Tanzania - Demographic and Health Survey - 2011

Publication date: 2011

Tanzania Demographic and Health Survey 2010 Tanzania 2010 D em ographic and H ealth Survey NBS Vision To be a preferable source of official statistics in Tanzania NBS Mission To facilitate informed decision-making process, through provision of relevant, timely and reliable user-driven statistical information, coordinating statistical activities and promoting the adherence to statistical methodologies and standards United Republic of Tanzania Tanzania Demographic and Health Survey 2010 National Bureau of Statistics Dar es Salaam, Tanzania ICF Macro Calverton, Maryland, USA April 2011 The 2010 Tanzania Demographic and Health Survey (2010 TDHS) was implemented by the National Bureau of Statistics (NBS) from December 19, 2009 to May 23, 2010. Funding for the survey was provided by the Ministry of Health and Social Welfare (MoHSW), Tanzania Food and Nutrition Centre (TFNC), Department for International Development (DFID), World Health Organization (WHO)/Zanzibar), United Nations Fund for Population Activities (UNFPA), United Nations Children’s Fund (UNICEF), World Food Programme (WFP), United Nations Development Programme (UNDP), and Irish Aid. ICF Macro provided technical assistance for the survey through its MEASURE DHS programme. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the U.S. Agency for International Development or the Government of Tanzania. Additional information about the survey may be obtained from the National Bureau of Statistics Director General, P.O. Box 796, Dar es Salaam, Tanzania (Telephone: 255-22-212-2724; Email: dg@nbs.go.tz) or National Bureau of Statistics General Office, P.O. Box 796, Dar es Salaam, Tanzania (Telephone: 255-22-212-2722/3; Fax 255-22-213-0852; website: www.nbs.go.tz). Information about the DHS programme may be obtained from MEASURE DHS, ICF Macro, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705, USA; Telephone: 301-572-0200, Fax: 301-572- 0999, E-mail: reports@measuredhs.com, Internet: http://www.measuredhs.com. Recommended citation: National Bureau of Statistics (NBS) [Tanzania] and ICF Macro. 2011. Tanzania Demographic and Health Survey 2010. Dar es Salaam, Tanzania: NBS and ICF Macro. Contents | iii CONTENTS Page TABLES AND FIGURES . ix FOREWORD . xvii SUMMARY OF FINDINGS . xix MAP OF TANZANIA . xvi CHAPTER 1 INTRODUCTION 1.1 Geography, History, and the Economy .1 1.2 Population.2 1.3 Population, Family Planning, and HIV Policies and Programmes.2 1.4 Objectives and Organisation of the Survey .5 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2.1 Population by Age and Sex.11 2.2 Household Composition .12 2.3 Children’s Living Arrangements and Parental Survival .13 2.4 Education of the Household Population .15 2.4.1 Educational Attainment.15 2.4.2 School Attendance Rates .18 2.5 Household Environment.21 2.5.1 Drinking Water.21 2.5.2 Household Sanitation Facilities .23 2.5.3 Housing Characteristics.24 2.5.4 Household Possessions .25 2.6 Wealth Index .26 2.7 Birth Registration.27 2.8 Household Food Security .29 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS 3.1 Characteristics of Survey Respondents.31 3.2 Education.33 3.2.1 Educational Attainment .33 3.2.2 Literacy .36 3.3 Access to Mass Media .38 3.4 Employment .41 3.4.1 Employment Status.41 3.4.2 Occupation.44 iv │ Contents 3.5 Adult Health Issues.47 3.5.1 Health Insurance Coverage .47 3.5.2 Tobacco Use .51 CHAPTER 4 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS 4.1 Current Fertility.55 4.2 Fertility Differentials by Background Characteristics.56 4.3 Fertility Trends .58 4.4 Children Ever Born and Living.60 4.5 Birth Intervals.61 4.6 Age at First Birth.63 4.7 Teenage Pregnancy and Motherhood.64 CHAPTER 5 FERTILITY REGULATION 5.1 Knowledge of Contraceptive Methods.67 5.2 Current Use of Contraceptive Methods .68 5.2.1 Trends in Contraceptive Use .69 5.2.2 Current Use of Contraception by Background Characteristics .70 5.2.3 Current Use of Socially Marketed Pill Brands .72 5.2.4 Current Use of Socially Marketed Condom Brands .72 5.3 Knowledge of Fertile Period .73 5.4 Source of Supply.74 5.5 Informed Choice.75 5.6 Future Use of Contraception .76 5.7 Exposure to Family Planning Messages .77 5.8 Contact of Nonusers with Family Planning Providers .80 5.9 Spousal Discussion about Family Planning.81 5.10 Exposure to Family Planning Dramas.83 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY 6.1 Current Marital Status .91 6.2 Polygyny .92 6.3 Age at First Marriage .94 6.4 Age at First Sexual Intercourse.96 6.5 Recent Sexual Activity .99 6.6 Postpartum Amenorrhoea, Abstinence, and Insusceptibility. 103 6.7 Menopause. 106 CHAPTER 7 FERTILITY PREFERENCES 7.1 Desire for More Children . 107 7.2 Desire to Limit Childbearing by Background Characteristics . 109 7.3 Need for Family Planning Services. 110 7.4 Ideal Number of Children . 112 7.5 Mean Ideal Number of Children by Background characteristics. 114 7.6 Fertility Planning Status . 114 Contents | v 7.7 Wanted Fertility Rates . 115 CHAPTER 8 INFANT AND CHILD MORTALITY 8.1 Levels and Trends in Infant and Child Mortality. 117 8.2 Data Quality . 119 8.3 Socioeconomic Differentials in Infant and Child Mortality . 120 8.4 Demographic Differentials in Infant and Child Mortality. 122 8.5 Perinatal Mortality. 124 8.6 High-Risk Fertility Behaviour . 125 CHAPTER 9 MATERNAL HEALTH 9.1 Antenatal Care . 127 9.1.1 Coverage of Antenatal Care. 127 9.1.2 Number of ANC Visits, Timing of First Visit, and Source Where ANC Was Received. 129 9.1.3 Components of Antenatal Care. 130 9.2 Tetanus Toxoid Injections . 132 9.3 Place of Delivery. 134 9.4 Assistance during Delivery. 136 9.5 Postnatal Care. 138 9.6 Problems in Accessing Health Care . 141 9.7 Fistula . 142 CHAPTER 10 CHILD HEALTH 10.1 Child’s Size at Birth . 143 10.2 Vaccination Coverage . 145 10.2.1 Vaccinations by Background Characteristics . 146 10.3 Trends in Vaccination Coverage . 148 10.4 Acute Respiratory Infection . 149 10.5 Diarrhoeal Disease. 151 10.5.1 Prevalence of Diarrhoea . 151 10.5.2 Treatment of Diarrhoea . 153 10.5.3 Feeding Practices during Diarrhoea. 154 10.6 Knowledge of ORS Packets . 156 10.7 Stool Disposal . 158 10.7.1 Disposal of Children’s Stools . 158 CHAPTER 11 CHILDREN’S AND WOMEN’S NUTRITION 11.1 Nutritional Status of Children . 161 11.1.1 Measurement of Nutritional Status among Young Children . 161 11.1.2 Data Collection. 162 11.1.3 Measures of Child Nutrition Status. 163 11.1.4 Trends in Children’s Nutritional Status . 166 vi │ Contents 11.2 Breastfeeding and Complementary Feeding . 167 11.2.1 Initiation of Breastfeeding . 167 11.2.2 Breastfeeding Status by Age . 169 11.2.3 Duration and Frequency of Breastfeeding . 171 11.2.4 Types of Complementary Foods. 172 11.2.5 Infant and Young Child Feeding (IYCF) Practices . 173 11.3 Prevalence of Anaemia in Children . 175 11.4 Micronutrient Intake among Children. 177 11.5 Iodisation of Household Salt . 181 11.6 Nutritional Status of Women. 182 11.7 Micronutrient Intake among Mothers . 184 11.8 Prevalence of Anaemia in Women . 186 11.9 Micronutrient Intake among Women . 188 CHAPTER 12 MALARIA 12.1 Introduction. 193 12.2 Mosquito Nets . 194 12.2.1 Ownership of Mosquito Nets . 194 12.2.2 Use of Mosquito Nets . 196 12.2.3 Use of Mosquito Nets by Pregnant Women . 199 12.3 Use of Antimalarial Drugs during Pregnancy. 200 12.4 Treatment of Children with Fever. 202 12.4.1 Type and Timing of Antimalarial Drugs . 202 12.5 Anaemia Prevalence. 207 CHAPTER 13 HIV AND AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR 13.1 Introduction. 209 13.2 HIV/AIDS Knowledge, Transmission, and Prevention Methods . 209 13.2.1 Awareness of HIV/AIDS . 209 13.2.3 Rejection of Misconceptions about HIV/AIDS . 212 13.3 Knowledge of Prevention of Mother-to-Child Transmission of HIV . 215 13.4 Attitudes towards People Living with AIDS . 217 13.5 Attitudes towards Negotiating Safer Sex. 219 13.6 High-Risk Sex. 221 13.6.1 Multiple Partners and Condom Use . 221 13.6.2 Transactional Sex. 224 13.7 Coverage of HIV Testing. 225 13.8 Male Circumcision . 229 13.9 Self-Reporting of Sexually Transmitted Infections. 230 13.10 Prevalence of Medical Injections . 232 13.11 HIV/AIDS Knowledge and Sexual Behaviour among Youth. 234 13.11.1 Knowledge about HIV/AIDS and Source for Condoms . 234 Contents | vii 13.11.2 Age at First Sex . 236 13.11.3 Recent Sexual Activity among Young Women and Men . 237 13.11.4 Multiple Partners among Young Adults. 238 13.12 Voluntary HIV Testing among Young Adults . 240 CHAPTER 14 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES 14.1 Employment and Form of Earnings . 243 14.2 Control over Earnings . 244 14.2.1 Control over Wife’s Earnings. 244 14.2.2 Control over Husband’s Earnings . 246 14.3 Women’s Empowerment . 248 14.3.1 Women’s Participation in Decision-Making . 248 14.4 Attitude towards Wife Beating. 251 14.5 Women’s Empowerment Indices. 255 14.6 Current Use of Contraception by Women’s Status. 256 14.7 Ideal Family Size and Unmet Need by Women’s Status. 257 14.8 Women’s Status and Reproductive Health Care . 258 14.9 Differentials in Infant and Child Mortality by Women’s Status . 259 CHAPTER 15 ADULT AND MATERNAL MORTALITY 15.1 Assessment of Data Quality . 261 15.2 Estimates of Adult Mortality. 262 15.3 Estimates of Maternal Mortality . 264 CHAPTER 16 GENDER-BASED VIOLENCE 16.1 Introduction. 267 16.2 Data Collection. 267 16.3 Experience of Physical Violence . 269 16.4 Experience of Sexual Violence . 271 16.5 Marital Control. 277 16.6 Marital Violence. 279 16.7 Frequency of Spousal Violence . 285 16.8 Physical Consequences of Spousal Violence . 287 16.9 Violence Initiated by Women Against Husbands . 288 16.10 Response to Violence. 290 CHAPTER 17 FEMALE GENITAL CUTTING 17.1 Knowledge of Female Genital Cutting . 293 17.2 Prevalence of Female Genital Cutting. 295 17.3 Age at Circumcision . 297 17.4 Circumcision of Daughters . 299 17.5 Attitudes towards Female Circumcision . 300 viii │ Contents REFERENCES . 303 APPENDIX A SAMPLE IMPLEMENTATION .309 APPENDIX B ESTIMATES OF SAMPLING ERRORS .311 APPENDIX C DATA QUALITY TABLES. 331 APPENDIX D PERSONS INVOLVED IN THE 2010 TANZANIA DEMOGRAPHIC AND HEALTH SURVEY . 339 APPENDIX E QUESTIONNAIRES. 343 APPENDIX F MILLENNIUM DEVELOPMENT GOAL INDICATORS.451 Tables and Figures | ix TABLES AND FIGURES Page CHAPTER 1 INTRODUCTION Table 1.1 Basic demographic indicators.2 Table 1.2 Results of the household and individual interviews.10 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS Table 2.1 Household population by age, sex, and residence.11 Table 2.2 Household composition.13 Table 2.3 Children’s living arrangements and orphanhood .14 Table 2.4.1 Educational attainment of the female household population .16 Table 2.4.2 Educational attainment of the male household population .17 Table 2.5 School attendance ratios .19 Table 2.6 Household drinking water.22 Table 2.7 Household sanitation facilities.23 Table 2.8 Household characteristics .24 Table 2.9 Household durable goods .26 Table 2.10 Wealth quintiles.27 Table 2.11 Birth registration of children under age 5 .28 Table 2.12 Household food security .29 Figure 2.1 Population Pyramid .12 Figure 2.2 Age-Specific Attendance Rates of the De Facto Population Age 5 to 24.21 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS Table 3.1 Background characteristics of respondents .32 Table 3.2.1 Educational attainment: Women.34 Table 3.2.2 Educational attainment: Men .35 Table 3.3.1 Literacy: Women .36 Table 3.3.2 Literacy: Men .37 Table 3.4.1 Exposure to mass media: Women.39 Table 3.4.2 Exposure to mass media: Men .40 Table 3.5.1 Employment status: Women .42 Table 3.5.2 Employment status: Men.43 Table 3.6.1 Occupation: Women.45 Table 3.6.2 Occupation: Men .46 Table 3.7 Type of employment: Women.47 Table 3.8.1 Health insurance coverage: Women .49 Table 3.8 2 Health insurance coverage: Men.50 Table 3.9.1 Use of tobacco: Women.52 Table 3.9.2 Use of tobacco: Men .53 Figure 3.1 Employment Status of Women and Men.44 x | Tables and Figures CHAPTER 4 FERTILITY LEVELS, TRENDS, AND DIFFERENTIALS Table 4.1 Current fertility .55 Table 4.2 Fertility by background characteristics .57 Table 4.3 Trends in age-specific fertility rates.58 Table 4.4 Trends in fertility rates.58 Table 4.5 Children ever born and living.61 Table 4.6 Birth intervals.62 Table 4.7 Age at first birth .63 Table 4.8 Median age at first birth .64 Table 4.9 Teenage pregnancy and motherhood.65 Figure 4.1 Age-Specific Fertility Rates by Residence.56 Figure 4.2 Trends in Age-Specific Fertility Rates, 1991, 1999, and 2010.59 Figure 4.3 Trends in Fertility Rates.59 Figure 4.4 Total Fertility Rates in Selected Sub-Saharan Countries .60 Figure 4.5 Adolescent Childbearing .66 CHAPTER 5 FERTILITY REGULATION Table 5.1 Knowledge of contraceptive methods .68 Table 5.2 Current use of contraception by age .69 Table 5.3 Current use of contraception by background characteristics .71 Table 5.4 Use of socially marketed pills by brand .72 Table 5.5 Use of socially marketed condoms by brand .73 Table 5.6 Knowledge of fertile period.74 Table 5.7 Source of modern contraception methods .74 Table 5.8 Informed choice .76 Table 5.9 Future use of contraception .77 Table 5.10.1 Exposure to family planning messages: Women .78 Table 5.10.2 Exposure to family planning messages: Men.79 Table 5.11 Contact of nonusers with family planning providers .80 Table 5.12 Husband’s/partner's knowledge of women's use of contraception.82 Table 5.13.1 Zinduka family planning message: Women.84 Table 5.13.2 Zinduka family planning message: Men .85 Table 5.14.1 Twende na Wakati: Women.86 Table 5.14.2 Twende na Wakati: Men .87 Table 5.15 Exposure to family planning dramas .88 Figure 5.1 Contraceptive Use among Currently Married Women, Tanzania 1991-2010 .70 Figure 5.2 Sources of Contraception among Women Tanzania, 1999-2010.75 Figure 5.3 Trend of Twende na Wakati and Zinduka Radio Drama Listenership, Tanzania, 1999-2010.89 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY Table 6.1 Current marital status .91 Table 6.2 Number of cowives and wives .93 Table 6.3 Age at first marriage .95 Table 6.4 Median age at first marriage.96 Tables and Figures | xi Table 6.5 Age at first sexual intercourse .97 Table 6.6 Median age at first intercourse .99 Table 6.7.1 Recent sexual activity: Women . 100 Table 6.7.2 Recent sexual activity: Men . 102 Table 6.8 Postpartum amenorrhoea, abstinence, and insusceptibility. 104 Table 6.9 Median duration of amenorrhoea, postpartum abstinence, and postpartum insusceptibility. 105 Table 6.10 Menopause. 106 Figure 6.1 Marital Status of Respondents .92 Figure 6.2 Percentage of Currently Married Women Whose Husbands Have at Least One Other Wife.94 Figure 6.3 Age at First Marriage and Age at First Sexual Intercourse .98 CHAPTER 7 FERTILITY PREFERENCES Table 7.1 Fertility preferences by number of living children . 107 Table 7.2.1 Desire to limit childbearing: Women . 109 Table 7.2.2 Desire to limit childbearing: Men. 110 Table 7.3 Need for family planning . 111 Table 7.4 Ideal number of children . 113 Table 7.5 Mean ideal number of children. 114 Table 7.6 Fertility planning status. 115 Table 7.7 Wanted fertility rates. 116 Figure 7.1 Desire for More Children among Currently Married Women. 108 Figure 7.2 Trends in Mean Ideal Family Size among Women and Men, Tanzania 1991-2010 . 113 CHAPTER 8 INFANT AND CHILD MORTALITY Table 8.1 Early childhood mortality rates . 118 Table 8.2 Trends in early childhood mortality rates. 118 Table 8.3 Early childhood mortality rates by socioeconomic characteristics. 120 Table 8.4 Early childhood mortality rates by demographic characteristics. 123 Table 8.5 Perinatal mortality. 124 Table 8.6 High-risk fertility behaviour . 126 Figure 8.1 Trends in Under-5, Infant, and Neonatal Mortality, 1990-2015 . 119 Figure 8.2 Trends in Infant Mortality Rates by Residence, 1991-2010. 121 Figure 8.3 Socioeconomic Differentials in Infant and Under-5 Mortality Rates . 122 Figure 8.4 Demographic Differentials in Infant and Under-5 Mortality. 123 CHAPTER 9 MATERNAL HEALTH Table 9.1 Antenatal care. 128 Table 9.2 Number of antenatal care visits and timing of first visit . 129 Table 9.3 Components of antenatal care . 131 Table 9.4 Tetanus toxoid injections . 133 Table 9.5 Place of delivery . 134 Table 9.6 Assistance during delivery . 137 xii | Tables and Figures Table 9.7 Timing of first postnatal checkup. 138 Table 9.8 Type of provider of first postnatal checkup. 140 Table 9.9 Problems in accessing health care . 141 Figure 9.1 Trends in Number of Antenatal Care Visits . 130 Figure 9.2 Percentage of Births Delivered at a Health Facility, by Mother's Education . 135 CHAPTER 10 CHILD HEALTH Table 10.1 Child's weight and size at birth. 144 Table 10.2 Vaccinations by source of information. 146 Table 10.3 Vaccinations by background characteristics . 147 Table 10.4 Vaccinations in first year of life. 148 Table 10.5 Prevalence of symptoms of ARI . 150 Table 10.6 Prevalence of diarrhoea . 152 Table 10.7 Diarrhoea treatment . 153 Table 10.8 Feeding practices during diarrhoea . 155 Table 10.9 Knowledge of ORS packets . 157 Table 10.10 Disposal of children's stools. 158 Figure 10.1 Proportion of Children with Low Birth Weight . 145 Figure 10.2 Proportion of Children Fully Vaccinated. 148 Figure 10.3 Vaccination Coverage among Children Age 12-23 Months, 2004-05 and 2010. 149 Figure 10.4 Trends in Feeding Practices during Diarrhoea, 1999-2010 . 156 CHAPTER 11 CHILDREN’S AND WOMEN’S NUTRITION Table 11.1 Nutritional status of children . 164 Table 11.2 Initial breastfeeding. 168 Table 11.3 Breastfeeding status by age . 170 Table 11.4 Median duration and frequency of breastfeeding . 171 Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 172 Table 11.6 Infant and young child feeding (IYCF) practices . 174 Table 11.7 Prevalence of anaemia in children . 176 Table 11.8 Micronutrient intake among children . 179 Table 11.9 Presence of iodised salt in household. 181 Table 11.10 Nutritional status of women . 183 Table 11.11 Foods consumed by mothers in the day or night preceding the interview. 185 Table 11.12 Prevalence of anaemia in women . 187 Table 11.13 Micronutrient intake among mothers . 190 Figure 11.1 Nutritional Status of Children by Age . 166 Figure 11.2 Trends in Nutritional Status of Children Under Age 5. 166 Figure 11.3 Infant Feeding Practices by Age . 170 Figure 11.4 Infant and Young Child Feeding (IYCF) Practices . 175 Figure 11.5 Figure 11.5 Trends in Anaemia Status among Children 6-59 Months. 177 Figure 11.6 Trends in Nutritional Status among Women Age 15-49. 184 Figure 11.7 Trends in Anaemia Status among Women Age 15-49. 188 Tables and Figures | xiii CHAPTER 12 MALARIA Table 12.1 Ownership of mosquito nets . 195 Table 12.2 Use of mosquito nets by household members . 196 Table 12.3 Use of mosquito nets by children. 198 Table 12.4 Use of mosquito nets by pregnant women . 199 Table 12.5 Prophylactic use of antimalarial drugs and use of Intermittent Preventive Treatment (IPT) by women during pregnancy. 201 Table 12.6 Prevalence and prompt treatment of fever . 203 Table 12.7 Type and timing of antimalarial drugs taken by children with fever . 205 Table 12.8 Prevalence of haemoglobin <8.0 g/dl in children. 207 Figure 12.1 Ownership of Mosquito Nets by Residence. 196 CHAPTER 13 HIV AND AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR Table 13.1 Knowledge of AIDS. 210 Table 13.2 Knowledge of HIV prevention methods. 211 Table 13.3.1 Comprehensive knowledge about AIDS: Women . 213 Table 13.3.2 Comprehensive knowledge about AIDS: Men. 214 Table 13.4 Knowledge of prevention of mother to child transmission of HIV . 216 Table 13.5.1 Accepting attitudes toward those living with HIV/AIDS: Women . 218 Table 13.5.2 Accepting attitudes toward those living with HIV/AIDS: Men . 219 Table 13.6 Attitudes toward negotiating safer sexual relations with husband . 220 Table 13.7.1 Multiple sexual partners: Women . 222 Table 13.7.2 Multiple sexual partners : Men. 223 Table 13.8 Payment for sexual intercourse and condom use at last paid sexual intercourse: Men. 224 Table 13.9.1 Coverage of prior HIV testing: Women . 226 Table 13.9.2 Coverage of prior HIV testing: Men. 227 Table 13.10 Pregnant women counselled and tested for HIV. 229 Table 13.11 Male circumcision. 230 Table 13.12 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms. 231 Table 13.13 Prevalence of medical injections . 233 Table 13.14 Comprehensive knowledge about AIDS and of a source of condoms among youth . 235 Table 13.15 Age at first sexual intercourse among youth. 236 Table 13.16 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth. 238 Table 13.17 Multiple sexual partners in the past 12 months among youth . 239 Table 13.18 Recent HIV tests among youth . 241 Figure 13.1 Type of Facility Where Last Medical Injection Was Received . 232 CHAPTER 14 WOMEN’S EMPOWERMENT AND DEMOGRAPHIC AND HEALTH OUTCOMES Table 14.1 Employment and cash earnings of currently married women and men . 244 xiv | Tables and Figures Table 14.2.1 Control over women’s cash earnings and relative magnitude of women’s earnings: Women . 245 Table 14.2.2 Control over men’s cash earnings. 247 Table 14.3 Women’s control over their own earnings and over those of their husband. 248 Table 14.4.1 Women’s participation in decision-making . 249 Table 14.4.2 Decision-making according to men. 249 Table 14.5 Women’s participation in decision-making by background characteristics . 250 Table 14.6.1 Attitude towards wife beating: Women. 252 Table 14.6.2 Attitude towards wife beating: Men . 254 Table 14.7 Indices of women’s empowerment . 255 Table 14.8 Current use of contraception by women’s status . 257 Table 14.9 Women’s empowerment and ideal number of children and unmet need for family planning . 258 Table 14.10 Reproductive health care by women’s empowerment. 259 Table 14.11 Early childhood mortality rates by women’s status. 260 Figure 14.1 Number of Decisions in Which Currently Married Women Participate. 249 CHAPTER 15 ADULT AND MATERNAL MORTALITY Table 15.1 Data on siblings . 262 Table 15.2 Adult mortality rates. 263 Table 15.3 Maternal mortality . 265 Figure 15.1 Trends in Adult Mortality, Tanzania 2004-05 and 2010 . 264 CHAPTER 16 GENDER-BASED VIOLENCE Table 16.1 Experience of physical violence. 270 Table 16.2 Persons committing physical violence . 271 Table 16.3 Force at sexual initiation . 272 Table 16.4 Experience of sexual violence . 273 Table 16.5 Persons committing sexual violence . 274 Table 16.6 Experience of different forms of violence . 275 Table 16.7 Violence during pregnancy . 276 Table 16.8 Degree of marital control exercised by husbands . 278 Table 16.9 Forms of spousal violence . 280 Table 16.10 Spousal violence by background characteristics. 282 Table 16.11 Spousal violence by husband's characteristics and empowerment indicators. 284 Table 16.12 Frequency of spousal violence among those who report violence. 285 Table 16.13 Onset of marital violence . 286 Table 16.14 Injuries to women due to spousal violence. 287 Table 16.15 Violence by women against their spouse. 288 Table 16.16 Help seeking to stop violence . 291 Table 16.17 Sources from where help was sought . 292 Tables and Figures | xv Figure 16.1 Percentage of Ever-married Women Who Have Experienced Violence by Their Current or Last Husband/Partner (Ever, Often, Sometimes, and in Past 12 Months) . 281 CHAPTER 17 FEMALE GENITAL CUTTING Table 17.1 Knowledge of female circumcision: Women . 294 Table 17.2 Prevalence of female circumcision and type of circumcision . 296 Table 17.3 Age at circumcision. 298 Table 17.4 Daughter's circumcision experience . 299 Table 17.5 Aspects of daughter's circumcision . 300 Table 17.6 Attitudes towards female genital cutting: women . 301 Figure 17.1 Percentage of Women Circumcised . 297 Figure 17.2 Age at Circumcision, 2004-05 TDHS and 2010 TDHS . 298 APPENDIX A SAMPLE IMPLEMENTATION Table A.1 Sample implementation: Women . 309 Table A.2 Sample implementation: Men. 310 APPENDIX B ESTIMATES OF SAMPLING ERRORS Table B.1 List of selected variables for sampling errors . 314 Table B.2.1 Sampling errors for National sample. 315 Table B.2.2 Sampling errors for Urban sample . 316 Table B.2.3 Sampling errors for Rural areas. 317 Table B.2.4 Sampling errors for Mainland . 318 Table B.2.5 Sampling errors for Mainland Urban . 319 Table B.2.6 Sampling errors for Mainland Rural . 320 Table B.2.7 Sampling errors for Zanzibar region . 321 Table B.2.8 Sampling errors for Unguga. 322 Table B.2.9 Sampling errors for Pemba. 323 Table B.2.10 Sampling errors for Western zone . 324 Table B.2.11 Sampling errors for Northern zone . 325 Table B.2.12 Sampling errors for Central zone . 326 Table B.2.13 Sampling errors for Southern zone . 327 Table B.2.14 Sampling errors for Lake zone. 328 Table B.2.15 Sampling errors for Eastern zone . 329 Table B.2.16 Sampling errors for Southern zone . 330 APPENDIX C DATA QUALITY TABLES Table C.1 Household age distribution . 331 Table C.2 Age distribution of eligible and interviewed women and men . 332 Table C.3 Completeness of reporting . 332 Table C.4 Births by calendar years . 333 Table C.5 Reporting of age at death in days . 334 Table C.6 Reporting of age at death in months. 335 Table C.7 Nutritional status of children . 336 Foreword | xvii FOREWORD The 2010 Tanzania Demographic and Health Survey (TDHS) is successful because of collaboration among government ministries, organisations, departments and individuals. The National Bureau of Statistics (NBS) wishes to extend its sincere gratitude to the Poverty Eradication Department in the Ministry of Finance and to the Ministry of Health and Social Welfare (MoHSW) for partial financing of the local costs of the survey through the pooled fund. Also, we would like to thank the MEASURE Demographic and Health Surveys programme of ICF Macro in Calverton, Maryland, U.S.A., for the provision of technical assistance, with funding from the United States Agency for International Development (USAID). Our sincere gratitude is also extended to all organizations that contributed to the questionnaire contents or to the training of the field staff. These organizations include the Reproductive and Child Health Section and the Policy and Planning Department of the MoHSW; the Tanzania Commission for AIDS (TACAIDS); the Ministry of Community Development, Gender and Children; and the Tanzania Food and Nutrition Centre (TFNC), as well as other development partners and stakeholders. We wish to express our appreciation for the financial support provided by the development partners, and in particular, the Department for International Development (DFID), USAID, the World Health Organisation (WHO), the World Food Programme (WFP), the United Nations Children’s Fund (UNICEF), United Nations Population Fund (UNFPA), the United Nations Development Programme (UNDP), Irish Aid, One UN Fund through Joint Programme 2 and 5 (through MoHWS – Zanzibar), and others who contributed to the successful implementation of the survey. Likewise, a considerable number of individuals contributed significantly to the success of this survey. We would like to thank Aldegunda Komba, Ahmed Makbel, Mlemba Abassy, Sylivia Meku, Deogratius Malamsha, Stephano G. Cosmas, Elinzuu Nicodemo, Israel Mwakapalala, Prisca Mkongwe and Joshua Mwaisemba from the NBS; Amour Bakari and Mbwana O. Mbwana from the Office of Chief Government Statistician (OCGS); Dr. Elias Kwesi, Josbert Rubona, and Clement Kihinga from MoHSW; Dr. Sabas Kimboka, Dr. Vincent Assey, and Michael Maganga from TFNC; Rashid K. Khamis from MoHSW – Zanzibar; Edith Mbatia from UNICEF; and Rosemary Komanga from the Ministry of Community Development, Gender and Children. We are even more grateful to the interviewers and supervisors who worked tirelessly to ensure that the data collected was of good quality, and to the survey respondents who generously contributed part of their time to enable the survey teams to gather crucial information for our country. Dr. Albina Chuwa, Director General, National Bureau of Statistics, Dar es Salaam. Summary of Findings | xix SUMMARY OF FINDINGS The 2010 Tanzania Demographic and Health Survey (TDHS) is the eighth in a series of Demographic and Health Surveys conducted in Tanzania. The 2010 TDHS is a nationally repre- sentative survey of 10,300 households selected from 475 sample points throughout Tanzania. All women age 15-49 in these households and all men age 15-49 in a subsample of one-third of the households were individually interviewed. The sample was designed to produce separate esti- mates on key indicators for the national level, for urban and rural areas, and for seven zones. For selected indicators, estimates can be calculated at the regional level. The survey collected information on fertility levels and preferences, marriage, sexual activity, awareness and use of family planning methods, maternal and child health, breastfeeding prac- tices, nutritional and anaemia status of women and young children, childhood mortality, use of bed nets and antimalarials, awareness and behav- iour regarding HIV/AIDS and other sexually transmitted infections (STIs), female genital cut- ting (FGC), and adult and maternal mortality. This survey also included an important module on domestic violence. The National Bureau of Statistics (NBS) conducted the survey, which took place in the field from 19 December 2010 to 23 May 2011. Funding for the survey was provided by the Tan- zanian government through the Ministry of Health and Social Welfare (MoHSW), Tanzania Food and Nutrition Centre (TFNC), Department for International Development (DFID), World Health Organization (WHO)/Zanzibar), United Nations Fund for Population Activities (UNFPA), United Nations Children’s Fund (UNICEF), World Food Programme (WFP), United Nations Development Programme (UNDP), and Irish Aid. ICF Macro provided technical assistance for the survey through its MEASURE DHS programme. FERTILITY Fertility Levels and Trends. The total fer- tility rate (TFR) in Tanzania is 5.4 children per woman. This means that, at current fertility lev- els, the average Tanzanian woman will have given birth to 5.4 children by the end of her life- time. The 2010 TDHS estimate of fertility is lower than the rate estimated by the 2004-05 TDHS (5.7 births per woman), which was similar to the rates established in the 1996 TDHS (5.8 births) and in the 1999 Tanzania Reproductive and Child Health Survey (TRCHS) (5.6 births). At the current level, evidence suggests that fertil- ity in Tanzania may have started to decline. Fertility Differentials. The TFR differs widely within Tanzania. The TFR in Mainland is 5.4, while in Zanzibar it is 5.1 births per woman. In Mainland, the TFR ranges from 3.9 in the Eastern zone to 7.1 in the Western zone. Fertility is negatively associated with the educational at- tainment of the mother. Women with secondary or higher education have four fewer children than women with no education (3.0 children per woman with education and 7.0 children per woman without education, respectively). Initiation of Childbearing. Twenty-three percent of women age 15-19 have begun child- bearing: 17 percent are already mothers, and 6 percent are pregnant with their first child. The percentage of women age 15-19 who have begun childbearing has declined from that in the 2004-05 TDHS (26 percent). The median age at first birth is age 19.5, which means that half of women give birth for the first time before age 20. The largest variation in age at first birth is by the level of a woman’s education, which ranges from 18.7 years among women with no education to 23.0 years among women with at least some secondary education. Fertility Preferences. Although two-thirds of currently married women say that they want more children, 44 percent of those currently mar- ried also say that they want to wait for two or more years before having their next child. Over time, the desire to space births among currently married women has increased slightly, from 36 percent in the 1999 TRCHS to 42 percent in the 2004-05 TDHS. However, the desire to limit xx * Summary of Findings births has hardly changed (32 percent in 2004-05 and 31 percent in 2010). Unplanned Fertility. While most births in Tanzania are wanted at the time of pregnancy (73 percent), 23 percent are mistimed and 4 percent are unwanted. The proportion of births that are mistimed increased from 18 percent in 2004-05, while the proportion of unwanted births has changed little. FAMILY PLANNING Knowledge of Contraception. Knowledge of contraception is almost universal in Tanzania. There has been a gradual increase since the early 1990s, when knowledge of any contraception was 74 percent for all women in the 1991-92 TDHS. The most commonly known methods among both men and women are the birth control pill, injectables, and male condoms. Use of Contraception. Thirty-four percent of currently married women are using a method of contraception, including 27 percent who are using a modern method. Injectables are the lead- ing method, used by 11 percent of married women. The pill and traditional methods are also common, each used by 7 percent of currently married women. Current contraceptive use is higher among sexually active unmarried women than among married women (51 and 34 percent, respec- tively), primarily due to the use of male condoms and injectables (16 percent and 15 percent, re- spectively). Trends in Contraceptive Use. The percent- age of married women using a modern method of contraception has changed significantly since the 1991-92 TDHS. The increase is partly the result of a small shift from traditional to modern meth- ods. Modern method use increased from 7 per- cent in 1991-92 to 27 percent in 2010. The most notable change in the mix of modern methods used by married women has been a gradual in- crease in the proportion using injectables (less than 1 percent in 1991-92 compared with 6 per- cent in 1999 and 11 percent in 2010. Differentials in Contraceptive Use. There are significant variations in contraceptive use by background characteristics. Married women in urban areas are much more likely than their rural counterparts to use a family planning method (46 and 31 percent, respectively). Current use of any method increases greatly with education, from 22 percent of married women with no education to 52 percent of married women with at least sec- ondary education. Women in the Lake and West- ern zones are least likely to use contraception (18 and 20 percent, respectively). Source of Modern Methods. Government and parastatal facilities are the most common sources of contraceptives, serving as the point of distribution for two-thirds of modern method users. Among these facilities, dispensaries are the most commonly used source of modern methods (36 percent). More than half of pill us- ers and users of injectables obtain their contra- ceptives from a dispensary. Public and private district hospitals are the primary source for fe- male sterilisation (65 percent and 14 percent, respectively). Private pharmacies and shops are the most important sources for male condoms (81 percent). Unmet Need for Family Planning and Fu- ture Use. Twenty-five percent of currently mar- ried women have an unmet need for family plan- ning: 16 percent have an unmet need for spacing, and 9 percent have an unmet need for limiting. The level of unmet need has not changed from that in the 2004-05 TDHS. The total demand for family planning among currently married women is 54 percent, of which more than half (58 per- cent) is satisfied. The demand for spacing pur- poses is one and a half times as high as the de- mand for limiting purposes 37 and 23 percent, respectively). Among currently married nonusers, 54 per- cent intend to use in the future. More than half of women who are not using family planning visited a health facility in the past 12 months: although 20 percent discussed family planning with staff, 32 percent did not talk about family planning during the visit. This data indicates missed op- portunities to increase acceptance and use. CHILD HEALTH Childhood Mortality. The 2010 TDHS es- timate of the infant mortality rate for the five years preceding the survey is 51 deaths per 1,000 live births. The overall under-5 mortality rate for the period is 81 per 1,000. The 2010 TDHS data indicate a continuing rapid decline in childhood mortality. Infant mortality has been cut almost in half, dropping from 96 deaths per 1,000 births in Summary of Findings | xxi the 1996-2000 period to 51 deaths per 1000 births in 2010. At this pace, in 2015, Tanzania will reach the goal set for the infant mortality rate of 38 deaths per 1,000 live births. Shorter birth intervals are strongly associated with higher mortality, both during and after in- fancy. Under-5 mortality for births that occur four or more years apart is almost half the mor- tality that occurs for births two years apart (74 and 136 deaths per 1,000 live births). Childhood Vaccination Coverage. The 2010 TDHS shows that, according to vaccination cards or mother’s report, 75 percent of children age 12-23 months are fully immunised. Child- hood immunisation has increased from the level measured in the 2004-05 TDHS (71 percent). With the exception of polio 0 and measles, more than 80 percent of the reported vaccinations were received by age 12 months, as recommended. Only 3 percent of children have not received any vaccinations at all. Childhood Illness and Treatment. Accord- ing to mothers’ reports, 4 percent of children un- der age 5 showed symptoms of acute respiratory infection (ARI), 23 percent had fever, and 15 percent had diarrhoea in the two weeks preceding the survey. Among children with diarrhoea, 53 percent were taken to a health care provider. Sixty-three percent of children with diarrhoea were given oral rehydration salt therapy, recom- mended home fluids, or increased fluids. Al- though 18 percent of mothers said they gave their sick child more liquid than usual to drink, four in ten mothers said they reduced or completely stopped fluid intake. NUTRITION Breastfeeding Practices and Complemen- tary Feeding. Almost all children in Tanzania (97 percent) are breastfed. Placing the child to the breast during the first day is also very com- mon (94 percent). However, only 49 percent of children are breastfed within the first hour after birth. These figures show little change since the 1996 TDHS. The median duration of breastfeeding in Tanzania (21 months) has not changed much in the past decade. Although WHO recommends exclusive breastfeeding for six months, half of children under age 3 in Tanzania are exclusively breastfed for only 2.4 months. Complementary feeding in Tanzania starts early. Fourteen percent of children age 2 to 3 months receive liquids other than breast milk, and one-third receive complementary foods. Half of children less than 6 months are exclusively breastfed. This is an increase from 32 percent in the 1999 TRCHS and from 41 percent in the 2004-05 TDHS. More than 9 in 10 children age 6 to 9 months are fed complementary foods. Foods made from grains constitute the majority of their diet. Intake of Vitamin A. Sixty-two percent of the youngest children age 6-35 months ate fruits and vegetables rich in vitamin A during the day and night before the interview. Sixty-one percent of the youngest children age 6-59 months who are living with their mother received a vitamin A supplement in the six months before the survey, a substantial increase from 46 percent in 2004-05. Prevalence of Anaemia. Anaemia contrib- utes to several serious health problems for women and children. The 2010 TDHS tested the haemoglobin level of children age 6-59 months and women age 15-49 years. The data show that there has been a decline in the prevalence of any anaemia among children (72 percent in 2004-05 down to 59 percent in 2010). Twenty-seven per- cent of children have mild anaemia, 29 percent have moderate anaemia, and 2 percent have se- vere anaemia. Anaemia is less prevalent among women than among children. Forty percent of women have some level of anaemia, with 29 percent be- ing mildly anaemic, 10 percent moderately anaemic, and 1 percent severely anaemic. Nutritional Status of Children. The 2010 TDHS measured three anthropometric indicators of nutritional status in children: height-for-age, weight-for-height, and weight-for-age. At the national level, 42 percent of children under 5 have low height-for-age or are stunted, 5 percent have low weight-for-height or are wasted, and 16 percent have low weight-for-age, which reflects both chronic and acute undernutrition. These re- sults reflect a mix in progress in nutritional status from the 2004-05 TDHS when these indicators were measured at 38, 3, and 22 percent, respec- tively. The children in the Central and Southern Highlands zone are particularly disadvantaged— at least half are stunted, which reflects long-term undernutrition in the area. xxii * Summary of Findings Nutritional Status of Women. A body mass index (BMI) of less than 18.5 is considered un- dernourished. In the 2010 TDHS, 11 percent of women were found to fall below this cutoff point. Twenty-two percent of Tanzanian women weigh more than they should: 15 percent are overweight and 6 percent are obese. MATERNAL HEALTH Antenatal Care. Almost all women (96 per- cent) who gave birth in the five years preceding the survey received antenatal care (ANC) from a health professional at least once. Only 43 percent of women received the recommended 4+ ANC visits, and only 15 percent received their first ANC visit during the first trimester of pregnancy. Nurses and midwives are the attendants that pro- vide most ANC (80 percent). During an antenatal visit, about two-thirds of women had their blood pressure measured, more than half had a blood sample taken, and less than half had a urine sample taken. Half of women (53 percent) were informed of the signs of preg- nancy complications, and 48 percent) received at least two tetanus toxoid injections during preg- nancy. Care during Childbirth. A skilled attendant at birth with the proper equipment and environ- ment can reduce the incidence and severity of obstetric and newborn complications. In the 2010 TDHS, 50 percent of births occurred in health facilities, compared with 44 percent in the 1999 TRCHS. Nearly all institutional births take place in public sector facilities. Half of births (51 percent) were assisted by health professionals. Nurses and midwives are the most common birth attendants, assisting in 42 percent of births. Doctors or AMOs attend 5 per- cent of births. Fifteen percent of births were as- sisted by trained or traditional birth attendants, and 30 percent of births were attended by rela- tives or other untrained people. Five percent of births are delivered by caesarean section, higher than the percentage observed in the 2004-05 TDHS. Care after Childbirth. Postnatal care is im- portant, both for the mother and the child, to treat complications arising from the delivery and to provide the mother with important information on how to care for herself and her child. The postnatal period is defined as the time between the delivery of the placenta and 42 days (6 weeks) following the delivery. The 2010 TDHS results show that two-thirds of women whose birth occurred in the past five years did not re- ceive a postnatal checkup (65 percent). In total, 31 percent were examined within two days of delivery, as recommended. Female Genital Cutting (FGC). Fifteen percent of women in Tanzania are circumcised. The 2003-04 Tanzania HIV/AIDS Indicator Sur- vey (THIS) and the 1996 TDHS measured the prevalence of FGC at 18 percent. Younger women in the 2010 TDHS are less likely to be circumcised, especially those age 15-19. Female genital cutting is common in the Northern and Central zones (more than 40 percent). It is much less common (less than 10 percent) in the rest of the country. More than 70 percent of women in Manyara region have been circumcised. Almost all women and men (approximately nine in ten) say that they favour the discontinua- tion of the practice of FGC. Even among women who are circumcised themselves, 77 percent be- lieve that FGC should be discontinued. ADULT MORTALITY Adult Mortality. The 10-year mortality rate among women (5.1 deaths per 1,000 years of exposure) is similar to that among men (5.0 deaths per 1,000 years of exposure). The age- specific rates among women age 15-39 increase with increasing age. Female mortality exceeds male mortality in the age group 20-34, which is when most women bear children. In the age group 35-44, male mortality exceeds female mor- tality by increasing margins as age advances. Maternal Mortality. The 2010 TDHS in- cluded questions on survival of siblings to meas- ure adult and maternal mortality. The estimate of the maternal mortality ratio (MMR) for the 10- year period preceding the survey is estimated as 454 maternal deaths per 100,000 live births. In other words, for every 1,000 live births in Tan- zania during this period, about four to five women died of pregnancy-related causes. The 95 percent confidence intervals indicate that the true maternal mortality ratio from the 2010 TDHS ranges from 353 to 556 deaths per 100,000 live births. Summary of Findings | xxiii MALARIA Nets. Three in four households own at least one mosquito net, but only 64 percent own an insecticide-treated net (ITN), and 54 percent own at least one long-lasting insecticide net (LLIN). Although urban households are much more likely to own at least one net than rural households, rural households are more likely than urban households to have LLINs (57 percent compared with 44 percent). Seventy-two percent of children under age 5 slept under a net the night before the interview, 64 percent slept under an ITN, and 24 percent slept under an LLIN. Net use is most common for children under 1 year, and decreases slightly with each year up to age 5. There is no difference in net use by sex of the child. Although urban children have more access to any net than rural children, rural chil- dren are more likely than urban children to sleep under an LLIN (26 and 17 percent, respectively). Use of a mosquito net among pregnant women is similar; 68 percent of pregnant women slept un- der a net the night before the survey, 57 percent slept under an ITN, and 25 percent slept under an LLIN. Antimalarials. Two in three pregnant women (66 percent) reported receiving at least one dose of SP/Fansidar during an antenatal care visit. However, only 27 percent of pregnant women received complete intermittent preventa- tive treatment or 2+ doses of SP/Fansidar during ANC visits. Two in three children with fever in the two weeks before the survey received advice or treatment from a health facility or provider, 59 percent received an antimalarial drug, and 41 percent of these children received the medication on the day the fever started or the day after. In Mainland, artemisinin-based combination ther- apy (ACT) is currently the recommended first- line antimalarial drug, given to 38 percent of children with fever. In Zanzibar, the first line malaria treatment is amodiaquine (9 percent). HIV/AIDS AND OTHER STIS Awareness of AIDS. Knowledge of AIDS is widespread, with 99 percent of respondents hav- ing heard of AIDS. At least 95 percent of all re- spondents, regardless of background characteris- tics, have heard of the epidemic. An in-depth understanding of AIDS, however, is less com- mon. Comprehensive knowledge of HIV/AIDS is defined as (1) knowing that both consistent con- dom use and limiting sex to one uninfected part- ner are HIV prevention methods, (2) being aware that a healthy-looking person can have HIV, and (3) rejecting the two most common local miscon- ceptions—that HIV/AIDS can be transmitted through mosquito bites and by sharing food with someone who has AIDS. Less than half of the respondents have comprehensive knowledge of HIV/AIDS transmission and prevention methods: 48 percent of women and 46 percent of men. Comprehensive knowledge is lowest among young people age 15-24 (43 percent). HIV Testing and Counselling. In Tanzania, 59 percent of women age 15-49 and 43 percent of men age 15-49 have ever been tested for HIV, and 55 percent of women and 40 percent of men have been tested at some time and have received the results of their HIV test. Three in ten women and 25 percent of men were tested for HIV in the year preceding the survey and received the re- sults of their test. These figures are much higher than those recorded in the 2004-05 TDHS (6 per- cent of women and 7 percent of men) and in the 2007-08 THMIS (19 percent of women and 19 percent of men), suggesting that Tanzanians are increasingly aware of opportunities for testing and learning their HIV status. Overall, 64 percent of women who gave birth in the two years preceding the survey received HIV counselling during antenatal care, and al- most all of these women also received post-test counselling (63 percent). Over half of the women (55 percent) had pretest counselling and then an HIV test, after which they received the test re- sults. Self-Reporting of Sexually Transmitted Infections. Three percent each of women and men in Tanzania reported having had an STI in the past 12 months. Five percent of women and 3 percent of men reported having had an abnormal genital discharge, and 3 percent each of women and men reported having had a genital sore or ulcer in the 12 months before the survey. In all, 7 percent of women and 6 percent of men reported having an STI, an abnormal discharge, or a geni- tal sore. These numbers, however, may be under- estimates because respondents may be embar- rassed or ashamed to admit to having STIs. xxiv * Summary of Findings HIV-Related Behavioural Indicators. Among those who reported having sex in the 12 months preceding the survey, 21 percent of men and 4 percent of women reported having had more than one sexual partner. Among those who had multiple sexual partners in the past year, 24 percent of men and 27 percent of women re- ported using a condom the last time they had sexual intercourse. Paid sex is considered a special category of higher-risk sex. Fifteen percent of men had commercial sex in the year before the survey. Six in ten men reported condom use during the most recent time they paid for sex. Six in ten never-married young women and 52 percent of never-married young men say that they have never had sex. For women and men, abstinence rates are considerably higher in Zan- zibar than in the Mainland (93 percent compared with 58 percent for women and 81 percent com- pared with 50 percent for men). One in three of never-married women and 37 percent of never- married men had sex in the past 12 months. About half of these women and men (49 and 54 percent, respectively) reported using a condom during their last sexual intercourse. xxvi | Map of Tanzania Introduction | 1 INTRODUCTION 1 1.1 GEOGRAPHY, HISTORY, AND THE ECONOMY Geography The United Republic of Tanzania is the largest country in East Africa, covering 940,000 square kilometres, 60,000 of which are inland water. Tanzania lies south of the equator and shares borders with eight countries: Kenya and Uganda to the north; Rwanda, Burundi, the Democratic Republic of Congo, and Zambia to the west; and Malawi and Mozambique to the south. Tanzania has an abundance of inland water, with several lakes and rivers. Lake Tanganyika runs along the western border and is Africa’s deepest and longest freshwater lake and the world’s second deepest lake. Lake Victoria, the world’s second largest lake, drains into the Nile River, which flows to the Mediterranean Sea. The Rufiji River is Tanzania’s largest river, and it drains into the Indian Ocean south of Dar es Salaam. Although there are many rivers, only the Rufiji and the Kagera, which empties into Lake Victoria, are navigable by anything larger than a canoe. One of Tanzania’s most distinctive geological features is the Great Rift Valley, which was caused by geological faulting throughout eastern Africa and is associated with volcanic activity in the northeastern regions of the country. Two branches of the Great Rift Valley run through Tanzania. The western branch holds Lakes Tanganyika, Rukwa, and Nyasa, while the eastern branch, which ends in northern Tanzania, includes Lakes Natron, Manyara, and Eyasi. Except for a narrow belt of 900 square kilometres along the coast, most of Tanzania lies 200 metres or more above sea level, and much of the country is higher than 1,000 metres. In the north, Mount Kilimanjaro rises to 5,895 metres—the highest point in Africa. The main climatic feature for most of the country is the long dry spell from May to October, followed by a period of rainfall between November and April. The main rainy season is from March to May, along the coast and around Mount Kilimanjaro, with short periods of rain arriving between October and December. In the western part of the country, around Lake Victoria, rainfall is well distributed throughout the year, with the peak period falling between March and May. History Tanzania (formerly Tanganyika) became independent of British colonial rule in December 1961. One year later, on 9 December 1962, it became a republic, severing all links with the British crown except for its membership in the Commonwealth. The offshore island of Zanzibar became independent on 12 January 1964, after the overthrow of the rule of the sultanate. On 26 April 1964, Tanganyika and Zanzibar joined to form the United Republic of Tanzania. Tanzania is currently operating under a multiparty democratic system of government, with the president and the national assembly members being elected every five years. Tanzania’s president can hold office for a maximum of two five-year terms. For administrative purposes, mainland Tanzania is divided into 21 regions, and Zanzibar is divided into 5 regions. Each region is subdivided into several districts. Economy Tanzania has a mixed economy. Agriculture, comprised of crop growing, animal husbandry, forestry, fishery, and hunting, played a key role in past years. In the current economy, activities in the 2 | Introduction service industry account for 42 percent of the gross domestic product (GDP). In 2009 the agricultural sector grew by 3.2 percent compared with growth of 4.6 percent in 2008 (National Bureau of Statistics, 2009). During the same period, the growth rate of crops decreased from 5.1 percent to 3.4 percent and that of livestock decreased from 2.6 percent in 2008 to 2.3 percent in 2009. Drought during the 2008-2009 planting season caused these decreases in growth, particularly in the northern part of Tanzania, where there was inadequate pasture and water for livestock. In 2009, the GDP grew by 6.0 percent, which compared poorly with 7.4 percent growth in 2008. The slowdown in growth for 2009 was attributed to the impact of the global financial crisis as well as the drought in 2008-2009, which affected agricultural production, hydro power generation, and industrial production. They all contribute significantly to total GDP (Ministry of Finance and Economic Affairs, 2009). The 2009 GDP at current prices is Tshs. 28,212,646 million, which is equivalent to Tshs. 15,721,301 million at 2001 constant prices. With an estimated population on the Tanzania Mainland of 40.7 million in 2009, the per capita income is Tshs. 693,185 at current prices, compared with Tshs. 628,259 in 2008, indicating an increase of 10.3 percent. 1.2 POPULATION Tanzania has undertaken four population and housing censuses since achieving independence in 1961. The first census, conducted in 1967, reported a total population of 12.3 million, whereas according to the 2002 census, the population has increased to 34.4 million (see Table 1.1). The 2010 projected population is 43 million (NBS, 2010). Although the population of Tanzania has tripled in the past four decades, the country is still sparsely populated. Despite the scarcity of population, density is high in some parts of the country and has been increasing over time. In 1967, the average population density was 14 persons per square kilometre; by 2002, it had increased to 39 persons per square kilometre. The high population growth rate in Tanzania has been brought about by high fertility and declining mortality levels. According to the 2002 census, the life expectancy at birth is 51 years. The population of Tanzania has continued to be predominantly rural despite the increase in proportion of urban residents over time, from 6 percent in 1967 to 23 percent in 2002. The 2010 projection of the proportion of urban residents is 26 percent (NBS, 2010). 1.3 POPULATION, FAMILY PLANNING, AND HIV POLICIES AND PROGRAMMES National Population Policy The government of the United Republic of Tanzania adopted the National Population Policy in 1992. Since then, developments have taken place, nationally and internationally, that have a direct bearing on population and development. The government revised the National Population Policy in Table 1.1 Basic demographic indicators Selected demographic indicators from various sources, Tanzania 1967-2002 Census year Indicators 1967 1978 1988 2002 Population (millions) 12.3 17.5 23.1 34.4 Intercensal growth rate (percent) 2.6 3.2 2.8 2.9 Sex ratio 95.2 96.2 94.2 96.0 Crude birth rate (CBR) 47 49 46 43 Total fertility rate (TFR) 6.6 6.9 6.5 6.3 Crude death rate (CDR) 24 19 15 14 Infant mortality rate (IMR) 155 137 115 95 Percent urban 6.4 13.8 18.3 23.1 Density (pop./km2) 14 20 26 39 Life expectancy at birth (years) 42 44 50 51 1 Reported rates. See the 1999 NDHS final report for information on data quality. Sources: Bureau of Statistics, 1967; 1978; 1988; National Bureau of Statistics, 2002 Introduction | 3 2006 to accommodate these developments (Ministry of Planning, Economy and Empowerment, 2006). The key objectives of the revised policy are to provide a framework and guidelines for integration of population variables in the development process. Specific issues addressed in the guidelines include (1) determining priorities in population and development programmes, (2) strengthening the preparation and implementation of socioeconomic development planning, and (3) coordinating and influencing other policies, strategies, and programmes that ensure sustainable development. Guidelines for promoting gender equality and the empowerment of women are also included (Ministry of Planning, Economy, and Empowerment, 2006). The 1992 National Population Policy achieved the following: • Increased awareness at all levels of the interrelationships among population, resources, environment, and development • Declines in fertility and infant and child mortality rates and increased life expectancy at birth • Awareness of HIV and AIDS among 95 percent of men and women over age 15 (Ministry of Health and Social Welfare [Tanzania], 2008; Ministry of Health and Social Welfare [Zanzibar], 2008). • Integration of family life education into secondary school and teacher training college curricula • Accelerated elimination of female genital mutilation (FGM) and other harmful traditional practices, as a result of the National Plan of Action 2001–2025 • More nongovernmental organisations (NGOs) and faith-based organisations with the capacity to engage in population-related activities, including advocacy and social mobilisation, service delivery, and capacity building Goals of the Policy The overriding concern of the revised 2006 National Population Policy has been to improve the standard of living and quality of life of the population. The main goal of the policy is to direct development of other policies, strategies, and programmes that ensure sustainable development of the people. Specific goals of this policy focus on: • Attainment of gender equity, equality, women’s empowerment, social justice, and development for all individuals • Sustainable development and eradication of poverty • Harmonious interrelationships among population, resource utilisation, and the environment • Increased and improved availability and accessibility of good quality social services Reproductive and Child Health Strategic Plan (2008-2015) The main goal of this strategic plan is to reduce maternal, neonatal, and child morbidity and mortality and to attain Millennium Development Goals number 4 (to reduce child mortality by two- thirds from the rate in 1990) and number 5 (to reduce maternal mortality by three-quarters from the rate in 1990). The target date for achievement of these goals is 2015. 4 | Introduction Broad objectives: • To provide skilled attendance to women and children during pregnancy, childbirth, postnatal and neonatal periods, and childhood by all levels of the health care delivery system • To strengthen the capacity of individuals, families, communities, and organisations to improve maternal, newborn, and child health Operational targets to be achieved by the end of 2015: • To reduce maternal mortality from 578 deaths to 193 deaths per 100,000 live births • To reduce neonatal mortality from 32 deaths to 29 deaths per 1,000 live births • To reduce under-5 mortality from 112 deaths to 54 deaths per 1,000 live births • To increase coverage of emergency obstetric care from 64 percent to 100 percent of hospitals and basic comprehensive emergency obstetric care services from 5 percent to 70 percent of health centres and dispensaries • To increase modern contraceptive prevalence among women age 15-49 from 20 percent to 60 percent • To increase provision of services that will prevent HIV transmission from mother to child to at least 80 percent of pregnant women, their babies, and their families • To increase the proportion of health facilities offering essential newborn care to 75 percent • To reduce the prevalence of stunting among children under age 5 from 38 percent to 22 percent and to reduce the prevalence of underweight among children under age 5 from 22 percent to 14 percent • To increase coverage of children under age 5 sleeping under ITNs from 47 percent to 80 percent • To increase the number of health facilities providing adolescent-friendly reproductive health services from 10 percent to 80 percent • To increase immunization coverage of DTP-HB3 and measles vaccine to above 90 percent in 90 percent of the districts Strategies: To achieve the targets set for 2015, the following strategies have been launched: • Advocacy and resource mobilization • Health system strengthening and capacity development • Community mobilization • Promotion of reproductive and child health behavioural change • Fostering of partnership and coordination The Ministry of Health and Social Welfare (MoHSW) will mobilize resources and advocate for the reduction of maternal, newborn, and child deaths. MoHSW is also responsible for the overall technical leadership, guidance, and coordination of the implementation and monitoring of the strategic plan. The goal is to accelerate the reduction of maternal, newborn, and child deaths and thereby reach the relevant Millennium Development Goals. The National Policy on HIV/AIDS In response to the HIV/AIDS pandemic, the government of Tanzania has progressed in nearly all areas of HIV/AIDS prevention, care, and treatment. Progress has also been made in impact Introduction | 5 mitigation through communication and advocacy and in community participation through multi- sectoral response. HIV/AIDS is included in the development agenda of the National Strategy for Poverty Eradication, commonly referred to by its Kiswahili acronym, MKUKUTA, and the National Development Vision of 2025. The policy emphasizes mainstreaming HIV/AIDS patients in all sectors. The development of the national guideline on prevention and control of HIV/AIDS in the public sector is an effort by the government to show its commitment to fight the epidemic and improve the well-being of the people (Prime Minister’s Office, 2001). In November 2001, the National Policy on HIV/AIDS was adopted with the goal of providing a framework for leadership and coordination of the national multisectoral response to the HIV/AIDS epidemic (Prime Minister’s Office, 2001). It also provides a framework for strengthening the capacity of institutions, communities, and individuals in all sectors to stop the spread of the epidemic. This includes formulation by all sectors of appropriate interventions to prevent the transmission of HIV/AIDS and other sexual transmitted infections, to protect and support vulnerable groups, and to mitigate the social and economic impact of HIV/AIDS. The National Policy on HIV/AIDS and the National Multisectoral Strategic Framework are tools that guide the implementation of national multisectoral responses. The Tanzania Commission for AIDS (TACAIDS) provides strategic leadership and coordination of multisectoral responses, including monitoring and evaluation, research, resource mobilisation, and advocacy. 1.4 OBJECTIVES AND ORGANISATION OF THE SURVEY The 2010 Tanzania Demographic and Health Survey (TDHS) is the eighth in a series of national sample surveys conducted in Tanzania to measure levels, patterns, and trends in demographic and health indicators. The first TDHS, conducted in 1991-92, was followed by the 1994 Tanzania Knowledge, Attitudes, and Practices Survey (TKAPS), the 1996 TDHS, the 1999 Tanzania Reproductive and Child Health Survey (TRCHS), the 2003-04 Tanzania HIV/AIDS Indicator Survey (THIS), the 2004-05 TDHS, and the 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey (THMIS). The principal objective of the 2010 TDHS is to collect data on household characteristics, fertility levels and preferences, awareness and use of family planning methods, childhood and adult mortality, maternal and child health, breastfeeding practices, antenatal care, childhood immunisation and diseases, nutritional status of young children and women, malaria prevention and treatment, women’s status, female circumcision, sexual activity, knowledge and behaviour regarding HIV/AIDS, and prevalence of domestic violence. The 2010 TDHS was implemented by the National Bureau of Statistics (NBS) and the Office of the Chief Government Statistician - Zanzibar (OCGS); in collaboration with the MoHSW. A Task Force team composed of members from the ministry was formed to oversee all technical issues related to the survey. Funding for the survey was provided by the Tanzania government through the MoHSW, Tanzania Food and Nutrition Centre (TFNC), Department for International Development (DFID), World Health Organization (WHO)/Zanzibar, United Nations Fund for Population Activities (UNFPA), United Nations Children’s Fund (UNICEF), World Food Programme (WFP), United Nations Development Programme (UNDP), and Irish Aid. ICF Macro provided technical assistance for the survey through the MEASURE DHS programme. The United States Agency for International Development (USAID) funded the technical assistance. 6 | Introduction Sample Design The 2010 TDHS sample was designed to provide estimates for the entire country, for urban and rural areas in the Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allowed the estimation of indicators for each of the then 26 regions. To estimate geographic differentials for certain demographic indicators, the regions of mainland Tanzania were collapsed into seven geographic zones. Although these are not official administrative zones, this classification is used by the Reproductive and Child Health Section of the MoHSW. Zones were used in each geographic area in order to have a relatively large number of cases and a reduced sampling error. It should be noted that the zones, which are defined below, differ slightly from the zones used in the 1991-92 and 1996 TDHS reports but are the same as those in the 2004-05 TDHS and the 2007-08 THMIS. Western: Tabora, Shinyanga, Kigoma Northern: Kilimanjaro, Tanga, Arusha, Manyara Central: Dodoma, Singida Southern Highlands: Mbeya, Iringa, Rukwa Lake: Kagera, Mwanza, Mara Eastern: Dar es Salaam, Pwani, Morogoro Southern: Lindi, Mtwara, Ruvuma Zanzibar: Unguja North, Unguja South, Town West, Pemba North, Pemba South A representative probability sample of 10,300 households was selected for the 2010 TDHS. The sample was selected in two stages. In the first stage, 475 clusters were selected from a list of enumeration areas in the 2002 Population and Housing Census. Twenty-five sample points were selected in Dar es Salaam, and 18 were selected in each of the other twenty regions in mainland Tanzania. In Zanzibar, 18 clusters were selected in each region for a total of 90 sample points. In the second stage, a complete household listing was carried out in all selected clusters between July and August 2009. Households were then systematically selected for participation in the survey. Twenty-two households were selected from each of the clusters in all regions, except for Dar es Salaam where 16 households were selected. All women age 15-49 who were either permanent residents in the households included in the 2010 TDHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. In a subsample of one-third of all the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey. Tables pertaining to the sample implementation are presented in Appendix A. Questionnaires Three questionnaires were used for the 2010 TDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. The content of these questionnaires was based on the model questionnaires developed by the MEASURE DHS programme. To reflect relevant issues in population and health in Tanzania, the questionnaires were adapted. Contributions were solicited from various stakeholders representing government ministries and agencies, nongovernmental organi- sations, and international donors. The final drafts of the questionnaires were discussed at a stake- holders’ meeting organised by the NBS. The adapted questionnaires were translated from English into Kiswahili and pretested from 23 July 2009 to 5 August 2009. The final versions of the English questionnaires are attached in Appendix E. The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person Introduction | 7 listed, including age, sex, education, and relationship to the head of the household. For children under age 18, survival status of the parents was determined. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, and ownership and use of mosquito nets. Another use of the Household Questionnaire was to identify the woman who was eligible to be interviewed with the domestic violence module. The Household Questionnaire was also used to record height, weight, and haemoglobin measurements of women age 15-49 and children under age 5, household use of cooking salt fortified with iodine, response to requests for blood samples to measure vitamin A and iron in women and children, and whether salt and urine samples were provided. The Women’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: • Background characteristics (e.g., education, residential history, media exposure) • Birth history and childhood mortality • Pregnancy, delivery, and postnatal care • Knowledge and use of family planning methods • Infant feeding practices, including patterns of breastfeeding • Fertility preferences • Episodes of childhood illness and responses to illness, with a focus on treatment of fevers in the two weeks prior to the survey • Vaccinations and childhood illnesses • Marriage and sexual activity • Husband’s background and women’s work status • Knowledge, attitudes, and behaviour related to HIV/AIDS and other sexually transmitted infections (STIs) • Domestic violence • Female genital cutting • Adult mortality, including maternal mortality • Fistula of the reproductive and urinary tracts • Other health issues, including knowledge of tuberculosis and medical injections The Men’s Questionnaire was administered to all men age 15-49 living in every third house- hold in the 2010 TDHS sample. The Men’s Questionnaire collected much of the same information as the Women’s Questionnaire, but it was shorter because it did not contain a detailed reproductive history, questions on maternal and child health or nutrition, questions about fistula, or questions about siblings for the calculation of maternal mortality. Biomarker Testing Height and Weight Measurement The 2010 TDHS survey included height and weight measurements of women age 15-49 and children under age 5. Weight measurements were obtained using lightweight, SECA mother-infant scales with a digital screen, designed and manufactured under the guidance of UNICEF. Height measurements were carried out using a measuring board by Shorr Productions. Children younger than 24 months were measured while lying down, and the height of older children was measured while they were standing. 8 | Introduction Anaemia Testing All children age 6-59 months and women age 15-49 were also eligible for anaemia testing. Individuals eligible for anaemia testing and the parents/guardians of eligible children were advised about the objectives, potential risks, voluntary nature, and confidentiality of the anaemia testing procedures as part of the informed consent process. Parents or guardians of never-married adolescents age 15-17 were asked for permission to test each adolescent before consent of the adolescent was sought. After obtaining informed consent, blood samples were collected with a microcuvette from a drop of blood taken from a finger prick (or a heel prick in the case of very young children or those with small fingers). Haemoglobin analysis was carried out on site using a battery-operated portable HemoCue analyzer, which produces a result in less than one minute. Results were given to the woman and to the child’s parent or guardian, both verbally and in writing. The parents or guardians of children who had anaemia requiring treatment (under 7 g/dl) were provided with a written referral to a health facility for treatment. Women with severe anaemia (haemoglobin less than 7g/dl for non-pregnant women or less than 9 g/dl for pregnant women) were also provided with a written referral form. Results of the anaemia test were recorded in the Household Questionnaire. In addition to the rapid test conducted at the homes of respondents using the HemoCue methodology, the 2010 TDHS included testing for transferrin receptor (TfR), a measure of iron- deficiency. TfR testing helps to identify the contribution that iron-deficiency makes toaanaemia levels, as opposed to malaria and parasites. TfR tests involved the collection of dried blood spot (DBS) samples on filter papers from both children age 6-59 months and women age 15-49. The DBS samples were taken immediately after the blood drop for the anaemia testing was collected. Filter papers were labelled with bar code identification stickers and dried in special drying boxes. The samples were then stored in ziplock bags with desiccants and sent to NBS headquarters to be registered along with the completed questionnaires from the same cluster, after which they were sent to the Tanzania Food and Nutrition Centre (TFNC) laboratory. Testing was done at the National Public Health Laboratory under TFNC oversight. Vitamin A Testing The same DBS samples were also tested to determine a measure of vitamin A deficiency based on the level of retinol binding protein (RBP). RBP provides a proxy indicator of retinol. This test utilises ELISA testing methodology. To adjust the RBP levels for the influence of infection, a test for C-reactive protein was conducted on a 15 percent subsample. In order to establish an adjustment factor to correct for the incomplete elution of RBP from filter paper cards, a study was implemented that involved taking both venous blood samples and DBS samples from a small group of about 50 individuals. Comparison of results from the two samples for the same individuals was used to calculate the correction factor that was applied to all DBS retinol binding protein measurements.6 Iodine Testing The 2010 TDHS included several tests related to iodine. First, in all households, interviewers asked for a teaspoon of salt. The salt was tested for iodine using a simple rapid test kit. Salt that turned any shade of purple after being diluted with a drop of the test solution was considered to be iodised. Second, in every third household, TDHS field teams asked for a slightly larger sample of household salt that was put into a screw-capped plastic container, appropriately labelled and trans- ported to the TFNC lab, where it was then tested for iodine content. Third, interviewing teams requested that women respondents provide a urine sample for subsequent testing for iodine levels. Women who consented were provided with a small plastic cup in Introduction | 9 which to urinate. While in the field the urine was transferred from the plastic cup via a vacuum method into small tubes with tightly fitted caps for transport to the TFNC laboratory, where samples were tested for iodine. Pretest All elements of the survey were pretested prior to the survey. Eleven women and five men participated in the pretest training conducted in Morogoro from 23 July 23 to 5 August 2009. Trainers were staff from NBS, the Zanzibar OCGS, and ICF Macro. Pretest fieldwork was conducted 2-5 August 2009, in Bigwa and Saba Saba wards. A total of 102 Household Questionnaires, 98 Women’s Questionnaires, and 52 Men’s Questionnaires were completed. Training of Field Staff Field staff training took place between 9 November 2009 and 5 December 2009. A total of 59 female nurses, 15 male nurses, 17 field editors, and 14 supervisors were trained. Supervisors and editors were also given specialized training to enable them to perform their duties. Trainers were from the NBS, the MoHSW, the Ministry of Community Development, Gender, and Children, the Tanzania Food and Nutrition Centre, and ICF Macro. Staff from the Methods, Standards, and Coordination Department and the Information Technology and Marketing Department of the NBS also participated in the training. The training was conducted following the DHS training procedures, including classroom presentations, mock interviews, field practice, and tests. Towards the end of the classroom training, the trainees were assigned to 14 teams, as if for the main data collection. The teams visited two health clinics in Hedaru (rural) and Same (urban) to practice the procedures learned in the classroom. Permission to test women and children at the clinics was granted by the medical officer in charge of the facility as well as by the women themselves. Field practice in interviews, anthropometric measurements, and biomarkers was also carried out at this time. During this period, field editors and team supervisors took additional training in methods of field editing, data quality control procedures, and fieldwork coordination. Fieldwork Data collection began on 19 December 2009 and was completed on 23 May 2010. Data were collected by 14 teams, 11 in Mainland and 3 in Zanzibar. Each team consists of four female inter- viewers, one male interviewer, a supervisor, a field editor, and a driver. The field editor and supervisor were responsible for reviewing all questionnaires for completeness, quality, and consistency before the team’s departure from the cluster. Fieldwork supervision was also coordinated at NBS headquarters and at the Office of the Chief Government Statistician—Zanzibar. Seven NBS senior staff formed the Quality Control team. They periodically visited teams to review their work and monitor data quality. Quality control personnel also independently re-interviewed certain households after the team had left a cluster. Close contact between NBS headquarters and the data collection teams was maintained using cell phones. ICF Macro staff participated in field supervision of interviews and biomarker collection. Data Processing The processing of the 2010 TDHS data began shortly after the fieldwork commenced. Completed questionnaires were returned to the NBS head office in Dar es Salaam, where they were entered and edited by data processing personnel who were specially trained for this task. Data processing included office editing, coding of open-ended questions, data entry, and editing of 10 | Introduction computer-identified errors. The data were processed by a team of 10 data entry clerks, 3 data editors, 2 data entry supervisors, and 2 programmers. One staff member was assigned to receive and check the blood samples received from the field. Data entry and editing were accomplished using the CSPro software. Field teams were advised of problems detected during the data entry to improve performance with the use of field check tables. The process of office editing and data processing was initiated on 25 January 2010 and completed on 15 June 2010. The DBS, urine, and salt samples received from the field were logged in at NBS, checked, and delivered to TFNC to be tested. The processing of DBS samples for the vitamin A testing was handled by three laboratory technicians, while anaemia testing was handled by three laboratory technicians, and iodine testing was done by four laboratory technicians. The samples were logged into the CSPro Test Tracking System (CHTTS) database, and each was given a laboratory number. Response Rates Table 1.2 shows household and individual response rates for the 2010 TDHS. Response rates are important because a high rate of nonresponse may affect the results. A total of 10,300 households were selected for the sample, of which 9,741 were found to be occupied during data collection. The shortfall occurred mainly because structures were vacant or destroyed. Of the 9,741 existing house- holds, 9,623 were successfully interviewed, yielding a household response rate of 99 percent. In the interviewed households, 10,522 women were identified for individual interview; com- plete interviews were conducted with 10,139 women, yielding a response rate of 96 percent. Of the 2,770 eligible men identified in the subsample of households selected, 91 percent were successfully interviewed. The principal reason for nonresponse among eligible women and men was the failure to find them at home despite repeated visits to the household. The lower response rate for men reflects the more frequent and longer absences of men from households. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Tanzania 2010 Mainland Result Urban Rural Total Zanzibar Total Household interviews Households selected 1,908 6,412 8,320 1,980 10,300 Households occupied 1,762 6,070 7,832 1,909 9,741 Households interviewed 1,720 6,000 7,720 1,903 9,623 Household response rate1 97.6 98.8 98.6 99.7 98.8 Interviews with women age 15-49 Number of eligible women 1,967 6,088 8,055 2,467 10,522 Number of eligible women interviewed 1,884 5,859 7,743 2,396 10,139 Eligible women response rate2 95.8 96.2 96.1 97.1 96.4 Household interviews for male survey Households selected 605 2,040 2,645 630 3,275 Households occupied 555 1,918 2,473 599 3,072 Households interviewed 544 1,902 2,446 598 3,044 Household response rate1 98.0 99.2 98.9 99.8 99.1 Interviews with men age 15-49 Number of eligible men 528 1,641 2,169 601 2,770 Number of eligible men interviewed 466 1,498 1,964 563 2,527 Eligible men response rate2 88.3 91.3 90.5 93.7 91.2 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Household Population and Housing Characteristics | 11 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2 Chapter 2 summarises demographic and socioeconomic characteristics of the population in the households sampled in the 2010 TDHS. Also examined are environmental conditions, such as housing facilities, and household characteristics. This information facilitates interpretation of key demographic, socioeconomic, and health indices and also assists in the assessment of the repre- sentativeness of the survey. For the 2010 TDHS, a household was defined as a person or a group of persons, related or unrelated, who live together and share a common source of food. The Household Questionnaire (see Appendix E) was used to collect information on all usual residents and visitors who spent the night preceding the interview in the household. This method of data collection allows the analysis of either de jure (usual residents) or de facto (those present at the time of the survey) populations. 2.1 POPULATION BY AGE AND SEX Age and sex are important demographic variables that are the primary basis for demographic classification in vital statistics, censuses, and surveys. They are also very important variables in the study of mortality, fertility, and marriage. The distribution of the de facto household population in the 2010 TDHS is shown in Table 2.1 by five-year age groups, according to sex and residence. Because of relatively high levels of fertility in the past, Tanzania has the majority of its population in young age groups. Table 2.1 Household population by age, sex, and residence Percent distribution of the de facto household population by five-year age groups, according to sex and residence, Tanzania 2010 Urban Rural Total Age Male Female Total Male Female Total Male Female Total <5 15.1 14.4 14.7 18.6 17.5 18.0 17.8 16.8 17.3 5-9 13.1 12.5 12.8 17.8 16.0 16.9 16.7 15.2 16.0 10-14 12.2 12.8 12.5 14.9 14.2 14.5 14.3 13.8 14.1 15-19 11.6 11.6 11.6 10.2 8.6 9.4 10.5 9.3 9.9 20-24 8.7 11.5 10.2 6.1 7.0 6.6 6.7 8.0 7.4 25-29 7.8 9.2 8.5 5.2 6.3 5.8 5.8 7.0 6.4 30-34 7.9 7.7 7.8 5.1 5.4 5.2 5.7 5.9 5.8 35-39 6.4 5.2 5.8 4.3 5.5 5.0 4.8 5.4 5.1 40-44 4.8 4.1 4.4 3.7 3.7 3.7 4.0 3.8 3.9 45-49 3.6 2.8 3.2 3.1 3.1 3.1 3.2 3.1 3.2 50-54 2.6 2.2 2.4 2.4 3.1 2.8 2.4 2.9 2.7 55-59 1.9 2.6 2.3 1.9 2.3 2.1 1.9 2.4 2.2 60-64 1.8 1.2 1.5 1.8 2.2 2.0 1.8 1.9 1.9 65-69 1.2 0.6 0.9 1.4 1.6 1.5 1.4 1.4 1.4 70-74 0.6 0.6 0.6 1.4 1.6 1.5 1.2 1.3 1.3 75-79 0.4 0.5 0.5 0.8 0.9 0.8 0.7 0.8 0.8 80 + 0.4 0.5 0.5 1.1 1.0 1.0 0.9 0.9 0.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 4,988 5,608 10,596 17,349 18,507 35,858 22,337 24,115 46,454 Table 2.1 indicates that less than half (47 percent) of the population is under age 15, and most of the other half (49 percent) is age 15 to 64, while the remaining 4 percent is age 65 or older. With only about half of the population in the economically productive age range (15-64), a substantial burden is placed on these people to support older and younger members of the population. The age 12 | Household Population and Housing Characteristics dependency ratio,1 an indicator of the economic responsibility of adults in their productive years, is 107 in Tanzania, indicating that there are 107 dependents for every 100 persons in the productive age group (15-64). This figure is higher than that found in the 1999 Tanzania Reproductive Health and Child Survey (TRCHS) and in the 2004-05 TDHS (both 104 per 100). Figure 2.1 illustrates the age structure of the household population in a population pyramid. The wide base of the pyramid reflects the young age structure of the Tanzanian population and indicates high fertility. This pattern is similar to but smoother than the ones observed in the 1996 TDHS, the 1999 TRCHS, and the 2002 Population and Housing Census. Nevertheless, the drop off from age 10-14 to 15-19 is implausibly sharp and is indicative of some age displacement, presumably to reduce interviewers’ workloads. 2.2 HOUSEHOLD COMPOSITION Information about the composition of households by sex of the head of the household and size of the household is presented in Table 2.2. These characteristics are important because they are associated with household welfare. Table 2.2 shows that one-quarter of Tanzanian households are headed by women. Female- headed households are typically poorer than male-headed households. The average household size is 5.0 persons, with the average household size being lower in the Mainland (4.9) than in Zanzibar (5.6). Over 55 percent of households in Tanzania have a household size of 3 to 6 members. Urban households are smaller than those in rural areas. In Mainland urban, 26 percent of households have 6 or more members compared with 39 percent in Mainland rural and 49 percent in Zanzibar. On the other hand, the proportion of single-person households is higher in Mainland urban households (14 percent) than in Mainland rural households (7 percent) or in Zanzibar (6 percent). Economic resources are often limited in larger households. Where the household size is large, crowd- ing can lead to health problems. 1 Dependency ratio is calculated as a ratio of the number of dependents (age 0-14 and age 65and over) to the total population age 15-64. Figure 2.1 Population Pyramid TDHS 2010 0.4 0.4 0.7 0.7 1 1.2 1.5 1.6 2 2.8 3.1 3.6 4.2 4.8 7.2 7.9 8.7 0.4 0.3 0.6 0.7 0.9 0.9 1.2 1.6 1.9 2.3 2.7 2.8 3.2 5.1 6.9 8.1 8.6 80+ 75-79 70-74 65-69 60-64 55-59 50-54 45-49 40-44 35-39 30-34 25-29 20-24 15-19 10-14 5-9 <5 Age group (years) 0246810 0 2 4 6 8 10 Percent Female Male 1.0 2.0 Household Population and Housing Characteristics | 13 Table 2.2 Household composition Percent distribution of households by sex of head of household and by household size, mean size of household, and percentage of households with orphans and foster children under 18, according to residence, Tanzania 2010 Mainland Characteristic Urban Rural Total Zanzibar Total Household headship Male 76.6 75.2 75.6 76.8 75.6 Female 23.4 24.8 24.4 23.2 24.4 Total 100.0 100.0 100.0 100.0 100.0 Number of usual members 1 13.5 7.0 8.7 5.6 8.6 2 12.4 9.6 10.3 7.7 10.3 3 17.4 13.2 14.3 12.1 14.3 4 17.7 15.9 16.3 12.5 16.2 5 12.7 15.4 14.7 13.1 14.7 6 8.9 12.3 11.4 13.5 11.5 7 7.8 9.9 9.4 10.4 9.4 8 3.9 6.1 5.5 8.6 5.6 9+ 5.7 10.5 9.3 16.6 9.5 Total 100.0 100.0 100.0 100.0 100.0 Mean size of households 4.2 5.2 4.9 5.6 5.0 Percentage of households with orphans and foster children under 18 Foster children1 26.0 26.1 26.1 29.5 26.2 Double orphans 3.1 2.4 2.6 0.8 2.5 Single orphans2 13.0 13.3 13.2 10.1 13.1 Foster and/or orphan children 30.1 31.7 31.3 32.4 31.3 Number of households 2,417 6,959 9,377 246 9,623 Note: Table is based on de jure household members, i.e., usual residents. 1 Foster children are those under age 18 living in households with neither their mother nor their father present. 2 Includes children with one dead parent and an unknown survival status of the other parent. 2.3 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Table 2.3 presents data on the prevalence of orphanhood in Tanzania. The table shows that 59 percent of children under age 18 are living with both parents, 18 percent live with their mothers but not their fathers; 6 percent live with their fathers but not their mothers; and 16 percent live with neither of their natural parents. Not surprisingly, the proportion of children living with both parents decreases with age. That is, younger children are more likely than older children to live with both natural parents. Among children under age 18, urban children are more likely not to live with either parent than rural children (20 and 15 percent, respectively). Table 2.3 shows that 10 percent of children under age 18 have lost at least one of their natural parents, and 1 percent has lost both natural parents. 14 | Household Population and Housing Characteristics Table 2.3 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, Tanzania 2010 Not living with either parent Living with mother but not with father Living with father but not with mother Background characteristic Living with both parents Father alive Father dead Mother alive Mother dead Both alive Only father alive Only mother alive Both dead Missing informa- tion on father/ mother Total Percent- age not living with a biologi- cal parent Percent- age with one or both parents dead Number of children Age 0-4 71.8 18.0 1.6 1.7 0.2 5.5 0.2 0.4 0.1 0.4 100.0 6.2 2.6 8,081 <2 76.7 20.1 1.0 0.5 0.1 1.4 0.1 0.1 0.0 0.2 100.0 1.6 1.2 3,263 2-4 68.5 16.6 2.1 2.6 0.2 8.3 0.2 0.7 0.2 0.6 100.0 9.4 3.6 4,818 5-9 59.0 13.8 3.9 5.2 1.0 13.0 1.0 1.7 0.6 0.9 100.0 16.2 8.2 7,494 10-14 51.6 11.8 6.3 6.4 1.9 14.2 1.6 3.2 2.1 0.8 100.0 21.2 15.4 6,610 15-17 42.6 9.7 7.8 5.7 1.9 18.3 2.9 5.1 4.3 1.8 100.0 30.6 22.1 2,994 Sex Male 60.1 14.0 4.4 4.8 1.2 10.5 1.0 2.0 1.1 0.9 100.0 14.6 9.8 12,570 Female 58.3 14.3 4.2 4.1 1.0 12.6 1.3 2.1 1.4 0.8 100.0 17.4 10.1 12,609 Residence Urban 53.4 16.4 3.9 4.5 1.0 13.6 1.8 2.4 2.2 0.9 100.0 19.9 11.5 5,016 Rural 60.7 13.6 4.4 4.4 1.1 11.0 1.0 2.0 1.1 0.8 100.0 15.0 9.6 20,164 Mainland/Zanzibar Mainland 59.0 14.3 4.3 4.5 1.1 11.5 1.1 2.1 1.3 0.8 100.0 16.0 10.1 24,474 Urban 52.8 16.6 4.0 4.5 1.1 13.5 1.8 2.5 2.2 0.9 100.0 20.1 11.8 4,756 Rural 60.5 13.7 4.4 4.5 1.1 11.0 1.0 2.0 1.1 0.8 100.0 15.0 9.7 19,718 Zanzibar 68.1 9.4 2.6 2.7 0.2 13.7 1.0 1.6 0.3 0.5 100.0 16.5 5.6 705 Unguja 64.1 10.5 2.5 3.0 0.3 15.5 1.2 1.9 0.5 0.6 100.0 19.0 6.4 416 Pemba 74.0 7.8 2.6 2.4 0.0 11.0 0.7 1.1 0.1 0.3 100.0 12.9 4.6 289 Zone Western 64.2 12.4 3.5 4.5 1.1 10.5 0.9 1.7 0.7 0.6 100.0 13.8 7.9 4,721 Northern 61.9 12.5 4.6 3.5 1.1 11.2 1.6 1.8 1.0 0.8 100.0 15.6 10.1 3,688 Central 62.2 16.5 3.4 2.5 1.2 10.4 1.0 1.3 0.8 0.7 100.0 13.5 7.8 2,402 Southern Highlands 62.0 11.5 5.0 4.8 0.7 8.9 1.0 2.6 2.7 0.8 100.0 15.1 12.0 3,489 Lake 53.7 15.0 5.0 5.6 1.4 13.4 0.8 2.7 1.3 1.2 100.0 18.1 11.3 5,153 Eastern 54.5 16.6 4.5 4.2 0.9 12.5 1.6 2.4 1.9 1.0 100.0 18.3 11.4 2,959 Southern 52.2 18.5 3.6 5.8 1.6 13.7 1.2 1.8 0.8 0.7 100.0 17.5 9.2 2,062 Region Dodoma 58.3 19.0 3.8 2.9 1.4 10.2 1.1 1.6 1.0 0.9 100.0 13.9 9.0 1,502 Arusha 62.3 14.1 6.4 3.1 2.9 7.7 0.8 1.7 0.5 0.6 100.0 10.6 12.3 1,021 Kilimanjaro 52.9 12.9 4.9 3.1 0.8 18.2 2.3 2.2 1.4 1.1 100.0 24.1 11.7 864 Tanga 59.1 14.9 4.1 4.3 0.2 10.8 2.3 1.9 1.4 1.0 100.0 16.4 10.0 1,136 Morogoro 58.9 17.5 4.4 4.2 1.2 10.0 0.9 0.9 1.2 0.9 100.0 12.9 8.6 1,149 Pwani 52.0 19.1 2.8 3.8 0.6 14.9 2.2 2.1 1.0 1.4 100.0 20.3 8.8 662 Dar es Salaam 51.6 14.2 5.6 4.3 0.8 13.7 1.9 4.1 3.0 0.8 100.0 22.7 15.6 1,148 Lindi 50.9 27.9 1.9 3.7 0.6 11.5 1.1 1.0 0.7 0.7 100.0 14.3 5.3 410 Mtwara 46.5 19.4 3.9 7.3 1.7 17.2 1.3 2.3 0.1 0.2 100.0 20.9 9.4 815 Ruvuma 58.5 13.0 4.2 5.4 2.1 11.3 1.1 1.7 1.6 1.1 100.0 15.7 11.0 837 Iringa 53.8 16.8 6.7 2.5 0.6 8.4 1.8 3.6 4.2 1.5 100.0 18.1 17.3 1,040 Mbeya 61.7 11.2 4.7 6.9 0.5 9.1 0.6 2.2 2.3 0.8 100.0 14.3 10.3 1,615 Singida 68.8 12.4 2.7 1.8 0.9 10.9 1.0 0.7 0.4 0.5 100.0 13.0 5.9 901 Tabora 63.9 11.2 2.0 6.1 1.3 10.1 1.3 2.3 1.1 0.7 100.0 14.8 7.9 1,215 Rukwa 72.9 5.6 3.6 3.8 1.1 9.0 0.7 1.9 1.4 0.1 100.0 12.9 8.6 833 Kigoma 65.1 16.6 5.4 2.1 0.7 7.6 0.3 1.0 0.9 0.3 100.0 9.8 8.2 1,217 Shinyanga 63.8 10.7 3.3 5.0 1.2 12.2 1.0 1.7 0.5 0.6 100.0 15.4 7.7 2,288 Kagera 57.8 11.5 5.8 6.4 1.9 10.1 1.0 3.0 1.0 1.7 100.0 15.1 12.8 1,607 Mwanza 49.5 17.3 4.1 5.6 1.4 16.8 0.9 2.5 1.1 0.9 100.0 21.2 10.1 2,410 Mara 56.9 15.0 5.8 4.4 0.7 10.9 0.4 2.8 2.0 1.1 100.0 16.1 12.0 1,135 Manyara 77.7 5.6 2.5 3.2 0.0 8.2 0.8 1.1 0.5 0.3 100.0 10.7 5.0 668 Unguja North 66.1 7.6 3.5 2.0 0.8 16.5 1.3 1.6 0.2 0.3 100.0 19.6 7.4 106 Unguja South 54.0 15.0 3.0 3.3 0.0 21.0 1.5 1.1 0.0 1.2 100.0 23.5 5.9 64 Town West 65.8 10.6 2.0 3.3 0.1 13.7 1.0 2.2 0.7 0.6 100.0 17.6 6.1 246 Pemba North 74.9 8.2 2.4 1.2 0.1 11.5 0.5 0.7 0.2 0.3 100.0 12.9 3.9 142 Pemba South 73.1 7.3 2.8 3.6 0.0 10.4 1.0 1.5 0.1 0.3 100.0 12.9 5.3 147 Wealth quintile Lowest 58.4 18.0 6.0 3.0 1.1 10.3 0.8 1.2 0.7 0.5 100.0 12.9 9.9 5,058 Second 60.8 14.1 4.7 3.9 1.7 10.0 0.9 2.2 0.8 0.8 100.0 13.9 10.3 5,640 Middle 61.4 12.5 4.4 5.6 0.8 10.9 0.8 1.8 1.1 0.8 100.0 14.5 9.0 5,721 Fourth 59.5 13.6 3.0 4.3 0.8 12.0 1.4 2.2 2.3 0.9 100.0 17.9 9.9 4,935 Highest 54.4 12.1 2.9 5.6 0.9 15.9 2.1 3.3 1.7 1.1 100.0 22.9 10.9 3,825 Total <15 61.5 14.7 3.8 4.3 1.0 10.6 0.9 1.7 0.9 0.7 100.0 14.1 8.3 22,185 Total <18 59.2 14.1 4.3 4.4 1.1 11.5 1.1 2.1 1.3 0.8 100.0 16.0 9.9 25,179 Note: Table is based on de jure members, i.e., usual residents. Total includes one child with missing information on sex Household Population and Housing Characteristics | 15 2.4 EDUCATION OF THE HOUSEHOLD POPULATION Education is a key determinant of the lifestyle and status an individual enjoys in a society. Studies have consistently shown that educational attainment has a strong effect on reproductive behaviour, contraceptive use, fertility, infant and child mortality, morbidity, and attitudes and awareness related to family health and hygiene. Results from the 2010 TDHS show educational attainment among household members and school attendance among youth. It is worth noting that analysing education indicators for Tanzania is challenging, given the differences in the formal education system between the Mainland and Zanzibar, as well as changes in the different systems over time. For the analysis presented here, all education indicators have been calculated using the following assumptions: the official age for entry into the primary level is age 7; the official primary level of schooling consists of seven grades; those children with at least some post- primary training are assumed to have completed the primary level; and the number of years assumed for completion of secondary school is six. 2.4.1 Educational Attainment Tables 2.4.1 and 2.4.2 present data for each sex on educational attainment of household members age 6 and older. The results confirm that there is a gap in educational attainment between males and females. Although the majority of the household population age 6 and older has some education, 27 percent of females have never attended school; this compares with 18 percent of males. The median number of years of schooling for females is 3.6 years, which is 1 year less than that for males (4.6 years). Urban residents are more likely than rural residents to have attended school and to have remained in school for a longer time. The median number of years of schooling for females and males in urban areas is almost the same (6.2 years and 6.4 years, respectively), compared with just 2.8 years and 3.7 years for rural females and males, respectively. Educational attainment also differs significantly among regions. For example, the highest proportion of the population who have never been to school is found in Tabora (42 percent for females and 34 percent for males) and Dodoma (40 percent for females and 33 percent for males). On the other hand, regions with the lowest proportion of household members who have never attended school are Kilimanjaro (10 percent for females and 4 percent for males) and Dar es Salaam (11 percent for females and 4 percent for males). In Zanzibar, North Pemba has the highest proportion of population with no education (39 percent of females and 29 percent of males). This is an improvement from the 2004-05 TDHS where the percentages are 47 for females and 37 for males, respectively. The most substantial variation in educational attainment is across the wealth quintiles. Only 7 percent of females in the wealthiest households have never been to school, compared with 46 percent of females from the poorest households. The wealth disparity in education is less evident among males; 33 percent of males in the poorest households have never been to school, compared with 4 percent of males in the wealthiest households. 16 | Household Population and Housing Characteristics Table 2.4.1 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 grade completed, according to background characteristics, Tanzania 2010 Background characteristic No education Some primary Completed primary Some secondary Completed secondary More than secondary Don't know/ missing Total Number Median years completed Age 6-9 35.1 64.6 0.0 0.0 0.0 0.0 0.3 100.0 2,863 0.0 10-14 7.5 82.4 5.9 3.9 0.0 0.0 0.3 100.0 3,337 3.6 15-19 9.3 20.3 36.7 33.4 0.2 0.0 0.0 100.0 2,241 6.5 20-24 19.1 14.0 46.9 17.8 1.3 0.6 0.2 100.0 1,933 6.4 25-29 20.4 13.7 54.3 10.7 0.2 0.5 0.0 100.0 1,676 6.3 30-34 19.4 12.8 57.9 8.3 1.3 0.2 0.1 100.0 1,424 6.3 35-39 25.1 11.2 56.8 6.0 0.3 0.6 0.0 100.0 1,313 6.2 40-44 18.4 9.3 65.0 6.3 0.3 0.6 0.2 100.0 920 6.3 45-49 34.4 17.2 41.1 5.8 0.6 0.5 0.3 100.0 742 4.8 50-54 53.7 19.7 20.3 4.8 0.5 0.3 0.6 100.0 706 0.0 55-59 56.5 26.6 11.9 4.2 0.0 0.2 0.5 100.0 578 0.0 60-64 73.0 20.1 4.7 1.2 0.0 0.0 1.0 100.0 470 0.0 65+ 79.7 17.3 1.4 0.5 0.0 0.0 1.1 100.0 1,050 0.0 Residence Urban 12.2 29.5 34.9 21.3 1.1 0.8 0.3 100.0 4,672 6.2 Rural 31.0 36.2 27.0 5.3 0.1 0.1 0.3 100.0 14,589 2.8 Mainland/Zanzibar Mainland 26.5 34.7 29.5 8.4 0.3 0.2 0.3 100.0 18,694 3.6 .Urban 12.1 29.4 36.1 20.2 1.1 0.8 0.3 100.0 4,442 6.2 .Rural 31.1 36.3 27.4 4.8 0.1 0.1 0.3 100.0 14,252 2.8 Zanzibar 23.6 32.7 8.2 34.0 1.0 0.3 0.2 100.0 567 4.8 .Unguja 18.1 32.6 9.5 37.8 1.3 0.5 0.3 100.0 360 5.9 .Pemba 33.3 33.0 6.0 27.3 0.5 0.0 0.0 100.0 208 3.0 Zone Western 35.2 33.4 25.6 5.3 0.2 0.0 0.3 100.0 3,263 2.4 Northern 22.7 32.4 33.3 10.7 0.3 0.2 0.4 100.0 2,979 4.8 Central 34.0 34.4 26.2 5.1 0.1 0.0 0.2 100.0 1,698 2.4 Southern Highlands 24.3 37.1 30.2 7.7 0.2 0.2 0.4 100.0 2,667 3.7 Lake 26.6 39.4 26.3 6.9 0.3 0.0 0.4 100.0 3,569 3.1 Eastern 19.6 29.1 33.3 15.9 1.0 1.1 0.1 100.0 2,674 6.0 Southern 23.9 36.3 32.9 6.7 0.1 0.0 0.1 100.0 1,844 3.8 Region Dodoma 39.6 32.8 22.3 5.2 0.1 0.0 0.0 100.0 1,067 1.4 Arusha 27.3 28.6 33.2 10.1 0.2 0.1 0.4 100.0 746 4.7 Kilimanjaro 9.9 36.7 36.7 15.3 0.8 0.7 0.0 100.0 828 6.1 Tanga 25.5 32.4 32.5 9.2 0.0 0.0 0.4 100.0 951 4.0 Morogoro 24.2 34.3 32.8 8.4 0.2 0.0 0.2 100.0 889 3.9 Pwani 31.9 35.2 26.4 6.5 0.0 0.0 0.0 100.0 532 2.4 Dar es Salaam 11.2 22.9 36.6 25.2 1.9 2.3 0.0 100.0 1,253 6.4 Lindi 35.6 34.8 27.6 2.0 0.0 0.0 0.0 100.0 362 2.2 Mtwara 27.0 35.6 30.8 6.5 0.0 0.0 0.1 100.0 819 3.5 Ruvuma 13.6 38.0 38.3 9.4 0.3 0.1 0.1 100.0 664 5.6 Iringa 16.3 37.7 34.4 10.8 0.1 0.5 0.2 100.0 881 5.0 Mbeya 25.5 36.1 30.0 7.7 0.2 0.0 0.5 100.0 1,247 3.8 Singida 24.5 37.2 32.9 5.0 0.0 0.0 0.5 100.0 631 3.7 Tabora 41.8 29.3 23.2 5.2 0.1 0.0 0.3 100.0 848 1.3 Rukwa 34.4 38.3 24.1 2.6 0.0 0.0 0.5 100.0 540 1.5 Kigoma 31.0 33.6 28.9 6.2 0.1 0.0 0.2 100.0 869 3.2 Shinyanga 33.9 35.6 25.0 4.8 0.4 0.0 0.4 100.0 1,545 2.4 Kagera 28.4 40.3 24.1 6.5 0.0 0.0 0.7 100.0 1,144 2.8 Mwanza 27.7 39.1 24.4 8.0 0.6 0.0 0.2 100.0 1,661 3.0 Mara 21.6 38.9 34.0 5.3 0.0 0.1 0.1 100.0 765 3.8 Manyara 32.7 30.8 29.1 6.3 0.1 0.2 0.9 100.0 454 3.1 Unguja North 31.8 34.4 6.4 26.4 0.7 0.1 0.3 100.0 87 3.1 Unguja South 17.1 35.6 11.5 35.4 0.3 0.0 0.0 100.0 55 5.7 Town West 12.9 31.1 10.2 43.0 1.8 0.7 0.4 100.0 218 6.5 Pemba North 38.7 32.3 4.0 24.5 0.5 0.0 0.0 100.0 100 1.8 Pemba South 28.2 33.6 7.9 29.9 0.4 0.0 0.0 100.0 108 3.8 Wealth quintile Lowest 46.2 32.4 19.7 1.4 0.0 0.0 0.2 100.0 3,565 0.1 Second 37.1 36.3 23.9 2.3 0.0 0.0 0.3 100.0 4,062 1.7 Middle 25.7 39.6 29.7 4.8 0.0 0.0 0.2 100.0 4,004 3.3 Fourth 17.1 36.1 35.4 11.0 0.1 0.0 0.3 100.0 3,796 5.2 Highest 6.9 28.2 35.4 26.5 1.6 1.1 0.2 100.0 3,834 6.4 Total 26.5 34.6 28.9 9.2 0.3 0.2 0.3 100.0 19,261 3.6 Note: Total includes 7 women with age information missing 1 Completed at least grade 7 at the primary level 2 Completed grade 6 at the secondary level Household Population and Housing Characteristics | 17 Table 2.4.2 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 grade completed, according to background characteristics, Tanzania 2010 Background characteristic No education Some primary Completed primary Some secondary Completed secondary More than secondary Don't know/ missing Total Number Median years completed Age 6-9 42.0 57.7 0.0 0.0 0.0 0.0 0.3 100.0 2,940 0.0 10-14 8.0 84.9 3.1 3.8 0.0 0.0 0.2 100.0 3,202 3.2 15-19 6.6 27.4 32.6 33.1 0.2 0.0 0.1 100.0 2,354 6.4 20-24 10.5 13.4 44.8 28.0 2.4 0.7 0.2 100.0 1,495 6.6 25-29 13.5 14.0 54.1 14.7 2.1 1.4 0.3 100.0 1,296 6.4 30-34 13.0 13.2 58.9 11.8 1.6 1.3 0.1 100.0 1,271 6.4 35-39 10.8 12.8 63.9 10.0 1.2 1.2 0.1 100.0 1,076 6.4 40-44 11.7 12.6 64.1 8.5 1.7 1.1 0.3 100.0 886 6.4 45-49 11.1 9.4 66.3 8.4 1.9 2.9 0.0 100.0 724 6.5 50-54 19.1 19.3 47.1 11.0 1.3 1.8 0.4 100.0 547 6.3 55-59 29.5 30.1 29.8 8.2 1.2 0.8 0.4 100.0 427 3.6 60-64 26.6 41.2 24.4 7.3 0.0 0.4 0.3 100.0 400 3.4 65+ 46.8 37.3 11.7 3.1 0.1 0.9 0.2 100.0 940 1.2 Residence Urban 7.8 29.2 33.7 24.3 2.7 2.2 0.1 100.0 4,112 6.4 Rural 21.6 40.7 29.2 7.8 0.2 0.2 0.2 100.0 13,450 3.7 Mainland/Zanzibar Mainland 18.4 38.0 30.9 11.0 0.8 0.6 0.2 100.0 17,057 4.6 Urban 7.7 28.9 34.9 23.4 2.7 2.2 0.1 100.0 3,912 6.4 Rural 21.6 40.7 29.7 7.4 0.2 0.2 0.2 100.0 13,145 3.7 Zanzibar 17.4 39.0 7.8 33.6 1.0 0.9 0.2 100.0 505 4.9 Unguja 12.2 37.8 8.5 38.7 1.1 1.4 0.3 100.0 317 6.0 Pemba 26.2 41.1 6.6 25.1 0.7 0.1 0.1 100.0 188 3.1 Zone Western 27.1 38.8 25.8 7.3 0.5 0.3 0.3 100.0 3,000 3.2 Northern 15.6 37.5 32.9 12.6 0.6 0.5 0.3 100.0 2,815 5.4 Central 27.0 37.1 29.5 5.7 0.3 0.2 0.1 100.0 1,517 3.3 Southern Highlands 14.8 39.4 33.1 10.9 1.0 0.7 0.2 100.0 2,339 5.1 Lake 18.4 41.8 27.2 11.7 0.2 0.5 0.3 100.0 3,204 3.9 Eastern 11.8 31.2 35.5 17.3 2.2 2.0 0.0 100.0 2,572 6.2 Southern 14.6 39.4 35.4 9.5 0.9 0.0 0.2 100.0 1,610 5.0 Region Dodoma 33.2 37.7 24.2 4.5 0.2 0.2 0.2 100.0 920 2.3 Arusha 19.9 35.9 33.0 10.6 0.3 0.1 0.1 100.0 743 4.7 Kilimanjaro 4.3 38.7 35.9 18.8 0.9 1.1 0.3 100.0 705 6.2 Tanga 16.7 40.7 30.6 10.7 1.0 0.1 0.1 100.0 878 4.7 Morogoro 17.9 36.3 34.6 9.3 1.2 0.7 0.0 100.0 956 4.9 Pwani 18.9 40.0 28.4 12.2 0.0 0.3 0.2 100.0 487 4.0 Dar es Salaam 3.7 23.0 39.3 26.2 4.1 3.8 0.0 100.0 1,129 6.6 Lindi 23.4 41.1 29.8 5.1 0.2 0.0 0.4 100.0 321 3.4 Mtwara 16.2 39.2 33.7 9.7 0.9 0.0 0.3 100.0 659 4.6 Ruvuma 8.5 38.7 40.1 11.4 1.3 0.0 0.0 100.0 629 6.1 Iringa 10.7 35.9 36.5 15.5 0.3 1.2 0.0 100.0 787 6.1 Mbeya 15.1 39.7 32.8 9.5 1.8 0.6 0.5 100.0 1,011 5.0 Singida 17.5 36.3 37.8 7.6 0.6 0.2 0.0 100.0 597 5.2 Tabora 34.2 34.6 24.0 6.2 0.2 0.3 0.5 100.0 839 2.4 Rukwa 20.1 43.7 28.7 6.7 0.5 0.3 0.0 100.0 541 3.4 Kigoma 21.8 44.3 23.1 10.0 0.4 0.2 0.3 100.0 751 3.5 Shinyanga 25.7 38.4 28.3 6.5 0.6 0.3 0.3 100.0 1,410 3.5 Kagera 22.5 41.7 23.4 11.1 0.2 0.5 0.6 100.0 1,069 3.2 Mwanza 18.5 40.4 27.8 12.3 0.1 0.8 0.1 100.0 1,484 4.0 Mara 11.6 44.9 32.0 11.2 0.3 0.0 0.0 100.0 651 4.7 Manyara 23.2 32.6 32.6 10.0 0.2 0.6 0.8 100.0 488 4.4 Unguja North 24.2 44.6 5.5 25.5 0.1 0.0 0.2 100.0 71 3.4 Unguja South 10.9 37.8 13.5 36.5 0.8 0.5 0.0 100.0 49 6.1 Town West 8.3 35.4 8.3 44.0 1.5 2.1 0.3 100.0 197 6.6 Pemba North 29.1 42.2 5.0 23.1 0.6 0.1 0.0 100.0 94 2.6 Pemba South 23.3 40.0 8.3 27.1 0.8 0.2 0.2 100.0 94 3.8 Wealth quintile Lowest 32.5 41.6 22.8 2.9 0.0 0.0 0.2 100.0 3,206 2.1 Second 26.9 41.0 27.8 3.9 0.0 0.0 0.2 100.0 3,582 3.0 Middle 17.9 42.4 31.8 7.5 0.1 0.1 0.3 100.0 3,912 4.0 Fourth 11.2 38.7 35.1 14.3 0.4 0.1 0.1 100.0 3,496 6.0 Highest 3.8 25.5 33.1 30.6 3.7 3.1 0.2 100.0 3,365 6.7 Total 18.4 38.0 30.3 11.7 0.8 0.6 0.2 100.0 17,562 4.6 Note: Total includes 5 men with age information missing 1 Completed at least grade 7 at the primary level 2 Completed grade 6 at the secondary level 18 | Household Population and Housing Characteristics 2.4.2 School Attendance Rates Table 2.5 presents for primary school and for secondary school the net and gross attendance ratio (NAR and GAR) for the school year that started in 2009. The presentation is by urban-rural residence, region, and wealth quintile. The NAR for primary school is the percentage of the primary school-age (7-13 years) population that attends primary school. The NAR for secondary school is the percentage of the secondary school-age (14-19 years) population that attends secondary school. By definition, the NAR cannot exceed 100 percent. The GAR for primary school is the total number of primary school students, of any age, expressed as a percentage of the official primary school-age population. The GAR for secondary school is the total number of secondary school students, of any age, expressed as a percentage of the official secondary school-age population. If there are significant numbers of over-age and under-age students at a given level of schooling, the GAR can exceed 100 percent. Persons are considered to be currently attending school if they attended formal academic school at any point during the given school year. The gender parity index (GPI) measures the sex-related differences in school attendance rates and is calculated by dividing the GAR for females by the GAR for males. A GPI of 1 indicates parity, or equality, between the participation rates for males and females. A GPI of less than 1 indicates a gender disparity in favour of males, i.e., a higher proportion of males than females attend that level of schooling. A GPI greater than 1 indicates a gender disparity in favour of females. As illustrated in Table 2.5, 80 percent of primary school-age children (age 7-13) in Tanzania attend primary school. Females age 7-13 are slightly more likely than males to attend primary school (81 and 78 percent, respectively). There is a sizable urban-rural difference in the NAR: 88 percent of children in urban areas attend primary school, compared with 78 percent in rural areas. School-age children from the wealthiest households are also far more likely to attend primary school than children from the least wealthy households (90 percent and 68 percent, respectively). In Tanzania, a substantial proportion of primary school pupils fall outside the official age range for primary schooling. Whereas the primary school NAR is 80 percent, the GAR is 99, indi- cating that for every 80 pupils age 7-13, there are 19 primary school pupils who are either younger than age 7 or older than age 13. The GAR for males (100) slightly exceeds that for females (98), producing a GPI of 0.98. Regional differences in Mainland Tanzania in both NAR and GAR are substantial. The primary school NAR ranges from 91 percent in Kilimanjaro and Ruvuma to 66 percent in Tabora. For primary school, the highest GAR (110 percent) is in Pwani and Iringa regions, and the lowest is in Tabora and Dodoma regions (85 percent). The NAR and GAR are relatively low at the secondary school level. Table 2.5 indicates that only one in four secondary school-age adolescents in Tanzania actually attends secondary school, and one in three youth of any age attends secondary school. While there is a small difference between the NAR for secondary school-age females and males (25 percent and 26 percent, respectively), the secondary school GPI is 0.85, indicating a higher proportion of males than females attends the secondary level (GAR of 34 for males and 29 for females). Secondary school-age youth in urban areas, however, are much more likely than their counterparts in rural areas to attend secondary school (44 percent and 19 percent, respectively). The most striking difference in the secondary school NAR is across wealth quintiles. The secondary school NAR in the wealthiest households (49 percent) is more than five times that in the poorest households (9 percent). Household Population and Housing Characteristics | 19 Table 2.5 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling; and the gender parity index (GPI), according to background characteristics, Tanzania 2010 Net attendance ratio Gross attendance ratio Background characteristic Male Female Total Gender Parity Index Male Female Total Gender Parity Index PRIMARY SCHOOL Residence Urban 89.6 87.1 88.2 0.97 110.6 102.6 106.2 0.93 Rural 75.6 79.6 77.6 1.05 97.8 96.8 97.3 0.99 Region Dodoma 63.5 71.7 67.7 1.13 84.6 85.8 85.2 1.01 Arusha 83.4 85.2 84.3 1.02 108.0 101.0 104.7 0.94 Kilimanjaro 89.7 92.9 91.3 1.04 107.7 108.2 108.0 1.00 Tanga 84.4 82.4 83.4 0.98 110.4 97.6 103.9 0.88 Morogoro 80.8 80.0 80.4 0.99 100.2 97.6 99.0 0.97 Pwani 84.9 87.9 86.6 1.04 119.3 102.5 110.3 0.86 Dar es Salaam 91.1 83.3 86.9 0.92 109.5 98.2 103.3 0.90 Lindi 71.3 75.9 73.4 1.06 90.3 100.1 94.8 1.11 Mtwara 80.6 83.4 82.2 1.03 102.1 102.8 102.5 1.01 Ruvuma 91.4 90.7 91.0 0.99 109.4 104.1 106.6 0.95 Iringa 90.8 89.1 89.9 0.98 110.1 110.4 110.3 1.00 Mbeya 82.2 83.3 82.8 1.01 109.7 99.0 103.6 0.90 Singida 75.5 84.1 79.7 1.11 91.4 96.0 93.7 1.05 Tabora 61.8 70.1 65.7 1.13 82.0 87.6 84.6 1.07 Rukwa 75.5 73.7 74.6 0.98 96.3 89.3 92.9 0.93 Kigoma 76.2 79.3 77.7 1.04 101.6 94.3 98.0 0.93 Shinyanga 70.9 76.6 73.7 1.08 97.1 94.0 95.5 0.97 Kagera 73.7 77.8 75.7 1.06 92.5 101.9 97.0 1.10 Mwanza 73.4 76.3 74.8 1.04 94.4 96.8 95.6 1.03 Mara 84.4 89.5 87.1 1.06 110.7 102.8 106.5 0.93 Manyara 79.3 78.3 78.9 0.99 95.0 92.4 93.8 0.97 Unguja North 71.3 89.3 80.7 1.25 99.7 112.6 106.4 1.13 Unguja South 90.3 94.7 92.6 1.05 112.0 107.5 109.7 0.96 Town West 90.5 92.3 91.5 1.02 108.1 101.0 104.4 0.93 Pemba North 78.2 76.1 77.2 0.97 106.1 95.4 101.1 0.90 Pemba South 75.6 82.9 79.1 1.10 98.1 100.7 99.3 1.03 Wealth quintile Lowest 67.0 68.0 67.5 1.01 87.9 84.6 86.4 0.96 Second 72.7 75.7 74.3 1.04 93.4 93.1 93.3 1.00 Middle 79.8 85.7 82.7 1.07 104.0 103.5 103.8 1.00 Fourth 85.3 87.2 86.3 1.02 110.0 105.0 107.4 0.95 Highest 91.3 89.5 90.3 0.98 109.5 103.3 106.1 0.94 Total 78.1 81.2 79.7 1.04 100.1 98.0 99.0 0.98 Continued. 20 | Household Population and Housing Characteristics Table 2.5—Continued Net attendance ratio Gross attendance ratio Background characteristic Male Female Total Gender Parity Index Male Female Total Gender Parity Index SECONDARY SCHOOL Residence Urban 44.7 43.2 43.9 0.97 59.9 54.2 56.9 0.91 Rural 20.0 17.7 18.9 0.88 26.4 19.7 23.2 0.75 Region Dodoma 10.6 21.6 15.8 2.04 16.6 25.1 20.6 1.51 Arusha 19.1 36.5 27.7 1.91 26.2 38.7 32.4 1.48 Kilimanjaro 45.9 58.0 51.7 1.26 54.1 68.0 60.8 1.26 Tanga 24.4 27.9 26.2 1.14 33.4 32.7 33.0 0.98 Morogoro 21.5 29.1 24.8 1.36 28.2 31.5 29.7 1.12 Pwani 26.1 19.1 23.3 0.73 33.1 24.1 29.4 0.73 Dar es Salaam 45.5 39.1 41.9 0.86 69.4 53.6 60.5 0.77 Lindi 17.1 4.6 11.1 0.27 17.1 4.6 11.1 0.27 Mtwara 27.2 25.6 26.5 0.94 34.0 28.1 31.2 0.83 Ruvuma 29.6 27.8 28.8 0.94 35.9 31.0 33.6 0.86 Iringa 36.5 31.3 34.2 0.86 48.3 38.2 43.9 0.79 Mbeya 18.5 19.7 19.1 1.06 26.0 21.7 23.8 0.83 Singida 20.7 22.9 21.7 1.11 23.2 25.2 24.0 1.09 Tabora 15.2 13.6 14.4 0.89 17.3 15.0 16.1 0.87 Rukwa 17.9 7.8 12.9 0.44 22.3 7.8 15.1 0.35 Kigoma 28.1 15.8 22.2 0.56 35.6 23.0 29.5 0.65 Shinyanga 15.5 12.8 14.1 0.83 20.1 13.3 16.5 0.66 Kagera 23.9 20.7 22.3 0.87 30.0 24.1 27.4 0.80 Mwanza 29.8 20.2 25.0 0.68 39.5 25.0 32.3 0.63 Mara 23.6 16.8 20.2 0.71 40.5 21.2 30.8 0.52 Manyara 31.7 20.6 26.2 0.65 44.4 22.0 33.3 0.49 Unguja North 25.2 43.1 34.6 1.71 37.1 47.2 42.4 1.27 Unguja South 37.2 45.5 41.2 1.23 43.0 50.4 46.6 1.17 Town West 54.0 61.8 57.8 1.14 68.8 83.4 75.9 1.21 Pemba North 35.6 49.7 42.6 1.39 50.1 58.5 54.2 1.17 Pemba South 39.8 46.0 43.0 1.16 55.0 52.8 53.9 0.96 Wealth quintile Lowest 10.0 6.9 8.6 0.69 13.3 7.1 10.5 0.54 Second 11.2 8.9 10.1 0.80 13.7 9.9 11.9 0.72 Middle 20.3 18.4 19.4 0.91 25.7 20.4 23.3 0.79 Fourth 34.2 31.8 33.1 0.93 46.2 36.7 41.5 0.79 Highest 52.5 45.8 48.8 0.87 71.4 57.3 63.6 0.80 Total 25.9 24.7 25.3 0.95 34.3 29.2 31.8 0.85 1 The NAR for primary school is the percentage of the primary-school age (7-13 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school age (14-19 years) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary-school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR(GAR) for females to the NAR(GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR(GAR) for females to the NAR(GAR) for males. Figure 2.2 illustrates age-specific attendance rates (i.e., the percentage of persons of a given age who attend school, regardless of the level attended: primary, secondary, or higher). The figure shows that at age 5-12, the proportion of female youth attending school is higher than male youth, and at age 13 and older the pattern reverses: the proportion of male youth attending school is higher than the proportion of female youth. For example by age 20, 27 percent of males are attending school compared with only 10 percent of females. Attendance rates peak around age 11, with nearly 9 in 10 males and females attending school at that age. Household Population and Housing Characteristics | 21 2.5 HOUSEHOLD ENVIRONMENT The physical characteristics of households are important determinants of the health status of household members, especially children. They can also be used as indicators of the socioeconomic status of households. The 2010 TDHS respondents were asked about their household environment, including questions about access to electricity; source of drinking water; type of sanitation facility; type of flooring, walls, and roof; and number of rooms in the dwelling. The results are presented in Table 2.6. 2.5.1 Drinking Water Increasing access to improved drinking water is one of the Millennium Development Goals that Tanzania along with other nations worldwide has adopted (United Nations General Assembly, 2002). Table 2.6 includes a number of indicators that are useful in monitoring household access to improved drinking water (WHO and UNICEF, 2004). The source of drinking water is an indicator of whether it is suitable for drinking. Sources that are likely to provide water suitable for drinking are identified as improved sources in Table 2.6. These include a piped source within the dwelling, yard, or plot; a public tap, tube well, or borehole; a protected well; and a spring or rainwater.2 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, if the water must be fetched from a source that is not immediately accessible to the household, it may be contaminated during transport or storage. Another factor in considering the accessibility to a water source is the fact that the burden of fetching water often falls disproportionately on female members of the household. Finally, home water treatment can be effective in improving the quality of household drinking water. 2 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 2004). Figure 2.2 Age-Specific Attendance Rates of the De Facto Population Age 5 to 24 TDHS 2010 6 30 65 76 85 90 89 89 81 66 57 47 41 27 20 10 7 3 4 32 22 53 74 83 87 90 88 84 77 65 55 47 40 37 27 17 14 11 8 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Age Percent Female Male 89 90 22 | Household Population and Housing Characteristics Table 2.6 Household drinking water Percent distribution of households and de jure population by source, time to collect, and person who usually collects drinking water; and percentage of households and the de jure population by treatment of drinking water, according to residence, Tanzania 2010 Households Population Mainland Mainland Characteristic Urban Rural Total Zanzibar Total Urban Rural Total Zanzibar Total Source of drinking water Improved source 80.0 47.9 56.2 79.5 56.8 81.2 46.0 53.8 79.6 54.5 Piped water into dwelling/ yard/plot 20.1 3.0 7.4 31.1 8.0 20.9 2.8 6.8 33.6 7.6 Shared tap/standpipe 25.4 4.6 10.0 9.4 10.0 24.5 3.9 8.5 8.4 8.5 Public tap/standpipe 12.4 15.4 14.6 33.6 15.1 12.1 13.8 13.4 32.3 13.9 Tube well or borehole 6.2 1.1 2.4 1.0 2.3 5.6 0.9 1.9 1.1 1.9 Protected dug well 9.9 13.9 12.8 4.1 12.6 11.9 15.5 14.7 4.0 14.4 Protected spring 4.9 9.0 8.0 0.2 7.8 5.3 8.2 7.5 0.2 7.3 Rainwater 0.9 1.0 1.0 0.0 0.9 1.0 0.9 0.9 0.0 0.9 Non-improved source 20.0 52.1 43.8 20.5 43.2 18.8 54.0 46.2 20.4 45.5 Unprotected dug well 9.2 26.9 22.3 18.9 22.2 9.7 29.2 24.9 19.0 24.7 Tanker truck/cart with small tank 5.1 1.1 2.1 1.6 2.1 4.4 0.9 1.6 1.3 1.6 Surface water 3.3 24.0 18.7 0.1 18.2 3.3 23.9 19.3 0.1 18.8 Bottled water 2.5 0.0 0.7 0.0 0.7 1.4 0.0 0.3 0.0 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Provider of water Authority 29.1 13.7 17.6 63.2 18.8 29.1 12.5 16.1 64.3 17.5 CBO/NGO 2.2 3.0 2.8 0.2 2.7 2.4 2.6 2.6 0.3 2.5 Private operator 1.2 1.2 1.2 1.2 1.2 1.4 1.2 1.2 1.3 1.2 No provider 67.4 81.6 78.0 35.3 76.9 67.0 83.4 79.8 34.1 78.4 Missing/don’t know 0.1 0.5 0.4 0.0 0.4 0.1 0.4 0.3 0.1 0.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 19.4 4.8 8.5 28.3 9.0 19.7 5.2 8.4 31.1 9.1 Less than 30 minutes 54.5 43.2 46.1 52.8 46.3 52.8 41.3 43.9 50.1 44.0 30 minutes or longer 25.7 51.9 45.2 18.8 44.5 27.0 53.4 47.6 18.7 46.7 Don’t know/missing 0.4 0.1 0.2 0.0 0.2 0.5 0.1 0.2 0.0 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking Boiled 47.2 24.2 30.1 22.1 29.9 49.4 24.3 29.8 21.2 29.6 Bleach/chlorine 4.8 1.5 2.4 2.1 2.4 5.0 1.6 2.4 2.3 2.4 Strained through cloth 11.6 8.5 9.3 0.3 9.0 13.0 10.0 10.7 0.2 10.4 Ceramic, sand or other filter 0.9 0.4 0.5 0.0 0.5 1.1 0.4 0.6 0.0 0.6 Solar disinfection 0.2 0.0 0.1 0.0 0.1 0.1 0.0 0.1 0.1 0.1 Other 6.6 5.4 5.7 4.2 5.6 6.9 5.2 5.6 4.5 5.5 No treatment 43.5 66.0 60.2 73.1 60.5 40.3 64.6 59.3 73.6 59.7 Percentage using an appropri- ate treatment method 52.9 30.7 36.5 23.8 36.1 55.9 32.3 37.5 23.1 37.1 Number 2,417 6,959 9,377 246 9,623 10,239 36,097 46,336 1,391 47,728 1 Because the quality of bottled water is not known, households using bottled water for drinking are classified as using an improved or non-improved source according to their water source for cooking and washing. 2 Respondents may report multiple treatment methods so the sum of treatment may exceed 100 percent. 3 Appropriate water treatment methods include boiling, bleaching, straining, filtering, and solar disinfecting. The source of drinking water is important because waterborne diseases, including diarrhoea and dysentery, are prevalent in Tanzania. Sources of water expected to be relatively free of these diseases are piped water, protected wells, and protected springs. Other sources such as unprotected wells, rivers or streams, and ponds, lakes, or dams are more likely to carry disease-causing agents. Table 2.6 indicates that a majority of Tanzanian households have access to clean water sources (33 percent from piped water, 13 percent from a protected well, and 8 percent from a spring). Households in Zanzibar are more likely than those on the Mainland to have access to clean water. For example, 74 percent of households in Zanzibar use piped water compared with 32 percent in the Mainland. Household Population and Housing Characteristics | 23 Respondents to the household interview were also asked who provides drinking water at their main source. The results in Table 2.6 show that two in ten households say that the water is provided by the water authority. Households in Zanzibar are more likely than those in Mainland Tanzania to obtain water from an authority (63 percent compared with 18 percent). Urban households are more likely than rural households to say that their drinking water is provided by the authority. For 9 percent of households in Mainland and 28 percent in Zanzibar, the source of water is on their premises. Overall, 46 percent of Tanzanian households are less than 30 minutes from a water source and 45 percent take 30 minutes or longer to obtain drinking water. 2.5.2 Household Sanitation Facilities Ensuring adequate sanitation facilities is another Millennium Development Goal that Tanzania shares with other countries. 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 the waste from human contact (WHO/UNICEF, 2004). Table 2.7 shows that 13 percent of households in Tanzania use improved toilet facilities that are not shared with other households. In Mainland urban areas, 22 percent of households have improved toilet facilities compared with 9 percent in rural areas. The most common type of non- improved toilet facility is an open pit latrine or one without slabs, used by 71 percent of households in rural areas and 50 percent of households in urban areas. Overall, 14 percent of households have no toilet facility. Most of these households are in rural areas (18 percent). Table 2.7 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Tanzania 2010 Households Population Mainland Mainland Type of toilet/latrine facility Urban Rural Total Zanzibar Total Urban Rural Total Zanzibar Total Improved, not shared facility Flush/pour flush to piped sewer system 0.9 0.0 0.2 1.8 0.3 1.1 0.0 0.2 2.0 0.3 Flush/pour flush to septic tank 4.2 0.1 1.1 1.5 1.1 5.2 0.1 1.2 1.8 1.2 Flush/pour flush to pit latrine 10.2 1.5 3.8 14.4 4.0 12.9 1.5 4.0 15.5 4.4 Ventilated improved pit (VIP) latrine 1.9 0.6 0.9 4.0 1.0 2.7 0.7 1.1 4.6 1.2 Pit latrine with slab 4.4 6.3 5.8 28.8 6.4 5.1 5.7 5.6 28.3 6.2 Non-improved facility Any facility shared with other households 24.4 2.0 7.8 7.4 7.8 19.7 1.3 5.4 5.3 5.4 Flush/pour flush not to sewer/septic tank/pit latrine 2.1 0.1 0.6 2.3 0.7 1.8 0.2 0.5 2.3 0.6 Pit latrine without slab/open pit 49.8 71.4 65.8 14.3 64.5 49.4 70.9 66.1 15.5 64.6 No facility/bush/field 2.0 17.8 13.7 24.9 14.0 1.9 19.5 15.6 24.2 15.9 Other 0.0 0.2 0.1 0.7 0.1 0.0 0.2 0.1 0.5 0.1 Missing 0.1 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Shared/not shared Not shared 42.7 80.2 70.6 89.9 71.1 52.6 84.1 77.2 92.7 77.6 Shared with 1 household 12.9 12.6 12.7 5.5 12.5 12.1 10.2 10.6 4.4 10.5 Shared with 2-4 households 28.2 6.1 11.8 4.1 11.6 22.7 5.0 8.9 2.5 8.7 Shared with 5+ households 16.1 1.0 4.9 0.5 4.8 12.5 0.6 3.2 0.3 3.1 Missing 0.0 0.1 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 2,417 6,959 9,377 246 9,623 10,239 36,097 46,336 1,391 47,728 Seven in ten households in Tanzania do not share their toilet facility, 13 percent share with another household, 12 percent share with two to four households, and 5 percent share the facility with five or more households. Although the likelihood of sharing a sanitation facility with one other household in urban and rural households of Mainland Tanzania is the same, urban households are much more likely than rural households to share the facility with two or more households. For example, 28 percent of urban households share the toilet facility with two to four households compared with 6 percent of rural households. 24 | Household Population and Housing Characteristics 2.5.3 Housing Characteristics Table 2.8 presents information on characteristics of the dwellings in which households live. In addition to reflecting the household’s socioeconomic situation, these characteristics also show the environmental conditions in which the household lives. For example, use of biomass fuels exposes the household members to indoor pollution, which has a direct bearing on their health and welfare. Table 2.8 Household characteristics Percent distribution of households and de jure population by housing characteristics and percentage using solid fuel for cooking; according to residence, Tanzania 2010 Households Population Mainland Mainland Housing characteristic Urban Rural Total Zanzibar Total Urban Rural Total Zanzibar Total Electricity Yes 45.4 3.4 14.2 35.3 14.8 45.4 3.0 13.2 38.0 13.1 No 54.5 96.6 85.7 64.7 85.2 54.4 97.0 86.7 62.0 86.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand, dung 23.1 83.9 68.2 35.6 67.4 24.3 84.2 69.7 33.4 69.9 Cement 70.7 15.2 29.5 61.2 30.3 69.4 14.9 28.1 62.9 28.0 Other 6.1 0.8 2.2 3.2 2.2 6.3 0.9 2.1 3.6 2.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Main wall material Grass 0.1 0.8 0.6 0.4 0.6 0.1 0.7 0.6 0.3 0.6 Poles and mud 7.8 32.7 26.3 34.3 26.5 7.9 31.0 26.1 33.9 26.1 Sun-dried bricks 20.1 31.9 28.8 1.2 28.1 20.8 34.5 30.3 1.0 30.6 Baked bricks 23.2 24.3 24.0 0.4 23.4 24.2 24.4 24.1 0.3 23.7 Wood, timer 0.2 1.9 1.5 0.1 1.4 0.2 1.8 1.5 0.2 1.4 Cement blocks 46.7 3.8 14.8 48.0 15.7 44.8 3.3 13.6 50.0 13.6 Stones 1.2 0.2 0.5 15.4 0.8 1.2 0.1 0.5 14.2 0.8 Other 0.7 4.4 3.5 0.2 3.4 0.8 4.1 3.4 0.1 3.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Main roof material Grass/thatch/mud 6.5 49.0 38.1 23.5 37.7 7.4 48.7 38.9 20.6 39.0 Iron sheets 88.0 50.5 60.1 75.2 60.5 86.2 50.7 59.3 78.5 59.1 Tiles 1.8 0.2 0.6 0.9 0.6 1.9 0.2 0.6 0.5 0.6 Concrete 2.8 0.0 0.7 0.2 0.7 3.2 0.0 0.7 0.2 0.7 Asbestos 0.8 0.2 0.4 0.2 0.4 1.3 0.2 0.4 0.2 0.5 Other 0.0 0.1 0.1 0.0 0.1 0.0 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping 1 room 40.8 25.7 29.6 18.4 29.3 24.7 16.0 22.3 8.7 17.7 2 rooms 29.1 40.1 37.3 33.2 37.2 30.8 37.6 36.5 28.6 35.9 3 rooms 19.1 21.8 21.1 32.9 21.4 26.7 25.6 24.1 39.2 26.3 4 rooms 7.4 7.9 7.8 11.5 7.9 11.4 11.6 10.1 16.6 11.7 5+ rooms 3.6 4.4 4.2 4.0 4.2 6.3 9.3 6.9 6.8 8.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 3.8 0.2 1.1 0.4 1.1 3.9 0.1 1.0 0.3 0.9 LPG/natural gas/biogas 0.9 0.0 0.3 0.4 0.3 1.0 0.0 0.2 0.4 0.2 Paraffin/Kerosene 9.4 0.4 2.7 1.1 2.7 5.7 0.1 1.9 0.4 1.3 Charcoal 62.2 6.3 20.7 25.6 20.8 64.6 4.5 19.0 26.0 18.1 Wood 20.7 92.4 73.9 71.0 73.9 23.6 94.8 77.1 72.6 78.9 Straw/shrubs/grass 0.3 0.3 0.3 0.0 0.3 0.5 0.3 0.3 0.0 0.3 No food cooked in household 2.7 0.3 0.9 1.5 0.9 0.7 0.1 0.5 0.3 0.2 Other 0.1 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 83.1 99.0 94.9 96.7 95.0 88.7 99.6 96.3 98.6 97.2 Number of households 2,417 6,959 9,377 246 9,623 10,239 36,097 74,959 1,391 47,728 Note: Total may not sum to 100.0 percent because of missing cases LPG = Liquid petroleum gas 1 Includes charcoal, wood, and straw/shrubs/grass. Household Population and Housing Characteristics | 25 Only 15 percent of households in Tanzania have electricity, with a very large disparity between urban and rural households in Mainland Tanzania (45 percent and 3 percent, respectively). Two in three households in Tanzania (67 percent) live in dwellings with floors made of earth, sand, or dung. The next most common type of flooring material is cement, accounting for 30 percent of households. Most urban households in Mainland Tanzania have floors made of cement (71 percent), while in rural areas the main flooring materials are earth, sand, or dung (84 percent). Good-quality walls ensure that household members are protected from harsh weather condi- tions and, therefore, exposure to hazardous factors. There are three main types of materials used to construct walls in Tanzania: sun-dried bricks (28 percent), poles and mud (27 percent), and baked bricks (23 percent). Cement blocks are mainly used in the urban areas of Mainland and Zanzibar (47 percent and 48 percent, respectively). Overall, six in ten households use iron sheets for roofing material. The remaining households mainly use grass, thatch, or mud. In Mainland Tanzania, almost nine in ten urban households use iron sheets, while in rural areas half of households use grass, thatch, or mud and the other half use iron sheets. The number of rooms used for sleeping is an indicator of the extent of crowding. Overcrowd- ing increases the risk of contracting diseases. Overall, 29 percent of Tanzanian households use one room for sleeping, 37 percent use two rooms, and 34 percent use three or more rooms for sleeping. Almost half of households in Zanzibar have three or more rooms for sleeping. Cooking and heating with solid fuels can lead to high levels of indoor smoke, a complex mix of health-damaging pollutants that could increase the risk of contracting diseases. Solid fuels are defined as charcoal, wood, straw, shrubs, and grass. In the 2010 TDHS, households were asked about their primary source of fuel for cooking. The results show that 95 percent of households use solid fuel for cooking, with wood being the major source of solid fuel (74 percent of households). There are large differentials in cooking fuel between urban and rural areas in the Mainland. Whereas 92 percent of households in the rural areas use wood for cooking, the main source of cooking fuel in the urban areas is charcoal (62 percent). 2.5.4 Household Possessions The availability of durable consumer goods is a good indicator of a household’s socio- economic status. Moreover, particular goods have 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 transportation allows greater access to many services away from the local area. Table 2.9 shows the availability of selected consumer goods by urban-rural residence. Nationally, the most commonly owned items are a radio (60 percent of households), a mobile telephone (46 percent), and a bicycle (43 percent). Additionally, 13 percent of households own a television, 6 percent of households own a refrigerator, and 3 percent own a motorcycle or scooter. All of these figures are higher than those recorded in the 2007-08 THMIS (TACAIDS, ZAC, NBS, OCGS, and Macro International Inc, 2008). In the Mainland, urban households are more likely than rural households to own each of the items, with the exception of bicycles, which are owned by 47 percent in rural areas compared with 34 percent in urban areas. Ownership of agricultural land is common in Tanzania, with about three in four households possessing land. Not surprisingly, rural households in the Mainland are much more likely than urban households to own agricultural land (87 percent and 38 percent, respectively). 26 | Household Population and Housing Characteristics Table 2.9 Household durable goods Percentage of households and de jure population possessing various household effects, means of transportation, and agricultural land, by residence, Tanzania 2010 Households Population Mainland Mainland Possession Urban Rural Total Zanzibar Total Urban Rural Total Zanzibar Total Radio 74.1 55.1 60.0 71.7 60.3 76.1 58.9 61.7 73.3 63.0 Television 39.9 3.3 12.7 29.0 13.1 41.8 3.3 12.2 31.5 12.4 Mobile telephone 77.5 34.2 45.4 69.8 46.0 79.9 39.3 47.3 74.0 49.0 Non-mobile telephone 3.4 0.2 1.0 3.1 1.1 5.3 0.3 1.3 3.5 1.4 Refrigerator 19.4 0.7 5.5 22.1 6.0 23.0 0.6 5.6 24.4 6.1 Bicycle 33.0 46.6 43.1 51.3 43.3 38.9 55.4 48.5 57.0 51.9 Motorcycle/scooter 4.8 2.2 2.9 9.9 3.1 6.5 3.1 3.5 10.8 4.0 Car/truck 5.3 0.6 1.8 3.9 1.8 7.3 0.8 2.1 4.6 2.3 Ownership of agricultural land 38.6 87.8 75.1 48.2 74.4 41.8 90.3 77.7 50.9 78.7 Number 2,417 6,959 9,377 246 9,623 10,239 36,097 74,959 1,391 47,728 2.6 WEALTH INDEX The wealth index, which is used as a background characteristic in many tables, has been tested in a number of countries in relation to inequities in household income, use of health services, and health outcomes (Rutstein et al., 2000). It is an indicator of the level of wealth that is consistent with expenditure and income measures (Rutstein, 1999). The wealth index was constructed using household asset data and principal components analysis. Asset information was collected in the 2010 TDHS Household Questionnaire and covers information on household ownership of a number of consumer items, ranging from a television to a bicycle or car, as well as information on dwelling characteristics, such as source of drinking water, type of sanitation facilities, and type of materials used in dwelling construction. Each asset was assigned a weight (factor score) generated through principal component analysis, and the resulting asset scores were standardized in relation to a standard normal distribution with a mean of 0 and standard deviation of 1 (Gwatkin et al., 2000). Each household was then assigned a score for each asset, and the scores were summed for each household. Individuals were ranked according to the total score of the household in which they resided. The sample was then divided into quintiles from lowest to highest or one to five. Table 2.10 shows the distribution of the de jure household population by five wealth levels (quintiles) based on the wealth index and by residence. This distribution indicates the degree to which wealth is evenly (or unevenly) distributed by geographic areas. The distribution of households by quintiles is not exactly 20 percent due to the fact that members of the households, not households themselves, were divided into quintiles. Wealth is more prevalent in urban areas, with 64 percent of the population falling in the highest wealth quintile. In contrast, the rural population is less wealthy, with 24 percent in the lowest quintile and only 5 percent in the highest quintile. Regions with the highest proportion of the population in the highest quintile are Dar es Salaam and Town West. Also included in Table 2.10 is the Gini Coefficient, which indicates the level of concentration of wealth, 0 being an equal distribution and 1 a totally unequal distribution. The Gini coefficient is calculated as a ratio of the areas on the Lorenz curve diagram. This ratio is expressed as a percentage, or as the numerical equivalent of that percentage, which is always a number between 0 and 100. The overall Gini Coefficient is 50; 22 in the urban areas and 41 in the rural areas, indicating that urban population is more evenly distributed in terms of wealth than rural population. The lowest Gini- coefficients are found in Dar es Salaam and Town West (11 and 12, respectively) and the highest (56) is found in Shinyanga. Household Population and Housing Characteristics | 27 Table 2.10 Wealth quintiles Percent distribution of the jure population by wealth quintiles, and the Gini coefficient, according to residence and region, Tanzania 2010 Wealth quintile Residence/region Lowest Second Middle Fourth Highest Total Number of population Gini coefficient Residence Urban 3.0 2.4 6.6 24.3 63.6 100.0 10,779 21.5 Rural 23.6 27.1 26.4 18.3 4.6 100.0 36,949 41.3 Mainland/Zanzibar Mainland 19.4 21.8 22.2 19.4 17.2 100.0 46,336 50.2 Urban 3.2 2.5 6.9 24.7 62.7 100.0 10,239 22.1 Rural 24.0 27.3 26.5 17.9 4.3 100.0 36,097 41.1 Zanzibar 4.9 10.9 13.0 28.3 42.9 100.0 1,391 33.9 Unguja 2.2 4.7 8.5 28.1 56.5 100.0 860 24.7 Pemba 9.2 20.9 20.3 28.7 21.0 100.0 532 39.9 Zone Western 22.0 34.0 23.4 11.1 9.6 100.0 8,440 51.9 Northern 16.7 17.1 19.8 24.3 22.1 100.0 7,259 46.4 Central 36.1 24.9 22.3 12.3 4.4 100.0 4,278 45.6 Southern Highlands 12.3 18.7 28.0 25.9 15.2 100.0 6,506 44.8 Lake 18.5 23.4 25.6 21.4 11.2 100.0 9,046 45.0 Eastern 10.8 9.9 12.5 21.8 45.0 100.0 6,480 37.4 Southern 28.2 22.5 22.2 17.0 10.2 100.0 4,328 44.9 Region Dodoma 37.7 25.7 21.0 12.4 3.2 100.0 2,663 44.4 Arusha 23.1 11.0 18.4 27.9 19.7 100.0 1,916 47.3 Kilimanjaro 1.1 8.1 21.9 38.9 30.0 100.0 1,835 33.8 Tanga 15.9 24.8 20.2 14.5 24.6 100.0 2,289 47.1 Morogoro 17.9 14.9 23.4 27.2 16.6 100.0 2,310 43.0 Pwani 21.4 22.4 16.9 23.6 15.6 100.0 1,324 46.0 Dar es Salaam 0.1 0.1 1.6 16.6 81.6 100.0 2,846 10.7 Lindi 40.6 29.7 18.7 7.5 3.6 100.0 883 47.7 Mtwara 35.5 22.2 19.8 10.5 11.9 100.0 1,792 47.2 Ruvuma 13.6 18.8 26.6 29.1 11.9 100.0 1,653 38.6 Iringa 7.6 11.1 30.4 29.1 21.8 100.0 2,091 35.8 Mbeya 7.7 18.7 31.9 27.4 14.3 100.0 2,966 46.1 Singida 33.3 23.5 24.5 12.2 6.4 100.0 1,615 47.7 Tabora 31.0 35.3 17.9 6.1 9.8 100.0 2,239 52.5 Rukwa 28.2 29.7 16.5 18.1 7.4 100.0 1,450 49.8 Kigoma 14.9 24.1 35.2 18.5 7.4 100.0 2,199 40.9 Shinyanga 20.8 38.7 20.0 9.9 10.6 100.0 4,001 55.9 Kagera 15.2 28.5 29.1 19.8 7.4 100.0 2,873 35.2 Mwanza 20.8 22.1 22.2 19.7 15.2 100.0 4,222 50.6 Mara 18.3 18.5 27.9 27.2 8.1 100.0 1,952 42.1 Manyara 31.5 26.0 18.0 15.1 9.4 100.0 1,219 52.8 Unguja North 7.3 13.1 21.6 45.9 12.1 100.0 209 29.5 Unguja South 2.8 9.1 15.3 46.9 26.0 100.0 133 30.0 Town West 0.0 0.2 1.4 16.1 82.4 100.0 517 12.4 Pemba North 13.0 27.1 20.2 24.5 15.1 100.0 263 41.7 Pemba South 5.6 14.7 20.3 32.7 26.7 100.0 269 37.0 Total 19.0 21.5 21.9 19.7 17.9 100.0 47,728 49.8 2.7 BIRTH REGISTRATION Birth registration is the formal inscription of the facts of the birth into an official log kept at the registrar’s office. A birth certificate is issued at the time of registration or later as proof of the registration of the birth. Birth registration is basic to ensuring a child’s legal status and, thus, basic rights and access to services (United Nations General Assembly, 2002). Table 2.11 presents the percentage of children under age 5 whose births were officially registered. Sixteen percent of children in Tanzania under age 5 have been registered with civil authorities, of whom about half (8 percent) received a birth certificate. Birth registration seems to have remained at the same level in the past 5 years; the coverage for children under 2 years is the same as for children age 2-4. However, registration coverage differs by urban-rural residence, regions, and wealth quintile. Forty-four percent of children in urban areas are registered compared with only 10 percent in rural areas. Registration in Zanzibar is much more widespread than in Mainland Tanzania (79 percent and 15 percent, respectively). Across regions in Mainland, the proportion of births that are registered ranges from 59 percent in Dar es Salaam to 5 percent or lower in Lindi, Tabora, Shinyanga, and Manyara. 28 | Household Population and Housing Characteristics Table 2.11 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, Tanzania 2010 Percentage of children whose births are registered Background characteristic Had a birth certificate Did not have a birth certificate Total registered Number of children Age <2 6.0 10.4 16.3 3,263 2-4 8.9 7.3 16.2 4,818 Sex Male 7.7 8.9 16.6 4,016 Female 7.7 8.2 15.9 4,065 Residence Urban 24.7 19.5 44.2 1,542 Rural 3.7 6.0 9.7 6,539 Mainland/Zanzibar Mainland 6.2 8.4 14.6 7,874 Urban 22.1 19.8 41.9 1,471 Rural 2.6 5.7 8.3 6,403 Zanzibar 63.0 15.7 78.7 207 Unguja 71.1 17.2 88.4 122 Pemba 51.3 13.5 64.7 85 Zone Western 2.5 2.3 4.8 1,690 Northern 9.0 12.6 21.6 1,037 Central 2.0 4.5 6.5 794 Southern Highlands 7.8 8.9 16.7 1,104 Lake 4.4 5.3 9.7 1,695 Eastern 17.3 26.4 43.7 910 Southern 3.5 3.8 7.3 643 Region Dodoma 0.6 5.3 5.9 490 Arusha 16.6 8.6 25.3 296 Kilimanjaro 10.3 29.9 40.2 206 Tanga 6.2 11.4 17.6 331 Morogoro 8.1 21.8 29.9 330 Pwani 9.9 28.8 38.7 210 Dar es Salaam 29.6 29.2 58.8 371 Lindi 3.0 1.6 4.6 138 Mtwara 5.2 1.7 6.9 240 Ruvuma 2.2 6.9 9.1 265 Iringa 10.7 12.0 22.7 311 Mbeya 8.7 9.4 18.1 517 Singida 4.3 3.2 7.5 304 Tabora 3.6 1.1 4.7 455 Rukwa 2.9 4.3 7.2 276 Kigoma 2.1 5.5 7.7 409 Shinyanga 2.1 1.3 3.5 825 Kagera 3.8 2.8 6.7 490 Mwanza 5.6 6.0 11.5 805 Mara 2.7 7.0 9.7 400 Manyara 1.3 2.8 4.1 204 Unguja North 55.4 20.6 76.0 33 Unguja South 66.1 21.7 87.9 20 Town West 79.8 14.4 94.3 70 Pemba North 52.1 10.4 62.6 44 Pemba South 50.4 16.7 67.0 41 Wealth quintile Lowest 1.0 3.4 4.4 1,720 Second 1.6 4.5 6.0 1,915 Middle 3.0 6.7 9.7 1,843 Fourth 10.3 12.5 22.8 1,536 Highest 34.0 21.8 55.8 1,067 Total 7.7 8.5 16.3 8,081 Household Population and Housing Characteristics | 29 2.8 HOUSEHOLD FOOD SECURITY The 2010 TDHS also included several questions to gauge household food security. Questions were asked about the number of meals the household usually takes each day, the number of days in the week preceding the survey in which the household consumed meat, the number of days in the week preceding the survey in which the household consumed fish, and how often the household had problems satisfying food needs in the year before the survey. Results are shown in Table 2.12. Fifty-seven percent of households usually have at least three meals per day, although a sizeable proportion (41 percent) has only two meals per day. While the national average is similar to that in the Mainland and Zanzibar, in Mainland, urban households are far more likely than those in rural areas to have three or more meals a day (78 percent and 49 percent, respectively). Table 2.12 Household food security Percent distribution of households by usual number of meals per day, number of days that meat was consumed, during the last week, number of days that fish was consumed during the last week, and frequency of problems satisfying food needs in the past year according to residence, Tanzania 2010 Mainland Food security characteristic Urban Rural Total Zanzibar Total Usual number of meals per day 1 meal 2.0 3.1 2.8 2.2 2.8 2 meals 19.6 47.8 40.5 37.8 40.5 3+ meals 78.3 49.0 56.6 60.0 56.7 Total 100.0 100.0 100.0 100.0 100.0 Number of days consumed meat in the past week 0 32.6 60.3 53.2 79.0 53.8 1 21.1 18.9 19.4 10.0 19.2 2 21.9 12.5 14.9 6.9 14.7 3 12.3 5.6 7.3 2.6 7.2 4 5.2 1.5 2.4 0.8 2.4 5 2.2 0.7 1.1 0.3 1.1 6 0.9 0.1 0.3 0.2 0.3 7 3.9 0.4 1.3 0.2 1.3 Total 100.0 100.0 100.0 100.0 100.0 Number of days consumed fish in the past week 0 22.6 51.1 43.8 5.7 42.8 1 20.1 14.0 15.6 3.9 15.3 2 19.8 12.9 14.7 7.6 14.5 3 14.9 8.5 10.1 11.1 10.2 4 8.2 4.1 5.1 10.4 5.3 5 6.1 3.0 3.8 11.2 4.0 6 3.5 2.2 2.5 11.7 2.8 7 4.8 4.1 4.3 38.4 5.2 Total 100.0 100.0 100.0 100.0 100.0 Frequency of problems satisfying food needs in past year Never 55.5 36.0 41.0 53.6 41.4 Seldom 16.9 19.6 18.9 17.9 18.9 Sometimes 12.7 17.9 16.6 19.0 16.6 Often 14.6 24.1 21.7 9.4 21.4 Always 0.2 2.1 1.6 0.2 1.6 Total 100.0 100.0 100.0 100.0 100.0 Number of households 2,417 6,959 9,377 246 9,623 1 Note: Totals may not add to 100 because of a small number of missing cases 30 | Household Population and Housing Characteristics Meat consumption is not common in Tanzania. More than half of the households interviewed (54 percent) reported that they had consumed no meat in the previous week, 19 percent ate meat once, and 15 percent ate it twice. Only 12 percent of households had meat three or more times in the past week. Consumption of meat varies significantly by urban-rural residence. In Mainland, 60 percent of rural households did not consume meat in the week preceding the survey compared with 33 percent in the urban areas. Households in Zanzibar are less likely than those in the Mainland to eat meat; 79 percent did not consume meat in the week preceding the survey. However, fish is more common in the diet in Zanzibar, with 83 percent of households in Zanzibar consuming fish 3 to 7 times a week compared with only 26 percent of households in Mainland Tanzania. When respondents were asked how often they had problems in meeting the food needs of the household in the 12 months before the survey, 41 percent reported never having a problem, 21 percent said they often have a problem, and 2 percent reported always having a problem meeting their food needs. In Mainland, urban households are less likely than rural households to report having a problem in securing food. For example, 56 percent of households in urban areas say they never had a problem satisfying the need for food in the past year compared with 36 percent of households in rural areas. Similarly, 24 percent of rural households say they often had a problem compared with 15 percent of urban households. Characteristics of Respondents | 31 CHARACTERISTICS OF RESPONDENTS 3 The objective of this chapter is to provide a descriptive summary of the demographic and socioeconomic profile of respondents in the 2010 TDHS. This basic information on the characteristics of the women and men interviewed in the survey is essential to interpret findings presented later in the report and can provide an approximate indication of the representativeness of the survey. The chapter begins by describing basic background characteristics, including age, marital status, residential characteristics, and educational levels. Next, more detailed information on educa- tion, literacy, and exposure to mass media are provided. 3.1 CHARACTERISTICS OF SURVEY RESPONDENTS Table 3.1 presents the distributions of interviewed women age 15-49 and men age 15-49 by key background characteristics—age, marital status, and residence. Other characteristics presented are the distribution of these populations by zone, region, education level, and wealth. A total of 10,139 women and 2,527 men were interviewed. For both sexes, the proportion in each age group decreases with increasing age, reflecting, in part, the young age structure of the population of Tanzania. About 6 in 10 women and 5 in 10 men are currently married, and an additional 5 percent of women and 4 percent of men are in ‘informal’ unions. The proportion never married is 25 percent for women and 41 percent for men. The sex difference can be attributed to the relatively older age of men at first marriage. Twelve percent of women and 7 percent of men are divorced, separated, or widowed. Twenty-nine percent of women and 27 percent of men live in urban areas. There are no marked differences between sexes by region. Ninety-seven percent of the nationally representative sample is from the Mainland. Nine percent of women and eight percent of men reside in the Dar es Salaam region. A sizable proportion of respondents also live in Mwanza (8 percent of women, 11 per- cent of men) and Shinyanga (8 percent of women, 7 percent of men) regions. These three regions are the largest in population size, according to the 2002 Population Census. About half of all respondents have completed primary education but have not gone on to attain higher education. Fifteen percent of women and 18 percent of men have gone to primary school but have not completed it. About one-fifth of respondents (16 percent of women and 23 percent of men) have at least some secondary education. Women are more disadvantaged in terms of educational attainment than men, with about twice as many women as men having no education. 32 | Characteristics of Respondents Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Tanzania 2010 Women Men Background characteristic Weighted percent Weighted Unweighted Weighted percent Weighted Unweighted Age 15-19 21.4 2,172 2,221 25.5 645 671 20-24 18.8 1,909 1,860 16.4 414 435 25-29 16.5 1,668 1,613 13.6 343 328 30-34 14.0 1,422 1,389 13.9 352 329 35-39 12.7 1,290 1,249 11.9 300 303 40-44 9.2 938 983 10.7 270 252 45-49 7.3 740 824 8.1 204 209 Marital status Never married 25.1 2,540 2,718 41.4 1,046 1,124 Married 58.3 5,909 5,917 48.6 1,229 1,188 Living together 5.0 503 393 3.5 88 69 Divorced/separated 8.8 892 856 5.5 138 125 Widowed 2.9 296 255 1.0 26 21 Residence Urban 28.5 2,892 2,591 27.4 693 624 Rural 71.5 7,247 7,548 72.6 1,834 1,903 Mainland/Zanzibar Mainland 96.8 9,813 7,743 97.0 2,452 1,964 Urban 27.2 2,758 1,884 26.2 662 466 Rural 69.6 7,055 5,859 70.8 1,790 1,498 Zanzibar 3.2 326 2,396 3.0 75 563 Unguja 2.1 212 1,457 2.1 53 372 Pemba 1.1 115 939 0.9 22 191 Zone Western 17.0 1,728 1,355 14.7 371 301 Northern 15.1 1,530 1,347 13.8 350 304 Central 8.0 812 709 8.2 208 187 Southern Highlands 13.5 1,370 1,009 14.0 355 277 Lake 17.8 1,809 1,249 20.6 521 350 Eastern 15.9 1,608 1,087 16.3 413 288 Southern 9.4 955 987 9.3 236 257 Region Dodoma 4.9 495 319 4.8 122 80 Arusha 4.0 401 359 3.4 87 82 Kilimanjaro 4.1 411 330 3.6 92 63 Tanga 4.9 498 329 4.9 124 85 Morogoro 4.7 481 335 5.8 146 107 Pwani 2.6 261 308 2.3 59 68 Dar es Salaam 8.5 866 444 8.2 207 113 Lindi 2.0 198 294 1.8 47 73 Mtwara 4.0 407 338 3.4 87 77 Ruvuma 3.5 350 355 4.0 102 107 Iringa 4.8 490 345 5.5 140 96 Mbeya 6.1 623 345 5.7 143 87 Singida 3.1 317 390 3.4 86 107 Tabora 4.4 447 477 4.2 105 116 Rukwa 2.5 257 319 2.8 72 94 Kigoma 4.6 462 363 3.8 96 80 Shinyanga 8.1 819 515 6.7 169 105 Kagera 5.8 590 361 6.4 161 97 Mwanza 8.3 844 471 10.9 276 155 Mara 3.7 376 417 3.3 83 98 Manyara 2.2 220 329 1.9 47 74 Unguja North 0.5 50 475 0.4 11 111 Unguja South 0.3 30 417 0.4 9 124 Town West 1.3 131 565 1.3 33 137 Pemba North 0.5 56 458 0.4 10 82 Pemba South 0.6 59 481 0.5 12 109 Education No education 19.1 1,940 1,912 9.5 239 228 Primary incomplete 14.6 1,482 1,529 18.2 460 483 Primary complete 50.0 5,071 4,338 49.4 1,249 1,058 Secondary+ 16.2 1,646 2,360 22.9 578 758 Wealth quintile Lowest 16.6 1,681 1,608 15.9 401 386 Second 19.2 1,947 1,891 17.7 447 445 Middle 19.7 1,997 1,911 19.4 490 481 Fourth 20.8 2,112 2,295 22.6 572 588 Highest 23.7 2,403 2,434 24.4 618 627 Total 15-49 100.0 10,139 10,139 100.0 2,527 2,527 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. Characteristics of Respondents | 33 3.2 EDUCATION 3.2.1 Educational Attainment Education provides people with the knowledge and skills that can lead to a better quality of life. Education correlates with the health of mothers and their children, and with reproductive behaviour. Tables 3.2.1 and 3.2.2 provide an overview of the relationship between the respondents’ level of education and other background characteristics. Fifty percent of women and 49 percent of men have completed primary school only. The proportion for men is slightly lower than in the 2004-05 TDHS (52 percent) (NBS and ORC Macro, 2005). Increasing age is generally associated with lower levels of education, particularly for women. The most disadvantaged are women age 45-49, an age group in which 36 percent have had no education. Educational differentials are also found by residence. The rural-urban differentials, as expected, show wide variations. Only 8 percent of urban women, compared with 24 percent of rural women, lack education. Three percent of urban men have had no education; this compares with 12 percent of rural men. About one-third (32 percent) of urban women and 42 percent of urban men have attended secondary education compared with 10 percent of women and 16 percent of men in rural areas. The urban-rural gap in education may, in part, reflect the predominantly urban locations of secondary and tertiary learning institutions. There are significant differentials across regions. Whereas 37 percent of women and 45 percent of men in Dar es Salaam have attended at least some secondary education, only 3 percent of women and 9 percent of men in Lindi have had the same level of education. In Zanzibar, women and men have more education than in other regions; 57 percent of women and 65 percent of men have had some secondary education. The median years of schooling, indicating the number of years spent in school by half the population, shows no great variation among regions. Differences are found in a few regions, namely Dodoma, Lindi, Tabora, and Pemba North, where high proportions of women have no education. As expected, for both women and men, educational attainment increases with wealth. 34 | 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 grade completed, according to background characteristics, Tanzania 2010 Highest level of schooling Background characteristic No education Some primary Completed primary1 Secondary+2 Total Median years completed Number of women Age 15-24 13.8 17.0 41.7 27.5 100.0 6.4 4,081 15-19 8.3 20.3 36.9 34.5 100.0 6.5 2,172 20-24 20.0 13.3 47.1 19.5 100.0 6.4 1,909 25-29 20.6 14.3 53.5 11.6 100.0 6.3 1,668 30-34 18.6 12.4 59.7 9.4 100.0 6.3 1,422 35-39 24.8 11.9 56.9 6.5 100.0 6.2 1,290 40-44 19.7 9.8 63.7 6.8 100.0 6.3 938 45-49 35.8 17.2 40.2 6.8 100.0 4.6 740 Residence Urban 7.7 9.3 50.8 32.2 100.0 6.7 2,892 Rural 23.7 16.7 49.7 9.9 100.0 6.2 7,247 Mainland/Zanzibar Mainland 19.2 14.6 51.3 14.9 100.0 6.3 9,813 Urban 7.8 9.2 52.5 30.5 100.0 6.6 2,758 Rural 23.7 16.7 50.8 8.8 100.0 6.2 7,055 Zanzibar 15.7 15.1 12.6 56.7 100.0 7.7 326 Unguja 10.1 13.7 14.3 61.9 100.0 8.2 212 Pemba 25.9 17.6 9.3 47.1 100.0 6.5 115 Zone Western 29.0 17.1 44.5 9.4 100.0 6.1 1,728 Northern 16.0 8.3 57.1 18.6 100.0 6.5 1,530 Central 23.7 16.0 51.0 9.4 100.0 6.2 812 Southern Highlands 16.8 15.3 53.5 14.3 100.0 6.3 1,370 Lake 19.4 20.5 48.2 12.0 100.0 6.2 1,809 Eastern 14.0 9.6 50.7 25.7 100.0 6.5 1,608 Southern 15.2 15.3 57.9 11.6 100.0 6.3 955 Region Dodoma 29.5 16.1 44.7 9.7 100.0 6.1 495 Arusha 19.9 6.2 56.8 17.1 100.0 6.4 401 Kilimanjaro 2.8 6.2 63.3 27.6 100.0 6.7 411 Tanga 19.6 11.5 53.1 15.8 100.0 6.4 498 Morogoro 20.1 12.7 53.7 13.6 100.0 6.3 481 Pwani 26.2 12.1 51.5 10.2 100.0 6.2 261 Dar es Salaam 6.9 7.2 48.7 37.2 100.0 6.8 866 Lindi 29.1 21.4 46.3 3.1 100.0 5.9 198 Mtwara 15.5 17.8 54.7 12.0 100.0 6.3 407 Ruvuma 6.9 8.9 68.3 15.9 100.0 6.5 350 Iringa 9.6 15.3 57.2 18.0 100.0 6.4 490 Mbeya 18.7 12.7 53.2 15.5 100.0 6.4 623 Singida 14.5 15.7 60.8 8.9 100.0 6.3 317 Tabora 39.7 13.5 38.4 8.4 100.0 5.2 447 Rukwa 26.3 21.9 47.5 4.3 100.0 6.0 257 Kigoma 21.4 16.2 50.5 11.9 100.0 6.2 462 Shinyanga 27.6 19.5 44.4 8.6 100.0 6.1 819 Kagera 22.7 21.2 44.9 11.2 100.0 6.1 590 Mwanza 20.0 23.6 42.3 14.1 100.0 6.2 844 Mara 12.7 12.3 66.5 8.5 100.0 6.4 376 Manyara 25.3 9.0 54.9 10.9 100.0 6.3 220 Unguja North 26.9 18.4 10.5 44.1 100.0 6.4 50 Unguja South 5.4 18.2 15.1 61.4 100.0 8.0 30 Town West 4.7 10.8 15.6 68.9 100.0 8.5 131 Pemba North 32.5 19.1 6.7 41.7 100.0 5.7 56 Pemba South 19.7 16.3 11.8 52.3 100.0 7.1 59 Wealth quintile Lowest 39.4 19.1 38.9 2.6 100.0 3.6 1,681 Second 29.8 19.8 45.9 4.4 100.0 6.0 1,947 Middle 19.3 16.7 55.1 8.9 100.0 6.3 1,997 Fourth 10.8 13.4 58.2 17.6 100.0 6.4 2,112 Highest 3.5 6.5 49.7 40.3 100.0 6.8 2,403 Total 19.1 14.6 50.0 16.2 100.0 6.3 10,139 1 Completed at least grade 7 at the primary level 2 Completed grade 6 at the secondary level Characteristics of Respondents | 35 Table 3.2.2 Educational attainment: Men Percent distribution of men age 15-49 by highest level of schooling attended or completed, and median grade completed, according to background characteristics, Tanzania 2010 Highest level of schooling Background characteristic No education Some primary Completed primary1 Secondary+2 Total Median years completed Number of men Age 15-24 6.7 22.6 34.0 36.6 100.0 6.5 1,058 15-19 4.9 26.5 29.5 39.1 100.0 6.5 645 20-24 9.6 16.6 41.1 32.7 100.0 6.6 414 25-29 11.2 18.1 52.6 18.1 100.0 6.4 343 30-34 13.7 16.4 57.2 12.6 100.0 6.4 352 35-39 11.2 12.8 62.9 13.1 100.0 6.4 300 40-44 11.9 14.6 66.7 6.8 100.0 6.4 270 45-49 7.4 11.3 68.1 13.2 100.0 6.5 204 Residence Urban 2.9 9.3 45.5 42.3 100.0 6.9 693 Rural 11.9 21.6 50.9 15.6 100.0 6.3 1,834 Mainland/Zanzibar Mainland 9.6 18.2 50.6 21.6 100.0 6.4 2,452 Urban 3.0 9.2 47.0 40.8 100.0 6.8 662 Rural 12.0 21.6 51.9 14.5 100.0 6.3 1,790 Zanzibar 5.4 17.6 11.8 65.1 100.0 8.1 75 Unguja 3.0 17.1 12.1 67.8 100.0 8.2 53 Pemba 11.3 18.8 11.1 58.9 100.0 7.5 22 Zone Western 9.9 22.9 48.1 19.2 100.0 6.4 371 Northern 8.8 15.1 56.8 19.3 100.0 6.5 350 Central 17.2 17.4 54.1 11.4 100.0 6.3 208 Southern Highlands 5.6 16.9 55.0 22.5 100.0 6.5 355 Lake 13.5 21.2 44.0 21.2 100.0 6.3 521 Eastern 6.5 12.0 49.1 32.4 100.0 6.7 413 Southern 6.2 22.7 52.5 18.6 100.0 6.4 236 Region Dodoma 22.9 20.0 45.3 11.8 100.0 6.2 122 Arusha 18.9 11.0 61.2 8.9 100.0 6.4 87 Kilimanjaro 1.7 12.6 50.7 35.0 100.0 6.8 92 Tanga 5.5 21.7 57.2 15.6 100.0 6.4 124 Morogoro 9.4 16.1 53.2 21.3 100.0 6.5 146 Pwani 19.2 20.5 44.2 16.0 100.0 6.2 59 Dar es Salaam 0.8 6.7 47.6 44.9 100.0 7.0 207 Lindi 18.0 30.2 42.6 9.2 100.0 6.0 47 Mtwara 5.2 25.8 45.3 23.7 100.0 6.4 87 Ruvuma 1.6 16.7 63.2 18.5 100.0 6.5 102 Iringa 4.0 15.0 52.8 28.2 100.0 6.6 140 Mbeya 6.1 14.9 59.0 20.0 100.0 6.5 143 Singida 9.0 13.6 66.5 10.9 100.0 6.4 86 Tabora 15.1 28.0 43.0 13.8 100.0 6.2 105 Rukwa 7.8 24.4 51.5 16.3 100.0 6.3 72 Kigoma 0.9 23.3 42.8 33.0 100.0 6.6 96 Shinyanga 11.7 19.4 54.3 14.6 100.0 6.4 169 Kagera 19.4 18.8 41.2 20.6 100.0 6.3 161 Mwanza 14.0 21.7 42.7 21.5 100.0 6.3 276 Mara 0.4 24.4 53.9 21.3 100.0 6.4 83 Manyara 12.5 10.5 59.6 17.4 100.0 6.4 47 Unguja North 10.1 28.9 13.4 47.7 100.0 6.8 11 Unguja South 3.0 12.0 14.0 71.1 100.0 8.1 9 Town West 0.6 14.5 11.2 73.7 100.0 8.6 33 Pemba North 14.0 21.6 11.1 53.3 100.0 7.0 10 Pemba South 9.1 16.5 11.1 63.3 100.0 8.0 12 Wealth quintile Lowest 25.6 27.2 39.8 7.4 100.0 5.3 401 Second 15.5 26.1 49.7 8.7 100.0 6.2 447 Middle 5.8 23.5 58.9 11.8 100.0 6.3 490 Fourth 5.9 13.2 55.0 26.0 100.0 6.6 572 Highest 0.8 7.2 42.8 49.2 100.0 7.5 618 Total 15-49 9.5 18.2 49.4 22.9 100.0 6.5 2,527 1 Completed grade 7 at the primary level 2 Completed grade 6 at the secondary level 36 | Characteristics of Respondents 3.2.2 Literacy The ability to read and write is an important personal asset, which allows women and men increased opportunities in life. Knowing the distribution of the literate population can help program managers, especially those who work in health and family planning, determine how to reach women and men with their messages. In the 2010 TDHS, information on ability to read was collected from each individual who had not received post-primary training or a secondary education. The re- spondents were asked to read from a card containing the following sentences in Kiswahili and English: ‘Parents love their children. Farming is hard work. The child is reading a book. Children work hard at school’. A person was defined as literate if he or she had post-primary education or training, or secondary or higher education, or was able to read all or part of a sentence in Kiswahili, English, or both. Tables 3.3.1 and 3.3.2 show that 72 percent of women and 82 percent of men are literate. These rates have not changed much since the 2004-05 TDHS, when 67 percent of the women and 80 percent of the men were literate. The illiteracy rate, expressed as the proportion of those who cannot read at all, is highest (40 percent) among women age 45-49 and among men age 30-39 (21 percent). There is no uniform pattern to the association between age and literacy rate for women and men. Literacy rates for women and men in urban areas are 88 percent and 94 percent, respectively, compared with 66 percent and 78 percent in rural areas. Women in Kilimanjaro, Unguja South, and Town West have the highest literacy rates in the country (90 percent or higher). For men, the literacy rate is 90 percent or higher in Kilimanjaro, Dar es Salaam, Iringa, Kigoma, Unguja South, and Town West. For women and men, the literacy rates increase directly with wealth. 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, Tanzania 2010 No schooling or primary school Background characteristic Post- primary, secondary school, or higher Can read a whole sentence Can read part of a sentence Cannot read at all Blind/ visually impaired Missing Total Percentage literate Number Age 15-19 35.1 45.1 3.8 15.8 0.0 0.2 100.0 84.0 2,172 20-24 20.5 44.9 6.1 28.3 0.0 0.3 100.0 71.5 1,909 25-29 13.0 51.7 5.5 29.4 0.0 0.4 100.0 70.1 1,668 30-34 10.5 59.0 4.1 26.0 0.1 0.3 100.0 73.6 1,422 35-39 8.1 49.6 5.3 36.5 0.1 0.4 100.0 63.0 1,290 40-44 7.7 56.6 6.4 29.0 0.2 0.1 100.0 70.7 938 45-49 8.6 42.7 8.7 39.7 0.1 0.2 100.0 60.0 740 Residence Urban 34.8 48.6 4.1 12.1 0.0 0.4 100.0 87.5 2,892 Rural 10.4 49.9 5.8 33.5 0.1 0.3 100.0 66.1 7,247 Mainland/Zanzibar Mainland 16.1 50.5 5.3 27.7 0.1 0.3 100.0 71.9 9,813 Urban 33.2 50.0 4.1 12.3 0.0 0.4 100.0 87.3 2,758 Rural 9.3 50.8 5.8 33.7 0.1 0.3 100.0 65.9 7,055 Zanzibar 56.8 20.0 4.6 18.4 0.0 0.2 100.0 81.4 326 Unguja 62.0 21.7 4.3 11.7 0.0 0.3 100.0 88.0 212 Pemba 47.3 16.8 5.1 30.8 0.0 0.1 100.0 69.1 115 Zone Western 10.1 45.2 6.7 37.8 0.0 0.1 100.0 62.0 1,728 Northern 20.4 48.5 8.2 22.4 0.1 0.4 100.0 77.1 1,530 Central 9.7 51.6 5.7 32.7 0.0 0.2 100.0 67.0 812 Southern Highlands 15.2 54.7 3.9 25.2 0.1 0.7 100.0 73.9 1,370 Lake 12.9 51.3 4.3 31.2 0.0 0.3 100.0 68.6 1,809 Eastern 28.1 50.2 2.9 18.6 0.1 0.1 100.0 81.2 1,608 Southern 12.0 55.7 5.9 26.1 0.1 0.1 100.0 73.7 955 Continued Characteristics of Respondents | 37 Table 3.3.1—Continued No schooling or primary school Background characteristic Post- primary, secondary school. or higher Can read a whole sentence Can read part of a sentence Cannot read at all Blind/ visually impaired Missing Total Percentage literate Number Region Dodoma 10.0 45.3 6.7 37.8 0.0 0.2 100.0 62.0 495 Arusha 18.8 47.5 8.4 23.7 0.0 1.6 100.0 74.7 401 Kilimanjaro 32.0 53.6 5.0 9.2 0.2 0.0 100.0 90.6 411 Tanga 16.4 47.7 6.0 29.9 0.0 0.0 100.0 70.1 498 Morogoro 15.3 55.1 2.9 26.0 0.3 0.4 100.0 73.3 481 Pwani 10.5 57.5 2.1 29.9 0.0 0.0 100.0 70.1 261 Dar es Salaam 40.4 45.3 3.3 11.0 0.0 0.0 100.0 89.0 866 Lindi 3.5 46.5 11.8 37.6 0.6 0.0 100.0 61.8 198 Mtwara 12.2 53.9 5.8 28.1 0.0 0.0 100.0 71.9 407 Ruvuma 16.6 63.0 2.8 17.3 0.0 0.3 100.0 82.4 350 Iringa 19.9 56.8 6.1 17.2 0.0 0.0 100.0 82.8 490 Mbeya 16.0 53.4 2.8 25.9 0.3 1.6 100.0 72.2 623 Singida 9.3 61.4 4.2 24.9 0.0 0.2 100.0 74.9 317 Tabora 9.4 38.9 7.9 43.8 0.0 0.0 100.0 56.2 447 Rukwa 4.5 53.7 2.6 39.1 0.0 0.0 100.0 60.8 257 Kigoma 12.1 54.9 4.8 27.8 0.0 0.5 100.0 71.7 462 Shinyanga 9.4 43.1 7.2 40.3 0.0 0.0 100.0 59.7 819 Kagera 11.9 54.2 1.6 31.7 0.0 0.7 100.0 67.6 590 Mwanza 15.6 45.6 5.8 32.8 0.0 0.1 100.0 67.0 844 Mara 8.5 59.6 5.3 26.6 0.0 0.0 100.0 73.4 376 Manyara 10.9 42.6 18.6 27.9 0.0 0.0 100.0 72.1 220 Unguja North 44.5 22.1 5.8 27.2 0.0 0.4 100.0 72.4 50 Unguja South 61.4 24.3 4.6 9.5 0.0 0.2 100.0 90.3 30 Town West 68.9 21.0 3.7 6.2 0.0 0.2 100.0 93.6 131 Pemba North 41.7 17.0 5.1 36.2 0.0 0.0 100.0 63.8 56 Pemba South 52.5 16.5 5.1 25.7 0.0 0.2 100.0 74.1 59 Wealth quintile Lowest 2.8 38.4 6.9 51.6 0.0 0.2 100.0 48.1 1,681 Second 4.5 47.3 7.0 41.1 0.0 0.1 100.0 58.8 1,947 Middle 9.6 55.1 5.8 29.0 0.2 0.3 100.0 70.5 1,997 Fourth 18.6 58.7 4.7 17.6 0.0 0.4 100.0 82.0 2,112 Highest 43.4 46.5 3.0 6.8 0.0 0.4 100.0 92.8 2,403 Total 17.4 49.6 5.3 27.4 0.1 0.3 100.0 72.2 10,139 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence 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, Tanzania 2010 No schooling or primary school Background characteristic Post- primary, secondary school, or higher Can read a whole sentence Can read part of a sentence Cannot read at all Missing Total Percentage literate Number Age 15-19 39.2 40.0 5.4 15.4 0.0 100.0 84.6 645 20-24 34.8 38.7 7.2 18.8 0.5 100.0 80.7 414 25-29 19.0 57.2 5.8 17.8 0.0 100.0 82.0 343 30-34 15.2 58.1 6.2 20.5 0.0 100.0 79.5 352 35-39 15.1 57.6 6.3 20.6 0.4 100.0 79.0 300 40-44 12.6 60.4 10.1 16.8 0.0 100.0 83.2 270 45-49 17.5 62.8 4.7 13.6 1.4 100.0 85.0 204 Residence Urban 46.7 43.8 3.6 5.5 0.4 100.0 94.1 693 Rural 16.7 53.4 7.5 22.2 0.2 100.0 77.6 1,834 Mainland/Zanzibar Mainland 23.7 51.7 6.4 17.9 0.3 100.0 81.8 2,452 Urban 45.5 44.8 3.6 5.7 0.4 100.0 93.9 662 Rural 15.6 54.3 7.5 22.4 0.2 100.0 77.4 1,790 Zanzibar 65.5 19.5 5.5 9.3 0.2 100.0 90.5 75 Unguja 68.0 20.6 3.8 7.2 0.3 100.0 92.4 53 Pemba 59.5 16.9 9.6 14.0 0.0 100.0 86.0 22 Zone Western 21.4 49.1 10.2 19.4 0.0 100.0 80.6 371 Northern 23.0 54.2 6.7 16.1 0.0 100.0 83.9 350 Central 11.4 62.4 3.0 21.6 1.6 100.0 76.8 208 Southern Highlands 24.3 54.5 7.9 12.7 0.4 100.0 86.7 355 Lake 21.7 47.4 5.0 25.9 0.0 100.0 74.1 521 Eastern 37.0 48.1 5.2 9.3 0.3 100.0 90.4 413 Southern 19.3 54.2 6.3 20.2 0.0 100.0 79.8 236 Continued . F 38 | Characteristics of Respondents Table 3.3.2 Literacy: Men No schooling or primary school Background characteristic Post- primary, secondary school, or higher Can read a whole sentence Can read part of a sentence Cannot read at all Missing Total Percentage literate Number Region Dodoma 11.8 57.4 3.6 27.2 0.0 100.0 72.8 122 Arusha 13.5 53.5 7.4 25.6 0.0 100.0 74.4 87 Kilimanjaro 42.7 51.5 1.1 4.7 0.0 100.0 95.3 92 Tanga 16.8 57.8 8.0 17.3 0.0 100.0 82.7 124 Morogoro 24.5 55.1 5.4 14.0 0.9 100.0 85.1 146 Pwani 18.9 55.1 9.1 17.0 0.0 100.0 83.0 59 Dar es Salaam 51.1 41.2 4.0 3.8 0.0 100.0 96.2 207 Lindi 9.2 50.6 6.6 33.5 0.0 100.0 66.5 47 Mtwara 23.7 49.6 4.8 21.9 0.0 100.0 78.1 87 Ruvuma 20.2 59.9 7.4 12.5 0.0 100.0 87.5 102 Iringa 31.4 54.5 5.0 9.2 0.0 100.0 90.8 140 Mbeya 20.8 55.6 9.5 13.0 1.0 100.0 86.0 143 Singida 10.9 69.5 2.1 13.7 3.9 100.0 82.4 86 Tabora 15.6 55.8 6.2 22.4 0.0 100.0 77.6 105 Rukwa 17.4 52.2 10.5 19.0 0.0 100.0 80.1 72 Kigoma 33.0 46.2 13.4 7.4 0.0 100.0 92.6 96 Shinyanga 18.3 46.5 10.8 24.3 0.0 100.0 75.7 169 Kagera 20.6 42.0 6.5 30.9 0.0 100.0 69.1 161 Mwanza 22.3 45.5 4.7 27.5 0.0 100.0 72.5 276 Mara 22.3 64.2 3.1 10.5 0.0 100.0 89.5 83 Manyara 18.5 51.4 12.7 17.4 0.0 100.0 82.6 47 Unguja North 48.9 22.3 6.7 21.3 0.9 100.0 77.8 11 Unguja South 71.1 22.1 1.6 4.5 0.7 100.0 94.7 9 Town West 73.7 19.6 3.5 3.2 0.0 100.0 96.8 33 Pemba North 54.6 13.9 14.3 17.2 0.0 100.0 82.8 10 Pemba South 63.3 19.2 5.9 11.5 0.0 100.0 88.5 12 Wealth quintile Lowest 7.4 43.9 9.7 38.9 0.0 100.0 60.9 401 Second 9.2 52.8 10.9 27.1 0.0 100.0 72.9 447 Middle 12.0 64.8 6.3 16.4 0.5 100.0 83.1 490 Fourth 28.1 54.4 5.3 11.8 0.5 100.0 87.7 572 Highest 55.0 39.3 2.2 3.3 0.2 100.0 96.5 618 Total 15-49 24.9 50.8 6.4 17.6 0.2 100.0 82.1 2,527 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence 3.3 ACCESS TO MASS MEDIA The 2010 TDHS collected information on the exposure of respondents to various common print and electronic media. Respondents were asked how often they read a newspaper, listen to the radio, or watch television in a week. This information helps determine the media channels to use in disseminating health information to targeted audiences. Findings of the survey, given in Tables 3.4.1 and 3.4.2, indicate that 9 percent of women and 20 percent of men are exposed to all three media types. These figures indicate that there have been no significant changes in mass media exposure over the last five years since the 2004-05 TDHS showed that 9 percent of women and 16 percent of men had weekly exposure to the three types of media. On the other hand, the 2010 TDHS shows that 36 percent of women and 19 percent of men are not exposed to any type of media. Fifty-eight percent of women and 77 percent of men listen to the radio, the most common type of mass media in Tanzania, at least once a week. One-fifth (19 percent) of women read a newspaper, and 24 percent watch television once a week. The corresponding rates for men are 30 and 40 percent, respectively. As expected, women and men living in urban areas are more likely than those living in rural areas to be exposed to mass media. Almost a quarter (23 percent) of urban women are exposed to all forms of media as are 44 percent of urban men. The corresponding proportions for rural dwellers are 3 percent for women and 11 percent for men. The most popular form of media for urban respondents is the radio: 73 percent of women and 86 percent of men listen to the radio at least once a week. Newspapers are the least popular media. Geographically, exposure to all forms of media is highest in the Eastern zone. There is a positive relationship between exposure to mass media and the respondent’s level of education and wealth. Characteristics of Respondents | 39 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, Tanzania 2010 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to radio at least once a week All three media at least once a week No media at least once a week Number Age 15-19 26.3 31.8 60.3 12.4 29.9 2,172 20-24 19.0 28.4 58.7 9.6 33.1 1,909 25-29 15.2 22.2 56.8 6.7 37.2 1,668 30-34 19.4 22.0 59.6 8.1 35.0 1,422 35-39 13.2 15.5 54.0 5.6 43.0 1,290 40-44 17.0 18.0 57.0 8.4 37.6 938 45-49 14.8 14.0 50.4 5.5 46.1 740 Residence Urban 34.4 57.6 72.7 22.5 14.7 2,892 Rural 12.5 10.0 51.5 3.0 44.5 7,247 Mainland/Zanzibar Mainland 18.9 23.1 57.1 8.6 36.4 9,813 Urban 35.0 57.4 72.6 22.7 14.7 2,758 Rural 12.6 9.7 51.1 3.0 44.9 7,055 Zanzibar 15.0 37.2 69.7 8.9 22.7 326 Unguja 16.8 46.0 76.4 11.9 16.8 212 Pemba 11.5 21.0 57.4 3.5 33.8 115 Zone Western 10.4 16.8 53.4 3.2 40.3 1,728 Northern 15.7 25.8 59.4 8.3 34.8 1,530 Central 15.1 6.7 48.9 3.4 47.2 812 Southern Highlands 25.9 21.8 63.7 10.9 30.1 1,370 Lake 11.7 16.3 47.1 4.3 47.6 1,809 Eastern 36.9 50.1 72.4 22.6 16.2 1,608 Southern 15.8 13.5 51.2 4.3 44.7 955 Region Dodoma 11.6 4.9 42.9 1.8 53.8 495 Arusha 21.4 25.2 59.0 10.3 35.7 401 Kilimanjaro 17.8 33.8 72.8 10.2 18.8 411 Tanga 11.8 26.8 55.3 7.3 39.2 498 Morogoro 27.8 25.2 68.1 12.9 27.0 481 Pwani 23.0 23.2 75.4 11.3 22.4 261 Dar es Salaam 46.1 72.0 73.9 31.4 8.4 866 Lindi 15.9 8.5 49.6 3.8 42.9 198 Mtwara 20.3 13.3 48.3 4.4 46.8 407 Ruvuma 10.7 16.5 55.5 4.4 43.1 350 Iringa 13.3 19.7 66.3 6.5 32.0 490 Mbeya 35.7 28.5 66.1 17.0 25.4 623 Singida 20.6 9.5 58.3 5.9 37.0 317 Tabora 8.8 17.3 51.2 2.8 44.2 447 Rukwa 26.1 9.6 52.9 4.3 37.9 257 Kigoma 17.0 18.4 50.9 4.3 37.6 462 Shinyanga 7.5 15.6 55.9 2.8 39.6 819 Kagera 10.4 19.3 57.8 3.6 35.5 590 Mwanza 13.7 16.9 41.1 5.7 54.4 844 Mara 9.6 10.5 43.5 2.3 51.6 376 Manyara 10.1 9.1 44.1 3.0 53.5 220 Unguja North 5.1 11.2 68.1 1.9 30.0 50 Unguja South 17.4 33.1 89.6 5.6 8.6 30 Town West 21.3 62.4 76.6 17.2 13.6 131 Pemba North 6.8 13.6 53.0 1.6 41.4 56 Pemba South 15.9 28.1 61.5 5.3 26.6 59 Education No education 0.6 5.6 35.6 0.1 62.3 1,940 Primary incomplete 10.6 12.0 50.3 2.6 43.8 1,482 Primary complete 20.6 23.1 62.1 7.8 31.3 5,071 Secondary+ 42.1 56.5 75.9 26.5 12.3 1,646 Wealth quintile Lowest 5.8 3.1 27.1 0.5 69.3 1,681 Second 8.2 4.1 42.9 0.8 53.8 1,947 Middle 14.3 9.0 56.7 3.1 39.3 1,997 Fourth 21.4 17.0 70.1 6.4 23.6 2,112 Highest 37.8 71.4 80.2 27.0 6.4 2,403 Total 18.8 23.6 57.5 8.6 36.0 10,139 40 | Characteristics of Respondents 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, Tanzania 2010 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week All three media at least once a week No media at least once a week Number Age 15-19 26.3 38.8 72.2 16.1 21.2 645 20-24 29.7 45.9 77.6 20.7 17.2 414 25-29 34.2 40.7 75.7 23.8 19.1 343 30-34 30.9 41.8 81.0 20.1 15.0 352 35-39 31.6 39.2 76.4 20.8 18.9 300 40-44 27.1 29.9 76.7 16.2 20.3 270 45-49 34.3 36.2 81.2 23.9 18.0 204 Residence Urban 55.0 74.9 85.9 43.6 5.2 693 Rural 20.5 26.1 72.9 10.6 23.9 1,834 Mainland/Zanzibar Mainland 29.4 38.7 76.3 19.0 19.0 2,452 Urban 54.2 74.5 85.6 42.8 5.4 662 Rural 20.2 25.4 72.8 10.3 24.1 1,790 Zanzibar 48.2 66.5 84.0 40.4 9.7 75 Unguja 59.7 77.9 93.9 53.1 2.2 53 Pemba 20.8 39.3 60.5 10.0 27.4 22 Zone Western 20.4 32.3 66.9 13.6 28.9 371 Northern 31.4 44.4 69.9 22.0 25.0 350 Central 21.1 20.9 68.8 8.4 28.0 208 Southern Highlands 32.6 45.2 77.1 21.6 15.5 355 Lake 13.1 27.5 81.2 7.7 16.7 521 Eastern 53.9 61.1 85.7 39.8 7.3 413 Southern 35.9 31.6 78.3 17.2 17.8 236 Region Dodoma 21.3 14.5 59.1 5.8 38.5 122 Arusha 15.5 23.9 47.4 5.4 45.1 87 Kilimanjaro 43.5 67.7 83.6 37.6 12.4 92 Tanga 40.9 52.1 80.9 27.9 13.1 124 Morogoro 38.6 37.8 82.7 25.6 13.2 146 Pwani 36.1 40.6 86.2 18.7 9.0 59 Dar es Salaam 69.8 83.3 87.7 55.9 2.6 207 Lindi 21.3 25.5 67.7 7.8 24.2 47 Mtwara 24.4 26.5 69.3 9.8 25.3 87 Ruvuma 52.4 38.8 90.8 27.9 8.5 102 Iringa 43.0 57.1 90.9 33.8 6.7 140 Mbeya 26.6 42.0 66.8 14.2 19.8 143 Singida 20.8 29.9 82.7 12.3 13.1 86 Tabora 21.9 34.1 70.6 15.0 28.5 105 Rukwa 24.4 28.5 70.5 12.4 24.2 72 Kigoma 40.4 55.2 79.0 23.2 11.5 96 Shinyanga 8.2 18.1 57.7 7.4 39.0 169 Kagera 20.4 39.0 80.4 9.4 15.9 161 Mwanza 10.5 23.7 79.4 8.6 18.8 276 Mara 7.8 18.0 88.5 1.3 11.5 83 Manyara 12.6 16.8 55.8 7.0 43.3 47 Unguja North 32.9 61.9 92.7 26.6 1.8 11 Unguja South 37.4 62.0 89.9 31.3 5.0 9 Town West 74.8 87.7 95.3 68.1 1.6 33 Pemba North 12.6 24.2 58.0 3.2 34.5 10 Pemba South 27.2 51.2 62.5 15.4 21.7 12 Education No education 1.1 13.9 48.6 0.9 48.7 239 Primary incomplete 13.0 27.0 66.8 7.1 28.5 460 Primary complete 30.5 36.2 80.1 18.0 15.5 1,249 Secondary+ 54.2 67.1 88.0 41.0 5.6 578 Wealth quintile Lowest 7.3 13.4 49.6 3.7 46.3 401 Second 14.2 14.8 64.9 3.1 33.2 447 Middle 22.5 26.4 83.8 11.1 12.4 490 Fourth 32.6 41.7 84.1 18.0 10.6 572 Highest 59.4 82.6 89.5 50.3 3.0 618 Total 15-49 29.9 39.5 76.5 19.7 18.8 2,527 Characteristics of Respondents | 41 3.4 EMPLOYMENT 3.4.1 Employment Status Like education, employment can also be a source of empowerment for both women and men. It may be particularly empowering for women if it puts them in control of income. Respondents were asked a number of questions to elicit their employment status at the time of the survey, the continuity of their employment in the 12 months preceding the survey, and, if employed, details about their employment. Tables 3.5.1 and 3.5.2 present information relating to the employment status of women and men. A person is classified as employed if she or he is currently working or has worked at any time during the 12-month period preceding the survey. Seventy-eight percent of women are currently employed and 3 percent worked in the 12 months preceding the survey, putting the level of employment among women at 80 percent. Among men, 84 percent are currently employed, and 1 percent worked in the last 12 months, resulting in a level of employment of 85 percent. For both sexes, the proportion employed is lowest at age 15-19. The proportion increases gradually with age. The low participation rate at young ages is expected because part of the labour force at those ages consists of students at secondary and higher learning institutions, who therefore are not available for work. Teenage boys are slightly more likely to be working than teenage girls. This pattern was the reverse in the 2004-05 TDHS, when teenage girls were much more likely than teenage boys to be working. Women and men who are divorced, separated, or widowed are more likely to be currently employed (90 and 98 percent, respectively) than never married women and men (51 and 63 percent, respectively). Employment varies by residence; rural respondents are more likely than those in the urban areas to be employed. For example, 85 percent of women in the rural areas were employed in the 12 months preceding the survey compared with 69 percent in the urban areas. Women and men with the most education and from the wealthiest households are the least likely to be employed. Figure 3.1 is a summary of data in Tables 3.5.1 and 3.5.2. One in five women (20 percent) and 15 percent of men were not employed during the 12 months preceding the survey. In the 2004-05 TDHS this rate was 17 percent for both women and men. 42 | Characteristics of Respondents Table 3.5.1 Employment status: Women Percent distribution of women age 15-49 by employment status, according to background characteristics, Tanzania 2010 Employed in the 12 months preceding the survey Background characteristic Currently employed1 Not currently employed Not employed in the 12 months preceding the survey Missing/ don't know Total Number of women Age 15-19 48.7 3.2 48.1 0.0 100.0 2,172 20-24 77.4 3.8 18.7 0.1 100.0 1,909 25-29 83.6 2.7 13.8 0.0 100.0 1,668 30-34 87.6 2.5 9.9 0.0 100.0 1,422 35-39 90.5 1.5 8.0 0.0 100.0 1,290 40-44 89.9 1.7 8.4 0.0 100.0 938 45-49 92.2 1.7 6.1 0.0 100.0 740 Marital status Never married 50.9 2.9 46.2 0.1 100.0 2,540 Married or living together 86.0 2.7 11.4 0.0 100.0 6,412 Divorced/separated/widowed 89.7 2.2 8.1 0.0 100.0 1,188 Number of living children 0 52.4 3.0 44.6 0.1 100.0 2,665 1-2 82.4 3.4 14.2 0.0 100.0 3,080 3-4 88.4 2.1 9.5 0.0 100.0 2,346 5+ 90.9 1.7 7.3 0.0 100.0 2,048 Residence Urban 66.2 2.9 30.8 0.1 100.0 2,892 Rural 82.2 2.6 15.3 0.0 100.0 7,247 Mainland/Zanzibar Mainland 78.3 2.7 19.0 0.0 100.0 9,813 Urban 66.9 3.0 30.0 0.1 100.0 2,758 Rural 82.7 2.6 14.7 0.0 100.0 7,055 Zanzibar 56.8 1.7 41.5 0.0 100.0 326 Unguja 60.7 2.6 36.7 0.0 100.0 212 Pemba 49.5 0.2 50.3 0.0 100.0 115 Zone Western 84.6 4.0 11.4 0.0 100.0 1,728 Northern 56.1 2.2 41.6 0.0 100.0 1,530 Central 93.9 2.3 3.9 0.0 100.0 812 Southern Highlands 85.2 1.1 13.5 0.1 100.0 1,370 Lake 82.8 3.5 13.7 0.0 100.0 1,809 Eastern 73.7 2.6 23.7 0.0 100.0 1,608 Southern 78.4 2.4 19.2 0.0 100.0 955 Region Dodoma 94.7 2.3 3.0 0.0 100.0 495 Arusha 37.9 1.8 60.2 0.1 100.0 401 Kilimanjaro 71.6 2.3 26.0 0.0 100.0 411 Tanga 70.9 3.0 26.0 0.0 100.0 498 Morogoro 82.0 2.9 15.1 0.0 100.0 481 Pwani 77.6 2.4 20.1 0.0 100.0 261 Dar es Salaam 68.0 2.5 29.5 0.0 100.0 866 Lindi 82.9 1.7 15.4 0.0 100.0 198 Mtwara 78.4 0.8 20.8 0.0 100.0 407 Ruvuma 75.8 4.6 19.6 0.0 100.0 350 Iringa 83.3 2.6 14.1 0.0 100.0 490 Mbeya 85.6 0.0 14.1 0.2 100.0 623 Singida 92.5 2.2 5.3 0.0 100.0 317 Tabora 89.3 2.7 8.0 0.0 100.0 447 Rukwa 88.0 1.0 11.0 0.0 100.0 257 Kigoma 74.5 7.6 18.0 0.0 100.0 462 Shinyanga 87.7 2.6 9.6 0.0 100.0 819 Kagera 78.2 5.6 16.1 0.0 100.0 590 Mwanza 82.3 2.3 15.4 0.0 100.0 844 Mara 91.3 2.8 5.9 0.0 100.0 376 Manyara 26.5 1.1 72.3 0.0 100.0 220 Unguja North 66.3 4.6 29.1 0.0 100.0 50 Unguja South 78.8 2.1 19.1 0.0 100.0 30 Town West 54.4 1.9 43.7 0.0 100.0 131 Pemba North 50.3 0.2 49.5 0.0 100.0 56 Pemba South 48.7 0.2 51.1 0.0 100.0 59 Education No education 86.5 2.3 11.2 0.0 100.0 1,940 Primary incomplete 76.5 2.5 21.0 0.0 100.0 1,482 Primary complete 84.0 3.0 13.0 0.0 100.0 5,071 Secondary+ 48.3 2.3 49.3 0.1 100.0 1,646 Wealth quintile Lowest 85.4 1.9 12.7 0.0 100.0 1,681 Second 85.5 2.7 11.9 0.0 100.0 1,947 Middle 81.6 2.8 15.5 0.0 100.0 1,997 Fourth 74.9 2.6 22.5 0.0 100.0 2,112 Highest 64.8 3.1 32.0 0.1 100.0 2,403 Total 77.6 2.7 19.7 0.0 100.0 10,139 1 Currently employed is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. Characteristics of Respondents | 43 Table 3.5.2 Employment status: Men Percent distribution of men age 15-49 by employment status, according to background characteristics, Tanzania 2010 Employed in the 12 months preceding the survey Background characteristic Currently employed1 Not currently employed Not employed in the 12 months preceding the survey Total Number of men Age 15-19 52.5 3.0 44.5 100.0 645 20-24 80.6 2.5 16.9 100.0 414 25-29 97.0 0.9 2.1 100.0 343 30-34 99.7 0.0 0.3 100.0 352 35-39 98.9 0.0 1.0 100.0 300 40-44 98.1 1.1 0.8 100.0 270 45-49 100.0 0.0 0.0 100.0 204 Marital status Never married 62.8 2.8 34.5 100.0 1,046 Married or living together 99.1 0.5 0.5 100.0 1,317 Divorced/separated/widowed 97.7 0.4 1.9 100.0 164 Number of living children 0 65.4 2.7 31.9 100.0 1,146 1-2 99.4 0.4 0.2 100.0 556 3-4 99.0 0.7 0.3 100.0 429 5+ 99.5 0.0 0.5 100.0 396 Residence Urban 78.9 1.3 19.8 100.0 693 Rural 85.9 1.5 12.7 100.0 1,834 Mainland/Zanzibar Mainland 84.3 1.3 14.4 100.0 2,452 Urban 79.3 1.0 19.6 100.0 662 Rural 86.1 1.4 12.5 100.0 1,790 Zanzibar 73.0 4.8 22.2 100.0 75 Unguja 76.6 6.3 17.2 100.0 53 Pemba 64.6 1.2 34.1 100.0 22 Zone Western 85.6 0.5 13.9 100.0 371 Northern 78.2 2.2 19.6 100.0 350 Central 99.0 1.0 0.0 100.0 208 Southern Highlands 87.7 0.7 11.6 100.0 355 Lake 78.2 0.7 21.1 100.0 521 Eastern 84.0 0.6 15.4 100.0 413 Southern 87.1 5.1 7.9 100.0 236 Region Dodoma 98.9 1.1 0.0 100.0 122 Arusha 80.6 3.3 16.1 100.0 87 Kilimanjaro 71.5 1.0 27.5 100.0 92 Tanga 82.0 3.1 14.9 100.0 124 Morogoro 87.4 0.0 12.6 100.0 146 Pwani 81.3 0.0 18.7 100.0 59 Dar es Salaam 82.4 1.2 16.4 100.0 207 Lindi 90.4 4.5 5.1 100.0 47 Mtwara 80.4 3.7 15.9 100.0 87 Ruvuma 91.2 6.5 2.3 100.0 102 Iringa 93.3 1.2 5.5 100.0 140 Mbeya 83.6 0.0 16.4 100.0 143 Singida 99.1 0.9 0.0 100.0 86 Tabora 87.2 0.0 12.8 100.0 105 Rukwa 85.0 1.0 14.0 100.0 72 Kigoma 82.3 1.9 15.8 100.0 96 Shinyanga 86.5 0.0 13.5 100.0 169 Kagera 78.3 2.4 19.4 100.0 161 Mwanza 79.4 0.0 20.6 100.0 276 Mara 74.0 0.0 26.0 100.0 83 Manyara 77.0 0.0 23.0 100.0 47 Unguja North 77.1 4.5 18.4 100.0 11 Unguja South 93.4 4.2 2.5 100.0 9 Town West 71.8 7.4 20.8 100.0 33 Pemba North 52.3 1.1 46.7 100.0 10 Pemba South 74.4 1.4 24.2 100.0 12 Education No education 95.5 1.5 2.9 100.0 239 Primary incomplete 81.2 1.7 17.1 100.0 460 Primary complete 96.2 0.7 3.1 100.0 1,249 Secondary+ 54.8 2.7 42.5 100.0 578 Wealth quintile Lowest 88.8 1.4 9.8 100.0 401 Second 88.2 1.7 10.0 100.0 447 Middle 85.8 1.4 12.8 100.0 490 Fourth 79.8 1.2 19.0 100.0 572 Highest 80.1 1.4 18.5 100.0 618 Total 15-49 83.9 1.4 14.6 100.0 2,527 1 Currently employed is defined as having done work in the past seven days. Includes persons who did not work in the past seven days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 44 | Characteristics of Respondents 3.4.2 Occupation Respondents who are currently employed or who were employed during the year preceding the survey were asked to state their principal occupation. Tables 3.6.1 and 3.6.2 show the findings for women and men, respectively. Tanzania, like many developing countries, is an agrarian economy. The agricultural sector remains the main employer, with 69 percent of women and 62 percent of men engaged in agricultural occupations. These figures are lower than those in the 2004-05 TDHS, when 78 percent of women and 71 percent of men were employed in agricultural occupations. Unskilled manual labour is an emerging sector, with 17 percent of women and 13 percent of men employed in this sector. Profes- sional, technical, and managerial occupations engage only 3 percent of women and 5 percent of men. Analysis by age suggests little association with occupational categories, with the exception of the professional, technical, and managerial occupations, the proportions of which generally increase with age. As expected, those women and men with at least some secondary education are most likely to be employed in a professional, technical, or managerial job. Women in the wealthiest quintile are most likely to be engaged in an unskilled manual occupation (38 percent), while men in the highest quintile are most likely to have a skilled manual occupation (30 percent). Residence has a close association with the type of occupation. The majority of rural women and men are engaged in agriculture, while urban dwellers are mostly found in skilled and unskilled occupations. Residents of Zanzibar have more varied occupations than those who live in the Main- land. Zanzibar respondents are more likely than those in the Mainland to be employed in professional, technical, and managerial occupations. In Zanzibar, 8 percent of women and men work as profes- sionals, technical workers, or managers compared with 2 percent of women and 4 percent of men in the Mainland. Figure 3.1 Employment Status of Women and Men Women Men Currently employed 78% Employed in 12 months preceding survey, but not currently employed 3% Not employed in the 12 months preceding the survey 20% Not employed in the 12 months preceding the survey 15% Currently employed 84% Employed in 12 months preceding survey, but not currently employed 1% TDHS 2010Note: Totals may not add to 100 percent because of rounding. Characteristics of Respondents | 45 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, Tanzania 2010 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agri- culture Missing Total Number of women Age 15-19 0.8 0.0 2.6 6.2 10.1 5.2 73.4 1.8 100.0 1,127 20-24 1.7 0.3 3.2 7.8 17.8 4.7 64.4 0.1 100.0 1,550 25-29 3.2 0.8 3.6 6.3 17.3 2.7 66.1 0.1 100.0 1,438 30-34 4.0 0.5 4.9 5.2 20.3 2.9 61.9 0.2 100.0 1,282 35-39 2.5 0.4 3.5 2.3 14.9 1.7 74.7 0.1 100.0 1,186 40-44 1.6 0.5 4.1 2.9 20.7 1.6 68.4 0.3 100.0 859 45-49 3.3 1.0 1.6 1.6 13.8 2.0 76.6 0.0 100.0 695 Marital status Never married 4.4 0.6 3.7 9.5 17.1 8.6 54.3 1.7 100.0 1,365 Married or living together 2.2 0.4 3.4 4.2 15.2 1.5 73.1 0.1 100.0 5,681 Divorced/separated/widowed 1.4 0.8 3.4 4.1 23.0 4.8 62.3 0.2 100.0 1,092 Number of living children 0 3.7 0.8 3.2 9.7 15.1 7.0 59.0 1.6 100.0 1,476 1-2 3.4 0.8 4.9 6.8 20.5 3.9 59.6 0.2 100.0 2,642 3-4 2.0 0.1 3.6 2.6 17.1 1.4 73.1 0.1 100.0 2,122 5+ 0.7 0.2 1.6 1.6 11.7 0.9 83.2 0.0 100.0 1,897 Residence Urban 6.9 1.8 8.8 12.8 41.0 9.2 19.0 0.5 100.0 1,998 Rural 1.0 0.0 1.7 2.5 8.6 1.1 84.6 0.3 100.0 6,140 Mainland/Zanzibar Mainland 2.3 0.5 3.4 4.8 16.1 3.1 69.4 0.4 100.0 7,947 Urban 6.7 1.8 8.7 12.8 40.7 9.2 19.5 0.6 100.0 1,927 Rural 0.9 0.0 1.7 2.3 8.2 1.1 85.3 0.3 100.0 6,020 Zanzibar 7.7 1.0 5.6 13.8 35.7 4.2 31.9 0.2 100.0 191 Unguja 8.6 1.0 6.9 15.3 44.6 5.3 18.2 0.0 100.0 134 Pemba 5.3 1.0 2.5 10.3 14.8 1.5 64.1 0.4 100.0 57 Zone Western 0.9 0.0 2.4 3.9 8.4 0.5 83.5 0.5 100.0 1,530 Northern 3.9 0.6 7.7 7.2 35.7 7.5 37.1 0.3 100.0 893 Central 0.9 0.4 1.2 1.0 5.4 1.1 89.1 0.9 100.0 780 Southern Highlands 2.2 0.0 3.2 5.3 14.0 2.2 72.4 0.7 100.0 1,183 Lake 1.7 0.5 1.9 4.9 8.8 1.4 80.8 0.0 100.0 1,562 Eastern 5.0 1.7 6.4 8.5 35.6 8.4 34.1 0.3 100.0 1,227 Southern 2.0 0.1 1.4 1.3 6.6 1.3 87.0 0.2 100.0 772 Region Dodoma 0.6 0.6 0.6 0.0 3.8 1.3 92.7 0.3 100.0 480 Arusha 4.7 2.2 12.6 14.4 44.2 12.0 9.2 0.7 100.0 159 Kilimanjaro 6.1 0.0 5.9 5.9 35.2 6.6 40.2 0.0 100.0 304 Tanga 1.7 0.4 6.4 4.8 32.8 5.8 47.8 0.4 100.0 369 Morogoro 2.0 0.3 1.9 6.9 15.5 4.2 69.2 0.0 100.0 409 Pwani 2.2 0.8 5.3 4.7 30.0 2.6 54.4 0.0 100.0 208 Dar es Salaam 8.0 2.9 9.7 10.9 51.0 13.1 3.6 0.7 100.0 610 Lindi 0.5 0.0 0.5 1.0 3.8 0.9 92.9 0.4 100.0 167 Mtwara 1.6 0.0 1.4 0.3 3.2 1.4 92.0 0.0 100.0 323 Ruvuma 3.4 0.3 1.9 2.6 12.1 1.6 77.8 0.4 100.0 281 Iringa 2.8 0.0 2.1 6.4 15.6 4.5 68.6 0.0 100.0 421 Mbeya 2.4 0.0 3.6 4.8 14.6 1.3 71.9 1.5 100.0 533 Singida 1.3 0.0 2.2 2.6 7.9 0.8 83.4 1.7 100.0 300 Tabora 1.2 0.0 0.6 3.3 2.5 0.8 89.8 1.8 100.0 411 Rukwa 0.7 0.0 4.3 4.4 9.3 0.3 80.9 0.0 100.0 228 Kigoma 0.5 0.0 2.1 5.6 20.7 0.2 71.0 0.0 100.0 379 Shinyanga 1.0 0.0 3.4 3.4 5.4 0.5 86.3 0.0 100.0 741 Kagera 0.2 0.3 1.0 3.3 9.5 1.2 84.5 0.0 100.0 495 Mwanza 2.9 0.8 2.2 6.9 9.5 1.9 75.7 0.0 100.0 714 Mara 1.1 0.0 2.7 2.9 6.4 0.9 86.0 0.0 100.0 353 Manyara 4.7 0.0 11.6 9.1 34.0 10.5 30.1 0.0 100.0 61 Unguja North 4.1 0.0 3.2 16.5 31.6 1.4 43.3 0.0 100.0 36 Unguja South 4.2 0.3 4.8 24.9 37.4 4.0 24.2 0.3 100.0 24 Town West 12.3 1.7 9.5 11.5 53.4 7.6 4.1 0.0 100.0 74 Pemba North 6.1 1.0 1.6 8.1 12.8 0.0 69.9 0.5 100.0 28 Pemba South 4.6 0.9 3.3 12.5 16.8 3.0 58.4 0.4 100.0 29 Education No education 0.0 0.0 0.6 0.9 9.6 1.5 87.4 0.0 100.0 1,722 Primary incomplete 0.1 0.0 1.1 2.5 14.2 3.1 77.9 1.0 100.0 1,172 Primary complete 0.8 0.2 3.8 6.5 18.4 3.6 66.7 0.1 100.0 4,411 Secondary+ 19.9 3.7 11.1 9.4 24.6 3.8 25.9 1.5 100.0 833 Wealth quintile Lowest 0.1 0.0 0.2 1.0 4.2 0.3 93.5 0.5 100.0 1,466 Second 0.0 0.0 0.5 0.8 5.8 0.6 92.2 0.2 100.0 1,716 Middle 0.4 0.0 1.2 1.6 9.5 0.6 86.7 0.0 100.0 1,686 Fourth 1.1 0.1 4.9 8.2 25.1 2.8 57.3 0.5 100.0 1,637 Highest 10.6 2.3 10.4 13.5 37.8 11.3 13.5 0.7 100.0 1,632 Total 2.5 0.5 3.5 5.0 16.6 3.1 68.5 0.4 100.0 8,138 46 | 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, Tanzania 2010 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Domestic service Agri- culture Missing Total Number of men Age 15-19 0.6 0.0 2.9 6.0 16.3 1.4 70.1 2.7 100.0 358 20-24 2.0 0.0 3.7 14.0 17.3 0.7 61.8 0.5 100.0 344 25-29 5.5 0.3 3.6 17.3 12.3 0.5 59.8 0.7 100.0 336 30-34 4.7 0.1 6.4 13.2 16.3 1.7 57.6 0.0 100.0 351 35-39 6.7 0.5 6.9 15.3 10.5 0.9 58.1 1.1 100.0 296 40-44 4.6 0.0 5.3 14.2 10.3 1.7 64.0 0.0 100.0 268 45-49 10.3 1.5 6.2 10.0 6.3 0.1 65.6 0.0 100.0 204 Marital status Never married 3.0 0.1 3.9 12.6 16.7 1.7 60.0 1.9 100.0 686 Married or living together 5.2 0.3 5.6 12.0 11.5 0.6 64.5 0.3 100.0 1,311 Divorced/separated/widowed 5.5 0.9 2.6 21.1 14.4 1.5 54.0 0.0 100.0 161 Number of living children 0 3.3 0.1 3.8 13.1 16.7 1.5 59.8 1.7 100.0 781 1-2 4.2 0.0 4.4 16.1 16.2 0.8 57.9 0.4 100.0 555 3-4 6.8 0.4 6.9 12.5 9.8 1.4 61.7 0.5 100.0 428 5+ 5.0 0.7 5.3 8.3 6.7 0.0 74.1 0.0 100.0 394 Residence Urban 10.8 0.9 11.5 28.6 25.1 2.9 18.2 2.0 100.0 556 Rural 2.3 0.1 2.5 7.4 9.3 0.4 77.6 0.4 100.0 1,601 Mainland/Zanzibar Mainland 4.4 0.3 4.6 12.6 13.2 1.0 63.2 0.8 100.0 2,099 Urban 10.9 0.8 10.8 28.5 25.4 2.9 18.6 2.1 100.0 532 Rural 2.2 0.1 2.4 7.2 9.0 0.3 78.3 0.4 100.0 1,567 Zanzibar 7.9 0.8 15.3 22.4 20.6 2.4 30.4 0.2 100.0 58 Unguja 7.9 1.1 17.3 25.1 22.0 3.2 23.4 0.0 100.0 44 Pemba 7.8 0.0 9.4 14.2 16.6 0.0 51.2 0.8 100.0 15 Zone Western 4.0 0.9 2.9 8.3 9.5 0.4 73.2 0.8 100.0 319 Northern 5.1 0.0 5.6 18.1 14.5 1.9 54.3 0.4 100.0 281 Central 0.7 0.0 1.0 2.9 6.9 1.4 85.5 1.5 100.0 208 Southern Highlands 1.8 0.0 2.5 13.7 15.1 0.0 65.1 1.8 100.0 314 Lake 5.8 0.2 5.6 8.5 12.5 0.0 67.4 0.0 100.0 411 Eastern 8.6 0.5 9.5 24.1 22.3 3.3 31.4 0.3 100.0 349 Southern 2.1 0.0 2.0 9.0 6.4 0.0 78.9 1.6 100.0 217 Region Dodoma 1.2 0.0 1.1 3.3 10.6 2.4 81.3 0.0 100.0 122 Arusha 4.2 0.0 6.8 24.3 18.3 5.7 40.7 0.0 100.0 73 Kilimanjaro 8.7 0.0 6.5 22.6 15.5 0.0 46.7 0.0 100.0 67 Tanga 4.5 0.0 4.0 14.4 15.9 1.2 58.8 1.2 100.0 105 Morogoro 5.0 0.0 4.5 16.5 10.4 1.0 61.7 0.9 100.0 128 Pwani 0.0 0.0 17.9 19.6 22.8 0.0 39.7 0.0 100.0 48 Dar es Salaam 13.6 0.9 10.9 31.0 31.0 5.8 6.8 0.0 100.0 173 Lindi 0.0 0.0 1.7 2.8 7.4 0.0 81.8 6.3 100.0 44 Mtwara 2.0 0.0 4.0 10.5 6.2 0.0 77.3 0.0 100.0 73 Ruvuma 3.2 0.0 0.6 10.6 6.1 0.0 78.7 0.7 100.0 100 Iringa 1.9 0.0 1.0 18.7 13.0 0.0 64.6 0.9 100.0 132 Mbeya 1.8 0.0 2.5 10.6 22.6 0.0 58.6 3.8 100.0 120 Singida 0.0 0.0 0.8 2.2 1.7 0.0 91.6 3.6 100.0 86 Tabora 5.0 0.0 1.5 4.7 6.7 0.0 80.8 1.4 100.0 92 Rukwa 1.8 0.0 5.8 9.0 4.9 0.0 78.6 0.0 100.0 62 Kigoma 4.1 1.4 3.3 13.8 17.4 1.4 57.1 1.4 100.0 81 Shinyanga 3.4 1.2 3.6 7.5 7.0 0.0 77.3 0.0 100.0 147 Kagera 4.1 0.0 3.3 10.1 18.2 0.0 64.3 0.0 100.0 130 Mwanza 7.5 0.4 6.7 8.2 8.5 0.0 68.7 0.0 100.0 219 Mara 3.2 0.0 6.8 5.9 14.8 0.0 69.4 0.0 100.0 62 Manyara 2.1 0.0 6.3 8.1 1.2 0.0 82.2 0.0 100.0 37 Unguja North 1.4 0.0 6.7 17.4 33.2 3.7 37.6 0.0 100.0 9 Unguja South 3.6 0.0 8.0 9.9 24.1 1.5 52.9 0.0 100.0 9 Town West 11.6 1.8 24.1 33.0 17.3 3.7 8.5 0.0 100.0 26 Pemba North 6.0 0.0 8.7 9.8 5.5 0.0 67.8 2.2 100.0 5 Pemba South 8.8 0.0 9.9 16.6 22.8 0.0 42.0 0.0 100.0 9 Education No education 0.9 0.0 0.9 6.6 8.0 0.7 82.9 0.0 100.0 232 Primary incomplete 0.8 0.3 1.4 6.8 16.1 0.9 72.5 1.3 100.0 382 Primary complete 2.0 0.3 6.4 13.5 13.0 1.1 63.3 0.5 100.0 1,211 Secondary+ 20.7 0.5 5.9 21.8 15.5 1.0 32.6 2.0 100.0 333 Wealth quintile Lowest 0.0 0.0 0.5 3.1 3.6 0.9 91.9 0.0 100.0 361 Second 0.9 0.0 1.1 4.3 7.8 0.0 85.6 0.3 100.0 402 Middle 0.4 0.2 1.3 5.7 10.4 0.3 80.9 0.8 100.0 427 Fourth 4.5 0.0 5.9 16.1 18.4 0.4 53.1 1.5 100.0 464 Highest 14.1 1.0 12.9 29.8 22.7 3.1 15.2 1.2 100.0 503 Total 15-49 4.5 0.3 4.8 12.9 13.4 1.0 62.3 0.8 100.0 2,157 Characteristics of Respondents | 47 Table 3.7 presents information on women’s employment status, including type of earnings and type of employer, and also the continuity of employment. The table takes into account whether women are involved in agricultural or nonagricultural occupations because all of the employment variables shown in the table are strongly influenced by the sector in which a woman is employed. The data show that in the agricultural sector the majority of women who work are not paid (72 percent), 42 percent are employed by a family member, 57 percent are self-employed, and 82 percent work seasonally. Among women employed in nonagricultural work, 87 percent earn only cash income, and 7 percent receive payment in cash and in kind. In the nonagricultural sector, 63 percent of women are self-employed, and 74 percent work all year. Table 3.7 Type of employment: Women Percent distribution of women age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Tanzania 2010 Employment characteristic Agricultural work Nonagricultural work Total Type of earnings Cash only 8.7 86.7 33.0 Cash and in-kind 16.5 6.8 13.4 In-kind only 2.3 0.8 1.8 Not paid 72.3 5.6 51.5 Missing 0.2 0.2 0.2 Total 100.0 100.0 100.0 Type of employer Employed by family member 41.9 11.1 32.3 Employed by nonfamily member 1.6 25.5 9.0 Self-employed 56.5 63.4 58.6 Missing 0.0 0.1 0.1 Total 100.0 100.0 100.0 Continuity of employment All year 14.7 74.0 33.3 Seasonal 81.8 15.6 61.0 Occasional 3.5 10.4 5.6 Missing 0.0 0.0 0.1 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 5,574 2,533 8,138 Note: Total includes 26 unweighted women with information missing on their type of employment. 3.5 ADULT HEALTH ISSUES 3.5.1 Health Insurance Coverage Health care financing is very challenging in most of the developing countries, including Tanzania, because of limited resources available to support the health systems. Unfortunately, there have been increasing need

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