National Family Health Survey - (NFHS - 5), 2019–21

Publication date: 2022

National Family Health Survey (NFHS - 5), 2019–21 (N F H S - 5 ) INDIA REPORT Internaonal Instute for Populaon Sciences Deonar, Mumbai- 400088 Government of India Ministry of Health and Family Welfare International Institute for Population Sciences Deonar, Mumbai- 400088 Technical assistance and additional funding for NFHS-5 was provided by the USAID- supported Demographic and Health Surveys (DHS) program, ICF, USA. The contents of this publication do not necessarily reflect the views of USAID or the United States Government. The opinions in this publication do not necessarily reflect the views of the funding agencies. For additional information on NFHS-5, visit https://www.iipsindia.ac.in or https://main.mohfw.gov.in For addional informaon, please contact: Director General (Stats.) Ministry of Health and Family Welfare Government of India Statistics Division Indian Red Cross Society Building, New Delhi - 110001 (India) Telephone: 011- 23736979 Email: sandhya.k@nic.in Director International Institute for Population Sciences Govandi Station Road, Deonar, Mumbai – 400088 (India) Telephone: 022 – 42372467 Email: director@iipsindia.ac.in N ational Fam ily H ealth Survey In d ia 2 0 1 9 – 2 1 NATIONAL FAMILY HEALTH SURVEY (NFHS-5) 2019-21 INDIA MARCH 2022 Suggested citation: International Institute for Population Sciences (IIPS) and ICF. 2021. National Family Health Survey (NFHS-5), 2019-21: India. Mumbai: IIPS. For additional information about the 2019-21 National Family Health Survey (NFHS-5), please contact: International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai-400088 Telephone: 022-4237 2442 Email: nfhs52017@gmail.com, director@iipsindia.ac.in For related information, visit http://www.rchiips.org/nfhs or http://www.iipsindia.ac.in CONTENTS TABLES AND FIGURES . KEY MESSAGE FROM HEALTH MINISTER OF MINISTRY OF HEALTH AND FAMILY WELFARE . KEY MESSAGE FROM MINISTER OF STATES MINISTRY OF HEALTH AND FAMILY WELFARE . FOREWORD FROM SECRETARY OF MINISTRY OF HEALTH AND FAMILY WELFARE . PREFACE . PROLOGUE . MESSAGE . FROM DIRECTOR’S DESK . ACKNOWLEDGEMENTS . CHAPTER 1 INTRODUCTION . 1.1 Survey Objectives . 1.2 Sample Design . 1.3 Questionnaires . 1.4 Biomarker Measurements and Tests . 1.5 Pretest . 1.6 Training of Field Staff . 1.7 Fieldwork . 1.8 Strategy to Ensure Data Quality . 1.9 Data Processing . 1.10 Response Rates. CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS . 2.1 Drinking Water Sources and Treatment . 2.2 Sanitation . 2.3 Exposure to Smoke inside the Home and Other Housing Characteristics . 2.3.1 Exposure to Smoke inside the Home . 2.3.2 Other Housing Characteristics . 2.4 Household Wealth . 2.5 Hand Washing . 2.6 Household Population and Composition . 2.7 Birth Registration . 2.8 Death Registration . 2.9 Children’s Living Arrangements and Parental Survival. 2.10 Schooling . 2.10.1 Educational Attainment . 2.10.2 Preschool Attendance . 2.10.3 School Attendance . 2.11 Disability . 2.12 Use of Tobacco and Alcohol . 2.13 Possession of Mosquito Nets . CONTENTS TABLES AND FIGURES . KEY MESSAGE FROM HEALTH MINISTER OF MINISTRY OF HEALTH AND FAMILY WELFARE . KEY MESSAGE FROM MINISTER OF STATES MINISTRY OF HEALTH AND FAMILY WELFARE . FOREWORD FROM SECRETARY OF MINISTRY OF HEALTH AND FAMILY WELFARE . PREFACE . PROLOGUE . MESSAGE . FROM DIRECTOR’S DESK . ACKNOWLEDGEMENTS . CHAPTER 1 INTRODUCTION . 1.1 Survey Objectives . 1.2 Sample Design . 1.3 Questionnaires . 1.4 Biomarker Measurements and Tests . 1.5 Pretest . 1.6 Training of Field Staff . 1.7 Fieldwork . 1.8 Strategy to Ensure Data Quality . 1.9 Data Processing . 1.10 Response Rates. CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS . 2.1 Drinking Water Sources and Treatment . 2.2 Sanitation . 2.3 Exposure to Smoke inside the Home and Other Housing Characteristics . 2.3.1 Exposure to Smoke inside the Home . 2.3.2 Other Housing Characteristics . 2.4 Household Wealth . 2.5 Hand Washing . 2.6 Household Population and Composition . 2.7 Birth Registration . 2.8 Death Registration . 2.9 Children’s Living Arrangements and Parental Survival. 2.10 Schooling . 2.10.1 Educational Attainment . 2.10.2 Preschool Attendance . 2.10.3 School Attendance . 2.11 Disability . 2.12 Use of Tobacco and Alcohol . 2.13 Possession of Mosquito Nets . Suggested citation: International Institute for Population Sciences (IIPS) and ICF. 2021. National Family Health Survey (NFHS-5), 2019-21: India. Mumbai: IIPS. For additional information about the 2019-21 National Family Health Survey (NFHS-5), please contact: International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai-400088 Telephone: 022-4237 2442 Email: nfhs52017@gmail.com, director@iipsindia.ac.in For related information, visit http://www.rchiips.org/nfhs or http://www.iipsindia.ac.in CONTRIBUTORS K. S. James S.K. Singh Hemkhothang Lhungdim Chander Shekhar Laxmi Kant Dwivedi Sarang Pedgaonkar Fred Arnold CONTENTS TABLES AND FIGURES . KEY MESSAGE FROM HEALTH MINISTER OF MINISTRY OF HEALTH AND FAMILY WELFARE . KEY MESSAGE FROM MINISTER OF STATES MINISTRY OF HEALTH AND FAMILY WELFARE . FOREWORD FROM SECRETARY OF MINISTRY OF HEALTH AND FAMILY WELFARE . PREFACE . PROLOGUE . MESSAGE . FROM DIRECTOR’S DESK . ACKNOWLEDGEMENTS . CHAPTER 1 INTRODUCTION . 1.1 Survey Objectives . 1.2 Sample Design . 1.3 Questionnaires . 1.4 Biomarker Measurements and Tests . 1.5 Pretest . 1.6 Training of Field Staff . 1.7 Fieldwork . 1.8 Strategy to Ensure Data Quality . 1.9 Data Processing . 1.10 Response Rates. CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS . 2.1 Drinking Water Sources and Treatment . 2.2 Sanitation . 2.3 Exposure to Smoke inside the Home and Other Housing Characteristics . 2.3.1 Exposure to Smoke inside the Home . 2.3.2 Other Housing Characteristics . 2.4 Household Wealth . 2.5 Hand Washing . 2.6 Household Population and Composition . 2.7 Birth Registration . 2.8 Death Registration . 2.9 Children’s Living Arrangements and Parental Survival. 2.10 Schooling . 2.10.1 Educational Attainment . 2.10.2 Preschool Attendance . 2.10.3 School Attendance . 2.11 Disability . 2.12 Use of Tobacco and Alcohol . 2.13 Possession of Mosquito Nets . CONTENTS TABLES AND FIGURES . KEY MESSAGE FROM HEALTH MINISTER OF MINISTRY OF HEALTH AND FAMILY WELFARE . KEY MESSAGE FROM MINISTER OF STATES MINISTRY OF HEALTH AND FAMILY WELFARE . FOREWORD FROM SECRETARY OF MINISTRY OF HEALTH AND FAMILY WELFARE . PREFACE . PROLOGUE . MESSAGE . FROM DIRECTOR’S DESK . ACKNOWLEDGEMENTS . CHAPTER 1 INTRODUCTION . 1.1 Survey Objectives . 1 1.2 Sample Design . 2 1.3 Questionnaires . 3 1.4 Biomarker Measurements and Tests . 4 1.5 Pretest . 6 1.6 Training of Field Staff . 6 1.7 Fieldwork . 6 1.8 Strategy to Ensure Data Quality . 7 1.9 Data Processing .11 1.10 Response Rates.11 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS .15 2.1 Drinking Water Sources and Treatment .16 2.2 Sanitation .17 2.3 Exposure to Smoke inside the Home and Other Housing Characteristics .17 2.3.1 Exposure to Smoke inside the Home .17 2.3.2 Other Housing Characteristics .18 2.4 Household Wealth .18 2.5 Hand Washing .19 2.6 Household Population and Composition .19 2.7 Birth Registration .20 2.8 Death Registration .21 2.9 Children’s Living Arrangements and Parental Survival.21 2.10 Schooling .21 2.10.1 Educational Attainment .21 2.10.2 Preschool Attendance .22 2.10.3 School Attendance .23 2.11 Disability .24 2.12 Use of Tobacco and Alcohol .25 2.13 Possession of Mosquito Nets .28 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS .79 3.1 Basic Characteristics of Survey Respondents .79 3.2 Schooling and Literacy .80 3.3 Mass Media Exposure .81 3.4 Employment .83 3.5 Occupation .83 CHAPTER 4 FERTILITY AND FERTILITY PREFERENCES .111 4.1 Current Fertility .111 4.2 Children Ever Born and Living .113 4.3 Birth Order .113 4.4 Birth Intervals .114 4.5 Age at First Birth .114 4.6 Menstrual Protection .115 4.7 Bathing Practices During Menstrual Period .116 4.8 Teenage Childbearing .116 4.9 Desire for Another Child .118 4.10 Ideal Family Size.119 4.11 Fertility Planning Status .120 4.12 Wanted Fertility Rates .120 CHAPTER 5 FAMILY PLANNING .157 5.1 Contraceptive Knowledge and Use .157 5.2 Source of Modern Contraceptive Methods.161 5.3 Informed Choice.162 5.4 Discontinuation of Contraceptives .162 5.5 Exposure to Family Planning Messages .163 5.6 Demand for Family Planning .163 5.7 Hysterectomy .165 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY .207 6.1 Marital Status .207 6.2 Age at First Marriage .208 6.3 Consanguineous Marriages .209 6.4 Age at First Sexual Intercourse .210 6.5 Recent Sexual Activity .211 6.6 Insusceptibility to Pregnancy .211 6.7 Pregnancy Outcomes .212 6.7.1 Characteristics of Abortions .213 CHAPTER 7 INFANT AND CHILD MORTALITY .241 7.1 Infant and Child Mortality.242 7.2 Biodemographic Risk Factors .243 7.3 Perinatal Mortality .244 CHAPTER 8 MATERNAL HEALTH .259 8.1 Pregnancy Registration .260 8.1.1 Registration of Pregnancies .260 8.1.2 Mother and Child Protection Card (MCP Card) .260 8.2 Antenatal Care Coverage and Content .260 8.2.1 Skilled Providers .260 8.2.2 Timing and Number of ANC Visits .261 8.3 Components of ANC Visits.263 8.4 Protection against Neonatal Tetanus .263 8.5 Ultrasound Testing during Pregnancy .264 8.6 Delivery Services .264 8.6.1 Institutional Deliveries .264 8.6.2 Skilled Assistance during Delivery .266 8.6.3 Delivery by Caesarean Section .267 8.7 Delivery Costs .269 8.8 Postnatal Care .270 8.8.1 Postnatal Health Check for Mothers .270 8.8.2 Postnatal Health Checks for Newborns .271 CHAPTER 9 CHILD HEALTH .323 9.1 Birth Weight .324 9.2 Vaccination of Children .324 9.3 Symptoms of Acute Respiratory Infection .329 9.4 Fever .329 9.5 Diarrhoeal Disease .329 9.5.1 Prevalence of Diarrhoea .329 9.5.2 Treatment of Diarrhoea .331 9.5.3 Feeding Practices .333 9.5.4 Knowledge of ORS Packets .333 9.6 Disposal of Children’s Stools .334 9.7 Utilization of Integrated Child Development Services (ICDS) .334 9.7.1 Utilization of ICDS by Pregnant and Lactating Mothers .335 CHAPTER 10 NUTRITION AND ANAEMIA .373 10.1 Nutritional Status of Children .374 10.1.1 Nutritional Status among Young Children .374 10.1.2 Levels of Child Malnutrition .375 10.2 Infant and Young Child Feeding Practices .376 10.2.1 Initiation of Breastfeeding .376 10.2.2 Exclusive Breastfeeding .377 10.2.3 Median Duration of Breastfeeding .377 10.2.4 Complementary Feeding .378 10.2.5 Minimum Acceptable Diet .378 10.3 Anaemia Prevalence in Children .380 10.4 Presence of Iodised Salt in Households .381 10.5 Micronutrient Intake and Supplementation among Children .381 10.6 Nutritional Status in Adults .381 10.7 Waist-to-Hip Ratio in Adults .383 10.8 Anaemia Prevalence in Adults .384 10.9 Food Consumption of Women and Men .385 CHAPTER 11 MORBIDITY AND HEALTH CARE .443 11.1 Tuberculosis .443 11.1.1 Prevalence of Tuberculosis .443 11.1.2 Knowledge and Attitudes toward Tuberculosis .444 11.2 Health Problems .445 11.3 Use of Tobacco .445 11.3.1 Consumption of Tobacco .445 11.3.2 Quitting Tobacco .446 11.4 Alcohol Use, Health Insurance, and Sources of Health Care .447 11.4.1 Use of Alcohol .447 11.5 Health Insurance Coverage .447 11.6 Sources of Health Care .448 11.7 Reasons for Not Using Government Health Care .449 11.8 Recent Contact with Health Workers .449 11.9 Problems in Accessing Health Care .449 CHAPTER 12 OTHER ADULT HEALTH ISSUES .487 12.1 Coverage of Testing for Blood Pressure and Random Blood Glucose Measurements .488 12.2 Blood Pressure .488 12.2.1 Self Reports of Blood Pressure Measurement and Medication .488 12.2.2 Blood Pressure Levels and Treatment Status .488 12.3 Random Blood Glucose .489 12.4 Health Examinations for Cancer Screening .490 12.5 Age-Specific Death Rates and Crude Death Rates .491 12.6 Adult Mortality.491 CHAPTER 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR .517 13.1 HIV/AIDS Knowledge, Transmission, and Prevention Methods .518 13.2 Comprehensive Knowledge .519 13.3 Knowledge about Mother-to-Child Transmission .520 13.4 Accepting Attitudes toward People Living with HIV .521 13.5 Attitudes toward Negotiating Sex with Husband .522 13.6 Multiple Sexual Partners .522 13.7 Paid Sex.523 13.8 Coverage of HIV Testing Services .523 13.8.1 Awareness of HIV Testing Services and Experience with HIV Testing .523 13.8.2 HIV Testing of Pregnant Women .525 13.9 Self-Reporting of Sexually Transmitted Infections .525 13.10 HIV/AIDS-related Knowledge and Behaviour among Young People .526 13.10.1 Knowledge of HIV/AIDS.526 13.10.2 First Sex .526 13.10.3 Premarital Sex .527 13.10.4 Multiple Sexual Partners .527 13.10.5 Coverage of HIV Testing Services .527 CHAPTER 14 WOMEN’S EMPOWERMENT .581 14.1 Currently Married Women’s and Men’s Employment .582 14.2 Control over Women’s Earnings .583 14.3 Control over Men’s Earnings .584 14.4 Participation in Household Decision Making .584 14.5 Men’s Attitudes toward Women’s Roles in Decision Making .585 14.6 Women’s Access to Money and Microcredit .586 14.7 Freedom of Movement .587 14.8 Attitudes toward Wife Beating .587 14.9 Attitudes toward Negotiating Safer Sexual Relations with Husband .588 14.10 Women’s and Men’s Ownership of Assets .589 14.11 Ownership and Use of a Mobile Phone .590 CHAPTER 15 DOMESTIC VIOLENCE .641 15.1 Measurement of Violence .642 15.2 Women’s Experience of Physical Violence .643 15.2.1 Perpetrators of Physical Violence .644 15.3 Experience of Sexual Violence .644 15.3.1 Prevalence of Sexual Violence .644 15.3.2 Perpetrators of Sexual Violence .644 15.4 Experience of Different Types of Violence.645 15.5 Marital Control by Husband .645 15.6 Forms of Spousal Violence .646 16.6.1 Prevalence of Spousal Violence .646 15.7 Injuries to Women due to Spousal Violence .649 15.8 Violence Initiated by Women against Husbands .649 15.9 Help-seeking among Women who have Experienced Violence .650 16.9.1 Sources of Help .650 TABLES AND FIGURES CHAPTER 1 INTRODUCTION . 1 Table 1.1 Results of the household and individual interviews . 13 Table 1.2 Number of households, women, and men interviewed by state/union territory . 14 CHAPTER 2 HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS . 15 Table 2.1 Household drinking water . 31 Table 2.2 Household sanitation facilities . 33 Table 2.3 Sanitation facility type by wealth quintile and state/union territory . 34 Table 2.4 Access to a toilet facility . 36 Table 2.5 Access to a toilet facility by state/union territory . 37 Table 2.6 Housing characteristics . 38 Table 2.7 Housing characteristics by state/union territory . 40 Table 2.8 Wealth quintiles by state/union territory . 41 Table 2.9 Religion and caste/tribe by wealth quintiles . 42 Table 2.10 Religion and caste/tribe of household head by state/union territory . 43 Table 2.11 Household possessions . 45 Table 2.12 Household ownership of agricultural land, house, and farm animals . 46 Table 2.13 Hand washing . 47 Table 2.14 Household composition . 48 Table 2.15 Household population by age, residence, sex, and possession of an Aadhaar card . 49 Table 2.16 Birth registration of children . 50 Table 2.17 Birth registration of children by state/union territory . 52 Table 2.18 Death registration . 53 Table 2.19 Death registration by state/union territory . 54 Table 2.20 Children's living arrangements and orphanhood . 55 Table 2.21 Children's living arrangements and orphanhood by state/union territory . 56 Table 2.22 Preschool attendance . 58 Table 2.23 Preschool attendance by state/union territory . 59 Table 2.24 Educational attainment of household population . 60 Table 2.25 Educational attainment of household population by state/union territory . 62 Table 2.26 School attendance by state/union territory . 64 Table 2.27 School attendance ratios . 66 Table 2.28 Reasons for children currently not attending school . 68 Table 2.29 Disability . 69 Table 2.30 Prevalence of any disability . 71 Table 2.31 Prevalence of any disability by state/union territory . 72 Table 2.32 Household possession of mosquito nets . 73 Table 2.33 Use of alcohol by the population age 15 and over . 75 Table 2.34 Use of alcohol by the population age 15 and over by state/union territory . 76 Table 2.35 Use of tobacco by the population age 15 and over . 77 Table 2.36 Use of tobacco by the population age 15 and over by state/union territory . 78 CHAPTER 3 CHARACTERISTICS OF RESPONDENTS . 79 Table 3.1 Background characteristics of respondents . 86 Table 3.2.1 Respondent's level of schooling: Women. 88 Table 3.2.2 Respondent's level of schooling: Men . 89 Table 3.3.1 Literacy: Women . 90 Table 3.3.2 Literacy: Men . 91 Table 3.4.1 Respondent's level of schooling and literacy by state/union territory: Women. 92 Table 3.4.2 Respondent's level of schooling and literacy by state/union territory: Men . 94 Table 3.5.1 Exposure to mass media: Women . 96 Table 3.5.2 Exposure to mass media: Men. 98 Table 3.6 Internet usage: Men and Women. 100 Table 3.7 Exposure to mass media and internet usage by state/union territory . 102 Table 3.8 Employment status: Women . 104 Table 3.9 Employment status: Men . 105 Table 3.10 Employment status of women and men by state/union territory . 106 Table 3.11 Occupation . 108 Table 3.12 Type of employment . 109 CHAPTER 4 FERTILITY AND FERTILITY PREFERENCES . 111 Table 4.1 Current fertility . 123 Table 4.2 Fertility by background characteristics . 124 Table 4.3 Fertility by state/union territory . 125 Table 4.4 Trends in age-specific fertility rates . 127 Table 4.5 Children ever born and living . 128 Table 4.6 Birth order . 129 Table 4.7 Birth intervals . 130 Table 4.8 Age at first birth . 132 Table 4.9 Median age at first birth . 133 Table 4.10 Teenage pregnancy and motherhood . 134 Table 4.11 Teenage pregnancy and motherhood by state/union territory . 136 Table 4.12 Fertility preferences by number of living children . 137 Table 4.13 Menstrual protection . 138 Table 4.14 Menstrual protection by state/union territory . 139 Table 4.15 Bathing practices during menstrual period . 141 Table 4.16 Bathing practices during menstrual period by state/union territory . 142 Table 4.17 Desire to limit childbearing . 144 Table 4.18 Desire to limit childbearing by state/union territory . 146 Table 4.19.1 Indicators of sex preference: Women . 148 Table 4.19.2 Indicators of sex preference: Men . 150 Table 4.20 Indicators of sex preference by state/union territory . 152 Table 4.21 Fertility planning status . 154 Table 4.22 Wanted fertility rates . 155 Table 4.23 Wanted fertility rates by state/union territory . 156 More Children by Number of Living Sons . Figure 4.8 Trends in Wanted and Actual Fertility . CHAPTER 5 FAMILY PLANNING . 157 Table 5.1 Knowledge of contraceptive methods . 167 Table 5.2 Current use of contraception by state/union territory . 170 Table 5.3.1 Current use of contraception by background characteristics . 176 Table 5.3.2 Contraceptive use by men with last partner . 178 Table 5.4 Knowledge of contraceptive methods among adolescents . 181 Table 5.5 Current use of contraception by age . 182 Table 5.6 Timing of sterilization . 184 Table 5.7 Compensation for sterilization and PPIUD . 185 Table 5.8 Compensation for sterilization and PPIUD by state/union territory . 186 Table 5.9 Source of Modern Contraceptive Methods . 187 Table 5.10 Public sector as source of modern contraceptives methods by state/union territory . 190 Table 5.11 Use and source of emergency contraceptive pills . 192 Table 5.12 Informed choice . 193 Table 5.13 Informed choice by state/union territory . 194 Table 5.14 Twelve-month contraceptive discontinuation rates . 195 Table 5.15 Twelve-month contraceptive discontinuation rates by state/union territory. 196 Table 5.16.1 Exposure to family planning messages: Women . 197 Table 5.16.2 Exposure to family planning messages: Men . 198 Table 5.17 Men's contraception-related perceptions and knowledge . 199 Table 5.18 Men's contraception-related perceptions and knowledge by state/union territory . 200 Table 5.19 Need and demand for family planning . 201 Table 5.20 Need and demand for family planning by state/union territory . 203 Table 5.21 Hysterectomy . 205 Table 5.22 Hysterectomy by state/union territory . 206 CHAPTER 6 OTHER PROXIMATE DETERMINANTS OF FERTILITY . 207 Table 6.1 Current marital status . 215 Table 6.2 Age at first marriage . 217 Table 6.3.1 Median age at first marriage: Women . 218 Table 6.3.2 Median age at first marriage: Men . 219 Table 6.4 Age at first marriage by state/union territory . 220 Table 6.5 Consanguineous marriages . 221 Table 6.6 Consanguineous marriages by state/union territory . 222 Table 6.7 Age at first sexual intercourse . 223 Table 6.8.1 Median age at first sexual intercourse: Women . 224 Table 6.8.2 Median age at first sexual intercourse: Men . 225 Table 6.9.1 Most recent sexual activity: Women . 226 Table 6.9.2 Most recent sexual activity: Men . 228 Table 6.10 Postpartum amenorrhoea, abstinence, and insusceptibility . 230 Table 6.11 Median duration of postpartum amenorrhoea, postpartum abstinence, and postpartum insusceptibility . 231 Table 6.12 Menopause . 232 Table 6.13 Non-live births . 233 Table 6.14 Non-live births by state/union territory . 234 Table 6.15 Pregnancy outcome . 235 Table 6.16 Pregnancy outcome by state/union territory . 236 Table 6.17 Characteristics of abortions . 237 Table 6.18 Main reason for abortions by state/union territory . 239 CHAPTER 7 INFANT AND CHILD MORTALITY . 241 Table 7.1 Early childhood mortality rates . 247 Table 7.2 Early childhood mortality rates by background characteristics . 248 Table 7.3 Early childhood mortality rates by demographic characteristics . 251 Table 7.4 Early childhood mortality rates by state/union territory . 254 Table 7.5 Perinatal mortality . 255 Table 7.6 Perinatal mortality by state/union territory . 256 Table 7.7 High-risk fertility behaviour . 257 Figure 7.1 Trends in Early Childhood Mortality Rates . Figure 7.2 Under-five Mortality Rate by State/UT . Figure 7.3 High-risk Births Have Higher Mortality Rates . CHAPTER 8 MATERNAL HEALTH . 259 Table 8.1 Pregnancy registration and Mother and Child Protection Card . 273 Table 8.2 Health problems during pregnancy . 274 Table 8.3 Antenatal care. 275 Table 8.4 Antenatal care by state/union territory . 276 Table 8.5 Number of antenatal care visits and timing of first visit . 277 Table 8.6 Number of antenatal care visits and timing of first visit by source . 278 Table 8.7 Components of antenatal care . 279 Table 8.8 Antenatal care services and information received . 280 Table 8.9 Male involvement in antenatal care . 282 Table 8.10 Reasons why child's mother did not receive antenatal care: Men . 284 Table 8.11 Antenatal care indicators by state/union territory. 285 Table 8.12 Pregnancies for which an ultrasound test was done . 287 Table 8.13 Place of delivery . 289 Table 8.14 Reasons for not delivering in a health facility . 291 Table 8.15 Institutional delivery of youngest child: Men . 292 Table 8.16 Delivery and other related information given to men: Men's reports . 293 Table 8.17 Delivery and other related information given to men by state/union territory: Men's reports . 295 Table 8.18 Adherence to delivery protocol for home delivery . 297 Table 8.19 Assistance during delivery . 298 Table 8.20 Delivery costs . 301 Table 8.21 Duration of stay in health facility after birth . 302 Table 8.22 Timing of first postnatal check for the mother . 303 Table 8.23 Type of provider of first postnatal check for the mother . 306 Table 8.24 Timing of first postnatal check for the newborn . 308 Table 8.25 Type of provider of first postnatal check for the newborn . 311 Table 8.26 Components of postnatal health check . 313 Table 8.27 Symptoms of postpartum complications . 314 Table 8.28 Maternal care indicators by state/union territory . 315 Table 8.29 Trends in maternal care indicators . 317 Table 8.30 Advice received during pregnancy . 318 Table 8.31 Delivery and postnatal care by state/union territory . 319 Table 8.32 Birth order and delivery characteristics by state/union territory . 321 CHAPTER 9 CHILD HEALTH . 323 Table 9.1 Child's weight and size at birth . 337 Table 9.2 Child's weight and size at birth by state/union territory . 339 Table 9.3 Vaccinations by source of information. 341 Table 9.4 Vaccinations by background characteristics . 343 Table 9.5 Vaccinations by state/union territory . 345 Table 9.6 Trends over time in vaccinations . 347 Table 9.7 Prevalence and treatment of symptoms of ARI . 348 Table 9.8 Prevalence and treatment of symptoms of ARI by state/union territory . 350 Table 9.9 Prevalence and treatment of fever . 352 Table 9.10 Prevalence of diarrhoea . 354 Table 9.11 Diarrhoea treatment . 356 Table 9.12 Diarrhoea treatment by state/union territory . 358 Table 9.13 Feeding practices during diarrhoea . 360 Table 9.14 Feeding practices during diarrhoea by state/union territory . 362 Table 9.15 Knowledge of ORS packets . 364 Table 9.16 Disposal of children's stools . 365 Table 9.17 Disposal of children's stools by state/union territory. 367 Table 9.18 Indicators of utilization of ICDS services . 368 Table 9.19 Indicators of utilization of ICDS services by state/union territory . 369 Table 9.20 Utilization of ICDS services during pregnancy and while breastfeeding . 371 Table 9.21 Indicators of women’s utilization of ICDS services during pregnancy and while breastfeeding by state/union territory . 372 CHAPTER 10 NUTRITION AND ANAEMIA . 373 Table 10.1 Nutritional status of children . 387 Table 10.2 Nutritional status of children by state/union territory . 391 Table 10.3 Trends in nutritional status of children . 394 Table 10.4 Initial breastfeeding . 395 Table 10.5 Initial breastfeeding by state/union territory . 397 Table 10.6 Breastfeeding status by age . 399 Table 10.7 Median duration of breastfeeding . 400 Table 10.8 Median duration of breastfeeding by state/union territory . 401 Table 10.9 Foods and liquids consumed by children in the day or night preceding the interview . 402 Table 10.10 Minimum acceptable diet . 403 Table 10.11 Minimum acceptable diet by state/union territory . 405 Table 10.12 Prevalence of anaemia in children . 408 Table 10.13 Prevalence of anaemia in children by state/union territory . 410 Table 10.14 Trends in prevalence of anaemia in children . 411 Table 10.15 Presence of iodized salt in household . 412 Table 10.16 Presence of iodized salt in household by state/union territory . 413 Table 10.17 Micronutrient intake among children . 414 Table 10.18 Micronutrient intake among children by state/union territory . 417 Table 10.19.1 Nutritional status of women . 420 Table 10.19.2 Nutritional status of men . 422 Table 10.20.1 Nutritional status of women by state/union territory . 424 Table 10.20.2 Nutritional status of men by state/union territory . 426 Table 10.21 Waist circumference and waist-to-hip ratio . 428 Table 10.22 Waist circumference and waist-to-hip ratio by state/union territory . 430 Table 10.23.1 Prevalence of anaemia in women . 432 Table 10.23.2 Prevalence of anaemia in men . 434 Table 10.24 Prevalence of anaemia in women and men by state/union territory . 436 Table 10.25 Women's and men's food consumption . 437 Table 10.26.1 Women's food consumption . 438 Table 10.26.2 Men's food consumption . 439 Table 10.27.1 Women's food consumption by state/union territory . 440 Table 10.27.2 Men's food consumption by state/union territory . 441 CHAPTER 11 MORBIDITY AND HEALTH CARE . 443 Table 11.1 Prevalence of tuberculosis . 451 Table 11.2 Prevalence of tuberculosis by persons per sleeping room and cooking fuel/cooking arrangements . 452 Table 11.3 Prevalence of tuberculosis by state/union territory . 453 Table 11.4.1 Knowledge and attitudes toward tuberculosis: Women . 454 Table 11.4.2 Knowledge and attitudes toward tuberculosis: Men . 455 Table 11.5.1 Self-reported health problems: Women. 456 Table 11.5.2 Self-reported health problems: Men . 458 Table 11.6 Self-reported health problems by state/union territory . 460 Table 11.7 Tobacco use by women and men . 461 Table 11.8 Use of tobacco by background characteristics . 462 Table 11.9 Quitting tobacco use and advice by a health care provider . 464 Table 11.10 Quitting tobacco use and advice by a health care provider by state/union territory . 466 Table 11.11.1 Use of alcohol: Women . 468 Table 11.11.2 Use of alcohol: Men . 469 Table 11.12 Use of alcohol by state/union territory . 470 Table 11.13 Health scheme/health insurance coverage . 471 Table 11.14.1 Health scheme/health insurance coverage: Women . 472 Table 11.14.2 Health scheme/health insurance coverage: Men . 474 Table 11.15 Health scheme/health insurance coverage among women and men by state/union territory . 476 Table 11.16 Source of health care . 477 Table 11.17 Reasons for not using a government health facility by state/union territory . 478 Table 11.18 Recent contacts with health workers . 479 Table 11.19 Matters discussed during contacts with a health worker . 481 Table 11.20 Contacts with health workers and visit to a health facility or camp by state/union territory . 482 Table 11.21 Problems in accessing health care . 484 CHAPTER 12 OTHER ADULT HEALTH ISSUES . 487 Table 12.1 Coverage of testing for blood pressure and random blood glucose measurements . 493 Table 12.2 Self reports of blood pressure measurement and medication . 494 Table 12.3.1 Blood pressure levels and treatment status: Women . 495 Table 12.3.2 Blood pressure levels and treatment status: Men . 498 Table 12.4.1 Blood pressure levels and treatment status by state/union territory: Women . 501 Table 12.4.2 Blood pressure levels and treatment status by state/union territory: Men . 503 Table 12.5.1 Random blood glucose levels: Women . 505 Table 12.5.2 Random blood glucose levels: Men . 507 Table 12.6.1 Random blood glucose levels by state/union territory: Women . 509 Table 12.6.2 Random blood glucose levels by state/union territory: Men . 510 Table 12.7 Screening tests for cancer . 511 Table 12.8 Screening tests for cancer by state/union territory . 512 Table 12.9 Age-specific death rates and crude death rates . 513 Table 12.10 Crude death rates by state/union territory . 514 Table 12.11 Adult mortality . 515 Table 12.12 Adult mortality by state/union territory . 516 CHAPTER 13 HIV/AIDS-RELATED KNOWLEDGE, ATTITUDES, AND BEHAVIOUR . 517 Table 13.1 Knowledge of HIV or AIDS . 530 Table 13.2 Knowledge of HIV/AIDS prevention methods . 531 Table 13.3.1 Comprehensive knowledge about HIV/AIDS: Women . 533 Table 13.3.2 Comprehensive knowledge about HIV/AIDS: Men . 535 Table 13.4 Knowledge of prevention of HIV/AIDS transmission from a mother to her baby . 537 Table 13.5 HIV/AIDS awareness indicators by state/union territory . 540 Table 13.6 Accepting attitudes toward those living with HIV/AIDS . 541 Table 13.7.1 Accepting attitudes toward those living with HIV/AIDS by state/union territory: Women. 542 Table 13.7.2 Accepting attitudes toward those living with HIV/AIDS by state/union territory: Men . 543 Table 13.8 Attitudes toward negotiating sex with husband . 544 Table 13.9 Attitudes toward negotiating sex with husband by state/union territory . 546 Table 13.10.1 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Women . 547 Table 13.10.2 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months: Men . 549 Table 13.11 Multiple sexual partners and higher-risk sexual intercourse in the past 12 months by state/union territory . 551 Table 13.12 Payment for sexual intercourse and condom use at last paid sexual intercourse: Men. . 554 Table 13.13.1 Coverage of prior HIV testing: Women . 556 Table 13.13.2 Coverage of prior HIV testing: Men . 558 Table 13.14.1 Coverage of prior HIV testing by state/union territory: Women . 560 Table 13.14.2 Coverage of prior HIV testing by state/union territory: Men . 561 Table 13.15 Coverage of prior HIV testing during antenatal care (ANC) or labour . 562 Table 13.16 Coverage of prior HIV testing during antenatal care (ANC) or labour by state/union territory . 563 Table 13.17 Self-reported prevalence of sexually transmitted infection (STI) and/or STI symptoms . 565 Table 13.18 Self-reported prevalence of sexually transmitted infection (STI) and/or STI symptoms by state/union territory . 567 Table 13.19 Comprehensive knowledge about HIV/AIDS and knowledge of a source of condoms among youth . 568 Table 13.20 Comprehensive knowledge about HIV/AIDS and knowledge of a source of condoms among youth by state/union territory . 570 Table 13.21 Age at first sexual intercourse among youth . 571 Table 13.22 Sexual intercourse and condom use among never married youth . 573 Table 13.23 Higher-risk sexual intercourse among youth and condom use at last higher-risk intercourse . 575 Table 13.24 Recent HIV tests among youth . 577 CHAPTER 14 WOMEN’S EMPOWERMENT . 581 Table 14.1 Employment and cash earnings . 593 Table 14.2 Employment and cash earnings by state/union territory. 594 Table 14.3.1 Control over women's cash earnings and relative magnitude of women's cash earnings: Women's reports. 595 Table 14.3.2 Control over women's cash earnings and relative magnitude of women's cash earnings: Men's reports . 597 Table 14.4 Control over men's cash earnings . 599 Table 14.5 Control over women's and men's cash earnings and relative magnitude of women's cash earnings by state/union territory . 601 Table 14.6 Participation in decision making . 603 Table 14.7.1 Women's participation in decision making by background characteristics . 604 Table 14.7.2 Men's participation in decision making by background characteristics . 606 Table 14.8 Women's participation in decision making by state/union territory . 608 Table 14.9 Men's attitudes toward a wife's participation in decision making . 610 Table 14.10 Men's attitudes toward a wife's participation in decision making by background . 611 Table 14.11 Women's access to money and credit . 613 Table 14.12 Women's access to money and credit and freedom of movement by state/union territory . 615 Table 14.13 Women's freedom of movement by background characteristics . 617 Table 14.14.1 Attitudes toward wife beating: Women . 619 Table 14.14.2 Attitudes toward wife beating: Men . 621 Table 14.15 Attitudes toward wife beating by state/union territory . 624 Table 14.16.1 Attitudes toward refusing sexual intercourse with husband: Women . 626 Table 14.16.2 Attitudes toward refusing sexual intercourse with husband: Men . 628 Table 14.17 Attitudes toward refusing sexual intercourse with husband by state/union territory . 630 Table 14.18 Men's attitudes toward a husband's rights when his wife refuses to have sexual intercourse . 632 Table 14.19 Men's attitudes toward a husband's rights when his wife refuses to have sexual intercourse by state/union territory . 634 Table 14.20 Ability to negotiate sexual relations with husband . 635 Table 14.21 Ability to negotiate sexual relations with husband by state/union territory . 636 Table 14.22 Ownership of assets . 637 Table 14.23 Ownership of assets by state/union territory . 639 CHAPTER 15 DOMESTIC VIOLENCE . 641 Table 15.1 Experience of physical violence . 652 Table 15.2 Experience of violence during pregnancy . 654 Table 15.3 Persons committing physical violence . 655 Table 15.4 Experience of sexual violence . 656 Table 15.5 Age at first experience of sexual violence . 657 Table 15.6 Persons committing sexual violence . 658 Table 15.7 Experience of different types of violence . 659 Table 15.8 Degree of marital control exercised by husbands . 661 Table 15.9 Forms of spousal violence . 664 Table 15.10 Violence by any husband in the past 12 months . 665 Table 15.11 Spousal violence by background characteristics . 666 Table 15.12 Spousal violence by husband's characteristics and empowerment indicators . 668 Table 15.13 Spousal violence by state/union territory . 670 Table 15.14 Experience of spousal violence by duration of marriage. 671 Table 15.15 Injuries to women due to spousal violence. 672 Table 15.16 Violence by women against their husband . 673 Table 15.17 Help seeking . 675 Table 15.18 Sources from where help was sought . 677 MESSAGE FROM HON'BLE HEALTH MINISTER ACKNOWLEDGEMENTS The National Family Health Survey (NFHS-5) was successfully completed in 707 districts (as on March 2017) drawn from all the 29 States and 7 Union Territories. The national report of the National Family Health Survey (NFHS-5) has been completed with joint efforts and involvement of numerous organizations and individuals in two phases, including the phase of a difficult period of COVID-19 pandemics. With the completion of the national report of NFHS-5, the unit-level data will be available for the use of the researchers and policy planners. At the outset, we are grateful to the officials of the Ministry of Health and Family Welfare, Government of India, New Delhi, for their overall guidance and support. I express our sincere thanks to Shri. Rajesh Bhushan, Secretary of Health and Family Welfare, Shri Vikas Sheel, AS&MD, Ashish Srivastava AS&FA, Smt. Sandhya Krishnamurthy DG(Stats.), Shri P Manoj Kumar CD (Stats.), and Ms. Nidhi Satija JD (Stats.). The involvement of many former officials of the MoHFW helped significantly towards the completion of the survey on time. They include Preeti Sudan former Secretary, Ms. Vandana Gurnani, former AS&MD, Dr. D. S. Gangwar, former AS&FA, Smt Nivedita Gupta, former CD(Stats.), Shir D.K. Ojha, former DDG (Stats.) I express our sincere gratitude to all the Steering Committee, Administrative & Financial Management Committee, Project Management Committee, and the Technical Advisory Committee, especially the Chairperson, Dr. N.S. Sastry and Co-Chair, Dr. Arvind Pandey for their contribution and for providing valuable guidance at different stages of implementation. The members of these committees provided constant guidance in carrying out the task even during the pandemic. I deeply appreciate the efforts of all the Principal Investigators (Prof. S. K. Singh, Prof. Hemkothang Lhungdim, Prof. Chander Shekhar, Prof. Laxmi Kant Dwivedi, and Dr. Sarang Pedgaonkar) at IIPS for their dedication, enthusiasm and unstinting efforts in bringing out the national report on time. Prof Balram Paswan (Rtd) was actively involved in the project in the early stages. I appreciate and acknowledge the untiring efforts and initiative taken by Dr. Fred Arnold, Dr. Sunita Kishor, and other staff members/consultants of ICF at every stage of the project. We also acknowledge the contribution of NFHS-5 Senior Project Officers, Project Officers, and other staff members for their constant support. The administrative staff at IIPS provided support at all stages of the project. I sincerely thank the Heads and staff of Field Agencies (FAs) for successfully carrying out the task of data collection in their respective states. This acknowledgment cannot be completed without expressing our appreciation for the hard work put in by the field teams in data collection and maintaining the quality of data. (Prof. K S JAMES) ACKNOWLEDGEMENTS The National Family Health Survey (NFHS-5) was successfully completed in 707 districts (as on March 2017) drawn from all the 29 States and 7 Union Territories. The national report of the National Family Health Survey (NFHS-5) has been completed with joint efforts and involvement of numerous organizations and individuals in two phases, including the phase of a difficult period of COVID-19 pandemics. With the completion of the national report of NFHS-5, the unit-level data will be available for the use of the researchers and policy planners. At the outset, we are grateful to the officials of the Ministry of Health and Family Welfare, Government of India, New Delhi, for their overall guidance and support. I express our sincere thanks to Shri. Rajesh Bhushan, Secretary of Health and Family Welfare, Shri Vikas Sheel, AS&MD, Ashish Srivastava AS&FA, Smt. Sandhya Krishnamurthy DG(Stats.), Shri P Manoj Kumar CD (Stats.), and Ms. Nidhi Satija JD (Stats.). The involvement of many former officials of the MoHFW helped significantly towards the completion of the survey on time. They include Preeti Sudan former Secretary, Ms. Vandana Gurnani, former AS&MD, Dr. D. S. Gangwar, former AS&FA, Smt Nivedita Gupta, former CD(Stats.), Shir D.K. Ojha, former DDG (Stats.) I express our sincere gratitude to all the Steering Committee, Administrative & Financial Management Committee, Project Management Committee, and the Technical Advisory Committee, especially the Chairperson, Dr. N.S. Sastry and Co-Chair, Dr. Arvind Pandey for their contribution and for providing valuable guidance at different stages of implementation. The members of these committees provided constant guidance in carrying out the task even during the pandemic. I deeply appreciate the efforts of all the Principal Investigators (Prof. S. K. Singh, Prof. Hemkothang Lhungdim, Prof. Chander Shekhar, Prof. Laxmi Kant Dwivedi, and Dr. Sarang Pedgaonkar) at IIPS for their dedication, enthusiasm and unstinting efforts in bringing out the national report on time. Prof Balram Paswan (Rtd) was actively involved in the project in the early stages. I appreciate and acknowledge the untiring efforts and initiative taken by Dr. Fred Arnold, Dr. Sunita Kishor, and other staff members/consultants of ICF at every stage of the project. We also acknowledge the contribution of NFHS-5 Senior Project Officers, Project Officers, and other staff members for their constant support. The administrative staff at IIPS provided support at all stages of the project. I sincerely thank the Heads and staff of Field Agencies (FAs) for successfully carrying out the task of data collection in their respective states. This acknowledgment cannot be completed without expressing our appreciation for the hard work put in by the field teams in data collection and maintaining the quality of data. (Prof. K S JAMES) 1 INTRODUCTION 1 he National Family Health Survey 2019-21 (NFHS-5), the fifth in the NFHS series, provides information on population, health, and nutrition for India, each state/union territory (UT), and for 707 districts as on March 31st 2017. All five NFHS surveys have been conducted under the stewardship of the Ministry of Health and Family Welfare (MoHFW), Government of India. MoHFW designated the International Institute for Population Sciences (IIPS), Mumbai, as the nodal agency for all the rounds of NFHS. Funding for NFHS-5 was provided by the MoHFW, Government of India. ICF, USA provided technical assistance through the Demographic and Health Surveys (DHS) Program, which is funded by USAID. Assistance for the Dried Blood Sample (DBS) component of the survey was provided by the Indian Council of Medical Research (ICMR) and the National AIDS Research Institute (NARI), Pune. NFHS-5 fieldwork for India was conducted in two phases— Phase-I from 17 June 2019 to 30 January 2020 covering 17 states and 5 UTs and Phase-II from 2 January 2020 to 30 April 2021 covering 11 states and 3 UTs — by 17 Field Agencies and gathered information from 636,699 households, 724,115 women, and 101,839 men. The first NFHS was conducted in 1992-93 and covered all states except Sikkim. NFHS-2 was conducted in 1998- 99 in all states with similar content and methods to those in NFHS-1. In addition, NFHS-2 provided information on reproductive health, women’s autonomy, and domestic violence, women’s and children’s nutrition, anaemia, and salt iodization. NFHS-3 built on the strengths and successes of NFHS-1 and NFHS-2 by maintaining continuity in content and methods with an additional component of community-based HIV testing in the country. It also included a men’s interview for the first time. With additional components of CAB (clinical, anthropometric, and biochemical testing), NFHS-4 has contents similar to NFHS-3, maintaining the continuity and comparability in information. However, NFHS-4 provided information at the district level through increasing the sample size by nearly fivefold as compared with NFHS 3. NFHS-4 used a modular approach, where the last four sections of woman’s questionnaire, interviews with men, and HIV testing were done only for the households included in the state module, and the information is provided only at the state level for those indicators. Like NFHS-4, NFHS-5 also provides district-level estimates for many important indicators. The contents of NFHS-5 are similar to NFHS-4 to allow comparisons over time. However, NFHS-5 includes some new topics, such as preschool education, disability, access to a toilet facility, death registration, bathing practices during menstruation, and methods and reasons for abortion. The scope of clinical, anthropometric, and biochemical testing (CAB) has also been expanded to include measurement of waist and hip circumferences, and the age range for the measurement of blood pressure and blood glucose has been expanded. However, HIV testing was not included in NFHS-5. The NFHS-5 sample was designed to provide national, state/union territory (UT), and district level estimates of various indicators covered in the survey. However, estimates of indicators of sexual behaviour; husband’s background and woman’s work; HIV/AIDS knowledge, attitudes, and behaviour; and domestic violence are available only at the state/union territory (UT) and national level. As in the earlier rounds, the MoHFW, Government of India, designated the International Institute for Population Sciences, Mumbai, as the nodal agency to conduct NFHS-5. The main objective of each successive round of the NFHS has been to provide high-quality data on health and family welfare and emerging issues in this area. NFHS- 5 data will be useful in setting benchmarks and examining the progress the health sector has made over time. Besides providing evidence for the effectiveness of ongoing programmes, the data from NFHS-5 help in identifying the need for new programmes with an area specific focus and identifying groups that are most in need of essential services. 1.1 SURVEY OBJECTIVES The primary objective of the 2019-21 round of National Family Health Surveys is to provide essential data on health and family welfare, as well as data on emerging issues in these areas, such as levels of fertility, infant and child mortality, maternal and child health, and other health and family welfare indicators by background T 2 characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, non- communicable diseases, and the use of emergency contraception. The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas. The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements. 1.2 SAMPLE DESIGN Decisions about the overall sample size required for NFHS-5 were guided by several considerations, paramount among which was the need to produce indicators at the district and/or state/union territory (UT) levels. Thus, NFHS-5 provides information for 707 districts, 28 states, and 8 union territories. A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs. NFHS-5 was designed to provide information on sexual behaviour; husband’s background and women’s work; HIV/AIDS knowledge, attitudes, and behaviour; and domestic violence only at the state level (in the state module), while indicators in the district module are reported at the district level. A subsample of 15 percent of households was selected for the implementation of the state module drawn from the district sample. In 15 percent of households randomly selected for the state module, a long questionnaire was administered that included all the questions needed for district-level estimates plus additional questions for the topics listed above. To achieve a representative sample of 15 percent of households, NFHS-5 conducted interviews in every alternate selected household in 30 percent of the randomly selected clusters. The NFHS-5 sample is a stratified two-stage sample. The 2011 census served as the sampling frame for the selection of PSUs. PSUs were villages in rural areas and Census Enumeration Blocks (CEBs) in urban areas. PSUs with fewer than 40 households were linked to the nearest PSU. Within each rural stratum, villages were selected from the sampling frame with probability proportional to size (PPS). In each stratum, six approximately equal substrata were created by crossing three substrata, each created based on the estimated number of households in each village, with two substrata, each created based on the percentage of the population belonging to scheduled castes and scheduled tribes (SCs/STs). Within each explicit sampling stratum, PSUs were sorted according to the prevalence of literacy of women age 6+ years. The final sample PSUs were selected with PPS systematic sampling. In urban areas, CEB information was obtained from the Office of the Registrar General and Census Commissioner, New Delhi. CEBs were sorted according to the percentage of the SC/ST population in each CEB, and sample CEBs were selected with PPS systematic sampling. In every selected rural and urban PSU, a complete household mapping and listing operation was conducted prior to the main survey. Selected PSUs with an estimated number of at least 300 households were segmented into segments of approximately 100-150 households. Two of the segments were randomly selected for the survey using systematic sampling with probability proportional to segment size. Therefore, an NFHS-5 cluster is either a PSU or a segment of a PSU. In the second stage, in every selected rural and urban cluster, 22 households were randomly selected with systematic sampling. A detailed description of sampling design, weight computation, estimation of standard errors, and strategies to enhance data quality measures is presented in Volume II of the national report. 1.3 QUESTIONNAIRES Four survey schedules/questionnaires—Household, Woman, Man, and Biomarker—were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI). In the Household Questionnaire, information was collected on all usual members of the household and visitors who stayed in the household the night before the interview. Basic demographic information was collected on the characteristics of each person listed, such as age, sex, marital status, schooling, ownership of an Aadhaar card, tobacco use, alcohol consumption, disabilities, and relationship to the head of the household. At the household level, information was collected on socio- economic characteristics; water, sanitation, and hygiene; water treatment; type of toilet facilities; type of cooking fuel; materials used for the floor, roof, and walls of the dwelling unit; ownership of various durable goods; health insurance coverage; land ownership; number of deaths in the household in the two years preceding the survey; and the ownership and use of mosquito nets. The parents’ survival status was determined for children under age 18. For children under age five, information was collected on whether each child has a birth certificate or whether the birth was registered with the civil authority. The information on age and sex of household members obtained in the Household Questionnaire was used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on the ownership and use of mosquito nets, exposure to second-hand smoke, and the reported prevalence of tuberculosis. A sample of cooking salt used in the household was tested for iodine content. The protocol for the NFHS-5 survey, including the content of all the survey questionnaires, was approved by the IIPS Institutional Review Board and the ICF Institutional Review Board. The protocol was also reviewed by the U.S. Centers for Disease Control and Prevention (CDC). The Woman’s Questionnaire collected information from all eligible women age 15-49, who were asked questions on a large variety of topics, including the following:  Background characteristics: age, literacy, schooling, religion, caste/tribe, media exposure  Reproduction: children ever born, birth history, current pregnancy, pregnancy terminations  Prevalence of hysterectomy  Menstrual hygiene (for women age 15-24 years)  Family planning: knowledge and use of contraception, sources of contraceptive methods, information on family planning  Contacts with community health workers  Maternal and child health, breastfeeding, and nutrition: antenatal care; delivery care; postnatal care; postpartum amenorrhoea; breastfeeding and child feeding practices; vaccination coverage; prevalence and treatment of diarrhoea: symptoms of acute respiratory infection (ARI), and fever; use of oral rehydration therapy (ORT); utilization of ICDS services  Marriage and sexual activity: marital status, age at first marriage, lifetime number of unions, polygyny, consanguinity, age at first sexual intercourse, recent sexual activity, number and type of sexual partners, use of condoms  Fertility preferences: desire for more children, ideal number of children, gender preferences for children, intention to use family planning  Husband’s background and woman’s work: husband’s age, schooling, and occupation, and the woman’s employment and type of earnings (state module subsample only)  Women’s empowerment: household decision making, mobility, use of a bank account and a mobile phone, ownership of a house or land, barriers to medical treatment (state module subsample only) 3 characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, non- communicable diseases, and the use of emergency contraception. The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas. The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements. 1.2 SAMPLE DESIGN Decisions about the overall sample size required for NFHS-5 were guided by several considerations, paramount among which was the need to produce indicators at the district and/or state/union territory (UT) levels. Thus, NFHS-5 provides information for 707 districts, 28 states, and 8 union territories. A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs. NFHS-5 was designed to provide information on sexual behaviour; husband’s background and women’s work; HIV/AIDS knowledge, attitudes, and behaviour; and domestic violence only at the state level (in the state module), while indicators in the district module are reported at the district level. A subsample of 15 percent of households was selected for the implementation of the state module drawn from the district sample. In 15 percent of households randomly selected for the state module, a long questionnaire was administered that included all the questions needed for district-level estimates plus additional questions for the topics listed above. To achieve a representative sample of 15 percent of households, NFHS-5 conducted interviews in every alternate selected household in 30 percent of the randomly selected clusters. The NFHS-5 sample is a stratified two-stage sample. The 2011 census served as the sampling frame for the selection of PSUs. PSUs were villages in rural areas and Census Enumeration Blocks (CEBs) in urban areas. PSUs with fewer than 40 households were linked to the nearest PSU. Within each rural stratum, villages were selected from the sampling frame with probability proportional to size (PPS). In each stratum, six approximately equal substrata were created by crossing three substrata, each created based on the estimated number of households in each village, with two substrata, each created based on the percentage of the population belonging to scheduled castes and scheduled tribes (SCs/STs). Within each explicit sampling stratum, PSUs were sorted according to the prevalence of literacy of women age 6+ years. The final sample PSUs were selected with PPS systematic sampling. In urban areas, CEB information was obtained from the Office of the Registrar General and Census Commissioner, New Delhi. CEBs were sorted according to the percentage of the SC/ST population in each CEB, and sample CEBs were selected with PPS systematic sampling. In every selected rural and urban PSU, a complete household mapping and listing operation was conducted prior to the main survey. Selected PSUs with an estimated number of at least 300 households were segmented into segments of approximately 100-150 households. Two of the segments were randomly selected for the survey using systematic sampling with probability proportional to segment size. Therefore, an NFHS-5 cluster is either a PSU or a segment of a PSU. In the second stage, in every selected rural and urban cluster, 22 households were randomly selected with systematic sampling. A detailed description of sampling design, weight computation, estimation of standard errors, and strategies to enhance data quality measures is presented in Volume II of the national report. 1.3 QUESTIONNAIRES Four survey schedules/questionnaires—Household, Woman, Man, and Biomarker—were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI). In the Household Questionnaire, information was collected on all usual members of the household and visitors who stayed in the household the night before the interview. Basic demographic information was collected on the characteristics of each person listed, such as age, sex, marital status, schooling, ownership of an Aadhaar card, tobacco use, alcohol consumption, disabilities, and relationship to the head of the household. At the household level, information was collected on socio- economic characteristics; water, sanitation, and hygiene; water treatment; type of toilet facilities; type of cooking fuel; materials used for the floor, roof, and walls of the dwelling unit; ownership of various durable goods; health insurance coverage; land ownership; number of deaths in the household in the two years preceding the survey; and the ownership and use of mosquito nets. The parents’ survival status was determined for children under age 18. For children under age five, information was collected on whether each child has a birth certificate or whether the birth was registered with the civil authority. The information on age and sex of household members obtained in the Household Questionnaire was used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on the ownership and use of mosquito nets, exposure to second-hand smoke, and the reported prevalence of tuberculosis. A sample of cooking salt used in the household was tested for iodine content. The protocol for the NFHS-5 survey, including the content of all the survey questionnaires, was approved by the IIPS Institutional Review Board and the ICF Institutional Review Board. The protocol was also reviewed by the U.S. Centers for Disease Control and Prevention (CDC). The Woman’s Questionnaire collected information from all eligible women age 15-49, who were asked questions on a large variety of topics, including the following:  Background characteristics: age, literacy, schooling, religion, caste/tribe, media exposure  Reproduction: children ever born, birth history, current pregnancy, pregnancy terminations  Prevalence of hysterectomy  Menstrual hygiene (for women age 15-24 years)  Family planning: knowledge and use of contraception, sources of contraceptive methods, information on family planning  Contacts with community health workers  Maternal and child health, breastfeeding, and nutrition: antenatal care; delivery care; postnatal care; postpartum amenorrhoea; breastfeeding and child feeding practices; vaccination coverage; prevalence and treatment of diarrhoea: symptoms of acute respiratory infection (ARI), and fever; use of oral rehydration therapy (ORT); utilization of ICDS services  Marriage and sexual activity: marital status, age at first marriage, lifetime number of unions, polygyny, consanguinity, age at first sexual intercourse, recent sexual activity, number and type of sexual partners, use of condoms  Fertility preferences: desire for more children, ideal number of children, gender preferences for children, intention to use family planning  Husband’s background and woman’s work: husband’s age, schooling, and occupation, and the woman’s employment and type of earnings (state module subsample only)  Women’s empowerment: household decision making, mobility, use of a bank account and a mobile phone, ownership of a house or land, barriers to medical treatment (state module subsample only) 4  HIV/AIDS: knowledge of HIV and AIDS, knowledge of methods of HIV transmission, sources of HIV information, ways to avoid HIV, previous HIV testing, HIV stigma, other sexually-transmitted infections (state module subsample only)  Other health issues: tobacco and alcohol use, knowledge of tuberculosis, current morbidity (diabetes, hypertension, asthma, goitre and other thyroid diseases, heart disease, cancer), and household decision making (state module subsample only)  Domestic violence: only one eligible woman per household was randomly selected to answer the questions in the domestic violence section to comply with ethical requirements. Women who were victims of domestic violence were provided with a list of appropriate local organizations that they could contact if they wanted help (women age 18-49 in the state module subsample only) The Man’s Questionnaire was administered only in the subsample of households selected for the state module. The Man’s Schedule covered the man’s characteristics, media exposure, marriage, employment, presence at antenatal care visits, number of children, contraceptive knowledge and use, fertility preferences, nutrition, sexual behaviour, attitudes toward gender roles, HIV/AIDS, health issues, attitudes towards gender roles, tobacco and alcohol use, knowledge of tuberculosis, current morbidity (diabetes, asthma, goitre and other thyroid diseases, heart disease, cancer), and household decision making. The Biomarker Schedule covered measurements of height, weight, and haemoglobin levels for children; measurements of height, weight, waist and hip circumference, and haemoglobin levels for women age 15-49 years and men age 15-54 years; and blood pressure and random blood glucose levels for women and men age 15 years and over. In addition, women and men were requested to provide a few additional drops of blood from a finger prick for laboratory testing for HbA1c, malaria parasites, and Vitamin D3. In contrast to the data collection procedure for the household and individual interviews, data related to the biomarkers were initially recorded on the Biomarker Questionnaire and subsequently entered into the interviewers’ mini-computers. Sample copies of all four questionnaires are presented in Volume – II of the national report. 1.4 BIOMARKER MEASUREMENTS AND TESTS NFHS-5 carried out several biomarker measurements and tests with the help of trained health investigators in each team. The list of biomarkers and tests administered for NFHS-5 along with the type of instrument used are presented in the box below. Except for HbA1c, malaria parasites, and Vitamin D3 testing, the results of all measurements and tests were immediately given to the respondents (or a parent or other adult responsible for children) in the field, along with information brochures. The results were explained to respondents by the specially trained health investigators who conducted the tests. All women and men who were eligible for HbA1c, malaria parasites, and Vitamin D3 testing were given a referral card. Details of Biomarker Measurements and Tests Eligible age group Type of Investigation Instrument Used Children 0-59 months Weight Length/Height Seca 874 Digital Scale (Weight) Seca 213 Stadiometer (Height) Seca 417 Infantometer (Length) (for children less than 2 years old or less than 85 cm) Children 6-59 months Haemoglobin HemoCue Hb 201+ Analyser (Haemoglobin) Women age 15-49 and Men age 15-54 Height Weight Waist and Hip Circumference Haemoglobin Seca 874 Digital Scale (Weight) Seca 213 Stadiometer (Height) Gulick tape (Waist and Hip Circumference) HemoCue Hb 201+ Analyser (Haemoglobin) Women and Men age 15 and over Blood Glucose Blood Pressure Accu-Chek Performa Glucometer (Blood Glucose) Omron Blood Pressure Monitor (Blood Pressure) Women and Men age 15 and over (subsample) HbA1c Vitamin D3 Malaria parasites Dried Blood Spot (DBS) on Filter Paper Card Anthropometry: Height and weight were measured for children age 0-59 months, women age 15-49, and (in the state module subsample of households only) men age 15-54. The Seca 874 digital scale was used to measure the weight of children and adults. The height of adults and children age 24-59 months was measured with the Seca 213 stadiometer. The Seca 417 infantometer was used to measure the recumbent length of children under two years or less than 85 cm. As per World Health Organization (WHO) guidelines, waist circumference (WC), waist- to-hip ratio (WHR) and waist-to-height ratio (WHtR) have been found to be appropriate measurements of abdominal obesity. For the first time, NFHS-5 included waist and hip circumference measurements provided by using Gulick tapes for both eligible women and men for measurements of abdominal obesity. Anaemia testing: Blood specimens for anaemia testing were collected by health investigators from eligible women age 15-49, men age 15-54 (in the state module subsample of households), and children age 6-59 months. Consent for the test was taken from eligible women and men. For children age 6-59 months, consent was obtained from a parent or an adult responsible for the child. Blood samples were drawn from a drop of blood taken from a finger prick (or a heel prick for children age 6-11 months) and collected in a microcuvette. Haemoglobin analysis was conducted on-site with a battery-operated portable HemoCue Hb 201+ analyser. Respondents found to have severe anaemia if the haemoglobin level is below 7 grams/decilitre (g/dl) for women, men, and children and if the haemoglobin level is below 9 g/dl for pregnant women were referred to a health facility for further evaluation and treatment. Blood glucose testing: Random blood glucose was measured using a finger-stick blood specimen for all women and men age 15 and above using the Accu-Chek Performa glucometer with glucose test strips for blood glucose testing. A referral form to a health facility for additional medical evaluation was provided for any respondent with a random blood glucose level ≥200 mg/dl. The results of blood glucose display on an LCD digital screen within five second and were given to respondents on a health card immediately after the test was completed. The health investigator described to the respondent the meaning of the results and advised the respondent if a referral to a medical centre is necessary. Blood pressure measurement: Blood pressure was measured for all women and men age 15 and above using an Omron Blood Pressure Monitor to determine the prevalence of hypertension. Blood pressure measurements for each respondent were taken three times with an interval of five minutes between readings. Respondents whose average systolic blood pressure (SBP) was >130 mm Hg and/or whose average diastolic blood pressure (DBP) was >85 mm Hg were considered to have elevated blood pressure readings and they were encouraged to see a doctor for a full evaluation. Dried Blood Spot (DBS) collection for HbA1c, malaria parasites and drug resistance, and Vitamin D3: DBS were collected from a subsample of households on specially designed filter paper cards from eligible respondents for various biomarkers. The various DBS based tests considered under NFHS-5 include: 5  HIV/AIDS: knowledge of HIV and AIDS, knowledge of methods of HIV transmission, sources of HIV information, ways to avoid HIV, previous HIV testing, HIV stigma, other sexually-transmitted infections (state module subsample only)  Other health issues: tobacco and alcohol use, knowledge of tuberculosis, current morbidity (diabetes, hypertension, asthma, goitre and other thyroid diseases, heart disease, cancer), and household decision making (state module subsample only)  Domestic violence: only one eligible woman per household was randomly selected to answer the questions in the domestic violence section to comply with ethical requirements. Women who were victims of domestic violence were provided with a list of appropriate local organizations that they could contact if they wanted help (women age 18-49 in the state module subsample only) The Man’s Questionnaire was administered only in the subsample of households selected for the state module. The Man’s Schedule covered the man’s characteristics, media exposure, marriage, employment, presence at antenatal care visits, number of children, contraceptive knowledge and use, fertility preferences, nutrition, sexual behaviour, attitudes toward gender roles, HIV/AIDS, health issues, attitudes towards gender roles, tobacco and alcohol use, knowledge of tuberculosis, current morbidity (diabetes, asthma, goitre and other thyroid diseases, heart disease, cancer), and household decision making. The Biomarker Schedule covered measurements of height, weight, and haemoglobin levels for children; measurements of height, weight, waist and hip circumference, and haemoglobin levels for women age 15-49 years and men age 15-54 years; and blood pressure and random blood glucose levels for women and men age 15 years and over. In addition, women and men were requested to provide a few additional drops of blood from a finger prick for laboratory testing for HbA1c, malaria parasites, and Vitamin D3. In contrast to the data collection procedure for the household and individual interviews, data related to the biomarkers were initially recorded on the Biomarker Questionnaire and subsequently entered into the interviewers’ mini-computers. Sample copies of all four questionnaires are presented in Volume – II of the national report. 1.4 BIOMARKER MEASUREMENTS AND TESTS NFHS-5 carried out several biomarker measurements and tests with the help of trained health investigators in each team. The list of biomarkers and tests administered for NFHS-5 along with the type of instrument used are presented in the box below. Except for HbA1c, malaria parasites, and Vitamin D3 testing, the results of all measurements and tests were immediately given to the respondents (or a parent or other adult responsible for children) in the field, along with information brochures. The results were explained to respondents by the specially trained health investigators who conducted the tests. All women and men who were eligible for HbA1c, malaria parasites, and Vitamin D3 testing were given a referral card. Details of Biomarker Measurements and Tests Eligible age group Type of Investigation Instrument Used Children 0-59 months Weight Length/Height Seca 874 Digital Scale (Weight) Seca 213 Stadiometer (Height) Seca 417 Infantometer (Length) (for children less than 2 years old or less than 85 cm) Children 6-59 months Haemoglobin HemoCue Hb 201+ Analyser (Haemoglobin) Women age 15-49 and Men age 15-54 Height Weight Waist and Hip Circumference Haemoglobin Seca 874 Digital Scale (Weight) Seca 213 Stadiometer (Height) Gulick tape (Waist and Hip Circumference) HemoCue Hb 201+ Analyser (Haemoglobin) Women and Men age 15 and over Blood Glucose Blood Pressure Accu-Chek Performa Glucometer (Blood Glucose) Omron Blood Pressure Monitor (Blood Pressure) Women and Men age 15 and over (subsample) HbA1c Vitamin D3 Malaria parasites Dried Blood Spot (DBS) on Filter Paper Card Anthropometry: Height and weight were measured for children age 0-59 months, women age 15-49, and (in the state module subsample of households only) men age 15-54. The Seca 874 digital scale was used to measure the weight of children and adults. The height of adults and children age 24-59 months was measured with the Seca 213 stadiometer. The Seca 417 infantometer was used to measure the recumbent length of children under two years or less than 85 cm. As per World Health Organization (WHO) guidelines, waist circumference (WC), waist- to-hip ratio (WHR) and waist-to-height ratio (WHtR) have been found to be appropriate measurements of abdominal obesity. For the first time, NFHS-5 included waist and hip circumference measurements provided by using Gulick tapes for both eligible women and men for measurements of abdominal obesity. Anaemia testing: Blood specimens for anaemia testing were collected by health investigators from eligible women age 15-49, men age 15-54 (in the state module subsample of households), and children age 6-59 months. Consent for the test was taken from eligible women and men. For children age 6-59 months, consent was obtained from a parent or an adult responsible for the child. Blood samples were drawn from a drop of blood taken from a finger prick (or a heel prick for children age 6-11 months) and collected in a microcuvette. Haemoglobin analysis was conducted on-site with a battery-operated portable HemoCue Hb 201+ analyser. Respondents found to have severe anaemia if the haemoglobin level is below 7 grams/decilitre (g/dl) for women, men, and children and if the haemoglobin level is below 9 g/dl for pregnant women were referred to a health facility for further evaluation and treatment. Blood glucose testing: Random blood glucose was measured using a finger-stick blood specimen for all women and men age 15 and above using the Accu-Chek Performa glucometer with glucose test strips for blood glucose testing. A referral form to a health facility for additional medical evaluation was provided for any respondent with a random blood glucose level ≥200 mg/dl. The results of blood glucose display on an LCD digital screen within five second and were given to respondents on a health card immediately after the test was completed. The health investigator described to the respondent the meaning of the results and advised the respondent if a referral to a medical centre is necessary. Blood pressure measurement: Blood pressure was measured for all women and men age 15 and above using an Omron Blood Pressure Monitor to determine the prevalence of hypertension. Blood pressure measurements for each respondent were taken three times with an interval of five minutes between readings. Respondents whose average systolic blood pressure (SBP) was >130 mm Hg and/or whose average diastolic blood pressure (DBP) was >85 mm Hg were considered to have elevated blood pressure readings and they were encouraged to see a doctor for a full evaluation. Dried Blood Spot (DBS) collection for HbA1c, malaria parasites and drug resistance, and Vitamin D3: DBS were collected from a subsample of households on specially designed filter paper cards from eligible respondents for various biomarkers. The various DBS based tests considered under NFHS-5 include: 6 Malaria parasites and drug resistance: Diagnosis of symptomatic and asymptomatic malaria (Plasmodium species like P. falciparum, P. vivax, P. malariae, P. ovale, and P. knowlesi) is important. Also, there is a need to detect markers of antimalarial drug resistance—specific molecular markers in the plasmodium DNA and hrp2 deletions in the malaria parasites (if present). Most malaria is being reported from states in the eastern, central and north-eastern parts of the country, such as Odisha, Chhattisgarh, Jharkhand, Madhya Pradesh, Tripura, and Meghalaya. To test for malaria, dried blood spots (DBS) were collected. In a random subsample of households, health investigators collected finger-prick blood specimens from eligible women age 15-49 and men age 15-54 who consented to laboratory malaria testing. HbA1c Testing: Glycosylated haemoglobin is a parameter to provide information on the status of diabetes control at the population level among diabetes patients. The testing results also provide useful information on diabetes management strategies and guide policymakers in programme planning. In a random subsample of households, health investigators collected finger-prick blood specimens on a filter paper card from eligible women age 15-49 and men age 15-54 who consented to laboratory HbA1c testing. Vitamin D3: The reported prevalence of Vitamin D3 deficiency is about 50-70% in India. Osteopenia and osteoporosis are common among India adults. Patients with chronic kidney diseases (CKD) may also present with bone disorders before or after developing kidney diseases. They may have osteoporosis and Vitamin D deficiency. Hence, determination of Vitamin D3 levels is of major importance. To test for vitamin D3 deficiency, DBS were collected. In a random subsample of households, health investigators collected finger-prick blood specimens on a filter paper card from eligible women age 15-49 and men age 15-54 who consented to laboratory Vitamin D3 testing. The results of these tests will be published in a separate report. 1.5 PRETEST The pretest was conducted during November-December 2017, and training of investigators for the pretest was held at the International Institute for Population Sciences (IIPS), Mumbai. The pretest fieldwork was conducted in five enumeration areas (4 rural, 1 urban) in and around Thane Taluka that had not been selected for the main survey. The pretest was conducted in Hindi speaking areas of Thane district followed by a debriefing session for the field teams. In all, 38 interviewers and 11 health investigators participated in the training. The pretest field practice covered 95 household interviews, 107 woman’s interviews, and 59 man’s interviews. Biomarkers measurements and testing were conducted on 50 children and 126 adults. 1.6 TRAINING OF FIELD STAFF Training was conducted in a tiered fashion. For each of the two fieldwork phases, a Training of Trainers (ToT) course was conducted by IIPS, Mumbai, and ICF. The ToT for the 19 states and union territories (UTs) included in the first phase was conducted in Goa from 22 April to 12 May, 2019. The ToT for the remaining 17 states and UTs was conducted from October 5-24, 2019 in Chandigarh. The trainees in both ToT workshops included project coordinators, health coordinators, statisticians/demographers, and information technology coordinators from the Field Agencies, and Project Officers/Senior Project Officers from IIPS. The coordinators from Field Agencies were responsible for training fieldworkers at the state/UT level. 1.7 FIELDWORK NFHS-5 fieldwork for India was conducted in two phases (phase one from 17 June 2019 to 30 January 2020 and phase two from 2 January 2020 to 30 April 2021) by 17 Field Agencies. NFHS-5 gathered information from 636,699 households, 724,115 women, and 101,839 men. Data collection was conducted by using 1,061 field teams. Each team consisted of one field supervisor, three female interviewers, one male interviewer, two health investigators, and a driver. The number of interviewing teams in each state varied according to the sample size. In each state, interviewers were hired by the selected Field Agencies, taking into consideration their educational background, experience, and other relevant qualifications. Female and male interviewers were assigned to interview respondents of the same sex. The assignment of Primary Sampling Units (PSUs) to the teams and various logistical decisions were made by the survey coordinators from each Field Agency. Each interviewer was required to make a minimum of three callbacks if no suitable informant was available for the household interview or if an eligible woman or man in the household was not present at the time of the interviewer’s visit. The field supervisor was responsible for the overall management of the field teams. In addition, the field supervisor conducted spot-checks to verify the accuracy of key information, particularly with respect to the eligibility of respondents. IIPS also appointed one or more project officers or senior project officers in each state for monitoring and supervision throughout the training and fieldwork period to ensure that correct survey procedures were followed and that data quality was maintained. Project directors and other senior staff from the Field Agencies, the Principal Investigators from IIPS, officials from MoHFW, and technical consultants from The DHS Program at ICF also visited the field sites to monitor data collection operations. 1.8 STRATEGY TO ENSURE DATA QUALITY Due to the size and complexity of the NFHS-5 survey, considerable thought went into devising strategies to minimize the non-sampling errors and ensure data quality. Some of the procedures adopted are summarized below.  NFHS-5 was conducted in two phases to make the administration of the training and fieldwork more manageable.  In the states included in each phase, fieldwork was conducted in a group of five adjacent districts at a time to facilitate close monitoring and supervision of the training of field staff and the implementation of the fieldwork.  To maintain uniform procedures across the states, several comprehensive manuals were prepared, including a Supervisor’s Manual, an Interviewer’s Manual, a Health Investigator’s Manual, a Household Mapping and Listing Manual, Data Processing Guidelines, and Training Guidelines.  There were multiple levels of monitoring and supervision of the fieldwork, including monitoring by district coordinators from the Field Agencies; monitoring by senior staff from the state offices of the Field Agencies; positioning two IIPS project officers with each Field Agency for the entire duration of the survey, in addition to monitoring and supervision by senior project officers, project coordinators, IIPS faculty coordinators, staff and consultants from ICF, and representatives from the development partners and the Ministry of Health and Family Welfare, Government of India. Immediate corrective measures were taken in case there were any deviations from the survey protocols.  The field supervisor on each interviewing team was required to observe interviews in a subsample of households and to conduct back-checks with respondents as a further check on the quality of the fieldwork.  Use of computer assisted personal interviewing (CAPI) and the transfer of field data to IIPS on a daily basis were instrumental in remotely monitoring progress of the field teams. Use of CAPI also enabled IIPS and ICF to run extensive data quality checks on the data from the field and to provide real-time feedback to Field Agencies and teams to help improve data quality. A standard set of 44 field-check tables (FCTs) were produced frequently throughout the fieldwork, covering such topics as response rates, age heaping and age displacement, completeness of reporting, sex ratios for children, patterns of height/length and weight measurements, and the contraceptive prevalence rate. (Please refer to the data collection flow chart below). 7 Malaria parasites and drug resistance: Diagnosis of symptomatic and asymptomatic malaria (Plasmodium species like P. falciparum, P. vivax, P. malariae, P. ovale, and P. knowlesi) is important. Also, there is a need to detect markers of antimalarial drug resistance—specific molecular markers in the plasmodium DNA and hrp2 deletions in the malaria parasites (if present). Most malaria is being reported from states in the eastern, central and north-eastern parts of the country, such as Odisha, Chhattisgarh, Jharkhand, Madhya Pradesh, Tripura, and Meghalaya. To test for malaria, dried blood spots (DBS) were collected. In a random subsample of households, health investigators collected finger-prick blood specimens from eligible women age 15-49 and men age 15-54 who consented to laboratory malaria testing. HbA1c Testing: Glycosylated haemoglobin is a parameter to provide information on the status of diabetes control at the population level among diabetes patients. The testing results also provide useful information on diabetes management strategies and guide policymakers in programme planning. In a random subsample of households, health investigators collected finger-prick blood specimens on a filter paper card from eligible women age 15-49 and men age 15-54 who consented to laboratory HbA1c testing. Vitamin D3: The reported prevalence of Vitamin D3 deficiency is about 50-70% in India. Osteopenia and osteoporosis are common among India adults. Patients with chronic kidney diseases (CKD) may also present with bone disorders before or after developing kidney diseases. They may have osteoporosis and Vitamin D deficiency. Hence, determination of Vitamin D3 levels is of major importance. To test for vitamin D3 deficiency, DBS were collected. In a random subsample of households, health investigators collected finger-prick blood specimens on a filter paper card from eligible women age 15-49 and men age 15-54 who consented to laboratory Vitamin D3 testing. The results of these tests will be published in a separate report. 1.5 PRETEST The pretest was conducted during November-December 2017, and training of investigators for the pretest was held at the International Institute for Population Sciences (IIPS), Mumbai. The pretest fieldwork was conducted in five enumeration areas (4 rural, 1 urban) in and around Thane Taluka that had not been selected for the main survey. The pretest was conducted in Hindi speaking areas of Thane district followed by a debriefing session for the field teams. In all, 38 interviewers and 11 health investigators participated in the training. The pretest field practice covered 95 household interviews, 107 woman’s interviews, and 59 man’s interviews. Biomarkers measurements and testing were conducted on 50 children and 126 adults. 1.6 TRAINING OF FIELD STAFF Training was conducted in a tiered fashion. For each of the two fieldwork phases, a Training of Trainers (ToT) course was conducted by IIPS, Mumbai, and ICF. The ToT for the 19 states and union territories (UTs) included in the first phase was conducted in Goa from 22 April to 12 May, 2019. The ToT for the remaining 17 states and UTs was conducted from October 5-24, 2019 in Chandigarh. The trainees in both ToT workshops included project coordinators, health coordinators, statisticians/demographers, and information technology coordinators from the Field Agencies, and Project Officers/Senior Project Officers from IIPS. The coordinators from Field Agencies were responsible for training fieldworkers at the state/UT level. 1.7 FIELDWORK NFHS-5 fieldwork for India was conducted in two phases (phase one from 17 June 2019 to 30 January 2020 and phase two from 2 January 2020 to 30 April 2021) by 17 Field Agencies. NFHS-5 gathered information from 636,699 households, 724,115 women, and 101,839 men. Data collection was conducted by using 1,061 field teams. Each team consisted of one field supervisor, three female interviewers, one male interviewer, two health investigators, and a driver. The number of interviewing teams in each state varied according to the sample size. In each state, interviewers were hired by the selected Field Agencies, taking into consideration their educational background, experience, and other relevant qualifications. Female and male interviewers were assigned to interview respondents of the same sex. The assignment of Primary Sampling Units (PSUs) to the teams and various logistical decisions were made by the survey coordinators from each Field Agency. Each interviewer was required to make a minimum of three callbacks if no suitable informant was available for the household interview or if an eligible woman or man in the household was not present at the time of the interviewer’s visit. The field supervisor was responsible for the overall management of the field teams. In addition, the field supervisor conducted spot-checks to verify the accuracy of key information, particularly with respect to the eligibility of respondents. IIPS also appointed one or more project officers or senior project officers in each state for monitoring and supervision throughout the training and fieldwork period to ensure that correct survey procedures were followed and that data quality was maintained. Project directors and other senior staff from the Field Agencies, the Principal Investigators from IIPS, officials from MoHFW, and technical consultants from The DHS Program at ICF also visited the field sites to monitor data collection operations. 1.8 STRATEGY TO ENSURE DATA QUALITY Due to the size and complexity of the NFHS-5 survey, considerable thought went into devising strategies to minimize the non-sampling errors and ensure data quality. Some of the procedures adopted are summarized below.  NFHS-5 was conducted in two phases to make the administration of the training and fieldwork more manageable.  In the states included in each phase, fieldwork was conducted in a group of five adjacent districts at a time to facilitate close monitoring and supervision of the training of field staff and the implementation of the fieldwork.  To maintain uniform procedures across the states, several comprehensive manuals were prepared, including a Supervisor’s Manual, an Interviewer’s Manual, a Health Investigator’s Manual, a Household Mapping and Listing Manual, Data Processing Guidelines, and Training Guidelines.  There were multiple levels of monitoring and supervision of the fieldwork, including monitoring by district coordinators from the Field Agencies; monitoring by senior staff from the state offices of the Field Agencies; positioning two IIPS project officers with each Field Agency for the entire duration of the survey, in addition to monitoring and supervision by senior project officers, project coordinators, IIPS faculty coordinators, staff and consultants from ICF, and representatives from the development partners and the Ministry of Health and Family Welfare, Government of India. Immediate corrective measures were taken in case there were any deviations from the survey protocols.  The field supervisor on each interviewing team was required to observe interviews in a subsample of households and to conduct back-checks with respondents as a further check on the quality of the fieldwork.  Use of computer assisted personal interviewing (CAPI) and the transfer of field data to IIPS on a daily basis were instrumental in remotely monitoring progress of the field teams. Use of CAPI also enabled IIPS and ICF to run extensive data quality checks on the data from the field and to provide real-time feedback to Field Agencies and teams to help improve data quality. A standard set of 44 field-check tables (FCTs) were produced frequently throughout the fieldwork, covering such topics as response rates, age heaping and age displacement, completeness of reporting, sex ratios for children, patterns of height/length and weight measurements, and the contraceptive prevalence rate. (Please refer to the data collection flow chart below). 8  The CAPI program used in NFHS has an inbuilt feature to select the appropriate language for the interviews from multiple regional languages. Control and management of fieldwork across the country is arranged from the central office by allotment of work to each of more than 500 teams working and accessing their progress on a real-time basis. An inbuilt algorithm in the CAPI program automatically handles skip patterns, filters, and eligibility for questionnaires and sections. The provision of synchronizing data from the interviewer’s CAPI instrument to the supervisor’s CAPI instrument provides an opportunity for back-checking information to improve data quality. An inbuilt mechanism partially saves incomplete questionnaires to provide opportunities to complete the interview in multiple sessions and minimize respondent’s fatigue. Use of SyncCloud Technology improves the data synchronization from the supervisor’s CAPI instrument to the Central Office, which gives access to real-time data from any device or computer. The CAPI programs help in generating field-check tables on key indicators on a daily basis which are reviewed by the Quality Assurance Team in the central office to allow individual level feedback to be communicated back to the teams working across different parts of the country.  NFHS assigns a unique code to each investigator within a state, which helps in tracking the progress and performance of the investigator after individual level feedback is provided.  Protocols for fieldwork implementation and monitoring are laid down for the smooth execution of the fieldwork. Also, rigorous procedures to check data quality are conducted throughout the course of the fieldwork. These include back-checks of the questionnaires in the field, and the frequent examination of an extensive set of field-check tables to detect systematic errors at the level of the interviewing teams and individual interviewers. Any problems that are detected by the field-check tables can be immediately relayed back to the Field Agencies to be addressed in a timely fashion.  To ensure uniformity in the implementation of the fieldwork protocols in every state, a centrally- organized Training of Trainers’ Workshop of four weeks duration was conducted in each phase. Four persons from each Field Agency participated in the workshop (two social scientists, one IT specialist, and one health coordinator). These trained persons were responsible for organizing the state-level training programmes in local and regional languages, for a minimum of four weeks’ duration, which were supported and supervised by IIPS and ICF.  To ensure that biomarker tests were conducted properly in a uniform manner, training videos in English and Hindi were produced to indicate the correct procedures for conducting height/length and weight measurements and to demonstrate in detail how to conduct anaemia and blood glucose testing and how to collect blood samples on filter paper cards.  The protocols used for collection of CAB data have been developed as per international standards which allow comparability with other DHS surveys.  NFHS-5 used standard, self-calibrating equipment having the latest technologies to ensure minimum instrument errors. The equipment used in the survey is also standardized periodically to ensure the accuracy and consistency of the measurements.  For the first time in NFHS-5 (2019-21), there was a provision for generating error messages to ensure internal inconsistency in the data with a condition of immediate corrections. IIPS and ICF have developed and implemented this application to reduce the burden of secondary editing after completion of data collection. This application has been designed so that any inconsistencies in the responses of a completed interview will be highlighted. The team supervisor may ask the interviewer about the inconsistencies and make the necessary corrections. The interviewer may revisit the respondent if required for any clarification of those issues. Hence, the error messages turned out to be a handy tool to ensure data quality in NFHS-5 before the survey team left the completed PSU.  It is worth mentioning that back-checks are an integral part of the quality control mechanism adopted in all the large-scale surveys. However, there are two questions generally raised on the issue of back-checks. First, how households should be selected to revisit. and second, how to incorporate the changes if required. To address these issues, NFHS-5 developed and used an algorithm called the Project Officer’s Query Report (POQR) on the Supervisor’s CAPI instrument. Once the data collection is completed in a PSU and data are synchronized on the supervisor’s CAPI instrument, the IIPS project officer, using a specific login and password, can run the query tool to view a list of households having some potential 9  The CAPI program used in NFHS has an inbuilt feature to select the appropriate language for the interviews from multiple regional languages. Control and management of fieldwork across the country is arranged from the central office by allotment of work to each of more than 500 teams working and accessing their progress on a real-time basis. An inbuilt algorithm in the CAPI program automatically handles skip patterns, filters, and eligibility for questionnaires and sections. The provision of synchronizing data from the interviewer’s CAPI instrument to the supervisor’s CAPI instrument provides an opportunity for back-checking information to improve data quality. An inbuilt mechanism partially saves incomplete questionnaires to provide opportunities to complete the interview in multiple sessions and minimize respondent’s fatigue. Use of SyncCloud Technology improves the data synchronization from the supervisor’s CAPI instrument to the Central Office, which gives access to real-time data from any device or computer. The CAPI programs help in generating field-check tables on key indicators on a daily basis which are reviewed by the Quality Assurance Team in the central office to allow individual level feedback to be communicated back to the teams working across different parts of the country.  NFHS assigns a unique code to each investigator within a state, which helps in tracking the progress and performance of the investigator after individual level feedback is provided.  Protocols for fieldwork implementation and monitoring are laid down for the smooth execution of the fieldwork. Also, rigorous procedures to check data quality are conducted throughout the course of the fieldwork. These include back-checks of the questionnaires in the field, and the frequent examination of an extensive set of field-check tables to detect systematic errors at the level of the interviewing teams and individual interviewers. Any problems that are detected by the field-check tables can be immediately relayed back to the Field Agencies to be addressed in a timely fashion.  To ensure uniformity in the implementation of the fieldwork protocols in every state, a centrally- organized Training of Trainers’ Workshop of four weeks duration was conducted in each phase. Four persons from each Field Agency participated in the workshop (two social scientists, one IT specialist, and one health coordinator). These trained persons were responsible for organizing the state-level training programmes in local and regional languages, for a minimum of four weeks’ duration, which were supported and supervised by IIPS and ICF.  To ensure that biomarker tests were conducted properly in a uniform manner, training videos in English and Hindi were produced to indicate the correct procedures for conducting height/length and weight measurements and to demonstrate in detail how to conduct anaemia and blood glucose testing and how to collect blood samples on filter paper cards.  The protocols used for collection of CAB data have been developed as per international standards which allow comparability with other DHS surveys.  NFHS-5 used standard, self-calibrating equipment having the latest technologies to ensure minimum instrument errors. The equipment used in the survey is also standardized periodically to ensure the accuracy and consistency of the measurements.  For the first time in NFHS-5 (2019-21), there was a provision for generating error messages to ensure internal inconsistency in the data with a condition of immediate corrections. IIPS and ICF have developed and implemented this application to reduce the burden of secondary editing after completion of data collection. This application has been designed so that any inconsistencies in the responses of a completed interview will be highlighted. The team supervisor may ask the interviewer about the inconsistencies and make the necessary corrections. The interviewer may revisit the respondent if required for any clarification of those issues. Hence, the error messages turned out to be a handy tool to ensure data quality in NFHS-5 before the survey team left the completed PSU.  It is worth mentioning that back-checks are an integral part of the quality control mechanism adopted in all the large-scale surveys. However, there are two questions generally raised on the issue of back-checks. First, how households should be selected to revisit. and second, how to incorporate the changes if required. To address these issues, NFHS-5 developed and used an algorithm called the Project Officer’s Query Report (POQR) on the Supervisor’s CAPI instrument. Once the data collection is completed in a PSU and data are synchronized on the supervisor’s CAPI instrument, the IIPS project officer, using a specific login and password, can run the query tool to view a list of households having some potential 10 gaps and inconsistencies in the information. After running POQR, the IIPS PO revisits the household and backchecks the information, maintaining gender sensitivity. Thus, the application of POQR in NFHS-5 has helped in reviewing a subsample of interviewed households to ensure accuracy and reliability of the information, and if there is any problem, to go back to the interviewer’s CAPI instrument to correct that information before resynchronizing the data on the supervisor’s CAPI instrument.  NFHS-5 has developed a protocol of accessing real-time data daily using the SyncCloud data streaming system. Continuous evaluation of data through field-check tables and regular feedback to field teams avoids errors and improves the quality of the data. The CAPI programs help in generating field-check tables on key indicators daily, which are reviewed by the Quality Assurance Team (QAT) in the central office to allow individual-level feedback to be communicated to the teams working in different parts of the country. A total of 51 indicators were developed as part of the FCTs covering various aspects of data quality, including response rates, age displacement, birth displacement, and skips associated with multiple questions. These FCTs were used to provide feedback on data quality. Moreover, online interactions with the core team of the Field Agency (FA) and the IIPS field POs once in every two weeks were arranged by the members of the quality assurance unit in the NFHS-5 office at IIPS. All these innovative measures have made a significant contribution in tracking and monitoring the daily field operations of NFHS-5, particularly to boost the morale of underperforming teams/interviewers and to motivate them by comparing their performance with the performance of other teams. Taking the COVID-19 situation into account, with the restart of the survey, several protective measures were taken into consideration for survey teams and respondents to prevent COVID-19 infection. Some of these measures were:  All core team members and survey teams were mandated to install the Aarogya Setu App on their phones and check their COVID status every day before leaving for the field.  Team members were advised to eat or drink alone with proper social distancing among them and maintaining all the practices for personal hygiene.  Physical distancing was instructed to maintain during the interview ensuring privacy and confidentiality.  Teams were educated to check for the well-being of each team member every morning before leaving for fieldwork with thermal screening, which was provided by IIPS. If any team member had developed symptoms, the fieldwork for that team was stopped. It was restarted only if the member was found to be COVID-19 negative.  Contacting the Headman of the village/frontline workers to get the COVID-19 status of the selected household members before the interviews were done.  Thermal screening of community people who were willing to be screened by Health Investigators of the survey team on the first day of the visit was carried out while distributing specially designed leaflets to the community members as a part of COVID-19 awareness.  NFHS made provisions of providing masks, sanitizers, and COVID-19 brochures to all the selected households.  Each respondent was instructed to give a new mask during the interview and CAB investigations. Compulsory thermal screening was conducted of all the members of the selected households. If anyone had a fever, that household was not allowed to be interviewed. A revisit was done for the reassessment of their status over the next three or four days.  The team members were obliged to wear a mask during fieldwork. Additional protective equipment like face shields, aprons, and goggles was encouraged. Updated guidelines from the government were adopted from time to time. The team members were directed to use sanitizer/soap and water to clean their hands frequently during fieldwork, preferably at the beginning and end of each interview.  The CAB investigations were done with minimum contact with the respondents. The protocol of using a new set of gloves for each respondent and disposal of bio-hazardous waste daily was to be strictly adhered to.  The CAB equipment was mandated to be cleaned after the end of interviews in each household. If the household had any member practicing isolation (very young or old members, and for whom the respondents demand), equipment was cleaned before use for that member.  The CAPI instrument was mandated to be cleaned after every interview. 1.9 DATA PROCESSING Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized. Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required. 1.10 RESPONSE RATES Table 1.1 shows response rates for the 2019-21 National Family Health Survey. A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent. In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent. Table 1.2 shows response rates for each state and union territory. Overall, response rates are quite high. Household response rates were over 95 percent in every state and union territory except Chandigarh (where the household response rate was 88%) and Madhya Pradesh (where the household response rate was 94%). The response rate for women was also 95 percent or higher in every state and union territory except in Chandigarh (where it was 81%). As expected, the response rate for men was lower than the response rate for women in every state and union territory. The response rate for men was particularly low in Chandigarh (63%). 11 gaps and inconsistencies in the information. After running POQR, the IIPS PO revisits the household and backchecks the information, maintaining gender sensitivity. Thus, the application of POQR in NFHS-5 has helped in reviewing a subsample of interviewed households to ensure accuracy and reliability of the information, and if there is any problem, to go back to the interviewer’s CAPI instrument to correct that information before resynchronizing the data on the supervisor’s CAPI instrument.  NFHS-5 has developed a protocol of accessing real-time data daily using the SyncCloud data streaming system. Continuous evaluation of data through field-check tables and regular feedback to field teams avoids errors and improves the quality of the data. The CAPI programs help in generating field-check tables on key indicators daily, which are reviewed by the Quality Assurance Team (QAT) in the central office to allow individual-level feedback to be communicated to the teams working in different parts of the country. A total of 51 indicators were developed as part of the FCTs covering various aspects of data quality, including response rates, age displacement, birth displacement, and skips associated with multiple questions. These FCTs were used to provide feedback on data quality. Moreover, online interactions with the core team of the Field Agency (FA) and the IIPS field POs once in every two weeks were arranged by the members of the quality assurance unit in the NFHS-5 office at IIPS. All these innovative measures have made a significant contribution in tracking and monitoring the daily field operations of NFHS-5, particularly to boost the morale of underperforming teams/interviewers and to motivate them by comparing their performance with the performance of other teams. Taking the COVID-19 situation into account, with the restart of the survey, several protective measures were taken into consideration for survey teams and respondents to prevent COVID-19 infection. Some of these measures were:  All core team members and survey teams were mandated to install the Aarogya Setu App on their phones and check their COVID status every day before leaving for the field.  Team members were advised to eat or drink alone with proper social distancing among them and maintaining all the practices for personal hygiene.  Physical distancing was instructed to maintain during the interview ensuring privacy and confidentiality.  Teams were educated to check for the well-being of each team member every morning before leaving for fieldwork with thermal screening, which was provided by IIPS. If any team member had developed symptoms, the fieldwork for that team was stopped. It was restarted only if the member was found to be COVID-19 negative.  Contacting the Headman of the village/frontline workers to get the COVID-19 status of the selected household members before the interviews were done.  Thermal screening of community people who were willing to be screened by Health Investigators of the survey team on the first day of the visit was carried out while distributing specially designed leaflets to the community members as a part of COVID-19 awareness.  NFHS made provisions of providing masks, sanitizers, and COVID-19 brochures to all the selected households.  Each respondent was instructed to give a new mask during the interview and CAB investigations. Compulsory thermal screening was conducted of all the members of the selected households. If anyone had a fever, that household was not allowed to be interviewed. A revisit was done for the reassessment of their status over the next three or four days.  The team members were obliged to wear a mask during fieldwork. Additional protective equipment like face shields, aprons, and goggles was encouraged. Updated guidelines from the government were adopted from time to time. The team members were directed to use sanitizer/soap and water to clean their hands frequently during fieldwork, preferably at the beginning and end of each interview.  The CAB investigations were done with minimum contact with the respondents. The protocol of using a new set of gloves for each respondent and disposal of bio-hazardous waste daily was to be strictly adhered to.  The CAB equipment was mandated to be cleaned after the end of interviews in each household. If the household had any member practicing isolation (very young or old members, and for whom the respondents demand), equipment was cleaned before use for that member.  The CAPI instrument was mandated to be cleaned after every interview. 1.9 DATA PROCESSING Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized. Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required. 1.10 RESPONSE RATES Table 1.1 shows response rates for the 2019-21 National Family Health Survey. A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent. In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent. Table 1.2 shows response rates for each state and union territory. Overall, response rates are quite high. Household response rates were over 95 percent in every state and union territory except Chandigarh (where the household response rate was 88%) and Madhya Pradesh (where the household response rate was 94%). The response rate for women was also 95 percent or higher in every state and union territory except in Chandigarh (where it was 81%). As expected, the response rate for men was lower than the response rate for women in every state and union territory. The response rate for men was particularly low in Chandigarh (63%). 12 LIST OF TABLES For more information on response rate, see the following tables: Tables 1.1 Results of the household and individual interviews 1.2 Number of households, women, and men interviewed by state/union territory Table 1.1 Results of the household and individual interviews Number of households, number of interviews with women and men, and response rates, according to residence, India, 2019-21 Result Residence Total Urban Rural Household interviews Households selected 171,709 493,256 664,972 Households occupied 167,591 485,546 653,144 Households interviewed 160,138 476,561 636,699 Household response rate1 95.6 98.1 97.5 Interviews with women age 15-49 Number of eligible women 186,921 560,255 747,176 Number of eligible women interviewed 179,535 544,580 724,115 Eligible women response rate2 96.0 97.2 96.9 Interviews with men age 15-54 Number of eligible men 29,558 81,621 111,179 Number of eligible men interviewed 26,420 75,419 101,839 Eligible men response rate2 89.4 92.4 91.6 Note: Eligible women and men are women age 15-49 and men age 15-54 who stayed in the household the night before the household interview (including both usual residents and visitors). This table is based on the unweighted sample. 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents 13 LIST OF TABLES For more information on response rate, see the following tables: Tables 1.1 Results of the household and individual interviews 1.2 Number of households, women, and men interviewed by state/union territory Table 1.1 Results of the household and individual interviews Number of households, number of interviews with women and men, and response rates, according to residence, India, 2019-21 Result Residence Total Urban Rural Household interviews Households selected 171,709 493,256 664,972 Households occupied 167,591 485,546 653,144 Households interviewed 160,138 476,561 636,699 Household response rate1 95.6 98.1 97.5 Interviews with women age 15-49 Number of eligible women 186,921 560,255 747,176 Number of eligible women interviewed 179,535 544,580 724,115 Eligible women response rate2 96.0 97.2 96.9 Interviews with men age 15-54 Number of eligible men 29,558 81,621 111,179 Number of eligible men interviewed 26,420 75,419 101,839 Eligible men response rate2 89.4 92.4 91.6 Note: Eligible women and men are women age 15-49 and men age 15-54 who stayed in the household the night before the household interview (including both usual residents and visitors). This table is based on the unweighted sample. 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Table 1.2 Number of households, women, and men interviewed by state/union territory Month and year of fieldwork, number of households, women, and men interviewed, and response rates by state/union territory, India, 2019-21 State/union territory Start month and year of fieldwork End month and year of fieldwork Households interviewed Women interviewed Men interviewed Month Year Month Year Number Response rate Number Response rate Number Response rate India 6 2019 4 2021 636,699 97.5 724,115 96.9 101,839 91.6 North Chandigarh 3 2021 4 2021 761 88.0 746 81.2 104 63.4 Delhi 1 2020 1 2021 9,486 95.2 11,159 94.6 1,700 84.2 Haryana 1 2020 4 2021 18,229 96.7 21,909 95.7 3,224 84.8 Himachal Pradesh 7 2019 11 2019 10,698 98.8 10,368 96.5 1,477 91.1 Jammu & Kashmir 7 2019 1 2020 18,086 98.7 23,037 96.6 3,087 88.1 Ladakh 8 2019 9 2019 1,818 99.2 2,355 97.7 307 92.7 Punjab 1 2020 3 2021 18,824 95.6 21,771 94.6 3,296 83.1 Rajasthan 1 2020 3 2021 31,817 98.1 42,990 97.5 6,353 94.1 Uttarakhand 1 2020 3 2021 12,169 97.3 13,280 94.9 1,586 85.2 Central Chhattisgarh 1 2020 3 2021 24,550 98.8 28,468 97.0 4,174 94.1 Madhya Pradesh 1 2020 4 2021 43,552 93.7 48,410 94.9 7,025 88.0 Uttar Pradesh 12 2019 4 2021 70,710 97.3 93,124 96.3 12,043 88.6 East Bihar 7 2019 2 2020 35,834 97.0 42,483 96.6 4,897 90.9 Jharkhand 1 2020 4 2021 22,863 97.3 26,495 97.5 3,414 92.1 Odisha 1 2020 3 2021 26,467 98.5 27,971 97.5 3,865 93.3 West Bengal 6 2019 11 2019 18,187 98.7 21,408 98.8 3,021 96.4 Northeast Arunachal Pradesh 1 2020 4 2021 18,268 98.6 19,765 98.4 2,881 96.6 Assam 6 2019 12 2019 30,119 99.3 34,979 97.6 4,973 93.9 Manipur 7 2019 1 2020 7,881 98.1 8,042 97.0 1,162 93.0 Meghalaya 7 2019 11 2019 10,148 99.8 13,089 98.8 1,824 97.0 Mizoram 7 2019 11 2019 7,257 99.4 7,279 98.7 1,105 98.0 Nagaland 7 2019 12 2019 10,112 99.9 9,694 99.8 1,456 99.6 Sikkim 8 2019 12 2019 3,516 98.4 3,271 95.4 469 94.4 Tripura 7 2019 11 2019 7,209 98.3 7,314 97.2 990 93.2 West Dadra & Nagar Haveli and Daman & Diu 7 2019 11 2019 2,676 97.6 2,713 97.4 427 91.6 Goa 8 2019 11 2019 1,856 98.3 2,030 98.2 313 96.0 Gujarat 6 2019 11 2019 29,368 98.2 33,343 97.6 5,351 95.0 Maharashtra 6 2019 12 2019 31,643 97.1 33,755 97.3 5,497 94.7 South Andaman & Nicobar Islands 10 2019 2 2020 2,624 97.3 2,397 97.8 367 94.3 Andhra Pradesh 7 2019 11 2019 11,346 96.9 10,975 97.4 1,558 92.2 Karnataka 7 2019 12 2019 26,574 97.4 30,455 97.6 4,516 93.8 Kerala 7 2019 12 2019 12,330 98.2 10,969 96.6 1,473 89.1 Lakshadweep 12 2019 1 2020 921 99.9 1,234 98.0 135 97.1 Puducherry 1 2020 3 2021 3,520 97.9 3,669 98.1 534 96.4 Tamil Nadu 1 2020 3 2021 27,929 97.3 25,650 98.3 3,372 94.9 Telangana 6 2019 11 2019 27,351 97.1 27,518 96.8 3,863 92.0 Note: This table is based on the unweighted sample; all subsequent tables are based on the weighted sample unless otherwise specified. The number of women and men is based on the de facto population. The household response rate is defined as the number of households interviewed divided by the number of occupied households. The response rates for women and men are the percentages of eligible women and men with completed interviews. 14 15 Table 1.2 Number of households, women, and men interviewed by state/union territory Month and year of fieldwork, number of households, women, and men interviewed, and response rates by state/union territory, India, 2019-21 State/union territory Start month and year of fieldwork End month and year of fieldwork Households interviewed Women interviewed Men interviewed Month Year Month Year Number Response rate Number Response rate Number Response rate India 6 2019 4 2,021 636,699 97.5 724,115 96.9 101,839 91.6 North Chandigarh 3 2021 4 2,021 761 88.0 746 81.2 104 63.4 Delhi 1 2020 1 2,021 9,486 95.2 11,159 94.6 1,700 84.2 Haryana 1 2020 4 2,021 18,229 96.7 21,909 95.7 3,224 84.8 Himachal Pradesh 7 2019 11 2,019 10,698 98.8 10,368 96.5 1,477 91.1 Jammu & Kashmir 7 2019 1 2,020 18,086 98.7 23,037 96.6 3,087 88.1 Ladakh 8 2019 9 2,019 1,818 99.2 2,355 97.7 307 92.7 Punjab 1 2020 3 2,021 18,824 95.6 21,771 94.6 3,296 83.1 Rajasthan 1 2020 3 2,021 31,817 98.1 42,990 97.5 6,353 94.1 Uttarakhand 1 2020 3 2,021 12,169 97.3 13,280 94.9 1,586 85.2 Central Chhattisgarh 1 2020 3 2,021 24,550 98.8 28,468 97.0 4,174 94.1 Madhya Pradesh 1 2020 4 2,021 43,552 93.7 48,410 94.9 7,025 88.0 Uttar Pradesh 12 2019 4 2,021 70,710 97.3 93,124 96.3 12,043 88.6 East Bihar 7 2019 2 2,020 35,834 97.0 42,483 96.6 4,897 90.9 Jharkhand 1 2020 4 2,021 22,863 97.3 26,495 97.5 3,414 92.1 Odisha 1 2020 3 2,021 26,467 98.5 27,971 97.5 3,865 93.3 West Bengal 6 2019 11 2,019 18,187 98.7 21,408 98.8 3,021 96.4 Northeast Arunachal Pradesh 1 2020 4 2,021 18,268 98.6 19,765 98.4 2,881 96.6 Assam 6 2019 12 2,019 30,119 99.3 34,979 97.6 4,973 93.9 Manipur 7 2019 1 2,020 7,881 98.1 8,042 97.0 1,162 93.0 Meghalaya 7 2019 11 2,019 10,148 99.8 13,089 98.8 1,824 97.0 Mizoram 7 2019 11 2,019 7,257 99.4 7,279 98.7 1,105 98.0 Nagaland 7 2019 12 2,019 10,112 99.9 9,694 99.8 1,456 99.6 Sikkim 8 2019 12 2,019 3,516 98.4 3,271 95.4 469 94.4 Tripura 7 2019 11 2,019 7,209 98.3 7,314 97.2 990 93.2 West Dadra & Nagar Haveli and Daman & Diu 7 2019 11 2,019 2,676 97.6 2,713 97.4 427 91.6 Goa 8 2019 11 2,019 1,856 98.3 2,030 98.2 313 96.0 Gujarat 6 2019 11 2,019 29,368 98.2 33,343 97.6 5,351 95.0 Maharashtra 6 2019 12 2,019 31,643 97.1 33,755 97.3 5,497 94.7 South Andaman & Nicobar Islands 10 2019 2 2,020 2,624 97.3 2,397 97.8 367 94.3 Andhra Pradesh 7 2019 11 2,019 11,346 96.9 10,975 97.4 1,558 92.2 Karnataka 7 2019 12 2,019 26,574 97.4 30,455 97.6 4,516 93.8 Kerala 7 2019 12 2,019 12,330 98.2 10,969 96.6 1,473 89.1 Lakshadweep 12 2019 1 2,020 921 99.9 1,234 98.0 135 97.1 Puducherry 1 2020 3 2,021 3,520 97.9 3,669 98.1 534 96.4 Tamil Nadu 1 2020 3 2,021 27,929 97.3 25,650 98.3 3,372 94.9 Telangana 6 2019 11 2,019 27,351 97.1 27,518 96.8 3,863 92.0 Note: This table is based on the unweighted sample; all subsequent tables are based on the weighted sample unless otherwise specified. The number of women and men is based on the de facto population. The household response rate is defined as the number of households interviewed divided by the number of occupied households. The response rates for women and men are the percentages of eligible women and men with completed interviews. HOUSEHOLD POPULATION AND HOUSING CHARACTERISTICS 2 Key Findings  Drinking water: Ninety-six percent of households use an improved source of drinking water.  Sanitation: Sixty-nine percent of households use an improved sanitation facility that is not shared with other households and 8 percent use a facility that would be considered improved if it were not shared. Nineteen percent of households have no facility, which means that the household members practice open defecation.  Access to sanitation: Eighty-three percent of households have access to a toilet facility.  Electricity: Ninety-seven percent of households have electricity (95% of rural households and 99% of urban households).  Cooking fuel: Only fifty-nine percent of households use clean fuel for cooking.  Age distribution: Twenty-seven percent of the population is under age 15, and 12 percent is age 60 years and above.  Aadhaar card: Ninety percent of the household population have an Aadhaar card.  Bank or post office account: Ninety-six percent of households have a bank or post office account.  Birth registration: Eighty-nine percent of children under age five had their birth registered.  Death registration: Seventy-one percent of deaths of usual household members were registered with the civil authorities (83% of urban households and 66% of rural households).  Orphans: Among children under age 18, 5 percent are orphans (one or both parents are dead) and 3 percent are not living with a biological parent.  Preschool attendance: Forty percent of boys and girls age 2-4 years attend preschool.  School attendance: The net attendance ratio falls from 83 percent in primary school to 71 percent in middle, secondary, and higher secondary school. The main reason given for not attending school was that the child is not interested in studies (36% for male children and 21% for female children).  Disability: Just 1 percent of the de jure household population have any disability. The most prominent type of disability is locomotor (0.4%).  Tobacco and Alcohol use: Thirty-eight percent of men and 9 percent of women age 15 and over currently use any tobacco products. Only 1 percent of women and 19 percent of men age 15 and over currently drink alcohol.  Household ownership of mosquito net: More than one-third of households (36%) in India have at least one mosquito net, and 8 percent have at least one Insecticide Treated Mosquito Net (ITN). nformation on the socioeconomic characteristics of the household population in the 2019-21 National Family Health Survey (NFHS-5) provides a context for interpreting demographic and health indicators and an approximate indication of the representativeness of the survey. In addition, this information describes the living conditions of the population. I 16 This chapter presents information on the sources of drinking water, sanitation, exposure to smoke inside the home, household wealth, hand washing, composition of the household population, educational attainment, school attendance, birth registration, children’s living arrangements, and parental survivorship, death registration, preschool education, current use of tobacco and alcohol by the adult population, and possession of mosquito nets. 2.1 DRINKING WATER SOURCES AND TREATMENT In India, almost all urban households (99%) and rural households (95%) have access to an improved source of drinking water (Table 2.1). Improved sources of water protect against outside contamination so that the water is more likely to be safe to drink. Urban and rural households rely on different sources of drinking water. The main sources of drinking water for urban households are water piped into their dwelling, yard, or plot (54%), tube wells or boreholes (16%), and public taps or standpipes (12%) (Table 2.1 and Figure 2.1). In contrast, rural households rely most on tube wells or boreholes (46%), followed by water piped into their dwelling, yard, or plot (23%). In rural areas, 68 percent of households have water on their premises or delivered to their dwelling, compared with 86 percent in urban areas. In households where water is not delivered or the source of water is not at the premises, women age 15 years and above are most likely to collect drinking water (71%). Clean water is a basic need for human life. However, 58 percent of households do not treat their water prior to drinking. Treatment is less common in rural areas than urban areas; 66 percent of rural households do not treat their water, compared with 44 percent of urban households. Boiling water and straining the water through a cloth before drinking are the most common water treatment procedures used prior to drinking (16% and 15% of households, respectively). Improved sources of drinking water Include piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, tanker truck, cart with small tank, bottled water, and community reverse osmosis (RO) plants. Sample: Households 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, pit latrines, or an unknown destination; ventilated improved pit (VIP)/biogas latrines; pit latrines with slabs; and twin pit/composting toilets Sample: Households Access of sanitation facility Households that any type of toilet facility that household members usually use and households that do not use a toilet facility but report they have access to a toilet facility. Sample: Households Sixty-nine percent of Indian households use improved toilet facilities, which are non-shared facilities that prevent people from coming into contact with human waste and can reduce the transmission of cholera, typhoid, and other diseases. Shared toilet facilities of an otherwise acceptable type are also common, especially in urban areas; 11 percent of urban households use a shared facility, compared with 7 percent of rural households (Table 2.2 and Figure 2.2). Nineteen percent of households do not use any toilet facility, meaning that they practice open defecation. Eighty-three percent of households have access to a toilet facility; a much higher accessibility in urban areas (96%) than in rural areas (76%). Access to a toilet facility ranges from 69 percent among scheduled tribe households to 93 percent among households which are not scheduled caste, scheduled tribe, or other backward class households (Table 2.4). Among the states/UTs, access to a toilet facility is lowest in Bihar (62%), followed by Jharkhand (70%) and Odisha (71%) (Table 2.5). \Trends: The percentage of households practicing open defecation decreased from 39 percent in 2015-16 to 19 percent in 2019-21. 2.3 EXPOSURE TO SMOKE INSIDE THE HOME AND OTHER HOUSING CHARACTERISTICS 2.3.1 Exposure to Smoke inside the Home Exposure to smoke inside the home, either from cooking with solid fuels or smoking tobacco, has potentially harmful health effects. Forty-one percent of households in India use some type of solid fuel for cooking, with virtually all being wood or dung cakes (Table 2.6). Exposure to cooking smoke is greater when cooking takes place inside the house rather than in a separate building or outdoors. In 25 percent of households, someone smokes inside the house on daily basis. 54 23 33 12 14 13 16 46 36 3.3 3.5 3.40.2 0.4 0.4 0.1 0.3 0.2 2.7 2.8 2.7 1.0 5.1 3.7 Urban Rural Total Unimproved source Community RO Plant Rain water Protected spring Protected dug well Tube well or borehole Public tap/standpipe Piped into dwelling/yard/plot Figure 2.1 Household Drinking Water by Residence Percent distribution of households by source of drinking water 17 This chapter presents information on the sources of drinking water, sanitation, exposure to smoke inside the home, household wealth, hand washing, composition of the household population, educational attainment, school attendance, birth registration, children’s living arrangements, and parental survivorship, death registration, preschool education, current use of tobacco and alcohol by the adult population, and possession of mosquito nets. 2.1 DRINKING WATER SOURCES AND TREATMENT In India, almost all urban households (99%) and rural households (95%) have access to an improved source of drinking water (Table 2.1). Improved sources of water protect against outside contamination so that the water is more likely to be safe to drink. Urban and rural households rely on different sources of drinking water. The main sources of drinking water for urban households are water piped into their dwelling, yard, or plot (54%), tube wells or boreholes (16%), and public taps or standpipes (12%) (Table 2.1 and Figure 2.1). In contrast, rural households rely most on tube wells or boreholes (46%), followed by water piped into their dwelling, yard, or plot (23%). In rural areas, 68 percent of households have water on their premises or delivered to their dwelling, compared with 86 percent in urban areas. In households where water is not delivered or the source of water is not at the premises, women age 15 years and above are most likely to collect drinking water (71%). Clean water is a basic need for human life. However, 58 percent of households do not treat their water prior to drinking. Treatment is less common in rural areas than urban areas; 66 percent of rural households do not treat their water, compared with 44 percent of urban households. Boiling water and straining the water through a cloth before drinking are the most common water treatment procedures used prior to drinking (16% and 15% of households, respectively). Improved sources of drinking water Include piped water, public taps, standpipes, tube wells, boreholes, protected dug wells and springs, rainwater, tanker truck, cart with small tank, bottled water, and community reverse osmosis (RO) plants. Sample: Households 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, pit latrines, or an unknown destination; ventilated improved pit (VIP)/biogas latrines; pit latrines with slabs; and twin pit/composting toilets Sample: Households Access of sanitation facility Households that any type of toilet facility that household members usually use and households that do not use a toilet facility but report they have access to a toilet facility. Sample: Households Sixty-nine percent of Indian households use improved toilet facilities, which are non-shared facilities that prevent people from coming into contact with human waste and can reduce the transmission of cholera, typhoid, and other diseases. Shared toilet facilities of an otherwise acceptable type are also common, especially in urban areas; 11 percent of urban households use a shared facility, compared with 7 percent of rural households (Table 2.2 and Figure 2.2). Nineteen percent of households do not use any toilet facility, meaning that they practice open defecation. Eighty-three percent of households have access to a toilet facility; a much higher accessibility in urban areas (96%) than in rural areas (76%). Access to a toilet facility ranges from 69 percent among scheduled tribe households to 93 percent among households which are not scheduled caste, scheduled tribe, or other backward class households (Table 2.4). Among the states/UTs, access to a toilet facility is lowest in Bihar (62%), followed by Jharkhand (70%) and Odisha (71%) (Table 2.5). \Trends: The percentage of households practicing open defecation decreased from 39 percent in 2015-16 to 19 percent in 2019-21. 2.3 EXPOSURE TO SMOKE INSIDE THE HOME AND OTHER HOUSING CHARACTERISTICS 2.3.1 Exposure to Smoke inside the Home Exposure to smoke inside the home, either from cooking with solid fuels or smoking tobacco, has potentially harmful health effects. Forty-one percent of households in India use some type of solid fuel for cooking, with virtually all being wood or dung cakes (Table 2.6). Exposure to cooking smoke is greater when cooking takes place inside the house rather than in a separate building or outdoors. In 25 percent of households, someone smokes inside the house on daily basis. 81 64 69 11 7.4 8.4 2.7 3.1 2.9 0.5 0.2 0.3 6.1 26 19 Urban Rural Total No facility/uses open space/field Other source Unimproved Shared facility Improved, not shared facility Figure 2.2 Household Toilet Facilities by Residence Percent distribution of households by type of toilet facilities 81 64 69 11 7.4 8.4 2.7 3.1 2.9 0.5 0.2 0.3 6.1 26 19 Urban Rural Total No facility/uses open space/field Other source Unimproved Shared facility Improved, not shared facility Figure 2.2 Household Toilet Facilities by Residence Percent distribution of households by type of toilet facilities 18 2.3.2 Other Housing Characteristics The survey collected data on access to electricity, on flooring materials, and on the number of rooms used for sleeping. Ninety-nine percent of urban households and 95 percent of rural households have electricity. Almost all households in India (97%) have electricity. Three-fifths of households (60%) have pucca houses (houses made with high quality materials throughout, including the floor, roof, and exterior walls) and 34 percent have semi-pucca houses. 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, and housing characteristics such as source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by their score, and then dividing the distribution into five equal categories, each with 20 percent of the population. Sample: Households Table 2.8 presents wealth quintiles according to urban-rural residence and state. In India, the wealthiest households are concentrated in urban areas. Seventy-four percent of the urban population is in the two highest wealth quintiles. By contrast, more than half of the rural population (54%) falls in the two lowest wealth quintiles (Figure 2.3). Chandigarh (79%), followed by Delhi (68%) and Punjab (61%), have the highest percentage of the population in the highest wealth quintile. The states with the highest percentages of population in the lowest wealth quintile are Jharkhand (46%), Bihar (43%) and Assam (38%) (Table 2.8). Seventy- one percent of the population in scheduled tribe households and 49 percent of the population in scheduled caste households are in the two lowest wealth quintiles (Table 2.9). The survey also collected information on household assets, means of transportation, agricultural land, and farm animals (Table 2.11 and Table 2.12 ). The percentage of households that have a bank account or a post office account is almost the same in urban (95%) and rural areas (96%). Urban households are somewhat more likely than rural households to have a mobile telephone (97% versus 92%). Rural households are more likely than urban households to own agricultural land (52% versus 13%) or farm animals (58% versus 10%). 2.5 HAND WASHING To obtain hand washing information, interviewers were asked to see the place where the de jure population most often wash their hands. A place for washing hands was observed for 96 percent of the de jure population. Soap was available at the place of hand washing for 75 percent of households and water was available for 92 percent of households, while 16 percent had material such as ash, mud or sand other than the soap and water only (Table 2.13). Twenty-six percent of the population did not have water, soap, or another cleansing agent for hand washing on the premises. 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. How data are calculated All tables are based on the de facto population, unless specified otherwise. A total of 2,768,371 individuals stayed overnight in the 636,699 sample households in the NFHS- 5 survey. The population pyramid in Figure 2.4 illustrates the distribution by five-year age groups and sex. The pyramid shows that India’s population is young, which is typical of developing countries with low life expectancy. The pyramid also shows that fertility has decreased considerably in the last 5 years. Children under age 15 represent 27 percent of the household population, while individuals age 60 and older represent only 12 percent of the household population (Table 2.15). Table 2.14 shows that 18 percent of households have female heads. Urban households are somewhat smaller, on average, than rural households (4.2 and 4.5 persons, respectively). Overall, 13 percent of households have one or more foster or orphan children under age 18. Trends: The percentage of children under age 15 declined from 29 percent in NFHS-4 (2015-16) to 27 percent in NFHS- 5 (2019-21). In contrast, the population 60 years and older increased slightly, from 10 percent in NFHS-4 to 12 percent in 3.2 28 7.2 26 16 22 29 16 46 8.1 Urban Rural Highest Fourth Middle Second Lowest Figure 2.3 Household Wealth by Residence Percent distribution of de jure population by wealth quintiles 19 2.3.2 Other Housing Characteristics The survey collected data on access to electricity, on flooring materials, and on the number of rooms used for sleeping. Ninety-nine percent of urban households and 95 percent of rural households have electricity. Almost all households in India (97%) have electricity. Three-fifths of households (60%) have pucca houses (houses made with high quality materials throughout, including the floor, roof, and exterior walls) and 34 percent have semi-pucca houses. 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, and housing characteristics such as source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by their score, and then dividing the distribution into five equal categories, each with 20 percent of the population. Sample: Households Table 2.8 presents wealth quintiles according to urban-rural residence and state. In India, the wealthiest households are concentrated in urban areas. Seventy-four percent of the urban population is in the two highest wealth quintiles. By contrast, more than half of the rural population (54%) falls in the two lowest wealth quintiles (Figure 2.3). Chandigarh (79%), followed by Delhi (68%) and Punjab (61%), have the highest percentage of the population in the highest wealth quintile. The states with the highest percentages of population in the lowest wealth quintile are Jharkhand (46%), Bihar (43%) and Assam (38%) (Table 2.8). Seventy- one percent of the population in scheduled tribe households and 49 percent of the population in scheduled caste households are in the two lowest wealth quintiles (Table 2.9). The survey also collected information on household assets, means of transportation, agricultural land, and farm animals (Table 2.11 and Table 2.12 ). The percentage of households that have a bank account or a post office account is almost the same in urban (95%) and rural areas (96%). Urban households are somewhat more likely than rural households to have a mobile telephone (97% versus 92%). Rural households are more likely than urban households to own agricultural land (52% versus 13%) or farm animals (58% versus 10%). 2.5 HAND WASHING To obtain hand washing information, interviewers were asked to see the place where the de jure population most often wash their hands. A place for washing hands was observed for 96 percent of the de jure population. Soap was available at the place of hand washing for 75 percent of households and water was available for 92 percent of households, while 16 percent had material such as ash, mud or sand other than the soap and water only (Table 2.13). Twenty-six percent of the population did not have water, soap, or another cleansing agent for hand washing on the premises. 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. How data are calculated All tables are based on the de facto population, unless specified otherwise. A total of 2,768,371 individuals stayed overnight in the 636,699 sample households in the NFHS- 5 survey. The population pyramid in Figure 2.4 illustrates the distribution by five-year age groups and sex. The pyramid shows that India’s population is young, which is typical of developing countries with low life expectancy. The pyramid also shows that fertility has decreased considerably in the last 5 years. Children under age 15 represent 27 percent of the household population, while individuals age 60 and older represent only 12 percent of the household population (Table 2.15). Table 2.14 shows that 18 percent of households have female heads. Urban households are somewhat smaller, on average, than rural households (4.2 and 4.5 persons, respectively). Overall, 13 percent of households have one or more foster or orphan children under age 18. Trends: The percentage of children under age 15 declined from 29 percent in NFHS-4 (2015-16) to 27 percent in NFHS- 5 (2019-21). In contrast, the population 60 years and older increased slightly, from 10 percent in NFHS-4 to 12 percent in 3.2 28 7.2 26 16 22 29 16 46 8.1 Urban Rural Highest Fourth Middle Second Lowest Figure 2.3 Household Wealth by Residence Percent distribution of de jure population by wealth quintiles 10 6 2 2 6 10 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80+ Percent Age in years Male Female 2610 Figure 2.4 Population Pyramid 20 NFHS-5. The average household size decreased slightly between 2015-16 and 2019-21 (from 4.6 to 4.4 persons), and the percentage of female-headed households increased slightly, from 15 percent in NFHS-4 to 18 percent in NFHS-5. 2.7 BIRTH REGISTRATION Registered birth Child has a birth certificate or child does not have a birth certificate, but his/her birth is registered with the civil authorities. Sample: De jure children under age five years Table 2.16 presents information on birth registration of children under age five years. At the time of the survey, 89 percent of children under age five years had their births registered with the civil authority; this includes 75 percent of children with birth certificates. Female and male children are equally likely to have their birth registered. Children in urban areas (93%) are more likely than children in rural areas (88%) to have their births registered. Birth registration is universal in Lakshadweep and Goa, is 95 percent or more in 21 States/UTs, and is below 80 percent in Bihar (76%), Jharkhand (74%), and Nagaland (73%). (Table 2.17 and Figure 2.5). Trends: Birth registration among children under age five years increased between NFHS-4 and NFHS-5 (from 80% to 89%). The percentage of births that were registered increased by more than 60 percentage points between 2015-16 and 2019-21 in Jharkhand, Bihar, Uttar Pradesh, and Nagaland. 2.8 DEATH REGISTRATION Registered death Deaths of usual household members occurred during the 3 years preceding the survey and are registered with the civil authority. Sample: De jure household population Table 2.18 presents information on death registration of usual household members in the three years preceding the survey with the civil authorities. Seventy-one percent of deaths of usual household members were registered with the civil authorities (51 percent of deaths at age 0-4, 76 percent of deaths at age 25-34, and 75 percent of deaths at age 35 and above). Death registration is higher in urban (83%) than rural areas (66%) and among males (75%) than females (66%). Death registration increases with wealth; the highest registration is in the highest wealth quintile (87%) and the lowest is in lowest wealth quintile (52%). Among the states/UTs, death registration is lowest in Bihar (36%), followed by Arunachal Pradesh (37%) and Nagaland (39%) (Table 2.19). 2.9 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: De jure children under age 18 years Only 3 percent of children under age 18 years are not living with a biological parent (Table 2.20). Five percent of children under age 18 years are orphans with one or both parents who have died. The percentage of children who are orphans rises rapidly with age, from less than 1 percent among children under age 2 to 9 percent among children age 15-17 (Figure 2.6). The Northeast region has the highest percentage of children who are orphans (6% or more in every state except Tripura) (Table 2.21). Trends: The percentage of children under age 18 who do not live with a biological parent has not changed between NFHS-4 and NFHS-5 (3%). The percentage of children under age 18 who are orphans (5%) did not change between 2015-16 and 2019-21. 2.10 SCHOOLING 2.10.1 Educational Attainment Median educational attainment Half the population has completed less than the median number of years of schooling and half the population has completed more than the median number of years of schooling. Sample: De facto household population age six and over 73 74 76 80 82 87 88 89 90 91 91 92 92 94 94 94 95 95 96 96 97 97 97 98 98 98 98 98 98 98 98 99 99 99 99 100 100 Nagaland Jharkhand Bihar Uttar Pradesh Meghalaya Manipur Arunachal Pradesh INDIA Telangana Odisha Rajasthan Uttarakhand Andhra Pradesh Tripura Madhya Pradesh Delhi Haryana Jammu & Kashmir Assam Maharashtra Sikkim Chhattisgarh Andaman & Nicobar Islands Gujarat Karnataka Chandigarh Punjab Himachal Pradesh Dadra & Nagar Haveli and Daman & Diu West Bengal Tamil Nadu Ladakh Kerala Puducherry Mizoram Goa Lakshadweep Figure 2.5 Birth Registration by State/UT Percentage of de jure children under age five whose births are registered with the civil authorities 21 NFHS-5. The average household size decreased slightly between 2015-16 and 2019-21 (from 4.6 to 4.4 persons), and the percentage of female-headed households increased slightly, from 15 percent in NFHS-4 to 18 percent in NFHS-5. 2.7 BIRTH REGISTRATION Registered birth Child has a birth certificate or child does not have a birth certificate, but his/her birth is registered with the civil authorities. Sample: De jure children under age five years Table 2.16 presents information on birth registration of children under age five years. At the time of the survey, 89 percent of children under age five years had their births registered with the civil authority; this includes 75 percent of children with birth certificates. Female and male children are equally likely to have their birth registered. Children in urban areas (93%) are more likely than children in rural areas (88%) to have their births registered. Birth registration is universal in Lakshadweep and Goa, is 95 percent or more in 21 States/UTs, and is below 80 percent in Bihar (76%), Jharkhand (74%), and Nagaland (73%). (Table 2.17 and Figure 2.5). Trends: Birth registration among children under age five years increased between NFHS-4 and NFHS-5 (from 80% to 89%). The percentage of births that were registered increased by more than 60 percentage points between 2015-16 and 2019-21 in Jharkhand, Bihar, Uttar Pradesh, and Nagaland. 2.8 DEATH REGISTRATION Registered death Deaths of usual household members occurred during the 3 years preceding the survey and are registered with the civil authority. Sample: De jure household population Table 2.18 presents information on death registration of usual household members in the three years preceding the survey with the civil authorities. Seventy-one percent of deaths of usual household members were registered with the civil authorities (51 percent of deaths at age 0-4, 76 percent of deaths at age 25-34, and 75 percent of deaths at age 35 and above). Death registration is higher in urban (83%) than rural areas (66%) and among males (75%) than females (66%). Death registration increases with wealth; the highest registration is in the highest wealth quintile (87%) and the lowest is in lowest wealth quintile (52%). Among the states/UTs, death registration is lowest in Bihar (36%), followed by Arunachal Pradesh (37%) and Nagaland (39%) (Table 2.19). 2.9 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents who are dead. Sample: De jure children under age 18 years Only 3 percent of children under age 18 years are not living with a biological parent (Table 2.20). Five percent of children under age 18 years are orphans with one or both parents who have died. The percentage of children who are orphans rises rapidly with age, from less than 1 percent among children under age 2 to 9 percent among children age 15-17 (Figure 2.6). The Northeast region has the highest percentage of children who are orphans (6% or more in every state except Tripura) (Table 2.21). Trends: The percentage of children under age 18 who do not live with a biological parent has not changed between NFHS-4 and NFHS-5 (3%). The percentage of children under age 18 who are orphans (5%) did not change between 2015-16 and 2019-21. 2.10 SCHOOLING 2.10.1 Educational Attainment Median educational attainment Half the population has completed less than the median number of years of schooling and half the population has completed more than the median number of years of schooling. Sample: De facto household population age six and over 0.9 1.6 3.3 6.1 8.9 <2 2-4 5-9 10-14 15-17 Figure 2.6 Orphanhood by Child's Age Percentage of de jure children under age 18 with one or both parents dead 22 Overall, 72 percent of females and 87 percent of males age six and over have ever attended school. Nearly one-third of females (31%) have 7 or less years of schooling; 14 percent completed 8-9 years of schooling. Among males, 34 percent have less than 7 years of schooling; 16 percent completed 8-9 years of schooling. Only 10 percent of females and 13 percent of males completed 10-11 years of schooling. Twenty-eight percent of females and 14 percent of males have never attended school. Seventeen percent of females and 23 percent of males completed 12 or more years of schooling. The median number of years of schooling completed is higher for males (7.3 years) than for females (4.9 years) (Tables 2.24). Trends: Educational attainment at the household level increased between 2015-16 and 2019-21. Among females, the median number of years of schooling increased from 4.4 years in NHFS-4 (2015-16) to 4.9 years in NHFS-5 (2019-21). The median number of years of schooling completed by males increased from 6.9 years in NHFS-4 to 7.3 years in NHFS- 5. Over the same period, the percentage of females and males with no schooling decreased from 31 percent of females and 15 percent of males to 28 percent of females and 14 percent of males. Patterns by background characteristics  Among both females and males, the median number of years of schooling is higher in urban areas than in rural areas (7.5 years versus 4.0 years among females and 8.8 years versus 6.5 years among males).  Educational attainment increases with household wealth. Females in the lowest wealth quintile have completed a median of 0.4 years of schooling, compared with a median of 9.3 years for females in the highest wealth quintile. The median number of years of schooling was 3.7 years among males in the lowest wealth quintile and 10.0 years among those in the highest quintile.  The median number of years of schooling is highest among those who do not belong to scheduled castes, scheduled tribes, and other backward classes (7.0 years for females and 8.5 years for males). The median number of years of schooling is lower among Muslims than for other specific religious groups (4.3 years for females and 5.4 years for males).  The percentage of the household population with no schooling is higher in rural areas than urban areas (33% versus 17% for females and 16% versus 8% for males). 2.10.2 Preschool attendance Preschool attendance Children age 2 to 4 years attending pre-primary education, such as at an anganwadi centre (Integrated Child Development Service), improves school readiness by providing quality learning through interactive play methods with qualified instructors. Sample: De facto household population age 2 to 4 years Attending pre-primary education, such as at an anganwadi centre, improves children’s school readiness. Also, parents or guardians can go to work at ease if children are enrolled in pre-primary education. Forty percent of both boys and girls age 2-4 years attend preschool. There is no difference in preschool attendance among children in nuclear households and non-nuclear households (40% each). Preschool attendance is the lowest among children in households with household head belonging to other religions (33%) and Muslim religion (34%). Preschool attendance is lower among children belonging to scheduled caste and other backward classes (38% each), compared with children from any other caste/tribe group. Preschool attendance is higher in households with 3 to 5 members (43%) than in households with 1-2 members (39%) and household with 6 or more members (38%). Overall, rural households (39%) show lower preschool attendance than urban households (44%) (Table 2.22). Preschool attendance is highest in Andaman and Nicobar Islands (89%), followed by Andhra Pradesh (75%) and Sikkim (74%) (Table 2.23). 2.10.3 School Attendance Net attendance ratio (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 6-10 for primary school NAR and children age 11-17 for secondary school NAR Gross attendance ratio (GAR) The total number of children attending primary school divided by the official primary school age population and the total number of children attending secondary school divided by the official secondary school age population. Sample: Children at the official primary school age for primary school GAR and children at the official secondary school age for secondary school GAR Eighty-seven percent of children age 6-17 attend school (88% of males and 87% of females) (Table 2.26). Almost all (95%) males and females age 6-10 attend school. This percentage decreases to 91 percent for children age 11-14 and then drops further to 70 percent for children age 15-17. There is almost no difference in school attendance by males (94%) and females (93%) at age 6-14, but males are more likely than females to attend school at age 15-17 (72% versus 68%). Urban- rural differentials in school attendance are minimal at age 6-10, but widen at older ages (Figure 2.7). Eighty-three percent of girls and 84 percent of boys age 6-10 attend primary school (Table 2.27). The net attendance ratio (NAR) drops in secondary school: only 70 percent of girls and 72 percent of boys age 11-17 attend secondary school. The gross attendance ratio (GAR) is 92 percent at the primary school level and 82 percent at the secondary school level. These figures indicate that a number of children outside the official school age population for that level are attending primary school, and not all those who should be are attending secondary school (Table 2.27). 23 Overall, 72 percent of females and 87 percent of males age six and over have ever attended school. Nearly one-third of females (31%) have 7 or less years of schooling; 14 percent completed 8-9 years of schooling. Among males, 34 percent have less than 7 years of schooling; 16 percent completed 8-9 years of schooling. Only 10 percent of females and 13 percent of males completed 10-11 years of schooling. Twenty-eight percent of females and 14 percent of males have never attended school. Seventeen percent of females and 23 percent of males completed 12 or more years of schooling. The median number of years of schooling completed is higher for males (7.3 years) than for females (4.9 years) (Tables 2.24). Trends: Educational attainment at the household level increased between 2015-16 and 2019-21. Among females, the median number of years of schooling increased from 4.4 years in NHFS-4 (2015-16) to 4.9 years in NHFS-5 (2019-21). The median number of years of schooling completed by males increased from 6.9 years in NHFS-4 to 7.3 years in NHFS- 5. Over the same period, the percentage of females and males with no schooling decreased from 31 percent of females and 15 percent of males to 28 percent of females and 14 percent of males. Patterns by background characteristics  Among both females and males, the median number of years of schooling is higher in urban areas than in rural areas (7.5 years versus 4.0 years among females and 8.8 years versus 6.5 years among males).  Educational attainment increases with household wealth. Females in the lowest wealth quintile have completed a median of 0.4 years of schooling, compared with a median of 9.3 years for females in the highest wealth quintile. The median number of years of schooling was 3.7 years among males in the lowest wealth quintile and 10.0 years among those in the highest quintile.  The median number of years of schooling is highest among those who do not belong to scheduled castes, scheduled tribes, and other backward classes (7.0 years for females and 8.5 years for males). The median number of years of schooling is lower among Muslims than for other specific religious groups (4.3 years for females and 5.4 years for males).  The percentage of the household population with no schooling is higher in rural areas than urban areas (33% versus 17% for females and 16% versus 8% for males). 2.10.2 Preschool attendance Preschool attendance Children age 2 to 4 years attending pre-primary education, such as at an anganwadi centre (Integrated Child Development Service), improves school readiness by providing quality learning through interactive play methods with qualified instructors. Sample: De facto household population age 2 to 4 years Attending pre-primary education, such as at an anganwadi centre, improves children’s school readiness. Also, parents or guardians can go to work at ease if children are enrolled in pre-primary education. Forty percent of both boys and girls age 2-4 years attend preschool. There is no difference in preschool attendance among children in nuclear households and non-nuclear households (40% each). Preschool attendance is the lowest among children in households with household head belonging to other religions (33%) and Muslim religion (34%). Preschool attendance is lower among children belonging to scheduled caste and other backward classes (38% each), compared with children from any other caste/tribe group. Preschool attendance is higher in households with 3 to 5 members (43%) than in households with 1-2 members (39%) and household with 6 or more members (38%). Overall, rural households (39%) show lower preschool attendance than urban households (44%) (Table 2.22). Preschool attendance is highest in Andaman and Nicobar Islands (89%), followed by Andhra Pradesh (75%) and Sikkim (74%) (Table 2.23). 2.10.3 School Attendance Net attendance ratio (NAR) Percentage of the school-age population that attends primary or secondary school. Sample: Children age 6-10 for primary school NAR and children age 11-17 for secondary school NAR Gross attendance ratio (GAR) The total number of children attending primary school divided by the official primary school age population and the total number of children attending secondary school divided by the official secondary school age population. Sample: Children at the official primary school age for primary school GAR and children at the official secondary school age for secondary school GAR Eighty-seven percent of children age 6-17 attend school (88% of males and 87% of females) (Table 2.26). Almost all (95%) males and females age 6-10 attend school. This percentage decreases to 91 percent for children age 11-14 and then drops further to 70 percent for children age 15-17. There is almost no difference in school attendance by males (94%) and females (93%) at age 6-14, but males are more likely than females to attend school at age 15-17 (72% versus 68%). Urban- rural differentials in school attendance are minimal at age 6-10, but widen at older ages (Figure 2.7). Eighty-three percent of girls and 84 percent of boys age 6-10 attend primary school (Table 2.27). The net attendance ratio (NAR) drops in secondary school: only 70 percent of girls and 72 percent of boys age 11-17 attend secondary school. The gross attendance ratio (GAR) is 92 percent at the primary school level and 82 percent at the secondary school level. These figures indicate that a number of children outside the official school age population for that level are attending primary school, and not all those who should be are attending secondary school (Table 2.27). 96 96 95 94 93 94 91 89 76 79 70 64 AGE 6-10, URBAN Male Female AGE 6-10, RURAL Male Female AGE 11-14, URBAN Male Female AGE 11-14, RURAL Male Female AGE 15-17, URBAN Male Female AGE 15-17, RURAL Male Female Figure 2.7 School Attendance by Age, Sex, and Residence Percentage of children age 6-17 years attending school 24 Gender parity index (GPI) The ratio of female to male children attending primary school and the ratio of female to male children attending secondary school. The index reflects the magnitude of the gender gap. Sample: Children attending primary school and children attending secondary school A gender parity index (GPI) of 1 indicates parity or equality between the school participation ratios for males and females. A GPI lower than 1 indicates a gender disparity in favour of males, with a higher proportion of males than females attending that level of schooling. A GPI higher than 1 indicates a gender disparity in favour of females. The GPI for the NAR is 0.99 at the primary school level and 0.97 at the secondary school level. This indicates that there is relatively little difference in overall school attendance by school-age girls and boys at either the primary or secondary school level. The GPI for the GAR is also slightly less than 1, which indicates that male children outside of the official school age population are only slightly more likely to attend school than their female counterparts; the GPIs for the GAR are almost the same at the primary school level (0.98) and at the secondary school level (.97). Patterns by background characteristics  At the primary school level, there is no difference in the NAR between urban and rural areas (83% each). However, at the secondary school level, the NAR is higher in urban areas than in rural areas (76% versus 70%).  The NARs increase with household wealth at the secondary school level. Attendance in the lowest wealth quintile is 57 percent for girls and 59 percent for boys, compared with 83 percent for girls and 84 percent for boys in the highest wealth quintile.  At the primary school level, there is a slight difference in the GAR between urban and rural areas (90% and 92%, respectively). However, at the secondary school level, the GAR is higher in urban areas than in rural areas (87% versus 80%).  The GARs increase with household wealth at the secondary school level. Attendance in the lowest wealth quintile is 66 percent for girls and 68 percent for boys, compared with 95 percent for girls and 96 percent for boys in the highest wealth quintile.  There is not much difference by caste/tribe in the NAR and GAR at of the primary school level, but at the secondary school level, children belonging to scheduled tribes have the lowest NARs and GARs. 2.11 DISABILITY Disability All usual household members who have any disability in specified domains such as hearing, speech, visual, mental, locomotor, and others. Sample:1) All de jure household population. 2) De jure household population age 15 years and over having any form of disability. The respondent to the Household Questionnaire provided information for all usual household members on whether or not they have any disability in specified domains. The domains of disability are hearing, speech, visual, mental, locomotor, and others. Just 1 percent of the de jure household population has any disability. The most prominent type of disability is locomotor (0.4%). Men are slightly more likely than women to have any disability (1.2% of men compared with 0.8% of women). The proportion of household members who have any disability rises with increasing age. For instance, 1.2 percent of the household members age 50 and above were reported to have any disability, compared with 0.3 percent of the youngest age group (Table 2.29). Men are slightly more likely than women to have any disability at age 15 years and above (1.4% of men compared with 0.9% of women). The rural population (1.2%) is slightly more likely to have any type of disability than the urban population (0.9%) (Table 2.30). Any type of disability is highest in Lakshadweep (1.9%), followed by Tamil Nadu (1.5%) and Punjab (1.4%) (Table 2.31). 2.12 USE OF TOBACCO AND ALCOHOL Tobacco Household population age 15 years and over who currently use any form of tobacco, such as cigar, pipe, hookah, gutkha / paan masala with tobacco, khaini, paan with tobacco, other chewing tobacco and snuff. Sample: De facto household population age 15 years and over. Alcohol Household population age 15 years and over who currently drink any form of alcohol. Sample: De facto household population age 15 years and over. Thirty-eight percent of men and 9 percent of women age 15 and over currently use any tobacco products. Among men as well as women, the use of tobacco is higher in rural areas (43% for men and 11% for women) than in urban areas (29% for men and 6% for women). Nearly three-fifths of men (58%) and 15 percent of women with no schooling or less than 5 years of schooling use tobacco. Tobacco use shows a steady and substantial decrease with increasing levels of education among both men and women. However, eighteen percent of men with 12 or more years of schooling use tobacco. There is an equally clear and continual decrease in tobacco use with increasing wealth quintiles. Over one-fifth of men (21%) in the highest wealth quintile use tobacco, in comparison with 58 percent of men in the lowest wealth quintile. Seventeen percent of women in the lowest wealth quintile use tobacco. Women (19%) and men (51%) belonging to scheduled tribes are more likely to use tobacco than those from any other caste/tribe groups (Table 2.35). Tobacco use among men age 15 and over is highest in Mizoram (73%), followed by Andaman & Nicobar Islands (59%) and Manipur (58%). Tobacco use among women is highest in Mizoram (62%), Tripura (51%), and Manipur (43%) (Table 2.36). Only 1 percent of women drink alcohol, compared with 19 percent of men. Drinking alcohol is more common among women from scheduled tribes (6%) than from any other caste/tribe groups. Among men, alcohol use is higher among those belonging to other religions (47%), those with no schooling (30%), scheduled tribes (33%), and those age 35-49 (27%) (Table 2.33). Alcohol use among women age 15 and over is highest in Arunachal Pradesh (24%) and Sikkim (16%). Alcohol use among men is highest in Arunachal Pradesh (53%) and Telangana (43%), and is the lowest in Lakshadweep (0.4%) (Table 2.34). 25 Gender parity index (GPI) The ratio of female to male children attending primary school and the ratio of female to male children attending secondary school. The index reflects the magnitude of the gender gap. Sample: Children attending primary school and children attending secondary school A gender parity index (GPI) of 1 indicates parity or equality between the school participation ratios for males and females. A GPI lower than 1 indicates a gender disparity in favour of males, with a higher proportion of males than females attending that level of schooling. A GPI higher than 1 indicates a gender disparity in favour of females. The GPI for the NAR is 0.99 at the primary school level and 0.97 at the secondary school level. This indicates that there is relatively little difference in overall school attendance by school-age girls and boys at either the primary or secondary school level. The GPI for the GAR is also slightly less than 1, which indicates that male children outside of the official school age population are only slightly more likely to attend school than their female counterparts; the GPIs for the GAR are almost the same at the primary school level (0.98) and at the secondary school level (.97). Patterns by background characteristics  At the primary school level, there is no difference in the NAR between urban and rural areas (83% each). However, at the secondary school level, the NAR is higher in urban areas than in rural areas (76% versus 70%).  The NARs increase with household wealth at the secondary school level. Attendance in the lowest wealth quintile is 57 percent for girls and 59 percent for boys, compared with 83 percent for girls and 84 percent for boys in the highest wealth quintile.  At the primary school level, there is a slight difference in the GAR between urban and rural areas (90% and 92%, respectively). However, at the secondary school level, the GAR is higher in urban areas than in rural areas (87% versus 80%).  The GARs increase with household wealth at the secondary school level. Attendance in the lowest wealth quintile is 66 percent for girls and 68 percent for boys, compared with 95 percent for girls and 96 percent for boys in the highest wealth quintile.  There is not much difference by caste/tribe in the NAR and GAR at of the primary school level, but at the secondary school level, children belonging to scheduled tribes have the lowest NARs and GARs. 2.11 DISABILITY Disability All usual household members who have any disability in specified domains such as hearing, speech, visual, mental, locomotor, and others. Sample:1) All de jure household population. 2) De jure household population age 15 years and over having any form of disability. The respondent to the Household Questionnaire provided information for all usual household members on whether or not they have any disability in specified domains. The domains of disability are hearing, speech, visual, mental, locomotor, and others. Just 1 percent of the de jure household population has any disability. The most prominent type of disability is locomotor (0.4%). Men are slightly more likely than women to have any disability (1.2% of men compared with 0.8% of women). The proportion of household members who have any disability rises with increasing age. For instance, 1.2 percent of the household members age 50 and above were reported to have any disability, compared with 0.3 percent of the youngest age group (Table 2.29). Men are slightly more likely than women to have any disability at age 15 years and above (1.4% of men compared with 0.9% of women). The rural population (1.2%) is slightly more likely to have any type of disability than the urban population (0.9%) (Table 2.30). Any type of disability is highest in Lakshadweep (1.9%), followed by Tamil Nadu (1.5%) and Punjab (1.4%) (Table 2.31). 2.12 USE OF TOBACCO AND ALCOHOL Tobacco Household population age 15 years and over who currently use any form of tobacco, such as cigar, pipe, hookah, gutkha / paan masala with tobacco, khaini, paan with tobacco, other chewing tobacco and snuff. Sample: De facto household population age 15 years and over. Alcohol Household population age 15 years and over who currently drink any form of alcohol. Sample: De facto household population age 15 years and over. Thirty-eight percent of men and 9 percent of women age 15 and over currently use any tobacco products. Among men as well as women, the use of tobacco is higher in rural areas (43% for men and 11% for women) than in urban areas (29% for men and 6% for women). Nearly three-fifths of men (58%) and 15 percent of women with no schooling or less than 5 years of schooling use tobacco. Tobacco use shows a steady and substantial decrease with increasing levels of education among both men and women. However, eighteen percent of men with 12 or more years of schooling use tobacco. There is an equally clear and continual decrease in tobacco use with increasing wealth quintiles. Over one-fifth of men (21%) in the highest wealth quintile use tobacco, in comparison with 58 percent of men in the lowest wealth quintile. Seventeen percent of women in the lowest wealth quintile use tobacco. Women (19%) and men (51%) belonging to scheduled tribes are more likely to use tobacco than those from any other caste/tribe groups (Table 2.35). Tobacco use among men age 15 and over is highest in Mizoram (73%), followed by Andaman & Nicobar Islands (59%) and Manipur (58%). Tobacco use among women is highest in Mizoram (62%), Tripura (51%), and Manipur (43%) (Table 2.36). Only 1 percent of women drink alcohol, compared with 19 percent of men. Drinking alcohol is more common among women from scheduled tribes (6%) than from any other caste/tribe groups. Among men, alcohol use is higher among those belonging to other religions (47%), those with no schooling (30%), scheduled tribes (33%), and those age 35-49 (27%) (Table 2.33). Alcohol use among women age 15 and over is highest in Arunachal Pradesh (24%) and Sikkim (16%). Alcohol use among men is highest in Arunachal Pradesh (53%) and Telangana (43%), and is the lowest in Lakshadweep (0.4%) (Table 2.34). 26 The percentage of men age 15 years and above who use any kind of tobacco exceeds 40 percent in most parts of Madhya Pradesh, Uttar Pradesh, Odisha, Jharkhand, West Bengal, Bihar, Chhattisgarh, Northeastern states, northern part of Maharashtra, western Gujarat, and southern Rajasthan. Use of tobacco is also high (30–40%) in Ladakh, Uttarakhand, most parts of Maharashtra, Karnataka, northern parts of Rajasthan, and northwestern Gujarat. Lower prevalence of tobacco use (below 30 percent) is mostly observed in Punjab and southern states, except in central parts of Karnataka (Map 2.1). A higher proportion (40% and above) of alcohol consumption among men age 15 years and over is found in Telangana, Arunachal Pradesh, upper Brahmaputra region of Assam, a few districts in Jharkhand and Bastar region of Chhattisgarh, and the Chhota Nagpur region of Jharkhand and Odisha. A 30-40 percent level of alcohol consumption is found in the districts of Chhattisgarh, Uttarakhand, Manipur, Meghalaya, Tripura, and a few districts of Odisha. A lower level (below 30%) of alcohol consumption is observed in the remaining parts of the states in India (Map 2.2). 27 The percentage of men age 15 years and above who use any kind of tobacco exceeds 40 percent in most parts of Madhya Pradesh, Uttar Pradesh, Odisha, Jharkhand, West Bengal, Bihar, Chhattisgarh, Northeastern states, northern part of Maharashtra, western Gujarat, and southern Rajasthan. Use of tobacco is also high (30–40%) in Ladakh, Uttarakhand, most parts of Maharashtra, Karnataka, northern parts of Rajasthan, and northwestern Gujarat. Lower prevalence of tobacco use (below 30 percent) is mostly observed in Punjab and southern states, except in central parts of Karnataka (Map 2.1). A higher proportion (40% and above) of alcohol consumption among men age 15 years and over is found in Telangana, Arunachal Pradesh, upper Brahmaputra region of Assam, a few districts in Jharkhand and Bastar region of Chhattisgarh, and the Chhota Nagpur region of Jharkhand and Odisha. A 30-40 percent level of alcohol consumption is found in the districts of Chhattisgarh, Uttarakhand, Manipur, Meghalaya, Tripura, and a few districts of Odisha. A lower level (below 30%) of alcohol consumption is observed in the remaining parts of the states in India (Map 2.2). 28 2.13 POSSESSION OF MOSQUITO NETS Ownership of insecticide-treated nets Households that have at least one insecticide-treated net (ITN). An ITN is defined as a factory-treated net that does not require any further treatment. Sample: Households Full household ITN coverage Percentage of households with at least one ITN for every two people. Sample: Households An important strategy in the control of malaria and kala-azar is prevention through use of mosquito nets to protect themselves from mosquito bites. More than one-third of households (36%) in India have at least one mosquito net, while 8 percent have at least one Insecticide Treated Mosquito Net (ITN). On average, there are 0.2 ITNs per household. Four percent of households have achieved full household ITN coverage, meaning a household has at least one ITN for every two persons who slept in the household the night before the survey. Twenty percent of households had at least one mosquito net of any type for every two persons who slept in the household last night. The proportion of households having at least one ITN for every two persons who slept in the household last night is highest in Nagaland (43%), Arunachal Pradesh (35%), and Mizoram (26%) (Table 2.32). Patterns by background characteristics  Seven percent of households in the lowest wealth quintile have full household ITN coverage, compared with two percent of households in the highest wealth quintile.  Urban households are less likely (2%) than rural households (5%) to have full household ITN coverage. LIST OF TABLES For more information on the household population and housing characteristics, see the following tables: Tables Table 2.1 Household drinking water Table 2.2 Household sanitation facilities Table 2.3 Sanitation facility type by wealth quintile and state/union territory Table 2.4 Access to a toilet facility Table 2.5 Access to a toilet facility by state/union territory Table 2.6 Housing characteristics Table 2.7 Housing characteristics by state/union territory Table 2.8 Wealth quintiles by state/union territory Table 2.9 Religion and caste/tribe by wealth quintiles Table 2.10 Religion and caste/tribe of household head by state/union territory Table 2.11 Household possessions Table 2.12 Household ownership of agricultural land, house, and farm animals Table 2.13 Hand washing Table 2.14 Household composition Table 2.15 Household population by age, residence, sex, and possession of an Aadhaar card Table 2.16 Birth registration of children Table 2.17 Birth registration of children by state/union territory Table 2.18 Death registration Table 2.19 Death registration by state/union territory 29 2.13 POSSESSION OF MOSQUITO NETS Ownership of insecticide-treated nets Households that have at least one insecticide-treated net (ITN). An ITN is defined as a factory-treated net that does not require any further treatment. Sample: Households Full household ITN coverage Percentage of households with at least one ITN for every two people. Sample: Households An important strategy in the control of malaria and kala-azar is prevention through use of mosquito nets to protect themselves from mosquito bites. More than one-third of households (36%) in India have at least one mosquito net, while 8 percent have at least one Insecticide Treated Mosquito Net (ITN). On average, there are 0.2 ITNs per household. Four percent of households have achieved full household ITN coverage, meaning a household has at least one ITN for every two persons who slept in the household the night before the survey. Twenty percent of households had at least one mosquito net of any type for every two persons who slept in the household last night. The proportion of households having at least one ITN for every two persons who slept in the household last night is highest in Nagaland (43%), Arunachal Pradesh (35%), and Mizoram (26%) (Table 2.32). Patterns by background characteristics  Seven percent of households in the lowest wealth quintile have full household ITN coverage, compared with two percent of households in the highest wealth quintile.  Urban households are less likely (2%) than rural households (5%) to have full household ITN coverage. LIST OF TABLES For more information on the household population and housing characteristics, see the following tables: Tables Table 2.1 Household drinking water Table 2.2 Household sanitation facilities Table 2.3 Sanitation facility type by wealth quintile and state/union territory Table 2.4 Access to a toilet facility Table 2.5 Access to a toilet facility by state/union territory Table 2.6 Housing characteristics Table 2.7 Housing characteristics by state/union territory Table 2.8 Wealth quintiles by state/union territory Table 2.9 Religion and caste/tribe by wealth quintiles Table 2.10 Religion and caste/tribe of household head by state/union territory Table 2.11 Household possessions Table 2.12 Household ownership of agricultural land, house, and farm animals Table 2.13 Hand washing Table 2.14 Household composition Table 2.15 Household population by age, residence, sex, and possession of an Aadhaar card Table 2.16 Birth registration of children Table 2.17 Birth registration of children by state/union territory Table 2.18 Death registration Table 2.19 Death registration by state/union territory 30 Tables Table 2.20 Children's living arrangements and orphanhood Table 2.21 Children's living arrangements and orphanhood by state/union territory Table 2.22 Preschool attendance Table 2.23 Preschool attendance by state/union territory Table 2.24 Educational attainment of household population Table 2.25 Educational attainment of household population by state/union territory Table 2.26 School attendance by state/union territory Table 2.27 School attendance ratios Table 2.28 Reasons for children currently not attending school Table 2.29 Disability Table 2.30 Prevalence of any disability Table 2.31 Prevalence of any disability by state/union territory Table 2.32 Household possession of mosquito nets Table 2.33 Use of alcohol by the population age 15 and over Table 2.34 Use of alcohol by the population age 15 and over by state/union territory Table 2.35 Use of tobacco by the population age 15 and over Table 2.36 Use of tobacco by the population age 15 and over by state/union territory Table 2.1 Household drinking water Percent distribution of urban, rural, and total households and de jure population by source of drinking water, time to collect drinking water, and person who usually collects drinking water, percentage of urban, rural, and total households and de jure population by treatment of drinking water, and percentage of households and de jure population with basic drinking water service and limited drinking water service, India, 2019-21 Characteristic Urban Rural Total De jure population Source of drinking water Improved source 98.7 94.5 95.9 95.9 Piped into dwelling/yard/ plot 53.6 22.6 32.9 32.3 Piped to neighbour 1.7 1.6 1.6 1.5 Public tap/standpipe 12.2 13.9 13.3 12.3 Tube well or borehole 16.1 45.9 36.0 38.6 Protected dug well 3.3 3.5 3.4 3.2 Protected spring 0.2 0.4 0.4 0.4 Rain water 0.1 0.3 0.2 0.3 Tanker truck/cart with small tank 1.7 1.3 1.5 1.5 Bottled water 7.0 2.2 3.8 3.4 Community RO plant 2.7 2.8 2.7 2.4 Unimproved source 1.0 5.1 3.7 3.7 Unprotected dug well 0.6 3.8 2.7 2.8 Unprotected spring 0.1 0.4 0.3 0.3 Surface water 0.4 0.9 0.7 0.7 Other 0.3 0.4 0.4 0.4 Total 100.0 100.0 100.0 100.0 Time to collect drinking water (round trip) Water on premises/delivered to dwelling 85.6 68.0 73.9 75.1 Thirty minutes or less 13.9 30.4 24.9 23.6 More than 30 minutes 0.4 1.6 1.2 1.2 Don't know 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 Number 211,271 425,428 636,699 2,780,724 Continued… 31 Tables Table 2.20 Children's living arrangements and orphanhood Table 2.21 Children's living arrangements and orphanhood by state/union territory Table 2.22 Preschool attendance Table 2.23 Preschool attendance by state/union territory Table 2.24 Educational attainment of household population Table 2.25 Educational attainment of household population by state/union territory Table 2.26 School attendance by state/union territory Table 2.27 School attendance ratios Table 2.28 Reasons for children currently not attending school Table 2.29 Disability Table 2.30 Prevalence of any disability Table 2.31 Prevalence of any disability by state/union territory Table 2.32 Household possession of mosquito nets Table 2.33 Use of alcohol by the population age 15 and over Table 2.34 Use of alcohol by the population age 15 and over by state/union territory Table 2.35 Use of tobacco by the population age 15 and over Table 2.36 Use of tobacco by the population age 15 and over by state/union territory Table 2.1 Household drinking water Percent distribution of urban, rural, and total households and de jure population by source of drinking water, time to collect drinking water, and person who usually collects drinking water, percentage of urban, rural, and total households and de jure population by treatment of drinking water, and percentage of households and de jure population with basic drinking water service and limited drinking water service, India, 2019-21 Characteristic Urban Rural Total De jure population Source of drinking water Improved source 98.7 94.5 95.9 95.9 Piped into dwelling/yard/ plot 53.6 22.6 32.9 32.3 Piped to neighbour 1.7 1.6 1.6 1.5 Public tap/standpipe 12.2 13.9 13.3 12.3 Tube well or borehole 16.1 45.9 36.0 38.6 Protected dug well 3.3 3.5 3.4 3.2 Protected spring 0.2 0.4 0.4 0.4 Rain water 0.1 0.3 0.2 0.3 Tanker truck/cart with small tank 1.7 1.3 1.5 1.5 Bottled water 7.0 2.2 3.8 3.4 Community RO plant 2.7 2.8 2.7 2.4 Unimproved source 1.0 5.1 3.7 3.7 Unprotected dug well 0.6 3.8 2.7 2.8 Unprotected spring 0.1 0.4 0.3 0.3 Surface water 0.4 0.9 0.7 0.7 Other 0.3 0.4 0.4 0.4 Total 100.0 100.0 100.0 100.0 Time to collect drinking water (round trip) Water on premises/delivered to dwelling 85.6 68.0 73.9 75.1 Thirty minutes or less 13.9 30.4 24.9 23.6 More than 30 minutes 0.4 1.6 1.2 1.2 Don't know 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 Number 211,271 425,428 636,699 2,780,724 Continued… 32 Table 2.1 Household drinking water—Continued Percent distribution of urban, rural, and total households and de jure population by source of drinking water, time to collect drinking water, and person who usually collects drinking water, percentage of urban, rural, and total households and de jure population by treatment of drinking water, and percentage of households and de jure population with basic drinking water service and limited drinking water service, India, 2019-21 Characteristic Urban Rural Total De jure population Person who usually collects drinking water1 Adult female 15 and over years 56.3 73.6 70.5 71.3 Adult male 15 and over years 39.3 21.2 24.5 23.0 Female child under age 15 years 1.7 3.1 2.8 3.4 Male child under age 15 years 1.4 1.1 1.1 1.2 Other 1.4 1.1 1.1 1.1 Total 100.0 100.0 100.0 100.0 Number 30,383 136,053 166,436 693,246 Water treatment prior to drinking2 Boil 21.4 13.3 16.0 14.8 Use alum 1.7 1.3 1.4 1.4 Bleach/chlorine added 3.5 3.3 3.4 3.3 Strain through cloth 14.9 14.8 14.8 15.2 Ceramic, sand, or other filter 11.8 4.6 7.0 6.7 Use electronic purifier 12.8 2.0 5.6 5.4 Solar disinfection 0.1 0.0 0.1 0.1 Let it stand and settle 0.6 0.8 0.8 0.8 Other 1.8 1.5 1.6 1.7 No treatment 43.5 65.7 58.3 59.3 Percentage using an appropriate treatment method3 43.8 20.5 28.2 26.8 Percentage with basic drinking water service 4 98.2 93.2 94.9 94.8 Percentage with limited drinking water service 5 0.4 1.2 0.9 1.0 Number of households/population 211,271 425,428 636,699 2,780,724 1 Excludes those who have source of water on premises or who have water delivered to the dwelling 2 Total may add to more than 100.0 because households may use more than one method of treatment 3 Appropriate water treatment methods are boiling, adding bleach/chlorine tablets, filtering, electronic purifying, and solar disinfection 4 Defined as drinking water from an improved source, provided either water is on the premises or round-trip collection time is 30 minutes or less. Includes safely managed drinking water, which is not shown separately. 5 Drinking water from an improved source, provided round-trip collection time is more than 30 minutes or is unknown. Table 2.2 Household sanitation facilities Percent distribution of households and de jure population by type of toilet facility, percentage of households and de jure population with basic sanitation services, and percentage with limited sanitation services, according to residence, India, 2019-21 Type of toilet/latrine facility Urban Rural Total De jure population Improved, not shared facility 80.7 63.6 69.3 70.2 Flush/pour flush to piped sewer system 22.8 2.7 9.3 9.0 Flush/pour flush to septic tank 47.4 36.2 39.9 40.1 Flush/pour flush to pit latrine 6.1 13.2 10.8 11.3 Flush/pour flush, don't know where 0.3 0.1 0.2 0.2 Ventilated improved pit (VIP) latrine/ biogas latrine 0.4 0.7 0.6 0.6 Pit latrine with slab 3.0 5.4 4.6 4.6 Twin pit, composting toilet 0.8 5.3 3.8 4.3 Shared facility1 10.5 7.4 8.4 7.6 Flush/pour flush to piped sewer system 2.8 0.2 1.1 1.0 Flush/pour flush to septic tank 5.8 4.0 4.6 4.2 Flush/pour flush to pit latrine 0.9 1.7 1.4 1.3 Flush/pour flush, don't know where 0.1 0.0 0.0 0.0 Ventilated improved pit (VIP) latrine/ biogas latrine 0.1 0.1 0.1 0.1 Pit latrine with slab 0.5 0.8 0.7 0.6 Twin pit, composting toilet 0.2 0.6 0.5 0.4 Unimproved 2.7 3.1 2.9 2.9 Flush/pour flush not to sewer/septic tank/pit latrine 1.4 0.6 0.9 0.8 Pit latrine without slab/open pit 0.5 1.4 1.1 1.1 Dry toilet 0.2 0.8 0.6 0.7 Other 0.5 0.2 0.3 0.3 Open defecation (No facility/bush/field) 6.1 25.9 19.4 19.3 Total 100.0 100.0 100.0 100.0 Number of households/population 211,271 425,428 636,699 2,780,724 Location of toilet facility In own dwelling 68.6 36.8 49.1 49.4 In own yard/plot 28.1 59.1 47.1 47.0 Elsewhere 3.2 4.1 3.8 3.7 Total 100.0 100.0 100.0 100.0 Number of households/population with a toilet/latrine facility 198,355 315,052 513,407 2,243,564 Percentage with basic sanitation service2 80.7 63.6 69.3 70.2 Percentage with limited sanitation service3 10.5 7.4 8.4 7.6 Number of households/population 211,271 425,428 636,699 2,780,724 1 Facilities that would be considered improved if they were not shared by two or more households 2 Defined as use of improved facilities that are not shared with other households 3 Defined as use of improved facilities shared by 2 or more households. 33 Table 2.1 Household drin

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