Afghanistan - Demographic and Health Survey - 2017

Publication date: 2017

Afghanistan Demographic and Health Survey 2015 A fghanistan 2015 D em ographic and H ealth S urvey AFGHANISTAN DEMOGRAPHIC AND HEALTH SURVEY 2015 Central Statistics Organization Ansari Watt, Kabul, Afghanistan Ministry of Public Health Wazir Akbar Khan, Kabul, Afghanistan The DHS Program ICF Rockville, Maryland, USA January 2017 The 2015 Afghanistan Demographic and Health Survey (2015 AfDHS) was implemented by the Central Statistics Organization and the Ministry of Public Health from 15 June, 2015, to 23 February, 2016. The funding for the AfDHS was provided by the United States Agency for International Development (USAID). 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 2015 AfDHS may be obtained from the Central Statistics Organization, Ansari Watt, Kabul, Afghanistan; Telephone: (+93) 0202104338; Internet: http://cso.gov.af and the Ministry of Public Health, Great Masoud Road, Wazir Akbar Khan area, Kabul, Afghanistan; Internet: http://moph.gov.af. 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; E-mail: info@DHSprogram.com; Internet: www.DHSprogram.com. Cover photo ©2013 Sayed Saber Samim/CSO Afghanistan. Used with permission. ISBN: 978-9936-8050-03 Suggested citation: Central Statistics Organization (CSO), Ministry of Public Health (MoPH), and ICF. 2017. Afghanistan Demographic and Health Survey 2015. Kabul, Afghanistan: Central Statistics Organization. Contents • iii CONTENTS TABLES AND FIGURES . vii FOREWORD.xv CONTRIBUTORS TO THE REPORT . xvii READING AND UNDERSTANDING TABLES FROM THE 2015 AFDHS . xix ADDITIONAL DHS PROGRAM RESOURCES . xxvii ACRONYMS AND ABBREVIATIONS . xxix MAP OF AFGHANISTAN . xxxii 1 INTRODUCTION AND SURVEY METHODOLOGY .1 1.1 Survey Objectives .1 1.2 Sample Design .1 1.3 Questionnaires.2 1.4 Pretest .3 1.5 Training of Trainers .3 1.6 Training of Field Staff .3 1.7 Fieldwork .4 1.7.1 Fieldwork Challenges .4 1.8 Data Processing .4 1.9 Response Rates .5 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION .7 2.1 Drinking Water Sources and Treatment .7 2.2 Sanitation .8 2.3 Other Household Characteristics .9 2.4 Household Wealth .9 2.5 Hand Washing .10 2.6 Household Population and Composition .10 2.7 Birth Registration .11 2.8 Children’s Living Arrangements and Parental Survival .11 2.9 Education .12 2.9.1 Educational Attainment .12 2.9.2 School Attendance .12 2.9.3 Reasons for Not Attending School .13 3 CHARACTERISTICS OF RESPONDENTS .31 3.1 Basic Characteristics of Survey Respondents .31 3.2 Education and Literacy .31 3.3 Mass Media Exposure .33 3.4 Employment .34 3.5 Occupation .34 3.6 Tobacco and Drug Use.35 3.7 Knowledge of Tuberculosis .36 3.8 Knowledge of Hepatitis .36 3.9 Hepatitis Prevalence.36 iv • Contents 3.10 Cancer Prevalence and Deaths Related to Cancer .37 4 MARRIAGE AND SEXUAL ACTIVITY .61 4.1 Marital Status .61 4.2 Polygyny .62 4.3 Age at First Marriage .63 4.4 Age at First Sexual Intercourse .64 4.5 Recent Sexual Activity .65 5 FERTILITY.77 5.1 Current Fertility .77 5.2 Children Ever Born and Living.79 5.3 Birth Intervals .79 5.4 Insusceptibility to Pregnancy .80 5.5 Age at First Birth .80 5.6 Teenage Childbearing .81 6 FERTILITY PREFERENCES .91 6.1 Desire for Another Child .91 6.2 Ideal Family Size .92 6.3 Fertility Planning Status .93 6.4 Wanted Fertility Rates .94 7 FAMILY PLANNING .103 7.1 Contraceptive Knowledge and Use .104 7.2 Source of Modern Contraceptive Methods .106 7.3 Informed Choice .107 7.4 Discontinuation of Contraceptives .107 7.5 Demand for Family Planning .108 7.6 Contact of Nonusers with Family Planning Providers .110 8 INFANT AND CHILD MORTALITY .127 8.1 Early Childhood Mortality .128 8.2 Biodemographic Risk Factors .129 8.3 Perinatal Mortality .130 9 MATERNAL HEALTH CARE .135 9.1 Antenatal Care Coverage and Content .136 9.1.1 Skilled Providers .136 9.1.2 Timing and Number of ANC Visits .136 9.2 Components of ANC Visits .137 9.3 Protection against Neonatal Tetanus .137 9.4 Delivery Services .138 9.4.1 Institutional Deliveries .138 9.4.2 Skilled Assistance during Delivery .139 9.4.3 Delivery by Cesarean .140 9.5 Postnatal Care .140 9.5.1 Postnatal Health Check for Mothers .140 9.5.2 Postnatal Health Checks for Newborns .141 9.6 Problems in Accessing Health Care .142 Contents • v 10 CHILD HEALTH .159 10.1 Birth Weight.159 10.2 Vaccination of Children .160 10.3 Symptoms of Acute Respiratory Infection .162 10.4 Fever .162 10.5 Diarrheal Disease .163 10.5.1 Prevalence of Diarrhea .163 10.5.2 Treatment of Diarrhea .163 10.5.3 Feeding Practices .164 10.5.4 Knowledge of ORS Packets .165 10.6 Disposal of Children’s Stools .165 11 NUTRITION OF CHILDREN AND WOMEN .185 11.1 Infant and Young Child Feeding Practices .185 11.1.1 Breastfeeding .185 11.1.2 Exclusive Breastfeeding.186 11.1.3 Median Duration of Breastfeeding.187 11.1.4 Complementary Feeding .187 11.1.5 Minimum Acceptable Diet .188 11.2 Micronutrient Intake and Supplementation among Children.189 11.3 Presence of Iodized Salt in Households .190 11.4 Micronutrient Intake among Mothers .190 12 MALARIA .201 12.1 Ownership of Insecticide-Treated Nets .202 12.2 Household Access and Use of ITNs .203 12.3 Use of ITNs by Children and Pregnant Women .204 12.4 Case Management of Malaria in Children .204 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR .215 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods .216 13.2 Knowledge about Mother-to-Child Transmission .218 13.3 HIV/AIDS Attitudes .218 13.3.1 Attitudes toward People Living with HIV/AIDS .218 13.3.2 Attitudes toward Negotiating Safer Sexual Relations with Husbands .219 13.3.3 Attitudes toward Condom Education for Young People .219 13.4 Coverage of HIV Testing Services .220 13.5 Male Circumcision .220 13.6 Self-reporting of Sexually Transmitted Infections .220 13.7 Injections .221 13.8 HIV/AIDS-Related Knowledge and Behavior among Young People .221 13.8.1 Knowledge .221 13.8.2 First Sex .222 13.8.3 Coverage of HIV Testing Services .222 14 ADULT AND MATERNAL MORTALITY .245 14.1 Data .245 14.2 Direct Estimates of Adult Mortality .246 14.3 Direct Estimates of Pregnancy-related Mortality .247 vi • Contents 15 WOMEN’S EMPOWERMENT .251 15.1 Married Women’s and Men’s Employment .251 15.2 Control over Women’s Earnings .252 15.3 Control over Men’s Earnings .253 15.4 Women’s and Men’s Ownership of Assets .253 15.5 Women’s Participation in Decision Making .254 15.6 Attitudes toward Wife Beating .255 16 DOMESTIC VIOLENCE .273 16.1 Measurement of Violence .274 16.2 Experience of Physical Violence from Anyone .274 16.2.1 Prevalence of Physical Violence .274 16.2.2 Perpetrators of Physical Violence .275 16.3 Marital Control.275 16.4 Spousal Violence .276 16.4.1 Prevalence of Spousal Violence.276 16.4.2 Onset of Spousal Violence .279 16.5 Injuries due to Spousal Violence .279 16.6 Violence Initiated by Women against Husbands .280 16.7 Response to Violence .280 16.7.1 Help Seeking Behavior to Stop the Violence .280 16.7.2 Sources for Help .280 17 FISTULA .299 17.1 Womens’ Knowledge of Fistula .299 17.2 Self-Reported Symptoms and Treatment .300 17.2.1 Self-reported Fistula Symptoms .300 17.2.2 Treatment Seeking for Fistula .300 REFERENCES .307 APPENDIX A SAMPLE DESIGN.309 APPENDIX B ESTIMATES OF SAMPLING ERRORS .319 APPENDIX C DATA QUALITY TABLES .359 APPENDIX D QUESTIONNAIRES .365 Tables and Figures • vii TABLES AND FIGURES INTRODUCTION AND SURVEY METHODOLOGY .1 Table 1.1 Results of the household and individual interviews . 5 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION .7 Table 2.1 Household drinking water . 15 Table 2.2 Household sanitation facilities . 16 Table 2.3 Household characteristics . 17 Table 2.4 Household possessions . 18 Table 2.5 Wealth quintiles . 19 Table 2.6 Hand washing . 20 Table 2.7 Household population by age, sex, and residence . 21 Table 2.8 Household composition . 21 Table 2.9 Birth registration of children under age 5 . 22 Table 2.10 Children’s living arrangements and orphanhood . 23 Table 2.11 School attendance by survivorship of parents . 24 Table 2.12.1 Educational attainment of the female household population . 25 Table 2.12.2 Educational attainment of the male household population . 26 Table 2.13 School attendance ratios . 27 Table 2.14 Reasons for children never attending school . 28 Table 2.15 Reasons for children dropping out of school . 29 Figure 2.1 Households with improved water sources . 8 Figure 2.2 Household drinking water by residence . 8 Figure 2.3 Household toilet facilities by residence . 9 Figure 2.4 Household wealth by residence . 10 Figure 2.5 Population pyramid . 11 Figure 2.6 Birth registration by wealth . 11 Figure 2.7 Orphanhood by age . 12 Figure 2.8 Secondary school attendance by wealth . 13 CHARACTERISTICS OF RESPONDENTS .31 Table 3.1 Background characteristics of respondents . 39 Table 3.2.1 Educational attainment: Women . 40 Table 3.2.2 Educational attainment: Men . 41 Table 3.3.1 Literacy: Women . 42 Table 3.3.2 Literacy: Men . 43 Table 3.4.1 Exposure to mass media: Women. 44 Table 3.4.2 Exposure to mass media: Men . 45 Table 3.5.1 Employment status: Women . 46 Table 3.5.2 Employment status: Men . 47 Table 3.6.1 Occupation: Women . 48 Table 3.6.2 Occupation: Men . 49 Table 3.7 Type of employment: Women . 50 Table 3.8.1 Use of tobacco: Women . 51 Table 3.8.2 Use of tobacco: Men . 52 Table 3.9 Use of drugs . 53 Table 3.10.1 Knowledge concerning tuberculosis: Women . 54 viii • Tables and Figures Table 3.10.2 Knowledge concerning tuberculosis: Men . 55 Table 3.11.1 Knowledge concerning hepatitis: Women . 56 Table 3.11.2 Knowledge concerning hepatitis: Men . 57 Table 3.12.1 Reported prevalence of hepatitis: Women . 58 Table 3.12.2 Reported prevalence of hepatitis: Men . 59 Table 3.13 Households with members diagnosed with cancer . 60 Table 3.14 Deaths of household members diagnosed with cancer . 60 Figure 3.1 Education of survey respondents . 32 Figure 3.2 Women with more than a secondary education . 33 Figure 3.3 Exposure to mass media . 33 Figure 3.4. Employment by education . 34 Figure 3.5 Occupation . 35 Figure 3.6 Use of tobacco . 36 MARRIAGE AND SEXUAL ACTIVITY .61 Table 4.1 Current marital status. 66 Table 4.2.1 Number of women's co-wives . 67 Table 4.2.2 Number of men's wives . 68 Table 4.3 Age at first marriage . 69 Table 4.4 Median age at first marriage by background characteristics . 70 Table 4.5 Age at first sexual intercourse . 71 Table 4.6 Median age at first sexual intercourse by background characteristics . 72 Table 4.7.1 Recent sexual activity: Women . 73 Table 4.7.2 Recent sexual activity: Men . 75 Figure 4.1 Marital status . 62 Figure 4.2 Polygyny . 63 Figure 4.3 Median age at first marriage by education . 64 Figure 4.4 Median age at first sexual intercourse and first marriage among women and men . 64 FERTILITY.77 Table 5.1 Current fertility . 83 Table 5.2 Fertility by background characteristics . 84 Table 5.3 Trends in age-specific fertility rates . 85 Table 5.4 Children ever born and living . 85 Table 5.5 Birth intervals . 86 Table 5.6 Postpartum amenorrhea, abstinence, and insusceptibility . 87 Table 5.7 Median duration of amenorrhea, postpartum abstinence, and postpartum insusceptibility . 87 Table 5.8 Menopause . 88 Table 5.9 Age at first birth . 88 Table 5.10 Median age at first birth. 89 Table 5.11 Teenage pregnancy and motherhood . 90 Figure 5.1 Age-specific fertility rates by residence . 78 Figure 5.2 Total fertility by education . 78 Figure 5.3 Fertility by province . 78 Figure 5.4 Birth intervals . 79 Figure 5.5 Median age at first birth by education . 81 Tables and Figures • ix FERTILITY PREFERENCES .91 Table 6.1 Fertility preferences by number of living children . 95 Table 6.2.1 Desire to limit childbearing: Women . 96 Table 6.2.2 Desire to limit childbearing: Men . 97 Table 6.3 Ideal number of children by number of living children . 98 Table 6.4 Mean ideal number of children by background characteristics . 99 Table 6.5 Fertility planning status . 100 Table 6.6 Wanted fertility rates . 101 Figure 6.1 Desire to limit childbearing . 92 Figure 6.2 Ideal family size . 92 Figure 6.3 Ideal family size by number of living children . 93 Figure 6.4 Fertility planning status . 93 Figure 6.5 Wanted and Actual Fertility . 94 FAMILY PLANNING .103 Table 7.1 Knowledge of contraceptive methods . 112 Table 7.2 Knowledge of contraceptive methods by background characteristics . 113 Table 7.3 Current use of contraception by age . 114 Table 7.4 Current use of contraception by background characteristics . 115 Table 7.5 Timing of sterilization . 116 Table 7.6 Source of modern contraception methods . 116 Table 7.7 Use of social marketing brand pills and condoms . 117 Table 7.8 Informed choice . 118 Table 7.9 Twelve-month contraceptive discontinuation rates . 118 Table 7.10 Reasons for discontinuation . 119 Table 7.11 Knowledge of fertile period . 119 Table 7.12.1 Need and demand for family planning among currently married women . 120 Table 7.12.2 Need and demand for family planning among ever-married women . 121 Table 7.13 Future use of contraception . 122 Table 7.14.1 Exposure to family planning messages: Women . 123 Table 7.14.2 Exposure to family planning messages: Men . 124 Table 7.15 Contact of nonusers with family planning providers . 125 Figure 7.1 Knowledge of contraceptive methods . 104 Figure 7.2 Contraceptive use . 104 Figure 7.3 Use of modern methods by education . 105 Figure 7.4 Modern contraceptive use by province . 106 Figure 7.5 Source of modern contraceptive methods . 106 Figure 7.6 Demand for family planning . 108 Figure 7.7 Unmet need for family planning by province . 109 INFANT AND CHILD MORTALITY .127 Table 8.1 Early childhood mortality rates . 131 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 131 Table 8.3 Early childhood mortality rates by demographic characteristics . 132 Table 8.4 Perinatal mortality . 133 Table 8.5 High-risk fertility behavior . 134 Figure 8.1 Under-5 mortality by mother’s education . 129 Figure 8.2 Under-5 mortality by birth interval. 129 x • Tables and Figures MATERNAL HEALTH CARE .135 Table 9.1 Antenatal care . 144 Table 9.2 Number of antenatal care visits and timing of first visit . 145 Table 9.3 Components of antenatal care . 146 Table 9.4 Knowledge of symptoms of pregnancy complications . 147 Table 9.5 Men's participation during ANC visits . 148 Table 9.6 Tetanus toxoid injections . 149 Table 9.7 Place of delivery . 150 Table 9.8 Assistance during delivery . 151 Table 9.9 Timing of first postnatal checkup for the mother . 153 Table 9.10 Type of provider of first postnatal checkup for the mother . 154 Table 9.11 Timing of first postnatal checkup for the newborn . 155 Table 9.12 Type of provider of first postnatal checkup for the newborn . 156 Table 9.13 Problems in accessing health care . 157 Figure 9.1 Antenatal care coverage . 136 Figure 9.2 Components of antenatal care . 137 Figure 9.3 Institutional deliveries by education . 138 Figure 9.4 Institutional deliveries by province . 139 Figure 9.5 Delivery assistance . 139 Figure 9.6 Delivery assistance by wealth . 140 Figure 9.7 Postnatal care by place of delivery . 141 Figure 9.8 Women with at least one problem in accessing health care by education . 142 CHILD HEALTH .159 Table 10.1 Child’s size and weight at birth . 167 Table 10.2 Vaccinations by source of information . 168 Table 10.3 Vaccinations by background characteristics . 169 Table 10.4 Vaccinations in first year of life . 171 Table 10.5 Prevalence and treatment of symptoms of ARI . 172 Table 10.6 Prevalence and treatment of fever . 174 Table 10.7 Prevalence of diarrhea . 175 Table 10.8 Diarrhea treatment . 177 Table 10.9 Feeding practices during diarrhea . 179 Table 10.10 Knowledge of ORS packets or ORS pre-packaged liquids . 181 Table 10.11 Disposal of children’s stools . 182 Table 10.12 Knowledge of childhood illness . 183 Figure 10.1 Childhood vaccinations . 160 Figure 10.2 Vaccination coverage by province . 161 Figure 10.3 Vaccinations in first year of life . 162 Figure 10.4 Diarrhea prevalence by age . 163 Figure 10.5 Treatment of diarrhea . 164 Figure 10.6 Feeding practices during diarrhea . 165 Figure 10.7 Prevalence and treatment of childhood illnesses . 165 NUTRITION OF CHILDREN AND WOMEN .185 Table 11.1 Initial breastfeeding . 190 Table 11.2 Breastfeeding status by age . 192 Table 11.3 Median duration of breastfeeding . 193 Table 11.4 Foods and liquids consumed by children in the day or night preceding the interview . 194 Table 11.5 Infant and young child feeding (IYCF) practices . 195 Table 11.6 Micronutrient intake among children . 197 Tables and Figures • xi Table 11.7 Presence of iodized salt in household . 199 Table 11.8 Micronutrient intake among mothers. 200 Figure 11.1 Breastfeeding practices by age . 186 Figure 11.2 IYCF breastfeeding indicators . 187 Figure 11.3 IYCF indicators on minimum acceptable diet . 189 MALARIA .201 Table 12.1 Household possession of mosquito nets . 206 Table 12.2 Access to an insecticide-treated net (ITN) . 207 Table 12.3 Use of mosquito nets by persons in the household . 208 Table 12.4 Use of existing ITNs . 209 Table 12.5 Use of mosquito nets by children . 210 Table 12.6 Use of mosquito nets by pregnant women . 211 Table 12.7 Prevalence, diagnosis, and prompt treatment of children with fever . 212 Table 12.8 Source of advice or treatment for children with fever . 213 Table 12.9 Type of antimalarial drugs used . 214 Figure 12.1 Household Ownership of ITNs . 202 Figure 12.2 ITN Ownership by household wealth . 203 Figure 12.3 Access to ITNs . 203 Figure 12.4 Use of ITNs . 204 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOR .215 Table 13.1 Knowledge of AIDS . 224 Table 13.2.1 Source of knowledge on HIV/AIDS: Women . 225 Table 13.2.2 Source of knowledge on HIV/AIDS: Men . 226 Table 13.3 Knowledge of HIV prevention methods . 227 Table 13.4.1 Comprehensive knowledge about HIV/AIDS: Women . 228 Table 13.4.2 Comprehensive knowledge about HIV/AIDS: Men . 229 Table 13.5 Knowledge of prevention of mother to child transmission of HIV . 230 Table 13.6.1 Accepting attitudes toward those living with HIV/AIDS: Women . 231 Table 13.6.2 Accepting attitudes toward those living with HIV/AIDS: Men . 232 Table 13.7 Attitudes toward negotiating safer sexual relations with husband . 233 Table 13.8 Adult support of education about condom use to prevent AIDS . 234 Table 13.9.1 Coverage of prior HIV testing: Women . 235 Table 13.9.2 Coverage of prior HIV testing: Men . 236 Table 13.10 Male circumcision . 237 Table 13.11 Place of circumcision. 238 Table 13.12 Age at circumcision . 239 Table 13.13 Self-reported prevalence of sexually-transmitted infections (STIs) and STI symptoms . 240 Table 13.14 Prevalence of medical injections . 241 Table 13.15 Comprehensive knowledge about AIDS and of a source of condoms among young people . 242 Table 13.16 Age at first sexual intercourse among young people . 243 Table 13.17 Recent HIV tests among youth . 244 Figure 13.1 Knowledge of AIDS by wealth status . 216 Figure 13.2 Comprehensive knowledge of HIV . 216 Figure 13.3 Knowledge of HIV prevention methods . 217 Figure 13.4 HIV knowledge by education . 218 Figure 13.5 Knowledge of Mother-to- Child Transmission of HIV . 218 Figure 13.6 Women and men seeking treatment for STIs. 221 xii • Tables and Figures Figure 13.7 Early Sexual Initiation . 222 ADULT AND MATERNAL MORTALITY .245 Table 14.1 Completeness of information on siblings . 249 Table 14.2 Adult mortality rates . 249 Table 14.3 Adult mortality probabilities . 249 Table 14.4 Pregnancy-related mortality rates . 250 WOMEN’S EMPOWERMENT .251 Table 15.1 Employment and cash earnings of currently married women and men . 257 Table 15.2.1 Control over women's cash earnings and relative magnitude of women's cash earnings 258 Table 15.2.2 Control over men's cash earnings . 259 Table 15.3 Women's control over their own earnings and over those of their husbands . 260 Table 15.4.1 Ownership of assets: Women . 261 Table 15.4.2 Ownership of assets: Men . 262 Table 15.5 Participation in decision making . 263 Table 15.6.1 Women's participation in decision making by background characteristics . 264 Table 15.6.2 Men's participation in decision making by background characteristics . 265 Table 15.7.1 Attitude toward wife beating: Women . 266 Table 15.7.2 Attitude toward wife beating: Men . 268 Table 15.8 Indicators of women's empowerment . 269 Table 15.9 Current use of contraception by women's empowerment . 270 Table 15.10 Ideal number of children and unmet need for family planning by women's empowerment . 270 Table 15.11 Reproductive health care by women's empowerment. 271 Table 15.12 Early childhood mortality rates by women's status . 271 Figure 15.1 Women's and men's employment by age . 252 Figure 15.2 Control over women's earnings . 252 Figure 15.3 Ownership of assets . 253 Figure 15.4 Women's participation in decision making . 254 Figure 15.5 Attitudes towards wife beating . 255 DOMESTIC VIOLENCE .273 Table 16.1 Experience of physical violence . 282 Table 16.2 Experience of violence during pregnancy . 284 Table 16.3 Persons committing physical violence . 285 Table 16.4 Marital control exercised by husbands . 286 Table 16.5 Forms of spousal violence . 287 Table 16.6 Spousal violence by background characteristics . 288 Table 16.7 Spousal violence by husband's characteristics and empowerment indicators. 290 Table 16.8 Physical or sexual violence in the past 12 months by any husband . 291 Table 16.9 Experience of spousal violence by duration of marriage . 292 Table 16.10 Injuries to women due to spousal violence . 293 Table 16.11 Women's violence against their spouse by background characteristics . 294 Table 16.12 Women's violence against their spouse by husband’s characteristics and empowerment indicators . 295 Table 16.13 Help seeking to stop violence . 296 Table 16.14 Sources for help to stop the violence . 297 Figure 16.1 Violence during pregnancy by number of living children . 275 Figure 16.2 Types of Spousal violence . 277 Figure 16.3 Spousal violence by subnational unit . 278 Tables and Figures • xiii Figure 16.4 Spousal violence by subnational unit . 279 Figure 16.5 Help seeking by type of violence experienced . 280 FISTULA .299 Table 17.1 Fistula . 302 Table 17.2 Characteristics of labor reported as cause of fistula symptoms . 303 Table 17.3 Type of provider for treatment of fistula . 304 Table 17.4 Outcome of treatment of fistula . 304 Table 17.5 Reasons for not seeking treatment for fistula symptoms . 305 Figure 17.1 Knowledge of fistula by age . 299 Figure 17.2 Reported cause of fistula . 300 Figure 17.3 Outcome of fistula treatment . 301 Figure 17.4 Reason for not seeking treatment . 301 Foreword • xv FOREWORD he Afghanistan Demographic and Health Survey (AfDHS) 2015 is the first survey of its kind to be implemented in the country as part of the worldwide Demographic and Health Surveys (DHS) Program. It was implemented by the joint effort of the Central Statistical Organization (CSO) and the Ministry of Public Health (MoPH), with the objective of providing reliable, accurate, and up-to- date data for the country. We hope that information contained in this report will assist policymakers and program managers in monitoring and designing programs and strategies for improving maternal and child health and family planning services in Afghanistan. This report presents comprehensive, final outcomes of the findings of the survey. Users will find the information useful for program planning and evaluation. The 2015 AfDHS is a national sample survey that provides up-to-date information on fertility levels; marriage; fertility preferences; awareness and use of family planning methods; child feeding practices; nutrition, adult, and childhood mortality; awareness and attitudes regarding HIV/AIDS; women’s empowerment; and domestic violence. The target groups were women and men age 15-49 in randomly selected households across Afghanistan. In addition to presenting national estimates, the report provides estimates of key indicators for both the urban and rural areas in Afghanistan and the provinces. The success of the 2015 AfDHS was made possible by a number of organizations and individuals. In this regard, we appreciate the support of the United States Agency for International Development in Afghanistan (USAID) for funding the survey. We would like to extend our gratitude to the United Nations Children’s Fund (UNICEF) for providing technical support during the training. We also appreciate the valuable technical input provided by the Technical Committee and the Steering Committee during the different phases of the survey; these contributed to its successful implementation. Furthermore, the support and collaboration witnessed from the national and provincial administration, nongovernmental and international development organizations, and other major stakeholders is highly acknowledged. We are grateful to the 2015 AfDHS core team for managing technical, administrative, and logistical aspects of the survey; the master trainers, for their support in training and monitoring the fieldwork; the field staff, for data collection; the data processing team; and, in particular, the survey respondents. Similarly, we wish to express our appreciation to ICF for its technical assistance in all stages of the survey. We wish to also acknowledge Avais Hyder Liaquat Nauman (AHLN) Chartered Accountants for providing accounting and disbursement services that allowed for the timely and efficient transfer of project funds throughout the survey period. T Contributors to the Report • xvii CONTRIBUTORS TO THE REPORT Dr. Sayed Ataullah Saeedzai, General Director, Evaluation and Health Information System General Directorate, MoPH Dr. Said Iftekhar Sadaat, EHIS Advisor, Evaluation and Health Information System General Directorate, MoPH Sayed Ali Aqa Hashimi, Deputy Director of Field Operation, CSO Dr. Edris Ayazi, DHS Survey Manager, MoPH Ataullah Serajy, Health Statistics Manager, Demography Department, CSO Dr. Abdul Nasir Ikram, Project Management Specialist-Health, Office of Health and Nutrition, USAID Dr. Hafez Rasooli, National Influenza & Zoonotic Surveillance Manager, Surveillance Department, MoPH Dr Roqia Naser, Training officer, National EPI, MoPH Dr. Zohra Shamszai, MNH Manager, Reproductive Health Directorate, MoPH Dr. Samim Soroush, M&E and Research Coordinator, Reproductive Health Directorate, MoPH Dr. Nezamuddin Jalil, Learning & Coordination Manager, Reproductive Health Directorate, MoPH Dr. Rangina Aziz, RH Morbidity Officer, Reproductive Health Directorate, MoPH Dr. Naziha Ahmadi, FP Public Officer, Reproductive Health Directorate, MoPH Dr. Muhammad Naeem Habib, Malaria program coordinator, National Malaria & Leishmaniosis Control Program (NMLCP), MoPH Ahmad Fahim Haidari, Member of Population Research, Demography Department, CSO Dr. Abdul Baseer Sardar Qureshi, National Nutrition Surveillance Coordinator, Public Nutrition Department Dr. Younas Bargami, Program technical coordinator, National AIDS Control Program, MoPH Bahar Rasoly, EHIS officer, Evaluation and Health Information System General Directorate, MoPH Fatima Arifi, EHIS officer, Evaluation and Health Information System General Directorate, MoPH Abida Jafari, M&E Officer, Gender Directorate, MoPH Reading and Understanding Tables from the 2015 AFDHS • xix READING AND UNDERSTANDING THE 2015 AFDHS In 2016, The DHS Program began producing final reports with a new format and style. The new style features about 90 figures to highlight trends, subnational patterns, and background characteristics. The text has been simplified to highlight key points in bullets and to clearly identify indicator definitions in boxes. All of the standard tables that have historically been included in the DHS continue to be included in this new style. They are located at the end of each chapter. Each DHS final report is based on approximately 200 tables of data. 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, DHS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organization of DHS 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 DHS tables. xx • Reading and Understanding Tables from the 2015 AFDHS Example 1: Exposure to Mass Media A Question Asked of All Survey Respondents Table 3.4.1 Exposure to mass media: Women Percentage of ever-married women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Afghanistan 2015 Background characteristic Reads a news- paper at least once a week Watches tele- vision at least once a week Listens to 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 4.3 36.7 23.5 1.5 47.9 1,825 20-24 3.5 37.6 27.0 1.1 46.4 6,089 25-29 2.7 38.8 25.3 1.2 46.2 6,299 30-34 1.4 40.3 23.1 0.4 47.2 4,302 35-39 2.7 41.8 21.4 1.5 47.5 4,463 40-44 1.7 38.5 23.2 0.9 47.6 3,113 45-49 1.4 40.2 21.3 0.9 48.5 3,369 Residence Urban 7.6 71.1 26.3 3.2 20.7 6,870 Rural 1.0 29.6 23.2 0.4 55.1 22,591 Province1 Kabul 9.2 70.4 27.1 4.0 21.2 3,658 Kapisa 6.5 41.6 47.0 4.2 37.9 205 Parwan 1.8 20.5 36.0 0.2 50.9 625 Wardak 0.0 16.9 10.1 0.0 76.1 382 Logar 5.9 15.1 52.1 1.6 41.9 472 Nangarhar 2.3 31.2 18.6 1.0 59.0 794 Laghman 1.4 14.2 36.5 0.4 59.9 583 Panjsher 4.8 52.3 10.4 0.6 42.9 54 Baghlan 3.8 51.3 11.1 1.2 43.0 839 Bamyan 1.8 38.6 10.8 0.6 56.0 303 Ghazni 1.8 31.8 34.1 0.5 48.1 1,328 Paktika 0.0 7.2 40.4 0.0 55.5 792 Paktya 0.1 20.6 60.4 0.1 37.4 542 Khost 0.2 33.6 55.6 0.1 38.8 851 Kunarha 1.5 6.1 13.7 0.7 83.2 559 Nooristan 0.6 0.1 2.0 0.0 97.9 222 Badakhshan 1.0 12.8 5.5 0.8 85.7 1,004 Takhar 0.5 22.3 19.7 0.2 70.4 1,105 Kunduz 1.9 49.1 23.9 1.2 46.0 1,232 Samangan 1.3 20.3 6.8 0.8 77.4 330 Balkh 2.1 53.2 7.2 0.7 44.0 1,781 Sar-E-Pul 1.2 26.6 2.1 0.4 72.5 654 Ghor 0.5 39.3 16.5 0.3 55.9 715 Daykundi 0.3 11.9 1.2 0.2 87.2 329 Urozgan 0.0 5.7 20.8 0.0 77.4 230 Kandahar 0.8 16.2 55.8 0.2 40.0 2,227 Jawzjan 5.1 54.0 22.8 3.3 42.5 614 Faryab 2.5 76.8 5.9 1.3 20.9 2,114 Helmand 0.8 23.2 40.8 0.4 46.7 875 Badghis 0.3 6.8 2.4 0.2 92.1 650 Herat 1.9 55.6 12.5 0.7 37.7 2,316 Farah 0.2 38.6 28.9 0.1 46.6 777 Nimroz 1.4 57.3 1.1 0.0 42.3 278 Education No education 0.2 33.2 24.1 0.0 51.8 24,604 Primary 3.8 64.7 20.5 1.9 28.0 2,330 Secondary 18.4 70.2 22.0 6.3 21.7 1,971 More than secondary 43.4 89.1 40.4 24.9 6.1 556 Wealth quintile Lowest 0.3 22.1 10.9 0.1 71.0 5,904 Second 0.5 24.1 22.3 0.2 59.5 6,001 Middle 0.7 26.4 27.2 0.3 53.3 5,888 Fourth 1.9 48.2 30.7 0.6 34.8 6,010 Highest 9.6 77.0 28.8 4.3 15.4 5,657 Total 2.5 39.2 24.0 1.1 47.1 29,461 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 1 3 2 4 5 Reading and Understanding Tables from the 2015 AFDHS • xxi Step 1: Read the title and subtitle. They tell you the topic and the specific population group being described. In this case, the table is about ever-married women age 15-49 and their exposure to different types of media. All eligible ever-married 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 categorized. In this table, the first three columns of data show different types of media that ever-married women access at least once a week. The fourth column shows ever-married women who access all three media, while the fifth column is ever-married women who do not access any of the three types of media at least once a week. The last column lists the number of ever-married women 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 ever-married women’s exposure to media by age, urban-rural residence, province, educational level, and wealth quintile. Most of the tables in the AfDHS report will be divided into these same categories. Step 4: Look at the row at the bottom of the table highlighted in red. These percentages represent the totals of all ever-married women age 15-49 and their access to different types of media. In this case, 2.5%* of ever-married women age 15-49 read a newspaper at least once a week, 39.2% watch television weekly, and 24.0% listen to the radio weekly. Step 5: To find out what percentage of ever-married women with more than secondary education access all three media weekly, draw two imaginary lines, as shown on the table. This shows that 24.9% of ever- married women age 15-49 with more than secondary education access all three types of media weekly. Step 6: By looking at patterns by background characteristics, we can see how exposure to mass media varies across Afghanistan. Mass media are often used to communicate health messages. Knowing how mass media exposure varies among different groups can help program planners and policy makers 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 ever-married women in Afghanistan do not access any of the three media at least once a week? b) What age group of ever-married women are most likely to watch television weekly? c) Compare ever-married women in urban areas to ever-married women in rural areas—which group is more likely to read the newspaper weekly? d) What are the lowest and highest percentages (range) of ever-married women who do not access any of the three media at least once a week by province? e) Is there a clear pattern in exposure to television on a weekly basis by education level? f) Is there a clear pattern in exposure to radio on a weekly basis by wealth quintile? Answers: a) 47.1% b) Ever-married women age 35-39: 41.8% of ever-married women in this age group watch television weekly c) Ever-married women in urban areas, 7.6% listen to the radio weekly, compared to 1.0% of ever-married women in rural areas d) 20.9% of ever-married women in the Faryab province do not access any of the three media at least once a week, compared to 97.9% of ever-married women in Nooristan. e) Exposure to television on a weekly basis increases as a woman’s level of education increases; 33.2% of ever-married women with no education watch television weekly, compared to 89.1% of ever-married women with more than secondary education. f) There is no clear pattern in exposure to radio on a weekly basis by wealth quintile. Ever-married women in the lowest wealth quintile are least likely to listen to the radio on a weekly basis (10.9%) and ever-married women in the fourth wealth quintile are most likely to listen to the radio on a weekly basis (30.7%). xxii • Reading and Understanding Tables from the 2015 AFDHS Example 2 Prevalence and Treatment of Symptoms of ARI A Question Asked of a Subgroup of Survey Respondents Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, the percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks preceding the survey and among children with symptoms of ARI, the percentage for whom advice or treatment was sought from a health facility or provider and the percentage who received antibiotics as treatment, according to background characteristics, Afghanistan 2015 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 sought from a health facility or provider2 Percentage who received antibiotics Number of children Age in months <6 10.0 3,095 71.1 49.8 308 6-11 14.7 2,720 64.0 60.7 400 12-23 13.9 5,708 67.3 61.5 792 24-35 14.8 6,598 54.5 52.1 977 36-47 11.3 6,282 61.4 53.5 708 48-59 10.7 5,902 58.5 48.1 631 Sex Male 12.9 15,605 62.4 55.2 2,017 Female 12.2 14,699 60.4 53.4 1,800 Mother’s smoking status Smokes cigarettes/tobacco 13.2 769 61.2 60.3 101 Does not smoke 12.6 29,460 61.5 54.2 3,715 Missing 0.3 75 * * 0 Cooking fuel Electricity or gas 9.9 9,089 70.7 55.8 904 Kerosene * 1 * * 0 Coal/lignite 14.5 99 * * 14 Charcoal 4.5 176 * * 8 Wood/straw3 13.7 15,015 60.2 50.9 2,052 Animal dung 14.1 5,751 55.4 61.7 814 Other fuel 17.9 130 (41.9) (68.9) 23 No food cooked in household (4.0) 20 * * 1 Missing (1.0) 22 * * 0 Residence Urban 11.8 7,040 65.1 50.7 834 Rural 12.8 23,264 60.4 55.4 2,983 Province4 Kabul 6.9 3,677 52.8 47.4 252 Kapisa 15.8 211 50.7 54.2 33 Parwan 2.6 688 * * 18 Wardak 17.3 329 57.1 50.8 57 Logar 1.4 417 * * 6 Nangarhar 18.2 972 68.6 56.8 177 Laghman 16.0 770 76.3 58.5 124 Panjsher 0.9 39 * * 0 Baghlan 26.3 700 37.8 36.2 184 Bamyan 9.3 314 51.3 57.3 29 Ghazni 0.4 778 * * 3 Paktika 2.5 856 (93.0) (86.2) 21 Paktya 7.7 578 75.5 30.0 44 Khost 7.8 991 46.8 93.4 78 Kunarha 4.3 704 (49.4) (70.0) 31 Nooristan 9.1 303 47.1 49.0 28 Badakhshan 17.6 870 22.9 26.0 153 Takhar 9.2 1,187 34.2 65.9 110 Kunduz 9.4 1,177 60.8 75.5 111 Samangan 5.7 345 (74.7) (48.5) 20 Balkh 15.2 1,874 63.8 67.3 285 Sar-E-Pul 3.6 596 * * 21 Ghor 28.3 846 58.2 56.6 239 Daykundi 7.5 308 (12.2) (23.8) 23 Urozgan 6.7 385 93.5 66.5 26 Kandahar 24.0 2,751 60.1 50.4 660 Jawzjan 18.4 569 50.4 56.9 105 Faryab 10.0 2,281 66.7 96.8 229 Helmand 7.7 893 87.2 66.7 69 Badghis 13.5 723 61.6 75.4 97 Herat 27.3 2,046 85.6 33.1 558 Farah 2.4 810 (62.6) (49.6) 19 Nimroz 2.4 290 * * 7 (Continued…) 1 2 a b 4 Reading and Understanding Tables from the 2015 AFDHS • xxiii Table 10.5—Continued Background characteristic Among children under age five: Among children under age five with symptoms of ARI: Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought from a health facility or provider2 Percentage who received antibiotics Number of children Mother’s education No education 12.9 25,261 61.1 54.0 3,256 Primary 13.1 2,429 62.1 53.0 319 Secondary 9.5 2,130 63.9 64.1 203 More than secondary 7.9 484 (77.7) (47.6) 38 Wealth quintile Lowest 16.2 5,795 52.9 51.0 939 Second 11.9 6,185 65.6 56.4 737 Middle 12.8 6,398 56.3 51.2 821 Fourth 11.3 6,312 67.1 57.2 714 Highest 10.8 5,614 70.0 58.2 606 Total 12.6 30,304 61.5 54.4 3,817 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 consist of cough accompanied by short, rapid breathing that was chest-related and/or by difficult breathing that was chest-related. 2 Excludes pharmacy, shop, market, and traditional practitioner 3 Includes grass, shrubs, and crop residues 4 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under age five (a) and children under age five who had symptoms of acute respiratory infection (ARI) in the two weeks before the survey (b). Step 2: Identify the two panels. First, identify the columns that refer to all children under age five (a), and then isolate the columns that refer only to those children under age five who had symptoms of ARI in the two weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under age five had symptoms of ARI in the two weeks before the survey? It’s 12.6%. Now look at the second panel. How many children under age five are there who had symptoms of ARI in the two weeks before the survey? It’s 3,817 children or 12.6% of the 30,304 children under age five (with rounding). The second panel is a subset of the first panel. Step 4: Only 12.6% of children under age five had symptoms of ARI in the two 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 under age five in Kunarha province who had symptoms of ARI in the two weeks before the survey received antibiotics? 70.0%. 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 4.)  What percentage of children under age five in Nimroz province who had symptoms of ARI in the two weeks before the survey received antibiotics? There is no number in this cell—only an asterisk. This is because fewer than 25 children under age five in Nimroz province had symptoms of ARI in the two weeks before the survey. 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 3 xxiv • Reading and Understanding Tables from the 2015 AFDHS Example 3: Understanding Sampling Weights in AfDHS Tables A sample is a group of people who have been selected for a survey. In the AfDHS, 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 minimum sample size per area. For the 2015 AfDHS, the survey sample is representative at the national and provincial levels, and for urban and rural areas. To generate statistics that are representative of the country as a whole and the 33 provinces, the number of women surveyed in each province should contribute to the size of the total (national) sample in proportion to size of the province. However, if some provinces have small populations, then a sample allocated in proportion to each province’s population may not include sufficient women from each province for analysis. To solve this problem, provinces with small populations are oversampled. For example, let’s say that you have enough money to interview 29,461 women and want to produce results that are representative of Afghanistan as a whole and its provinces (as in Table 3.1). However, the total population of Afghanistan is not evenly distributed among the provinces: some provinces, such as Kabul, are heavily populated while others, such as Panjsher are not. Thus, Panjsher must be oversampled. A sampling statistician determines how many women should be interviewed in each province in order to get reliable statistics. The blue column (1) in the table at the right shows the actual number of women interviewed in each province. Within the provinces, the number of women interviewed ranges from 652 in Bamyan to 1,398 in Nooristan province. The number of interviews is sufficient to get reliable results in each province. With this distribution of interviews, some provinces are overrepresented and some provinces are underrepresented. For example, the population in Kabul is about 12% of the population in Afghanistan, while Panjsher’s population contributes only 0.2% of the population in Afghanistan. But as the blue column shows, the number of women interviewed in Kabul accounts for only about 2.5% of the total sample of women interviewed (755/29,461) and the number of women interviewed in Panjsher accounts for almost the same percentage of the total sample of women interviewed (2.3%, or 681/29,461). This unweighted distribution of women does not accurately represent the population. In order to get statistics that are representative of Afghanistan, 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 province, Panjsher, should only contribute a small amount to the national Table 3.1 Background characteristics of respondents Percent distribution of ever-married women age 15-49 by selected background characteristics, Afghanistan 2015 Women Background characteristic Weighted percent Weighted number Unweighted number Province1 Kabul 12.4 3,658 755 Kapisa 0.7 205 874 Parwan 2.1 625 744 Wardak 1.3 382 870 Logar 1.6 472 915 Nangarhar 2.7 794 1,023 Laghman 2.0 583 800 Panjsher 0.2 54 681 Baghlan 2.8 839 740 Bamyan 1.0 303 652 Ghazni 4.5 1,328 1,146 Paktika 2.7 792 1,110 Paktya 1.8 542 1,174 Khost 2.9 851 1,338 Kunarha 1.9 559 734 Nooristan 0.8 222 1,398 Badakhshan 3.4 1,004 835 Takhar 3.8 1,105 819 Kunduz 4.2 1,232 839 Samangan 1.1 330 682 Balkh 6.0 1,781 909 Sar-E-Pul 2.2 654 812 Ghor 2.4 715 886 Daykundi 1.1 329 669 Urozgan 0.8 230 805 Kandahar 7.6 2,227 952 Jawzjan 2.1 614 865 Faryab 7.2 2,114 742 Helmand 3.0 875 843 Badghis 2.2 650 875 Herat 7.9 2,316 989 Farah 2.6 777 1,133 Nimroz 0.9 278 680 Total 100.0 29,461 29,461 Note: Education categories refer to the highest level of education attended. 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 3 2 1 Reading and Understanding Tables from the 2015 AFDHS • xxv total. Women from a large province, like Kabul, should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” which is used to adjust the number of women from each province so that each province’s contribution to the total is proportional to the actual population of the province. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at provincial level. The total national sample size of 29,461 women has not changed after weighting, but the distribution of the women in the provinces 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 red column (3) to the actual population distribution of Afghanistan, you would see that women in each province 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 Kabul and the proportion of women who live in Panjsher. With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and provincial levels. In general, only the weighted numbers are shown in each of the AfDHS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of women interviewed. Additional DHS Program Resources • xxvii ADDITIONAL DHS PROGRAM RESOURCES The DHS Program Website – Download free DHS reports, standard documentation, key indicator data, and training tools, and view announcements. DHSprogram.com STATcompiler – Build custom tables, graphs, and maps with data from 90 countries and thousands of indicators. Statcompiler.com DHS Program Mobile App – Access key DHS indicators for 90 countries on your mobile device (Apple, Android, or Windows). Search DHS Program in your iTunes or Google Play store DHS Program User Forum – Post questions about DHS data, and search our archive of FAQs. userforum.DHSprogram.com Tutorial Videos – Watch interviews with experts and learn DHS basics, such as sampling and weighting, downloading datasets, and How to Read DHS Tables. www.youtube.com/DHSProgram Datasets – Download DHS datasets for analysis. DHSprogram.com/Data Spatial Data Repository – Download geographically linked health and demographic data for mapping in a geographic information system (GIS). spatialdata.DHSprogram.com Social Media – Follow The DHS Program and join the conversation. Stay up to date through: Facebook www.facebook.com/DHSprogram Twitter www.twitter.com/ DHSprogram Pinterest www.pinterest.com/ DHSprogram LinkedIn www.linkedin.com/ company/dhs-program YouTube www.youtube.com/DHSprogram Blog Blog.DHSprogram.com Acronyms and Abbreviations • xxix ACRONYMS AND ABBREVIATIONS ACT artemisinin-based combination therapy AfDHS Afghanistan Demographic and Health Survey AFGA Afghan Family Guidance Association AIDS acquired immunodeficiency syndrome ANC antenatal care ANDS Afghanistan National Development Strategy ARI acute respiratory infection ART antiretroviral therapy ASFR age-specific fertility rate BCG Bacille-Calmette-Guerin vaccine against tuberculosis BPHS basic package of health services BMI body mass index CBMM community based management of malaria CHC comprehensive health center CPR contraceptive prevalence rate CSO Central Statistics Organization DHS Demographic and Health Survey DPT Diphtheria, pertussis, and tetanus vaccine EA enumeration area EPI Expanded Program on Immunization EVAW elimination of violence against women GAR gross attendance ratio GFR general fertility rate GPI gender parity index HIV human immunodeficiency virus HMIS health management information system ICPD International Conference on Population and Development IRB institutional review board ITN insecticide-treated net IUD intrauterine device IYCF infant and young child feeding LAM lactational amenorrhea method LLIN long-lasting insecticide-treated bed net LPG liquid petroleum gas MAD minimum acceptable diet MDGs Millennium Development Goals MMR maternal mortality ratio MoPH Ministry of Public Health xxx • Acronyms and Abbreviations MTCT mother-to-child transmission NAPWA National Action Plan for Women of the Afghanistan NAR net attendance ratio NGO nongovernmental organization NMLCP National Malaria and Leishmaniosis Control Program NN neonatal mortality NNS national nutrition survey NTG national treatment guideline OPV oral polio vaccine ORS oral rehydration salts ORT oral rehydration therapy PAHO Pan American Health Organization PCV Pneumococcal conjugate vaccine PHD provincial health directorate PNN postneonatal mortality PSOs provincial statistical officers PSU primary sampling unit RHF recommended homemade fluids RMNCA reproductive, maternal, neonatal, child, and adolescent SP sulfadoxine/pyrimethamine STI sexually transmitted infection TB tuberculosis TFR total fertility rate TWFR total wanted fertility rate UN United Nations UNAIDS Joint United Nations Programme on HIV/AIDS UNDP United Nations Development Program UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD vitamin A deficiency VIP ventilated improved pit WHO World Health Organization xxxii • Map of Afghanistan Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 he 2015 Afghanistan Demographic and Health Survey (AfDHS) was implemented by the Central Statistics Organization (CSO) and the Ministry of Public Health (MoPH). Data collection took place from June 15, 2015, to February 23, 2016. 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. The United Nations Children’s Fund (UNICEF) facilitated the successful implementation of the survey through its technical support. 1.1 SURVEY OBJECTIVES The primary objective of the 2015 AfDHS project is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the AfDHS collected information on knowledge and practice of family planning, fertility levels, marriage, fertility preferences, child feeding practices, nutritional status of children and women, childhood mortality, maternal and child health, awareness and attitudes regarding HIV/AIDS, knowledge about other illnesses (e.g., tuberculosis, hepatitis B and C), and domestic violence. The information collected through the AfDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population. 1.2 SAMPLE DESIGN The sampling frame used for the 2015 AfDHS is an updated version of the Household Listing Frame, prepared in 2003-04 and updated in 2009, provided by the Central Statistics Organization (CSO). The sampling frame had information on 25,974 enumeration areas (EAs). An EA is a geographic area consisting of a convenient number of dwelling units that serve as counting units for the census. The sampling frame contained information about the location (province, district, and control area), the type of residence (urban or rural), and the estimated number of residential households for each of the 25,974 EAs. Satellite maps were also available for each EA, which delimited the geographic boundaries of the area. The sampling frame excluded institutional populations such as persons in hotels, barracks, and prisons. The 2015 AfDHS followed a stratified two-stage sample design and was intended to allow estimates of key indicators at the national level, in urban and rural areas, and for each of the 34 provinces of Afghanistan. The first stage involved selecting sample points (clusters) consisting of EAs. A total of 950 clusters were selected, 260 in urban areas and 690 in rural areas. It was recognized that some areas of the country might be difficult to reach because of ongoing security issues. Therefore, to mitigate the situation, reserve clusters were selected in all of the provinces to replace the inaccessible clusters. The 101 reserve clusters that were preselected did not exceed 10% of the selected clusters in the province. The second stage involved systematic sampling of households. A household listing operation was undertaken in all of the selected clusters, and a fixed number of 27 households per cluster were selected through an equal probability systematic selection process, for a total sample size of 25,650 households. Because of the approximately equal sample size in each province, the sample is not self-weighting at the national level, and weighting factors have been calculated, added to the data file, and applied so that results are representative at the national level. All ever-married women age 15-49 who were either permanent residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. In half of the households, all ever-married men age 15-49 who were either residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. T 2 • Introduction and Survey Methodology During the household listing operation, more than 70 selected clusters were identified as insecure. Therefore, a decision was made to carry out the household listing operation in all of the 101 preselected reserve clusters, which also accounted for the possibility of identifying more insecure clusters during data collection. Household listing was successfully completed in 976 of 1,051 clusters. Overall, the survey was successfully carried out in 956 clusters.1 1.3 QUESTIONNAIRES Three questionnaires were used for the 2015 AfDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires, based on the DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Afghanistan. Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, the questionnaires were translated into Dari and Pashto. The survey protocol and the questionnaires were approved by the ICF Institutional Review Board (IRB) and the Ministry of Public Health of Afghanistan. The Household Questionnaire listed all household members and visitors; basic information was collected on their age, sex, education, relationship to the head of the household, marital status, and, for children under age 18, parents’ survival status. Data on age and sex were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on the characteristics of the household’s dwelling unit, such as water source, toilet facilities, fuel use, and flooring materials, as well as on possessions such as durable goods and mosquito nets. In addition, a small sample of salt was requested from each household, and the sample was tested for iodine content using a rapid test kit. The Woman’s Questionnaire was administered to all ever-married women age 15-49 in the selected households. These women were asked questions on the following topics:  Background characteristics (including age, education, and media exposure)  Birth history and child 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  Women’s work and husbands’ background characteristics  Awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs)  Adult and maternal mortality  Knowledge, attitudes, and behavior related to other health issues (e.g., tuberculosis, hepatitis, fistula)  Domestic violence (questions asked of one woman per household) The Man’s Questionnaire was administered to all ever-married men age 15-49 in the subsample of households selected for the male survey. The Man’s Questionnaire collected much of the same information found in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health. 1 Because of extreme security issues in rural areas of Zabul, only seven urban clusters could be covered. Consequently, it is not possible to provide provincial-level estimates for Zabul; however, the information collected from this province is included in national-level estimates. Introduction and Survey Methodology • 3 1.4 PRETEST Eleven women and 16 men participated in training to pretest the AfDHS survey protocol over a three-week period in March 2015. The participants were staff of CSO and MoPH from various departments, including CSO Field Operations, Database, Census, Sampling, Cartography, and Demography and MoPH Monitoring and Evaluation. Twelve days of classroom training was provided. The training was led by The DHS Program staff, supported by the in-country AfDHS core team that translated the sessions into Dari and Pashto. Furthermore, resource persons from MoPH and UNICEF attended the sessions to provide technical background on topics such as family planning, reproductive health, child health, and salt testing for iodine. The fieldwork for the pretest was carried out in four locations in and around Kabul. There were four teams deployed: two teams for testing the Dari language questionnaires and two teams for testing the Pashto language questionnaires. Following the field practice, a debriefing session was held with the pretest field staff, and modifications to the questionnaires were made based on lessons drawn from the exercise. 1.5 TRAINING OF TRAINERS The training of trainers was conducted from May 9-13, 2015, for the master trainers, who had earlier participated in the pretest training in March 2015. The purpose of the training was to prepare the master trainers for the main training. Seventeen master trainers were selected, based on their performance, from among the individuals who participated in the pretest. The DHS Program survey manager facilitated the session, highlighting the concept of adult learning principles and guidelines on conducting effective training. As the participants had gone through the pretest training and fieldwork, they were well versed in the components of the AfDHS. The training focused on key components such as interview techniques and procedures for completing the AfDHS questionnaires; birth history, family planning, and contraceptive calendar; and completing the vaccination section. The participants worked in groups to develop teach- backs on these topics using various training techniques. They were encouraged to develop participatory methods for the training. Several tests were carried out, which also helped them design test questions for the main training. 1.6 TRAINING OF FIELD STAFF The CSO recruited and trained 300 people for the main fieldwork to serve as supervisors, field editors, interviewers, and reserve interviewers. Additionally, five staff from MoPH joined the training to serve as fieldwork monitors and secondary editors. The field staff main training took place from May 21 to June 13, 2015, at Rana University in Kabul. The training course consisted of instruction regarding interviewing techniques and field procedures, a detailed review of questionnaire content, instruction on how to administer the paper questionnaires, mock interviews between participants in the classroom, and practice interviews with real respondents in areas outside the sample points selected for the survey. The main fieldwork training was led by the master trainers and backstopped by The DHS Program trainers. The sessions included discussing concepts, procedures, and methodology of conducting the survey. Participants were guided through the questionnaires. Furthermore, resource persons from the MoPH and UNICEF attended the sessions to provide technical input. The master trainers used various techniques they had learned to facilitate the training sessions. These techniques included presentations, lectures, hands-on exercises, mock interviews, role plays, group work, and quizzes. In-class exercises included probing for age, checking age consistencies, filling out vaccination cards, completing the reproductive calendar, and practicing interviews. The trainees were taken for field practice twice in the nonsampled areas of Kabul district, where they had an opportunity to implement the survey in a real-world situation. Participants were evaluated through in-class exercises, quizzes, and observations made during field practice. Ultimately, 33 supervisors and 33 field editors were identified based on their performance. Similarly, 198 participants were selected to serve as interviewers while the rest were kept as reserves. The 4 • Introduction and Survey Methodology supervisors and field editors received additional training in data quality control procedures, fieldwork coordination, and management. 1.7 FIELDWORK Data collection was carried out by 33 field teams, each consisting of one team supervisor, one field editor, three female interviewers, and three male interviewers. However, the team composition had to be adjusted during the different phases of the fieldwork operation because of security challenges (see below). Data collection took place from June 15, 2015, through February 23, 2016, although most of the teams completed the fieldwork by November 2015. The extension of fieldwork in some provinces was due to the ongoing unrest and insurgency in the provinces of Kunduz, Helmand, Faryab, Badghis, and Ghazni. In the case of Badakhshan, the team had to pass through Tajikistan to access the clusters; this entailed getting visa approval, which took more than 3 months. Despite substantial challenges in the field, the AfDHS field teams successfully completed the fieldwork. Fieldwork monitoring was an integral part of the AfDHS, and five rounds of monitoring were carried out by the AfDHS core team and the 17 master trainers. Two levels of monitoring strategies were identified: technical monitoring and coverage monitoring. The technical monitoring was carried out by the AfDHS core team and the master trainers, while the coverage monitoring was carried out by provincial statistical officers (PSOs) and the Provincial Health Directorate (PHD) of MoPH. The monitors were provided with guidelines for overseeing the fieldwork. 1.7.1 Fieldwork Challenges A number of challenges were faced by the field teams during data collection, especially in provinces under the control of the insurgents. There was a need to get support from security officers and local civil elders to obtain access to the selected clusters. This process delayed the fieldwork schedule. Due to security concerns, in some areas the teams could not collect data as a group but had to split into smaller groups, which hindered efficient management of the fieldwork. One such case was Zabul, where complete data were gathered for only seven urban clusters. Consultative meetings with security officers, civil agencies, and the Zabul local government were arranged, as most of the districts in this province were under the control of the insurgents, making data collection impossible. Thus, this survey cannot provide provincial estimates for Zabul. In provinces such as Kunduz, Helmand, Badakhshan, Ghazni, Faryab, Nooristan, Baghlan, and Kunarha, the household listing operation was delayed as a result of security challenges, which impacted data collection. In addition, the teams faced mobility problems due to security issues and tough terrain. Consequently, the fieldwork in these areas was prolonged, but the data collection was completed. There were unique problems in Badakhshan as, due to security concerns and weather conditions, four clusters could not be accessed through Afghanistan. The household listing team and the data collection team had to move together to access these clusters through Tajikistan. It was very difficult to find suitable candidates for data collection in Helmand, Zabul, and Urozgan. These provinces had to be covered by interviewers from the nearby provinces. 1.8 DATA PROCESSING The processing of the 2015 AfDHS data began simultaneously with the fieldwork. All completed questionnaires were edited immediately while in the field by the field editors and checked by the supervisors before being dispatched to the data processing center at the CSO central office in Kabul. These completed questionnaires were edited and entered by 23 data processing personnel specially trained for this task. All data were entered twice for 100% verification. Data were entered using the CSPro computer Introduction and Survey Methodology • 5 package. The concurrent processing of the data offered a distinct advantage, because it maximized the likelihood of the data being error-free and authentic. Moreover, the double entry of data enabled easy comparison and identification of errors and inconsistencies. Inconsistencies were resolved by tallying with the paper questionnaire entries. The secondary editing of the data was completed in the first week of March 2016. The final cleaning of the data set was carried out by The DHS Program data processing specialist and was completed by mid-April 2016. 1.9 RESPONSE RATES A total of 25,741 households were selected for the sample, of which 24,941 were occupied during the survey fieldwork (Table 1.1). Of the occupied households, 24,395 were successfully interviewed, yielding a response rate of 98%. In the interviewed households, 30,434 ever-married women age 15-49 were identified for individual interviews; interviews were completed with 29,461 of these women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 11,778 ever-married men age 15-49 were identified and 10,760 were successfully interviewed, yielding a response rate of 91%. The lower response rate for men was likely due to their more frequent and longer absences from the household. The response rates are lower in urban areas than in rural areas. The difference is more prominent for men than women, as men in the urban areas are often away from their households for work. Moreover, given the security situation in the country, the field teams could not carry out interviews in the late evenings when more men are at home. Table 1.1 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Afghanistan 2015 Residence Total Result Urban Rural Household interviews Households selected 6,977 18,764 25,741 Households occupied 6,663 18,278 24,941 Households interviewed 6,391 18,004 24,395 Household response rate1 95.9 98.5 97.8 Interviews with women age 15-49 Number of eligible women 7,396 23,038 30,434 Number of eligible women interviewed 7,025 22,436 29,461 Eligible women response rate2 95.0 97.4 96.8 Interviews with men age 15-49 Number of eligible men 2,771 9,007 11,778 Number of eligible men interviewed 2,333 8,427 10,760 Eligible men response rate2 84.2 93.6 91.4 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 7 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings  Drinking water: Sixty-five percent of household in Afghanistan have access to an improved source of drinking water.  Sanitation: Twenty-five percent of households in Afghanistan have improved toilet facilities.  Household population and composition: The population of Afghanistan remains young, with 47% under age 15 (male 48% and female 46%).  Birth registration: About two in five children under age 5 (42%) had their births registered with the government.  Orphans: Among children under age 18, 4% are orphans (that is, one or both parents are dead).  School attendance: The net attendance ratio falls from 60% in primary school to 38% in secondary school. Boys are much more likely to attend both primary and secondary school than girls. nformation on the socioeconomic characteristics of the household population in the 2015 AfDHS provides a context to interpret demographic and health indicators and can furnish an approximate indication of the representativeness of the survey. In addition, this information sheds light on the living conditions of the population. This chapter presents information on source of drinking water, sanitation, exposure to smoke inside the home, relative wealth, hand washing, household population and composition, educational attainment, school attendance, birth registration, and family living arrangements. 2.1 DRINKING WATER SOURCES AND TREATMENT Improved sources of drinking water Include piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, and bottled water. Sample: Households Improved drinking water sources protect against outside contamination so that water is more likely to be safe to drink. Overall, 65% of households in Afghanistan have access to an improved source of drinking water. Eighty-six percent of urban households have access to an improved drinking water source, in contrast to only 58% of rural households (Table 2.1). Access to an improved water source varies by province (Figure 2.1). I 8 • Housing Characteristics and Household Population Figure 2.1 Households with improved water sources Percentage of households Urban and rural households rely on different sources of drinking water. Twenty-one percent of urban households have piped water in their dwelling or yard, while 11% use public taps and 29% use tube wells or boreholes (Figure 2.2). In contrast, only 2% of rural households have piped water in their dwelling or yard. Rural households mainly rely on tube wells or boreholes and protected dug wells (17% each). Only 35% of rural households have a water source on the premises, as compared with 77% of urban households. Seventeen percent of rural residents travel 30 minutes or longer roundtrip to fetch drinking water. Clean water is a basic need for human life. Most households (90%) report that they do not treat their water prior to drinking. Twelve percent of urban households and 4% of rural households treat their drinking water. Appropriate treatment methods include boiling, adding bleach/chlorine, filtering, and solar disinfecting (Table 2.1). 2.2 SANITATION Improved toilet facilities Include any non-shared toilet of the following types: flush/pour flush toilets to piped sewer systems, septic tanks, and pit latrines; ventilated improved pit (VIP) latrines; pit latrines with slabs; and composting toilets. Sample: Households Figure 2.2 Household drinking water by residence 21 2 7 11 15 14 29 17 20 25 23 23 12 40 33 Urban Rural All Unimproved source Protected well or spring Tubewell or borehole Public tap/standpipe Piped water into dwelling/yard/plot Percent distribution of households by source of drinking water Housing Characteristics and Household Population • 9 One-fourth of households in Afghanistan have access to improved toilet facilities. More than half of the households in urban areas (52%) have access to improved toilet facilities, as compared with only 16% of rural households (Figure 2.3). Thirteen percent of households do not have any toilet facility. In urban areas, improved toilet facilities generally consist of some kind of flush or pour flush toilet. In rural areas, they are mostly VIP pit latrines or pit latrines with slabs or composting toilets (Table 2.2). Three-fourths of rural households (75%) have unimproved toilet facilities or no toilet facilities at all, which increases the risk of disease transmission. Traditional dry vault toilets are the most common non-improved facility, used by half of rural households. 2.3 OTHER HOUSEHOLD CHARACTERISTICS Exposure to smoke inside the home, either from cooking with solid fuels or from smoking tobacco, has potentially harmful health effects. Sixty-seven percent of households in Afghanistan use some type of solid fuel for cooking. The majority of households in urban areas use liquefied petroleum gas (LPG) or natural gas (83%), but in rural areas most households use solid fuel (84%) such as wood, animal dung, or straw/shrubs/grass (Table 2.3). Exposure to cooking smoke is greater when cooking takes place inside the house rather than in a separate building or outdoors. In Afghanistan, cooking is done inside the home in more than half (55%) of households. Additionally, in 19% of households someone smokes inside the house daily. The survey also collected data on access to electricity, flooring materials, and the number of rooms used for sleeping. Seventy-two percent of households in Afghanistan have electricity, with a large urban-rural divide; 93% of urban households and 64% of rural households have electricity. Carpet is the most common material for flooring (56%). Overall, 48% of households reported having three or more rooms for sleeping (Table 2.3). 2.4 HOUSEHOLD WEALTH 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, in addition to 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 his or her score, and then dividing the distribution into five equal categories, each comprising 20% of the population. Sample: Households In Afghanistan, the wealthiest households are concentrated in urban areas. Almost all of the urban population falls in the fourth and highest wealth quintiles, while most of the rural population is in the three lowest wealth quintiles (Figure 2.4). Figure 2.3 Household toilet facilities by residence 52 16 25 17 5 8 29 58 50 2 17 13 4 3 Urban Rural All Other No facility/bush/field Unimproved facility Shared facility Improved facility Percent distribution of households by type of toilet facilities 10 • Housing Characteristics and Household Population There are large provincial variations in wealth. In Kabul, 67% of the population is concentrated in the highest wealth quintile, while a large majority of the population in Ghor (76%), Bamyan (69%), and Daykundi (65%) is concentrated in the lowest wealth quintile (Table 2.5). Household Durable Goods The survey also collected information on household effects, means of transportation, agricultural land, farm animals, and bank accounts. Urban households are more likely than rural households to own a television (84% versus 39%), a mobile telephone (94% versus 85%), a refrigerator (51% versus 8%), and a computer (28% versus 5%). In contrast, 78% of rural households own farm animals. For complete information on household possessions, see Table 2.4. 2.5 HAND WASHING To obtain hand washing information, interviewers asked to see the place where members of the household most often washed their hands. Soap and water—the ideal hand washing agents—were observed in 36% of households; another 28% had water only (Table 2.6). Some 28% of households did not have water, soap, or any other cleaning agent. These results probably overstate the availability of cleaning agents because they exclude 15% of urban and 28% of rural households where interviewers were unable to observe the place where household members usually wash their hands. The most common reason for this was that there was no designated place for hand washing. Urban households were almost three times as likely as rural households to have soap and water at the usual place for hand washing. The availability of soap and water increased with increasing wealth. Households in the highest wealth quintile were almost seven times as likely as those in the lowest quintile to have soap and water. 2.6 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. Figure 2.4 Household wealth by residence 3 26 2 26 4 25 18 21 73 3 Urban Rural Percent distribution of de jure population by wealth quintiles Wealthiest Fourth Middle Second Poorest Housing Characteristics and Household Population • 11 A total of 192,389 individuals stayed overnight in the 24,395 interviewed households in the 2015 AfDHS. Forty-nine percent of them (93,963) were female, and 51% (98,426) were male (Table 2.7). The population pyramid in Figure 2.5 shows their distribution by five-year age groups and sex. The broad base of the pyramid indicates that Afghanistan’s population is young, which is typical of countries with high fertility rates. Forty-seven percent of the population is under age 15, while 3% of residents are age 65 or older (Table 2.7). The average size of households in Afghanistan is 8.0 persons (Table 2.8). Urban households are slightly smaller than rural households (7.7 persons versus 8.2 persons). Men head most of Afghan households (98%), with only 2% of households headed by women. 2.7 BIRTH REGISTRATION Registered birth Child has a birth certificate or his or her birth has been registered with the civil authority. Sample: De jure children under age 5 Forty-two percent of children under age 5 had their births registered with the civil authority at the time of the survey, and 20% had a birth certificate (Table 2.9). Boys and girls are equally likely to have their births registered and to have a birth certificate. There is evidence that registration may have improved recently: half of children under age 2 were registered, as compared with 38% of those age 2-4. Registration of births varies widely across provinces. Children are most likely to have their births registered in Badghis (78%) and least likely in Nooristan (less than 1%). Birth registration increases with increasing household wealth (Figure 2.6). 2.8 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents dead Sample: Children under age 18 Figure 2.5 Population pyramid Figure 2.6 Birth registration by wealth 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 261210 30 31 35 48 70 42 Lowest Second Middle Fourth Highest Total Percentage of children under age 5 whose births are registered with the civil authorities WealthiestPoorest 12 • Housing Characteristics and Household Population Four percent of Afghan children under age 18 are orphaned, meaning that one or both of their parents are dead (Table 2.10). The proportion of orphaned children increases rapidly with age, rising from 1% among children under age 2 to 10% among children age 15-17 (Figure 2.7). Nine in 10 children under age 18 live with both of their parents (94%). Children age 10-14 whose parents are alive and who are living with at least one parent are more likely to attend school than those whose parents are deceased (67% versus 55%) (Table 2.11). 2.9 EDUCATION 2.9.1 Educational Attainment Median educational attainment Number of years of schooling completed by half of the population. Sample: De facto household population age 6 and older In Afghanistan, 57% of males age 6 and over have ever attended school, almost double the 31% of females (Tables 2.12.1 and 2.12.2). Only 4% of women and 10% of men have completed secondary school or gone beyond secondary school. The median number of years of schooling completed for women and men is 0.0 and 1.6 years, respectively. Patterns by background characteristics  Urban residents are much more likely to have completed secondary school than rural residents. Among women in urban households, 10% have completed secondary school, as compared with 2% of women in rural households. Similarly, 19% of men in urban areas have completed secondary school, compared with 8% of men in rural areas.  Educational attainment increases with increasing household wealth among both women and men. Thirteen percent of women in the wealthiest households have completed secondary school, as compared with 1% of women in the poorest households.  Educational attainment varies by province. Urozgan has the lowest level of educational attainment, with 96% of women and 79% of men having no education. For more details, see Table 2.12.1 and Table 2.12.2. 2.9.2 School Attendance Net attendance ratio (NAR) Percentage of the school age population that attends primary or secondary school. Sample: Children age 7-12 for primary school NAR and children age 13-18 for secondary school NAR Gross attendance ratio (GAR) The total number of primary and secondary school students expressed as a percentage of the official primary and secondary school age population. Sample: Children age 7-12 for primary school GAR and children age 13-18 for secondary school GAR Figure 2.7 Orphanhood by age 1 2 3 6 10 4 <2 2-4 5-9 10-14 15-17 0-17 Percentage of children under age 18 with one or both parents dead, by age of child Age in years Housing Characteristics and Household Population • 13 Sixty-nine percent of boys and 50% of girls age 7-12 attend primary school (Table 2.13). The net attendance ratio drops in secondary school: only 50% of boys and 25% of girls age 13-18 attend secondary school. Patterns by background characteristics  Urban children are considerably more likely than rural children to attend both primary and secondary school (Table 2.13).  There are large differences in secondary school attendance by province. Attendance ranges from 16% for boys in Urozgan and 2% for girls in Paktika to 76% for boys and 51% for girls in Panjsher (Table 2.13).  Children in the highest wealth quintile are more likely than those in the lowest quintile to attend primary school (76% versus 57%) (Table 2.13).  The net attendance ratio for secondary school increases with increasing wealth among both girls and boys, from 16% in the lowest quintile to 44% in the highest quintile for girls and from 38% in the lowest quintile to 64% in the highest quintile for boys (Figure 2.8). Other Measures of School Attendance The survey also collected data on two other indicators. The gross attendance ratio (GAR), which measures participation at each level of schooling among all persons age 5-24, is 78% at the primary school level and 49% at the secondary school level. This indicates that children outside the official school age population for a given level are attending school. The gender parity index (GPI), which is the ratio of female to male attendance rates, is 0.7 for primary school and 0.5 for secondary school. That is, there are about two girls per three boys in primary school and one girl per two boys in secondary school. For complete information on these indicators, see Table 2.13. 2.9.3 Reasons for Not Attending School The survey included questions on why children had never attended school and why those who had attended school but were not attending at the time of the survey had stopped attending. Among de facto household members age 5-24 who had never attended school, the most common reason given was that their parents simply did not send them to school (48% of females and 19% of males). Distance to school was also a common reason. The need to work or earn money was more often cited as a reason for boys never attending school than for girls (Table 2.14). Table 2.15 shows the percent distribution of the de facto population age 5-24 who dropped out of school by reasons for dropping out, according to sex and place of residence. The main reasons for males dropping out of school are the need to work (44%) and the need to help at home (15%). Among females, 30% dropped out because their parents did not send them to school, while 19% dropped out because they got married. Figure 2.8 Secondary school attendance by wealth 16 17 17 29 44 25 38 46 44 55 64 50 Lowest Second Middle Fourth Highest Total Girls Boys WealthiestPoorest Net attendance ratio for secondary school among children age 13-18 14 • Housing Characteristics and Household Population LIST OF TABLES For more information on household population and housing characteristics, see the following tables:  Table 2.1 Household drinking water  Table 2.2 Household sanitation facilities  Table 2.3 Household characteristics  Table 2.4 Household possessions  Table 2.5 Wealth quintiles  Table 2.6 Hand washing  Table 2.7 Household population by age, sex, and residence  Table 2.8 Household composition  Table 2.9 Birth registration of children under age 5  Table 2.10 Children’s living arrangements and orphanhood  Table 2.11 School attendance by survivorship of parents  Table 2.12.1 Educational attainment of the female household population  Table 2.12.2 Educational attainment of the male household population  Table 2.13 School attendance ratios  Table 2.14 Reasons for children never attending school  Table 2.15 Reasons for children dropping out of school Housing Characteristics and Household Population • 15 Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Afghanistan 2015 Households Population Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 86.3 58.0 65.3 86.4 59.9 66.4 Piped into dwelling/yard/plot 21.0 2.4 7.2 19.4 2.5 6.6 Public tap/standpipe 10.6 15.4 14.2 11.0 16.7 15.3 Tube well or borehole 28.8 17.1 20.1 29.9 17.1 20.3 Protected dug well 23.9 16.7 18.5 24.1 17.2 18.9 Protected spring 1.4 5.8 4.7 1.4 5.9 4.8 Rain water 0.0 0.5 0.4 0.0 0.5 0.4 Bottled water 0.6 0.0 0.2 0.6 0.0 0.2 Non-improved source 11.9 40.3 33.0 11.9 38.6 32.1 Unprotected dug well 4.4 13.5 11.1 4.3 13.2 11.0 Unprotected spring 1.4 11.2 8.6 1.1 10.5 8.2 Tanker truck/cart with drum 5.2 6.2 5.9 5.7 5.8 5.8 Surface water 0.9 9.5 7.3 0.9 9.1 7.0 Other source 1.7 1.7 1.7 1.6 1.4 1.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 76.7 34.5 45.3 77.4 36.5 46.6 Less than 30 minutes 17.3 47.8 39.9 16.3 46.4 39.0 30 minutes or longer 4.6 16.6 13.5 4.9 16.1 13.3 Don’t know 1.4 1.2 1.2 1.4 1.1 1.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking1 Boiled 8.5 2.4 3.9 8.3 2.3 3.8 Bleach/chlorine added 3.8 1.0 1.7 3.8 1.1 1.8 Strained through cloth 0.7 0.3 0.4 0.8 0.3 0.4 Ceramic, sand, or other filter 1.0 0.7 0.8 1.1 0.7 0.8 Solar disinfection 0.2 0.0 0.1 0.1 0.0 0.0 Other 1.7 1.1 1.2 2.0 1.1 1.3 No treatment 85.3 91.9 90.2 85.0 92.1 90.4 Percentage using an appropriate treatment method2 12.4 3.8 6.0 12.5 3.9 6.0 Number 6,269 18,126 24,395 48,246 147,802 196,048 1 Respondents may report multiple treatment methods, so the sum of treatment may exceed 100%. 2 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. 16 • Housing Characteristics and Household Population Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet/latrine facilities, according to residence, Afghanistan 2015 Households Population Type of toilet/latrine facility Urban Rural Total Urban Rural Total Improved, not shared facility 52.1 16.2 25.4 54.6 16.9 26.2 Flush/pour flush to piped sewer system 7.6 0.3 2.2 8.0 0.3 2.2 Flush/pour flush to septic tank 26.4 2.0 8.3 28.2 2.4 8.7 Flush/pour flush to pit latrine 4.5 1.7 2.4 4.6 1.8 2.5 Ventilated improved pit (VIP) latrine 7.5 4.9 5.6 7.9 5.2 5.9 Pit latrine with slab 4.2 3.8 3.9 4.1 3.8 3.9 Composting toilet 1.9 3.5 3.1 1.9 3.4 3.0 Shared facility1 16.5 5.4 8.2 13.3 4.3 6.5 Flush/pour flush to piped sewer system 2.3 0.0 0.6 1.9 0.0 0.5 Flush/pour flush to septic tank 8.2 0.8 2.7 6.7 0.6 2.1 Flush/pour flush to pit latrine 1.5 0.3 0.7 1.2 0.3 0.5 Ventilated improved pit (VIP) latrine 2.1 1.2 1.4 1.6 1.1 1.2 Pit latrine with slab 1.8 1.3 1.4 1.2 1.2 1.2 Composting toilet 0.7 1.6 1.4 0.6 1.2 1.0 Non-improved facility 31.1 74.9 63.6 31.8 74.5 64.1 Flush/pour flush not to sewer/septic tank/pit latrine 3.0 0.4 1.1 3.3 0.4 1.1 Pit latrine without slab/open pit 2.2 5.7 4.8 2.4 5.2 4.5 Bucket 0.1 0.4 0.4 0.1 0.5 0.4 Traditional dry vault toilet 23.7 50.7 43.7 24.4 51.9 45.2 Eco sanitation 0.2 0.5 0.4 0.2 0.4 0.4 No facility/bush/field 1.9 17.2 13.2 1.4 16.1 12.5 Other 0.2 3.5 2.7 0.1 4.2 3.2 Missing 0.1 0.0 0.1 0.1 0.0 0.0 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 6,269 18,126 24,395 48,246 147,802 196,048 1 Facilities that would be considered improved if they were not shared by two or more households Housing Characteristics and Household Population • 17 Table 2.3 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Afghanistan 2015 Residence Housing characteristic Urban Rural Total Electricity Yes 92.5 64.2 71.5 No 7.5 35.8 28.5 Total 100.0 100.0 100.0 Flooring material Earth/sand 3.7 2.2 2.6 Dung 0.2 0.1 0.1 Mud and hay 4.5 3.2 3.6 Wood planks 0.4 0.1 0.2 Parquet or polished wood 0.1 0.1 0.1 Ceramic tiles 1.8 0.1 0.5 Cement 15.4 1.2 4.8 Rugs/mat 23.9 26.6 25.9 Carpet 48.0 58.6 55.9 Other 2.0 7.7 6.2 Total 100.0 100.0 100.0 Rooms used for sleeping One 20.0 15.2 16.4 Two 33.3 34.0 33.8 Three or more 44.0 49.6 48.2 Missing 2.6 1.2 1.6 Total 100.0 100.0 100.0 Place for cooking In the house 62.9 52.7 55.3 In a separate building 22.8 25.8 25.0 Outdoors 12.2 19.2 17.4 No food cooked in household 0.2 0.0 0.1 Other 1.9 2.2 2.1 Missing 0.0 0.1 0.1 Total 100.0 100.0 100.0 Cooking fuel Electricity 0.4 0.1 0.2 LPG/natural gas/biogas 83.1 15.1 32.6 Coal/lignite 0.1 0.6 0.5 Charcoal 0.3 0.9 0.7 Wood 9.3 28.0 23.2 Straw/shrubs/grass 2.7 21.8 16.9 Agricultural crop 0.9 8.0 6.2 Animal dung 2.8 24.8 19.2 Other fuel 0.1 0.5 0.4 No food cooked in household 0.2 0.0 0.1 Missing 0.1 0.1 0.1 Total 100.0 100.0 100.0 Percentage using solid fuel for cooking1 16.0 84.2 66.7 Frequency of smoking in the home Daily 19.3 19.2 19.2 Weekly 2.3 2.7 2.6 Monthly 0.5 0.6 0.6 Less than monthly 0.4 0.5 0.4 Never 77.5 76.9 77.1 Missing 0.0 0.1 0.1 Total 100.0 100.0 100.0 Number 6,269 18,126 24,395 LPG = Liquefied petroleum gas 1 Includes coal/lignite, charcoal, wood, straw/shrubs/grass, agricultural crops, and animal dung 18 • Housing Characteristics and Household Population Table 2.4 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Afghanistan 2015 Residence Possession Urban Rural Total Household effects Radio 45.1 48.1 47.3 Television 84.2 39.1 50.7 Mobile telephone 93.5 85.1 87.3 Non-mobile telephone 6.0 0.7 2.1 Refrigerator 50.7 8.4 19.2 Table 20.4 6.7 10.2 Chair 17.6 5.5 8.6 Sofa 9.2 2.0 3.9 Bed 30.9 15.6 19.5 Cupboard 54.5 29.1 35.6 Stand fan 58.4 18.2 28.5 Generator 19.0 8.8 11.4 Sewing machine 62.3 58.8 59.7 Computer 28.4 5.3 11.3 Means of transport Bicycle 40.3 26.4 30.0 Animal-drawn cart 1.3 7.4 5.8 Rickshaw 2.6 4.1 3.7 Motorcycle/scooter 25.4 38.7 35.2 Car/truck/tractor 16.4 13.2 14.0 Ownership of agricultural land 18.9 64.4 52.7 Ownership of farm animals1 20.4 78.2 63.4 Number 6,269 18,126 24,395 1 Cattle, cows, bulls, horses, donkeys, goats, sheep, camels, ducks, or chickens Housing Characteristics and Household Population • 19 Table 2.5 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini coefficient, according to residence and province, Afghanistan 2015 Residence/province Wealth quintile Number of persons Gini coefficient Lowest Second Middle Fourth Highest Total Residence Urban 3.3 2.4 3.5 18.3 72.5 100.0 48,246 0.09 Rural 25.5 25.7 25.4 20.6 2.9 100.0 147,802 0.20 Province1 Kabul 0.3 1.7 6.3 24.3 67.4 100.0 25,119 0.15 Kapisa 7.2 40.4 28.6 21.3 2.4 100.0 1,413 0.11 Parwan 13.3 26.1 36.1 17.7 6.7 100.0 4,557 0.26 Wardak 36.3 16.8 26.0 20.7 0.2 100.0 2,597 0.22 Logar 2.8 29.0 33.1 31.6 3.6 100.0 3,360 0.24 Nangarhar 1.1 10.8 22.9 39.0 26.3 100.0 5,896 0.23 Laghman 2.5 26.8 38.4 29.0 3.3 100.0 4,138 0.24 Panjsher 37.2 35.2 18.0 9.2 0.4 100.0 429 0.32 Baghlan 44.8 23.3 12.2 7.1 12.6 100.0 5,630 0.22 Bamyan 68.7 15.4 8.6 6.3 1.1 100.0 2,370 0.15 Ghazni 10.9 30.3 24.6 31.5 2.7 100.0 7,265 0.24 Paktika 4.4 37.7 33.0 21.9 2.9 100.0 4,789 0.28 Paktya 3.7 26.5 42.2 23.8 3.9 100.0 3,566 0.19 Khost 4.2 17.8 24.4 41.9 11.7 100.0 5,478 0.19 Kunarha 9.4 27.4 34.7 22.8 5.7 100.0 4,560 0.16 Nooristan 6.5 42.6 30.6 20.1 0.2 100.0 1,257 0.27 Badakhshan 54.3 26.2 13.3 3.8 2.4 100.0 6,329 0.16 Takhar 33.3 28.8 17.8 12.3 7.8 100.0 7,664 0.22 Kunduz 25.1 31.5 17.2 14.9 11.3 100.0 8,583 0.24 Samangan 55.1 10.7 18.8 10.2 5.2 100.0 2,230 0.24 Balkh 29.3 18.6 11.6 16.0 24.5 100.0 12,078 0.33 Sar-E-Pul 46.2 21.9 21.6 7.9 2.4 100.0 4,291 0.16 Ghor 75.8 13.3 6.2 3.2 1.4 100.0 4,747 0.24 Daykundi 65.4 27.9 5.6 1.0 0.1 100.0 2,383 0.21 Urozgan 3.3 40.0 39.3 15.7 1.7 100.0 1,512 0.14 Kandahar 0.5 9.5 32.1 22.5 35.5 100.0 15,910 0.30 Jawzjan 20.1 26.5 14.6 24.1 14.7 100.0 4,738 0.24 Faryab 20.0 16.6 22.2 27.0 14.1 100.0 13,614 0.12 Helmand 4.1 33.7 28.9 18.0 15.3 100.0 6,171 0.25 Badghis 53.5 24.1 18.0 2.8 1.6 100.0 4,136 0.33 Herat 26.2 20.2 16.6 16.5 20.4 100.0 13,116 0.30 Farah 28.7 36.1 12.7 15.3 7.1 100.0 4,190 0.34 Nimroz 3.9 8.1 10.7 38.3 39.1 100.0 1,773 0.17 Total 20.0 20.0 20.0 20.0 20.0 100.0 196,048 0.14 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 20 • Housing Characteristics and Household Population Table 2.6 Hand washing Percentage of households in which the place most often used for washing hands was observed, and among households in which the place for hand washing was observed, percent distribution by availability of water, soap, and other cleansing agents, Afghanistan 2015 Background characteristic Percent- age of house- holds where place for washing hands was observed Number of house- holds Among households where place for hand washing was observed, percentage with: Number of house- holds with place for hand washing observed Soap and water1 Water and cleansing agent2 other than soap only Water only Soap but no water3 Cleansing agent other than soap only2 No water, no soap, no other cleansing agent Missing Total Residence Urban 85.5 6,269 64.9 1.1 20.3 4.4 0.1 9.0 0.3 100.0 5,361 Rural 72.1 18,126 23.9 1.9 31.4 5.5 1.4 35.5 0.3 100.0 13,065 Province4 Kabul 86.5 3,369 72.9 1.4 16.7 5.0 0.1 3.6 0.3 100.0 2,913 Kapisa 97.0 179 58.1 1.0 23.6 6.7 0.1 10.5 0.0 100.0 173 Parwan 94.5 601 36.0 4.2 13.6 12.4 2.7 31.1 0.0 100.0 568 Wardak 82.1 351 27.9 3.2 38.1 9.7 0.5 20.4 0.1 100.0 289 Logar 72.4 398 60.1 7.4 5.3 4.3 0.9 21.6 0.4 100.0 288 Nangarhar 60.0 625 56.8 0.9 21.0 6.4 0.0 14.9 0.0 100.0 375 Laghman 77.3 446 26.2 0.6 8.8 3.6 0.8 59.9 0.0 100.0 345 Panjsher 96.7 54 65.5 0.4 2.0 27.5 0.0 3.9 0.7 100.0 52 Baghlan 75.5 776 13.6 1.0 30.5 1.6 0.6 51.9 0.7 100.0 586 Bamyan 98.8 300 17.2 0.6 21.4 7.2 0.8 52.1 0.5 100.0 296 Ghazni 41.0 864 25.9 3.3 40.3 0.8 2.6 26.9 0.3 100.0 354 Paktika 64.7 514 30.8 3.0 30.4 1.1 0.3 34.3 0.2 100.0 333 Paktya 83.4 353 59.9 4.1 14.1 4.8 2.7 14.2 0.2 100.0 294 Khost 49.9 457 35.8 9.8 54.3 0.0 0.0 0.1 0.0 100.0 228 Kunarha 70.2 507 23.1 8.1 16.4 2.4 5.6 44.3 0.1 100.0 356 Nooristan 52.2 127 15.8 1.4 25.0 22.2 5.7 29.9 0.0 100.0 66 Badakhshan 94.1 849 24.8 1.1 20.8 0.1 0.2 53.1 0.0 100.0 799 Takhar 78.1 1,027 16.1 0.4 53.2 0.3 0.2 29.4 0.6 100.0 803 Kunduz 97.6 1,070 12.6 1.6 12.4 18.2 4.2 50.5 0.5 100.0 1,044 Samangan 79.0 316 26.0 12.7 41.7 0.1 0.4 18.5 0.7 100.0 250 Balkh 98.2 1,510 40.6 1.8 23.2 5.8 2.1 26.5 0.0 100.0 1,482 Sar-E-Pul 88.6 644 23.0 1.3 60.0 1.4 0.1 14.2 0.0 100.0 571 Ghor 87.1 626 18.8 0.3 10.3 4.7 4.6 60.9 0.4 100.0 545 Daykundi 3.6 346 (10.7) (3.2) (62.9) (1.8) (0.0) (16.2) (5.2) 100.0 12 Urozgan 4.8 167 (62.0) (4.4) (25.4) (0.0) (0.0) (4.8) (3.4) 100.0 8 Kandahar 35.7 1,659 42.5 0.0 43.6 0.0 0.0 12.9 0.9 100.0 593 Jawzjan 89.4 563 28.6 2.4 7.8 37.7 2.3 21.1 0.1 100.0 503 Faryab 96.9 1,680 21.2 0.0 59.5 0.1 0.0 19.2 0.1 100.0 1,627 Helmand 29.6 718 48.2 0.5 19.0 0.0 0.0 29.5 2.7 100.0 213 Badghis 58.6 531 5.7 0.2 16.5 0.4 0.0 76.8 0.4 100.0 311 Herat 82.1 2,011 30.3 0.0 31.8 3.1 0.0 34.2 0.6 100.0 1,651 Farah 60.9 501 27.6 1.1 33.9 0.1 0.0 37.3 0.0 100.0 305 Nimroz 76.7 238 48.2 0.5 31.4 0.0 0.0 19.8 0.1 100.0 183 Wealth quintile Lowest 79.2 4,852 11.4 1.0 32.6 5.2 1.8 47.6 0.3 100.0 3,841 Second 70.8 4,838 17.1 2.0 32.8 5.6 1.3 40.9 0.4 100.0 3,424 Middle 67.5 4,871 25.8 2.9 31.4 4.8 1.5 33.0 0.5 100.0 3,286 Fourth 72.7 4,859 43.3 1.6 29.5 6.7 0.5 18.1 0.3 100.0 3,534 Highest 87.2 4,976 73.7 1.2 17.0 3.8 0.1 4.0 0.2 100.0 4,340 Total 75.5 24,395 35.8 1.7 28.2 5.2 1.0 27.8 0.3 100.0 18,426 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Soap includes soap or detergent in bar, liquid, powder, or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 2 Cleansing agents other than soap include locally available materials such as ash, mud, or sand. 3 Includes households with soap only as well as those with soap and another cleansing agent 4 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Housing Characteristics and Household Population • 21 Table 2.7 Household population by age, sex, and residence Percent distribution of the de facto household population by 5-year age groups, according to sex and residence, Afghanistan 2015 Urban Rural Age Male Female Total Male Female Total Male Female Total <5 15.2 14.9 15.1 16.5 16.5 16.5 16.2 16.1 16.1 5-9 14.9 14.8 14.8 17.6 16.8 17.2 17.0 16.3 16.6 10-14 14.3 14.2 14.2 15.0 13.7 14.4 14.8 13.8 14.3 15-19 12.5 13.2 12.8 11.4 11.3 11.4 11.7 11.8 11.7 20-24 9.2 11.1 10.1 8.3 9.5 8.8 8.5 9.9 9.2 25-29 7.8 7.1 7.4 6.6 7.7 7.1 6.9 7.6 7.2 30-34 4.6 4.6 4.6 4.9 4.7 4.8 4.8 4.7 4.8 35-39 4.8 5.0 4.9 4.0 4.7 4.3 4.2 4.7 4.5 40-44 3.1 3.2 3.2 3.1 3.4 3.3 3.1 3.4 3.2 45-49 3.3 3.2 3.2 3.7 3.8 3.7 3.6 3.6 3.6 50-54 2.6 2.9 2.7 1.8 2.4 2.1 2.0 2.5 2.3 55-59 2.2 2.1 2.2 1.9 2.3 2.1 2.0 2.3 2.1 60-64 1.8 1.5 1.7 2.0 1.5 1.7 1.9 1.5 1.7 65-69 1.2 0.8 1.0 1.1 0.8 1.0 1.1 0.8 1.0 70-74 1.2 0.7 0.9 1.0 0.5 0.8 1.1 0.5 0.8 75-79 0.8 0.3 0.5 0.5 0.2 0.3 0.6 0.2 0.4 80+ 0.7 0.4 0.6 0.5 0.2 0.4 0.5 0.3 0.4 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number 23,788 23,406 47,194 74,638 70,557 145,195 98,426 93,963 192,389 Table 2.8 Household composition Percent distribution of households by sex of head of household and by household size, mean size of household, and percentage of households with orphans and foster children under age 18, according to residence, Afghanistan 2015 Residence Characteristic Urban Rural Total Household headship Male 97.2 98.7 98.3 Female 2.8 1.3 1.7 Total 100.0 100.0 100.0 Number of usual members 1 0.4 0.1 0.2 2 2.2 2.2 2.2 3 5.1 4.0 4.3 4 8.1 7.0 7.3 5 11.1 9.1 9.6 6 13.3 12.2 12.5 7 14.5 13.4 13.7 8 12.4 12.7 12.6 9+ 32.9 39.4 37.7 Total 100.0 100.0 100.0 Mean size of households 7.7 8.2 8.0 Percentage of households with orphans and foster children under age 18 Foster children1 3.5 4.3 4.1 Double orphans 1.2 1.3 1.2 Single orphans2 5.7 6.2 6.0 Foster and/or orphan children 8.3 9.6 9.3 Number of households 6,269 18,126 24,395 Note: Table is based on de jure household members, i.e., usual residents. 1 Foster children are those under age 18 living in households with neither their mother nor their father present. 2 Includes children with one dead parent and an unknown survival status of the other parent 22 • Housing Characteristics and Household Population Table 2.9 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Afghanistan 2015 Children whose births are registered Background characteristic Percentage who had a birth certificate Percentage who did not have a birth certificate Percentage registered Number of children Age <2 25.0 24.5 49.6 11,615 2-4 16.8 21.3 38.0 19,785 Sex Male 19.9 22.8 42.7 16,068 Female 19.8 22.1 41.9 15,332 Residence Urban 36.1 27.4 63.5 7,222 Rural 15.0 21.0 36.0 24,178 Province1 Kabul 45.5 25.1 70.6 3,755 Kapisa 30.2 37.3 67.4 212 Parwan 25.2 32.7 57.9 698 Wardak 42.4 6.2 48.6 355 Logar 15.7 11.5 27.2 424 Nangarhar 13.9 30.0 43.8 1,024 Laghman 3.0 2.0 5.0 782 Panjsher 40.2 18.7 58.9 41 Baghlan 13.7 2.7 16.4 752 Bamyan 14.5 47.6 62.1 344 Ghazni 18.7 6.3 25.0 785 Paktika 5.6 19.4 25.0 858 Paktya 0.8 69.8 70.6 613 Khost 11.0 25.6 36.6 1,008 Kunarha 14.7 19.9 34.6 809 Nooristan 0.0 0.1 0.1 299 Badakhshan 16.4 15.8 32.2 898 Takhar 6.2 21.2 27.4 1,227 Kunduz 16.9 8.9 25.8 1,201 Samangan 10.6 7.9 18.5 350 Balkh 19.7 21.0 40.6 1,951 Sar-E-Pul 33.4 18.7 52.1 614 Ghor 9.0 24.2 33.2 873 Daykundi 1.5 25.1 26.6 332 Urozgan 1.3 3.6 4.9 392 Kandahar 5.1 36.3 41.4 2,909 Jawzjan 31.6 5.5 37.1 604 Faryab 10.1 41.8 51.9 2,412 Helmand 16.0 1.3 17.3 949 Badghis 50.2 27.8 78.1 765 Herat 36.9 10.0 46.9 2,014 Farah 10.2 30.7 41.0 825 Nimroz 67.3 3.9 71.2 300 Wealth quintile Lowest 13.3 16.6 29.8 6,060 Second 12.7 18.3 30.9 6,385 Middle 13.7 21.3 34.9 6,708 Fourth 22.8 25.3 48.2 6,453 Highest 38.4 31.5 69.9 5,794 Total 19.8 22.5 42.3 31,400 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Housing Characteristics and Household Population • 23 Table 2.10 Children’s living arrangements and orphanhood Percent distribution of de jure children under 18 years of age by living arrangements and survival status of parents, the percentage of children not living with a biological parent, and the percentage of children with one or both parents dead, according to background characteristics, Afghanistan 2015 Background characteristic Living with both parents Living with mother but not with father Living with father but not with mother Not living with either parent Total Percent- age not living with a biolo- gical parent Percent- age with one or both parents dead1 Number of children Father alive Father dead Mother alive Mother dead Both alive Only mother alive Only father alive Both dead Missing infor- mation on father/ mother Age 0-4 97.2 1.3 0.7 0.0 0.4 0.2 0.0 0.0 0.1 0.1 100.0 0.3 1.2 31,400 <2 97.9 1.2 0.5 0.0 0.0 0.1 0.0 0.0 0.1 0.0 100.0 0.2 0.6 11,615 2-4 96.8 1.4 0.8 0.1 0.6 0.2 0.0 0.0 0.1 0.1 100.0 0.3 1.6 19,785 5-9 95.8 1.3 1.6 0.0 0.7 0.2 0.2 0.0 0.1 0.1 100.0 0.5 2.6 32,226 10-14 92.8 1.1 3.2 0.1 1.3 0.3 0.4 0.0 0.6 0.1 100.0 1.3 5.5 27,801 15-17 86.4 0.9 5.3 0.1 2.0 2.3 0.2 0.2 1.7 0.9 100.0 4.4 9.5 13,748 Sex Male 94.7 1.2 2.2 0.1 0.8 0.3 0.2 0.0 0.4 0.1 100.0 0.9 3.7 54,602 Female 93.7 1.2 2.2 0.1 1.1 0.7 0.2 0.1 0.5 0.3 100.0 1.4 4.1 50,573 Residence Urban 94.6 1.0 2.3 0.1 0.8 0.5 0.1 0.1 0.4 0.1 100.0 1.1 3.7 24,787 Rural 94.1 1.3 2.2 0.1 1.0 0.5 0.2 0.0 0.5 0.2 100.0 1.2 3.9 80,389 Province2 Kabul 95.4 1.3 1.6 0.4 0.6 0.4 0.0 0.2 0.2 0.1 100.0 0.7 2.6 12,607 Kapisa 93.5 1.6 3.1 0.1 0.8 0.1 0.1 0.0 0.3 0.3 100.0 0.6 4.3 731 Parwan 91.2 0.8 4.3 0.1 2.6 0.3 0.1 0.1 0.3 0.3 100.0 0.7 7.3 2,362 Wardak 95.1 0.4 2.4 0.0 0.5 0.4 0.0 0.0 0.7 0.4 100.0 1.1 3.6 1,269 Logar 98.2 0.0 0.9 0.0 0.3 0.1 0.0 0.0 0.4 0.1 100.0 0.5 1.7 1,949 Nangarhar 94.0 1.3 3.4 0.0 0.4 0.4 0.1 0.1 0.2 0.2 100.0 0.7 4.1 3,228 Laghman 95.4 0.0 2.9 0.1 0.5 0.4 0.1 0.0 0.2 0.4 100.0 0.7 3.6 2,422 Panjsher 96.5 0.1 2.4 0.0 0.0 0.6 0.0 0.0 0.2 0.1 100.0 0.8 2.7 211 Baghlan 96.2 0.7 1.5 0.0 0.3 0.9 0.0 0.0 0.2 0.2 100.0 1.1 2.0 2,923 Bamyan 90.5 2.2 2.9 0.3 2.1 0.7 0.3 0.1 0.6 0.3 100.0 1.7 6.0 1,233 Ghazni 96.4 0.1 0.6 0.0 0.5 0.6 0.0 0.0 1.4 0.3 100.0 2.0 2.5 3,664 Paktika 93.9 1.2 1.8 0.1 2.4 0.1 0.0 0.0 0.3 0.2 100.0 0.4 4.5 2,541 Paktya 93.2 0.8 2.3 0.1 1.6 0.1 0.0 0.0 1.7 0.2 100.0 1.9 5.6 1,950 Khost 93.4 2.9 2.0 0.0 0.5 0.3 0.1 0.0 0.5 0.1 100.0 0.9 3.2 3,207 Kunarha 94.5 1.7 2.6 0.0 0.7 0.2 0.0 0.0 0.2 0.1 100.0 0.4 3.6 2,741 Nooristan 92.0 0.3 4.3 0.2 2.3 0.2 0.0 0.1 0.2 0.2 100.0 0.6 7.0 723 Badakhshan 93.0 1.3 3.1 0.0 1.2 0.5 0.4 0.1 0.1 0.1 100.0 1.1 5.0 3,354 Takhar 91.2 1.8 3.4 0.0 1.7 0.6 0.1 0.0 0.8 0.4 100.0 1.4 6.1 4,032 Kunduz 95.3 1.0 1.6 0.0 0.8 0.1 0.0 0.0 0.9 0.2 100.0 1.0 3.4 4,569 Samangan 93.6 0.8 2.8 0.0 0.6 0.7 0.2 0.1 1.1 0.1 100.0 2.1 4.8 1,172 Balkh 94.9 0.3 2.0 0.0 1.3 0.8 0.4 0.0 0.2 0.1 100.0 1.3 3.9 6,135 Sar-E-Pul 92.8 1.0 3.4 0.0 0.6 0.6 0.1 0.1 1.1 0.2 100.0 1.9 5.3 2,194 Ghor 94.5 0.7 1.0 0.0 2.5 0.8 0.1 0.0 0.4 0.1 100.0 1.3 3.9 2,734 Daykundi 86.7 7.0 2.8 0.0 0.8 1.7 0.2 0.4 0.1 0.2 100.0 2.3 4.3 1,293 Urozgan 98.4 0.0 1.0 0.0 0.4 0.0 0.0 0.0 0.1 0.2 100.0 0.1 1.4 947 Kandahar 96.7 0.4 1.3 0.0 1.0 0.1 0.0 0.0 0.4 0.1 100.0 0.6 2.7 9,101 Jawzjan 97.5 0.5 1.2 0.0 0.2 0.3 0.0 0.0 0.3 0.1 100.0 0.6 1.7 2,508 Faryab 87.6 4.9 3.7 0.0 1.1 0.8 1.6 0.0 0.3 0.1 100.0 2.7 6.6 6,967 Helmand 97.8 0.0 0.3 0.0 0.6 0.3 0.0 0.1 0.5 0.4 100.0 0.9 1.6 3,621 Badghis 94.0 0.1 2.5 0.0 1.3 1.2 0.1 0.0 0.4 0.4 100.0 1.8 4.3 2,321 Herat 93.9 1.0 3.3 0.0 0.8 0.3 0.1 0.0 0.4 0.2 100.0 0.9 4.6 6,947 Farah 93.3 0.1 4.0 0.0 0.3 1.2 0.0 0.0 0.7 0.4 100.0 1.9 4.9 2,405 Nimroz 92.5 0.4 3.4 0.0 0.7 1.6 0.0 0.3 0.9 0.2 100.0 2.8 5.4 1,019 Wealth quintile Lowest 94.2 0.8 2.1 0.1 1.3 0.5 0.1 0.1 0.4 0.2 100.0 1.1 4.1 21,194 Second 94.8 0.7 2.2 0.0 0.9 0.6 0.0 0.0 0.5 0.2 100.0 1.1 3.6 21,387 Middle 93.1 1.9 2.5 0.1 0.9 0.5 0.2 0.0 0.6 0.3 100.0 1.3 4.3 21,585 Fourth 93.9 1.6 2.3 0.0 0.8 0.4 0.5 0.0 0.4 0.2 100.0 1.3 4.0 21,374 Highest 95.0 0.9 2.1 0.2 0.8 0.5 0.1 0.1 0.3 0.1 100.0 1.0 3.4 19,634 Total <15 95.4 1.3 1.8 0.1 0.8 0.2 0.2 0.0 0.3 0.1 100.0 0.7 3.0 91,427 Total <18 94.2 1.2 2.2 0.1 0.9 0.5 0.2 0.0 0.4 0.2 100.0 1.2 3.9 105,175 Note: Table is based on de jure members, i.e., usual residents. 1 Includes children with father dead, mother dead, both dead and one parent dead but missing information on survival status of the other parent. 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 24 • Housing Characteristics and Household Population Table 2.11 School attendance by survivorship of parents For de jure children age 10-14, the percentage attending school by parental survival and the ratio of the percentage attending, by parental survival, according to background characteristics, Afghanistan 2015 Percentage attending school by survivorship of parents Background characteristic Both parents deceased Number Both parents alive and living with at least one parent Number Ratio1 Sex Male 72.0 82 79.7 13,907 0.90 Female 36.2 74 52.9 12,247 0.68 Residence Urban (65.7) 28 84.2 6,400 0.78 Rural 52.6 127 61.6 19,754 0.85 Wealth quintile Lowest (69.4) 40 61.5 5,444 1.13 Second (39.0) 26 57.1 5,334 0.68 Middle 49.1 47 57.3 5,108 0.86 Fourth (51.2) 25 74.0 5,288 0.69 Highest * 18 87.0 4,980 0.76 Total 54.9 156 67.2 26,154 0.82 Note: Table is based only on children who usually live in the household. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. Provincial-level disaggregation is not shown due to the small number of cases. 1 Ratio of the percentage with both parents deceased to the percentage with both parents alive and living with a parent Housing Characteristics and Household Population • 25 Table 2.12.1 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, Afghanistan 2015 Background characteristic No edu- cation Some primary Com- pleted primary1 Some secon- dary Com- pleted secon- dary2 More than secon- dary Don’t know/ missing Total Number Median years com- pleted Age 6-9 69.8 29.1 0.0 0.0 0.0 0.0 1.1 100.0 12,649 0.0 10-14 40.8 45.1 6.5 7.2 0.0 0.0 0.4 100.0 13,004 1.6 15-19 48.7 12.1 5.9 26.3 5.5 1.1 0.4 100.0 11,094 1.6 20-24 64.9 7.3 3.1 9.7 8.8 5.8 0.4 100.0 9,272 0.0 25-29 80.5 6.3 2.1 3.9 3.6 3.3 0.3 100.0 7,095 0.0 30-34 88.0 4.5 1.5 2.9 1.4 1.5 0.2 100.0 4,416 0.0 35-39 89.4 3.8 0.9 2.6 1.4 1.5 0.4 100.0 4,462 0.0 40-44 89.0 4.6 1.2 1.8 0.9 2.1 0.4 100.0 3,159 0.0 45-49 91.2 3.7 0.8 1.3 1.7 1.0 0.3 100.0 3,412 0.0 50-54 94.1 2.0 0.9 0.9 0.6 0.9 0.6 100.0 2,394 0.0 55-59 94.2 2.2 0.7 0.9 0.5 0.4 1.1 100.0 2,116 0.0 60-64 94.5 2.8 0.2 0.3 0.5 0.4 1.3 100.0 1,404 0.0 65+ 96.9 0.8 0.6 0.9 0.0 0.2 0.6 100.0 1,713 0.0 Residence Urban 50.1 22.8 4.1 12.9 5.6 4.2 0.4 100.0 19,392 0.0 Rural 74.9 14.7 2.4 5.2 1.5 0.6 0.6 100.0 56,798 0.0 Province3 Kabul 49.1 23.2 4.1 13.1 6.2 4.0 0.4 100.0 10,061 0.2 Kapisa 55.0 22.5 4.6 11.0 3.5 2.9 0.6 100.0 577 0.0 Parwan 67.9 18.1 2.5 6.2 3.1 1.3 1.0 100.0 1,865 0.0 Wardak 84.4 11.2 1.4 2.1 0.2 0.0 0.7 100.0 1,017 0.0 Logar 66.6 17.1 2.9 9.5 2.8 0.6 0.4 100.0 1,308 0.0 Nangarhar 68.5 16.6 3.4 7.4 2.3 1.2 0.5 100.0 2,248 0.0 Laghman 72.7 18.8 1.6 4.7 1.2 0.4 0.5 100.0 1,503 0.0 Panjsher 51.4 21.1 5.4 16.2 4.0 1.0 1.0 100.0 182 0.0 Baghlan 70.6 14.6 4.5 5.4 2.4 1.3 1.3 100.0 2,246 0.0 Bamyan 60.2 21.6 5.2 9.7 2.0 0.8 0.5 100.0 936 0.0 Ghazni 68.1 16.9 2.8 8.5 1.8 0.5 1.4 100.0 3,091 0.0 Paktika 94.8 3.5 0.4 0.5 0.2 0.0 0.4 100.0 1,746 0.0 Paktya 84.4 11.3 0.9 1.9 0.6 0.1 0.7 100.0 1,235 0.0 Khost 88.6 6.7 1.6 1.5 0.7 0.1 0.8 100.0 1,972 0.0 Kunarha 66.5 21.9 4.4 4.6 0.9 0.3 1.4 100.0 1,681 0.0 Nooristan 91.7 5.5 0.8 1.3 0.2 0.0 0.5 100.0 445 0.0 Badakhshan 58.2 23.3 4.4 10.5 2.2 1.1 0.3 100.0 2,529 0.0 Takhar 68.1 17.1 3.3 7.6 1.9 1.8 0.3 100.0 3,025 0.0 Kunduz 80.3 9.8 1.1 5.1 1.7 1.0 1.1 100.0 3,346 0.0 Samangan 71.0 17.5 2.5 6.6 0.8 1.2 0.4 100.0 876 0.0 Balkh 59.3 20.7 3.7 10.0 4.5 1.7 0.2 100.0 4,761 0.0 Sar-E-Pul 70.5 16.7 4.8 5.5 1.2 0.7 0.6 100.0 1,748 0.0 Ghor 66.2 20.8 4.5 6.6 1.4 0.3 0.2 100.0 1,779 0.0 Daykundi 60.7 19.3 3.5 13.4 1.9 0.9 0.3 100.0 1,020 0.0 Urozgan 95.6 1.9 0.5 0.7 0.3 0.0 1.1 100.0 525 0.0 Kandahar 87.7 8.7 1.0 1.6 0.5 0.1 0.4 100.0 5,900 0.0 Jawzjan 62.8 17.2 2.7 9.1 4.5 2.7 0.9 100.0 1,839 0.0 Faryab 58.2 20.3 3.0 10.1 4.5 3.8 0.0 100.0 5,318 0.0 Helmand 84.1 9.8 1.5 2.9 0.8 0.4 0.6 100.0 2,259 0.0 Badghis 73.7 21.8 1.4 2.6 0.3 0.0 0.3 100.0 1,553 0.0 Herat 69.7 16.6 2.4 6.8 1.8 2.1 0.6 100.0 5,341 0.0 Farah 80.2 13.2 1.9 3.4 1.0 0.3 0.0 100.0 1,532 0.0 Nimroz 64.0 24.3 3.1 6.1 1.2 1.0 0.3 100.0 667 0.0 Wealth quintile Lowest 75.1 16.3 2.8 4.4 0.8 0.2 0.6 100.0 15,333 0.0 Second 77.8 13.5 2.0 4.8 1.0 0.3 0.6 100.0 15,297 0.0 Middle 78.6 13.0 2.0 4.3 1.2 0.4 0.5 100.0 14,779 0.0 Fourth 65.9 18.5 3.2 8.0 2.8 0.8 0.7 100.0 15,050 0.0 Highest 46.6 22.3 4.2 14.0 6.8 5.8 0.4 100.0 15,731 0.8 Total 68.6 16.8 2.8 7.1 2.5 1.5 0.5 100.0 76,190 0.0 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 3 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 26 • Housing Characteristics and Household Population Table 2.12.2 Educational attainment of the male household population Percent distribution of the de facto male household population age 6 and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Afghanistan 2015 Background characteristic No edu- cation Some primary Com- pleted primary1 Some secon- dary Com- pleted secon- dary2 More than secon- dary Don’t know/ missing Total Number Median years com- pleted Age 6-9 62.8 35.9 0.2 0.1 0.0 0.0 1.0 100.0 13,808 0.0 10-14 16.4 64.0 10.0 9.2 0.0 0.0 0.3 100.0 14,598 3.0 15-19 18.5 13.4 9.4 51.6 5.9 1.1 0.2 100.0 11,487 6.8 20-24 30.2 9.4 5.1 25.6 20.4 8.9 0.3 100.0 8,354 7.3 25-29 43.6 10.7 5.3 15.0 14.7 10.4 0.2 100.0 6,797 3.4 30-34 52.0 12.2 5.4 13.4 10.6 6.3 0.2 100.0 4,768 0.0 35-39 54.4 10.6 5.5 12.8 10.5 6.0 0.2 100.0 4,153 0.0 40-44 60.7 11.2 5.2 10.1 8.4 4.4 0.0 100.0 3,065 0.0 45-49 59.8 13.6 4.0 10.0 7.3 4.9 0.5 100.0 3,532 0.0 50-54 63.7 6.4 4.9 11.3 8.1 5.3 0.3 100.0 1,975 0.0 55-59 67.4 6.9 5.1 7.0 7.1 6.2 0.2 100.0 1,940 0.0 60-64 71.0 7.7 4.1 5.0 5.5 6.3 0.5 100.0 1,885 0.0 65+ 81.4 4.0 5.0 2.2 4.4 2.4 0.6 100.0 3,225 0.0 Residence Urban 28.7 24.9 6.2 20.8 11.5 7.6 0.3 100.0 19,490 4.3 Rural 47.1 24.7 5.6 14.6 5.2 2.3 0.4 100.0 60,099 0.6 Province3 Kabul 26.7 25.1 6.0 21.5 12.6 7.7 0.4 100.0 10,411 4.6 Kapisa 25.0 26.9 6.7 19.8 11.0 10.4 0.2 100.0 552 4.7 Parwan 31.3 26.4 4.9 21.1 10.1 5.5 0.7 100.0 1,786 3.2 Wardak 45.0 19.9 6.1 16.5 7.0 5.1 0.4 100.0 1,103 1.2 Logar 33.3 25.5 5.5 23.2 9.6 2.5 0.4 100.0 1,538 3.0 Nangarhar 35.2 24.9 5.5 19.1 8.7 6.2 0.4 100.0 2,335 2.8 Laghman 41.3 28.9 6.3 14.4 6.3 2.5 0.3 100.0 1,602 1.4 Panjsher 24.5 23.2 6.3 27.5 12.8 5.0 0.7 100.0 190 5.3 Baghlan 36.3 23.4 7.3 18.8 9.8 3.5 1.0 100.0 2,408 3.0 Bamyan 40.3 24.3 7.2 17.4 6.2 4.0 0.6 100.0 904 2.1 Ghazni 44.8 22.9 6.0 17.8 5.2 2.5 0.9 100.0 3,224 1.1 Paktika 44.8 24.1 5.7 13.4 9.9 1.7 0.3 100.0 2,031 0.8 Paktya 39.1 26.7 5.8 20.2 4.7 3.2 0.4 100.0 1,542 2.1 Khost 42.7 24.9 5.8 15.5 7.1 3.4 0.6 100.0 2,264 1.2 Kunarha 26.2 30.7 6.4 22.2 7.8 5.4 1.1 100.0 1,718 3.7 Nooristan 64.8 13.3 3.3 12.0 5.4 0.8 0.3 100.0 444 0.0 Badakhshan 41.7 27.9 6.7 15.8 4.4 3.2 0.3 100.0 2,624 1.9 Takhar 47.4 25.3 5.3 14.9 3.3 3.4 0.3 100.0 2,774 0.7 Kunduz 53.0 19.2 4.4 16.6 4.7 1.5 0.6 100.0 3,792 0.0 Samangan 49.9 22.8 6.5 13.2 4.7 2.8 0.1 100.0 907 0.0 Balkh 40.4 26.9 6.0 16.7 6.9 3.0 0.0 100.0 4,634 2.0 Sar-E-Pul 47.4 31.2 8.7 9.1 1.9 1.4 0.3 100.0 1,746 0.5 Ghor 42.1 24.9 5.5 16.7 6.4 4.0 0.3 100.0 1,992 1.5 Daykundi 47.9 26.2 5.2 15.4 3.0 2.1 0.3 100.0 881 0.4 Urozgan 79.0 9.9 2.0 4.9 2.3 0.4 1.4 100.0 515 0.0 Kandahar 63.9 17.5 3.2 10.2 3.9 1.0 0.3 100.0 6,398 0.0 Jawzjan 34.9 24.3 6.4 18.4 11.2 4.6 0.2 100.0 2,054 2.8 Faryab 37.5 27.9 7.8 16.7 6.7 3.3 0.1 100.0 5,043 2.3 Helmand 42.1 28.3 6.7 14.9 5.4 1.8 0.8 100.0 2,720 1.5 Badghis 55.5 29.9 3.9 7.6 2.3 0.6 0.2 100.0 1,627 0.0 Herat 51.5 25.1 5.2 11.0 3.1 3.9 0.4 100.0 5,446 0.0 Farah 51.9 24.5 5.7 11.0 5.2 1.5 0.2 100.0 1,620 0.0 Nimroz 49.1 31.9 4.2 9.9 3.3 1.2 0.4 100.0 699 0.1 Wealth quintile Lowest 51.6 24.8 5.8 12.7 3.2 1.4 0.5 100.0 16,141 0.0 Second 49.8 24.3 5.7 14.2 4.1 1.5 0.4 100.0 15,847 0.0 Middle 49.0 24.6 5.3 13.9 4.9 2.0 0.4 100.0 15,736 0.2 Fourth 38.3 26.5 5.8 17.5 7.8 3.7 0.5 100.0 15,875 2.3 Highest 24.5 23.7 6.1 22.2 13.9 9.4 0.3 100.0 15,990 5.3 Total 42.6 24.8 5.7 16.1 6.8 3.6 0.4 100.0 79,589 1.6 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 3 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Housing Characteristics and Household Population • 27 Table 2.13 School attendance ratios Net attendance ratios (NAR) and gross attendance ratios (GAR) for the de facto household population by sex and level of schooling, and the gender parity index (GPI), according to background characteristics, Afghanistan 2015 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender parity index3 Male Female Total Gender parity index3 PRIMARY SCHOOL Residence Urban 77.6 70.9 74.2 0.91 101.6 88.9 95.2 0.88 Rural 67.2 43.5 56.2 0.65 87.3 56.8 73.1 0.65 Province4 Kabul 79.7 74.5 77.1 0.94 107.9 93.6 100.6 0.87 Kapisa 83.3 69.5 76.8 0.83 104.9 90.5 98.1 0.86 Parwan 79.6 55.1 67.0 0.69 103.4 70.8 86.6 0.69 Wardak 75.5 31.0 54.2 0.41 94.8 42.4 69.7 0.45 Logar 72.2 53.0 63.9 0.73 95.2 67.2 83.0 0.71 Nangarhar 72.1 46.4 60.1 0.64 97.0 62.4 80.9 0.64 Laghman 72.0 40.3 57.2 0.56 95.1 55.8 76.8 0.59 Panjsher 79.8 72.4 76.1 0.91 105.7 98.6 102.2 0.93 Baghlan 70.2 41.9 57.4 0.60 95.6 63.1 80.9 0.66 Bamyan 76.2 64.5 70.4 0.85 94.6 83.6 89.1 0.88 Ghazni 72.0 54.9 63.4 0.76 89.8 67.4 78.5 0.75 Paktika 92.3 19.7 63.5 0.21 127.8 30.5 89.1 0.24 Paktya 85.1 39.5 65.6 0.46 119.3 56.3 92.4 0.47 Khost 80.8 23.8 55.7 0.29 112.9 35.3 78.7 0.31 Kunarha 78.1 42.1 60.3 0.54 103.7 55.1 79.7 0.53 Nooristan 37.4 20.2 29.7 0.54 44.2 27.1 36.5 0.61 Badakhshan 72.0 64.7 68.4 0.90 91.9 76.8 84.4 0.84 Takhar 67.0 51.9 59.7 0.77 83.2 69.3 76.5 0.83 Kunduz 48.7 28.3 39.1 0.58 61.7 36.7 50.0 0.59 Samangan 71.2 56.9 64.2 0.80 100.0 77.0 88.8 0.77 Balkh 76.2 67.9 71.9 0.89 98.2 84.3 91.1 0.86 Sar-E-Pul 71.4 50.6 62.4 0.71 88.1 64.4 77.8 0.73 Ghor 81.3 69.5 75.9 0.86 96.4 87.2 92.2 0.90 Daykundi 70.7 64.1 67.6 0.91 86.3 82.8 84.6 0.96 Urozgan 28.3 6.5 17.2 0.23 35.4 8.2 21.6 0.23 Kandahar 40.8 25.5 33.8 0.62 55.7 32.5 45.0 0.58 Jawzjan 68.4 48.4 59.5 0.71 83.3 56.5 71.3 0.68 Faryab 76.6 69.7 73.4 0.91 90.7 88.4 89.6 0.97 Helmand 66.4 23.0 47.2 0.35 86.3 32.9 62.7 0.38 Badghis 83.6 67.0 75.4 0.80 121.4 91.8 106.8 0.76 Herat 64.3 44.8 54.8 0.70 83.1 57.8 70.8 0.70 Farah 50.1 38.4 44.8 0.77 61.7 48.0 55.5 0.78 Nimroz 66.2 54.1 60.8 0.82 86.2 65.2 76.8 0.76 Wealth quintile Lowest 66.5 47.0 57.1 0.71 86.6 61.1 74.3 0.71 Second 63.6 38.9 51.9 0.61 83.6 49.3 67.3 0.59 Middle 66.1 37.8 53.4 0.57 86.4 51.2 70.6 0.59 Fourth 73.5 56.1 65.4 0.76 94.4 72.0 84.0 0.76 Highest 79.3 72.9 76.0 0.92 103.1 91.5 97.3 0.89 Total 69.4 50.4 60.4 0.73 90.4 64.8 78.3 0.72 SECONDARY SCHOOL Residence Urban 59.2 41.6 50.4 0.70 78.2 51.8 65.0 0.66 Rural 46.5 18.8 33.2 0.41 60.2 23.9 42.7 0.40 Province4 Kabul 58.2 39.6 49.0 0.68 77.9 50.0 64.1 0.64 Kapisa 64.5 33.8 48.2 0.52 80.7 42.2 60.3 0.52 Parwan 55.7 19.8 36.7 0.36 67.6 22.9 43.9 0.34 Wardak 51.9 4.4 29.8 0.09 66.9 6.1 38.6 0.09 Logar 63.2 29.2 48.5 0.46 81.8 35.8 61.9 0.44 Nangarhar 57.1 21.4 39.2 0.37 79.3 30.1 54.7 0.38 Laghman 47.2 9.4 29.7 0.20 60.9 13.9 39.2 0.23 Panjsher 76.3 50.6 64.2 0.66 109.3 69.7 90.7 0.64 Baghlan 50.4 17.0 34.0 0.34 68.3 20.9 45.0 0.31 Bamyan 57.3 33.2 44.0 0.58 76.3 41.9 57.3 0.55 Ghazni 62.4 39.2 50.5 0.63 82.9 49.3 65.6 0.59 Paktika 61.5 2.4 35.1 0.04 71.2 3.8 41.1 0.05 Paktya 60.0 9.1 41.7 0.15 74.8 10.8 51.7 0.14 Khost 58.7 9.5 37.1 0.16 73.5 13.0 46.9 0.18 Kunarha 59.4 17.6 41.8 0.30 71.8 21.6 50.7 0.30 Nooristan 39.3 5.1 23.1 0.13 46.8 6.2 27.5 0.13 (Continued…) 28 • Housing Characteristics and Household Population Table 2.13—Continued Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender parity index3 Male Female Total Gender parity index3 Badakhshan 45.9 36.4 41.5 0.79 61.1 43.8 53.1 0.72 Takhar 42.6 22.8 32.4 0.54 53.2 29.1 40.8 0.55 Kunduz 38.5 18.7 29.3 0.49 55.3 23.0 40.3 0.42 Samangan 42.5 22.7 33.5 0.53 54.3 27.8 42.3 0.51 Balkh 49.4 33.5 41.5 0.68 58.5 41.5 50.0 0.71 Sar-E-Pul 25.0 19.4 22.2 0.77 33.6 23.1 28.3 0.69 Ghor 66.5 31.7 50.4 0.48 90.6 38.7 66.6 0.43 Daykundi 59.4 45.2 51.2 0.76 77.7 56.6 65.5 0.73 Urozgan 15.5 3.2 9.2 0.21 20.7 3.7 11.9 0.18 Kandahar 34.3 5.1 19.8 0.15 45.2 7.3 26.4 0.16 Jawzjan 64.4 34.7 51.6 0.54 81.5 42.9 64.8 0.53 Faryab 55.3 38.0 46.5 0.69 75.7 47.3 61.2 0.62 Helmand 48.9 13.9 33.6 0.28 63.9 19.5 44.6 0.30 Badghis 20.2 10.5 15.4 0.52 30.2 13.9 22.1 0.46 Herat 34.0 23.4 28.7 0.69 41.6 28.5 35.1 0.68 Farah 40.9 12.3 25.6 0.30 52.8 16.2 33.2 0.31 Nimroz 30.7 16.4 23.0 0.53 38.8 20.6 29.0 0.53 Wealth quintile Lowest 38.4 15.9 27.6 0.41 50.9 20.3 36.2 0.40 Second 46.4 16.9 31.9 0.36 59.1 21.6 40.7 0.36 Middle 43.9 17.3 31.0 0.40 57.0 20.4 39.3 0.36 Fourth 55.4 28.9 42.7 0.52 70.4 36.0 53.8 0.51 Highest 64.1 44.0 54.1 0.69 85.4 56.3 71.0 0.66 Total 49.8 25.1 37.8 0.50 64.8 31.5 48.6 0.49 1 The NAR for primary school is the percentage of the primary school age (7-12 years) population that is attending primary school. The NAR for secondary school is the percentage of the secondary school age (13-18 years) population that is attending secondary school. By definition, the NAR cannot exceed 100%. 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%. 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. 4 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Table 2.14 Reasons for children never attending school Percent distribution of de facto household members age 5-24 who never attended school by the main reason for not attending school, according to sex and residence, Afghanistan 2015 Reasons for never attending Residence Total Urban Rural Male Female Male Female Male Female Too expensive 1.3 0.9 0.3 0.3 0.5 0.4 School too far 8.1 6.3 18.6 12.0 17.0 11.1 Insecure 1.8 4.1 7.2 8.4 6.4 7.7 Need to help at home 3.7 2.1 5.5 2.5 5.3 2.4 Parents did not send 22.4 54.2 18.1 47.3 18.7 48.4 Got married 0.1 1.1 0.1 0.9 0.1 1.0 School lacked basic facilities 1.1 0.5 2.0 2.0 1.9 1.8 Need to work, earn 10.6 1.1 11.2 0.5 11.1 0.5 Other 50.8 29.8 36.9 26.2 38.9 26.8 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 2,403 4,046 13,789 22,600 16,192 26,650 Housing Characteristics and Household Population • 29 Table 2.15 Reasons for children dropping out of school Percent distribution of de facto household members age 5-24 who dropped out of school by the main reason for not attending school, according to sex and residence, Afghanistan 2015 Reasons for dropping out Residence Total Urban Rural Male Female Male Female Male Female Too expensive 1.5 2.8 0.6 0.2 0.8 1.1 School too far 1.0 2.3 2.6 6.2 2.1 4.7 Insecure 0.9 4.0 10.0 9.1 7.7 7.2 Need to help at home 18.2 7.1 13.9 4.5 15.0 5.5 Parents did not send 3.1 25.0 2.1 32.3 2.4 29.7 Got married 0.8 21.2 3.6 18.0 2.9 19.2 School lacked basic facilities 0.7 2.3 1.5 1.6 1.3 1.8 Need to work, earn 47.6 5.1 42.7 2.0 43.9 3.1 Other 26.3 30.3 23.2 26.1 24.0 27.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 Number 1,789 2,137 5,195 3,713 6,984 5,850 Characteristics of Respondents • 31 CHARACTERISTICS OF RESPONDENTS 3 Key Findings  Education: Nine percent of ever-married women and 31% of ever-married men age 15-49 in Afghanistan have completed at least some secondary education. However, only 5% of women and 17% of men have completed secondary school or beyond. Eighty-four percent of women and half of men have never attended school.  Literacy: Only 15% of women and 49% of men are literate.  Exposure to mass media: Nearly half of women (47%) and one-third of men (34%) have no regular exposure to any mass media.  Employment: Twelve percent of women and 91% of men are currently employed.  Tobacco use: Half of men use tobacco products, as compared with only 6% of women. his chapter presents information on the demographic and socioeconomic characteristics of the survey respondents such as age, education, place of residence, marital status, employment, and wealth status. This information is useful for understanding the factors that affect use of reproductive health services, contraceptive use, and other health behaviors. 3.1 BASIC CHARACTERISTICS OF SURVEY RESPONDENTS A total of 29,461 ever-married women and 10,760 ever-married men age 15-49 were interviewed in the 2015 AfDHS. Forty-eight percent of ever-married women and 35% percent of ever-married men are under age 30. Among those who have ever been married, 6% of women and only 1% of men are age 15-19, a reflection of the somewhat older age at marriage among men than women (Table 3.1). Three percent of women and only 1% of men are widowed or divorced. The geographical distributions of women and men are similar. More than three quarters of ever-married women and men (77% each) are living in rural areas, and about one quarter (23%) are living in urban areas. 3.2 EDUCATION AND LITERACY Literacy Respondents who had attended secondary school or higher were assumed to be literate. All other respondents were given a sentence to read, and they were considered to be literate if they could read all or part of the sentence. Sample: Ever-married women and men age 15-49 In Afghanistan, educational levels and literacy rates are both low. The proportion of ever-married women with no education is higher than the proportion among men (84% versus 51%) (Figure 3.1). Nine percent T 32 • Characteristics of Respondents of women and 31% of men have completed at least some secondary education. However, only 5% of women and 17% of men have completed secondary school or beyond (Table 3.2.1 and Table 3.2.2). Overall, 15% of women and 49% of men are literate (Table 3.3.1 and Table 3.3.2). Patterns by background characteristics  Younger respondents have more education than older ones. Ever-married women age 15- 19 are five times more likely than women age 45-49 to have completed at least some secondary education (17% versus 3%), and the pattern is similar for men (49% versus 24%) (Table 3.2.1 and Table 3.2.2).  Kabul (6%), Faryab (4%), and Jawzjan (4%) have the highest proportions of women with more than a secondary school education (Figure 3.2). The pattern is different among men; 15% of men in Kunarha, 14% in Nangarhar, and 13% each in Panjsher, Kapisa, and Jawzjan have more than a secondary education (Table 3.2.1 and Table 3.2.2).  Women in urban areas are more than three times as likely to be literate as those in rural areas (32% versus 10%). Similarly, urban men are more likely to be literate than rural men (65% versus 45%) (Table 3.3.1 and Table 3.3.2).  Women in the highest wealth quintile are six times more likely than those in the lowest quintile to have at least some secondary education (24% versus 4%); the gap is smaller among men (53% versus 21%). The literacy rate also increases with wealth, rising from 7-8% among women in the lowest three quintiles to 38% among those in the highest quintile and from 37% among men in the lowest quintile to 71% among those in the highest quintile (Table 3.2.1 and Table 3.2.2). Figure 3.1 Education of survey respondents 84 51 6 13 2 6 4 14 3 11 2 7 Women Men Percent distribution of ever-married women and men age 15-49 by highest level of schooling attended or completed More than secondary Completed secondary Some secondary Primary complete Primary incomplete No education Characteristics of Respondents • 33 Figure 3.2 Women with more than a secondary education Percentage of women age 15-49 with more than secondary education or higher 3.3 MASS MEDIA EXPOSURE Exposure to mass media Respondents were asked how often they read a newspaper, listened to the radio, or watched television. Those who responded at least once a week are considered to be regularly exposed to that form of media. Sample: Ever-married women and men age 15-49 Mass media are important means of conveying messages on family planning, HIV/AIDS awareness, and other health topics. In Afghanistan, ever-married men are more likely than women to be regularly exposed to all three major forms of mass media (newspapers, television, and radio) (Figure 3.3). About half of women (47%) and one-third of men (34%) are not regularly exposed to any of these media. Figure 3.3 Exposure to mass media 3 39 24 1 47 13 46 44 7 34 Reads newspaper Watches television Listens to radio All three media None of these media Percentage of ever-married women and men age 15-49 who are exposed to media on a weekly basis Women Men 34 • Characteristics of Respondents Patterns by background characteristics  Rural women are almost three times more likely than urban women to have no regular exposure to any form of mass media (55% versus 21%) (Table 3.4.1). The same pattern holds true for men (41% versus 11%) (Table 3.4.2).  Highly educated women and men are much more likely to have regular exposure to mass media. Only 6% of women and 7% of men with more than a secondary education lack regular exposure to any media, as compared with 52% of women and 46% of men with no education (Table 3.4.1 and Table 3.4.2). 3.4 EMPLOYMENT Currently employed Respondents who were employed in the 7 days before the survey. Sample: Ever-married women and men age 15-49 Men are more likely than women to be employed. Ninety-one percent of ever-married men are currently employed, compared with 12% of ever-married women (Tables 3.5.1 and 3.5.2). An additional 5% of men and 2% of women reported working in the past 12 months even though they were not currently employed. Patterns by background characteristics  Women are more likely to work if they are divorced, separated, or widowed than if they are married (21% versus 11%). There is no relation between men’s marital status and employment (Table 3.5.1 and Table 3.5.2).  Women with more than a secondary education are almost four times as likely as women with no education to be currently employed (41% versus 11%). Among men, employment is not related to education (Figure 3.4).  There are large provincial differences in employment levels, especially for women. However, there is no difference in current employment levels by urban-rural residence among either women or men (Table 3.5.1 and Table 3.5.2). 3.5 OCCUPATION Occupation Categorized as professional/technical/managerial, clerical, sales and services, skilled manual, unskilled manual, domestic service, agriculture, and other. Sample: Ever-married women and men age 15-49 who were currently employed or had worked in the 12 months before the survey Women are most often employed in professional, technical, or managerial positions (50%), followed by skilled manual jobs (25%) (Table 3.6.1). Men are most commonly employed in agriculture (31%) and skilled manual labor (20%) (Table 3.6.2, Figure 3.5). Figure 3.4. Employment by education 11 14 15 41 12 91 93 92 91 91 No education Primary Secondary More than secondary Total Percentage of ever-married women and men age 15-49 who are currently employed Women Men Characteristics of Respondents • 35 Patterns by background characteristics  Agriculture is the leading occupation in rural areas for men (39%); among rural women, however, the leading type of occupation is professional/technical/managerial (41%). In urban areas, the most common occupations are professional/technical/managerial among women (77%) and sales and services and skilled manual labor among men (29% and 25%, respectively) (Table 3.6.1 and Table 3.6.2).  Most women and men with more than a secondary education are employed in professional, technical, and managerial occupations (91% and 62%, respectively). Men with no education or only a primary education most often work in agriculture (Table 3.6.1 and Table 3.6.2).  Employed men in the lowest wealth quintile are concentrated in agricultural occupations (55%). In the highest wealth quintile, the most common occupations are professional/technical/managerial among women (84%) and sales and services among men (31%) (Table 3.6.1 and Table 3.6.2).  Most of the women who had worked in the past year were employed entirely for cash (61%); however, 27% worked without pay. Cash earnings were more common for work in the non- agricultural sector than for jobs in agriculture (Table 3.7). Women employed in the agricultural sector were more likely to work for a family member (93%) than those employed in the non- agricultural sector (42%). 3.6 TOBACCO AND DRUG USE The vast majority of women (94%) and more than half of men age 15-49 (52%) reported that they do not use any tobacco product (Table 3.8.1 and Table 3.8.2). Among men, 22% smoke cigarettes (Figure 3.6). Fifty-eight percent of these men reported smoking 10 or more cigarettes in the 24 hours prior to the interview. Patterns by background characteristics  Among men, cigarette smoking generally rises with age, from a low of 14% among men age 15-19 to 28% among men age 35-39 (Table 3.8.2).  There is little difference in cigarette smoking among men by residence. Twenty-four percent of men in urban areas and 21% of men in rural areas smoke cigarettes.  Men with more than a secondary education are less likely to smoke cigarettes than men with less education (10% versus 19-24%).  Use of drugs is not common among ever-married women, while 3% of ever-married men reported using drugs (Table 3.9). The most commonly used drug is opium, reported by 45% of men who use drugs. Figure 3.5 Occupation 31 17 20 17 3 12 16 8 25 1 0 50 Agriculture Unskilled manual Skilled manual Sales and services Clerical Professional/ technical/ managerial Percentage of ever-married women and men age 15-49 by occupation Women Men 36 • Characteristics of Respondents 3.7 KNOWLEDGE OF TUBERCULOSIS Knowledge of tuberculosis among the general population is widespread. The majority of ever- married women and men have heard of tuberculosis (82% and 83%, respectively). Among those who have heard of tuberculosis, 63% of women and 72% of men believe that the disease can spread through the air via coughing. More than four in five women (81%) and men (88%) believe that tuberculosis can be cured, while 7% of women and 5% of men have ever been told by a doctor or nurse that they had tuberculosis (Table 3.10.1 and Table 3.10.2). Patterns by background characteristics  Among women who have heard of tuberculosis, there is a slight rise with age in the proportion who were ever told they had the disease, from 5% among those age 15-19 to 10% among those age 45- 49. There is no such pattern among men (Table 3.10.1 and Table 3.10.2).  Data by residence show that rural women are twice as likely as urban women to have been diagnosed with tuberculosis (8% versus 4%). However, there are minimal differences among men by urban and rural residence (4% versus 5%). 3.8 KNOWLEDGE OF HEPATITIS Overall, 67% of both women and men have heard of hepatitis. The results in Table 3.11.1 and Table 3.11.2 indicate that knowledge about ways to prevent hepatitis is slightly higher among men than among women. Among those who have heard of hepatitis, women most often reported avoiding contaminated food and water (21%), using disposable syringes (20%), and having safe sex and safe blood transfusions (17% each) as means of avoiding the disease. Similarly, men most often reported using disposable syringes and having safe sex (32% each). Patterns by background characteristics  There is a slight rise with age in knowledge of hepatitis, from 64% among women age 15-19 to 71% among women age 45-49. The pattern is similar among men (59% and 69%, respectively) (Table 3.11.1 and Table 3.11.2).  There is no difference in awareness of hepatitis between rural and urban respondents.  Knowledge of hepatitis increases with increasing education. Sixty-six percent of women and 61% men who have no education have heard of hepatitis, as compared with 83% of women and 90% of men with more than a secondary education. 3.9 HEPATITIS PREVALENCE Among ever-married women and men who have heard of hepatitis, 8% of women and 6% of men have ever been told by a doctor or nurse that they had hepatitis. Among women ever diagnosed with hepatitis, 60%, 25%, and 11% were diagnosed with hepatitis A, B, and C, respectively. Two in five women who had ever been diagnosed with hepatitis were currently suffering from it, as compared with only 16% of men (Table 3.12.1 and Table 3.12.2). Figure 3.6 Use of tobacco 1 3 3 22 2 32 Cigarettes Chelam Other tobacco products Percentage of ever-married women and men age 15-49 who use specific types of tobacco Women Men Characteristics of Respondents • 37 3.10 CANCER PREVALENCE AND DEATHS RELATED TO CANCER All households were asked if any household members had been diagnosed with cancer. Overall, 3% of households reported that a member had been diagnosed with cancer (Table 3.13). Among the households that reported a member diagnosed with cancer, 21% had members diagnosed with breast cancer and 19% each had members diagnosed with intestinal cancer and liver cancer. Sixteen percent had a member diagnosed with lung cancer, and 5% reported a member diagnosed with cervical cancer. Among households in which any member had been diagnosed with cancer, 16% had a death in the three years before the survey from breast cancer, 14% had a death from liver cancer, 11% had a death from intestinal cancer, 10% had a death from lung cancer, and 3% had a death from cervical cancer (Table 3.14). Patterns by background characteristics  Among households that reported a member diagnosed with cancer, the proportion in which a cancer death occurred in the three years before the survey was about twice as high in rural areas as in urban areas.  Fifty-nine percent of households in the highest wealth quintile in which a member had been diagnosed with cancer reported no cancer deaths, as compared with only 31% of households in the lowest quintile. LIST OF TABLES For more information on the characteristics of survey respondents, see the following tables:  Table 3.1 Background characteristics of respondents  Table 3.2.1 Educational attainment: Women  Table 3.2.2 Educational attainment: Men  Table 3.3.1 Literacy: Women  Table 3.3.2 Literacy: Men  Table 3.4.1 Exposure to mass media: Women  Table 3.4.2 Exposure to mass media: Men  Table 3.5.1 Employment status: Women  Table 3.5.2 Employment status: Men  Table 3.6.1 Occupation: Women  Table 3.6.2 Occupation: Men  Table 3.7 Type of employment: Women  Table 3.8.1 Use of tobacco: Women  Table 3.8.2 Use of tobacco: Men  Table 3.9 Use of drugs  Table 3.10.1 Knowledge concerning tuberculosis: Women  Table 3.10.2 Knowledge concerning tuberculosis: Men  Table 3.11.1 Knowledge concerning hepatitis: Women  Table 3.11.2 Knowledge concerning hepatitis: Men  Table 3.12.1 Reported prevalence of hepatitis: Women 38 • Characteristics of Respondents  Table 3.12.2 Reported prevalence of hepatitis: Men  Table 3.13 Households with members diagnosed with cancer  Table 3.14 Deaths of household members diagnosed with cancer Characteristics of Respondents • 39 Table 3.1 Background characteristics of respondents Percent distribution of ever-married women and ever-married men age 15-49 by selected background characteristics, Afghanistan 2015 Women Men Background characteristic Weighted percent Weighted number Un- weighted number Weighted percent Weighted number Un- weighted number Age 15-19 6.2 1,825 1,829 1.3 142 158 20-24 20.7 6,089 6,083 10.8 1,162 1,302 25-29 21.4 6,299 6,447 22.5 2,422 2,355 30-34 14.6 4,302 4,481 18.7 2,008 2,017 35-39 15.1 4,463 4,304 18.0 1,935 1,850 40-44 10.6 3,113 3,191 13.0 1,402 1,483 45-49 11.4 3,369 3,126 15.7 1,688 1,595 Marital status Married 97.3 28,671 28,661 99.3 10,679 10,687 Divorced/separated 0.2 59 86 0.2 17 14 Widowed 2.5 731 714 0.6 64 59 Residence Urban 23.3 6,870 7,025 23.0 2,479 2,333 Rural 76.7 22,591 22,436 77.0 8,281 8,427 Province1 Kabul 12.4 3,658 755 12.5 1,350 207 Kapisa 0.7 205 874 0.6 63 280 Parwan 2.1 625 744 2.0 220 259 Wardak 1.3 382 870 1.6 171 418 Logar 1.6 472 915 1.9 204 404 Nangarhar 2.7 794 1,023 2.5 273 353 Laghman 2.0 583 800 2.1 227 334 Panjsher 0.2 54 681 0.2 18 202 Baghlan 2.8 839 740 2.6 281 246 Bamyan 1.0 303 652 0.9 94 193 Ghazni 4.5 1,328 1,146 5.8 619 576 Paktika 2.7 792 1,110 3.0 322 451 Paktya 1.8 542 1,174 1.9 206 472 Khost 2.9 851 1,338 3.1 334 560 Kunarha 1.9 559 734 1.4 151 186 Nooristan 0.8 222 1,398 0.6 66 419 Badakhshan 3.4 1,004 835 2.9 316 246 Takhar 3.8 1,105 819 2.8 296 217 Kunduz 4.2 1,232 839 4.5 479 297 Samangan 1.1 330 682 1.2 125 269 Balkh 6.0 1,781 909 5.7 616 314 Sar-E-Pul 2.2 654 812 1.8 195 260 Ghor 2.4 715 886 3.0 322 398 Daykundi 1.1 329 669 0.7 77 150 Urozgan 0.8 230 805 0.9 92 337 Kandahar 7.6 2,227 952 8.1 874 411 Jawzjan 2.1 614 865 2.0 218 331 Faryab 7.2 2,114 742 6.6 706 230 Helmand 3.0 875 843 3.3 355 344 Badghis 2.2 650 875 2.1 231 304 Herat 7.9 2,316 989 8.0 863 367 Farah 2.6 777 1,133 2.7 295 457 Nimroz 0.9 278 680 0.9 93 199 Education No education 83.5 24,604 25,201 50.6 5,447 5,516 Primary 7.9 2,330 1,978 18.5 1,987 1,741 Secondary 6.7 1,971 1,786 24.5 2,632 2,717 More than secondary 1.9 556 496 6.5 695 786 Wealth quintile Lowest 20.0 5,904 5,647 18.9 2,029 1,965 Second 20.4 6,001 6,756 20.8 2,233 2,482 Middle 20.0 5,888 6,356 20.1 2,160 2,420 Fourth 20.4 6,010 6,253 21.0 2,260 2,387 Highest 19.2 5,657 4,449 19.3 2,078 1,506 Total 100.0 29,461 29,461 100.0 10,760 10,760 Note: Education categories refer to the highest level of education attended. 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 40 • Characteristics of Respondents Table 3.2.1 Educational attainment: Women Percent distribution of ever-married women age 15-49 by highest level of schooling attended or completed, according to background characteristics, Afghanistan 2015 Highest level of schooling Background characteristic No edu- cation Some primary Com- pleted primary1 Some secon- dary Com- pleted secon- dary2 More than secon- dary Total Number of women Age 15-24 71.4 8.7 3.7 8.7 4.9 2.6 100.0 7,915 15-19 67.6 11.2 4.1 12.7 3.4 1.2 100.0 1,825 20-24 72.6 7.9 3.6 7.5 5.3 3.0 100.0 6,089 25-29 83.0 6.8 1.9 3.5 3.0 1.9 100.0 6,299 30-34 88.4 4.8 1.6 2.4 1.5 1.2 100.0 4,302 35-39 90.3 3.1 1.0 2.4 1.1 2.1 100.0 4,463 40-44 90.9 4.1 0.8 1.6 1.0 1.6 100.0 3,113 45-49 90.9 5.0 0.7 0.9 1.4 1.0 100.0 3,369 Residence Urban 66.9 10.1 3.3 8.0 6.0 5.7 100.0 6,870 Rural 88.6 4.7 1.6 2.9 1.6 0.7 100.0 22,591 Province3 Kabul 65.7 10.4 3.8 8.1 6.5 5.5 100.0 3,658 Kapisa 77.2 6.8 4.0 5.3 4.0 2.7 100.0 205 Parwan 86.0 4.6 1.6 3.0 2.3 2.5 100.0 625 Wardak 94.5 3.1 0.8 1.3 0.2 0.0 100.0 382 Logar 72.4 8.4 3.8 8.5 5.2 1.7 100.0 472 Nangarhar 84.6 6.4 2.4 3.6 1.7 1.3 100.0 794 Laghman 92.2 4.2 0.7 1.5 0.8 0.5 100.0 583 Panjsher 82.4 5.3 1.7 4.3 5.2 1.2 100.0 54 Baghlan 85.3 4.0 3.3 4.3 1.9 1.3 100.0 839 Bamyan 84.5 6.0 2.6 4.9 0.9 1.0 100.0 303 Ghazni 89.4 4.3 1.7 3.0 0.9 0.7 100.0 1,328 Paktika 98.7 0.2 0.3 0.4 0.4 0.0 100.0 792 Paktya 96.6 2.0 0.4 0.6 0.4 0.1 100.0 542 Khost 98.5 0.3 0.4 0.8 0.0 0.0 100.0 851 Kunarha 89.8 3.9 2.6 2.1 1.1 0.5 100.0 559 Nooristan 96.4 1.8 0.6 0.9 0.3 0.0 100.0 222 Badakhshan 76.3 7.2 3.5 8.0 3.2 1.8 100.0 1,004 Takhar 84.9 4.4 1.6 5.2 1.5 2.4 100.0 1,105 Kunduz 90.2 4.4 0.6 2.2 1.2 1.5 100.0 1,232 Samangan 88.2 3.7 1.7 3.8 1.1 1.5 100.0 330 Balkh 77.4 9.5 2.0 4.8 4.4 1.9 100.0 1,781 Sar-E-Pul 80.6 7.0 5.4 4.2 1.5 1.2 100.0 654 Ghor 89.0 1.5 2.9 3.8 2.1 0.7 100.0 715 Daykundi 82.3 2.9 1.8 8.7 2.8 1.5 100.0 329 Urozgan 98.2 0.1 0.2 1.0 0.5 0.0 100.0 230 Kandahar 95.5 1.9 0.8 1.0 0.6 0.3 100.0 2,227 Jawzjan 72.6 12.0 2.7 3.2 5.9 3.5 100.0 614 Faryab 72.1 10.4 2.0 6.0 6.1 3.5 100.0 2,114 Helmand 94.5 1.1 1.0 2.2 0.6 0.5 100.0 875 Badghis 93.3 3.9 1.5 0.9 0.3 0.1 100.0 650 Herat 82.4 8.3 1.0 4.4 1.6 2.3 100.0 2,316 Farah 91.9 4.4 0.9 1.4 1.0 0.3 100.0 777 Nimroz 77.5 11.9 1.5 6.0 2.1 0.9 100.0 278 Wealth quintile Lowest 90.6 4.2 1.7 2.5 0.8 0.3 100.0 5,904 Second 91.0 4.5 1.0 2.4 0.8 0.3 100.0 6,001 Middle 90.8 4.1 1.2 2.2 1.3 0.4 100.0 5,888 Fourth 81.6 7.4 2.2 4.6 2.6 1.5 100.0 6,010 Highest 62.7 9.6 3.7 9.0 7.8 7.2 100.0 5,657 Total 83.5 6.0 2.0 4.1 2.6 1.9 100.0 29,461 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 3 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Characteristics of Respondents • 41 Table 3.2.2 Educational attainment: Men Percent distribution of ever-married men age 15-49 by highest level of schooling attended or completed, and median years completed, according to background characteristics, Afghanistan 2015 Highest level of schooling Background characteristic No edu- cation Some primary Com- pleted primary1 Some secon- dary Com- pleted secon- dary2 More than secon- dary Total Median years com- pleted Number of men Age 15-24 42.8 10.8 5.0 19.1 14.6 7.8 100.0 4.3 1,305 15-19 28.9 11.6 10.2 33.6 12.5 3.3 100.0 5.9 142 20-24 44.5 10.7 4.3 17.3 14.8 8.3 100.0 4.0 1,162 25-29 44.4 11.7 7.0 15.5 13.2 8.2 100.0 2.6 2,422 30-34 49.2 15.9 5.8 13.4 10.0 5.7 100.0 1.3 2,008 35-39 50.8 13.0 5.1 12.6 12.3 6.3 100.0 0.0 1,935 40-44 59.1 13.2 5.7 9.5 6.8 5.7 100.0 0.0 1,402 45-49 60.0 11.1 5.3 11.5 7.3 4.8 100.0 0.0 1,688 Residence Urban 31.3 16.3 6.7 16.9 15.8 13.0 100.0 5.4 2,479 Rural 56.4 11.6 5.5 12.6 9.4 4.5 100.0 0.0 8,281 Province3 Kabul 28.4 16.4 6.9 18.3 18.4 11.6 100.0 5.8 1,350 Kapisa 26.7 18.0 8.6 20.0 13.7 12.8 100.0 5.6 63 Parwan 38.3 13.9 3.3 22.1 12.0 10.4 100.0 4.2 220 Wardak 49.4 5.7 6.0 15.0 13.5 10.4 100.0 1.7 171 Logar 35.6 11.7 2.9 22.0 20.2 7.6 100.0 5.9 204 Nangarhar 38.5 11.4 6.2 17.8 12.3 13.8 100.0 5.0 273 Laghman 51.6 13.4 5.7 13.1 9.1 7.2 100.0 0.0 227 Panjsher 32.2 6.5 3.5 17.1 27.6 13.2 100.0 8.1 18 Baghlan 43.4 8.2 8.5 16.1 17.6 6.1 100.0 4.1 281 Bamyan 60.7 14.4 3.1 10.2 3.3 8.2 100.0 0.0 94 Ghazni 58.9 10.9 8.0 12.7 5.4 4.2 100.0 0.0 619 Paktika 59.2 2.5 3.6 13.4 16.6 4.8 100.0 0.0 322 Paktya 52.7 11.0 6.4 14.4 9.5 6.0 100.0 0.0 206 Khost 57.2 2.5 9.0 9.8 15.5 6.1 100.0 0.0 334 Kunarha 44.7 9.8 6.7 13.6 10.3 14.9 100.0 3.3 151 Nooristan 66.6 5.2 3.4 15.4 7.7 1.7 100.0 0.0 66 Badakhshan 54.9 16.0 3.1 10.3 8.7 7.0 100.0 0.0 316 Takhar 58.9 19.2 3.2 7.5 4.8 6.4 100.0 0.0 296 Kunduz 56.3 13.6 1.8 13.8 9.5 4.9 100.0 0.0 479 Samangan 69.0 4.5 6.9 8.8 5.9 4.9 100.0 0.0 125 Balkh 50.2 16.4 6.2 14.7 7.0 5.4 100.0 0.0 616 Sar-E-Pul 54.8 21.3 9.4 7.4 3.0 4.1 100.0 0.0 195 Ghor 49.8 3.7 4.2 13.8 20.9 7.6 100.0 2.1 322 Daykundi 63.1 13.8 1.5 10.8 7.8 2.9 100.0 0.0 77 Urozgan 81.4 3.8 1.3 7.4 5.1 1.1 100.0 0.0 92 Kandahar 69.0 8.4 3.8 9.8 5.6 3.5 100.0 0.0 874 Jawzjan 32.3 16.8 4.1 11.9 21.7 13.2 100.0 5.2 218 Faryab 33.7 20.2 11.8 16.1 15.0 3.2 100.0 4.3 706 Helmand 44.7 12.2 9.2 21.7 8.5 3.7 100.0 3.6 355 Badghis 77.1 5.9 1.2 11.2 3.2 1.4 100.0 0.0 231 Herat 63.5 14.1 3.5 9.2 4.2 5.4 100.0 0.0 863 Farah 58.2 16.1 7.3 7.2 8.8 2.4 100.0 0.0 295 Nimroz 61.4 19.0 3.4 8.5 5.3 2.4 100.0 0.0 93 Wealth quintile Lowest 64.3 10.5 4.4 10.3 7.8 2.6 100.0 0.0 2,029 Second 60.0 12.7 5.9 11.8 6.7 3.0 100.0 0.0 2,233 Middle 58.3 11.0 6.0 12.1 8.7 3.9 100.0 0.0 2,160 Fourth 44.3 15.0 6.0 15.1 12.3 7.2 100.0 2.9 2,260 Highest 26.1 14.1 6.5 18.6 19.0 15.7 100.0 6.8 2,078 Total 50.6 12.7 5.8 13.6 10.9 6.5 100.0 0.0 10,760 1 Completed grade 6 at the primary level 2 Completed grade 12 at the secondary level 3 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 42 • Characteristics of Respondents Table 3.3.1 Literacy: Women Percent distribution of ever-married women age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Afghanistan 2015 No schooling or primary school Background characteristic Secon- dary school or higher Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Total Percent- age literate1 Number of women Age 15-24 16.2 3.2 6.2 74.3 0.1 0.0 0.1 100.0 25.5 7,915 15-19 17.2 3.6 6.8 72.3 0.0 0.0 0.1 100.0 27.6 1,825 20-24 15.9 3.0 6.0 74.9 0.1 0.0 0.1 100.0 24.9 6,089 25-29 8.3 1.8 5.3 84.3 0.1 0.0 0.2 100.0 15.5 6,299 30-34 5.2 1.5 3.6 89.6 0.0 0.0 0.2 100.0 10.3 4,302 35-39 5.6 1.3 3.1 89.9 0.0 0.0 0.1 100.0 10.0 4,463 40-44 4.2 1.0 3.0 91.8 0.0 0.0 0.0 100.0 8.2 3,113 45-49 3.4 0.8 2.0 93.7 0.0 0.0 0.0 100.0 6.2 3,369 Residence Urban 19.7 5.0 7.3 67.9 0.0 0.0 0.0 100.0 32.1 6,870 Rural 5.2 0.9 3.4 90.3 0.0 0.0 0.1 100.0 9.5 22,591 Province2 Kabul 20.1 5.8 7.2 66.6 0.2 0.0 0.0 100.0 33.2 3,658 Kapisa 12.0 2.1 6.0 79.5 0.0 0.0 0.4 100.0 20.1 205 Parwan 7.8 0.4 4.0 87.4 0.0 0.0 0.4 100.0 12.2 625 Wardak 1.5 2.2 3.3 92.9 0.0 0.0 0.1 100.0 7.0 382 Logar 15.4 0.1 9.6 74.7 0.0 0.0 0.3 100.0 25.0 472 Nangarhar 6.6 1.5 3.1 88.3 0.2 0.0 0.3 100.0 11.2 794 Laghman 2.8 0.2 4.0 92.7 0.0 0.1 0.1 100.0 7.1 583 Panjsher 10.7 1.3 9.2 78.3 0.0 0.0 0.5 100.0 21.1 54 Baghlan 7.5 1.5 4.8 86.2 0.0 0.0 0.0 100.0 13.8 839 Bamyan 6.8 2.7 4.6 85.1 0.0 0.0 0.7 100.0 14.2 303 Ghazni 4.6 2.1 4.6 88.6 0.0 0.0 0.1 100.0 11.3 1,328 Paktika 0.8 0.3 1.3 97.3 0.0 0.1 0.3 100.0 2.3 792 Paktya 1.1 0.1 1.8 96.7 0.0 0.0 0.4 100.0 3.0 542 Khost 0.9 0.2 0.6 98.3 0.0 0.0 0.0 100.0 1.7 851 Kunarha 3.7 0.3 4.5 91.3 0.0 0.2 0.0 100.0 8.4 559 Nooristan 1.2 0.5 1.4 96.8 0.0 0.0 0.1 100.0 3.1 222 Badakhshan 13.0 1.2 5.3 80.6 0.0 0.0 0.0 100.0 19.4 1,004 Takhar 9.1 1.0 4.4 85.5 0.0 0.0 0.0 100.0 14.5 1,105 Kunduz 4.8 1.0 3.9 89.7 0.0 0.0 0.6 100.0 9.7 1,232 Samangan 6.5 1.0 3.6 88.8 0.0 0.0 0.2 100.0 11.0 330 Balkh 11.2 2.5 4.0 82.3 0.0 0.0 0.0 100.0 17.7 1,781 Sar-E-Pul 7.0 4.0 5.9 83.0 0.0 0.0 0.0 100.0 17.0 654 Ghor 6.7 0.2 2.7 90.4 0.0 0.0 0.0 100.0 9.5 715 Daykundi 13.0 1.4 3.8 81.7 0.0 0.0 0.2 100.0 18.1 329 Urozgan 1.5 0.2 0.0 98.0 0.0 0.0 0.2 100.0 1.8 230 Kandahar 1.9 1.0 3.7 93.4 0.0 0.0 0.0 100.0 6.6 2,227 Jawzjan 12.6 0.9 6.6 79.9 0.0 0.0 0.0 100.0 20.1 614 Faryab 15.5 0.3 3.0 81.1 0.0 0.0 0.0 100.0 18.9 2,114 Helmand 3.3 0.2 1.7 94.5 0.0 0.0 0.2 100.0 5.3 875 Badghis 1.3 0.5 2.4 95.6 0.0 0.0 0.2 100.0 4.2 650 Herat 8.3 2.3 6.0 83.4 0.0 0.0 0.1 100.0 16.5 2,316 Farah 2.8 3.2 2.2 91.7 0.0 0.0 0.1 100.0 8.2 777 Nimroz 9.0 5.0 6.6 79.4 0.0 0.0 0.0 100.0 20.6 278 Wealth quintile Lowest 3.5 0.7 3.4 92.3 0.0 0.0 0.1 100.0 7.5 5,904 Second 3.5 0.7 2.9 92.8 0.0 0.0 0.1 100.0 7.0 6,001 Middle 3.9 0.8 2.8 92.3 0.0 0.0 0.1 100.0 7.6 5,888 Fourth 8.7 1.5 5.0 84.6 0.1 0.0 0.2 100.0 15.2 6,010 Highest 24.0 5.8 7.7 62.5 0.0 0.0 0.0 100.0 37.5 5,657 Total 8.6 1.8 4.3 85.1 0.0 0.0 0.1 100.0 14.8 29,461 1 Refers to women who attended secondary school or higher and women who can read a whole sentence or part of a sentence 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Characteristics of Respondents • 43 Table 3.3.2 Literacy: Men Percent distribution of ever-married men age 15-49 by level of schooling attended and level of literacy, and percentage literate, according to background characteristics, Afghanistan 2015 No schooling or primary school Background characteristic Secon- dary school or higher Can read a whole sentence Can read part of a sentence Cannot read at all No card with required language Blind/ visually impaired Missing Total Percent- age literate1 Number of men Age 15-24 41.4 5.6 9.7 43.2 0.0 0.0 0.1 100.0 56.7 1,305 15-19 49.4 9.3 10.0 31.4 0.0 0.0 0.0 100.0 68.6 142 20-24 40.5 5.1 9.7 44.6 0.0 0.0 0.2 100.0 55.2 1,162 25-29 36.9 5.8 9.9 47.2 0.0 0.1 0.1 100.0 52.5 2,422 30-34 29.1 5.7 15.5 49.1 0.0 0.0 0.5 100.0 50.3 2,008 35-39 31.1 6.8 11.3 50.6 0.0 0.1 0.2 100.0 49.2 1,935 40-44 22.0 6.2 14.1 57.6 0.0 0.0 0.1 100.0 42.3 1,402 45-49 23.6 6.5 13.3 56.4 0.1 0.0 0.1 100.0 43.4 1,688 Residence Urban 45.7 6.7 12.5 35.0 0.0 0.0 0.1 100.0 64.9 2,479 Rural 26.5 5.9 12.2 55.1 0.0 0.0 0.2 100.0 44.6 8,281 Province2 Kabul 48.3 7.1 10.3 34.3 0.0 0.0 0.0 100.0 65.7 1,350 Kapisa 46.6 1.5 14.6 37.2 0.0 0.0 0.0 100.0 62.8 63 Parwan 44.5 2.6 9.6 42.9 0.0 0.0 0.4 100.0 56.7 220 Wardak 38.9 11.0 8.5 41.0 0.0 0.6 0.0 100.0 58.4 171 Logar 49.8 1.5 9.4 39.1 0.0 0.0 0.2 100.0 60.7 204 Nangarhar 44.0 2.4 14.2 38.5 0.2 0.0 0.7 100.0 60.6 273 Laghman 29.4 1.1 17.3 51.8 0.0 0.0 0.4 100.0 47.8 227 Panjsher 57.9 1.4 6.9 33.5 0.0 0.0 0.3 100.0 66.2 18 Baghlan 39.9 4.4 14.6 41.2 0.0 0.0 0.0 100.0 58.8 281 Bamyan 21.7 18.5 18.0 41.3 0.0 0.0 0.4 100.0 58.2 94 Ghazni 22.2 9.1 11.8 54.6 0.2 0.0 2.1 100.0 43.1 619 Paktika 34.8 1.5 14.5 48.9 0.0 0.0 0.3 100.0 50.8 322 Paktya 29.9 5.1 10.7 54.3 0.0 0.0 0.0 100.0 45.7 206 Khost 31.4 9.3 4.1 55.2 0.0 0.0 0.0 100.0 44.8 334 Kunarha 38.7 0.6 10.6 50.1 0.0 0.0 0.0 100.0 49.9 151 Nooristan 24.8 8.1 22.0 44.9 0.2 0.0 0.0 100.0 54.9 66 Badakhshan 26.0 4.4 13.7 56.0 0.0 0.0 0.0 100.0 44.0 316 Takhar 18.7 7.1 7.8 66.4 0.0 0.0 0.0 100.0 33.6 296 Kunduz 28.2 2.9 8.6 60.2 0.0 0.0 0.0 100.0 39.8 479 Samangan 19.6 5.1 8.2 67.0 0.0 0.0 0.0 100.0 33.0 125 Balkh 27.1 6.9 10.8 55.1 0.0 0.0 0.0 100.0 44.9 616 Sar-E-Pul 14.4 13.5 18.7 53.3 0.0 0.0 0.0 100.0 46.7 195 Ghor 42.2 2.7 6.9 48.2 0.0 0.0 0.0 100.0 51.8 322 Daykundi 21.6 11.8 12.7 54.0 0.0 0.0 0.0 100.0 46.0 77 Urozgan 13.6 1.3 3.4 81.7 0.0 0.0 0.0 100.0 18.3 92 Kandahar 18.8 2.2 14.0 64.9 0.0 0.0 0.0 100.0 35.1 874 Jawzjan 46.7 4.5 10.8 37.9 0.0 0.0 0.0 100.0 62.1 218 Faryab 34.3 6.9 13.9 44.9 0.0 0.0 0.0 100.0 55.1 706 Helmand 33.9 2.1 18.3 44.9 0.0 0.0 0.8 100.0 54.3 355 Badghis 15.8 3.1 9.4 71.7 0.0 0.0 0.0 100.0 28.3 231 Herat 18.9 10.9 16.0 53.9 0.0 0.3 0.0 100.0 45.8 863 Farah 18.5 14.2 17.6 49.6 0.0 0.0 0.1 100.0 50.3 295 Nimroz 16.2 12.5 13.8 57.4 0.0 0.0 0.2 100.0 42.4 93 Wealth quintile Lowest 20.8 5.3 10.9 62.9 0.0 0.0 0.1 100.0 37.1 2,029 Second 21.4 6.7 13.1 58.4 0.1 0.0 0.3 100.0 41.2 2,233 Middle 24.7 5.7 11.6 57.5 0.0 0.1 0.4 100.0 42.0 2,160 Fourth 34.7 6.5 13.7 44.8 0.0 0.0 0.2 100.0 55.0 2,260 Highest 53.3 6.2 11.6 28.9 0.0 0.0 0.1 100.0 71.0 2,078 Total 30.9 6.1 12.2 50.5 0.0 0.0 0.2 100.0 49.3 10,760 1 Refers to men who attended secondary school or higher and men who can read a whole sentence or part of a sentence 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 44 • Characteristics of Respondents Table 3.4.1 Exposure to mass media: Women Percentage of ever-married women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Afghanistan 2015 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to radio at least once a week 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 4.3 36.7 23.5 1.5 47.9 1,825 20-24 3.5 37.6 27.0 1.1 46.4 6,089 25-29 2.7 38.8 25.3 1.2 46.2 6,299 30-34 1.4 40.3 23.1 0.4 47.2 4,302 35-39 2.7 41.8 21.4 1.5 47.5 4,463 40-44 1.7 38.5 23.2 0.9 47.6 3,113 45-49 1.4 40.2 21.3 0.9 48.5 3,369 Residence Urban 7.6 71.1 26.3 3.2 20.7 6,870 Rural 1.0 29.6 23.2 0.4 55.1 22,591 Province1 Kabul 9.2 70.4 27.1 4.0 21.2 3,658 Kapisa 6.5 41.6 47.0 4.2 37.9 205 Parwan 1.8 20.5 36.0 0.2 50.9 625 Wardak 0.0 16.9 10.1 0.0 76.1 382 Logar 5.9 15.1 52.1 1.6 41.9 472 Nangarhar 2.3 31.2 18.6 1.0 59.0 794 Laghman 1.4 14.2 36.5 0.4 59.9 583 Panjsher 4.8 52.3 10.4 0.6 42.9 54 Baghlan 3.8 51.3 11.1 1.2 43.0 839 Bamyan 1.8 38.6 10.8 0.6 56.0 303 Ghazni 1.8 31.8 34.1 0.5 48.1 1,328 Paktika 0.0 7.2 40.4 0.0 55.5 792 Paktya 0.1 20.6 60.4 0.1 37.4 542 Khost 0.2 33.6 55.6 0.1 38.8 851 Kunarha 1.5 6.1 13.7 0.7 83.2 559 Nooristan 0.6 0.1 2.0 0.0 97.9 222 Badakhshan 1.0 12.8 5.5 0.8 85.7 1,004 Takhar 0.5 22.3 19.7 0.2 70.4 1,105 Kunduz 1.9 49.1 23.9 1.2 46.0 1,232 Samangan 1.3 20.3 6.8 0.8 77.4 330 Balkh 2.1 53.2 7.2 0.7 44.0 1,781 Sar-E-Pul 1.2 26.6 2.1 0.4 72.5 654 Ghor 0.5 39.3 16.5 0.3 55.9 715 Daykundi 0.3 11.9 1.2 0.2 87.2 329 Urozgan 0.0 5.7 20.8 0.0 77.4 230 Kandahar 0.8 16.2 55.8 0.2 40.0 2,227 Jawzjan 5.1 54.0 22.8 3.3 42.5 614 Faryab 2.5 76.8 5.9 1.3 20.9 2,114 Helmand 0.8 23.2 40.8 0.4 46.7 875 Badghis 0.3 6.8 2.4 0.2 92.1 650 Herat 1.9 55.6 12.5 0.7 37.7 2,316 Farah 0.2 38.6 28.9 0.1 46.6 777 Nimroz 1.4 57.3 1.1 0.0 42.3 278 Education No education 0.2 33.2 24.1 0.0 51.8 24,604 Primary 3.8 64.7 20.5 1.9 28.0 2,330 Secondary 18.4 70.2 22.0 6.3 21.7 1,971 More than secondary 43.4 89.1 40.4 24.9 6.1 556 Wealth quintile Lowest 0.3 22.1 10.9 0.1 71.0 5,904 Second 0.5 24.1 22.3 0.2 59.5 6,001 Middle 0.7 26.4 27.2 0.3 53.3 5,888 Fourth 1.9 48.2 30.7 0.6 34.8 6,010 Highest 9.6 77.0 28.8 4.3 15.4 5,657 Total 2.5 39.2 24.0 1.1 47.1 29,461 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Characteristics of Respondents • 45 Table 3.4.2 Exposure to mass media: Men Percentage of ever-married men age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Afghanistan 2015 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of men Age 15-19 13.3 44.4 50.8 6.2 30.3 142 20-24 12.6 39.7 45.5 6.6 37.0 1,162 25-29 13.3 46.3 43.6 5.9 33.3 2,422 30-34 10.7 43.6 43.6 6.0 35.2 2,008 35-39 17.3 51.1 42.1 8.9 31.9 1,935 40-44 11.2 45.9 47.6 6.3 32.7 1,402 45-49 12.8 46.0 43.4 7.7 34.9 1,688 Residence Urban 26.2 79.5 56.9 16.4 11.0 2,479 Rural 9.2 35.7 40.3 4.0 40.8 8,281 Province1 Kabul 30.6 80.7 60.6 18.4 8.4 1,350 Kapisa 25.0 69.0 83.8 20.5 11.2 63 Parwan 5.5 54.9 57.4 4.5 25.7 220 Wardak 4.5 19.4 60.1 2.2 33.8 171 Logar 25.7 25.7 64.0 7.1 27.6 204 Nangarhar 18.4 36.3 60.3 8.1 25.7 273 Laghman 9.3 15.0 37.1 3.5 57.4 227 Panjsher 32.0 70.5 52.7 22.1 21.5 18 Baghlan 6.4 32.5 8.9 2.9 63.9 281 Bamyan 15.4 38.4 26.6 7.8 48.7 94 Ghazni 7.4 42.1 51.0 3.9 34.3 619 Paktika 7.6 11.6 52.3 4.0 45.9 322 Paktya 14.0 27.4 81.8 6.5 11.7 206 Khost 14.5 46.7 60.8 11.6 25.0 334 Kunarha 17.4 16.4 37.3 10.4 58.4 151 Nooristan 5.7 0.5 34.5 0.0 62.9 66 Badakhshan 12.6 28.2 35.0 7.9 54.7 316 Takhar 8.5 45.5 32.8 4.8 42.4 296 Kunduz 5.8 50.9 38.2 4.4 33.8 479 Samangan 5.4 21.1 15.5 2.5 71.6 125 Balkh 12.9 55.3 28.5 7.3 40.5 616 Sar-E-Pul 2.5 48.8 21.2 1.1 45.1 195 Ghor 12.9 46.7 39.0 3.3 34.0 322 Daykundi 8.8 34.3 18.2 7.6 63.1 77 Urozgan 1.2 13.4 49.6 0.5 43.2 92 Kandahar 4.5 23.6 61.2 3.2 35.0 874 Jawzjan 26.8 60.5 69.0 15.6 19.2 218 Faryab 22.1 74.6 16.7 3.2 21.4 706 Helmand 6.2 22.4 33.5 3.9 57.4 355 Badghis 3.2 14.3 14.6 0.5 71.5 231 Herat 10.0 57.3 41.4 7.0 27.2 863 Farah 3.3 41.4 39.4 2.1 40.4 295 Nimroz 7.5 69.2 30.2 4.9 25.3 93 Education No education 0.4 32.1 36.3 0.2 46.2 5,447 Primary 7.5 55.9 43.0 3.6 27.8 1,987 Secondary 30.8 59.0 56.1 16.4 20.2 2,632 More than secondary 61.4 74.4 63.6 32.8 6.7 695 Wealth quintile Lowest 4.9 31.1 28.6 2.0 53.7 2,029 Second 5.4 28.7 37.7 1.9 45.9 2,233 Middle 8.1 30.8 42.8 3.0 40.1 2,160 Fourth 14.0 55.1 52.1 7.7 22.8 2,260 Highest 33.5 84.0 58.9 20.1 7.3 2,078 Total 13.1 45.8 44.1 6.9 33.9 10,760 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 46 • Characteristics of Respondents Table 3.5.1 Employment status: Women Percent distribution of ever-married women age 15-49 by employment status, according to background characteristics, Afghanistan 2015 Background characteristic Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/don’t know Total Number of women Currently employed1 Not currently employed Age 15-19 8.8 1.2 89.9 0.1 100.0 1,825 20-24 11.0 2.0 86.8 0.2 100.0 6,089 25-29 11.7 1.8 86.2 0.3 100.0 6,299 30-34 10.1 1.4 88.4 0.1 100.0 4,302 35-39 13.5 1.5 84.5 0.5 100.0 4,463 40-44 13.2 1.1 85.4 0.3 100.0 3,113 45-49 12.6 0.8 86.4 0.2 100.0 3,369 Marital status Married 11.4 1.5 86.9 0.2 100.0 28,671 Divorced/separated/widowed 21.2 1.4 75.7 1.8 100.0 790 Number of living children 0 11.8 1.2 86.9 0.1 100.0 2,948 1-2 10.8 1.5 87.2 0.5 100.0 7,353 3-4 12.9 1.7 85.2 0.2 100.0 7,698 5+ 11.4 1.5 87.0 0.2 100.0 11,463 Residence Urban 12.4 2.2 84.9 0.6 100.0 6,870 Rural 11.5 1.3 87.1 0.2 100.0 22,591 Province2 Kabul 12.2 1.9 85.2 0.8 100.0 3,658 Kapisa 0.6 0.2 99.3 0.0 100.0 205 Parwan 10.2 0.0 89.8 0.1 100.0 625 Wardak 2.4 0.5 97.0 0.1 100.0 382 Logar 8.0 0.0 92.0 0.0 100.0 472 Nangarhar 12.6 0.8 86.3 0.2 100.0 794 Laghman 15.6 0.5 83.6 0.3 100.0 583 Panjsher 4.5 0.0 95.5 0.0 100.0 54 Baghlan 1.0 0.1 99.0 0.0 100.0 839 Bamyan 8.8 0.2 91.0 0.0 100.0 303 Ghazni 19.7 0.2 79.5 0.6 100.0 1,328 Paktika 2.0 0.1 97.2 0.7 100.0 792 Paktya 6.3 0.0 92.3 1.3 100.0 542 Khost 2.6 0.4 97.0 0.0 100.0 851 Kunarha 1.4 0.2 98.3 0.0 100.0 559 Nooristan 43.9 42.6 13.4 0.0 100.0 222 Badakhshan 1.5 0.2 98.3 0.0 100.0 1,004 Takhar 4.3 0.0 95.6 0.0 100.0 1,105 Kunduz 11.0 0.2 88.4 0.4 100.0 1,232 Samangan 2.0 0.5 97.5 0.0 100.0 330 Balkh 18.7 0.2 80.8 0.3 100.0 1,781 Sar-E-Pul 15.5 0.3 84.2 0.0 100.0 654 Ghor 13.2 0.1 86.7 0.0 100.0 715 Daykundi 2.8 0.2 97.1 0.0 100.0 329 Urozgan 0.7 0.0 99.1 0.2 100.0 230 Kandahar 15.7 9.5 74.5 0.3 100.0 2,227 Jawzjan 33.4 0.0 66.6 0.0 100.0 614 Faryab 32.8 1.3 65.7 0.1 100.0 2,114 Helmand 0.4 0.1 99.4 0.1 100.0 875 Badghis 2.6 0.0 97.4 0.0 100.0 650 Herat 4.3 0.2 95.5 0.0 100.0 2,316 Farah 9.7 0.2 90.1 0.0 100.0 777 Nimroz 9.3 0.0 90.6 0.1 100.0 278 Education No education 10.5 1.5 87.7 0.3 100.0 24,604 Primary 14.1 1.3 84.6 0.0 100.0 2,330 Secondary 15.1 1.6 83.2 0.2 100.0 1,971 More than secondary 41.3 2.6 55.7 0.4 100.0 556 Wealth quintile Lowest 10.1 0.2 89.7 0.0 100.0 5,904 Second 13.8 1.1 84.9 0.1 100.0 6,001 Middle 11.3 2.0 86.5 0.2 100.0 5,888 Fourth 11.0 2.0 86.8 0.2 100.0 6,010 Highest 12.1 2.2 84.9 0.8 100.0 5,657 Total 11.7 1.5 86.6 0.3 100.0 29,461 1 "Currently employed" is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Characteristics of Respondents • 47 Table 3.5.2 Employment status: Men Percent distribution of ever-married men age 15-49 by employment status, according to background characteristics, Afghanistan 2015 Employed in the 12 months preceding the survey Not employed in the 12 months preceding the survey Missing/don’t know Total Number of men Background characteristic Currently employed1 Not currently employed Age 15-19 83.2 3.9 12.9 0.0 100.0 142 20-24 87.4 6.3 6.0 0.3 100.0 1,162 25-29 92.6 4.4 2.9 0.1 100.0 2,422 30-34 93.8 4.5 1.6 0.1 100.0 2,008 35-39 91.1 6.3 2.3 0.3 100.0 1,935 40-44 93.1 5.0 1.8 0.2 100.0 1,402 45-49 89.1 6.8 4.1 0.1 100.0 1,688 Marital status Married 91.4 5.4 3.1 0.2 100.0 10,679 Divorced/separated/widowed 92.6 4.1 3.2 0.0 100.0 81 Number of living children 0 88.3 5.0 6.7 0.0 100.0 1,087 1-2 91.1 5.5 3.2 0.2 100.0 2,831 3-4 93.1 5.1 1.6 0.2 100.0 2,843 5+ 91.2 5.7 3.0 0.2 100.0 3,999 Residence Urban 91.5 5.1 3.1 0.3 100.0 2,479 Rural 91.3 5.5 3.0 0.1 100.0 8,281 Province2 Kabul 88.4 8.1 3.6 0.0 100.0 1,350 Kapisa 83.0 12.0 5.0 0.0 100.0 63 Parwan 97.4 2.0 0.3 0.4 100.0 220 Wardak 97.3 1.2 1.2 0.3 100.0 171 Logar 97.3 2.4 0.3 0.0 100.0 204 Nangarhar 92.3 0.7 7.0 0.0 100.0 273 Laghman 92.4 1.9 5.7 0.0 100.0 227 Panjsher 91.9 4.2 3.9 0.0 100.0 18 Baghlan 85.4 13.1 1.3 0.2 100.0 281 Bamyan 95.0 3.4 1.6 0.0 100.0 94 Ghazni 96.6 2.2 1.1 0.2 100.0 619 Paktika 94.0 1.0 4.8 0.1 100.0 322 Paktya 97.4 1.3 1.3 0.0 100.0 206 Khost 91.8 0.5 7.6 0.0 100.0 334 Kunarha 78.6 1.6 19.8 0.0 100.0 151 Nooristan 96.1 2.0 1.0 0.9 100.0 66 Badakhshan 89.8 6.4 3.8 0.0 100.0 316 Takhar 94.5 4.6 0.9 0.0 100.0 296 Kunduz 95.8 3.2 1.0 0.0 100.0 479 Samangan 71.4 24.5 4.1 0.0 100.0 125 Balkh 88.2 6.6 3.5 1.7 100.0 616 Sar-E-Pul 94.8 5.1 0.1 0.0 100.0 195 Ghor 75.5 19.5 5.0 0.0 100.0 322 Daykundi 96.5 0.9 2.6 0.0 100.0 77 Urozgan 95.5 0.4 4.1 0.0 100.0 92 Kandahar 97.8 0.3 1.7 0.2 100.0 874 Jawzjan 93.7 5.8 0.5 0.0 100.0 218 Faryab 94.3 5.1 0.6 0.0 100.0 706 Helmand 89.9 2.6 7.3 0.2 100.0 355 Badghis 73.9 22.8 3.3 0.0 100.0 231 Herat 90.5 7.1 2.4 0.0 100.0 863 Farah 95.9 1.4 2.7 0.0 100.0 295 Nimroz 86.4 9.9 3.6 0.0 100.0 93 Education No education 90.8 6.5 2.5 0.2 100.0 5,447 Primary 92.7 5.3 1.9 0.1 100.0 1,987 Secondary 91.7 3.8 4.4 0.1 100.0 2,632 More than secondary 90.9 3.5 5.6 0.0 100.0 695 Wealth quintile Lowest 86.5 10.2 3.0 0.2 100.0 2,029 Second 92.7 4.8 2.5 0.1 100.0 2,233 Middle 93.4 4.2 2.3 0.1 100.0 2,160 Fourth 91.5 3.7 4.6 0.2 100.0 2,260 Highest 92.5 4.6 2.8 0.1 100.0 2,078 Total 91.4 5.4 3.1 0.2 100.0 10,760 1 "Currently employed" is defined as having done work in the past 7 days. Includes persons who did not work in the past 7 days but who are regularly employed and were absent from work for leave, illness, vacation, or any other such reason. 2 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 48 • Characteristics of Respondents Table 3.6.1 Occupation: Women Percent distribution of ever-married women age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Afghanistan 2015 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Number of women Age 15-19 49.8 0.1 0.0 21.0 5.5 23.2 0.4 100.0 182 20-24 62.1 0.0 0.5 15.3 6.8 14.9 0.5 100.0 790 25-29 56.9 0.3 0.7 21.1 5.8 15.1 0.2 100.0 847 30-34 43.3 0.2 0.5 24.6 12.1 17.6 1.7 100.0 493 35-39 47.9 0.6 0.3 29.5 5.6 15.9 0.3 100.0 670 40-44 45.1 0.5 0.5 28.0 9.3 15.8 0.8 100.0 447 45-49 30.7 1.2 1.7 40.0 8.9 17.0 0.5 100.0 454 Marital status Married 50.5 0.4 0.6 24.1 7.4 16.4 0.6 100.0 3,705 Divorced/separated/ widowed 37.3 0.2 0.4 39.5 9.9 12.3 0.5 100.0 178 Number of living children 0 52.2 0.0 0.4 26.1 4.5 16.1 0.7 100.0 384 1-2 53.1 0.6 0.5 22.2 7.5 15.6 0.5 100.0 905 3-4 54.1 0.1 0.9 22.1 7.9 14.2 0.6 100.0 1,124 5+ 44.1 0.6 0.5 28.1 8.0 18.1 0.6 100.0 1,471 Residence Urban 77.1 0.8 1.4 11.5 7.9 0.4 0.9 100.0 1,000 Rural 40.5 0.3 0.3 29.4 7.4 21.6 0.5 100.0 2,883 Education No education 43.1 0.1 0.5 27.0 8.6 20.2 0.5 100.0 2,953 Primary 55.0 0.9 0.8 32.8 7.0 3.4 0.2 100.0 358 Secondary 74.8 1.5 1.6 14.7 2.5 4.8 0.2 100.0 328 More than secondary 91.1 2.1 0.0 0.0 1.7 2.0 3.1 100.0 244 Wealth quintile Lowest 31.1 0.3 0.6 45.4 2.3 19.7 0.6 100.0 608 Second 33.3 0.0 0.2 21.1 10.4 34.6 0.4 100.0 897 Middle 39.4 0.0 0.4 33.8 9.5 16.5 0.3 100.0 784 Fourth 59.2 0.8 0.4 22.6 8.3 8.1 0.5 100.0 781 Highest 83.5 0.9 1.4 7.0 5.5 0.6 1.1 100.0 813 Total 49.9 0.4 0.6 24.8 7.5 16.2 0.6 100.0 3,883 Note: Provincial-level estimates are not presented because there are too few cases. Characteristics of Respondents • 49 Table 3.6.2 Occupation: Men Percent distribution of ever-married men age 15-49 employed in the 12 months preceding the survey by occupation, according to background characteristics, Afghanistan 2015 Background characteristic Profes- sional/ technical/ managerial Clerical Sales and services Skilled manual Unskilled manual Agriculture Missing Total Number of men Age 15-19 16.2 0.2 8.1 15.4 18.2 41.8 0.0 100.0 124 20-24 13.5 2.8 18.0 19.8 16.0 29.9 0.0 100.0 1,089 25-29 15.3 2.4 14.7 23.3 17.1 27.1 0.0 100.0 2,347 30-34 11.6 2.3 17.3 18.0 17.7 33.1 0.0 100.0 1,974 35-39 11.8 3.8 19.4 20.6 16.9 27.6 0.1 100.0 1,886 40-44 10.3 2.6 20.9 17.0 15.7 31.9 1.5 100.0 1,375 45-49 8.3 1.9 16.0 19.1 15.5 39.2 0.0 100.0 1,618 Marital status Married 12.0 2.6 17.3 19.9 16.6 31.4 0.2 100.0 10,337 Divorced/separated/ widowed 16.0 5.0 16.6 14.7 26.0 21.6 0.0 100.0 78 Number of living children 0 12.9 3.6 16.5 22.0 22.1 23.0 0.0 100.0 1,014 1-2 14.5 2.6 14.4 20.8 16.3 30.6 0.8 100.0 2,734 3-4 11.0 2.8 19.4 22.4 15.6 28.8 0.0 100.0 2,793 5+ 10.8 2.2 18.1 16.8 16.2 35.8 0.0 100.0 3,874 Residence Urban 17.6 5.1 29.1 25.1 15.6 6.6 0.9 100.0 2,395 Rural 10.4 1.8 13.8 18.3 16.9 38.7 0.0 100.0 8,019 Province1 Kabul 17.9 4.0 25.2 21.2 18.1 12.0 1.6 100.0 1,302 Kapisa 31.0 3.3 12.5 25.2 10.6 17.3 0.0 100.0 60 Parwan 21.3 2.1 13.6 19.5 5.7 37.8 0.0 100.0 219 Wardak 11.1 4.9 6.6 4.6 9.8 62.9 0.1 100.0 169 Logar 17.7 6.2 14.1 33.2 3.8 24.9 0.0 100.0 203 Nangarhar 15.3 4.4 17.5 19.5 23.8 19.5 0.0 100.0 254 Laghman 15.6 0.1 10.9 16.6 33.7 22.6 0.4 100.0 214 Panjsher 34.7 7.2 12.0 10.5 6.9 28.5 0.0 100.0 17 Baghlan 15.3 3.7 19.9 21.8 10.8 28.5 0.0 100.0 277 Bamyan 6.6 1.6 8.7 7.9 20.9 54.3 0.0 100.0 92 Ghazni 6.3 2.4 23.9 19.6 6.3 41.5 0.0 100.0 611 Paktika 15.1 4.6 18.9 18.7 17.5 25.0 0.2 100.0 306 Paktya 11.9 1.4 17.0 28.9 22.6 18.2 0.0 100.0 203 Khost 19.7 3.5 17.5 23.0 24.8 11.5 0.0 100.0 309 Kunarha 31.7 0.8 4.8 4.3 45.2 13.2 0.0 100.0 121 Nooristan 9.0 2.8 11.1 9.9 15.5 51.5 0.2 100.0 65 Badakhshan 10.8 0.5 6.8 7.1 29.9 45.0 0.0 100.0 304 Takhar 8.4 1.3 8.9 18.5 35.1 27.7 0.0 100.0 293 Kunduz 7.8 2.3 27.9 21.5 15.9 24.7 0.0 100.0 475 Samangan 6.0 1.8 8.5 11.1 39.1 33.6 0.0 100.0 120 Balkh 7.5 1.8 14.7 25.9 9.9 40.2 0.0 100.0 584 Sar-E-Pul 9.9 0.6 16.0 19.4 27.9 26.2 0.0 100.0 195 Ghor 24.5 2.6 7.8 11.3 2.5 50.9 0.3 100.0 306 Daykundi 9.2 0.6 10.5 9.5 18.7 51.5 0.0 100.0 75 Urozgan 5.0 1.0 10.5 7.9 7.7 68.0 0.0 100.0 88 Kandahar 8.6 2.7 17.9 19.0 10.3 41.6 0.0 100.0 857 Jawzjan 23.0 4.0 22.4 18.8 8.1 23.7 0.0 100.0 217 Faryab 4.6 1.0 12.9 45.6 20.5 15.4 0.0 100.0 702 Helmand 12.8 1.9 31.9 16.6 5.4 31.6 0.0 100.0 328 Badghis 12.2 0.6 7.6 7.1 2.8 69.6 0.0 100.0 223 Herat 5.7 3.2 16.3 14.6 24.4 35.8 0.0 100.0 842 Farah 9.5 2.3 14.5 7.2 8.3 58.2 0.0 100.0 287 Nimroz 8.9 2.4 20.1 19.8 35.5 13.2 0.0 100.0 90 Education No education 3.5 0.3 15.9 17.7 19.5 42.8 0.4 100.0 5,298 Primary 5.9 0.5 18.3 26.8 20.1 28.4 0.0 100.0 1,948 Secondary 21.9 6.0 22.1 22.8 10.5 16.7 0.0 100.0 2,513 More than secondary 62.1 14.7 7.7 5.4 7.0 3.2 0.0 100.0 656 Wealth quintile Lowest 8.2 0.9 10.2 10.5 14.9 55.4 0.1 100.0 1,962 Second 8.6 1.2 12.7 15.7 19.1 42.7 0.0 100.0 2,176 Middle 11.1 1.4 15.3 19.3 17.3 35.5 0.0 100.0 2,108 Fourth 12.8 3.9 18.1 28.2 19.4 17.6 0.0 100.0 2,151 Highest 19.7 5.7 30.5 25.1 12.1 5.8 1.0 100.0 2,018 Total 12.0 2.6 17.3 19.9 16.6 31.3 0.2 100.0 10,415 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 50 • Characteristics of Respondents Table 3.7 Type of employment: Women Percent distribution of ever-married women age 15-49 employed in the 12 months preceding the survey by type of earnings, type of employer, and continuity of employment, according to type of employment (agricultural or nonagricultural), Afghanistan 2015 Employment characteristic Agricultural work Non- agricultural work Total Type of earnings Cash only 6.1 71.2 60.6 Cash and in-kind 12.8 5.7 6.8 In-kind only 18.3 2.5 5.0 Not paid 61.9 20.1 27.0 Missing 0.9 0.4 0.6 Total 100.0 100.0 100.0 Type of employer Employed by family member 93.0 42.3 50.6 Employed by non-family member 2.0 33.7 28.5 Self-employed 4.1 23.0 19.8 Missing 0.8 1.0 1.1 Total 100.0 100.0 100.0 Continuity of employment All year 48.7 64.8 62.2 Seasonal 45.0 18.3 22.6 Occasional 5.8 16.9 15.0 Missing 0.5 0.1 0.2 Total 100.0 100.0 100.0 Number of women employed during the last 12 months 628 3,233 3,883 Note: Total includes women with missing information on type of employment who are not shown separately. Characteristics of Respondents • 51 Table 3.8.1 Use of tobacco: Women Percentage of ever-married women age 15-49 who smoke cigarettes or a chelam or use other tobacco products, according to background characteristics and maternity status, Afghanistan 2015 Uses tobacco Does not use tobacco Number of women Background characteristic Cigarettes Chelam Other tobacco Age 15-19 0.5 0.5 0.5 98.5 1,825 20-24 0.7 1.0 0.9 97.3 6,089 25-29 1.3 1.2 1.1 96.2 6,299 30-34 0.7 1.8 2.2 95.3 4,302 35-39 1.3 2.7 3.2 92.8 4,463 40-44 1.2 4.1 5.2 89.6 3,113 45-49 1.2 7.8 6.9 85.2 3,369 Maternity status Pregnant 0.9 1.7 2.0 95.5 6,412 Breastfeeding (not pregnant) 1.0 1.0 1.5 96.4 2,904 Neither 1.0 3.0 3.0 93.1 20,145 Residence Urban 1.1 1.2 0.6 96.7 6,870 Rural 1.0 2.9 3.2 93.1 22,591 Province1 Kabul 0.8 0.0 0.6 97.6 3,658 Kapisa 0.1 0.0 0.1 99.8 205 Parwan 0.9 0.0 0.1 98.8 625 Wardak 0.6 0.0 2.3 97.1 382 Logar 0.7 0.7 1.6 97.3 472 Nangarhar 0.0 0.0 0.3 99.5 794 Laghman 0.9 0.0 0.9 98.6 583 Panjsher 0.1 0.0 0.1 99.8 54 Baghlan 1.0 0.3 3.6 95.4 839 Bamyan 0.0 0.0 2.6 97.4 303 Ghazni 0.8 0.4 3.2 95.5 1,328 Paktika 0.0 0.0 1.2 98.0 792 Paktya 0.2 0.0 14.9 83.5 542 Khost 0.0 0.0 1.0 99.0 851 Kunarha 0.2 0.0 1.1 98.8 559 Nooristan 0.9 0.1 3.4 95.4 222 Badakhshan 0.1 0.0 0.0 99.9 1,004 Takhar 0.0 0.0 0.0 99.8 1,105 Kunduz 0.3 0.2 0.1 99.5 1,232 Samangan 0.0 0.0 1.9 98.0 330 Balkh 4.7 3.4 6.4 87.2 1,781 Sar-E-Pul 4.8 0.3 3.0 92.1 654 Ghor 0.2 4.6 18.0 77.3 715 Daykundi 0.1 0.0 1.5 98.4 329 Urozgan 0.2 0.0 3.4 96.2 230 Kandahar 0.4 5.3 0.2 93.8 2,227 Jawzjan 4.5 0.5 4.0 92.7 614 Faryab 1.0 0.0 1.4 97.4 2,114 Helmand 3.5 4.2 1.5 91.5 875 Badghis 0.6 15.3 6.1 78.3 650 Herat 0.5 12.7 2.3 85.1 2,316 Farah 0.2 9.1 10.3 83.6 777 Nimroz 0.0 3.8 0.5 95.3 278 Education No education 1.0 2.9 3.0 93.2 24,604 Primary 1.9 0.7 0.9 96.7 2,330 Secondary 0.7 0.2 0.4 98.5 1,971 More than secondary 0.1 0.1 0.0 99.4 556 Wealth quintile Lowest 1.3 4.2 5.5 89.7 5,904 Second 1.0 2.8 3.6 92.9 6,001 Middle 0.9 3.2 2.1 93.9 5,888 Fourth 0.6 1.3 1.2 96.8 6,010 Highest 1.2 1.1 0.5 96.6 5,657 Total 1.0 2.5 2.6 94.0 29,461 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 52 • Characteristics of Respondents Table 3.8.2 Use of tobacco: Men Percentage of ever-married men age 15-49 who smoke cigarettes or a chelam or use other tobacco products and the percent distribution of cigarette smokers by number of cigarettes smoked in the preceding 24 hours, according to background characteristics, Afghanistan 2015 Uses tobacco Does not use tobacco Number of men Percent distribution of men who smoke cigarettes by number of cigarettes smoked in the past 24 hours Total Number of ciga- rette smok- ers Background characteristic Ciga- rettes Chelam Other tobacco 0 1-2 3-5 6-9 10+ Don’t know/ missing Age 15-19 13.9 0.0 18.4 71.3 142 (0.0) (3.5) (21.9) (20.6) (40.0) (14.0) 100.0 20 20-24 20.4 0.5 25.0 59.0 1,162 0.0 2.0 18.7 17.7 60.0 1.6 100.0 237 25-29 23.7 1.7 29.6 54.0 2,422 0.0 8.1 17.8 14.5 57.6 2.0 100.0 574 30-34 19.6 1.4 31.5 53.7 2,008 0.1 6.6 18.4 18.0 54.7 2.1 100.0 394 35-39 28.1 1.0 30.4 48.0 1,935 0.1 10.8 22.2 13.3 52.0 1.5 100.0 544 40-44 19.2 1.8 37.0 49.6 1,402 0.7 2.8 17.1 13.3 64.8 1.4 100.0 270 45-49 18.8 2.4 39.5 45.9 1,688 2.1 3.9 13.2 8.9 70.0 1.9 100.0 317 Residence Urban 23.6 0.2 17.4 62.0 2,479 0.0 12.0 13.6 10.7 62.7 1.0 100.0 584 Rural 21.4 1.9 36.3 48.7 8,281 0.5 4.9 19.9 15.5 57.0 2.2 100.0 1,771 Province1 Kabul 24.2 0.2 12.8 64.6 1,350 (0.0) (16.1) (14.3) (10.3) (58.4) (0.9) 100.0 327 Kapisa 27.3 0.0 29.0 49.9 63 0.0 6.5 25.2 21.0 41.9 5.4 100.0 17 Parwan 28.7 0.3 29.3 52.6 220 0.0 2.3 5.1 3.0 89.6 0.0 100.0 63 Wardak 18.2 0.3 39.8 48.5 171 4.6 8.6 41.0 12.8 33.0 0.0 100.0 31 Logar 19.5 2.3 16.2 66.5 204 0.0 5.6 15.4 18.7 58.8 1.5 100.0 40 Nangarhar 23.4 0.0 21.3 59.5 273 0.0 3.0 22.4 20.6 54.0 0.0 100.0 64 Laghman 23.2 1.2 37.5 49.2 227 0.0 1.5 28.4 25.1 41.8 3.2 100.0 53 Panjsher 28.2 0.0 26.3 58.5 18 0.0 0.0 6.6 10.4 81.2 1.8 100.0 5 Baghlan 15.8 0.6 56.6 32.6 281 (0.0) (10.9) (7.2) (22.5) (57.7) (1.7) 100.0 45 Bamyan 6.9 0.0 36.0 58.3 94 * * * * * * 100.0 6 Ghazni 25.6 2.2 37.7 45.4 619 0.9 4.4 23.5 28.9 42.2 0.0 100.0 159 Paktika 11.0 1.7 51.5 43.4 322 0.0 1.4 17.3 17.4 63.9 0.0 100.0 35 Paktya 14.0 0.7 48.1 46.3 206 0.0 7.1 7.2 3.9 81.8 0.0 100.0 29 Khost 16.5 0.0 61.0 31.9 334 0.0 2.3 13.7 25.0 59.1 0.0 100.0 55 Kunarha 5.4 0.0 36.0 61.8 151 * * * * * * 100.0 8 Nooristan 27.1 2.0 46.3 36.8 66 0.9 16.2 48.6 17.5 16.2 0.6 100.0 18 Badakhshan 4.0 1.6 12.5 85.3 316 * * * * * * 100.0 12 Takhar 8.2 0.0 15.4 77.1 296 * * * * * * 100.0 24 Kunduz 29.7 3.6 28.9 47.7 479 0.0 0.6 6.1 7.8 85.5 0.0 100.0 143 Samangan 8.3 0.3 22.1 71.6 125 (0.0) (6.9) (28.2) (5.0) (54.6) (5.3) 100.0 10 Balkh 15.7 0.0 25.1 59.6 616 (0.0) (13.1) (29.6) (7.0) (46.9) (3.4) 100.0 97 Sar-E-Pul 15.2 0.0 23.8 61.6 195 (0.0) (2.1) (43.1) (18.2) (36.7) (0.0) 100.0 30 Ghor 20.7 0.5 36.5 45.9 322 0.0 4.3 21.2 21.6 51.4 1.5 100.0 67 Daykundi 2.6 0.0 27.0 71.1 77 * * * * * * 100.0 2 Urozgan 24.9 0.4 40.4 34.4 92 0.0 0.0 0.0 1.1 90.1 8.8 100.0 23 Kandahar 33.6 3.1 55.3 29.9 874 0.0 9.0 6.9 9.0 74.7 0.4 100.0 294 Jawzjan 49.5 1.3 30.1 32.2 218 0.0 0.9 4.3 12.4 81.5 0.9 100.0 108 Faryab 22.3 2.9 11.3 71.5 706 (2.5) (0.6) (47.7) (25.5) (22.9) (0.9) 100.0 157 Helmand 19.3 3.4 31.4 55.4 355 0.0 4.6 5.5 5.3 72.0 12.6 100.0 69 Badghis 13.0 3.7 28.6 58.0 231 (0.0) (0.0) (12.9) (6.6) (57.6) (22.9) 100.0 30 Herat 25.5 2.7 46.8 32.0 863 1.1 3.5 20.6 13.3 56.8 4.7 100.0 220 Farah 37.2 1.9 36.3 31.5 295 0.0 5.0 34.6 17.8 42.6 0.0 100.0 110 Nimroz 2.5 0.0 8.5 89.8 93 * * * * * * 100.0 2 Education No education 23.6 1.9 41.2 42.7 5,447 0.3 4.9 18.8 12.9 60.8 2.3 100.0 1,283 Primary 19.4 0.6 28.8 56.2 1,987 0.0 4.8 26.5 16.2 51.5 1.0 100.0 386 Secondary 23.4 1.6 22.2 58.5 2,632 0.8 11.7 13.2 14.8 58.0 1.5 100.0 616 More than secondary 10.1 0.1 5.9 84.7 695 0.0 4.2 12.1 23.4 57.3 3.0 100.0 70 Wealth quintile Lowest 19.2 2.2 37.1 46.5 2,029 0.6 3.1 18.0 12.5 63.5 2.3 100.0 389 Second 21.5 1.4 39.7 45.0 2,233 1.2 4.6 25.4 18.9 46.5 3.3 100.0 480 Middle 21.6 1.9 38.2 49.1 2,160 0.1 7.1 16.8 10.2 64.4 1.5 100.0 466 Fourth 23.4 1.7 30.5 53.3 2,260 0.1 5.5 17.8 14.6 60.6 1.4 100.0 530 Highest 23.6 0.3 13.7 65.3 2,078 0.0 12.4 13.8 14.8 57.9 1.1 100.0 490 Total 21.9 1.5 32.0 51.8 10,760 0.4 6.6 18.4 14.3 58.4 1.9 100.0 2,355 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 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Characteristics of Respondents • 53 Table 3.9 Use of drugs Percentage of ever-married women and ever-married men age 15-49 who use drugs and among men using drugs, the percentage using different types of drugs, according to background characteristics, Afghanistan 2015 Background characteristic Women Men Uses drugs Number of women Uses drugs Number of men Percentage by type of drugs used: Opium Heroin Other Number of men Age 15-19 0.1 1,825 0.7 142 * * * 1 20-24 0.2 6,089 1.9 1,162 * * * 22 25-29 0.0 6,299 3.0 2,422 71.6 0.6 53.2 73 30-34 0.1 4,302 2.6 2,008 (26.6) (10.1) (68.2) 53 35-39 0.1 4,463 2.0 1,935 (57.9) (3.9) (38.1) 38 40-44 0.2 3,113 2.9 1,402 (39.1) (0.0) (59.6) 40 45-49 0.4 3,369 2.4 1,688 (27.7) (3.4) (67.6) 40 Residence Urban 0.1 6,870 1.5 2,479 * * * 37 Rural 0.2 22,591 2.8 8,281 44.8 3.2 60.1 231 Education No education 0.1 24,604 3.0 5,447 41.7 3.4 53.5 165 Primary 0.3 2,330 2.1 1,987 (33.4) (7.8) (63.6) 42 Secondary 0.0 1,971 2.3 2,632 (63.6) (1.4) (69.5) 59 More than secondary 0.0 556 0.3 695 * * * 2 Wealth quintile Lowest 0.2 5,904 3.5 2,029 (48.7) (0.0) (50.0) 72 Second 0.2 6,001 2.8 2,233 40.1 4.3 52.9 62 Middle 0.1 5,888 1.7 2,160 (48.4) (10.0) (44.9) 36 Fourth 0.2 6,010 3.2 2,260 (49.3) (3.6) (75.3) 72 Highest 0.0 5,657 1.2 2,078 * * * 26 Total 0.1 29,461 2.5 10,760 45.3 3.6 58.3 268 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. Provincial-level estimates are not presented because there are too few cases. 54 • Characteristics of Respondents Table 3.10.1 Knowledge concerning tuberculosis: Women Percentage of ever-married women age 15-49 who have heard of tuberculosis (TB), and among women who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who have ever been told by a doctor or nurse that they have TB, according to background characteristics, Afghanistan 2015 Among all respondents: Among respondents who have heard of TB: Background characteristic Percent- age who have heard of TB Number Percent- age who report that TB is spread through coughing Percent- age who believe that TB can be cured Percent- age who have been told by doctor/ nurse that they have TB Number Age 15-19 78.2 1,825 60.5 80.5 4.6 1,427 20-24 79.6 6,089 61.5 79.8 5.6 4,846 25-29 81.4 6,299 64.1 80.5 5.1 5,125 30-34 80.9 4,302 63.0 80.6 7.5 3,479 35-39 81.8 4,463 64.8 82.6 6.9 3,653 40-44 81.3 3,113 66.6 85.3 9.1 2,532 45-49 87.2 3,369 61.5 80.1 10.4 2,936 Residence Urban 74.3 6,870 76.1 88.2 4.0 5,105 Rural 83.6 22,591 59.7 79.3 7.7 18,892 Province1 Kabul 60.0 3,658 79.4 91.0 5.3 2,194 Kapisa 82.7 205 67.3 92.2 5.1 170 Parwan 92.3 625 60.8 87.0 11.2 577 Wardak 78.3 382 89.5 71.6 14.2 299 Logar 87.2 472 67.3 85.8 6.9 411 Nangarhar 95.9 794 57.7 95.0 4.7 762 Laghman 96.9 583 79.8 93.7 14.8 565 Panjsher 34.6 54 94.2 97.2 24.8 19 Baghlan 88.0 839 81.8 89.8 17.0 739 Bamyan 74.7 303 70.4 92.5 4.2 226 Ghazni 65.7 1,328 48.3 62.7 10.0 873 Paktika 58.9 792 18.9 31.0 6.4 466 Paktya 95.0 542 38.3 52.4 6.9 515 Khost 96.6 851 52.9 84.7 2.0 822 Kunarha 86.5 559 64.2 93.9 6.3 483 Nooristan 62.8 222 23.9 78.6 21.0 140 Badakhshan 65.1 1,004 86.6 91.7 5.6 654 Takhar 92.2 1,105 21.8 89.9 0.9 1,019 Kunduz 70.6 1,232 78.4 52.7 2.3 871 Samangan 65.9 330 62.6 86.8 16.2 217 Balkh 94.3 1,781 74.3 95.3 6.8 1,680 Sar-E-Pul 79.6 654 78.2 72.1 7.6 520 Ghor 98.0 715 92.2 93.7 23.3 700 Daykundi 44.4 329 70.0 86.6 8.0 146 Urozgan 47.3 230 72.7 36.2 5.1 109 Kandahar 95.5 2,227 64.1 53.0 5.0 2,127 Jawzjan 77.1 614 95.3 92.5 1.7 473 Faryab 87.8 2,114 47.4 68.2 1.9 1,855 Helmand 84.0 875 84.0 98.2 10.1 734 Badghis 98.7 650 89.8 97.8 13.5 641 Herat 98.5 2,316 38.4 96.4 4.0 2,281 Farah 67.3 777 59.7 75.3 12.2 523 Nimroz 64.2 278 53.8 83.9 1.7 179 Education No education 81.3 24,604 61.7 79.3 7.4 20,006 Primary 80.2 2,330 65.9 88.1 4.6 1,868 Secondary 83.2 1,971 73.6 92.2 4.0 1,640 More than secondary 87.0 556 82.6 95.0 3.4 484 Wealth quintile Lowest 83.7 5,904 63.1 84.0 9.5 4,941 Second 81.0 6,001 56.7 76.7 7.8 4,862 Middle 84.3 5,888 58.6 76.0 7.1 4,965 Fourth 81.8 6,010 63.8 82.2 5.9 4,919 Highest 76.2 5,657 75.6 87.6 3.6 4,310 Total 81.5 29,461 63.2 81.1 6.9 23,997 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Characteristics of Respondents • 55 Table 3.10.2 Knowledge concerning tuberculosis: Men Percentage of ever-married men age 15-49 who have heard of tuberculosis (TB), and among men who have heard of TB, the percentage who know that TB is spread through the air by coughing, the percentage who believe that TB can be cured, and the percentage who have ever been told by a doctor or nurse that they have TB, according to background characteristics, Afghanistan 2015 Among all respondents: Among respondents who have heard of TB: Background characteristic Percent- age who have heard of TB Number Percent- age who report that TB is spread through coughing Percent- age who believe that TB can be cured Percent- age who have been told by doc- tor/nurse that they have TB Number Age 15-19 81.9 142 74.5 84.4 4.4 117 20-24 81.5 1,162 69.8 87.7 2.9 947 25-29 81.9 2,422 72.3 87.8 5.1 1,984 30-34 82.5 2,008 71.9 86.6 5.0 1,656 35-39 85.1 1,935 73.2 88.8 5.4 1,646 40-44 81.2 1,402 72.9 88.9 3.1 1,139 45-49 85.9 1,688 72.4 87.9 5.0 1,451 Residence Urban 79.8 2,479 78.2 91.5 3.7 1,978 Rural 84.1 8,281 70.5 86.8 4.9 6,962 Province1 Kabul 73.0 1,350 82.9 88.2 4.6 985 Kapisa 96.6 63 73.6 95.5 3.4 61 Parwan 95.2 220 81.7 93.9 1.5 210 Wardak 83.5 171 90.8 89.1 6.8 143 Logar 61.6 204 54.4 78.1 6.9 126 Nangarhar 80.8 273 91.1 98.4 3.2 220 Laghman 90.0 227 73.0 96.0 7.2 204 Panjsher 89.6 18 99.1 86.3 0.7 16 Baghlan 67.8 281 47.5 94.8 8.0 191 Bamyan 83.8 94 66.9 88.2 2.5 78 Ghazni 82.5 619 82.4 87.3 5.2 511 Paktika 73.3 322 39.6 68.1 6.5 236 Paktya 98.4 206 73.5 98.7 0.5 202 Khost 98.4 334 62.7 86.2 2.1 329 Kunarha 81.6 151 89.8 91.8 2.6 123 Nooristan 74.5 66 34.8 81.2 14.1 49 Badakhshan 73.5 316 73.1 74.4 9.2 232 Takhar 83.8 296 74.6 91.6 4.5 248 Kunduz 74.9 479 83.8 96.4 11.7 359 Samangan 82.9 125 58.5 64.8 1.1 104 Balkh 83.7 616 83.2 83.0 1.7 515 Sar-E-Pul 94.6 195 72.8 86.3 5.2 184 Ghor 97.7 322 39.5 92.1 3.9 315 Daykundi 78.2 77 65.7 86.1 2.7 60 Urozgan 19.3 92 37.6 86.6 1.9 18 Kandahar 90.2 874 30.0 93.1 2.0 789 Jawzjan 91.4 218 74.0 86.9 3.1 200 Faryab 97.0 706 80.9 91.2 3.4 685 Helmand 83.3 355 86.1 85.2 6.1 296 Badghis 99.9 231 91.6 96.8 12.2 231 Herat 90.8 863 88.1 81.0 4.8 783 Farah 64.1 295 72.9 79.7 4.7 189 Nimroz 46.6 93 87.2 76.9 0.7 44 Education No education 79.9 5,447 67.5 83.3 4.9 4,350 Primary 83.8 1,987 72.5 89.3 3.4 1,665 Secondary 86.4 2,632 77.6 93.5 5.3 2,274 More than secondary 93.8 695 84.8 94.9 3.8 652 Wealth quintile Lowest 84.5 2,029 67.1 83.9 6.9 1,715 Second 79.7 2,233 74.3 85.9 3.6 1,780 Middle 85.2 2,160 68.0 86.3 5.5 1,841 Fourth 83.5 2,260 72.3 90.0 4.0 1,887 Highest 82.6 2,078 79.8 93.2 3.2 1,717 Total 83.1 10,760 72.3 87.9 4.6 8,940 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 56 • Characteristics of Respondents Table 3.11.1 Knowledge concerning hepatitis: Women Percentage of ever-married women age 15-49 who have heard of hepatitis, and among women who have heard of hepatitis, the percentage who believe that hepatitis can be avoided in different ways, according to background characteristics, Afghanistan 2015 Among all respondents: Among respondents who have heard of hepatitis, percentage who report that it can be avoided through: Background characteristic Per- centage who have heard of hepatitis Number Safe sex Safe blood transfer Using dis- posable syringes Avoiding contami- nated food/ water Avoiding contact with infected person Ensuring dentists use sterilized instru- ments Other Don’t know Number Age 15-19 63.6 1,825 16.3 14.6 18.9 21.9 13.7 1.8 5.1 2.4 1,161 20-24 66.3 6,089 17.9 16.0 19.6 20.2 16.0 2.4 4.7 3.1 4,035 25-29 67.2 6,299 17.2 16.7 20.0 19.2 15.8 2.9 5.1 2.2 4,231 30-34 65.9 4,302 16.9 17.6 19.5 21.0 15.4 3.1 4.6 2.6 2,834 35-39 68.7 4,463 15.1 18.3 20.8 20.5 15.2 2.9 4.5 2.6 3,067 40-44 68.4 3,113 16.7 17.8 21.8 22.9 17.8 4.1 4.2 4.4 2,129 45-49 71.0 3,369 16.3 14.7 19.2 20.0 15.1 2.1 5.0 2.2 2,393 Residence Urban 68.1 6,870 24.1 23.2 25.3 27.4 16.4 4.3 3.1 3.1 4,681 Rural 67.1 22,591 14.5 14.7 18.4 18.4 15.5 2.3 5.2 2.6 15,169 Province1 Kabul 54.4 3,658 22.6 26.6 30.3 31.3 15.4 5.1 7.6 4.7 1,992 Kapisa 78.1 205 9.3 12.9 7.9 15.9 1.5 0.5 61.4 6.2 160 Parwan 73.0 625 15.9 22.5 18.5 16.6 14.3 0.8 5.3 2.3 457 Wardak 60.3 382 8.8 19.6 17.0 5.4 7.9 0.7 0.4 0.0 230 Logar 74.9 472 8.0 8.6 36.2 55.2 25.0 0.4 0.8 1.1 353 Nangarhar 97.8 794 8.4 9.5 17.1 7.5 7.6 3.2 14.3 1.3 777 Laghman 94.8 583 50.8 37.6 42.3 52.8 25.5 7.2 1.6 5.9 552 Panjsher 22.1 54 6.0 58.6 58.1 5.7 3.7 0.4 0.0 3.3 12 Baghlan 49.3 839 22.8 25.9 15.4 11.1 4.0 0.5 0.0 0.4 414 Bamyan 62.6 303 3.5 12.4 3.4 34.2 3.7 0.0 0.1 9.8 190 Ghazni 32.9 1,328 11.0 21.2 16.6 12.9 10.7 4.7 0.4 1.0 436 Paktika 22.3 792 3.4 34.8 71.6 8.1 4.0 1.2 0.5 4.8 176 Paktya 94.3 542 5.7 4.1 7.6 10.6 20.9 1.0 0.0 0.3 512 Khost 98.6 851 3.2 4.6 8.9 13.9 14.8 0.6 17.6 0.7 839 Kunarha 89.4 559 9.7 2.3 5.5 9.2 12.7 3.4 2.2 17.6 500 Nooristan 46.7 222 0.2 0.0 3.4 1.3 4.8 0.0 15.6 0.8 104 Badakhshan 51.2 1,004 27.1 19.7 29.5 36.9 26.2 21.0 0.4 0.1 514 Takhar 90.3 1,105 7.0 3.7 3.6 10.5 19.9 1.0 0.2 1.5 998 Kunduz 52.9 1,232 26.0 27.5 26.4 20.9 9.8 15.1 0.0 1.4 652 Samangan 54.0 330 0.5 0.8 0.1 0.4 0.1 2.5 0.0 0.5 178 Balkh 77.4 1,781 18.8 11.9 20.2 36.2 31.7 2.4 0.7 8.0 1,378 Sar-E-Pul 63.4 654 43.4 36.8 42.9 43.9 49.5 6.7 2.1 0.7 415 Ghor 85.0 715 23.4 31.9 28.0 18.6 7.8 0.1 20.9 0.1 607 Daykundi 32.9 329 0.9 0.5 0.0 2.4 1.2 0.0 30.3 10.9 108 Urozgan 45.2 230 0.3 0.0 0.0 1.0 2.0 0.3 0.0 0.1 104 Kandahar 98.3 2,227 12.4 3.5 1.9 11.8 8.0 0.6 0.0 0.2 2,189 Jawzjan 62.0 614 8.6 9.4 11.1 5.4 0.8 0.0 4.2 0.2 381 Faryab 76.7 2,114 8.3 13.5 24.0 3.9 5.4 0.0 6.3 0.5 1,622 Helmand 41.2 875 83.7 89.3 80.5 61.9 38.5 4.4 0.0 0.2 361 Badghis 75.7 650 28.5 29.9 29.6 19.2 21.5 0.6 2.0 0.2 492 Herat 67.6 2,316 13.3 15.1 20.5 22.3 23.9 0.2 3.2 3.2 1,565 Farah 52.1 777 19.2 17.4 20.2 30.8 17.8 1.3 0.1 1.0 405 Nimroz 59.1 278 2.2 1.8 8.3 14.2 4.5 0.5 2.6 21.0 164 Education No education 66.4 24,604 14.4 14.8 17.5 18.9 14.9 2.2 4.7 2.7 16,339 Primary 68.0 2,330 23.1 19.9 26.2 26.7 16.0 3.6 5.7 3.1 1,583 Secondary 74.4 1,971 31.2 28.8 35.0 28.5 21.4 5.7 4.4 3.3 1,467 More than secondary 82.7 556 31.9 36.8 38.5 31.1 23.2 11.4 3.8 0.3 460 Wealth quintile Lowest 61.8 5,904 14.2 14.7 15.7 20.9 18.6 2.8 5.5 3.2 3,649 Second 61.1 6,001 14.6 14.4 16.6 19.3 16.2 2.6 5.6 3.2 3,667 Middle 70.7 5,888 14.4 14.4 18.7 18.3 14.1 1.9 3.5 2.2 4,161 Fourth 72.5 6,010 15.6 15.4 21.5 17.9 14.2 2.2 4.8 2.7 4,358 Highest 71.0 5,657 24.8 24.5 26.7 26.4 15.8 4.7 4.5 2.5 4,014 Total 67.4 29,461 16.8 16.7 20.0 20.5 15.7 2.8 4.7 2.8 19,850 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. Characteristics of Respondents • 57 Table 3.11.2 Knowledge concerning hepatitis: Men Percentage of ever-married men age 15-49 who have heard of hepatitis, and among men who have heard of hepatitis, the percentage who believe that hepatitis can be avoided in different ways, according to background characteristics, Afghanistan 2015 Among all respondents: Among respondents who have heard of hepatitis, percentage who report that it can be avoided through: Background characteristic Per- centage who have heard of hepatitis Number Safe sex Safe blood transfer Using dis- posable syringes Avoiding con- taminated food/ water Avoiding contact with infected person Ensuring dentists use sterilized instru- ments Other Don’t know Number Age 15-19 58.7 142 43.1 34.8 42.1 46.7 28.1 24.6 4.7 0.7 84 20-24 67.3 1,162 32.4 28.4 34.3 31.6 22.9 12.5 3.3 1.6 782 25-29 64.6 2,422 34.2 30.9 32.1 30.1 19.1 15.0 4.6 0.9 1,564 30-34 67.0 2,008 32.4 29.0 34.4 30.0 24.6 16.0 5.5 1.4 1,345 35-39 70.9 1,935 32.7 26.6 29.6 27.1 20.8 10.3 5.2 0.5 1,372 40-44 67.0 1,402 29.1 28.3 27.2 31.0 20.6 15.7 5.6 2.1 939 45-49 69.4 1,688 29.1 30.9 34.6 30.1 24.7 11.3 4.1 1.1 1,172 Residence Urban 68.7 2,479 34.6 31.5 33.9 37.3 22.7 14.5 3.0 1.9 1,702 Rural 67.1 8,281 31.2 28.4 31.6 27.7 21.8 13.4 5.3 1.0 5,556 Province1 Kabul 57.9 1,350 41.3 39.6 41.8 39.9 26.5 17.4 5.1 1.9 782 Kapisa 94.3 63 21.3 19.4 11.6 16.4 25.6 0.7 32.6 3.5 59 Parwan 88.6 220 51.3 56.3 54.3 56.6 33.2 20.0 0.6 0.9 195 Wardak 58.6 171 22.7 12.2 9.9 13.4 16.7 0.8 16.6 2.3 100 Logar 49.9 204 35.2 12.7 14.8 22.7 25.2 1.9 0.0 0.6 102 Nangarhar 71.4 273 46.0 21.1 31.4 23.6 37.1 9.7 7.3 0.0 195 Laghman 77.9 227 36.5 33.2 36.1 47.7 33.9 16.6 1.0 2.0 176 Panjsher 56.1 18 88.1 88.8 88.1 86.4 79.4 16.2 0.0 0.0 10 Baghlan 65.4 281 10.6 27.9 22.5 11.0 6.8 1.0 0.0 0.1 184 Bamyan 69.4 94 10.3 16.5 10.3 25.4 11.7 0.9 5.3 3.4 65 Ghazni 33.9 619 25.6 33.1 34.2 18.3 11.0 9.4 0.0 0.2 210 Paktika 41.7 322 2.5 19.7 61.8 5.7 0.9 0.7 0.0 1.6 134 Paktya 97.8 206 56.3 14.4 48.5 54.8 51.2 46.7 0.0 0.0 201 Khost 97.8 334 30.6 22.6 23.7 40.0 22.9 35.6 17.4 0.7 327 Kunarha 77.0 151 51.9 42.2 26.4 14.3 20.8 39.6 1.2 0.9 116 Nooristan 18.2 66 4.1 5.7 8.9 13.9 13.2 4.6 2.0 2.2 12 Badakhshan 57.0 316 34.9 44.2 47.5 45.8 43.4 11.2 0.2 0.0 180 Takhar 79.0 296 8.5 10.2 9.8 4.6 3.4 0.0 6.3 1.4 234 Kunduz 57.7 479 47.5 37.3 41.1 50.1 29.8 15.6 0.0 1.6 277 Samangan 38.9 125 28.4 22.4 30.4 13.2 15.6 7.8 0.0 0.0 49 Balkh 82.7 616 34.8 32.8 29.8 41.7 30.2 12.0 0.6 0.3 510 Sar-E-Pul 68.2 195 27.7 28.1 31.5 32.5 25.8 18.3 2.2 1.0 133 Ghor 73.4 322 45.8 47.7 50.8 34.2 8.3 1.4 34.2 2.6 236 Daykundi 43.9 77 5.4 3.8 2.0 6.1 2.7 0.0 16.2 5.6 34 Urozgan 14.4 92 (12.9) (2.9) (2.7) (12.9) (2.7) (2.7) (0.0) (4.1) 13 Kandahar 89.6 874 5.4 4.2 11.5 29.9 2.9 1.6 7.9 0.8 783 Jawzjan 89.9 218 60.3 59.0 61.1 59.6 54.3 32.2 1.7 0.3 196 Faryab 75.2 706 37.6 31.8 26.3 5.5 19.3 3.1 1.3 0.5 531 Helmand 67.8 355 56.7 60.1 63.1 61.2 54.0 59.9 0.1 2.7 241 Badghis 74.4 231 35.1 40.9 46.0 17.9 44.8 7.0 5.8 1.6 172 Herat 73.4 863 20.4 19.1 20.4 3.5 3.8 10.2 0.3 0.0 633 Farah 41.5 295 53.5 40.1 48.9 46.5 19.5 7.5 0.0 0.1 122 Nimroz 42.0 93 0.0 1.9 6.8 19.2 15.0 0.6 0.0 37.5 39 Education No education 61.1 5,447 23.1 22.1 24.1 24.7 16.4 8.8 5.9 1.3 3,330 Primary 67.1 1,987 33.3 25.6 29.1 29.2 23.4 16.9 3.1 1.1 1,334 Secondary 74.8 2,632 41.7 38.9 42.6 36.8 27.0 17.2 3.8 1.4 1,969 More than secondary 90.0 695 46.2 43.8 48.8 38.2 33.2 21.0 5.6 0.3 625 Wealth quintile Lowest 66.1 2,029 27.6 27.1 28.6 23.5 16.1 7.2 6.5 0.9 1,342 Second 61.8 2,233 33.3 30.6 32.2 30.4 26.4 19.6 3.7 0.6 1,379 Middle 66.5 2,160 30.3 27.2 32.2 29.9 21.3 12.7 6.0 1.4 1,436 Fourth 71.1 2,260 31.9 29.0 33.7 27.5 24.5 12.1 4.5 0.8 1,606 Highest 71.9 2,078 36.5 31.7 33.6 38.3 21.3 16.4 3.3 2.1 1,495 Total 67.4 10,760 32.0 29.2 32.2 30.0 22.0 13.6 4.8 1.2 7,258 Note: Figures in parentheses are based on 25-49 unweighted cases. 1 Estimates for Zabul are not presented separately due to sample coverage issues; however, they are included in the total national estimates. 58 • Characteristics of Respondents Table 3.12.1 Reported prevalence of hepatitis: Women Among ever-married women age 15-49 who have heard of hepatitis, the percentage who have ever been diagnosed with hepatitis by type of hepatitis, and among those, the percentage with specific types of hepatitis, and the percentage of those currently suffering from hepatitis by type of hepatitis diagnosed, according to background characteristics, Afghanistan 2015 Among respondents who have heard of hepatitis: Among those who have ever been diagnosed with hepatitis, percentage diagnosed with specific types of hepatitis: Among respondents currently suffering from hepatitis, percentage having specific types of hepatitis: Background characteristic Percent- age who have ever been told by doctor/ nurse they have/had hepatitis Number of respon- dents Hepatitis A Hepatitis B Hepatitis C Don’t know Percent- age who are currently suffering from hepatitis Number of respon- dents Hepatitis A Hepatitis B Hepatitis C Number of respon- dents Age 15-19 8.8 1,161 61.9 17.9 13.8 10.7 23.3 102 * * * 24 20-24 8.0 4,035 59.2 21.6 10.0 10.0 45.3 323 54.7 41.4 4.2 146 25-29 7.6 4,231 59.4 24.3 10.2 6.8 34.7 320 52.1 36.8 7.3 111 30-34 8.0 2,834 64.1 21.4 12.7 4.6 39.9 227 54.4 35.2 10.4 91 35-39 8.4 3,067 63.5 22.2 12.3 3.0 39.7 258 53.6 31.0 17.4 103 40-44 9.1 2,129 53.5 35.1 10.6 4.7 45.4 193 35.5 53.6 11.2 88 45-49 8.0 2,393 57.7 30.9 5.9 7.0 48.1 192 46.4 45.2 7.2 93 Residence Urban 6.3 4,681 55.6 20.5 11.3 12.7 45.9 295 53.1 38.0 10.4 135 Rural 8.7 15,169 60.9 25.6 10.5 5.1 39.3 1,322 48.6 42.0 8.6 520 Education No education 9.0 16,339 60.4 24.3 10.7 6.2 40.6 1,477 50.0 41.7 8.4 599 Primary 4.8 1,583 54.5 30.3 10.2 10.8 43.5 77 (39.4) (41.6) (10.4) 33 Secondary 3.5 1,467 59.7 26.5 11.9 2.5 42.1 51 * * * 21 More than secondary 2.7 460 37.1 21.0 2.9 38.9 6.9 12 * * * 1 Wealth quintile Lowest 7.8 3,649 50.4 33.6 14.7 3.9 62.1 283 39.9 48.4 13.5 176 Second 9.6 3,667 57.9 27.6 9.2 7.6 39.4 354 47.2 45.6 6.8 139 Middle 10.7 4,161 64.7 25.1 9.3 2.8 35.4 445 55.6 40.6 5.7 157 Fourth 7.6 4,358 63.1 17.5 9.7 11.5 33.4 333 45.1 39.1 8.4 111 Highest 5.1 4,014 61.3 18.0 11.8 8.3 35.1 203 71.5 18.8 9.8 71 Total 8.1 19,850 59.9 24.7 10.6 6.5 40.5 1,617 49.5 41.2 8.9 655 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. Provincial-level estimates are not presented because there are too few cases. Characteristics of Respondents • 59 Table 3.12.2 Reported prevalence of hepatitis: Men Among ever-married men age 15-49 who have heard of hepatitis, the percentage who have ever been diagnosed with hepatitis by type of hepatitis, and among those, the percentage with specific types of hepatitis, and the percentage of those currently suffering from hepatitis by type of hepatitis diagnosed, according to background characteristics, Afghanistan 2015 Among respondents who have heard of hepatitis: Among those who have ev

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