with caution because of the comparatively small number of children with fever in some subgroups and the small percentage who took antimalarial medicines. Malaria • 165 Table 13.9 Prevalence, diagnosis, and prompt treatment of children with fever Percentage of children under age 5 with fever in the two weeks preceding the survey; and among children under age 5 with fever, the percentage for whom advice or treatment was sought, the percentage who had blood taken from a finger or heel, the percentage who took any artemisinin-based combination therapy (ACT), the percentage who took ACT the same or next day following the onset of fever, the percentage who took antimalarial medicines, and the percentage who took the medicines the same or next day following the onset of fever, by background characteristics, Namibia 2013 Among children under age 5: Among children under age 5 with fever: Background characteristic Percentage with fever in the two weeks preceding the survey Number of children Percentage for whom advice or treatment was sought1 Percentage who had blood taken from a finger or heel for testing Percentage who took any ACT Percentage who took any ACT same or next day Percentage who took antimalarial medicines Percentage who took antimalarial medicines same or next day Number of children Age (in months) <12 30.7 1,012 64.6 18.8 3.3 3.0 7.5 7.1 310 12-23 27.7 938 71.7 27.9 5.6 5.2 10.7 9.1 260 24-35 24.1 926 54.3 23.2 2.7 2.1 7.4 5.2 223 36-47 21.0 883 63.4 15.0 5.4 3.7 12.0 9.1 186 48-59 15.4 830 59.2 24.3 0.9 0.9 2.9 2.5 128 Sex Male 25.0 2,237 64.3 23.7 3.0 2.6 8.8 7.4 559 Female 23.3 2,351 62.4 19.8 4.5 3.8 8.1 6.6 547 Residence Urban 25.2 2,249 64.2 18.4 2.9 2.4 7.9 6.7 567 Rural 23.0 2,340 62.4 25.4 4.7 4.1 9.0 7.3 538 Region Zambezi 50.2 279 66.6 18.6 0.0 0.0 1.5 1.5 140 Erongo 22.6 320 71.1 21.2 0.0 0.0 15.2 13.8 72 Hardap 15.8 166 55.0 0.0 0.0 0.0 1.5 0.0 26 //Karas 20.8 160 58.6 6.6 0.0 0.0 6.6 6.6 33 Kavango 36.3 541 62.8 38.7 17.6 15.9 19.9 18.2 196 Khomas 26.3 858 55.4 7.5 0.8 0.0 7.7 6.2 225 Kunene 13.4 170 57.7 16.7 0.0 0.0 1.8 0.0 23 Ohangwena 18.8 561 66.1 30.5 0.0 0.0 4.5 2.1 105 Omaheke 23.4 143 61.9 7.2 0.0 0.0 0.9 0.0 33 Omusati 14.4 440 78.7 31.8 5.9 3.9 14.7 10.4 64 Oshana 17.5 300 77.9 34.6 0.0 0.0 1.7 0.0 53 Oshikoto 24.1 353 60.9 22.0 2.1 2.1 5.7 4.5 85 Otjozondjupa 16.7 298 55.7 18.7 0.0 0.0 1.6 1.6 50 Mother’s education No education 15.6 281 46.9 12.6 5.1 5.1 6.9 5.1 44 Primary 26.4 1,061 60.6 24.0 9.3 7.8 14.2 12.4 280 Secondary 24.0 2,948 65.3 22.1 1.7 1.6 6.2 4.9 707 More than secondary 24.9 300 65.0 16.5 1.6 0.0 9.4 7.8 75 Wealth quintile Lowest 25.0 988 57.7 27.0 8.3 7.4 12.0 10.2 247 Second 23.2 1,009 63.0 22.3 1.9 1.9 4.9 4.2 234 Middle 24.8 952 69.6 26.7 4.4 3.6 10.4 7.5 236 Fourth 22.2 954 63.0 18.0 3.1 2.1 9.5 8.5 212 Highest 25.8 686 63.7 12.0 0.0 0.0 4.4 3.8 177 Total 24.1 4,588 63.3 21.8 3.8 3.2 8.4 7.0 1,106 1 Excludes market and traditional practitioner Table 13.10 shows the sources of advice or treatment for children with fever in the two weeks preceding the survey. The public sector was the principal source for advice or treatment (81 percent), followed by the private sector (19 percent). Government health posts (51 percent) and government hospitals (26 percent) were the primary public sources of advice or treatment. Pharmacies (7 percent), private doctors (6 percent), and private hospitals or clinics (4 percent) were the primary private sources. Other sources accounted for treating 2 percent of children. 166 • Malaria Table 13.10 Source of advice or treatment for children with fever Percentage of children under age 5 with fever in the two weeks preceding the survey for whom advice or treatment was sought from specific sources and, among children under age five with fever in the two weeks preceding the survey for whom advice or treatment was sought, the percentage for whom advice or treatment was sought from specific sources, by background characteristics, Namibia 2013 Percentage for whom advice or treatment was sought from each source: Source Among children with fever Among children with fever for whom advice or treatment was sought Any public sector source 51.7 80.6 Government hospital 16.3 25.5 Government health centre 3.7 5.7 Government health post 32.5 50.7 Mobile clinic 0.3 0.5 Fieldworker 0.5 0.8 Any private sector source 12.0 18.7 Private hospital/clinic 2.8 4.4 Pharmacy 4.5 7.0 Private doctor 3.9 6.1 Mobile clinic 0.7 1.1 Any other source 1.3 2.1 Shop 0.3 0.4 Traditional practitioner 0.3 0.4 Other 0.8 1.3 Number of children 1,106 709 More than four in ten children under age 5 with a fever (45 percent) took ACT; 25 percent took quinine; and 48 percent took other antimalarials (data not shown due to the small numbers of children who had a fever and who took antimalarials). 13.7 PREVALENCE OF LOW HAEMOGLOBIN IN CHILDREN One of the objectives of the 2013 NHDS was to assess the prevalence of anaemia among children age 6-59 months. Table 12.7 in the chapter on nutrition presents the percentage of children who are anaemic (children are classified as anaemic if their haemoglobin level is below 11.0 g/dl and as severely anaemic if their haemoglobin level is below 7.0 g/dl). However, poor dietary intake of iron is only one of numerous causes of anaemia; malaria infection can also result in a person becoming anaemic. A haemoglobin concentration of less than 8.0 g/dl is considered low and may be an indication that an individual has malaria (Korenromp et al., 2004). Overall, only 3 percent of children age 6-59 months have a haemoglobin level less than 8.0 g/dl (Table 13.11). Children age 9-17 months (7-8 percent) and those residing in Erongo (7 percent), //Kavango (6 percent), and Kunene (5 percent) are most likely to have low haemoglobin levels. Malaria • 167 Table 13.11 Haemoglobin <8.0 g/dl in children Percentage of children age 6-59 months with haemoglobin lower than 8.0 g/dl, by background characteristics, Namibia 2013 Background characteristic Haemoglobin < 8.0 g/dl Number of children Age (in months) 6-8 1.6 135 9-11 8.3 126 12-17 6.6 252 18-23 2.1 244 24-35 3.2 559 36-47 0.7 491 48-59 0.9 490 Sex Male 2.9 1,136 Female 2.3 1,161 Mother’s interview status Interviewed 2.9 1,491 Not interviewed but in household 2.8 104 Not interviewed and not in the household1 2.1 702 Residence Urban 2.7 840 Rural 2.6 1,458 Region Zambezi 4.1 149 Erongo 6.8 116 Hardap 2.5 87 //Karas 3.4 71 Kavango 6.4 247 Khomas 1.7 269 Kunene 5.2 89 Ohangwena 0.7 360 Omaheke 0.5 79 Omusati 1.9 295 Oshana 0.0 165 Oshikoto 2.2 212 Otjozondjupa 2.0 159 Mother’s education2 No education 2.9 112 Primary 4.1 382 Secondary 2.3 1,014 More than secondary 4.0 86 Wealth quintile Lowest 2.6 588 Second 2.5 502 Middle 2.9 484 Fourth 3.2 464 Highest 1.4 259 Total 2.6 2,297 Note: Table is based on children who stayed in the household the night before the interview. Prevalence of anaemia is based on haemoglobin levels and is adjusted for altitude using CDC formulas (CDC, 1998). Haemoglobin is measured in grams per decilitre (g/dl). Total includes 2 cases for which information on mother’s education is missing. 1 Includes children whose mothers are deceased 2 For women who are not interviewed, information is taken from the Household Questionnaire. Excludes children whose mothers are not listed in the Household Questionnaire. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 169 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 14 cquired immune deficiency syndrome (AIDS) is caused by the human immunodeficiency virus (HIV), which weakens the immune system and makes the body susceptible to and unable to recover from other opportunistic diseases. The predominant mode of HIV transmission is through heterosexual intercourse, followed by perinatal transmission, in which the mother passes the virus to her child during pregnancy, delivery, or breastfeeding. Other modes of transmission include infected blood and unsafe injections. The Namibian response to HIV/AIDS has been aggressive and persistent. Namibia is in the fourth year of its five-year strategy to address HIV/AIDS within the country. This strategy addresses a number of factors important with respect to the future course of Namibia’s HIV epidemic (Ministry of Health and Social Services [MoHSS], 2010c), including efforts to increase levels of HIV/AIDS-related knowledge among the general population, decrease social stigmatisation of people living with HIV/AIDS, and modify risk behaviours. Other goals are to improve access to high-quality services for treating sexually transmitted infections (STIs), increase the provision and uptake of HIV counselling and testing, and enhance access to care and antiretroviral therapy (ART), including prevention and treatment of opportunistic infections. Results from the 2010-11 “Estimates and Projections of the Impact of HIV/AIDS in Namibia” report highlight a mature epidemic within the population that is indicative of the need for a continued and strengthened prevention-focused, decentralised multisectoral response that can effectively contain the spread of HIV and reduce the impact of AIDS (MoHSS, 2012a). To address the problems presented by the HIV/AIDS epidemic, substantial changes have taken place in Namibia over the past few years. These changes include increased funding; increased involvement among organisations in the public, private, and civil society sectors; expanded geographic coverage for services and programmes; and increased coverage of the needs and demands of beneficiaries. Furthermore, the system through which HIV-related A Key Findings • Knowledge of HIV/AIDS in Namibia is universal; almost all women and men age 15-64 have heard of AIDS. • Overall, women are more likely than men to have comprehensive knowledge about HIV/AIDS (63 percent of women versus 49 percent of men age 15-49 and 43 percent of women versus 34 percent of men age 50-64). • Women are more aware than men that HIV can be transmitted through breastfeeding and that this risk can be reduced by taking special drugs. • Women age 15-49 are less likely to have multiple sexual partners than their male counterparts (2 percent versus 10 percent). • Overall, 26 percent of men age 15-49 and 32 percent of those age 50-64 have been circumcised. • Forty-two percent of women and 57 percent of men age 18-24 reported having sexual intercourse before age 18. • Among never-married young women and men age 15-24, 52 percent each reported that they had sexual intercourse in the past 12 months. In this group of respondents, women were less likely than men to reported having used a condom during their last sexual encounter (68 percent versus 83 percent). 170 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour programmes in Namibia are monitored and evaluated has been strengthened and now provides critical information on programme quality and assists in identifying existing programmatic gaps. The principal objective of this chapter is to examine levels of HIV/AIDS-related knowledge and perceptions and the prevalence of risk behaviours related to HIV infection at the national level and in geographic and socioeconomic subgroups of the population. In this way, prevention programmes can target those individuals most in need of information and most at risk for HIV infection. In this chapter, indicators for HIV/AIDS knowledge, attitudes, and related behaviours are presented for the adult population (age 15- 49 and age 50-64). The chapter also highlights HIV/AIDS knowledge and patterns of sexual behaviour among young people, because young adults are more likely than their older counterparts to be in the process of establishing patterns of sexual behaviours and hence are the primary target of many prevention strategies. 14.1 HIV/AIDS KNOWLEDGE, TRANSMISSION, AND PREVENTION METHODS The 2013 NDHS included a series of questions that addressed women’s and men’s awareness of HIV/AIDS. These questions sought information on respondents’ overall knowledge, their knowledge of ways to avoid the disease, and their knowledge regarding use of condoms to prevent sexually transmitted infections. 14.1.1 Knowledge of AIDS According to the findings presented in Table 14.1, knowledge of AIDS is almost universal among NDHS respondents age 15-64 (98 percent or more of both women and men have heard of AIDS). HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 171 Table 14.1 Knowledge of AIDS Percentage of women and men age 15-49 who have heard of AIDS, by background characteristics, Namibia 2013 Women Men Background characteristic Has heard of AIDS Number of respondents Has heard of AIDS Number of respondents Age 15-24 99.4 3,691 99.0 1,730 15-19 99.3 1,906 98.4 922 20-24 99.5 1,786 99.7 808 25-29 99.8 1,489 98.7 658 30-39 99.3 2,370 99.4 968 40-49 99.5 1,625 99.3 665 Marital status Never married 99.6 5,458 99.0 2,745 Ever had sex 99.8 4,155 99.2 2,122 Never had sex 99.0 1,304 98.3 623 Married/living together 99.3 3,121 99.7 1,160 Divorced/separated/ widowed 99.6 597 96.4 116 Residence Urban 99.7 5,190 99.2 2,282 Rural 99.2 3,986 99.0 1,739 Region Zambezi 99.1 457 100.0 218 Erongo 99.8 771 99.0 372 Hardap 98.6 304 99.2 152 //Karas 99.7 343 96.9 151 Kavango 99.4 835 99.1 316 Khomas 99.7 2,202 99.2 1,023 Kunene 98.4 258 97.9 104 Ohangwena 99.7 894 99.6 328 Omaheke 98.8 225 99.0 103 Omusati 99.7 884 99.3 342 Oshana 99.7 755 100.0 335 Oshikoto 99.6 707 99.6 335 Otjozondjupa 98.5 540 96.9 241 Education No education 95.9 419 97.8 310 Primary 99.2 1,798 98.7 944 Secondary 99.9 6,029 99.4 2,400 More than secondary 99.3 930 99.2 368 Wealth quintile Lowest 99.2 1,429 98.8 594 Second 99.0 1,625 98.7 769 Middle 99.6 1,795 99.1 886 Fourth 99.8 2,116 99.4 917 Highest 99.6 2,211 99.4 855 Total 15-49 99.5 9,176 99.1 4,021 50-64 98.7 797 97.6 460 14.1.2 Knowledge of HIV Prevention In Namibia, HIV is transmitted among adults primarily through heterosexual contact between an infected partner and a non-infected partner (MoHSS, 2012b). Consequently, HIV prevention programmes focus their messages and efforts on promoting the following specific behaviours: use of condoms, voluntary male circumcision, limiting the number of sexual partners or staying faithful to one uninfected sexual partner, preventing mother-to-child transmission, and, for young people, delaying their first sexual intercourse (sexual debut). Table 14.2 shows the percentage of women and men age 15-49 who, in response to prompted questions, say that people can reduce their risk of getting HIV by using condoms every time they have sexual intercourse and having one sexual partner who is not infected and has no other partners. Eighty- eight percent of women and 90 percent of men age 15-49 know that consistent use of condoms is a means of preventing the spread of HIV; these percentages are similar to those reported in the 2006-07 NDHS (84 percent of women and 87 percent of men). The proportion of respondents who know that consistent condom use is a means of preventing the spread of HIV is slightly lower among those age 50-64 (81 172 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour percent of women and 83 percent of men). Ninety-two percent of women and men age 15-49 know that limiting sexual intercourse to one faithful and uninfected partner can reduce the chances of contracting HIV; the percentages are slightly lower among women and men age 50-64 (87 percent and 90 percent, respectively). Table 14.2 Knowledge of HIV prevention methods Percentage of women and men age 15-49 who, in response to prompted questions, say that people can reduce the risk of getting the AIDS virus by using condoms every time they have sexual intercourse and by having one sex partner who is not infected and has no other partners, by background characteristics, Namibia 2013 Women Men Percentage who say HIV can be prevented by: Number of women Percentage who say HIV can be prevented by: Number of men Background characteristic Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Using condoms1 Limiting sexual intercourse to one uninfected partner2 Using condoms and limiting sexual intercourse to one uninfected partner1,2 Age 15-24 85.8 90.3 81.3 3,691 89.0 90.0 83.0 1,730 15-19 82.1 87.5 76.7 1,906 87.5 87.9 80.6 922 20-24 89.6 93.3 86.3 1,786 90.7 92.3 85.6 808 25-29 88.6 93.4 85.2 1,489 91.9 93.6 88.5 658 30-39 89.6 92.7 86.0 2,370 91.7 94.5 88.3 968 40-49 89.2 93.7 86.6 1,625 89.3 93.3 86.1 665 Marital status Never married 87.2 91.5 83.1 5,458 90.3 91.0 84.9 2,745 Ever had sex 89.4 93.1 85.7 4,155 91.7 92.8 87.0 2,122 Never had sex 80.1 86.3 74.8 1,304 85.7 85.0 77.7 623 Married/living together 88.4 92.4 85.0 3,121 90.4 95.3 88.1 1,160 Divorced/separated/ widowed 90.6 94.7 88.4 597 84.5 88.7 79.3 116 Residence Urban 90.8 93.4 86.7 5,190 91.3 93.6 87.8 2,282 Rural 84.0 90.3 80.7 3,986 88.7 90.3 82.9 1,739 Region Zambezi 87.9 89.6 81.8 457 85.6 95.4 83.1 218 Erongo 93.1 94.9 89.8 771 90.2 94.3 86.6 372 Hardap 86.5 91.5 83.0 304 89.4 86.3 78.9 152 //Karas 92.0 94.9 88.8 343 76.2 82.6 71.3 151 Kavango 87.5 89.9 83.7 835 88.0 88.5 81.8 316 Khomas 90.8 92.4 85.7 2,202 94.0 94.3 91.1 1,023 Kunene 88.6 93.5 86.2 258 90.8 92.5 88.3 104 Ohangwena 89.0 94.1 86.2 894 95.3 94.4 91.1 328 Omaheke 84.5 90.1 80.7 225 91.5 94.2 88.1 103 Omusati 76.6 86.5 74.3 884 89.5 92.6 84.6 342 Oshana 87.0 92.8 83.8 755 89.1 92.2 83.8 335 Oshikoto 84.6 93.8 81.4 707 85.7 87.6 76.0 335 Otjozondjupa 89.6 92.7 86.7 540 90.8 93.3 89.8 241 Education No education 76.1 78.3 68.8 419 85.3 89.2 80.4 310 Primary 82.8 87.4 77.7 1,798 86.2 88.5 80.7 944 Secondary 89.2 93.8 85.9 6,029 91.9 93.3 87.4 2,400 More than secondary 94.1 95.6 91.6 930 92.8 97.1 91.4 368 Wealth quintile Lowest 81.3 87.8 77.9 1,429 87.5 89.9 82.1 594 Second 84.2 90.1 79.5 1,625 90.5 90.3 85.1 769 Middle 87.2 91.6 83.4 1,795 89.4 92.9 85.5 886 Fourth 91.5 94.0 88.1 2,116 89.5 92.3 84.8 917 Highest 91.7 94.6 88.2 2,211 93.2 94.6 89.7 855 Total 15-49 87.8 92.0 84.1 9,176 90.2 92.2 85.7 4,021 50-64 81.3 86.7 76.0 797 83.1 90.2 79.0 460 1 Using condoms every time they have sexual intercourse 2 Partner who has no other partners Knowledge of HIV prevention methods is lowest among women and men age 15-19 and among respondents who have never had sexual intercourse. In addition, knowledge is lower among respondents in rural than in urban areas. Women in Omusati and men in //Karas are least likely to know about HIV prevention methods. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 173 The proportion of women and men with knowledge of HIV prevention methods increases with increasing education. For example, knowledge of both prevention methods rises from 69 percent among women with no education to 92 percent among those with more than a secondary education. Similarly, knowledge of HIV prevention methods increases with increasing wealth. These findings indicate that HIV prevention education could be strengthened further in certain groups of individuals, particularly those who are young, those who have little or no education, and those living in the poorest households. 14.1.3 Comprehensive Knowledge about HIV/AIDS In addition to knowing effective ways to avoid contracting HIV, it is useful to be able to identify incorrect beliefs about HIV transmission. Common misconceptions about HIV/AIDS include the following: a healthy-looking person cannot have HIV, HIV/AIDS can be transmitted by mosquito bites, HIV/AIDS can be transmitted by supernatural means, and a person can become infected by sharing food with a person who has HIV/AIDS. Respondents were asked about these misconceptions, and the findings are presented in Tables 14.3.1 and 14.3.2 for women and men, respectively. Eighty-nine percent of women and 90 percent of men age 15-49 agreed that a healthy-looking person can have HIV. In terms of different misconceptions about HIV transmission, 82 percent of women and 77 percent of men said that HIV cannot be transmitted by mosquito bites; 90 percent of women and 75 men knew that HIV cannot be transmitted by supernatural means; and 91 percent of women and 88 percent of men said that a person cannot become infected by sharing food with a person who has AIDS. The questions asked in the 2013 NDHS allow an assessment of comprehensive knowledge of HIV/AIDS among respondents. Comprehensive knowledge is defined as knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission (that the AIDS virus can be transmitted by mosquito bites and that a person can become infected by sharing food with a person who has the AIDS virus). Overall, women are more likely than men to have comprehensive knowledge about HIV/AIDS (63 percent of women versus 49 percent of men age 15-49 and 43 percent of women versus 34 percent of men age 50-64). Comprehensive knowledge about HV/AIDS has decreased somewhat since the 2006-07 NDHS, which reported that 67 percent of women and 63 percent of men age 15-49 had comprehensive knowledge. The youngest women (age 15-19), those who have never had sex, those who are currently married, and those living in rural areas are less likely than other women to have comprehensive knowledge of HIV/AIDS. Among men, those age 40-49 and those who are widowed, separated, or divorced are least likely to have comprehensive knowledge of HIV/AIDS. By region, comprehensive knowledge is highest among women in Erongo (75 percent) and men in Oshana (63 percent) and lowest among women in Kavango and Omaheke (46 percent and 49 percent, respectively) and men in Hardap (11 percent). Comprehensive knowledge of HIV/AIDS increases steadily with increasing education. Among women, comprehensive knowledge also shows a notable increase with increasing wealth, from 49 percent among those in the lowest quintile to 73 percent among those in the highest quintile. 174 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.3.1 Comprehensive knowledge about AIDS: Women Percentage of women age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of the AIDS virus, and the percentage with comprehensive knowledge about AIDS, by background characteristics, Namibia 2013 Percentage of respondents who say that: Percentage who say that a healthy-looking person can have the AIDS virus and who reject the two most common local misconceptions1 Percentage with comprehensive knowledge about AIDS2 Number of women Background characteristic A healthy-looking person can have the AIDS virus The AIDS virus cannot be transmitted by mosquito bites The AIDS virus cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has the AIDS virus Age 15-24 86.6 84.0 89.5 91.8 71.6 61.6 3,691 15-19 83.0 82.4 87.4 90.8 68.0 55.9 1,906 20-24 90.5 85.8 91.7 92.8 75.5 67.8 1,786 25-29 90.6 82.1 89.7 92.3 73.3 65.0 1,489 30-39 91.2 80.2 89.9 90.4 71.4 63.5 2,370 40-49 90.6 80.7 89.8 88.9 71.5 63.7 1,625 Marital status Never married 89.8 84.8 90.7 92.5 74.9 64.8 5,458 Ever had sex 91.6 84.4 91.3 92.7 75.7 66.6 4,155 Never had sex 84.0 85.9 88.7 91.7 72.3 58.9 1,304 Married/living together 88.2 78.4 88.6 88.4 67.3 60.3 3,121 Divorced/separated/ widowed 88.2 77.7 86.6 90.5 67.2 61.6 597 Residence Urban 91.7 84.1 89.9 93.1 75.4 67.4 5,190 Rural 85.9 79.6 89.4 88.2 67.1 57.3 3,986 Region Zambezi 84.0 83.0 90.5 91.5 68.7 60.1 457 Erongo 93.0 89.4 94.3 95.4 81.4 74.9 771 Hardap 87.4 78.9 74.8 82.9 63.8 57.0 304 //Karas 92.2 82.3 87.7 93.8 74.2 68.5 343 Kavango 77.6 67.3 86.5 89.2 51.5 45.7 835 Khomas 92.5 83.9 87.8 92.4 75.4 66.7 2,202 Kunene 89.6 72.2 82.1 85.1 66.9 62.3 258 Ohangwena 91.0 79.7 92.4 87.6 71.2 63.3 894 Omaheke 82.7 70.1 84.0 81.4 55.3 48.5 225 Omusati 88.2 88.4 90.9 91.2 76.7 60.8 884 Oshana 90.5 87.6 96.2 95.8 78.1 67.1 755 Oshikoto 90.8 84.0 94.6 92.5 73.8 61.6 707 Otjozondjupa 88.1 82.0 88.7 87.3 71.1 66.0 540 Education No education 75.9 52.7 69.7 65.4 38.6 33.5 419 Primary 80.5 67.5 84.8 85.1 53.7 45.1 1,798 Secondary 91.6 87.2 91.7 94.0 77.4 67.8 6,029 More than secondary 96.0 91.2 95.5 94.4 85.1 79.7 930 Wealth quintile Lowest 83.7 72.9 86.8 84.2 59.3 49.2 1,429 Second 84.1 74.2 88.4 88.3 62.1 52.5 1,625 Middle 89.7 83.2 89.7 91.9 72.5 62.6 1,795 Fourth 91.7 86.9 91.2 94.2 78.2 70.9 2,116 Highest 93.4 88.7 91.1 93.6 80.4 72.5 2,211 Total 15-49 89.1 82.2 89.7 91.0 71.8 63.0 9,176 50-64 84.0 66.2 83.0 79.0 52.5 43.1 797 1 Two most common local misconceptions: the AIDS virus can be transmitted by mosquito bites and a person can become infected by sharing food with a person who has the AIDS virus. 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the 2 most common local misconceptions about AIDS transmission or prevention. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 175 Table 14.3.2 Comprehensive knowledge about AIDS: Men Percentage of men age 15-49 who say that a healthy-looking person can have the AIDS virus and who, in response to prompted questions, correctly reject local misconceptions about transmission or prevention of the AIDS virus, and the percentage with comprehensive knowledge about AIDS, by background characteristics, Namibia 2013 Percentage of respondents who say that: Percentage who say that a healthy-looking person can have the AIDS virus and who reject the two most common local misconceptions1 Percentage with comprehensive knowledge about AIDS2 Number of men Background characteristic A healthy-looking person can have the AIDS virus The AIDS virus cannot be transmitted by mosquito bites The AIDS virus cannot be transmitted by supernatural means A person cannot become infected by sharing food with a person who has the AIDS virus Age 15-24 88.8 79.8 78.4 89.4 58.5 51.1 1,730 15-19 87.4 81.2 77.7 90.0 59.8 51.4 922 20-24 90.3 78.1 79.1 88.7 57.0 50.6 808 25-29 91.9 77.0 75.9 86.5 58.2 53.3 658 30-39 90.3 76.1 73.6 87.4 51.8 47.8 968 40-49 90.6 72.6 66.8 83.9 46.5 41.4 665 Marital status Never married 89.7 78.3 77.5 88.1 57.0 50.8 2,745 Ever had sex 90.4 78.4 77.9 88.4 57.3 51.6 2,122 Never had sex 87.5 77.6 76.0 87.1 56.0 48.0 623 Married/living together 90.9 75.9 69.6 86.9 50.2 45.4 1,160 Divorced/separated/ widowed 85.5 67.8 66.3 80.1 49.1 42.9 116 Residence Urban 90.8 82.4 70.5 90.1 54.0 49.3 2,282 Rural 88.8 70.5 80.7 84.2 56.0 48.7 1,739 Region Zambezi 90.7 81.1 83.5 91.0 66.1 55.6 218 Erongo 89.0 88.8 46.8 86.5 36.1 31.0 372 Hardap 86.8 71.0 25.2 76.7 16.8 11.4 152 //Karas 83.9 60.7 68.0 81.4 41.1 34.2 151 Kavango 79.3 84.0 92.2 93.0 66.2 57.9 316 Khomas 90.8 83.4 78.3 93.5 61.0 57.7 1,023 Kunene 90.5 75.9 50.4 81.5 35.3 32.6 104 Ohangwena 96.3 61.1 88.7 82.6 55.2 51.7 328 Omaheke 88.9 82.7 59.9 87.7 50.8 49.8 103 Omusati 94.0 75.0 89.8 85.1 67.1 59.0 342 Oshana 95.4 76.9 93.3 88.9 71.2 62.9 335 Oshikoto 87.4 63.3 82.3 80.9 50.5 40.3 335 Otjozondjupa 88.5 79.2 50.3 84.4 41.2 37.5 241 Education No education 83.1 50.7 68.3 68.6 30.9 28.3 310 Primary 88.1 60.8 74.6 79.3 45.7 39.1 944 Secondary 90.8 85.0 74.5 92.2 58.6 52.8 2,400 More than secondary 95.1 91.3 83.9 94.2 73.6 67.2 368 Wealth quintile Lowest 85.6 66.5 81.6 82.0 51.9 46.2 594 Second 89.0 70.6 80.6 83.4 56.1 50.6 769 Middle 90.8 75.2 77.9 87.7 57.5 51.1 886 Fourth 90.5 82.9 68.7 90.4 53.8 46.8 917 Highest 92.4 86.9 68.6 92.0 54.1 49.9 855 Total 15-49 89.9 77.3 74.9 87.5 54.8 49.0 4,021 50-64 88.3 64.0 61.4 71.9 39.9 33.9 460 1 Two most common local misconceptions: the AIDS virus can be transmitted by mosquito bites and the AIDS virus can be transmitted by supernatural means. 2 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about AIDS transmission or prevention. 176 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 14.2 KNOWLEDGE ABOUT MOTHER-TO-CHILD TRANSMISSION In Namibia, a programme aimed at prevention of mother-to-child transmission of HIV (PMTCT) has been in place since 2002. The programme, supported by the Global Fund and other partners, has been scaled up rapidly and is currently available in more than 90 percent of health facilities in the country (MoHSS, 2012c). In accordance with the increase in the availability of PMTCT services, increasing the level of general knowledge about HIV transmission and reducing the risk of transmission using antiretroviral drugs are critical in reducing mother-to-child transmission (MTCT) of HIV. To assess PMTCT knowledge, respondents were asked whether HIV can be transmitted from a mother to a child through breastfeeding and whether a mother with HIV can reduce the risk of transmission to her baby by taking certain drugs during pregnancy. Table 14.4 shows that, among respondents age 15-49, women are more aware than men that HIV can be transmitted through breastfeeding (86 percent versus 69 percent) and that the risk of MTCT can be reduced by taking special drugs (87 percent versus 67 percent). Overall, 81 percent of women and 56 percent of men age 15-49 are aware both that HIV can be transmitted through breastfeeding and that this risk can be reduced by taking special drugs; the corresponding percentages among female and male respondents age 50-64 are 70 percent and 52 percent, respectively. There has been an increase in knowledge about MTCT among women and a decrease among men in Namibia over the last six years. According to the 2006-07 NDHS, 76 percent of women and 60 percent of men age 15-49 were aware that HIV can be transmitted through breastfeeding and that this risk can be reduced by taking special drugs. Knowledge of MTCT is highest among women and men age 25-29 and those who are married or living with a partner. There is little difference in level of MTCT knowledge by women’s current pregnancy status. MTCT knowledge is higher among both women and men who live in urban areas than among those who live in rural areas. Knowledge varies widely by region; it is lowest among women in Omaheke (71 percent) and men in Hardap (34 percent) and highest among women in Kavango (86 percent) and men in Khomas (67 percent). Among both women and men, awareness that HIV can be transmitted through breastfeeding and that this risk can be reduced by taking special drugs during pregnancy increases with increasing education and, in general, increasing wealth. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 177 Table 14.4 Knowledge of prevention of mother-to-child transmission of HIV Percentage of women and men age 15-49 who know that HIV can be transmitted from mother to child by breastfeeding and that the risk of mother-to-child transmission (MTCT) of HIV can be reduced by the mother taking special drugs during pregnancy, by background characteristics, Namibia 2013 Women Men Percentage who know that: Number of women Percentage who know that: Number of men Background characteristic HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding Risk of MTCT can be reduced by mother taking special drugs during pregnancy HIV can be transmitted by breastfeeding and risk of MTCT can be reduced by mother taking special drugs during pregnancy Age 15-24 85.5 83.3 77.7 3,691 70.5 61.9 52.1 1,730 15-19 82.7 77.0 71.7 1,906 71.7 56.1 48.5 922 20-24 88.6 89.9 84.2 1,786 69.2 68.5 56.2 808 25-29 88.4 93.0 85.4 1,489 71.0 71.4 60.1 658 30-39 87.7 90.2 83.6 2,370 67.8 69.5 58.3 968 40-49 83.3 87.1 78.1 1,625 66.7 70.7 59.1 665 Marital status Never married 86.0 86.5 79.8 5,458 69.7 64.6 54.4 2,745 Ever had sex 88.3 90.1 83.4 4,155 70.5 68.1 57.0 2,122 Never had sex 78.5 74.9 68.3 1,304 66.9 52.9 45.6 623 Married/living together 86.5 88.5 81.7 3,121 68.9 71.2 59.9 1,160 Divorced/separated/ widowed 85.9 88.9 81.5 597 64.6 71.8 56.0 116 Currently pregnant Pregnant 89.2 89.8 84.1 600 na na na na Not pregnant or not sure 85.9 87.1 80.3 8,576 na na na na Residence Urban 87.6 88.4 82.1 5,190 70.7 71.2 60.2 2,282 Rural 84.3 85.8 78.6 3,986 67.5 60.9 50.6 1,739 Region Zambezi 88.9 87.9 82.5 457 84.8 61.8 55.0 218 Erongo 85.4 86.4 80.5 771 51.0 51.5 37.5 372 Hardap 80.1 76.2 71.8 304 49.7 35.9 34.3 152 //Karas 85.1 86.0 76.7 343 64.0 64.7 50.6 151 Kavango 92.1 89.6 86.1 835 53.1 53.3 43.5 316 Khomas 89.7 89.3 83.6 2,202 77.1 78.9 67.3 1,023 Kunene 83.2 79.3 74.5 258 51.6 42.7 40.4 104 Ohangwena 82.4 85.7 76.3 894 78.8 77.5 64.9 328 Omaheke 79.5 77.2 71.0 225 55.6 53.2 46.6 103 Omusati 84.6 90.4 82.9 884 75.5 68.7 56.2 342 Oshana 83.1 87.1 79.2 755 69.2 73.0 57.8 335 Oshikoto 84.5 89.8 78.8 707 72.0 69.5 59.1 335 Otjozondjupa 84.6 86.3 79.9 540 76.1 67.9 63.2 241 Education No education 69.9 67.2 59.4 419 55.4 51.1 44.3 310 Primary 81.6 81.4 74.3 1,798 66.9 62.3 52.1 944 Secondary 88.2 89.7 83.2 6,029 71.0 67.7 57.0 2,400 More than secondary 88.9 92.0 85.0 930 76.5 85.2 69.5 368 Wealth quintile Lowest 84.1 85.1 77.8 1,429 65.9 59.4 49.6 594 Second 83.1 84.2 77.1 1,625 66.2 62.2 51.1 769 Middle 86.2 88.4 81.8 1,795 68.8 66.8 55.7 886 Fourth 88.4 88.6 82.7 2,116 73.2 70.9 61.8 917 Highest 87.5 88.9 81.8 2,211 70.8 71.4 59.3 855 Total 15-49 86.1 87.3 80.6 9,176 69.3 66.7 56.1 4,021 50-64 75.1 78.7 69.5 797 62.4 65.4 52.0 460 na = Not applicable 178 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 14.3 ATTITUDES TOWARD PEOPLE LIVING WITH HIV/AIDS Widespread stigma and discrimination against those living with HIV/AIDS can adversely affect both people’s willingness to be tested for HIV and their adherence to antiretroviral therapy (ART). Indeed, HIV/AIDS-related stigma and discrimination undermine HIV prevention efforts by making people afraid to seek out information about how to reduce their risk of exposure to HIV and adopt safer behaviours, given the possibility that such inquiries will raise suspicion about their HIV status. With support from sponsor organisations, Namibia has campaigned against stigma and discrimination against people living with HIV (de La Torre et al., 2009). Reductions in stigma and discrimination are an important indicator of the success of programmes targeting HIV/AIDS prevention and control. In the 2013 NDHS, respondents who had heard of AIDS were asked a number of questions to assess the level of stigma associated with HIV/AIDS. Respondents were asked about their willingness or unwillingness to buy vegetables from an infected shopkeeper or vendor, to let others know the HIV status of family members, and to take care of a member of their family with AIDS in their own household. They were also asked whether an HIV-positive female teacher who is not sick should be allowed to continue teaching. Tables 14.5.1 and 14.5.2 present the results for women and men, respectively. Ninety-six percent of women and 90 percent of men age 15-49 said that they would be willing to care for a relative with AIDS in their home, and 95 percent of women and 91 percent of men agreed that a female teacher infected with HIV should be allowed to continue teaching. A lower percentage (85 percent of both women and men) indicated that they would buy vegetables from a shopkeeper with HIV. About one-third of women (35 percent) and four in ten men (39 percent) said that they would not want to keep secret that a family member was infected with HIV. Women age 50-64 have greater accepting attitudes toward those living with HIV/AIDS than their male counterparts in the same age group. Overall, only 28 percent of women and 26 percent of men age 15-49 expressed accepting attitudes with regard to all four indicators (i.e., they would care for a family member with AIDS in their own home, they would buy fresh vegetables from a shopkeeper with HIV, they would allow an HIV-positive female teacher to continue teaching, and they would not want to keep the HIV-positive status of a family member a secret). Over the last six years, there has been a decrease in accepting attitudes toward people living with HIV/AIDS. In the 2006-07 NDHS, 40 percent of women and 36 percent of men age 15-49 expressed accepting attitudes on all four indicators. This lower level of acceptance is of concern because stigma prevents or delays people from getting tested for HIV, and, among those living with HIV, stigma prevents them from seeking care and treatment services. There are associations between accepting attitudes and some of the background characteristics of survey respondents. There are marked differences by region in the proportions of women and men expressing accepting attitudes on all four indicators. Among women, the proportion ranges from 6 percent in Zambezi to 44 percent in Omusati; among men, it ranges from 12 percent in Otjozondjupa to 41 percent in Oshana. The proportion of women who express accepting attitudes on all four indicators increases with increasing education and wealth. Among men, the proportion generally increases with increasing education and decreases somewhat with increasing wealth. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 179 Table 14.5.1 Accepting attitudes toward those living with HIV/AIDS: Women Among women age 15-49 who have heard of AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Namibia 2013 Percentage of women who: Percentage expressing accepting attitudes on all four indicators Number of women who have heard of AIDS Background characteristic Are willing to care for a family member with AIDS in the respondent's home Would buy fresh vegetables from shopkeeper who has the AIDS virus Say that a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with the AIDS virus Age 15-24 96.0 84.4 93.8 33.3 26.5 3,670 15-19 95.4 82.7 92.9 31.4 23.9 1,893 20-24 96.7 86.1 94.8 35.3 29.2 1,777 25-29 95.7 86.8 95.6 33.0 25.6 1,486 30-39 96.8 86.6 95.0 36.4 30.5 2,355 40-49 97.1 84.6 94.2 39.2 30.8 1,618 Marital status Never married 96.6 86.3 95.3 35.6 29.2 5,435 Ever had sex 96.8 87.5 95.8 35.6 29.6 4,145 Never had sex 96.1 82.1 93.5 35.6 27.9 1,291 Married/living together 95.6 84.1 93.3 35.1 27.2 3,098 Divorced/separated/ widowed 97.9 84.2 92.9 30.8 23.4 595 Residence Urban 96.2 86.7 95.2 35.2 28.3 5,174 Rural 96.5 83.6 93.5 34.9 27.9 3,954 Region Zambezi 98.2 89.7 95.4 7.9 5.9 453 Erongo 96.5 86.3 95.4 39.8 30.4 770 Hardap 93.6 78.6 88.4 45.5 32.6 300 //Karas 96.5 84.0 95.6 32.9 25.4 342 Kavango 95.8 84.3 92.3 27.4 19.2 831 Khomas 95.1 84.8 96.2 32.9 26.7 2,195 Kunene 91.4 76.5 79.8 37.8 30.0 254 Ohangwena 99.1 86.3 96.5 37.9 31.2 892 Omaheke 92.4 78.0 88.9 27.9 19.4 222 Omusati 95.6 88.6 97.2 49.4 43.5 881 Oshana 98.9 92.6 97.5 39.5 35.8 753 Oshikoto 98.1 83.2 94.8 37.9 29.7 704 Otjozondjupa 96.6 82.2 87.6 31.2 22.1 532 Education No education 90.4 66.8 76.6 24.9 12.2 401 Primary 95.6 79.0 88.5 30.5 21.1 1,783 Secondary 97.1 87.3 96.7 36.7 30.5 6,020 More than secondary 95.5 92.9 99.4 38.0 33.7 923 Wealth quintile Lowest 95.6 81.7 92.1 30.8 23.0 1,418 Second 96.9 83.0 92.8 34.0 26.1 1,610 Middle 97.4 86.4 94.7 34.8 29.2 1,787 Fourth 96.9 85.9 95.0 36.1 29.2 2,111 Highest 95.1 88.0 96.5 37.9 31.0 2,202 Total 15-49 96.4 85.4 94.5 35.1 28.1 9,128 50-64 96.3 78.1 89.2 40.1 29.1 787 180 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.5.2 Accepting attitudes toward those living with HIV/AIDS: Men Among men age 15-49 who have heard of HIV/AIDS, percentage expressing specific accepting attitudes toward people with HIV/AIDS, by background characteristics, Namibia 2013 Percentage of men who: Percentage expressing accepting attitudes on all four indicators Number of men who have heard of AIDS Background characteristic Are willing to care for a family member with AIDS in the respondent's home Would buy fresh vegetables from shopkeeper who has the AIDS virus Say that a female teacher who has the AIDS virus but is not sick should be allowed to continue teaching Would not want to keep secret that a family member got infected with the AIDS virus Age 15-24 92.5 85.1 88.9 34.6 23.3 1,713 15-19 92.1 83.8 86.9 34.1 22.4 908 20-24 93.0 86.5 91.1 35.2 24.3 805 25-29 90.3 87.9 93.4 40.4 29.3 650 30-39 88.5 84.5 92.7 44.4 28.2 962 40-49 87.7 82.0 89.0 42.9 26.0 660 Marital status Never married 91.9 85.2 90.4 38.2 26.3 2,717 Ever had sex 92.4 86.9 92.1 39.0 28.0 2,105 Never had sex 90.1 79.5 84.3 35.2 20.3 612 Married/living together 87.1 85.3 91.9 41.5 25.3 1,157 Divorced/separated/ widowed 86.7 72.8 80.8 43.1 23.0 112 Residence Urban 88.7 87.2 93.9 37.4 24.3 2,263 Rural 92.6 81.8 86.1 41.7 28.0 1,722 Region Zambezi 98.5 78.9 85.9 15.1 12.9 218 Erongo 75.1 85.7 95.2 47.3 20.8 368 Hardap 94.5 82.8 85.4 16.5 14.0 151 //Karas 83.8 71.2 81.2 48.2 31.4 147 Kavango 68.9 91.3 92.2 71.5 35.4 313 Khomas 91.2 89.0 93.7 32.7 21.8 1,015 Kunene 92.7 74.6 83.6 41.4 28.9 102 Ohangwena 99.6 83.9 90.0 43.1 32.4 327 Omaheke 88.8 71.9 88.9 29.5 13.0 102 Omusati 98.9 83.1 91.2 36.7 28.6 339 Oshana 98.4 88.7 94.4 48.8 41.4 335 Oshikoto 96.5 82.1 84.3 46.3 34.5 334 Otjozondjupa 88.0 84.9 87.9 21.9 12.1 234 Education No education 83.4 77.0 83.2 42.6 22.8 303 Primary 91.5 76.1 82.8 37.1 20.6 931 Secondary 90.6 88.2 93.5 39.8 27.8 2,386 More than secondary 91.9 91.8 97.3 38.8 29.3 365 Wealth quintile Lowest 89.1 80.9 85.7 46.7 27.7 587 Second 91.1 82.1 87.3 41.0 27.8 759 Middle 92.4 84.6 90.9 36.3 25.9 878 Fourth 90.1 87.5 92.2 39.5 25.9 911 Highest 88.9 87.6 94.7 35.5 23.1 850 Total 15-49 90.4 84.9 90.6 39.3 25.9 3,985 50-64 88.0 73.6 85.0 43.3 23.3 449 14.4 ATTITUDES TOWARD NEGOTIATING SAFER SEXUAL RELATIONS WITH HUSBANDS Knowledge about HIV transmission and ways to prevent it is of little use if people feel powerless to negotiate safer sex practices with their partners. The high levels of sexual transmission of HIV make negotiating for safer sex indispensable, especially in marital unions in which women’s status is compromised by societal expectations, thereby increasing their vulnerability to HIV transmission. In the 2013 NDHS, women and men were asked if they thought that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women or in asking that he use condoms if she knows that he has a sexually transmitted infection. Table 14.6 shows that 88 percent of women and 85 percent of men age 15-49 believe that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women. In addition, 93 percent of women and 91 percent of men believe that a woman has a right to ask her husband to use a condom if she knows that he has an STI. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 181 Among those age 50-64, 85 percent of women and 82 percent of men believe that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women, and 89 percent of women and 87 percent of men believe that a woman has a right to ask her husband to use a condom if she knows that he has an STI. Table 14.6 Attitudes toward negotiating safer sexual relations with husband Percentage of women and men age 15-64 who believe that a woman is justified in refusing to have sexual intercourse with her husband if she knows that he has sexual intercourse with other women, and percentage who believe that a woman is justified in asking that they use a condom if she knows that her husband has a sexually transmitted infection (STI), by background characteristics, Namibia 2013 Women Men Woman is justified in: Number of women Woman is justified in: Number of men Background characteristic Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Refusing to have sexual intercourse with her husband if she knows he has sex with other women Asking that they use a condom if she knows that her husband has an STI Age 15-24 83.7 89.8 3,691 82.0 90.8 1,730 15-19 79.1 85.2 1,906 78.9 88.3 922 20-24 88.6 94.8 1,786 85.6 93.6 808 25-29 90.9 96.2 1,489 87.4 93.2 658 30-39 91.0 95.5 2,370 85.1 91.2 968 40-49 89.8 95.5 1,625 87.1 91.2 665 Marital status Never married 86.7 92.1 5,458 83.3 91.3 2,745 Ever had sex 90.0 95.6 4,155 86.1 93.4 2,122 Never had sex 76.3 80.9 1,304 73.7 84.2 623 Married/living together 89.5 95.2 3,121 87.9 91.7 1,160 Divorced/separated/ widowed 89.8 94.8 597 79.4 88.9 116 Residence Urban 90.3 95.6 5,190 87.3 91.2 2,282 Rural 84.7 90.4 3,986 80.7 91.6 1,739 Region Zambezi 73.4 87.6 457 71.0 94.6 218 Erongo 93.4 97.8 771 65.5 73.9 372 Hardap 91.8 92.5 304 95.6 96.6 152 //Karas 93.5 97.5 343 85.7 89.8 151 Kavango 85.1 91.7 835 82.1 83.6 316 Khomas 89.3 95.7 2,202 90.9 93.7 1,023 Kunene 93.9 96.4 258 95.5 96.2 104 Ohangwena 82.1 89.4 894 85.5 95.9 328 Omaheke 85.8 91.3 225 90.4 90.9 103 Omusati 83.8 85.7 884 80.7 93.7 342 Oshana 93.6 96.0 755 91.5 97.8 335 Oshikoto 88.5 96.7 707 82.2 93.9 335 Otjozondjupa 89.7 92.8 540 83.9 89.2 241 Education No education 77.4 83.9 419 81.7 86.2 310 Primary 82.0 87.7 1,798 77.4 89.4 944 Secondary 89.6 94.9 6,029 86.2 92.4 2,400 More than secondary 92.7 98.4 930 93.6 94.2 368 Wealth quintile Lowest 79.8 86.5 1,429 79.1 91.9 594 Second 85.8 91.4 1,625 82.5 90.6 769 Middle 88.3 93.6 1,795 86.4 93.8 886 Fourth 90.5 95.9 2,116 85.3 91.4 917 Highest 91.6 96.5 2,211 87.1 89.0 855 Total 15-49 87.9 93.3 9,176 84.5 91.4 4,021 50-64 84.5 89.1 797 82.0 86.8 460 The percentage of women age 15-49 who believe that a wife is justified in refusing to have sexual intercourse with her husband if she knows he has sex with other women and who believe that a woman has a right to ask her husband to use a condom if she knows that he has an STI is lowest among those in the youngest age group (15-19) (79 percent and 85 percent, respectively), those who have never been married and never had sex (76 percent and 81 percent, respectively), those in rural areas (85 percent and 90 percent, respectively), those in Zambezi and Omusati (73 percent and 86 percent, respectively), those with 182 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour no education (77 percent and 84 percent, respectively), and those in the lowest wealth quintile (80 percent and 87 percent, respectively). The same patterns are generally observed among men age 15-49. Programme planners and implementers focusing on HIV/AIDS and sexually transmitted infections should take advantage of the relatively high level of acceptance among all respondents of women as negotiators of safer sex with their husbands. This high degree of acceptance affords an opportunity to expand and further strengthen messages and interventions that promote preventive practices (e.g., use of male and female condoms) and empower women to take ownership of their sexual health. 14.5 ATTITUDES TOWARD CONDOM EDUCATION FOR YOUNG PEOPLE Condom use is one of the main strategies for combating the spread of HIV. However, educating young people about condoms is sometimes controversial, with some believing that it promotes early sexual experimentation. To gauge attitudes toward condom education, respondents were asked whether they thought that children age 12-14 should be taught about using a condom to avoid getting AIDS. Because the focus is on adults’ opinions, results are tabulated for respondents age 18-49. Table 14.7 shows that 85 percent of women and 83 percent of men age 18-49 support teaching children age 12-14 about condoms. Women and men age 50-64 are less likely to support education of children on condom use (76 percent of women and 71 percent of men). Among women, support for educating children about condom use is lowest among those age 40-49 and among men it is lowest among those age 18-19. Also, it is lower among respondents in rural than in urban areas. Women in Oshana (91 percent) and men in Erongo (92 percent) are most likely to support education of children on condom use, while support is lowest among women in Zambezi (79 percent) and men in Kunene (71 percent). Adult support for educating children about condom use generally increases with increasing education and wealth. For example, 72 percent of women and 74 percent of men with no education support teaching children about condom use, as compared with 86 percent of women with secondary and higher education and 91 percent of men with more than a secondary education. Table 14.7 Adult support of education about condom use to prevent AIDS Percentage of women and men age 18-49 who agree that children age 12-14 should be taught about using a condom to avoid AIDS, by background characteristics, Namibia 2013 Women Men Background characteristic Percentage who agree Number of women Percentage who agree Number of men Age 18-24 85.9 2,616 82.4 1,154 18-19 85.0 830 79.6 346 20-24 86.3 1,786 83.6 808 25-29 86.8 1,489 85.8 658 30-39 84.1 2,370 82.8 968 40-49 82.4 1,625 81.8 665 Marital status Never married 86.4 4,416 83.3 2,170 Married/living together 82.4 3,091 82.8 1,159 Divorced/separated/ widowed 85.8 593 81.3 116 Residence Urban 85.9 4,735 85.3 2,054 Rural 83.3 3,365 79.7 1,391 Region Zambezi 78.7 402 77.5 194 Erongo 90.0 693 91.5 340 Hardap 79.8 276 58.4 134 //Karas 89.4 312 77.6 130 Kavango 80.0 706 72.3 265 Khomas 83.7 2,043 84.7 932 Kunene 86.6 238 71.3 95 Ohangwena 83.8 755 90.4 239 Omaheke 82.3 204 82.6 98 Omusati 81.8 719 81.9 238 Oshana 90.7 675 89.1 277 Oshikoto 87.5 601 88.2 289 Otjozondjupa 89.3 475 83.6 214 Education No education 71.7 403 74.4 301 Primary 82.9 1,460 79.4 734 Secondary 86.2 5,312 84.3 2,043 More than secondary 85.5 925 90.7 368 Wealth quintile Lowest 79.8 1,213 76.6 489 Second 81.8 1,421 80.5 647 Middle 86.7 1,581 81.1 761 Fourth 88.0 1,909 87.6 791 Highest 85.5 1,976 86.7 756 Total 18-49 84.8 8,100 83.1 3,445 50-64 75.8 797 71.0 460 HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 183 14.6 HIGHER-RISK SEX 14.6.1 Multiple Sexual Partners Given that most HIV infections in Namibia are contracted through heterosexual contact, information on sexual behaviour is important in designing and monitoring intervention programmes to control the spread of the epidemic. The 2013 NDHS included questions on respondents’ sexual partners during their lifetimes and over the 12 months preceding the survey. Men were also asked whether they paid for sex during the 12 months preceding the interview. In addition, information was collected on women’s and men’s use of condoms during their most recent sexual intercourse. These questions are sensitive, and it is recognised that some respondents may have been reluctant to provide information on recent sexual behaviour. Potentially risky sexual activities relate to men and women having multiple sexual partners and failing to use condoms, particularly if they have more than one sexual partner. Tables 14.8.1 and 14.8.2 present information collected from women and men who have ever had intercourse on the number of sexual partners they had during the 12 months before the survey and over their lifetime and, among those reporting more than one sexual partner in the past 12 months, whether they used a condom during their most recent intercourse. The data show that women age 15-49 are much less likely than their male counterparts to have multiple sexual partners in the past 12 months (2 percent versus 10 percent). Among women, those in the 20-24 age groups; those who are divorced, separated, or widowed; those living in urban areas and in Kunene; those women with no education; and those in the highest two wealth quintiles are more likely than other women to report having multiple sexual partners in the past 12 months. Among men, those age 25-29 (16 percent), those who have never been married men (12 percent), those living in rural areas (11 percent), and those living in Oshana (16 percent) are most likely to report that they had multiple sexual partners in the past 12 months. The percentage of men with multiple sexual partners in the past 12 months increases steadily with increasing education, from 8 percent among those with no education to 16 percent among those with more than a secondary education. There is no clear pattern in the relationship of this indicator with wealth. Seventy-two percent of men age 15-49 who had two or more sexual partners in the past 12 months reported using a condom during their last sexual intercourse.1 Men age 20-24 and those who have never been married (81 percent each), men living in urban areas (74 percent) and, and men in the highest wealth quintile (78 percent) are more likely than other groups to report using a condom during their last sexual intercourse. Women age 15-49 reported an average of 2.6 lifetime sexual partners, as compared with 7.4 lifetime partners among their male counterparts. Among men, there are pronounced differences in mean number of lifetime partners by background characteristics. For example, the mean number of lifetime sexual partners is highest among men age 40-49 (10.6); those who are divorced, separated, or widowed (10.1); those living in Kunene (11.9); those with more than a secondary education (8.6); and those in the highest wealth quintile (8.5). It is notable that men age 50-64 reported a much higher mean number of lifetime sexual partners (11.8) than those age 15-49 (7.4). 1 Data for women are not shown due to the small number of cases. 184 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.8.1 Multiple sexual partners: Women Among all women age 15-49, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse; and the mean number of sexual partners during their lifetime for women who ever had sexual intercourse, by background characteristics, Namibia 2013 All women Among women who ever had sexual intercourse1: Background characteristic Percentage who had 2+ partners in the past 12 months Number of women Mean number of sexual partners in lifetime Number of women Age 15-24 2.8 3,691 2.0 2,452 15-19 2.1 1,906 1.7 852 20-24 3.6 1,786 2.2 1,600 25-29 2.7 1,489 2.6 1,443 30-39 1.6 2,370 2.9 2,274 40-49 1.2 1,625 2.9 1,561 Marital status Never married 2.5 5,458 2.5 4,104 Married/living together 1.2 3,121 2.5 3,040 Divorced/separated/ widowed 5.3 597 3.4 586 Residence Urban 2.9 5,190 2.7 4,423 Rural 1.3 3,986 2.3 3,307 Region Zambezi 1.1 457 2.4 414 Erongo 3.5 771 3.2 673 Hardap 1.7 304 2.9 259 //Karas 1.4 343 2.9 300 Kavango 0.5 835 2.0 765 Khomas 3.7 2,202 2.7 1,844 Kunene 7.2 258 3.5 246 Ohangwena 0.8 894 2.2 710 Omaheke 5.2 225 4.0 203 Omusati 0.5 884 2.0 670 Oshana 0.9 755 2.3 627 Oshikoto 2.1 707 2.2 574 Otjozondjupa 2.1 540 3.0 446 Education No education 3.7 419 2.9 395 Primary 1.3 1,798 2.5 1,506 Secondary 2.3 6,029 2.6 5,027 More than secondary 2.4 930 2.6 801 Wealth quintile Lowest 1.0 1,429 2.3 1,218 Second 1.4 1,625 2.5 1,382 Middle 1.6 1,795 2.4 1,549 Fourth 3.3 2,116 2.7 1,818 Highest 3.0 2,211 2.8 1,763 Total 15-49 2.2 9,176 2.6 7,731 50-64 0.2 797 2.5 769 1 Means are calculated excluding respondents who gave non-numeric responses. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 185 Table 14.8.2 Multiple sexual partners: Men Among all men age 15-49, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months; among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse; and the mean number of sexual partners during their lifetime for men who ever had sexual intercourse, by background characteristics, Namibia 2013 All men Among men who had 2+ partners in the past 12 months: Among men who ever had sexual intercourse1: Background characteristic Percentage who had 2+ partners in the past 12 months Number of men Percentage who reported using a condom during last sexual intercourse Number of men Mean number of sexual partners in lifetime Number of men Age 15-24 9.2 1,730 79.4 160 4.3 1,124 15-19 4.9 922 (75.1) 46 3.0 396 20-24 14.1 808 81.1 114 5.0 728 25-29 15.5 658 77.5 102 7.9 602 30-39 11.0 968 58.6 106 8.9 882 40-49 7.7 665 (67.2) 51 10.6 569 Marital status Never married 12.0 2,745 81.0 331 6.5 2,013 Married/living together 6.7 1,160 35.9 78 8.8 1,066 Divorced/separated/ widowed 9.8 116 * 11 10.1 98 Type of union In polygynous union (44.9) 25 * 11 (12.4) 24 In non-polygynous union 5.8 1,135 38.5 66 8.7 1,042 Not currently in union 12.0 2,861 80.4 342 6.7 2,112 Residence Urban 9.8 2,282 73.6 223 7.6 1,864 Rural 11.3 1,739 70.6 197 7.1 1,314 Region Zambezi 12.0 218 (42.9) 26 5.9 197 Erongo 6.5 372 (59.9) 24 8.6 297 Hardap 7.7 152 * 12 8.0 126 //Karas 6.8 151 * 10 7.5 110 Kavango 9.6 316 (45.0) 30 7.2 269 Khomas 10.5 1,023 (77.8) 108 7.2 838 Kunene 12.9 104 (74.7) 13 11.9 93 Ohangwena 11.9 328 (82.7) 39 6.9 246 Omaheke 5.6 103 * 6 8.9 89 Omusati 11.9 342 (81.4) 41 6.8 191 Oshana 15.6 335 (79.9) 52 8.2 263 Oshikoto 14.1 335 (77.6) 47 5.5 262 Otjozondjupa 4.6 241 * 11 7.3 196 Education No education 7.9 310 (63.7) 24 7.4 275 Primary 8.6 944 72.8 81 7.3 694 Secondary 10.7 2,400 71.0 256 7.2 1,895 More than secondary 16.0 368 (80.1) 59 8.6 313 Wealth quintile Lowest 9.5 594 67.0 56 6.2 474 Second 10.8 769 62.1 83 7.4 587 Middle 9.1 886 76.0 81 6.9 716 Fourth 11.1 917 75.1 102 7.6 727 Highest 11.4 855 77.5 98 8.5 673 Total 15-49 10.4 4,021 72.2 420 7.4 3,177 50-64 6.5 460 (38.6) 30 11.8 380 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 Means are calculated excluding respondents who gave non-numeric responses. 186 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 14.6.2 Point Prevalence and Cumulative Prevalence of Concurrent Sexual Partners The point prevalence and cumulative prevalence of concurrent sexual partners are new concepts that were incorporated for the first time in the 2013 NDHS. The point prevalence of concurrent sexual partners is defined as the percentage of respondents who had two (or more) sexual partners concurrently at the point in time six months before the survey. The cumulative prevalence of concurrent sexual partners is defined as the percentage of respondents who had two (or more) sexual partners concurrently at any time during the 12 months preceding the survey. Table 14.9 shows the point prevalence and cumulative prevalence of concurrent sexual partners among all respondents before the survey. It also shows the percentage of respondents who had concurrent sexual partners among those who had multiple sexual partners during the 12 months before the survey. Among women age 15-49, both the point prevalence and the cumulative prevalence are 1 percent or less. Among men in the same age group, the point prevalence is 2 percent and the cumulative prevalence is 7 percent. Women age 50-64 have a point prevalence and cumulative prevalence of less than 1 percent each, while men have a point prevalence of 4 percent and a cumulative prevalence of 6 percent. Among female respondents, point prevalence and cumulative prevalence vary only marginally by background characteristics. Among men, there are some notable variations in the cumulative prevalence; it is highest among men age 25-29 (11 percent), those who have never been married (7 percent), and men living in rural areas (7 percent). Table 14.9 also shows that, among all respondents age 15-49 who had multiple partners during the 12 months preceding the survey, 54 percent of women and 65 percent of men had concurrent sexual partners. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 187 Table 14.9 Point prevalence and cumulative prevalence of concurrent sexual partners Percentage of all women and men age 15-49 who had concurrent sexual partners six months before the survey (point prevalence1), percentage of all women and all men age 15-49 who had any concurrent sexual partners during the 12 months before the survey (cumulative prevalence2), and among women and men age 15-49 who had multiple sexual partners during the 12 months before the survey, percentage who had concurrent sexual partners, by background characteristics, Namibia 2013 Among all respondents: Among all respondents who had multiple partners during the 12 months before the survey: Background characteristic Point prevalence of concurrent sexual partners1 Cumulative prevalence of concurrent sexual partners2 Number of respondents Percentage who had concurrent sexual partners2 Number of respondents WOMEN Age 15-24 0.4 1.1 3,691 37.8 105 15-19 0.1 0.4 1,906 (20.4) 40 20-24 0.7 1.8 1,786 48.4 65 25-29 0.5 1.8 1,489 (68.1) 40 30-39 0.4 1.0 2,370 (63.4) 38 40-49 0.5 1.1 1,625 * 20 Marital status Never married 0.3 1.2 5,458 49.6 136 Married/living together 0.5 0.8 3,121 67.6 36 Divorced/separated/ widowed 0.7 3.0 597 (57.6) 31 Residence Urban 0.4 1.5 5,190 51.9 151 Rural 0.4 0.8 3,986 60.3 52 Total 15-49 0.4 1.2 9,176 54.1 203 50-64 0.1 0.2 797 * 1 MEN Age 15-24 1.5 4.8 1,730 52.1 160 15-19 0.8 1.8 922 (37.2) 46 20-24 2.2 8.2 808 58.0 114 25-29 2.3 10.9 658 70.4 102 30-39 4.0 8.7 968 79.4 106 40-49 1.4 4.8 665 (61.5) 51 Marital status Never married 2.2 7.4 2,745 61.6 331 Married/living together 2.4 5.6 1,160 83.1 78 Divorced/separated/ widowed 1.3 2.6 116 * 11 Type of union In polygynous union (34.9) (35.4) 25 * 11 In non-polygynous union 1.6 4.9 1,135 83.8 66 Not currently in union 2.1 7.2 2,861 60.4 342 Residence Urban 2.2 6.3 2,282 64.2 223 Rural 2.2 7.4 1,739 65.1 197 Total 15-49 2.2 6.7 4,021 64.6 420 50-64 3.7 6.2 460 (95.0) 30 Note: Two sexual partners are considered to be concurrent if the date of the most recent sexual intercourse with the earlier partner is after the date of the first sexual intercourse with the later partner. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 The percentage of respondents who had two (or more) sexual partners that were concurrent at the point in time six months before the survey 2 The percentage of respondents who had two (or more) sexual partners that were concurrent anytime during the 12 months preceding the survey 14.7 PAID SEX The act of paying for sex introduces an uneven negotiating ground for safer sexual intercourse. Condom use is an important indicator in efforts to ascertain the level of risk associated with sexual intercourse involving payments. Table 14.10 shows the percentage of men age 15-49 who paid for sexual intercourse ever and in the past 12 months by background characteristics. 188 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.10 Payment for sexual intercourse and condom use at last paid sexual intercourse Percentage of men age 15-49 who ever paid for sexual intercourse and percentage reporting payment for sexual intercourse in the past 12 months, by background characteristics, Namibia 2013 Background characteristic Percentage who ever paid for sexual intercourse Percentage who paid for sexual intercourse in the past 12 months Number of men Age 15-24 1.5 0.7 1,730 15-19 0.3 0.1 922 20-24 2.9 1.4 808 25-29 2.3 0.8 658 30-39 3.2 1.5 968 40-49 3.0 0.6 665 Marital status Never married 2.0 1.0 2,745 Married/living together 2.5 0.8 1,160 Divorced/separated/ widowed 7.0 1.0 116 Residence Urban 2.6 0.9 2,282 Rural 1.9 0.9 1,739 Region Zambezi 3.8 2.7 218 Erongo 0.7 0.0 372 Hardap 1.2 0.4 152 //Karas 4.2 2.8 151 Kavango 4.8 1.5 316 Khomas 3.5 1.1 1,023 Kunene 1.3 0.4 104 Ohangwena 1.3 0.7 328 Omaheke 1.7 0.0 103 Omusati 0.0 0.0 342 Oshana 2.2 0.6 335 Oshikoto 1.9 1.3 335 Otjozondjupa 0.6 0.3 241 Education No education 2.4 1.7 310 Primary 0.9 0.4 944 Secondary 2.3 1.1 2,400 More than secondary 5.8 0.7 368 Wealth quintile Lowest 2.0 0.7 594 Second 1.7 0.6 769 Middle 1.7 0.8 886 Fourth 3.0 1.3 917 Highest 3.0 1.0 855 Total 15-49 2.3 0.9 4,021 50-64 3.5 1.6 460 Only 2 percent of men age 15-49 and 4 percent of those age 50-64 reported ever paying for sex; 1 percent and 2 percent, respectively, reported paying for sex during the 12 months preceding the survey. Men who are divorced, separated, or widowed (7 percent); those living in Kavango (5 percent); and those with more than a secondary education (6 percent) are more likely than their counterparts to have ever paid for sexual intercourse. Other variations by background characteristics are minimal. Among men who paid for sex in the past 12 months, 67 percent reported using a condom at their last paid sexual intercourse (data are not shown separately). HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 189 14.8 MALE CIRCUMCISION Circumcision is a common practice in many parts of sub-Saharan Africa for traditional, health, and other reasons. Male circumcision has been associated with a lower risk of HIV transmission from women to men (Williams et al., 2006; WHO and UNAIDS, 2007). To examine the practice of circumcision at the national level, men interviewed in the 2013 NDHS were asked whether they had been circumcised and when they were circumcised. The results are presented in Table 14.11. The data show that 26 percent of men age 15-49 and 32 percent of those age 50-64 are circumcised. There are some marked differences across background characteristics. Men age 40-49 (30 percent), those living in urban areas (30 percent), those living in Kunene (51 percent) and Omaheke (48 percent), and those who reported having no religious affiliation (44 percent) are more likely than men in other groups to have been circumcised. These results are in line with previous MoHSS assessments indicating that there are gaps in attitudes and behaviours regarding circumcision practices across the country (MoHSS, 2014). The roll-out of the Voluntary Medical Male Circumcision initiative by the MoHSS will address and resolve some of the current barriers in Namibia with respect to circumcision practices. Table 14.12 shows the percent distribution of men by the person who performed the circumcision and the place where it took place. Forty-seven percent of male circumcisions were performed by a traditional practitioner or family friend and 46 percent by a health worker or professional. With respect to the place at which circumcisions occurred, 43 percent were performed at a health care facility, 23 percent were performed at the respondent’s home, 10 percent each took place at the home of a health worker or professional and at a ritual site, and 8 percent took place at another person’s home or elsewhere. Table 14.12 Provider and place of circumcision Among men age 15-64 who report having been circumcised, percent distribution by person who performed the circumcision and by place circumcised, Namibia 2013 Person/place of circumcision Percentage Person who performed circumcision Traditional practitioner/family friend 47.1 Health worker/professional 45.6 Other 0.4 Don’t know 6.2 Missing 0.7 Total 100.0 Place of circumcision Health care facility 43.3 Home of a health worker/health professional 9.7 Respondent’s home 23.2 Ritual site 9.8 Other home/elsewhere 8.2 Don’t know 5.5 Missing 0.4 Total 100.0 Number of circumcised men 1,172 Table 14.11 Male circumcision Percentage of men age 15-49 who report having been circumcised, by background characteristics, Namibia 2013 Background characteristic Percentage circumcised Number of men Age 15-24 21.8 1,730 15-19 21.0 922 20-24 22.8 808 25-29 27.8 658 30-39 27.4 968 40-49 30.3 665 Residence Urban 30.0 2,282 Rural 19.7 1,739 Region Zambezi 13.9 218 Erongo 31.1 372 Hardap 13.2 152 //Karas 21.4 151 Kavango 32.6 316 Khomas 31.2 1,023 Kunene 51.4 104 Ohangwena 12.2 328 Omaheke 48.2 103 Omusati 15.6 342 Oshana 18.4 335 Oshikoto 15.5 335 Otjozondjupa 39.7 241 Religion Roman Catholic 23.1 1,137 Protestant/Anglican 33.9 576 ELCIN 21.8 1,944 Seventh-Day Adventist 20.6 176 No religion 43.5 85 Other 39.0 553 Total 15-49 25.5 4,021 50-64 31.5 460 ELCIN = Evangelical Lutheran Church in Namibia 190 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.13 shows attitudes toward male circumcision among men age 15-49 by background characteristics. A large majority of men age 15-49 (80 percent) and men age 50-64 (70 percent) said that they would have their baby boy circumcised. This percentage is somewhat lower among men age 40-49 (73-74 percent) than among younger respondents. By region, men in Hardap (61 percent) and //Karas (62 percent) are least likely to report that they would have their baby boy circumcised, and men in Omaheke (88 percent) are most likely to report that they would do so. The percentage of men who would have their baby boy circumcised is lowest among those with no education or a primary education (77 percent each) and those in the lowest wealth quintile (71 percent). Table 14.13 Attitudes toward male circumcision Among men age 15-49, percent distribution by whether they would have their baby boy circumcised, by background characteristics, Namibia 2013 Background characteristic No Yes Don't know Missing Total Number Age 15-19 18.2 78.8 2.9 0.1 100.0 922 20-24 14.9 82.1 2.8 0.1 100.0 808 25-29 13.3 83.2 3.3 0.3 100.0 658 30-34 17.7 80.2 2.0 0.0 100.0 520 35-39 19.0 78.6 2.0 0.4 100.0 448 40-44 22.6 73.5 3.9 0.0 100.0 376 45-49 22.7 73.3 3.8 0.2 100.0 289 Residence Urban 18.1 79.2 2.4 0.2 100.0 2,494 Rural 18.6 77.5 3.7 0.2 100.0 1,987 Region Zambezi 20.8 71.3 7.7 0.2 100.0 234 Erongo 21.2 76.7 2.1 0.0 100.0 420 Hardap 30.4 61.1 8.5 0.0 100.0 179 //Karas 26.9 61.7 10.6 0.8 100.0 178 Kavango 25.3 71.7 2.6 0.4 100.0 347 Khomas 20.4 78.1 1.5 0.0 100.0 1,095 Kunene 9.2 85.3 5.2 0.4 100.0 120 Ohangwena 17.2 80.9 1.5 0.3 100.0 359 Omaheke 9.8 87.8 2.2 0.2 100.0 131 Omusati 10.4 85.9 3.7 0.0 100.0 392 Oshana 11.7 86.6 1.2 0.5 100.0 362 Oshikoto 15.0 82.7 2.0 0.3 100.0 374 Otjozondjupa 15.6 81.7 2.7 0.0 100.0 292 Education No education 18.6 77.3 4.0 0.0 100.0 310 Primary 20.0 76.8 3.1 0.2 100.0 944 Secondary 16.3 80.8 2.7 0.1 100.0 2,400 More than secondary 17.6 79.2 2.8 0.5 100.0 368 Wealth quintile Lowest 24.8 71.4 3.4 0.4 100.0 656 Second 16.3 80.2 3.4 0.1 100.0 845 Middle 15.2 81.9 2.9 0.0 100.0 984 Fourth 15.5 81.5 2.9 0.1 100.0 1,020 Highest 22.0 75.1 2.7 0.3 100.0 975 Total 15-49 17.5 79.5 2.9 0.2 100.0 4,021 50-64 25.8 69.9 4.0 0.3 100.0 460 Table 14.14 shows the percent distribution of men by their opinion on whether or not there are any benefits to male circumcision, according to background characteristics. Eight in ten men age 15-49 (80 percent) and 72 percent of men age 50-64 believe that there are benefits to male circumcision. Men age 40- 49 (77 percent), those living in //Karas (62 percent), those with no education or only a primary education (76-77 percent), and those in the lowest wealth quintile (75 percent) are less likely than men in other groups to believe that there are benefits to male circumcision. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 191 Table 14.14 Benefits of male circumcision Among men age 15-49, percent distribution by whether they think that there are benefits to male circumcision, by background characteristics, Namibia 2013 Background characteristic No Yes Don't know Missing Total Number Age 15-19 9.0 79.1 11.6 0.3 100.0 922 20-24 7.3 84.3 8.3 0.0 100.0 808 25-29 5.9 83.0 10.6 0.5 100.0 658 30-34 6.5 79.7 13.8 0.0 100.0 520 35-39 6.8 78.2 14.5 0.4 100.0 448 40-44 9.7 77.3 13.0 0.0 100.0 376 45-49 8.3 76.7 15.0 0.0 100.0 289 Residence Urban 8.4 80.1 11.3 0.2 100.0 2,494 Rural 7.6 78.8 13.4 0.2 100.0 1,987 Region Zambezi 14.2 77.8 8.1 0.0 100.0 234 Erongo 10.0 78.4 11.6 0.0 100.0 420 Hardap 10.9 68.6 20.5 0.0 100.0 179 //Karas 17.9 62.2 19.9 0.0 100.0 178 Kavango 10.9 67.8 20.7 0.7 100.0 347 Khomas 9.3 78.0 12.5 0.2 100.0 1,095 Kunene 6.0 81.8 12.3 0.0 100.0 120 Ohangwena 3.7 88.7 7.3 0.3 100.0 359 Omaheke 4.9 86.0 8.9 0.2 100.0 131 Omusati 2.9 87.1 10.0 0.0 100.0 392 Oshana 5.1 87.3 7.1 0.5 100.0 362 Oshikoto 5.9 81.5 12.6 0.0 100.0 374 Otjozondjupa 6.0 82.0 11.9 0.0 100.0 292 Education No education 5.5 76.7 17.8 0.0 100.0 310 Primary 9.4 75.5 15.0 0.1 100.0 944 Secondary 7.1 82.2 10.5 0.2 100.0 2,400 More than secondary 8.1 84.9 6.5 0.5 100.0 368 Wealth quintile Lowest 9.2 74.7 15.9 0.2 100.0 656 Second 6.2 81.4 12.2 0.1 100.0 845 Middle 6.1 81.5 12.3 0.1 100.0 984 Fourth 7.2 82.2 10.4 0.2 100.0 1,020 Highest 11.8 76.4 11.6 0.2 100.0 975 Total 15-49 7.6 80.4 11.8 0.2 100.0 4,021 50-64 12.1 71.8 16.1 0.0 100.0 460 Table 14.15 shows the percentage of men age 15-64 citing specific benefits of male circumcision. Protection against HIV (56 percent) and protection against sexually transmitted infections (54 percent) are most likely to be cited as benefits of male circumcision. More than four in ten (42 percent) believe that male circumcision is good for health and hygiene, and one in ten (10 percent) say that it is recommended by tradition or religion. Table 14.15 Specific benefits of male circumcision Among men age 15-64 who believe that there are benefits to male circumcision, percentage who report specific benefits, Namibia 2013 Benefits of male circumcision Percentage Recommended by tradition/religion 10.0 Good for health/hygiene 42.1 Protects against getting HIV 55.7 Protects against getting STIs 53.5 Increases sexual satisfaction 1.1 Easier to put on condom 0.7 Other 1.2 Don’t know 0.8 Number of respondents 3,564 192 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour 14.9 SELF-REPORTING OF SEXUALLY TRANSMITTED INFECTIONS In the 2013 NDHS, respondents who had ever had sex were asked whether they had a sexually transmitted infection or symptoms of an STI (a bad-smelling, abnormal discharge from the vagina/penis or a genital sore or ulcer) in the 12 months preceding the survey. Table 14.16 shows the self-reported prevalence of STIs and/or STI symptoms among women and men age 15-49, by background characteristics. Women are more likely than men to report having had an STI or having experienced STI symptoms in the past 12 months (10 percent versus 6 percent). Five percent of women and men age 50-64 reported having had an STI or STI symptoms in the past 12 months. Table 14.16 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms Among women and men age 15-49 who ever had sexual intercourse, the percentage reporting having an STI and/or symptoms of an STI in the past 12 months, by background characteristics, Namibia 2013 Women Men Percentage of women who reported having in the past 12 months: Number of women who ever had sexual inter- course Percentage of men who reported having in the past 12 months: Number of men who ever had sexual inter- course Background characteristic STI Bad- smelling/ abnormal genital discharge Genital sore or ulcer STI/genital discharge/ sore or ulcer STI Bad- smelling/ abnormal discharge from penis Genital sore or ulcer STI/ abnormal discharge from penis/ sore or ulcer Age 15-24 3.9 8.0 4.0 11.4 2,467 1.9 4.0 2.8 6.4 1,141 15-19 2.4 7.4 4.3 10.4 852 0.6 3.4 1.7 5.1 395 20-24 4.6 8.3 3.9 11.9 1,615 2.6 4.4 3.3 7.0 745 25-29 4.1 7.0 5.5 11.1 1,457 4.1 4.6 4.1 8.4 639 30-39 3.6 5.3 3.9 8.8 2,328 3.1 3.1 3.8 5.9 953 40-49 3.2 5.4 3.7 8.4 1,600 3.2 3.1 1.8 4.9 650 Marital status Never married 3.4 6.2 3.3 9.2 4,155 2.5 4.3 3.3 6.3 2,122 Married/living together 3.9 6.6 5.0 10.5 3,104 3.2 2.6 3.1 6.1 1,146 Divorced/separated/ widowed 4.7 8.1 6.0 12.9 593 6.8 3.6 1.9 8.1 115 Male circumcision Circumcised na na na na na 4.2 5.1 3.6 8.1 908 Not circumcised na na na na na 2.5 3.2 3.0 5.7 2,462 Residence Urban 4.2 7.6 4.2 11.0 4,510 2.7 3.6 2.5 5.9 2,014 Rural 3.0 5.0 4.2 8.6 3,342 3.2 3.8 4.1 6.9 1,369 Region Zambezi 1.7 5.5 2.6 8.0 420 4.7 3.3 3.5 6.1 204 Erongo 2.9 7.4 3.6 10.5 675 2.1 2.5 1.9 3.5 326 Hardap 5.4 9.5 3.3 12.6 261 0.0 0.0 0.7 0.7 130 //Karas 2.7 7.8 5.1 11.1 301 2.8 3.2 3.2 4.2 121 Kavango 5.3 6.3 11.7 15.0 774 3.7 1.9 4.7 8.0 271 Khomas 4.0 7.1 3.2 10.0 1,903 2.8 4.2 2.0 6.9 930 Kunene 9.4 8.5 5.3 14.7 247 2.8 2.8 2.6 5.7 94 Ohangwena 1.6 6.2 2.7 7.8 714 1.4 1.9 5.1 6.0 247 Omaheke 7.6 12.1 5.7 15.9 208 14.4 17.0 11.3 19.1 93 Omusati 0.9 2.1 1.4 3.2 671 2.6 2.4 2.0 4.9 211 Oshana 3.2 3.6 3.2 6.0 631 1.7 4.8 3.6 7.0 265 Oshikoto 2.9 5.6 4.0 9.4 582 2.2 5.8 4.9 8.5 285 Otjozondjupa 7.0 9.8 4.6 14.3 466 3.2 2.6 1.7 3.5 205 Education No education 3.8 6.4 6.3 11.1 402 2.6 3.4 4.6 6.1 291 Primary 3.8 6.8 6.4 10.8 1,541 3.5 4.7 4.7 8.1 734 Secondary 3.9 6.4 3.5 9.6 5,091 2.9 3.9 2.6 6.3 2,012 More than secondary 2.5 6.9 3.4 9.7 818 1.9 1.1 1.5 3.0 346 Wealth quintile Lowest 2.9 5.7 4.9 9.1 1,225 2.9 3.2 4.0 6.7 492 Second 3.4 4.9 4.6 8.6 1,413 3.0 3.3 4.0 6.7 622 Middle 3.7 6.0 3.8 9.8 1,574 3.2 6.3 4.2 8.9 749 Fourth 4.6 8.0 4.6 11.6 1,844 3.2 3.7 2.7 5.7 783 Highest 3.6 7.2 3.2 10.1 1,797 2.1 1.8 1.4 3.7 738 Total 15-49 3.7 6.5 4.2 10.0 7,852 2.9 3.7 3.1 6.3 3,383 50-64 1.8 2.7 2.7 4.8 787 3.6 1.7 2.6 5.0 450 Note: Total includes 14 men with missing information on circumcision. na = Not applicable HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 193 The prevalence of STIs or STI symptoms is somewhat higher among women and men age 20-29 and those who are divorced, separated, or widowed than among their counterparts. Circumcised men have a slightly higher prevalence of STIs or STI symptoms than uncircumcised men (8 percent and 6 percent, respectively). The prevalence of STIs or STI symptoms is higher among urban than rural women (11 percent versus 9 percent), while among men the proportions are similar in urban (6 percent) and rural (7 percent) areas. By region, the proportion of women reporting an STI or STI symptoms ranges from 3 percent in Omusati to 16 percent in Omaheke. Among men, the proportion is lowest in Hardap (1 percent) and highest in Omaheke (19 percent). There is no clear overall pattern in the prevalence of STIs or STI symptoms by education or wealth. Among men, however, the prevalence is lowest among those with more than a secondary education (3 percent) and those in the highest wealth quintile (4 percent). There has been a slight increase since the 2006-07 NDHS in the percentage of respondents age 15- 49 who had an STI or STI symptoms in the preceding 12 months, from 7 percent to 10 percent of women and from 4 percent to 6 percent of men. Figure 14.1 shows that more than six in ten women (63 percent) and men (62 percent) who had an STI or STI symptoms sought advice or treatment from a clinic, hospital, private doctor, or other health professional. Few respondents sought advice or treatment from a shop or pharmacy (3 percent of women and less than 1 percent of men) or any other source (1 percent each). About three in ten women (29 percent) and one in four men (26 percent) did not seek any treatment when they had an STI or STI symptoms. Figure 14.1 Women and men seeking advice for treatment of STIs 14.10 INJECTIONS Injection overuse in a health care setting can contribute to the transmission of blood-borne pathogens because it amplifies the effect of unsafe practices such as reuse of injection equipment. To measure the potential risk of transmission of HIV associated with medical injections, NDHS respondents were asked whether they had received any injections from a health worker in the 12 months preceding the survey and, if so, whether their last injection was administered with a syringe from a new, unopened package. It should be noted that self-administered medical injections (e.g., insulin injections for diabetes) were not included in the calculations. 63 3 1 29 62 <1 1 26 Clinic/hospital/private doctor/other health professional Advice or medicine from shop/pharmacy Advice or treatment from any other source No advice or treatment Percentage Women Men NDHS 2013 194 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.17 shows the reported prevalence of injections and of safe injection practices. Thirty- seven percent of women and 17 percent of men age 15-49 reported receiving an injection from a health worker during the 12 months preceding the survey. Among respondents age 50-64, 23 percent of women and 20 percent of men had received an injection from a health worker in the past 12 months. Table 14.17 Prevalence of medical injections Percentage of women and men age 15-49 who received at least one medical injection in the past 12 months, the average number of medical injections per person in the past 12 months, and among those who received a medical injection, the percentage of last medical injections for which the syringe and needle were taken from a new, unopened package, by background characteristics, Namibia 2013 Women Men Background characteristic Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of women For last injection, syringe and needle taken from a new, unopened package Number of women receiving medical injections in the past 12 months Percentage who received a medical injection in the past 12 months Average number of medical injections per person in the past 12 months Number of men For last injection, syringe and needle taken from a new, unopened package Number of men receiving medical injections in the past 12 months Age 15-24 39.6 1.1 3,691 97.4 1,462 16.6 0.4 1,730 95.8 287 15-19 41.2 1.0 1,906 96.7 784 19.0 0.4 922 94.6 175 20-24 37.9 1.2 1,786 98.3 677 13.9 0.4 808 97.6 112 25-29 41.7 1.5 1,489 98.2 622 16.4 0.6 658 96.1 108 30-39 34.1 1.3 2,370 97.8 807 16.8 0.5 968 98.7 163 40-49 28.0 1.1 1,625 96.8 456 18.6 0.8 665 97.3 124 Marital status Never married 37.6 1.1 5,458 97.7 2,050 16.4 0.4 2,745 95.4 451 Ever had sex 37.5 1.2 4,155 97.7 1,559 15.8 0.4 2,122 95.7 335 Never had sex 37.7 0.8 1,304 97.8 491 18.7 0.4 623 94.8 116 Married/living together 35.3 1.3 3,121 97.3 1,101 17.8 0.5 1,160 99.3 207 Divorced/separated/ widowed 32.8 1.5 597 97.5 196 20.5 1.7 116 * 24 Residence Urban 35.9 1.3 5,190 97.9 1,862 17.4 0.5 2,282 99.2 397 Rural 37.2 1.1 3,986 97.1 1,484 16.4 0.5 1,739 93.5 284 Region Zambezi 52.7 1.9 457 98.7 240 17.2 0.4 218 98.3 37 Erongo 33.8 1.1 771 98.0 261 15.3 0.8 372 97.3 57 Hardap 36.8 1.3 304 98.0 112 10.4 0.5 152 (97.4) 16 //Karas 42.3 1.3 343 98.3 145 17.1 0.4 151 100.0 26 Kavango 33.4 1.2 835 96.0 279 19.3 0.5 316 94.9 61 Khomas 34.2 1.3 2,202 98.9 753 18.8 0.4 1,023 100.0 192 Kunene 35.5 1.2 258 96.0 92 8.6 0.2 104 * 9 Ohangwena 37.7 1.1 894 97.9 337 19.5 0.9 328 (89.3) 64 Omaheke 34.2 1.2 225 89.6 77 4.1 0.9 103 * 4 Omusati 39.2 1.1 884 99.3 347 12.7 0.3 342 (94.0) 43 Oshana 35.9 1.1 755 97.2 271 17.3 0.5 335 (94.9) 58 Oshikoto 39.4 1.2 707 95.5 279 25.5 0.5 335 97.6 85 Otjozondjupa 28.5 1.3 540 95.0 154 11.9 0.3 241 (97.8) 29 Education No education 21.2 0.6 419 93.7 89 13.7 0.5 310 (95.1) 42 Primary 34.6 1.2 1,798 97.0 622 16.5 0.5 944 93.7 156 Secondary 37.8 1.3 6,029 97.7 2,281 16.9 0.5 2,400 97.9 406 More than secondary 38.2 1.2 930 99.0 355 21.1 0.6 368 98.3 78 Wealth quintile Lowest 36.9 1.2 1,429 97.7 528 15.0 0.6 594 93.0 89 Second 36.7 1.3 1,625 96.7 597 18.8 0.5 769 92.0 144 Middle 37.5 1.1 1,795 97.2 673 13.5 0.3 886 99.3 120 Fourth 37.1 1.2 2,116 98.0 786 18.0 0.4 917 99.3 165 Highest 34.5 1.3 2,211 98.0 763 19.2 0.7 855 98.7 164 Total 15-49 36.5 1.2 9,176 97.6 3,346 17.0 0.5 4,021 96.8 682 50-64 22.5 1.0 797 96.2 179 19.9 1.1 460 91.5 92 Note: Medical injections are those given by a doctor, nurse, pharmacist, dentist, or other health worker. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. The percentage of women who received medical injections is highest among those age 25-29 (42 percent). This percentage varies by region, ranging from a high of 53 percent in Zambezi to a low of 29 percent in Otjozondjupa. Among men, there are slight variations by age. By region, the percentage of men who received a medical injection in the past 12 months is lowest among those in Omaheke (4 percent) and highest among those in Oshikoto (26 percent). In the case of both women and men, the proportion who HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 195 received medical injections in the past 12 months is highest among those with more than a secondary education. There is no clear association with wealth. Table 14.17 further shows that, on average, respondents age 15-49 received about one medical injection in the preceding 12 months. More than 9 in 10 women and men age 15-49 (98 percent of women and 97 percent of men) reported that their last injection was given with a syringe and needle taken from a new, unopened package. There are no major variations by background characteristics. 14.11 HIV/AIDS-RELATED KNOWLEDGE AND BEHAVIOUR AMONG YOUNG PEOPLE This section addresses HIV/AIDS-related knowledge among young Namibians age 15-24 and assesses the extent to which young people are engaged in behaviours that may place them at risk of contracting HIV. 14.11.1 Knowledge about HIV/AIDS and Source for Condoms Knowledge of how HIV is transmitted is crucial to enabling people to avoid HIV infection, and this is especially true for young people, who are often at greater risk because they may have shorter relationships with more partners or engage in other risky behaviours. Table 14.18 shows the level of comprehensive knowledge of HIV/AIDS among young people and the percentage of young people who know a source for condoms. As discussed earlier, comprehensive knowledge of HIV/AIDS is defined as knowing that condom use and limiting sexual intercourse to one uninfected partner are HIV prevention methods, knowing that a healthy-looking person can have HIV, and rejecting the two most common local misconceptions about HIV transmission. Table 14.18 shows that 62 percent of young women and 51 percent of young men have comprehensive knowledge of HIV/AIDS. In the case of young women, comprehensive knowledge about AIDS is lowest among those age 15-17 (52 percent), while among young men it varies only slightly by age. Never-married youth who have had sex and those who live in urban areas are more likely than those in other groups to have comprehensive knowledge about AIDS. For example, 67 percent of urban young women have comprehensive knowledge about AIDS, as compared with 55 percent of those in rural areas. Among both young women and young men, the percentage with comprehensive knowledge about AIDS increases with increasing education. Knowledge of a source for condoms is very high among Namibian youth. Ninety-one percent of young women and 94 percent of young men know a place where they can obtain a condom. 196 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.18 Comprehensive knowledge about AIDS and of a source of condoms among youth Percentage of young women and young men age 15-24 with comprehensive knowledge about AIDS and percentage with knowledge of a source of condoms, by background characteristics, Namibia 2013 Women age 15-24 Men age 15-24 Background characteristic Percentage with comprehensive knowledge of AIDS1 Percentage who know a condom source2 Number of women Percentage with comprehensive knowledge of AIDS1 Percentage who know a condom source2 Number of men Age 15-19 55.9 85.3 1,906 51.4 90.0 922 15-17 52.2 80.5 1,076 49.5 86.2 576 18-19 60.7 91.6 830 54.5 96.4 346 20-24 67.8 96.6 1,786 50.6 98.4 808 20-22 67.8 95.9 1,136 51.7 97.7 494 23-24 67.7 98.0 650 49.0 99.5 314 Marital status Never married 63.4 90.2 3,184 51.9 93.6 1,642 Ever had sex 66.0 95.5 1,963 53.6 97.9 1,054 Never had sex 59.2 81.5 1,221 48.8 85.9 588 Ever married 50.7 94.8 507 35.6 100.0 88 Residence Urban 67.3 95.9 2,008 51.8 97.8 858 Rural 54.9 84.7 1,683 50.3 90.1 872 Education No education 22.7 72.2 66 20.6 88.1 63 Primary 38.2 78.4 638 36.9 82.5 409 Secondary 66.0 93.1 2,620 56.0 97.7 1,159 More than secondary 78.0 99.4 368 71.1 100.0 100 Total 15-24 61.6 90.8 3,691 51.1 93.9 1,730 1 Comprehensive knowledge means knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting the AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the 2 most common local misconceptions about AIDS transmission or prevention of the AIDS virus. The components of comprehensive knowledge are presented in Tables 14.2, 14.3.1, and 14.3.2. 2 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 14.11.2 First Sex Age at first sex is an important indicator of exposure to the risk of pregnancy and sexually transmitted infections. Young people who initiate sex at an early age are typically at higher risk of becoming pregnant or contracting an STI than young people who delay the onset of sexual activity. Consistent condom use can reduce such risks. Among respondents age 15-24, a higher percentage of young men (13 percent) than young women (5 percent) have had sex before age 15 (Table 14.19). Similarly, 42 percent of women and 57 percent of men age 18-19 had sexual intercourse before age 18. As expected, the proportion of youth age 15-24 initiating sexual intercourse by age 15 is higher among those who have ever been married than among those who were not yet married at the time of the survey. This percentage is also higher among youth who know of a source of condoms than among those who do not. Rural women age 15-24 are more likely than their urban counterparts to have initiated sex before age 15 (7 percent and 4 percent, respectively). The difference is less pronounced among young men (12 percent in urban areas versus 14 percent in rural areas). Young people with no formal education are most likely to have had sexual intercourse by age 15 (21 percent of women and 18 percent of men), and those with more than a secondary education are least likely to have done so (less than 1 percent of women and 7 percent of men). Similarly, among women age 18-24, those with no formal education are more than three times as likely to have had sex for the first time before age 18 than those with more than a secondary education (67 percent versus 21 percent). By contrast, the proportion of young men age 18-24 who initiated sexual intercourse before age 18 shows little difference by educational status. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 197 Table 14.19 Age at first sexual intercourse among young people Percentage of young women and young men age 15-24 who had sexual intercourse before age 15 and percentage of young women and young men age 18-24 who had sexual intercourse before age 18, by background characteristics, Namibia 2013 Women age 15-24 Women age 18-24 Men age 15-24 Men age 18-24 Background characteristic Percentage who had sexual intercourse before age 15 Number of women Percentage who had sexual intercourse before age 18 Number of women Percentage who had sexual intercourse before age 15 Number of men Percentage who had sexual intercourse before age 18 Number of men Age 15-19 6.8 1,906 na na 13.4 922 na na 15-17 8.2 1,076 na na 13.3 576 na na 18-19 5.0 830 47.4 830 13.5 346 59.4 346 20-24 3.9 1,786 39.7 1,786 12.7 808 55.2 808 20-22 4.0 1,136 41.2 1,136 12.8 494 56.1 494 23-24 3.8 650 36.9 650 12.5 314 53.8 314 Marital status Never married 4.3 3,184 37.0 2,142 12.8 1,642 56.7 1,067 Ever married 12.2 507 65.3 474 17.1 88 53.2 87 Knows condom source1 Yes 5.5 3,351 42.3 2,486 13.4 1,625 56.5 1,129 No 4.8 340 38.2 130 8.6 105 (54.7) 26 Residence Urban 3.7 2,008 37.0 1,553 12.2 858 57.4 631 Rural 7.4 1,683 49.6 1,063 13.9 872 55.3 524 Education No education 21.3 66 67.2 50 18.4 63 59.1 53 Primary 13.8 638 66.2 300 14.0 409 52.7 199 Secondary 3.7 2,620 41.6 1,903 13.0 1,159 57.2 801 More than secondary 0.4 368 21.4 363 6.8 100 56.7 100 Total 5.4 3,691 42.1 2,616 13.1 1,730 56.5 1,154 Note: Figures in parentheses are based on 25-49 unweighted cases. na = Not applicable 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. Figure 14.2 shows trends in age at first sexual intercourse among young people between 2000 and 2013. The percentage of young women age 15-19 who had sex before age 15 decreased slightly between the 2000 and 2006-07 NDHS surveys, from 10 percent to 7 percent, and remained at 7 percent in 2013. Among young men age 15-19, there has been a steady decrease over the last 13 years in the proportion who had sex before age 15, from 31 percent in 2000 to 19 percent in 2006-07 and 13 percent in 2013. The percentage of women 18-19 who had sex before age 18 has decreased steadily over time, from 59 percent in 2000 to 47 percent in 2013. The percentage has decreased among young men as well, from 74 percent in 2000 to 59 percent in 2013. 198 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Figure 14.2 Trends in age at first sexual intercourse 14.11.3 Premarital Sex Table 14.20 shows the percentage of never-married women and men age 15-24 who have never had sex, the percentage who engaged in sexual intercourse in the past 12 months, and, among those who had sexual intercourse within the past 12 months, the percentage who used a condom during their most recent sexual encounter. Overall, 38 percent of women and 36 percent of men age 15-24 have never had sexual intercourse. Never-married young women and men age 15-19 have a relatively high level of abstinence (59 percent and 58 percent, respectively). Youth who do not know of a condom source, those who live in rural areas, and those with a primary education are more likely to have never had sex than youth in other groups. Table 14.20 further shows that, among never-married young women age 15-24, 52 percent had sexual intercourse in the past 12 months. Among these women, only 68 percent reported using a condom during their last sexual encounter. Among never-married young men in this age group, again 52 percent reported having a sexual encounter in the past 12 months. More than eight in ten of these young men (83 percent) used a condom during their last sexual intercourse. The percentage of never-married youth who had sexual intercourse in the past 12 months increases with increasing age, as expected. However, among both young women and young men, the percentage who used a condom during their last sexual intercourse varies only slightly according to age. The percentage of never-married youth who had sexual intercourse in the past 12 months is slightly higher among those living in urban (55 percent of women and 57 percent of men) than rural (47 percent of women and 48 percent of men) areas. There is no clear pattern with respect to education in the percentage of young men and women who have had sex in the past 12 months. On the other hand, there is a clear and increasing correlation between educational attainment and the percentage of never-married women and men who used a condom during their last sexual intercourse, with respondents at higher levels of education being more likely than those at lower levels to report having used a condom. 10 31 59 74 7 19 50 61 7 13 47 59 Percentage of women 15-19 who had sexual intercourse before exact age 15 Percentage of men 15-19 who had sexual intercourse before exact age 15 Percentage of women 18-19 who had sexual intercourse before exact age 18 Percentage of men 18-19 who had sexual intercourse before exact age 18 Percent 2000 NDHS 2006-07 NDHS 2013 NDHS HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 199 Table 14.20 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth Among never-married women and men age 15-24, the percentage who have never had sexual intercourse, the percentage who had sexual intercourse in the past 12 months, and, among those who had premarital sexual intercourse in the past 12 months, the percentage who used a condom at the last sexual intercourse, by background characteristics, Namibia 2013 Women Men Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of never- married women Women who had sexual intercourse in the past 12 months Percentage who have never had sexual intercourse Percentage who had sexual intercourse in the past 12 months Number of never- married men Men who had sexual intercourse in the past 12 months Background characteristic Percentage who used a condom at last sexual intercourse Number of women Percentage who used a condom at last sexual intercourse Number of men Age 15-19 58.7 34.1 1,793 68.1 612 57.5 32.5 915 82.4 297 15-17 72.1 23.7 1,042 66.1 248 72.3 20.5 575 75.9 118 18-19 40.2 48.5 751 69.5 364 32.7 52.7 340 86.7 179 20-24 12.0 73.9 1,391 67.9 1,027 8.4 76.9 727 82.8 559 20-22 14.9 71.3 933 65.6 665 11.8 73.8 462 82.6 341 23-24 6.2 79.1 458 72.1 362 2.5 82.2 265 83.1 218 Knows condom source1 Yes 34.7 55.0 2,871 68.9 1,578 32.9 54.8 1,537 83.2 842 No 72.0 19.5 313 44.2 61 78.7 13.3 105 * 14 Residence Urban 35.2 55.3 1,724 72.8 953 29.7 56.9 804 84.8 457 Rural 42.0 47.0 1,461 61.3 686 41.6 47.6 838 80.2 399 Education No education 22.1 68.5 43 (42.9) 29 18.5 62.2 55 (61.2) 34 Primary 48.9 41.3 497 54.1 205 49.9 39.0 392 66.3 153 Secondary 38.0 51.0 2,306 69.3 1,175 33.4 54.3 1,098 87.2 597 More than secondary 27.0 67.8 338 77.2 229 15.6 74.2 98 90.0 73 Total 15-24 38.3 51.5 3,184 68.0 1,639 35.8 52.1 1,642 82.6 856 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 14.11.4 Multiple Sexual Partners among Youth The most common means of transmission of HIV in Namibia is through unprotected sex with an infected person. To prevent HIV transmission, it is important that young people practice safe sex. Tables 14.21.1 and 14.21.2 present data on the percentage of young people who engaged in sexual intercourse with more than one partner in the 12 months before the survey and the percentage who used a condom during their last sexual encounter. Young men are more likely than young women to report having multiple sexual partners in the 12 months preceding the survey (9 percent and 3 percent, respectively). In general, the percentage of young men and young women who reported having sexual intercourse with more than one partner in the past 12 months increases with increasing age; in addition, it is higher among ever-married youth, those who know of a source of condoms, and those living in urban areas. The percentage of young women with multiple sexual partners is highest among those with no formal education (12 percent), while among young men the percentage is highest among those with more than a secondary education (15 percent). Among young women and men who had multiple partners in the past 12 months, 68 percent and 79 percent, respectively, reported using a condom during their last sexual intercourse. There has been a notable decrease over the last six years in the percentage of young men age 15- 24 who reported having more than one partner in the past 12 months, from 16 percent in 2006-07 to 9 percent in 2013. The percentage of young men with multiple partners who reported using a condom during their last sexual intercourse has increased from 74 percent to 79 percent over the same period. 200 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Table 14.21.1 Multiple sexual partners in the past 12 months among young people: Women Among all young women age 15-24, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months, and among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse, by background characteristics, Namibia 2013 Women age 15-24 Women age 15-24 who had 2+ partners in the past 12 months Background characteristic Percentage who had 2+ partners in the past 12 months Number of women Percentage who reported using a condom at last intercourse Number of women Age 15-19 2.1 1,906 (61.4) 40 15-17 1.2 1,076 * 13 18-19 3.3 830 (74.1) 27 20-24 3.6 1,786 71.8 65 20-22 3.8 1,136 (69.6) 43 23-24 3.4 650 * 22 Marital status Never married 2.7 3,184 73.6 87 Ever married 3.5 507 * 18 Knows condom source1 Yes 2.9 3,351 71.0 99 No 1.9 340 * 6 Residence Urban 3.8 2,008 73.1 77 Rural 1.7 1,683 (53.5) 28 Education No education 11.9 66 * 8 Primary 2.1 638 * 13 Secondary 2.7 2,620 76.0 72 More than secondary 3.2 368 * 12 Total 15-24 2.8 3,691 67.8 105 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. HIV/AIDS-Related Knowledge, Attitudes, and Behaviour • 201 Table 14.21.2 Multiple sexual partners in the past 12 months among young people: Men Among all young men age 15-24, the percentage who had sexual intercourse with more than one sexual partner in the past 12 months, and among those having more than one partner in the past 12 months, the percentage reporting that a condom was used at last intercourse, by background characteristics, Namibia 2013 Men age 15-24 Men age 15-24 who had 2+ partners in the past 12 months Background characteristic Percentage who had 2+ partners in the past 12 months Number of men Percentage who reported using a condom at last intercourse Number of men Age 15-19 4.9 922 (75.1) 46 15-17 2.6 576 * 15 18-19 8.9 346 (82.8) 31 20-24 14.1 808 81.1 114 20-22 11.3 494 82.6 56 23-24 18.5 314 79.8 58 Marital status Never married 9.1 1,642 81.0 149 Ever married 12.1 88 * 11 Knows condom source1 Yes 9.8 1,625 79.4 159 No 0.2 105 * 0 Residence Urban 10.0 858 84.0 86 Rural 8.5 872 74.1 74 Education No education 8.1 63 * 5 Primary 7.3 409 (66.0) 30 Secondary 9.4 1,159 81.8 109 More than secondary 15.1 100 * 15 Total 15-24 9.2 1,730 79.4 160 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 14.11.5 Age Mixing in Sexual Relationships Research from around the world shows a steady and significant increase in rates of HIV infection among women, particularly women in Africa, Asia, Latin America, and the Caribbean. A substantial proportion of HIV/AIDS cases occur among young women age 15-29, indicating that many of these women were infected with HIV as adolescents. In many societies, young women have sexual relationships with men who are considerably older than they are. This practice can contribute to the spread of HIV and other STIs because if a younger, uninfected partner has sex with an older, infected partner, this can introduce the virus into a younger, uninfected cohort. This section examines the prevalence of sexual intercourse between partners with large age differences. Women age 15-19 who had higher-risk sexual intercourse in the past 12 months were asked the age of all of their partners. In the event they did not know a partner’s exact age, they were asked if the partner was older or younger than they were and, if older, whether the partner was 10 or more years older. Table 14.22 shows that, in the year preceding the survey, 6 percent of young women age 15-19 who had sexual intercourse had sex with a man 10 or more years older. A higher percentage of young women who had sexual intercourse with an older man resided in rural than urban areas. The likelihood of a woman having higher-risk sexual intercourse with an older man does not change with age. Sexual intercourse between women age 15-19 and men 10 or more years older appears to decrease with increasing education. 202 • HIV/AIDS-Related Knowledge, Attitudes, and Behaviour Young men age 15-19 who reported that they had a sexual partner in the past 12 months were also asked the age of the partner. Less than 1 percent of young men reported having a partner 10 or more years older. Table 14.22 Age mixing in sexual relationships among women and men age 15-19 Among women and men age 15-19 who had sexual intercourse in the past 12 months, percentage who had sexual intercourse with a partner who was 10 or more years older than themselves, by background characteristics, Namibia 2013 Women age 15-19 who had sexual intercourse in the past 12 months Men age 15-19 who had sexual intercourse in the past 12 months Background characteristic Percentage who had sexual intercourse with a man 10+ years older Number of women Percentage who had sexual intercourse with a woman 10+ years older Number of men Age 15-17 5.4 279 0.0 119 18-19 5.8 441 0.3 185 Marital status Never married 4.0 612 0.0 297 Ever married 14.9 107 * 7 Knows condom source1 Yes 5.5 675 0.2 294 No (8.6) 45 * 10 Residence Urban 4.2 333 0.0 140 Rural 6.9 386 0.3 164 Education No education (11.2) 21 * 7 Primary 9.3 182 0.7 70 Secondary 4.4 482 0.0 217 More than secondary * 34 * 9 Total 5.7 719 0.2 304 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. HIV Prevalence • 203 HIV PREVALENCE 15 nformation about the magnitude of and trends in national HIV prevalence in Namibia is obtained from sentinel surveillance of HIV among pregnant women attending antenatal care (ANC) clinics. The national HIV prevalence among pregnant women was estimated at 18.2 percent according to the 2012 HIV Antenatal Clinic Sentinel Surveillance Report (MoHSS, 2012e). In addition, Namibia is currently conducting its first Integrated Bio-Behavioural Surveillance Survey with high-risk populations, namely men who have sex with men and female sex workers. However, these surveillance data do not provide an estimate of the HIV prevalence among the general population in Namibia. In the absence of population- based data, data from ANC sentinel surveillance are used (via the Spectrum model) to estimate the national HIV prevalence. Based on this model, the 2011/2012 HIV prevalence among adult population age 15-49 was estimated at 13.4 percent (MoHSS, 2012b). The 2013 NDHS is the first nationally representative survey to provide direct HIV prevalence estimates for the general population in Namibia. The survey included HIV testing of a nationally representative sample of women and men age 15-64 in half of the selected survey households (the same households selected for the male survey). HIV prevalence is disaggregated by various background characteristics, such as age, residence, region, education, and wealth. In addition, HIV prevalence is I Key Findings • In Namibia, 14.0 percent of adults age 15-49 and 16.4 percent of those age 50-64 are infected with HIV. • HIV prevalence among respondents age 15-49 is 16.9 percent for women and 10.9 percent for men. HIV prevalence rates among women and men age 50-64 are similar (16.7 percent and 16.0 percent, respectively). • HIV prevalence peaks in the 35-39 age group for both women and men (30.9 percent and 22.6 percent, respectively). It is lowest among respondents age 15-24 (2.5-6.4 percent for women and 2.0-3.4 percent for men). • Among respondents age 15-49, HIV prevalence is highest for women and men in Zambezi (30.9 percent and 15.9 percent, respectively) and lowest for women in Omaheke (6.9 percent) and men in Ohangwena (6.6 percent). • Among women and men age 5-49, the percentage HIV positive decreases with education and it generally decreases with wealth. • More than half of widowed women (51.7 percent) are infected with the AIDS virus. • Men age 15-49 with a sexually transmitted infection (STI) or STI symptoms in the past 12 months are much more likely to test HIV positive than those who did not have an STI or STI symptoms (24.8 percent versus11.7 percent). • In 76.4 percent of the 1,007 cohabiting couples who were tested for HIV in the 2013 NDHS, both partners were HIV negative; in 10.1 percent of the couples, both partners were HIV positive; and 13.5 percent of the couples were discordant (that is, one partner was infected with HIV and the other was not). 204 • HIV Prevalence analysed according to demographic characteristics and sexual behaviour to identify factors associated with the epidemic. Test results will be used to further refine HIV prevalence estimates based on the sentinel surveillance system and allow better monitoring of the epidemic. HIV prevalence estimates will also be used to project the future path of the HIV epidemic in Namibia and to target prevention, care, and treatment interventions effectively and efficiently. The methodology for HIV testing is described in detail in Chapter 1. This chapter presents the results of the testing and provides information on HIV testing coverage rates among eligible survey respondents. 15.1 PARTICIPATION RATES FOR HIV TESTING Tables 15.1.1 and 15.1.2 show the distributions of respondents age 15-49 and age 50-64, respectively, who were eligible for HIV testing by background characteristics, residence, and region. Overall, 79 percent of NDHS respondents age 15-49 who were eligible for testing were both interviewed and tested and 2 percent were tested but not interviewed. Among respondents age 50-64, 80 percent were interviewed and tested and 3 percent were tested but not interviewed. Among respondents age 15-49 and 50-64 eligible for HIV testing, 8 percent each refused to provide blood. Six percent of respondents age 15-49 and 4 percent of respondents age 50-64 were absent at the time of blood collection. HIV testing rate does not vary much by age for women. Among men, it ranges from 68 percent among those age 40-44 to 80 percent among those age 15-19. Participation of all eligible respondents age 15-49 in HIV testing was higher among rural (84 percent) than urban residents (74 percent). By region, testing rates among respondents age 15-49 ranges from 60 percent in Khomas to 90 percent in Ohangwena. HIV testing rates among all respondents age 15-49 were lowest for respondents with more than secondary education (65 percent) and for those in the highest wealth quintile (68 percent). HIV Prevalence • 205 Table 15.1.1 Coverage of HIV testing by background characteristics: Respondents age 15-49 Percent distribution of women and men age 15-49 eligible for HIV testing by testing status, according to background characteristics (unweighted), Namibia 2013 Testing status DBS tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Background characteristic Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Total Number WOMEN 15-49 Age 15-19 85.6 1.3 4.7 1.3 1.7 1.9 2.4 1.0 100.0 991 20-24 83.3 2.0 4.5 1.7 2.3 3.4 1.1 1.7 100.0 974 25-29 81.4 2.2 6.3 1.2 3.1 2.1 1.5 2.2 100.0 813 30-34 82.5 2.9 5.0 1.9 1.6 2.9 1.4 1.9 100.0 699 35-39 82.8 2.0 5.8 1.7 0.9 2.1 1.8 2.9 100.0 656 40-44 84.1 1.0 5.7 1.6 3.3 1.2 1.4 1.6 100.0 491 45-49 81.7 2.1 6.5 1.6 2.1 2.1 1.4 2.6 100.0 431 Residence Urban 78.7 2.2 7.2 2.2 2.5 3.0 1.9 2.2 100.0 2,724 Rural 88.4 1.6 3.2 0.8 1.7 1.6 1.2 1.5 100.0 2,331 Region Zambezi 79.5 2.7 6.7 1.3 2.7 1.1 2.4 3.5 100.0 371 Erongo 80.3 3.4 5.7 1.9 0.8 3.4 1.7 2.9 100.0 476 Hardap 88.4 0.0 4.9 0.3 1.7 2.6 0.6 1.5 100.0 344 //Karas 87.2 0.7 4.9 0.2 2.8 2.1 1.2 0.9 100.0 430 Kavango 79.9 6.8 4.1 2.2 2.7 2.7 0.5 1.2 100.0 413 Khomas 66.1 1.8 11.0 4.8 5.2 5.3 2.5 3.4 100.0 563 Kunene 82.4 2.0 8.1 1.3 0.7 0.7 2.9 2.0 100.0 307 Ohangwena 94.6 1.3 0.3 0.3 0.8 1.6 0.3 1.0 100.0 386 Omaheke 82.8 1.0 6.8 0.0 2.4 1.7 3.4 2.0 100.0 296 Omusati 89.7 1.6 1.3 0.8 2.1 1.3 2.1 1.1 100.0 377 Oshana 88.8 0.5 2.4 1.6 0.8 3.2 1.6 1.1 100.0 374 Oshikoto 86.4 0.3 5.5 0.6 2.0 2.0 0.6 2.6 100.0 346 Otjozondjupa 84.9 1.9 6.2 3.0 1.1 0.5 1.6 0.8 100.0 372 Education No education 76.9 5.5 7.0 1.8 0.0 1.2 2.1 5.5 100.0 329 Primary 86.5 2.0 3.2 1.3 2.3 1.5 1.7 1.4 100.0 1,052 Secondary 84.6 1.6 5.2 1.4 2.1 2.3 1.4 1.5 100.0 3,281 More than secondary 68.9 0.8 11.6 3.1 3.6 5.7 2.8 3.6 100.0 389 Missing 0.0 25.0 0.0 0.0 0.0 50.0 0.0 25.0 100.0 4 Wealth quintile Lowest 88.5 2.3 2.3 0.5 2.1 1.8 1.5 0.9 100.0 777 Second 87.3 1.7 4.1 1.0 1.7 1.2 1.5 1.5 100.0 882 Middle 87.9 1.2 3.0 1.1 2.4 2.1 1.2 1.2 100.0 1,007 Fourth 81.7 2.5 6.0 1.8 2.0 2.5 1.3 2.1 100.0 1,262 Highest 73.8 1.8 9.8 2.8 2.3 3.6 2.5 3.3 100.0 1,127 Total 15-49 83.2 1.9 5.4 1.6 2.1 2.3 1.6 1.9 100.0 5,055 MEN 15-49 Age 15-19 79.6 1.8 5.1 2.9 2.1 3.4 2.5 2.5 100.0 989 20-24 73.5 2.3 8.7 2.4 2.8 5.9 2.1 2.3 100.0 884 25-29 73.6 2.5 5.8 3.8 2.6 6.7 2.5 2.5 100.0 728 30-34 69.6 2.3 8.1 3.1 3.2 7.0 2.4 4.2 100.0 616 35-39 71.3 2.1 6.1 3.9 1.6 7.1 2.1 5.7 100.0 561 40-44 67.8 3.9 6.6 3.3 4.5 5.1 3.7 5.1 100.0 488 45-49 75.1 1.4 6.5 1.7 4.2 4.5 1.4 5.1 100.0 354 Residence Urban 67.7 2.7 7.7 4.0 4.0 6.6 3.0 4.3 100.0 2,425 Rural 80.0 1.9 5.6 2.0 1.5 4.5 1.8 2.7 100.0 2,195 Region Zambezi 69.2 3.3 9.6 2.1 3.3 3.3 5.1 4.2 100.0 334 Erongo 71.7 1.8 4.3 1.8 5.3 5.1 4.9 4.9 100.0 488 Hardap 78.5 0.0 8.9 2.8 2.8 2.8 1.5 2.8 100.0 326 //Karas 78.3 1.5 3.1 4.1 3.3 6.6 0.3 2.8 100.0 392 Kavango 75.0 6.0 6.6 3.0 1.8 3.6 1.2 2.7 100.0 332 Khomas 53.8 2.5 11.6 5.6 5.7 11.8 3.2 5.7 100.0 558 Kunene 74.7 1.4 13.7 1.1 0.4 2.9 2.2 3.6 100.0 277 Ohangwena 84.6 0.7 1.4 1.8 0.0 3.9 5.4 2.2 100.0 279 Omaheke 77.6 3.7 7.1 3.1 1.4 3.4 0.7 3.1 100.0 295 Omusati 80.2 2.3 3.0 1.7 1.7 7.3 1.7 2.3 100.0 303 Oshana 75.3 1.5 3.7 2.5 3.7 7.7 1.9 3.7 100.0 324 Oshikoto 76.9 0.0 6.9 3.5 2.3 6.4 1.2 2.9 100.0 346 Otjozondjupa 76.8 4.6 5.2 4.6 1.1 3.3 1.4 3.0 100.0 366 Continued… 206 • HIV Prevalence Table 15.1.1—Continued Testing status DBS tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Background characteristic Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Total Number Education No education 72.7 4.1 4.9 1.5 1.7 5.5 1.5 8.1 100.0 469 Primary 78.8 2.0 4.4 3.5 2.3 4.0 2.0 3.0 100.0 1,118 Secondary 73.8 2.1 7.4 2.8 3.1 5.4 2.7 2.8 100.0 2,655 More than secondary 60.2 1.9 11.0 4.4 4.4 9.9 3.3 4.7 100.0 362 Missing 0.0 6.3 0.0 31.3 0.0 56.3 0.0 6.3 100.0 16 Wealth quintile Lowest 80.9 2.1 5.0 1.8 1.9 3.7 1.9 2.7 100.0 674 Second 80.0 1.6 5.3 2.5 1.8 4.8 1.4 2.4 100.0 867 Middle 77.1 2.4 5.2 2.3 2.3 6.0 2.0 2.6 100.0 1,035 Fourth 72.0 2.8 7.3 3.7 3.1 5.3 2.1 3.7 100.0 1,080 Highest 60.6 2.4 9.9 4.5 4.7 7.6 4.5 6.0 100.0 964 Total 15-49 73.6 2.3 6.7 3.1 2.8 5.6 2.4 3.5 100.0 4,620 TOTAL 15-49 Age 15-19 82.6 1.6 4.9 2.1 1.9 2.7 2.5 1.8 100.0 1,980 20-24 78.6 2.1 6.5 2.0 2.5 4.6 1.6 2.0 100.0 1,858 25-29 77.7 2.3 6.0 2.5 2.9 4.3 1.9 2.3 100.0 1,541 30-34 76.5 2.6 6.5 2.4 2.4 4.8 1.9 3.0 100.0 1,315 35-39 77.5 2.1 5.9 2.7 1.2 4.4 2.0 4.2 100.0 1,217 40-44 76.0 2.5 6.1 2.5 3.9 3.2 2.6 3.4 100.0 979 45-49 78.7 1.8 6.5 1.7 3.1 3.2 1.4 3.7 100.0 785 Residence Urban 73.5 2.4 7.4 3.1 3.2 4.7 2.4 3.2 100.0 5,149 Rural 84.4 1.7 4.3 1.4 1.6 3.0 1.5 2.1 100.0 4,526 Region Zambezi 74.6 3.0 8.1 1.7 3.0 2.1 3.7 3.8 100.0 705 Erongo 75.9 2.6 5.0 1.9 3.1 4.3 3.3 3.9 100.0 964 Hardap 83.6 0.0 6.9 1.5 2.2 2.7 1.0 2.1 100.0 670 //Karas 83.0 1.1 4.0 2.1 3.0 4.3 0.7 1.8 100.0 822 Kavango 77.7 6.4 5.2 2.6 2.3 3.1 0.8 1.9 100.0 745 Khomas 59.9 2.1 11.3 5.2 5.4 8.6 2.9 4.5 100.0 1,121 Kunene 78.8 1.7 10.8 1.2 0.5 1.7 2.6 2.7 100.0 584 Ohangwena 90.4 1.1 0.8 0.9 0.5 2.6 2.4 1.5 100.0 665 Omaheke 80.2 2.4 6.9 1.5 1.9 2.5 2.0 2.5 100.0 591 Omusati 85.4 1.9 2.1 1.2 1.9 4.0 1.9 1.6 100.0 680 Oshana 82.5 1.0 3.0 2.0 2.1 5.3 1.7 2.3 100.0 698 Oshikoto 81.6 0.1 6.2 2.0 2.2 4.2 0.9 2.7 100.0 692 Otjozondjupa 80.9 3.3 5.7 3.8 1.1 1.9 1.5 1.9 100.0 738 Education No education 74.4 4.6 5.8 1.6 1.0 3.8 1.8 7.0 100.0 798 Primary 82.5 2.0 3.8 2.4 2.3 2.8 1.8 2.3 100.0 2,170 Secondary 79.8 1.9 6.1 2.0 2.5 3.7 2.0 2.1 100.0 5,936 More than secondary 64.7 1.3 11.3 3.7 4.0 7.7 3.1 4.1 100.0 751 Missing 0.0 10.0 0.0 25.0 0.0 55.0 0.0 10.0 100.0 20 Wealth quintile Lowest 85.0 2.2 3.6 1.1 2.0 2.7 1.7 1.7 100.0 1,451 Second 83.7 1.7 4.7 1.8 1.8 3.0 1.4 1.9 100.0 1,749 Middle 82.4 1.8 4.1 1.7 2.4 4.1 1.6 1.9 100.0 2,042 Fourth 77.2 2.6 6.6 2.7 2.5 3.8 1.7 2.9 100.0 2,342 Highest 67.7 2.1 9.9 3.6 3.4 5.5 3.4 4.5 100.0 2,091 Total 15-49 78.6 2.1 6.0 2.3 2.4 3.9 2.0 2.7 100.0 9,675 1 Includes all dried blood samples (DBS) tested at the lab and for which there is a result (i.e., positive, negative, or indeterminate). Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes (1) other results of blood collection (e.g., technical problem in the field), (2) lost specimens, (3) non-corresponding bar codes, and (4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. HIV Prevalence • 207 Table 15.1.2 Coverage of HIV testing by background characteristics: Respondents age 50-64 Percent distribution of women and men age 50-64 eligible for HIV testing by testing status, according to background characteristics (unweighted), Namibia 2013 Testing status Total Number DBS tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Background characteristic Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed WOMEN 50-64 Age 50-54 86.2 2.5 3.4 2.0 1.2 1.5 0.7 2.5 100.0 407 55-59 82.0 3.3 7.4 2.2 1.1 0.7 1.1 2.2 100.0 272 60-64 85.0 2.5 4.2 0.4 1.3 0.8 0.4 5.4 100.0 240 Residence Urban 77.7 3.6 8.4 2.5 1.7 1.4 1.4 3.3 100.0 359 Rural 89.1 2.1 2.5 1.1 0.9 0.9 0.4 3.0 100.0 560 Region Zambezi 79.2 0.0 11.3 1.9 1.9 1.9 0.0 3.8 100.0 53 Erongo 86.7 0.0 5.0 0.0 0.0 3.3 1.7 3.3 100.0 60 Hardap 73.3 0.0 13.3 5.3 1.3 0.0 1.3 5.3 100.0 75 //Karas 91.3 1.4 1.4 1.4 2.9 0.0 1.4 0.0 100.0 69 Kavango 78.8 10.0 3.8 1.3 0.0 2.5 0.0 3.8 100.0 80 Khomas 64.6 4.6 13.8 6.2 3.1 1.5 1.5 4.6 100.0 65 Kunene 84.3 4.3 5.7 1.4 1.4 0.0 1.4 1.4 100.0 70 Ohangwena 91.0 4.5 1.5 0.0 0.0 0.0 0.0 3.0 100.0 67 Omaheke 91.9 1.6 1.6 0.0 1.6 0.0 0.0 3.2 100.0 62 Omusati 90.6 0.0 1.9 0.0 0.0 0.9 1.9 4.7 100.0 106 Oshana 90.5 0.0 1.6 0.0 3.2 3.2 0.0 1.6 100.0 63 Oshikoto 92.5 1.5 1.5 0.0 0.0 1.5 0.0 3.0 100.0 67 Otjozondjupa 84.1 6.1 2.4 3.7 1.2 0.0 0.0 2.4 100.0 82 Education No education 81.1 7.0 4.5 1.0 0.0 1.0 1.0 4.5 100.0 201 Primary 90.5 1.5 3.5 0.7 1.2 0.0 0.5 2.0 100.0 401 Secondary 84.2 0.8 4.6 2.5 2.5 2.1 0.8 2.5 100.0 241 More than secondary 67.1 4.1 13.7 4.1 0.0 2.7 1.4 6.8 100.0 73 Missing 0.0 0.0 0.0 33.3 0.0 33.3 0.0 33.3 100.0 3 Wealth quintile Lowest 87.0 3.6 4.2 0.5 0.5 1.0 0.5 2.6 100.0 192 Second 88.9 2.9 2.3 0.6 1.8 0.6 1.2 1.8 100.0 171 Middle 86.7 3.8 3.8 0.6 0.0 1.9 0.6 2.5 100.0 158 Fourth 89.2 2.0 2.9 1.5 1.0 0.0 0.5 2.9 100.0 204 Highest 72.2 1.5 10.3 4.6 2.6 2.1 1.0 5.7 100.0 194 Total 50-64 84.7 2.7 4.8 1.6 1.2 1.1 0.8 3.2 100.0 919 MEN 50-64 Age 50-54 70.3 2.2 6.6 4.8 1.5 7.7 1.1 5.9 100.0 273 55-59 76.1 5.1 5.6 2.0 1.5 4.1 1.5 4.1 100.0 197 60-64 73.5 3.9 6.1 3.9 0.6 5.5 1.1 5.5 100.0 181 Residence Urban 65.3 4.0 7.4 6.4 2.0 7.4 1.3 6.1 100.0 297 Rural 79.4 3.1 5.1 1.4 0.6 4.8 1.1 4.5 100.0 354 Region Zambezi 58.6 6.9 13.8 3.4 0.0 3.4 3.4 10.3 100.0 29 Erongo 74.6 0.0 7.5 3.0 1.5 7.5 1.5 4.5 100.0 67 Hardap 82.0 0.0 3.3 3.3 0.0 4.9 1.6 4.9 100.0 61 //Karas 81.0 3.2 7.9 0.0 0.0 3.2 1.6 3.2 100.0 63 Kavango 64.3 14.3 2.4 7.1 2.4 4.8 0.0 4.8 100.0 42 Khomas 44.4 11.1 0.0 5.6 3.7 24.1 1.9 9.3 100.0 54 Kunene 81.8 6.8 4.5 4.5 2.3 0.0 0.0 0.0 100.0 44 Ohangwena 79.3 0.0 3.4 0.0 3.4 0.0 3.4 10.3 100.0 29 Omaheke 77.1 1.4 8.6 1.4 1.4 5.7 0.0 4.3 100.0 70 Omusati 76.1 2.2 4.3 2.2 2.2 4.3 2.2 6.5 100.0 46 Oshana 74.1 3.7 11.1 0.0 0.0 7.4 0.0 3.7 100.0 27 Oshikoto 75.6 0.0 4.4 2.2 0.0 6.7 0.0 11.1 100.0 45 Otjozondjupa 73.0 1.4 9.5 10.8 0.0 2.7 1.4 1.4 100.0 74 Education No education 78.0 6.4 2.8 2.1 0.7 4.3 0.7 5.0 100.0 141 Primary 80.7 2.7 5.4 2.2 1.3 3.6 1.3 2.7 100.0 223 Secondary 69.0 2.4 10.0 4.3 1.9 6.2 0.5 5.7 100.0 210 More than secondary 58.0 4.3 4.3 7.2 0.0 15.9 4.3 5.8 100.0 69 Missing 0.0 0.0 0.0 25.0 0.0 12.5 0.0 62.5 100.0 8 Continued… 208 • HIV Prevalence Table 15.1.2—Continued Testing status Total Number DBS tested1 Refused to provide blood Absent at the time of blood collection Other/missing2 Background characteristic Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Inter- viewed Not inter- viewed Wealth quintile Lowest 80.3 7.9 3.9 1.3 0.0 2.6 1.3 2.6 100.0 76 Second 78.6 2.7 6.3 0.0 1.8 2.7 0.9 7.1 100.0 112 Middle 83.9 3.2 3.2 3.2 1.6 3.2 1.6 0.0 100.0 124 Fourth 70.4 1.3 8.2 5.7 0.6 6.9 0.0 6.9 100.0 159 Highest 61.1 4.4 7.2 5.6 1.7 10.6 2.2 7.2 100.0 180 Total 50-64 73.0 3.5 6.1 3.7 1.2 6.0 1.2 5.2 100.0 651 TOTAL 50-64 Age 50-54 79.9 2.4 4.7 3.1 1.3 4.0 0.9 3.8 100.0 680 55-59 79.5 4.1 6.6 2.1 1.3 2.1 1.3 3.0 100.0 469 60-64 80.0 3.1 5.0 1.9 1.0 2.9 0.7 5.5 100.0 421 Residence Urban 72.1 3.8 7.9 4.3 1.8 4.1 1.4 4.6 100.0 656 Rural 85.3 2.5 3.5 1.2 0.8 2.4 0.7 3.6 100.0 914 Region Zambezi 72.0 2.4 12.2 2.4 1.2 2.4 1.2 6.1 100.0 82 Erongo 80.3 0.0 6.3 1.6 0.8 5.5 1.6 3.9 100.0 127 Hardap 77.2 0.0 8.8 4.4 0.7 2.2 1.5 5.1 100.0 136 //Karas 86.4 2.3 4.5 0.8 1.5 1.5 1.5 1.5 100.0 132 Kavango 73.8 11.5 3.3 3.3 0.8 3.3 0.0 4.1 100.0 122 Khomas 55.5 7.6 7.6 5.9 3.4 11.8 1.7 6.7 100.0 119 Kunene 83.3 5.3 5.3 2.6 1.8 0.0 0.9 0.9 100.0 114 Ohangwena 87.5 3.1 2.1 0.0 1.0 0.0 1.0 5.2 100.0 96 Omaheke 84.1 1.5 5.3 0.8 1.5 3.0 0.0 3.8 100.0 132 Omusati 86.2 0.7 2.6 0.7 0.7 2.0 2.0 5.3 100.0 152 Oshana 85.6 1.1 4.4 0.0 2.2 4.4 0.0 2.2 100.0 90 Oshikoto 85.7 0.9 2.7 0.9 0.0 3.6 0.0 6.3 100.0 112 Otjozondjupa 78.8 3.8 5.8 7.1 0.6 1.3 0.6 1.9 100.0 156 Education No education 79.8 6.7 3.8 1.5 0.3 2.3 0.9 4.7 100.0 342 Primary 87.0 1.9 4.2 1.3 1.3 1.3 0.8 2.2 100.0 624 Secondary 77.2 1.6 7.1 3.3 2.2 4.0 0.7 4.0 100.0 451 More than secondary 62.7 4.2 9.2 5.6 0.0 9.2 2.8 6.3 100.0 142 Missing 0.0 0.0 0.0 27.3 0.0 18.2 0.0 54.5 100.0 11 Wealth quintile Lowest 85.1 4.9 4.1 0.7 0.4 1.5 0.7 2.6 100.0 268 Second 84.8 2.8 3.9 0.4 1.8 1.4 1.1 3.9 100.0 283 Middle 85.5 3.5 3.5 1.8 0.7 2.5 1.1 1.4 100.0 282 Fourth 81.0 1.7 5.2 3.3 0.8 3.0 0.3 4.7 100.0 363 Highest 66.8 2.9 8.8 5.1 2.1 6.1 1.6 6.4 100.0 374 Total 50-64 79.8 3.1 5.4 2.5 1.2 3.1 1.0 4.0 100.0 1,570 1 Includes all dried blood samples (DBS) tested at the lab and for which there is a result (i.e., positive, negative, or indeterminate). Indeterminate means that the sample went through the entire algorithm, but the final result was inconclusive. 2 Includes (1) other results of blood collection (e.g., technical problem in the field), (2) lost specimens, (3) non-corresponding bar codes, and (4) other lab results such as blood not tested for technical reason, not enough blood to complete the algorithm, etc. 15.2 HIV PREVALENCE 15.2.1 HIV Prevalence by Age Table 15.2 shows that the overall HIV prevalence among eligible respondents age 15-49 is 14.0 percent and among those age 50-64 it is 16.4 percent. Among respondents age 15-49, the prevalence rate is 16.9 percent for women and 10.9 percent for men. HIV prevalence rates for women and men age 50-64 are similar (16.7 percent and 16.0 percent, respectively). HIV prevalence peaks in the 35-39 age group for both women and men (30.9 percent and 22.6 percent, respectively), while the lowest rates are among respondents age 15-24 (2.5-6.4 percent for women and 2.0-3.4 percent for men). HIV prevalence for the 15-24 age group is assumed to represent newer infections and therefore serves as a proxy for HIV incidence. The low HIV prevalence in this age group according to the 2013 NDHS HIV testing indicates a low recent infection rate among youth. HIV Prevalence • 209 Table 15.2 HIV prevalence by age Among de facto women and men age 15-64 who were interviewed and tested, the percentage HIV positive, by age, Namibia 2013 Women Men Total Age Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number 15-19 2.5 835 2.0 860 2.3 1,695 20-24 6.4 815 3.4 734 5.0 1,548 25-29 16.3 647 9.4 614 13.0 1,261 30-34 28.0 566 16.6 465 22.8 1,031 35-39 30.9 513 22.6 429 27.1 942 40-44 27.1 376 21.9 313 24.8 689 45-49 28.6 300 21.8 265 25.4 565 50-54 22.0 320 16.7 177 20.1 497 55-59 15.5 187 19.4 141 17.2 327 60-64 8.7 183 11.0 121 9.6 303 Total 15-49 16.9 4,051 10.9 3,680 14.0 7,731 50-64 16.7 689 16.0 438 16.4 1,127 15.2.2 HIV Prevalence by Socioeconomic Characteristics Table 15.3.1 shows the variation in HIV prevalence among respondents age 15-49 by various socioeconomic characteristics (religion, employment, residence, region, educational level, and wealth quintile). Respondents who were employed in the last 12 months (16.5 percent) are more likely than those who were not employed (11.2 percent) to be HIV positive (in this chapter, HIV positive refers to positive for HIV-1). This pattern is more pronounced among women, where 20.8 percent of employed women are HIV positive compared with 13.8 percent of unemployed women. Women in rural areas (19.3 percent) are more likely than those in urban areas (15.0 percent) to be HIV positive. However, the opposite is true for men; rural residents have a slightly lower HIV prevalence than their urban counterparts (10.1 percent versus 11.5 percent). There are substantial variations in HIV prevalence by region. Only 6.9 percent of women age 15-49 in Omaheke are HIV positive compared with 30.9 of those in Zambezi. Among men, HIV prevalence is lowest in Ohangwena (6.6 percent) and highest in Zambezi (15.9 percent). HIV prevalence among women and men decreases with education and it generally decreases with wealth. Women and men with no education have the highest HIV prevalence (26.6 percent and 15.8 percent, respectively) and those with more than a secondary education have the lowest prevalence rates (5.6 percent and 6.0 percent, respectively). Men and women in the highest wealth quintile are the least likely to be HIV positive (5.5 percent and 3.0 percent, respectively). 210 • HIV Prevalence Table 15.3.1 HIV prevalence by socioeconomic characteristics: Respondents age 15-49 Percentage HIV positive among women and men age 15-49 who were tested, by socioeconomic characteristics, Namibia 2013 Women Men Total Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Religion Roman Catholic 19.2 790 12.1 969 15.3 1,759 Protestant/Anglican 17.2 861 8.0 463 14.0 1,324 ELCIN 16.8 1,782 12.2 1,620 14.6 3,402 Seventh-Day Adventist 23.1 207 15.4 139 20.0 346 No religion (4.8) 50 3.0 53 3.9 103 Other 9.5 351 5.9 430 7.6 780 Employment (last 12 months) Not employed 13.8 2,255 7.2 1,398 11.2 3,653 Employed 20.8 1,794 13.2 2,281 16.5 4,075 Residence Urban 15.0 2,280 11.5 2,088 13.3 4,367 Rural 19.3 1,771 10.1 1,592 15.0 3,364 Region Zambezi 30.9 212 15.9 197 23.7 409 Erongo 14.6 332 10.4 342 12.5 674 Hardap 8.8 151 7.5 138 8.2 289 //Karas 15.0 155 9.5 139 12.4 294 Kavango 19.8 364 13.5 290 17.0 654 Khomas 12.2 940 11.6 927 11.9 1,868 Kunene 8.9 112 10.6 95 9.7 206 Ohangwena 22.1 420 6.6 304 15.6 724 Omaheke 6.9 104 7.7 96 7.3 199 Omusati 21.9 380 12.1 316 17.4 695 Oshana 20.3 352 11.3 308 16.1 660 Oshikoto 16.4 299 10.5 306 13.4 605 Otjozondjupa 14.2 231 9.7 223 12.0 454 Education No education 26.6 193 15.8 295 20.0 488 Primary 25.8 807 14.0 897 19.6 1,704 Secondary 15.0 2,698 9.6 2,191 12.6 4,889 More than secondary 5.6 353 6.0 297 5.8 650 Wealth quintile Lowest 23.8 631 11.8 552 18.2 1,182 Second 24.4 739 15.7 743 20.0 1,481 Middle 20.4 791 14.1 839 17.2 1,630 Fourth 14.4 989 9.5 839 12.1 1,828 Highest 5.5 901 3.0 708 4.4 1,609 Total 15-49 16.9 4,051 10.9 3,680 14.0 7,731 Note: Figures in parentheses are based on 25-49 unweighted cases. Total includes 2 women with missing information on employment in the last 12 months. ELCIN = Evangelical Lutheran Church in Namibia Table 15.3.2 shows the variation in HIV prevalence among women and men age 50-64 by socioeconomic characteristics. Women in rural areas (15.7 percent) are less likely to be HIV positive than those in urban areas (18.2 percent), while rural men are more likely than urban men to be HIV positive (18.3 percent versus 13.5 percent). The regional differentials are notable, with HIV prevalence being highest in Zambezi (29.4 percent) and Oshana (27.3 percent), and lowest in Hardap (4.9 percent). Similar to respondents age 15-49, HIV prevalence for those age 50-64 generally decreases with education and wealth, although the patterns are not linear. HIV Prevalence • 211 Table 15.3.2 HIV prevalence by socioeconomic characteristics: Respondents age 50-64 Percentage HIV positive among women and men age 50-64 who were tested, by socioeconomic characteristics, Namibia 2013 Women Men Total Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Religion Roman Catholic 21.2 157 20.1 86 20.8 244 Protestant/Anglican 11.2 139 10.4 64 10.9 203 ELCIN 18.1 309 20.0 191 18.8 500 Seventh-Day Adventist (23.8) 25 * 14 16.7 40 No religion * 10 * 13 (1.6) 23 Other 8.2 48 9.0 67 8.7 115 Employment (last 12 months) Not employed 15.8 399 14.9 159 15.5 559 Employed 18.0 290 16.7 279 17.3 568 Residence Urban 18.2 265 13.5 206 16.1 471 Rural 15.7 424 18.3 232 16.6 656 Region Zambezi (37.6) 31 * 14 29.4 45 Erongo 11.4 41 21.8 45 16.8 86 Hardap 6.0 29 3.7 26 4.9 56 //Karas 9.4 27 10.1 24 9.7 51 Kavango 10.2 69 (20.8) 29 13.3 98 Khomas (13.9) 93 * 80 11.5 172 Kunene 8.9 25 (5.6) 16 7.6 41 Ohangwena 13.9 68 * 27 18.6 95 Omaheke 7.3 22 9.0 25 8.2 48 Omusati 20.7 113 (23.6) 45 21.5 158 Oshana 32.8 57 * 25 27.3 82 Oshikoto 20.2 62 (29.0) 38 23.5 99 Otjozondjupa 12.5 51 13.3 45 12.9 96 Education No education 14.3 133 20.1 87 16.6 220 Primary 17.7 325 21.2 166 18.9 491 Secondary 18.2 182 10.8 143 15.0 325 More than secondary (10.7) 49 (5.1) 42 8.2 91 Wealth quintile Lowest 17.9 159 15.4 59 17.2 219 Second 18.9 134 22.3 72 20.1 206 Middle 17.0 120 24.4 93 20.2 213 Fourth 18.4 149 19.7 96 18.9 245 Highest 10.5 127 2.9 117 6.8 244 Total 50-64 16.7 689 16.0 438 16.4 1,127 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. Total includes 2 women with missing information on employment in the last 12 months. ELCIN = Evangelical Lutheran Church in Namibia 15.2.3 HIV Prevalence by Demographic and Health Characteristics Tables 15.4.1 and 15.4.2 show HIV prevalence among respondents age 15-49 and 50-64, respectively, by demographic characteristics. Widowed women age 15-49 are notably more likely to be HIV positive (51.7 percent) than women with different marital status (13.1-37.1 percent). HIV prevalence is higher among women in polygynous unions (22.6 percent) than those in non-polygynous unions (17.8 percent) and women not in union (16.1 percent). Number of times away from home has an inverse relationship with HIV prevalence among women; 18.3 percent of women who have not slept away from home in the past 12 months are HIV positive compared with 7.1 percent of those who have slept away five or more times. The amount of time spent away from home does not appear to be associated with HIV prevalence among women. Women who were not pregnant or unsure of their pregnancy status at the time of the survey have a higher HIV prevalence than those who were pregnant (17.2 percent compared with 12.8 percent). Women who received antenatal care (ANC) from a public sector provider in the three years preceding the survey are more likely to be infected with HIV (18.3 percent) than those who did not receive ANC or did not have 212 • HIV Prevalence a birth in the last three years (16.7 percent) and those who received ANC from a source other than the public sector (5.4 percent). Among men, HIV prevalence is highest for divorced or separated men (19.8 percent) and those currently married or cohabiting at the time of the survey (19.1 percent) compared with men who never married (7.2 percent). Men who spent more than one month away from home have lower HIV prevalence (8.8 percent) when compared with those who spent less than one month away (12.1 percent) and those who did not spend any time away from home (11.0 percent). Male circumcision reduces the risk of HIV infection, in part because of physiological differences that decrease the susceptibility to HIV infection among circumcised men. Three randomised controlled clinical trials conducted in Uganda, South Africa, and Kenya demonstrated that medical circumcision reduces the risk of HIV transmission among heterosexual men by 60-70 percent (Auvert et al., 2005). Table 15.4.1 shows that uncircumcised men are more likely to be HIV positive (11.9 percent) than men who have been circumcised (8.0 percent). Table 15.4.1 HIV prevalence by demographic characteristics: Respondents age 15-49 Percentage HIV positive among women and men age 15-49 who were tested, by demographic characteristics, Namibia 2013 Women Men Total Demographic characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Marital status Never married 13.1 2,403 7.2 2,526 10.1 4,929 Ever had sexual intercourse 16.2 1,870 8.9 1,951 12.5 3,820 Never had sexual intercourse 2.2 534 1.4 576 1.8 1,109 Married/living together 18.4 1,366 19.1 1,057 18.7 2,423 Divorced or separated 37.1 193 19.8 92 31.5 285 Widowed 51.7 88 * 5 48.7 94 Type of union In polygynous union 22.6 87 * 23 18.7 110 In non-polygynous union 17.8 1,045 19.5 1,033 18.6 2,079 Not currently in union 16.1 2,685 7.6 2,623 11.9 5,308 Times slept away from home in past 12 months None 18.3 2,579 11.0 2,106 15.1 4,685 1-2 16.4 959 10.3 598 14.1 1,557 3-4 14.1 232 11.4 310 12.6 542 5+ 7.1 278 10.8 644 9.6 922 Time away in past 12 months Away for more than 1 month 16.0 746 8.8 637 12.7 1,383 Away for less than 1 month 12.7 719 12.1 913 12.4 1,631 Not away 18.3 2,581 11.0 2,106 15.0 4,687 Currently pregnant Pregnant 12.8 279 na na na na Not pregnant or not sure 17.2 3,772 na na na na ANC for last birth in past 3 years ANC provided by the public sector 18.3 1,104 na na na na ANC provided by other than the public sector 5.4 91 na na na na No ANC/no birth in last 3 years 16.7 2,853 na na na na Male circumcision Circumcised na na 8.0 919 na na Not circumcised na na 11.9 2,745 na na Total 15-49 16.9 4,051 10.9 3,680 14.0 7,731 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Total includes 234 women with missing information on type of union, 2 women and 22 men with missing information on times slept away from home in the past 12 months, 6 women and 24 men with missing information on time away in the past 12 months, 3 women with missing information on ANC for last birth in the past 3 years, and 17 men with missing information on circumcision. na = Not applicable HIV Prevalence • 213 Table 15.4.2 shows that HIV prevalence among respondents age 50-64 is highest for those who are widowed (25.2 percent) and divorced or separated (23.9 percent) and lowest among those who are married/living together (12.0 percent). Respondents who are not currently in union (23.4 percent) are more likely than other men to be HIV positive. There is no clear pattern in the relationship of HIV prevalence among respondents age 50-64 and the number of times or the amount of time spent away from home. Table 15.4.2 HIV prevalence by demographic characteristics: Respondents age 50-64 Percentage HIV positive among women and men age 50-64 who were tested, by demographic characteristics, Namibia 2013 Women Men Total Demographic characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Marital status Never married 21.4 121 20.6 49 21.2 170 Ever had sexual intercourse 21.4 121 21.1 48 21.3 169 Never had sexual intercourse * 0 * 1 * 1 Married/living together 9.4 338 14.5 349 12.0 687 Divorced or separated 27.3 64 (16.6) 30 23.9 94 Widowed 24.1 166 * 11 25.2 176 Type of union In polygynous union (15.0) 30 * 15 (17.0) 45 In non-polygynous union 7.8 273 14.2 334 11.3 607 Not currently in union 23.7 351 21.9 89 23.4 440 Times slept away from home in past 12 months None 20.1 447 14.2 194 18.3 641 1-2 9.0 132 18.2 79 12.5 211 3-4 12.2 50 (35.0) 42 22.6 91 5+ 12.0 59 11.1 123 11.4 182 Time away in past 12 months Away for more than 1 month 11.7 99 19.0 103 15.5 202 Away for less than 1 month 9.5 142 16.5 140 13.0 282 Not away 20.1 448 14.2 194 18.3 642 Male circumcision Circumcised na na 16.1 136 na na Not circumcised na na 16.0 301 na na Total 50-64 16.7 689 16.0 438 16.4 1,127 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. Total includes 35 women with missing information on type of union, 1 man with missing information on times slept away from home in the past 12 months, 2 men with missing information on time away in the past 12 months, and 1 man with missing information on circumcision. na = Not applicable 15.2.4 HIV Prevalence by Sexual Risk Behaviour Although HIV knowledge in the general population is relatively high, risky behaviours, including lack of condom use, are common and therefore remain a significant public health concern, as shown in Chapter 14. Tables 15.5.1 and 15.5.2 present HIV prevalence by sexual behaviour characteristics among respondents age 15-49 and 50-64, respectively, who have ever had sexual intercourse. In reviewing these results, it is important to remember that responses about sexual risk behaviours may be subject to reporting bias. Also, sexual behaviour in the 12 months preceding the survey may not adequately reflect lifetime sexual risk. Nor is it possible to know the sequence of events (e.g., whether any reported condom use occurred before or after HIV transmission). Table 15.5.1 shows that among all respondents age 15-49 who had ever had sex and were tested for HIV, 16.1 percent are HIV positive (19.1 percent of women and 12.6 percent of men). Among women, HIV prevalence is higher among those who had their first sexual intercourse before the age of 20 (18.9- 19.9 percent) when compared with women whose age at first sex was age 20 or older (16.5 percent). By contrast, HIV prevalence among men increases with increasing age at sexual debut, from 8.4 percent of men who had sexual intercourse before age 16 to 18.0 percent among those whose first sexual encounter was at age 20 or older. Caution should be used when interpreting HIV prevalence levels by number of sexual partners and partner concurrency in the past 12 months among women, because very few women report more than one 214 • HIV Prevalence partner. HIV prevalence is higher among women who had no sexual partners (26.3 percent) in the past 12 months than among those who had one or more partners (17.9 percent and 17.6 percent, respectively). Among men, those with one sexual partner in the past 12 months (13.3 percent) are more likely to be infected with HIV than those with no partners or more than one partner (9.1 percent and 9.9 percent, respectively) in the past 12 months. Among men with multiple partners, those who had concurrent partners were more likely to be HIV positive (10.6 percent) than those who did not (8.7 percent). Table 15.5.1 shows no clear correlation between condom use at last sexual intercourse and HIV status among women or men. HIV prevalence is higher among women who did not have sexual intercourse in the past 12 months (25.9 percent) and those who used a condom during their most recent sexual encounter (20.6 percent) than among women who did not use a condom during their last sexual intercourse (15.3 percent). In contrast, men who did not use a condom during their most recent sexual intercourse (13.7 percent) are more likely to be HIV positive than men who used a condom (12.1 percent) or those who did not have sexual intercourse in the past 12 months (11.6 percent). HIV prevalence generally increases with increasing number of lifetime partners for both women and men. The number of men who paid for sexual intercourse is too small for meaningful data interpretation and conclusions and is not shown separately in Tables 15.5.1 and 15.5.2. Table 15.5.1 HIV prevalence by sexual behaviour: Respondents age 15-49 Percentage HIV positive among women and men age 15-49 who ever had sex and were tested for HIV, by sexual behaviour characteristics, Namibia 2013 Women Men Total Sexual behaviour characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Age at first sexual intercourse <16 19.9 572 8.4 844 13.1 1,416 16-17 19.7 958 11.9 855 16.0 1,812 18-19 18.9 906 13.2 761 16.3 1,667 20+ 16.5 854 18.0 613 17.2 1,467 Multiple sexual partners and partner concurrency in past 12 months 0 26.3 533 9.9 381 19.5 915 1 17.9 2,863 13.3 2,314 15.8 5,177 2+ 17.6 104 9.1 379 11.0 483 Had concurrent partners1 * 14 10.6 87 12.4 102 None of the partners were concurrent 16.8 90 8.7 291 10.6 381 Condom use at last sexual intercourse in past 12 months Used condom 20.6 1,441 12.1 1,655 16.1 3,096 Did not use condom 15.3 1,523 13.7 1,035 14.7 2,558 No sexual intercourse in past 12 months 25.9 546 11.6 401 19.8 947 Number of lifetime partners 1 8.6 1,075 7.5 448 8.3 1,523 2 18.6 1,033 10.6 472 16.1 1,505 3-4 27.9 1,057 10.3 704 20.9 1,762 5-9 24.5 252 12.3 690 15.6 942 10+ 25.5 38 18.4 598 18.8 636 Paid for sexual intercourse in past 12 months Yes na na (16.8) 35 na na Used condom na na * 26 na na Did not use condom na na * 9 na na Total 15-49 19.1 3,513 12.6 3,094 16.1 6,607 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. Total includes 223 women and 21 men with missing information on age at first sexual intercourse, 12 women and 20 men with missing information on multiple sexual partners and partner concurrency in the past 12 months, 3 women and 3 men with missing information on condom use at last sexual intercourse in the past 12 months, and 56 women and 182 men with missing information on number of lifetime partners. na = Not applicable 1 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with 2 or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with 2 or more wives.) HIV Prevalence • 215 Table 15.5.2 shows that HIV prevalence among respondents age 50-64 who have ever had sex is 16.3 percent among women and 15.7 percent among men. The overall HIV prevalence among women and men in this age group is higher among individuals who used a condom at their last sexual encounter (35.0 percent) than among those who did not have sexual intercourse in the past 12 months (18.1 percent) or who did not use a condom during their last sexual intercourse (9.7 percent). HIV prevalence is lowest among respondents who have only one lifetime partner (9.8 percent) when compared with those with two or more partners (16.2-20.5 percent). Table 15.5.2 HIV prevalence by sexual behaviour: Respondents age 50-64 Percentage HIV positive among women and men age 50-64 who ever had sex and were tested for HIV, by sexual behaviour characteristics, Namibia 2013 Women Men Total Sexual behaviour characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Age at first sexual intercourse <16 14.4 78 (13.7) 35 14.2 114 16-17 13.3 97 14.1 86 13.7 183 18-19 18.5 153 14.8 116 16.9 269 20+ 17.1 343 17.4 193 17.2 536 Multiple sexual partners and partner concurrency in past 12 months 0 18.8 382 14.2 88 17.9 470 1 13.5 294 13.8 308 13.6 602 2+ * 1 (34.8) 29 (33.4) 30 Had concurrent partners1 * 1 * 15 * 15 None of the partners were concurrent * 0 * 14 * 14 Condom use at last sexual intercourse in past 12 months Used condom 27.1 56 41.6 67 35.0 123 Did not use condom 10.2 239 9.2 270 9.7 509 No sexual intercourse in past 12 months 18.6 386 15.9 94 18.1 480 Number of lifetime partners 1 11.5 247 2.1 54 9.8 301 2 20.0 193 (8.6) 41 18.0 233 3-4 19.7 162 7.7 68 16.2 230 5-9 12.9 52 25.7 76 20.5 128 10+ * 14 20.9 118 19.7 132 Paid for sexual intercourse in past 12 months Yes na na * 5 na na Used condom na na * 2 na na Did not use condom na na * 3 na na Total 50-64 16.3 681 15.7 431 16.1 1,112 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. Total includes 9 women and 1 man with missing information on age at first sexual intercourse, 4 women and 6 men with missing information on multiple sexual partners and partner concurrency in the past 12 months, and 15 women and 73 men with missing information on number of lifetime partners. na = Not applicable 1 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with 2 or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with 2 or more wives.) In summary, the results presented in Tables 15.5.1 and 15.5.2 do not demonstrate a consistent relationship between sexual risk behaviours and HIV prevalence. Additional analysis may be necessary to understand such relationships because they are often confounded by other factors associated with both sexual behaviours and HIV prevalence. 216 • HIV Prevalence 15.3 HIV PREVALENCE AMONG YOUNG PEOPLE As specified in the United Nations General Assembly Special Session (UNGASS) on HIV and AIDS, young people in the 15-24 age range are an important group to monitor with regard to reductions in HIV incidence at the population level (UN General Assembly, 2001). Table 15.6 shows that HIV prevalence among youth age 15-24 is 3.6 percent (4.4 percent among young women and 2.7 percent among young men). Given the low overall HIV prevalence among youth, there are no major variations in HIV prevalence levels by most background characteristics. Table 15.6 HIV prevalence among young people by background characteristics Percentage HIV positive among women and men age 15-24 who were tested for HIV, by background characteristics, Namibia 2013 Women Men Total Background characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Age 15-19 2.5 835 2.0 860 2.3 1,695 15-17 2.4 465 1.9 535 2.1 1,000 18-19 2.8 370 2.2 325 2.5 695 20-24 6.4 815 3.4 734 5.0 1,548 20-22 4.5 494 2.4 442 3.5 937 23-24 9.3 320 5.0 292 7.2 612 Marital status Never married 4.0 1,401 2.5 1,517 3.3 2,918 Ever had sex 5.1 900 3.3 968 4.1 1,868 Never had sex 2.2 501 1.2 549 1.7 1,051 Married/living together 6.6 225 5.9 74 6.4 298 Divorced/separated/widowed (6.3) 24 * 3 (5.6) 27 Currently pregnant Pregnant 3.5 128 na na na na Not pregnant or not sure 4.5 1,521 na na na na Residence Urban 4.5 903 2.9 804 3.8 1,707 Rural 4.4 746 2.4 790 3.3 1,536 Region Zambezi 19.2 87 12.8 74 16.3 161 Erongo 3.5 124 4.8 116 4.1 240 Hardap 3.8 55 2.4 44 3.2 98 //Karas 3.0 50 2.7 57 2.8 107 Kavango 4.6 166 1.9 132 3.4 298 Khomas 2.8 385 1.8 334 2.3 719 Kunene 2.2 40 1.8 32 2.0 73 Ohangwena 2.7 189 0.0 174 1.4 363 Omaheke 2.7 36 3.9 36 3.3 72 Omusati 3.8 158 3.6 209 3.7 367 Oshana 5.9 145 1.2 158 3.4 303 Oshikoto 3.5 128 1.8 142 2.6 270 Otjozondjupa 4.6 86 3.0 86 3.8 172 Education No education (8.5) 28 2.1 59 4.1 87 Primary 7.6 282 2.3 385 4.5 666 Secondary 3.6 1,174 2.7 1,062 3.2 2,236 More than secondary 4.0 166 4.8 88 4.3 254 Wealth quintile Lowest 3.6 251 2.6 241 3.1 492 Second 6.5 293 3.2 317 4.8 610 Middle 5.1 300 4.4 378 4.7 678 Fourth 3.8 411 2.1 346 3.0 757 Highest 3.5 395 0.7 312 2.3 706 Total 15-24 4.4 1,649 2.7 1,594 3.6 3,243 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable In general, HIV prevalence among young women and men increases with age. Young people who are married or living together with a partner are more likely to be infected with HIV than those who have never been married. By region, Zambezi has the highest HIV prevalence among young people (16.3 percent), while Ohangwena has the lowest prevalence (1.4 percent). There is no clear pattern in the HIV Prevalence • 217 relationship between HIV prevalence and education. Young respondents age 15-24 in the second and middle wealth quintiles (4.7-4.8 percent) are somewhat more likely to be infected with HIV than those in the other quintiles (2.3-3.1 percent). Table 15.7 shows HIV prevalence among young people by sexual behaviour. HIV prevalence among respondents age 15-24 who have ever had sex is 4.5 percent (5.4 percent for women and 3.4 percent for men). HIV prevalence is lowest among women and men with two or more sexual partners (4.1 percent and 1.5 percent, respectively). There are too few young people age 15-24 with concurrent partners in the past 12 months to allow for meaningful interpretations regarding the relationship between HIV prevalence and this indicator. Young women and men who did not use a condom during their most recent sexual intercourse are more likely to be HIV positive (6.2 percent and 6.0 percent, respectively) than those who reported using a condom during their last sexual intercourse (4.6 percent and 2.8 percent, respectively). Table 15.7 HIV prevalence among young people by sexual behaviour Percentage HIV positive among women and men age 15-24 who have ever had sex and were tested for HIV, by sexual behaviour, Namibia 2013 Women Men Total Sexual behaviour characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Multiple sexual partners and partner concurrency in past 12 months 0 6.7 156 3.4 184 4.9 340 1 5.3 933 3.9 716 4.7 1,649 2+ 4.1 55 1.5 141 2.2 196 Had concurrent partners1 * 6 * 26 (0.0) 32 None of the partners were concurrent (4.7) 49 1.8 115 2.6 163 Missing * 4 * 2 * 6 Condom use at last sexual intercourse in past 12 months Used condom 4.6 579 2.8 679 3.6 1,258 Did not use condom 6.2 406 6.0 177 6.1 584 No sexual intercourse in past 12 months 6.6 160 3.3 186 4.8 346 Total 15-24 5.4 1,148 3.4 1,043 4.5 2,191 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. Total includes 4 women and 2 men with missing information on multiple sexual partners and partner concurrency in the past 12 months and 3 women with missing information on condom use at last sexual intercourse in the past 12 months. 1 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with 2 or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with 2 or more wives.) 15.4 HIV PREVALENCE BY OTHER CHARACTERISTICS RELATED TO HIV RISK A strong link exists between sexually transmitted infections and sexual transmission of HIV. Many studies have demonstrated that STIs are a co-factor in HIV transmission. Management and treatment of STIs can play an important role in the reduction of HIV transmission. The 2013 NDHS asked respondents who had ever had sex if they had contracted a disease through sexual contact in the past 12 months or if they had any symptoms associated with STIs (an abnormal discharge from the vagina or penis or a genital sore or ulcer). Table 15.8 shows HIV prevalence among respondents age 15-64 who have ever had sex and were tested for HIV by whether they had an STI or symptoms in the past 12 months and by prior HIV testing. Data show that for women age 15-49, there is no notable difference in HIV prevalence by whether or not the woman had an STI or STI symptoms in the past 12 months. Among men age 15-49, however, the percentage HIV positive is notably higher among those who had an STI or STI symptoms in the past 12 months (24.8 percent) than those who did not have an STI or STI symptoms (11.7 percent). Respondents who had been tested for HIV previously are more likely to be HIV positive than those who had not been tested previously (18.3 percent and 6.6 percent, respectively). Among respondents who had been tested 218 • HIV Prevalence previously for HIV, the prevalence was somewhat higher for those who had not received the test results (20.1 percent) than among individuals who had received the results of their last test (18.2 percent). Similar patterns are observed for respondents age 50-64, as shown in the bottom panel of Table 15.8. Table 15.8 HIV prevalence by other characteristics: Respondents age 15-64 Percentage HIV positive among women and men age 15-64 who ever had sex and were tested for HIV, by whether they had an STI or STI symptoms in the past 12 months and by prior testing for HIV, Namibia 2013 Women Men Total Characteristic Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number 15-49 Sexually transmitted infection in past 12 months Had STI or STI symptoms 20.4 348 24.8 207 22.1 555 No STI, no symptoms 19.1 3,138 11.7 2,856 15.6 5,994 Prior HIV testing Ever tested 20.6 3,157 14.9 2,202 18.3 5,359 Received results 20.6 3,099 14.9 2,134 18.2 5,233 Did not receive results 24.3 58 16.5 68 20.1 126 Never tested 6.0 335 6.8 892 6.6 1,226 Total 15-49 19.1 3,513 12.6 3,094 16.1 6,607 50-64 Sexually transmitted infection in past 12 months Had STI or STI symptoms (33.7) 34 (31.1) 23 32.7 57 No STI, no symptoms 15.6 639 14.8 402 15.3 1,040 Prior HIV testing Ever tested 21.1 468 21.1 301 21.1 769 Received results 21.3 457 20.9 288 21.2 746 Did not receive results * 10 * 13 (18.5) 24 Never tested 6.0 213 2.8 129 4.8 342 Total 50-64 16.3 681 15.7 431 16.1 1,112 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. Total includes 35 women and 37 men with missing information on sexually transmitted infections in the past 12 months and 21 women with missing information on prior HIV testing. Table 15.9 shows HIV prevalence among men age 15-49 by circumcision status, according to background characteristics. As mentioned earlier, HIV prevalence for men age 15-49 is lower among circumcised (8.0 percent) than among uncircumcised men (11.9 percent). The pattern of lower HIV prevalence among circumcised than uncircumcised men is observed across most background characteristics. For each age group, circumcised men have lower HIV prevalence than those who are not circumcised; the difference is especially pronounced for men age 35-39 and 45-49 (11.7 percentage points each). The difference in HIV prevalence between uncircumcised and circumcised men is larger among urban than rural men (5.2 percentage points versus 2.1 percentage points). For all regions, with the exception of //Karas, Kavango, and Ohangwena, HIV prevalence is lower among circumcised men than uncircumcised men. Among uncircumcised men age 15-49, the highest HIV prevalence was recorded in Zambezi (17.6 percent) and the lowest in Ohangwena (5.2 percent). Among circumcised men, there are too few cases who are HIV-positive to allow for a robust analysis of HIV prevalence by region. By education and wealth, the largest gap in HIV prevalence between uncircumcised and circumcised men is observed among those with no education (11.2 percentage points higher) and men in the middle wealth quintile (9.5 percentage points higher). HIV Prevalence • 219 Table 15.9 HIV prevalence by male circumcision Among men age 15-49 who were tested for HIV, the percentage HIV positive by whether circumcised, according to background characteristics, Namibia 2013 Circumcised Not circumcised Background characteristic Percentage HIV positive Number Percentage HIV positive Number Age 15-19 0.0 171 2.5 682 20-24 1.8 167 3.9 566 25-29 8.4 170 9.9 443 30-34 10.9 125 18.7 340 35-39 14.1 114 25.8 313 40-44 17.5 88 23.7 226 45-49 13.7 84 25.4 176 Religion Roman Catholic 10.2 208 12.8 753 Protestant/Anglican 8.2 159 7.9 302 ELCIN 7.9 333 13.3 1,283 Seventh-Day Adventist * 28 18.2 110 No religion (0.0) 27 (6.2) 26 Other 7.4 162 5.1 267 Residence Urban 7.8 605 13.0 1,471 Rural 8.5 313 10.6 1,273 Region Zambezi (7.7) 31 17.6 165 Erongo 6.4 104 12.2 238 Hardap (3.4) 18 8.1 120 //Karas 10.9 30 9.1 107 Kavango 14.7 93 12.2 195 Khomas 6.8 268 13.7 652 Kunene 9.4 47 11.8 47 Ohangwena (16.2) 38 5.2 265 Omaheke 6.7 44 8.7 51 Omusati (11.2) 51 12.3 264 Oshana (6.6) 62 12.5 246 Oshikoto (2.1) 46 11.9 260 Otjozondjupa 5.6 89 12.5 135 Education No education 7.6 81 18.8 213 Primary 13.2 187 14.3 706 Secondary 7.7 551 10.3 1,630 More than secondary 0.7 100 8.0 195 Wealth quintile Lowest 13.1 86 11.6 464 Second 11.6 170 17.0 570 Middle 6.5 160 16.0 677 Fourth 11.7 245 8.7 587 Highest 1.4 257 3.6 448 Total 15-49 8.0 919 11.9 2,745 50-64 16.1 136 16.0 301 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. ELCIN = Evangelical Lutheran Church in Namibia 15.5 HIV PREVALENCE AMONG COUPLES A total of 1,007 cohabiting couples were tested for HIV in the 2013 NDHS. The results shown in Table 15.10 indicate that, among 76.4 percent of cohabiting couples, both partners tested negative for HIV. Both partners were HIV positive in 10.1 percent of cohabiting couples, while 13.5 percent of couples were discordant (i.e., one partner was infected and the other was not). In 8.1 percent of the couples, the male partner was infected and the woman was not, while in 5.4 percent of the couples, the woman was infected and the man was not. Differences by background characteristics exist. The percentage who are discordant is highest among couples where the female and the male partner are age 30-39 (17.0 percent and 18.4 percent, respectively), where the man is older than the woman by 15 years or more (20.8 percent), in couples where the woman or the man has no education (16.8 percent and 17.4 percent, respectively), and among couples in the second wealth quintile (21.5 percent). 220 • HIV Prevalence Table 15.10 HIV prevalence among couples Percent distribution of couples living in the same household, both of whom were tested for HIV, by HIV status, according to background characteristics, Namibia 2013 Background characteristic Both HIV positive Man HIV positive, woman HIV negative Woman HIV positive, man HIV negative Both HIV negative Total Number Woman’s age 15-19 (2.0) (0.0) (1.3) (96.7) 100.0 48 20-29 6.6 7.2 3.9 82.3 100.0 330 30-39 14.8 10.7 6.3 68.2 100.0 376 40-49 9.4 6.7 7.0 76.9 100.0 252 Man’s age 15-19 * * * * 100.0 5 20-29 6.9 3.6 4.4 85.2 100.0 166 30-39 10.0 10.1 8.3 71.7 100.0 318 40-49 14.8 8.2 4.4 72.7 100.0 288 50-64 7.1 8.6 3.7 80.6 100.0 229 Age difference between partners Woman older 8.2 7.4 9.2 75.2 100.0 153 Same age/man older by 0-4 years 8.5 7.2 5.8 78.6 100.0 377 Man older by 5-9 years 9.2 6.6 2.9 81.3 100.0 302 Man older by 10-14 years 15.0 12.0 5.3 67.7 100.0 105 Man older by 15+ years 20.3 14.7 6.1 59.0 100.0 69 Type of union Non-polygynous 10.1 8.4 5.1 76.3 100.0 819 Polygynous (12.2) (3.2) (4.0) (80.7) 100.0 53 Multiple partners in past 12 months1 Both no 9.3 8.1 5.2 77.4 100.0 910 Man yes, woman no 13.9 7.1 5.3 73.7 100.0 55 Woman yes, man no * * * * 100.0 7 Both yes * * * * 100.0 1 Either missing (28.8) (11.5) (2.4) (57.3) 100.0 34 Concurrent sexual partners in past 12 months2 Both no 10.2 7.9 5.5 76.4 100.0 981 Man yes, woman no (8.5) (16.0) (1.9) (73.7) 100.0 24 Woman yes, man no * * * * 100.0 2 Both yes * * * * 100.0 0 Residence Urban 9.4 7.4 5.5 77.7 100.0 610 Rural 11.2 9.1 5.4 74.3 100.0 397 Region Zambezi 9.6 10.0 11.1 69.3 100.0 63 Erongo 13.0 4.6 4.7 77.7 100.0 110 Hardap 5.3 3.6 7.3 83.8 100.0 60 //Karas 5.7 4.7 3.7 86.0 100.0 55 Kavango 14.7 9.0 5.0 71.4 100.0 108 Khomas 7.2 9.4 3.5 79.9 100.0 233 Kunene 2.5 10.2 6.3 81.1 100.0 36 Ohangwena (13.2) (19.6) (4.7) (62.5) 100.0 42 Omaheke 3.8 5.1 1.5 89.6 100.0 39 Omusati (24.9) (5.0) (12.1) (57.9) 100.0 55 Oshana (11.7) (14.5) (5.8) (68.0) 100.0 46 Oshikoto 15.1 7.1 4.2 73.7 100.0 61 Otjozondjupa 6.6 5.9 6.0 81.5 100.0 97 Woman’s education No education 8.7 8.0 8.8 74.5 100.0 100 Primary 11.8 8.6 5.9 73.6 100.0 260 Secondary 11.4 7.9 5.0 75.7 100.0 550 More than secondary 0.0 7.5 2.8 89.7 100.0 97 Man’s education No education 12.7 9.0 8.4 69.9 100.0 128 Primary 15.2 7.9 5.9 71.1 100.0 258 Secondary 8.8 8.6 4.5 78.0 100.0 506 More than secondary 1.8 4.8 5.1 88.2 100.0 115 Wealth quintile Lowest 16.2 8.4 9.6 65.7 100.0 162 Second 13.3 14.2 7.3 65.2 100.0 179 Middle 17.0 9.7 7.3 66.1 100.0 208 Fourth 4.0 6.1 3.4 86.4 100.0 225 Highest 3.3 3.5 1.3 91.9 100.0 232 Total couples 10.1 8.1 5.4 76.4 100.0 1,007 Note: The table is based on couples for whom a valid test result (positive or negative) is available for both partners. 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. Total includes 135 couples with missing information on type of union. 1 A respondent is considered to have had multiple sexual partners in the past 12 months if he or she had sexual intercourse with 2 or more people during this time period. (Respondents with multiple partners include polygynous men who had sexual intercourse with 2 or more wives.) 2 A respondent is considered to have had concurrent partners if he or she had overlapping sexual partnerships with 2 or more people during the 12 months before the survey. (Respondents with concurrent partners include polygynous men who had overlapping sexual partnerships with 2 or more wives.) Self-reported Prior HIV Testing and Treatment • 221 SELF-REPORTED PRIOR HIV TESTING AND TREATMENT 16 his chapter presents information related to prior HIV testing and treatment among 2013 NDHS respondents and provides insight into the coverage of HIV programmes in Namibia. The Namibian government has instituted programmes that provide voluntary counselling and HIV testing to the country’s general population and, specifically, pregnant women. Also, programmes are in place, in which drugs that suppress opportunistic infections (e.g., cotrimoxazole) and anti-retroviral drugs are provided to people living with HIV when their condition warrants such treatment. Finally, the government encourages safe medical circumcision of men, based on research indicating that it reduces the risk of HIV acquisition. 16.1 COVERAGE OF HIV TESTING SERVICES Knowledge of HIV status is important for helping individuals decide to adopt safer sex practices to reduce the risk of becoming infected or transmitting HIV. For those who are HIV-positive, knowledge of their HIV status allows them to take measures to protect their sexual partners and to access treatment services. To assess awareness and coverage of prior HIV testing behaviour, respondents were asked if they knew where to get an HIV test and whether they had ever been tested for HIV. If they said they had been tested for HIV, respondents were asked if they had received the results of their last test. Tables 16.1.1 and 16.1.2 present information on prior testing among women and men, respectively. Overall, 97 percent of women age 15-49 and 95 percent of women age 50-64 know a place where they can get an HIV test (Table 16.1.1). Women age 15-19 (93 percent) and those who have not yet initiated sexual activity (91 percent) are less likely than other women to know of a place to obtain an HIV test. Knowledge of a place to obtain an HIV test increases with increasing education, from 89 percent among women with no education to 99 percent among those with a secondary education or higher. There is little variation by residence, region, or wealth. T Key Findings • Forty-nine percent of women and 38 percent of men age 15-49 were tested for HIV in the year preceding the survey and received the test results. This is a notable increase since the 2006-07 NDHS, when the corresponding percentages were 29 percent and 18 percent. • Young women age 15-24 who have had sexual intercourse in the last 12 months are much more likely than their male counterparts in the same age group to have been tested for HIV and to have received the results of their test (58 percent versus 39 percent). • The majority of HIV testing occurs at public health facilities (84 percent of women and 76 percent of men age 15-64). • Only 61 percent of women and 37 percent of men age 15-49 who tested HIV positive in the 2013 NDHS reported that they were HIV positive based on previous testing. • Among women age 15-64 who tested positive for HIV in the 2013 NDHS, only slightly more than half (51 percent) reported they are HIV positive and are currently taking ARVs. • Ninety-four percent of women had an HIV test either during antenatal care or during labour and received the results for their most recent birth. 222 • Self-reported Prior HIV Testing and Treatment More than eight in ten women age 15-49 in Namibia (81 percent) have been tested for HIV. This percentage is notably lower among women age 50-64 (68 percent). Only 2 percent of women age 15-49 and 1 percent of those age 50-64 have been tested for HIV and did not receive the test results. The percentage of women who have been tested for HIV is higher among those age 25-39, those currently or previously married, those in urban areas, and those in Oshana. The likelihood of women having been tested for HIV increases with increasing education. Women in the highest wealth quintile are less likely to have been tested (77 percent) than women in the lowest four quintiles (81-84 percent). About half of women age 15-49 (49 percent) and about three in ten women age 50-64 (27 percent) had been tested in the past 12 months and received the results of their last test. Table 16.1.2 shows that 94 percent of men know where to get an HIV test. Variations by background characteristics are similar to those observed for women. More than six in ten men age 15-49 (63 percent) and more than seven in ten of those age 50-64 (71 percent) have been tested for HIV. A small proportion of men age 15-64 have been tested for HIV and did not receive the results (2-3 percent). The percentage of men age 15-49 who have been tested for HIV is highest among those age 30-39 (81 percent) and those currently married (82 percent). Men in urban areas (71 percent) are much more likely than those in rural areas (53 percent) to have ever been tested for HIV. By region, this percentage ranges from 47 percent in Omusati to 74 percent each in Erongo and Khomas. The percentage of men who have been tested for HIV generally increases with increasing education and wealth. For example, 57 percent of men with no education have been tested for HIV, as compared with 86 percent of men with more than a secondary education. Thirty-eight percent of men age 15-49 and 31 percent of those age 50-64 had been tested in the past 12 months and received the results of their last test. Coverage of HIV testing has shown a remarkable increase in the last six years, from 55 percent of women and 34 percent of men age 15-49 in the 2006-07 NDHS survey to 81 percent and 63 percent, respectively, in 2013. Self-reported Prior HIV Testing and Treatment • 223 Table 16.1.1 Coverage of prior HIV testing: Women Percentage of women age 15-49 who know where to get an HIV test, percent distribution of women age 15-49 by testing status and by whether they received the results of the last test, the percentage of women ever tested, and the percentage of women age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Namibia 2013 Percentage who know where to get an HIV test Percent distribution of women by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of women Background characteristic Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 95.4 62.0 1.9 36.1 100.0 63.9 43.4 3,691 15-19 93.2 41.7 1.7 56.6 100.0 43.4 28.5 1,906 20-24 97.7 83.6 2.1 14.3 100.0 85.7 59.3 1,786 25-29 98.5 93.4 2.2 4.4 100.0 95.6 61.9 1,489 30-39 98.7 91.5 2.4 6.1 100.0 93.9 54.6 2,370 40-49 98.6 87.6 2.5 9.8 100.0 90.2 42.5 1,625 Marital status Never married 96.8 72.4 1.7 25.9 100.0 74.1 47.6 5,458 Ever had sex 98.6 86.3 1.9 11.8 100.0 88.2 57.5 4,155 Never had sex 91.0 28.1 1.1 70.8 100.0 29.2 16.1 1,304 Married/living together 98.0 89.0 2.9 8.1 100.0 91.9 51.4 3,121 Divorced/separated/widowed 99.1 90.8 2.7 6.5 100.0 93.5 51.1 597 Residence Urban 98.3 80.5 2.0 17.4 100.0 82.6 49.7 5,190 Rural 96.1 77.6 2.4 20.0 100.0 80.0 48.4 3,986 Region Zambezi 96.7 78.6 4.7 16.7 100.0 83.3 49.2 457 Erongo 98.3 82.7 1.2 16.1 100.0 83.9 50.2 771 Hardap 97.7 74.2 2.0 23.8 100.0 76.2 41.3 304 //Karas 99.2 80.7 2.8 16.5 100.0 83.5 49.8 343 Kavango 96.1 79.7 4.5 15.9 100.0 84.1 52.9 835 Khomas 98.2 79.2 1.9 18.9 100.0 81.1 47.7 2,202 Kunene 94.8 79.9 1.8 18.3 100.0 81.7 49.8 258 Ohangwena 96.1 79.6 1.7 18.6 100.0 81.4 53.1 894 Omaheke 95.3 81.6 2.1 16.3 100.0 83.7 50.3 225 Omusati 96.9 74.2 0.7 25.1 100.0 74.9 46.3 884 Oshana 98.9 84.9 1.3 13.8 100.0 86.2 51.4 755 Oshikoto 98.0 79.6 2.5 17.8 100.0 82.2 50.4 707 Otjozondjupa 95.3 74.5 2.8 22.6 100.0 77.4 44.3 540 Education No education 88.8 73.3 4.1 22.6 100.0 77.4 40.0 419 Primary 94.4 75.0 2.8 22.2 100.0 77.8 42.6 1,798 Secondary 98.6 80.2 1.9 17.9 100.0 82.1 51.0 6,029 More than secondary 98.7 83.9 2.3 13.8 100.0 86.2 53.9 930 Wealth quintile Lowest 95.9 77.7 3.6 18.7 100.0 81.3 48.8 1,429 Second 96.0 80.2 2.5 17.3 100.0 82.7 50.4 1,625 Middle 97.7 82.0 1.7 16.4 100.0 83.6 53.3 1,795 Fourth 98.1 81.4 1.5 17.1 100.0 82.9 51.0 2,116 Highest 98.2 75.2 2.2 22.6 100.0 77.4 43.3 2,211 Total 15-49 97.3 79.2 2.2 18.6 100.0 81.4 49.1 9,176 50-64 95.0 67.0 1.3 31.7 100.0 68.3 26.8 797 1 Includes “don’t know/missing” 224 • Self-reported Prior HIV Testing and Treatment Table 16.1.2 Coverage of prior HIV testing: Men Percentage of men age 15-49 who know where to get an HIV test, percent distribution of men age 15-49 by testing status and by whether they received the results of the last test, the percentage of men ever tested, and the percentage of men age 15-49 who were tested in the past 12 months and received the results of the last test, according to background characteristics, Namibia 2013 Percentage who know where to get an HIV test Percent distribution of men by testing status and by whether they received the results of the last test Total Percentage ever tested Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Background characteristic Ever tested and received results Ever tested, did not receive results Never tested1 Age 15-24 90.9 39.9 1.3 58.8 100.0 41.2 26.1 1,730 15-19 86.9 24.6 1.2 74.2 100.0 25.8 13.9 922 20-24 95.5 57.3 1.5 41.2 100.0 58.8 40.0 808 25-29 96.3 75.1 2.7 22.2 100.0 77.8 47.5 658 30-39 97.1 79.3 2.1 18.6 100.0 81.4 50.9 968 40-49 97.3 76.5 3.1 20.5 100.0 79.5 41.7 665 Marital status Never married 93.3 53.2 1.8 45.0 100.0 55.0 34.3 2,745 Ever had sex 96.4 63.7 1.8 34.5 100.0 65.5 42.0 2,122 Never had sex 82.7 17.7 1.7 80.6 100.0 19.4 8.1 623 Married/living together 97.1 79.1 2.8 18.1 100.0 81.9 46.5 1,160 Divorced/separated/widowed 91.6 69.8 0.3 29.8 100.0 70.2 45.7 116 Residence Urban 97.2 69.0 1.9 29.0 100.0 71.0 44.3 2,282 Rural 90.6 50.9 2.2 46.9 100.0 53.1 30.0 1,739 Region Zambezi 98.1 59.6 2.1 38.3 100.0 61.7 31.0 218 Erongo 97.3 71.2 2.7 26.0 100.0 74.0 46.7 372 Hardap 97.5 66.4 2.5 31.1 100.0 68.9 32.0 152 //Karas 91.8 52.8 3.9 43.3 100.0 56.7 33.7 151 Kavango 85.9 46.2 2.9 50.9 100.0 49.1 31.4 316 Khomas 97.9 72.4 1.9 25.7 100.0 74.3 47.0 1,023 Kunene 91.2 54.4 0.7 44.9 100.0 55.1 30.3 104 Ohangwena 92.2 57.2 0.8 42.0 100.0 58.0 36.0 328 Omaheke 94.7 64.9 2.8 32.3 100.0 67.7 44.1 103 Omusati 91.0 45.7 1.7 52.6 100.0 47.4 26.2 342 Oshana 97.0 62.8 1.2 35.9 100.0 64.1 38.9 335 Oshikoto 90.8 49.9 2.5 47.6 100.0 52.4 30.2 335 Otjozondjupa 92.3 63.4 1.6 35.0 100.0 65.0 39.9 241 Education No education 84.2 54.4 2.1 43.5 100.0 56.5 36.5 310 Primary 89.4 51.1 2.3 46.6 100.0 53.4 29.4 944 Secondary 96.9 62.8 1.7 35.5 100.0 64.5 39.9 2,400 More than secondary 98.8 82.2 3.6 14.2 100.0 85.8 50.2 368 Wealth quintile Lowest 88.9 48.9 2.0 49.1 100.0 50.9 27.9 594 Second 91.4 54.9 1.9 43.3 100.0 56.7 34.8 769 Middle 94.5 59.6 1.7 38.7 100.0 61.3 37.4 886 Fourth 96.9 67.8 1.7 30.6 100.0 69.4 44.4 917 Highest 97.8 70.0 2.9 27.0 100.0 73.0 42.4 855 Total 15-49 94.3 61.2 2.0 36.8 100.0 63.2 38.1 4,021 50-64 93.5 67.9 3.0 29.1 100.0 70.9 31.1 460 1 Includes “don’t know/missing” 16.2 HIV TESTING AMONG YOUTH Obtaining an HIV test can be more difficult for youth than for adults because many youth lack experience or face barriers in accessing health services. Table 16.2 shows that 80 percent of young women and 55 percent of young men age 15-24 who were sexually active in the 12 months before the survey have been tested for HIV and received the results. The percentage of young women and men who have been tested for HIV and received the test results increases steadily with age and peaks among those age 23-24 (91 percent of women and 72 percent of men). Ever-married youth are more likely to have had an HIV test and received the results than those who have never been married. Young women and men in urban areas are more likely to have been tested for HIV than their rural counterparts, the gap being much more pronounced among young men (62 percent Self-reported Prior HIV Testing and Treatment • 225 versus 47 percent). The percentage of young women and men who have been tested and received the results increases with increasing education. For example, only 67 percent of young women with no education have been tested for HIV and received the results, as compared with 85 percent of those with more than a secondary education. Table 16.2 further shows that 58 percent of sexually active young women and 39 percent of sexually active young men had been tested for HIV in the past 12 months and received the results of their last test. Differentials by background characteristics are similar to those observed with respect to the percentage of young women and men who had ever been tested and received the results. Table 16.2 Recent HIV tests among youth Among young women and young men age 15-24 who have had sexual intercourse in the past 12 months, the percentage who were tested for HIV in the past 12 months and received the results of the last test, by background characteristics, Namibia 2013 Women age 15-24 who have had sexual intercourse in the past 12 months: Men age 15-24 who have had sexual intercourse in the past 12 months: Background characteristic Percentage who have ever been tested for HIV and received results Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of women Percentage who have ever been tested for HIV and received results Percentage who have been tested for HIV in the past 12 months and received the results of the last test Number of men Age 15-19 64.7 48.4 719 41.5 27.6 304 15-17 52.7 39.3 279 41.9 27.2 119 18-19 72.3 54.1 441 41.2 27.8 185 20-24 87.2 63.1 1,402 61.2 43.6 638 20-22 85.0 60.3 854 53.6 36.9 371 23-24 90.6 67.4 548 71.8 53.0 267 Marital status Never married 77.3 58.1 1,639 54.4 37.9 856 Ever married 87.2 58.1 481 59.2 44.3 86 Knows condom source1 Yes 80.5 58.9 2,032 55.2 38.8 928 No 57.4 39.5 89 * * 14 Residence Urban 80.4 59.2 1,225 61.7 44.8 511 Rural 78.4 56.5 896 46.7 30.9 431 Education No education 67.4 41.5 52 31.9 19.8 42 Primary 70.2 49.2 334 38.5 23.1 169 Secondary 81.2 60.2 1,478 59.5 42.2 656 More than secondary 84.9 60.9 257 63.8 51.1 75 Total 15-24 79.6 58.1 2,121 54.8 38.5 942 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 For this table, the following responses are not considered a source for condoms: friends, family members, and home. 16.3 COUPLE COUNSELLING AND TESTING Respondents who indicated that they had been tested for HIV were asked whether they received HIV counselling and testing individually or as a couple. Those who received individual HIV counselling and testing were asked if they would consider counselling and testing as a couple in the future. Results are shown in Tables 16.3.1 and 16.3.2. Among women and men age 15-49 who have ever been tested for HIV and who ever had sex, one- fourth (25 percent each) received HIV counselling and testing as a couple. Respondents age 15-19 (17 percent of women and 9 percent of men) were the least likely to have been counselled and tested as a couple (Table 16.3.1). As expected, currently married women and men were most likely to have been counselled and tested as a couple (32 percent of women and 38 percent of men). Urban women were slightly more likely to have been counselled and tested as a couple than those in rural areas (26 percent versus 23 percent). Among women, the percentage who received counselling and testing as a couple ranged from 20 percent in Ohangwena to 30 percent in Omaheke. Among men, the percentage was lowest 226 • Self-reported Prior HIV Testing and Treatment in Hardap (17 percent) and highest in Omusati (36 percent). Women with more than a secondary education (30 percent) and those in the highest wealth quintile (28 percent) were most likely to have been counselled and tested as a couple. Differentials by education and wealth did not follow a clear pattern among men. Table 16.3.2 shows that a large majority of respondents age 15-49 who received HIV counselling and testing individually reported that they would consider HIV counselling and testing as a couple in the future (88 percent of women and 90 percent of men, respectively). This percentage tends to decrease with age among both women and men. It is highest among never-married women and men who have ever had sex (89 percent and 92 percent, respectively) and among urban respondents (91 percent each). The percentage of women who would consider HIV counselling and testing as a couple in the future ranges from 73 percent in Omusati to 97 percent in Otjozondjupa, while among men it is lowest in Kavango (57 percent) and highest in Omaheke and Oshana (98 percent each). This percentage is highest among women and men with more than secondary education (94 percent and 95 percent, respectively) and among women in the highest wealth quintile and men in the highest two wealth quintiles (93 percent each). Among women and men age 50-64 who were tested individually, 59 percent and 88 percent, respectively, would consider HIV counselling and testing as a couple in the future. Self-reported Prior HIV Testing and Treatment • 227 Table 16.3.1 Couple counselling and testing Among women and men age 15-49 who have who ever had sex and who have ever been tested for HIV, percentage who received HIV counselling and testing as a couple, according to background characteristics, Namibia 2013 Women Men Background characteristic Percentage who received HIV counselling and testing as a couple Number Percentage who received HIV counselling and testing as a couple Number Age 15-24 21.4 2,027 12.4 608 15-19 17.1 577 8.7 153 20-24 23.1 1,450 13.7 455 25-29 26.4 1,404 26.1 501 30-34 24.4 1,175 27.4 414 35-39 27.3 1,024 33.4 367 40-44 27.6 835 33.6 302 45-49 24.2 608 31.3 218 Marital status Never married 19.6 3,666 17.0 1,390 Married/living together 32.4 2,853 38.3 939 Divorced/separated/ widowed 18.6 555 20.3 82 Residence Urban 25.7 4,067 25.3 1,569 Rural 23.4 3,007 25.6 841 Region Zambezi 27.4 370 35.1 131 Erongo 27.5 619 29.9 267 Hardap 27.8 225 17.4 101 //Karas 25.1 274 24.3 82 Kavango 20.4 682 24.5 145 Khomas 26.9 1,701 21.6 740 Kunene 20.3 209 23.8 56 Ohangwena 19.7 677 26.6 171 Omaheke 29.5 183 31.1 69 Omusati 25.6 612 35.6 133 Oshana 21.1 593 27.1 197 Oshikoto 27.4 530 18.9 168 Otjozondjupa 23.2 399 27.4 149 Education No education 22.3 321 30.7 173 Primary 22.8 1,342 24.0 465 Secondary 24.6 4,658 24.8 1,473 More than secondary 29.7 754 27.5 300 Wealth quintile Lowest 23.5 1,104 26.3 281 Second 22.8 1,279 24.1 419 Middle 23.5 1,436 28.1 509 Fourth 24.9 1,665 25.2 610 Highest 28.0 1,590 23.8 590 Total 15-49 24.7 7,074 25.4 2,410 50-64 19.6 541 28.7 320 228 • Self-reported Prior HIV Testing and Treatment Table 16.3.2 Consideration of couple counselling and testing in the future Among women and men age 15-49 who have ever been tested for HIV and who were tested individually, percentage who would consider HIV counselling and testing as a couple in the future, according to background characteristics, Namibia 2013 Women Men Background characteristic Percentage who would consider HIV counselling and testing as couple in future Number Percentage who would consider HIV counselling and testing as couple in future Number Age 15-24 88.2 1,904 85.2 635 15-19 82.7 718 76.3 225 20-24 91.6 1,186 90.2 410 25-29 92.8 1,045 93.0 381 30-34 91.7 888 91.6 301 35-39 88.8 755 90.4 248 40-44 85.7 614 92.7 202 45-49 74.4 471 94.0 155 Marital status Never married 86.2 3,294 89.1 1,273 Ever had sex 88.8 2,927 91.6 1,153 Never had sex 65.0 366 65.2 120 Married/living together 95.0 1,929 92.9 583 Divorced/separated/ widowed 75.0 455 80.0 65 Residence Urban 90.9 3,210 91.4 1,214 Rural 84.8 2,468 87.5 707 Region Zambezi 96.4 274 93.9 87 Erongo 92.9 476 94.5 194 Hardap 86.7 167 96.0 87 //Karas 94.4 218 92.1 66 Kavango 87.2 563 56.5 115 Khomas 91.1 1,312 90.5 601 Kunene 94.8 167 94.9 44 Ohangwena 80.9 593 90.2 145 Omaheke 87.2 132 98.0 48 Omusati 73.3 502 74.5 115 Oshana 86.3 517 97.7 161 Oshikoto 89.9 434 96.9 144 Otjozondjupa 96.5 323 94.3 115 Education No education 84.8 250 85.8 122 Primary 83.3 1,089 88.5 391 Secondary 89.2 3,768 90.0 1,179 More than secondary 93.5 570 94.5 229 Wealth quintile Lowest 83.4 898 86.6 228 Second 85.3 1,046 85.6 334 Middle 88.9 1,159 87.3 398 Fourth 89.3 1,328 93.2 481 Highest 92.5 1,247 93.4 479 Total 15-49 88.3 5,678 89.9 1,921 50-64 58.8 438 87.9 233 Self-reported Prior HIV Testing and Treatment • 229 16.4 PLACE OF LAST HIV TEST Table 16.4 shows the place where women and men age 15-64 who had been tested for HIV received their last test. The majority of respondents (84 percent of women and 76 percent of men) were tested at a public sector facility; only 14 percent of women and 19 percent of men were tested at a private sector facility. With respect to specific types of public facilities, 37 percent of women and 40 percent of men were tested in a government hospital, and 39 percent of women and 21 percent of men were tested in a government primary health care clinic. In the private sector, women (10 percent) and men (13 percent) were most likely to have received their last test in a private hospital, clinic, or doctor’s office. 16.5 HIV PREVALENCE BY PRIOR HIV TEST RESULTS Respondents who said that they had ever been tested for HIV were asked to provide the result of their last HIV test. Tables 16.5.1 and 16.5.2 show the percentage of respondents age 15-49 and 50-64, respectively, who tested positive in the 2013 NDHS, according to their self-reported HIV status. Among respondents age 15-49 who were previously tested and who reported that their last HIV test result was positive, 91 percent of women and 84 percent of men tested positive in the 2013 NDHS. Among respondents age 50-64, the respective percentages were 90 percent and 86 percent. This means that 9-10 percent of women and 14-16 percent of men who reported in the interview that they were HIV- positive had negative or indeterminate HIV test results in the 2013 NDHS. The possible reasons for these differences cannot be fully explained without further investigation. A combination of false positives with regard to previous testing and false negatives with regard to testing in the 2013 NDHS may have contributed to the differences among these respondents. Due to the high sensitivity and specificity of the HIV tests used, this is likely to be a small number of cases. However, these possibilities are hypotheses and cannot be verified because of the limitations of anonymous testing within the context of a large-scale, population-based survey, which does not allow for follow-up interviews and subsequent HIV testing among respondents that would elicit additional information. Seven percent of women and 8 percent of men age 15-49 who reported that their last HIV test result prior to the survey was negative tested HIV positive in the 2013 NDHS. These percentages were 6 percent and 8 percent, respectively, among women and men age 50-64. There are a few possible reasons that could explain this difference. First, respondents could have seroconverted since their last HIV test. Second, respondents could have knowingly reported a false negative HIV status due to discomfort about disclosing that they are HIV positive to the survey interviewer. Third, respondents could have received a false negative on their prior HIV test or a false positive on their NDHS test. The likelihood of the third possibility is very small given the high sensitivity and specificity of HIV tests. The proportion of respondents who seroconverted between their last HIV test and the survey is also likely to be small given the estimated incidence rates of HIV and the relatively short duration between the date of respondents’ last HIV test and the 2013 NDHS. Again, these are only hypotheses that are difficult to verify without further follow-up interviews and subsequent HIV testing. Table 16.4 Place of last HIV test Among women and men age 15-64 ever tested for HIV, percent distribution by place of the last test, Namibia 2013 Place of last test Women Men Public sector 84.0 76.3 Government hospital 36.5 40.3 Government health centre 3.4 4.0 Public stand-alone VCT centre 2.5 6.3 Government primary health care clinic 38.5 20.9 Outreach point 1.1 0.8 Mobile clinic 1.1 2.0 School-based clinic 0.6 0.6 Other public 0.3 1.4 Private sector 13.8 18.5 Private hospital, clinic, or doctor 9.8 13.3 Private stand-alone VCT centre 2.6 2.8 Pharmacy 0.2 0.3 Private mobile clinic 0.3 0.6 Private field worker 0.2 0.3 School-based clinic 0.3 0.6 Other private medical 0.4 0.6 Other source 1.6 5.1 Home 0.2 0.0 Correctional facility 0.1 0.2 Other 1.3 4.9 Total 100.0 100.0 Number 8,017 2,868 230 • Self-reported Prior HIV Testing and Treatment Table 16.5.1 also shows that 35 percent of women and 21 percent of men age 15-49 who declined to disclose their status or who reported that their last HIV test result was indeterminate, or for whom privacy was not obtained, had positive HIV test results in the 2013 NDHS. Table 16.5.1 HIV prevalence by self-reported prior HIV testing: Respondents 15-49 Among women and men age 15-49 who were tested in the 2013 NDHS, the percentage who tested positive for HIV in the 2013 NDHS, by prior testing for HIV and self-reported HIV status, Namibia 2013 Women Men Percentage HIV positive Number Self-reported HIV status Percentage HIV positive Number Percentage HIV positive Number Previously tested Received results Positive 90.7 456 84.0 175 88.8 630 Negative 7.3 2,713 8.0 1,951 7.6 4,664 Other1 34.9 69 21.1 110 26.4 180 Did not receive results 21.3 98 14.1 79 18.1 178 Not previously tested 4.0 694 4.7 1,365 4.5 2,058 Total 15-49 16.9 4,051 10.9 3,680 14.0 7,731 Note: Total includes 21 women with missing information on prior HIV testing. 1 Includes respondents who reported their test result as indeterminate, respondents who declined to disclose their test result, missing responses, and respondents for whom privacy was not obtained to ask the question on result of last HIV test Table 16.5.2 HIV prevalence by self-reported prior HIV testing: Respondents age 50-64 Among women and men age 50-64 who were tested in the 2013 NDHS, the percentage who tested positive for HIV in the 2013 NDHS, by prior testing for HIV and self-reported HIV status, Namibia 2013 Women Men Total Self-reported HIV status Percentage HIV positive Number Percentage HIV positive Number Percentage HIV positive Number Previously tested Received results Positive 90.2 83 (86.2) 44 88.8 126 Negative 5.6 371 8.3 239 6.7 610 Other1 * 6 * 9 * 15 Did not receive result of last test * 10 * 14 (18.1) 24 Not previously tested 7.0 219 2.7 132 5.4 351 Total 50-64 16.7 689 16.0 438 16.4 1,127 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Includes respondents who reported their test result as indeterminate, respondents who declined to disclose their test result, missing responses, and respondents for whom privacy was not obtained to ask the question on result of last HIV test Tables 16.6.1 and 16.6.2 show the percent distribution of HIV positive and HIV negative women and men age 15-49 and 50-64, respectively, by self-reported HIV status. Tables 16.6.1 and 16.6.2 differ from Tables 16.5.1 and 16.5.2 in that the denominators and numerators represent different groups of people. In Tables 16.5.1 and 16.5.2, the numerators include the number of respondents who are HIV positive, and the denominators include the number of respondents in the various categories of prior HIV testing and self-reported test results. For example, as mentioned above, among women age 15-49 who self- reported their HIV status as positive, 91 percent are HIV positive according to the 2013 NDHS testing. In Tables 16.6.1 and 16.6.2, the denominators are respondents who are HIV positive or HIV negative based on the 2013 NDHS testing, and the numerators include the number of respondents in the various prior HIV testing categories. Table 16.6.1 shows that 61 percent of women and 37 percent of men age 15-49 who tested positive in the 2013 NDHS actually reported that they were HIV positive based on prior testing. These percentages are somewhat higher among women and men age 50-64 (65 percent and 54 percent, respectively) (Table 16.6.2). Among women and men age 15-49 who were HIV positive according to the 2013 NDHS testing, 29 percent and 39 percent, respectively, reported that they had been tested for HIV prior to the survey and that the result of their last HIV test was negative. The proportions for women and Self-reported Prior HIV Testing and Treatment • 231 men age 50-64 were 18 percent and 28 percent, respectively. It is possible that some respondents knew they were HIV positive but were unwilling to disclose their status to the interviewer. Other possible explanations for this discrepancy between self-reported and actual HIV status include some respondents seroconversion since the most recent HIV test, receiving a false negative result on the prior HIV test, or receiving a false positive result on the 2013 NDHS test. These explanations, however, are only possibilities that can be neither ruled out nor verified. Remarkably, only four percent of HIV-positive women and 16 percent of HIV-positive men age 15-49 reported that they had never been tested for HIV prior to the survey. Among respondents age 50-64, the respective percentages were 13 percent and 5 percent. Among HIV-negative women age 15-49, 75 percent had had an HIV test with a negative result, and 20 percent had never been tested for HIV prior to the survey; among women age 50-64, these percentages were 61 percent and 36 percent, respectively. Fifty-five percent of HIV-negative men age 15- 49 and 60 percent of those age 50-64 had had an HIV test with a negative result. An additional 40 percent of HIV-negative men age 15-49 and 35 percent of HIV-negative men age 50-64 had not been previously tested. Table 16.6.1 Prior HIV testing by current HIV status: Respondents 15-49 Percent distribution of women and men age 15-49 by self-reported HIV status, according to HIV status from the 2013 NDHS HIV test result, Namibia 2013 Women Men Total Self-reported HIV status HIV positive HIV negative HIV positive HIV negative HIV positive HIV negative Previously tested Received results Positive 60.5 1.3 36.6 0.9 51.6 1.1 Negative 28.8 74.7 38.8 54.7 32.5 64.9 Other1 3.5 1.3 5.8 2.7 4.4 2.0 Did not receive results 3.0 2.3 2.8 2.1 3.0 2.2 Not previously tested 4.1 19.8 16.0 39.7 8.5 29.6 Total 15-49 100.0 100.0 100.0 100.0 100.0 100.0 Number 683 3,367 401 3,279 1,085 6,646 1 Includes respondents who reported their test result as indeterminate, respondents who declined to disclose their test result, missing responses, and respondents for whom privacy was not obtained to ask the question on result of last HIV test Table 16.6.2 Prior HIV testing by current HIV status: Respondents 50-64 Percent distribution of women and men age 50-64 by self-reported HIV status, according to HIV status from the 2013 NDHS HIV test result, Namibia 2013 Women Men Total Self-reported HIV status HIV positive HIV negative HIV positive HIV negative HIV positive HIV negative Previously tested Received results Positive 64.9 1.4 53.7 1.6 60.6 1.5 Negative 18.1 61.0 28.2 59.7 21.9 60.5 Other1 2.9 0.5 7.6 1.0 4.7 0.7 Did not receive results 0.9 1.6 4.7 2.8 2.4 2.1 Not previously tested 13.2 35.5 5.1 34.9 10.1 35.2 Total 50-64 100.0 100.0 100.0 100.0 100.0 100.0 Number 115 574 70 368 185 942 1 Includes respondents who reported their test result as indeterminate, respondents who declined to disclose their test result, missing responses, and respondents for whom privacy was not obtained to ask the question on result of last HIV test Given the amount of discordance between the 2013 NDHS HIV test results and the self-reported information on HIV status among respondents who said they had been tested prior to the survey and knew their test result, and the high percentage of respondents who have been tested within the 12 months 232 • Self-reported Prior HIV Testing and Treatment preceding the survey (see Tables 16.1.1 and 16.1.2) leaving little time for seroconversion, the information on self-reported HIV status in the 2013 NDHS should be interpreted with caution. 16.6 SELF-REPORTED USE OF ANTIRETROVIRAL MEDICATIONS (ARVS) In the 2013 NDHS, respondents who reported that the result of their last HIV test was positive were asked whether they were taking ARVs daily at the time of the survey. Table 16.7 presents the percentage of women age 15-64 who have been previously tested for HIV and received the result of their last test and the percent distribution of women who have been tested for HIV and received the test results by the self-reported result of their last HIV test. It also shows the percentage of women who reported that they are HIV positive and that they were taking ARVs daily at the time of the survey. It can be seen in Table 16.7 that 79 percent of women age 15-49 and 95 percent of women age 50- 64 who reported they are HIV positive are currently taking ARVs. As shown in the bottom half of the table, the results on self-reported ARV use among the subsample of respondents who were eligible for and participated in the 2014 NDHS HIV test are similar to those for the entire survey. However, as presented in Tables 16.6.1 and 16.6.2, the group with self-reported positive results accounts for only 61-65 percent of all women who tested positive for HIV in the survey. Table 16.7 Self-reported HIV status and ARV use: Women Percentage of women age 15-64 who have ever been tested for HIV and received the result of their last test, percent distribution of women who have ever been tested for HIV and received the test results by the self-reported result of the last HIV test, and among women who reported that they are HIV positive, the percentage who were taking ARVs daily at the time of the survey, according to age, Namibia 2013 Among all women Among women who have ever been tested for HIV and received the result of the last HIV test: Number Among respondents who reported that they were HIV positive: Age Ever tested for HIV and received the result of the last test Number Positive Negative Other1 Total Percentage currently taking ARVs daily Number ALL WOMEN 15-49 79.2 9,176 12.6 84.4 3.0 100.0 7,271 79.3 918 50-64 67.0 797 17.0 81.3 1.7 100.0 534 95.4 91 WOMEN TESTED FOR HIV IN THE 2013 NDHS 15-49 79.9 4,051 14.1 83.8 2.1 100.0 3,238 80.0 456 50-64 66.7 689 18.0 80.7 1.3 100.0 460 95.5 83 ARV = antiretroviral 1 Includes respondents who reported their test result as indeterminate, respondents who declined to disclose their test result, missing responses, and respondents for whom privacy was not obtained to ask the question on result of last HIV test Figure 16.1 presents the percent distribution of all women age 15-64 who tested positive for HIV in the 2013 NDHS according to their self-reported HIV status and current ARV use. The figure shows that, among women age 15-64 who had a positive HIV test result in the 2013 NDHS, only slightly more than half (51 percent) are currently taking ARVs. If some respondents knew they were HIV positive and were taking ARVs but did not report that they were HIV positive during the interview, then they would be misclassified as non-users, and the percentage of HIV-positive women taking ARVs could be underestimated. Self-reported Prior HIV Testing and Treatment • 233 Figure 16.1 Self-reported ARV use and HIV status among HIV-positive women age 15-64 16.7 HIV TESTING DURING PREGNANCY Table 16.8 presents information on HIV screening during pregnancy among women who gave birth in the two years preceding the survey. This service is a key tool in reducing HIV transmission from mother to child. According to Table 16.8, 83 percent of women who gave birth during the two years preceding the survey received HIV counselling during antenatal care (ANC) visits (i.e., someone talked with the respondent about all three of the following topics: (1) babies getting the AIDS virus from their mother, (2) preventing the virus, and (3) getting tested for the virus). More than eight in ten women who were tested for HIV received the test results and post-test counselling (82 percent), and about one in ten (11 percent) received the results but did not receive post-test counselling. Less than 1 percent of women were tested for HIV during an antenatal care visit but did not receive their test results. Eighty-one percent of women who gave birth in the two years preceding the survey received pre- and post-test counselling on HIV, an HIV test during ANC, and the test results. Women age 25-29 (87 percent) and never-married women (84 percent) are more likely than other women to have been counselled and tested for HIV during ANC and to have received the test results. This percentage increases with increasing education, from 57 percent among women with no education to 84 percent among those with a secondary education or higher. Wealth does not appear to have a clear relationship with counselling and testing for HIV during ANC among women with a birth in the two years preceding the survey. Ninety-four percent of women had an HIV test either during antenatal care or during labour for their most recent birth and received the results, and 87 percent of women received the test results and disclosed them to their partner. Forty-five percent of women who received ANC for their last birth in the past two years reported that their partner was tested for HIV during any of their ANC visits. Reported HIV positive, on ARVs 51% Reported HIV positive, not on ARVs 11% Reported HIV negative 27% Tested, other results* 4% Tested, did not receive results 3% Never tested 5% * Includes women who reported their test result as indeterminate, women who declined to disclose their test result, missing responses, and women for whom privacy was not obtained to ask the question on result of last HIV test NDHS 2013 234 • Self-reported Prior HIV Testing and Treatment Table 16.8 Pregnant women counselled and tested for HIV Among all women age 15-49 who gave birth in the two years preceding the survey, the percentage who received HIV counselling, the percentage who received an HIV test during antenatal care for their most recent birth by whether they received their results and pre- and post-test counselling, and percentage who received an HIV test at the time during ANC or labour for their most recent birth by whether they received their test results, according to background characteristics, Namibia 2013 Percentage who received counselling on HIV during antenatal care1 Percentage who were tested for HIV during antenatal care and who: Percentage who received counselling on HIV and an HIV test during ANC, and the results Percentage who had an HIV test during ANC or labour and who:2 Received results and disclosed them to their partner Number of women who gave birth in the past two years3 Percentage of women who received ANC care for their last birth in the past two years whose partner was tested for HIV during any of the ANC visits Number of women who received ANC care for their last birth in the past two years Background characteristic Received results and received pre- and post-test counselling Received results and did not receive pre- and post-test counselling Did not receive results Received results Did not receive results Age 15-24 79.8 77.8 14.1 1.4 77.9 93.2 1.2 83.8 704 40.5 681 15-19 73.7 76.0 16.6 1.9 71.6 94.4 1.9 82.6 209 34.4 201 20-24 82.4 78.6 13.0 1.2 80.6 92.7 1.0 84.3 496 43.0 481 25-29 87.9 83.9 11.0 0.7 87.0 95.8 0.7 90.3 497 48.3 486 30-39 83.4 84.5 7.5 0.3 81.7 94.1 0.1 88.8 631 46.4 608 40-49 79.4 84.1 6.1 0.7 77.3 93.2 0.7 87.7 115 48.4 108 Marital status Never married 86.0 83.4 10.5 0.9 84.4 95.5 0.6 86.5 1,009 44.4 987 Married/living together 80.7 79.8 11.6 0.8 78.9 92.7 0.8 88.7 860 45.6 824 Divorced/separated/ widowed 70.6 85.8 3.6 0.0 70.1 91.8 0.0 82.6 78 43.2 73 Residence Urban 81.7 80.1 13.2 0.1 81.0 94.6 0.1 89.0 925 45.0 899 Rural 84.2 83.6 8.4 1.5 81.8 93.7 1.3 85.8 1,022 44.8 985 Region Zambezi 84.7 89.3 3.8 1.4 82.2 93.7 1.4 89.0 112 38.9 109 Erongo 86.8 82.9 11.8 0.0 86.5 95.9 0.0 88.2 136 36.5 135 Hardap 80.1 81.7 7.5 2.0 77.5 89.9 2.0 83.4 73 36.6 70 //Karas 86.1 83.4 12.4 0.0 86.1 97.3 0.0 94.5 61 55.4 60 Kavango 79.6 82.9 7.2 1.5 76.8 91.6 1.5 83.6 231 31.2 221 Khomas 75.9 71.7 20.7 0.0 75.5 94.5 0.0 90.8 344 47.5 333 Kunene 75.7 78.1 11.5 1.3 73.5 90.4 1.3 81.3 69 35.3 65 Ohangwena 92.2 89.3 7.5 1.4 90.8 97.7 0.9 89.0 254 51.5 250 Omaheke 69.0 78.8 8.9 0.0 66.7 89.2 0.0 73.9 59 40.1 54 Omusati 90.5 89.2 3.7 1.4 86.9 94.5 1.4 82.9 189 45.4 186 Oshana 91.8 84.3 14.0 0.0 91.8 98.3 0.0 95.8 127 56.4 127 Oshikoto 82.3 81.8 13.3 1.2 80.9 97.1 0.5 95.4 154 57.3 152 Otjozondjupa 76.5 75.7 7.0 0.6 74.6 87.0 0.6 75.9 137 42.3 123 Education No education 58.8 73.5 3.6 2.7 56.9 79.7 2.7 70.3 110 29.2 96 Primary 81.6 80.2 8.4 1.8 78.2 90.6 1.5 83.8 438 42.0 416 Secondary 85.4 84.4 10.8 0.4 84.3 96.6 0.3 89.6 1,295 46.9 1,268 More than secondary 84.2 67.1 26.8 0.0 84.2 93.9 0.0 91.8 105 46.4 105 Wealth quintile Lowest 80.7 81.9 8.9 1.6 78.6 91.9 1.0 83.8 415 44.6 393 Second 83.7 84.1 8.0 1.8 81.7 93.6 1.8 86.8 439 44.1 425 Middle 86.4 86.0 8.1 0.3 84.5 95.8 0.3 88.7 423 42.9 415 Fourth 85.0 83.3 9.4 0.1 84.4 95.3 0.1 89.1 389 47.4 378 Highest 77.3 70.5 23.3 0.0 76.3 94.4 0.0 88.7 281 46.0 274 Total 15-49 83.0 81.9 10.7 0.8 81.4 94.2 0.7 87.3 1,947 44.9 1,884 1 In this context, “pre-test counselling” means that someone talked with the respondent about all three of the following topics: (1) babies getting the AIDS virus from their mother, (2) preventing the virus, and (3) getting tested for the virus. 2 Women were asked whether they were tested for HIV during labour only if they were not tested for HIV during ANC. 3 The denominator for percentages includes women who did not receive antenatal care for their last birth in the past two years. Self-reported Prior HIV Testing and Treatment • 235 16.8 EARLY INFANT DIAGNOSIS Women who gave birth in the two years preceding the survey were asked about the HIV testing status of their last-born child; the results are shown in Table 16.9. Twenty-eight percent of women age 15-49 with a birth in the two years preceding the survey reported that their last- born child was tested during the first eight weeks of his/her life, an additional 1 percent reported that their child was not tested during the first eight weeks but was tested during the first 18 months of his/her life. Fifteen percent of women reported that their last-born child was tested more than once during the first 18 months. Among the 752 unweighted women with a birth in the two years preceding the survey whose last-born child was tested for HIV, only 18 reported that their child received a positive test result. This number of cases is too few to investigate coverage of ARVs among HIV-positive children. Table 16.9 Early infant diagnosis Among women age 15-49 who gave birth in the two years preceding the survey, the percentage who reported their last- born child was tested for HIV during the first 8 weeks of his/her life, during the first 18 months of his/her life, and more than once during the first 18 months of his/her life, Namibia 2013 Percentage who reported their last-born child was tested for HIV during the first 8 weeks of his/her life 28.2 Percentage who reported their last-born child was tested for HIV during the first 18 months of his/her life but not during the first 8 weeks 1.3 Percentage who reported their last-born child was tested for HIV more than once during the first 18 months of his/her life 14.6 Number of women with a birth in the two years preceding the survey 1,947 Blood Pressure and Blood Glucose • 237 BLOOD PRESSURE AND BLOOD GLUCOSE 17 round the world, whether in developed or developing countries, the rapid increase in noncommunicable diseases (NCDs) is becoming a challenge to achieving global progress in improving population health. This group of chronic diseases—that is, diabetes, cardiovascular disease, cancer, and chronic respiratory disease—contributes to almost 60 percent of the death toll around the world, and 80 percent of these deaths occur in developing countries, including Namibia. With each passing day, this death toll will rise unless proper measures are taken. Based on current trends, by 2020 NCDs will account for 73 percent of deaths and 60 percent of the disease burden in developing countries (WHO, 2010b). In most cases, these NCD-associated risk factors are modifiable and preventable. Hence, early identification and prevention of high blood pressure and elevated plasma lipid and blood glucose levels can reduce people’s risk of developing coronary heart disease and stroke by 80 percent and their risk of type 2 diabetes by 90 percent (CDC, 2009). As in many countries throughout the world, NCDs such as cardiovascular diseases, diabetes, cancer and chronic respiratory diseases are the leading cause of death in Namibia, accounting for 43 percent of all deaths.1 17.1 COVERAGE RATES FOR BLOOD PRESSURE AND BLOOD GLUCOSE MEASUREMENT The 2013 NDHS is the first national survey in Namibia to include biomarker measurements of blood pressure and fasting blood glucose. These biomarkers were collected in an effort to provide information on the prevalence of high blood pressure and elevated fasting blood glucose among a subsample of women and men age 35-64 in half of the survey households (the same households selected for the male survey). Blood pressure and blood glucose levels were measured among consenting respondents. Table 17.1 shows that 2,584 women and 2,163 men age 35-64 were eligible for these tests. 1 http://www.who.int/nmh/countries/nam_en.pdf?ua=1 A Key Findings • Among eligible respondents age 35-64, more than 4 in 10 women (44 percent) and men (45 percent) have elevated blood pressure or are currently taking medicine to lower their blood pressure. • Forty-nine percent of women and 61 percent of men are not aware that they have elevated blood pressure. • Forty-three percent of women and 34 percent of men with hypertension are taking medication for their condition. • Only 29 percent of women and 20 percent of men with hypertension are taking medication and have their blood pressure under control. • Six percent of women and 7 percent of men are diabetic; that is, they have elevated fasting plasma glucose values or report that they are taking diabetes medication. An additional 7 percent of women and 6 percent of men are prediabetic. • Sixty-seven percent of women and 74 percent of men with diabetes are taking medication to lower their blood glucose. • Women and men with a higher-than-normal body mass index (25.0 or higher) are more likely to have elevated blood pressure and elevated fasting blood glucose. 238 • Blood Pressure and Blood Glucose Among these individuals, 81 percent of women and 71 percent of men had their blood pressure measured, and 75 percent of women and 64 percent of men had their blood glucose measured. Table 17.1 Coverage of testing for blood pressure and fasting blood glucose measurement among women and men age 35-64 Percentage of women and men age 35-64 eligible for blood pressure and blood glucose measurements, by testing status, according to selected background characteristics (unweighted), Namibia 2013 Women Men Background characteristic Percentage measured for blood pressure1 Percentage measured for fasting blood glucose Number of women Percentage measured for blood pressure1 Percentage measured for fasting blood glucose Number of men Age 35-39 76.0 69.9 674 66.8 58.2 581 40-44 81.8 74.9 506 66.0 60.6 515 45-49 83.4 77.8 446 72.9 64.2 377 50-54 83.1 78.0 432 70.7 65.2 290 55-59 81.9 75.8 281 80.0 73.2 205 60-64 80.8 77.6 245 81.0 75.9 195 Residence Urban 77.5 70.9 1,249 63.7 56.7 1,172 Rural 83.7 78.8 1,335 79.0 72.1 991 Region Zambezi 77.6 73.3 161 64.2 57.5 120 Erongo 84.3 77.9 204 66.4 61.4 259 Hardap 81.6 77.0 196 75.9 73.8 191 //Karas 84.0 77.3 238 75.3 67.1 219 Kavango 83.9 77.8 180 80.0 68.1 135 Khomas 60.6 50.6 241 48.5 38.1 239 Kunene 86.6 79.3 179 81.3 71.5 144 Ohangwena 84.6 79.8 188 73.8 66.7 84 Omaheke 83.1 79.7 172 74.7 70.2 198 Omusati 83.5 81.9 243 72.1 67.2 122 Oshana 85.1 70.1 174 70.5 54.5 112 Oshikoto 81.3 80.1 176 76.2 69.8 126 Otjozondjupa 77.6 74.1 232 73.4 70.6 214 Education No education 78.1 72.5 375 76.8 69.7 366 Primary 86.0 82.1 827 76.2 70.1 608 Secondary 80.8 74.0 1,132 69.2 62.4 931 More than secondary 68.1 60.3 229 60.3 49.6 224 Wealth quintile Lowest 87.9 82.6 447 82.9 76.7 275 Second 83.0 78.1 466 77.7 69.0 355 Middle 84.7 79.0 471 74.2 65.7 434 Fourth 78.7 73.7 596 66.9 61.5 538 Highest 72.4 65.1 604 61.3 54.7 561 50-64 82.2 77.2 958 76.4 70.6 690 Total 35-64 80.7 75.0 2,584 70.7 63.8 2,163 Note: Total includes 21 women (unweighted) and 34 men (unweighted) with missing data on education. 17.2 HIGH BLOOD PRESSURE High blood pressure, or hypertension, is among the major risk factors for cardiovascular disease. Health facility-based records indicate that hypertension is the leading cause of disability among adults in Namibia. According to the Ministry of Health and Social Services (MoHSS) Health Information System (2007), heart failure, hypertension, and stroke collectively were responsible for 8 percent of all health facility deaths. NDHS respondents were asked several questions to determine their history of hypertension, including whether they had ever been told by a doctor or other health worker that they had high blood pressure and, if so, whether they had been told that on two or more occasions. If they reported being told one or more times that they had high blood pressure, they were asked additional questions about specific actions they were taking at the time of the survey to lower their blood pressure. Blood Pressure and Blood Glucose • 239 17.2.1 History and Treatment of High Blood Pressure In addition to the NDHS blood pressure measurement, women and men age 35-64 were asked questions related to their experiences with blood pressure measurement and treatment or advice received to lower their blood pressure. Tables 17.2 and 17.3 summarise the findings. Overall, 20 percent of women and 13 percent of men age 35-64 reported that they were told by a health professional that they have high blood pressure or hypertension. As might be expected, these percentages generally increase with age and are higher among respondents who are obese or overweight. Women and men in urban areas are more likely than those in rural areas to have been told they have high blood pressure or hypertension by a health professional. By region, this percentage ranges from 11 percent in Ohangwena to 31 percent in Kunene among women and from 7 percent in Oshana to 20 percent in Kunene and Erongo among men. Overall, the percentage of women who have been told that they have high blood pressure or hypertension decreases with increasing education, while the percentage increases among men. The percentage of respondents who have been told by a health professional that they have high blood pressure or hypertension tends to increase with increasing wealth, with the relationship being more linear among men than among women. 240 • Blood Pressure and Blood Glucose Table 17.2 History of hypertension Percentage of women and men age 35-64 who were ever told by a health professional that they have high blood pressure or hypertension, according to selected background characteristics, Namibia 2013 Women Men Background characteristic Percentage of women ever told by a health professional they had hypertension or high blood pressure Number of women Percentage of men ever told by a health professional they had hypertension or high blood pressure Number of men Age 35-39 7.8 713 5.7 577 40-44 18.2 523 8.3 503 45-49 21.3 435 10.7 365 50-54 26.7 442 18.2 274 55-59 34.1 264 28.2 198 60-64 28.5 243 34.1 173 Nutritional status1 Thin (BMI <18.5) 7.4 213 7.8 246 Normal (BMI 18.5-24.9) 16.1 894 13.0 831 Overweight (BMI 25-29.9) 24.2 515 32.4 264 Obese (BMI ≥30.0) 41.5 538 40.7 151 Residence Urban 22.7 1,314 14.6 1,229 Rural 17.0 1,307 11.5 862 Region Zambezi 16.4 120 10.7 90 Erongo 23.7 185 20.0 234 Hardap 25.6 110 13.7 105 //Karas 23.3 115 14.8 100 Kavango 17.6 206 8.7 151 Khomas 21.7 530 14.9 514 Kunene 30.6 85 20.3 64 Ohangwena 11.0 264 7.6 118 Omaheke 20.2 79 9.8 90 Omusati 21.9 323 15.2 162 Oshana 12.5 213 7.2 142 Oshikoto 16.8 204 11.9 146 Otjozondjupa 26.0 187 11.5 174 Education No education 23.7 348 11.4 309 Primary 20.9 816 12.5 575 Secondary 18.3 1,164 13.9 900 More than secondary 18.8 268 16.9 273 Wealth quintile Lowest 11.2 476 6.2 278 Second 18.5 468 10.7 322 Middle 21.0 465 11.6 401 Fourth 26.0 560 15.2 507 Highest 21.0 652 17.8 583 50-64 29.2 950 25.5 645 Total 35-64 19.9 2,621 13.3 2,091 Note: Total includes 26 women and 34 men with missing information on education. 1 Body mass index is expressed as the ratio of weight in kilograms to the square of height in metres (kg/m2). Blood Pressure and Blood Glucose • 241 Table 17.3 shows that three-fourths of women and men who were told that they had high blood pressure were taking prescribed medication to control their blood pressure. More than six in ten respondents (64 percent of both women and men) received advice to reduce their salt intake, 34 percent of women and 38 percent of men received advice or treatment to lose weight, 26 percent of women and 31 percent of men received advice or treatment to stop smoking, and 42 percent of women and 51 percent of men received advice to start exercising or do more exercise. In addition, 11 percent of women and 8 percent of men reported that they were taking herbal or traditional remedies. 17.2.2 Prevalence of High Blood Pressure The 2013 NDHS Woman’s Questionnaire and Man’s Questionnaire included questions to determine if respondents had been diagnosed as hypertensive and if they were taking medication to control their blood pressure. Respondents were also asked if their blood pressure could be measured as part of the survey. It should be noted that the blood pressure measurements taken in the survey are not intended to provide a medical diagnosis of the disease and are regarded only as a statistical description of the survey population. To measure blood pressure, the survey interviewers were provided with a fully automatic, digital device with automatic upper-arm inflation and automatic pressure release. Interviewers were trained in the use of this device according to the manufacturer’s recommended protocol. Three measurements of systolic and diastolic blood pressure (measured in millimetres of mercury [mmHg]) were taken during the survey interview, with an interval of at least 10 minutes between measurements. The average of the second and third measurements was used to classify individuals with respect to hypertension, following internationally recommended categories (WHO, 1999). Individuals were classified as hypertensive if their systolic blood pressure was 140 mmHg or higher or if their diastolic blood pressure was 90 mmHg or higher. Elevated blood pressure was classified as mild, moderate, or severe according to the cutoff points recommended by the World Health Organization and the National Institutes of Health (WHO, 1999; NIH, 1997). Blood pressure status Systolic (mmHg) Diastolic (mmHg) Optimal <120 and <80 Normal 120-129 or 80-84 High normal 130-139 or 85-89 Level of hypertension Grade 1, mild 140-159 or 90-99 Grade 2, moderate 160-179 or 100-109 Grade 3, severe 180+ or 110+ Following internationally recommended guidelines, individuals were considered hypertensive if they had a normal average blood pressure reading but were taking antihypertensive medication. Tables 17.4.1 and 17.4.2 show the prevalence of hypertension among survey respondents age 35- 64. Forty-four percent of women and 45 percent of men were classified as hypertensive; that is, they had a systolic blood pressure of at least 140 mmHg or a diastolic blood pressure of at least 90 mmHg at the time of the survey or they were currently taking antihypertensive medication to control their blood pressure. The term “hypertension” as used in this report is not meant to be a clinical diagnosis of the disease; rather, it is intended to provide an indication of the disease burden in the population at the time of the survey. Table 17.3 Actions taken or advice received to lower blood pressure Among respondents age 15-64 who were ever told by a health professional that they have high blood pressure or hypertension, the percentage taking specific actions or who received specific advice to lower blood pressure, Namibia 2013 Actions taken/advice received to lower blood pressure Women Men Prescribed medication 75.3 75.0 Advice to reduce salt intake 64.4 64.4 Advice/treatment to lose weight 33.6 38.0 Advice/treatment to stop smoking 26.3 30.9 Advice to start/do more exercise 42.2 51.0 Taking any herbal or traditional remedies 11.3 8.4 Number of respondents told they have high blood pressure or hypertension by a health provider 521 279 242 • Blood Pressure and Blood Glucose As expected, the prevalence of hypertension is associated with age; it is lowest among respondents age 35-39 and highest among those age 55-64. Fifty-one percent of urban women and men are considered hypertensive, as compared with 38 percent of rural respondents. The prevalence of hypertension is highest among women and men living in Khomas (57 percent each), women with no formal education (53 percent), and men with more than a secondary education (59 percent). The prevalence of hypertension tends to increase with increasing wealth among both women and men, although the relationship is not linear. Although overall rates of hypertension among adults in Namibia are relatively low, hypertension is a serious health problem among adults age 45 and older and those who are obese. A first step toward bringing hypertension under control is awareness by individuals of their condition and its implications in terms of premature disability and death. Educating the population about the adverse effects of hypertension and promoting blood pressure screening, particularly for older individuals, should be an important focus of health programmes. B lo od P re ss ur e an d B lo od G lu co se • 2 43 Ta bl e 17 .4 .1 B lo od p re ss ur e st at us : W om en A m on g w om en a ge 3 5- 64 , p re va le nc e of h yp er te ns io n, p er ce nt d is tri bu tio n of b lo od p re ss ur e va lu es , a nd p er ce nt ag e ha vi ng n or m al b lo od p re ss ur e an d ta ki ng m ed ic at io n, a cc or di ng to s el ec te d ba ck gr ou nd c ha ra ct er is tic s, N am ib ia 2 01 3 P re va le nc e of hy pe rte ns io n1 C la ss ifi ca tio n of b lo od p re ss ur e To ta l N or m al b lo od pr es su re a nd ta ki ng m ed ic in e N um be r o f w om en N or m al E le va te d B ac kg ro un d ch ar ac te ris tic O pt im al < 12 0 an d 80 m m H g N or m al 1 20 -1 29 / 80 -8 4 m m H g H ig h no rm al 13 0- 13 9/ 85 -8 9 m m H g M ild ly e le va te d (G ra de 1 ) 14 0- 15 9/ 90 -9 9 m m H g M od er at el y el ev at ed (G ra de 2 ) 1 60 -1 79 / 10 0- 10 9 m m H g S ev er el y el ev at ed (G ra de 3 ) 18 0+ /1 10 + m m H g A ge 35 -3 9 26 .6 41 .2 18 .9 16 .9 16 .9 5. 5 0. 7 10 0. 0 3. 6 51 4 40 -4 4 40 .6 34 .4 18 .8 13 .2 23 .1 8. 1 2. 4 10 0. 0 7. 0 41 2 45 -4 9 48 .8 27 .1 12 .4 18 .0 27 .9 9. 6 4. 9 10 0. 0 6. 4 35 4 50 -5 4 51 .3 23 .8 14 .4 19 .8 23 .9 13 .3 4. 8 10 0. 0 9. 3 36 1 55 -5 9 62 .1 20 .6 14 .6 15 .0 29 .3 16 .2 4. 2 10 0. 0 12 .4 21 0 60 -6 4 55 .4 26 .2 12 .9 23 .1 22 .8 9. 4 5. 7 10 0. 0 17 .5 19 6 N ut rit io na l s ta tu s2 Th in (B M I < 18 .5 ) 24 .6 46 .5 17 .5 13 .6 15 .8 4. 7 1. 8 10 0. 0 2. 3 17 4 N or m al (B M I 1 8. 5- 24 .9 ) 37 .5 36 .1 15 .6 15 .3 20 .8 8. 7 3. 4 10 0. 0 4. 6 82 0 O ve rw ei gh t ( B M I 2 5- 29 .9 ) 46 .3 25 .9 13 .5 22 .6 25 .5 8. 9 3. 5 10 0. 0 8. 3 48 0 O be se (B M I ≥ 30 .0 ) 62 .0 18 .1 17 .4 18 .2 29 .2 13 .3 3. 9 10 0. 0 15 .6 49 6 R es id en ce U rb an 50 .6 26 .7 14 .3 18 .2 25 .2 12 .6 3. 0 10 0. 0 9. 9 95 3 R ur al 38 .3 34 .3 17 .3 16 .4 21 .3 7. 0 3. 6 10 0. 0 6. 3 1, 09 4 R eg io n Za m be zi 38 .8 32 .5 19 .0 19 .8 19 .5 8. 1 1. 0 10 0. 0 10 .1 94 E ro ng o 48 .2 31 .3 11 .2 23 .8 21 .5 7. 4 4. 8 10 0. 0 14 .4 15 6 H ar da p 52 .1 21 .9 14 .6 19 .1 27 .2 14 .7 2. 6 10 0. 0 7. 7 91 //K ar as 45 .7 28 .1 16 .8 18 .7 22 .8 10 .2 3. 4 10 0. 0 9. 4 96 K av an go 37 .1 42 .3 15 .0 13 .0 18 .3 9. 2 2. 3 10 0. 0 7. 4 17 2 K ho m as 57 .3 25 .2 13 .2 13 .6 26 .6 18 .3 3. 2 10 0. 0 9. 3 31 9 K un en e 41 .9 30 .3 23 .6 14 .6 18 .4 9. 0 4. 2 10 0. 0 10 .3 74 O ha ng w en a 35 .5 30 .9 20 .2 19 .5 20 .9 5. 6 2. 8 10 0. 0 6. 2 22 2 O m ah ek e 51 .0 22 .7 23 .0 15 .8 27 .7 6. 9 4. 0 10 0. 0 12 .5 66 O m us at i 39 .8 32 .4 12 .7 19 .9 22 .7 7. 0 5. 3 10 0. 0 4. 8 27 0 O sh an a 32 .6 35 .5 17 .5 15 .9 19 .9 8. 2 3. 1 10 0. 0 1. 4 18 2 O sh ik ot o 41 .0 36 .6 18 .9 11 .3 26 .3 4. 8 2. 2 10 0. 0 7. 8 16 1 O tjo zo nd ju pa 52 .2 23 .6 13 .5 21 .6 28 .0 10 .3 3. 1 10 0. 0 10 .8 14 5 Ed uc at io n N o ed uc at io n 52 .8 27 .0 14 .4 12 .4 24 .2 15 .6 6. 4 10 0. 0 6. 6 26 3 P rim ar y 42 .9 28 .6 17 .1 17 .8 24 .1 8. 5 4. 0 10 0. 0 6. 4 69 7 S ec on da ry 41 .7 34 .0 15 .3 17 .6 22 .4 8. 3 2. 4 10 0. 0 8. 6 90 4 M or e th an s ec on da ry 45 .2 29 .4 18 .2 20 .6 19 .5 11 .2 1. 1 10 0. 0 13 .5 17 2 C on tin ue d… Blood Pressure and Blood Glucose • 243 24 4 • B lo od P re ss ur e an d B lo od G lu co se Ta bl e 17 .4 .1 — C on tin ue d P re va le nc e of hy pe rte ns io n1 C la ss ifi ca tio n of b lo od p re ss ur e To ta l N or m al b lo od pr es su re a nd ta ki ng m ed ic in e N um be r o f w om en N or m al E le va te d B ac kg ro un d ch ar ac te ris tic O pt im al < 12 0 an d 80 m m H g N or m al 1 20 -1 29 / 80 -8 4 m m H g H ig h no rm al 13 0- 13 9/ 85 -8 9 m m H g M ild ly e le va te d (G ra de 1 ) 14 0- 15 9/ 90 -9 9 m m H g M od er at el y el ev at ed (G ra de 2 ) 1 60 -1 79 / 10 0- 10 9 m m H g S ev er el y el ev at ed (G ra de 3 ) 18 0+ /1 10 + m m H g W ea lth q ui nt ile Lo w es t 32 .5 39 .0 19 .5 13 .0 19 .0 6. 6 2. 8 10 0. 0 4. 0 41 8 S ec on d 41 .2 32 .0 17 .0 17 .6 22 .3 7. 4 3. 6 10 0. 0 7. 8 38 4 M id dl e 44 .6 28 .0 14 .8 18 .0 25 .5 9. 3 4. 3 10 0. 0 5. 5 38 6 Fo ur th 52 .9 25 .5 11 .5 20 .4 27 .2 11 .8 3. 6 10 0. 0 10 .3 43 2 H ig he st 48 .4 29 .5 17 .0 17 .1 21 .5 12 .4 2. 4 10 0. 0 12 .0 42 7 50 -6 4 55 .3 23 .5 14 .1 19 .3 25 .1 13 .1 4. 9 10 0. 0 12 .3 76 8 To ta l 3 5- 64 44 .0 30 .8 15 .9 17 .2 23 .1 9. 6 3. 3 10 0. 0 8. 0 2, 04 8 N ot e: T ot al in cl ud es 1 2 w om en w ith m is si ng in fo rm at io n on e du ca tio n. 1 A n in di vi du al w as c la ss ifi ed a s ha vi ng h yp er te ns io n if he /s he h ad a s ys to lic b lo od p re ss ur e le ve l o f 1 40 m m H g or a bo ve o r a d ia st ol ic b lo od p re ss ur e le ve l o f 9 0 m m H g or a bo ve a t t he ti m e of th e su rv ey o r w as c ur re nt ly ta ki ng an tih yp er te ns iv e m ed ic at io n to c on tro l h is /h er b lo od p re ss ur e. T he te rm “ hy pe rte ns io n” a s us ed in th is ta bl e is n ot m ea nt to b e a cl in ic al d ia gn os is o f t he d is ea se ; r at he r, it pr ov id es a n in di ca tio n of th e di se as e bu rd en in th e po pu la tio n at th e tim e of th e su rv ey . 2 B od y m as s in de x is e xp re ss ed a s th e ra tio o f w ei gh t i n ki lo gr am s to th e sq ua re o f h ei gh t i n m et re s (k g/ m 2 ) . 244 • Blood Pressure and Blood Glucose B lo od P re ss ur e an d B lo od G lu co se • 2 45 Ta bl e 17 .4 .2 B lo od p re ss ur e st at us : M en A m on g m en a ge 3 5- 64 , pr ev al en ce o f hy pe rte ns io n, p er ce nt d is tri bu tio n of b lo od p re ss ur e va lu es , an d pe rc en ta ge h av in g no rm al b lo od p re ss ur e an d ta ki ng m ed ic at io n, a cc or di ng t o se le ct ed b ac kg ro un d ch ar ac te ris tic s, N am ib ia 2 01 3 P re va le nc e of hy pe rte ns io n1 C la ss ifi ca tio n of b lo od p re ss ur e To ta l N or m al b lo od pr es su re a nd ta ki ng m ed ic in e N um be r o f m en N or m al E le va te d B ac kg ro un d ch ar ac te ris tic O pt im al < 12 0 an d 80 m m H g N or m al 12 0- 12 9/ 80 -8 4 m m H g H ig h no rm al 1 30 - 13 9/ 85 -8 9 m m H g M ild ly e le va te d (G ra de 1 ) 14 0- 15 9/ 90 -9 9 m m H g M od er at el y el ev at ed (G ra de 2 ) 16 0- 17 9/ 10 0- 10 9 m m H g S ev er el y el ev at ed (G ra de 3 ) 18 0+ /1 10 + m m H g A ge 35 -3 9 30 .8 32 .9 24 .2 14 .3 18 .8 7. 8 1. 9 10 0. 0 2. 2 36 6 40 -4 4 40 .2 28 .9 19 .5 15 .5 22 .9 9. 5 3. 8 10 0. 0 4. 0 31 2 45 -4 9 41 .7 31 .5 17 .6 13 .2 21 .9 12 .4 3. 4 10 0. 0 4. 0 25 0 50 -5 4 51 .8 22 .2 16 .3 16 .0 29 .5 12 .0 3. 9 10 0. 0 6. 3 18 4 55 -5 9 63 .7 25 .7 9. 1 13 .9 29 .6 16 .0 5. 7 10 0. 0 12 .5 15 4 60 -6 4 65 .2 19 .5 13 .3 17 .0 25 .2 11 .2 13 .8 10 0. 0 15 .0 14 0 N ut rit io na l s ta tu s2 Th in (B M I < 18 .5 ) 29 .2 44 .2 19 .0 10 .7 20 .5 3. 4 2. 2 10 0. 0 3. 0 21 4 N or m al (B M I 1 8. 5- 24 .9 ) 39 .1 31 .4 18 .0 15 .0 21 .2 10 .4 4. 0 10 0. 0 3. 6 77 6 O ve rw ei gh t ( B M I 2 5- 29 .9 ) 58 .5 17 .4 19 .0 17 .2 24 .3 14 .8 7. 4 10 0. 0 12 .0 24 9 O be se (B M I ≥ 30 .0 ) 69 .8 8. 8 17 .0 15 .6 37 .4 16 .4 4. 8 10 0. 0 11 .2 14 6 R es id en ce U rb an 50 .8 23 .5 18 .8 14 .4 25 .7 12 .2 5. 4 10 0. 0 7. 6 73 1 R ur al 37 .8 33 .4 17 .6 15 .2 21 .1 9. 2 3. 5 10 0. 0 4. 0 67 5 R eg io n Za m be zi 46 .7 20 .8 25 .3 13 .7 30 .9 6. 6 2. 7 10 0. 0 6. 5 59 E ro ng o 53 .1 18 .5 22 .6 18 .6 23 .0 11 .3 6. 2 10 0. 0 12 .7 15 8 H ar da p 42 .5 27 .4 19 .3 16 .0 21 .4 11 .7 4. 2 10 0. 0 5. 2 79 //K ar as 47 .1 25 .7 17 .2 14 .6 28 .2 11 .1 3. 3 10 0. 0 4. 6 74 K av an go 30 .4 42 .7 17 .2 12 .8 21 .4 5. 1 0. 8 10 0. 0 3. 1 12 1 K ho m as 56 .5 21 .6 16 .8 13 .9 25 .8 14 .8 7. 1 10 0. 0 8. 8 25 3 K un en e 39 .0 28 .4 16 .6 21 .2 20 .2 9. 7 3. 9 10 0. 0 5. 2 51 O ha ng w en a 43 .6 30 .9 19 .2 9. 1 22 .0 16 .2 2. 5 10 0. 0 2. 8 84 O m ah ek e 45 .1 25 .0 17 .2 16 .6 24 .2 12 .9 4. 2 10 0. 0 3. 9 69 O m us at i 43 .0 30 .9 15 .6 12 .9 25 .3 9. 6 5. 7 10 0. 0 2. 3 11 7 O sh an a 35 .0 34 .4 22 .8 11 .6 21 .6 8. 6 1. 1 10 0. 0 3. 8 10 2 O sh ik ot o 33 .4 41 .2 13 .8 16 .7 16 .3 7. 9 4. 1 10 0. 0 5. 0 11 1 O tjo zo nd ju pa 44 .3 26 .9 16 .3 16 .5 24 .6 9. 8 5. 9 10 0. 0 4. 0 12 7 Ed uc at io n N o ed uc at io n 43 .4 34 .0 14 .1 13 .5 22 .2 11 .2 5. 0 10 0. 0 5. 0 23 6 P rim ar y 43 .1 31 .4 16 .2 15 .6 22 .7 10 .5 3. 6 10 0. 0 6. 3 42 2 S ec on da ry 42 .9 25 .8 21 .0 14 .7 22 .7 10 .7 5. 1 10 0. 0 4. 4 59 4 M or e th an s ec on da ry 58 .8 19 .2 19 .2 14 .8 31 .4 11 .6 3. 9 10 0. 0 12 .0 14 7 C on tin ue d… Blood Pressure and Blood Glucose • 245 24 6 • B lo od P re ss ur e an d B lo od G lu co se Ta bl e 17 .4 .2 — C on tin ue d P re va le nc e of hy pe rte ns io n1 C la ss ifi ca tio n of b lo od p re ss ur e To ta l N or m al b lo od pr es su re a nd ta ki ng m ed ic in e N um be r o f m en N or m al E le va te d B ac kg ro un d ch ar ac te ris tic O pt im al < 12 0 an d 80 m m H g N or m al 12 0- 12 9/ 80 -8 4 m m H g H ig h no rm al 1 30 - 13 9/ 85 -8 9 m m H g M ild ly e le va te d (G ra de 1 ) 14 0- 15 9/ 90 -9 9 m m H g M od er at el y el ev at ed (G ra de 2 ) 16 0- 17 9/ 10 0- 10 9 m m H g S ev er el y el ev at ed (G ra de 3 ) 18 0+ /1 10 + m m H g W ea lth q ui nt ile Lo w es t 30 .3 39 .3 20 .2 12 .3 20 .8 6. 4 0. 9 10 0. 0 2. 2 23 0 S ec on d 43 .8 30 .6 15 .8 14 .4 24 .3 12 .2 2. 7 10 0. 0 4. 6 24 8 M id dl e 40 .9 28 .3 17 .4 16 .9 20 .9 12 .2 4. 4 10 0. 0 3. 4 28 7 Fo ur th 50 .5 27 .4 15 .4 14 .1 23 .0 11 .8 8. 3 10 0. 0 7. 3 32 5 H ig he st 52 .9 19 .2 22 .3 15 .8 27 .7 10 .5 4. 5 10 0. 0 10 .2 31 6 50 -6 4 59 .6 22 .6 13 .1 15 .6 28 .3 13 .1 7. 4 10 0. 0 10 .8 47 8 To ta l 3 5- 64 44 .6 28 .3 18 .2 14 .8 23 .5 10 .8 4. 5 10 0. 0 5. 9 1, 40 6 N ot e: T ot al in cl ud es 7 m en w ith m is si ng in fo rm at io n on e du ca tio n. 1 A n in di vi du al w as c la ss ifi ed a s ha vi ng h yp er te ns io n if he /s he h ad a s ys to lic b lo od p re ss ur e le ve l o f 1 40 m m H g or a bo ve o r a d ia st ol ic b lo od p re ss ur e le ve l o f 9 0 m m H g or a bo ve a t t he ti m e of th e su rv ey o r w as c ur re nt ly ta ki ng an tih yp er te ns iv e m ed ic at io n to c on tro l h is /h er b lo od p re ss ur e. T he te rm “ hy pe rte ns io n” a s us ed in th is ta bl e is n ot m ea nt to b e a cl in ic al d ia gn os is o f t he d is ea se ; r at he r, it pr ov id es a n in di ca tio n of th e di se as e bu rd en in th e po pu la tio n at th e tim e of th e su rv ey . 2 B od y m as s in de x is e xp re ss ed a s th e ra tio o f w ei gh t i n ki lo gr am s to th e sq ua re o f h ei gh t i n m et re s (k g/ m 2 ) . 246 • Blood Pressure and Blood Glucose Blood Pressure and Blood Glucose • 247 Figure 17.1 shows the level of awareness and treatment status of hypertensive women and men. About half of women (49 percent) and about six in ten men (61 percent) who have high blood pressure reported that they are unaware of their condition. Twenty-nine percent of hypertensive women and 20 percent of hypertensive men are being treated and have brought their blood pressure under control, and 14 percent each are being treated but still have elevated blood pressure. Eight percent of hypertensive women and 6 percent of hypertensive men are aware that they have elevated blood pressure. Figure 17.1 Awareness of high blood pressure and treatment status among women and men age 35-64 with high blood pressure2 17.3 DIABETES Diabetes is a chronic disease characterised by chronic hyperglycaemia that requires lifelong treatment. Over time, diabetes can damage the heart, blood vessels, eyes, kidneys, and nerves. The global spread of diabetes has given it the characteristics of a pandemic. WHO estimates that 347 million people worldwide have diabetes. In 2004, an estimated 3.4 million people died from consequences of fasting high blood sugar. More than 80 percent of diabetes deaths occur in low- and middle-income countries.3 WHO estimated that in 2008 diabetes caused 4 percent of adult deaths in Namibia.4 As mentioned above, all women and men age 35-64 in the subsample of households selected for the male survey for the 2013 NDHS were eligible to have their blood glucose levels tested. Respondents were asked if they had eaten or drunk anything at all (except water) from the time they had awakened in the morning until the time of the glucose testing. If respondents were fasting at the time of the interview, a capillary blood sample was obtained from their middle or ring finger. If they were not fasting at the time of the interview, an appointment was made for the next morning to collect and test a fasting capillary blood sample (as described below). Blood glucose was measured using the HemoCue 201+ blood glucose analyser in capillary whole blood obtained from adults’ middle or ring finger after an overnight fast. The finger was cleaned with a swab containing 70 percent isopropyl alcohol, allowed to dry, and pricked with a retractable, non-reusable lancet. The first two drops of blood were wiped away, and the third drop was drawn into the glucose microcuvette by capillary action after placing the tip of the microcuvette in the middle of the blood drop. The outside of the microcuvette was wiped clean with gauze and placed in the HemoCue 201+ analyser to obtain a glucose measurement. The analyser displayed blood glucose measurements in millimoles per litre (mmol/L). 2 Percentages may not add up to 100 percent due to rounding. 3 http://www.who.int/mediacentre/factsheets/fs312/en/ 4 http://www.who.int/nmh/countries/nam_en.pdf?ua=1 Aware, treated, controlled 29% Aware, treated, not controlled 14% Aware, not treated 8% Unaware 49% Women Aware, treated, controlled 20% Aware, treated, not controlled 14% Aware, not treated 6% Unaware 61% Men NDHS 2013 248 • Blood Pressure and Blood Glucose The WHO cutoff points for measuring fasting plasma glucose were used (WHO, 2006b). These cutoff points correspond to the clinical classifications of normal fasting plasma glucose levels, prediabetes, and diabetes. Fasting plasma glucose values between 3.9 and 6.0 mmol/L are considered to be normal. A fasting plasma glucose value of 6.1 to 6.9 mmol/L is classified as prediabetes, and values of 7.0 mmol/L or above are considered to be diabetes. The chart below summarises fasting plasma glucose values as they relate to diabetes classifications. The data are presented according to the fasting plasma glucose measurements obtained from the respondents. These measurements provide a cross-sectional assessment of the prevalence of diabetes in the surveyed population at the time of the NDHS interviews and do not represent a medical diagnosis of diabetes. Although the results of the fasting plasma glucose measurements are regarded only as a statistical description of the survey population, they are useful in providing insight into the size and characteristics of the population at risk for diabetes. For the purposes of the survey, fasting plasma glucose values are not presented using the diagnostic terms prediabetes and diabetes. In a clinical setting, an individual’s fasting plasma glucose would be measured and the levels monitored over a prolonged period of time, with a clinical history for that individual prior to diagnosing whether he or she had diabetes. In the survey setting, an individual’s fasting plasma glucose was measured for one day only, and the value was recorded to provide information on the national status of this important NCD. 17.3.1 History of Diabetes In addition to the NDHS blood glucose measurement, women and men age 35-64 were asked questions related to their experiences with blood glucose measurement and treatment or advice to lower their blood glucose. Table 17.5 presents the findings. Overall, only 3 percent of women and men age 35-64 reported that they were told by a health professional that they had high blood sugar levels or diabetes prior to the survey. Blood Pressure and Blood Glucose • 249 Table 17.5 History of diabetes Percentage of women and men age 35-64 who were ever told by a health professional that they have high blood sugar or diabetes, according to selected background characteristics, Namibia 2013 Women Men Background characteristic Percentage of women ever told by a health professional they had high blood sugar or diabetes Number of women Percentage of men ever told by a health professional they had high blood sugar or diabetes Number of men Age 35-39 1.4 713 0.5 577 40-44 1.9 523 1.4 503 45-49 2.9 435 1.2 365 50-54 4.0 442 4.7 274 55-59 3.7 264 6.7 198 60-64 3.4 243 7.8 173 Nutritional status1 Thin (BMI <18.5) 0.1 225 0.5 263 Normal (BMI 18.5-24.9) 0.8 1,048 0.8 1,051 Overweight (BMI 25-29.9) 3.2 609 5.2 407 Obese (BMI ≥30.0) 6.0 652 6.1 327 Residence Urban 3.8 1,314 3.3 1,229 Rural 1.4 1,307 1.6 862 Region Zambezi 3.2 120 2.6 90 Erongo 2.2 185 4.7 234 Hardap 9.8 110 5.9 105 //Karas 6.5 115 3.9 100 Kavango 0.5 206 1.4 151 Khomas 3.0 530 2.1 514 Kunene 10.7 85 4.5 64 Ohangwena 1.7 264 0.0 118 Omaheke 1.7 79 0.9 90 Omusati 0.8 323 1.6 162 Oshana 0.6 213 2.1 142 Oshikoto 0.0 204 1.5 146 Otjozondjupa 3.5 187 3.5 174 Education No education 1.5 348 0.5 309 Primary 2.1 816 1.4 575 Secondary 2.9 1,164 3.1 900 More than secondary 3.8 268 6.0 273 Wealth quintile Lowest 0.4 476 0.4 278 Second 1.0 468 0.6 322 Middle 1.6 465 0.8 401 Fourth 4.5 560 2.3 507 Highest 4.5 652 6.2 583 50-64 3.7 950 6.2 645 Total 35-64 2.6 2,621 2.6 2,091 Note: Total includes 26 women and 34 men with missing information on education. 1 Body mass index is expressed as the ratio of weight in kilograms to the square of height in metres (kg/m2). 250 • Blood Pressure and Blood Glucose Table 17.6 shows that 67 percent of women and 74 percent of men who were told they had high blood glucose or diabetes were taking prescribed medication to lower their blood glucose. More than seven in ten respondents (76 percent of women and 73 percent of men) received advice on a special diet, 58 percent of women and 72 percent of men received advice or treatment to lose weight, 48 percent of women and 53 percent of men received advice or treatment to stop smoking, and 64 percent of women and 75 percent of men received advice to start exercising or do more exercise. Also, 14 percent of women and 20 percent of men reported that they were taking herbal or traditional remedies. 17.3.2 Prevalence and Treatment of Diabetes The fasting whole blood glucose measurements taken in the survey provide a cross-sectional assessment of elevated fasting plasma values in the surveyed population at the time of the NDHS interviews and do not represent a medical diagnosis of diabetes. Tables 17.7.1 and 17.7.2 present fasting plasma glucose levels among women and men, respectively. The data show that 6 percent of women and 7 percent of men have diabetes; that is, they either have fasting plasma glucose (FPG) values of 7 mmol/L or higher or report that they are currently taking diabetes medication. Similar to “hypertension,” the term “diabetes” in this report is not meant to be a clinical diagnosis of the disease; rather, it provides an indication of the disease burden in the population at the time of the survey. The findings also show that 7 percent of women and 6 percent of men are prediabetic (i.e., their FPG values are 6.1-6.9 mmol/L). Only 1 percent of women and men are taking medication for diabetes. Table 17.7.1 shows that, among women, diabetes increases with age; 3 percent of women age 35- 39 have elevated FPG values or are currently taking diabetes medicine, as compared with 8 percent of women age 55-59. Obese women (12 percent) are much more likely than other women to have high blood glucose or diabetes. The data further show that urban women are twice as likely as rural women to be classified as having diabetes (8 percent versus 4 percent). By region, women in Hardap have the highest prevalence of diabetes (19 percent), and women in Kavango have the lowest prevalence (1 percent). The prevalence of diabetes is highest among women with more than a secondary education (7 percent) and women in the highest wealth quintile (9 percent). Table 17.7.2 shows that men age 60-64 have the highest prevalence of diabetes (13 percent). Similar to women, the prevalence is highest among obese men (19 percent) and is higher among urban (8 percent) than rural (5 percent) men. Men in Hardap are most likely to have diabetes (14 percent) and men in Kavango least likely (3 percent). Diabetes prevalence increases with increasing education, ranging from 2 percent among men with no education to 15 percent among those with more than a secondary education. The prevalence of diabetes generally increases with increasing wealth. Table 17.6 Actions taken or advice received to lower high blood glucose or diabetes Among respondents who were ever told by a health professional that they have high blood glucose or diabetes, the percentage taking specific actions or who received specific advice to lower blood glucose, Namibia 2013 Actions taken/advice received to lower high blood glucose/diabetes Women Men Prescribed medication 66.6 73.8 Advice on special diet 75.9 72.7 Advice/treatment to lose weight 58.2 71.6 Advice/treatment to stop smoking 48.2 53.2 Advice to start/do more exercise 64.4 75.5 Taking any herbal or traditional remedies 14.2 20.0 Number of respondents told they have high blood glucose or diabetes by a health provider 68 54 Blood Pressure and Blood Glucose • 251 Table 17.7.1 Prevalence of diabetes by background characteristics: Women Among women age 35-64, prevalence of diabetes, percent distribution by fasting plasma glucose (FPG) values, and percentage with normal fasting plasma glucose level and taking medication, according to selected background characteristics, Namibia 2013 Prevalence of diabetes1 Fasting plasma glucose values Total Normal FPG and taking medicine Number of women Background characteristic <3.9 mmol/L (below normal) 3.9-6.0 mmol/L (normal) 6.1-6.9 mmol/L (prediabetic) ≥7 mmol/L (elevated) Age 35-39 2.9 5.9 85.5 5.8 2.7 100.0 0.1 465 40-44 6.5 1.7 87.5 4.8 6.1 100.0 0.4 370 45-49 6.7 3.4 82.7 8.2 5.8 100.0 0.9 321 50-54 5.5 4.3 84.0 7.6 4.1 100.0 1.4 337 55-59 7.6 2.4 82.3 9.3 6.0 100.0 1.6 192 60-64 7.2 8.1 75.7 10.3 5.8 100.0 1.4 187 Nutritional status2 Thin (BMI <18.5) 1.7 11.3 76.4 10.6 1.7 100.0 0.0 168 Normal (BMI 18.5-24.9) 3.3 4.5 85.3 7.1 3.0 100.0 0.3 760 Overweight (BMI 25-29.9) 5.7 2.7 87.9 4.4 5.0 100.0 0.7 438 Obese (BMI ≥30.0) 11.5 2.1 79.8 8.8 9.2 100.0 2.4 444 Residence Urban 8.0 4.7 82.2 6.5 6.6 100.0 1.4 839 Rural 3.7 3.8 85.2 7.7 3.3 100.0 0.4 1,034 Region Zambezi 5.7 1.8 89.2 4.9 4.2 100.0 1.5 88 Erongo 4.7 2.7 86.5 7.5 3.4 100.0 1.3 143 Hardap 19.4 5.9 71.6 8.3 14.2 100.0 5.2 86 //Karas 9.5 5.8 82.9 3.6 7.6 100.0 1.9 89 Kavango 0.7 4.4 84.3 10.6 0.7 100.0 0.0 159 Khomas 6.3 6.4 82.5 5.4 5.7 100.0 0.6 261 Kunene 11.0 6.7 81.3 4.4 7.7 100.0 3.2 68 Ohangwena 6.6 3.1 83.0 7.4 6.6 100.0 0.0 207 Omaheke 2.9 6.2 81.0 10.6 2.1 100.0 0.7 63 Omusati 2.6 5.1 85.5 7.3 2.1 100.0 0.5 265 Oshana 6.5 1.7 83.4 8.5 6.5 100.0 0.0 147 Oshikoto 3.1 3.6 88.6 4.7 3.1 100.0 0.0 161 Otjozondjupa 4.9 2.5 83.3 9.8 4.3 100.0 0.6 135 Education No education 5.1 5.3 81.7 8.3 4.7 100.0 0.3 248 Primary 5.1 4.3 84.2 6.8 4.6 100.0 0.4 660 Secondary 5.8 4.1 85.1 6.1 4.7 100.0 1.1 803 More than secondary 7.3 2.8 81.0 10.9 5.3 100.0 2.0 149 Wealth quintile Lowest 1.5 4.8 86.0 7.7 1.5 100.0 0.0 394 Second 3.6 5.3 84.7 6.4 3.6 100.0 0.0 362 Middle 4.2 3.7 86.2 6.3 3.8 100.0 0.4 356 Fourth 9.4 3.3 82.6 6.5 7.6 100.0 1.8 393 Highest 9.3 3.9 79.8 8.8 7.5 100.0 1.8 369 50-64 6.5 4.8 81.4 8.8 5.0 100.0 1.5 717 Total 35-64 5.6 4.2 83.8 7.1 4.8 100.0 0.8 1,873 Note: Total includes 12 women with missing information on education. 1 An individual was classified as having diabetes if he/she had a fasting plasma glucose of 7 mmol/L or above at the time of the survey or was currently taking medication to manage diabetes. The term “diabetes” as used in this table is not meant to be a clinical diagnosis of the disease; rather, it provides an indication of the disease burden in the population at the time of the survey. 2 Body mass index is expressed as the ratio of weight in kilograms to the square of height in metres (kg/m2). 252 • Blood Pressure and Blood Glucose Table 17.7.2 Prevalence of diabetes by socioeconomic characteristics: Men Among men age 35-64, prevalence of diabetes, percent distribution by fasting plasma glucose (FPG) values, and percentage with normal fasting plasma glucose level and taking medication, according to selected background characteristics, Namibia 2013 Prevalence of diabetes1 Fasting plasma glucose values Total Normal FPG and taking medicine Number of men Background characteristic <3.9 mmol/L (below normal) 3.9-6.0 mmol/L (normal) 6.1-6.9 mmol/L (prediabetic) ≥7 mmol/L (elevated) Age 35-39 4.2 9.0 83.2 3.6 4.2 100.0 0.0 308 40-44 5.2 10.2 80.1 5.5 4.3 100.0 0.9 269 45-49 2.9 6.2 83.5 8.1 2.3 100.0 0.7 214 50-54 12.3 8.2 72.2 8.9 10.8 100.0 1.5 163 55-59 8.1 14.2 72.4 9.5 3.9 100.0 4.2 136 60-64 13.3 7.7 77.3 4.9 10.1 100.0 3.1 131 Nutritional status2 Thin (BMI <18.5) 4.3 12.5 77.3 6.2 4.0 100.0 0.3 192 Normal (BMI 18.5-24.9) 3.6 9.5 81.9 5.6 3.0 100.0 0.6 674 Overweight (BMI 25-29.9) 11.1 8.2 78.2 4.2 9.4 100.0 1.7 221 Obese (BMI ≥30.0) 19.0 3.4 69.5 13.6 13.5 100.0 5.5 121 Residence Urban 8.4 9.3 78.0 6.3 6.3 100.0 2.1 608 Rural 4.9 8.9 80.5 6.2 4.4 100.0 0.6 613 Region Zambezi 4.4 13.2 80.5 5.3 1.1 100.0 3.3 52 Erongo 8.2 6.2 82.0 6.2 5.6 100.0 2.6 146 Hardap 14.4 12.0 71.6 6.5 9.9 100.0 4.4 76 //Karas 7.0 5.3 81.2 7.2 6.3 100.0 0.7 68 Kavango 3.1 5.8 84.8 6.3 3.1 100.0 0.0 103 Khomas 7.5 11.2 75.1 8.2 5.5 100.0 2.0 187 Kunene 6.7 10.9 75.9 7.3 5.9 100.0 0.8 45 Ohangwena 4.6 7.6 78.5 9.3 4.6 100.0 0.0 73 Omaheke 3.5 6.5 83.4 7.0 3.2 100.0 0.4 64 Omusati 6.1 11.3 79.9 3.8 5.0 100.0 1.1 110 Oshana 4.0 11.3 79.0 7.2 2.4 100.0 1.6 75 Oshikoto 8.7 7.0 79.0 5.3 8.7 100.0 0.0 102 Otjozondjupa 5.9 10.8 80.2 3.1 5.9 100.0 0.0 120 Education No education 1.7 8.4 84.3 5.6 1.7 100.0 0.0 212 Primary 4.9 10.3 79.0 6.7 4.0 100.0 0.9 376 Secondary 8.2 9.3 79.1 4.5 7.2 100.0 1.1 509 More than secondary 14.6 6.3 70.9 14.2 8.5 100.0 6.1 118 Wealth quintile Lowest 5.1 9.0 81.3 5.2 4.5 100.0 0.5 213 Second 1.2 12.2 78.5 8.1 1.2 100.0 0.0 208 Middle 4.6 8.8 84.0 3.2 4.0 100.0 0.6 248 Fourth 6.9 8.0 81.9 4.4 5.7 100.0 1.1 283 Highest 13.8 8.2 71.0 10.7 10.1 100.0 3.8 269 50-64 11.3 9.9 73.8 7.9 8.4 100.0 2.9 431 Total 35-64 6.7 9.1 79.3 6.3 5.3 100.0 1.3 1,221 Note: Total includes 7 men with missing information on education. 1 An individual was classified as having diabetes if he/she had a fasting plasma glucose of 7 mmol/L or above at the time of the survey or was currently taking medication to manage diabetes. The term “diabetes” as used in this table is not meant to be a clinical diagnosis of the disease; rather, it provides an indication of the disease burden in the population at the time of the survey. 2 Body mass index is expressed as the ratio of weight in kilograms to the square of height in metres (kg/m2). Other Health Issues • 253 OTHER HEALTH ISSUES 18 healthy population is an end in itself, along with being one of the most basic requirements for quality of life and a basic foundation for a country’s economic growth and development. It is important for the population to live a healthy lifestyle, free from communicable and noncommunicable diseases and free from use of destructive substances. Healthy eating habits and positive mental health are also associated with improved health outcomes. Around the world, whether in developed or developing countries, the rapid increases in noncommunicable diseases such as diabetes, cardiovascular diseases, and cancer are becoming a challenge in achieving global progress. Namibia, similar to other countries that are in an epidemiological transition, is experiencing an increase in noncommunicable diseases, obesity, and other conditions associated with urbanisation and modern, less active lifestyles, combined with new and reemerging infectious diseases such as HIV/AIDS and sexually transmitted infections. This imposes a double burden on the country, with Namibia facing exposure to diseases characteristic of both developed and developing societies. This chapter presents information on adult health issues in Namibia such as cancer screening, knowledge of and attitudes concerning tuberculosis, fruit and vegetable consumption, mental health, use of tobacco and alcohol, and health insurance coverage. 18.1 KNOWLEDGE OF AND ATTITUDES TOWARD TUBERCULOSIS Tuberculosis (TB) is a communicable disease that is of public health concern in Namibia. Since TB primarily affects economically productive age groups, it has a negative socioeconomic impact on individuals, families, and society at large (Ministry of Health and Social Services [MoHSS], 2010d). TB is caused by Mycobacterium tuberculosis, whose transmission is mainly airborne through droplets coughed or sneezed out by infected persons. The infection is primarily concentrated in the lungs, but in some cases it can be transmitted to other areas of the body. With a case notification rate of 529 cases per 100,000 inhabitants in 2012, Namibia continues to experience TB in epidemic proportions (MoHSS, 2013a). Namibia developed the Second Medium Term Strategic Plan (MTP) for Tuberculosis and Leprosy A Key Findings • Knowledge of tuberculosis (TB) among women and men age 15-49 is nearly universal (99 percent and 98 percent, respectively). • Eighty-six percent of women and 81 percent of men age 15-49 correctly responded that TB is spread through the air by coughing. • Thirty percent of women and 31 percent of men would want to keep a family member’s TB status a secret. • Only 4 percent of women age 15-49 smoke cigarettes, as compared with 19 percent of men. • Forty-four percent of women and 62 percent of men age 15-49 always use seatbelts, whereas 20 percent of young women and 13 percent of young men age 15-19 never use seatbelts. • Five percent of women and 12 percent of men age 15-49 are physically active at work, while 16 percent of women and 32 percent of men engage in non-work-related physical activity. • Most men who are physically active exercise five to seven days each week in both urban and rural areas. 254 • Other Health Issues covering the period 2010-2015; this plan focuses on fighting TB through prevention and treatment efforts at the national, regional, and district levels. Namibia’s first drug resistance TB survey, conducted in 2008, showed a multidrug-resistant TB prevalence of 4 percent among patients who had not previously been treated for TB and 17 percent among those who had previously received at least one month of TB treatment. If the second MTP is to succeed, it is vital that the strategies put in place also address community knowledge and attitudes. The 2013 NDHS collected information from women and men age 15–64 on knowledge of and attitudes toward TB. Specifically, respondents were asked whether they had ever heard of the illness, how it spreads from one person to another, whether it can be cured, and whether they would want to keep the information secret if a member of their family contracted TB. This information is useful in policy formulation and implementation of programmes designed to combat and limit the spread of the disease and address issues of discrimination. The findings are presented in Tables 18.1.1 and 18.1.2. Table 18.1.1 Knowledge of 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, according to background characteristics, Namibia 2013 All women Women who have heard of TB Background characteristic Percentage who have heard of TB Number of women Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member’s TB kept secret Number of women Age 15-19 98.2 1,906 82.0 86.9 40.1 1,871 20-24 98.7 1,786 86.0 92.9 28.9 1,763 25-29 99.2 1,489 86.3 95.2 28.9 1,477 30-34 99.2 1,260 88.3 96.2 27.1 1,250 35-39 98.7 1,110 85.0 96.2 26.3 1,096 40-44 98.8 917 87.5 96.6 22.6 906 45-49 99.8 708 85.6 95.0 24.2 707 50-54 99.0 797 78.8 94.4 25.4 789 Residence Urban 98.7 5,503 89.0 95.4 25.9 5,432 Rural 99.1 4,470 80.0 91.2 33.6 4,427 Region Zambezi 97.2 494 85.2 92.8 45.5 480 Erongo 99.5 820 90.3 96.3 19.1 815 Hardap 97.7 341 89.5 88.5 27.5 333 //Karas 99.2 374 91.3 96.7 27.8 371 Kavango 99.0 913 84.4 88.8 48.4 905 Khomas 97.9 2,317 89.8 95.7 28.0 2,269 Kunene 98.6 286 84.0 92.3 23.2 282 Ohangwena 99.8 974 72.0 93.9 28.9 971 Omaheke 98.7 249 88.5 93.3 24.4 246 Omusati 99.6 1,013 77.9 91.5 24.8 1,009 Oshana 99.5 822 82.6 95.7 24.5 818 Oshikoto 99.4 774 84.4 93.6 34.4 769 Otjozondjupa 98.9 596 89.7 89.6 21.4 590 Education No education 96.7 572 69.3 84.0 33.8 554 Primary 98.8 2,168 77.7 90.0 37.4 2,141 Secondary 99.1 6,238 87.5 95.0 27.9 6,180 More than secondary 98.9 995 93.6 97.0 18.3 985 Wealth quintile Lowest 98.8 1,614 75.4 89.3 40.4 1,595 Second 98.6 1,776 80.4 92.0 33.7 1,751 Middle 98.6 1,927 83.4 93.3 29.9 1,901 Fourth 99.0 2,285 88.7 95.4 25.2 2,263 Highest 99.1 2,371 92.6 95.8 22.0 2,349 Total 15-49 98.8 9,176 85.5 93.4 29.7 9,070 50-64 99.0 797 78.8 94.4 25.4 789 Other Health Issues • 255 Table 18.1.2 Knowledge of and attitudes concerning tuberculosis: Men Percentage of men age 15-49 who have heard of tuberculosis (TB), and among men who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who would want to keep secret that a family member has TB, according to background characteristics, Namibia 2013 All men Men who have heard of TB Background characteristic Percentage who have heard of TB Number of men Percentage who report that TB is spread through the air by coughing Percentage who believe that TB can be cured Percentage who would want a family member’s TB kept secret Number of men Age 15-19 97.6 922 77.7 88.9 40.4 900 20-24 98.4 808 81.4 92.4 34.6 795 25-29 98.1 658 81.7 96.4 29.0 646 30-34 98.0 520 82.2 94.7 22.8 510 35-39 98.9 448 83.2 97.2 23.9 443 40-44 98.0 376 84.2 96.4 31.1 368 45-49 99.4 289 83.8 96.1 25.9 287 Residence Urban 98.3 2,282 86.3 95.3 31.1 2,243 Rural 98.2 1,739 74.8 91.7 31.6 1,707 Region Zambezi 98.0 218 83.4 84.2 37.0 213 Erongo 97.9 372 90.7 95.8 19.3 364 Hardap 99.2 152 77.8 81.6 32.8 151 //Karas 93.2 151 84.5 92.5 25.0 141 Kavango 98.8 316 93.1 94.3 11.8 312 Khomas 98.2 1,023 85.1 97.1 34.0 1,004 Kunene 95.0 104 83.2 94.2 41.3 99 Ohangwena 99.6 328 63.7 97.2 34.5 327 Omaheke 98.5 103 91.1 96.3 45.1 102 Omusati 98.9 342 67.2 92.7 32.1 338 Oshana 99.0 335 79.9 93.6 26.0 331 Oshikoto 99.0 335 74.3 92.0 29.8 332 Otjozondjupa 97.2 241 85.6 90.6 56.8 234 Education No education 96.8 310 67.0 91.0 28.8 300 Primary 97.3 944 72.2 90.2 35.0 918 Secondary 98.8 2,400 85.2 95.1 31.6 2,372 More than secondary 97.9 368 91.4 96.4 22.3 360 Wealth quintile Lowest 97.6 594 71.4 91.7 28.9 580 Second 98.1 769 77.5 91.8 32.8 754 Middle 98.6 886 78.0 93.7 31.8 874 Fourth 98.9 917 83.8 94.8 30.7 906 Highest 97.7 855 92.5 95.8 31.9 835 Total 15-49 98.2 4,021 81.3 93.7 31.3 3,950 50-64 97.7 460 83.8 96.7 26.0 449 Nearly all women and men have heard of TB. Eighty-six percent of women and 81 percent of men age 15-49 correctly responded that TB is spread through the air by coughing. A lower proportion of women age 50-64 (79 percent) responded that TB is spread through the air by coughing, when compared with men in the same age group (84 percent). Knowledge increases with education and wealth among both women and men. For example, seven in ten women and men age 15-49 with no education report that TB is spread through the air by coughing, compared with more than nine in ten women and men with more than a secondary education. More than 90 percent of both women and men believe that TB can be cured, with small differences across subgroups. When asked whether they would want to keep a family member’s TB status a secret, 30 percent of women and 31 percent of men age 15-49 responded that they would. This is a noticeable increase since the 2006-07 NDHS survey, when 15 percent of women and 18 percent of men reported that they would want to keep a family member’s TB status a secret. Fear of discrimination is highest among young women and men age 15-19. 18.2 CANCER SCREENING 18.2.1 Breast Cancer and Cervical Cancer Screening Breast self-examination (BSE) for cancer is a very important part of every adult woman’s personal health regimen. BSE should be performed monthly beginning at age 20 and should continue each month 256 • Other Health Issues throughout a woman’s lifetime. In addition to BSE, adult women should undergo regular clinical breast examinations performed by a health professional. Table 18.2 shows the percentage of women who have performed a breast cancer self-exam or had an exam by a health professional (doctor or nurse/midwife). Questions on BSE and clinical breast exams were included for the first time in the 2013 NDHS. About one-third of women (33 percent) age 15-49 have ever had a breast cancer examination; 31 percent have performed a self-exam, and 23 percent have had a clinical exam. Women age 45-49, those who have 3-4 children, women who are divorced, separated, or widowed, those with more than a secondary education, and those in the highest wealth quintile are more likely to have performed a breast cancer self-exam or to have had an examination by a health professional than other women. Thirty nine percent of women in urban areas have ever had a breast cancer self-exam compared with 18 percent of women in rural areas. More than half of the women in Erongo (52 percent) have ever had a breast cancer self-exam compared with only one in ten women in Kavango. The 2013 NDHS also included questions on cervical cancer screening. The Pap test checks for changes in the cells of the cervix (the lower part of the uterus/womb that opens into the birth canal) that show cervical cancer or conditions that may develop into cervical cancer. Pre-cancerous changes are usually caused by the sexually transmitted human papillomavirus (HPV). The Pap test aims to detect and prevent the progression of HPV-induced cervical cancer and other abnormalities in the female genital tract. If detected early, cervical cancer can be cured. All women who are age 21 or older or who are sexually active should have an annual Pap test. During the survey, all women age 15-64 were asked whether they had ever heard of cervical cancer and whether they had had an exam for cervical cancer. Women who reported having had a cervical cancer exam were asked about the type of exam they had. Table 18.2 shows that 66 percent of women age 15-49 have heard of cervical cancer and 25 percent have had a cervical cancer exam. Women age 35 and older, those with 3-4 children, women who are married or living together with a partner, urban women and those living in Oshana, women with more than a secondary education, and those in the highest wealth quintile are more likely than their counterparts in the other categories to have had a cervical cancer exam. Other Health Issues • 257 Table 18.2 Breast cancer examination and cervical cancer examination or test Percentage of women age 15-49 who have ever performed a breast cancer self-examination or had an examination by a health professional, percentage who have heard of cervical cancer, and percentage who have ever had a cervical cancer test or examination by type, according to background characteristics, Namibia 2013 Ever had a breast cancer self-examina- tion Ever had a breast cancer examina- tion by a health profes- sional Ever had a breast cancer self- examination or examination by a health professional Ever heard of cervical cancer Ever had a cervical cancer examination Number of women Type of test or examination for cervical cancer Background characteristic Pap test Visual inspection with acetic acid Don’t know/ unsure Number of women Age 15-19 13.7 6.7 14.8 44.3 2.8 1,906 69.1 9.6 20.2 54 20-24 26.3 17.2 28.4 64.1 15.2 1,786 89.6 1.0 9.4 271 25-29 32.7 25.0 35.2 69.8 27.2 1,489 92.0 1.5 7.0 405 30-34 37.2 29.8 40.9 71.7 34.6 1,260 93.2 2.6 5.0 436 35-39 40.4 32.4 42.5 75.1 40.4 1,110 92.2 2.8 5.1 449 40-44 41.2 35.4 44.3 76.8 44.4 917 96.4 2.7 1.7 407 45-49 42.3 33.6 44.2 77.8 43.6 708 96.6 1.5 2.8 309 Number of living children 0 20.8 12.5 21.7 57.9 10.0 3,034 87.8 6.0 6.4 304 1-2 35.3 28.1 38.3 69.2 32.0 3,606 93.4 1.9 5.6 1,153 3-4 37.6 30.3 40.9 71.6 36.7 1,750 94.6 1.6 3.7 643 5+ 31.7 23.3 33.6 65.4 29.5 785 91.3 1.5 7.7 232 Marital status Never married 25.4 17.6 27.3 64.3 19.7 5,458 91.5 2.3 7.1 1,077 Married or living together 38.2 30.4 40.9 67.2 34.3 3,121 94.0 2.6 3.6 1,071 Divorced/separated/ widowed 39.2 33.1 41.9 68.5 30.8 597 93.6 0.7 5.9 184 Residence Urban 38.5 29.7 41.3 72.4 30.2 5,190 94.1 2.5 4.0 1,567 Rural 20.5 14.2 21.9 56.7 19.2 3,986 90.1 1.9 8.1 764 Region Zambezi 27.2 12.7 29.6 55.6 9.4 457 93.0 3.7 5.6 43 Erongo 51.9 29.2 53.8 77.5 32.2 771 98.3 0.0 1.7 248 Hardap 36.5 18.1 38.7 63.2 23.8 304 97.3 8.8 0.0 72 //Karas 46.1 30.6 47.8 79.8 29.5 343 94.9 1.8 3.8 101 Kavango 10.4 11.6 12.8 9.7 3.0 835 77.6 * * * Khomas 41.7 37.3 44.8 75.4 33.3 2,202 94.1 3.6 3.5 734 Kunene 38.1 19.5 42.1 64.6 23.2 258 99.3 0.7 0.0 60 Ohangwena 14.9 10.5 17.0 65.0 21.2 894 77.4 1.1 20.5 189 Omaheke 44.8 27.5 47.3 65.6 30.9 225 98.3 1.1 0.6 70 Omusati 17.7 12.9 18.4 74.1 28.4 884 94.7 0.5 4.8 251 Oshana 23.8 16.0 25.1 86.6 35.0 755 92.6 1.6 5.2 264 Oshikoto 25.0 24.0 25.8 55.6 21.0 707 86.4 2.4 11.2 148 Otjozondjupa 31.0 24.7 35.5 67.0 23.2 540 94.2 1.6 4.2 125 Education No education 17.2 12.5 19.2 45.8 15.3 419 92.5 7.3 6.5 64 Primary 20.8 15.1 22.6 49.0 18.3 1,798 89.5 0.8 9.8 329 Secondary 31.3 22.7 33.7 68.0 24.8 6,029 92.7 2.2 5.3 1,498 More than secondary 51.5 44.1 54.1 90.9 47.3 930 95.6 3.0 2.0 440 Wealth quintile Lowest 14.8 10.2 16.1 43.9 11.9 1,429 84.2 0.5 15.3 170 Second 22.4 16.0 23.6 57.6 20.8 1,625 90.2 1.5 8.4 338 Middle 27.6 20.2 30.2 65.2 24.0 1,795 91.3 2.3 6.6 430 Fourth 32.8 23.9 35.8 71.1 27.7 2,116 95.4 2.1 3.8 586 Highest 47.4 37.5 50.0 80.5 36.5 2,211 94.7 3.2 2.6 807 Total 15-64 30.6 22.9 32.9 65.6 25.4 9,176 92.8 2.3 5.4 2,331 50-64 35.2 28.0 36.9 69.2 35.9 797 91.1 2.5 6.2 286 Note: An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Among women age 15-49 who have had a cervical cancer exam, the vast majority (93 percent) have had a Pap test; 2 percent have had a visual exam with acetic acid. 18.2.2 Prostate Cancer Screening Prostate cancer starts in the prostate gland, which is a small, walnut-sized structure that makes up part of a man’s reproductive system. Prostate cancer can be detected through a digital rectal exam. Also, the blood level of prostate-specific antigen (PSA), a protein that is produced by the prostate, can be tested. 258 • Other Health Issues All men age 40-64 were asked whether they had ever heard of prostate cancer. Men who had heard of prostate cancer were also asked if they had ever had a prostate cancer test or exam. Table 18.3 shows that 64 percent of men age 40-64 have heard of prostate cancer. Men age 50-54, urban men, men in Omaheke, those with more than a secondary education, and men in the highest wealth quintile are most likely to have heard of prostate cancer. Twenty-seven percent of men 40- 64 reported that they have had a test or exam for prostate cancer. This percentage increases with age, from 23 percent among men age 40-44 to 31 percent among men age 55-64. Urban men are nearly twice as likely as rural men to report having had a test or exam (29 percent versus 17 percent). Forty-two percent of men in //Karas report having had a test or exam for prostate cancer, as compared with 10 percent of men in Kunene. The percentage of men who have had a prostate cancer test or exam increases with increasing education and wealth. Men with more than a secondary education are nearly seven times as likely as men with no education to have had a test or exam (40 percent compared with 6 percent). Similarly, men in the highest wealth quintile are more than three times as likely as men in the lowest quintile to report having had a test or exam for prostate cancer. 18.3 USE OF TOBACCO Smoking has a powerful negative impact on population health. Smoking is a known risk factor for cardiovascular disease; it causes lung cancer and other forms of cancer and contributes to the severity of pneumonia, emphysema, and chronic bronchitis. It may also have an impact on individuals who are exposed to secondhand smoke. For example, inhaling secondhand smoke may adversely affect children’s growth and cause childhood illnesses, especially respiratory diseases. Because smoking is an acquired behaviour, all morbidity and mortality caused by smoking is preventable. On 29 May 2007 in Geneva, the World Health Organization (WHO) signalled the urgent need for countries to make all indoor public places and workplaces 100 percent smoke-free with the release of its new policy recommendations on protection from exposure to secondhand tobacco smoke.1 The Namibian government’s Tobacco Control Act (Act No. 1 of 2010) aims to control the use of tobacco products. Tobacco use is addictive, affects the health of persons of all ages, and negates the achievements gained through the programs of the Namibian Health Policy Framework. 1 http://www.who.int/mediacentre/news/releases/2007/pr26/en/ Table 18.3 Knowledge of and testing for prostate cancer Percentage of men age 40-64 who have heard of prostate cancer, and among men who have heard of prostate cancer, the percentage who have ever had an examination or test, according to background characteristics, Namibia 2013 Background characteristic Heard of prostate cancer Number of men Ever had a test/exam for prostate cancer Number of men Age 40-44 53.3 376 22.9 200 45-49 63.0 289 25.9 182 50-54 75.1 184 29.0 138 55-59 73.1 152 31.0 111 60-64 68.0 124 31.4 84 Residence Urban 10.4 2,282 28.9 237 Rural 8.4 1,739 16.8 146 Region Zambezi 6.7 218 24.1 15 Erongo 10.6 372 27.1 40 Hardap 12.7 152 20.6 19 //Karas 11.5 151 41.5 17 Kavango 7.4 316 24.4 24 Khomas 10.2 1,023 28.5 105 Kunene 7.4 104 9.7 8 Ohangwena 6.4 328 27.9 21 Omaheke 18.0 103 18.2 19 Omusati 8.2 342 16.6 28 Oshana 10.0 335 10.7 33 Oshikoto 7.1 335 15.4 24 Otjozondjupa 12.9 241 32.3 31 Education No education 9.6 310 6.3 30 Primary 10.7 944 13.3 101 Secondary 7.4 2,400 26.9 176 More than secondary 20.6 368 40.0 76 Wealth quintile Lowest 8.1 594 13.5 48 Second 6.9 769 10.4 53 Middle 6.0 886 11.0 53 Fourth 11.2 917 21.8 103 Highest 14.6 855 42.0 125 Total 40-64 63.7 1,125 27.1 716 Other Health Issues • 259 According to WHO, tobacco kills more than 6 million people worldwide each year, among whom more than 10 percent are non-users exposed to secondhand smoke. Tobacco smoking is responsible for 90 percent of lung cancer, 70 percent of chronic respiratory illnesses, and 25 percent of heart disease. More than 80 percent of the world’s smokers live in low- and middle-income countries. Because there is a lag of several years between when people start using tobacco and when their health suffers, the health consequences are not felt immediately. Women and men interviewed in the 2013 NDHS were asked about their smoking habits. Tables 18.4.1 and 18.4.2 show the percentage of women and men who smoke cigarettes or tobacco and the percent distribution of male cigarette smokers by number of cigarettes smoked in the preceding 24 hours, according to background characteristics. Due to the small numbers of female smokers, a breakdown by number of cigarettes smoked by background characteristics is not shown separately. Table 18.4.1 Use of tobacco: Women Percentage of women age 15-49 who smoke cigarettes or a pipe or use other tobacco products, and the percentage who use tobacco daily among tobacco users, according to background characteristics and maternity status, Namibia 2013 Background characteristic Uses tobacco Does not use tobacco Number of women Smokes tobacco products daily Number of women Cigarettes Pipe Other tobacco Age 15-19 1.4 0.0 0.6 98.1 1,906 (5.7) 36 20-24 3.5 0.3 0.8 96.1 1,786 13.1 70 25-29 4.4 0.3 0.9 95.1 1,489 18.4 73 30-34 4.4 0.6 1.5 94.6 1,260 33.1 68 35-39 5.5 0.2 2.0 93.1 1,110 23.4 77 40-44 7.7 0.9 3.8 89.9 917 33.4 93 45-49 5.6 0.3 3.4 92.6 708 39.9 53 Maternity status Pregnant 3.2 0.1 0.9 96.6 600 (23.3) 21 Breastfeeding (not pregnant) 4.6 0.4 1.8 94.4 1,234 25.6 69 Neither 4.2 0.3 1.5 94.8 7,342 24.9 380 Residence Urban 5.5 0.3 1.5 93.5 5,190 18.5 336 Rural 2.4 0.4 1.5 96.6 3,986 41.1 134 Region Zambezi 1.8 0.0 1.3 97.7 457 * 11 Erongo 7.1 1.1 0.5 92.2 771 14.9 60 Hardap 15.8 0.3 4.7 82.4 304 20.2 53 //Karas 12.2 0.9 3.5 87.0 343 20.5 45 Kavango 3.6 0.4 2.9 95.6 835 (45.4) 37 Khomas 4.6 0.1 1.2 94.4 2,202 12.7 123 Kunene 5.8 0.6 3.0 90.9 258 33.0 24 Ohangwena 0.5 0.3 1.0 98.5 894 * 14 Omaheke 9.1 1.0 7.2 84.3 225 42.8 35 Omusati 0.3 0.0 0.0 99.5 884 * 4 Oshana 1.5 0.0 0.0 98.5 755 * 12 Oshikoto 2.7 0.3 0.7 96.9 707 * 22 Otjozondjupa 4.8 0.3 2.9 94.3 540 (42.8) 31 Education No education 10.0 1.6 8.5 83.8 419 49.0 68 Primary 4.9 0.8 3.1 93.4 1,798 44.6 119 Secondary 3.8 0.2 0.8 95.8 6,029 12.2 255 More than secondary 2.6 0.0 0.0 97.0 930 (0.0) 28 Wealth quintile Lowest 3.4 0.7 2.6 95.4 1,429 56.9 66 Second 3.0 0.5 1.9 95.7 1,625 43.5 70 Middle 2.6 0.1 1.4 96.5 1,795 29.2 64 Fourth 5.1 0.3 1.3 94.3 2,116 17.2 121 Highest 5.9 0.1 0.9 93.3 2,211 6.6 149 Total 15-49 4.2 0.3 1.5 94.9 9,176 25.0 470 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. 26 0 • O th er H ea lth Is su es Ta bl e 18 .4 .2 U se o f t ob ac co : M en P er ce nt ag e of m en a ge 1 5- 49 w ho s m ok e ci ga re tte s or a p ip e or u se o th er to ba cc o pr od uc ts , t he p er ce nt ag e w ho u se to ba cc o da ily a m on g to ba cc o us er s, a nd th e pe rc en t d is tri bu tio n of c ig ar et te sm ok er s by n um be r o f c ig ar et te s sm ok ed in th e pr ec ed in g 24 h ou rs , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, N am ib ia 2 01 3 U se s to ba cc o D oe s no t us e to ba cc o N um be r of m en P er ce nt d is tri bu tio n of m en w ho s m ok e ci ga re tte s by n um be r o f ci ga re tte s sm ok ed in th e pa st 2 4 ho ur s To ta l N um be r of m en S m ok es to ba cc o pr od uc ts da ily N um be r o f m en B ac kg ro un d ch ar ac te ris tic C ig ar et te s P ip e O th er to ba cc o 0 1- 2 3- 5 6- 9 10 + D on ’t kn ow / m is si ng A ge 15 -1 9 5. 5 0. 5 1. 4 93 .7 92 2 10 .1 32 .4 32 .7 14 .9 6. 0 4. 0 10 0. 0 51 24 .3 58 20 -2 4 19 .7 1. 3 4. 8 79 .2 80 8 4. 3 31 .3 33 .2 15 .6 13 .2 2. 4 10 0. 0 15 9 10 .4 16 8 25 -2 9 23 .7 1. 4 5. 4 75 .2 65 8 7. 9 27 .7 37 .1 15 .0 9. 8 2. 5 10 0. 0 15 6 13 .0 16 3 30 -3 4 24 .2 1. 0 6. 0 73 .7 52 0 5. 9 25 .5 38 .4 15 .2 14 .3 0. 8 10 0. 0 12 6 9. 1 13 7 35 -3 9 23 .8 1. 1 5. 5 74 .6 44 8 3. 5 36 .4 25 .3 8. 9 22 .1 3. 9 10 0. 0 10 7 3. 9 11 4 40 -4 4 23 .1 2. 0 5. 9 72 .8 37 6 2. 3 12 .8 47 .8 18 .2 13 .9 5. 1 10 0. 0 87 10 .1 10 2 45 -4 9 22 .2 0. 6 5. 8 74 .6 28 9 5. 1 18 .8 33 .1 20 .1 20 .1 2. 8 10 0. 0 64 8. 8 73 R es id en ce U rb an 20 .1 0. 7 5. 0 78 .7 2, 28 2 4. 5 28 .0 32 .7 18 .0 14 .5 2. 4 10 0. 0 46 0 9. 0 48 7 R ur al 16 .7 1. 5 4. 0 81 .1 1, 73 9 6. 9 25 .9 39 .6 10 .6 13 .5 3. 5 10 0. 0 29 0 13 .0 32 9 R eg io n Za m be zi 32 .4 0. 4 6. 9 67 .6 21 8 7. 4 29 .7 38 .2 10 .0 13 .9 0. 9 10 0. 0 71 1. 2 71 E ro ng o 19 .5 1. 3 2. 4 78 .9 37 2 2. 1 32 .4 33 .1 13 .2 19 .1 0. 0 10 0. 0 72 13 .3 78 H ar da p 38 .6 0. 7 13 .0 58 .6 15 2 3. 9 23 .9 42 .9 16 .4 11 .5 1. 4 10 0. 0 59 19 .4 63 //K ar as 29 .0 2. 2 13 .5 64 .4 15 1 6. 3 29 .6 31 .5 13 .2 18 .3 1. 0 10 0. 0 44 13 .2 54 K av an go 19 .5 0. 8 3. 1 78 .7 31 6 3. 8 26 .3 47 .3 11 .0 10 .2 1. 4 10 0. 0 62 12 .0 67 K ho m as 17 .1 1. 0 5. 0 81 .7 1, 02 3 4. 0 29 .6 28 .2 22 .9 15 .4 0. 0 10 0. 0 17 5 2. 6 18 7 K un en e 34 .8 1. 3 7. 5 62 .4 10 4 4. 1 14 .3 41 .2 17 .3 17 .2 6. 0 10 0. 0 36 10 .9 39 O ha ng w en a 7. 7 1. 4 1. 2 90 .4 32 8 * * * * * * 10 0. 0 25 * 32 O m ah ek e 35 .9 3. 3 11 .1 61 .6 10 3 1. 9 15 .6 51 .6 18 .6 12 .3 0. 0 10 0. 0 37 22 .4 40 O m us at i 7. 1 1. 3 1. 6 92 .5 34 2 * * * * * * 10 0. 0 24 * 26 O sh an a 10 .9 0. 0 0. 5 89 .1 33 5 (4 .0 ) (1 8. 0) (4 2. 9) (1 8. 8) (1 3. 5) (2 .8 ) 10 0. 0 36 (0 .0 ) 36 O sh ik ot o 11 .7 1. 4 3. 8 85 .6 33 5 (2 1. 4) (3 2. 7) (2 9. 6) (8 .9 ) (4 .3 ) (3 .0 ) 10 0. 0 39 (1 3. 4) 48 O tjo zo nd ju pa 28 .8 0. 9 5. 8 69 .0 24 1 0. 7 21 .6 30 .3 13 .5 15 .6 18 .3 10 0. 0 69 12 .7 75 Ed uc at io n N o ed uc at io n 20 .4 3. 1 7. 7 73 .5 31 0 6. 6 28 .3 43 .4 12 .1 5. 4 4. 2 10 0. 0 63 19 .4 82 P rim ar y 18 .6 1. 5 5. 4 79 .1 94 4 6. 4 25 .0 35 .6 16 .9 12 .4 3. 8 10 0. 0 17 6 13 .1 19 7 S ec on da ry 19 .3 0. 7 4. 3 79 .7 2, 40 0 4. 6 28 .1 35 .6 15 .1 14 .3 2. 2 10 0. 0 46 4 9. 0 48 6 M or e th an s ec on da ry 12 .7 0. 8 1. 6 86 .5 36 8 (8 .4 ) (2 4. 3) (2 1. 1) (1 2. 0) (3 1. 0) (3 .3 ) 10 0. 0 47 (1 .4 ) 50 W ea lth q ui nt ile Lo w es t 17 .5 1. 7 5. 5 79 .1 59 4 8. 2 32 .4 36 .2 12 .5 9. 0 1. 7 10 0. 0 10 4 12 .4 12 4 S ec on d 18 .2 1. 6 4. 8 79 .2 76 9 7. 2 25 .3 38 .7 15 .7 11 .6 1. 5 10 0. 0 14 0 18 .4 16 0 M id dl e 15 .4 0. 5 2. 9 83 .9 88 6 4. 0 26 .5 41 .0 11 .5 12 .8 4. 2 10 0. 0 13 7 18 .5 14 3 Fo ur th 22 .4 0. 7 6. 4 76 .8 91 7 4. 7 23 .0 35 .8 20 .1 12 .4 4. 0 10 0. 0 20 6 5. 2 21 3 H ig he st 19 .1 1. 2 3. 4 79 .4 85 5 4. 2 31 .2 26 .7 13 .0 22 .8 2. 0 10 0. 0 16 3 2. 5 17 6 To ta l 1 5- 49 18 .6 1. 1 4. 5 79 .7 4, 02 1 5. 4 27 .2 35 .4 15 .1 14 .1 2. 8 10 0. 0 75 0 10 .6 81 5 N ot e: F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. A n as te ris k in di ca te s th at a fi gu re is b as ed o n fe w er th an 2 5 un w ei gh te d ca se s an d ha s be en s up pr es se d. 260 • Other Health Issues Other Health Issues • 261 Only 4 percent of women age 15-49 smoke cigarettes, less than 1 percent smoke a pipe, and 2 percent smoke other tobacco. Older women are more likely to smoke than younger women; 1 percent of women age 15-19 smoke cigarettes, as compared with 8 percent of women age 40-44. Women in the oldest age group are also more likely to use tobacco other than cigarettes or pipes, and 40 percent of women age 45-49 smoke tobacco products daily. One in six women in Hardap (16 percent) smoke cigarettes, and 5 percent use tobacco in other forms. On the other hand, 1 percent or less of women in Ohangwena and Omusati use either cigarettes or other types of tobacco. Seven percent of women in Omaheke use any type of tobacco, and 43 percent smoke tobacco products daily. Women’s level of education and wealth status are related to their propensity to smoke. Women with no education (10 percent) and women in the highest wealth quintile (6 percent) are more likely to smoke cigarettes than other women. Among women who smoke, 29 percent smoked 3-5 cigarettes in the past 24 hours, 13 percent smoked 6-9 cigarettes, and 23 percent smoked 10 or more cigarettes (data not shown separately). Smoking is more popular among urban than rural women. Table 18.4.2 shows that smoking is more common among Namibian men than women; 19 percent of men smoke cigarettes or pipe, as compared with 5 percent of women. The likelihood of a man smoking cigarettes or pipe increases with age, from 6 percent among those age 15-19 to 21-24 percent among older men. Across regions, men in Hardap are most likely to smoke cigarettes or pipe (39 percent) and men in Omusati least likely (8 percent). There is little variation in tobacco use among men by residence, level of education, or wealth quintile. Among men who smoke cigarettes, 27 percent smoked 1-2 cigarettes, 35 percent smoked 3-5 cigarettes, 15 percent smoked 6-9 cigarettes, and 14 percent smoked 10 or more cigarettes within the past 24 hours. Heavy smoking (10 cigarettes or more in the past 24 hours) is more prevalent among men age 35-39 (22 percent) than among men age 15-19 (6 percent). The proportion of men who smoke cigarettes is relatively higher in Hardap than in the other regions (39 percent). However, only 12 percent of smokers in Hardap smoked 10 or more cigarettes in the past 24 hours, with the majority (43 percent) smoking 3-5 cigarettes. Tobacco use among men varies somewhat by wealth status. For example, men in the lowest wealth quintile are least likely to have smoked 10 or more cigarettes in the past 24 hours (9 percent), and men in the highest wealth quintile are most likely to have done so (23 percent). Average ages at first use among tobacco users are 21 years for men and 34 years for women (data not shown separately). 18.4 ALCOHOL CONSUMPTION Tables 18.5.1 and 18.5.2 show the percentage of respondents age 15-49 who had ever consumed alcoholic drinks and the percent distribution by the number of days they had consumed alcohol in the last two weeks, according to background characteristics. One in two women (50 percent) and almost three in five men age 15-49 (57 percent) reported drinking alcohol at some point in their lives. Women age 25-39 are more likely to have ever consumed alcohol than women in the other age groups. Two in three women (68 percent) in Oshikoto report that they have ever consumed alcohol. Women with more than a secondary education (63 percent) and those in the highest wealth quintile are more likely than their counterparts in the other categories to report ever having consumed alcohol. The percentage of men who have ever consumed alcoholic drinks is highest among those age 25-29 (66 percent), among men in Oshana (80 percent), those with more than a secondary education (68 percent), and among men in the highest wealth quintile (60 percent). 26 2 • O th er H ea lth Is su es Ta bl e 18 .5 .1 U se o f a lc oh ol : W om en P er ce nt ag e of w om en a ge 1 5- 49 w ho h av e ev er c on su m ed a lc oh ol , t he p er ce nt d is tri bu tio n of a lc oh ol u se rs b y nu m be r of d ay s at le as t o ne a lc oh ol ic d rin k w as c on su m ed in th e pr ec ed in g tw o w ee ks , a nd th e pe rc en t di st rib ut io n of a lc oh ol u se rs b y nu m be r o f d rin ks c on su m ed in th e pr ec ed in g tw o w ee ks , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s an d m at er ni ty s ta tu s, N am ib ia 2 01 3 E ve r c on su m ed al co ho l N um be r o f w om en N um be r o f d ay s co ns um ed a lc oh ol in th e pa st tw o w ee ks To ta l N um be r o f w om en N um be r o f d rin ks c on su m ed p er d ay To ta l N um be r o f w om en B ac kg ro un d ch ar ac te ris tic 0 1- 2 3- 4 5+ D on ’t kn ow / m is si ng 1- 2 3- 4 5+ D on ’t kn ow / m is si ng A ge 15 -1 9 36 .9 1, 90 6 75 .1 15 .6 5. 6 2. 9 0. 8 10 0. 0 70 4 52 .7 28 .4 14 .5 4. 5 10 0. 0 17 0 20 -2 4 52 .8 1, 78 6 54 .4 30 .7 7. 2 5. 5 2. 1 10 0. 0 94 3 45 .2 22 .0 24 .9 7. 9 10 0. 0 41 0 25 -2 9 54 .2 1, 48 9 48 .1 30 .4 9. 7 8. 7 3. 1 10 0. 0 80 7 45 .1 24 .5 24 .1 6. 3 10 0. 0 39 4 30 -3 4 53 .6 1, 26 0 47 .5 28 .2 11 .3 9. 6 3. 4 10 0. 0 67 5 44 .6 22 .8 18 .6 14 .1 10 0. 0 33 1 35 -3 9 54 .4 1, 11 0 54 .3 24 .7 9. 6 10 .2 1. 3 10 0. 0 60 4 45 .7 28 .0 20 .6 5. 8 10 0. 0 26 8 40 -4 4 50 .5 91 7 47 .3 24 .1 11 .5 13 .1 4. 1 10 0. 0 46 3 39 .3 21 .4 25 .0 14 .3 10 0. 0 22 5 45 -4 9 49 .4 70 8 46 .8 29 .7 9. 9 10 .0 3. 6 10 0. 0 35 0 46 .3 26 .1 18 .6 9. 0 10 0. 0 17 3 50 -5 4 52 .6 79 7 52 .4 23 .0 9. 7 9. 5 5. 4 10 0. 0 42 0 51 .7 15 .8 19 .0 13 .5 10 0. 0 17 7 R es id en ce U rb an 50 .9 5, 50 3 53 .2 27 .9 8. 6 7. 0 3. 3 10 0. 0 2, 80 2 44 .1 25 .9 22 .9 7. 1 10 0. 0 1, 21 9 R ur al 48 .4 4, 47 0 55 .0 23 .8 9. 5 9. 7 2. 0 10 0. 0 2, 16 3 47 .8 20 .6 19 .5 12 .0 10 0. 0 92 9 R eg io n Za m be zi 14 .2 49 4 56 .5 21 .3 3. 3 10 .8 8. 1 10 0. 0 70 (3 8. 8) (2 2. 0) (2 0. 9) (1 8. 3) 10 0. 0 25 E ro ng o 47 .8 82 0 47 .8 34 .6 10 .0 5. 6 2. 0 10 0. 0 39 2 39 .6 30 .3 22 .6 7. 5 10 0. 0 19 7 H ar da p 42 .4 34 1 52 .7 21 .6 11 .0 12 .8 1. 9 10 0. 0 14 5 23 .4 30 .9 36 .0 9. 7 10 0. 0 66 //K ar as 42 .7 37 4 52 .1 33 .4 8. 3 5. 2 1. 0 10 0. 0 16 0 41 .4 28 .6 28 .0 2. 0 10 0. 0 75 K av an go 36 .8 91 3 52 .7 22 .3 9. 6 14 .1 1. 3 10 0. 0 33 6 33 .7 15 .1 19 .1 32 .2 10 0. 0 15 5 K ho m as 52 .9 2, 31 7 51 .3 28 .8 8. 6 6. 7 4. 7 10 0. 0 1, 22 5 45 .2 24 .9 22 .1 7. 7 10 0. 0 53 9 K un en e 48 .2 28 6 69 .0 17 .2 8. 0 4. 4 1. 5 10 0. 0 13 8 27 .9 22 .9 37 .3 11 .9 10 0. 0 41 O ha n g w en a 54 .3 97 4 52 .8 21 .6 13 .5 7. 6 4. 5 10 0. 0 52 9 47 .5 20 .5 19 .8 12 .2 10 0. 0 22 6 O m ah ek e 46 .5 24 9 55 .5 26 .4 8. 0 8. 0 2. 1 10 0. 0 11 6 32 .1 23 .0 33 .7 11 .3 10 0. 0 49 O m us at i 58 .5 1, 01 3 55 .1 26 .7 7. 7 9. 4 1. 1 10 0. 0 59 3 56 .8 23 .7 13 .7 5. 8 10 0. 0 25 9 O sh an a 61 .8 82 2 58 .4 21 .4 9. 7 8. 5 1. 9 10 0. 0 50 8 51 .7 26 .4 19 .8 2. 0 10 0. 0 20 1 O sh ik ot o 67 .9 77 4 60 .0 24 .8 6. 1 7. 9 1. 2 10 0. 0 52 5 63 .3 16 .1 15 .4 5. 2 10 0. 0 20 4 O tjo zo nd ju pa 38 .4 59 6 48 .8 29 .5 9. 7 9. 9 2. 0 10 0. 0 22 9 33 .7 25 .1 30 .2 11 .0 10 0. 0 11 3 Ed uc at io n N o ed uc at io n 47 .2 57 2 51 .6 17 .7 12 .0 13 .1 5. 6 10 0. 0 27 0 36 .4 20 .7 16 .5 26 .4 10 0. 0 11 6 P rim ar y 46 .8 2, 16 8 52 .2 22 .2 11 .4 10 .8 3. 4 10 0. 0 1, 01 5 41 .4 20 .0 23 .0 15 .6 10 0. 0 45 1 S ec on da ry 49 .0 6, 23 8 55 .1 26 .8 8. 3 7. 5 2. 4 10 0. 0 3, 05 4 45 .8 25 .4 21 .6 7. 2 10 0. 0 1, 30 0 M or e th an s ec on da ry 62 .8 99 5 52 .6 32 .9 7. 6 4. 6 2. 3 10 0. 0 62 5 56 .2 22 .5 20 .1 1. 2 10 0. 0 28 2 M at er ni ty s ta tu s P re gn an t 51 .1 60 0 69 .8 18 .0 5. 5 4. 9 1. 7 10 0. 0 30 7 54 .2 21 .5 16 .7 7. 7 10 0. 0 87 B re as tfe ed in g (n ot p re gn an t) 49 .4 1, 23 4 55 .7 23 .5 10 .2 9. 0 1. 6 10 0. 0 61 0 41 .6 20 .7 24 .7 13 .0 10 0. 0 26 0 N ei th er 49 .7 8, 13 9 52 .5 27 .1 9. 1 8. 2 3. 0 10 0. 0 4, 04 8 45 .9 24 .1 21 .2 8. 8 10 0. 0 1, 80 1 W ea lth q ui nt ile Lo w es t 46 .5 1, 61 4 49 .6 21 .8 10 .0 15 .3 3. 4 10 0. 0 75 1 41 .0 19 .8 18 .8 20 .5 10 0. 0 35 4 S ec on d 46 .7 1, 77 6 55 .1 23 .9 10 .6 7. 5 2. 9 10 0. 0 83 0 46 .5 25 .0 19 .3 9. 2 10 0. 0 34 8 M id dl e 50 .1 1, 92 7 56 .4 25 .8 9. 1 6. 7 2. 0 10 0. 0 96 6 48 .5 23 .3 20 .7 7. 5 10 0. 0 40 2 Fo ur th 48 .8 2, 28 5 54 .2 25 .9 8. 9 8. 6 2. 4 10 0. 0 1, 11 6 40 .4 26 .4 25 .4 7. 8 10 0. 0 48 5 H i g he st 54 .9 2, 37 1 53 .9 30 .4 7. 5 5. 1 3. 1 10 0. 0 1, 30 1 50 .9 22 .9 21 .6 4. 6 10 0. 0 56 0 To ta l 1 5- 49 49 .5 9, 17 6 54 .1 26 .4 9. 0 8. 0 2. 5 10 0. 0 4, 54 5 45 .2 24 .3 21 .7 8. 8 10 0. 0 1, 97 1 50 -6 4 52 .6 79 7 52 .4 23 .0 9. 7 9. 5 5. 4 10 0. 0 42 0 51 .7 15 .8 19 .0 13 .5 10 0. 0 17 7 N ot e: F ig ur es in p ar en th es es a re b as ed o n 25 -4 9 un w ei gh te d ca se s. 262 • Other Health Issues O th er H ea lth Is su es • 2 63 Ta bl e 18 .5 .2 U se o f a lc oh ol : M en P er ce nt ag e of m en a ge 1 5- 49 w ho h av e ev er c on su m ed a lc oh ol , t he p er ce nt d is tri bu tio n of a lc oh ol u se rs b y nu m be r of d ay s at le as t o ne a lc oh ol ic d rin k w as c on su m ed in th e pr ec ed in g tw o w ee ks , a nd th e pe rc en t d is tri bu tio n of a lc oh ol u se rs b y nu m be r o f d rin ks c on su m ed in th e pr ec ed in g tw o w ee ks , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, N am ib ia 2 01 3 E ve r c on su m ed al co ho l N um be r o f m en N um be r o f d ay s co ns um ed a lc oh ol in th e pa st tw o w ee ks To ta l N um be r o f m en N um be r o f d rin ks c on su m ed pe r d ay To ta l N um be r o f m en B ac kg ro un d ch ar ac te ris tic 0 1- 2 3- 4 5+ D on ’t kn ow / m is si ng 1- 2 3- 4 5+ D on ’t kn ow / m is si ng A ge 15 -1 9 38 .5 1, 00 9 54 .5 29 .7 8. 4 6. 6 0. 8 10 0. 0 38 8 56 .9 24 .0 13 .4 5. 6 10 0. 0 17 4 20 -2 4 64 .1 85 4 32 .4 34 .2 19 .6 12 .1 1. 7 10 0. 0 54 7 36 .9 28 .2 24 .9 10 .0 10 0. 0 36 1 25 -2 9 65 .5 70 9 28 .8 32 .7 20 .1 17 .4 1. 1 10 0. 0 46 5 31 .1 28 .7 31 .5 8. 7 10 0. 0 32 6 30 -3 4 64 .4 54 5 30 .6 32 .9 16 .0 19 .1 1. 4 10 0. 0 35 1 34 .3 30 .4 28 .0 7. 3 10 0. 0 23 9 35 -3 9 63 .3 46 7 31 .2 29 .0 21 .8 16 .8 1. 2 10 0. 0 29 6 37 .2 25 .1 32 .1 5. 6 10 0. 0 20 0 40 -4 4 55 .6 39 4 23 .5 34 .2 22 .7 16 .5 3. 2 10 0. 0 21 9 39 .1 23 .6 30 .5 6. 8 10 0. 0 16 1 45 -4 9 58 .5 30 1 32 .4 22 .6 30 .3 13 .8 0. 9 10 0. 0 17 6 33 .0 35 .7 25 .6 5. 6 10 0. 0 11 8 R es id en ce U rb an 58 .3 2, 38 6 30 .2 35 .5 20 .3 13 .0 1. 0 10 0. 0 1, 39 0 35 .7 27 .9 28 .6 7. 7 10 0. 0 95 6 R ur al 55 .5 1, 89 5 39 .0 26 .3 16 .6 16 .1 1. 9 10 0. 0 1, 05 3 40 .2 27 .8 24 .5 7. 5 10 0. 0 62 1 R eg io n Za m be zi 51 .5 22 5 31 .6 27 .3 17 .7 12 .6 10 .8 10 0. 0 11 6 16 .0 13 .7 41 .7 28 .6 10 0. 0 67 E ro ng o 41 .7 39 3 30 .1 40 .1 18 .7 11 .1 0. 0 10 0. 0 16 4 29 .9 23 .0 41 .3 5. 8 10 0. 0 11 5 H ar da p 50 .2 16 5 36 .6 37 .5 17 .5 8. 4 0. 0 10 0. 0 83 20 .4 18 .2 58 .4 3. 0 10 0. 0 52 //K ar as 53 .6 16 4 38 .5 34 .8 18 .9 7. 2 0. 6 10 0. 0 88 28 .2 24 .5 34 .2 13 .1 10 0. 0 54 K av an go 42 .3 33 3 57 .5 25 .6 8. 6 5. 8 2. 5 10 0. 0 14 1 28 .4 30 .5 41 .1 0. 0 10 0. 0 56 K ho m as 64 .3 1, 05 4 27 .1 36 .7 22 .1 13 .7 0. 4 10 0. 0 67 8 35 .5 28 .7 28 .5 7. 4 10 0. 0 49 1 K un en e 38 .4 11 5 41 .6 23 .4 21 .8 11 .5 1. 7 10 0. 0 44 31 .9 37 .2 25 .9 5. 1 10 0. 0 25 O ha ng w en a 62 .6 36 4 33 .8 21 .3 21 .0 23 .5 0. 4 10 0. 0 22 8 46 .6 30 .8 21 .2 1. 4 10 0. 0 15 0 O m ah ek e 36 .9 11 9 34 .7 33 .5 13 .2 16 .5 2. 1 10 0. 0 44 23 .1 23 .7 52 .4 0. 9 10 0. 0 28 O m us at i 52 .1 37 8 20 .5 30 .6 20 .0 25 .5 3. 4 10 0. 0 19 7 41 .0 37 .0 15 .7 6. 4 10 0. 0 15 0 O sh an a 79 .5 35 4 46 .6 24 .2 13 .9 15 .3 0. 0 10 0. 0 28 2 60 .4 29 .7 8. 3 1. 5 10 0. 0 15 0 O sh ik ot o 72 .7 35 7 37 .8 31 .6 17 .9 11 .1 1. 6 10 0. 0 26 0 47 .9 28 .0 15 .4 8. 7 10 0. 0 15 7 O tjo zo nd ju pa 46 .1 25 9 30 .0 35 .5 20 .6 12 .7 1. 3 10 0. 0 11 9 22 .4 21 .0 31 .4 25 .2 10 0. 0 82 Ed uc at io n N o ed uc at io n 51 .7 33 8 33 .6 23 .7 18 .0 22 .8 2. 0 10 0. 0 17 5 30 .4 24 .5 35 .8 9. 4 10 0. 0 11 3 P rim ar y 54 .4 1, 01 8 40 .6 26 .7 15 .5 15 .6 1. 6 10 0. 0 55 4 39 .7 28 .8 26 .8 4. 8 10 0. 0 32 0 S ec on da ry 57 .1 2, 54 4 32 .9 34 .1 18 .1 13 .5 1. 4 10 0. 0 1, 45 4 36 .9 28 .6 26 .3 8. 2 10 0. 0 95 5 M or e th an s ec on da ry 68 .4 38 1 26 .8 32 .6 29 .5 10 .6 0. 5 10 0. 0 26 0 40 .8 24 .9 25 .9 8. 5 10 0. 0 18 9 W ea lth q ui nt ile Lo w es t 55 .4 64 5 39 .4 24 .6 15 .9 18 .5 1. 6 10 0. 0 35 7 39 .7 26 .6 29 .4 4. 2 10 0. 0 21 1 S ec on d 55 .8 81 2 41 .3 25 .2 17 .5 14 .6 1. 5 10 0. 0 45 3 38 .5 33 .0 23 .2 5. 4 10 0. 0 25 9 M id dl e 57 .1 95 2 32 .6 30 .9 20 .2 14 .3 2. 0 10 0. 0 54 4 45 .2 24 .2 22 .0 8. 5 10 0. 0 35 6 Fo ur th 56 .2 97 1 33 .1 34 .7 18 .0 13 .0 1. 2 10 0. 0 54 6 28 .6 31 .9 29 .0 10 .5 10 0. 0 35 9 H ig he st 60 .3 90 0 26 .8 38 .8 20 .8 12 .8 0. 8 10 0. 0 54 3 36 .7 24 .8 30 .9 7. 6 10 0. 0 39 3 To ta l 1 5- 49 57 .1 4, 28 1 34 .0 31 .5 18 .7 14 .3 1. 4 10 0. 0 2, 44 3 37 .5 27 .9 27 .0 7. 6 10 0. 0 1, 57 7 50 -6 4 54 .2 54 8 35 .2 25 .7 12 .4 25 .6 1. 2 10 0. 0 29 7 40 .7 29 .1 23 .7 6. 5 10 0. 0 18 9 Other Health Issues • 263 264 • Other Health Issues Fifty-four percent of women and 34 percent of men age 15-49 reported that they had not consumed alcohol in the past two weeks. Twenty-six percent of women and 32 percent of men reported that they had consumed alcohol on 1-2 days during the last two weeks; 9 percent and 19 percent, respectively, had consumed alcohol on 3-4 days during the last two weeks, and 8 percent and 14 percent, respectively, had consumed alcohol on 5 or more days. Women and men who reported that they had consumed alcohol on at least one day in the two weeks before the survey were also asked to report on the number of drinks they consumed on average per day. The data show that 45 percent of women and 38 percent of men consumed 1-2 drinks per day, 24 percent of women and 28 percent of men consumed 3-4 drinks per day, and 22 percent of women and 27 percent of men consumed 5 or more drinks per day. Women age 20-24 and 40-44, urban women, women who live in Kunene, those with a primary education, breastfeeding women, and women in the fourth wealth quintile are more likely than their counterparts to have consumed five or more drinks per day. Alcohol consumption is also very high (five or more drinks per day) among men age 25-29, 35-39, and 40- 44 (about one in three men), urban men, men in Hardap, men with no education and those in the highest wealth quintile. 18.5 USE OF SEATBELTS Seatbelt use is of high priority in Namibia, which has the highest per capita motor vehicle mortality rate in the world (WHO, 2013).2 In the 2013 NDHS, women and men age 15-64 were asked whether they had used a seatbelt in the last 30 days while they were seated in a vehicle as either a driver or a passenger and how often they had used a seatbelt. Table 18.6 shows that 44 percent of women and 62 percent of men age 15-49 always used seatbelts. Among women who had been in a vehicle in the last 30 days, the proportion who always used seatbelts ranged from a high of 53 percent in the 40-44 age group to a low of 30 percent in the 15-19 age group. Use among men was higher, ranging from a high of 72 percent in the 35-39 age group to a low of 43 percent in the 15-19 age group. The lowest seatbelt usage by far among men and women is in the youngest age group 15-19. Seatbelt usage is much higher in urban areas than rural areas. Fifty-six percent of women in urban areas always used seatbelts in the past 30 days, as compared with 29 percent of women in rural areas.; Among men, 76 percent of those in urban areas always used seatbelts in the past 30 days, compared with 43 percent of in rural areas. 2 http://www.who.int/violence_injury_prevention/road_safety_status/2013/en/ Other Health Issues • 265 Table 18.6 Use of seatbelts Percent distribution of women and men age 15-49 by whether they used a seatbelt in the last 30 days, according to background characteristics, Namibia 2013 Used seatbelt in the last 30 days Total Number of respondents Background characteristic All of the time Sometimes Never Have not been in vehicle in last 30 days No seatbelt in car Don’t know/ not sure/ missing WOMEN Age 15-19 30.4 39.6 20.3 7.9 1.7 0.1 100.0 1,906 20-24 43.4 37.8 12.2 5.0 1.5 0.2 100.0 1,786 25-29 44.2 38.4 10.9 5.0 1.3 0.2 100.0 1,489 30-34 50.9 31.5 10.0 5.9 1.4 0.3 100.0 1,260 35-39 47.1 34.8 9.3 7.1 1.8 0.0 100.0 1,110 40-44 52.9 29.5 9.1 5.2 2.8 0.5 100.0 917 45-49 52.5 27.5 11.7 6.1 2.1 0.2 100.0 708 50-54 42.8 28.5 14.4 11.3 2.9 0.1 100.0 797 Residence Urban 55.6 34.3 7.4 2.2 0.3 0.2 100.0 5,503 Rural 29.4 35.6 19.5 11.8 3.6 0.1 100.0 4,470 Region Zambezi 29.5 39.9 23.9 2.5 4.2 0.0 100.0 494 Erongo 54.2 37.2 6.2 1.8 0.4 0.1 100.0 820 Hardap 51.9 30.9 5.7 10.9 0.4 0.3 100.0 341 //Karas 58.7 26.6 9.4 3.4 1.7 0.3 100.0 374 Kavango 14.8 32.2 39.0 10.4 3.3 0.3 100.0 913 Khomas 59.0 34.7 5.2 0.7 0.2 0.3 100.0 2,317 Kunene 36.5 29.9 12.0 20.0 1.5 0.1 100.0 286 Ohangwena 39.2 25.7 16.9 15.0 3.2 0.0 100.0 974 Omaheke 38.9 30.9 10.1 17.3 2.0 0.7 100.0 249 Omusati 27.3 55.8 8.4 5.4 3.0 0.0 100.0 1,013 Oshana 43.7 42.0 11.6 1.5 1.3 0.0 100.0 822 Oshikoto 44.6 22.4 15.5 13.5 4.0 0.0 100.0 774 Otjozondjupa 54.1 29.4 9.0 6.9 0.3 0.4 100.0 596 Education No education 21.3 25.3 24.0 23.7 4.5 1.3 100.0 572 Primary 27.1 35.5 21.5 12.3 3.2 0.3 100.0 2,168 Secondary 47.5 36.7 10.6 3.8 1.3 0.0 100.0 6,238 More than secondary 70.4 27.0 1.6 0.6 0.3 0.0 100.0 995 Wealth quintile Lowest 17.2 31.6 28.1 17.8 4.9 0.3 100.0 1,614 Second 28.7 40.0 17.6 10.6 2.7 0.4 100.0 1,776 Middle 37.7 41.8 13.1 5.5 1.9 0.0 100.0 1,927 Fourth 53.2 36.0 7.9 2.2 0.5 0.2 100.0 2,285 Highest 69.4 26.4 3.4 0.6 0.1 0.0 100.0 2,371 Total 15-49 44.0 35.4 12.7 6.1 1.7 0.2 100.0 9,176 50-64 42.8 28.5 14.4 11.3 2.9 0.1 100.0 797 MEN Age 15-19 42.9 29.0 13.4 10.6 3.5 0.5 100.0 922 20-24 59.6 24.2 8.4 5.1 2.4 0.3 100.0 808 25-29 68.7 18.6 3.3 5.3 3.6 0.4 100.0 658 30-34 71.4 17.2 2.5 6.4 2.2 0.3 100.0 520 35-39 71.5 16.1 3.9 6.3 2.0 0.2 100.0 448 40-44 70.2 18.5 3.3 6.5 1.3 0.2 100.0 376 45-49 71.4 16.1 4.9 5.2 1.5 0.8 100.0 289 Residence Urban 76.1 17.9 3.0 2.0 0.8 0.2 100.0 2,282 Rural 43.4 26.2 11.5 13.3 5.0 0.6 100.0 1,739 Region Zambezi 55.2 23.6 14.5 6.0 0.7 0.0 100.0 218 Erongo 73.1 18.6 0.6 6.5 1.0 0.2 100.0 372 Hardap 70.2 19.1 1.3 9.5 0.0 0.0 100.0 152 //Karas 68.7 17.2 5.3 7.0 0.7 1.1 100.0 151 Kavango 41.9 32.1 14.0 7.9 3.2 0.8 100.0 316 Khomas 74.7 20.1 3.5 0.9 0.8 0.0 100.0 1,023 Kunene 73.7 6.0 1.7 13.8 2.6 2.3 100.0 104 Ohangwena 38.5 25.9 14.5 11.9 8.8 0.4 100.0 328 Omaheke 48.7 22.1 3.2 24.7 0.0 1.3 100.0 103 Omusati 38.2 31.3 15.4 12.9 1.4 0.8 100.0 342 Oshana 76.7 15.5 4.0 1.8 1.5 0.5 100.0 335 Oshikoto 50.0 21.7 6.3 11.1 10.9 0.0 100.0 335 Otjozondjupa 75.9 14.3 2.9 5.3 0.9 0.7 100.0 241 Education No education 50.2 20.3 9.0 17.4 2.4 0.7 100.0 310 Primary 47.4 22.9 12.0 12.0 4.9 0.8 100.0 944 Secondary 66.4 21.7 5.2 4.4 2.0 0.2 100.0 2,400 More than secondary 80.0 17.3 1.0 0.7 1.0 0.0 100.0 368 Wealth quintile Lowest 34.0 23.9 17.9 15.4 8.2 0.7 100.0 594 Second 51.4 24.4 7.8 12.0 3.7 0.7 100.0 769 Middle 62.2 23.4 5.4 6.8 1.7 0.6 100.0 886 Fourth 73.4 19.3 3.7 2.4 1.2 0.0 100.0 917 Highest 78.5 17.4 2.7 1.1 0.2 0.1 100.0 855 Total 15-49 62.0 21.5 6.7 6.9 2.6 0.4 100.0 4,021 50-64 71.7 11.3 5.0 9.6 1.3 1.2 100.0 460 266 • Other Health Issues Among the regions, women in Khomas and //Karas (59 percent) and men in Oshana (77 percent) were most likely to always use seatbelts. In general, seatbelt use increases with increasing education. Twenty-one percent of women with no education reported always using a seatbelt, as compared with 70 percent of women with more than a secondary education; the corresponding percentages among men were 50 percent and 80 percent. Likewise, seatbelt use increases with increasing household wealth among both women and men. 18.6 PHYSICAL ACTIVITY The World Health Organization defines physical activity as any bodily movement produced by skeletal muscles that requires energy expenditure, including activities undertaken while working, playing, carrying out household chores, travelling, and engaging in recreational pursuits.3 The term “physical activity” should not be confused with “exercise,” which is a subcategory of physical activity that is planned, structured, and repetitive and aims to improve or maintain one or more components of physical fitness. In order to be beneficial for cardiorespiratory health, all activity should be performed in bouts of at least 10 minutes in duration. WHO recommends regular and adequate levels of physical activity to reduce the risk of hypertension, coronary heart disease, stroke, diabetes, breast and colon cancer, and depression. Physical activity also aids in weight control and increases people’s chances of living longer. In the 2013 NDHS, women and men age 15-64 were asked about their physical activity and, among those who engaged in non-work-related physical activities, the number of days they engaged in such activities for at least 10 minutes continuously per day. Tables 18.7.1 and 18.7.2 show data on physical activity. 3 http://www.who.int/dietphysicalactivity/pa/en/ Other Health Issues • 267 Table 18.7.1 Physical activity: Women Percent distribution of women age 15-49 by whether they are physically active, and among women who did non-work-related physical activity, the percent distribution of women by the number of days they did non-work-related physical activity for at least 10 minutes continuously per day, according to background characteristics, Namibia 2013 Physical activity1 Total Number of women Number of days in the last week non-work-related physical activity done for at least 10 minutes per day continuously Total Number of women Background characteristic Physically active at work Did non- work- related physical activity No Missing 0 1-2 3-4 5-7 Don’t know/ unsure/ missing Age 15-19 2.4 19.6 78.0 0.0 100.0 1,906 6.2 52.0 18.0 20.6 3.3 100.0 374 20-24 3.7 16.1 80.1 0.1 100.0 1,786 8.3 50.0 17.8 17.4 6.5 100.0 291 25-29 5.6 14.1 80.3 0.0 100.0 1,489 3.4 38.8 23.3 30.6 3.9 100.0 210 30-34 7.2 11.7 81.1 0.1 100.0 1,260 6.9 39.9 24.8 22.9 5.4 100.0 148 35-39 6.4 13.7 79.5 0.4 100.0 1,110 8.7 34.2 18.9 32.1 6.1 100.0 156 40-44 6.1 14.3 79.5 0.1 100.0 917 9.8 29.6 20.7 32.1 7.8 100.0 133 45-49 5.6 16.9 77.6 0.0 100.0 708 11.0 26.9 21.4 37.3 3.3 100.0 119 50-54 5.7 18.7 75.6 0.0 100.0 797 9.0 26.5 20.4 38.0 6.1 100.0 149 Residence Urban 5.9 15.8 78.1 0.1 100.0 5,503 8.2 41.7 19.5 25.0 5.6 100.0 878 Rural 3.8 15.7 80.5 0.0 100.0 4,470 6.5 39.7 20.8 28.5 4.4 100.0 702 Region Zambezi 3.8 29.7 66.5 0.0 100.0 494 1.7 58.8 19.3 15.1 5.1 100.0 147 Erongo 4.4 16.9 78.6 0.1 100.0 820 2.0 41.1 19.4 30.0 7.5 100.0 139 Hardap 1.4 14.4 84.1 0.0 100.0 341 4.2 32.0 21.3 41.5 1.1 100.0 49 //Karas 7.2 13.7 79.1 0.0 100.0 374 6.4 40.6 24.6 27.3 1.2 100.0 51 Kavango 2.1 17.2 80.7 0.0 100.0 913 3.7 62.7 16.6 16.9 0.0 100.0 157 Khomas 7.6 16.1 76.2 0.2 100.0 2,317 8.5 39.0 19.1 27.1 6.3 100.0 376 Kunene 11.9 9.2 78.9 0.0 100.0 286 3.3 43.7 29.9 21.0 2.1 100.0 26 Ohangwena 2.1 17.2 80.7 0.0 100.0 974 18.1 28.7 16.7 32.9 3.7 100.0 167 Omaheke 10.6 16.7 72.7 0.0 100.0 249 5.6 18.7 22.9 40.1 12.7 100.0 42 Omusati 1.8 15.8 82.3 0.1 100.0 1,013 1.4 30.7 28.3 34.8 4.7 100.0 161 Oshana 3.1 9.7 87.3 0.0 100.0 822 19.0 49.0 14.1 16.8 1.2 100.0 79 Oshikoto 8.9 10.0 81.0 0.1 100.0 774 11.8 36.0 14.3 32.0 5.8 100.0 78 Otjozondjupa 3.5 17.5 78.6 0.4 100.0 596 9.0 33.9 25.9 19.6 11.6 100.0 107 Education No education 5.1 11.5 83.1 0.2 100.0 572 10.8 25.5 17.7 35.9 10.0 100.0 67 Primary 2.9 13.3 83.7 0.1 100.0 2,168 8.8 39.8 20.3 25.5 5.6 100.0 291 Secondary 5.2 16.0 78.7 0.0 100.0 6,238 6.9 43.5 19.4 26.1 4.1 100.0 1,001 More than secondary 8.0 21.8 69.8 0.4 100.0 995 7.2 34.8 23.6 26.9 7.4 100.0 221 Wealth quintile Lowest 3.2 15.2 81.6 0.0 100.0 1,614 7.1 37.0 23.5 29.5 3.0 100.0 245 Second 3.9 16.1 79.9 0.1 100.0 1,776 8.8 42.4 19.1 26.1 3.5 100.0 288 Middle 5.0 13.9 81.0 0.1 100.0 1,927 6.2 43.1 19.0 27.0 4.8 100.0 270 Fourth 4.7 13.2 82.0 0.1 100.0 2,285 7.8 42.1 16.2 28.6 5.3 100.0 304 Highest 7.2 19.8 72.8 0.2 100.0 2,371 7.3 39.7 22.1 23.8 7.1 100.0 474 Total 15-49 4.9 15.5 79.5 0.1 100.0 9,176 7.3 42.3 20.1 25.4 5.0 100.0 1,431 50-64 5.7 18.7 75.6 0.0 100.0 797 9.0 26.5 20.4 38.0 6.1 100.0 149 1 Physical activity is defined as exercise that causes an increase in heart rate for at least 10 minutes continuously. 268 • Other Health Issues Table 18.7.2 Physical activity: Men Percent distribution of men age 15-49 by whether they are physically active, and among men who did non-work-related physical activity, the percent distribution of men by the number of days they did non-work-related physical activity for at least 10 minutes continuously per day, according to background characteristics, Namibia 2013 Physical activity1 Total Number of respon- dents Number of days in the last week non-work-related physical activity done for at least 10 minutes per day continuously Total Number of men Background characteristic Phys- ically active at work Did non- work- related physical activity No Missing 0 1-2 3-4 5-7 Don’t know/ unsure/ missing Age 15-19 2.3 42.5 55.1 0.0 100.0 922 6.5 26.0 24.0 42.5 1.0 100.0 392 20-24 10.3 36.2 53.5 0.0 100.0 808 9.9 25.6 26.1 36.2 2.1 100.0 293 25-29 16.7 31.1 52.0 0.2 100.0 658 10.1 29.6 28.2 28.0 4.1 100.0 206 30-34 12.0 28.7 59.3 0.0 100.0 520 6.9 31.5 24.5 34.4 2.7 100.0 149 35-39 17.2 22.1 60.7 0.0 100.0 448 10.8 29.8 36.3 20.0 3.2 100.0 99 40-44 17.3 19.1 63.5 0.0 100.0 376 2.3 32.0 24.5 39.0 2.2 100.0 72 45-49 14.6 22.5 62.6 0.3 100.0 289 16.2 28.5 30.7 24.0 0.7 100.0 66 Residence Urban 12.7 31.7 55.5 0.0 100.0 2,282 4.6 31.9 27.6 33.3 2.6 100.0 724 Rural 9.8 31.7 58.4 0.1 100.0 1,739 13.6 22.6 25.2 37.0 1.6 100.0 553 Region Zambezi 2.6 75.1 22.3 0.0 100.0 218 0.5 32.1 28.0 36.9 2.5 100.0 163 Erongo 9.1 31.0 59.9 0.0 100.0 372 3.3 26.8 35.5 33.0 1.4 100.0 115 Hardap 12.0 25.2 62.8 0.0 100.0 152 0.0 23.7 48.7 26.5 1.1 100.0 38 //Karas 16.2 46.9 36.9 0.0 100.0 151 1.6 31.5 28.7 35.2 3.1 100.0 71 Kavango 4.4 33.1 62.5 0.0 100.0 316 15.3 23.2 23.4 38.0 0.0 100.0 105 Khomas 16.0 33.3 50.8 0.0 100.0 1,023 3.9 39.9 22.9 30.0 3.3 100.0 340 Kunene 21.0 23.0 56.0 0.0 100.0 104 7.6 20.0 29.2 41.4 1.8 100.0 24 Ohangwena 5.3 51.7 42.7 0.4 100.0 328 22.1 19.3 17.6 40.2 0.7 100.0 171 Omaheke 15.0 22.7 62.3 0.0 100.0 103 2.4 25.1 52.0 18.2 2.3 100.0 23 Omusati 8.1 13.4 78.5 0.0 100.0 342 21.3 11.1 28.5 36.5 2.6 100.0 46 Oshana 13.9 7.3 78.8 0.0 100.0 335 19.4 0.0 28.8 46.6 5.2 100.0 24 Oshikoto 13.2 28.4 58.4 0.0 100.0 335 16.9 21.7 28.1 32.4 0.9 100.0 95 Otjozondjupa 11.9 24.7 63.2 0.3 100.0 241 4.4 19.6 24.3 47.2 4.6 100.0 60 Education No education 23.6 17.2 59.2 0.0 100.0 310 33.9 10.7 20.2 34.4 0.8 100.0 53 Primary 10.3 24.1 65.5 0.1 100.0 944 9.9 26.7 27.9 34.3 1.2 100.0 228 Secondary 10.7 35.5 53.7 0.1 100.0 2,400 7.5 28.0 25.6 36.2 2.7 100.0 854 More than secondary 9.2 38.6 52.2 0.0 100.0 368 2.6 35.5 32.3 28.3 1.4 100.0 142 Wealth quintile Lowest 10.1 35.0 54.7 0.2 100.0 594 19.1 27.8 21.3 30.5 1.2 100.0 209 Second 10.9 28.9 60.2 0.0 100.0 769 9.3 22.3 26.5 40.5 1.4 100.0 222 Middle 13.7 24.9 61.4 0.0 100.0 886 5.7 30.4 28.7 31.9 3.3 100.0 220 Fourth 13.2 32.3 54.5 0.1 100.0 917 6.6 24.4 27.5 38.1 3.4 100.0 297 Highest 8.8 38.5 52.8 0.0 100.0 855 4.8 33.1 27.6 33.0 1.5 100.0 329 Total 15-49 11.5 31.7 56.8 0.0 100.0 4,021 8.5 27.9 26.5 34.9 2.2 100.0 1,277 50-64 11.9 20.2 67.9 0.0 100.0 460 16.3 32.1 23.8 24.2 3.7 100.0 93 1 Physical activity is defined as exercise that causes an increase in heart rate for at least 10 minutes continuously. Five percent of women and 12 percent of men age 15-49 were physically active at work, while 16 percent of women and 32 percent of men engaged in non-work-related physical activity. The vast majority of women (80 percent) and men (57 percent) neither were physically active at work nor engaged in non- work-related physical activity. Non-work-related physical activity is highest among women and men age 15-19, those in Zambezi, women and men with a secondary education or higher, and those in the highest wealth quintile. Among women who engaged in non-work-related physical activity, 42 percent were physically active on 1-2 days in the week prior to the survey, 20 percent were physically active on 3-4 days, and 25 percent were physically active on 5-7 days. Seven percent reported that they had not exercised in the last week. Among men, 28 percent engaged in physical activity on 1-2 days, 27 percent on 3-4 days, and 35 percent on 5-7 days. Nine percent did not engage in any physical activity in the week prior to the survey. Continuous non-work-related physical activity (5-7 days per week) is highest among women older than age 40, women in Hardap and Omaheke, women with no education, and those in the lowest wealth quintile. Among men, continuous physical activity is highest among those age 15-19, men in rural areas, those in Other Health Issues • 269 Oshana and Otjozondjupa, men with a secondary education or lower, and those in the second and fourth wealth quintiles. 18.7 CONSUMPTION OF WATER, FRUITS, AND VEGETABLES Water is a human body’s principal chemical component and makes up about 60 percent of body weight. Every system in a human body depends on water. Each day a person loses water through breathing, perspiration, and urine and bowel movements. If their body is to function properly, people must replenish its water supply by consuming beverages and foods that contain water. Lack of water can lead to dehydration, a condition that occurs when the body does not have enough water to carry out normal functions. Even mild dehydration can drain people’s energy and make them tired. Eating enough fruits and vegetables has its own health benefits as well. According to WHO, at least 400 grams of fruits and vegetables (about five 80-gram portions) are needed to meet people’s daily nutritional requirements and protect them from diseases. In fact, five portions each day is the minimum. Nevertheless, it appears that the more fruits and vegetables we eat, the greater our protection from diet-related diseases (World Health Report, 2002). A diet rich in vegetables and fruits can lower blood pressure, reduce the risk of heart disease and stroke, prevent some types of cancer, lower the risk of eye and digestive problems, and have a positive effect on blood sugar, which can help people keep their appetite in check. In the 2013 NHDS, women and men age 15-64 were asked about their consumption of water, fruits, and vegetables, including the number of glasses of water they consumed per day, the average number of days each week they ate fruits and vegetables, and the average number of times per day they ate fruits and vegetables (Tables 18.8.1 and 18.8.2). Women age 15-49 consume an average of four glasses of water per day. Women age 50-64 consume slightly more glasses of water on average per day than women age 15-49. The average number of days each week that women age 15-49 consume fruits and vegetables is two and three, respectively, and they do so on average only once per day. Men age 15-49 and 50-64 consume, on average, one glass of water more per day than women in the same age groups (about five glasses). Similar to women, men consume fruits and vegetables on two and three days per week, respectively, and do so once a day on average. Overall, consumption of water increases with age among both women and men. The prevalence of fruit and vegetable consumption is higher among urban women than among rural women. Water consumption among women is highest in Kunene, among those with more than a secondary education, and among women in the highest wealth quintile. Older women (age 45-64) are more likely to consume water than younger women. Number of glasses of water consumed per day among women and men does not vary extensively by residence, level of education, or wealth quintile. However, while women and men in urban areas eat fruit and vegetables three days a week on average, their counterparts in rural areas eat fruit only one day a week and vegetables two days a week. 270 • Other Health Issues Table 18.8.1 Consumption of water, fruits, and vegetables: Women Among women age 15-49, the average number of glasses of water consumed per day, the average number of days per week fruits are consumed, the average number of times per day fruits are consumed, the average number of days per week vegetables are consumed, and the average number of times per day vegetables are consumed, according to background characteristics, Namibia 2013 Background characteristic Average number of glasses of water consumed per day Average number of days per week fruits consumed Average number of times per day fruits consumed Average number of days per week vegetables consumed Average number of times per day vegetables consumed Number of women Age 15-19 3.4 2.0 1.1 3.2 1.4 1,906 20-24 3.6 2.3 1.2 3.3 1.3 1,786 25-29 4.0 2.4 1.1 3.3 1.3 1,489 30-34 4.3 2.4 1.1 3.2 1.3 1,260 35-39 4.4 2.1 1.0 3.0 1.2 1,110 40-44 4.4 2.2 1.0 3.4 1.3 917 45-49 4.7 2.2 1.1 3.2 1.2 708 Residence Urban 4.2 3.0 1.4 3.9 1.4 5,190 Rural 3.7 1.2 0.7 2.4 1.2 3,986 Region Zambezi 4.0 1.6 0.9 4.3 1.5 457 Erongo 4.0 3.0 1.3 3.6 1.3 771 Hardap 5.3 3.1 1.1 4.2 1.2 304 //Karas 4.0 2.7 1.3 4.0 1.4 343 Kavango 2.9 1.0 0.7 2.7 1.2 835 Khomas 4.3 3.5 1.5 4.0 1.4 2,202 Kunene 5.3 1.5 1.4 2.4 1.0 258 Ohangwena 3.4 1.2 0.6 1.8 0.9 894 Omaheke 4.2 1.7 0.8 2.0 0.8 225 Omusati 3.4 1.2 0.7 2.6 1.8 884 Oshana 4.3 2.1 0.9 3.1 1.1 755 Oshikoto 3.8 2.0 1.1 3.5 1.4 707 Otjozondjupa 4.3 2.0 1.1 2.8 1.1 540 Education No education 3.5 0.8 0.5 1.8 0.9 419 Primary 3.8 1.2 0.7 2.4 1.2 1,798 Secondary 4.0 2.4 1.2 3.4 1.3 6,029 More than secondary 4.2 3.7 1.5 4.5 1.5 930 Wealth quintile Lowest 3.5 0.6 0.5 2.0 1.1 1,429 Second 3.8 1.3 0.8 2.4 1.1 1,625 Middle 4.0 1.9 1.0 3.0 1.3 1,795 Fourth 4.2 2.8 1.3 3.6 1.4 2,116 Highest 4.3 3.7 1.6 4.6 1.5 2,211 Total 15-49 4.0 2.2 1.1 3.2 1.3 9,176 50-64 4.5 1.7 0.8 2.9 1.3 797 Other Health Issues • 271 Table 18.8.2 Consumption of water, fruits, and vegetables: Men Among men age 15-49, the average number of glasses of water consumed per day, the average number of days per week fruits are consumed, the average number of times per day fruits are consumed, the average number of days per week vegetables are consumed, and the average number of times per day vegetables are consumed, according to background characteristics, Namibia 2013 Background characteristic Average number of glasses of water consumed per day Average number of days per week fruits consumed Average number of times per day fruits consumed Average number of days per week vegetables consumed Average number of times per day vegetables consumed Number of men Age 15-19 4.5 2.0 1.2 2.9 1.2 922 20-24 4.5 2.0 1.1 2.9 1.2 808 25-29 5.0 2.0 1.1 2.9 1.2 658 30-34 5.0 2.1 1.2 2.9 1.2 520 35-39 5.3 2.3 1.2 2.9 1.2 448 40-44 5.1 2.1 1.1 2.7 1.2 376 45-49 5.1 2.4 1.2 3.0 1.3 289 Residence Urban 4.9 2.8 1.5 3.4 1.4 2,282 Rural 4.7 1.2 0.8 2.3 1.0 1,739 Region Zambezi 5.0 1.6 0.6 4.3 1.2 218 Erongo 5.2 2.9 1.3 3.5 1.3 372 Hardap 4.9 1.8 1.0 2.5 1.1 152 //Karas 5.3 2.4 1.3 3.1 1.7 151 Kavango 4.2 1.3 1.0 2.4 1.1 316 Khomas 4.8 3.0 1.6 3.4 1.4 1,023 Kunene 6.9 1.1 1.0 1.4 0.9 104 Ohangwena 5.5 1.3 0.9 3.1 1.2 328 Omaheke 5.3 1.1 0.9 1.1 0.8 103 Omusati 3.2 1.4 0.7 1.7 0.9 342 Oshana 5.1 2.1 1.1 3.1 1.2 335 Oshikoto 4.1 1.3 1.0 2.6 1.2 335 Otjozondjupa 5.5 2.1 1.2 2.0 1.2 241 Education No education 5.3 1.1 0.7 2.0 0.8 310 Primary 4.6 1.4 0.8 2.3 1.0 944 Secondary 4.8 2.3 1.3 3.1 1.3 2,400 More than secondary 5.3 3.1 1.5 3.9 1.4 368 Wealth quintile Lowest 4.6 0.9 0.6 2.1 0.9 594 Second 4.6 1.5 0.9 2.3 1.0 769 Middle 4.7 1.8 1.1 2.8 1.1 886 Fourth 4.9 2.6 1.3 3.4 1.4 917 Highest 5.2 3.2 1.6 3.6 1.5 855 Total 15-49 4.8 2.1 1.2 2.9 1.2 4,021 50-64 5.4 2.1 1.1 3.1 1.3 460 Women in Hardap and Kunene consume five glasses of water per day on average, whereas women in the other regions consume three to four glasses per day. Among men, water consumption is highest in Kunene, Ohangwena, and Otjozondjupa. Women in Khomas eat fruit four days a week on average, as compared with one to three days a week among women in the other regions. Women in Ohangwena and Omaheke are less likely to eat vegetables (only two days per week on average) than women in the other regions. Consumption of fruits and vegetables is higher among women with more than a secondary education than among women with no education. 18.8 MENTAL HEALTH Mental health refers to a broad array of activities directly or indirectly related to the mental well- being component included in the WHO definition of health4: “a state of complete physical, mental and social well-being, and not merely the absence of disease.” It is related to the promotion of well-being, the prevention of mental disorders, and the treatment and rehabilitation of people affected by mental disorders. 4 http://www.who.int/topics/mental_health 272 • Other Health Issues Mental disorders comprise a broad range of problems, with different symptoms. They are generally characterised by some combination of abnormal thoughts, emotions, behaviours, and relationships with others. Mental illness, on the other hand, is characterised by alterations in thinking, mood, or behaviour (or some combination thereof) associated with distress and/or impaired functioning. Most of these disorders can be successfully treated. In the health care and public health arena, increased emphasis and resources are being devoted to screening, diagnosis, and treatment of mental illness. The 2013 NDHS collected information from women and men age 15-49 on whether they have ever seen or heard things that are actually not there, whether they felt worthless or hopeless or wished they were dead during the past 12 months, the average number of days in the past two weeks they had little interest or pleasure in doing things; and the average number of days in the past two weeks they had felt low in energy, been in a bad mood, or been sad. Tables 18.9.1 and 18.9.2 present the results of the data collected on mental health. Table 18.9.1 Mental health: Women Percentage of women age 15-49 who have ever seen or heard things that are actually not there; the percentage who, in the past 12 months, felt seriously worthless, hopeless, or wished to be dead; the average number of days in the past two weeks women felt little interest or pleasure in doing things; the average number of days in the past two weeks women felt low in energy, had been in a bad mood, or had been sad all of the time; and among women who had experienced any mental health issue,1 the percentage who sought medical care, according to background characteristics, Namibia 2013 Background characteristic Ever seen or heard things that are actually not there Felt seriously worthless, hopeless, or wished to be dead in the past 12 months Average number of days felt little interest or pleasure in doing things in the past 2 weeks Average number of days felt low in energy, been in a bad mood, or been sad all of the time in the past 2 weeks Number of women Sought medical care Number of women Age 15-19 14.4 13.1 0.6 0.6 1,906 11.5 715 20-24 14.1 14.7 0.7 0.8 1,786 16.2 735 25-29 13.2 13.4 0.8 0.8 1,489 18.0 558 30-34 11.7 10.6 0.7 0.8 1,260 21.9 459 35-39 14.7 12.6 0.6 0.8 1,110 21.1 379 40-44 14.5 11.8 0.6 0.7 917 22.3 318 45-49 15.0 9.4 0.6 0.7 708 25.0 232 Residence Urban 12.8 15.4 0.7 0.8 5,190 17.3 2,021 Rural 15.3 9.0 0.6 0.6 3,986 19.0 1,375 Region Zambezi 13.4 18.2 1.0 0.9 457 24.7 219 Erongo 11.4 13.1 0.6 0.7 771 16.1 256 Hardap 15.3 16.3 0.5 0.8 304 16.9 97 //Karas 21.0 27.4 1.2 1.2 343 10.1 186 Kavango 12.7 13.3 1.0 1.1 835 23.4 380 Khomas 12.8 15.7 0.8 0.9 2,202 17.2 899 Kunene 8.3 6.8 0.4 0.5 258 21.9 59 Ohangwena 13.0 6.9 0.5 0.4 894 16.7 270 Omaheke 16.5 14.1 0.6 0.7 225 19.3 76 Omusati 15.0 5.5 0.4 0.4 884 18.4 234 Oshana 10.6 7.5 0.5 0.5 755 19.8 210 Oshikoto 23.0 11.2 0.7 0.6 707 15.0 317 Otjozondjupa 12.5 15.1 0.6 0.8 540 16.6 194 Education No education 10.2 11.0 0.6 0.6 419 19.2 122 Primary 15.9 10.9 0.7 0.8 1,798 22.3 679 Secondary 14.1 12.8 0.7 0.7 6,029 16.9 2,232 More than secondary 10.1 15.6 0.7 0.7 930 16.3 363 Wealth quintile Lowest 16.4 9.3 0.7 0.8 1,429 20.5 538 Second 14.2 9.5 0.6 0.6 1,625 22.6 574 Middle 14.6 11.2 0.6 0.6 1,795 17.1 628 Fourth 13.7 14.4 0.7 0.8 2,116 16.1 767 Highest 11.5 16.7 0.8 0.9 2,211 15.8 890 Total 15-49 13.9 12.7 0.7 0.7 9,176 18.0 3,396 50-64 15.2 13.3 0.0 0.0 797 32.9 280 1 Refers to women who had ever seen or heard things that are actually not there; who, in the past 12 months, had ever felt seriously worthless, hopeless, or wished to be dead; who, in the past 2 weeks, felt that they had little interest or pleasure in doing things; or who, in the past 2 weeks, felt low in energy, had been in a bad mood, or had been sad all of the time Other Health Issues • 273 Table 18.9.2 Mental health: Men Percentage of men age 15-49 who have ever seen or heard things that are actually not there; the percentage who, in the past 12 months, felt seriously worthless, hopeless, or wished to be dead; the average number of days in the past two weeks men felt little interest or pleasure in doing things; the average number of days in the past two weeks men felt low in energy, had been in a bad mood, or had been sad all of the time; and among men who had experienced any mental health issue,1 the percentage who sought medical care, according to background characteristics, Namibia 2013 Background characteristic Ever seen or heard things that are actually not there Felt seriously worthless, hopeless, or wished to be dead in the past 12 months Average number of days felt little interest or pleasure in doing things in the past 2 weeks Average number of days felt low in energy, been in a bad mood, or been sad all of the time in the past 2 weeks Number of men Sought medical care Number of men Age 15-19 11.5 7.0 0.5 0.4 922 7.6 297 20-24 15.7 9.2 0.5 0.5 808 9.5 279 25-29 11.6 8.5 0.4 0.5 658 8.8 194 30-34 11.2 8.1 0.5 0.4 520 10.5 136 35-39 9.6 5.6 0.3 0.3 448 8.9 96 40-44 11.7 6.3 0.3 0.4 376 5.2 76 45-49 16.8 11.7 0.3 0.5 289 6.6 86 Residence Urban 10.2 9.4 0.4 0.4 2,282 8.3 608 Rural 15.6 6.1 0.4 0.4 1,739 8.7 556 Region Zambezi 16.6 17.0 0.7 0.4 218 9.6 79 Erongo 4.7 3.1 0.2 0.1 372 11.2 46 Hardap 6.0 5.1 0.1 0.1 152 (4.6) 19 //Karas 11.6 14.5 0.7 0.8 151 9.7 60 Kavango 13.8 12.4 0.5 0.7 316 9.8 100 Khomas 13.8 10.1 0.4 0.5 1,023 7.6 318 Kunene 3.7 3.5 0.0 0.1 104 * 7 Ohangwena 14.4 7.1 0.7 0.6 328 6.6 157 Omaheke 4.8 3.8 0.2 0.3 103 (7.5) 12 Omusati 14.7 3.5 0.4 0.2 342 8.0 100 Oshana 19.9 4.3 0.5 0.4 335 11.5 120 Oshikoto 14.1 5.8 0.5 0.4 335 9.4 114 Otjozondjupa 7.2 9.4 0.2 0.2 241 (5.3) 32 Education No education 11.5 3.6 0.2 0.4 310 2.1 75 Primary 15.4 7.6 0.5 0.4 944 6.6 293 Secondary 11.8 8.5 0.4 0.4 2,400 9.4 691 More than secondary 10.7 8.9 0.4 0.6 368 12.2 104 Wealth quintile Lowest 14.5 7.6 0.5 0.5 594 8.6 213 Second 12.7 6.0 0.4 0.4 769 9.4 215 Middle 14.7 7.7 0.4 0.4 886 9.4 266 Fourth 13.8 8.6 0.4 0.4 917 3.8 250 Highest 7.2 9.5 0.4 0.4 855 11.6 219 Total 15-49 12.5 8.0 0.4 0.4 4,021 8.5 1,164 50-64 10.4 4.2 0.2 0.3 460 7.2 96 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 Refers to men who had ever seen or heard things that are actually not there; who, in the past 12 months, had ever felt seriously worthless, hopeless, or wished to be dead; who, in the past 2 weeks, felt that they had little interest or pleasure in doing things; or who, in the past 2 weeks, felt low in energy, had been in a bad mood, or had been sad all of the time Fourteen percent of women age 15-49 reported that they had seen or heard things that were actually not there in the two weeks prior to the survey. Thirteen percent of women reported that they felt worthless or hopeless or wished that they were dead in the 12 months prior to the survey. The average number of days that women felt little interest or pleasure in doing things in the past two weeks was less than one, as was the average number of days women felt low in energy, had been in a bad mood, or had been sad. Among women who reported experiencing at least one of these four mental health issues, 18 percent sought medical care. Nearly twice as many women age 50-64 as women age 15-49 sought medical help for their symptoms (33 percent versus 18 percent). Women age 45-49, rural women and those living in Oshikoto, women with a primary education, and those in the lowest wealth quintile were most likely to report that they had seen or heard things that were actually not there in the two weeks before the survey. Women age 20-24, urban women, women in //Karas, women with more than a secondary education, and women in the highest wealth quintile were 274 • Other Health Issues more likely than their counterparts to report that they had felt worthless or hopeless or wished that they were dead in the past 12 months. There were minimal differences by background characteristics in the average number of days women felt little interest or pleasure in doing things in the past two weeks and the average number of days women felt low in energy, had been in a bad mood, or had been sad. Thirteen percent of men age 15-49 reported that they had seen or heard things that were actually not there in the two weeks prior to the survey. Eight percent of men reported that they felt worthless or hopeless or that they wished they were dead in the 12 months prior to the survey. Similar to women, the average number of days that men felt little interest or pleasure in doing things in the past two weeks was less than one, as was the average number of days they felt low in energy, had been in a bad mood, or had been sad. Among men who reported experiencing at least one of these four issues, 9 percent sought medical care. Men age 45-49, rural men, men in Oshana, men with a primary education, and men in the fourth and middle wealth quintiles were most likely to report that they had seen or heard things that were ac