Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS), 2022 - Final Report (English)

Publication date: 2023

Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) 2022 Tanzania 2022 D em ographic and H ealth S urvey and M alaria Indicator S urvey (TD H S -M IS ) The United Republic of Tanzania Tanzania Demographic and Health Survey and Malaria Indicator Survey 2022 Ministry of Health Dodoma Ministry of Health Zanzibar National Bureau of Statistics Dodoma Office of the Chief Government Statistician Zanzibar The DHS Program ICF Rockville, Maryland, USA September 2023 The 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS-MIS) was implemented by the Tanzania National Bureau of Statistics (NBS) and the Office of Chief Government Statistician (OCGS) in collaboration with the Ministries of Health of Tanzania Mainland and Zanzibar. The Tanzania Food and Nutrition Centre (TFNC) collaborated on several aspects of the survey, especially biomarkers. Funding for the 2022 TDHS-MIS was provided by the Government of Tanzania; the United States Agency for International Development (USAID); the President’s Malaria Initiative (PMI); the Canadian International Development Agency (CIDA); the Centers for Disease Control and Prevention (CDC); the Foreign, Commonwealth and Development Office (FCDO); the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); the Hilton Foundation; Irish AID; the Royal Norwegian Embassy and Legal and Human Rights Centre (LHRC); Nutrition International, United Nations Children’s Fund (UNICEF); the World Food Programme (WFP); and the Bill & Melinda Gates Foundation. ICF provided technical assistance through The DHS Program, a USAID-funded project providing support and technical assistance in the implementation of population and health surveys in countries worldwide. Additional information about the 2022 TDHS-MIS may be obtained from the National Bureau of Statistics, Head Office, 64 Lusinde Road, P.O. Box 2683, 41104 Tambukareli, Dodoma, Tanzania; telephone: +255-26-296-3822; fax: +255-26-296-3828; email: sg@nbs.go.tz; website: www.nbs.go.tz and the Office of the Chief Government Statistician, P.O. Box 2321, Zanzibar, Tanzania; telephone: +255-24-224-0134; email: zanstat@ocgs.go.tz; website: https://www.ocgs.go.tz. Information about The DHS Program may be obtained from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; telephone: +1-301-407-6500; fax: +1-301-407-6501; email: info@DHSprogram.com; internet: www.DHSprogram.com. The contents of this report are the sole responsibility of the National Bureau of Statistics (NBS), the Office of the Chief Government Statistician (OCGS), and ICF and do not necessarily reflect the views of USAID, the United States Government, or other donor agencies. Recommended citation: Ministry of Health (MoH) [Tanzania Mainland], Ministry of Health (MoH) [Zanzibar], National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. 2022. Tanzania Demographic and Health Survey and Malaria Indicator Survey 2022 Final Report. Dodoma, Tanzania, and Rockville, Maryland, USA: MoH, NBS, OCGS, and ICF. http://www.nbs.go.tz/ mailto:zanstat@ocgs.go.tz https://www.ocgs.go.tz/ http://www.dhsprogram.com/ Contents • iii CONTENTS TABLES, FIGURES, AND MAPS . ix FOREWORD . xxi ACKNOWLEDGEMENTS . xxiii ACRONYMS AND ABBREVIATIONS . xxv READING AND UNDERSTANDING TABLES FROM THE 2022 TANZANIA DEMOGRAPHIC AND HEALTH SURVEY AND MALARIA INDICATOR SURVEY (TDHS-MIS) . xxix SUSTAINABLE DEVELOPMENT GOAL INDICATORS . xxxvii MAP OF TANZANIA . xl 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Survey Objectives . 1 1.2 Sample Design . 2 1.3 Questionnaires . 3 1.4 Anthropometry, Anaemia, Malaria and Iodine Testing, and Blood Pressure Measurements . 4 1.5 Training of Trainers and Pretest . 6 1.6 Training of Field Staff . 6 1.7 Fieldwork . 7 1.8 Data Processing . 7 1.9 Response Rates . 8 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 2.1 Housing Characteristics . 9 2.1.1 Use of Clean Fuels and Technologies . 10 2.1.2 Cooking . 10 2.1.3 Heating and Lighting . 10 2.1.4 Primary Reliance on Clean Fuels and Technologies . 11 2.2 Household Wealth . 11 2.2.1 Household Durable Goods . 11 2.2.2 Wealth Index . 11 2.3 Coverage of Assistance Programmes . 12 2.4 Household Population and Composition . 12 2.5 Children’s Living Arrangements and Parental Survival . 13 2.6 Birth Registration . 14 2.7 Education . 15 2.7.1 Educational Attainment . 15 2.7.2 Primary and Secondary School Attendance . 16 2.7.3 Participation Rate in Organised Learning among Children Age 5 . 17 2.8 Disability . 17 2.8.1 Disability by Domain and Age . 18 2.8.2 Disability among Adults by Other Background Characteristics . 18 3 CHARACTERISTICS OF RESPONDENTS . 43 3.1 Basic Characteristics of Survey Respondents . 43 3.2 Education and Literacy . 44 3.3 Mass Media Exposure and internet Usage . 46 3.4 Employment . 47 iv • Contents 3.5 Occupation . 47 3.6 Health Insurance Coverage . 48 3.7 Tobacco Use . 49 3.8 Alcohol Consumption . 49 3.9 Place of Birth and Recent Migration . 50 3.9.1 Type of Migration . 50 3.9.2 Reason for Migration . 50 3.10 Blood Pressure . 51 3.10.1 History of Blood Pressure Measurement Prior to the Survey . 51 3.10.2 Blood Pressure Status . 52 3.10.3 Awareness, Treatment, and Control of Hypertension . 53 3.11 Tuberculosis . 54 3.11.1 Knowledge and Attitudes toward Tuberculosis . 54 3.11.2 Households with a Member Diagnosed with Tuberculosis . 55 4 MARRIAGE AND SEXUAL ACTIVITY . 121 4.1 Marital Status . 121 4.2 Marriage Registration . 122 4.3 Polygyny . 123 4.4 Age at First Marriage . 123 4.5 Age at First Sexual Intercourse . 124 4.6 Recent Sexual Activity . 125 5 FERTILITY . 139 5.1 Current Fertility . 139 5.2 Children Ever Born and Living . 142 5.3 Birth Intervals . 142 5.4 Insusceptibility to Pregnancy . 143 5.5 Age of First Menstruation . 144 5.6 Arrival of Menopause . 144 5.7 Age at First Birth . 144 5.8 Teenage Pregnancy . 144 5.9 Pregnancy Outcomes . 146 6 FERTILITY PREFERENCES . 159 6.1 Desire for Another Child . 159 6.2 Ideal Family Size . 160 6.3 Fertility Planning Status . 161 6.4 Wanted Fertility Rates . 162 7 FAMILY PLANNING . 171 7.1 Contraceptive Knowledge and Use . 171 7.1.1 Use of Emergency Contraception . 173 7.1.2 Knowledge of the Fertile Period . 174 7.2 Source of Modern Contraceptive Methods . 174 7.3 Informed Choice . 174 7.4 Discontinuation of Contraceptives . 175 7.5 Demand for Family Planning . 176 7.6 Decision Making about Family Planning . 178 7.7 Exposure to Family Planning Messages . 178 7.8 Contact of Nonusers with Family Planning Providers . 179 Contents • v 8 INFANT AND CHILD MORTALITY . 207 8.1 Infant and Child Mortality . 208 8.2 Perinatal Mortality . 210 8.3 High-risk Fertility Behaviours . 211 9 MATERNAL AND NEWBORN HEALTH CARE . 217 9.1 Antenatal Care Coverage and Content . 218 9.1.1 Skilled Providers . 218 9.1.2 Timing and Number of Antenatal Care Visits . 218 9.2 Components of Antenatal Care . 219 9.2.1 Deworming and Iron Supplementation during Pregnancy . 220 9.2.2 Source of Iron-containing Supplements . 220 9.3 Protection against Neonatal Tetanus . 221 9.4 Delivery Services . 221 9.4.1 Institutional Deliveries . 221 9.4.2 Delivery by Caesarean . 223 9.4.3 Skilled Assistance during Delivery . 224 9.4.4 Birth Companion . 225 9.4.5 Respectful Care and Nondignified Treatment in Health Facilities . 225 9.4.6 Presence of and Access to Toilets in Health Facilities. 226 9.4.7 Experience of Physical and Verbal Abuse in Health Facilities . 226 9.4.8 Duration of Stay at the Health Facility . 227 9.5 Postnatal Care . 227 9.5.1 Postnatal Health Check for Mothers . 227 9.5.2 Postnatal Health Check for Newborns . 228 9.5.3 Postnatal Health Checks for Mothers and Newborns . 229 9.6 Men’s Involvement in Maternal Health Care . 229 9.7 Breast and Cervical Cancer Examinations . 230 9.8 Problems in Accessing Health Facilities . 231 9.9 Distance and Means of Transport to the Nearest Health Facility . 231 10 CHILD HEALTH . 289 10.1 Child’s Size at Birth . 289 10.2 Vaccination of Children . 290 10.2.1 Vaccination Card Ownership and Availability . 290 10.2.2 Basic Antigen Coverage . 290 10.2.3 National Schedule Coverage . 292 10.3 Symptoms of Acute Respiratory Infection and Care-seeking Behaviour . 293 10.4 Fever and Care-seeking Behaviour . 293 10.5 Diarrhoeal Disease . 294 10.5.1 Diarrhoea and Care-seeking Behaviour . 294 10.5.2 Feeding Practices . 294 10.5.3 Oral Rehydration Therapy, Continued Feeding, and Other Treatments . 295 10.6 Treatment of Childhood Illness . 296 10.7 Early Childhood Development Index 2030 . 296 11 NUTRITION OF CHILDREN AND ADULTS . 317 11.1 Nutritional Status of Children . 318 11.2 Growth Monitoring and Promotion . 321 11.3 Infant and Young Child Feeding Practices . 322 11.3.1 Ever Breastfed, Early Initiation of Breastfeeding, and Exclusive Breastfeeding for the First 2 Days after Birth . 322 11.3.2 Exclusive Breastfeeding and Mixed Milk Feeding . 323 vi • Contents 11.3.3 Continued Breastfeeding and Bottle Feeding . 324 11.3.4 Introduction of Complementary Foods . 325 11.3.5 Minimum Dietary Diversity, Minimum Meal Frequency, Minimum Milk Feeding Frequency, Minimum Acceptable Diet, and Egg and/or Flesh Food Consumption . 325 11.3.6 Sweet Beverage Consumption, Unhealthy Food Consumption, and Zero Vegetable or Fruit Consumption among Children . 327 11.3.7 Infant and Young Child Feeding (IYCF) Indicators . 328 11.4 Infant and Young Child Feeding Counselling . 328 11.5 Micronutrient Supplementation and Deworming among Children . 328 11.6 Anaemia Prevalence in Children and Women . 329 11.6.1 Anaemia in Children Based on Capillary Blood Samples . 330 11.6.2 Anaemia in Women Based on Capillary Blood Samples . 331 11.6.3 Anaemia in Children and Women Based on Venous Blood Samples . 332 11.7 Adults’ Nutritional Status . 332 11.7.1 Nutritional Status of Women . 333 11.7.2 Nutritional Status of Men . 334 11.8 Women’s Dietary Practices . 335 11.9 Presence of Iodised Salt in Households . 336 11.10 Urinary Iodine Concentrations in Women . 337 12 MALARIA . 375 12.1 Ownership of Insecticide-treated Nets . 376 12.2 Household Access to and Use of ITNs . 377 12.3 Use of ITNs by Children and Pregnant Women . 378 12.4 Reasons Mosquito Nets Were Not Used . 380 12.5 Malaria in Pregnancy . 380 12.6 Case Management of Malaria in Children . 381 12.7 Prevalence of Low Haemoglobin Levels in Children . 382 12.8 Prevalence of Malaria in Children . 383 12.9 Exposure to Malaria Messages . 384 12.10 Most Serious Health Problem in the Community . 385 12.11 Knowledge of Ways to Avoid Malaria . 386 12.12 Access to Artemisinin-based Combination Therapy (ACT) and Visits from Health Workers . 386 12.13 Perceived Susceptibility, Severity, and Self-efficacy . 387 12.14 Attitudes toward Malaria-related Behaviours and Perceptions of Community Norms . 387 13 KNOWLEDGE, ATTITUDES, AND BEHAVIOUR RELATED TO HIV AND AIDS . 435 13.1 Knowledge and Attitudes about Medicines to Treat or Prevent HIV . 435 13.2 Discriminatory Attitudes towards People Living with HIV . 436 13.3 Multiple Sexual Partners . 437 13.4 Coverage of HIV Testing Services . 438 13.4.1 HIV Testing of Pregnant Women . 438 13.4.2 Experience with Prior HIV Testing . 439 13.5 Disclosure, Shame, and Stigma among People Living with HIV . 439 13.6 Male Circumcision . 441 13.7 Self-reporting of Sexually Transmitted Infections . 442 13.8 Knowledge and Behaviour Related to HIV and AIDS among Young People . 442 13.8.1 Knowledge about HIV Prevention . 442 13.8.2 First Sex . 443 13.8.3 Premarital Sex . 444 Contents • vii 13.8.4 Multiple Sexual Partners . 444 13.8.5 Recent HIV Testing . 444 14 ADULT AND MATERNAL MORTALITY . 473 14.1 Policies and Programmes for the Prevention of Maternal Mortality in Tanzania . 473 14.2 Data . 475 14.3 Direct Estimates of Adult Mortality . 475 14.4 Trends in Adult Mortality . 476 14.5 Direct Estimates of Maternal Mortality . 477 14.6 Trends in Pregnancy-related and Maternal Mortality . 478 15 WOMEN’S EMPOWERMENT . 483 15.1 Married Women’s and Men’s Employment . 483 15.2 Control over Women’s Earnings . 484 15.3 Control over Men’s Earnings . 485 15.4 Women’s and Men’s Ownership of Assets . 486 15.4.1 Ownership of a House or Land and Documentation of Ownership . 486 15.4.2 Ownership and Use of Mobile Phones and Bank Accounts . 487 15.5 Participation in Decision Making . 487 15.6 Attitudes toward Wife Beating . 488 15.7 Negotiating Sexual Relations . 489 15.8 Women’s Participation in Decision Making regarding Sexual and Reproductive Health . 490 16 HOUSEHOLD WATER, SANITATION, AND HYGIENE . 525 16.1 Drinking Water Sources, Availability, and Treatment . 525 16.1.1 Drinking Water Service Ladder . 526 16.1.2 Person Collecting Drinking Water . 528 16.1.3 Availability of Drinking Water . 529 16.1.4 Treatment of Drinking Water . 529 16.2 Sanitation . 529 16.2.1 Sanitation Service Ladder . 530 16.2.2 Removal and Disposal of Excreta . 531 16.3 Disposal of Children’s Stools . 532 16.4 Menstrual Health and Hygiene . 533 17 FEMALE GENITAL MUTILATION/CUTTING . 547 17.1 Respondents’ Knowledge of Female Genital Mutilation/Cutting . 548 17.2 Female Genital Mutilation/Cutting Among Women . 548 17.2.1 Prevalence and Type of FGM/C . 548 17.2.2 Age at Circumcision . 550 17.3 Circumcision of Daughters . 550 17.4 Person Who Performed the Circumcision . 551 17.5 Attitudes towards Female Circumcision . 551 18 DOMESTIC VIOLENCE . 559 18.1 Measurement of Violence . 561 18.2 Women’s Experience of Physical Violence . 562 18.2.1 Prevalence of Physical Violence . 562 18.2.2 Perpetrators of Physical Violence . 562 18.2.3 Experience of Physical Violence during Pregnancy . 563 viii • Contents 18.3 Experience of Sexual Violence . 563 18.3.1 Prevalence of Sexual Violence . 563 18.3.2 Perpetrators of Sexual Violence . 563 18.3.3 Experience of Sexual Violence by a Non-intimate Partner . 564 18.3.4 Age at First Experience of Sexual Violence . 564 18.4 Experience of Multiple Forms of Violence . 564 18.5 Forms of Controlling Behaviours and Intimate Partner Violence . 564 18.5.1 Prevalence of Controlling Behaviours and Violence Perpetrated by the Current or Most Recent Husband or Intimate Partner . 564 18.5.2 Violence in the Last 12 Months Perpetrated by Any Husband or Intimate Partner . 568 18.6 Injuries to Women due to Intimate Partner Violence . 569 18.7 Violence Initiated by Women against Their Husband/Intimate Partner . 569 18.8 Help Seeking among Women Who Have Experienced Violence . 570 REFERENCES . 593 Appendix A SAMPLE DESIGN . 599 A.1 Introduction . 599 A.2 Sampling Frame . 599 A.3 Sample Allocation and Sampling Procedure . 602 A.4 Selection Probability and Sampling Weights . 604 A.5 Survey Results . 605 Appendix B ESTIMATES OF SAMPLING ERRORS . 609 Appendix C DATA QUALITY TABLES . 651 Appendix D PERSONS INVOLVED IN THE 2022 TANZANIA DHS-MIS . 681 Appendix E QUESTIONNAIRES . 687 Household Questionnaire . 689 Woman Questionnaire . 709 Man’s Questionnaire . 809 Biomarker Questionnaire . 845 Remeasurement Questionnaire . 871 Fieldworker Questionnaire . 875 Tables, Figures, and Maps • ix TABLES, FIGURES, AND MAPS 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Selected demographic indicators from various sources, Tanzania 1967–2012 . 2 Table 1.2 Results of the household and individual interviews . 8 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 9 Table 2.1 Household characteristics . 20 Table 2.2 Household characteristics: Cooking . 21 Table 2.3 Household characteristics: Heating and lighting . 22 Table 2.4 Primary reliance on clean fuels and technologies . 23 Table 2.5 Household possessions . 24 Table 2.6 Wealth quintiles . 25 Table 2.7 Coverage of TASAF programmes . 26 Table 2.8 Household population by age, sex, and residence . 27 Table 2.9 Household composition . 28 Table 2.10 Children’s living arrangements and orphanhood . 29 Table 2.11 Birth registration of children under age 5 . 31 Table 2.12 Birth notification forms . 32 Table 2.13.1 Educational attainment of the female household population . 34 Table 2.13.2 Educational attainment of the male household population . 35 Table 2.14 School attendance ratios . 36 Table 2.15 Participation rate in organised learning . 38 Table 2.16 Disability by domain and age . 39 Table 2.17.1 Disability among adults according to background characteristics: Women . 40 Table 2.17.2 Disability among adults according to background characteristics: Men . 41 Figure 2.1 Primary reliance on clean fuels and technologies . 11 Figure 2.2 Household wealth by residence. 12 Figure 2.3 Population pyramid . 13 Figure 2.4 Secondary school attendance by household wealth . 17 Map 2.1 Orphanhood by region . 14 Map 2.2 Birth registration by region . 15 3 CHARACTERISTICS OF RESPONDENTS . 43 Table 3.1 Background characteristics of respondents . 57 Table 3.2.1 Educational attainment: Women . 59 Table 3.2.2 Educational attainment: Men . 60 Table 3.3.1 Literacy: Women . 61 Table 3.3.2 Literacy: Men . 62 Table 3.4.1 Exposure to mass media: Women . 63 Table 3.4.2 Exposure to mass media: Men . 64 Table 3.5.1 internet usage: Women . 65 Table 3.5.2 internet usage: Men . 67 Table 3.6.1 Employment status: Women . 69 Table 3.6.2 Employment status: Men . 71 Table 3.7.1 Occupation: Women . 73 Table 3.7.2 Occupation: Men . 75 Table 3.8 Type of employment: Women . 76 x • Tables, Figures, and Maps Table 3.9.1 Health insurance coverage: Women . 77 Table 3.9.2 Health insurance coverage: Men . 78 Table 3.9.3 Health insurance coverage: Children age 0–14 years . 79 Table 3.9.4 Health insurance coverage: women age 50+ . 80 Table 3.9.5 Health insurance coverage: men age 50+ . 82 Table 3.10.1 Tobacco smoking: Women . 84 Table 3.10.2 Tobacco smoking: Men . 85 Table 3.11 Average number of cigarettes smoked daily: Men . 86 Table 3.12 Smokeless tobacco use and any tobacco use . 86 Table 3.13 Any tobacco use by background characteristics . 87 Table 3.14.1 Alcohol consumption: Women . 88 Table 3.14.2 Alcohol consumption: Men . 90 Table 3.15.1 Usual number of alcoholic drinks consumed: Women . 92 Table 3.15.2 Usual number of alcoholic drinks consumed: Men . 94 Table 3.16.1 Place of birth and recent migration: Women . 96 Table 3.16.2 Place of birth and recent migration: Men . 98 Table 3.17 Type of migration . 99 Table 3.18.1 Reason for migration: Women . 100 Table 3.18.2 Reason for migration: Men . 102 Table 3.19.1 Blood pressure measured and medication prescribed and taken: Women . 104 Table 3.19.2 Blood pressure measured and medication prescribed and taken: Men . 106 Table 3.20.1 Blood pressure status of women . 108 Table 3.20.2 Blood pressure status of men . 110 Table 3.21.1 Prevalence of controlled hypertension among women . 112 Table 3.21.2 Controlled hypertension among men . 114 Table 3.22.1 Knowledge about tuberculosis: Women . 116 Table 3.22.2 Knowledge about tuberculosis: Men . 118 Table 3.23 Conditions that increase the risk of acquiring tuberculosis . 119 Table 3.24 First source of care for symptoms of tuberculosis . 119 Table 3.25 Households with any member diagnosed with tuberculosis . 120 Figure 3.1 Education of survey respondents . 44 Figure 3.2 Secondary education by household wealth . 45 Figure 3.3 Exposure to mass media . 46 Figure 3.4 Employment status by marital status . 47 Figure 3.5 Occupation . 48 Figure 3.6 Any tobacco use by education . 49 Figure 3.7 Hypertension by age . 53 Figure 3.8 Awareness, treatment, and control of hypertension . 54 Map 3.1 Education by region . 45 4 MARRIAGE AND SEXUAL ACTIVITY . 121 Table 4.1 Current marital status . 126 Table 4.2 Marriage registration . 127 Table 4.3.1 Number of women’s co-wives . 128 Table 4.3.2 Number of men’s wives . 129 Table 4.4 Age at first marriage . 130 Table 4.5 Median age at first marriage by background characteristics . 131 Table 4.6 Age at first sexual intercourse . 132 Table 4.7 Median age at first sexual intercourse according to background characteristics 133 Tables, Figures, and Maps • xi Table 4.8.1 Recent sexual activity: Women . 134 Table 4.8.2 Recent sexual activity: Men . 136 Figure 4.1 Marital status . 122 Figure 4.2 Median age at first sex and first marriage . 124 5 FERTILITY . 139 Table 5.1 Current fertility . 147 Table 5.2 Fertility by background characteristics . 148 Table 5.3.1 Trends in age-specific fertility rates . 149 Table 5.3.2 Trends in age-specific and total fertility rates . 149 Table 5.4 Children ever born and living . 149 Table 5.5 Birth intervals . 150 Table 5.6 Postpartum amenorrhoea, abstinence and insusceptibility . 151 Table 5.7 Median duration of amenorrhoea, postpartum abstinence and postpartum insusceptibility . 152 Table 5.8 Age at first menstruation . 153 Table 5.9 Menopause . 153 Table 5.10 Age at first birth . 153 Table 5.11 Median age at first birth . 154 Table 5.12 Teenage pregnancy . 155 Table 5.13 Sexual and reproductive health behaviours before age 15 . 156 Table 5.14 Pregnancy outcome by background characteristics . 157 Table 5.15 Induced abortion rates . 158 Figure 5.1 Trends in fertility by residence . 140 Figure 5.2 Trends in age-specific fertility . 140 Figure 5.3 Fertility by residence . 140 Map 5.1 Fertility by region . 141 Figure 5.4 Fertility by education . 141 Figure 5.5 Birth intervals . 142 Map 5.2 Teenage pregnancy by region . 145 6 FERTILITY PREFERENCES . 159 Table 6.1 Fertility preferences according to number of living children . 164 Table 6.2.1 Desire to limit childbearing: Women . 165 Table 6.2.2 Desire to limit childbearing: Men . 166 Table 6.3 Ideal number of children by number of living children . 167 Table 6.4 Mean ideal number of children . 168 Table 6.5 Fertility planning status . 169 Table 6.6 Wanted fertility rates . 170 Figure 6.1 Trends in desire to limit childbearing . 160 Figure 6.2 Desire to limit childbearing by number of living children . 160 Figure 6.3 Ideal family size . 161 Figure 6.4 Fertility planning status . 162 Figure 6.5 Trends in wanted and actual fertility . 163 7 FAMILY PLANNING . 171 Table 7.1 Knowledge of contraceptive methods . 181 Table 7.2 Knowledge of contraceptive methods according to background characteristics . 182 xii • Tables, Figures, and Maps Table 7.3 Current use of contraception by age . 183 Table 7.4.1 Trends in current use of contraception . 184 Table 7.4.2 Current use of contraception according to background characteristics . 185 Table 7.5 Timing of sterilisation . 186 Table 7.6 Use of emergency contraception . 187 Table 7.7 Knowledge of fertile period . 188 Table 7.8 Knowledge of fertile period by age . 188 Table 7.9 Source of modern contraceptive methods . 189 Table 7.10 Use of social marketing brand pills and condoms . 190 Table 7.11 Informed choice . 191 Table 7.12 Twelve-month contraceptive discontinuation rates . 192 Table 7.13 Reasons for discontinuation . 193 Table 7.14.1 Need and demand for family planning among currently married women . 194 Table 7.14.2 Need and demand for family planning among all women and among sexually active unmarried women . 196 Table 7.15 Decision making about family planning . 198 Table 7.16 Decision making about family planning by background characteristics . 199 Table 7.17 Pressure to become pregnant . 201 Table 7.18 Future use of contraception . 202 Table 7.19.1 Exposure to family planning messages: Women . 203 Table 7.19.2 Exposure to family planning messages: Men . 204 Table 7.20 Contact of nonusers with family planning providers . 205 Figure 7.1 Contraceptive use . 172 Figure 7.2 Trends in contraceptive use . 172 Figure 7.3 Source of modern contraceptive methods . 174 Figure 7.4 Contraceptive discontinuation rates . 175 Figure 7.5 Demand for family planning . 176 Figure 7.6 Trends in demand for family planning . 177 Map 7.1 Modern contraceptive use by region . 173 Map 7.2 Unmet need by region . 178 8 INFANT AND CHILD MORTALITY . 207 Table 8.1 Early childhood mortality rates . 212 Table 8.2 Five-year childhood mortality rates according to background characteristics . 212 Table 8.3.1 Ten-year childhood mortality rates according to additional characteristics . 212 Table 8.3.2 Ten-year childhood mortality rates according to geographic regions . 213 Table 8.4 Perinatal mortality . 214 Table 8.5 High-risk fertility behaviour . 215 Figure 8.1 Trends in early childhood mortality rates . 209 Figure 8.2 Childhood mortality by previous birth interval . 209 Figure 8.3 Perinatal mortality by wealth . 211 9 MATERNAL AND NEWBORN HEALTH CARE . 217 Table 9.1 Antenatal care . 233 Table 9.2 Number of antenatal care visits and timing of first visit . 235 Table 9.3.1 Components of antenatal care among women receiving ANC . 237 Table 9.3.2 Components of antenatal care among all women . 239 Table 9.4 Deworming and iron-containing supplementation during pregnancy . 241 Table 9.5 Source of iron-containing supplements . 243 Tables, Figures, and Maps • xiii Table 9.6 Tetanus toxoid injections . 244 Table 9.7 Place of delivery . 246 Table 9.8 Caesarean section . 248 Table 9.9 Assistance during delivery . 250 Table 9.10 Presence of a companion during labour and delivery . 252 Table 9.11 Respectful care . 254 Table 9.12 Nondignified treatment at the health facility . 256 Table 9.13 Toilet for patients in the health facility . 258 Table 9.14 Experience of physical abuse in a health facility . 260 Table 9.15 Experience of verbal abuse in a health facility . 262 Table 9.16 Duration of stay in health facility after birth . 263 Table 9.17 Timing of first postnatal check for the mother . 264 Table 9.18 Type of provider of first postnatal check for the mother . 266 Table 9.19 Content of postnatal care for the mother . 268 Table 9.20 Timing of first postnatal check for the newborn . 270 Table 9.21 Type of provider of first postnatal check for the newborn . 272 Table 9.22 Content of postnatal care for newborns . 274 Table 9.23 Postnatal checks on mother and newborn . 276 Table 9.24 Men’s involvement in maternal health care . 278 Table 9.25 Husband’s or partner’s involvement in antenatal care . 280 Table 9.26 Examinations for breast and cervical cancer . 282 Table 9.27 Problems in accessing health care . 284 Table 9.28 Distance from health care . 286 Figure 9.1 Trends in antenatal care coverage . 218 Figure 9.2 Components of antenatal care . 220 Figure 9.3 Trends in place of birth . 222 Figure 9.4 Caesarean sections by household wealth . 224 Figure 9.5 Skilled assistance at delivery by birth order . 225 Figure 9.6 Postnatal care by place of delivery . 228 Figure 9.7 Breast and cervical cancer screening by residence . 230 Map 9.1 Health facility births by region . 223 10 CHILD HEALTH . 289 Table 10.1 Child’s size . 299 Table 10.2 Possession and observation of vaccination cards, according to background characteristics . 301 Table 10.3 Vaccinations by source of information . 302 Table 10.4 Vaccinations by background characteristics . 303 Table 10.5 Source of vaccinations . 305 Table 10.6 Children with symptoms of ARI and care seeking for symptoms of ARI . 306 Table 10.7 Source of advice or treatment for children with symptoms of ARI . 308 Table 10.8 Children with fever and care seeking for fever . 309 Table 10.9 Children with diarrhoea and care seeking for diarrhoea . 311 Table 10.10 Feeding practices during diarrhoea . 313 Table 10.11 Oral rehydration salts, continued feeding, and other treatments for diarrhoea . 314 Table 10.12 Source of advice or treatment for children with diarrhoea . 315 Table 10.13 Early Childhood Development Index 2030. 316 Figure 10.1 Childhood vaccinations . 291 Figure 10.2 Trends in childhood vaccinations . 291 xiv • Tables, Figures, and Maps Figure 10.3 Diarrhoea prevalence by age . 294 Figure 10.4 Feeding practices during diarrhoea . 295 Figure 10.5 Treatment of diarrhoea . 296 Figure 10.6 Symptoms of childhood illness and care seeking . 296 11 NUTRITION OF CHILDREN AND ADULTS . 317 Table 11.1 Nutritional status of children . 339 Table 11.2 Child growth monitoring . 341 Table 11.3 Early breastfeeding . 343 Table 11.4 Breastfeeding status according to age . 345 Table 11.5 Infant feeding practices by age . 346 Table 11.6 Liquids consumed by children in the day or night preceding the interview . 347 Table 11.7 Foods consumed by children in the day or night preceding the interview . 348 Table 11.8 Minimum dietary diversity, minimum meal frequency, and minimum acceptable diet among children . 349 Table 11.9 Egg and/or flesh food consumption and unhealthy feeding practices among children age 6–23 months . 351 Table 11.10 Infant and young child feeding (IYCF) indicators . 353 Table 11.11 Infant and young child feeding counselling . 354 Table 11.12 Micronutrient supplementation and deworming among children . 356 Table 11.13.1 Prevalence of anaemia in children: Capillary blood . 358 Table 11.13.2 Prevalence of anaemia in children: Venous blood . 360 Table 11.14.1 Prevalence of anaemia in women: Capillary blood . 361 Table 11.14.2 Prevalence of anaemia in women: Venous blood . 362 Table 11.15.1 Nutritional status of women age 20–49 . 363 Table 11.15.2 Nutritional status of adolescent women age 15–19 . 364 Table 11.15.3 Nutritional status of men age 20–49 . 365 Table 11.15.4 Nutritional status of adolescent men age 15–19 . 366 Table 11.16 Foods and liquids consumed by women in the day or night preceding the interview . 367 Table 11.17 Minimum dietary diversity and unhealthy food and beverage consumption among women . 369 Table 11.18 Presence of iodised salt in household . 371 Table 11.19.1 Urinary iodine concentrations in nonpregnant women . 372 Table 11.19.2 Urinary iodine concentrations in pregnant women . 373 Figure 11.1 Nutritional status of children . 320 Figure 11.2 Trends in child growth measures . 320 Figure 11.3 Infant feeding practices by age . 323 Figure 11.4 Trends in exclusive breastfeeding . 324 Figure 11.5 IYCF indicators on minimum acceptable diet by breastfeeding status . 326 Figure 11.6 Trends in childhood anaemia: capillary blood . 330 Figure 11.7 Anaemia in pregnant and nonpregnant women: capillary blood . 332 Figure 11.8 Nutritional status of adolescent and adult women . 334 Map 11.1 Stunting in children by region . 321 Map 11.2 Anaemia in children by region: capillary blood . 331 12 MALARIA . 375 Table 12.1 Household possession of mosquito nets . 389 Table 12.2.1 Source of mosquito nets . 390 Table 12.2.2 Cost of mosquito nets . 391 Tables, Figures, and Maps • xv Table 12.3 Access to an insecticide-treated net (ITN) . 392 Table 12.4 Use of mosquito nets by persons in the household . 393 Table 12.5 Use of existing ITNs . 395 Table 12.6 Use of mosquito nets by children . 396 Table 12.7 Use of mosquito nets by pregnant women . 398 Table 12.8 Main reason mosquito net was not used the night before the survey . 399 Table 12.9 Use of intermittent preventive treatment (IPTp) by women during pregnancy . 400 Table 12.10 Children with fever and care seeking, prompt treatment, and diagnosis . 402 Table 12.11 Source of advice or treatment for children with fever . 404 Table 12.12 Type of antimalarial drugs used . 405 Table 12.13 Coverage of testing for anaemia and malaria in children . 406 Table 12.14 Haemoglobin <8.0 g/dl in children . 408 Table 12.15 Prevalence of malaria in children . 410 Table 12.16.1 Most serious health problem in community: Women . 412 Table 12.16.2 Most serious health problem in community: Men . 413 Table 12.17.1 Media exposure to malaria messages: Women . 414 Table 12.17.2 Media exposure to malaria messages: Men . 416 Table 12.18 Malaria messages . 417 Table 12.19.1 Knowledge of ways to avoid malaria: Women . 418 Table 12.19.2 Knowledge of ways to avoid malaria: Men . 420 Table 12.20 Access to ACT and visits from health workers . 422 Table 12.21.1 Malaria susceptibility, severity, and self-efficacy: Women . 423 Table 12.21.2 Malaria susceptibility, severity, and self-efficacy: Men . 425 Table 12.22.1 Attitudes toward malaria-related behaviours and perceptions of community norms: Women . 427 Table 12.22.2 Attitudes toward malaria-related behaviours and perceptions of community norms: Men . 429 Table 12.23.1 Malaria knowledge: Women . 431 Table 12.23.2 Malaria knowledge: Men . 433 Figure 12.1 Household ownership of ITNs . 376 Figure 12.2 Trends in household ownership of ITNs . 376 Figure 12.3 Source of ITNs . 377 Figure 12.4 Trends in ITN access and use . 378 Figure 12.5 Trends in use of ITNs by children and pregnant women . 379 Figure 12.6 Reason ITN was not used . 380 Figure 12.7 Trends in IPTp use by pregnant women . 381 Figure 12.8 Trend in ACT use by children with fever . 382 Map 12.1 Prevalence of malaria in children by region . 384 13 KNOWLEDGE, ATTITUDES, AND BEHAVIOUR RELATED TO HIV AND AIDS . 435 Table 13.1 Knowledge of and attitudes about medicines to treat HIV or prevent HIV transmission . 446 Table 13.2 Discriminatory attitudes towards people living with HIV . 447 Table 13.3.1 Multiple sexual partners and higher-risk sexual intercourse in the last 12 months: Women . 449 Table 13.3.2 Multiple sexual partners and higher-risk sexual intercourse in the last 12 months: Men . 451 Table 13.4 Pregnant women tested for HIV. 453 Table 13.5.1 Coverage of prior HIV testing: Women . 455 Table 13.5.2 Coverage of prior HIV testing: Men . 457 xvi • Tables, Figures, and Maps Table 13.6 Number of times tested for HIV in lifetime . 459 Table 13.7 Knowledge and coverage of self-testing for HIV . 459 Table 13.8.1 Disclosure, shame, and stigma experienced by people living with HIV: Women . 460 Table 13.8.2 Disclosure, shame, and stigma experienced by people living with HIV: Men . 461 Table 13.9 Male circumcision . 462 Table 13.10 Self-reported prevalence of sexually transmitted infections (STIs) and STI symptoms . 464 Table 13.11.1 Knowledge about HIV prevention among young people: Women . 466 Table 13.11.2 Knowledge about HIV prevention among young people: Men . 468 Table 13.12 Age at first sexual intercourse among young people . 470 Table 13.13 Premarital sexual intercourse among young people . 470 Table 13.14.1 Multiple sexual partners and higher-risk sexual intercourse in the last 12 months among young people: Women . 471 Table 13.14.2 Multiple sexual partners and higher-risk sexual intercourse in the last 12 months among young people: Men . 472 Table 13.15 Recent HIV tests among young people . 472 Figure 13.1 Knowledge of medicines to treat HIV or prevent HIV transmission . 436 Figure 13.2 Discriminatory attitudes towards people living with HIV by education . 437 Figure 13.3 Sex and condom use with non-cohabiting partners . 438 Figure 13.4 HIV testing . 439 Figure 13.5 Trends in HIV testing . 439 Figure 13.6 Disclosure, shame, and stigma experienced by people living with HIV . 440 Figure 13.7 Trends in male circumcision . 441 Figure 13.8 Knowledge about HIV prevention among young people . 443 14 ADULT AND MATERNAL MORTALITY . 473 Table 14.1 Adult mortality rates . 480 Table 14.2 Adult mortality probabilities . 480 Table 14.3 Maternal mortality . 481 Table 14.4 Maternal mortality ratio . 481 Figure 14.1 Adult mortality rates by age . 476 Figure 14.2 Trends in pregnancy-related mortality ratios with confidence intervals . 479 15 WOMEN’S EMPOWERMENT . 483 Table 15.1 Employment and cash earnings of currently married women and men . 492 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 493 Table 15.2.2 Control over men’s cash earnings . 495 Table 15.3.1 House and land ownership: Women . 497 Table 15.3.2 House and land ownership: Men . 497 Table 15.4.1 House ownership and documentation of ownership: Women . 498 Table 15.4.2 House ownership and documentation of ownership: Men . 500 Table 15.5.1 Land ownership and documentation of ownership: Women . 502 Table 15.5.2 Land ownership and documentation of ownership: Men . 504 Table 15.6.1 Ownership and use of mobile phones and bank accounts: Women . 506 Table 15.6.2 Financial account possession and sharing by women 15–49 . 508 Table 15.6.3 Ownership and use of mobile phones and bank accounts: Men . 510 Table 15.7 Participation in decision making . 511 Table 15.8.1 Women’s participation in decision making by background characteristics . 512 Table 15.8.2 Men’s participation in decision making by background characteristics . 514 Tables, Figures, and Maps • xvii Table 15.9.1 Attitude toward wife beating: Women . 516 Table 15.9.2 Attitude toward wife beating: Men . 518 Table 15.10 Attitudes toward negotiating safer sexual relations with husband . 520 Table 15.11 Ability to negotiate sexual relations with husband . 522 Table 15.12 Women’s participation in decision making regarding sexual and reproductive health. 523 Figure 15.1 Employment by age . 484 Figure 15.2 Control over women’s earnings . 485 Figure 15.3 Ownership of assets . 486 Figure 15.4 Women’s participation in decision making. 488 Figure 15.5 Attitudes towards wife beating . 489 Figure 15.6 Women’s participation in decision making regarding sexual and reproductive health by education . 490 16 HOUSEHOLD WATER, SANITATION, AND HYGIENE . 525 Table 16.1 Household drinking water . 535 Table 16.2 Drinking water service ladder . 536 Table 16.3 Person collecting drinking water . 537 Table 16.4 Availability of sufficient drinking water . 538 Table 16.5 Treatment of household drinking water . 539 Table 16.6 Household sanitation facilities . 540 Table 16.7 Sanitation service ladder . 541 Table 16.8 Emptying and removal of waste from on-site sanitation facilities . 542 Table 16.9 Management of household excreta . 543 Table 16.10 Disposal of children’s stools . 544 Table 16.11 Menstrual hygiene . 546 Figure 16.1 Household population drinking water service by residence . 527 Figure 16.2 Person collecting drinking water . 528 Figure 16.3 Household population sanitation service by residence . 530 Figure 16.4 Appropriate management of household excreta . 532 Figure 16.5 Appropriate management of household excreta by wealth . 532 Map 16.1 At least basic drinking water service by region . 528 17 FEMALE GENITAL MUTILATION/CUTTING . 547 Table 17.1 Knowledge of female circumcision . 552 Table 17.2 Prevalence of female circumcision . 553 Table 17.3 Age at circumcision . 554 Table 17.4 Prevalence of circumcision and age at circumcision: Girls age 0–14 . 554 Table 17.5 Circumcision of girls age 0–14 by mother’s background characteristics . 555 Table 17.6 Provider of circumcision among circumcised girls age 0–14 and women age 15–49 . 555 Table 17.7 Opinions of women and men about whether circumcision is required by religion . 556 Table 17.8 Opinions of women and men about whether the practice of circumcision should continue . 557 Figure 17.1 Type of FGM/C . 549 Figure 17.2 Trends in FGM/C . 549 Figure 17.3 FGM/C by age . 549 Figure 17.4 Age at circumcision . 550 Map 17.1 FGM/C by region . 550 xviii • Tables, Figures, and Maps 18 DOMESTIC VIOLENCE . 559 Table 18.1 Experience of physical violence by any perpetrator . 572 Table 18.2 Persons committing physical violence . 573 Table 18.3 Experience of violence during pregnancy . 574 Table 18.4 Experience of sexual violence by any perpetrator . 576 Table 18.5 Persons committing sexual violence . 577 Table 18.6 Experience of sexual violence by any non-intimate partner . 578 Table 18.7 Age at first experience of sexual violence . 579 Table 18.8 Experience of different forms of violence . 579 Table 18.9 Forms of controlling behaviours and intimate partner violence . 580 Table 18.11 Intimate partner violence by background characteristics . 582 Table 18.12 Intimate partner violence by husband’s/intimate partner’s characteristics and women’s empowerment indicators . 584 Table 18.13 Violence by any husband or intimate partner in the last 12 months . 585 Table 18.14 Injuries to women due to intimate partner violence . 586 Table 18.15 Violence by women against their husband/intimate partner by women’s background characteristics . 587 Table 18.16 Violence by women against their husband/intimate partner by husband’s/ intimate partner’s characteristics and women’s empowerment indicators . 589 Table 18.17 Help seeking to stop violence . 590 Table 18.18 Sources for help to stop the violence . 591 Figure 18.1 Women’s experience of violence by marital status . 562 Figure 18.2 Forms of controlling behaviours . 565 Figure 18.3 Forms of intimate partner violence . 566 Figure 18.4 Intimate partner violence by husband’s/intimate partner’s alcohol consumption . 568 Map 18.1 Intimate partner violence by region . 567 REFERENCES . 593 Appendix A SAMPLE DESIGN . 599 Table A.1 Distribution of residential households by region and according to type of residence . 601 Table A.2 Distribution of EAs and their average size in number of households by region and according to type of residence . 602 Table A.3 Sample allocation of EAs and households by region and according to type of residence . 603 Table A.4 Sample allocation of expected numbers of female and male interviews by region and by type of residence . 604 Table A.5 Sample implementation: Women . 606 Table A.6 Sample implementation: Men . 607 Appendix B ESTIMATES OF SAMPLING ERRORS . 609 Table B.1 List of selected variables for sampling errors, Tanzania DHS-MIS 2022 . 611 Table B.2 Sampling errors: Total sample, Tanzania DHS-MIS 2022 . 614 Table B.3 Sampling errors: Urban sample, Tanzania DHS-MIS 2022 . 617 Table B.4 Sampling errors: Rural sample, Tanzania DHS-MIS 2022 . 619 Table B.5 Sampling errors: Mainland sample, Tanzania DHS-MIS 2022 . 621 Table B.6 Sampling errors: Mainland urban sample, Tanzania DHS-MIS 2022 . 623 Table B.7 Sampling errors: Mainland rural sample, Tanzania DHS-MIS 2022 . 625 Table B.8 Sampling errors: Zanzibar sample, Tanzania DHS-MIS 2022 . 627 Tables, Figures, and Maps • xix Table B.9 Sampling errors: Unguja (Zanzibar Island) sample, Tanzania DHS-MIS 2022 . 629 Table B.10 Sampling errors: Pemba (Pemba Island) sample, Tanzania DHS-MIS 2022 . 631 Table B.11 Sampling errors: Western sample, Tanzania DHS-MIS 2022 . 633 Table B.12 Sampling errors: Northern sample, Tanzania DHS-MIS 2022 . 635 Table B.13 Sampling errors: Central sample, Tanzania DHS-MIS 2022 . 637 Table B.14 Sampling errors: Southern Highlands sample, Tanzania DHS-MIS 2022 . 639 Table B.15 Sampling errors: Southern sample, Tanzania DHS-MIS 2022 . 641 Table B.16 Sampling errors: South West Highlands sample, Tanzania DHS-MIS 2022 . 643 Table B.17 Sampling errors: Lake sample, Tanzania DHS-MIS 2022 . 645 Table B.18 Sampling errors: Eastern sample, Tanzania DHS-MIS 2022 . 647 Table B.19 Sampling errors for the ECDI2030 according to background characteristics, Tanzania DHS-MIS 2022 . 649 Table B.20 Sampling errors for adult and maternal mortality rates, Tanzania DHS-MIS 2022 . 650 Appendix C DATA QUALITY TABLES . 651 Table C.1 Household age distribution . 651 Table C.2.1 Age distribution of eligible and interviewed women . 652 Table C.2.2 Age distribution of eligible and interviewed men . 653 Table C.3 Age displacement at ages 14/15 . 654 Table C.4 Age displacement at ages 49/50 . 656 Table C.5 Pregnancy outcomes by years preceding the survey . 658 Table C.6 Completeness of reporting . 659 Table C.6.1 Reporting of age at death in days . 659 Table C.6.2 Reporting of age at death in months . 660 Table C.7 Standardisation exercise results from anthropometry training . 660 Table C.8 Height and weight data completeness and quality for children . 661 Table C.9 Height measurements from random subsample of measured children . 664 Table C.10 Interference in height and weight measurements of children . 665 Table C.11 Interference in height and weight measurements of women and men . 667 Table C.12 Heaping in anthropometric measurements for children (digit preference) . 668 Table C.13.1 Coverage of testing for anaemia in children: Capillary blood sample . 669 Table C.13.2 Coverage of testing for anaemia in children: Venous blood sample . 670 Table C.14.1 Coverage of testing for anaemia in women: Capillary blood sample . 671 Table C.14.2 Coverage of testing for anaemia in women: Venous blood sample . 672 Table C.15 Comparison of haemoglobin concentration and anaemia by type of blood sample: Children and women . 673 Table C.16 Coverage of urine testing for iodine among women . 674 Table C.17 Observation of mosquito nets . 675 Table C.18 Number of enumeration areas completed by month and region . 676 Table C.19 School attendance by single year of age . 677 Table C.20 Vaccination cards photographed . 678 Table C.21 Completeness of information on siblings . 679 Table C.22 Sibship size and sex ratio of siblings . 679 Table C.23 Pregnancy-related mortality trends . 679 Figure C.1 Population pyramid . 652 Foreword  xxi FOREWORD he 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS- MIS) is the seventh in a series of DHS surveys in Tanzania conducted through The Demographic and Health Surveys (DHS) Program, a global programme coordinated by ICF. The 2022 TDHS-MIS was implemented by the National Bureau of Statistics (NBS) and the Office of the Chief Government Statistician Zanzibar (OCGS) in collaboration with the Ministries of Health of the United Republic of Tanzania and Zanzibar. The Tanzania Food and Nutrition Centre (TFNC) collaborated on several aspects of the survey, especially biomarkers. ICF provided technical assistance in the implementation of the survey. Funding for the 2022 TDHS-MIS was provided by the Government of the United Republic of Tanzania; ICF; the United Nations Children’s Fund (UNICEF); the United States Agency for International Development (USAID); the President’s Malaria Initiative (PMI); the Canadian International Development Agency (CIDA); the Centers for Disease Control and Prevention (CDC); the Foreign, Commonwealth and Development Office (FCDO); the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); the Hilton Foundation; Irish AID; Nutrition International; the Royal Norwegian Embassy and Legal and Human Rights Centre (LHRC); the World Food Programme (WFP) and Bill & Melinda Gates Foundation. The main purpose of the 2022 TDHS-MIS was to provide current data needed to monitor and evaluate population, health, and nutrition programmes on a regular basis. It is a useful source of information for assessing national, regional, and global commitments such as Tanzania Development Vision 2025, the Third National Five-Year Development Plan III (FYDP III 2021/22–2025/26), East Africa Community Vision 2050 (EAC 2050), Africa Development Agenda 2063 (ADA 2063), and the Global Agenda 2030 on Sustainable Development Goals (2030 SDGs). The 2022 TDHS-MIS also helps to assess the progress made in improving the living standards of the people in Tanzania. First and foremost, deepest and heartfelt appreciation is directed to Her Excellency Dr. Samia Suluhu Hassan, the President of the United Republic of Tanzania, and His Excellency Dr. Hussein Ali Mwinyi, the President of the Revolution Government of Zanzibar, for their dedication in ensuring the social welfare of their citizens. The survey results are expected to play a key role in informing the development, implementation, monitoring, evaluation, and review of their agendas, which touch upon all of the topics covered in the survey. The findings from the survey show significant improvements in some indicators and declines in others. This report is therefore an important tool to address health concerns and inform policymakers and other stakeholders of priority areas for intervention, future planning, and resource allocation. T xxii  Foreword We are pleased to present this report to the line Ministries and to Development Partners, Non- Governmental organizations, policymakers, program implementers, and researchers. We believe that the findings can be used to make informed decisions and help guide policy formulation, development, implementation, and review. Also, those in academia are encouraged to undertake further analytical work to provide a deeper understanding of key topical areas that touch the lives of Tanzanians. We hope that this report will provide useful information to address intervention concerns and future planning in the health sector. Ummy A. Mwalimu Minister for Health United Republic of Tanzania Nassor Ahmed Mazrui Minister for Health Revolutionary Government of Zanzibar Acknowledgements  xxiii ACKNOWLEDGEMENTS he 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS- MIS) report has been prepared with the participation of organizations and individuals. We would like to express our gratitude to all of them. First, we sincerely acknowledge all local leaders and all survey respondents who provided their valuable time participating during survey interviews. The response rate was very high (99% household, 97% women and 91% men). We also present our sincere thanks to the President’s Office, Regional Administration and Local Government (PO-RALG) Tanzania Mainland and President’s Office, Regional Administration and Local Government and Special Department (PO-RALGSP) Zanzibar for its assistance and contributions to the smooth implementation of the survey. We would like to express our appreciation to the Ministry of Health from the United Republic of Tanzania and that of Revolutionary Government of Zanzibar for playing a key role in providing policy guidance in setting the survey objectives and relevant data needs. The strategic guidance of the National Bureau of Statistics (NBS), Office of the Chief Government Statistician Zanzibar (OCGS) and Tanzania Food and Nutrition Centre (TFNC) is highly appreciated. We express our gratitude to our development partners for their vital financial support. Contributions from the United States Agency for International Development (USAID); the Canadian International Development Agency (CIDA); the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); ICF; the United Nations Children’s Fund (UNICEF); the President’s Malaria Initiative (PMI); the Centers for Disease Control and Prevention (CDC); the Foreign Commonwealth and Development Office (FCDO); the Hilton Foundation; Irish AID; Nutrition International; the Royal Norwegian Embassy, the Legal and Human Rights Centre (LHRC); the World Food Programme (WFP) and the Bill & Melinda Gates Foundation were of immense importance to the effective accomplishment of the survey. We express our profound gratitude to the team from ICF, in particular. Livia Montana, Gulnara Semenov, Ruilin Ren, Michelle Winner, Hanna Useem, Ms. Lady Ortiz Parra, and Joy Fishel. Their technical assistance and mentorship during the implementation of the survey are highly appreciated. We are grateful for the technical guidance of the Technical Committee (TC) members from the Ministries of Health of the United Republic of Tanzania (URT) and Revolutionary Government of Zanzibar (RGZ), the Tanzania Food and Nutrition Centre (TFNC), the National Malaria Control Program (NMCP), the Eastern Africa Statistical Training Centre (EASTC), the Sokoine University of Agriculture (SUA), and the University of Dodoma (UDOM). The TC was managed by the Secretariat from NBS and OCGS and coordinated by survey directors, managers, and desk officers on our behalf. We congratulate the Quality Control Team, NBS regional staff, IT, team leaders, field supervisors, CAPI supervisors, cartographers, and listers and the nurses who worked tirelessly as interviewers. Likewise, we thank the biomarker technicians for their valuable efforts and the drivers who were able to overcome fatigue and fieldwork transport challenges. We acknowledge the contributions made by chapter authors and reviewers from the Muhimbili University of Health and Allied Sciences, the Kilimanjaro Christian Medical Centre (KCMC), the University of Dar es Salaam (UDSM), UDOM, and SUA. Also, we thank the retired statisticians and demographers from NBS, OCGS, the ministries responsible for health and gender in Mainland and Zanzibar, TFNC, the T xxiv  Acknowledgements Tanzania Commission for AIDS (TACAIDS), UNICEF Tanzania, and the Tanzania Association of Persons with Disabilities. Lastly, we wish to recognize the valuable contributions made by the staff of TFNC Laboratories in Mikocheni, Dar es Salaam, in conducting laboratory microscopic analysis of malaria, urinary iodine, and salt iodine tests and other biomarker lab tests for the survey. Dr. Albina Chuwa Statistician General National Bureau of Statistics Dodoma Salum Kassim Ali Chief Government Statistician Office of the Chief Government Statistician Zanzibar Acronyms and Abbreviations • xxv ACRONYMS AND ABBREVIATIONS ACT artemisinin-based combination therapy ADDO accredited drug dispensing outlet AIDS acquired immunodeficiency syndrome AMO assistant medical officer ANC antenatal care ARI acute respiratory infection ART antiretroviral therapy ASFR age-specific fertility rate BCG bacillus Calmette-Guérin BMI body mass index CAPI computer-assisted personal interviewing CBO community-based organisation CDC Centers for Disease Control and Prevention CHV community health volunteer CHW community health worker CIDA Canadian International Development Agency COVID coronavirus disease CSO community service organisation DBP diastolic blood pressure DHS Demographic and Health Survey DPT diphtheria, pertussis (whooping cough), and tetanus vaccine DPT-HepB-Hib pentavalent or diphtheria, pertussis, tetanus, hepatitis B, and Haemophilus influenzae type b vaccine DVD digital video disc EA enumeration area ECDI2030 Early Childhood Development Index 2030 EmONC emergency obstetric newborn care FGM/C female genital mutilation/cutting GAR gross attendance ratio GFR general fertility rate GPI gender parity index GPS Global Positioning System HIV human immunodeficiency virus ICCPR International Covenant on Civil and Political Rights IPV inactivated polio vaccine ITN insecticide-treated net IUD intrauterine device JMP Joint Monitoring Programme for Water Supply, Sanitation, and Hygiene xxvi • Acronyms and Abbreviations LAM lactational amenorrhoea method LLIN long-lasting insecticidal net LPG liquefied petroleum gas MCH maternal and child health MDG Millennium Development Goal MDSR Maternal Death Surveillance and Response MIS Malaria Indicator Survey MMAM Primary Health Care Service Development Programme (for its name in Kiswahili, Mpango wa maendeleo wa afya ya msingi) mmHg millimetres of mercury MMR maternal mortality ratio MoH Ministry of Health MoHCDGEC Ministry of Health, Community Development, Gender, Elderly and Children MR measles-rubella vaccine MTCT mother-to-child transmission NAR net attendance ratio NBS National Bureau of Statistics NGO nongovernmental organisation NHIF National Health Insurance Fund NMCP National Malaria Control Programme NPA-VAWC National Plan of Action to End Violence against Women and Children NSSF National Social Security Fund OCGS Office of the Chief Government Statistician Zanzibar OPV oral polio vaccine ORS oral rehydration salts ORT oral rehydration therapy PCV pneumococcal conjugate vaccine PHNB public health nurse B PHSDP Primary Health Service Development Programme PMI U.S. President’s Malaria Initiative PNN postneonatal mortality PrEP pre-exposure prophylaxis PRMR pregnancy-related mortality ratio RDT rapid diagnostic test RHF recommended homemade fluids RMNCAH reproductive, maternal, newborn, child, and adolescent health RV rotavirus vaccine SBC social behaviour change SBP systolic blood pressure SDG Sustainable Development Goal SDM standard days method SHIB Social Health Insurance Benefit STI sexually transmitted infection Acronyms and Abbreviations • xxvii TAR total induced abortion rate TASAF Tanzania Social Action Fund TDHS Tanzania Demographic and Health Survey TDHS-MIS Tanzania Demographic and Health Survey and Malaria Indicator Survey TFNC Tanzania Food and Nutrition Centre TFR total fertility rate THMIS Tanzania HIV/AIDS and Malaria Indicator Survey TIKA Tiba kwa Kadi TMIS Tanzania Malaria Indicator Survey TRCHS Tanzania Reproductive and Child Health Survey TZS Tanzania shilling UNICEF United Nations Children’s Fund USAID United States Agency for International Development VCT voluntary counselling and testing VIA visual inspection with acetic acid VIP ventilated improved pit WG Washington Group on Disability Statistics WHO World Health Organization Reading and Understanding Tables from the 2022 TDHS-MIS • xxix READING AND UNDERSTANDING TABLES FROM THE 2022 TANZANIA DEMOGRAPHIC AND HEALTH SURVEY AND MALARIA INDICATOR SURVEY (TDHS-MIS) he 2022 Tanzania DHS-MIS final report is based on approximately 303 tables of data. For quick reference, they are located at the end of each chapter and can be accessed through links in the pertinent text (electronic version). Additionally, this more reader-friendly version features about 126 figures that clearly highlight trends, subnational patterns, and background characteristics. Large, colourful maps display breakdowns for region in Tanzania. The text has been simplified to highlight key points in bullets and to clearly identify indicator definitions in boxes. While the text and figures featured in each chapter highlight some of the most important findings from the tables, not every finding can be discussed or displayed graphically. For this reason, TDHS-MIS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organization of TDHS-MIS tables, the presentation of background characteristics, and a brief summary of sampling and understanding denominators. In addition, this section provides some exercises for users as they practice their new skills in interpreting TDHS-MIS tables. T xxx • Reading and Understanding Tables from the 2022 TDHS-MIS Example 1: Exposure to mass media: Women A Question Asked of All Survey Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, according to background characteristics, Tanzania DHS-MIS 2022 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15–19 6.5 30.4 28.5 2.8 54.8 3,083 20–24 5.9 31.8 34.5 3.3 52.4 2,727 25–29 6.6 33.3 35.3 3.0 50.1 2,533 30–34 5.8 30.3 32.9 3.1 54.5 2,076 35–39 6.6 26.9 31.1 3.1 56.8 1,884 40–44 7.3 27.2 31.3 3.4 56.3 1,588 45–49 5.8 24.0 28.7 2.9 59.4 1,363 Residence Urban 8.8 52.3 42.3 5.1 34.1 5,446 Rural 5.0 17.3 26.2 1.9 65.6 9,808 Mainland/Zanzibar Mainland 6.4 29.2 31.6 3.1 55.0 14,737 Urban 9.0 52.2 42.2 5.3 34.3 5,268 Rural 5.0 16.4 25.6 1.9 66.6 9,468 Zanzibar 4.5 46.6 42.1 1.9 35.4 517 Unguja 5.2 51.8 48.7 2.4 28.6 381 Pemba 2.5 31.8 23.8 0.4 54.5 137 Zone Western 4.7 14.7 20.5 2.0 72.3 1,268 Northern 6.1 30.3 31.5 3.2 55.7 1,733 Central 5.5 28.6 26.3 3.4 61.9 1,573 Southern Highlands 13.8 31.6 44.3 8.6 45.5 924 Southern 1.8 15.8 11.4 0.8 78.0 805 South West Highlands 12.4 28.0 38.3 5.0 49.9 1,322 Lake 5.9 26.8 34.9 2.3 52.8 4,454 Eastern 4.6 43.8 32.8 2.5 45.0 2,657 Zanzibar 4.5 46.6 42.1 1.9 35.4 517 Region Dodoma 6.0 36.8 30.7 4.1 55.3 772 Arusha 5.5 35.9 36.6 2.8 49.7 558 Kilimanjaro 15.2 45.6 48.2 8.3 36.2 417 Tanga 1.4 17.7 18.5 0.7 71.0 758 Morogoro 3.9 19.9 17.3 2.1 72.4 727 Pwani 1.7 31.7 26.2 0.2 56.3 539 Dar es Salaam 6.1 61.1 43.4 3.7 26.3 1,391 Lindi 0.5 12.1 4.5 0.0 84.6 336 Mtwara 2.8 18.5 16.3 1.3 73.3 468 Ruvuma 11.4 25.2 32.5 5.4 53.7 382 Iringa 21.8 43.2 65.4 16.9 28.7 326 Mbeya 11.7 38.2 52.1 4.6 33.6 489 Singida 3.7 26.6 25.5 2.6 64.1 384 Tabora 2.8 16.0 20.7 1.5 71.6 723 Rukwa 21.0 23.1 29.3 10.1 61.2 317 Kigoma 7.2 12.8 20.3 2.6 73.2 545 Shinyanga 9.5 21.9 38.8 5.4 55.0 533 Kagera 3.4 23.8 25.1 1.4 62.9 769 Mwanza 9.7 36.2 43.7 3.3 38.8 1,245 Mara 1.6 25.0 37.8 0.8 53.5 749 Manyara 6.3 15.1 18.9 2.6 72.0 417 Njombe 5.7 25.2 33.4 1.5 56.6 216 Katavi 8.7 23.2 21.8 4.4 65.8 197 Simiyu 6.0 14.1 33.7 2.9 61.8 374 Geita 4.1 25.7 25.4 0.8 58.3 782 Songwe 7.3 20.2 36.4 1.0 53.8 319 Kaskazini Unguja 8.1 27.1 44.4 3.0 47.3 70 Kusini Unguja 4.0 42.6 52.3 1.8 31.1 38 Mjini Magharibi 4.6 59.5 49.3 2.3 23.4 272 Kaskazini Pemba 2.8 28.2 17.8 0.6 60.5 64 Kusini Pemba 2.3 35.0 29.0 0.3 49.3 73 Education No education 0.3 9.3 16.7 0.0 79.0 2,450 Primary incomplete 3.1 17.3 27.7 0.8 63.6 1,380 Primary complete 6.4 26.5 31.0 2.7 56.6 6,744 Secondary+ 10.3 49.0 42.5 5.9 35.5 4,681 Wealth quintile Lowest 2.1 2.5 12.1 0.5 86.1 2,466 Second 4.3 5.5 19.6 1.4 77.2 2,578 Middle 5.3 12.4 27.3 1.3 65.9 2,880 Fourth 7.4 34.5 39.6 3.2 44.1 3,359 Highest 10.1 71.3 49.0 6.9 20.2 3,971 Total 6.3 29.8 31.9 3.1 54.4 15,254 1 2 3 4 5 Reading and Understanding Tables from the 2022 TDHS-MIS • xxxi Step 1: Read the title and subtitle, highlighted in orange in the table above. They tell you the topic and the specific population group being described. In this case, the table is about women age 15–49 and their exposure to different types of media. All eligible female respondents age 15–49 were asked these questions. Step 2: Scan the column headings—highlighted in green in Example 1. They describe how the information is categorised. In this table, the first three columns of data show different types of media that women access at least once a week. The fourth column shows women who access all three types of media, while the fifth column shows women who do not access any of the three types of media on a weekly basis. The last column lists the number of women age 15–49 interviewed in the survey. Step 3: Scan the row headings—the first vertical column highlighted in blue in Example 1. These show the different ways the data are divided into categories based on population characteristics. In this case, the table presents women’s exposure to media by age, urban-rural residence, Mainland/Zanzibar residence, zone, region, level of education, and wealth quintile. Most of the tables in the TDHS-MIS report will be divided into these same categories. Step 4: Look at the row at the bottom of the table highlighted in pink. These percentages represent the totals of all women age 15–49 and their weekly access to different types of media. In this case, 6.3% of women age 15–49 read a newspaper at least once a week, 29.8% watch television at least weekly, and 31.9% listen to the radio on a weekly basis.* Step 5: To find out what percentage of women in rural areas listen to the radio at least once a week, draw two imaginary lines, as shown on the table. This shows that 26.2% of women in rural areas listen to the radio at least once a week. By looking at patterns by background characteristics, we can see how exposure to mass media varies across Tanzania. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help programme planners and policymakers determine how to most effectively reach their target populations. *For the purpose of this document data are presented exactly as they appear in the table, including decimal places. However, the text in the remainder of this report rounds data to the nearest whole percentage point. Practice: Use the table in Example 1 to answer the following questions: a) What percentage of women in Tanzania do not access any of the three media at least once a week? b) Which age group of women is most likely to watch television at least once a week? c) What percentage of women read a newspaper at least once a week by educational level? d) Which age group is the least exposed to newspapers at least once a week? e) What are the lowest and highest percentages (range) of women who access none of the three media once a week by educational level? f) Is there a clear pattern in women who access all three media at least once a week by wealth quintile? Answers: a) 54.4%. b) Women age 25–29 are most likely to watch television at least once a week. c) 10.3% of women with a secondary education or higher read a newspaper a least once a week, as compared with 6.4% of women with a complete primary education, 3.1% with an incomplete primary education, and 0.3% with no education. d) Women age 30–34 and 45–49 are least exposed to newspapers at least once a week, at 5.8%. e) The percentage of women who access none of the three media at least once a week ranges from 35.5% among those with a secondary education or higher to 79.0% among those with no education. f) Yes, weekly exposure to all three media increases with increasing wealth, from 0.5% among women in the lowest wealth quintile to 6.9% among women in the highest quintile. xxxii • Reading and Understanding Tables from the 2022 TDHS-MIS Example 2: Children with symptoms of ARI and care seeking for symptoms of ARI A Question Asked of a Subgroup of Survey Respondents Table 10.6 Children with symptoms of ARI and care seeking for symptoms of ARI Among children under age 5, percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks preceding the survey, and among children with symptoms of ARI in the 2 weeks preceding the survey, percentage for whom advice or treatment was sought, according to background characteristics, Tanzania DHS- MIS 2022 Among children under age 5: Among children under age 5 with symptoms of ARI: Background characteristic Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought2 Percentage for whom advice or treatment was sought the same or next day2 Number of children Age in months <6 1.0 1,115 * * 11 6–11 2.9 1,073 (95.1) (60.3) 32 12–23 1.8 2,180 (80.4) (51.2) 39 24–35 1.5 2,009 (68.5) (48.9) 31 36–47 1.1 2,023 * * 21 48–59 1.3 2,097 (83.4) (53.5) 27 Sex Male 1.8 5,349 81.8 49.4 94 Female 1.3 5,147 75.8 43.2 68 Residence Urban 2.3 2,853 82.7 54.9 65 Rural 1.3 7,643 77.0 41.3 97 Mainland/Zanzibar Mainland 1.5 10,181 78.7 46.8 157 Urban 2.3 2,757 82.5 55.4 64 Rural 1.2 7,424 76.0 40.9 92 Zanzibar 1.7 315 (97.8) (45.1) 5 Unguja 2.1 216 (97.4) (42.3) 5 Pemba 0.7 100 * * 1 Zone Western 0.1 1,085 * * 1 Northern 2.4 1,135 (81.6) (51.0) 28 Central 0.8 1,068 * * 9 Southern Highlands 1.4 537 * * 8 Southern 0.4 387 * * 1 South West Highlands 1.2 990 * * 12 Lake 1.8 3,617 (87.7) (51.5) 65 Eastern 2.5 1,363 * * 34 Zanzibar 1.7 315 (97.8) (45.1) 5 Region Dodoma 0.6 436 * * 3 Arusha 4.3 355 * * 15 Kilimanjaro 2.4 243 * * 6 Tanga 1.2 537 * * 7 Morogoro 0.6 455 * * 3 Pwani 1.2 320 * * 4 Dar es Salaam 4.6 588 * * 27 Lindi 0.8 171 * * 1 Mtwara 0.0 215 * * 0 Ruvuma 1.5 237 * * 3 Iringa 0.9 181 * * 2 Mbeya 1.4 287 * * 4 Singida 0.0 282 * * 0 Tabora 0.0 652 * * 0 Rukwa 2.0 277 * * 5 Kigoma 0.3 434 * * 1 Shinyanga 1.0 415 * * 4 Kagera 5.1 623 * * 32 Mwanza 1.9 867 * * 16 Mara 0.0 621 * * 0 Manyara 1.7 350 * * 6 Njombe 2.2 118 * * 3 Katavi 1.1 162 * * 2 Simiyu 0.5 373 * * 2 Geita 1.4 718 * * 10 Songwe 0.3 264 * * 1 Kaskazini Unguja 2.4 44 * * 1 Kusini Unguja 6.8 25 * * 2 Mjini Magharibi 1.3 147 * * 2 Kaskazini Pemba 0.5 46 * * 0 Kusini Pemba 0.9 54 * * 0 a b 1 4 2 Reading and Understanding Tables from the 2022 TDHS-MIS • xxxiii Mother's education No education 1.0 2,249 * * 23 Primary incomplete 2.0 992 * * 19 Primary complete 1.5 4,958 78.8 48.4 73 Secondary+ 2.1 2,297 81.4 50.5 47 Wealth quintile Lowest 1.0 2,409 * * 25 Second 1.4 2,088 (79.8) (37.8) 30 Middle 1.3 2,001 (75.9) (34.2) 27 Fourth 2.1 2,110 (90.7) (60.4) 43 Highest 1.9 1,889 (75.4) (50.5) 37 Total 1.5 10,497 79.3 46.8 162 Note: Figures in parentheses are based on 25–49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI include short, rapid breathing that is chest-related and/or difficult breathing that is chest- related. 2 Includes advice or treatment from the following sources: public sector, religious/voluntary sector, private medical sector, pharmacy, accredited drug dispensing outlet (ADDO), and nongovernmental organisation (NGO)/voluntary testing and counselling (VCT) centre. Excludes advice or treatment from a shop/kiosk/market/traditional practitioner. Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under age 5 (a) and children under age 5 with symptoms of acute respiratory infection (ARI) in the 2 weeks before the survey (b). Step 2: Identify the two panels. First, identify the columns that refer to all children under age 5 (a), and then isolate the columns that refer only to children under age 5 with symptoms of ARI in the 2 weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under age 5 had symptoms of ARI in the 2 weeks before the survey? It is 1.5%. Now look at the second panel. How many children under age 5 had symptoms of ARI in the 2 weeks before the survey? It’s 162 children, or 1.5% of the 10,497 children (with rounding). The second panel is a subset of the first panel. Step 4: Only 1.5% of children under age 5 had symptoms of ARI in the 2 weeks before the survey. Once these children are further divided into the background characteristic categories, there may be too few cases for the percentages to be reliable. ▪ What percentage of children age 6–11 months with symptoms of ARI had advice or treatment sought the same or next day? 60.3%. This percentage is in parentheses because there are between 25 and 49 children (unweighted) in this category. Readers should use this number with caution—it may not be reliable. (For more information on weighted and unweighted numbers, see Example 3.) ▪ What percentage of children under age 5 with symptoms of ARI from Dodoma had advice or treatment sought the same or next day? There is no number in this cell—only an asterisk. This is because fewer than 25 children under age 5 from Dodoma had advice or treatment sought the same or next day. Results for this group are not reported. The subgroup is too small, and therefore the data are not reliable. Note: When parentheses or asterisks are used in a table, the explanation will be noted under the table. If there are no parentheses or asterisks in a table, you can proceed with confidence that enough cases were included in all categories that the data are reliable. 3 xxxiv • Reading and Understanding Tables from the 2022 TDHS-MIS Example 3: Understanding Sampling Weights in TDHS-MIS Tables A sample is a group of people who have been selected for a survey. In the TDHS-MIS, the sample is designed to represent the national population age 15–49. In addition to national data, most countries want to collect and report data on smaller geographical or administrative areas. However, doing so requires a large enough sample size in each area. For the 2022 TDHS-MIS, the survey sample is representative at the national and regional levels and for urban and rural areas. To generate statistics that are representative of the country as a whole and the 31 regions, the number of women surveyed in each region should contribute to the size of the total (national) sample in proportion to size of the region. However, if some regions have small populations, then a sample allocated in proportion to each region’s population may not include sufficient women from each region for analysis. To solve this problem, regions with small populations are oversampled. For example, let’s say that you have enough money to interview 15,254 women and want to produce results that are representative of Tanzania as a whole and its regions (as in Table 3.1). However, the total population of Tanzania is not evenly distributed among the regions: some regions, such as Dar es Salaam, are heavily populated while others, such as Lindi, are not. Thus, Lindi must be oversampled. A sampling statistician determines how many women should be interviewed in each region in order to get reliable statistics. The blue column (1) in the table at right shows the actual number of women interviewed in each region. Within the regions, the number of women interviewed ranges from 362 in Lindi to 835 in Dar es Salaam. The number of interviews is sufficient to get reliable results in each region. With this distribution of interviews, some regions are overrepresented and some regions are underrepresented. For example, the population in Dar es Salaam is about 9.1% of the population in Tanzania, while Lindi’s population contributes only 2.2% of the country’s population. But as the blue column shows, the number of women interviewed in Dar es Salaam accounts for only 5.5% of the total sample of women interviewed (835/15,254), and the number of women interviewed in Lindi accounts for 2.4% of the total sample of women interviewed (362/15,254). This unweighted distribution of women does not accurately represent the population. In order to get statistics that are representative of Tanzania, the distribution of the women in the sample needs to be weighted (or mathematically adjusted) such that it resembles the true distribution in the country. Women from a small region, like Lindi, should contribute only a small amount to the national total. Women from a large region, like Dar es Salaam, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” that is used to adjust the number of women from each Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15–49 by selected background characteristics, Tanzania DHS-MIS 2022 Women Background characteristic Weighted percent Weighted number Unweighted number Mainland/Zanzibar Mainland 96.6 14,737 12,686 Urban 34.5 5,268 4,576 Rural 62.1 9,468 8,110 Zanzibar 3.4 517 2,568 Unguja 2.5 381 1,566 Pemba 0.9 137 1,002 Region Dodoma 5.1 772 463 Arusha 3.7 558 545 Kilimanjaro 2.7 417 399 Tanga 5.0 758 517 Morogoro 4.8 727 538 Pwani 3.5 539 479 Dar es Salaam 9.1 1,391 835 Lindi 2.2 336 362 Mtwara 3.1 468 432 Ruvuma 2.5 382 456 Iringa 2.1 326 368 Mbeya 3.2 489 454 Singida 2.5 384 403 Tabora 4.7 723 626 Rukwa 2.1 317 406 Kigoma 3.6 545 501 Shinyanga 3.5 533 539 Kagera 5.0 769 526 Mwanza 8.2 1,245 592 Mara 4.9 749 510 Manyara 2.7 417 462 Njombe 1.4 216 385 Katavi 1.3 197 525 Simiyu 2.5 374 437 Geita 5.1 782 544 Songwe 2.1 319 382 Kaskazini Unguja 0.5 70 461 Kusini Unguja 0.3 38 426 Mjini Magharibi 1.8 272 679 Kaskazini Pemba 0.4 64 494 Kusini Pemba 0.5 73 508 Education No education 16.1 2,450 2,387 Primary incomplete 9.0 1,380 1,412 Primary complete 44.2 6,744 6,001 Secondary+ 30.7 4,681 5,454 Wealth quintile Lowest 16.2 2,466 2,271 Second 16.9 2,578 2,498 Middle 18.9 2,880 3,063 Fourth 22.0 3,359 3,378 Highest 26.0 3,971 4,044 Total 100.0 15,254 15,254 Note: Education categories refer to the highest level of education attended, whether or not that level was completed. 1 2 3 Reading and Understanding Tables from the 2022 TDHS-MIS • xxxv region so that each region’s contribution to the total is proportional to the actual population of the region. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at the regional level. The total national sample size of 15,254 women has not changed after weighting, but the distribution of the women in the regions has been changed to represent their contribution to the total population size. How do statisticians weight each category? They take into account the probability that a woman was selected in the sample. If you were to compare the green column (3) to the actual population distribution of Tanzania, you would see that women in each region are contributing to the total sample with the same weight that they contribute to the population of the country. The weighted number of women in the survey now accurately represents the proportion of women who live in Dar es Salaam and the proportion of women who live in Lindi. With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and regional levels. In general, only the weighted numbers are shown in each of the TDHS-MIS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of women interviewed. Sustainable Development Goals Indicators  xxxvii SUSTAINABLE DEVELOPMENT GOAL INDICATORS Sustainable Development Goal Indicators, 2022 Tanzania DHS-MIS Residence Total TDHS-MIS table number Indicator Urban Rural 1. No poverty 1.4.1 Proportion of population living in households with access to basic services a) Access to basic drinking water services 93.9 51.5 63.8 16.2 b) Access to basic sanitation services 57.8 53.5 54.7 16.7 d) Access to electricity1 73.9 15.2 32.2 2.3 e) Access to clean fuels and technologies2 18.4 1.8 6.6 2.4 Sex Male Female Total 2. Zero hunger 2.2.1 Prevalence of stunting among children under 5 years of age 33.3 26.6 30.0 11.1 2.2.2 Prevalence of malnutrition among children under 5 years of age 7.9 5.7 6.8 na a) Prevalence of wasting among children under 5 years of age 4.2 2.4 3.3 11.1 b) Prevalence of overweight among children under 5 years of age 3.7 3.3 3.5 11.1 2.2.3 Prevalence of anaemia in women age 15 to 49 years, by pregnancy status a) Prevalence of anaemia in nonpregnant women age 15 to 49 years na 40.3 na 11.17.1 b) Prevalence of anaemia in pregnant women age 15 to 49 years na 55.7 na 11.17.1 3. Good health and well-being 3.1.1 Maternal mortality ratio3 na na 104 14.4 3.1.2 Proportion of births attended by skilled health personnel na na 85.0 9.9 3.2.1 Under-5 mortality rate4 52 34 43 8.1 and 8.2 3.2.2 Neonatal mortality rate4 27 21 24 8.1 and 8.2 3.7.1 Proportion of women of reproductive age (aged 15–49 years) who have their need for family planning satisfied with modern methods na 53.9 na 7.14.2 3.7.2 Adolescent birth rates per 1,000 women a) Girls aged 10–14 years5 na 1 na 5.1 b) Women aged 15–19 years6 na 112.0 na 5.1 3.a.1 Age-standardised prevalence of current tobacco use among persons aged 15 years and older7 11.1 0.6 5.9a 3.13 3.b.1 Proportion of the target population covered by all vaccines included in their national programme a) Coverage of DPT containing vaccine (3rd dose)8 90.9 89.1 90.0 10.4 b) Coverage of measles containing vaccine (2nd dose)9 62.7 65.0 63.8 10.4 c) Coverage of pneumococcal conjugate vaccine (last dose in schedule)10 88.0 87.8 87.9 10.4 4. Quality education 4.2.1 Proportion of children aged 24–59 months who are developmentally on track in health, learning, and psychosocial well-being 44.1 50.8 47.4 10.13 4.2.2 Participation rate in organised learning (one year before the official primary entry age) 71.7 72.3 72.0 2.15 5. Gender equality 5.2.1 Proportion of ever-partnered women and girls aged 15 years and older subjected to physical, sexual, or psychological violence by a current or former intimate partner in the previous 12 months11,12 na 32.5 na 18.13 a) Physical violence na 23.9 na 18.13 b) Sexual violence na 8.9 na 18.13 c) Psychological violence na 22.2 na 18.13 5.2.2 Proportion of women and girls aged 15 years and older subjected to sexual violence by persons other than an intimate partner in the previous 12 months13 na 0.3 na 18.6 5.3.1 Proportion of women aged 20–24 years who were married or in a union before age 15 and before age 18 a) before age 15 na 5.2 na 4.4 b) before age 18 na 29.1 na 4.4 5.3.2 Proportion of girls and women aged 15–49 years who have undergone female genital mutilation/cutting na 8.2 na 17.2 5.6.1 Proportion of women aged 15–49 years who make their own informed decisions regarding sexual relations, contraceptive use, and reproductive health care14 na 49.6 na 15.12 5.b.1 Proportion of individuals who own a mobile telephone15 75.1 59.4 67.3a 15.6.1 and 15.6.3 Residence Urban Rural Total 6. Clean water and sanitation 6.1.1 Proportion of population using safely managed drinking water services a) Proportion with basic drinking water services 93.9 51.5 63.8 16.2 b) Proportion with water available when needed 67.7 77.7 74.8 16.4 6.2.1 Proportion of population using (a) safely managed sanitation services and (b) hand-washing facility with soap and water a) Proportion using basic sanitation service 57.8 53.5 54.7 16.7 b) Proportion in which excreta are safely disposed of in situ or treated off site 93.1 63.4 72.0 16.9 c) Proportion using open defecation 0.7 13.4 9.7 16.6 Continued… xxxviii  Sustainable Development Goals Indicators Continued Residence Urban Rural Total 7. Affordable clean energy 7.1.1 Proportion of population with access to electricity1 73.0 15.2 32.0 2.3 7.1.2 Proportion of population with primary reliance on clean fuels and technology2 18.4 1.8 6.6 2.4 Sex Male Female Total 8. Decent work and economic growth 8.10.2 Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service provider15 10.5 7.1 8.8a 15.6.1 and 15.6.2 16. Peace, justice, and strong institutions 16.2.3 Proportion of young women aged 18–29 years who experienced sexual violence by age 1816 na 4.9 na 18.7 16.9.1 Proportion of children under 5 years of age whose births have been registered with a civil authority 68.1 67.3 67.7 2.11 17. Partnerships for the goals 17.8.1 Proportion of individuals using the internet17 25.8 12.8 19.3a 3.5.1 and 3.5.2 na = not applicable 1 Persons living in households that report the primary source of lighting is electricity 2 Persons living in households that report no cooking, no space heating, or no lighting are not excluded from the numerator 3 Expressed in terms of maternal deaths per 100,000 live births in the 7-year period preceding the survey 4 Expressed in terms of deaths per 1,000 live births for the 5-year period preceding the survey 5 Equivalent to the age-specific fertility rate for girls age 10–14 for the 3-year period preceding the survey, expressed in terms of births per 1,000 girls age 10–14 6 Equivalent to the age-specific fertility rate for women age 15–19 for the 3-year period preceding the survey, expressed in terms of births per 1,000 women age 15–19 7 Data are not age-standardised and are available for women and men age 15–49 only. 8 The percentage of children age 12–23 months who received three doses of DPT-HepB-Hib 9 The percentage of children age 24–35 months who received two doses of measles and rubella (MR) 10 The percentage of children age 12–23 months who received three doses of pneumococcal conjugate vaccine 11 Data are available for women age 15–49 who have ever been in union only. 12 In the DHS, psychological violence is termed emotional violence. 13 Data are available for women age 15–49 only. 14 Data are available for currently married women only. 15 Data are available for women and men age 15–49 only. 16 Data are available for women only. 17 Data are available for women and men age 15–49 who have used the Internet in the last 12 months. a The total is calculated as the simple arithmetic mean of the percentages in the columns for males and females. xl  Map of Tanzania Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2022 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2022 TDHS- MIS) was implemented by the National Bureau of Statistics (NBS) and the Office of the Chief Government Statistician Zanzibar (OCGS) in collaboration with the Ministries of Health (MoH) in Tanzania Mainland and Zanzibar. The Tanzania Food and Nutrition Centre (TFNC) collaborated on several aspects of the survey, especially biomarkers. Data collection took place from February to July 2022. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organisations that facilitated the successful implementation of the survey through technical or financial support were the President’s Malaria Initiative (PMI); the Canadian International Development Agency (CIDA); the Centers for Disease Control and Prevention (CDC); the Foreign, Commonwealth and Development Office (FCDO); the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ); Hilton Foundation; Irish AID; Legal and Human Rights Centre (LHRC); Nutrition International; Royal Norwegian Embassy; United Nations Children’s Fund (UNICEF); and World Food Programme (WFP). The United Nations Children’s Fund (UNICEF) in Tanzania acted as a disbursing entity for most of the donors’ funds. 1.1 SURVEY OBJECTIVES The primary objective of the 2022 TDHS-MIS is to provide current and reliable information on population and health issues. Specifically, the 2022 TDHS-MIS collected information on marriage and sexual activity, fertility and fertility preferences, family planning, infant and child mortality, maternal health care, disability among the household population, child health, nutrition of children and women, malaria prevalence, knowledge, and communication, women’s empowerment, women’s experience of domestic violence, adult maternal mortality via sisterhood method, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections (STIs), female genital cutting, and early childhood development. Other information collected on health-related issues included smoking, blood pressure, anaemia, malaria, and iodine testing, height and weight, and micronutrients. The information collected through the 2022 TDHS-MIS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of Tanzania’s population. The 2022 TDHS-MIS also provides indicators to monitor and evaluate international, regional, and national programmes, such as the Global Agenda 2030 on Sustainable Development Goals (2030 SDGs), Tanzania Development Vision 2025, the Third National Five-Year Development Plan (FYDP III 2021/22–2025/26), East Africa Community Vision 2050 (EAC 2050), and Africa Development Agenda 2063 (ADA 2063). Tanzania has undertaken five population and housing censuses since its independence in 1961. The first census, conducted in 1967, reported a total population of 12.3 million. According to the 2012 census, the population had increased to 44.9 million (Table 1.1). The average population density of the country is still relatively low. However, 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 2012, it had increased to 51 persons per square kilometre. T 2 • Introduction and Survey Methodology Table 1.1 Selected demographic indicators from various sources, Tanzania 1967–2012 Indicator Census year 1967 1978 1988 2002 2012 Population (millions) 12.3 17.5 23.1 34.4 44.9 Intercensal growth rate (%) 2.6 3.2 2.8 2.9 2.7 Sex ratio 95.2 96.2 94.2 96.0 95.0 Crude birth rate 47 49 46 43 42 Total fertility 6.6 6.9 6.5 6.3 5.5 Crude death rate 24 19 15 14 9.3 Infant mortality 155 137 115 95 46.2 Percent urban 6.4 13.8 18.3 23.1 29.6 Density (population/km2) 14 20 26 39 51 Life expectancy (years) 42 44 50 51 61.8 Male 6,005,339 8,586,713 11,327,511 16,829,861 21,869,990 Female 6,308,130 8,925,897 11,846,825 17,613,742 23,058,933 Source: National Bureau of Statistics 1.2 SAMPLE DESIGN The sample design for the 2022 TDHS-MIS was carried out in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allows for estimation of indicators for each of the 31 regions—26 regions in Tanzania Mainland and 5 regions in Zanzibar. The sampling frame excluded institutional populations, such as persons in hospitals, hotels, barracks, camps, hostels, and prisons. The 2022 TDHS-MIS followed a stratified two-stage sample design. The first stage involved selection of sampling points (clusters) consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census (2012 PHC). The EAs were selected with a probability proportional to their size within each sampling stratum. A total of 629 clusters were selected. Among the 629 EAs, 211 were from urban areas and 418 were from rural areas. In the second stage, 26 households were selected systematically from each cluster, for a total anticipated sample size of 16,354 households for the 2022 TDHS-MIS. A household listing operation was carried out in all the selected EAs before the main survey. During the household listing operation, field staff visited each of the selected EAs to draw location maps and detailed sketch maps and to list all residential households found in each EA with addresses and the names of the heads of the households. The resulting list of households served as a sampling frame for the selection of households in the second stage. During the listing operation, field teams collected global positioning system (GPS) data—latitude, longitude, and altitude readings—to produce one GPS point per EA. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the Ministry of Health. Grouping of regions into zones allows for larger denominators and smaller sampling errors for indicators at the zonal level. The zones are as follows: Tanzania Mainland:  Western zone: Tabora, Kigoma  Northern zone: Kilimanjaro, Tanga, Arusha  Central zone: Dodoma, Singida, Manyara  Southern Highlands zone: Iringa, Njombe, Ruvuma  Southern zone: Lindi, Mtwara  Southwest Highlands zone: Mbeya, Rukwa, Katavi, Songwe  Lake zone: Kagera, Mwanza, Geita, Mara, Simiyu, Shinyanga  Eastern zone: Dar es Salaam, Pwani, Morogoro Introduction and Survey Methodology • 3 Zanzibar:  Zanzibar zone: Kaskazini Unguja, Kusini Unguja, Mjini Magharibi, Kaskazini Pemba, Kusini Pemba All women age 15–49 who were either usual residents or visitors in the household on the night before the survey interview were included in the 2022 TDHS-MIS and were eligible to be interviewed. In a subsample of half of all households selected for the survey, all men age 15–49 were eligible to be interviewed if they were either usual residents or visitors in the household on the night before the survey interview. In this subsample, children age 0–59 months, women age 15–49, and men age 15–49 were eligible for height and weight measurement. Children age 6–59 months were also eligible for anaemia and malaria testing using rapid tests. Women were eligible for anaemia testing and were asked to provide a urine sample for laboratory testing to detect the presence of iodine. In this subsample of half of households, anaemia and malaria testing were conducted using capillary blood. A subsample of approximately 20% of all households was selected for the micronutrient component. Within those households, all interviewed women age 15–49 and children age 6–59 months were eligible for venous blood collection. In 40% of the households selected for micronutrient testing, a dose of vitamin A was administered, and an additional blood sample was collected approximately 4 hours later for relative dose response testing. Questions on food fortification were asked, and samples of salt, wheat flour, maize flour, and cooking oil were collected from the household. Blood specimens and food samples were collected, processed, and sent to TFNC for storage and analysis. Drops of the venous blood collected from women and children in the field were tested on-the-spot for anaemia and malaria. Haematocrit was measured in venous blood collected from women, and all blood samples were processed on the same day they were collected to prepare them for frozen storage until the start of laboratory testing. A range of micronutrient laboratory analyses was carried out by TFNC. The results for all tests conducted in the 20% of households included in the micronutrient component will be published in a separate report. Results of the anaemia testing for children and women in this micronutrient subsample using venous blood are published in this report and will be included in the separate micronutrient report as well. 1.3 QUESTIONNAIRES Five questionnaires were used for the 2022 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, and the Micronutrient Questionnaire. The questionnaires, based on The DHS Program’s Model Questionnaires, were adapted to reflect the population and health issues relevant to Tanzania. In addition, a self-administered Fieldworker’s Questionnaire collected information about the survey’s fieldworkers. The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic demographic information was collected on characteristics of each person listed, including age, sex, marital status, education, and relationship to the head of the household. Parents’ survival status was determined for children under age 18. The data on age and sex of household members obtained from the Household Questionnaire were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of drinking water, type of toilet facilities, materials used for the floor of the dwelling unit, ownership of various durable goods, and ownership and use of mosquito nets. Questions were also asked about the disability status of household members age 5 or above. The Household Questionnaire also collected information on the results of iodine tests conducted on the salt consumed by households. 4 • Introduction and Survey Methodology The Woman’s Questionnaire was used to collect information from all eligible women age 15–49. These women were asked questions on the following topics:  Background characteristics (age, education, media exposure, etc.)  Birth history and childhood mortality  Knowledge and use of family planning methods  Fertility preferences, antenatal, delivery, and postnatal care  Breastfeeding and infant feeding practices  Vaccinations and childhood illnesses  Marriage and sexual activity  Women’s work and husband’s background characteristics  Other health issues  Adult mortality, including maternal mortality  Female genital cutting  Early childhood development  Malaria  Domestic violence The Man’s Questionnaire was administered to all men age 15–49 in the subsample of households selected for the men’s survey. The Man’s Questionnaire collected much of the same information found in the Woman’s Questionnaire, but it was shorter because it did not contain a detailed reproductive history or questions on maternal and child health. The Biomarker Questionnaire was used to record anthropometric (height and weight) measurements for children under age 5 and women and men age 15–49; to record anaemia test results for children age 6–59 months and women age 15–49; to record malaria rapid test results for children age 6–59 months; and to document responses to requests to women age 15–49 to collect urine samples for laboratory testing of urinary iodine. The samples were to be tested later for iodine at the TFNC laboratory. A Micronutrient Questionnaire was used to record anthropometric measurements, anaemia and malaria test results, and haematocrit results for women and to document the outcome of venous blood collection procedures and, in the relevant subset, the time for each step in the vitamin A relative dose response test. The Fieldworker Questionnaire recorded basic background information on the people collecting data in the field, including the team supervisors, computer-assisted personal interviewing (CAPI) supervisors, interviewers, and biomarker technicians. The questionnaires and the survey protocol, including administration of questionnaires and collection of biomarkers, were approved by the Medical Research Council of Tanzania and the Zanzibar Health Research Institute and reviewed by ICF’s Internal Review Board (IRB). 1.4 ANTHROPOMETRY, ANAEMIA, MALARIA AND IODINE TESTING, AND BLOOD PRESSURE MEASUREMENTS The 2022 TDHS-MIS included biomarker measurements such as anthropometry (height and weight), anaemia testing, and blood pressure. The Biomarker Questionnaire was used to record anthropometric measurements and the results of anaemia and malaria testing, while blood pressure measurement data were recorded in the Woman’s and Man’s Questionnaires. In the households selected for the micronutrient component, a Micronutrient Questionnaire was used to record anthropometric measurements, the results of anaemia, malaria, and haematocrit testing. Blood pressure measurements were conducted in all households. In the subsample of 50% of households selected for the male interview, anthropometry measurements were taken for children, women and men, malaria testing was conducted for children, urine was collected from women for iodine testing, and Introduction and Survey Methodology • 5 anaemia and malaria testing were conducted for women and children using capillary blood. This report also includes results from the anaemia testing conducted for women and children in the 20% subsample for the micronutrient component. In this subsample, anaemia testing was conducted using venous blood. Anthropometry: Weight and height measurements were recorded for children age 0–59 months and for women and men age 15–49. SECA model 878U scales with a digital display number were used to measure weight, while height and length were measured using ShorrBoard® measuring boards. Children younger than 24 months were measured lying down (recumbent length), while older children and adults were measured standing (height). Children with a z score of less than −3 or more than 3 for height-for-age, weight-for-height, or weight-for-age were flagged and measured a second time. The remeasurement of flagged cases was performed to ensure accurate reporting of height and weight measurements. For children having severe acute malnutrition, referral was made to the nearest health facility for further investigation. Anaemia: Blood specimens for anaemia testing were collected from eligible women age 15–49 who consented to the testing. Blood specimens were also collected from children age 6–59 months whose parents or guardians consented to the testing. In the 50% of households selected for the male interview, blood samples were drawn from a drop of blood taken from a finger prick (or a heel prick in the case of children age 6–11 months) and collected in a microcuvette. In the 20% of households selected for the micronutrient component, anticoagulated blood from venous collection was used to fill a microcuvette. Haemoglobin analysis was carried out on-site using a battery-operated portable analysis device (HemoCue® 201+ photometer), which produces a result in less than 1 minute. HemoTrol® controls were used as quality control materials for haemoglobin measurements using a HemoCue® 201+ photometer. Results were provided verbally and in writing to those being tested. Parents or guardians of children with a haemoglobin level below 8 g/dl were provided with a referral and instructed to take the child to a health facility for follow-up care. Likewise, adults were referred for follow-up care if their haemoglobin levels were below 8 g/dl. Malaria: Malaria testing was conducted for children age 6–59 months. Using the same finger- (or heel-) prick or venous blood sample used for anaemia testing, a drop of blood was tested immediately using the SD Bioline Ag Pf rapid diagnostic test (RDT), which is a rapid qualitative test for malaria specific to Plasmodium falciparum (Pf), the major cause of malaria in Tanzania. Children who tested positive for malaria using the RDT were screened to determine whether malaria was severe. Those with uncomplicated malaria in Tanzania Mainland were offered a full course of treatment according to Tanzania national malaria treatment guidelines, provided they were not currently on treatment with artemisinin-based combination therapy (ACT) and had not completed a full course of ACT during the preceding 2 weeks. To ascertain the correct dose, health technicians were provided with treatment guidance charts and were instructed to ask about signs of severe malaria and about any medications the child might already be taking. The nurses then provided the age-appropriate dose of ACT along with instructions on how to administer the medicine to the child.1 Children who tested positive and showed symptoms of severe malaria—haemoglobin levels below 8 g/dl, extreme weakness, loss of consciousness, rapid breathing, seizures, bleeding, jaundice, and dark urine—were not offered the treatment. Because the first-line treatment for severe malaria is parenteral quinine, the parents or guardians were advised to take the child to a health facility immediately. The parents or guardians of all other children treated were told to take the child to a health facility immediately if they became sicker, developed a fever or difficulty breathing, or were not able to drink or breastfeed. Parents also received counselling on how to prevent malaria. Women who tested positive for malaria were not offered treatment; all were referred to a health facility. Children who tested positive for malaria in Zanzibar were not treated but referred to a health facility for 1 Dosage of ACT was based on recipient’s age. The proper dosage for a child age 6 months to 3 years is one tablet of artemether-lumefantrine (co-formulated tablets containing 20 mg of artemether and 120 mg of lumefantrine) to be taken twice daily for 3 days, while the dosage for a child age 4–7 is two tablets of artemether-lumefantrine to be taken twice daily for 3 days. 6 • Introduction and Survey Methodology management based on the current procedure for malaria elimination on the island. Their parents or guardians were advised to go to the nearest health facility immediately. In those households in which anthropometry, anaemia, or malaria testing were done, a brochure was provided returning all results and explaining the causes and prevention of malnutrition, anaemia, and malaria. Urinary iodine: Urine samples were requested from women age 15–49, regardless of current pregnancy status. The sample was collected into a 50 ml bottle and then transferred into two screw-capped vials (2 ml each). The samples were then transported to TFNC for iodine testing by Sandell-Kolthoff reaction. To ensure quality in the determination of urinary iodine concentrations, TFNC participated in an external quality control programme organised by the Centers for Disease Control and Prevention (CDC) known as the programme for Ensuring the Quality of Urinary Iodine Procedures (EQUIP). Blood pressure: During the woman’s interview, three blood pressure measurements were taken from women age 15–49 who consented to the measurement. The measurement was done using the Life Source blood pressure monitor (UA-767F) or a similar digital oscillometric device with automatic upper-arm inflation and automatic pressure release. Measurements were taken at intervals of 10 minutes or more. Systolic and diastolic blood pressure values are expressed in millimetres of mercury (mmHg). The average of the second and third measurements was used to classify the respondent with respect to hypertension, according to internationally recommended categories (WHO 1999). The results of the respondent’s average blood pressure were given to respondents, along with a corresponding referral for advice when necessary. The results were read aloud and then provided to the respondent in writing via the Blood Pressure Reporting Form. 1.5 TRAINING OF TRAINERS AND PRETEST A pretest was conducted in Kilimanjaro region from 30 September to 21 October 2021. Eighteen interviewers (12 women and 6 men) and 6 health technicians (3 male and 3 female) participated in the training, which was conducted by trainers from NBS, OCGS, TFNC, the National Malaria Control Programme (NMCP), and MoH, with technical assistance from ICF. Classroom instructions were provided during the first 15 days, and a pretest field practice took place over 4 days in two rural clusters and one urban cluster. Following the field practice, a debriefing session was held with the pretest field staff, and modifications were made to the questionnaires and CAPI applications based on lessons learnt from the exercise. A training of trainers (TOT) for questionnaire content and the CAPI system was held before the main training from 19 January to 25 January 2022 in Moshi, Kilimanjaro region. 1.6 TRAINING OF FIELD STAFF The main training for the 2022 TDHS-MIS took place in Kilimanjaro region from 26 January 2022 to 21 February 2022. A total of 120 potential interviewers from all over the country—including 60 female nurses, 20 male nurses, 20 team leaders, and 20 CAPI supervisors—were invited to participate in the training. The training sessions were conducted by NBS, OCGS, and MoH trainers with support from ICF. Trainers from TFNC and UNICEF provided training to 80 biomarker technicians, including 40 who were trained on the standard survey biomarkers (anthropometry and haemoglobin) and 40 who were trained on procedures for the micronutrient component. Participants were evaluated through in-class exercises, quizzes, and observations made during the field practice. By the end of the main training, 18 teams were formed, with 18 individuals serving as team leaders, 18 as CAPI supervisors, 18 as male interviewers, 54 as female interviewers, and 72 as biomarker technicians (36 technicians for standard biomarkers and 36 for micronutrients). All the interviewers were nurses and clinicians. The team leaders and CAPI supervisors received additional training on how to Introduction and Survey Methodology • 7 identify the selected households, implementation of different subsamples, data quality control procedures, and coordination of the fieldwork. Nurses and clinicians were trained on how to provide doses of antimalarial drugs for eligible respondents who were diagnosed as malaria positive. The course of ACT was based on the recipient’s age. During the training, biomarkers were trained on how to measure the height and weight of children and adults, including standardisation and restandardisation exercises. All biomarkers and interviewers who passed the exams on both theory and practicals were given opportunities to participate in the data collection exercise. 1.7 FIELDWORK Data collection was carried out by 18 field teams, 3 teams for Zanzibar and 15 teams for Tanzania Mainland. Each team was provided with two vehicles (four-wheel drive trucks) with two drivers. Each team consisted of a team supervisor, a CAPI supervisor, three female interviewers, one male interviewer, and four biomarker technicians (two for standard biomarkers and two for micronutrients). During fieldwork, EA maps, listing forms, and local leaders assisted the field staff in identifying the sampled clusters and households. The team leaders and CAPI supervisors were responsible for data quality in the field. Fieldwork monitoring was an integral part of the 2022 TDHS-MIS. Quality control teams consisted of staff from NBS, OCGS, TFNC, and the ministry responsible for health from both Tanzania Mainland and Zanzibar. Fieldwork monitoring involved visiting teams regularly to ensure that the survey was conducted according to the survey protocol and providing real time solutions to field challenges by observing the biomarker measurements of eligible respondents. All biomarker questionnaires and urine specimens were sent to the nearest TFNC laboratory every week. Field check tables were generated regularly from Syncloud to monitor data quality and fieldwork progress. For field teams with specific problems, quality control staff provided specific instructions to help those teams to improve their performance, otherwise feedback was regularly provided to all field teams. ICF provided technical assistance during the entire 5- month data collection period, which ran from 24 February to 21 July 2022. All teams completed their first cluster in Kilimanjaro region. Data collection in other regions started in March 2022. 1.8 DATA PROCESSING In the 2022 TDHS-MIS survey, CAPI was used during data collection. The devices used for CAPI were Android-based computer tablets programmed using a mobile version of CSPro. Programming of questionnaires into the android application was done by ICF, while configuration of tablets was done by NBS and OCGS in collaboration with ICF. All fieldwork personnel were assigned usernames, and devices were password protected to ensure the integrity of the data collected. Selected households were assigned to CAPI supervisors, whereas households were assigned to interviewers’ tablets via Bluetooth. The data for all interviewed households were sent back to CAPI supervisors, who were responsible for initial data consistency and editing, before being sent to the central servers hosted at NBS Headquarters via Syncloud. The data processing of the 2022 TDHS-MIS ran concurrently with the data collection exercise. The electronic data files from each completed cluster were transferred via Syncloud to the NBS central office server in Dodoma. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were communicated to the field teams for review and correction. Secondary central data editing was done by NBS and OCGS survey staff at the central office. A CSPro batch editing tool was used for cleaning data and included coding of open-ended questions and resolving inconsistencies. The Biomarker paper questionnaires were collected by field supervisors and compared with the electronic data files to check for any inconsistencies that may have occurred during data entry. The concurrent data collection and processing offered an advantage because it maximised the likelihood of having error-free 8 • Introduction and Survey Methodology data. Timely generation of field check tables allowed effective monitoring. The secondary data editing exercise was completed in October 2022. 1.9 RESPONSE RATES Table 1.2 presents the response rates for the 2022 TDHS-MIS. A total of 16,312 households were selected for the 2022 TDHS-MIS sample. This number is slightly less than the targeted sample size of 16,354 because one EA could not be reached due to security reasons, while a few EAs had less than the targeted 26 households. Of the 16,312 households selected, 15,907 were found to be occupied. Of the occupied households, 15,705 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 15,699 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 15,254 women, yielding a response rate of 97%. In the subsample (50% of households) of households selected for the male questionnaire, 6,367 men age 15–49 were identified as eligible for individual interviews, and 5,763 were successfully interviewed, yielding a response rate of 91%. Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Tanzania DHS-MIS 2022 Tanzania Mainland Zanzibar Tanzania Result Urban Rural Total Household interviews Households selected 4,771 9,201 13,972 2,340 16,312 Households occupied 4,595 9,019 13,614 2,293 15,907 Households interviewed 4,493 8,957 13,450 2,255 15,705 Household response rate1 97.8 99.3 98.8 98.3 98.7 Interviews with women age 15–49 Number of eligible women 4,741 8,345 13,086 2,613 15,699 Number of eligible women interviewed 4,576 8,110 12,686 2,568 15,254 Eligible women response rate2 96.5 97.2 96.9 98.3 97.2 Household interviews in subsample Households selected 2,382 4,600 6,982 1,170 8,152 Households occupied 2,288 4,502 6,790 1,147 7,937 Households interviewed 2,232 4,469 6,701 1,129 7,830 Household response rate in subsample1 97.6 99.3 98.7 98.4 98.7 Interviews with men age 15–49 Number of eligible men 1,788 3,545 5,333 1,034 6,367 Number of eligible men interviewed 1,547 3,225 4,772 991 5,763 Eligible men response rate2 86.5 91.0 89.5 95.8 90.5 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 9 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings  Cooking: 7% of the population in Tanzania relies primarily on clean fuels and technologies for cooking.  Household population composition: The population of Tanzania is young, with 46% under age 15.  Birth registration: Registration of children under age 5 has increased substantially, from 26% in the 2015–16 TDHS-MIS to 68% in the 2022 TDHS-MIS.  Orphans: In Tanzania, 28% of households have a child under age 18 who is either an orphan or does not live with a biological parent.  School attendance: The net attendance ratio (NAR) has increased from 23% in 2015–16 to 37% in 2022 for secondary school. The primary school NAR also increased between the two surveys.  Disability by domain: 8% of household members age 5 and older have some level of difficulty in at least one functional domain, and 3% have a lot of difficulty or cannot function at all in at least one domain. nformation collected in the 2022 TDHS-MIS on the socioeconomic characteristics of the household population provides context for interpreting demographic and health indicators and furnishes an approximate indication of the representativeness of the survey. The information also sheds light on the living conditions of the population. This chapter presents information on housing characteristics, frequency of smoking in the home, household possessions, means of transportation, agriculture land and livestock/farm animals, wealth, and use of clean fuels and technologies (related to cooking, heating, and lighting). The chapter also includes information on household population and composition, children’s living arrangements and orphanhood, birth registration, educational attainment, school attendance, participation in organised learning, and disability. 2.1 HOUSING CHARACTERISTICS The 2022 TDHS-MIS collected information on access to electricity, flooring materials, and the number of rooms used for sleeping (Table 2.1). Nationally, more than one-third of households (36%) have electricity. The lowest rate is 17% in Tanzania Mainland rural households and the highest is 75% of Tanzania Mainland urban households. Two-thirds of households in Zanzibar have electricity. Access to electricity has increased in all these areas since the 2015–16 TDHS-MIS. Furthermore, the survey results on flooring material reveal that earth and sand are the most common flooring materials for households in Tanzania (46%), followed by cement (43%). Earth or sand flooring is most common in rural households of Tanzania Mainland (64%), while cement is the most common flooring material in urban households of Tanzania Mainland (67%) and Zanzibar (71%). In Tanzania, smoking in the home is not common, with 83% of households in Tanzania reporting that smoking never occurs inside the home. Daily smoking in the home occurs in 10% of households in Tanzania—12% of I 10 • Housing Characteristics and Household Population households in rural Tanzania Mainland, 7% in urban Tanzania Mainland, and 6% of households in Zanzibar. 2.1.1 Use of Clean Fuels and Technologies Primary reliance on clean fuels and technologies The percentage of the population using clean fuels and technologies for cooking, heating, and lighting, where each component is defined as follows: Clean cooking fuels and technologies Includes electric stove, solar cooker, liquefied petroleum gas (LPG)/cooking gas stove, piped natural gas stove, biogas stove, liquid fuel stove, manufactured solid fuel stove, traditional solid fuel stove, three-stone stove/open fire. Clean heating fuels and technologies Includes alcohol/ethanol, gasoline/diesel, kerosene/paraffin, coal/lignite, charcoal, wood, straw/shrubs/grass, agriculture crops, animal dung/waste, processed biomass (pellets) or woodchips, garbage/plastic and sawdust. Clean lighting fuels and technologies Includes electricity, solar lantern, battery powered or rechargeable flashlight/torch/lantern, biogas lamp, gasoline lamp, kerosene or paraffin lamp, charcoal, wood, straw/shrubs/grass, agriculture crops, animal dung/waste, oil lamp and candle. Sample: Households and de jure population 2.1.2 Cooking Only 7% of the Tanzanian population lives in households that use clean fuels and technologies for cooking, and there is a notable difference by residence. Clean fuels and technologies are used by 18% of the population in urban Tanzania Mainland, as compared with 11% in Zanzibar and just 2% in rural Tanzania Mainland. In Tanzania, the most commonly used cooking technology is a three-stone stove or open fire (67%), and the most common type of cooking fuel is wood (67%), followed by charcoal (25%) (Table 2.2). 2.1.3 Heating and Lighting Ninety-three percent of the population in Tanzania uses clean fuels and technologies for lighting. Moreover, 38% of household residents rely on a solar lantern for lighting, followed by 32% who use electricity. In Tanzania Mainland, 74% of the population in urban areas and 16% in rural areas use electricity, while in Zanzibar it is used by 65% of the population (Table 2.3). The use of space heating is uncommon in Tanzania. Housing Characteristics and Household Population • 11 2.1.4 Primary Reliance on Clean Fuels and Technologies Seven percent of the population relies primarily on clean fuels and technologies for cooking, space heating, and lighting. The vast majority of the population relies on clean fuels and technologies for lighting (93%). However, only 7% relies on clean fuels and technologies for cooking. Ninety-three percent of the population relies primarily on solid fuels for cooking, including 93% in Tanzania Mainland and 88% in Zanzibar (Table 2.4 and Figure 2.1). 2.2 HOUSEHOLD WEALTH 2.2.1 Household Durable Goods The survey also collected information on household effects, means of transportation, and ownership of agricultural land and farm animals. About 8 in 10 households (83%) own a mobile phone; nearly half (44%) own a radio, and almost 3 in 10 (27%) own a television. Possession of all types of household effects tends to be highest among households in urban areas in Tanzania Mainland, followed by Zanzibar, and then rural areas in Tanzania Mainland. In contrast, Tanzania Mainland rural households are more likely to own agricultural land (69%) or farm animals (62%) than are Tanzania Mainland urban households (21% and 26%, respectively) and Zanzibar households (20% and 29%, respectively). A bicycle is the most common means of transport, especially among households in Zanzibar (35%) and in Tanzania Mainland rural areas (31%). For further information on household durable goods, see Table 2.5. 2.2.2 Wealth Index Wealth index Households are given scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, and housing characteristics such as source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by her or his score, and then dividing the distribution into five equal categories, each with 20% of the population. Sample: Households Figure 2.1 Primary reliance on clean fuels and technologies 7 4 93 7 Cooking Space heating Lighting Cooking, space heating, and lighting Percentage of de jure population relying on clean fuels and technologies for: 12 • Housing Characteristics and Household Population Table 2.6 and Figure 2.2 show that 55% of the de jure population in urban areas are in the highest wealth quintile, as compared with 6% in rural areas. In Tanzania Mainland, households are equally distributed across the five wealth quintiles, in contrast to Zanzibar, where the highest wealth quintile holds the greatest percentage of the population (44%). By zone, the Western and Central zones have the greatest percentages of the population falling in the lowest quintile (32% each). Table 2.6 shows the distribution of the population by wealth quintile within each region. 2.3 COVERAGE OF ASSISTANCE PROGRAMMES Table 2.7 shows that 10% of households are currently benefitting from a Tanzania Social Action Fund (TASAF) programme. Cash transfers are the most common type of programme. Rural households are more likely than urban households to be receiving benefits from a TASAF programme (12% versus 5%). TASAF programme coverage is the lowest in the Eastern zone and in Dar es Salaam 2.4 HOUSEHOLD POPULATION AND COMPOSITION Household A person or group of related or unrelated persons who live together in the same dwelling unit(s), who acknowledge one adult male or female as the head of the household, who share the same housekeeping arrangements, and who are considered a single unit. De facto population All persons who stayed in the selected households the night before the interview (whether usual residents or visitors). De jure population All persons who are usual residents of the selected households, whether or not they stayed in the household the night before the interview. How data are calculated All tables are based on the de facto population, unless specified otherwise. A total population of 69,664 individuals stayed overnight in the 15,705 households interviewed in the 2022 TDHS-MIS. Fifty-two percent of them (36,541) were female, and 48% (33,123) were male. Nearly half of the population is under age 15 (46%), while only 5% is age 65 and older (Table 2.8). Figure 2.2 Household wealth by residence 1 282 27 10 24 32 15 55 6 Urban Rural Percent distribution of de jure population by wealth quintiles Highest Fourth Middle Second Lowest Housing Characteristics and Household Population • 13 The population pyramid in Figure 2.3 shows the population distribution by 5-year age groups, separately for males and females. The broad base of the pyramid illustrates that Tanzania’s population is young, which is typical of countries with low life expectancy and high fertility. The average household size in Tanzania is 4.5 people per household (Table 2.9). Tanzania Mainland urban households are slightly smaller (4.0 people per household) than Tanzania Mainland rural households (4.7 people per household). Zanzibar has the highest average household size (5.3 people). Twenty-nine percent of households in the 2022 TDHS-MIS are headed by women. Trends: The age-sex structure of the Tanzanian population has shown little change over the past decade. The percentage of children under age 15 is the same as in the 2015–16 TDHS-MIS (46%). 2.5 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: Children under age 18 In Tanzania, 7% of children age under age 18 are orphans, meaning that one or both of their parents are dead. The percentage of children not living with a biological parent and the percentage of children with one or both parents dead increase with age. Among children age 15–17, 29% do not live with a biological parent, while 15% are orphans (Table 2.10). By region, orphanhood ranges from 4% in Kaskazini Pemba to 10% in Iringa, Mbeya, and Simiyu (Map 2.1). Figure 2.3 Population pyramid 10 6 2 2 6 10 <5 5–9 10–14 15–19 20–24 25–29 30–34 35–39 40–44 45–49 50–54 55–59 60–64 65–69 70–74 75–79 80+ Age Percent distribution of the household population Male Female 2610 14 • Housing Characteristics and Household Population Map 2.1 Orphanhood by region Percentage of de jure children under age 18 with one or both parents dead Trends: The percentage of children under age 18 who are orphans has slightly decreased, from 10% in the 2010 TDHS, to 8% in the 2015–2016 TDHS-MIS, and to 7% in the 2022 TDHS-MIS. 2.6 BIRTH REGISTRATION Registered birth Child has a birth certificate or child does not have a birth certificate, but the birth is registered with the civil authorities. Sample: De jure children under age 5 The global concern regarding the need to have all births registered by 2030 is evident in targets 16.9.1 and 17.19.2 of the SDGs. Birth registration is important because a child who is not registered is in danger of being denied the right to an official identity, a recognised name, and a nationality. Respondents were asked whether they had birth certificates for the children in the household who were under age 5. If a child did not have a birth certificate, they were asked whether the birth had been registered with the civil authority. The 2022 TDHS-MIS found that 58% of children had birth certificates and 10% did not have birth certificates but had birth notifications. In total, 68% of children under age 5 had been registered with the civil authority. Boys and girls under age 5 are equally likely to be registered. The registration of births is more common in Tanzania Mainland urban areas (75%) than in Tanzania Mainland rural areas (65%). The registration of births in Tanzania Mainland as a whole (67%) is lower than in Zanzibar (94%). The percentage of births that have been registered increases with increasing household wealth, from 55% in the lowest wealth quintile to 82% in the highest wealth quintile (Table 2.11). By region, birth registration ranges from 40% in Kigoma to 96% in Kaskazini Pemba and Kusini Pemba (Map 2.2). Housing Characteristics and Household Population • 15 Map 2.2 Birth registration by region Percentage of de jure children under age 5 whose births are registered with the civil authorities For all births that occurred in a health facility during the 2 years preceding the survey, the mother was asked if she received a birth notification form. Women who received a birth notification form were asked if they received the form from the health facility where they gave birth or from another place. For 54% of facility births, the mothers reported receiving a birth notification form from the health facility where they gave birth. Birth notification forms were received from another place for an additional 5% of facility births (Table 2.12). Provision of birth notification forms is nearly universal in Zanzibar, with mothers reporting they received a notification form from the health facility where the birth occurred for 98% of facility births. Trends: Registration of children has increased dramatically, from 26% in the 2015–16 TDHS-MIS to 68% in the 2022 TDHS. 2.7 EDUCATION 2.7.1 Educational Attainment Median educational attainment Half of the population has completed less than the median number of years of schooling, and half of the population has completed more than the median number of years of schooling. Sample: De facto household population age 6 and older Educational attainment is fairly similar among women and men in Tanzania. Overall, 21% of females age 6 and older have no formal education, compared with 16% of males. The percentage who completed primary school and no higher is 30% among females and 29% among males. Nine percent of women and 10% of men completed secondary school and no higher. Attendance after the secondary level is slightly higher for 16 • Housing Characteristics and Household Population men (2%) than women (1%) (Tables 2.13.1 and 2.13.2). The median number of years of schooling completed among females is 5.5 years, compared with 5.8 years among males. Trends: The percentage of the population with no education has declined slightly over time, from 24% of females and 22% of males in the 2015–16 TDHS-MIS to 21% of females and 16% of males in the 2022 TDHS-MIS. Patterns by background characteristics  The median number of years of schooling is higher in urban areas than in rural areas among both females (6.5 years versus 4.0 years) and males (6.5 years versus 4.5 years).  Among both females and males, the median number of years of schooling increases with increasing wealth. For example, among females, the median number of years of schooling completed rises from 1.0 years in the lowest wealth quintile to 6.7 years in the highest quintile. 2.7.2 Primary and Secondary School Attendance Net attendance ratio (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 7–13 for primary school NAR and children age 14–17 for secondary school NAR Gross attendance ratio (GAR) The total number of children attending primary school divided by the official primary school age population and the total number of children attending secondary school divided by the official secondary school age population. Sample: Children age 7–13 for primary school GAR and children age 14–17 for secondary school GAR In Tanzania, the average primary school net attendance ratio (NAR) for children age 7–13 is 79% (80% for girls and 78% for boys). The secondary school NAR for children age 14–17 is 37% (40% for girls and 33% for boys) (Table 2.14). The secondary school NAR has increased from 23% in the 2015–16 TDHS-MIS. The primary school gross attendance ratio (GAR) for children age 7–13 is 98%, overall and for both girls and boys. The secondary school GAR for children age 14–17 is 53%, and the ratio is higher for girls (58%) than for boys (49%). Gender parity indices (GPI) The ratio of female to male students attending primary school and the ratio of female to male students attending secondary school. The index reflects the magnitude of the gender gap. Sample: Primary school students and secondary school students The primary school gender parity index (GPI) for the GAR is 0.99, indicating that similar percentages of girls and boys are attending primary school. The secondary school GPI for the GAR is 1.18, indicating that secondary school attendance is higher among girls than boys (Table 2.14). Patterns by background characteristics  According to the NAR, more children in urban areas attend primary school than children in rural areas (85% versus 77%). Similar patterns exist for secondary school attendance—the NAR for secondary school is 51% in urban areas and 31% in rural areas. Housing Characteristics and Household Population • 17  In 19 of the 31 regions, primary school attendance is higher among girls than boys.  The primary and secondary school NAR and GAR both increase with increasing household wealth. For example, the NAR for secondary school increases from 14% for girls and 10% for boys in the lowest quintile to 53% for girls and boys in the highest quintile (Figure 2.4). 2.7.3 Participation Rate in Organised Learning among Children Age 5 Participation rate in organised learning—adjusted net attendance ratio (NAR) Percentage of children 1 year younger than the official primary school entry age (at the beginning of school year) who are attending an early childhood education programme or primary school. The ratio is termed adjusted since it includes children in primary school. Sample: Children age 6 at the beginning of the school year Seventy-two percent of children who were age 6 at the beginning of the school year participated in organised learning; 23% attended an early childhood education programme, and nearly half (49%) attended primary school (Table 2.15). Patterns by background characteristics  The adjusted NAR for children age 6 at the beginning of the school year is the same among girls and boys (72%).  The adjusted NAR is higher in Zanzibar (93%) than in Tanzania Mainland (72%)  By zone, the adjusted NAR is lowest in Western Zone (46%) and highest in Zanzibar (93%).  The percentage of children age 6 at the beginning of the school year who participate in early learning increases with wealth. Those in the lowest wealth quintile have the lowest adjusted NAR (52%), and those in the highest wealth quintile have the highest adjusted NAR (97%). 2.8 DISABILITY The 2022 TDHS-MIS included The DHS Program’s Disability Module, a series of questions based on the Washington Group on Disability Statistics (WG) questions, which are based on the framework of the World Health Organization’s International Classification of Functioning, Disability, and Health. The questions address six core functional domains—seeing, hearing, communication, cognition, walking, and self-care—and provide the basic necessary information on disability. This information is comparable to that collected worldwide via the WG disability tools. Figure 2.4 Secondary school attendance by household wealth 14 31 44 52 53 10 23 34 49 53 Lowest Second Middle Fourth Highest Net attendance ratio for secondary school among children age 14–17 Girls Boys WealthiestPoorest 18 • Housing Characteristics and Household Population 2.8.1 Disability by Domain and Age The respondent to the Household Questionnaire provided information for all household members and visitors on whether they had no difficulty, some difficulty, a lot of difficulty, or no ability at all in the specified domain. Results, based on over 58,443 people, are presented in Table 2.16 for the de facto household population age 5 and older. Functional domains Seeing, hearing, communicating, remembering or concentrating, walking or climbing steps, and washing all over or dressing. Sample: De facto household population age 5 and above Overall, 8% of the population age 5 and older was reported to have some level of difficulty in at least one domain. Three percent of the population was reported to have either a lot of difficulty functioning in at least one domain or could not function in a domain at all. The percentage of people who have a lot of difficulty or cannot function at all in at least one domain is higher among individuals age 60 and older (14%) than among younger individuals (4% or lower). 2.8.2 Disability among Adults by Other Background Characteristics Functional domains Seeing, hearing, communicating, remembering or concentrating, walking or climbing steps, and washing all over or dressing. Sample: De facto household population age 15 and above Eighty-four percent of women and 86% of men have no difficulty in any domain. Eleven percent of women and 9% of men have difficulty seeing, the most prominent type of difficulty in the population age 15 and older. Six percent of women and 4% of men have at least some difficulty walking or climbing steps. Four percent of women and 3% of men have a lot of difficulty or cannot perform the function at all in at least one domain (Tables 2.17.1 and 2.17.2). Patterns by background characteristics  By region, the percentage who have some difficulty in at least one domain is highest in Kilimanjaro among both women and men (25% and 24%, respectively). Among women, this percentage is lowest in Singida and Tabora (6% and 4%, respectively). Among men, it is lowest in Tabora (4%) (Tables 2.17.1 and 2.17.2).  The percentage of men who have some difficulty in at least one domain decreases with increasing education, from 13% among those with no education to 8% among those with more than a secondary education.  The trend by level of education is less clear among women (Table 2.17.2). Housing Characteristics and Household Population • 19 LIST OF TABLES For more information on disability, see the following tables:  Table 2.1 Household characteristics  Table 2.2 Household characteristics: Cooking  Table 2.3 Household characteristics: Heating and lighting  Table 2.4 Primary reliance on clean fuels and technologies  Table 2.5 Household possessions  Table 2.6 Wealth quintiles  Table 2.7 Coverage of TASAF programmes  Table 2.8 Household population by age, sex, and residence  Table 2.9 Household composition  Table 2.10 Children’s living arrangements and orphanhood  Table 2.11 Birth registration of children under age 5  Table 2.12 Birth notification forms  Table 2.13.1 Educational attainment of the female household population  Table 2.13.2 Educational attainment of the male household population  Table 2.14 School attendance ratios  Table 2.15 Participation rate in organised learning  Table 2.16 Disability by domain and age  Table 2.17.1 Disability among adults according to background characteristics: Women  Table 2.17.2 Disability among adults according to background characteristics: Men 20 • Housing Characteristics and Household Population Table 2.1 Household characteristics Percent distribution of households and de jure population by housing characteristics and percent distribution by frequency of smoking in the home, according to residence, Tanzania DHS-MIS 2022 Households Population Characteristic Tanzania Mainland Zanzibar Tanzania Tanzania Mainland Zanzibar Tanzania Urban Rural Total Urban Rural Total Electricity Yes 74.7 16.8 35.6 66.1 36.4 73.9 15.2 32.2 67.4 33.3 No 25.3 83.2 64.4 33.9 63.6 26.1 84.8 67.8 32.6 66.7 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 12.4 63.9 47.2 13.9 46.3 13.0 65.5 50.3 13.3 49.1 Dung 0.0 0.2 0.1 0.0 0.1 0.0 0.2 0.1 0.0 0.1 Wood/planks 1.9 2.2 2.1 0.5 2.0 1.8 2.2 2.1 0.6 2.1 Palm/bamboo 0.0 0.1 0.1 0.0 0.1 0.0 0.1 0.1 0.0 0.1 Parquet or polished wood 1.4 0.6 0.9 0.0 0.8 1.3 0.7 0.9 0.0 0.8 Vinyl or asphalt strips 0.1 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 Ceramic tiles 16.0 2.1 6.6 10.0 6.7 17.3 1.9 6.3 10.1 6.5 Cement 66.7 30.3 42.1 71.4 42.9 65.2 29.0 39.5 72.0 40.5 Carpet 1.3 0.3 0.6 4.0 0.7 1.0 0.2 0.4 3.9 0.5 Other 0.2 0.3 0.3 0.1 0.3 0.3 0.3 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 Rooms used for sleeping One 39.1 29.0 32.3 20.8 32.0 24.9 18.0 20.0 11.1 19.7 Two 27.5 39.0 35.3 30.8 35.2 29.2 39.0 36.1 28.3 35.9 Three or more 33.4 31.9 32.4 48.3 32.8 45.8 43.0 43.8 60.6 44.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Frequency of smoking in the home Daily 6.9 11.5 10.0 5.5 9.9 7.7 12.0 10.8 6.1 10.6 Weekly 2.8 2.1 2.3 2.2 2.3 2.7 2.2 2.3 2.2 2.3 Monthly 3.1 0.5 1.3 4.6 1.4 2.6 0.4 1.0 4.7 1.1 Less than once a month 4.0 2.9 3.3 9.0 3.4 3.7 2.8 3.1 8.9 3.3 Never 83.3 82.9 83.1 78.7 82.9 83.3 82.6 82.8 78.1 82.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/ population 4,965 10,313 15,278 427 15,705 19,795 48,565 68,360 2,255 70,615 Housing Characteristics and Household Population • 21 Table 2.2 Household characteristics: Cooking Percent distribution of households and de jure population by place for cooking, cooking technology, and cooking fuel, according to residence, Tanzania DHS-MIS 2022 Households Population Characteristic Tanzania Mainland Zanzibar Tanzania Tanzania Mainland Zanzibar Tanzania Urban Rural Total Urban Rural Total Place for cooking In the house 50.0 21.6 30.8 75.4 32.0 46.1 17.7 25.9 75.3 27.5 Separate room/kitchen 20.7 8.1 12.2 67.1 13.7 22.2 7.2 11.5 67.8 13.3 No separate room/ kitchen 29.3 13.4 18.6 8.3 18.3 23.9 10.6 14.4 7.6 14.2 In a separate building 20.7 54.7 43.7 5.7 42.6 25.0 60.1 50.0 5.7 48.5 Outdoors 26.6 23.0 24.2 16.1 23.9 27.9 21.9 23.6 17.8 23.4 Other 0.3 0.1 0.2 0.0 0.1 0.3 0.1 0.1 0.0 0.1 No food cooked in household 2.4 0.6 1.2 2.7 1.3 0.8 0.2 0.4 1.1 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Main cooking technology Clean fuels and technologies 22.4 2.4 8.9 12.8 9.0 18.2 1.5 6.3 10.7 6.5 Electric stove 0.6 0.1 0.3 1.1 0.3 0.6 0.1 0.2 1.2 0.3 Solar cooker 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.1 LPG/cooking gas stove 21.4 2.2 8.4 11.5 8.5 17.2 1.3 5.9 9.2 6.0 Piped natural gas stove 0.3 0.0 0.1 0.2 0.1 0.3 0.0 0.1 0.2 0.1 Biogas stove 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 Other fuels and technologies 75.1 97.0 89.9 84.5 89.7 81.1 98.3 93.3 88.3 93.2 Liquid fuel stove not using alcohol/ethanol 1.2 0.0 0.4 0.6 0.4 0.8 0.0 0.2 0.2 0.2 Manufactured solid fuel stove 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.0 0.1 With a chimney 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Without a chimney 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.0 0.1 Traditional solid fuel stove 57.7 13.7 28.0 32.4 28.1 60.4 11.1 25.4 32.2 25.6 With a chimney 1.5 0.3 0.7 0.8 0.7 1.5 0.2 0.6 0.7 0.6 Without a chimney 56.2 13.4 27.3 31.6 27.4 59.0 10.9 24.8 31.5 25.0 Three stone stove/open fire 16.0 83.0 61.3 51.3 61.0 19.6 87.1 67.5 55.6 67.1 Other 0.1 0.1 0.1 0.2 0.1 0.0 0.1 0.1 0.2 0.1 No food cooked in household 2.4 0.6 1.2 2.7 1.3 0.8 0.2 0.4 1.1 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Cooking fuel Clean fuels and technologies1 22.4 2.4 8.9 12.8 9.0 18.2 1.5 6.3 10.7 6.5 Solid fuels for cooking 73.6 96.8 89.3 83.0 89.1 80.1 98.2 93.0 87.4 92.8 Coal/lignite 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Charcoal 57.0 13.3 27.5 32.0 27.7 60.1 10.8 25.1 32.0 25.3 Wood 15.8 82.5 60.8 50.1 60.5 19.4 86.4 67.0 54.6 66.6 Straw/shrubs/grass 0.2 0.7 0.6 0.5 0.6 0.2 0.8 0.6 0.5 0.6 Agricultural crop 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.1 0.0 0.1 Processed biomass (pellets) or woodchips 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Garbage/plastic 0.3 0.2 0.2 0.3 0.2 0.2 0.1 0.2 0.3 0.2 Sawdust 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 Other fuels 1.6 0.2 0.6 1.5 0.6 1.0 0.1 0.3 0.9 0.4 Gasoline/diesel 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Kerosene/paraffin 1.4 0.1 0.5 1.3 0.6 0.9 0.1 0.3 0.8 0.3 Other 0.2 0.0 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 No food cooked in household 2.4 0.6 1.2 2.7 1.3 0.8 0.2 0.4 1.1 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/ population 4,965 10,313 15,278 427 15,705 19,795 48,565 68,360 2,255 70,615 LPG = liquefied petroleum gas 1 Includes stoves/cookers using electricity, LPG/natural gas/biogas, solar, and alcohol/ethanol 22 • Housing Characteristics and Household Population Table 2.3 Household characteristics: Heating and lighting Percent distribution of households and de jure population by heating technology, heating fuel, and main lighting fuel or technology, according to residence, Tanzania DHS-MIS 2022 Households Population Characteristic Tanzania Mainland Zanzibar Tanzania Tanzania Mainland Zanzibar Tanzania Urban Rural Total Urban Rural Total Heating technology Central heating 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Traditional space heater 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 With a chimney 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Without a chimney 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Manufactured cookstove 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.1 0.0 0.1 With a chimney 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Without a chimney 0.1 0.1 0.1 0.0 0.1 0.1 0.1 0.1 0.0 0.1 Traditional cookstove 0.8 0.4 0.6 0.0 0.6 0.9 0.4 0.5 0.0 0.5 With a chimney 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Without a chimney 0.8 0.4 0.6 0.0 0.6 0.9 0.4 0.5 0.0 0.5 Three stone stove/open fire 0.4 2.0 1.5 0.4 1.4 0.4 1.8 1.4 0.4 1.4 Other 0.2 0.3 0.3 0.0 0.3 0.2 0.2 0.2 0.0 0.2 No heating in household 98.4 97.1 97.5 99.6 97.6 98.4 97.5 97.7 99.6 97.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Heating fuel Clean fuels and technologies1 0.2 0.1 0.1 0.1 0.1 0.2 0.0 0.1 0.1 0.1 Central heating 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Electricity 0.2 0.0 0.1 0.1 0.1 0.2 0.0 0.0 0.1 0.1 Solar air heater 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Liquified petroleum gas (LPG)/cooking gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Kerosene/paraffin 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.1 0.0 Charcoal 1.1 0.5 0.7 0.2 0.7 1.1 0.4 0.6 0.2 0.6 Wood 0.2 2.1 1.5 0.0 1.5 0.2 1.9 1.4 0.0 1.4 Other fuel 0.0 0.1 0.1 0.0 0.1 0.0 0.1 0.1 0.0 0.1 No heating in household 98.4 97.1 97.5 99.6 97.6 98.4 97.5 97.7 99.6 97.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Main lighting fuel or technology Clean fuels and technologies 94.9 91.8 92.8 71.7 92.3 94.7 92.6 93.2 72.0 92.5 Electricity 73.5 15.5 34.4 64.5 35.2 72.5 13.9 30.9 65.5 32.0 Solar lantern 12.6 45.7 34.9 4.9 34.1 14.3 49.5 39.3 4.8 38.2 Rechargeable flashlight/ torch/lantern 3.9 8.8 7.2 1.2 7.0 3.4 8.2 6.8 0.8 6.6 Battery powered flashlight/torch/lantern 4.9 21.9 16.3 1.1 15.9 4.4 20.9 16.2 0.8 15.7 Biogas lamp 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Gasoline lamp 0.2 0.2 0.2 0.0 0.2 0.2 0.3 0.2 0.0 0.2 Kerosene/paraffin lamp 1.9 4.0 3.3 25.8 3.9 2.0 3.6 3.1 25.4 3.8 Charcoal 1.0 0.4 0.6 0.4 0.6 1.0 0.3 0.5 0.3 0.5 Wood 0.2 2.1 1.5 1.1 1.5 0.3 2.2 1.7 1.3 1.6 Straw/shrubs/grass 0.0 0.1 0.1 0.0 0.1 0.0 0.1 0.0 0.0 0.0 Agricultural crop 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Oil lamp 0.2 0.2 0.2 0.8 0.2 0.3 0.1 0.1 0.9 0.2 Candle 1.4 0.3 0.6 0.1 0.6 1.3 0.2 0.5 0.0 0.5 Other fuel 0.2 0.6 0.5 0.1 0.4 0.3 0.5 0.4 0.0 0.4 No lighting in household 0.0 0.3 0.2 0.1 0.2 0.0 0.1 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/ population 4,965 10,313 15,278 427 15,705 19,795 48,565 68,360 2,255 70,615 LPG = liquefied petroleum gas 1 Includes central heating, electricity, LPG/natural gas/biogas, solar air heater, and alcohol/ethanol Housing Characteristics and Household Population • 23 Table 2.4 Primary reliance on clean fuels and technologies Percentage of de jure population relying on clean fuels and technologies for cooking, percentage relying on solid fuels for cooking, percentage relying on clean fuel and technologies for space heating, percentage relying on clean fuel and technologies for lighting, and percentage relying on clean fuels and technologies for cooking, space heating, and lighting, according to background characteristics, Tanzania DHS-MIS 2022 Background characteristic Primary reliance on clean fuels and technologies for cooking1 Primary reliance on solid fuels for cooking2 Number of persons in households that reported cooking in the house Primary reliance on clean fuels and technologies for space heating3 Number of persons in households that reported use of space heating Primary reliance on clean fuels and technologies for lighting4 Number of persons in households that reported use of lighting Primary reliance on clean fuels and technologies for cooking, space heating, and lighting5 Number of persons Residence Urban 18.3 80.7 20,346 13.6 309 94.4 20,497 18.4 20,499 Rural 1.7 98.2 50,000 1.6 1,240 91.9 50,050 1.8 50,116 Mainland/Zanzibar Mainland 6.3 93.3 68,115 3.8 1,540 93.3 68,292 6.5 68,360 Urban 18.3 80.7 19,646 13.6 309 94.7 19,792 18.4 19,795 Rural 1.5 98.4 48,469 1.4 1,231 92.7 48,500 1.6 48,565 Zanzibar 10.8 88.4 2,230 * 8 72.0 2,254 11.2 2,255 Unguja 14.8 83.9 1,553 * 8 79.6 1,576 15.3 1,576 Pemba 1.5 98.5 677 nc 0 54.2 679 1.6 679 Zone Western 1.0 99.0 6,466 * 163 95.3 6,466 1.1 6,480 Northern 10.2 89.0 8,092 6.0 273 84.0 8,109 10.1 8,109 Central 4.7 95.3 7,913 (0.4) 199 97.7 7,923 4.8 7,935 Southern Highlands 3.3 96.6 4,138 3.4 371 96.8 4,136 3.3 4,143 Southern 1.3 98.6 3,417 (0.0) 89 95.1 3,440 1.8 3,441 South West Highlands 3.1 96.9 6,379 1.9 182 92.4 6,378 3.2 6,389 Lake 4.7 95.1 21,662 (9.1) 208 93.7 21,689 4.6 21,705 Eastern 16.6 82.3 10,048 * 55 93.8 10,151 17.1 10,158 Zanzibar 10.8 88.4 2,230 * 8 72.0 2,254 11.2 2,255 Region Dodoma 8.9 91.1 3,518 * 64 97.6 3,525 8.8 3,526 Arusha 18.6 79.8 2,344 * 119 90.5 2,344 18.6 2,344 Kilimanjaro 11.9 87.2 1,964 * 79 87.5 1,970 11.3 1,970 Tanga 4.1 95.6 3,785 * 75 78.1 3,795 4.3 3,795 Morogoro 1.9 97.4 3,195 * 52 91.5 3,196 2.2 3,204 Pwani 5.9 93.4 2,193 * 4 92.5 2,198 5.9 2,198 Dar es Salaam 31.7 66.7 4,660 nc 0 95.9 4,757 32.2 4,757 Lindi 0.4 99.6 1,501 * 11 94.3 1,507 0.7 1,507 Mtwara 2.1 97.8 1,916 (0.0) 79 95.8 1,932 2.7 1,933 Ruvuma 1.6 98.3 1,752 (0.0) 142 97.5 1,753 1.7 1,756 Iringa 6.9 93.1 1,449 (0.0) 100 94.9 1,448 6.7 1,450 Mbeya 6.8 93.2 2,128 * 48 93.4 2,131 6.9 2,131 Singida 1.1 98.9 2,193 nc 0 98.9 2,205 1.7 2,206 Tabora 0.8 99.2 3,829 * 119 94.2 3,843 1.0 3,843 Rukwa 0.8 99.2 1,686 * 49 88.2 1,684 0.9 1,688 Kigoma 1.4 98.6 2,637 * 44 96.9 2,623 1.4 2,637 Shinyanga 1.5 98.4 2,727 * 26 94.6 2,729 1.6 2,729 Kagera 2.5 97.4 3,684 * 38 92.1 3,679 2.1 3,684 Mwanza 11.2 88.1 5,305 * 78 92.7 5,324 11.1 5,326 Mara 4.2 95.8 3,571 * 38 91.8 3,573 4.3 3,580 Manyara 1.6 98.3 2,202 (0.7) 134 96.7 2,193 1.6 2,203 Njombe 1.0 99.0 937 9.7 129 98.6 936 0.9 937 Katavi 0.5 99.5 944 * 3 95.7 943 0.6 945 Simiyu 2.2 97.8 2,434 * 9 97.0 2,439 2.4 2,440 Geita 2.2 97.6 3,940 * 20 95.5 3,946 2.0 3,946 Songwe 2.0 98.0 1,621 (4.1) 82 93.5 1,620 2.2 1,625 Kaskazini Unguja 0.9 98.8 337 * 2 51.5 341 1.6 341 Kusini Unguja 7.8 85.4 163 nc 0 77.2 164 7.6 164 Mjini Magharibi 20.3 79.0 1,053 * 7 89.0 1,071 20.8 1,071 Kaskazini Pemba 0.9 99.1 312 nc 0 51.9 313 1.1 313 Kusini Pemba 2.0 98.0 365 nc 0 56.2 366 2.1 366 Wealth quintile Lowest 0.0 100.0 14,120 0.2 573 89.6 14,081 0.0 14,123 Second 0.0 100.0 14,080 2.8 216 90.5 14,103 0.2 14,123 Middle 0.4 99.2 14,069 0.1 283 89.6 14,115 0.6 14,121 Fourth 4.5 94.5 14,015 8.7 272 94.3 14,127 4.8 14,127 Highest 27.5 72.1 14,062 15.0 205 99.0 14,121 27.4 14,121 Total 6.5 93.2 70,346 4.0 1,549 92.6 70,547 6.6 70,615 Note: Figures in parentheses are based on 25–49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. nc = no cases 1 Includes stoves/cookers using electricity, LPG/natural gas/biogas, solar, and alcohol/ethanol 2 Includes coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung/waste, processed biomass (pellets) or woodchips, garbage/plastic, and sawdust 3 Includes central heating, electricity, LPG/natural gas/biogas, solar air heater, and alcohol/ethanol 4 Includes electricity, solar lantern, rechargeable flashlight/torch/lantern, battery powered flashlight/torch/lantern, and biogas lamp 5 In order to calculate SDG indicator 7.1.2, persons living in households that report no cooking, no space heating, or no lighting are included in the numerator. 24 • Housing Characteristics and Household Population Table 2.5 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land and livestock/farm animals by residence, Tanzania DHS-MIS 2022 Tanzania Mainland Zanzibar Tanzania Possession Urban Rural Total Household effects Radio 60.5 36.0 44.0 49.1 44.1 Television 54.9 14.1 27.3 47.1 27.9 Mobile phone 93.2 77.9 82.9 92.4 83.1 Computer 7.8 1.0 3.2 6.0 3.3 Non-mobile telephone 2.5 1.1 1.5 1.1 1.5 Refrigerator 22.8 2.5 9.1 33.2 9.8 Battery or generator 3.7 12.9 9.9 1.2 9.7 Iron 49.2 15.5 26.5 45.6 27.0 Table 76.2 56.8 63.1 58.8 63.0 Chair 79.5 71.7 74.3 48.1 73.5 Sofa 53.7 12.3 25.7 15.8 25.5 Bed 93.8 80.3 84.7 94.6 85.0 Cupboard/cabinet 37.8 10.2 19.2 26.9 19.4 Water pump 2.6 0.7 1.3 4.0 1.4 Sewing machine 9.4 3.2 5.2 19.1 5.6 Blender 19.8 2.2 7.9 31.2 8.6 CD/DVD player 26.8 5.0 12.1 26.5 12.5 Washing machine 1.4 0.1 0.5 3.8 0.6 Microwave oven 4.6 0.4 1.8 4.7 1.8 Air conditioner 5.6 0.4 2.1 1.1 2.0 Means of transportation Bicycle 19.8 30.5 27.0 35.4 27.3 Animal drawn cart 0.7 2.8 2.1 1.1 2.1 Motorcycle/scooter 11.7 11.3 11.4 16.9 11.6 Car/truck 7.0 1.2 3.1 7.0 3.2 Boat with a motor 0.3 0.2 0.3 0.7 0.3 Ownership of agricultural land 21.3 69.4 53.8 19.7 52.9 Ownership of farm animals1 25.6 61.9 50.1 29.2 49.5 Number of households 4,965 10,313 15,278 427 15,705 1 Cows, bulls, other cattle, horses, donkeys, mules, goats, sheep, chickens, other poultry, or pigs Housing Characteristics and Household Population • 25 Table 2.6 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and region, Tanzania DHS- MIS 2022 Wealth quintile Total Number of persons Gini coefficient Residence/region Lowest Second Middle Fourth Highest Residence Urban 1.4 2.2 9.8 31.9 54.7 100.0 20,499 0.15 Rural 27.6 27.3 24.2 15.1 5.8 100.0 50,116 0.36 Mainland/Zanzibar Mainland 20.6 20.4 20.0 19.8 19.2 100.0 68,360 0.36 Urban 1.4 2.2 9.9 32.2 54.3 100.0 19,795 0.15 Rural 28.4 27.9 24.1 14.8 4.9 100.0 48,565 0.35 Zanzibar 2.8 6.5 20.6 25.9 44.3 100.0 2,255 0.29 Unguja 1.2 3.3 16.4 24.6 54.5 100.0 1,576 0.25 Pemba 6.4 13.9 30.2 28.9 20.6 100.0 679 0.34 Zone Western 32.3 29.6 19.4 11.2 7.5 100.0 6,480 0.45 Northern 21.2 16.3 20.2 22.5 19.8 100.0 8,109 0.40 Central 31.9 21.4 14.8 16.5 15.5 100.0 7,935 0.41 Southern Highlands 9.0 21.9 31.7 20.6 16.8 100.0 4,143 0.36 Southern 25.4 24.8 26.5 15.2 8.0 100.0 3,441 0.31 South West Highlands 19.7 23.4 24.6 18.5 13.9 100.0 6,389 0.34 Lake 19.8 21.8 20.4 21.7 16.4 100.0 21,705 0.40 Eastern 9.0 10.5 13.4 23.9 43.2 100.0 10,158 0.30 Zanzibar 2.8 6.5 20.6 25.9 44.3 100.0 2,255 0.29 Region Dodoma 24.8 20.4 12.9 18.7 23.1 100.0 3,526 0.40 Arusha 27.8 10.0 15.5 20.9 25.8 100.0 2,344 0.45 Kilimanjaro 3.0 8.8 22.3 40.1 25.7 100.0 1,970 0.26 Tanga 26.4 24.1 22.0 14.4 13.1 100.0 3,795 0.43 Morogoro 16.4 23.2 28.3 20.3 11.7 100.0 3,204 0.40 Pwani 17.8 14.7 16.6 24.0 26.9 100.0 2,198 0.39 Dar es Salaam 0.0 0.0 1.9 26.2 71.9 100.0 4,757 0.15 Lindi 29.2 27.5 24.3 13.3 5.6 100.0 1,507 0.36 Mtwara 22.5 22.7 28.2 16.7 9.9 100.0 1,933 0.30 Ruvuma 15.2 24.7 32.2 17.6 10.3 100.0 1,756 0.40 Iringa 5.7 22.1 30.6 18.3 23.3 100.0 1,450 0.35 Mbeya 18.0 15.3 16.5 24.7 25.6 100.0 2,131 0.37 Singida 30.9 25.3 18.1 13.4 12.3 100.0 2,206 0.50 Tabora 38.4 25.9 17.6 11.2 6.9 100.0 3,843 0.50 Rukwa 23.2 28.3 26.5 14.2 7.8 100.0 1,688 0.39 Kigoma 23.5 34.8 22.0 11.1 8.6 100.0 2,637 0.40 Shinyanga 28.5 27.1 16.9 16.2 11.3 100.0 2,729 0.52 Kagera 20.5 25.3 22.8 15.4 15.9 100.0 3,684 0.42 Mwanza 10.6 14.3 17.4 30.4 27.3 100.0 5,326 0.33 Mara 15.9 24.0 28.4 17.2 14.6 100.0 3,580 0.45 Manyara 44.3 18.9 14.5 15.9 6.5 100.0 2,203 0.43 Njombe 2.6 16.0 32.6 29.6 19.2 100.0 937 0.28 Katavi 25.7 24.1 25.3 15.9 9.1 100.0 945 0.47 Simiyu 46.9 24.7 11.0 12.7 4.7 100.0 2,440 0.52 Geita 12.3 20.9 23.1 29.2 14.4 100.0 3,946 0.40 Songwe 14.7 28.8 32.7 16.3 7.5 100.0 1,625 0.28 Kaskazini Unguja 2.9 7.6 47.7 30.5 11.3 100.0 341 0.28 Kusini Unguja 4.5 4.8 21.8 35.0 33.9 100.0 164 0.29 Mjini Magharibi 0.1 1.7 5.7 21.1 71.4 100.0 1,071 0.19 Kaskazini Pemba 5.8 12.8 33.1 29.0 19.4 100.0 313 0.36 Kusini Pemba 7.0 14.9 27.8 28.8 21.5 100.0 366 0.36 Total 20.0 20.0 20.0 20.0 20.0 100.0 70,615 0.36 26 • Housing Characteristics and Household Population Table 2.7 Coverage of TASAF programmes Percentage of households ever or currently benefitting from a Tanzania Social Action Fund (TASAF) programme, and percentage of households benefitting from different types of TASAF programmes, according to residence and region, Tanzania DHS-MIS 2022 Percentage ever or currently benefitting from TASAF TASAF programme Number of households Residence/region Cash transfer Public work Other Residence Urban 5.1 4.8 0.4 0.0 5,094 Rural 12.3 12.1 0.4 0.1 10,611 Mainland/Zanzibar Mainland 9.9 9.7 0.4 0.1 15,278 Urban 5.0 4.8 0.4 0.0 4,965 Rural 12.3 12.1 0.4 0.1 10,313 Zanzibar 10.3 10.0 0.4 0.1 427 Unguja 9.1 9.0 0.2 0.1 307 Pemba 13.3 12.8 0.7 0.1 120 Zone Western 14.5 14.4 0.0 0.1 1,159 Northern 12.8 12.5 0.4 0.2 1,849 Central 11.0 11.0 0.0 0.0 1,816 Southern Highlands 9.9 9.6 0.0 0.3 1,077 Southern 9.7 9.2 0.5 0.1 1,031 South West Highlands 8.6 8.6 0.1 0.0 1,483 Lake 9.7 9.3 1.1 0.1 4,252 Eastern 6.5 6.3 0.1 0.0 2,611 Zanzibar 10.3 10.0 0.4 0.1 427 Region Dodoma 10.1 10.1 0.0 0.0 882 Arusha 13.1 12.9 0.0 0.2 499 Kilimanjaro 12.1 11.9 0.5 0.4 528 Tanga 13.0 12.5 0.6 0.0 822 Morogoro 13.3 12.9 0.4 0.0 743 Pwani 7.3 7.3 0.0 0.0 555 Dar es Salaam 2.3 2.2 0.1 0.0 1,313 Lindi 10.5 10.1 0.2 0.1 438 Mtwara 9.2 8.5 0.7 0.0 593 Ruvuma 13.9 13.9 0.0 0.0 428 Iringa 6.8 6.8 0.0 0.0 381 Mbeya 10.9 10.9 0.0 0.0 552 Singida 8.1 8.1 0.0 0.0 469 Tabora 11.2 11.0 0.0 0.2 602 Rukwa 7.4 7.4 0.0 0.0 379 Kigoma 18.2 18.2 0.0 0.0 557 Shinyanga 8.9 8.7 0.1 0.0 505 Kagera 10.8 10.0 0.9 0.3 851 Mwanza 9.2 8.6 2.8 0.0 1,067 Mara 10.4 10.4 0.0 0.0 710 Manyara 15.7 15.7 0.0 0.0 465 Njombe 7.8 6.7 0.0 1.1 267 Katavi 4.3 4.3 0.0 0.0 168 Simiyu 14.0 14.0 0.0 0.0 410 Geita 6.3 6.3 1.0 0.0 709 Songwe 8.3 8.3 0.3 0.0 385 Kaskazini Unguja 15.9 15.9 0.3 0.0 67 Kusini Unguja 7.8 6.3 1.5 1.0 37 Mjini Magharibi 7.2 7.2 0.0 0.0 204 Kaskazini Pemba 12.9 12.3 0.4 0.1 54 Kusini Pemba 13.7 13.2 0.9 0.0 65 Total 10.0 9.7 0.4 0.1 15,705 Housing Characteristics and Household Population • 27 Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by age groups, according to sex and residence, Tanzania DHS-MIS 2022 Urban Rural Total Total Age Male Female Total Male Female Total Male Female <5 15.9 13.3 14.5 17.7 15.9 16.8 17.2 15.1 16.1 5–9 14.4 12.0 13.1 16.7 15.6 16.1 16.1 14.5 15.2 10–14 12.3 12.2 12.2 15.8 15.4 15.6 14.8 14.5 14.6 15–19 10.0 9.8 9.9 9.8 7.9 8.8 9.8 8.5 9.1 20–24 7.7 9.6 8.7 5.7 7.1 6.4 6.3 7.8 7.1 25–29 7.6 9.1 8.4 5.3 6.3 5.9 6.0 7.2 6.6 30–34 6.2 7.2 6.8 4.8 5.1 5.0 5.2 5.7 5.5 35–39 6.1 6.2 6.2 4.3 4.8 4.5 4.8 5.2 5.0 40–44 4.7 5.2 4.9 3.9 4.1 4.0 4.1 4.4 4.2 45–49 3.9 3.8 3.8 3.3 3.6 3.5 3.5 3.7 3.6 50–54 3.3 3.4 3.3 3.2 3.7 3.5 3.2 3.6 3.4 55–59 2.4 2.0 2.2 2.5 2.7 2.6 2.4 2.5 2.5 60–64 2.0 2.2 2.1 2.3 2.5 2.4 2.2 2.4 2.3 65–69 1.5 1.3 1.4 1.4 1.4 1.4 1.5 1.4 1.4 70–74 1.0 0.9 0.9 1.3 1.3 1.3 1.2 1.2 1.2 75–79 0.6 0.6 0.6 0.7 0.9 0.8 0.7 0.8 0.8 80 + 0.5 1.0 0.8 1.2 1.6 1.4 1.0 1.4 1.2 Don’t know 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0–14 42.6 37.5 39.9 50.2 46.9 48.5 48.1 44.1 46.0 15–64 53.7 58.6 56.3 45.0 47.7 46.4 47.5 51.0 49.3 65+ 3.6 3.8 3.7 4.7 5.3 5.0 4.3 4.9 4.6 Don’t know 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Child and adult populations 0–17 48.5 43.3 45.7 56.7 51.7 54.1 54.4 49.2 51.7 18+ 51.4 56.6 54.2 43.2 48.2 45.8 45.5 50.7 48.3 Don’t know 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Adolescents 10–19 22.3 22.0 22.1 25.6 23.3 24.4 24.6 22.9 23.8 Number of persons 9,378 10,885 20,263 23,745 25,656 49,401 33,123 36,541 69,664 28 • Housing Characteristics and Household Population Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size; mean size of households; and percentage of households with orphans and children under age 18 not living with a biological parent, according to residence, Tanzania DHS-MIS 2022 Tanzania Mainland Zanzibar Tanzania Characteristic Urban Rural Total Household headship Male 69.0 72.3 71.2 75.2 71.4 Female 31.0 27.7 28.8 24.8 28.6 Total 100.0 100.0 100.0 100.0 100.0 Number of usual members 0 0.0 0.0 0.0 0.0 0.0 1 14.5 10.3 11.7 5.6 11.5 2 13.4 10.9 11.7 10.3 11.7 3 18.1 15.4 16.2 12.9 16.2 4 17.7 16.4 16.8 13.5 16.7 5 13.7 14.5 14.2 15.4 14.3 6 10.0 11.3 10.9 12.4 10.9 7 5.6 8.1 7.3 10.6 7.4 8 3.3 5.1 4.5 7.5 4.6 9+ 3.6 8.0 6.5 11.9 6.7 Total 100.0 100.0 100.0 100.0 100.0 Mean size of households 4.0 4.7 4.5 5.3 4.5 Percentage of households with children under age 18 who are orphans or not living with a biological parent Double orphans 1.3 1.2 1.2 0.5 1.2 Single orphans1 8.4 9.7 9.2 8.4 9.2 Children not living with a biological parent2 22.0 25.3 24.2 23.9 24.2 Orphans and/or children not living with a biological parent 25.1 29.1 27.8 27.0 27.8 Number of households 4,965 10,313 15,278 427 15,705 Note: Table is based on de jure household members, i.e., usual residents. 1 Includes children with one dead parent and an unknown survival status of the other parent 2 Children not living with a biological parent are those under age 18 living in households with neither their mother nor their father present. Housing Characteristics and Household Population • 29 Table 2.10 Children’s living arrangements and orphanhood Percent distribution of de jure children under age 18 by living arrangements and survival status of parents, percentage of children not living with a biological parent, and percentage of children with one or both parents dead, according to background characteristics, Tanzania DHS-MIS 2022 Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biologi- cal parent Percent- age with one or both parents dead1 Number of children Background characteristic Father alive Father dead Mother alive Mother dead Both alive Only mother alive Only father alive Both dead Missing informa- tion on father/ mother Age 0–4 66.5 21.6 1.3 1.7 0.2 7.3 0.4 0.4 0.1 0.5 100.0 8.2 2.4 11,092 <2 71.9 24.2 0.8 0.6 0.2 1.7 0.1 0.2 0.0 0.2 100.0 2.0 1.3 4,336 2–4 63.0 20.0 1.5 2.4 0.3 10.9 0.6 0.5 0.2 0.7 100.0 12.2 3.1 6,756 5–9 56.6 15.9 2.4 5.1 0.6 16.1 1.3 0.7 0.4 0.8 100.0 18.5 5.6 10,595 10–14 47.9 14.6 4.8 7.4 1.1 18.2 2.4 1.6 1.0 0.9 100.0 23.3 11.1 10,239 15–17 43.4 12.4 6.8 6.8 1.2 21.6 3.8 1.5 1.9 0.6 100.0 28.8 15.4 3,954 Sex Male 56.8 16.8 3.2 5.3 0.7 13.3 1.6 0.9 0.7 0.7 100.0 16.5 7.1 18,017 Female 54.6 17.0 3.3 4.5 0.7 15.8 1.7 1.0 0.7 0.7 100.0 19.2 7.4 17,864 Residence Urban 51.6 20.8 3.3 4.5 0.5 14.8 1.9 0.9 0.8 0.8 100.0 18.5 7.5 9,217 Rural 57.1 15.6 3.2 5.0 0.8 14.5 1.5 1.0 0.6 0.7 100.0 17.6 7.2 26,663 Mainland/Zanzibar Mainland 55.4 17.0 3.3 4.9 0.7 14.6 1.6 1.0 0.7 0.7 100.0 17.9 7.3 34,790 Urban 51.1 21.1 3.3 4.5 0.5 15.0 1.9 0.9 0.8 0.9 100.0 18.7 7.6 8,893 Rural 56.9 15.6 3.3 5.1 0.8 14.5 1.5 1.0 0.6 0.7 100.0 17.6 7.2 25,897 Zanzibar 64.7 13.8 1.9 3.0 0.6 13.1 1.3 0.9 0.2 0.4 100.0 15.6 5.1 1,091 Unguja 63.6 14.5 1.9 3.2 0.5 13.0 1.3 1.1 0.3 0.6 100.0 15.7 5.3 717 Pemba 66.8 12.6 1.9 2.7 0.7 13.2 1.4 0.6 0.1 0.0 100.0 15.3 4.7 373 Zone Western 59.5 15.2 3.9 5.8 0.5 11.9 1.5 0.8 0.4 0.5 100.0 14.6 7.2 3,605 Northern 56.1 18.1 2.9 3.4 0.5 15.8 1.5 0.7 0.4 0.7 100.0 18.3 6.0 3,855 Central 54.1 18.5 2.7 3.8 0.6 16.6 1.1 0.9 0.3 1.3 100.0 18.9 5.7 4,072 Southern Highlands 51.2 18.8 3.1 6.0 0.9 14.9 1.7 1.6 0.8 1.0 100.0 19.1 8.3 1,893 Southern 35.9 28.4 2.6 7.6 0.0 21.7 1.1 1.6 0.6 0.4 100.0 24.9 5.9 1,491 South West Highlands 58.1 14.2 4.1 5.3 0.9 13.5 1.4 1.1 0.9 0.4 100.0 17.0 8.5 3,397 Lake 57.4 14.2 3.5 5.1 0.7 14.3 2.1 0.8 1.0 0.8 100.0 18.2 8.2 12,017 Eastern 53.8 21.3 2.5 4.6 1.0 13.0 1.7 1.2 0.5 0.5 100.0 16.3 6.9 4,460 Zanzibar 64.7 13.8 1.9 3.0 0.6 13.1 1.3 0.9 0.2 0.4 100.0 15.6 5.1 1,091 Region Dodoma 51.3 19.5 3.1 4.0 0.3 17.5 1.5 1.0 0.3 1.4 100.0 20.4 6.4 1,673 Arusha 62.0 19.6 2.9 0.9 1.0 11.1 0.9 0.4 0.2 1.1 100.0 12.6 5.4 1,159 Kilimanjaro 49.8 17.0 2.1 4.3 0.3 22.4 1.7 0.8 0.6 1.0 100.0 25.5 5.7 779 Tanga 55.0 17.7 3.2 4.5 0.3 16.0 1.7 0.7 0.4 0.4 100.0 18.9 6.4 1,917 Morogoro 56.0 18.4 2.3 5.1 1.5 12.5 1.7 1.6 0.4 0.5 100.0 16.2 7.6 1,578 Pwani 50.0 23.3 3.0 4.3 0.3 15.3 1.9 1.4 0.2 0.4 100.0 18.7 6.8 1,034 Dar es Salaam 54.1 22.7 2.4 4.3 0.9 12.2 1.6 0.7 0.7 0.4 100.0 15.1 6.3 1,847 Lindi 35.6 29.9 3.1 5.9 0.0 22.5 0.3 1.5 0.5 0.7 100.0 24.8 5.6 664 Mtwara 36.2 27.3 2.3 9.0 0.0 21.1 1.7 1.7 0.6 0.2 100.0 25.0 6.2 827 Ruvuma 49.6 17.2 2.2 8.9 0.9 16.6 1.2 1.3 0.8 1.3 100.0 19.8 6.7 838 Iringa 51.0 19.8 4.2 3.7 1.0 14.5 2.3 2.2 0.5 0.9 100.0 19.5 10.3 658 Mbeya 53.7 13.8 4.7 4.0 0.6 17.8 1.7 1.6 1.3 0.8 100.0 22.4 10.2 1,008 Singida 53.7 16.3 2.5 4.0 1.2 19.4 0.7 0.9 0.1 1.0 100.0 21.2 5.5 1,207 Tabora 57.5 14.4 3.8 7.4 0.6 12.7 1.7 0.7 0.5 0.7 100.0 15.6 7.5 2,213 Rukwa 56.9 18.3 4.2 5.9 0.8 11.2 0.7 0.9 1.1 0.1 100.0 13.9 7.7 968 Kigoma 62.6 16.6 3.9 3.2 0.4 10.7 1.1 1.0 0.1 0.3 100.0 13.0 6.7 1,392 Shinyanga 57.4 10.4 3.3 6.5 1.0 15.4 2.0 1.2 1.6 1.1 100.0 20.2 9.3 1,527 Kagera 63.2 11.0 4.1 4.1 1.0 13.2 1.2 0.5 0.9 0.7 100.0 15.9 7.8 1,962 Mwanza 54.2 16.9 3.3 4.7 0.4 15.9 2.3 0.8 1.0 0.7 100.0 19.9 7.7 2,785 Mara 52.9 19.7 4.9 3.9 0.2 14.5 1.9 0.6 0.7 0.6 100.0 17.7 8.4 1,970 Manyara 58.6 19.3 2.4 3.2 0.5 12.6 0.9 0.6 0.4 1.6 100.0 14.4 4.8 1,192 Njombe 54.6 20.6 3.2 3.7 0.6 12.2 2.0 1.2 1.5 0.4 100.0 16.8 8.5 398 Katavi 60.0 14.0 3.6 7.0 0.8 12.2 1.4 0.6 0.1 0.4 100.0 14.3 6.5 545 Simiyu 53.7 10.9 3.6 9.4 2.0 15.3 1.6 1.3 1.7 0.4 100.0 20.0 10.2 1,473 Geita 62.4 13.7 2.3 3.8 0.3 11.8 3.0 0.7 0.7 1.2 100.0 16.2 7.1 2,301 Songwe 63.3 10.5 3.5 5.2 1.4 12.0 2.0 1.1 0.7 0.4 100.0 15.7 8.7 875 Kaskazini Unguja 64.7 10.4 2.5 2.1 0.8 16.2 1.4 1.2 0.4 0.4 100.0 19.2 6.2 161 Kusini Unguja 57.6 14.2 1.2 2.9 0.5 18.3 1.3 1.5 0.5 1.9 100.0 21.6 5.2 75 Mjini Magharibi 64.1 15.9 1.9 3.6 0.5 11.2 1.2 1.0 0.3 0.5 100.0 13.6 4.9 481 Kaskazini Pemba 66.0 13.0 2.1 2.9 0.9 13.6 1.1 0.4 0.0 0.1 100.0 15.0 4.4 175 Kusini Pemba 67.5 12.2 1.7 2.5 0.6 12.9 1.7 0.8 0.2 0.0 100.0 15.5 5.0 199 Continued… 30 • Housing Characteristics and Household Population Table 2.10—Continued Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biologi- cal parent Percent- age with one or both parents dead1 Number of children Background characteristic Father alive Father dead Mother alive Mother dead Both alive Only mother alive Only father alive Both dead Missing informa- tion on father/ mother Wealth quintile Lowest 57.2 17.8 4.6 4.3 0.9 12.1 1.2 0.7 0.6 0.5 100.0 14.7 8.1 8,062 Second 56.9 15.2 3.4 5.4 0.6 14.4 1.6 1.2 0.8 0.6 100.0 18.0 7.7 7,711 Middle 55.3 16.6 3.0 4.7 0.7 15.3 1.8 0.9 0.6 1.0 100.0 18.7 7.2 7,339 Fourth 53.4 17.3 2.5 5.7 0.6 16.2 1.7 1.0 0.6 0.9 100.0 19.6 6.5 6,694 Highest 55.3 17.9 2.3 4.2 0.6 15.3 2.0 0.8 0.8 0.8 100.0 18.9 6.5 6,074 Total <15 57.2 17.5 2.8 4.6 0.6 13.7 1.4 0.9 0.5 0.7 100.0 16.5 6.2 31,926 Total <18 55.7 16.9 3.2 4.9 0.7 14.6 1.6 0.9 0.7 0.7 100.0 17.8 7.3 35,880 Note: Table is based on de jure members, i.e., usual residents. 1 Includes children with father dead, mother dead, both dead and one parent dead but missing information on survival status of the other parent Housing Characteristics and Household Population • 31 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 DHS-MIS 2022 Percentage of children whose births are registered and who: Total percentage of children whose births are registered Number of children Background characteristic Had a birth certificate Did not have birth certificate Age <1 41.4 15.7 57.1 2,122 1–4 61.6 8.6 70.2 8,970 Sex Male 58.2 9.8 68.1 5,646 Female 57.2 10.2 67.3 5,446 Residence Urban 62.4 12.5 74.9 2,911 Rural 56.1 9.1 65.2 8,181 Mainland/Zanzibar Mainland 57.0 9.9 66.9 10,765 Urban 61.7 12.5 74.2 2,816 Rural 55.4 9.0 64.3 7,949 Zanzibar 80.3 13.4 93.7 327 Unguja 79.9 12.7 92.7 224 Pemba 81.1 14.9 96.1 102 Zone Western 24.2 16.8 41.0 1,120 Northern 72.7 6.5 79.2 1,188 Central 72.8 4.6 77.4 1,131 Southern Highlands 76.1 3.5 79.6 564 Southern 81.2 2.8 84.0 409 South West Highlands 58.4 9.7 68.1 1,070 Lake 48.6 11.3 59.9 3,890 Eastern 64.8 12.4 77.3 1,394 Zanzibar 80.3 13.4 93.7 327 Region Dodoma 74.7 5.4 80.0 458 Arusha 72.6 4.4 77.0 370 Kilimanjaro 77.6 8.8 86.4 259 Tanga 70.4 6.8 77.3 559 Morogoro 68.8 6.7 75.4 473 Pwani 75.1 5.0 80.1 322 Dar es Salaam 56.2 21.0 77.2 599 Lindi 83.3 3.0 86.3 186 Mtwara 79.5 2.7 82.2 223 Ruvuma 70.7 2.2 72.9 255 Iringa 84.3 3.8 88.0 188 Mbeya 66.0 10.7 76.7 322 Singida 75.4 1.3 76.7 308 Tabora 33.4 8.1 41.5 677 Rukwa 59.7 9.2 68.9 300 Kigoma 10.0 30.2 40.3 443 Shinyanga 45.3 4.0 49.3 456 Kagera 23.2 19.0 42.2 688 Mwanza 50.9 16.4 67.3 897 Mara 72.2 3.3 75.5 656 Manyara 68.4 6.4 74.8 364 Njombe 74.9 5.8 80.7 121 Katavi 37.6 17.5 55.0 168 Simiyu 46.8 2.8 49.6 438 Geita 51.6 14.4 66.0 755 Songwe 60.7 4.3 65.0 279 Kaskazini Unguja 84.0 10.2 94.2 45 Kusini Unguja 76.3 16.4 92.7 24 Mjini Magharibi 79.3 12.9 92.2 155 Kaskazini Pemba 78.6 17.3 95.9 47 Kusini Pemba 83.3 12.9 96.2 56 Wealth quintile Lowest 47.3 7.7 55.0 2,568 Second 53.9 8.4 62.3 2,291 Middle 60.5 10.3 70.8 2,139 Fourth 61.5 11.5 73.0 2,173 Highest 68.8 13.1 81.8 1,922 Total 57.7 10.0 67.7 11,092 32 • Housing Characteristics and Household Population Table 2.12 Birth notification forms Among live births in a health facility in the 2 years preceding the survey, percent distribution by whether or not the mother received a birth notification form and source of the form, according to background characteristics, Tanzania DHS-MIS 2022 Received a birth notification form from: Did not receive a birth notification form Total Number of births Background characteristic Health facility where delivered Other place Age at birth <20 45.2 3.8 51.0 100.0 545 20–34 55.5 5.3 39.2 100.0 2,483 35–49 57.4 6.8 35.8 100.0 580 Birth order 1 55.7 5.1 39.2 100.0 932 2–3 56.2 4.4 39.4 100.0 1,441 4–5 53.5 6.3 40.2 100.0 737 6+ 47.1 6.6 46.3 100.0 498 Managing authority of health facility Public sector 53.5 5.3 41.2 100.0 3,306 Religious/voluntary 64.5 6.2 29.3 100.0 197 Private medical sector 58.3 2.6 39.1 100.0 105 Residence Urban 61.9 4.9 33.2 100.0 1,161 Rural 50.6 5.5 43.9 100.0 2,447 Mainland/Zanzibar Mainland 52.8 5.5 41.7 100.0 3,493 Urban 60.7 5.1 34.2 100.0 1,125 Rural 49.1 5.6 45.3 100.0 2,368 Zanzibar 97.9 0.6 1.5 100.0 115 Unguja 98.0 0.7 1.3 100.0 84 Pemba 97.5 0.4 2.1 100.0 32 Zone Western 26.7 5.4 67.9 100.0 368 Northern 62.4 8.3 29.3 100.0 334 Central 64.4 6.6 29.0 100.0 330 Southern Highlands 61.5 3.6 34.9 100.0 236 Southern 71.0 3.7 25.3 100.0 175 South West Highlands 59.1 9.8 31.2 100.0 364 Lake 44.1 4.3 51.6 100.0 1,157 Eastern 62.6 3.9 33.5 100.0 528 Zanzibar 97.9 0.6 1.5 100.0 115 Region Dodoma 69.0 6.0 25.0 100.0 169 Arusha 60.3 7.8 31.9 100.0 93 Kilimanjaro 73.7 5.0 21.3 100.0 99 Tanga 56.0 10.8 33.2 100.0 142 Morogoro 51.8 3.9 44.3 100.0 167 Pwani 54.5 5.3 40.3 100.0 105 Dar es Salaam 73.0 3.4 23.6 100.0 255 Lindi 71.4 2.6 26.0 100.0 82 Mtwara 70.6 4.7 24.6 100.0 94 Ruvuma 47.7 6.6 45.7 100.0 108 Iringa 76.5 0.9 22.6 100.0 82 Mbeya 68.3 4.9 26.8 100.0 105 Singida 71.0 3.6 25.4 100.0 82 Tabora 23.6 9.0 67.3 100.0 199 Rukwa 68.2 16.8 15.0 100.0 111 Kigoma 30.3 1.1 68.6 100.0 169 Shinyanga 25.1 3.9 71.0 100.0 134 Kagera 30.4 1.7 67.9 100.0 211 Mwanza 52.4 8.7 39.0 100.0 291 Mara 59.4 4.7 35.9 100.0 196 Manyara 47.9 10.8 41.3 100.0 79 Njombe 67.5 1.3 31.2 100.0 45 Katavi 48.3 14.2 37.5 100.0 47 Simiyu 30.9 0.3 68.8 100.0 115 Geita 51.5 3.0 45.5 100.0 209 Songwe 44.4 4.9 50.7 100.0 101 Kaskazini Unguja 99.8 0.0 0.2 100.0 15 Kusini Unguja 96.4 0.0 3.6 100.0 10 Mjini Magharibi 97.8 0.9 1.2 100.0 59 Kaskazini Pemba 96.7 1.0 2.4 100.0 14 Kusini Pemba 98.2 0.0 1.8 100.0 17 Mother’s education No education 42.1 5.0 52.9 100.0 607 Primary incomplete 45.2 7.0 47.8 100.0 328 Primary complete 54.2 5.7 40.2 100.0 1,668 Secondary+ 64.7 4.3 31.0 100.0 1,005 Continued… Housing Characteristics and Household Population • 33 Table 2.12—Continued Received a birth notification form from: Did not receive a birth notification form Total Number of births Background characteristic Health facility where delivered Other place Wealth quintile Lowest 39.3 6.5 54.2 100.0 645 Second 45.1 4.2 50.7 100.0 678 Middle 56.8 6.3 36.9 100.0 708 Fourth 57.6 4.9 37.5 100.0 777 Highest 68.6 4.8 26.7 100.0 800 Total 54.3 5.3 40.4 100.0 3,608 Note: Table is restricted to live births occurring in a health facility. 34 • Housing Characteristics and Household Population Table 2.13.1 Educational attainment of the female household population Percent distribution of the de facto female household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Tanzania DHS-MIS 2022 Background characteristic No education Some primary Com- pleted primary1 Some secondary Com- pleted second- dary2 More than secondary Don’t know Total Number Median years completed Age 6–9 31.7 68.1 0.1 0.0 0.0 0.0 0.0 100.0 4,303 0.2 10–14 8.1 78.0 5.7 8.2 0.1 0.0 0.0 100.0 5,291 4.0 15–19 7.7 15.2 26.5 34.7 15.8 0.0 0.0 100.0 3,093 11.2 20–24 12.7 8.3 41.7 9.1 26.1 2.1 0.1 100.0 2,861 6.7 25–29 10.9 7.3 45.4 8.2 25.4 2.8 0.0 100.0 2,616 6.7 30–34 16.7 8.7 47.9 6.0 18.1 2.5 0.2 100.0 2,094 6.5 35–39 22.3 10.1 54.2 3.1 8.2 1.9 0.2 100.0 1,902 6.3 40–44 20.1 10.0 56.7 2.5 9.1 1.4 0.4 100.0 1,606 6.4 45–49 20.9 8.8 60.8 2.3 6.0 1.0 0.3 100.0 1,343 6.3 50–54 24.6 8.4 59.2 1.8 4.7 0.8 0.4 100.0 1,322 6.3 55–59 27.2 13.8 53.0 1.3 3.7 0.8 0.1 100.0 912 6.2 60–64 43.9 13.5 36.1 1.1 4.2 0.7 0.6 100.0 875 3.1 65+ 65.4 22.2 10.4 0.4 1.0 0.4 0.2 100.0 1,773 0.0 Don’t know (73.0) (7.8) (19.2) (0.0) (0.0) (0.0) (0.0) 100.0 33 (0.0) Residence Urban 9.1 26.4 32.6 10.7 18.5 2.6 0.2 100.0 9,184 6.5 Rural 25.7 33.3 29.0 6.3 5.4 0.2 0.1 100.0 20,839 4.0 Mainland/Zanzibar Mainland 20.8 31.2 30.9 7.0 9.1 0.9 0.1 100.0 29,062 0.0 Urban 9.0 26.3 33.5 10.1 18.3 2.5 0.2 100.0 8,870 6.4 Rural 26.0 33.3 29.7 5.7 5.0 0.2 0.1 100.0 20,192 4.0 Zanzibar 14.9 30.8 6.9 25.8 18.7 2.1 0.8 100.0 961 0.0 Unguja 12.7 27.4 7.8 27.5 21.1 2.7 0.8 100.0 675 11.7 Pemba 20.1 38.7 4.9 21.9 13.1 0.5 0.7 100.0 286 4.2 Zone Western 29.3 36.4 25.3 4.9 3.8 0.1 0.0 100.0 2,686 3.1 Northern 20.6 27.5 31.1 8.0 11.4 1.3 0.0 100.0 3,510 6.1 Central 23.5 30.3 31.9 6.3 7.3 0.7 0.0 100.0 3,483 5.1 Southern Highlands 13.3 31.0 37.5 6.9 10.2 0.9 0.1 100.0 1,830 6.2 Southern 21.7 27.9 36.9 6.1 7.0 0.3 0.0 100.0 1,597 6.0 South West Highlands 23.8 32.4 28.0 7.6 7.5 0.5 0.2 100.0 2,647 4.7 Lake 21.8 34.1 29.3 6.5 7.8 0.4 0.1 100.0 8,832 4.7 Eastern 12.8 26.4 33.0 9.1 15.7 2.8 0.2 100.0 4,477 6.3 Zanzibar 14.9 30.8 6.9 25.8 18.7 2.1 0.8 100.0 961 6.6 Region Dodoma 24.1 26.0 32.5 7.3 9.2 0.9 0.0 100.0 1,598 6.0 Arusha 21.3 24.2 28.2 9.6 15.1 1.5 0.1 100.0 1,003 6.2 Kilimanjaro 7.8 26.4 37.3 11.1 15.2 2.1 0.0 100.0 879 6.5 Tanga 27.1 30.1 29.6 5.3 7.1 0.7 0.0 100.0 1,627 4.1 Morogoro 18.3 33.6 33.5 8.3 5.8 0.4 0.2 100.0 1,348 5.6 Pwani 20.4 29.0 30.8 7.2 11.7 0.7 0.2 100.0 992 6.0 Dar es Salaam 5.9 20.7 33.6 10.5 23.7 5.3 0.3 100.0 2,137 6.7 Lindi 24.4 27.3 37.7 5.0 5.0 0.5 0.0 100.0 690 5.5 Mtwara 19.5 28.4 36.4 7.0 8.4 0.2 0.0 100.0 908 6.1 Ruvuma 11.7 34.3 39.0 6.8 7.3 0.6 0.2 100.0 763 6.1 Iringa 13.8 28.3 36.4 7.0 13.0 1.6 0.0 100.0 642 6.2 Mbeya 12.3 29.2 32.2 11.9 12.8 1.0 0.5 100.0 910 6.3 Singida 18.1 37.7 31.9 6.4 5.4 0.6 0.0 100.0 993 5.0 Tabora 33.8 36.0 22.2 4.7 3.3 0.0 0.0 100.0 1,513 2.4 Rukwa 31.7 32.3 26.8 5.3 3.7 0.2 0.0 100.0 703 2.8 Kigoma 23.5 37.1 29.4 5.2 4.5 0.3 0.0 100.0 1,173 3.9 Shinyanga 28.5 32.1 27.0 6.2 5.9 0.2 0.0 100.0 1,131 4.1 Kagera 20.2 35.9 30.8 5.7 7.1 0.3 0.0 100.0 1,480 4.4 Mwanza 12.2 34.8 31.6 8.3 12.2 0.5 0.4 100.0 2,199 6.1 Mara 17.5 31.8 33.2 8.0 8.7 0.7 0.0 100.0 1,472 6.0 Manyara 28.4 29.9 30.8 4.6 5.9 0.4 0.0 100.0 892 4.0 Njombe 15.4 29.2 36.7 7.1 11.3 0.2 0.2 100.0 425 6.2 Katavi 33.5 35.8 21.4 4.5 4.2 0.2 0.5 100.0 380 2.3 Simiyu 39.7 28.3 23.8 3.5 4.4 0.4 0.0 100.0 971 1.8 Geita 24.9 38.3 26.2 5.5 4.8 0.3 0.0 100.0 1,578 3.3 Songwe 25.6 34.8 27.2 5.9 6.3 0.3 0.0 100.0 654 3.7 Kaskazini Unguja 21.2 33.7 5.0 25.3 13.9 0.3 0.6 100.0 142 4.6 Kusini Unguja 11.3 27.3 12.4 29.4 18.7 0.3 0.6 100.0 68 7.5 Mjini Magharibi 10.4 25.4 7.9 27.9 23.6 3.8 0.9 100.0 465 13.0 Kaskazini Pemba 21.1 39.7 5.5 20.3 12.3 0.2 0.9 100.0 134 3.7 Kusini Pemba 19.3 37.9 4.4 23.3 13.8 0.9 0.5 100.0 152 4.6 Wealth quintile Lowest 42.2 32.0 22.3 2.4 1.0 0.0 0.0 100.0 5,767 1.0 Second 26.7 36.8 29.1 4.9 2.4 0.0 0.1 100.0 5,880 3.5 Middle 18.9 34.7 32.7 8.1 5.4 0.1 0.1 100.0 6,011 5.2 Fourth 11.6 30.2 34.8 10.7 12.0 0.4 0.3 100.0 5,919 6.2 Highest 5.7 22.9 31.1 11.5 24.6 4.0 0.1 100.0 6,445 6.7 Total 20.6 31.2 30.1 7.6 9.4 1.0 0.1 100.0 30,023 5.5 Note: Figures in parentheses are based on 25–49 unweighted cases. 1 Completed grade 7 at the primary level 2 Completed grade 4 at the secondary level Housing Characteristics and Household Population • 35 Table 2.13.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Tanzania DHS-MIS 2022 Background characteristic No education Some primary Com- pleted primary1 Some secondary Com- pleted second- dary2 More than secondary Don’t know Total Number Median years completed Age 6–9 35.7 64.1 0.1 0.1 0.0 0.0 0.1 100.0 4,311 0.0 10–14 8.6 80.5 3.8 6.8 0.2 0.0 0.1 100.0 4,908 3.5 15–19 8.6 23.7 23.3 32.9 11.3 0.2 0.1 100.0 3,256 6.8 20–24 9.6 14.6 35.0 12.2 26.1 2.4 0.1 100.0 2,071 6.8 25–29 7.9 12.6 39.5 8.3 25.9 5.5 0.4 100.0 1,978 6.8 30–34 9.4 9.8 44.1 6.6 24.9 4.9 0.2 100.0 1,726 6.7 35–39 12.2 12.4 50.0 4.6 16.3 4.2 0.3 100.0 1,583 6.5 40–44 14.0 9.9 61.0 3.2 8.5 3.0 0.4 100.0 1,353 6.4 45–49 12.8 9.6 61.3 3.5 10.1 2.4 0.3 100.0 1,159 6.5 50–54 12.9 6.8 67.1 2.6 8.3 1.8 0.4 100.0 1,069 6.5 55–59 13.8 6.9 68.2 1.3 8.2 1.3 0.3 100.0 810 6.4 60–64 19.3 11.8 55.1 3.1 9.5 0.9 0.3 100.0 725 6.4 65+ 32.8 30.9 25.0 1.3 7.2 2.0 0.7 100.0 1,438 3.5 Don’t know (26.3) (4.7) (41.7) (4.8) (20.6) (1.5) (0.3) 100.0 27 * Residence Urban 6.0 29.7 27.8 11.5 20.1 4.4 0.4 100.0 7,659 6.5 Rural 19.7 37.5 29.1 6.9 6.1 0.6 0.1 100.0 18,755 4.5 Mainland/Zanzibar Mainland 15.9 35.2 29.4 7.7 10.0 1.7 0.2 100.0 25,579 0.0 Urban 5.9 29.7 28.5 10.9 20.1 4.4 0.4 100.0 7,393 6.5 Rural 19.9 37.4 29.8 6.4 5.9 0.5 0.1 100.0 18,186 4.5 Zanzibar 11.7 37.0 5.9 25.5 15.0 2.5 2.3 100.0 834 0.0 Unguja 9.8 32.4 6.4 28.4 17.4 3.2 2.3 100.0 584 11.1 Pemba 16.2 47.6 4.7 18.7 9.6 0.9 2.2 100.0 250 3.8 Zone Western 25.8 37.9 24.2 6.1 5.3 0.6 0.0 100.0 2,351 3.3 Northern 14.8 33.0 31.4 8.1 10.6 2.0 0.0 100.0 3,085 6.1 Central 19.1 33.5 31.3 6.7 7.6 1.6 0.2 100.0 3,005 5.3 Southern Highlands 8.5 33.5 38.9 6.7 11.3 1.1 0.0 100.0 1,580 6.2 Southern 14.6 37.2 33.5 7.7 6.7 0.3 0.0 100.0 1,341 5.6 South West Highlands 17.1 36.8 29.2 6.9 8.2 1.7 0.1 100.0 2,388 5.2 Lake 17.0 38.0 26.3 8.0 9.5 1.0 0.2 100.0 7,929 5.0 Eastern 8.5 30.0 30.9 9.2 16.8 4.2 0.4 100.0 3,900 6.4 Zanzibar 11.7 37.0 5.9 25.5 15.0 2.5 2.3 100.0 834 6.0 Region Dodoma 18.3 32.3 29.1 7.6 10.1 2.2 0.4 100.0 1,321 5.8 Arusha 18.7 29.0 29.0 8.0 12.4 2.8 0.0 100.0 886 6.1 Kilimanjaro 4.8 29.4 39.8 11.2 12.9 1.9 0.0 100.0 781 6.4 Tanga 18.0 37.6 28.3 6.5 8.2 1.4 0.1 100.0 1,418 4.7 Morogoro 12.5 37.8 32.3 8.8 7.4 0.9 0.3 100.0 1,229 5.9 Pwani 14.4 32.2 29.2 9.1 12.4 2.5 0.1 100.0 803 6.1 Dar es Salaam 3.3 23.9 30.8 9.5 24.8 7.1 0.6 100.0 1,868 6.8 Lindi 15.9 38.3 31.2 7.5 7.0 0.1 0.0 100.0 585 5.2 Mtwara 13.6 36.3 35.3 7.8 6.5 0.4 0.0 100.0 756 6.0 Ruvuma 10.8 33.3 41.1 6.1 7.9 0.7 0.0 100.0 682 6.1 Iringa 7.2 34.9 34.6 7.7 14.0 1.8 0.0 100.0 553 6.2 Mbeya 10.2 33.0 30.2 10.2 13.1 3.0 0.4 100.0 822 6.2 Singida 15.8 36.9 34.7 5.6 5.3 1.6 0.1 100.0 834 5.2 Tabora 29.5 37.7 22.3 5.6 4.4 0.5 0.0 100.0 1,453 2.8 Rukwa 21.4 37.5 30.1 4.2 5.7 1.2 0.0 100.0 607 4.3 Kigoma 20.0 38.2 27.3 6.7 6.7 0.9 0.1 100.0 899 4.1 Shinyanga 25.9 33.8 27.0 5.3 7.6 0.4 0.0 100.0 1,019 3.8 Kagera 13.5 40.0 29.9 6.4 9.3 0.9 0.0 100.0 1,347 5.3 Mwanza 10.3 39.3 24.8 10.8 12.8 1.4 0.6 100.0 1,969 6.0 Mara 11.7 34.4 31.0 9.9 11.1 1.9 0.0 100.0 1,243 6.1 Manyara 23.7 32.1 31.3 6.5 6.0 0.5 0.0 100.0 850 4.8 Njombe 6.3 31.7 41.4 6.5 13.6 0.5 0.0 100.0 344 6.3 Katavi 24.9 42.1 22.1 4.2 5.8 0.8 0.1 100.0 353 3.0 Simiyu 35.1 32.2 21.2 5.1 5.9 0.5 0.0 100.0 891 2.3 Geita 16.5 43.7 23.6 8.0 7.6 0.5 0.1 100.0 1,460 4.3 Songwe 17.4 38.3 31.1 6.8 5.6 0.8 0.0 100.0 607 4.9 Kaskazini Unguja 13.4 48.5 5.1 23.2 7.9 0.4 1.4 100.0 117 3.7 Kusini Unguja 5.9 37.6 9.3 29.3 14.2 0.4 3.4 100.0 60 6.7 Mjini Magharibi 9.4 27.0 6.4 29.8 20.6 4.4 2.4 100.0 407 13.0 Kaskazini Pemba 17.8 49.2 3.7 17.9 9.1 0.7 1.6 100.0 115 3.2 Kusini Pemba 14.9 46.3 5.6 19.4 10.0 1.2 2.6 100.0 135 4.2 Wealth quintile Lowest 34.2 38.6 23.2 2.7 1.3 0.0 0.1 100.0 5,107 2.1 Second 20.0 41.4 29.9 5.4 3.1 0.1 0.1 100.0 5,242 3.9 Middle 13.2 37.9 33.8 8.5 6.3 0.2 0.1 100.0 5,338 5.8 Fourth 8.0 33.1 31.4 12.7 13.4 1.1 0.2 100.0 5,417 6.3 Highest 4.1 25.5 24.9 11.6 26.2 7.0 0.6 100.0 5,309 6.9 Total 15.7 35.3 28.7 8.2 10.2 1.7 0.2 100.0 26,414 5.8 Note: Figures in parentheses are based on 25–49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Completed grade 7 at the primary level 2 Completed grade 4 at the secondary level 36 • Housing Characteristics and Household Population Table 2.14 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 DHS-MIS 2022 Net attendance ratio 1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 85.2 85.1 85.1 1.00 107.6 105.4 106.5 0.98 Rural 76.1 78.3 77.2 1.03 95.3 95.3 95.3 1.00 Mainland/Zanzibar Mainland 78.0 79.7 78.8 1.02 97.8 97.6 97.7 1.00 Urban 85.0 84.8 84.9 1.00 107.5 105.3 106.4 0.98 Rural 75.6 78.0 76.8 1.03 94.6 95.1 94.9 1.00 Zanzibar 91.1 89.3 90.1 0.98 116.1 103.9 109.5 0.89 Unguja 92.5 88.7 90.4 0.96 117.4 102.3 109.2 0.87 Pemba 88.8 90.4 89.6 1.02 113.7 106.8 110.2 0.94 Zone Western 63.6 66.1 64.9 1.04 79.5 81.1 80.4 1.02 Northern 79.9 79.5 79.7 1.00 101.9 97.8 99.9 0.96 Central 79.7 83.7 81.8 1.05 96.7 101.4 99.2 1.05 Southern Highlands 87.3 89.5 88.4 1.02 108.5 113.7 111.1 1.05 Southern 86.4 86.0 86.2 1.00 102.7 102.0 102.3 0.99 South West Highlands 77.2 77.8 77.5 1.01 96.9 97.3 97.1 1.00 Lake 74.6 78.6 76.6 1.05 95.9 95.3 95.6 0.99 Eastern 87.7 84.9 86.3 0.97 108.6 105.2 106.9 0.97 Zanzibar 91.1 89.3 90.1 0.98 116.1 103.9 109.5 0.89 Region Dodoma 78.7 81.0 79.8 1.03 92.1 100.3 96.1 1.09 Arusha 77.2 79.9 78.6 1.04 106.9 95.9 101.2 0.90 Kilimanjaro 85.3 87.6 86.5 1.03 110.6 108.7 109.6 0.98 Tanga 79.5 76.3 78.0 0.96 96.8 94.9 95.9 0.98 Morogoro 85.1 82.3 83.7 0.97 106.1 101.4 103.7 0.96 Pwani 84.1 84.4 84.2 1.00 108.9 104.5 106.5 0.96 Dar es Salaam 91.6 87.5 89.7 0.96 110.4 109.2 109.8 0.99 Lindi 87.3 89.7 88.5 1.03 106.9 101.9 104.5 0.95 Mtwara 85.6 83.2 84.5 0.97 99.4 102.0 100.7 1.03 Ruvuma 87.5 88.4 88.0 1.01 108.9 108.5 108.7 1.00 Iringa 86.3 89.3 87.7 1.04 106.4 118.2 112.0 1.11 Mbeya 85.6 85.0 85.3 0.99 105.9 108.3 107.1 1.02 Singida 82.9 86.8 85.2 1.05 100.2 102.7 101.7 1.02 Tabora 63.2 63.5 63.4 1.00 79.6 75.2 77.4 0.94 Rukwa 75.1 75.9 75.5 1.01 88.4 96.2 92.4 1.09 Kigoma 64.4 69.5 67.2 1.08 79.4 89.1 84.9 1.12 Shinyanga 73.1 80.8 77.2 1.11 97.3 102.5 100.1 1.05 Kagera 82.6 84.1 83.4 1.02 104.6 104.9 104.8 1.00 Mwanza 70.9 79.4 75.1 1.12 92.2 95.2 93.7 1.03 Mara 83.7 88.3 86.2 1.05 108.3 105.4 106.8 0.97 Manyara 78.2 83.7 81.0 1.07 100.5 101.4 101.0 1.01 Njombe 89.1 91.8 90.5 1.03 111.6 117.3 114.6 1.05 Katavi 71.5 71.1 71.3 1.00 93.0 90.5 91.8 0.97 Simiyu 61.9 67.5 64.8 1.09 80.4 79.5 79.9 0.99 Geita 75.0 71.7 73.3 0.96 93.5 85.6 89.4 0.92 Songwe 74.0 76.3 75.1 1.03 99.0 91.1 95.0 0.92 Kaskazini Unguja 91.4 91.7 91.6 1.00 120.9 111.4 115.8 0.92 Kusini Unguja 92.5 91.6 92.1 0.99 107.9 100.6 104.5 0.93 Mjini Magharibi 92.9 87.4 89.8 0.94 118.1 99.6 107.7 0.84 Kaskazini Pemba 87.3 89.7 88.6 1.03 111.9 104.0 107.8 0.93 Kusini Pemba 90.0 91.1 90.6 1.01 115.3 109.4 112.3 0.95 Wealth quintile Lowest 64.2 67.8 66.0 1.06 82.1 81.3 81.7 0.99 Second 77.9 81.2 79.6 1.04 97.2 99.7 98.5 1.03 Middle 81.9 83.0 82.5 1.01 103.6 99.9 101.6 0.96 Fourth 84.7 84.5 84.6 1.00 102.4 104.4 103.4 1.02 Highest 87.5 86.2 86.8 0.99 112.3 108.2 110.2 0.96 Total 78.3 80.0 79.2 1.02 98.4 97.8 98.1 0.99 Continued… Housing Characteristics and Household Population • 37 Table 2.14—Continued Net attendance ratio 1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 SECONDARY SCHOOL Residence Urban 48.4 53.6 51.2 1.11 79.0 79.9 79.5 1.01 Rural 27.6 33.9 30.5 1.23 38.2 47.4 42.4 1.24 Mainland/Zanzibar Mainland 32.7 39.5 35.9 1.21 48.2 56.5 52.2 1.17 Urban 48.1 53.0 50.8 1.10 78.7 78.9 78.8 1.00 Rural 27.1 32.9 29.7 1.21 37.2 45.5 41.0 1.22 Zanzibar 46.8 65.4 56.1 1.40 74.3 101.2 87.7 1.36 Unguja 53.9 65.5 59.9 1.22 83.2 100.8 92.2 1.21 Pemba 33.8 65.3 48.7 1.93 58.0 101.9 78.8 1.76 Zone Western 23.2 23.1 23.1 1.00 30.5 29.6 30.1 0.97 Northern 41.1 48.6 45.0 1.18 59.9 69.1 64.6 1.15 Central 35.9 43.0 39.3 1.20 50.1 59.3 54.6 1.18 Southern Highlands 28.9 41.5 34.6 1.44 49.7 57.4 53.2 1.16 Southern 47.5 41.0 44.2 0.86 63.6 59.2 61.3 0.93 South West Highlands 31.0 39.2 35.0 1.27 47.2 57.6 52.2 1.22 Lake 28.2 34.7 31.1 1.23 41.5 49.2 45.0 1.18 Eastern 40.8 50.6 45.7 1.24 64.5 77.6 71.0 1.20 Zanzibar 46.8 65.4 56.1 1.40 74.3 101.2 87.7 1.36 Region Dodoma 39.4 41.5 40.5 1.05 66.2 58.7 62.1 0.89 Arusha 43.2 52.9 47.9 1.22 49.4 81.8 64.9 1.66 Kilimanjaro 60.4 65.1 62.8 1.08 100.8 96.4 98.5 0.96 Tanga 28.2 37.2 33.0 1.32 45.2 46.3 45.8 1.02 Morogoro 30.6 41.4 35.4 1.35 36.5 56.2 45.1 1.54 Pwani 39.1 40.0 39.6 1.02 67.1 68.1 67.6 1.02 Dar es Salaam 54.2 63.0 59.0 1.16 96.8 98.8 97.9 1.02 Lindi 47.5 45.7 46.7 0.96 58.9 60.8 59.7 1.03 Mtwara 47.5 37.8 42.1 0.80 68.2 58.1 62.6 0.85 Ruvuma 26.2 27.9 26.9 1.06 38.1 39.8 38.8 1.05 Iringa 36.0 65.8 49.8 1.83 74.5 83.0 78.4 1.11 Mbeya 52.4 55.6 54.1 1.06 81.6 82.5 82.1 1.01 Singida 38.5 44.7 41.6 1.16 43.4 64.2 53.9 1.48 Tabora 20.1 22.7 21.2 1.13 24.8 29.5 26.8 1.19 Rukwa 18.8 32.6 25.5 1.74 33.6 43.9 38.6 1.31 Kigoma 30.2 23.7 26.7 0.78 43.5 29.7 36.1 0.68 Shinyanga 23.9 30.8 27.3 1.29 33.8 45.3 39.4 1.34 Kagera 30.0 29.9 29.9 1.00 35.9 44.8 39.7 1.25 Mwanza 27.6 36.8 32.2 1.33 51.7 54.7 53.2 1.06 Mara 34.2 40.8 37.2 1.19 50.5 51.7 51.0 1.02 Manyara 29.5 44.3 34.9 1.50 36.0 54.0 42.6 1.50 Njombe 25.7 39.0 32.2 1.52 45.5 62.3 53.7 1.37 Katavi 9.2 20.5 15.0 2.21 15.2 25.9 20.7 1.70 Simiyu 20.8 31.3 25.0 1.50 27.3 46.7 35.0 1.71 Geita 28.6 33.5 30.8 1.17 38.2 45.6 41.5 1.20 Songwe 28.6 31.4 29.7 1.10 38.0 52.0 43.6 1.37 Kaskazini Unguja 40.9 59.1 48.9 1.44 62.6 102.2 80.1 1.63 Kusini Unguja 46.7 72.6 59.5 1.56 74.9 94.1 84.3 1.26 Mjini Magharibi 59.9 66.3 63.4 1.11 92.3 101.3 97.1 1.10 Kaskazini Pemba 26.3 68.6 46.3 2.61 49.4 109.5 77.8 2.22 Kusini Pemba 40.6 62.3 50.9 1.53 65.7 95.1 79.7 1.45 Wealth quintile Lowest 9.7 14.2 11.6 1.47 15.6 21.0 17.9 1.35 Second 23.4 31.4 27.1 1.34 27.7 41.8 34.3 1.51 Middle 34.1 43.6 38.4 1.28 45.3 59.4 51.7 1.31 Fourth 48.9 52.2 50.4 1.07 73.8 78.3 75.9 1.06 Highest 52.7 52.7 52.7 1.00 90.7 78.0 83.3 0.86 Total 33.1 40.4 36.6 1.22 49.1 58.1 53.4 1.18 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 (14–17 years) population that is attending secondary school. By definition the NAR cannot exceed 100.0. 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 100.0. 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. 38 • Housing Characteristics and Household Population Table 2.15 Participation rate in organised learning Percent distribution of children age one year younger than the official primary school entry age at the beginning of the school year by attendance at an early childhood education programme or primary school, and the adjusted net attendance ratio (NAR), according to background characteristics, Tanzania DHS-MIS 2022 Percent distribution of children attending Adjusted NAR1 Number of children age 6 years at beginning of the school year Background characteristic An early childhood education programme Primary school Neither an early childhood education programme nor primary school Total Sex Male 25.1 46.6 28.3 100.0 71.7 1,102 Female 21.5 50.9 27.7 100.0 72.3 1,098 Residence Urban 12.8 78.7 8.6 100.0 91.4 515 Rural 26.5 39.6 33.9 100.0 66.1 1,686 Mainland/Zanzibar Mainland 23.1 48.4 28.5 100.0 71.5 2,142 Urban 12.1 79.1 8.8 100.0 91.2 497 Rural 26.4 39.1 34.5 100.0 65.5 1,645 Zanzibar 31.6 61.2 7.2 100.0 92.8 58 Unguja 27.4 66.1 6.5 100.0 93.5 37 Pemba 39.4 52.3 8.3 100.0 91.7 21 Zone Western 12.6 33.5 53.9 100.0 46.1 222 Northern 27.5 48.4 24.1 100.0 75.9 223 Central 34.2 40.1 25.7 100.0 74.3 273 Southern Highlands 18.6 70.8 10.7 100.0 89.3 113 Southern 29.1 56.8 14.1 100.0 85.9 93 South West Highlands 16.0 59.6 24.4 100.0 75.6 225 Lake 25.3 41.3 33.3 100.0 66.7 726 Eastern 16.2 66.7 17.1 100.0 82.9 267 Zanzibar 31.6 61.2 7.2 100.0 92.8 58 Region Dodoma 28.6 42.2 29.2 100.0 70.8 105 Arusha 23.3 48.6 28.1 100.0 71.9 72 Kilimanjaro (17.9) (82.1) (0.0) 100.0 (100.0) 35 Tanga 33.0 38.2 28.8 100.0 71.2 116 Morogoro 19.3 58.2 22.5 100.0 77.5 92 Pwani 13.4 59.2 27.4 100.0 72.6 61 Dar es Salaam 15.3 77.6 7.1 100.0 92.9 114 Lindi (38.2) (46.4) (15.4) 100.0 (84.6) 43 Mtwara (21.3) (65.6) (13.1) 100.0 (86.9) 50 Ruvuma 29.8 48.4 21.8 100.0 78.2 47 Iringa 12.3 85.6 2.1 100.0 97.9 44 Mbeya 16.4 71.9 11.7 100.0 88.3 68 Singida 40.9 42.4 16.7 100.0 83.3 73 Tabora 13.0 19.9 67.1 100.0 32.9 142 Rukwa 20.2 50.9 29.0 100.0 71.0 65 Kigoma 11.9 57.4 30.7 100.0 69.3 81 Shinyanga 9.8 51.5 38.7 100.0 61.3 98 Kagera 27.7 48.6 23.7 100.0 76.3 120 Mwanza 20.7 51.0 28.3 100.0 71.7 129 Mara 54.1 31.7 14.2 100.0 85.8 116 Manyara 35.2 35.9 28.9 100.0 71.1 94 Njombe (7.2) (88.6) (4.2) 100.0 (95.8) 22 Katavi 17.3 49.1 33.6 100.0 66.4 38 Simiyu 18.4 26.0 55.5 100.0 44.5 121 Geita 20.7 40.2 39.1 100.0 60.9 141 Songwe 9.8 61.7 28.5 100.0 71.5 54 Kaskazini Unguja (21.7) (69.8) (8.4) 100.0 (91.6) 7 Kusini Unguja (50.2) (43.9) (5.9) 100.0 (94.1) 3 Mjini Magharibi 25.9 68.0 6.1 100.0 93.9 27 Kaskazini Pemba 48.2 43.9 7.8 100.0 92.2 9 Kusini Pemba 32.1 59.3 8.7 100.0 91.3 11 Wealth quintile Lowest 27.5 24.2 48.3 100.0 51.7 579 Second 25.3 39.5 35.1 100.0 64.9 538 Middle 26.5 49.1 24.4 100.0 75.6 390 Fourth 21.3 67.4 11.4 100.0 88.6 357 Highest 11.1 85.4 3.4 100.0 96.6 336 Total 23.3 48.7 28.0 100.0 72.0 2,200 Note: Figures in parentheses are based on 25–49 unweighted cases. 1 The adjusted net attendance ratio (NAR) to organised learning is the percentage of children of age one year younger than official primary school entry age (at the beginning of school year) who are attending early childhood education or primary school. Housing Characteristics and Household Population • 39 Table 2.16 Disability by domain and age Percent distribution of de facto household population age 5 and over by the degree of difficulty in functioning according to domain, and percent distribution by the highest degree of difficulty in functioning in at least one domain by age, Tanzania DHS-MIS 2022 Degree of difficulty A lot of difficulty, or cannot do at all Number of persons Domain and age No difficulty Some difficulty A lot of difficulty Cannot do at all Total Domain Difficulty seeing 92.9 6.1 1.0 0.1 100.0 1.0 58,443 Difficulty hearing 97.8 1.6 0.4 0.1 100.0 0.5 58,443 Difficulty communicating 98.8 0.7 0.4 0.1 100.0 0.5 58,443 Difficulty remembering or concentrating 97.8 1.6 0.4 0.2 100.0 0.6 58,443 Difficulty walking or climbing steps 96.7 2.3 0.8 0.2 100.0 0.9 58,443 Difficulty washing all over or dressing 98.9 0.7 0.2 0.3 100.0 0.4 58,443 Difficulty in at least one domain by age1 5–9 96.3 2.7 0.6 0.4 100.0 0.9 10,620 10–14 96.3 2.8 0.6 0.2 100.0 0.9 10,199 15–19 94.5 4.1 1.0 0.4 100.0 1.4 6,348 20–29 94.6 4.1 1.0 0.3 100.0 1.2 9,526 30–39 91.9 6.1 1.4 0.5 100.0 1.9 7,305 40–49 84.9 12.6 2.0 0.5 100.0 2.5 5,461 50–59 75.3 20.7 3.7 0.3 100.0 4.0 4,112 60+ 50.7 34.9 11.9 2.5 100.0 14.4 4,811 Don’t know age 73.7 7.5 10.5 8.2 100.0 18.7 61 Age 15 and over 84.9 11.5 2.9 0.7 100.0 3.6 37,624 Total 88.9 8.4 2.1 0.5 100.0 2.6 58,443 1 If a person was reported to have difficulty in more than one domain, only the highest level of difficulty is shown. 40 • Housing Characteristics and Household Population Table 2.17.1 Disability among adults according to background characteristics: Women Percentage of the de facto female household population age 15 and over who have difficulty in functioning according to domain, by the highest degree of difficulty in at least one domain, and percentage with a lot of difficulty or cannot do at all in more than one domain, according to background characteristics, Tanzania DHS- MIS 2022 No difficulty in any domain Some difficulty, a lot of difficulty, or cannot do at all Difficulty in at least one domain1 A lot of difficulty or cannot do at all A lot of difficulty or cannot do at all in more than one domain Number of women Background characteristic Seeing Hearing Commu- nicating Remem- bering or concen- trating Walking or climbing steps Washing all over or dressing Some difficulty A lot of difficulty Cannot do at all Marital status Never married 90.8 5.5 1.9 1.9 1.9 1.1 0.5 6.6 2.1 0.6 2.6 1.1 4,246 Married/living together 87.8 8.6 1.8 0.6 1.5 3.5 0.4 10.2 1.9 0.2 2.0 0.3 11,699 Divorced or separated 81.8 12.0 3.2 1.5 2.6 5.3 1.2 14.5 2.9 0.8 3.7 1.1 2,227 Widowed 51.5 35.0 11.3 5.5 13.4 25.8 7.8 33.4 12.1 3.0 15.0 5.6 2,222 Residence Urban 82.6 12.5 2.5 1.1 2.3 5.0 1.1 13.4 3.5 0.5 3.9 0.9 6,803 Rural 84.4 10.6 3.3 1.8 3.4 5.9 1.5 11.9 3.0 0.7 3.7 1.3 13,625 Region Dodoma 89.8 8.1 1.8 1.1 2.4 1.8 0.7 8.0 1.9 0.3 2.2 0.9 1,122 Arusha 82.2 13.3 2.2 2.0 4.7 5.9 2.4 13.4 3.4 0.9 4.3 1.3 721 Kilimanjaro 66.9 25.4 7.4 2.9 9.6 13.1 3.4 25.3 7.0 0.9 7.9 2.7 690 Tanga 77.0 16.9 3.6 1.7 2.1 8.6 1.8 16.4 5.7 0.9 6.6 1.8 1,087 Morogoro 84.8 10.1 2.6 1.4 1.9 3.5 1.3 13.0 1.2 1.0 2.2 1.1 956 Pwani 81.4 12.9 1.5 1.9 2.5 6.4 1.8 13.1 4.1 1.2 5.3 2.6 696 Dar es Salaam 81.0 14.4 2.8 1.0 1.7 5.1 1.2 14.4 3.9 0.5 4.4 0.9 1,691 Lindi 85.0 10.2 5.0 2.7 3.9 7.1 1.7 11.8 2.4 0.7 3.1 1.6 516 Mtwara 80.8 14.3 4.5 1.9 3.2 6.0 1.7 14.2 3.9 1.0 4.9 1.4 676 Ruvuma 86.5 8.0 5.5 1.5 2.2 5.0 1.5 8.9 3.5 1.1 4.6 1.5 535 Iringa 82.4 12.4 4.3 1.3 1.0 4.3 1.4 13.1 4.3 0.1 4.5 0.8 461 Mbeya 82.9 13.3 2.0 1.7 5.6 5.8 2.2 13.8 2.9 0.3 3.3 0.7 640 Singida 92.1 5.5 2.3 1.5 2.7 3.1 0.8 5.7 1.3 0.9 2.2 0.8 573 Tabora 92.4 3.3 2.8 2.1 1.7 2.3 1.2 4.4 1.8 1.2 3.0 1.1 947 Rukwa 78.5 11.6 2.9 0.8 7.5 10.4 1.3 15.6 5.7 0.1 5.9 1.5 415 Kigoma 86.4 9.8 3.3 0.6 1.9 4.0 1.1 10.7 2.8 0.0 2.8 0.6 775 Shinyanga 85.7 8.9 3.0 1.5 2.5 6.8 1.6 9.5 3.9 0.8 4.8 1.4 692 Kagera 79.9 12.0 2.6 1.4 5.1 7.8 1.5 17.3 1.8 1.0 2.8 1.3 989 Mwanza 81.9 12.2 3.7 0.5 1.7 5.6 0.5 13.7 4.2 0.2 4.4 0.5 1,540 Mara 90.2 6.1 1.2 1.7 1.5 3.3 0.5 7.7 1.6 0.4 2.0 0.8 966 Manyara 84.5 11.7 2.5 2.2 3.1 6.7 1.0 12.6 2.0 0.9 2.9 1.2 576 Njombe 79.3 16.1 5.4 3.0 4.9 8.4 2.9 13.2 6.3 1.3 7.5 2.8 313 Katavi 81.8 10.7 3.7 0.4 5.7 8.1 1.0 13.6 4.4 0.2 4.6 1.1 237 Simiyu 85.7 9.9 1.0 1.2 3.4 7.5 0.9 11.0 2.4 0.9 3.3 1.5 548 Geita 89.8 5.3 2.3 1.1 1.7 3.6 0.6 8.5 1.5 0.2 1.7 0.6 969 Songwe 83.4 10.4 5.2 4.3 6.6 9.3 3.2 14.0 2.3 0.3 2.6 1.0 430 Kaskazini Unguja 78.1 17.3 4.7 1.2 1.8 3.8 0.3 19.4 2.2 0.3 2.5 0.3 98 Kusini Unguja 76.0 19.9 3.9 2.4 3.3 8.6 1.7 20.9 2.4 0.7 3.1 1.3 50 Mjini Magharibi 88.9 8.8 0.9 0.7 0.9 2.4 0.8 10.3 0.6 0.2 0.8 0.3 331 Kaskazini Pemba 83.5 13.1 2.8 1.2 1.7 2.8 1.5 14.3 1.8 0.4 2.2 1.1 85 Kusini Pemba 85.7 12.0 1.6 1.0 1.5 3.2 1.5 12.1 1.4 0.8 2.2 1.0 101 Education No education 75.4 15.7 6.5 4.1 7.1 12.7 4.1 16.6 6.2 1.9 8.1 3.4 4,401 Primary incomplete 75.9 15.8 5.2 2.1 5.0 9.6 1.8 18.6 4.8 0.7 5.5 1.7 2,302 Primary complete 86.7 9.5 1.7 0.7 1.7 3.6 0.5 10.7 2.2 0.3 2.6 0.5 8,731 Secondary+ 89.7 8.3 1.4 0.5 0.8 1.1 0.2 8.9 1.3 0.1 1.4 0.2 4,960 Don’t know 84.8 2.5 0.0 0.0 0.0 13.2 0.2 14.9 0.2 0.0 0.2 0.0 34 Wealth quintile Lowest 86.2 9.1 3.2 2.5 3.5 6.2 1.7 10.5 2.7 0.7 3.4 1.2 3,575 Second 82.0 11.9 4.0 2.0 3.9 7.2 2.1 13.1 3.8 1.0 4.8 1.9 3,735 Middle 85.6 9.5 2.8 1.3 2.9 5.0 1.2 11.1 2.6 0.7 3.4 1.2 3,984 Fourth 82.6 11.8 3.4 1.2 3.2 6.1 1.2 13.0 3.9 0.5 4.4 0.9 4,280 Highest 83.0 13.2 2.1 0.9 1.9 4.1 0.9 13.9 2.7 0.4 3.1 0.8 4,855 Total 83.8 11.2 3.0 1.5 3.0 5.6 1.4 12.4 3.1 0.6 3.8 1.2 20,429 Note: Table includes 33 women with information missing on marital status who are not shown separately. 1 If a person was reported to have difficulty in more than one domain, only the highest level of difficulty is shown. Housing Characteristics and Household Population • 41 Table 2.17.2 Disability among adults according to background characteristics: Men Percentage of the de facto male household population age 15 and over who have difficulty in functioning according to domain, by the highest degree of difficulty in at least one domain, and percentage with a lot of difficulty or cannot do at all in more than one domain, according to background characteristics, Tanzania DHS- MIS 2022 No difficulty in any domain Some difficulty, a lot of difficulty, or cannot do at all Difficulty in at least one domain1 A lot of difficulty or cannot do at all A lot of difficulty or cannot do at all in more than one domain Number of men Background characteristic Seeing Hearing Commu- nicating Remem- bering or concen- trating Walking or climbing steps Washing all over or dressing Some difficulty A lot of difficulty Cannot do at all Marital status Never married 93.0 2.7 1.5 2.3 2.5 1.2 1.2 4.3 1.6 1.1 2.7 1.5 5,863 Married/living together 83.9 11.9 2.4 0.7 2.5 4.7 0.8 12.8 2.8 0.4 3.2 0.6 10,066 Divorced or separated 80.8 12.9 3.3 1.4 2.7 5.6 2.0 14.3 3.9 1.0 4.9 1.3 906 Widowed 51.4 33.6 11.0 6.6 13.7 23.6 8.1 33.6 12.5 2.4 14.9 5.7 333 Residence Urban 86.2 9.6 1.9 1.4 2.3 3.2 0.9 10.6 2.4 0.8 3.2 1.0 5,379 Rural 86.2 9.1 2.5 1.4 3.0 4.2 1.2 10.3 2.8 0.7 3.5 1.0 11,816 Region Dodoma 88.8 6.8 2.2 1.3 2.1 1.9 0.4 7.8 2.9 0.5 3.4 0.1 861 Arusha 84.5 9.6 1.5 1.4 3.4 5.3 1.0 12.5 2.8 0.3 3.1 0.6 584 Kilimanjaro 70.6 21.2 5.1 4.0 8.8 7.8 2.6 23.6 4.8 1.0 5.8 1.8 600 Tanga 79.7 14.7 2.1 1.5 1.8 6.8 1.3 13.6 5.5 1.1 6.7 1.6 882 Morogoro 84.4 10.6 2.5 0.9 2.2 3.8 0.7 13.5 1.8 0.3 2.1 0.6 837 Pwani 84.2 10.9 3.0 1.9 2.4 3.7 0.8 12.8 2.2 0.7 2.9 1.0 539 Dar es Salaam 84.1 11.1 1.9 1.1 1.7 4.3 1.0 12.2 2.5 1.0 3.5 1.1 1,402 Lindi 87.3 8.3 3.6 3.0 3.1 5.1 1.2 8.3 3.2 1.2 4.5 2.0 390 Mtwara 87.7 8.8 3.1 0.3 1.8 4.8 2.1 8.1 2.7 1.5 4.2 1.3 513 Ruvuma 84.9 10.0 3.8 1.8 3.2 3.6 0.8 12.6 1.9 0.6 2.6 1.6 474 Iringa 89.7 6.5 1.7 1.0 2.4 4.2 1.0 8.6 1.5 0.2 1.7 0.6 368 Mbeya 85.1 10.3 2.8 1.8 3.6 4.1 1.1 10.7 3.0 1.2 4.2 0.7 564 Singida 92.6 3.9 0.9 1.6 1.6 2.1 1.7 4.8 1.9 0.8 2.6 1.1 530 Tabora 93.2 3.6 1.8 1.6 1.3 1.5 0.8 3.7 2.2 0.8 3.1 1.3 882 Rukwa 78.7 12.2 2.5 1.6 7.5 7.9 1.0 15.8 4.7 0.8 5.5 1.8 356 Kigoma 86.5 8.5 2.6 0.9 2.4 4.0 1.4 10.2 3.1 0.3 3.4 1.3 583 Shinyanga 89

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