India - Demographic and Health Survey - 2000

Publication date: 2000

����� ���� �� �� � �� �� � � � � ���� ����G46������������ ���������G46�� �� � � �� � � ��G46 � � ��� �� � � ��� �� � � � � � ��� G46 � � � � �� ���� � ������� � � ��� ��� ���� � ���������� ������������ ��������� World Summit for Children Indicators: India, 1998–99 BASIC INDICATORS Childhood mortality Childhood malnutrition Clean water supply Sanitary excreta disposal Basic education Children in especially difficult situations Infant mortality rate Under-five mortality rate Percent stunted (children 0–35 months) Percent wasted (children 0–35 months) Percent underweight (children 0–35 months) Percent of households within 15 minutes of a safe water supply1 Percent of households with flush toilets Percent of women age 15–49 with completed primary education Percent of men age 15–49 with completed primary education Percent of girls age 6–12 attending school Percent of boys age 6–12 attending school Percent of women age 15–49 who are literate Percent of children age 0–14 who live in single adult households 68 per 1,000 95 per 1,000 45.5 15.5 47.0 62.3 24.0 44.4 68.9 76.5 84.7 50.8 2.3 SUPPORTING INDICATORS Birth spacing Safe motherhood Family planning Percent of births within 24 months of a previous birth Percent of births with medical antenatal care Percent of births with antenatal care in first trimester Percent of births with medical assistance at delivery Percent of births in a medical facility Percent of births at high risk Contraceptive prevalence rate (any method, currently married women) Percent of currently married women with an unmet need for family planning Percent of currently married women with an unmet need for family planning to avoid a high-risk birth 28.3 65.2 33.0 42.3 33.6 50.7 48.2 15.8 11.2 Maternal nutrition Low birth weight Breastfeeding Iodized salt intake Percent of mothers with low BMI Percent of births with low birth weight (of those reporting a numeric weight) Percent of children under 4 months who are exclusively breastfed Percent of households that use iodized salt 35.8 22.7 55.2 49.3 Vaccinations Diarrhoea control Acute respiratory infection Percent of children whose mothers received tetanus toxoid vaccinations during pregnancy Percent of children 12–23 months with measles vaccination Percent of children 12–23 months fully vaccinated Percent of children with diarrhoea in the preceding 2 weeks who received ORS, sugar-salt-water solution, or gruel Percent of children with acute respiratory infection in the preceding 2 weeks seen by medical personnel 75.0 50.7 42.0 35.5 64.0 1Water from pipes, handpump, covered well, or tanker truck NATIONAL FAMILY HEALTH SURVEY (NFHS-2) 1998–99 INDIA International Institute for Population Sciences Mumbai, India ORC MACRO Calverton, Maryland, USA October 2000 Suggested citation: International Institute for Population Sciences (IIPS) and ORC Macro. 2000. National Family Health Survey (NFHS-2), 1998–99: India. Mumbai: IIPS. For additional information about the National Family Health Survey (NFHS-2) please contact: International Institute for Population Sciences Govandi Station Road, Deonar, Mumbai-400 088 Telephone: 5564883, 5563254, 5563255, 5563256 Fax: 5563257 E-mail: iipsnfhs@vsnl.com Website: http://www.nfhsindia.org CONTRIBUTORS T. K. Roy Fred Arnold Sumati Kulkarni Sunita Kishor Kamla Gupta Vinod Mishra Parveen Nangia Robert D. Retherford Arvind Pandey Sushil Kumar CONTENTS Page Tables . v Figures. xi Preface.xiii Acknowledgements . xv Fact Sheet .xviii Summary of Findings . xix CHAPTER 1 INTRODUCTION 1.1 Background of the Survey. 1 1.2 Basic Demographic Features. 1 1.3 Economic Development .2 1.4 Performance of Social Sectors and Demographic Change.3 1.5 Population Policies and Programmes. 4 1.6 Questionnaires. 6 1.7 Sample Design and Implementation . 8 Sample Size and Reporting Domains. 8 Sample Design. 8 Sample Selection in Rural Areas. 9 Sample Selection in Urban Areas. 10 Sample Weights. 10 Sample Implementation. 11 1.8 Recruitment, Training, and Fieldwork . 11 1.9 Data Processing . 14 CHAPTER 2 BACKGROUND CHARACTERISTICS OF HOUSEHOLDS 2.1 Age-Sex Distribution of the Household Population. 15 2.2 Marital Status . 18 2.3 Household Composition. 22 2.4 Educational Attainment. 25 2.5 Housing Characteristics. 35 2.6 Lifestyle Indicators. 41 2.7 Availability of Facilities and Services to the Rural Population . 46 CHAPTER 3 BACKGROUND CHARACTERISTICS OF RESPONDENTS 3.1 Background Characteristics. 49 3.2 Educational Level. 52 3.3 Age at First Marriage . 54 3.4 Exposure to Mass Media . 57 3.5 Women’s Employment. 61 3.6 Women’s Autonomy . 64 3.7 Women’s Educational Aspirations for Their Children . 69 3.8 Domestic Violence: Attitudes and Experience. 71 ii Page CHAPTER 4 FERTILITY AND FERTILITY PREFERENCES 4.1 Age at First Cohabitation . 81 4.2 Fertility Levels . 83 4.3 Fertility Differentials and Trends. 90 4.4 Pregnancy Outcomes. 95 4.5 Children Ever Born and Living. 96 4.6 Birth Order . 98 4.7 Birth Intervals. 98 4.8 Age at First and Last Birth . 103 4.9 Postpartum Amenorrhoea, Abstinence, Insusceptibility, and Menopause. 107 4.10 Desire for More Children . 111 4.11 Ideal Number of Children . 115 4.12 Sex Preference for Children . 119 4.13 Fertility Planning. 122 CHAPTER 5 FAMILY PLANNING 5.1 Knowledge of Family Planning Methods. 127 Interstate Variations in Knowledge. 129 5.2 Contraceptive Use . 129 Ever Use of Family Planning Methods . 129 Current Use of Family Planning Methods. 131 Socioeconomic Differentials in Current Use of Family Planning Methods. 134 Interstate Variations in Current Use of Family Planning Methods. 139 Number of Living Children at First Use of Contraception . 144 Problems with Current Method. 144 5.3 Sterilization . 146 Timing of Sterilization . 146 Interstate Variations in Timing of Sterilization. 148 Methods Used before Sterilization. 149 5.4 Sources of Contraceptive Methods . 149 Interstate Variations in the Role of the Public Sector . 154 5.5 Reasons for Discontinuation/Non-Use of Contraception. 158 5.6 Future Intentions Regarding Contraceptive Use . 158 Interstate Variations in the Intentions to Use Contraception in the Future . 161 Reasons for Not Intending to Use Contraception. 162 Preferred Future Method of Contraception . 163 5.7 Exposure to Family Planning Messages. 165 5.8 Discussion of Family Planning . 167 Interstate Variations in Exposure to Family Planning Messages and Discussions about Family Planning . 167 5.9 Need for Family Planning . 169 Interstate Variations in Unmet Need. 173 iii Page CHAPTER 6 MORTALITY, MORBIDITY, AND IMMUNIZATION 6.1 Crude Death Rates and Age-Specific Death Rates . 178 6.2 Infant and Child Mortality. 181 Assessment of Data Quality . 181 Levels, Trends, and Differentials in Infant and Child Mortality. 183 Socioeconomic Differentials in Infant and Child Mortality. 185 Demographic Differentials in Infant and Child Mortality . 188 6.3 Maternal Mortality . 195 6.4 Morbidity. 196 Asthma . 198 Tuberculosis . 198 Jaundice. 198 Malaria . 199 Comparisons by State. 199 6.5 Child Immunization . 202 6.6 Vitamin A Supplementation. 213 6.7 Child Morbidity and Treatment. 216 Acute Respiratory Infection . 216 Fever. 218 Diarrhoea. 220 6.8 HIV/AIDS . 230 Knowledge of AIDS. 230 Source of Knowledge about AIDS. 233 Knowledge of Ways to Avoid AIDS. 235 CHAPTER 7 NUTRITION AND THE PREVALENCE OF ANAEMIA 7.1 Women’s Food Consumption . 241 7.2 Nutritional Status of Women . 243 7.3 Anaemia Among Women. 247 7.4 Infant Feeding Practices . 251 7.5 Nutritional Status of Children . 263 7.6 Anaemia Among Children . 271 7.7 Iodization of Salt . 274 CHAPTER 8 MATERNAL AND REPRODUCTIVE HEALTH 8.1 Antenatal Problems and Care. 280 Problems During Pregnancy. 281 Antenatal Check-Ups . 281 Reasons for Not Receiving Antenatal Check-Ups . 285 Number and Timing of Antenatal Check-Ups . 285 Components of Antenatal Check-Ups. 287 Tetanus Toxoid Vaccination . 289 Iron and Folic Acid Supplementation . 291 Antenatal Care Indicators by State. 292 iv Page 8.2 Delivery Care . 294 Place of Delivery. 294 Assistance During Delivery . 297 Delivery Characteristics . 299 8.3 Postnatal Care. 300 Postpartum Complications . 303 8.4 Summary of Maternal Care Indicators by State . 304 8.5 Reproductive Health Problems. 307 Reproductive Health Problems by State. 311 CHAPTER 9 QUALITY OF CARE 9.1 Source of Health Care for Households. 315 9.2 Contacts at Home with Health and Family Planning Workers . 316 9.3 Quality of Home Visits . 317 9.4 Matters Discussed during Home Visits or Visits to Health Facilities. 320 9.5 Quality of Services Received at the Most Recent Visit to a Health Facility . 322 9.6 Family Planning Information and Advice Received . 325 9.7 Person Motivating Users of a Modern Contraceptive Method . 326 9.8 Quality of Care of Family Planning Services. 327 REFERENCES . 333 APPENDICES Appendix A Organizations Involved in NFHS-2 Fieldwork . 341 Appendix B Sample Characteristics for States . 343 Appendix C Estimates of Sampling Errors . 347 Appendix D Data Quality Tables . 357 Appendix E NFHS-2 Survey Staff . 365 Appendix F Survey Instruments. 369 NFHS-2 FACT SHEET - STATES . 439 TABLES Page Table 1.1 Number of households and women interviewed by state. 12 Table 2.1 Household population by age and sex. 16 Table 2.2 Population by age and sex from the SRS and NFHS-2. 17 Table 2.3 Marital status of the household population . 19 Table 2.4 Singulate mean age at marriage by state . 21 Table 2.5 Household characteristics. 23 Table 2.6 Religion and caste/tribe of household head by state . 24 Table 2.7 Educational level of the household population . 26 Table 2.8 Educational level of the household population by state. 30 Table 2.9 School attendance by state . 33 Table 2.10 Reasons for children not attending school . 35 Table 2.11 Housing characteristics . 36 Table 2.12 Housing characteristics by state . 38 Table 2.13 Household ownership of agricultural land, house, and livestock. 39 Table 2.14 Household ownership of durable goods and standard of living. 40 Table 2.15 Lifestyle indicators. 42 Table 2.16 Lifestyle indicators by state . 44 Table 2.17 Distance from the nearest health facility. 46 Table 2.18 Availability of facilities and services. 47 Table 3.1 Background characteristics of respondents. 50 Table 3.2 Respondent’s level of education by background characteristics. 53 Table 3.3 Respondent’s level of education by state . 55 Table 3.4 Age at first marriage. 56 Table 3.5 Age at first marriage by state . 57 Table 3.6 Exposure to mass media. 58 Table 3.7 Exposure to mass media by state . 60 Table 3.8 Employment . 63 Table 3.9 Work status of respondents by state. 65 Table 3.10 Household decisionmaking . 66 Table 3.11 Women’s autonomy . 67 Table 3.12 Women’s autonomy by state. 70 vi Page Table 3.13 Perceived educational needs of girls and boys. 72 Table 3.14 Reasons given for justifying a husband beating his wife. 73 Table 3.15 Women’s experience with beatings or physical mistreatment. 76 Table 3.16 Women’s experience with beatings or physical mistreatment by state. 79 Table 4.1 Age at first cohabitation with husband. 82 Table 4.2 Current fertility. 84 Table 4.3 Fertility by state. 87 Table 4.4 Fertility by background characteristics . 91 Table 4.5 Fertility trends . 93 Table 4.6 Fertility by marital duration . 94 Table 4.7 Outcome of pregnancy by state. 95 Table 4.8 Children ever born and living . 97 Table 4.9 Birth order . 99 Table 4.10 Birth order by state. 100 Table 4.11 Birth interval . 101 Table 4.12 Birth interval by state . 103 Table 4.13 Median age at first birth . 104 Table 4.14 Age at last birth . 105 Table 4.15 Median age at first and last birth by state . 106 Table 4.16 Postpartum amenorrhoea, abstinence, and insusceptibility. 108 Table 4.17 Menopause by state . 109 Table 4.18 Fertility preferences . 110 Table 4.19 Fertility preferences by state . 113 Table 4.20 Desire to have no more children by background characteristics. 114 Table 4.21 Ideal and actual number of children. 116 Table 4.22 Ideal number of children by background characteristics . 118 Table 4.23 Ideal number of children by state. 119 Table 4.24 Indicators of sex preference . 120 Table 4.25 Indicators of sex preference by state . 122 Table 4.26 Fertility planning. 124 Table 4.27 Wanted fertility rates. 125 Table 4.28 Wanted fertility rates by state . 126 vii Page Table 5.1 Knowledge of contraceptive methods. 128 Table 5.2 Knowledge of contraceptive methods by state. 130 Table 5.3 Ever use of contraception. 131 Table 5.4 Current use of contraception . 132 Table 5.5 Current use by background characteristics . 136 Table 5.6 Current use by religion and education . 139 Table 5.7 Current use by state. 140 Table 5.8 Number of living children at first use . 145 Table 5.9 Problems with current method . 146 Table 5.10 Timing of sterilization. 147 Table 5.11 Timing of sterilization by state . 148 Table 5.12 Methods used before sterilization by state . 150 Table 5.13 Source of modern contraceptive methods . 151 Table 5.14 Public sector as source of modern contraceptives by state . 155 Table 5.15 Reasons for discontinuation/non-use . 159 Table 5.16 Future use of contraception. 160 Table 5.17 Future use of contraception by state. 161 Table 5.18 Reasons for not intending to use contraception . 162 Table 5.19 Preferred method. 164 Table 5.20 Exposure to family planning messages . 166 Table 5.21 Discussion of family planning . 168 Table 5.22 Exposure to messages and discussion of family planning by state . 169 Table 5.23 Need for family planning services . 171 Table 5.24 Need for family planning services by state . 174 Table 6.1 Age-specific death rates and crude death rates . 179 Table 6.2 Crude death rates by state . 180 Table 6.3 Infant and child mortality. 184 Table 6.4 Infant and child mortality by background characteristics . 186 Table 6.5 Infant and child mortality by demographic characteristics . 189 Table 6.6 Infant and child mortality by state . 194 Table 6.7 Morbidity. 197 Table 6.8 Morbidity by state . 200 viii Page Table 6.9 Childhood vaccinations by source of information . 204 Table 6.10 Childhood vaccinations by background characteristics . 207 Table 6.11 Childhood vaccinations by state. 209 Table 6.12 Childhood vaccinations received by 12 months of age. 211 Table 6.13 Source of childhood vaccinations . 212 Table 6.14 Vitamin A supplementation for children. 214 Table 6.15 Vitamin A supplementation for children by state . 215 Table 6.16 Prevalence of acute respiratory infection, fever, and diarrhoea. 217 Table 6.17 Prevalence of acute respiratory infection, fever, and diarrhoea by state. 219 Table 6.18 Knowledge of diarrhoea care . 222 Table 6.19 Knowledge of diarrhoea care by state . 223 Table 6.20 Treatment of diarrhoea. 225 Table 6.21 Treatment of diarrhoea by state. 227 Table 6.22 Source of ORS packets. 228 Table 6.23 Feeding practices during diarrhoea by state. 229 Table 6.24 Source of knowledge about AIDS. 231 Table 6.25 Source of knowledge about AIDS by state . 234 Table 6.26 Knowledge about avoidance of AIDS. 236 Table 6.27 Knowledge about avoidance of AIDS by state . 239 Table 7.1 Women’s food consumption . 242 Table 7.2 Women’s food consumption by background characteristics . 242 Table 7.3 Women’s food consumption by state. 244 Table 7.4 Nutritional status of women . 245 Table 7.5 Nutritional status of women by state. 246 Table 7.6 Anaemia among women. 249 Table 7.7 Anaemia among women by state . 252 Table 7.8 Initiation of breastfeeding . 254 Table 7.9 Initiation of breastfeeding by state. 255 Table 7.10 Breastfeeding status by child’s age . 256 Table 7.11 Type of food received by children . 258 Table 7.12 Median duration of breastfeeding . 262 Table 7.13 Median duration of breastfeeding by state . 264 ix Page Table 7.14 Recommended feeding indicators by state. 265 Table 7.15 Nutritional status of children by demographic characteristics. 266 Table 7.16 Nutritional status of children by background characteristics. 269 Table 7.17 Nutritional status of children by state . 270 Table 7.18 Anaemia among children . 272 Table 7.19 Aneamia among children by state . 273 Table 7.20 Iodization of salt. 276 Table 7.21 Iodization of salt by state . 277 Table 8.1 Health problems during pregnancy . 281 Table 8.2 Antenatal check-ups . 283 Table 8.3 Reason for not receiving an antenatal check-up . 285 Table 8.4 Number and timing of antenatal check-ups and stage of pregnancy. 286 Table 8.5 Components of antenatal check-ups. 288 Table 8.6 Tetanus toxoid vaccination and iron and folic acid tablets or syrup. 290 Table 8.7 Antenatal care indicators by state . 293 Table 8.8 Place of delivery. 295 Table 8.9 Assistance during delivery . 298 Table 8.10 Characteristics of births. 300 Table 8.11 Postpartum check-ups . 301 Table 8.12 Symptoms of postpartum complications. 304 Table 8.13 Maternal care indicators by state. 305 Table 8.14 Symptoms of reproductive health problems . 309 Table 8.15 Treatment of reproductive health problems . 312 Table 8.16 Symptoms of reproductive tract infections by state. 313 Table 9.1 Source of health care. 316 Table 9.2 Home visits by a health or family planning worker. 318 Table 9.3 Quality of home visits . 319 Table 9.4 Matters discussed during contacts with a health or family planning worker. 321 Table 9.5 Quality of care indicators for home visits by state. 322 Table 9.6 Quality of care during most recent visit to a health facility. 323 Table 9.7 Quality of care indicators for facility visits by state . 324 x Page Table 9.8 Family planning discussions with a health or family planning worker . 326 Table 9.9 Availability of regular supply of condoms/pills. 326 Table 9.10 Motivation to use family planning . 327 Table 9.11 Discussions about alternative methods of family planning. 328 Table 9.12 Information on side effects and follow-up for current method . 329 Table 9.13 Quality of care indicators for contraceptive users by state . 330 Appendix B Table B.1 Sample characteristics . 344 Appendix C Table C.1 List of selected variables for sampling errors, India, 1998–99 . 349 Table C.2 Sampling errors, India, 1998–99 . 350 Appendix D Table D.1 Household age distribution. 358 Table D.2 Age distribution of eligible and interviewed women . 359 Table D.3 Completeness of reporting . 359 Table D.4 Births by calendar year. 361 Table D.5 Reporting of age at death in days . 362 Table D.6 Reporting of age at death in months. 363 FIGURES Page Figure 2.1 Population Pyramid. 16 Figure 2.2 Percentage Literate by Age and Sex . 29 Figure 2.3 Percentage of Women Age 6+ Who Are Illiterate by State. 32 Figure 2.4 School Attendance by Age, Sex, and Residence . 34 Figure 3.1 Employment Status of Women by Residence. 52 Figure 3.2 Percentage of Women Not Regularly Exposed to Any Mass Media by State. 61 Figure 3.3 Percentage of Women Participating in Decisions About Their Own Health Care by State. 71 Figure 3.4 Percentage Who Agree With At Least One Reason Justifying a Husband Beating His Wife. 75 Figure 4.1 Age-Specific Fertility Rates by Residence . 84 Figure 4.2 Age-Specific Fertility Rates, NFHS-1, NFHS-2, and SRS . 85 Figure 4.3 Total Fertility Rate by State. 90 Figure 4.4 Total Fertility Rate by Selected Background Characteristics. 92 Figure 4.5 Fertility Preferences Among Currently Married Women . 112 Figure 5.1 Current Use of Contraceptive Methods . 133 Figure 5.2 Current Use of Family Planning by Residence, NFHS-1 and NFHS-2. 134 Figure 5.3 Current Use of Family Planning by State . 143 Figure 5.4 Sources of Family Planning Among Current Users of Modern Contraceptive Methods . 154 Figure 5.5 Unmet Need for Family Planning by State. 175 Figure 6.1 Infant Mortality Rates for Five-Year Periods by Residence. 184 Figure 6.2 Infant Mortality Rates by Selected Background Characteristics . 188 Figure 6.3 Infant Mortality Rates by Selected Demographic Characteristics. 192 Figure 6.4 Infant Mortality Rates by State. 195 Figure 6.5 Percentage of Children Age 12–23 Months Who Have Received Specific Vaccinations, NFHS-1 and NFHS-2. 205 Figure 6.6 Percentage of Children Age 12–23 Months Who Have Received All Vaccinations. 208 xii Page Figure 6.7 Percentage of Children Age 12–23 Months Who Have Received All Vaccinations by State. 210 Figure 6.8 Source of Childhood Vaccinations by Residence. 213 Figure 6.9 Percentage Who Have Heard About AIDS by State. 235 Figure 7.1 Anaemia Among Women . 250 Figure 7.2 Percentage of Breastfeeding Children Given Milk, Other Liquid, or Solid/Mushy Food the Day or Night Before the Interview. 261 Figure 7.3 Percentage of Children Under Age 3 Who Are Underweight, NFHS-1 and NFHS-2. 267 Figure 7.4 Percentage of Children Under Age 3 Who Are Stunted by Mother’s Education and SLI. 268 Figure 7.5 Anaemia Among Children . 271 Figure 7.6 Anaemia Among Children by State . 274 Figure 8.1 Problems During Pregnancy . 282 Figure 8.2 Source of Antenatal Check-Ups During Pregnancy . 284 Figure 8.3 Number and Timing of Antenatal Check-Ups. 287 Figure 8.4 Place of Delivery and Assistance During Delivery . 296 Figure 8.5 Percentage of Deliveries Assisted by a Health Professonal by State . 306 Figure 8.6 Reproductive Health Problems Among Currently Married Women Age 15–49 . 311 Figure 9.1 Motivator for Current Users of Modern Contraceptive Methods . 328 PREFACE The success of the first National Family Health Survey, conducted in 1992–93, in creating an important demographic and health database in India has paved the way for repeating the survey. The second National Family Health Survey (NFHS-2), undertaken in 1998–99, is designed to strengthen the database further and facilitate implementation and monitoring of population and health programmes in the country. As in the earlier survey, the principal objective of NFHS-2 is to provide state and national estimates of fertility, the practice of family planning, infant and child mortality, maternal and child health, and the utilization of health services provided to mothers and children. In addition, the survey provides indicators of the quality of health and family welfare services, women’s reproductive health problems, and domestic violence, and includes information on the status of women, education, and the standard of living. Another feature of NFHS-2 is measurement of the nutritional status of women. Height and weight measurements, which were available only for young children in the earlier survey, were extended to cover all eligible women in NFHS-2. In addition, ever-married women and their children below age three had their blood tested for the level of haemoglobin, using the HemoCue instrument. Through these blood tests, for the first time the survey provides information on the prevalence of anaemia throughout India. In two metropolitan cities, Delhi and Mumbai, a further test was done for children below age three to measure the lead content in their blood. The survey also measured the extent to which households in India use cooking salt that has been fortified with iodine. The NFHS-2 survey was funded by the United States Agency for International Development (USAID) through ORC Macro, USA. UNICEF provided additional financial support for the nutritional components of the survey. The survey is the outcome of the collaborative efforts of many organizations. The International Institute for Population Sciences (IIPS) was designated as the nodal agency for this project by the Ministry of Health and Family Welfare, Government of India, New Delhi. Thirteen reputed field organizations (FOs) in India, including five Population Research Centres, were selected to carry out the houselisting operation and data collection for NFHS-2. ORC Macro, Calverton, Maryland, USA, and the East-West Center, Honolulu, Hawaii, USA, provided technical assistance for all survey operations. The NFHS-2 survey covered a representative sample of more than 90,000 eligible women age 15–49 from 26 states that comprise more than 99 percent of India’s population. The data collection was carried out in two phases, starting in November 1998 and March 1999. The survey provides state-level estimates of demographic and health parameters as well as data on various socioeconomic and programmatic factors that are critical for bringing about desired changes in India’s demographic and health situation. The survey provides urban and rural estimates for most states, regional estimates for four states (Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh), separate estimates for three metro cities (Calcutta, Chennai and Mumbai), and estimates for slum areas in Mumbai. The survey used uniform questionnaires, sample designs, and field procedures to facilitate comparability of the data and to achieve a high level of data quality. Preliminary reports with selected results were prepared earlier for each state and presented to policymakers and programme administrators responsible for improving health and family welfare programmes in xiv the states. The report presents survey findings from all Indian states except Tripura, where the fieldwork was delayed due to a local problem. The contents of this report are based on a standard tabulation plan developed at a workshop held in Kodaikanal during the period 15–17 January 1999. IIPS finalized the tabulation plan according to the recommendations of the NFHS-2 Technical Advisory Committee and produced the tables and figures for the final reports. This report has been written jointly by authors from IIPS, ORC Macro, and the East-West Center. We are happy to present the final NFHS-2 national report, through which the information collected in NFHS-2 is being made public. We hope that the report will provide helpful insights into the changes that are taking place in the country and will provide policymakers and programme managers with up-to-date estimates of indicators that can be used for effective management of health and family welfare programmes, with an emphasis on reproductive health dimensions. The report should also contribute to the knowledge of researchers and analysts in the fields of population, health, and nutrition. T.K. Roy Director International Institute for Population Sciences Mumbai ACKNOWLEDGEMENTS The second National Family Health Survey was successfully completed due to the efforts and involvement of numerous organizations and individuals at different stages of the survey. We would like to thank everyone who was involved in the survey and made it a success. First of all, we are grateful to the Ministry of Health and Family Welfare, Government of India, New Delhi, for its overall guidance and support during the project. Mr. Y.N. Chaturvedi and Mr. K.S. Sugathan, the then Secretary and Joint Secretary, respectively, at the Department of Family Welfare deserve special thanks. They initiated the project and designated the International Institute for Population Sciences (IIPS) as the nodal agency for the survey. They also formed the Steering Committee, the Administrative and Financial Management Committee, and the Technical Advisory Committee for the smooth and efficient functioning of the project. Special thanks are due to Mr. A.R. Nanda, the present Secretary of the Department of Family Welfare, who continued to take an active interest in the project and provided timely guidance and support. The contributions of Mr. Vijay Singh, Joint Secretary (FA), Ms. Meenakshi Dutta Ghosh, Joint Secretary (S), Mr. Gautam Basu, Joint Secretary (RCH), Mr. P.K. Saha, Chief Director (S), and Dr. K.V. Rao, Chief Director (S), are acknowledged with gratitude. We gratefully acknowledge the immense help received from the Office of the Registrar General, India, New Delhi (particularly Dr. M. Vijayanunni, the then Registrar General of India, Mr. J.K. Banthia, the present Registrar General of India, Mr. S.P. Sharma, Consultant, and Mr. S.K. Sinha, Deputy Registrar General, Vital Statistics) in implementing the sample design and making the latest SRS results available to cite in the reports. We thank all the expert participants in the series of workshops to finalize the questionnaire design, the sample design and tabulations plans for the survey. Special mention and thanks are due to Dr. Vijay Verma for his expert advice on the sample design and the calculation of sample weights. We are grateful to the Directorate of Census Operations, Directorate of Health Services, and Office of the Integrated Child Development Scheme, Maharashtra, for their support in conducting training of the houselisters and investigators. We acknowledge the support of the All India Institute of Medical Sciences, New Delhi, which extended its facilities for training of the health investigators. We are thankful to the Department of Health and Family Welfare of each state covered in NFHS-2 for helping the Field Organizations (FOs) by providing them with logistic assistance, whenever possible. Special thanks go to the local officials in all of the sample areas for facilitating the data collection. The United States Agency for International Development (USAID) provided generous funding for NFHS-2. USAID’s contribution to the project is sincerely acknowledged. Special thanks are due to Mr. William Goldman, the former Director of the Office of Population, Health and Nutrition (PHN), USAID, New Delhi, Ms. Sheena Chhabra, Team Leader, Policy, Research, Evaluation, and Marketing (PHN), and Dr. Victor K. Barbiero, current Director of PHN, for their initiative and involvement in the project. Many thanks are due to UNICEF for providing additional funding for the nutrition component of the project and the most modern medical equipment for carrying out the height-weight measurements and anaemia testing. Special thanks are due to xvi Dr. Sanjiv Kumar, Project Officer (Health), UNICEF, New Delhi, for his earnest cooperation in this respect. We gratefully acknowledge the help and cooperation given by Dr. Rameshwar Sharma, the then Director, and Dr. Shiv Chandra Mathur, Professor, State Institute of Health and Family Welfare (SIHFW), Jaipur, during the national pretest of the NFHS-2 questionnaires in Rajasthan. Thanks are due to all the members of the Steering Committee, Administrative and Financial Management Committee, and Technical Advisory Committee for participating in various meetings and providing valuable guidance for successful execution of the project. Dr. K.B. Pathak was the Director of IIPS during the development of the project and throughout the first phase of data collection. His immense interest and great assistance to NFHS-2 are gratefully acknowledged. We appreciate and acknowledge the untiring efforts, interest, and initiative taken by Dr. Fred Arnold, Dr. Sunita Kishor, Mr. Sushil Kumar, and Mr. Zaheer Ahmad Khan from ORC Macro, and Dr. Robert D. Retherford and Dr. Vinod Mishra from the East-West Center. It is only due to their hard work that NFHS-2 could be completed successfully. Thanks go to Dr. Umesh Kapil, Additional Professor, Department of Human Nutrition, All India Institute of Medical Sciences, New Delhi, for organizing, in collaboration with IIPS, the training programme for the health component of the survey, and to Dr. Almaz Sharman of ORC Macro for assisting with the training programme. Dr. Rachel Kaufmann and her colleagues from the Centers for Disease Control and Prevention, Atlanta, also deserve special thanks for providing special training to the health investigators for analyzing lead levels in the blood of young children in Delhi and Mumbai. ORC Macro made available the ISSA (Integrated System for Survey Analysis) computer package for data entry and tabulation. Special thanks go to Mr. Martin Wulfe and Mr. Hendrik J. Raggers for their immense help in the data processing operation, data analysis, and preparation of the tables for NFHS-2 reports and to Dr. Rajib Acharya for his assistance at every stage of the data processing operation and report writing and his maintenance of the NFHS website. Special thanks go to Mr. Somnath W. Choughule, Data Entry Operator, for designing the NFHS website. We gratefully acknowledge the valuable contribution of IIPS Senior Research Officers Dr. Rajeshri Chitanand, Dr. Damodar Sahu, and Dr. Yonah Bhutia, and Research Officers Mr. M.N. Murthy, Ms. Y. Vaidehi, Ms. Pavani Upadrashta, Dr. Madhumita Das, and Mr. Nizamuddin Khan. We also thank the other Research Officers and the health coordinators listed in Appendix E for their valuable assistance during the fieldwork. Thanks are also due to the other supporting staff of the project, particularly Mr. R.S. Hegde, Sr. Accountant, Mr. Dandapani Lokanathan, Sr. Secretarial Assistant, Mr. Sadashiv Jathade, Jr. Secretarial Assistant, and Office Assistants Mr. Parasnath Verma and Mr. Pramod T. Sawant, as well as the Administrative, Accounts, and Library staff of IIPS, for their continuous cooperation during the entire project period. The difficult task of data collection, office editing and data entry for NFHS-2 was successfully carried out by several field organizations. Our heartfelt thanks are due to the directors and staff of all 13 FOs: ACNielsen, New Delhi; Centre for Operations Research and Training, Vadodara; Centre for Population and Development Studies, Hyderabad; Economic Information Technology, Calcutta; Indian Institute of Health and Family Welfare, Hyderabad; Operations Research Group, New Delhi; PRC, Centre for Research in Rural and Industrial Development, Chandigarh; PRC, Institute of Economic Growth, New Delhi; PRC, Institute of Rural Health and xvii Family Welfare Trust, Gandhigram; PRC, Institute of Social and Economic Change, Bangalore; PRC, J.S.S. Institute of Economic Research, Dharwad; PRC, M.S. University of Baroda, Vadodara; and Taylor Nelson Sofres MODE, New Delhi. This acknowledgement cannot be concluded without expressing appreciation for the hard work put in by the interviewers, health investigators, supervisors and field editors in collecting data for NFHS-2. Last but not the least, credit goes to all the eligible women and the household respondents who spent their time and responded to the rather lengthy questionnaires with tremendous patience and without any expectation from NFHS-2. T.K. Roy Sumati Kulkarni Arvind Pandey Kamla Gupta Parveen Nangia NFHS-2 Coordinators, IIPS FACT SHEET - INDIA NATIONAL FAMILY HEALTH SURVEY, 1998–99 Sample Size Households . 91,196 Ever-married women age 15–49. 89,199 Characteristics of Households Percent with electricity . 60.1 Percent within 15 minutes of safe water supply1 . 62.3 Percent with flush toilet. 24.0 Percent with no toilet facility. 64.0 Percent using govt. health facilities for sickness . 28.7 Percent using iodized salt (at least 15 ppm). 49.3 Characteristics of Women2 Percent urban. 26.2 Percent illiterate. 58.2 Percent completed high school and above . 14.3 Percent Hindu . 81.7 Percent Muslim. 12.5 Percent Christian . 2.5 Percent regularly exposed to mass media . 59.7 Percent working in the past 12 months . 39.2 Status of Women2 Percent involved in decisions about own health . 51.6 Percent with control over some money. 59.6 Marriage Percent never married among women age 15–19 . 66.4 Median age at marriage among women age 20–49. 16.7 Fertility and Fertility Preferences Total fertility rate (for the past 3 years) . 2.85 Mean number of children ever born to women 40–49. 4.45 Median age at first birth among women age 20–49. 19.6 Percent of births3 of order 3 and above . 45.2 Mean ideal number of children4. 2.7 Percent of women with 2 living children wanting another child . 23.0 Current Contraceptive Use5 Any method . 48.2 Any modern method . 42.8 Pill . 2.1 IUD. 1.6 Condom . 3.1 Female sterilization . 34.2 Male sterilization . 1.9 Any traditional method. 5.0 Rhythm/safe period . 3.0 Withdrawal . 2.0 Other traditional or modern method . 0.4 Unmet Need for Family Planning5 Percent with unmet need for family planning. 15.8 Percent with unmet need for spacing. 8.3 1Water from pipes, handpump, covered well or tanker truck 2Ever-married women age 15–49 3For births in the past 3 years 4Excluding women giving non-numeric responses 5Among currently married women age 15–49 Quality of Family Planning Services6 Percent told about side effects of method. 21.7 Percent who received follow-up services . 69.1 Childhood Mortality Infant mortality rate7 . 67.6 Under-five mortality rate7. 94.9 Safe Motherhood and Women’s Reproductive Health Maternal mortality ratio. 540 Percent of births8 within 24 months of previous birth . 28.3 Percent of births3 whose mothers received: Antenatal check-up from a health professional . 65.1 Antenatal check-up in first trimester . 33.0 Two or more tetanus toxoid injections . 66.8 Iron and folic acid tablets or syrup . 57.6 Percent of births3 whose mothers were assisted at delivery by a: Doctor . 30.3 Nurse/midwife. 11.4 Traditional birth attendant . 35.0 Percent5 reporting at least one reproductive health problem. 39.2 Awareness of AIDS Percent of women who have heard of AIDS . 40.3 Child Health Percent of children age 0–3 months exclusively breastfed . 55.2 Median duration of breastfeeding (months) . 25.4 Percent of children9 who received vaccinations: BCG . 71.6 DPT (3 doses) . 55.1 Polio (3 doses) . 62.8 Measles. 50.7 All vaccinations. 42.0 Percent of children10 with diarrhoea in the past 2 weeks who received oral rehydration salts (ORS). 26.8 Percent of children10 with acute respiratory infection in the past 2 weeks taken to a health facility or provider. 64.0 Nutrition Percent of women with anaemia11 . 51.8 Percent of women with moderate/severe anaemia11 . 16.7 Percent of children age 6–35 months with anaemia11. 74.3 Percent of children age 6–35 months with moderate/ severe anaemia11. 51.3 Percent of children chronically undernourished (stunted)12. 45.5 Percent of children acutely undernourished (wasted)12 . 15.5 Percent of children underweight12 . 47.0 6For current users of modern methods 7For the 5 years preceding the survey (1994–98) 8For births in the past 5 years (excluding first births) 9Children age 12–23 months 10Children under 3 years 11Anaemia–haemoglobin level < 11.0 grams/decilitre (g/dl) for children and pregnant women and < 12.0 g/dl for nonpregnant women. Moderate/severe anaemia –haemoglobin level < 10.0 g/dl. 12Stunting assessed by height-for-age, wasting assessed by weight-for-height, underweight assessed by weight-for-age SUMMARY OF FINDINGS The second National Family Health Survey (NFHS-2), conducted in 1998–99, provides information on fertility, mortality, family planning, and important aspects of nutrition, health, and health care. The International Institute for Population Sciences (IIPS) coordinated the survey, which collected information from a nationally representative sample of more than 90,000 ever-married women age 15–49. The NFHS-2 sample covers 99 percent of India’s population living in all 26 states. This report is based on the survey data for 25 of the 26 states, however, since data collection in Tripura was delayed due to local problems in the state. IIPS also coordinated the first National Family Health Survey (NFHS-1) in 1992–93. Most of the types of information collected in NFHS-2 were also collected in the earlier survey, making it possible to identify trends over the intervening period of six and one-half years. In addition, the NFHS-2 questionnaire covered a number of new or expanded topics with important policy implications, such as reproductive health, women’s autonomy, domestic violence, women’s nutrition, anaemia, and salt iodization. The NFHS-2 survey was carried out in two phases. Ten states were surveyed in the first phase which began in November 1998 and the remaining states (except Tripura) were surveyed in the second phase which began in March 1999. The field staff collected information from 91,196 households in these 25 states and interviewed 89,199 eligible women in these households. In addition, the survey collected information on 32,393 children born in the three years preceding the survey. One health investigator on each survey team measured the height and weight of eligible women and children and took blood samples to assess the prevalence of anaemia. Background Characteristics of the Survey Population Three-quarters (73 percent) of the population lives in rural areas. The age distribution is typical of populations that have recently experienced a fertility decline, with relatively low proportions in the younger and older age groups. Thirty-six percent of the population is below age 15, and 5 percent is age 65 and above. The sex ratio is 957 females for every 1,000 males in rural areas but only 928 females for every 1,000 males in urban areas, suggesting that more men than women have migrated to urban areas. The survey provides a variety of demographic and socioeconomic background information. In the country as a whole, 82 percent of household heads are Hindu, 12 percent are Muslim, 3 percent are Christian, and 2 percent are Sikh. Muslims live disproportionately in urban areas, where they comprise 15 percent of household heads. Nineteen percent of household heads belong to scheduled castes, 9 percent belong to scheduled tribes, and 32 percent belong to other backward classes (OBCs). Two-fifths of household heads do not belong to any of these groups. Questions about housing conditions and the standard of living of households indicate some improvements since the time of NFHS-1. Sixty percent of households in India now have electricity and 39 percent have piped drinking water compared with 51 percent and 33 percent, respectively, at the time of NFHS-1. Sixty-four percent of households have no toilet facility compared with 70 percent at the time of NFHS-1. xx About three-fourths (75 percent) of males and half (51 percent) of females age six and above are literate, an increase of 6–8 percentage points from literacy rates at the time of NFHS-1. The percentage of illiterate males varies from 6–7 percent in Mizoram and Kerala to 37 percent in Bihar and the percentage of illiterate females varies from 11 percent in Mizoram and 15 percent in Kerala to 65 percent in Bihar. Seventy-nine percent of children age 6–14 are attending school, up from 68 percent in NFHS-1. The proportion of children attending school has increased for all ages, particularly for girls, but girls continue to lag behind boys in school attendance. Moreover, the disparity in school attendance by sex grows with increasing age of children. At age 6–10, 85 percent of boys attend school compared with 78 percent of girls. By age 15–17, 58 percent of boys attend school compared with 40 percent of girls. The percentage of girls 6–17 attending school varies from 51 percent in Bihar and 56 percent in Rajasthan to over 90 percent in Himachal Pradesh and Kerala. Women in India tend to marry at an early age. Thirty-four percent of women age 15–19 are already married including 4 percent who are married but gauna has yet to be performed. These proportions are even higher in the rural areas. Older women are more likely than younger women to have married at an early age: 39 percent of women currently age 45–49 married before age 15 compared with 14 percent of women currently age 15–19. Although this indicates that the proportion of women who marry young is declining rapidly, half the women even in the age group 20–24 have married before reaching the legal minimum age of 18 years. On average, women are five years younger than the men they marry. The median age at marriage varies from about 15 years in Madhya Pradesh, Bihar, Uttar Pradesh, Rajasthan, and Andhra Pradesh to 23 years in Goa. As part of an increasing emphasis on gender issues, NFHS-2 asked women about their participation in household decisionmaking. In India, 91 percent of women are involved in decision-making on at least one of four selected topics. A much lower proportion (52 percent), however, are involved in making decisions about their own health care. There are large variations among states in India with regard to women’s involvement in household decisionmaking. More than three out of four women are involved in decisions about their own health care in Himachal Pradesh, Meghalaya, and Punjab compared with about two out of five or less in Madhya Pradesh, Orissa, and Rajasthan. Thirty-nine percent of women do work other than housework, and more than two-thirds of these women work for cash. Only 41 percent of women who earn cash can decide independently how to spend the money that they earn. Forty-three percent of working women report that their earnings constitute at least half of total family earnings, including 18 percent who report that the family is entirely dependent on their earnings. Women’s work-participation rates vary from 9 percent in Punjab and 13 percent in Haryana to 60–70 percent in Manipur, Nagaland, and Arunachal Pradesh. Fertility and Family Planning Fertility continues to decline in India. At current fertility levels, women will have an average of 2.9 children each throughout their childbearing years. The total fertility rate (TFR) is down from 3.4 children per woman at the time of NFHS-1, but is still well above the replacement level of just over two children per woman. There are large variations in fertility among the states in India. Goa and Kerala have attained below replacement level fertility and Karnataka, Himachal Pradesh, Tamil Nadu, and Punjab are at or close to replacement level fertility. By contrast, fertility is 3.3 or more children per woman in Meghalaya, Uttar Pradesh, Rajasthan, Nagaland, xxi Bihar, and Madhya Pradesh. More than one-third to less than half of all births in these latter states are fourth or higher-order births compared with 7–9 percent of births in Kerala, Goa, and Tamil Nadu. Efforts to encourage the trend towards lower fertility might usefully focus on groups within the population that have higher fertility than average. In India, rural women and women from scheduled tribes and scheduled castes have somewhat higher fertility than other women, but fertility is particularly high for illiterate women, poor women, and Muslim women. Another striking feature is the high level of childbearing among young women. More than half of women age 20–49 had their first birth before reaching age 20, and women age 15–19 account for almost one-fifth of total fertility. Studies in India and elsewhere have shown that health and mortality risks increase when women give birth at such young agesboth for the women themselves and for their children. Family planning programmes focusing on women in this age group could make a significant impact on maternal and child health and help to reduce fertility. The appropriate design of family planning programmes depends, to a large extent, on women’s fertility preferences. Women may have large families because they want many children, or they may prefer small families but, for a variety of reasons, may have more children than they actually want. For 9 percent of births over the three years preceding the survey and current pregnancies, mothers report that they did not want the pregnancy at all, and for another 12 percent, mothers say that they would have preferred to delay the pregnancy. When asked about their preferred family size, 41 percent of women who already have three children and 24 percent of women with four or more children respond that they consider the two-child family ideal. This gap between women’s actual fertility experience and what they want or would consider ideal suggests a need for expanded or improved family welfare services to help women achieve their fertility goals. On average, a woman in India considers less than 3 children (2.7) ideal, but in Bihar, Uttar Pradesh, and several of the northeastern states, women’s ideal number of children is 3.1 or above. In the country as a whole, 85 percent of women want at least one son and 80 percent want at least one daughter. A preference for sons is indicated by the fact that one-third want more sons than daughters but only a negligible proportion want more daughters than sons. If many women in India are not using family planning, it is not due to lack of knowledge. Knowledge of contraception is nearly universal: 99 percent of currently married women know at least one modern family planning method. Women are most familiar with female sterilization (98 percent), followed by male sterilization (89 percent), the pill (80 percent), the condom (71 percent), and the IUD (71 percent). Knowledge of modern spacing methods has increased by 10–13 percentage points since the time of NFHS-1, although use rates for these methods remain extremely low. Forty-eight percent of currently married women are using some method of contraception, up from 41 percent at the time of NFHS-1. Contraceptive prevalence is considerably higher in urban areas (58 percent) than in rural areas (45 percent). Female sterilization is by far the most popular method: 34 percent of currently married women are sterilized, a substantial increase from 27 percent at the time of NFHS-1. By contrast, only 2 percent of women report that their husbands are sterilized, a decrease from 4 percent in NFHS-1. Overall, sterilization accounts for 75 percent of total contraceptive use. Only 18 percent of sterilized couples have ever used any xxii method other than sterilization. Current-use rates for the pill, IUD, and condom remain very low, each at about 2–3 percent. Contraceptive prevalence varies widely among socioeconomic groups. Muslim women, scheduled-tribe women, and women belonging to poor households are less likely (37–40 percent) than most other women to use contraception at all. The three modern spacing methods—pills, IUDs, and condoms—are used more by Sikh women, more educated women, women from households with a high standard of living, Jain women, and urban women (13–23 percent) than other women. Contraceptive prevalence varies by state from 20 percent in Meghalaya, 25 percent in Bihar, and 28 percent in Uttar Pradesh to 67–68 percent in Punjab and Himachal Pradesh. Other states where contraceptive prevalence is at or below the national average of 48 percent are Rajasthan, Madhya Pradesh, Orissa, Goa, and all northeastern states except Mizoram and Sikkim. Modern temporary methods are most prevalent in Delhi, Punjab, and Sikkim (17–28 percent) and are also relatively common (9–14 percent) in West Bengal, Haryana, Jammu and Kashmir, and other northeastern states. Traditional methods are used most widely in West Bengal, followed by Assam, Manipur, Punjab, and Sikkim. Sterilization dominates the contraceptive method-mix in most states, but especially so in Maharashtra, Madhya Pradesh, Bihar, Rajasthan, and all the southern states. Given the near-exclusive emphasis on sterilization in the contraceptive method-mix, women tend to adopt family planning only after they have achieved their desired family size. As a result, contraceptive use can be expected to rise steadily with age and with number of living children. In India, contraceptive use does indeed go up with age, peaking at 67 percent for women age 35–39. Use also goes up with the number of children, peaking at 68 percent for women with three living children. Son preference appears to have a strong effect on contraceptive use, especially the adoption of sterilization. Among women with two or more living children, only 23–30 percent of women with only daughters have been sterilized compared with 41–67 percent of women with at least one son. Eight percent of currently married women are not using contraception but say that they want to wait at least two years before having another child. Another 8 percent are not using contraception although they do not want any more children. These women are described as having an ‘unmet need’ for family planning. Unmet need is highest (27 percent) for young women below age 20, who are particularly interested in spacing their births. Unmet need in different states varies from 7–9 percent of currently married women in Punjab, Haryana, Andhra Pradesh, Gujarat, and Himachal Pradesh to 25–36 percent in Meghalaya, Nagaland, Arunachal Pradesh, Uttar Pradesh, and Bihar. These results underscore the need for strategies that provide spacing as well as terminal methods in order to meet the changing needs of women over their lifecycle. For many years, the Government of India has been using electronic and other mass media to promote family planning. Among the different types of media, television has the broadest reach across almost all categories of women, including illiterate women and women living in rural areas. Overall, 46 percent of ever-married women watch television at least once a week. Despite the fact that 40 percent of women are not regularly exposed to television, radio, and other types of media, however, 60 percent of women saw or heard a family planning message in the media during the few months before the survey. Women are more likely to have seen or heard a family planning message on television than through any other form of media. Exposure xxiii to family planning messages is relatively low among poor, scheduled-tribe, illiterate, and rural women. Nonetheless, family planning messages are reaching about two out of five or more socioeconomically disadvantaged women. Exposure to family planning messages is particularly limited in Rajasthan, Bihar, Uttar Pradesh, and Madhya Pradesh, where less than half the women were exposed to a family planning message in the past few months. More than three-fourths (76 percent) of current users of modern contraceptives obtained their method from a government hospital or other source in the public sector. Only 17 percent obtained their method from the private medical sector. The private medical sector along with shops is the major source of pills and condoms, however. Overall, the public medical sector plays a larger role in rural areas than in urban areas, and at least two-thirds of modern contraceptive users obtain their method from a public-sector source in every state except Meghalaya, Delhi, Nagaland, Assam, and Punjab. An important indicator of the quality of family planning services is the information that women receive when they obtain contraception and the extent to which they receive follow-up services after accepting contraception. In India, only 15 percent of users of modern contraceptives who were motivated by someone to use their method were told about any other method. Only 22 percent were told about possible side effects of their current method by a health or family planning worker at the time of adopting the method. Sixty-nine percent of contraceptive users, however, received follow-up services. From the information provided in NFHS-2, a picture emerges of women marrying early, having their first child soon after marriage, having a second and possibly a third child in close succession, and then being sterilizedall by the time they reach their mid-20s. The median age for female sterilization has been declining in recent years and is now 26 years, one year earlier than at the time of NFHS-1. Very few women use modern spacing methods that could help them delay their first births and increase intervals between pregnancies. Infant and Child Mortality NFHS-2 provides estimates of infant and child mortality and examines factors associated with the survival of young children. During the five years preceding the survey, the infant mortality rate was 68 deaths at age 0–11 months per 1,000 live births, substantially lower than 79 per 1,000 in the five years preceding the NFHS-1 survey. The child mortality rate, 29 deaths at age 1–4 years per 1,000 children reaching age one, also declined from the corresponding rate of 33 per 1,000 in NFHS-1. Ninety-five children out of 1,000 born do not live to age five years. Expressed differently, 1 in 15 children die in the first year of life, and 1 in 11 die before reaching age five. Child-survival programmes might usefully focus on specific groups of children with particularly high infant and child mortality rates, such as children who live in rural areas, children whose mothers are illiterate, children belonging to scheduled castes or scheduled tribes, and children from poor households. Infant mortality rates are more than two and one-half times as high for women who did not receive any of the recommended types of maternity related medical care than for mothers who did receive all recommended types of care. Along with various socioeconomic groups, efforts to promote child survival need to concentrate on very young mothers and mothers whose children are closely spaced. Infant mortality is almost 50 percent higher among children born to mothers under age 20 than among xxiv children born to mothers age 20–29 (93 deaths, compared with 63, per 1,000 live births). Infant mortality is nearly three times as high among children born less than 24 months after a previous birth as among children born after a gap of 48 months or more (110 deaths, compared with 39, per 1,000 live births). Clearly, efforts to expand the use of temporary contraceptive methods for delaying and spacing births would help reduce infant mortality as well as fertility. There are large variations in infant mortality among states. Infant mortality ranges from a high of 80–89 deaths per 1,000 live births in Meghalaya, Uttar Pradesh, Madhya Pradesh, Orissa, and Rajasthan to a low of 16 per 1,000 live births in Kerala and 34–37 per 1,000 live births in Himachal Pradesh, Goa, Mizoram, and Manipur. Health, Health Care, and Nutrition Promotion of maternal and child health has been one of the most important components of the Family Welfare Programme of the Government of India. One goal is for each pregnant woman to receive at least three antenatal check-ups plus two tetanus toxoid injections and a full course of iron and folic acid supplementation. In India, mothers of 65 percent of the children born in the three years preceding NFHS-2 received at least one antenatal check-up and 44 percent received at least three check-ups. For 67 percent of these births, mothers received the recommended number of tetanus toxoid vaccinations during pregnancy, up from 54 percent in NFHS-1. For 58 percent, mothers received iron and folic acid supplementation during pregnancy. Women in disadvantaged socioeconomic groups are less likely than other women to be covered by each of these interventions. Coverage is also low for women who already have four or more children. States that perform well below the national average with regard to the provision of recommended components of antenatal care include Bihar, Madhya Pradesh, Rajasthan, Uttar Pradesh, and several of the northeastern states. Kerala, Goa, and Tamil Nadu, by contrast, have achieved relative success with regard to antenatal care. In these states, mothers of over 90 percent of births receive at least three antenatal check-ups, at least 86 percent receive two or more tetanus toxoid injections, and at least 93 percent receive iron and folic acid tablets. Even in these states, however, a substantial proportion of women do not receive all of the recommended components of antenatal care. The Family Welfare Programme encourages women to deliver in a medical facility or if at home, with assistance from a trained health professional and to receive at least three check-ups after delivery. During the three years preceding NFHS-2, only one-third of births in India took place in a medical facility, up from one-fourth at the time of NFHS-1. Among births at home, over 50 percent were assisted by a traditional birth attendant, and only 13 percent were assisted by a health professional. Only 17 percent of births outside a medical facility were followed by a postpartum check-up within two months of delivery. While over 84 percent of deliveries were assisted by a health professional in Kerala, Goa, and Tamil Nadu, less than one-fourth were assisted by a health professional in Meghalaya, Assam, Uttar Pradesh, and Bihar. The proportion of noninstitutional deliveries with a postpartum check-up within two months ranges from a high of only 53 percent in Tamil Nadu to below 10 percent in Nagaland, Rajasthan, and Uttar Pradesh. Overall, these results show that maternal health services in India are reaching many more women during pregnancy than during delivery or after childbirth. They also point to the important role of traditional birth attendants for the substantial proportion of births that occur at home. xxv The Government of India recommends that breastfeeding should begin immediately after childbirth and that infants should be exclusively breastfed for the first four months of life. Although breastfeeding is nearly universal in India, very few children begin breastfeeding immediately after birthonly 16 percent in the first hour and 37 percent in the first day. Fifty-five percent of children under four months of age are exclusively breastfed. The median duration of breastfeeding is 25 months, or slightly over two years, and the median duration of exclusive breastfeeding is two months. At age 6–9 months, all children should be receiving solid or mushy food in addition to breast milk to provide sufficient nutrients for optimal growth. However, only 34 percent of children age 6–9 months receive the recommended combination of breast milk and solid or mushy food. The proportion of children age 6–9 months who receive solid or mushy food is even lower than the national average in six states, including Bihar, Uttar Pradesh, and Rajasthan, where this proportion is only 15–18 percent. NFHS-2 uses three internationally recognized standards to assess children’s nutritional statusweight-for-age, height-for-age, and weight-for-height. Children who are more than two standard deviations below the median of an international reference population are considered underweight (measured in terms of weight-for-age), stunted (height-for-age), or wasted (weight- for-height). Stunting is a sign of chronic, long-term undernutrition, wasting is a sign of acute, short-term undernutrition, and underweight is a composite measure that takes into account both chronic and acute undernutrition. Based on international standards, 47 percent of children under age three years in India are underweight, down slightly from 52 percent at the time of NFHS-1. Forty-six percent of children are stunted and 16 percent are wasted. Undernutrition is much higher in rural areas than in urban areas, and is particularly high among children from disadvantaged socioeconomic groups. Nearly three-quarters (74 percent) of children age 6–35 months are anaemic, with very little variation in anaemia rates for children in most subgroups of the population. Christian children, children whose mothers have completed at least high school, children from households with a relatively high standard of living, and children whose mothers are not anaemic, have anaemia rates that are substantially below the national average. Even among these groups, however, at least 61 percent of children are anaemic. The prevalence of anaemia among children age 6–35 months varies from 44 percent in Kerala and Nagaland to 80–84 percent in Haryana, Rajasthan, Bihar, and Punjab. Child immunization is an important component of child-survival programmes in India, with efforts focussing on six serious but preventable diseasestuberculosis, diphtheria, pertussis, tetanus, polio, and measles. The objective of the Universal Immunization Programme (UIP), launched in 1985–86, was to extend immunization coverage against these diseases to at least 85 percent of infants by 1990. In India, 42 percent of children age 12–23 months have received all the recommended vaccinations, 44 percent have received some but not all, and 14 percent have received none of the recommended vaccinations. Immunization coverage, although far from complete, has improved substantially since NFHS-1, when only 36 percent of children were fully vaccinated and 30 percent had not been vaccinated at all. Coverage of individual vaccines has also increased considerably, and is much higher than would appear from information on full coverage alone. According to NFHS-2, 72 percent of children age 12–23 months have been vaccinated against tuberculosis, 63 percent have received three doses of the polio vaccine, 55 percent have received three doses of the DPT xxvi vaccine, and 51 percent have been vaccinated against measles. The largest increases in vaccination coverage between NFHS-1 and NFHS-2 are for the first two doses of polio vaccine, undoubtedly because of the introduction of the Pulse Polio Immunization Campaign in 1995. Dropout rates for the series of DPT and polio vaccinations continue to be a problem, however. Eighty-four percent of children received the first polio vaccination, but only 63 percent received all three doses; 71 percent received the first DPT vaccination, but only 55 percent received all three doses. It is also recommended that children under age five years should receive oral doses of vitamin A every six months starting at age nine months. However, only 30 percent of children age 12–35 months have received any vitamin A supplementation and only 17 percent received a dose of vitamin A in the six months preceding the survey. NFHS-2 collected information on the prevalence and treatment of three health problems that cause considerable mortality in young childrenfever, acute respiratory infection (ARI), and diarrhoea. In India 30 percent of children under age three had fever during the two weeks preceding the survey, 19 percent had symptoms of ARI, and 19 percent had diarrhoea. About two-thirds of the children who had symptoms of ARI or diarrhoea were taken to a health facility or health-care provider. Knowledge of the appropriate treatment of diarrhoea remains low. Only 62 percent of mothers of children age less than 3 years know about oral rehydration salt (ORS) packets and 34 percent of mothers incorrectly believe that children should be given less to drink than usual when sick with diarrhoea. Forty-eight percent of children with diarrhoea received some form of oral rehydration therapy (ORT), including 27 percent who received ORS. The percentage of children with diarrhoea who received ORS has increased substantially since NFHS-1, when it was only 18 percent, suggesting some improvement in the management of childhood diarrhoea. Among children sick with diarrhoea in the two weeks prior to the survey, the proportion who were given some form of ORT varies from 90 percent in Kerala, 76 percent in Goa, and 73 percent in West Bengal to 34 percent in Rajasthan and 36 percent in Uttar Pradesh. The proportion given ORS varies from 56 percent in Goa and 51 percent in Manipur to only 15–16 percent in Bihar and Uttar Pradesh. Based on a weight-for-height index (the body mass index), more than one-third (36 percent) of women in India are undernourished. Nutritional deficiency is particularly acute for women in rural areas, younger women, women in disadvantaged socioeconomic groups, and women who work for someone else. Women who are undernourished themselves are also much more likely than other women to have children who are undernourished. The proportion of women undernourished is highest in Orissa (48 percent) and West Bengal (44 percent) and lowest in Arunachal Pradesh (11 percent), Sikkim (11 percent), and Delhi (12 percent). Obesity is a substantial problem among several groups of women in India, particularly urban women, well-educated women, and women from households with a high standard of living. Approximately one-quarter of these women have a body mass index of 25 or more, compared with 11 percent of all women in India. Obesity is particularly prevalent in Delhi and Punjab. Overall, 52 percent of women in India have some degree of anaemia and 40 percent or more of women in every population subgroup are anaemic. The prevalence of anaemia is particularly high for scheduled-tribe women and poor women. Pregnant women are much more likely than nonpregnant women to be moderately to severely anaemic. The prevalence of anaemia is lowest in Kerala, Manipur, Goa, and Nagaland, where 23–38 percent of women are anaemic, and highest in Assam, Bihar, Meghalaya, Orissa, West Bengal, Arunachal Pradesh, and Sikkim, where 61–70 percent are anaemic. xxvii Less than half of the households use cooking salt that is iodized at the recommended level of 15 parts per million, suggesting that iodine deficiency disorders are likely to be a serious problem. Rural households and households with a low standard of living are much less likely than other households to be using adequately iodized cooking salt. While 88–91 percent of households in Himachal Pradesh, Mizoram, Delhi, and Manipur consume adequately iodized salt, only 21 percent of households in Tamil Nadu and 27 percent in Andhra Pradesh do so. About two-fifths (39 percent) of currently married women in India report some type of reproductive-health problem, including abnormal vaginal discharge, symptoms of a urinary tract infection, and pain or bleeding associated with intercourse. Among these women, 66 percent have not sought any advice or treatment. These results suggest a need to expand reproductive- health services and IEC programmes that encourage women to discuss their problems with a health-care provider. The percentage of currently married women reporting at least one reproductive-health problem varies among states from 19 percent in Karnataka to above 60 percent in Meghalaya and Jammu and Kashmir. In recent years, there has been growing concern about domestic violence in India. NFHS-2 found that there is widespread acceptance among ever-married women that the beating of wives by husbands is justified under some circumstances. More than half (56 percent) the women accept at least one of six reasons as justification for a husband beating his wife. Domestic violence is also fairly common. At least one in five women have experienced beatings or physical mistreatment since age 15 and at least one in nine experienced such violence in the 12 months preceding the survey. Most of these women have been beaten or physically mistreated by their husbands. Domestic violence against women is especially prevalent (27–29 percent) among women working for cash, poor women, scheduled-caste women, and widowed, divorced, or deserted women. Overall, only 13 percent of women received a home visit from a health or family planning worker during the 12 months preceding the survey. Women who received visits were visited three times, on average, in the year preceding the survey. A large majority of women who received a home visit expressed satisfaction with the amount of time that the worker spent with them and with the way the worker talked to them. Home visits are much more common in the southern states, western states, Mizoram, and West Bengal, where 17–33 percent of ever-married women received a home visit from a health and family planning worker, than in all other states. The survey collected information on the prevalence of tuberculosis, asthma, malaria, and jaundice among all household members. Disease prevalence based on reports from household heads must be interpreted with caution, however. The survey found that less than 1 percent of the population suffers from tuberculosis, 2 percent suffers from asthma, 4 percent suffered from malaria during the three months preceding the survey, and 1 percent suffered from jaundice during the 12 months preceding the survey. Prevalence of all four conditions is higher in rural areas than in urban areas and among men than among women. Most households in India (65 percent) go to private hospitals/clinics or doctors for treatment when a family member is ill. Only 29 percent normally use the public medical sector. Even among poor households, only 34 percent normally use the public medical sector when members become ill. Most respondents are generally satisfied with the health care they receive. xxviii Ratings on quality of services are, however, lower for public-sector facilities both in rural and urban areas than for private sector/NGO/trust facilities. NFHS-2 also collected information on selected lifestyle indicators for household members. According to household respondents, 29 percent of men and 3 percent of women smoke, 17 percent of men and 2 percent of women drink alcohol, and 28 percent of men and 12 percent of women chew paan masala or tobacco. Although the spread of HIV/AIDS is a major concern in India, 60 percent of women in India have not heard of AIDS. Awareness of AIDS is particularly low among women who are not regularly exposed to media, scheduled-tribe women, illiterate women, women living in households with a low standard of living, and rural women. Among women who have heard of AIDS, 79 percent learned about the disease from television and 42 percent from radio, suggesting that the government’s efforts to promote AIDS awareness through the electronic mass media have achieved some success. Among women who have heard of AIDS, however, one-third do not know of any way to avoid infection. Survey results suggest that health personnel could play a much larger role in promoting AIDS awareness. In India, only 4 percent of women who know about AIDS learned about the disease from a health worker. Only 12 percent of women have heard of AIDS in Bihar and 20–23 percent in Uttar Pradesh, Rajasthan, and Madhya Pradesh, compared with 87 percent or more in Mizoram, Manipur, Tamil Nadu, and Kerala. Among women who have heard of AIDS, at least one-fourth do not know of any way to avoid it in all states except Mizoram, Tamil Nadu, Orissa, and Delhi. These results suggest the need for effective IEC strategies throughout India. CHAPTER 1 INTRODUCTION 1.1 Background of the Survey India’s first National Family Health Survey (NFHS-1) was conducted in 1992–93. The Ministry of Health and Family Welfare (MOHFW) subsequently designated the International Institute for Population Sciences (IIPS), Mumbai, as the nodal agency to initiate a second survey (NFHS-2), which was conducted in 1998–99. An important objective of NFHS-2 is to provide state-level and national-level information on fertility, family planning, infant and child mortality, reproductive health, child health, nutrition of women and children, and the quality of health and family welfare services. Another important objective is to examine this information in the context of related socioeconomic and cultural factors. The survey is also intended to provide estimates at the regional level for four states (Bihar, Madhya Pradesh, Rajasthan, and Uttar Pradesh) and estimates for three metro cities (Calcutta, Chennai, and Mumbai), as well as slum areas in Mumbai. This information will assist policymakers and programme administrators in planning and implementing strategies for improving population, health, and nutrition programmes. The NFHS-2 sample covers more than 99 percent of India’s population living in all 26 states. It does not cover the union territories. NFHS-2 is a household survey with an overall target sample size of approximately 90,000 ever-married women in the age group 15–49. This report presents findings based on the analysis of all the states in India except Tripura, where the fieldwork was delayed. NFHS-2 was conducted with financial support from the United States Agency for International Development (USAID), with additional funding from UNICEF. Technical assistance was provided by ORC Macro, Calverton, Maryland, USA, and the East-West Center, Honolulu, Hawaii, USA. Thirteen field organizations were selected to collect the data. Eight of the field organizations are private sector organizations and five are Population Research Centres (PRCs) established by the Government of India in various states. Each field organization had responsibility for collecting the data in one or more states. A complete list of these field organizations is given in Appendix A. 1.2 Basic Demographic Features of India India crossed the one billion population mark in May 2000. According to the Census of India, India had a population of 548 million in 1971, 683 million in 1981, and 846 million in 1991. The exponential growth rate was virtually constant between 1961–71 and 1971–81 (2.22 and 2.20 percent, respectively), but it declined to 2.14 in 1981–91. The sex ratio of the Indian population has been unfavourable to females since the beginning of this century and has declined in every decade except 1971–81. The sex ratios were 930, 934, and 927 females per 1,000 males in 1971, 1981, and 1991, respectively. Population density increased from 177 persons per km2 in 1971 to 216 in 1981 and 267 in 1991, indicating increasing population pressure on the land. As per the 1991 Census, 37 percent of the population is in the childhood ages (0–14 years), 7 percent is in the age group 60 and over, and 55 percent is in the working-age group 15–59, which indicates a 2 high dependency burden. The process of urbanization has been rather slow in India. The percentage of the total population living in urban areas increased from 20 percent in 1971 to 23 percent in 1981 and 26 percent in 1991. During the decade 1981–91 the growth rate of the rural population was 2.00 percent per annum, while that of the urban population was 3.65 percent per annum. One-fifth of India’s population lives in Class I cities and Class II towns that have populations of 50,000 and above. One-fourth of India’s population lives in villages that have fewer than 1,000 residents. As per the 1991 Census, 16 percent of India’s population belongs to scheduled castes and 8 percent belongs to scheduled tribes1 (Central Statistical Organisation, 1999; Ministry of Health and Family Welfare, 1998a). 1.3 Economic Development India’s gross national product in the year 1999–2000 was Rs. 17.5 trillion at current prices. India’s national income (NNP at factor cost) was five times as high in 1992–93 (Rs. 2.0 trillion) as in 1950–51 (Rs. 0.4 trillion) at constant (1980–81) prices. From 1993–94 to 1998–99, the NNP increased by an additional 38 percent, reaching Rs. 9.5 trillion at 1993–94 prices. Between 1950–51 and 1992–93, however, per capita income only doubled and it increased further by only 27 percent between 1993–94 and 1998–99. In 1998–99, India’s per capita income was Rs. 14,682 at current prices. The growth rate of national income at constant prices increased from 3.6 percent per annum during the first plan (1951–56) to 6.6 percent per annum during the eighth plan (1992–97). The corresponding increase in the growth rate of per capita income was from 1.8 percent to 4.6 percent per annum (Ministry of Finance, 2000). Between 1950–51 and 1998–99, gross domestic savings and gross domestic capital formation as a percentage of the gross domestic product (GDP) increased from around 10 percent to 22 percent. Agricultural production increased nearly fourfold from 1950–51 to 1998–99. The century ended with the country’s output of food grains crossing 200 million tonnes, a fourfold increase since 1950–51, mainly due to the success of the green revolution since the 1970s. Although the area under cultivation with food grains has remained virtually constant since 1970–71, the yield has increased by 65 percent. India had to import food grains for some time after independence, but now it has emerged as a marginal exporter of food grains (Ministry of Finance, 2000). Agriculture contributes nearly one-fourth of the GDP (Reserve Bank of India, 1999) and provides a livelihood to about two-thirds of all workers in the country (Central Statistical Organisation, 1999). Although the percentage of land cultivated with food crops that is irrigated increased from 24 percent in 1970–71 to 41 percent in 1996–97, the performance of Indian agriculture still largely depends on monsoon rains. In spite of a fourfold increase in food production since the early fifties, daily per capita net availability of cereals and pulses has increased by only 18 percent, from 395 grams to 467 grams per day (Ministry of Finance, 2000). At the time of independence, India had a weak industrial base. Since 1948, within the framework of planned development of the economy, India has adopted the concept of a mixed economy for overall industrial development. The industrial policy resolution of 1948 demarcated the scope for development of industries in the private sector and also provided for reservation of some areas for exclusive development in the public sector. In subsequent industrial policy statements, the government adopted a variety of measures to modify licensing policies and 1Scheduled castes and scheduled tribes are castes and tribes that the Government of India officially recognizes as socially and economically backward and in need of special protection from injustice and exploitation. 3 regulate the private sector. Since 1980, however, the government has taken several steps towards liberalization of industrial policy (Singh, 1986). With the introduction of the New Industrial Policy, 1991, a substantial programme of structural reforms for liberalization and globalization has been undertaken to accelerate the process of making Indian industry internationally competitive. The industrial production index was more than 18 times as high in 1999–2000 (148) as it was in 1950–51 (8). Production of finished steel has increased from 1 million tonnes to 24 million tonnes, and production of coal from 32 million tonnes to 316 million tonnes. The generation of electricity has increased from 5 billion kwh to 448 billion kwh. The Indian economy is expected to grow by 5 percent in 1999–2000 and, as a result of industrial recovery, the growth of GDP from manufacturing will almost double to 7.0 percent in 1999–2000 from 3.6 percent in 1998–99. From 1950–51 to 1998–99, exports increased from US $1.3 billion to US $33.7 billion, while imports increased from US $1.3 billion to US $41.9 billion (Ministry of Finance, 2000). India’s achievements in the field of information technology have been internationally recognized. Software exports continued to show vigorous growth of over 50 percent from April to September 1999. 1.4 Performance of Social Sectors and Demographic Change The approach to the Ninth Five-Year Plan adopted by the National Development Council has accorded priority to social sector development. The goal is growth with social justice and equity. As per the latest Human Development Report (United Nations Development Program, 2000), India’s rank among countries in terms of GDP per capita is 121, while in terms of the human development index India ranks somewhat lower (128). In contrast, China’s rank in terms of the human development index (99) is not only much above India’s rank, but China ranks slightly higher than India in terms of GDP per capita (106). Some indicators of the performance of social sectors in India underscore the need for giving high priority to key sectors like education, health, and poverty eradication; these areas are also crucial for accelerating the demographic transition in India. As per the estimates of the Planning Commission, the percentage of the population living below the poverty line declined from 55 percent in 1973–74 to 36 percent in 1993–94 (Central Statistical Organisation, 1999). The literacy rate in India increased from 18 percent in 1951 to 52 percent in 1991. The literacy rate for adults in India (62 percent) is much lower than the rate in China (83 percent); in the Philippines and Thailand, the adult literacy rate is as high as 95 percent. In India, gross enrolment as a percentage of the total population for the age group 6–11 years increased from 43 percent in 1950–51 to 90 percent in 1997–98, while for ages 11–14 the corresponding increase was from 13 percent to 59 percent (Central Statistical Organisation, 1999). During the half century since India adopted the family planning programme as its official programme, India has seen the following improvements in its demographic situation (Ministry of Health and Family Welfare, 2000): • A reduction of the crude birth rate from 40.8 births per 1,000 population in 1951 to 26.4 in 1998 4 • A halving of the infant mortality rate from 146 per 1,000 live births in 1951 to 72 per 1,000 live births in 1998 • A quadrupling of the couple protection rate from 10 percent in 1971 to 44 percent in 1999 • A reduction of the crude death rate from 25 deaths per 1,000 population in 1951 to 9 in 1998 • The addition of 25 years to life expectancy from 37 years to 62 years • A reduction in the total fertility rate from 6.0 in 1951 to 3.3 in 1997 However, achievements in these areas have been less evident in India than in most other countries in Asia. India’s maternal mortality ratio (estimated at 408 maternal deaths per 100,000 live births in 1997) is several times as high as the MMR of 115 in China or 30 in Sri Lanka (Ministry of Health and Family Welfare, 2000). India’s infant mortality rate is much higher than that of China (31), Indonesia (46), and Thailand (22). Life expectancy at birth in India (62 years) is much lower than that of China, the Republic of Korea, and Malaysia (all above 70 years). India’s total fertility rate (3.3) is much higher than that of countries like China (1.8), Sri Lanka (2.1), and Thailand (1.9). Although India’s crude death rate is fairly low (9), it is still somewhat higher than the crude death rate in countries like China, Vietnam, and Sri Lanka (6). Similarly, India’ s crude birth rate is much higher than the birth rate of China (15), Thailand (16), and Sri Lanka (18) (Population Reference Bureau, 2000). India’s population, which already exceeds one billion, is expected to reach 1.26 billion by March 2016 (Ministry of Health and Family Welfare, 2000). With the objective of stabilizing the population at a level consistent with the requirements of the national economy for improving the quality of life, several measures have been adopted recently to make the family welfare programme more broad based. These measures are summarized in the next section. 1.5 Population Policies and Programmes The Family Welfare Programme in India has undergone important changes in recent years, particularly during the last five or six years. The government has dispensed with its procedure, initiated during the Fourth Five-Year Plan, of monitoring the family welfare programme on the basis of method-specific family planning targets to achieve a couple protection rate (CPR) of 60 percent. Experience has shown that the emphasis on achieving method-specific targets, particularly sterilization targets, has created a situation in which targets for numbers of acceptors gained precedence over everything else and the programme was not driven by demand. This led to the acceptance of sterilization by older and higher-parity couples at the expense of the promotion of spacing between children among younger couples. The target approach, along with incentive schemes to encourage better performance, led to unhealthy competition among states and among personnel at different levels within states. This emphasis had an adverse impact on the quality of services and care provided by the programme. Adequate emphasis was not placed on informed choice, counselling, and follow-up services to clients. The scope of the services provided by the progamme has increased consistently over the years. At the time of initiation of the programme in 1952, it was primarily a clinic-based family planning programme. After the adoption of the extension approach in 1963 and subsequent 5 integration with the maternal and child health (MCH) programme, the activities of the programme broadened significantly. In addition to family planning, the programme was supposed to provide a variety of services to mothers and children, including antenatal, delivery, and postnatal care, immunization of children against various vaccine-preventable diseases, and counselling on maternal and child health problems and nutrition. In 1992, the Child Survival and Safe Motherhood (CSSM) Programme was launched as part of the Family Welfare Programme. This was done with the intention of having an integrated package of interventions for the betterment of the health status of mothers and children. Under this programme, treatment of diarrhoea and acute respiratory infections, essential newborn care, and strengthening of emergency obstetric care services were the additional areas emphasized. In 1993, the Government of India constituted a committee under the chairmanship of Dr. M.S. Swaminathan to draft a new National Population Policy. The committee submitted its report in May 1994. The report consisted of a number of important recommendations, one of which was to abolish the target-oriented approach. After the International Conference on Population and Development (ICPD) in 1994 in Cairo, the programme was gradually reoriented towards the holistic approach of the Reproductive and Child Health (RCH) Programme. In addition to the activities covered under the CSSM Programme, the RCH Programme includes components relating to sexually transmitted diseases (STD) and reproductive tract infections (RTI). The family welfare programme’s target-free approach (TFA) was implemented throughout the country in 1996. This was done after some initial experiments to gauge the impact of making the programme target free in a few selected districts. The essence of the TFA was to modify the system of monitoring the programme and to make it a demand-driven system in which a worker would assess the needs of the community at the beginning of each year. Such an assessment would form the basis for planning and monitoring the programme during the year. Workers are supposed to assess the needs of the community on the basis of consultations with families in the area, Mahila Swasthya Sangh, anganwadis, and panchayats (Ministry of Health and Family Welfare, 1998b). To remove any misconceptions about the TFA, it was subsequently renamed the community needs assessment (CNA) approach. The recent National Population Policy (NPP), released in February 2000, paid special attention to the health and education of women and children to achieve population stabilization for the country by 2045. This suggests a paradigm shift to reproductive and child health with utmost concern towards improving the quality of care. The policy document begins with the statement that ‘the overriding objective of economic and social development is to improve the quality of lives that people lead, to enhance their well-being, and to provide them with opportunities and choices to become productive assets in society’ (Ministry of Health and Family Welfare, 2000). For the first time, the policy prepones to 2010 the time period for attaining the goal of replacement level fertility (that is, a net reproduction rate of 1.0). The NPP has elaborated 12 strategies to achieve its socio-demographic goals. The strategies can have far-reaching implications, including reductions in the high level of unwanted as well as wanted fertility. Unwanted fertility is high due to high levels of unmet need for family planning as first revealed by the 1992–93 National Family Health Survey (International Institute for Population Sciences, 1995). Wanted fertility is expected to decline with the control of infant and child mortality. 6 To achieve its objectives, the NPP reaffirms continuation of the TFA and emphasizes informed contraceptive choice and the availability of good quality services. The policy proposes decentralized planning and programme implementation. Towards the goal of lowering fertility, a number of strategies were suggested to improve RCH services, including an emphasis on education, women’s empowerment, and the involvement of men in the programme. The policy envisages free and compulsory school education up to age 14, a reduction in the infant mortality rate to less than 30 infant deaths per 1,000 live births, and a reduction in the maternal mortality ratio to less than 100 maternal deaths per 100,000 live births. The policy also aims to achieve universal immunization of children, delivery assistance by trained personnel for all births, and 100 percent registration of births, deaths, marriages, and pregnancies. Another important emphasis of the policy is the need for promoting delayed marriages for girls, the provision of wider choice and universal access to family planning information and services, and the prevention of major infectious diseases, including RTIs and AIDS. All these goals are to be achieved by 2010 to realize replacement level fertility by that year with an estimated population of 1.11 billion and population stabilization by 2045. 1.6 Questionnaires NFHS-2 collected information on a variety of indicators that will assist policymakers and programme managers to formulate and implement strategies to reach the goals set in the National Population Policy. NFHS-2 used three types of questionnaires: the Household Questionnaire, the Woman’s Questionnaire, and the Village Questionnaire. The overall content and format of the questionnaires were determined through a series of workshops held at IIPS in Mumbai in 1997 and 1998. The workshops were attended by representatives of a wide range of organizations in the population and health fields, as well as experts working on gender issues. The questionnaires for each state were bilingual, with questions in both the language of the state and English. The Household Questionnaire listed all usual residents in each sample household plus any visitors who stayed in the household the night before the interview. For each listed person, the survey collected basic information on age, sex, marital status, relationship to the head of the household, education, and occupation. The Household Questionnaire also collected information on the prevalence of asthma, tuberculosis, malaria, and jaundice, as well as three risk behaviours—chewing paan masala or tobacco, drinking alcohol, and smoking. Information was also collected on the usual place where household members go for treatment when they get sick, the main source of drinking water, type of toilet facility, source of lighting, type of cooking fuel, religion of the household head, caste/tribe of the household head, ownership of a house, ownership of agricultural land, ownership of livestock, and ownership of other selected items. In addition, a test was conducted to assess whether the household uses cooking salt that has been fortified with iodine. Finally, the Household Questionnaire asked about deaths occurring to household members in the two years before the survey, with particular attention to maternal mortality. The information on the age, sex, and marital status of household members was used to identify eligible respondents for the Woman’s Questionnaire. 7 The Woman’s Questionnaire collected information from all ever-married women age 15–49 who were usual residents of the sample household or visitors who stayed in the sample household the night before the interview. The questionnaire covered the following topics: Background characteristics: Questions on age, marital status, education, employment status, and place of residence provide information on characteristics likely to influence demographic and health behaviour. Questions are also asked about a woman’s husband, gender roles, and the treatment of women in the household. Reproductive behaviour and intentions: Questions cover dates and survival status of all births, current pregnancy status, and future childbearing intentions of each woman. Quality of care: Questions assess the quality of family planning and health services. Knowledge and use of contraception: Questions cover knowledge and use of specific family planning methods. For women not using family planning, questions are included about reasons for nonuse and intentions about future use. Sources of family planning: Questions determine where a user obtained her family planning method. Antenatal, delivery, and postpartum care: The questionnaire collects information on whether women received antenatal and postpartum care, who attended the delivery, and the nature of complications during pregnancy for recent births. Breastfeeding and health: Questions cover feeding practices, the length of breastfeeding, immunization coverage, and recent occurrences of diarrhoea, fever, and cough for young children. Reproductive health: Questions assess various aspects of women’s reproductive health and the type of care sought for health problems. Status of Women: The questionnaire asks about women’s autonomy and violence against women. Knowledge of AIDS: Questions assess women’s knowledge of AIDS and the sources of their knowledge, as well as knowledge about ways to avoid getting AIDS. In addition, the health investigator on each survey team measured the height and weight of each woman and each of her children born since January 1995 (in states where fieldwork started in 1998) or January 1996 (in states where fieldwork started in 1999) [see Table 1.1 for the month and year of fieldwork in each state]. This height and weight information is useful for assessing levels of nutrition prevailing in the population. The health investigators also took blood samples from each woman and each of her children born since January 1995/1996 to assess haemoglobin levels. This information is useful for assessing prevalence rates of anaemia among women and children. Haemoglobin levels were measured in the field at the end of each interview using portable equipment (the HemoCue) that provides test results in less than one minute. Severely anaemic women and children were referred to local medical authorities for treatment. In 8 Delhi and Mumbai, the blood samples of young children were also used to test levels of lead using the portable LeadCare instrument. For each village selected in the NFHS-2 sample, the Village Questionnaire collected information on the availability of various facilities in the village (especially health and education facilities) and amenities such as electricity and telephone connections. Respondents to the Village Questionnaire were also asked about development and welfare programmes operating in the village. The village survey included a short, open-ended questionnaire that was administered to the village head, with questions on major problems in the village and actions that could be taken to alleviate the problems. 1.7 Sample Design and Implementation Sample Size and Reporting Domains The sample size for each state was specified in terms of a target number of completed interviews with eligible women. The target sample size was set considering the size of the state, the resources available for the survey, and the aggregate level (urban/rural, region, metropolitan cities) at which separate estimates were needed. The initial target sample size was 4,000 completed interviews with eligible women in states with a 1991 population of more than 25 million, 3,000 completed interviews with eligible women in states with a 1991 population between 2 and 25 million, and 1,500 completed interviews with eligible women in states with a population of less than 2 million. However, there are some exceptions. For Uttar Pradesh, Bihar, Madhya Pradesh, and Rajasthan, the samples were designed to provide estimates for major regions of the states. The target sample size was set at 10,000 completed interviews with eligible women in Uttar Pradesh and 7,000 completed interviews with eligible women in Madhya Pradesh, Bihar, and Rajasthan. For Maharashtra, West Bengal, and Tamil Nadu, the initial target samples were increased to allow separate estimates to be made for the metropolitan cities of Mumbai, Calcutta, and Chennai. The target sample size was 5,500 in Maharashtra, 4,750 in West Bengal, and 4,750 in Tamil Nadu. For Mumbai, the target sample was large enough to allow separate estimates for its slum and non-slum populations. The urban and rural samples within each state were drawn separately and, to the extent possible, the sample within each state was allocated proportionally to the size of the state’s urban and rural populations. In states where the proportion of urban population was not sufficiently large to provide a sample of at least 1,000 completed interviews with eligible women, the urban areas were appropriately oversampled (except in Goa, Sikkim, and the six small northeastern states where the target sample size was only 1,500 eligible women each). The state samples are not large enough to provide reliable estimates for individual districts in any state. Sample Design A uniform sample design was adopted in all the states (see Table B.1 in Appendix B for a summary of the sample characteristics). In each state, the rural sample was selected in two stages: the selection of Primary Sampling Units (PSUs), which are villages, with probability proportional to population size (PPS) at the first stage, followed by the random selection of 9 households within each PSU in the second stage. In urban areas, a three-stage procedure was followed. In the first stage, wards were selected with PPS sampling. In the next stage, one census enumeration block (CEB) was randomly selected from each sample ward (except in Jammu and Kashmir, where two CEBs were randomly selected from each sample ward). In the final stage, households were randomly selected within each sample CEB. Sample Selection in Rural Areas In rural areas, the 1991 Census list of villages served as the sampling frame. The list was stratified by a number of variables. Except in Delhi, the first level of stratification was geographic, with districts being subdivided into contiguous regions. Within each of these regions, villages were further stratified using selected variables from the following list: subregions, village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. However, not all variables were used in every state. Each state was examined individually and a subset of variables was selected for stratification with the aim of creating not more than 6 strata for small states, not more than 12 strata for medium size states, and not more than 15 strata for large states. Female literacy was used for implicit stratification (i.e., the villages were ordered prior to selection according to the proportion of females who were literate) in every state except Kerala and Orissa, where female literacy was an explicit stratification variable. From the list of villages arranged in this way, villages were selected systematically with probability proportional to the 1991 Census population of the village. Small villages with 5–49 households were linked with an adjoining village to form PSUs with a minimum of 50 households. Villages with fewer than five households were excluded from the sampling frame. In every state, a mapping and household listing operation was carried out in each sample area. The listing provided the necessary frame for selecting households at the second stage. The household listing operation involved preparing up-to-date notional and layout sketch maps of each selected PSU, assigning numbers to structures, recording addresses of these structures, identifying residential structures, and listing the names of heads of all the households in residential structures in the selected PSUs. Large sample villages (with more than a specified number of households, usually 500) were segmented, and two segments were selected randomly using the PPS method. Household listing in the segmented PSUs was carried out only in the selected segments. Each household listing team comprised one lister and one mapper. Senior field staff of the concerned field organization supervised the listing operation. The households to be interviewed were selected with equal probability from the household list in each area using systematic sampling. The interval applied for the selection was determined to obtain a self-weighting sample of households. On average, 30 households were initially targeted for selection in each selected enumeration area. To avoid extreme variations in the workload, minimum and maximum limits were put on the number of households that could be selected from any area, at 15 and 60, respectively. Each survey team supervisor was provided with the original household listing, layout sketch map, and the list of selected households for each PSU. All the households which were selected were contacted during the main survey, and no replacement was made if a selected household was absent during data collection. However, if a PSU was inaccessible, a replacement PSU with similar characteristics was selected by IIPS and provided to the field organization. 10 Sample Selection in Urban Areas The procedure adopted for the first stage of the sample design in urban areas was similar to the one followed in rural areas. The 1991 Census list of wards was arranged according to districts and within districts by the level of female literacy, and a sample of wards was selected systematically with probability proportional to size. Next, one census enumeration block, consisting of approximately 150–200 households, was selected from each selected ward using the PPS method. In Jammu and Kashmir, two census enumeration blocks were selected in each selected ward. As in rural areas, a household listing operation was carried out in each selected census enumeration block, which provided the necessary frame for selecting households in the third stage of sample selection. On average, 30 households per block were targeted for selection (except in Jammu and Kashmir and in Mumbai, where the target was 20 households per block). Sample Weights2 At the national level, the overall sample weight for each household or woman is the product of the design weight for each state (after adjustment for nonresponse) and the state weight. The national weights are defined below: Let Wsij = weight for the j th household (or woman) in the ith PSU in state s Wasij = weight for the j th household (or woman) in the ith PSU in state s for the national estimate where Ps = projected population of state s After adjustment for nonresponse, the weights are normalized so that the total number of weighted cases is equal to the total number of unweighted cases. The final normalized weight for a household (or eligible woman) for the national estimate is: Wbsij = normalized weight for the j th household (or woman) in the ith PSU in state s for the national estimate 2The population covered in NFHS-2 differs slightly from that in NFHS-1. NFHS-1 did not include Sikkim and the Kashmir region of Jammu and Kashmir. NFHS-2 covered all the 26 states, but the survey work in Tripura was delayed considerably due to some local problems. Therefore, estimates for Tripura are not included in the national estimates. However, the population of the regions not common in the two surveys is small and should have only a negligible impact on the comparability of the national estimates from the two surveys. sij ij sij s W W P *∑= W W P P n sij ij sij si **∑ ∑ = 11 where P = projected population of the 25 states3 ni = sample size in the i th state For the tabulations on anaemia and height/weight of women and children, two separate sets of weights were calculated using a similar procedure. In this case, however, the response rates for anaemia (for both women and children) are based on the percentage of eligible women whose haemoglobin level was measured and the response rates for height/weight (for both women and children) are based on the percentage of eligible women who were weighed or measured. Sample Implementation In order to achieve better coordination and supervision, the NFHS-2 survey operation was carried out in two phases. The first phase included the states of Andhra Pradesh, Bihar, Gujarat, Haryana, Madhya Pradesh, Punjab, Rajasthan, Sikkim, Uttar Pradesh, and West Bengal. The second phase states were Arunachal Pradesh, Assam, Delhi, Goa, Himachal Pradesh, Jammu and Kashmir, Karnataka, Kerala, Maharashtra, Manipur, Meghalaya, Mizoram, Nagaland, Orissa, and Tamil Nadu. Tripura fieldwork was delayed due to local problems. Table 1.1 shows the period of fieldwork, number of households and eligible women interviewed (excluding Tripura), and the household and women’s response rates. A total of 91,196 households were interviewed, two-thirds of which were rural. The overall household response rate—the number of households interviewed per 100 occupied households—was 98 percent. The household response rate was more than 94 percent in every state except Meghalaya and Delhi where it was 89 percent and 91 percent, respectively. The household response rate was almost 100 percent in Tamil Nadu. In the interviewed households, interviews were completed with 89,199 eligible women who stayed in the household the night before the household interview. The individual response rate—the number of completed interviews per 100 identified eligible women in the households with completed interviews—was 96 percent for the country as a whole. The variation in the women’s response rate by state was similar to that observed for the household response rate. 1.8 Recruitment, Training, and Fieldwork In order to maintain uniform survey procedures across the states, four manuals dealing with different aspects of the survey were prepared. The Interviewer’s Manual consists of instructions to the interviewers regarding interviewing techniques, field procedures, and the method of asking questions and recording answers. The Manual for Field Editors and Supervisors contains a detailed description of the role of field editors and supervisors in the survey. A list of checks to be made by the field editor in the filled-in questionnaires is also provided in this manual. The Household Listing Manual, designed for household listing teams, contains procedures to be adopted for household listing. Guidelines for the training of the field staff are described in the manual entitled Training Guidelines. 3All states except Tripura 12 Representatives of each field organization were trained in Training of Trainers Workshops organized by IIPS at the beginning of each phase of data collection. The purpose of these workshops was to ensure uniformity in data collection procedures in different states. The workshops covered the objectives of NFHS-2, different aspects of the survey, roles of various organizations participating in the survey, details of each of the three questionnaires used in the survey, methods of data collection and field supervision, and guidelines for the training of the field staff. Persons who were trained in each workshop subsequently trained the field staff in each state according to the standard procedures discussed in the Training of Trainers Workshops. Table 1.1 Number of households and women interviewed by state Month and year of fieldwork and number of households and women interviewed by residence and state (based on the unweighted sample), India, 1998–99 Month and year of fieldwork Number of households interviewed Number of women interviewed State From To Urban Rural Total Urban Rural Total Household response rate Women’s response rate India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 11/98 12/99 30,435 60,761 91,196 27,862 61,337 89,199 97.5 95.5 3/99 4/99 2,564 199 2,763 2,287 190 2,477 91.3 90.8 11/98 5/99 891 1,950 2,841 826 2,082 2,908 98.5 97.6 4/99 8/99 1,086 2,357 3,443 835 2,177 3,012 99.3 96.5 4/99 9/99 887 1,899 2,786 797 1,947 2,744 97.0 93.4 11/98 5/99 1,066 1,901 2,967 993 1,803 2,796 98.5 97.3 11/98 2/99 1,546 4,765 6,311 1,592 5,221 6,813 95.9 92.8 11/98 4/99 1,799 4,950 6,749 1,829 5,112 6,941 97.5 97.5 12/98 3/99 1,835 6,847 8,682 1,813 7,479 9,292 96.7 93.0 12/98 4/99 701 5,644 6,345 687 6,337 7,024 98.8 96.2 3/99 6/99 932 3,757 4,689 868 3,557 4,425 99.2 98.4 12/98 4/99 2,335 2,390 4,725 1,947 2,461 4,408 96.6 96.6 5/99 8/99 174 1,245 1,419 145 972 1,117 94.4 91.6 3/99 6/99 838 2,283 3,121 808 2,633 3,441 98.1 96.1 7/99 10/99 536 1,153 1,689 479 956 1,435 99.6 96.8 5/99 12/99 256 984 1,240 193 752 945 89.0 90.5 6/99 8/99 781 592 1,373 597 451 1,048 97.6 94.3 5/99 12/99 237 896 1,133 167 651 818 98.4 98.0 12/98 3/99 164 1,135 1,299 129 978 1,107 96.2 94.3 3/99 6/99 623 976 1,599 491 755 1,246 98.6 95.0 11/98 3/99 1,709 2,223 3,932 1,657 2,188 3,845 98.4 96.6 3/99 6/99 3,662 2,168 5,830 3,191 2,200 5,391 97.6 94.1 11/98 3/99 1,018 2,854 3,872 1,068 2,964 4,032 99.4 98.2 3/99 9/99 1,552 2,721 4,273 1,504 2,870 4,374 97.1 94.7 3/99 7/99 855 1,979 2,834 846 2,038 2,884 98.0 92.9 3/99 6/99 2,388 2,893 5,281 2,113 2,563 4,676 99.8 99.7 Note: This table is based on the unweighted sample; all other tables are based on the weighted sample unless otherwise specified. This table shows the number of households and de facto women with completed interviews. The household response rate is defined as the number of households interviewed per 100 occupied households. The women’s response rate is defined as the number of eligible women interviewed per 100 eligible women identified in the selected households. Information on Tripura is not included in this report because the fieldwork was not completed at the time this report was prepared. 13 The fieldwork in each state was carried out by a number of interviewing teams, each team consisting of one field supervisor, one female field editor, four female interviewers, and one health investigator. The number of interviewing teams in each state varied according to the sample size. In each state, interviewers were hired specifically for NFHS-2, taking into consideration their educational background, experience, and other relevant qualifications. All interviewers were female, a stipulation that was necessary to ensure that women who were survey respondents would feel comfortable talking about topics that they may find somewhat sensitive. Training of the field staff lasted for a minimum of three weeks in each state. The training course consisted of instruction in interviewing techniques and survey field procedures, a detailed review of each item in the questionnaires, instruction and practice in weighing and measuring children, mock interviews between participants in the classroom, and practice interviews in the field. In addition, at least two special lectures were arranged in each state: one on the topic of family planning at the beginning of training on the section on contraception in the Woman’s Questionnaire, and one on maternal and child health practices, including immunizations, at the beginning of training on the section on the health of children. In addition to the main training, two days’ training was arranged for field editors and supervisors, which focused on the organization of fieldwork as well as methods of detecting errors in field procedures and in the filled-in questionnaires. Health investigators attached to interviewing teams were given additional specialized training on measuring height and weight and testing for anaemia in a centralized training programme conducted by IIPS in collaboration with the All India Institute of Medical Sciences (AIIMS), New Delhi. This specialized training included classroom training and extensive field practice in schools, anganwadis, and communities. Assignment of Primary Sampling Units (PSUs) to the teams and various logistical decisions were made by the survey coordinators from each field organization. Each interviewer was instructed not to conduct more than three individual interviews a day and was required to make a minimum of three callbacks if no suitable informant was available for the household interview or if the eligible woman identified in the selected household was not present at the time of the household interview. The main duty of the field editor was to examine the completed questionnaires in the field for completeness, consistency, and legibility of the information collected, and to ensure that all necessary corrections were made. Special attention was paid to missing information, skip instructions, filter questions, age information, and completeness of the birth history and the health section. If major problems were detected, such as discrepancies between the birth history and the health section, the interviewers were required to revisit the respondent to correct the errors. An additional duty of the field editor was to observe ongoing interviews and verify the accuracy of the method of asking questions, recording answers, and following skip instructions. The field supervisor was responsible for the overall operation of the field team and collection of information on villages using the Village Questionnaire. In addition, the field supervisor conducted spot-checks to verify the accuracy of information collected on the eligibility of respondents. IIPS also appointed one or more research officers in each state to help with monitoring throughout the training and fieldwork period in order to ensure that correct survey procedures were followed and data quality was maintained. Survey directors and other senior staff from the field organizations, project coordinators, other faculty members from IIPS, 14 senior research officers, and staff members from ORC Macro and the East-West Center also visited the field sites to monitor the data collection operation. Medical health coordinators appointed by IIPS monitored the nutritional component of the survey. Field data were quickly entered into microcomputers, and field-check tables were produced to identify certain types of errors that might have occurred in eliciting information and filling out questionnaires. Information from the field-check tables was fed back to the interviewing teams and their supervisors so that their performance could be improved. 1.9 Data Processing All completed questionnaires were sent to the office of the concerned field organization (FO) for editing and data processing (including office editing, coding, data entry, and machine editing). Although field editors examined every completed questionnaire in the field, the questionnaires were re-edited at the FO headquarters by specially trained office editors. The office editors checked all skip sequences, response codes that were circled, and information recorded in filter questions. Special attention was paid to the consistency of responses to age questions and the accurate completion of the birth history. In the second stage of office editing, appropriate codes were assigned for open-ended responses on occupation and cause of death, and commonly mentioned “other” responses were added to the coding scheme. For each state, the data were processed with microcomputers using the data entry and editing software known as the Integrated System for Survey Analysis (ISSA). The data were entered directly from the precoded questionnaires, usually starting within one week of the receipt of the first set of completed questionnaires. Data entry and editing operations were usually completed a few days after the end of fieldwork in each state. Computer-based checks were used to clean the data and remove inconsistencies. Age imputation was also completed at this stage. Age variables such as the woman’s current age and the year and month of birth of all of her children were imputed for those cases in which information was missing or incorrect entries were detected. Preliminary reports with selected results were prepared for each state within a few months of data collection and presented to policymakers and programme administrators responsible for improving health and family welfare programmes. Detailed NFHS-2 state reports are being prepared by IIPS, in collaboration with the Population Research Centres, other local organizations, ORC Macro, and the East-West Center. The state reports contain detailed information on such topics as the state’s survey design and implementation, household and respondent background characteristics, fertility and fertility preferences, family planning, mortality, morbidity, child immunization, lifestyle indicators, domestic violence, knowledge of HIV/AIDS, nutritional status of women and children, infant feeding practices, anaemia among women and children, maternal care and reproductive health, and the quality of care of health and family welfare services. CHAPTER 2 BACKGROUND CHARACTERISTICS OF HOUSEHOLDS This chapter presents a profile of the demographic and socioeconomic characteristics of NFHS-2 households and describes facilities and services that are available in villages in India. The chapter also includes some comparisons of NFHS-2 results with results from NFHS-1, the Census of India, and the Sample Registration System (SRS). 2.1 Age-Sex Distribution of the Household Population The NFHS-2 household population can be tabulated in two ways: de facto (the place each person stayed the night before the survey interview) or de jure (the place of usual residence). The de facto and de jure populations in India may differ because of temporary population movements within or between states. Table 2.1 shows the de facto population in the NFHS-2 household sample for India, classified by age, residence, and sex. The total de facto sample population is 486,011. The sample is 27 percent urban and 73 percent rural. The age distribution of the population in India is typical of populations in which fertility has fallen recently, with relatively low proportions of the population in the younger and older age groups (Figure 2.1). Thirty-six percent are below 15 years of age and 5 percent are age 65 or older. The proportion below age 15 is slightly higher in rural areas (38 percent) than in urban areas (32 percent). The single-year age distributions by sex in the de facto population (see Appendix Table D.1) indicate that there is some misreporting of ages, including considerable preference for ages ending in particular digits, especially 0, 2, and 5. One of the most commonly used measures of digit preference in age reporting is Myers’ Index (United Nations, 1955). This index provides an overall summary of preferences for, or avoidance of, each of the 10 digits, from 0 to 9. Values of Myers’ Index computed for the age range 10–69 in the household sample population in India are 23 for males and 18 for females. The index is often used as one indicator of survey quality. The lower estimate for females is probably due to the emphasis during the interviewer training on obtaining accurate age information for women to correctly determine the eligibility of women for the individual interview. The values of Myers’ Index from NFHS-2 are almost the same as from NFHS-1 (revised from the published NFHS-1 estimates). This indicates that age reporting on the household questionnaire is of the same quality in NFHS-2 and NFHS-1. Table 2.2 compares the age distributions by sex from the NFHS-2 de jure sample with the age distributions by sex from the Sample Registration System for 1997. The SRS baseline survey, which is de jure, counts all usual residents in a sample area (Office of the Registrar General, 1999a). The NFHS-2 and SRS age distributions are similar for broad age groups, despite the misreporting of age that is evident in the NFHS-2 single-year age data. 16 Table 2.1 Household population by age and sex Percent distribution of the household population by age, according to residence and sex, India, 1998–99 Urban Rural Total Age Male Female Total Male Female Total Male Female Total < 1 1–4 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+ Total percent Number of persons Sex ratio1 2.0 1.9 1.9 2.6 2.4 2.5 2.4 2.3 2.3 7.7 7.8 7.8 9.7 9.5 9.6 9.2 9.0 9.1 10.7 10.6 10.6 13.8 13.0 13.4 13.0 12.4 12.7 11.5 11.1 11.3 12.5 11.9 12.2 12.2 11.7 12.0 11.1 10.8 11.0 10.0 10.3 10.1 10.3 10.4 10.4 9.8 10.3 10.0 7.8 9.2 8.5 8.4 9.5 8.9 8.7 9.1 8.9 7.4 8.6 8.0 7.7 8.7 8.2 7.2 7.5 7.3 6.4 6.9 6.6 6.6 7.0 6.8 7.0 7.2 7.1 6.4 6.0 6.2 6.5 6.3 6.4 5.7 5.3 5.5 4.8 4.4 4.6 5.1 4.7 4.9 5.1 4.6 4.8 4.2 3.9 4.1 4.4 4.1 4.3 3.6 3.4 3.5 3.3 2.9 3.1 3.4 3.0 3.2 2.8 3.1 3.0 2.6 3.2 2.9 2.6 3.2 2.9 2.6 2.6 2.6 3.0 3.1 3.1 2.9 3.0 2.9 1.8 2.0 1.9 2.1 2.0 2.0 2.0 2.0 2.0 1.4 1.4 1.4 1.8 1.4 1.6 1.7 1.4 1.6 0.7 0.6 0.7 0.7 0.6 0.6 0.7 0.6 0.6 0.6 0.8 0.7 0.9 0.8 0.8 0.8 0.8 0.8 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 66,790 62,520 129,310 181,223 175,477 356,700 248,014 237,997 486,011 NA NA 936 NA NA 968 NA NA 960 Note: Table is based on the de facto population, i.e., persons who stayed in the household the night before the interview (including both usual residents and visitors). NA: Not applicable 1Females per 1,000 males Figure 2.1 Population Pyramid 8 6 4 2 0 2 4 6 8 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+ Age Percent FemaleMale NFHS-2, India, 1998–99 17 Table 2.2 Population by age and sex from the SRS and NFHS-2 Percent distribution of population by age and sex from the SRS and NFHS-2, India, 1997–99 SRS (1997) NFHS-2 (1998–99) Age Male Female Male Female Sex ratio1 URBAN 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+ Total Median age 9.9 9.8 10.7 10.6 11.2 11.2 10.1 10.0 10.0 10.5 9.3 9.4 8.3 8.6 7.3 6.9 6.2 5.9 4.9 4.4 3.8 3.7 2.7 2.7 2.3 2.5 1.5 1.7 1.9 2.1 100.0 100.0 U U 9.4 9.5 931 10.6 10.5 920 11.5 11.2 902 11.1 10.7 893 9.8 10.2 958 8.6 9.0 966 7.2 7.5 968 7.1 7.3 951 5.8 5.3 857 5.1 4.7 856 3.6 3.4 869 2.8 3.2 1,055 2.6 2.6 950 1.8 2.0 1,010 2.7 2.9 972 100.0 100.0 928 23.6 23.8 NA RURAL 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+ Total Median age 11.8 11.5 13.5 13.2 12.4 11.9 10.1 9.3 8.9 9.0 8.1 8.4 7.0 7.6 6.3 6.0 5.1 5.3 4.2 4.0 3.6 3.7 2.6 2.8 2.6 2.9 1.7 1.9 2.2 2.6 100.0 100.0 U U 11.9 11.7 948 13.6 13.0 915 12.3 12.0 929 10.2 10.1 953 8.0 9.0 1,075 7.5 8.6 1,096 6.5 6.9 1,022 6.5 6.0 891 4.9 4.5 890 4.2 4.0 891 3.3 2.9 850 2.6 3.3 1,221 3.0 3.2 996 2.1 2.0 928 3.4 2.7 755 100.0 100.0 957 20.8 21.2 NA 18 Tables 2.1 and 2.2 also present sex ratios (females per 1,000 males) in India from NFHS-2. The sex ratio for the de facto population (960) in Table 2.1 is slightly higher than the sex ratio of the de jure population (949) in Table 2.2. The sex ratio for the de facto sample is 936 in urban areas and 968 in rural areas, suggesting that rural-urban migration has been dominated by males in India. 2.2 Marital Status NFHS-2 includes information on the marital status of all household members age six and above. Table 2.3 shows the marital status distribution of the de facto household population, classified by age, residence, and sex. Among females age six and above, 53 percent are currently married and 36 percent have never been married. The proportion never married is higher for males (48 percent) than for females (36 percent) and slightly higher in urban areas (49 percent for males and 38 percent for females) than in rural areas (47 percent for males and 35 percent for females). The proportion divorced, separated, or deserted is small and widowhood is quite limited until the older ages. Forty-three percent of women age 50 or older are widowed, but only 12 percent of men in that age group are widowed. Table 2.2 Population by age and sex from the SRS and NFHS-2 (contd.) Percent distribution of population by age and sex from the SRS and NFHS-2, India, 1997–99 SRS (1997) NFHS-2 (1998–99) Age Male Female Male Female Sex ratio1 TOTAL 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+ Total Median age 11.4 11.1 12.8 12.6 12.1 11.7 10.1 9.5 9.2 9.4 8.3 8.6 7.3 7.8 6.5 6.2 5.4 5.4 4.3 4.1 3.6 3.7 2.6 2.8 2.5 2.8 1.7 1.9 2.2 2.5 100.0 100.0 U U 11.2 11.1 944 12.8 12.4 916 12.1 11.8 922 10.4 10.3 936 8.5 9.3 1,039 7.8 8.7 1,057 6.7 7.1 1,007 6.6 6.4 908 5.1 4.7 880 4.5 4.2 880 3.4 3.1 855 2.6 3.3 1,173 2.9 3.0 985 2.0 2.0 948 3.3 2.8 803 100.0 100.0 949 21.8 22.1 NA Note: Table is based on the de jure population, i.e., usual residents. NA: Not applicable U: Not available 1Females per 1,000 males Source for SRS: Office of the Registrar General, 1999a 19 Table 2.3 Marital status of the household population Percent distribution of the household population age 6 and above by marital status, according to age, residence, and sex, India, 1998–99 Marital status Age Never married Currently married Married, gauna not performed Widowed Divorced Separated Deserted Total percent URBAN Male 6–12 13–14 15–19 20–24 25–29 30–49 50+ Total 99.7 0.2 0.1 0.0 0.0 0.0 0.0 100.0 99.6 0.2 0.2 0.0 0.0 0.0 0.0 100.0 97.5 2.0 0.5 0.0 0.0 0.0 0.0 100.0 78.4 20.7 0.5 0.2 0.1 0.0 0.1 100.0 39.1 59.7 0.2 0.3 0.1 0.3 0.4 100.0 5.7 92.4 0.0 1.0 0.2 0.2 0.4 100.0 1.3 89.0 0.0 9.3 0.0 0.1 0.2 100.0 49.4 48.3 0.2 1.8 0.1 0.1 0.2 100.0 Female 6–12 13–14 15–19 20–24 25–29 30–49 50+ Total 99.6 0.2 0.2 0.0 0.0 0.0 0.0 100.0 99.0 0.6 0.5 0.0 0.0 0.0 0.0 100.0 82.2 16.4 1.2 0.1 0.1 0.1 0.1 100.0 36.3 61.8 0.4 0.3 0.5 0.2 0.5 100.0 9.8 87.4 0.0 1.1 0.5 0.3 0.7 100.0 2.3 88.9 0.1 6.8 0.5 0.5 0.9 100.0 1.0 52.8 0.0 45.2 0.2 0.4 0.4 100.0 38.2 51.3 0.3 9.2 0.3 0.3 0.5 100.0 RURAL Male 6–12 13–14 15–19 20–24 25–29 30–49 50+ Total 99.3 0.4 0.3 0.0 0.0 0.0 0.0 100.0 98.7 0.4 0.9 0.0 0.0 0.0 0.0 100.0 92.2 4.9 2.8 0.0 0.0 0.0 0.1 100.0 59.6 37.6 2.1 0.3 0.1 0.1 0.1 100.0 23.1 74.9 0.6 0.6 0.3 0.2 0.3 100.0 3.3 94.2 0.1 1.7 0.2 0.2 0.3 100.0 1.3 85.0 0.0 13.3 0.1 0.1 0.2 100.0 46.8 49.4 0.7 2.8 0.1 0.1 0.2 100.0 Female 6–12 13–14 15–19 20–24 25–29 30–49 50+ Total 98.8 0.4 0.8 0.0 0.0 0.0 0.0 100.0 95.0 1.6 3.4 0.0 0.0 0.0 0.0 100.0 60.4 34.4 4.5 0.1 0.2 0.1 0.2 100.0 15.1 81.7 0.9 0.8 0.6 0.3 0.6 100.0 3.9 92.7 0.1 1.7 0.5 0.4 0.6 100.0 1.0 90.0 0.0 6.9 0.6 0.5 1.0 100.0 0.5 55.7 0.0 42.8 0.2 0.3 0.4 100.0 35.1 53.9 1.0 9.0 0.3 0.3 0.5 100.0 20 Also of interest is the proportion of persons who marry young. At age 15–19, the proportions ever married are 3 percent for males and 18 percent for females in urban areas, 8 percent for males and 40 percent for females in rural areas, and 6 percent for males and 34 percent for females in the country as a whole. By age 25–29, almost all women (95 percent) have ever been married. Only 72 percent of males in this age group have ever been married (61 percent in urban areas and 77 percent in rural areas). Overall, the table shows that women in India marry at much younger ages than men, and that both men and women marry at younger ages in rural areas than in urban areas. Table 2.4 shows estimates of the singulate mean age at marriage (SMAM), which can be calculated from age-specific proportions single in a census or household survey. SMAM is calculated from the de jure population in NFHS-2 in order to arrive at estimates that are more comparable to those derived from the censuses, which are modified de jure counts. According to the SMAM measure, men in India tend to marry women who are five years younger than themselves. The census and NFHS-2 data indicate that the age at marriage has been rising for both men and women at approximately the same rate (about two and one-half years between 1971 and 1998–99). Marriage ages are higher in urban areas, with urban men and women marrying about two and one-half years later than their rural counterparts. The SMAM for Table 2.3 Marital status of the household population (contd.) Percent distribution of the household population age 6 and above by marital status, according to age, residence, and sex, India, 1998–99 Marital status Age Never married Currently married Married, gauna not performed Widowed Divorced Separated Deserted Total percent TOTAL Male 6–12 13–14 15–19 20–24 25–29 30–49 50+ Total 99.4 0.3 0.2 0.0 0.0 0.0 0.0 100.0 98.9 0.4 0.7 0.0 0.0 0.0 0.0 100.0 93.7 4.0 2.1 0.0 0.0 0.0 0.1 100.0 65.6 32.3 1.6 0.3 0.1 0.1 0.1 100.0 27.9 70.3 0.5 0.5 0.2 0.3 0.3 100.0 4.0 93.7 0.1 1.5 0.2 0.2 0.3 100.0 1.3 86.0 0.0 12.3 0.1 0.1 0.2 100.0 47.5 49.1 0.6 2.5 0.1 0.1 0.2 100.0 Female 6–12 13–14 15–19 20–24 25–29 30–49 50+ Total 99.0 0.3 0.6 0.0 0.0 0.0 0.0 100.0 96.1 1.3 2.6 0.0 0.0 0.0 0.0 100.0 66.4 29.5 3.6 0.1 0.2 0.1 0.2 100.0 21.2 76.0 0.8 0.6 0.6 0.3 0.6 100.0 5.5 91.3 0.1 1.5 0.5 0.4 0.7 100.0 1.4 89.7 0.1 6.9 0.6 0.5 1.0 100.0 0.6 55.0 0.0 43.4 0.2 0.3 0.4 100.0 35.9 53.2 0.8 9.0 0.3 0.3 0.5 100.0 Note: Table is based on the de facto population, i.e., persons who stayed in the household the night before the interview (including both usual residents and visitors). The marital status distribution for females by age cannot be directly compared with the published distribution for NFHS-1 because the ages in the current table are based entirely on the reports of the household respondents, whereas in NFHS-1 the ages of ever-married women age 13–49 were taken from the Woman’s Questionnaire. Table 2.4 Singulate mean age at marriage by state Singulate mean age at marriage from selected sources by sex and state, India, 1971–1998/99 NFHS-2 (1998–99) 1971 Census 1981 Census 1991 Census Urban Rural Total State Male Female Male Female Male Female Male Female Male Female Male Female India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 22.6 17.2 23.5 18.4 24.0 19.3 24.0 20.0 24.3 20.5 24.2 20.6 20.9 17.7 25.2 17.9 22.8 18.8 23.5 17.7 24.2 19.2 24.5 20.3 U U U U U U 24.1 20.1 25.0 21.1 24.3 21.0 19.9 15.1 20.6 16.1 21.3 17.5 19.5 15.0 20.8 16.6 21.7 17.8 19.8 15.5 21.3 16.7 21.9 18.0 20.0 15.3 21.6 16.6 22.1 17.5 22.7 17.3 24.3 19.1 25.0 20.2 24.6 18.0 26.0 19.3 25.9 19.7 25.6 19.6 U U 25.1 20.1 25.8 18.7 U U U U 26.4 22.2 27.3 23.4 28.1 24.7 25.5 20.2 26.0 21.0 25.8 21.4 U U U U 26.7 22.4 27.8 24.0 29.0 24.8 28.9 24.9 U U U U 25.8 21.4 U U 28.5 23.0 29.4 24.2 22.4 18.5 23.3 19.6 23.4 19.9 23.8 17.6 24.4 18.8 24.8 19.7 22.8 16.3 23.1 17.3 23.5 18.3 25.2 17.9 26.0 19.3 26.2 20.1 27.0 21.3 27.5 22.1 27.7 22.2 26.1 19.6 26.1 20.3 26.4 20.9 26.5 21.5 24.2 19.0 24.9 19.7 26.0 22.1 24.1 19.9 25.8 21.9 25.2 21.4 24.3 19.2 24.6 19.8 27.2 23.7 26.6 21.9 26.7 22.1 29.1 24.5 26.5 21.9 27.1 22.5 26.4 23.2 25.5 21.6 25.7 22.1 24.1 19.9 21.6 17.8 22.3 18.3 26.0 20.9 22.4 18.2 23.5 18.9 26.2 21.5 22.4 18.3 23.3 19.0 26.3 20.9 23.5 18.5 23.8 18.8 27.7 22.8 26.4 21.0 26.6 21.2 29.0 22.4 25.2 18.7 26.2 19.6 23.9 21.9 25.3 21.6 25.1 21.6 29.3 23.6 27.7 21.5 27.8 21.7 28.7 25.9 28.6 25.0 28.6 25.4 27.8 25.0 26.7 22.2 27.0 23.0 27.5 24.7 26.3 23.2 27.0 24.1 28.4 23.4 27.3 22.9 27.6 23.0 24.7 23.0 26.5 21.7 26.2 21.9 30.3 25.2 30.1 24.4 30.2 24.8 25.0 21.1 23.8 19.6 24.4 20.2 26.0 21.3 24.6 18.6 25.3 19.8 25.8 20.3 23.1 17.6 23.9 18.3 27.8 21.5 26.1 19.4 26.7 20.1 28.9 22.7 27.6 21.2 27.9 21.5 27.1 21.7 26.4 20.4 26.6 20.9 Note: Table is based on the de jure population. U: Not available 22 females in India as estimated in NFHS-2 is 21.5 years in urban areas, 19.0 years in rural areas, and 19.7 years for the country as a whole. SMAM varies substantially across states. The female SMAM is lowest in Rajasthan and Andhra Pradesh (18.3 years) and highest in Manipur (25.4 years), followed by Goa (24.8 years). The mean age at marriage for females is also below the national average in the Central Region, and in Bihar and West Bengal. In addition to Goa, the SMAM is higher than 21 years in all of the northeastern states, most states in the North Region, Kerala and Orissa. Similar differences across the states are also found for the SMAM for males. 2.3 Household Composition Table 2.5 shows the percent distribution of households by various characteristics of the household head (sex, age, religion, and caste/tribe), as well as by household type and the number of usual household members. The table is based on the de jure population because household type and the number of usual household members pertain to the usual-resident population. The table shows that 89–90 percent of household heads are male, regardless of area of residence (rural or urban). More than two-thirds of household heads are 30–59 years of age and the median age of household heads is 45 years in both urban and rural areas. Eighty-two percent of household heads are Hindu, 12 percent are Muslim, 3 percent are Christian, 2 percent are Sikh, 1 percent are Buddhist or Neo-Buddhist, and less than 0.5 percent are Jain. The percent distribution of household heads by religion is almost identical in NFHS-2 and NFHS-1, and is very close to the religious distribution of the population enumerated in the 1991 Census. Muslims constitute 15 percent of urban households, but only 10 percent of rural households. Christians, Jains, and Buddhists are also more concentrated in urban areas than in rural areas. Nineteen percent of household heads belong to scheduled castes and 9 percent belong to scheduled tribes. Both of these groups, but especially scheduled tribes, constitute higher proportions of households in rural areas than in urban areas. Almost one-third of household heads belong to other backward classes (OBC)1. The largest proportion of household heads (39 percent) belong to the ‘other’ caste category. Fifty-seven percent of all households are nuclear family households (consisting of an unmarried adult living alone or a married person or couple and their unmarried children, if any). Mean household size (5.4 persons per household in India as a whole) is slightly higher in rural areas (5.5) than in urban areas (5.2). States differ substantially in terms of the distribution of household heads by religion and caste/tribe (Table 2.6). In 18 of the 25 states, a large majority of household heads are Hindu. More than half of household heads in Jammu and Kashmir, more than one-quarter in Assam and Kerala, and more than one-fifth in West Bengal are Muslim. Other states with at least 15 percent of Muslim household heads are Uttar Pradesh and Bihar and with at least 10 percent of Muslim household heads are Karnataka and Maharashtra. The largest percentages of households headed by Christians are in Mizoram (96 percent), Nagaland (82 percent), Meghalaya (73 percent), Manipur (37 percent), and Goa (33 percent). Sikhs are concentrated primarily in Punjab, where they constitute 54 percent of households. One-third of household heads in Sikkim are Buddist or Neo-Buddhist. Eleven percent of household heads in Arunchal Pradesh and 7 percent in Maharashtra are also Buddhist or Neo-Buddhist. The proportion of household heads who come from ‘other religions’ is 36 percent in Arunachal Pradesh (almost all of whom are from the Doni- polo religion) and 11 percent in Manipur (almost all of whom are from the Sanamahi religion). 1Other backward classes are castes and communities that have been designated by the Government of India as socially and educationally backward and in need of protection from social injustice. 23 Table 2.5 Household characteristics Percent distribution of households by selected characteristics of the household head, household type, and household size, according to residence, India, 1998–99 Characteristic Urban Rural Total Sex of household head Male Female Age of household head < 30 30–44 45–59 60+ Median age Religion of household head Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Missing Caste/tribe of household head Scheduled caste Scheduled tribe Other backward class Other Don’t know/missing Household type Nuclear household Non-nuclear household Number of usual members 1 2 3 4 5 6 7 8 9+ Mean household size Total percent Number of households 88.9 90.0 89.7 11.1 10.0 10.3 9.7 11.4 10.9 39.1 38.2 38.4 32.1 28.1 29.2 19.2 22.4 21.5 45.2 45.1 45.1 77.2 83.7 81.9 15.0 10.4 11.7 3.6 2.7 3.0 1.6 1.8 1.7 0.9 0.2 0.4 1.4 0.6 0.8 0.1 0.3 0.3 0.0 0.1 0.1 0.1 0.1 0.1 14.7 20.2 18.7 3.7 11.2 9.1 29.6 33.5 32.4 51.5 33.9 38.8 0.5 1.1 1.0 59.3 55.6 56.6 40.7 44.3 43.3 3.2 3.1 3.1 7.6 7.9 7.8 13.1 10.9 11.5 21.4 17.5 18.6 19.3 18.4 18.7 13.7 14.9 14.5 7.9 10.0 9.4 4.9 6.3 5.9 8.8 11.0 10.4 5.2 5.5 5.4 100.0 100.0 100.0 25,243 65,953 91,196 Note: Table is based on the de jure population. Table 2.6 Religion and caste/tribe of household head by state Percent distribution of households by religion and caste/tribe of the household head, according to state, India, 1998–99 Religion of household head Caste/tribe of household head State Hindu Muslim Christian Sikh Jain Buddhist/ Neo- Buddhist Other1 No religion Missing Total percent Sched- uled caste Sched- uled tribe Other back- ward class Other Missing Total percent India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 81.9 11.7 3.0 1.7 0.4 0.8 0.3 0.1 0.1 100.0 84.3 8.3 1.2 4.6 0.8 0.1 0.2 0.1 0.3 100.0 88.5 4.1 0.1 7.1 0.1 0.0 0.0 0.0 0.1 100.0 93.1 3.1 0.1 1.3 0.1 2.3 0.0 0.0 0.1 100.0 45.2 52.8 0.3 1.6 0.0 0.0 0.0 0.0 0.0 100.0 41.9 2.1 2.0 53.9 0.0 0.0 0.0 0.0 0.1 100.0 88.6 9.1 0.1 1.0 1.2 0.0 0.1 0.0 0.0 100.0 92.2 5.0 1.4 0.2 1.0 0.2 0.0 0.0 0.0 100.0 82.6 16.3 0.1 0.7 0.0 0.0 0.0 0.0 0.2 100.0 83.2 14.8 1.1 0.0 0.0 0.0 0.9 0.0 0.0 100.0 96.5 1.6 1.9 0.0 0.0 0.0 0.0 0.0 0.0 100.0 75.8 21.8 0.3 0.1 0.0 0.4 1.3 0.1 0.2 100.0 37.5 1.3 13.0 0.1 0.0 11.0 35.8 1.1 0.2 100.0 66.9 29.4 2.4 0.0 0.0 0.2 0.3 0.1 0.7 100.0 49.5 3.0 36.8 0.0 0.0 0.1 10.6 0.1 0.0 100.0 9.6 3.4 73.1 0.0 0.0 0.0 2.1 11.6 0.2 100.0 2.5 0.4 95.6 0.1 0.0 1.2 0.1 0.0 0.2 100.0 10.3 6.3 81.8 0.0 0.0 0.1 0.3 0.4 0.9 100.0 59.9 1.3 5.3 0.0 0.0 32.9 0.3 0.0 0.3 100.0 63.0 3.8 32.9 0.0 0.2 0.0 0.0 0.1 0.0 100.0 89.8 8.1 0.7 0.2 1.2 0.0 0.1 0.0 0.0 100.0 79.7 9.8 1.3 0.2 1.4 7.1 0.5 0.1 0.0 100.0 87.8 6.1 6.0 0.0 0.0 0.0 0.0 0.1 0.0 100.0 85.4 10.6 3.2 0.0 0.7 0.0 0.0 0.0 0.0 100.0 55.0 25.6 19.3 0.1 0.1 0.0 0.0 0.0 0.0 100.0 89.1 5.3 5.3 0.0 0.1 0.0 0.1 0.0 0.1 100.0 18.7 9.1 32.4 38.8 1.0 100.0 17.7 0.9 14.9 66.4 0.1 100.0 21.3 0.1 21.4 57.2 0.0 100.0 22.4 0.6 17.3 59.7 0.0 100.0 14.8 2.5 11.3 71.5 0.0 100.0 29.8 0.1 16.8 53.4 0.0 100.0 18.6 12.0 23.2 46.1 0.1 100.0 16.1 23.7 39.8 20.2 0.0 100.0 20.2 2.2 26.2 46.2 5.1 100.0 20.8 9.9 49.9 19.3 0.0 100.0 21.6 21.7 29.6 27.0 0.0 100.0 22.8 7.2 4.5 65.1 0.5 100.0 13.7 68.0 12.4 5.9 0.0 100.0 9.9 21.3 12.5 54.0 2.4 100.0 5.0 38.0 4.5 52.2 0.3 100.0 2.1 89.5 1.2 7.1 0.2 100.0 0.4 98.4 0.2 1.1 0.0 100.0 5.7 83.5 3.4 6.8 0.6 100.0 7.1 27.9 33.3 31.5 0.2 100.0 6.2 0.3 6.4 86.8 0.2 100.0 14.7 19.7 23.6 42.0 0.0 100.0 13.4 10.2 22.6 53.3 0.5 100.0 20.1 5.0 43.5 31.1 0.2 100.0 16.7 5.6 40.3 36.3 1.0 100.0 9.3 1.1 40.5 49.2 0.0 100.0 23.5 0.9 73.4 2.2 0.0 100.0 1Includes 34.2 percent belonging to the Doni-polo religion in Arunachal Pradesh and 9.9 percent belonging to the Sanamahi religion in Manipur 25 Thirty percent of households in Punjab, and more than one-fifth in Tamil Nadu, Himachal Pradesh, Haryana, Uttar Pradesh, Andhra Pradesh, and the East Region, belong to scheduled castes. Between 10 and 20 percent of households belong to scheduled castes in Rajasthan, Delhi, Karnataka, Madhya Pradesh, Jammu and Kashmir, Gujarat, Arunachal Pradesh, and Maharashtra. Scheduled tribes are more concentrated in the northeastern states, particularly Mizoram (where 98 percent of household heads belong to scheduled tribes), Meghalaya (90 percent), Nagaland (84 percent), and Arunachal Pradesh (68 percent). Scheduled tribes constitute 38 percent of the household heads in Manipur, 28 percent in Sikkim, 24 percent in Madhya Pradesh, 22 percent in Orissa, and 21 percent in Assam. The percentage of scheduled tribes is negligible (3 percent or less) in the North Region (except for Rajasthan), and in Goa, Tamil Nadu, Kerala, and Uttar Pradesh. Other backward classes (OBCs) are particularly prominent in the South Region (where 40–73 percent of household heads belongs to OBCs), and in Bihar (50 percent), Madhya Pradesh (40 percent), and Sikkim (33 percent). The highest proportions of household heads who do not belong to scheduled castes, scheduled tribes, and OBCs are in Goa (87 percent), Jammu and Kashmir (72 percent), Delhi (66 percent), West Bengal (65 percent), and Himachal Pradesh (60 percent). 2.4 Educational Attainment The level of education of household members may affect reproductive behaviour, contraceptive use, the health of children, and proper hygienic practices. Table 2.7 shows the percent distribution of the de facto household population by literacy and educational level, according to age, residence, and sex. (This table and all subsequent tables and figures in this report are based on the de facto sample, unless otherwise specified.) Table 2.7 shows that in India 49 percent of females and 26 percent of males age six and above are illiterate. Comparable figures from NFHS-1 are 57 percent of females and 31 percent of males, indicating a substantial decline in illiteracy in only six and one-half years. Cohort differences in literacy also suggest that there has been considerable progress over time (Table 2.7 and Figure 2.2). For example, while only 21 percent of women age 50 and over are literate, the literacy rate doubles for those age 30–39, and steadily increases to 76 percent for women age 10–14. The literacy gap between males and females has narrowed over time, but even at age 10–14 there is still a gap of 11 percentage points (although the gap has decreased from 18 percentage points in NFHS-1). Changes over time in educational attainment can be seen by examining the differences in educational levels by age. For example, the proportion of males completing at least high school rises from 18 percent at age 50 and above to 40 percent at ages 20–29. For females, the proportion completing at least high school is almost negligible (only 4 percent) at age 50 and above but reaches a level of 23 percent at age 20–29. A higher percentage of males than of females have completed each level of schooling. The median number of years of schooling is 5.5 for males and 1.6 for females. The proportion illiterate is lowest at age 10–14 for both males and females and is highest at age 50 and above. 26 Table 2.7 Educational level of the household population Percent distribution of the household population age 6 and above by literacy and level of education, and median number of completed years of schooling, according to age, residence, and sex, India,1998–99 Educational level1 Age Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Missing Total percent Number of persons Median number of years of schooling URBAN Male 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 16.2 83.1 0.7 0.0 0.0 0.0 0.0 100.0 5,648 1.8 7.0 30.0 48.9 13.6 0.5 0.0 0.0 100.0 7,714 5.7 8.8 5.4 18.1 31.0 24.7 12.0 0.0 100.0 7,418 9.3 9.1 4.4 13.1 17.3 19.4 36.6 0.0 100.0 12,338 10.4 12.8 5.8 14.4 13.9 18.6 34.5 0.0 100.0 9,504 10.2 14.4 6.8 15.1 12.7 20.3 30.7 0.0 100.0 7,193 10.1 20.6 12.6 16.7 9.5 18.6 22.0 0.0 100.0 8,987 8.1 12.5 17.2 18.2 14.6 15.6 21.9 0.0 100.0 58,804 8.3 Female 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 19.7 79.5 0.8 0.0 0.0 0.0 0.0 100.0 5,293 1.9 9.6 28.4 46.2 15.2 0.6 0.0 0.0 100.0 6,926 5.7 13.4 5.3 17.3 26.0 24.1 13.9 0.0 100.0 6,770 9.3 21.6 4.7 14.1 13.3 15.4 30.9 0.0 100.0 12,107 9.4 32.5 5.6 16.0 11.5 14.3 20.1 0.0 100.0 9,153 7.3 36.7 7.7 17.0 9.5 14.6 14.4 0.0 100.0 6,178 5.7 55.9 10.8 14.4 6.3 6.9 5.6 0.1 100.0 8,721 0.0 27.8 16.4 17.9 12.0 11.5 14.3 0.0 100.0 55,156 5.8 Total 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 17.9 81.3 0.7 0.0 0.0 0.0 0.0 100.0 10,942 1.9 8.2 29.3 47.6 14.4 0.5 0.0 0.0 100.0 14,640 5.7 11.0 5.4 17.7 28.6 24.4 12.9 0.0 100.0 14,187 9.3 15.3 4.6 13.6 15.3 17.4 33.8 0.0 100.0 24,445 10.1 22.4 5.7 15.2 12.7 16.5 27.4 0.0 100.0 18,656 9.0 24.7 7.2 16.0 11.2 17.7 23.2 0.0 100.0 13,371 8.3 38.0 11.7 15.6 7.9 12.8 14.0 0.1 100.0 17,708 5.1 19.9 16.8 18.1 13.3 13.6 18.2 0.0 100.0 113,959 7.3 27 Table 2.7 Educational level of the household population (contd.) Percent distribution of the household population age 6 and above by literacy and level of education, and median number of completed years of schooling, according to age, residence, and sex, India,1998–99 Educational level1 Age Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Missing Total percent Number of persons Median number of years of schooling RURAL Male 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 30.0 69.1 0.8 0.0 0.0 0.0 0.1 100.0 19,420 1.4 15.0 39.3 37.3 8.1 0.2 0.0 0.0 100.0 22,646 4.7 17.0 9.0 22.7 30.0 16.1 5.1 0.0 100.0 18,196 8.1 23.7 8.0 16.7 18.3 15.9 17.3 0.0 100.0 27,623 8.2 35.1 10.5 16.9 13.9 11.6 11.9 0.0 100.0 23,153 5.6 37.9 12.2 17.8 11.7 11.8 8.7 0.0 100.0 16,339 5.0 52.3 15.8 15.6 6.1 6.4 3.7 0.0 100.0 25,973 0.0 30.5 22.6 18.4 12.5 8.9 7.1 0.0 100.0 153,381 4.6 Female 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 36.4 63.1 0.4 0.0 0.0 0.0 0.1 100.0 17,951 1.2 28.6 32.8 31.5 7.0 0.3 0.0 0.0 100.0 20,958 4.1 38.7 8.2 18.6 19.8 11.0 3.7 0.0 100.0 17,992 5.5 55.2 6.8 13.9 9.8 7.7 6.5 0.0 100.0 31,136 0.0 68.4 7.2 12.4 5.3 4.2 2.5 0.0 100.0 22,533 0.0 74.3 7.9 10.2 3.5 2.8 1.3 0.0 100.0 14,662 0.0 87.1 6.0 4.8 1.0 0.7 0.3 0.1 100.0 24,452 0.0 56.3 17.4 13.2 6.7 4.0 2.4 0.0 100.0 149,714 0.0 Total 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 33.1 66.2 0.6 0.0 0.0 0.0 0.1 100.0 37,371 1.3 21.5 36.2 34.5 7.6 0.2 0.0 0.0 100.0 43,604 4.5 27.8 8.6 20.7 24.9 13.6 4.4 0.0 100.0 36,188 7.1 40.4 7.4 15.3 13.8 11.5 11.6 0.0 100.0 58,759 5.4 51.5 8.9 14.7 9.7 8.0 7.3 0.0 100.0 45,687 2.1 55.1 10.2 14.2 7.8 7.5 5.2 0.0 100.0 31,001 0.0 69.2 11.1 10.4 3.6 3.7 2.1 0.0 100.0 50,425 0.0 43.3 20.0 15.9 9.6 6.5 4.7 0.0 100.0 303,095 2.6 28 Table 2.7 Educational level of the household population (contd.) Percent distribution of the household population age 6 and above by literacy and level of education, and median number of completed years of schooling, according to age, residence, and sex, India,1998–99 Educational level1 Age Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Missing Total percent Number of persons Median number of years of schooling TOTAL Male 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 26.9 72.3 0.8 0.0 0.0 0.0 0.1 100.0 25,068 1.5 13.0 37.0 40.3 9.5 0.3 0.0 0.0 100.0 30,359 5.0 14.7 8.0 21.4 30.3 18.6 7.1 0.0 100.0 25,614 8.5 19.2 6.9 15.6 18.0 17.0 23.3 0.0 100.0 39,961 9.0 28.6 9.1 16.2 13.9 13.7 18.5 0.0 100.0 32,657 7.3 30.8 10.5 17.0 12.0 14.4 15.4 0.0 100.0 23,532 6.2 44.1 15.0 15.9 7.0 9.5 8.4 0.0 100.0 34,960 3.5 25.5 21.1 18.4 13.0 10.7 11.2 0.0 100.0 212,185 5.5 Female 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 32.6 66.8 0.5 0.0 0.0 0.0 0.1 100.0 23,244 1.4 23.9 31.7 35.1 9.0 0.3 0.0 0.0 100.0 27,885 4.6 31.8 7.4 18.2 21.5 14.6 6.5 0.0 100.0 24,762 7.0 45.8 6.2 14.0 10.8 9.9 13.3 0.0 100.0 43,243 4.5 58.0 6.8 13.4 7.1 7.1 7.6 0.0 100.0 31,686 0.0 63.2 7.9 12.2 5.3 6.3 5.2 0.0 100.0 20,840 0.0 78.9 7.2 7.3 2.4 2.3 1.7 0.1 100.0 33,173 0.0 48.6 17.1 14.5 8.1 6.0 5.6 0.0 100.0 204,870 1.6 Total 6–9 10–14 15–19 20–29 30–39 40–49 50+ Total 29.6 69.6 0.7 0.0 0.0 0.0 0.1 100.0 48,312 1.5 18.2 34.4 37.8 9.3 0.3 0.0 0.0 100.0 58,244 4.8 23.1 7.7 19.8 26.0 16.6 6.8 0.0 100.0 50,376 7.9 33.0 6.5 14.8 14.3 13.3 18.1 0.0 100.0 83,204 7.2 43.1 8.0 14.8 10.6 10.4 13.1 0.0 100.0 64,343 4.8 46.0 9.3 14.7 8.8 10.6 10.6 0.0 100.0 44,372 3.9 61.1 11.2 11.7 4.7 6.0 5.2 0.0 100.0 68,133 0.0 36.9 19.2 16.5 10.6 8.4 8.4 0.0 100.0 417,055 4.0 Note: This table and all the subsequent tables (unless otherwise indicated) are based on the de facto population. Illiterate persons may have been to school, but they cannot read and write. Total includes persons with missing information on age, who are not shown separately. 1In this report, ‘primary school complete’ means 5–7 completed years of education, ‘middle school complete’ means 8–9 completed years of education, ‘high school complete’ means 10–11 completed years of education, and ‘higher secondary complete and above’ means 12 or more completed years of education. 29 Education levels are much higher in urban areas than in rural areas for both males and females. The proportion illiterate is twice as high for rural females (56 percent) as for urban females (28 percent), and is more than twice as high for rural males (31 percent) as for urban males (13 percent). There are large interstate variations in the level of female and male literacy and educational attainment (Table 2.8 and Figure 2.3). At least three-quarters of females age six and above are literate in Mizoram (89 percent), Kerala (85 percent), Delhi (78 percent), and Goa (75 percent). At the other extreme, less than half of females age six and over are literate in Bihar (35 percent), Rajasthan (37 percent), Uttar Pradesh (43 percent), Madhya Pradesh (45 percent), Jammu and Kashmir (45 percent), and Andhra Pradesh (46 percent). The percentage of females who have a high school level of education or above is highest in Delhi (33 percent, up from 29 percent in NFHS-1), followed by Kerala (31 percent, up from 19 percent in NFHS-1), Goa (28 percent, up from 23 percent in NFHS-1), and Punjab (23 percent, up from 15 percent in NFHS-1). Figure 2.2 Percentage Literate by Age and Sex 0 20 40 60 80 100 6–9 10–14 15–19 20–29 30–39 40–49 50+ Age P e rc e n t Male Female NFHS-2, India, 1998–99 30 The states with the highest literacy rates for males are the same states that have the highest literacy rates for females (Mizoram, Kerala, Delhi, and Goa). Literacy rates for males are lowest in Bihar (63 percent), Andhra Pradesh (67 percent), and Jammu and Kashmir (69 percent). In every state, the percentage of the population that is literate is higher for males than for females, and a higher percentage of males than females have completed at least high school. The literacy gap between males and females is highest in Rajasthan and Uttar Pradesh, and the differences are least pronounced in Mizoram, Meghalaya, and Kerala. Table 2.8 Educational level of the household population by state Percent distribution of the de facto household population age 6 and above by literacy and level of education, and median number of completed years of schooling, according to sex and state, India, 1998–99 Educational level State Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Miss- ing Total percent Median number of years of schooling MALE India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 25.5 21.1 18.4 13.0 10.7 11.2 0.0 100.0 5.5 8.5 15.4 15.9 14.6 16.9 28.7 0.0 100.0 9.3 21.2 19.6 17.8 13.1 16.0 12.3 0.0 100.0 6.2 14.6 17.8 21.0 14.8 19.7 12.1 0.0 100.0 7.5 31.2 15.0 14.9 18.1 11.6 9.1 0.0 100.0 5.7 22.1 18.0 17.3 12.9 17.4 12.3 0.0 100.0 6.4 28.2 22.0 18.4 13.2 9.3 8.9 0.0 100.0 5.0 27.9 24.0 20.4 11.4 5.6 10.7 0.0 100.0 4.8 28.2 22.0 15.9 13.8 8.9 11.2 0.1 100.0 5.0 36.8 19.7 14.2 9.7 10.4 9.2 0.0 100.0 3.6 24.0 24.8 20.8 13.2 8.5 8.6 0.0 100.0 5.1 24.0 29.0 16.7 12.5 7.6 10.2 0.0 100.0 4.7 27.0 26.6 16.5 13.2 7.4 9.2 0.1 100.0 4.4 25.4 27.2 15.7 15.8 6.9 8.9 0.1 100.0 4.7 20.3 15.0 14.7 20.5 12.3 17.3 0.0 100.0 8.0 28.3 35.1 14.0 11.2 5.5 5.8 0.1 100.0 3.2 6.4 31.9 24.4 19.7 7.6 9.9 0.1 100.0 6.4 19.4 27.6 20.3 15.3 8.7 8.5 0.1 100.0 5.4 20.7 32.0 20.2 11.2 7.2 8.6 0.1 100.0 4.7 11.3 19.3 17.4 15.8 17.7 18.5 0.1 100.0 8.3 23.3 18.3 20.3 13.4 12.2 12.4 0.0 100.0 6.3 17.3 21.6 19.0 16.0 12.8 13.3 0.0 100.0 7.1 33.1 18.1 19.8 8.9 10.5 9.6 0.0 100.0 4.9 25.7 17.6 19.6 10.9 12.8 13.4 0.0 100.0 6.0 7.2 18.4 23.4 17.4 21.2 12.4 0.0 100.0 8.1 20.3 15.2 24.2 16.4 12.8 11.0 0.0 100.0 6.4 31 The median years of schooling for males and females also vary substantially over the states. All states in the West Region, all states in the South Region except Andhra Pradesh, and all states in the North Region except Rajasthan have median years of schooling above the national average for males. In the Central and East Regions, all states are below the national average. Among the northeastern states, only Manipur and Mizoram have a median number of years of schooling higher than the national average. For females, the median number of years of schooling ranges from a high of 7–8 years in Kerala, Delhi, and Goa to a low of zero years in six states where the majority of women have never been to school. Table 2.8 Educational level of the household population by state (contd.) Percent distribution of the de facto household population age 6 and above by literacy and level of education, and median number of completed years of schooling, according to sex and state, India, 1998–99 Educational level State Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Miss- ing Total percent Median number of years of schooling FEMALE India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 48.6 17.1 14.5 8.1 6.0 5.6 0.0 100.0 1.6 21.7 15.3 17.6 12.3 12.4 20.6 0.0 100.0 7.0 42.7 17.4 16.5 8.4 7.8 7.2 0.0 100.0 2.4 31.3 16.0 21.7 12.1 11.8 7.1 0.0 100.0 5.2 55.3 12.1 11.6 10.8 5.6 4.7 0.0 100.0 0.0 35.1 14.7 17.3 9.5 13.3 10.1 0.0 100.0 5.0 62.9 15.7 9.9 5.3 3.2 2.9 0.0 100.0 0.0 55.5 18.7 12.7 5.6 2.7 4.8 0.0 100.0 0.0 57.3 16.2 11.4 6.3 3.6 5.1 0.1 100.0 0.0 65.2 14.5 9.3 4.8 4.1 2.0 0.0 100.0 0.0 48.7 20.4 15.8 7.8 4.1 3.2 0.0 100.0 1.2 42.6 26.4 13.9 8.4 4.1 4.6 0.0 100.0 2.1 43.0 22.0 14.5 11.3 5.2 4.0 0.1 100.0 2.1 40.9 24.0 12.5 13.7 4.9 3.8 0.2 100.0 2.5 41.3 13.1 11.6 15.5 7.4 11.0 0.0 100.0 4.3 33.2 35.9 13.0 9.4 4.6 3.9 0.1 100.0 2.3 10.6 36.3 21.7 17.9 7.5 6.0 0.1 100.0 5.5 31.7 26.3 19.1 13.2 5.4 4.3 0.0 100.0 3.7 35.6 26.4 18.0 10.3 5.2 4.5 0.0 100.0 3.3 25.2 17.6 15.8 13.5 13.6 14.2 0.1 100.0 6.7 46.4 13.7 16.5 8.4 7.0 8.1 0.0 100.0 3.2 38.6 18.1 17.8 10.8 7.9 6.9 0.0 100.0 4.1 54.0 15.2 16.3 5.4 5.5 3.6 0.0 100.0 0.0 44.5 15.1 16.6 7.9 8.9 7.0 0.0 100.0 3.2 14.9 16.9 21.4 16.0 18.5 12.3 0.0 100.0 7.6 41.7 12.6 19.4 12.5 7.2 6.5 0.1 100.0 4.5 32 Table 2.9 and Figure 2.4 show school attendance rates for the school-age household population by age, sex, and residence in different states. In the country as a whole, 79 percent of children age 6–14 are attending school, up from 68 percent in NFHS-1. The attendance rate drops off sharply to 49 percent at age 15–17. For the age group 6–17, the attendance rate is 78 percent for males, 66 percent for females, and 72 percent for India as a whole. In urban areas, attendance rates for males and females differ by less than 5 percentage points for every age group. In rural areas, however, attendance rates are considerably higher for males than for females at every age, and the gap widens with increasing age. For both males and females, school attendance rates are much higher in urban areas than in rural areas in every age group. School attendance at age 6–17 years is more than 90 percent in Himachal Pradesh and Kerala, and 85–90 percent in Goa, Delhi, Manipur, Mizoram, and Punjab. Overall, school attendance is lowest in Bihar (only 60 percent), and it is also 70 percent or lower in the Central Region, Rajasthan, Gujarat, and Andhra Pradesh. Generally, the lower the overall attendance rate, the higher the difference in children’s school attendance by residence and sex. Figure 2.3 Percentage of Women Age 6+ Who Are Illiterate by State 0 10 20 30 40 50 60 70 B ihar Ra jasthan Uttar P radesh M adhya P radesh Jam m u & K ashm ir A ndhra P radesh O rissa INDIA G ujara t K arnataka A runacha l P radesh Haryana W est B enga l Tam il N adu M anipur A ssam M aharashtra S ikk im P unjab M eghalaya Nagaland H im acha l P radesh G oa De lh i K era la M izoram P ercent NFHS-2, India, 1998–99 33 Fifty percent of school-age girls in Bihar are not attending school. School attendance for school-age girls is also low in Rajasthan (56 percent), Uttar Pradesh (61 percent), Andhra Pradesh (62 percent), and Madhya Pradesh and Gujarat (63 percent each). Among females age 6–14 years, less than three-quarters attend school in 5 states compared with 11 states in NFHS-1. Similarly, for males age 6–14 years, less than 75 percent attend school only in Bihar, whereas there were eight such states in NFHS-1 (data not shown). Table 2.9 School attendance by state Percentage of the household population age 6–17 years attending school by sex, residence, age, and state, India, 1998–99 Male Female Total State Urban Rural Total Urban Rural Total Urban Rural Total India Age 6–10 years 11–14 years 15–17 years 6–14 years 6–17 years North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 91.7 83.2 85.2 89.1 75.1 78.3 90.4 79.3 81.9 85.1 78.5 80.2 82.8 61.6 67.0 84.0 70.4 73.9 65.3 54.8 57.7 60.5 32.8 40.3 63.0 44.0 49.3 88.7 81.4 83.1 86.3 69.7 73.7 87.6 75.7 78.6 83.0 75.8 77.6 80.0 61.7 66.2 81.5 69.0 72.1 86.0 89.2 86.2 87.6 83.2 87.2 86.7 86.2 86.7 87.1 85.4 85.9 86.1 74.7 77.8 86.7 80.5 82.2 96.4 95.4 95.5 96.3 92.8 93.0 96.3 94.1 94.3 83.0 85.8 85.3 85.2 67.6 70.4 84.0 76.6 77.8 93.0 84.1 86.7 92.7 78.1 82.7 92.8 81.5 84.9 83.9 80.4 81.3 73.5 49.9 55.6 79.0 66.0 69.1 84.0 73.1 75.9 77.9 58.0 62.8 81.2 65.7 69.6 77.7 77.3 77.3 77.0 57.3 61.4 77.3 68.0 69.9 79.1 66.8 68.2 72.1 47.5 50.5 75.5 57.4 59.6 78.2 77.1 77.2 75.4 65.8 66.8 76.9 71.5 72.1 78.5 72.5 73.7 76.1 65.9 68.0 77.3 69.3 70.9 96.7 82.3 84.2 87.3 74.3 75.9 92.2 78.3 80.1 86.8 73.3 74.2 81.1 69.0 69.9 83.8 71.2 72.1 91.8 87.8 89.1 89.3 82.0 84.4 90.5 84.7 86.6 91.4 75.3 78.5 91.3 76.8 79.9 91.3 76.0 79.2 92.6 78.6 85.5 89.8 79.8 85.3 91.0 79.2 85.4 87.3 84.5 85.1 84.8 78.0 79.4 86.0 81.1 82.2 88.0 82.7 83.2 73.4 83.6 82.6 80.6 83.2 82.9 91.2 88.5 89.6 87.2 86.5 86.8 89.2 87.5 88.1 82.8 69.6 74.8 73.4 56.7 63.1 78.3 63.2 69.1 86.3 82.6 84.1 84.6 75.7 79.1 85.5 79.3 81.8 80.1 71.3 73.5 78.5 56.0 61.5 79.4 63.9 67.7 81.9 71.4 74.9 79.7 62.4 68.0 80.8 66.9 71.4 95.6 89.7 91.0 94.5 89.8 90.8 95.0 89.8 90.9 84.4 81.6 82.6 84.7 73.3 76.9 84.5 77.4 79.7 34 Table 2.10 shows reasons for children never attending school or not currently attending school. For both boys and girls, the cost of schooling is cited most often as the main reason for never attending school. This reason is mentioned in one-quarter of cases for both boys and girls. This reason is almost twice as likely to be mentioned for children never attending school as for children not currently attending school. The most mentioned reason for not currently attending school is that the child is not interested in studies, which was cited for 41 percent of boys and 26 percent of girls. A lack of interest in school is also frequently given as a reason for children (especially boys) never attending school. Not surprisingly, the need for children to work in the household is mentioned more for girls than for boys, and the need for children to work on the family farm, in the family business, or outside the home for payment is more frequently mentioned for boys than for girls. Education is not considered necessary for 13 percent of girls and 8 percent of boys who never attended school. The lack of accessibility of schools (‘school too far away’ or ‘transport not available’) is mentioned infrequently for both boys and girls. The pattern of the reasons for not attending school for boys and girls is similar in urban and rural areas with the exception that the cost of schooling is cited more often in urban areas and the distance from school and the need for work (in the household, on a family farm, or in a family business) are mentioned slightly less often in urban areas. Figure 2.4 School Attendance by Age, Sex, and Residence 75 83 79 62 85 92 89 83 0 10 20 30 40 50 60 70 80 90 100 AGE 6–10, URBAN Male Female AGE 6–10, RURAL Male Female AGE 11–14, URBAN Male Female AGE 11–14, RURAL Male Female Percent NFHS-2, India, 1998–99 35 2.5 Housing Characteristics Table 2.11 provides information on housing characteristics by residence. Overall, three in every five households in India have electricity (up from one in two households in NFHS-1). The proportion of households with electricity is 91 percent in urban areas and 48 percent in rural areas, an increase of 10 and 24 percent, respectively, over the NFHS-1 results. Table 2.10 Reasons for children not attending school Percent distribution of children age 6–17 years who never attended school by the main reason for never attending school and percent distribution of children age 6–17 years who have dropped out of school by the main reason for not currently attending school, according to residence and sex, India, 1998–99 Urban Rural Total Reason Male Female Male Female Male Female Main reason for never attending school1 School too far away Transport not available Education not considered necessary Required for household work Required for work on farm/family business Required for outside work for payment in cash or kind Costs too much No proper school facilities for girls Required for care of siblings Not interested in studies Other Don’t know Total percent Number of children 1.3 2.8 3.8 4.5 3.5 4.3 0.2 0.6 0.6 0.7 0.6 0.7 6.1 12.9 7.8 13.1 7.6 13.1 4.6 9.6 6.7 15.5 6.4 14.9 2.8 1.2 5.2 3.4 4.9 3.2 4.6 2.9 4.3 2.6 4.4 2.6 28.5 30.1 25.8 23.8 26.2 24.5 0.0 1.1 0.0 2.6 0.0 2.5 0.6 1.7 0.9 3.0 0.9 2.9 26.5 15.7 25.7 15.9 25.8 15.8 21.9 18.6 17.0 12.8 17.6 13.4 3.0 2.8 2.0 2.1 2.2 2.2 100.0 100.0 100.0 100.0 100.0 100.0 1,107 1,438 7,081 12,614 8,188 14,052 Main reason for not currently attending school2 School too far away Transport not available Further education not considered necessary Required for household work Required for work on farm/family business Required for outside work for payment in cash or kind Costs too much No proper school facilities for girls Required for care of siblings Not interested in studies Repeated failures Got married Other Don’t know Total percent Number of children 0.2 1.0 1.0 5.9 0.8 4.8 0.1 0.2 0.4 1.6 0.3 1.3 2.4 5.4 2.3 4.3 2.4 4.5 5.7 14.7 8.7 17.3 8.0 16.7 4.7 1.6 9.2 2.9 8.0 2.6 11.3 3.0 9.9 3.7 10.3 3.5 15.2 17.0 13.3 11.4 13.8 12.6 0.0 1.2 0.0 3.5 0.0 3.0 0.2 1.5 0.6 2.3 0.5 2.2 42.5 30.2 40.0 24.8 40.6 26.0 6.0 6.1 5.3 3.7 5.5 4.2 0.1 4.9 0.2 8.5 0.2 7.7 5.8 8.2 5.3 6.2 5.5 6.6 5.7 5.1 3.8 4.0 4.2 4.2 100.0 100.0 100.0 100.0 100.0 100.0 1,852 1,747 5,475 6,121 7,327 7,868 1For children who have never attended school 2For children who have dropped out of school 36 Table 2.11 Housing characteristics Percent distribution of households by housing characteristics, according to residence, India, 1998–99 Housing characteristic Urban Rural Total Electricity Yes No Total percent Source of drinking water Piped Hand pump Well water Surface water Other Total percent Time to get drinking water Percentage < 15 minutes Median time (minutes) Method of drinking water purification1 Strains water by cloth Uses alum Uses water filter Boils water Uses electronic purifier Uses other method Does not purify water Sanitation facility Flush toilet Pit toilet/latrine Other No facility Total percent Main type of fuel used for cooking Wood Crop residues Dung cakes Coal/coke/lignite/charcoal Kerosene Electricity Liquid petroleum gas Biogas Other Total percent Type of house Kachha Semi-pucca Pucca Missing Total percent Persons per room < 3 3–4 5–6 7+ Missing Total percent Mean number of persons per room Number of households 91.3 48.1 60.1 8.7 51.9 39.9 100.0 100.0 100.0 74.5 25.0 38.7 18.1 47.3 39.2 6.0 23.5 18.7 0.4 3.5 2.6 1.0 0.7 0.8 100.0 100.0 100.0 86.4 69.3 74.1 0.0 4.9 4.3 25.1 16.1 18.6 1.4 1.2 1.2 14.8 2.4 5.8 13.6 6.1 8.2 1.2 0.1 0.4 0.6 0.8 0.7 50.4 75.3 68.4 63.9 8.8 24.0 16.8 10.0 11.9 0.0 0.1 0.1 19.3 81.1 64.0 100.0 100.0 100.0 23.1 73.1 59.3 0.5 8.1 6.0 1.4 8.4 6.5 4.9 1.7 2.6 21.5 2.7 7.9 0.8 0.2 0.4 46.9 5.1 16.7 0.6 0.5 0.5 0.2 0.2 0.2 100.0 100.0 100.0 9.4 41.4 32.5 24.4 39.5 35.3 66.0 19.0 32.0 0.2 0.2 0.2 100.0 100.0 100.0 68.6 60.2 62.5 19.5 24.4 23.1 8.3 10.7 10.0 3.5 4.5 4.2 0.1 0.1 0.1 100.0 100.0 100.0 2.5 2.8 2.7 25,243 65,953 91,196 1Totals add to more than 100.0 because households may use more than one method of purification. 37 Water sources and sanitation facilities have an important influence on the health of household members, especially children. NFHS-1 and NFHS-2 included questions on sources of drinking water and types of sanitation facilities. NFHS-2 found that 39 percent of households in India use piped drinking water (up from 31 percent in NFHS-1), the same proportion drink water from hand pumps (also up from 31 percent in NFHS-1), 19 percent drink water from wells (down from 26 percent in NFHS-1), and 3 percent drink surface water (down from 11 percent in NFHS-1). As in the case of electricity, there are large urban-rural differences in sources of drinking water. Three-quarters of households in urban areas use piped drinking water compared with only one-quarter in rural areas. The median time to get drinking water is five minutes in rural areas, whereas in urban areas the majority of households do not have any travel time to their source of drinking water. Only one-third of households in India purify water by any method (half of households in urban areas and one-quarter of households in rural areas). The most popular methods of water purification are straining and boiling water. Water filters are used by 30 percent of urban households that purified their drinking water. Regarding sanitation facilities, only 24 percent of households have a flush toilet that uses either piped water or bucket water for flushing (up slightly from 22 percent in NFHS-1), 12 percent have a pit toilet or latrine, and 64 percent have no facility. Again there are large urban- rural differences: 64 percent of urban households have a flush toilet compared with only 9 percent of rural households. A large majority (81 percent) of rural households have no toilet facility at all. Several types of fuel are used for cooking in India, with wood as the most common type. Overall, 59 percent of households rely mainly on wood, 17 percent on liquid petroleum gas, 13 percent on either crop residues or dung cakes, 8 percent on kerosene, and the rest on other fuels. Sixty-eight percent of urban households rely mainly on liquid petroleum gas or kerosene, while 73 percent of rural households rely mainly on wood. Regarding type of house construction, one-third of households in India live in houses that are kachha (made from mud, thatch, or other low-quality materials), one-third live in semi-pucca houses (using partly low-quality and partly high-quality materials), and one-third live in pucca houses (made with high-quality materials throughout, including the roof, walls, and floor). By residence, 66 percent of households in urban areas live in pucca houses compared with 19 percent of households in rural areas. Crowded housing conditions may affect health as well as the quality of life. Thirty-seven percent of households live in houses with three or more persons per room. The mean number of persons per room is 2.5 in urban areas, 2.8 in rural areas, and 2.7 overall (only a slight decrease from 2.8 persons per room in NFHS-1). Table 2.12 presents an interstate comparison of housing characteristics. The percentage of households with electricity is lowest in Bihar (18 percent), Assam (26 percent), Orissa (34 percent), and West Bengal and Uttar Pradesh (37 percent each). At least 90 percent of households have electricity in Delhi (98 percent), Himachal Pradesh (97 percent), Punjab (96 percent), Goa (94 percent), and Jammu and Kashmir (90 percent). In addition, over three- quarters of households have electricity in Haryana, Gujarat, Mizoram, Sikkim, Tamil Nadu, and Manipur. More than 60 percent of households use piped water or water from a hand pump for drinking in every state except Kerala and a few states in the Northeast Region. In Manipur, 38 Meghalaya, and Nagaland, piped water or water from a hand pump is used for drinking by 41–49 percent of households, and less than 20 percent of households use these water sources in Kerala. The majority of households in Kerala obtain their drinking water from wells. Most of the states in India have inadequate toilet facilities. There are only seven states where more than 70 percent of households have any type of toilet facility. In order of decreasing proportions, these states are Mizoram, Delhi, Manipur, Kerala, Nagaland, Arunachal Pradesh, and Sikkim. Less than 30 percent of households have a toilet or latrine facility in Central India and in Orissa, Bihar, Himachal Pradesh, Andhra Pradesh, and Rajasthan. In Delhi, only 4 percent of households use biomass fuel for cooking. In every other state except Goa, a majority of households use biomass fuel for cooking. Table 2.12 Housing characteristics by state Selected housing characteristics by state, India, 1998–99 Percentage of households: State With electricity With drinking water that is piped or from a hand pump With a toilet or latrine facility Using biomass fuel for cooking Living in a pucca house Mean number of persons per room India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 60.1 77.9 35.9 71.7 32.0 2.7 97.7 98.7 94.4 3.6 88.2 2.2 89.1 88.0 39.0 66.9 46.7 2.4 97.2 77.4 26.7 64.0 28.7 1.8 90.1 70.6 51.0 65.8 36.1 2.2 95.5 98.9 51.4 60.6 52.1 2.1 64.4 69.8 27.8 81.0 41.4 3.0 68.1 63.5 22.2 79.3 19.2 2.9 36.6 85.6 26.5 82.8 24.8 3.1 18.2 75.4 16.8 85.9 15.5 2.9 33.8 65.3 13.5 86.8 14.8 2.4 36.7 89.3 44.8 65.7 32.8 2.7 68.9 80.7 73.0 80.8 14.2 2.2 26.4 60.1 63.0 87.1 10.9 2.1 75.3 48.9 92.0 69.2 7.1 2.1 41.2 42.1 52.0 83.5 14.5 2.0 84.1 63.2 97.7 57.4 16.2 2.6 56.3 40.5 74.3 86.1 18.1 1.6 80.7 84.6 72.7 63.2 50.6 2.0 93.5 61.8 58.9 41.4 51.0 1.6 84.3 84.5 44.9 54.5 45.2 2.7 82.1 81.9 45.9 51.9 28.3 3.0 74.4 78.5 27.3 74.1 39.9 2.9 80.9 87.0 38.6 67.8 41.2 2.5 71.8 19.9 85.2 81.7 79.8 1.3 78.8 85.0 34.0 66.5 27.6 2.2 39 The percentage of households living in pucca houses is quite low in most states. In Orissa, Bihar, Madhya Pradesh, and all the states in the Northeast Region except Sikkim, less than 20 percent of households live in pucca houses. Delhi (88 percent) and Kerala (80 percent) are the only states in which more than 60 percent of households live in houses classified as pucca. Households are least crowded in Kerala (1.3 persons per room), followed by Goa and Nagaland (where the average number of persons per room is 1.6). Households in Uttar Pradesh, Rajasthan, Maharashtra, Andhra Pradesh, Bihar, and Madhya Pradesh have an average of around 3 persons per room, which puts them in the most crowded category. Table 2.13 gives a number of measures related to the socioeconomic status of the household (ownership of land, a house, and livestock). Overall, half of households in India do not own any agricultural land. Thirty-nine percent of households in rural areas do not own agricultural land (up slightly from 36 percent in NFHS-1), compared with 80 percent of households in urban areas. In rural areas, among those who own land, 64 percent have at least some irrigated land. The proportion of households owning a house is 78 percent in urban areas, 95 percent in rural areas, and 90 percent overall. The proportion of households owning livestock is 14 percent in urban areas, 59 percent in rural areas, and 47 percent overall. The possession of durable goods is another indicator of a household’s socioeconomic level, although these goods may also have other benefits. For example, having access to a radio or television may expose household members to innovative ideas or important information about health and family welfare; a refrigerator prolongs the wholesomeness of food; and a means of transportation allows greater access to many services outside the local area. Table 2.14 shows that the majority of Indian households have a cot or a bed (81 percent) or a clock or watch (67 Table 2.13 Household ownership of agricultural land, house, and livestock Percent distribution of households owning agricultural land and percentage owning a house and livestock by residence, India, 1998–99 Asset Urban Rural Total No agricultural land Irrigated land only < 1 acre 1–5 acres 6+ acres Nonirrigated land only < 1 acre 1–5 acres 6+ acres Both irrigated and nonirrigated land < 1 acre 1–5 acres 6+ acres Missing Total percent Percentage owning a house Percentage owning livestock Number of households 80.0 38.6 50.1 1.6 9.4 7.2 5.4 16.1 13.2 2.2 4.2 3.6 1.5 5.1 4.1 4.2 13.2 10.7 1.4 3.6 3.0 0.2 0.8 0.6 0.9 5.0 3.9 1.1 3.4 2.8 1.4 0.6 0.8 100.0 100.0 100.0 78.2 94.8 90.2 13.7 59.3 46.7 25,243 65,953 91,196 40 percent). Other durable goods found in many households are bicycles (48 percent), mattresses (47 percent), chairs or electric fans (46 percent each), tables (40 percent), radios (38 percent), pressure cookers (30 percent), and black and white televisions (25 percent). A small proportion of households own sewing machines (18 percent), motorcycles, scooters, or mopeds (11 percent), refrigerators (11 percent), colour televisions (10 percent), water pumps (9 percent), telephones (7 percent), or cars (2 percent). Urban households are much more likely than rural households to own each of these durable goods. In rural areas, 9 percent of households own a bullock cart, 3 percent own a thresher, and 2 percent own a tractor. Six percent of households in India do not own any of the above durable goods. The majority of households (57 percent) use stainless steel kitchenware and two in every five households use aluminium kitchenware. Table 2.14 shows a summary household measure called the standard of living index (SLI), which is calculated by adding the following scores: Table 2.14 Household ownership of durable goods and standard of living Percentage of households owning selected durable goods and percent distribution of households by type of kitchenware and the standard of living index, according to residence, India, 1998–99 Asset Urban Rural Total Durable goods Mattress Pressure cooker Chair Cot/bed Table Clock/watch Electric fan Bicycle Radio/transistor Sewing machine Telephone Refrigerator Television (black and white) Television (colour) Moped/scooter/motorcycle Car Water pump Bullock cart Thresher Tractor None of the above Main type of kitchenware used Clay Aluminium Cast iron Brass/copper Stainless steel Total percent Standard of living index Low Medium High Missing Total percent Number of households 71.7 38.1 47.4 65.2 16.0 29.6 71.3 35.6 45.5 86.1 79.4 81.2 64.9 30.0 39.6 90.1 57.5 66.5 82.2 31.4 45.5 53.5 45.7 47.8 53.2 32.2 38.0 35.5 11.9 18.4 20.1 2.6 7.4 28.8 3.7 10.6 44.8 17.0 24.7 27.3 3.5 10.1 25.0 6.0 11.2 4.4 0.6 1.6 9.3 8.2 8.5 1.4 9.4 7.2 0.7 2.5 2.0 0.8 2.0 1.6 1.9 7.3 5.8 0.5 1.1 0.9 29.8 45.5 41.1 0.2 0.3 0.3 0.6 1.2 1.0 68.9 51.9 56.6 100.0 100.0 100.0 14.3 44.7 36.3 45.2 44.0 44.3 39.0 10.3 18.2 1.5 1.0 1.2 100.0 100.0 100.0 25,243 65,953 91,196 41 House type: 4 for pucca, 2 for semi-pucca, 0 for kachha; Toilet facility: 4 for own flush toilet, 2 for public or shared flush toilet or own pit toilet, 1 for shared or public pit toilet, 0 for no facility; Source of lighting: 2 for electricity, 1 for kerosene, gas, or oil, 0 for other source of lighting; Main fuel for cooking: 2 for electricity, liquid petroleum gas, or biogas, 1 for coal, charcoal, or kerosene, 0 for other fuel; Source of drinking water: 2 for pipe, hand pump, or well in residence/yard/plot, 1 for public tap, hand pump, or well, 0 for other water source; Separate room for cooking: 1 for yes, 0 for no; Ownership of house: 2 for yes, 0 for no; Ownership of agricultural land: 4 for 5 acres or more, 3 for 2.0–4.9 acres, 2 for less than 2 acres or acreage not known, 0 for no agricultural land; Ownership of irrigated land: 2 if household owns at least some irrigated land, 0 for no irrigated land; Ownership of livestock: 2 if owns livestock, 0 if does not own livestock; Ownership of durable goods: 4 each for a car or tractor, 3 each for a moped/scooter/motorcycle, telephone, refrigerator, or colour television, 2 each for a bicycle, electric fan, radio/transistor, sewing machine, black and white television, water pump, bullock cart, or thresher, 1 each for a mattress, pressure cooker, chair, cot/bed, table, or clock/watch. Index scores range from 0–14 for a low SLI to 15–24 for a medium SLI and 25–67 for a high SLI. By this measure, more than one-third (36 percent) of Indian households have a low standard of living, 44 percent have a medium standard of living, and 18 percent have a high standard of living. The proportion with a low standard of living is much higher in rural areas than in urban areas (45 and 14 percent, respectively), and the proportion with a high standard of living is much higher in urban areas than in rural areas (39 and 10 percent, respectively). The proportion with a medium standard of living is almost the same in urban and rural areas. 2.6 Lifestyle Indicators The NFHS-2 Household Questionnaire asked about certain aspects of the lifestyle of household members. Table 2.15 shows the percentages of men and women age 15 and above who chew paan masala or tobacco, drink alcohol, or smoke. These lifestyle indicators are of considerable interest because the use of paan masala, tobacco, and alcohol all have detrimental effects on health. 42 Table 2.15 Lifestyle indicators Percentage of usual household members age 15 and above who chew paan masala or tobacco, drink alcohol, currently smoke, or have ever smoked by selected background characteristics and sex, India, 1998–99 Background characteristic Chew paan masala or tobacco Drink alcohol Currently smoke Ever smoked1 Number of household members MALE Age 15–19 20–24 25–29 30–39 40–49 50–59 60+ Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Standard of living index Low Medium High Total 9.4 2.4 4.4 4.8 26,297 20.3 7.7 13.7 14.6 21,461 28.0 14.9 25.1 27.3 19,641 34.1 23.6 37.6 41.2 33,554 35.6 26.1 45.0 49.9 24,151 35.4 23.9 45.3 52.3 15,195 37.6 18.6 38.2 46.6 20,571 20.8 12.4 21.4 24.5 46,245 31.3 18.5 32.6 36.5 114,626 38.0 26.7 44.8 49.6 44,661 31.5 17.8 33.1 37.5 43,328 23.2 11.8 21.2 23.7 25,376 18.9 8.9 15.9 18.5 47,485 37.6 24.8 39.4 43.5 46,887 27.7 15.0 29.1 32.7 76,510 17.2 9.8 16.9 20.2 35,463 28.3 16.7 29.4 33.1 160,871 FEMALE Age 15–19 20–24 25–29 30–39 40–49 50–59 60+ Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Standard of living index Low Medium High Total 2.1 0.6 0.2 0.3 24,602 4.3 1.1 0.6 0.6 22,288 8.0 2.0 1.1 1.2 20,761 12.3 2.5 2.2 2.4 32,127 18.6 3.1 4.0 4.5 21,253 22.8 3.8 5.7 6.4 15,108 25.0 3.1 5.3 6.0 18,588 8.8 0.5 0.9 1.0 43,173 13.8 2.9 3.1 3.4 111,554 17.4 3.5 4.0 4.5 86,359 10.2 0.8 0.8 0.9 30,563 3.8 0.5 0.3 0.3 14,217 1.8 0.2 0.1 0.2 23,529 18.7 4.4 4.2 4.7 47,225 11.7 1.7 2.2 2.4 71,497 5.2 0.3 0.6 0.8 34,144 12.4 2.2 2.5 2.8 154,726 Total male and female 20.5 9.6 16.2 18.2 315,598 Note: Total includes 23 males and 58 females with missing information on education and 2,012 males and 1,861 females with missing information on the standard of living index, who are not shown separately. 1Includes household members who currently smoke 43 The respondent to the Household Questionnaire reports on these lifestyle indicators for all persons in the household, and therefore the results should be interpreted with caution because the household respondent may not be aware of use that takes place outside the household environs. In addition, to the extent that social stigma may be attached to the use of some of the substances, underreporting is likely. Twenty-one percent of persons age 15 and above are reported to chew paan masala or tobacco. This proportion rises from 9 percent of men and 2 percent of women at age 15–19 to 38 percent and 25 percent, respectively, at age 60 and above. Chewing of paan masala or tobacco for both men and women is about one and one-half times as common in rural areas as in urban areas. Chewing of paan masala or tobacco is inversely related with education. It is twice as high among illiterate men as among men who have completed at least high school. Chewing of paan masala or tobacco is rare among educated women, and it is much higher among men and women in households with a low standard of living than in households with a high standard of living. Seventeen percent of men, but only 2 percent of women, age 15 and above are reported to drink alcohol. The proportion of men who drink alcohol rises with age up to age 40–49. The proportion of men who drink is one and one-half times as high in rural areas as in urban areas. Illiterate men are three times as likely to drink alcohol as men who have completed at least high school. Drinking alcohol by household members is negatively related to the household’s standard of living. Only 3 percent of women are reported to have ever smoked and to currently smoke. Among men age 15 and above, 29 percent currently smoke. The proportion of men who smoke rises from 4 percent at age 15–19 to 45 percent at age 40–59 and then falls to 38 percent at age 60 and above. As for chewing paan masala or tobacco and drinking alcohol, the proportion of men who smoke is one and one-half times as high in rural areas as in urban areas. It is much higher among illiterate than literate men, and more than twice as high among men with a low standard of living as among men with a high standard of living. Eighty-nine percent of men who ever smoked were still smokers at the time of the survey. The pattern of differentials for ever- smokers closely resembles the pattern for current smokers. An interstate comparison of life style indicators is presented in Table 2.16. The percentage of men chewing paan masala or tobacco is quite low (7–10 percent) in Jammu and Kashmir, Goa, Himachal Pradesh, Haryana, Punjab, and Kerala. More than half of men in Mizoram, Arunachal Pradesh, and Bihar and 40–50 percent in Orissa, Assam, Nagaland, Madhya Pradesh, and Sikkim chew paan masala or tobacco. In the northeastern states, chewing paan masala or tobacco is also quite common among women, particularly in Mizoram where the proportion chewing paan masala or tobacco is the same for men and women. Outside of the Northeast Region, chewing paan masala or tobacco is most common for women in Orissa, Maharashtra, West Bengal, Karnataka, and Madhya Pradesh. 44 Alcohol consumption is highest in Arunachal Pradesh, where 65 percent of men and 49 percent of women drink alcohol. There are only two other states, Sikkim and Assam, where more than 10 percent of women drink alcohol. In addition to Arunachal Pradesh, more than one- quarter of men drink alcohol in Sikkim, Manipur, Goa, Punjab, Meghalaya, Nagaland, and Andhra Pradesh. The lowest prevalence of alcohol consumption is in Gujarat, where there is a state ban on alcohol. Table 2.16 Lifestyle indicators by state Percentage of usual household members age 15 and above who chew paan masala or tobacco, drink alcohol, currently smoke, or have ever smoked by sex and state, India, 1998–99 State Chew paan masala or tobacco Drink alcohol Currently smoke Ever smoked1 MALE India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 28.3 16.7 29.4 33.1 13.1 17.9 24.0 26.4 8.0 20.7 40.6 42.4 7.9 24.2 38.8 42.3 7.2 10.0 44.5 49.0 9.3 28.3 13.9 15.8 19.1 10.7 37.9 41.0 40.6 20.6 29.5 35.1 36.3 11.6 34.0 37.2 51.7 22.4 26.3 32.0 49.5 19.2 25.4 29.4 23.3 11.0 39.6 43.1 52.0 64.5 25.1 34.3 48.2 24.9 31.7 34.9 34.4 30.5 35.2 39.2 16.7 28.1 55.2 57.6 60.3 16.8 59.4 67.1 45.3 26.8 38.2 49.5 39.6 31.9 19.5 29.0 7.7 28.7 17.8 23.5 24.6 6.6 25.5 29.1 34.7 12.1 13.4 15.5 10.8 26.1 35.7 39.0 13.9 16.4 26.0 29.6 9.5 14.5 28.3 35.0 13.0 20.5 27.0 29.8 45 More than half of men have ever smoked in Mizoram and Meghalaya, and 41–50 percent have ever smoked in Nagaland, Jammu and Kashmir, West Bengal, Haryana, Himachal Pradesh, and Rajasthan. Current smoking is also highest in these states. Less 20 percent of men smoke in Maharashtra, Punjab, Goa, and Sikkim. In most states, around 90 percent of men who ever smoked currently smoke. In Mizoram, where the proportion of women who chew paan masala or tobacco is the highest, the proportions of women who have ever smoked and who currently smoke are also the highest. In a large majority of states, less than 5 percent of women smoke or have ever smoked. Between 5 and 15 percent of women currently smoke in Manipur, Jammu and Kashmir, Sikkim, Meghalaya, Bihar, and Arunachal Pradesh. Table 2.16 Lifestyle indicators by state (contd.) Percentage of usual household members age 15 and above who chew paan masala or tobacco, drink alcohol, currently smoke, or have ever smoked by sex and state, India, 1998–99 State Chew paan masala or tobacco Drink alcohol Currently smoke Ever smoked1 FEMALE India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 12.4 2.2 2.5 2.8 2.5 0.1 1.8 1.9 0.9 0.1 3.6 3.8 0.5 0.2 2.4 2.6 0.9 0.3 8.5 10.2 0.2 0.2 0.3 0.4 3.9 0.2 4.3 4.4 14.8 3.4 0.9 1.1 11.4 0.2 3.1 3.5 6.9 3.3 6.4 7.2 34.9 6.2 0.9 1.0 15.6 2.0 2.6 2.8 33.2 48.9 5.4 7.2 24.9 11.1 2.7 3.1 19.6 2.0 12.2 14.4 27.6 3.1 6.8 7.0 60.7 0.4 22.1 29.3 16.5 2.6 2.5 3.7 18.9 17.1 8.3 11.8 8.2 4.5 2.1 3.1 8.2 1.0 1.4 1.7 18.5 0.5 0.2 0.2 10.3 7.5 4.4 4.9 14.9 1.0 0.3 0.4 10.5 0.2 0.4 0.6 11.0 0.5 0.4 0.4 1Includes household members who currently smoke 46 2.7 Availability of Facilities and Services to the Rural Population The NFHS-2 Village Questionnaire collected information from the sarpanch, other village officials, or other knowledgeable persons in the village on facilities and services in the village that can affect health and family planning. One important set of questions was on the distance of the village from various types of health facilities, including Primary Health Centres (PHCs), sub- centres, hospitals, and dispensaries or clinics. Table 2.17 summarizes findings on distance from a health facility. The unit of analysis is ever-married women age 15–49 who reside in rural areas. Thirteen percent of rural women live in a village with a Primary Health Centre, 33 percent live in a village with a sub-centre, and 37 percent live in a village with either a PHC or a sub-centre. The proportions who live in a village with other health facilities are 10 percent for hospitals and 28 percent for dispensaries or clinics. Nearly half of women (47 percent) live in a village that has some kind of health facility. Median distances from particular health facilities are 4.9 km for a Primary Health Centre, 1.3 km for a sub-centre, 6.7 km for a hospital, and 2.4 km for a dispensary or a clinic. Fourteen percent of rural women need to travel at least five kilometres to reach the nearest health facility. Table 2.18 shows the proportion of residents (the de jure rural population) in rural India that live in villages which have various facilities and services. Eighty percent of rural residents live in villages that have a primary school, 45 percent live in villages with a middle school, and more than one-quarter (26 percent) live in villages that have a secondary school. Higher secondary schools are available in villages where 14 percent of the rural population live. Almost two-thirds of rural residents (64 percent) live in villages that have an anganwadi2 (a nursery school for children age 3–6 years) and nearly one-quarter (24 percent) live in villages with an adult education centre. Forty-two percent of rural residents live in villages that have a private doctor and 59 percent live in villages with a traditional birth attendant. 2Anganwadi workers provide integrated child development services and may also engage in the promotion of family planning among parents of preschool age children. Table 2.17 Distance from the nearest health facility Percent distribution of ever-married rural women age 15–49 by distance from the nearest health facility, India, 1998–99 Health facility Distance Primary Health Centre Sub- centre Either PHC or sub-centre Hospital1 Dispensary/ clinic Any health facility Within village < 5 km 5–9 km 10+ km Don’t know/missing Total percent Median distance 13.1 33.0 36.5 9.7 28.3 47.4 28.4 39.7 40.8 25.0 32.4 38.9 29.2 16.3 15.3 25.1 17.4 9.7 28.8 9.6 7.0 40.0 21.7 3.9 0.5 1.4 0.3 0.2 0.2 0.2 100.0 100.0 100.0 100.0 100.0 100.0 4.9 1.3 1.0 6.7 2.4 0.0 Note: The category ‘< 5 km’ excludes cases where the facility is within the village. When median distance is calculated, ‘within village’ cases and cases with a facility less than 1 km from the village are assigned a distance of zero. PHC: Primary Health Centre 1Includes community health centre, rural hospital, government hospital, and private hospital 47 Eighty-one percent of rural residents live in villages that are at least partly electrified. Although only 14 percent of rural residents live in villages with an STD booth (for telephoning within India), 61 percent live in villages that have at least one household with a private telephone. Almost one-fifth of rural Indians live in villages that have a community television set, and 28 percent of rural residents live in villages that have cable television service, providing further evidence that the exposure to electronic mass media is limited in rural India. Slightly more than one-third live in villages with a mahila mandal, a women’s community group. Other facilities and clubs that are available in villages where more than one-third of rural residents live are kirana shops (small grocery stores), fair price shops, paan shops, post offices, and youth clubs. The most widely available rural development programmes as reported by the respondents to the Village Questionnaire are the Indira Awas Yojana (IAY) and the Integrated Rural Development Programme (IRDP). Table 2.18 Availability of facilities and services Percentage of rural residents living in villages that have selected facilities and services, India, 1998–99 Facility/service Percentage of residents Facility/service Percentage of residents Primary school Middle school Secondary school Higher secondary school College Anganwadi Adult education centre Primary Health Centre Sub-centre Hospital1 Dispensary/clinic Private doctor Visiting doctor Village health guide Traditional birth attendant Mobile health unit Electricity Bank Post office Telegraph office STD (Subscriber Trunk Dialling) phone booth 79.7 44.6 26.3 14.0 2.8 63.8 24.2 12.9 32.3 9.6 28.3 41.9 31.4 33.0 58.9 12.1 81.3 20.7 43.2 10.9 13.7 At least one village household has a telephone Mill/small-scale industry Credit cooperative society Agricultural cooperative society Fishermen’s cooperative society Milk cooperative society Kirana/general market shop Weekly market Fair price shop Paan shop Pharmacy/medical shop Mahila mandal Youth club Community centre Community television set Cable connection Integrated Rural Development Programme (IRDP) National Rural Employment Programme (NREP) Training Rural Youth for Self-Employment (TRYSEM) Employment Guarantee Scheme (EGS) Development of Women and Children of Rural Areas (DWACRA) Indira Awas Yojana (IAY) Sanjay Gandhi Niradhar Yojana (SGNY) Total population 61.0 24.8 25.0 27.2 5.5 21.8 67.0 23.1 61.1 57.6 25.6 33.7 38.8 19.9 17.7 28.3 53.6 13.3 22.2 9.5 28.4 59.1 27.4 360,764 Note: Table is based on the de jure population. 1Includes community health centre, rural hospital, government hospital, and private hospital CHAPTER 3 BACKGROUND CHARACTERISTICS OF RESPONDENTS Women's demographic and health-seeking behaviour is associated with several characteristics including their age, marital status, religion, and caste. Modernizing influences such as education and exposure to mass media are also important catalysts for demographic and socioeconomic change. In addition, women’s status and autonomy are critical in promoting change in reproductive attitudes and behaviour, especially in patriarchal societies (Dyson and Moore, 1983; Das Gupta, 1987; Jeffery and Basu, 1996). The National Population Policy, 2000, of the Government of India identifies the low status of women in India, typified by factors such as discrimination against the girl child and female adolescents, early age at marriage, and high rates of maternal mortality, as an important barrier to the achievement of population and maternal and child welfare goals (Ministry of Health and Family Welfare, 2000). This chapter presents a profile of the demographic and socioeconomic characteristics of ever-married women age 15–49 who were identified by the NFHS-2 Household Questionnaire as eligible respondents for the Woman’s Questionnaire. In addition, data are presented on the extent to which women in India enjoy autonomy as measured by their participation in household decisionmaking, freedom of movement, and access to money they can spend as they wish. Finally, data on women's attitudes towards the acceptance of spousal violence under specific circumstances and their experience of physical violence are discussed. 3.1 Background Characteristics Table 3.1 presents the percentage distribution of ever-married women age 15–49 by age, marital status, coresidence with husband, education, religion, caste/tribe, work status, and husband’s education. In India, the proportion of respondents in five-year age groups increases from 9 percent in the age group 15–19 years to 20 percent in the age group 25–29 years, and then falls steadily to 9 percent in the age group 45–49 years. The initial increase reflects the increasing share of ever-married women in each of these age groups. The decline after age 25–29 (an age by which most women have been married) reflects the normal pyramid shape of the population's age distribution. The age distribution of rural and urban respondents is similar with the notable exception that the proportion of rural respondents who are age 15–19 (11 percent) is more than twice as high as the proportion of urban respondents in this age group (5 percent). The proportion of rural respondents age 20–24 years is also somewhat higher than the proportion of urban respondents in this age group. Thus, the average rural respondent is somewhat younger than the average urban respondent. The higher share of younger respondents, especially respondents age 15–19, among rural women than among urban women is largely a consequence of the lower age at marriage in rural areas. Ninety-four percent of respondents are currently married, 4 percent are widowed, and 2 percent are divorced, separated, or deserted. The proportion of respondents living with their husbands is 89 percent, indicating that an overwhelming majority of all currently married women were coresident with their husbands at the time of the survey. Women in rural areas are slightly more likely than women in urban areas to be living apart from their husbands. 50 For India as a whole, 82 percent of all respondents are Hindu, 13 percent are Muslim, 3 percent are Christian, 2 percent are Sikh, and 1 percent are Buddhist/Neo-Buddhist. The remaining religions together account for only 1 percent of all respondents. The proportion of respondents who are Hindu is lower in urban areas (76 percent) than in rural areas (84 percent), whereas the proportion who are Muslim is higher in urban areas (17 percent) than in rural areas Table 3.1 Background characteristics of respondents Percent distribution of ever-married women age 15–49 by selected background characteristics, according to residence, India, 1998–99 Residence Number of women Background characteristic Urban Rural Total Weighted Unweighted Age 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Marital status Currently married Widowed Divorced Separated Deserted Coresidence with husband Living with husband Not living with husband Not currently married Education Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Missing Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Jewish Zoroastrian/Parsi Doni-polo Sanamahi Other No religion Missing Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Missing 5.1 10.6 9.2 8,182 6,962 16.2 19.2 18.4 16,389 15,787 19.8 19.9 19.9 17,745 17,941 18.3 16.4 16.9 15,094 15,612 16.6 14.0 14.7 13,089 13,603 13.4 11.2 11.8 10,521 10,839 10.6 8.7 9.2 8,179 8,455 93.7 93.8 93.8 83,649 83,832 4.3 4.2 4.2 3,749 3,598 0.4 0.4 0.4 344 373 0.9 1.0 1.0 860 828 0.7 0.7 0.7 599 568 90.7 88.5 89.0 79,424 79,515 3.0 5.4 4.7 4,225 4,317 6.3 6.2 6.2 5,550 5,367 33.2 67.0 58.2 51,871 48,410 5.5 6.1 5.9 5,284 5,377 16.4 12.4 13.4 11,986 12,256 12.2 6.8 8.2 7,328 8,300 14.5 4.9 7.4 6,627 7,527 18.3 2.8 6.8 6,092 7,317 0.0 0.0 0.0 11 12 76.0 83.8 81.7 72,903 69,234 16.5 11.1 12.5 11,190 10,668 3.3 2.3 2.5 2,263 4,987 1.5 1.6 1.6 1,427 2,084 0.9 0.2 0.4 331 358 1.5 0.5 0.8 676 922 0.0 0.0 0.0 1 4 0.0 0.0 0.0 8 7 0.0 0.0 0.0 29 361 0.0 0.0 0.0 16 142 0.1 0.3 0.3 231 197 0.0 0.1 0.0 44 154 0.1 0.1 0.1 79 81 14.7 19.5 18.3 16,301 15,000 3.6 10.5 8.7 7,750 10,740 30.1 33.9 32.9 29,383 25,751 51.1 34.9 39.1 34,904 37,062 0.5 1.1 1.0 862 646 Contd. 51 (11 percent). Also, a higher proportion of urban respondents than rural respondents are Christian, Jain, or Buddhist/Neo-Buddhist. One-third of all respondents belong to other backward classes, about one-fifth (18 percent) belong to scheduled castes, and about one-tenth (9 percent) belong to scheduled tribes. The largest proportion (39 percent), however, are respondents who do not belong to any scheduled caste, scheduled tribe, or other backward class, and this proportion is much higher in urban areas (51 percent) than in rural areas (35 percent). Women belonging to scheduled castes, scheduled tribes, or other backward classes constitute a higher proportion of rural than urban respondents. The educational levels of respondents and their husbands have an important influence on demographic and health-seeking behaviour. Fifty-eight percent of ever-married women age 15–49 in India are illiterate, down from 63 percent at the time of NFHS-1. This decline is due to declines in illiteracy for both rural and urban women. Between NFHS-1 and NFHS-2, the proportion illiterate declined from 72 percent to 67 percent in rural areas and from 37 percent to 33 percent in urban areas. Notably, however, the urban-rural difference in illiteracy remains high. Only 14 percent of all respondents have completed at least high school, slightly higher than at the time of NFHS-1 when this proportion was 11 percent. Thirty-three percent of urban respondents have attained this educational level compared with 8 percent of rural respondents. Among respondents who are literate, the largest proportion are those who have completed primary school (but not middle school). Sixteen percent of women in urban areas have completed primary school (but not middle school) compared with 12 percent in rural areas. Thirty-one percent of respondents have illiterate husbands, down from 35 percent in NFHS-1. The proportion of respondents with illiterate husbands is more than twice as high in rural areas (36 percent) as in urban areas (15 percent). In both rural and urban areas, the Table 3.1 Background characteristics of respondents (contd.) Percent distribution of ever-married women age 15–49 by selected background characteristics, according to residence, India, 1998–99 Residence Number of women Background characteristic Urban Rural Total Weighted Unweighted Work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Missing Husband’s education Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Don’t know/missing Total percent Number of women Weighted Unweighted 4.4 18.0 14.4 12,849 12,987 15.3 21.3 19.7 17,571 15,449 5.9 4.7 5.0 4,483 4,727 74.4 56.0 60.8 54,271 56,016 0.0 0.0 0.0 25 20 14.9 36.4 30.8 27,449 24,953 6.4 9.9 9.0 7,991 7,675 14.8 16.9 16.4 14,614 14,282 13.6 13.3 13.3 11,907 12,815 19.4 12.8 14.5 12,936 14,039 30.6 10.4 15.7 14,037 15,183 0.3 0.3 0.3 266 252 100.0 100.0 100.0 NA NA 23,370 65,829 89,199 89,199 NA 27,862 61,337 89,199 NA 89,199 NA: Not applicable 52 proportion of women with illiterate husbands has declined since NFHS-1 (when the percentages were 41 and 17 in rural and urban areas, respectively). At the other educational extreme, 30 percent of women have husbands who have completed at least high school (up from 27 percent in NFHS-1), and the percentage in urban areas (50 percent) is more than twice that in rural areas (23 percent). By contrast, there are only small differences by residence in the proportion of women with husbands who have completed primary or middle school. Sixty-one percent of respondents in India did not participate in work other than their regular housework during the 12 months preceding the NFHS-2 survey. More than half (56 percent) of rural respondents and almost three-quarters (74 percent) of urban respondents fall into this category. The highest proportions of working women in both urban and rural areas were employed by someone else (21 percent of all rural women and 15 percent of all urban women). Eighteen percent of rural women worked on their own family farm or in a family business compared with only 4 percent of urban women (Figure 3.1). The proportion of women who were self-employed is about the same in rural and urban areas (5–6 percent). 3.2 Educational Level Table 3.2 presents the percent distribution of ever-married women age 15–49 by the highest level of education attained, according to age, religion, caste/tribe, and husband’s education. The educational distribution of women in different age groups illustrates the progress in the spread of education over a period of about three decades. Illiteracy declines with declining age from 65 percent for women age 45–49 to 52 percent for women age 20–24, but rises to 59 percent for women age 15–19 (undoubtedly because illiterate women are more likely than literate women to marry at a young age). Thus, even though illiteracy is declining, more than half of even the youngest cohorts of ever-married women continue to be illiterate. At the other end of the educational spectrum, the proportion of respondents who have completed at least high school, although still very low, is almost 50 percent higher for women age 20–24 (17 percent) than for Figure 3.1 Employment Status of Women by Residence Note: Urban percents add to less than 100 due to rounding NFHS-2, India, 1998–99 Urban Self-Employed 6% Employed by Someone Else 15% Working in Family Farm/Business 4% Not Worked in Past 12 Months 74% Rural Not Worked in Past 12 Months 56% Working in Family Farm/Business 18% Employed by Someone Else 21% Self-Employed 5% 53 women age 40–49 (11–12 percent). The proportions of respondents who have completed primary school or middle school also tend to increase with decreasing age. A similar proportion of Hindu (59 percent) and Muslim (61 percent) women are illiterate but illiteracy is very low among Jain women (only 7 percent). Jain women are also much more likely to have completed at least high school (54 percent) than other women. Christian and Sikh women also have substantially higher literacy and educational attainment than Hindu and Muslim women. Women's educational attainment varies widely by their caste/tribe. While 44 percent of women not belonging to any scheduled caste, scheduled tribe, or other backward class are illiterate, much larger proportions are illiterate among women belonging to scheduled tribes (79 percent), scheduled castes (73 percent), and other backward classes (61 percent). Scheduled- Table 3.2 Respondent’s level of education by background characteristics Percent distribution of ever-married women age 15–49 by highest level of education attained, according to selected background characteristics, India, 1998–99 Respondent’s level of education Background characteristic Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Missing Total percent Number of women Age 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Husband’s education Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Total 59.0 6.1 16.8 11.1 5.2 1.8 0.0 100.0 8,182 52.1 5.3 14.0 11.6 9.3 7.7 0.0 100.0 16,389 55.2 5.3 13.0 8.8 8.4 9.3 0.0 100.0 17,745 58.1 5.7 13.3 7.5 7.3 8.1 0.0 100.0 15,094 60.9 6.3 13.1 6.3 6.8 6.6 0.0 100.0 13,089 62.8 6.8 12.6 5.6 6.5 5.7 0.0 100.0 10,521 65.4 7.1 11.7 5.1 6.2 4.5 0.0 100.0 8,179 59.3 5.4 13.0 8.3 7.2 6.8 0.0 100.0 72,903 60.5 9.5 14.8 6.1 5.6 3.5 0.1 100.0 11,190 32.9 7.3 15.4 13.1 14.6 16.7 0.0 100.0 2,263 38.9 3.0 18.1 9.8 16.4 13.8 0.0 100.0 1,427 6.8 2.5 22.6 14.3 23.4 30.4 0.0 100.0 331 44.7 10.8 14.6 13.2 8.7 7.9 0.0 100.0 676 70.3 6.2 8.5 8.8 4.0 2.1 0.0 100.0 285 51.2 17.7 5.3 12.3 5.5 8.0 0.0 100.0 44 73.0 5.1 9.8 6.2 3.6 2.4 0.0 100.0 16,301 79.0 5.3 7.1 4.7 2.2 1.6 0.0 100.0 7,750 60.9 5.3 13.8 8.3 6.9 4.8 0.0 100.0 29,383 43.8 7.0 16.3 10.0 10.9 11.9 0.0 100.0 34,904 90.0 3.4 4.8 1.3 0.4 0.1 0.0 100.0 27,449 70.0 14.0 10.6 3.5 1.6 0.3 0.1 100.0 7,991 60.7 8.5 20.2 6.4 3.5 0.8 0.0 100.0 14,614 48.1 8.0 21.2 14.7 6.2 1.9 0.0 100.0 11,907 34.9 4.9 19.8 16.1 17.9 6.3 0.0 100.0 12,936 16.2 2.7 12.6 13.7 20.0 34.7 0.0 100.0 14,037 58.2 5.9 13.4 8.2 7.4 6.8 0.0 100.0 89,199 Note: Total includes 79, 862, and 266 women with missing information on religion, caste/tribe, and husband’s education, respectively, who are not shown separately. 54 tribe women, followed by scheduled-caste women, are less likely than other women to have completed primary school, middle school, or high school. Ninety percent of women with illiterate husbands are themselves illiterate. Notably, 35 percent of women whose husbands have completed high school (but not higher secondary school) and 16 percent of women whose husbands have completed higher secondary school are illiterate. These results show that husbands at each level of education are more likely to have wives with a lower level of education than an equal or a higher level of education. Specifically, the proportion of women who have lower education than their husbands is 70 percent for women whose husbands are literate but have not completed primary school, 69 percent for women whose husbands have completed primary school, 77 percent for women whose husbands have completed middle school, 76 percent for women whose husbands have completed high school, and 65 percent for women whose husbands have completed higher secondary school. Among women with literate husbands, women whose husbands have completed higher secondary school are most likely to have equal or higher education than their husbands (35 percent). Table 3.3 shows state differentials in literacy and educational attainment for ever-married women age 15–49. The literacy rate for ever-married women is highest in Mizoram (90 percent), closely followed by Kerala (87 percent), and is lowest in Bihar (23 percent), Rajasthan (25 percent), and Uttar Pradesh (30 percent). The percentage of respondents who have completed high school ranges from only 7 percent in Rajasthan to 44 percent in Delhi. Other states where the percentage of respondents who have completed high school is relatively high (30 percent or higher) are Kerala, Goa, and Punjab. States other than Rajasthan where less than 10 percent of women have completed high school are Orissa, Bihar, Meghalaya, Madhya Pradesh, Arunachal Pradesh, and Assam. A comparison between NFHS-1 and NFHS-2 by state shows that literacy rates of ever-married women have increased in 22 out of 23 states where comparable data are available from both surveys. The literacy rate increased most rapidly in the northeastern states of Arunachal Pradesh and Meghalaya and in the northern states of Himachal Pradesh and Punjab. Bihar and Rajasthan continue to have very low literacy among ever-married women; these states were the last-ranked states in India in female literacy in both NFHS-1 and NFHS-2. 3.3 Age at First Marriage Table 3.4 gives information on age at first marriage. The table shows the percentage of all women (ever-married and never-married) who first married by specified exact ages, and the median age at first marriage and first cohabitation by current age and residence. The median age at first marriage and median age at first cohabitation with husband for a cohort of women is the age by which 50 percent of the cohort marries and cohabits, respectively. The table provides evidence of a steady rise in the age at first marriage in India. The proportion married by exact age 15 falls steadily from the oldest to the youngest age group, but even more remarkable is the fact that the proportion falls from 24 percent for women age 20–24 to 14 percent for women age 15–19 who are only five years younger, on average. In rural areas, the proportion of women married by age 15 declines from 29 percent among women age 20–24 to 18 percent among women age 15–19; the corresponding decline in urban areas is from 9 percent to 5 percent. The practice of very early marriage (before age 13) has virtually disappeared in urban areas and has become quite rare in rural areas as well. 55 The median age at first marriage has also risen over the past three decades. In rural areas, the median age at first marriage is more than one and one-half years higher for women age 20–24 than for women age 45–49, and in urban areas it is also more than one and one-half years higher for women age 25–29 than for women age 45–49. (The median age at first marriage could not be calculated for women age 15–19 and 20–24 in urban areas and for women age 15–19 in rural areas as more than half of the women in these age groups were not married at the time of the survey). Despite this evidence of a rising age at marriage, the table shows that the majority of women age 20–49 in India married before they reached the legal minimum age at marriage of 18 years, as set by the Child Marriage Restraint Act of 1978. Specifically, 61 percent of all women, 69 percent of rural women, and 41 percent of urban women age 20–49 married before age 18. The median age at first marriage for women age 20–49 in rural areas is only 16 years, well below Table 3.3 Respondent’s level of education by state Percent distribution of ever-married women age 15–49 by highest level of education attained, according to state, India, 1998–99 Respondent’s level of education State Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Missing Total percent India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 58.2 5.9 13.4 8.2 7.4 6.8 0.0 100.0 29.1 2.7 12.5 11.5 15.4 28.7 0.0 100.0 55.2 2.4 14.3 8.1 10.8 9.2 0.0 100.0 36.3 4.3 23.6 12.6 15.6 7.6 0.0 100.0 69.8 1.5 7.9 8.9 6.5 5.4 0.0 100.0 38.8 2.9 18.3 10.5 16.8 12.7 0.0 100.0 75.5 2.8 8.6 5.9 3.7 3.5 0.0 100.0 68.5 5.3 11.0 5.7 3.5 5.9 0.0 100.0 70.2 2.7 9.1 6.8 4.3 6.9 0.0 100.0 76.6 3.0 8.1 3.8 5.7 2.7 0.0 100.0 59.5 9.6 16.5 6.9 4.4 3.1 0.0 100.0 50.0 14.4 14.9 10.1 5.1 5.5 0.1 100.0 52.7 9.4 14.5 13.8 5.5 4.1 0.0 100.0 53.9 11.9 10.5 14.1 5.4 4.2 0.0 100.0 42.9 7.6 9.3 17.1 8.6 14.5 0.0 100.0 38.1 28.4 12.6 11.6 4.6 4.6 0.0 100.0 10.0 25.7 25.4 22.8 10.3 5.8 0.0 100.0 39.8 11.3 22.2 15.1 6.8 4.7 0.1 100.0 49.4 11.8 15.8 11.2 6.5 5.2 0.1 100.0 28.6 10.9 16.3 12.5 15.4 16.3 0.0 100.0 50.3 6.1 14.7 8.7 9.2 11.0 0.0 100.0 44.6 8.8 18.1 10.8 9.8 7.9 0.0 100.0 63.8 5.2 15.4 4.8 6.8 4.0 0.0 100.0 55.2 4.4 14.3 6.6 11.0 8.5 0.0 100.0 12.6 9.3 20.9 17.1 24.6 15.6 0.0 100.0 47.5 4.5 18.7 13.4 8.2 7.6 0.0 100.0 56 the legal minimum. The median age at first marriage is 2–3 years higher for urban women than for rural women in all age groups for which a comparison is possible. The difference between the median age at first marriage and the median age at first cohabitation is no more than one year among women in any age group, even in rural areas. In addition, the difference between these two medians has been decreasing over time. This suggests that gauna or similar cultural practices that introduce a lag between marriage and cohabitation are no longer widely observed in India. Table 3.5 presents information on age at first marriage for women age 25–49 by state. There are considerable differences across states in the age at first marriage of women. About half of women age 25–49 married before age 15 in Madhya Pradesh, Bihar, Uttar Pradesh, Andhra Pradesh, and Rajasthan, and about four-fifths of women in these states married before reaching the legal minimum age at marriage of 18 years. By contrast, the median age at first marriage is Table 3.4 Age at first marriage Percentage of women married by specific exact ages, median age at first marriage, and median age at first cohabitation with husband, according to current age and residence, India, 1998–99 Percentage ever married by exact age Current age1 13 15 18 20 22 25 Median age at first marriage Median age at first cohabitation with husband URBAN 15–19 20–24 25–29 30–34 35–39 40–44 45–49 20–49 25–49 1.1 4.8 NA NA NA NA NC NC 2.8 9.0 27.9 47.0 NA NA NC NC 4.4 13.9 36.6 57.2 71.0 83.9 19.1 19.3 6.2 16.9 43.3 63.4 76.6 88.3 18.5 18.7 8.3 21.4 49.4 67.2 79.3 89.5 18.1 18.3 7.9 20.2 51.2 69.9 82.0 91.0 17.9 18.2 9.4 23.3 54.4 71.1 83.2 92.8 17.5 18.0 5.9 16.2 41.3 60.4 NA NA 18.7 18.9 6.8 18.4 45.5 64.6 77.4 88.4 18.4 18.6 RURAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 20–49 25–49 6.0 17.8 NA NA NA NA NC NC 11.4 29.1 58.6 74.8 NA NA 16.9 17.6 15.0 35.0 67.4 81.8 89.2 93.9 16.1 16.9 17.5 38.0 73.0 85.6 92.6 96.2 15.8 16.6 19.2 39.7 73.9 87.1 93.3 96.7 15.7 16.5 22.8 44.1 76.0 88.4 94.7 97.6 15.4 16.4 25.6 45.9 77.3 88.0 94.3 97.2 15.3 16.3 17.1 36.9 69.2 82.9 NA NA 16.0 16.8 19.0 39.4 72.5 85.5 92.3 96.0 15.8 16.6 TOTAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 20–49 25–49 4.7 14.3 NA NA NA NA NC NC 8.9 23.5 50.0 67.1 NA NA 18.0 18.3 12.1 29.2 58.9 74.9 84.1 91.0 16.9 17.5 14.2 31.9 64.3 79.1 87.8 93.8 16.4 17.1 15.9 34.1 66.5 81.0 89.0 94.4 16.2 16.9 18.4 37.0 68.7 83.0 91.1 95.8 16.0 16.8 20.7 39.0 70.4 82.9 91.0 95.9 15.8 16.7 13.9 30.9 61.1 76.4 NA NA 16.7 17.4 15.4 33.3 64.6 79.4 87.9 93.7 16.4 17.0 NA: Not applicable NC: Not calculated because less than 50 percent of women in the age group have married or started living with their husband by the start of the five-year age group 1The current age group includes both never-married and ever-married women. 57 22–23 years in Goa, Mizoram, and Manipur, and 20 years in Kerala, Nagaland, Punjab, and Sikkim. Notably, however, in Kerala, Nagaland, Punjab, and Manipur at least one out of five women were already married by age 18. The difference between the median age at marriage and the median age at cohabitation with the husband is at least one year in Bihar, Rajasthan, Madhya Pradesh, Uttar Pradesh, and Haryana, indicating that in these states gauna is still followed, albeit on a limited scale. In other states, however, this practice is followed to only a negligible extent, if at all. 3.4 Exposure to Mass Media In a country like India where a large majority of women are illiterate or have little formal education, informal channels such as the mass media can play an important role in bringing about modernization. In NFHS-2, women were asked questions about whether they read a newspaper or magazine, watch television, or listen to the radio at least once a week, and whether Table 3.5 Age at first marriage by state Percentage of women age 25–49 married by specific exact ages, median age at first marriage, and median age at first cohabitation with husband, according to state, India, 1998–99 Percentage ever married by exact age State 13 15 18 20 22 25 Median age at first marriage Median age at first cohabitation with husband India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 15.4 33.3 64.6 79.4 87.9 93.7 16.4 17.0 4.7 13.3 37.6 57.7 75.5 90.3 19.0 19.3 10.1 18.3 59.9 78.3 89.8 96.2 16.9 17.9 2.1 6.7 38.2 67.1 83.3 93.3 18.6 18.8 6.0 17.3 47.5 64.9 78.0 88.2 18.2 18.4 1.2 2.5 22.7 49.4 74.6 90.5 20.0 20.1 30.1 47.8 81.5 91.0 96.3 98.5 15.1 16.4 30.8 52.6 78.5 87.4 92.3 95.5 14.7 16.0 27.7 49.7 79.6 89.9 94.7 97.3 15.0 16.3 23.0 51.0 83.9 93.6 96.7 97.9 14.9 16.6 2.8 15.2 58.2 78.5 88.8 93.8 17.5 17.6 9.0 24.9 62.1 78.2 86.3 92.2 16.8 16.9 3.7 11.1 39.7 64.0 77.7 86.4 18.7 18.8 3.4 14.1 49.1 66.4 77.4 85.9 18.1 18.2 0.3 3.1 20.6 37.8 51.6 67.2 21.7 21.8 1.1 7.0 34.8 58.0 72.5 81.7 19.1 19.3 0.1 0.8 13.0 32.5 50.0 68.7 22.0 22.0 0.6 4.2 24.4 48.2 64.1 77.9 20.1 20.2 2.4 9.5 35.5 51.7 65.1 78.4 19.8 19.8 1.7 4.2 15.3 28.2 42.3 61.7 23.2 23.2 8.4 21.0 54.1 73.2 86.4 94.2 17.6 18.2 11.3 33.5 65.1 80.4 88.2 93.9 16.4 16.7 22.1 48.9 79.8 89.8 94.5 96.8 15.1 15.4 9.1 27.5 60.6 76.3 84.6 91.7 16.8 17.0 0.9 5.1 27.1 48.4 64.5 82.0 20.2 20.3 2.6 11.6 41.6 64.7 79.6 90.3 18.7 18.8 58 they visit the cinema or theatre at least once a month. Table 3.6 gives information on women’s exposure to these forms of mass media by selected background characteristics. In India two-fifths of women are not regularly exposed to any mass media. As expected, regular exposure to any media is much more widespread among urban women (87 percent) than among rural women (50 percent). Media exposure varies even more widely by education and standard of living. A negligible proportion (4 percent) of women who have completed at least Table 3.6 Exposure to mass media Percentage of ever-married women age 15–49 who usually read a newspaper or magazine, watch television, or listen to the radio at least once a week, who usually visit a cinema/theatre at least once a month, or who are not regularly exposed to any of these media by selected background characteristics, India, 1998–99 Exposure to mass media Background characteristic Reads a newspaper or magazine at least once a week Watches television at least once a week Listens to the radio at least once a week Visits the cinema/theatre at least once a month Not regularly exposed to any media Number of women Age 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 14.6 38.0 33.3 14.3 45.0 8,182 21.7 45.2 37.0 14.5 39.1 16,389 22.5 46.7 37.3 12.1 39.3 17,745 21.9 46.5 36.4 10.0 40.0 15,094 21.1 46.7 36.2 8.2 40.7 13,089 20.5 47.5 37.6 6.6 39.7 10,521 19.5 47.0 36.3 6.0 41.2 8,179 43.4 80.6 46.3 18.1 12.9 23,370 12.8 33.4 33.0 7.9 50.1 65,829 0.0 27.2 23.5 6.5 59.8 51,871 29.9 59.2 47.8 11.8 21.5 17,270 49.2 71.9 54.7 15.1 11.0 7,328 77.0 88.1 63.7 23.0 3.5 12,719 20.2 45.4 36.4 11.2 40.9 72,903 17.2 39.6 32.8 6.2 44.8 11,190 43.7 57.6 54.0 14.2 20.4 2,263 30.9 75.5 34.9 5.7 19.4 1,427 69.5 88.4 48.6 15.0 7.3 331 32.7 67.8 42.6 14.1 23.0 676 10.2 23.5 32.4 5.3 57.9 285 26.5 37.1 30.3 13.6 48.9 44 11.0 36.9 31.1 10.3 48.3 16,301 8.5 22.7 25.1 5.4 61.8 7,750 18.8 45.1 36.3 12.5 40.7 29,383 30.2 56.1 42.0 10.5 31.0 34,904 4.1 18.5 20.3 8.2 66.9 29,033 17.4 46.5 38.9 9.5 36.2 41,289 55.5 88.2 57.2 17.0 6.8 17,845 20.8 45.7 36.5 10.6 40.3 89,199 Note: Total includes 11, 79, 862, and 1,032 women with missing information on education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. 59 high school are not regularly exposed to any media compared with 60 percent of illiterate women. Sixty-seven percent of women in households with a low standard of living are not exposed to any media compared with 36 percent of women in households with a medium standard of living and 7 percent of women in households with a high standard of living. Regular exposure to media is highest for Jain women (93 percent), followed by Sikh (81 percent) and Christian (80 percent) women, and it is slightly higher for Hindu women (59 percent) than for Muslim women (55 percent). Scheduled-tribe women are much less likely (38 percent) to be regularly exposed to media than scheduled-caste women (52 percent) or women belonging to other backward classes (59 percent). More than two-thirds (69 percent) of women who do not belong to any scheduled caste, scheduled tribe, or other backward class are regularly exposed to any form of mass media. Exposure to mass media varies little by age although the youngest women (age 15–19) are somewhat less likely than older women to be regularly exposed to any media. Among the different types of mass media, television has the greatest reach across almost all categories of women. Overall, 46 percent of respondents watch television at least once a week, 37 percent listen to the radio at least once a week, 21 percent read a newspaper or magazine at least once a week, and 11 percent visit the cinema or theatre at least once a month. The proportion of women who watch television at least once a week has increased sharply since the time of NFHS-1, when it was 32 percent. There has, however, been a decline in exposure to the radio and cinema/theatre in the six and one-half years between the two surveys. The proportion of women listening to the radio at least once a week declined from 44 percent in NFHS-1 to 37 percent in NFHS-2 and the proportion who visit the cinema or theatre at least once a month declined from 15 percent to 11 percent over the same period. Exposure to the cinema or theatre decreases with age, whereas the youngest women are less likely than older women to be exposed to the other forms of media. Exposure to each of the different forms of media increases sharply with urban residence, education, and standard of living. Jain women are more likely than women of any other religion or no religion to be exposed to each of the different forms of media. Urban women are much more likely to watch television (81 percent) than to listen to the radio at least once a week (46 percent), whereas rural women are equally likely to be regularly exposed to television and radio (both 33 percent). Notably, women who have completed at least high school are more likely to be regularly exposed to the print media than to the radio or cinema. Interstate variations in media exposure are presented in Table 3.7. The proportion of ever-married women age 15–49 not regularly exposed to any form of media varies from a low of 7 percent in Delhi to a high of 73 percent in Bihar. More than three-quarters of women are regularly exposed to at least one form of media in Delhi, Himachal Pradesh, and Punjab in the north, Manipur, Mizoram, and Sikkim in the northeast, Goa in the west, and all four of the southern states. By contrast, less than half of women are regularly exposed to any form of mass media in Bihar, Rajasthan, Orissa, and Uttar Pradesh (Figure 3.2). The pattern of exposure to each of the different forms of media also varies greatly by state. Regular exposure to television is highest in Delhi where 90 percent of women watch television at least once a week and lowest in Bihar where only 17 percent of women do so. The proportion listening to the radio at least once a week varies from a high of 71 percent in Kerala to 17 percent in Rajasthan. In 16 of the 25 states, women are more likely to be regularly exposed 60 to television than to any other form of media. The exposure to print media, which is dependent on literacy, varies from a high of 64–65 percent in Mizoram and Kerala (the two Indian states where literacy is highest) to a low of 9 percent in Bihar and 11 percent in Arunachal Pradesh and Orissa. Cinema or theatre is most popular in Andhra Pradesh where 35 percent of women visit a cinema or theatre at least once a month and least popular in Mizoram and Nagaland where only 1 percent of women do so. Cinema or theatre is also popular in Tamil Nadu, Karnataka, and Sikkim, where 19–22 percent of women visit the cinema/theatre regularly. The proportion of women regularly exposed to the cinema or theatre is less than the proportion exposed to each of the other forms of media in every state except Andhra Pradesh and Arunachal Pradesh. During the six and one-half years between NFHS-1 and NFHS-2, every state registered an increase in the proportion of women who watch television, with increases of 20 percentage Table 3.7 Exposure to mass media by state Percentage of ever-married women age 15–49 who usually read a newspaper or magazine, watch television, or listen to the radio at least once a week, who usually visit a cinema/theatre at least once a month, or who are not regularly exposed to any of these media according to state, India, 1998–99 Exposure to mass media State Reads a newspaper or magazine at least once a week Watches television at least once a week Listens to the radio at least once a week Visits the cinema/theatre at least once a month Not regularly exposed to any media India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 20.8 45.7 36.5 10.6 40.3 50.1 90.1 54.1 14.5 7.3 21.7 60.9 31.4 4.0 33.1 27.5 73.9 56.5 2.0 16.3 12.7 54.6 57.6 2.5 25.6 31.4 77.3 35.4 5.7 18.0 12.4 30.2 16.7 2.9 63.1 16.4 44.5 28.2 7.4 45.2 12.6 32.1 29.5 3.5 54.7 9.3 16.8 20.3 4.4 72.7 10.7 27.7 33.1 4.6 55.7 15.0 40.8 41.6 9.7 38.6 10.5 47.5 41.5 10.6 36.7 16.5 28.8 40.8 5.6 47.4 39.3 61.2 72.6 13.0 16.2 31.9 39.7 39.0 4.1 37.3 65.1 44.1 66.7 1.1 16.9 26.9 46.0 44.4 1.4 35.7 19.1 56.1 54.0 19.0 21.5 48.4 80.8 52.0 4.3 11.6 29.7 55.9 30.5 7.5 33.8 32.2 61.8 36.1 8.3 29.6 19.5 58.2 39.2 35.1 23.7 27.9 58.4 60.9 19.7 21.4 64.2 62.4 70.9 12.1 11.5 23.1 63.0 51.7 21.9 20.3 61 points or more in Himachal Pradesh, Nagaland, Manipur, Kerala, and Punjab . Regular exposure to radio increased in all of the northeastern states and slightly in Himachal Pradesh, but declined elsewhere. Regular visits to the cinema/theatre declined in 17 of the 23 states for which comparisons can be made and the decline was largest in the states where such visits were most common at the time of NFHS-1. The decrease was especially pronounced in Tamil Nadu where the percentage of women visiting the cinema/theatre at least once a month declined from 43 percent to 22 percent. 3.5 Women’s Employment Labor force participation not only gives women an opportunity to earn income, but also exposes them to the outside world and to authority structures and networks other than kin-based ones (Dixon-Mueller, 1993). In a developing country such as India, however, where women's workforce participation is often motivated by poverty, these benefits are likely to be mediated by the social context of women's work and their total work burden (Bardhan, 1985; Desai and Jain, 1994). In addition, the empowering effects of employment for women are likely to depend on their occupation, the continuity of their workforce participation, and whether they earn and Figure 3.2 Percentage of Women Not Regularly Exposed to Any Mass Media by State 0 10 20 30 40 50 60 70 80 B ihar Rajasthan O rissa U ttar P radesh Assam M adhya Pradesh IN DIA W est Benga l M egha laya Arunacha l P radesh Nagaland G ujarat Haryana M aharashtra Jam m u & K ashm ir Andhra P radesh S ikk im Karnataka Tam il N adu Punjab M izoram Him achal P radesh M anipur G oa Kera la Delh i Percent NFHS-2, India, 1998–99 62 control income. It is generally expected that women who work at a regular job, who earn money, and who perceive that their contribution is a substantial part of total family earnings are more likely to be empowered than other employed and unemployed women (Youssef, 1982; Sen, 1990; Mahmud and Johnston, 1994). The National Population Policy adopted by the Government of India in 2000 (Ministry of Health and Family Welfare, 2000) explicitly recognizes the importance of women’s paid employment in achieving the goal of population stabilization in India and also specifies measures that will encourage paid employment and self-employment of women. Table 3.8 provides information on women’s employment status for ever-married women age 15–49 by residence. For the country as a whole, 39 percent of ever-married women age 15–49 were either currently employed at the time of NFHS-2 or were employed during the 12 months preceding the survey. Current employment of ever-married women increased from 32 percent in NFHS-1 to 37 percent in NFHS-2. Forty-four percent of rural respondents but only 26 percent of urban respondents worked at any time during the year preceding the survey. The majority of women who worked during the 12 months before the survey worked throughout the year in both urban areas (77 percent) and rural areas (63 percent). A large majority of urban women (89 percent) and more than half of rural women (62 percent) who worked during the year before the survey earned money for their work. Three in 10 working women in rural areas and 1 in 10 working women in urban areas were unpaid workers. Two-thirds of women who work in India work on farms. Agricultural workers (including farmers, farm workers, and women in other agricultural occupations) account for more than three-quarters (76 percent) of women who work in rural areas. In urban areas, by contrast, there is greater occupational diversity. Twenty-seven percent of urban women who work are production workers, 17 percent are professionals, 15 percent are agricultural workers, and 13 percent are in sales and service occupations. A significant feature of women’s work participation in India is their substantial contribution to family earnings. Nearly one in five (17–18 percent) urban as well as rural women who worked for money at any time in the 12 months preceding the survey report that the family is entirely dependent on their earnings. Another 30 percent in urban areas and 24 percent in rural areas report that they contribute half or more (but not all) of the total family earnings. Only 12 percent of women in urban areas and 9 percent in rural areas report that they contribute almost nothing to total family earnings. Women who worked away from home and had a child under age three living at home were asked who took care of the child while they worked. Overall, 40 percent of the women said that they took their youngest child with them to work; this proportion was higher in urban areas (53 percent) than in rural areas (39 percent). Fifty-nine percent of women who did not take their child with them to work left the child with relatives other than their husband or older children, and 23 percent left the child with an older girl. Rural working women were more likely than urban working women to leave their child with an older girl. Less than 10 percent left the child with their husband or an older boy. 63 Table 3.8 Employment Percent distribution of ever-married women age 15–49 by employment characteristics, according to residence, India, 1998–99 Employment characteristic Urban Rural Total Employment status Currently working Worked in past 12 months (not currently working) Not worked in past 12 months Continuity of employment1 Throughout the year Seasonally/part of the year Once in a while Missing Type of earning1 Cash only Cash and kind Kind only Not paid Missing Occupation1 Professional Sales worker Service worker Production worker Agricultural worker Other worker Missing Earnings contribution to total family earnings2 Almost none Less than half About half More than half All Missing Person caring for youngest child while woman works3 Child usually taken to work Husband Older boys Older girls Other relatives Neighbours/friends Servants/hired help Child is in school Institutional child care Other Missing Total percent Number of women Number of employed women1 Number of women earning cash Number of women with a child under age three3 24.2 42.1 37.4 1.4 1.9 1.7 74.4 56.0 60.8 76.8 63.4 65.7 16.6 31.8 29.2 6.5 4.7 5.0 0.1 0.1 0.1 85.9 50.9 56.9 3.0 11.5 10.0 1.2 7.4 6.3 9.8 30.1 26.6 0.1 0.0 0.1 17.0 2.5 5.0 9.2 2.4 3.6 4.0 0.4 1.0 27.2 8.6 11.8 15.0 76.1 65.6 26.1 9.2 12.1 1.5 0.8 0.9 12.0 9.3 9.9 41.0 48.2 46.6 20.6 17.5 18.2 9.5 6.7 7.3 16.8 18.2 17.9 0.1 0.1 0.1 52.5 38.8 40.4 1.7 1.7 1.7 2.4 4.2 4.0 6.2 14.8 13.8 28.4 35.9 35.0 1.9 2.0 2.0 2.5 0.2 0.5 0.6 0.1 0.2 1.5 0.4 0.5 1.9 1.7 1.7 0.4 0.3 0.3 100.0 100.0 100.0 23,370 65,829 89,199 5,979 28,949 34,928 5,316 18,075 23,391 935 7,025 7,960 1For currently working women and women who have worked in the past 12 months 2For women earning cash 3 For women who work away from home and have a child under age three who is living at home 64 Table 3.9 shows interstate variations in the work status of ever-married women age 15–49. As noted above, the majority of women in India (61 percent) were not working at the time of the survey and had not worked in the 12 months preceding the survey. Twenty percent were employed by someone else, 14 percent worked on a family farm or in a family business, and 5 percent were self-employed. Significant statewise differences exist in the work patterns of ever-married women. The highest percentages of women who work are in the northeastern states of Manipur (70 percent), Nagaland (64 percent), and Arunachal Pradesh (60 percent), and lowest are in Punjab (9 percent) and Haryana (13 percent). Women’s work participation is also relatively low (25 percent or less) in Assam, Himachal Pradesh, Delhi, Sikkim, Uttar Pradesh, and Kerala. Work participation of women is relatively high in all the southern states except Kerala, all the western states, some northeastern states, and Madhya Pradesh. The most common form of employment in the majority of states is work that is done for someone else. More than one-third of ever-married women were employed by someone else in Tamil Nadu and Andhra Pradesh, and less than 10 percent were employed by someone else in Uttar Pradesh, Arunachal Pradesh, and all of the northern states except Delhi. Arunachal Pradesh and Manipur are the only states where working for someone else is the least important form of employment among ever-married women. Working on a family farm or in a family business is the most common type of employment in Arunachal Pradesh and Nagaland where it accounts for 37–38 percent of women, in Jammu and Kashmir and Rajasthan where it accounts for 30 percent of women, and in four other states. Self-employment is the most important form of employment in Manipur (28 percent) and more than 10 percent of women are also self-employed in Arunachal Pradesh and Nagaland. 3.6 Women’s Autonomy Education, work participation, and exposure to mass media are some of the means by which women gain status and autonomy, both important aspects of their empowerment. To measure women's autonomy and empowerment more directly, NFHS-2 asked about women's participation in household decisionmaking, their freedom of movement, and access to money that they can spend as they wish. Women's autonomy is likely to have a significant impact on the demographic and health-seeking behaviour of couples by altering women's relative control over fertility and contraceptive use, and by influencing their attitudes (for example, attitudes towards the sex composition of children) and abilities (for example, the ability to obtain health services for themselves and their children) (Sen and Batliwala, 1997). In order to measure women's participation in household decisionmaking, NFHS-2 asked women to report who in their households makes decisions about the following: what items to cook, obtaining health care for herself, purchasing jewellery or other major household items, and her going and staying with parents or siblings. The survey also asked women who earn money who decides how the money they earn is spent. Table 3.10 gives the percent distribution of the person (or persons) who makes each of the specified household decisions, according to residence. As expected, ever-married women in India are most likely to participate in decisions about what to cook: 71 percent make these decisions on their own and another 14 percent make them jointly with their husbands or someone else in the household. Fifteen percent of ever- married women, however, are not involved at all in decisions regarding what to cook. About half 65 of women are not involved at all in decisions about seeking health care for themselves (49 percent), purchasing jewellery or other major household items (47 percent), and going and staying with parents or siblings (52 percent). Among these three types of decisions, the decision that women are most likely to take on their own is the one about their own health care (28 percent), and the decision that they are least likely to take on their own is about the purchase of jewellery or other major household items (11 percent). Urban women are more likely than rural women to make all these four types of decisions on their own. Thirty percent of women who earn money report that only their husbands or only others in the household make the decision on how the money they earn will be used, 41 percent report that they make the decision on their own, and 28 percent report that they make the decision together with their husbands or someone else in their household. The proportion of women who do not participate in the decision about how the money they earn should be used is higher in rural areas (35 percent) than in urban areas (16 percent), and the proportion who make this decision alone is higher in urban areas (57 percent) than in rural areas (37 percent). Table 3.9 Work status of respondents by state Percent distribution of ever-married women age 15–49 by work status, according to state, India, 1998–99 State Working in family farm/business Employed by someone else Self- employed Not worked in the past 12 months Missing Total percent India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 14.4 19.7 5.0 60.8 0.0 100.0 3.5 13.4 3.9 79.1 0.0 100.0 3.3 8.5 0.8 87.4 0.0 100.0 11.8 8.6 0.4 79.2 0.0 100.0 30.1 7.8 4.6 57.6 0.0 100.0 0.4 8.0 1.0 90.6 0.0 100.0 30.3 8.9 4.4 56.5 0.0 100.0 26.2 27.4 3.6 42.8 0.0 100.0 12.5 7.2 3.5 76.6 0.1 100.0 9.1 11.6 5.7 73.6 0.0 100.0 7.2 15.9 7.5 69.4 0.0 100.0 5.5 14.9 8.1 71.5 0.0 100.0 37.7 7.9 13.9 40.4 0.1 100.0 4.8 10.8 4.5 79.8 0.0 100.0 22.9 18.6 28.4 30.1 0.0 100.0 18.6 20.1 8.8 52.4 0.1 100.0 23.5 19.2 7.2 50.1 0.0 100.0 37.3 14.8 11.7 36.1 0.1 100.0 4.2 14.0 3.9 77.9 0.0 100.0 12.0 28.1 7.3 52.6 0.1 100.0 23.4 22.8 4.6 49.2 0.0 100.0 20.7 28.7 6.3 44.3 0.0 100.0 17.9 35.6 5.2 41.3 0.0 100.0 16.6 29.6 5.8 47.9 0.0 100.0 2.4 16.9 5.7 75.0 0.0 100.0 10.4 39.2 4.2 46.2 0.0 100.0 66 Women’s participation in household decisionmaking, alone or jointly with others in the household, increases with age, suggesting that autonomy also increases with age (Table 3.11). Specifically, among women age 30 and over, only 4–6 percent in each five-year age group do not participate in any decisionmaking compared with 24 percent of women age 15–19 and 15 percent of women age 20–24. Participation in each of the four specified decisions increases more or less steadily with age. Table 3.10 Household decisionmaking Percent distribution of ever-married women by person who makes specific household decisions, according to residence, India, 1998–99 Household decision Respondent only Husband only Respondent with husband Others in household only Respondent with others in household Missing Total percent URBAN What items to cook Obtaining health care for herself Purchasing jewellery or other major household items Going and staying with her parents or siblings How the money she earns will be used1 71.2 3.5 4.7 10.2 10.5 0.0 100.0 35.0 34.2 17.7 7.0 6.2 0.0 100.0 13.3 28.5 35.7 11.1 11.4 0.0 100.0 18.0 36.3 28.4 9.0 8.2 0.0 100.0 57.0 14.2 24.0 1.9 2.8 0.1 100.0 RURAL What items to cook Obtaining health care for herself Purchasing jewellery or other major household items Going and staying with her parents or siblings How the money she earns will be used1 71.1 3.7 4.3 11.6 9.3 0.0 100.0 25.7 41.1 16.7 10.0 6.6 0.0 100.0 9.7 35.7 29.2 14.4 11.0 0.0 100.0 12.4 41.2 23.9 13.0 9.4 0.1 100.0 36.5 31.0 25.3 3.5 3.6 0.2 100.0 TOTAL What items to cook Obtaining health care for herself Purchasing jewellery or other major household items Going and staying with her parents or siblings How the money she earns will be used1 71.2 3.6 4.4 11.2 9.6 0.0 100.0 28.1 39.3 16.9 9.2 6.5 0.0 100.0 10.7 33.8 30.9 13.5 11.1 0.0 100.0 13.9 39.9 25.1 12.0 9.1 0.1 100.0 41.1 27.2 25.0 3.1 3.4 0.1 100.0 1For women earning cash 67 Table 3.11 Women’s autonomy Percentage of ever-married women involved in household decisionmaking, percentage with freedom of movement, and percentage with access to money by selected background characteristics, India, 1998–99 Percentage involved in decisionmaking on: Percentage who do not need permission to: Background characteristic Percentage not involved in any decision- making What to cook Own health care Purchasing jewellery, etc. Staying with her parents/ siblings Go to the market Visit friends/ relatives Per- centage with access to money Number of women Age 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Cash employment Working for cash Working but not for cash Not worked in past 12 months Standard of living index Low Medium High Total 24.4 66.6 38.6 39.8 37.4 13.8 10.2 45.5 8,182 15.4 77.3 45.0 46.1 43.1 22.0 16.6 54.1 16,389 9.4 84.9 49.7 51.5 46.2 28.8 21.1 58.8 17,745 6.1 89.4 53.6 54.8 49.3 34.0 25.1 61.1 15,094 4.8 91.9 56.5 57.7 52.7 37.9 29.8 64.3 13,089 3.7 92.6 59.3 59.3 53.6 43.0 35.1 65.9 10,521 3.8 91.6 60.1 60.3 56.1 45.4 37.5 67.6 8,179 7.1 86.3 58.9 60.4 54.6 46.9 35.0 73.6 23,370 10.3 84.7 49.0 49.9 45.7 26.1 20.6 54.6 65,829 9.6 86.1 48.6 49.6 45.1 27.0 21.6 52.8 51,871 9.1 85.2 52.5 54.0 49.2 32.6 24.3 61.3 17,270 11.3 81.6 53.5 54.3 49.7 35.9 25.6 66.6 7,328 8.1 83.3 61.2 62.0 57.6 46.2 35.0 81.0 12,719 9.6 85.2 50.8 52.4 48.0 31.8 24.6 59.4 72,903 10.7 82.8 50.5 48.1 43.4 23.4 19.0 56.0 11,190 5.8 88.0 63.0 65.6 61.7 44.6 35.6 68.5 2,263 2.4 93.6 74.6 72.5 64.6 46.2 25.6 74.0 1,427 9.8 84.3 54.7 55.9 47.0 50.9 39.8 74.0 331 4.6 89.7 57.0 58.7 52.7 56.3 38.7 72.2 676 4.9 89.1 52.8 61.7 58.4 33.3 31.0 60.6 285 4.2 91.2 64.6 65.4 71.9 41.5 33.8 72.3 44 9.1 86.2 49.7 51.8 47.4 31.3 23.7 56.0 16,301 7.6 87.6 49.8 52.9 48.8 30.7 26.2 50.7 7,750 10.2 84.4 51.3 52.5 48.4 34.7 26.6 62.4 29,383 9.3 84.7 53.3 53.3 48.2 29.6 22.7 61.0 34,904 5.7 89.8 57.0 59.6 54.6 41.4 33.2 64.7 23,391 10.2 85.1 46.5 47.1 43.1 26.4 21.4 50.6 11,519 10.9 83.1 50.3 50.8 46.3 28.5 21.2 59.3 54,271 8.5 87.7 48.5 49.9 45.5 28.5 23.0 52.1 29,033 10.2 84.3 50.8 51.6 47.2 30.0 22.8 58.1 41,289 9.3 82.9 58.4 59.6 54.5 40.1 30.2 75.1 17,845 9.4 85.1 51.6 52.6 48.1 31.6 24.4 59.6 89,199 Note: Total includes 11, 79, 862, 18, and 1,032 women with missing information on education, religion, caste/tribe, cash employment, and the standard of living index, respectively, who are not shown separately. 68 The proportion of women not involved in any decisionmaking varies little by education, caste/tribe, or standard of living. Participation in decisions about women’s own health care, about purchasing jewellery and other major household items, and about staying with parents or siblings, increases with education and with the household standard of living, but participation in decisions about what to cook is somewhat higher among less educated women than among more educated women, and this participation declines with the standard of living. Muslim women, closely followed by Hindu women, are less likely than women belonging to other religions to be involved in decisions about purchasing jewellery or other major household items and about staying with parents or siblings. About half of both Hindu and Muslim women do not participate in decisions about their own health care. Women working for money are more likely than women in other employment categories to participate in each of the four types of decisions and women who work without earning money are least likely to participate in all the decisions with the exception of the decision about what to cook. These results suggest that decisionmaking autonomy is not greater for all employed women; greater decisionmaking autonomy is associated with employment for women only if they are working for money. Table 3.11 also gives information on two other dimensions of women’s autonomy measured in NFHS-2, namely, women's freedom of movement and their access to money that they can spend as they wish. With regard to freedom of movement, respondents were asked whether they need permission to go to the market or to visit friends or relatives. Women's access to spending money was measured by asking respondents, ‘Are you allowed to have some money set aside that you can use as you wish?’ Freedom of movement is limited for the majority of ever-married women in India. Only 32 percent of women say that they do not need permission to go to the market, and only 24 percent say that they do not need permission to visit friends or relatives. Freedom of movement increases rapidly with age. For example, only 14 percent of women age 15–19 do not need permission to go to the market compared with 45 percent of women age 45–49. Urban women have much more freedom of movement than rural women and freedom of movement increases with education. Muslim women have much less freedom of movement than women of other religions, especially Buddhists/Neo-Buddhists and Jain women. As expected, women who earn money have much more freedom of movement than other women. What is most remarkable, however, is how limited the freedom of movement is for all categories of women. The proportion of women who do not need permission to go to the market is never greater than 56 percent for any category, and the proportion who do not need permission to go to visit friends and relatives is never greater than 40 percent. There is substantial variation in women's access to money by background characteristics. Overall, 60 percent of women say that they are allowed to have some money set aside that they can spend as they wish, but this proportion varies widely by age, residence, education, religion, caste/tribe, employment status, and household standard of living. Specifically, access to money increases with age, education, and the standard of living, and it is much greater for urban women than for rural women. Muslim and Hindu women are less likely to have access to money than women belonging to other religions. Women from scheduled castes and scheduled tribes are less likely than other women to have access to money. As expected, women who worked during the year and earned money are more likely than women in other employment categories to have access to money; however, women who did not work at all are more likely to have access to money (59 percent) than women who worked but did not earn money (51 percent). 69 Table 3.12 shows the interstate variation in all three indicators of women’s autonomy— women’s decisionmaking, freedom of movement, and access to money. In all states except Uttar Pradesh, Bihar, Rajasthan, Madhya Pradesh, Jammu and Kashmir, and Orissa, more than 90 percent of women are involved in at least one household decision. In each state women are most likely to be involved in decisions about what to cook (78–97 percent). There are only seven states in which more than 70 percent of women participate in decisions about their own health care (Himachal Pradesh, Meghalaya, Punjab, Mizoram, Kerala, Gujarat, and Arunachal Pradesh). By contrast, in Madhya Pradesh and Orissa only 37–39 percent of women participate in such decisions (Figure 3.3). More than 9 out of 10 women in Himachal Pradesh (93 percent) are involved in decisions about purchasing jewellery or other major household items compared with only 4 out of 10 women in Uttar Pradesh, Rajasthan, Bihar, and Madhya Pradesh. Participation in decisions about the purchase of jewellery or other major items is also high in Haryana, Punjab, Gujarat, and most of the northeastern states. In about half of the states, women are least likely to be involved in decisions about going to stay with their parents or siblings. A much higher proportion of women reported that they do not need permission to go to the market in Tamil Nadu (79 percent), Goa (67 percent), and Mizoram (64 percent) than in the rest of the states. Only 8 percent of women do not need permission to visit friends or relatives in Jammu and Kashmir compared with 59–60 percent of women in Mizoram and Goa. Overall, women’s freedom of movement is most restricted in Jammu and Kashmir, Uttar Pradesh, and Assam. and At least 80 percent of women have access to money that they can spend as they wish in Goa, Delhi, Meghalaya, and Himachal Pradesh, but only 28 percent have access to money in Nagaland and 35 percent in Assam. A few states perform relatively well on all of the autonomy indicators: Arunachal Pradesh, Goa, Gujarat, Himachal Pradesh, Meghalaya, Punjab, Sikkim, and Tamil Nadu. Most other states have a mixed record on women’s autonomy except for Madhya Pradesh, Rajasthan, and Uttar Pradesh, which have a consistently poor record on all of the indicators. 3.7 Women’s Educational Aspirations for Their Children The desire to invest in improving the quality of children, including investing in their education, is important for bringing about transition from uncontrolled to controlled fertility. In order to obtain information on this subject, NFHS-2 asked ever-married women for their opinion about how much education should be given to a girl or a boy. Women’s responses to these questions also provide an indication of the degree of son preference prevailing at the time of the survey. As shown in Table 3.13, 43 percent of women believe that a boy should be given as much education as he desires compared with only 31 percent who believe that a girl should be given as much education as she desires. Twenty-eight percent of women believe that an education above high school (higher secondary school, graduate and above, or professional degree) is appropriate for boys whereas 20 percent feel that it is appropriate for girls. Notably, only 1 percent of women feel that girls should not be given any education, and 16 percent feel that girls should be given an education but not beyond middle school. The corresponding proportions for boys are negligible. 70 Table 3.13 indicates that there are sharp urban-rural differences in women’s educational aspirations for girls and boys. Rural respondents have lower educational aspirations than urban respondents, particularly for girls. Rural respondents are also much less likely than urban respondents to say that girls and boys should be given as much education as they desire. It is notable, however, that even in rural areas more than two-thirds of women say that girls should be given at least a high school education or as much education as they desire. Table 3.12 Women’s autonomy by state Percentage of ever-married women involved in household decisionmaking, percentage with freedom of movement, and percentage with access to money by state, India, 1998–99 Percentage involved in decisionmaking on: Percentage who do not need permission to: State Percentage not involved in any decision- making What to cook Own health care Purchasing jewellery, etc. Staying with her parents/ siblings Go to the market Visit friends/ relatives Percentage with access to money India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 9.4 85.1 51.6 52.6 48.1 31.6 24.4 59.6 5.3 83.0 68.7 58.5 46.5 51.7 33.9 82.3 3.4 93.5 67.2 77.8 64.5 36.7 20.8 70.8 0.8 95.1 80.8 93.4 91.4 32.5 31.1 80.1 12.4 80.0 55.5 58.2 48.9 12.0 7.8 58.1 1.0 96.7 78.5 75.3 67.6 50.1 28.0 78.3 13.3 82.3 40.6 42.7 39.3 19.0 17.0 40.5 12.5 81.7 36.6 44.3 38.1 21.0 19.5 49.3 16.4 77.8 44.8 41.4 36.1 17.4 12.4 52.3 13.5 82.4 47.6 42.9 44.0 21.7 20.5 66.7 10.6 86.3 38.6 54.8 48.3 18.2 15.4 46.3 8.0 87.4 45.1 48.4 46.7 17.8 14.1 51.4 1.4 93.6 70.0 76.5 74.8 46.8 53.7 78.6 4.6 88.4 65.1 54.3 45.4 13.2 13.9 35.0 3.3 87.4 43.3 66.3 63.2 28.6 28.3 76.8 2.6 91.7 78.9 70.6 78.4 46.5 48.5 81.5 5.8 88.2 73.2 77.8 77.0 64.2 59.5 55.0 0.4 97.4 69.4 77.3 80.0 17.3 20.1 27.9 2.7 92.1 60.2 57.9 56.7 38.2 41.6 78.9 3.6 89.9 61.6 62.5 72.4 66.7 58.7 82.4 4.1 90.4 71.4 73.6 65.1 55.1 50.6 73.6 7.2 87.5 49.9 50.3 44.4 48.5 32.1 64.2 7.4 86.2 56.1 61.4 57.7 20.1 14.6 57.7 8.1 88.4 49.3 47.3 44.5 43.0 34.3 67.0 7.2 80.9 72.6 63.4 59.7 47.7 37.9 66.2 2.4 92.1 61.1 67.4 62.4 78.5 55.9 79.0 71 3.8 Domestic Violence: Attitudes and Experience In recent years, there has been increasing concern about violence against women in general, and domestic violence in particular, in both developed and developing countries (United Nations General Assembly, 1991). Not only has domestic violence against women been acknowledged worldwide as a violation of the basic human rights of women, but an increasing amount of research highlights the health burdens, intergenerational effects, and demographic consequences of such violence (Heise et al., 1998; 1994; Jejeebhoy, 1998; Ramasubban and Singh, 1998; Rao and Bloch, 1993). In patriarchal societies such as India, women are not only socialized into being silent about their experience of violence but traditional norms teach them to accept, tolerate, and even rationalize domestic violence (Jaisingh, 1995; Hegde, 1996; Prasad, 1999). Both tolerance of and experience of domestic violence are significant barriers to the empowerment of women, with consequences for women’s health, their health-seeking behaviour, their adoption of a small family norm, and the health of their children. In NFHS-2 an attempt was made to assess whether women view wife-beating as justified and to measure the prevalence of violence against women including, but not limited to, violence committed by a woman’s husband. Figure 3.3 Percentage of Women Participating in Decisions About Their Own Health Care by State 0 10 20 30 40 50 60 70 80 90 Himachal Pradesh Meghalaya Punjab Mizoram Kerala Gujarat Arunachal Pradesh Nagaland Delhi Haryana Assam Goa Tamil Nadu Sikkim Andhra Pradesh Jammu & Kashmir INDIA Maharashtra Karnataka Bihar West Bengal Uttar Pradesh Manipur Rajasthan Orissa Madhya Pradesh Percent NFHS-2, India, 1998–99 72 In order to assess women’s attitudes towards wife-beating, the survey asked whether respondents thought that a husband is justified in beating his wife for each of the following reasons: if he suspects her of being unfaithful; if her natal family does not give expected money, jewellery, or other items; if she shows disrespect for her in-laws; if she goes out without telling him; if she neglects the house or children; or if she does not cook food properly. These reasons, which range from reasons that involve suspicions about a wife's moral character to those that may be considered more trivial, such as not cooking properly, were chosen to provide variation in the perceived seriousness of violations of behavioural norms. Table 3.14 gives the percentages of ever-married women who agree with various reasons for wife-beating by background characteristics. Almost three out of five women (56 percent) in India accept at least one reason as a justification for wife-beating. Women are most likely to agree that neglecting the house or children (40 percent) justifies wife-beating and least likely to agree that wife-beating is justified if the woman’s natal family does not give expected money, jewellery, or other items (7 percent). Each of the remaining reasons is given as a justification of wife-beating by 25–37 percent of women. Table 3.14 indicates that there are no sharp differences by age or marital duration in women’s attitudes towards wife-beating, but it is notable that the youngest women (age 15–19) are consistently most likely to agree with each of the different reasons justifying wife-beating. There are large urban-rural differences in these attitudes. Not only do a higher proportion of rural Table 3.13 Perceived educational needs of girls and boys Percent distribution of ever-married women by their opinion on how much education should be given to girls and boys, according to residence, India, 1998–99 Educational level Urban Rural Total Education for girls No education Less than primary school Primary school Middle school High school Higher secondary school Graduate and above Professional degree As much as she desires Depends Don’t know Total percent 0.2 1.3 1.0 0.2 1.1 0.9 1.7 7.0 5.6 3.9 11.2 9.2 13.7 24.1 21.4 7.9 9.6 9.2 11.8 5.6 7.2 7.0 2.5 3.7 44.1 26.0 30.8 8.7 9.2 9.0 0.8 2.4 2.0 100.0 100.0 100.0 Education for boys No education Less than primary school Primary school Middle school High school Higher secondary school Graduate and above Professional degree As much as he desires Depends Don’t know Total percent 0.1 0.3 0.2 0.0 0.2 0.2 0.3 1.3 1.1 1.1 3.5 2.9 5.8 13.0 11.1 6.3 11.5 10.1 11.6 10.6 10.9 10.6 5.4 6.8 53.1 39.5 43.0 10.4 12.6 12.0 0.7 2.0 1.7 100.0 100.0 100.0 73 Table 3.14 Reasons given for justifying a husband beating his wife Percentage of ever-married women who agree with specific reasons for justifying a husband beating his wife by selected background characteristics, India, 1998–99 Percentage who agree with specific reasons Background characteristic Percentage who agree with at least one reason Husband suspects wife is unfaithful Natal family does not give money or other items Wife shows disrespect for in-laws Wife goes out without telling husband Wife neglects house or children Wife does not cook food properly Number of women Age 15–19 20–29 30–39 40–49 Marital duration (in years) < 5 5–9 10 or more Not currently married Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Household composition Nuclear household Non-nuclear household Cash employment Working for cash Working but not for cash Not worked in past 12 months Standard of living index Low Medium High Total 61.1 37.2 8.6 38.7 41.7 43.1 28.8 8,182 56.3 32.6 6.8 34.0 36.6 40.4 24.9 34,134 56.3 32.8 6.5 33.6 36.1 40.0 24.1 28,183 54.1 31.1 6.5 32.1 35.0 38.0 22.9 18,701 54.2 31.0 6.2 33.1 35.3 38.0 23.0 20,268 56.1 32.9 6.6 33.2 35.6 40.1 24.9 13,002 57.2 33.7 6.8 34.2 37.1 40.6 25.1 50,377 55.3 30.9 8.6 35.1 38.1 42.0 24.9 5,550 47.1 24.7 3.9 28.2 29.0 34.1 17.7 23,370 59.5 35.6 7.8 35.9 39.2 42.1 27.0 65,829 61.6 38.6 9.0 37.3 41.3 43.7 29.1 51,871 56.4 29.8 5.0 34.4 36.6 41.8 23.6 17,270 51.2 25.3 3.3 30.9 32.0 36.3 18.6 7,328 37.1 17.3 2.1 21.1 19.6 24.9 11.1 12,719 56.5 32.8 7.0 34.1 36.7 40.3 25.2 72,903 56.5 34.8 5.9 33.6 38.1 38.7 23.2 11,190 65.2 34.0 9.4 41.9 42.8 52.4 20.7 2,263 27.0 18.8 0.2 8.2 6.9 8.2 3.9 1,427 38.8 14.0 0.7 24.3 20.5 27.8 16.9 331 73.7 36.3 7.7 54.0 48.8 63.0 47.9 676 44.0 16.6 5.8 26.3 31.8 34.0 18.5 285 75.4 36.0 13.1 35.4 51.6 66.7 27.2 44 57.9 34.6 7.3 34.6 38.4 41.1 26.0 16,301 62.8 40.2 11.2 40.1 41.4 45.9 28.7 7,750 61.7 34.0 7.6 36.8 40.3 44.8 26.7 29,383 49.1 28.8 4.9 29.3 31.1 33.9 20.8 34,904 57.1 32.8 6.8 33.9 37.2 41.1 24.7 41,114 55.5 32.8 6.8 33.8 36.0 39.1 24.5 48,069 62.2 34.5 9.7 39.2 42.3 48.1 28.9 23,391 67.5 41.2 10.3 42.9 46.9 50.9 35.4 11,519 51.3 30.3 4.7 29.7 31.9 34.3 20.5 54,271 62.0 36.9 9.1 38.1 42.3 45.1 29.1 29,033 58.8 34.4 6.8 35.5 38.3 42.0 26.0 41,289 40.9 22.3 3.0 23.3 23.1 27.3 14.2 17,845 56.3 32.8 6.8 33.9 36.6 40.0 24.6 89,199 Note: Total includes 16 women from households with no usual residents, and 2, 11, 79, 862, 18, and 1,032 women with missing information on marital duration, education, religion, caste/tribe, cash employment, and the standard of living index, respectively, who are not shown separately. 74 women (60 percent) than urban women (47 percent) agree with at least one reason justifying wife-beating, but rural women are also more likely than urban women to agree with each specific reason. Agreement with at least one reason and with each of the different reasons for wife- beating declines sharply with education. Sixty-two percent of illiterate women agree with at least one reason justifying wife-beating compared with 51–56 percent of literate women who have not completed high school and 37 percent of women who have completed at least high school (Figure 3.4). Sikh and Jain women (27–39 percent) are less likely to agree with any reason justifying wife-beating than Hindu or Muslim women (both 57 percent), Christian women (65 percent), or Buddhist/Neo-Buddhist women (74 percent). Sikh and Jain women are also least likely to agree with each specific reason justifying wife-beating. One possible explanation for this difference may be that Sikh and Jain women in India are more likely than other women to be educated. Jain women are also more likely to be living in urban areas than are women in any other religious group (Tables 3.1 and 3.2). Table 3.14 also shows that women belonging to scheduled tribes, scheduled castes, or other backward classes (58–63 percent) are more tolerant of wife-beating than are women not belonging to a scheduled caste, scheduled tribe, or other backward class (49 percent). As expected, the proportion of women who agree that wife-beating is justified declines as the standard of living rises. The difference is greatest between women with a low or medium standard of living (59–62 percent) and women with a high standard of living (41 percent). However, the expectation that women who work, especially those who work for money, would be less likely than other women to justify wife-beating is not borne out for India (Figure 3.4). Women who have not worked in the past 12 months are less likely than women who have worked to justify wife-beating for each reason given in Table 3.14. This finding can be partly explained by the fact that the majority of working women in India are agricultural workers, who are likely to have relatively low educational attainment. Overall, with a few notable exceptions, the majority of women in almost all groups agree with at least one reason for wife-beating. This finding attests to the widespread socialization of women in norms that give husbands the right to use force to discipline wives who are perceived to be violating traditional gender norms. In order to assess the prevalence of domestic violence, NFHS-2 asked women if they had been beaten or mistreated physically since age 151. Women who reported being beaten or physically mistreated were asked who beat or physically mistreated them. Interviewers recorded all the persons mentioned by the respondent. As mentioned earlier, there is a culture of silence around the topic of domestic violence that makes the collection of data on this sensitive topic particularly difficult. Even women who want to speak about their experience with domestic violence may find it difficult because of feelings of shame or fear. This may be more true if violence occurred recently (for example, in the preceding 12 months) than in the more distant past. In addition, depending on the varied cultural meanings ascribed to different acts, there may be women who do not report their experience of domestic violence because they do not view it as violence or physical mistreatment. For these reasons, NFHS-2 results on the prevalence of domestic violence need to be interpreted with caution. 1The question does not limit women to reporting only domestic violence. Nonetheless, almost all women who report any violence report beatings or physical mistreatment only by husbands or relatives. 75 Table 3.15 presents results on the prevalence of beatings or physical mistreatment since age 15 by women's background characteristics. Prevalence is also shown according to the person(s) who beat or physically mistreated them—their husbands, their in-laws, or other persons. According to the reports of respondents, 21 percent of women in India have experienced violence since age 15, and 19 percent have been beaten or physically mistreated by their husbands. Two percent have been beaten or physically mistreated by in-laws and 3 percent by other persons. This implies that among women who report beatings, 9 out of 10 have been beaten by their husbands, 1 out of 7 have been beaten by other persons, and 1 out of 12 have been beaten by their in-laws. Women age 15–19 are less likely than older women to have been beaten, but because of their young age they have also had less time to be exposed to the risk of being beaten since age 15. Similarly, women who have been married for less than five years are less likely to have been beaten (14 percent) than women who have been married longer (21–23 percent) or who are currently not married (27 percent). Urban women (17 percent) are less likely than rural women (23 percent) to experience violence and illiterate women (26 percent) are three times as likely to experience violence as women who have at least completed high school (9 percent). Figure 3.4 Percentage Who Agree With At Least One Reason Justifying a Husband Beating His Wife 56 62 56 51 37 62 68 51 0 10 20 30 40 50 60 70 80 TOTAL EDUCATION Illiterate Literate, < Middle School Complete Middle School Complete High School Complete and Above CASH EMPLOYMENT Working for Cash Working but Not for Cash Not Worked in Past 12 Months Percent NFHS-2, India, 1998–99 76 The prevalence of domestic violence decreases substantially as the standard of living increases. Specifically, 29 percent of women with a low standard of living have experienced violence compared with 20 percent of women with a medium standard of living and 10 percent of women with a high standard of living. Christian, Hindu, Muslim, and Buddhist/Neo-Buddhist women are more likely to experience violence (all 21–22 percent) than are Sikh women (14 percent) or Jain women (7 percent). Women from nuclear households are more likely than women from non-nuclear households to experience domestic violence. This result is consistent with the findings of Visaria (1999) among women in rural Gujarat. The prevalence of violence also varies by the caste or tribe status of women. Sixteen percent of women not belonging to a Table 3.15 Women’s experience with beatings or physical mistreatment Percentage of ever-married women who have been beaten or physically mistreated by their husband, in-laws, or other persons since age 15 and percentage beaten or physically mistreated in the past 12 months, according to selected background characteristics, India, 1998–99 Percentage beaten or physically mistreated since age 15 by: Background characteristic Percentage beaten or physically mistreated since age 15 Husband In-laws Other person Percentage beaten or physically mistreated in the past 12 months Number of women Age 15–19 20–29 30–39 40–49 Marital duration (in years) < 5 5–9 10 or more Not currently married Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Household composition Nuclear household Non-nuclear household 15.4 12.8 1.3 3.1 11.5 8,182 21.1 18.8 1.8 3.2 12.4 34,134 23.0 20.9 1.9 3.0 11.3 28,183 20.3 18.3 1.7 2.9 7.6 18,701 14.4 11.5 1.0 3.9 9.6 20,268 21.2 19.0 1.5 3.1 12.8 13,002 22.9 21.1 1.9 2.6 11.5 50,377 27.4 24.2 4.2 4.1 6.8 5,550 16.8 14.3 1.5 3.6 7.7 23,370 22.5 20.4 1.9 2.9 12.2 65,829 25.5 23.6 2.1 2.8 14.1 51,871 19.2 16.7 1.7 3.5 8.8 17,270 15.2 12.1 1.4 4.0 7.0 7,328 8.6 5.9 0.7 3.2 3.6 12,719 21.2 19.1 1.7 3.0 11.1 72,903 21.2 19.1 2.1 2.8 11.4 11,190 21.8 16.1 2.0 6.8 10.3 2,263 13.9 11.6 1.1 4.3 7.1 1,427 6.8 5.5 0.0 1.4 2.8 331 20.8 20.0 2.5 3.0 10.0 676 16.8 13.5 0.7 4.5 11.4 285 26.1 15.1 1.2 10.4 11.2 44 27.4 25.2 2.2 3.3 15.4 16,301 23.0 20.8 1.8 3.0 13.0 7,750 23.0 20.7 1.7 3.6 11.7 29,383 15.7 13.6 1.6 2.6 7.8 34,904 24.5 22.2 1.9 3.4 12.7 41,114 18.1 15.9 1.7 2.8 9.5 48,069 Contd. 77 scheduled caste, scheduled tribe, or other backward class have been beaten compared with 23 percent of women belonging to scheduled tribes and other backward classes and 27 percent of women belonging to scheduled castes. Working women, most of whom are agricultural workers, are more likely than non-working women to experience violence. Women who worked for money in the 12 months preceding the survey are much more likely than women who did not work to have been beaten (29 percent compared with 17 percent). It is generally believed that not bearing children and not bearing a son are important reasons for wife-beating. However, in India women with no living children are somewhat less likely than women with living children to have experienced violence since they were 15 years old (16 percent compared with 20–22 percent). This may be due in part to the fact that childless women tend to be younger women, and younger women have a lower prevalence of domestic violence than do older women. There does not appear to be variation in the prevalence of domestic violence by whether or not women have a son. The proportions of women who have been beaten or physically mistreated by their husbands according to various background characteristics are similar to the proportions of all women who have experienced domestic violence. This is not surprising since, as already noted, 90 percent of women who report beatings are beaten by their husbands. The proportion of women who have been beaten or physically mistreated by their in-laws or by other persons is too small to allow a meaningful discussion of differentials by women’s background characteristics. Nonetheless, it is notable that women who are not currently married (divorced, separated, deserted, or widowed women) are more likely than currently married women to have been beaten Table 3.15 Women’s experience with beatings or physical mistreatment (contd.) Percentage of ever-married women who have been beaten or physically mistreated by their husband, in-laws, or other persons since age 15 and percentage beaten or physically mistreated in the past 12 months, according to selected background characteristics, India, 1998–99 Percentage beaten or physically mistreated since age 15 by: Background characteristic Percentage beaten or physically mistreated since age 15 Husband In-laws Other person Percentage beaten or physically mistreated in the past 12 months Number of women Cash employment Working for cash Working but not for cash Not worked in past 12 months Standard of living index Low Medium High Living children No living children Only daughters Only sons Both daughters and sons Total 29.0 26.5 2.3 3.8 14.5 23,391 24.0 22.2 2.3 2.5 12.1 11,519 16.9 14.8 1.4 2.9 9.3 54,271 29.2 27.0 2.2 3.3 16.6 29,033 20.1 18.0 1.8 3.1 10.1 41,289 10.1 7.8 1.0 2.7 4.0 17,845 16.3 12.9 1.8 4.1 9.6 10,754 20.3 17.9 1.6 3.5 11.1 12,447 20.6 18.2 1.6 3.3 11.4 17,706 22.4 20.6 1.8 2.6 11.2 48,293 21.0 18.8 1.8 3.1 11.0 89,199 Note: Total includes 16 women from households with no usual residents, and 2, 11, 79, 862, 18, and 1,032 women with missing information on marital duration, education, religion, caste/tribe, cash employment, and the standard of living index, respectively, who are not shown separately. 78 by their in-laws. Christian women and women with no religion are more likely than women in any other religious group to have been beaten by persons other than their husbands and in-laws. Table 3.15 also shows the percentage of women who experienced beatings or physical mistreatment in the 12 months preceding the survey. More than half of the women (52 percent) who experienced violence were beaten at least once during the 12 months preceding the survey. As mentioned earlier, largely due to the inherent tendency for underreporting of domestic violence, these results need to be interpreted with caution. Nevertheless, the NFHS-2 estimates set a lower bound on the proportion of women experiencing domestic violence in India: at least 1 in 5 ever-married women in India have experienced domestic violence since age 15, and at least 1 in 9 experienced domestic violence in the 12 months preceding the survey. These estimates of the prevalence of physical violence are almost identical to estimates provided by the IndiaSAFE study of family violence in India conducted at about the same time as NFHS-2. According to the IndiaSAFE study, one in five women report ever being hit, kicked, or beaten by husbands and 1 in 10 women report violent physical behaviours by husbands in the past 12 months (International Clinical Epidemiology Network, 2000). There is relatively little variation in the proportion of women beaten in the 12 months preceding the survey by background characteristics. Nonetheless, illiterate women (14 percent), scheduled-caste women (15 percent), women working for money (15 percent), and women who live in households with a low standard of living (17 percent) are more likely than other women to have been beaten in the past 12 months. By contrast women age 40–49, women who are not currently married, women who live in urban areas, women who have completed at least middle school, Sikh and Jain women, and women who live in households with a high standard of living are least likely to have been beaten in the 12 months preceding the survey. There are substantial statewise differences in the proportion of ever-married women who have been beaten or physically mistreated since age 15 (Table 3.16). Caution should be exercised in making cross-state comparisons, however, since there are likely to be differences across states in cultural norms about revealing the experience of violence to strangers and the extent to which women perceive the violence they may be experiencing as ‘beatings or physical mistreatment’ (the words used to describe violence in NFHS-2). Even if one of these factors varies across states, the prevalence of violence may be underestimated in some states more than in others. Forty percent of ever-married women in Tamil Nadu and at least one-quarter of ever-married women in Meghalaya, Orissa, Bihar, and Arunachal Pradesh have been physically mistreated since age 15. Himachal Pradesh is the only state where the proportion of ever-married women who have been physically mistreated since age 15 is less than 10 percent. In almost every state except the small northeastern states, at least three-quarters of women who have experienced physical violence were beaten by their husbands. In Meghalaya, by contrast, only 9 percent of women who experienced violence were physically mistreated by their husbands and about 90 percent were physically mistreated by other persons. Beatings by persons other than the husband or in-laws constitute a substantial proportion of beatings in most of the remaining northeastern states, as well as in the northern states of Delhi, Jammu and Kashmir, and Punjab. Table 3.16 also shows the percentage of women who reported beatings or physical mistreatment in the 12 months preceding the survey by state. The percentage of women beaten in the 12 months preceding the survey varies from less than 5 percent in Himachal Pradesh and Kerala to more than 15 percent in Bihar, Arunachal Pradesh, Tamil Nadu, and Nagaland. In 79 Nagaland, Bihar, and Sikkim, more than two-thirds of women who experienced violence since age 15 were beaten at least once during the 12 months preceding the survey. These results underscore the widespread prevalence of domestic violence in India, especially violence perpetrated by husbands against wives. The high level of acceptance of wife- beating also revealed by these data suggests that women may feel powerless against such violence and will tend to accept it without question. The experience of violence and the silent acceptance of violence by women undermines attempts to empower women and will continue to be a barrier to the achievement of demographic, health, and socioeconomic development goals. Table 3.16 Women’s experience with beatings or physical mistreatment by state Percentage of ever-married women who have been beaten or physically mistreated by their husband, in-laws, or other persons since age 15 and percentage beaten or physically mistreated in the past 12 months, according to state, India, 1998–99 Percentage beaten or physically mistreated since age 15 by: State Percentage beaten or physically mistreated since age 15 Husband In-laws Other person Percentage beaten or physically mistreated in the past 12 months India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 21.0 18.8 1.8 3.1 11.0 14.1 9.8 1.1 5.1 7.6 13.2 10.8 2.3 3.4 5.1 5.8 3.9 1.2 1.5 2.1 22.0 15.4 4.8 7.1 9.3 13.7 11.7 1.3 4.4 6.4 10.9 9.8 1.5 0.9 5.4 21.2 19.7 1.9 1.6 11.8 22.4 20.8 1.9 2.2 13.5 26.6 24.9 2.4 3.1 18.5 28.9 22.9 3.0 7.9 13.6 17.6 15.7 1.7 2.4 8.7 26.4 18.8 1.6 10.1 16.2 15.5 14.1 0.8 2.3 8.6 19.7 8.3 3.7 9.3 5.6 31.1 2.8 0.9 28.8 9.6 20.1 11.5 0.0 9.5 9.5 19.0 12.8 0.7 7.8 15.2 11.4 6.9 0.5 4.6 7.6 17.9 13.9 2.4 4.0 6.4 10.1 8.6 0.9 1.6 5.8 18.1 16.7 2.0 2.1 7.3 23.2 21.2 2.8 2.0 12.8 21.5 19.7 1.1 2.2 9.9 10.2 7.5 0.2 3.2 3.5 40.4 36.0 0.5 9.0 16.1 CHAPTER 4 FERTILITY AND FERTILITY PREFERENCES A major objective of NFHS-2 is to provide detailed information on fertility levels, differentials, and trends. This chapter presents a description of current and past fertility, cumulative fertility and family size, birth intervals, age at first cohabitation with husband, age at first and last birth, age at menopause, and durations of postpartum amenorrhoea, abstinence, and insusceptibility. Also discussed are fertility preferences, ideal and actual number of children, preference for sons or daughters, planning status of pregnancies, and wanted and actual total fertility rates. Most of the fertility measures presented in this chapter are based on the complete birth histories collected from ever-married women age 15–49 years. Several measures and procedures were used to obtain complete and accurate reporting of births, deaths, and the timing of these events. First, women were asked a series of questions aimed at recording all the live births that had occurred in their lifetime. Second, for each live birth, information was collected on the age, sex, and survival status of the child. For dead children, age at death was recorded. Interviewers were given extensive training in probing techniques designed to help respondents report this information accurately. For example, interviewers were instructed to check any documents (such as horoscopes, school certificates, or vaccination cards) that might provide additional information on dates of birth, and to probe for the reason for any birth interval of four or more years in order to prevent omission of births, especially of children who died soon after birth. Stillbirths, miscarriages, and induced abortions that occurred between live births were also recorded. Despite these measures to improve data quality, NFHS-2 is subject to the same types of errors that are inherent in all retrospective sample surveys—namely, the omission of some births (especially births of children who died at a very young age) and the difficulty of determining the date of birth of each child accurately. These difficulties can bias estimates of fertility levels and trends. 4.1 Age at First Cohabitation The number of children that a woman will have in her lifetime is strongly influenced by the age at which she marries. In many parts of India, however, formal marriage is not always immediately followed by cohabitation. Rather, the husband and the wife begin to cohabit only after the gauna ceremony. Even in states where gauna is not practised, a marriage may not be consummated immediately if it occurs at a very young age. In such instances, there is a difference between age at marriage and age at consummation of marriage. Age at consummation of marriage is, of course, what is relevant for fertility. NFHS-2 measured age at first cohabitation as a proxy for age at consummation of marriage. Accordingly, Table 4.1 presents information on the median age at first cohabitation to supplement the information on the median age at first marriage presented in Chapter 3. In Table 4.1, the median age at first cohabitation for a group of women is defined as the age by which half of the entire group began to cohabit, rather than the age by which half of all ever-cohabiting women in the group began to cohabit. 82 Table 4.1 shows that, in India, the median age at first cohabitation with husband is 17.4 years for women age 20–49. For age groups, the lowest median age at first cohabitation is 16.8 for women age 40–49, and the highest is 18.3 for women age 20–24, suggesting a modest increase of 1.5 years in the median age at first cohabitation over a period of approximately 23 years. The value of 18.3 for the youngest age group is still rather low, however, suggesting that the considerable decline in fertility that has occurred in India has resulted mostly from family limitation within marriage rather than from an increase in age at first cohabitation. Table 4.1 also shows that the median age at first cohabitation is two years higher for urban women than for rural women. Over time, the median age at first cohabitation has risen in both urban and rural areas, but the rise has been greater in urban areas. Differentials in the median age at first cohabitation by education are larger than differentials by residence. For women age 25–49, the median age at first cohabitation ranges from 16.0 for illiterate women to Table 4.1 Age at first cohabitation with husband Median age at first cohabitation with husband among women age 20–49 years by current age and selected background characteristics, India, 1998–99 Current age Background characteristic 20–24 25–29 30–34 35–39 40–49 20–49 25–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total NC 19.3 18.7 18.3 18.1 18.9 18.6 17.6 16.9 16.6 16.5 16.3 16.8 16.6 16.3 16.1 16.1 16.1 16.0 16.1 16.0 18.1 17.6 17.3 17.2 17.3 17.5 17.4 19.3 18.9 18.7 18.9 18.6 18.9 18.8 NC 21.8 21.4 21.3 21.1 NC 21.5 18.2 17.4 17.0 16.8 16.7 17.2 16.9 18.2 17.3 16.8 16.7 16.6 17.1 16.9 NC 21.2 20.2 20.4 20.2 NC 20.5 NC 20.2 20.2 19.9 20.2 NC 20.1 NC 20.6 19.1 18.9 18.3 19.6 18.9 19.8 17.5 17.0 16.8 16.7 17.6 16.9 19.1 17.2 17.1 17.2 17.5 18.0 17.2 (19.2) (18.7) (18.1) (19.9) (18.3) 18.8 18.7 17.8 16.7 16.4 16.3 16.0 16.6 16.3 17.1 16.8 16.5 16.7 16.5 16.7 16.6 18.2 17.4 16.9 16.8 16.7 17.2 16.9 18.9 18.3 17.8 17.5 17.3 18.1 17.7 16.5 16.2 16.1 16.1 15.9 16.2 16.1 18.3 17.5 17.0 16.7 16.6 17.2 16.9 NC 20.1 19.4 18.9 18.4 19.6 19.1 18.3 17.5 17.1 16.9 16.8 17.4 17.0 Note: Total includes women with missing information on education, religion, caste/tribe, and the standard of living index, who are not shown separately. NC: Not calculated because less than 50 percent of women have started living with their husband by age 20 ( ) Based on 25–49 unweighted cases 83 21.5 for women with at least a high school education. Increases over time in the median age have been small in all educational groups, but the increase among illiterate women has been almost negligible. By religion, the median age at first cohabitation for women age 25–49 ranges from 16.9 for Hindus, Muslims, and Buddhists to 20.1 for Sikhs and 20.5 for Christians. By caste/tribe, for women age 20–49, the median age ranges from 16.6–16.7 for scheduled-caste and scheduled-tribe women to 18.1 for women who belong neither to a scheduled caste or tribe nor to an other backward class. The median age of first cohabitation increases steadily with the standard of living, from 16.2 for women living in households with a low standard of living to 19.6 for women living in households with a high standard of living. 4.2 Fertility Levels NFHS-2 provides estimates of age-specific fertility rates (ASFR), total fertility rates (TFR), and crude birth rates (CBR) for the three-year period preceding the survey, which in NFHS-2 corresponds roughly to the period 1996–98. This three-year period was chosen as a compromise between the need to obtain recent information (suggesting the use of a short period closer to the survey date) and the need to reduce sampling variation and minimize problems related to displacement of births from recent years to earlier years (suggesting the use of a longer period). The ASFR for any specific age group is calculated by dividing the number of births to women in the age group during the period 1–36 months preceding the survey by the number of woman- years lived by women in the age group during the same three-year time period. The TFR is a summary measure, based on the ASFRs, that gives the number of children a woman would bear during her reproductive years if she were to experience the ASFRs prevailing at the time of the survey. Mathematically, the TFR is five times the sum of all the ASFRs for the five-year age groups. The CBR is defined as the annual number of births per 1,000 population. Based on estimates for the three-year period before NFHS-2, the CBR was 24.8 births per 1,000 population, and the TFR was 2.9 births per woman, as shown in Table 4.2. Fertility is higher in rural areas than in urban areas. The CBR is 20.9 in urban areas and 26.2 in rural areas, and the TFR is 2.27 in urban areas and 3.07 in rural areas. Table 4.2 and Figure 4.1 show that the TFR is lower in urban areas than in rural areas because ASFRs are lower at all ages in urban areas than in rural areas. Sixty-seven percent of urban total fertility and 61 percent of rural total fertility are concentrated in the prime childbearing ages 20–29. There is also a moderate amount of early childbearing. Fertility at age 15–19 accounts for 15 percent of total fertility in urban areas, 20 percent in rural areas, and 19 percent overall. Fertility at ages 35 and older accounts for only 5 percent of total fertility in urban areas, 8 percent in rural areas, and 7 percent overall. Based on estimates for the three-year period preceding NFHS-1 and NFHS-2, the CBR fell from 28.7 to 24.8 between the two surveys, a decline of 14 percent in approximately six and one-half years. Over the same period, the TFR fell by 0.54 child from 3.39 to 2.85, a decline of 16 percent. Fertility fell mainly at ages 20 and above and very little at age 15–19 (Figure 4.2). Although fertility fell at ages 40–44 and 45–49, fertility at these ages was already very low in NFHS-1, so that fertility declines above age 40 had a negligible impact on the changes in the CBR and TFR that occurred between the two surveys. 84 Figure 4.1 Age-Specific Fertility Rates by Residence 0 50 100 150 200 250 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Age B ir th s p e r 1 ,0 0 0 W o m e n Urban Rural Note: Rates are for the three years preceding the survey (1996–98) NFHS-2, India, 1998–99 Table 4.2 Current fertility Age-specific and total fertility rates and crude birth rates from NFHS-1, NFHS-2, and the SRS by residence, India NFHS-1 (1990–92) NFHS-2 (1996–98) SRS (1997) Age Total Urban Rural Total Urban Rural Total 15–19 20–24 25–29 30–34 35–39 40–44 45–49 TFR 15–44 TFR 15–49 CBR 0.116 0.231 0.170 0.097 0.044 0.015 0.005 3.36 3.39 28.7 0.068 0.121 0.107 0.179 0.222 0.210 0.127 0.150 0.143 0.057 0.075 0.069 0.018 0.033 0.028 0.003 0.011 0.008 0.001 0.004 0.003 2.27 3.06 2.84 2.27 3.07 2.85 20.9 26.2 24.8 0.032 0.061 0.054 0.178 0.242 0.226 0.152 0.200 0.188 0.071 0.122 0.109 0.029 0.063 0.055 0.012 0.030 0.026 0.003 0.009 0.008 2.36 3.59 3.29 2.38 3.63 3.32 21.5 28.9 27.2 Note: Rates from NFHS-1 and NFHS-2 are for the period 1–36 months preceding the survey. Rates for the age group 45–49 might be slightly biased due to truncation. Rates from the SRS are for one calendar year. Age-specific and total fertility rates are expressed per woman. TFR: Total fertility rate ; CBR: Crude birth rate, expressed per 1,000 population Source for SRS data: Office of the Registrar General, 1999a 85 The pattern of fertility change by age is consistent with the findings that there has been only a small increase in the age at cohabitation, only a weak effort to promote spacing between children, and the predominant use of permanent methods of contraception (discussed elsewhere in this report). The NFHS-2 fertility estimates can be compared with estimates from the Sample Registration System (SRS), which is maintained by the Office of the Registrar General, India. Since the NFHS-2 rates refer to 1996–98, it is appropriate to compare them with the SRS estimates for 1997, which are also shown in Table 4.2. The NFHS-2 estimate of the CBR, at 24.8, is lower than the SRS estimate of the CBR, at 27.2. Similarly, the NFHS-2 estimate of the TFR, at 2.85, is lower than the SRS estimate of the TFR, at 3.32. Differences between the fertility estimates from NFHS-2 and the SRS are considerably smaller in urban areas than in rural areas. The larger discrepancy in rural areas may be caused by more age misreporting in rural areas, which tends to result in the displacement of births further into the past in the birth histories. Retrospective surveys such as NFHS-1 and NFHS-2 are subject to such displacement, whereas the SRS, in which births are recorded during the year in which they occur, is not. In the analysis of the earlier NFHS-1 survey, Narasimhan et al. (1997) compared NFHS-1 and SRS estimates of fertility and concluded that both are probably underestimates. Nonetheless, since the SRS estimates are not subject to displacement, they are likely to be closer to the true level of fertility than the NFHS-1 estimates. This argument is probably equally valid for NFHS-2 estimates of fertility as compared with the corresponding SRS estimates. Figure 4.2 Age-Specific Fertility Rates NFHS-1, NFHS-2, and SRS 0 50 100 150 200 250 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Age B ir th s p e r 1 ,0 0 0 W o m e n NFHS-1 NFHS-2 SRS Note: NFHS rates are for the three years preceding the NFHS-1 (1990–92) and NFHS-2 (1996–98) surveys. Rates from the SRS are for 1997. India 86 Table 4.3 and Figure 4.3 compare fertility levels and trends in each state. There is a wide diversity of fertility levels among the states. Total fertility rates range from 1.8 in Goa to 4.6 in Meghalaya. Almost two-thirds of the states (16 out of 25) have TFRs below the all-India mean of 2.85 children per woman. This skewed pattern occurs because the mean is strongly affected by the relatively high fertility of a handful of populous states in the northern half the country—Uttar Pradesh (with a TFR of 4.0), Rajasthan (3.8), Bihar (3.5), and Madhya Pradesh (3.3). Fertility is uniformly low in the West and South Regions (where most states are close to the replacement level of about 2.1 children per woman). Fertility is higher than average in the two states in the Central Region, but the picture is mixed in the other regions. In the North Region, the TFR is close to the replacement level in Himachal Pradesh (2.1) and Punjab (2.2), and it is also low in Delhi (2.4), but it is quite high in Rajasthan (3.8). In the East Region, the TFR ranges from 2.3 in West Bengal to 3.5 in Bihar. Two of the states in the Northeastern Region (Meghalaya and Nagaland) have high levels of fertility, but the remaining states in the region have much lower fertility. As already mentioned, these estimates for states must be viewed with some caution, because they are affected by displacement of births from the first three years before the survey to earlier years and tend to be lower than comparable estimates from the Sample Registration System, which does not suffer from displacement. Table 4.3 also shows the estimated change in the TFR between NFHS-1 and NFHS-2 for each state. As already noted, the TFR for the whole country is estimated from the two surveys to have declined by about half a child per woman between the two surveys (slightly higher than the SRS decline of 0.4 child during the same period). The estimated change varies greatly by state, however, ranging from a decline of 1.7 children per woman in Arunachal Pradesh to an increase of 0.8 child per woman in Meghalaya. Excluding the northeastern states, the change in the TFR ranges from a decline of 1.1 children per woman in Haryana to an increase of 0.2 child per woman in Rajasthan. The TFR declined by more than the all-India average in every state in the North Region except Rajasthan, in both states in the Central Region, and in West Bengal, Arunachal Pradesh, Assam, and Karnataka. States in which the TFR declined by less than the all- India average are Bihar, Orissa, and all the states in the West and South Regions except Karnataka. The TFR increased between the two surveys in Rajasthan, Manipur, Meghalaya, Mizoram, and Nagaland. These estimates of change in the TFR between the two surveys must be interpreted with great caution, mainly because of possible differences in the extent of age misreporting between the two surveys. These differences in age misreporting, to the extent that they exist, translate into differences in the degree of displacement of births from the three years immediately preceding the survey (the period to which the TFR estimates pertain) to earlier years. If this differential displacement is large, it can seriously bias the estimated trend in the TFR. Because the two surveys are only six and one-half years apart, the estimation errors due to differential displacement can be as large or larger than the actual change in the TFR. Differential displacement of births (and in some cases differential omission of births) is probably the principal explanation of the estimated fertility increases (which in all likelihood are not real) in Rajasthan, Manipur, Meghalaya, Mizoram, and Nagaland. An initial study of the accuracy of the NFHS-2 fertility estimates suggests that in Uttar Pradesh differential displacement largely accounts for the more rapid TFR decline estimated from the two surveys than from the Sample Registration System (Retherford et al., 2000). Further research addressing the question of accuracy of the NFHS fertility estimates is currently underway for other states. 87 Table 4.3 Fertility by state NFHS-2 age-specific and total fertility rates (TFR) and crude birth rate for the three-year period preceding the survey, and NFHS-1 TFR, according to residence and state, India NFHS-2 age-specific fertility rates NFHS-2 TFR NFHS-1 TFR State 15–19 20–24 25–29 30–34 35–39 40–44 45–49 15–49 15–49 NFHS-2 crude birth rate URBAN India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 0.068 0.179 0.127 0.057 0.018 0.003 0.001 2.27 2.70 20.9 0.035 0.185 0.176 0.058 0.018 0.003 0.000 2.37 3.00 20.9 0.031 0.186 0.151 0.063 0.011 0.000 (0.006) 2.24 3.14 18.1 0.025 0.132 0.116 0.052 0.019 0.003 (0.000) 1.74 2.03 15.7 0.028 0.082 0.145 0.063 0.010 0.003 (0.000) 1.66 U 16.4 0.015 0.145 0.143 0.047 0.007 0.000 (0.000) 1.79 2.48 15.4 0.092 0.219 0.157 0.076 0.036 0.013 0.004 2.98 2.77 25.3 0.087 0.195 0.131 0.075 0.030 0.004 0.000 2.61 3.27 22.9 0.057 0.195 0.173 0.095 0.040 0.012 0.004 2.88 3.58 23.5 0.072 0.200 0.160 0.088 0.030 0.000 (0.000) 2.75 3.25 22.3 0.057 0.166 0.123 0.059 0.023 0.009 (0.000) 2.19 2.53 20.1 0.049 0.133 0.102 0.047 0.007 0.000 0.000 1.69 2.14 15.1 (0.045) (0.158) * * * * * NC NC NC 0.040 0.110 0.084 0.052 0.014 0.000 (0.000) 1.50 2.53 15.8 0.033 0.114 0.154 0.099 0.049 (0.014) (0.008) 2.36 NC 21.4 (0.030) (0.182) (0.138) * (0.063) * * NC NC NC 0.038 0.143 0.144 0.091 0.046 (0.013) * 2.37 NC 22.4 (0.034) (0.187) * * * * * NC NC NC (0.053) (0.158) * * * * * NC U NC 0.022 0.103 0.093 0.078 0.033 (0.008) (0.000) 1.69 1.80 16.2 0.062 0.205 0.139 0.048 0.011 0.001 0.000 2.33 2.65 21.4 0.094 0.185 0.111 0.045 0.014 0.000 0.000 2.24 2.54 21.6 0.099 0.189 0.093 0.026 0.007 0.000 0.000 2.07 2.35 21.4 0.069 0.160 0.091 0.042 0.010 0.005 0.000 1.89 2.38 18.5 0.013 0.128 0.097 0.042 0.022 0.000 0.000 1.51 1.78 14.8 0.071 0.172 0.122 0.042 0.011 0.004 0.000 2.11 2.36 21.3 88 Table 4.3 Fertility by state (contd.) NFHS-2 age-specific and total fertility rates (TFR) and crude birth rate for the three-year period preceding the survey, and NFHS-1 TFR, according to residence and state, India NFHS-2 age-specific fertility rates NFHS-2 TFR NFHS-1 TFR State 15–19 20–24 25–29 30–34 35–39 40–44 45–49 15–49 15–49 NFHS-2 crude birth rate RURAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 0.121 0.222 0.150 0.075 0.033 0.011 0.004 3.07 3.67 26.2 (0.046) (0.251) * * * * * NC NC NC 0.116 0.260 0.150 0.062 0.018 0.013 0.008 3.13 4.32 25.0 0.030 0.210 0.132 0.044 0.014 0.006 0.000 2.18 3.07 20.4 0.048 0.192 0.192 0.112 0.039 0.013 0.004 3.00 U 24.6 0.050 0.197 0.165 0.053 0.015 0.005 0.000 2.42 3.09 20.9 0.139 0.280 0.190 0.113 0.053 0.027 0.011 4.06 3.87 31.4 0.162 0.240 0.170 0.083 0.034 0.015 0.009 3.56 4.11 27.9 0.137 0.272 0.217 0.137 0.071 0.020 0.006 4.31 5.19 33.0 0.119 0.226 0.182 0.115 0.053 0.020 0.003 3.59 4.14 28.8 0.081 0.175 0.140 0.073 0.023 0.006 0.001 2.50 3.00 22.4 0.125 0.185 0.112 0.047 0.019 0.004 0.006 2.49 3.25 22.7 0.075 0.160 0.138 0.072 0.045 (0.016) * 2.68 4.38 23.2 0.094 0.152 0.119 0.072 0.033 0.008 0.000 2.39 3.68 22.3 0.044 0.139 0.181 0.189 0.080 0.032 (0.017) 3.41 3.03 27.8 0.103 0.222 0.261 0.208 0.123 (0.094) * 5.16 3.80 38.4 0.064 0.248 0.198 0.139 0.040 (0.005) * 3.47 (2.30) 28.4 0.060 0.237 0.212 0.172 0.091 (0.025) (0.014) 4.06 3.60 31.7 0.069 0.166 0.145 0.083 0.064 0.036 (0.012) 2.87 U 24.7 0.017 0.083 0.141 0.099 0.021 0.005 0.000 1.83 1.99 16.9 0.105 0.250 0.156 0.056 0.023 0.009 0.006 3.03 3.17 26.4 0.156 0.254 0.101 0.026 0.010 0.000 0.000 2.74 3.12 23.8 0.144 0.186 0.085 0.031 0.014 0.003 0.000 2.32 2.67 21.4 0.135 0.180 0.089 0.033 0.009 0.002 0.002 2.25 3.08 21.4 0.041 0.179 0.137 0.039 0.014 0.004 0.000 2.07 2.09 19.7 0.090 0.199 0.120 0.026 0.009 0.002 0.000 2.23 2.54 21.5 89 Table 4.3 Fertility by state (contd.) NFHS-2 age-specific and total fertility rates (TFR) and crude birth rate for the three-year period preceding the survey, and NFHS-1 TFR, according to residence and state, India NFHS-2 age-specific fertility rates NFHS-2 TFR NFHS-1 TFR State 15–19 20–24 25–29 30–34 35–39 40–44 45–49 15–49 15–49 NFHS-2 crude birth rate TOTAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 0.107 0.210 0.143 0.069 0.028 0.008 0.003 2.85 3.39 24.8 0.036 0.191 0.174 0.059 0.017 0.003 0.000 2.40 3.02 21.3 0.092 0.240 0.150 0.062 0.015 0.009 0.007 2.88 3.99 23.1 0.029 0.203 0.130 0.045 0.015 0.006 0.000 2.14 2.97 19.9 0.044 0.171 0.181 0.100 0.033 0.010 0.003 2.71 U 23.1 0.040 0.178 0.158 0.051 0.012 0.003 0.000 2.21 2.92 19.1 0.126 0.264 0.181 0.103 0.048 0.023 0.009 3.78 3.63 29.9 0.142 0.228 0.159 0.081 0.033 0.012 0.006 3.31 3.90 26.7 0.120 0.256 0.208 0.127 0.064 0.018 0.006 3.99 4.82 31.1 0.113 0.223 0.180 0.112 0.050 0.018 0.002 3.49 4.00 28.1 0.079 0.174 0.138 0.071 0.023 0.006 0.001 2.46 2.92 22.1 0.107 0.173 0.110 0.047 0.015 0.003 0.004 2.29 2.92 20.8 0.066 0.160 0.129 0.068 0.043 (0.013) * 2.52 4.25 22.6 0.089 0.149 0.116 0.070 0.031 0.007 0.000 2.31 3.53 21.8 0.042 0.132 0.173 0.153 0.068 0.026 0.014 3.04 2.76 25.8 0.086 0.211 0.232 0.184 0.105 0.080 (0.014) 4.57 3.73 35.7 0.054 0.188 0.167 0.110 0.048 0.009 (0.000) 2.89 2.30 25.7 0.056 0.224 0.203 0.162 0.076 0.023 (0.012) 3.77 3.26 30.4 0.065 0.171 0.141 0.078 0.053 0.032 (0.011) 2.75 U 24.5 0.021 0.089 0.122 0.090 0.026 0.007 0.000 1.77 1.90 16.6 0.087 0.230 0.148 0.052 0.018 0.005 0.003 2.72 2.99 24.3 0.129 0.223 0.106 0.034 0.012 0.000 0.000 2.52 2.86 23.0 0.132 0.186 0.087 0.029 0.012 0.003 0.000 2.25 2.59 21.4 0.112 0.172 0.090 0.037 0.009 0.003 0.001 2.13 2.85 20.4 0.039 0.166 0.128 0.040 0.016 0.003 0.000 1.96 2.00 18.8 0.083 0.189 0.121 0.032 0.010 0.003 0.000 2.19 2.48 21.4 NC: Not calculated because there are too few women U: Not available ( ) Rate based on 125–249 woman-years of exposure *Rate not shown; based on fewer than 125 woman-years of exposure 90 4.3 Fertility Differentials and Trends Table 4.4 and Figure 4.4 show how the TFR, the percentage currently pregnant, and the mean number of children ever born to women age 40–49 vary by selected background characteristics. In NFHS-2, the TFR for India is 1.5 children higher for illiterate women than for women with at least a high school education. The TFR is 0.8 child higher for Muslims than for Hindus, and both of these groups have much higher fertility than any other religious group. By caste/tribe, the TFR is 0.5 child higher for scheduled-caste women, 0.4 child higher for scheduled-tribe women, and 0.2 child higher for OBC women than for women who do not belong to any of these groups. The TFR is 1.3 children higher for women living in households with a low standard of living and 0.8 child higher for women living in households with a medium standard of living than for women living in households with a high standard of living. Fertility transitions in other countries have shown that fertility differentials typically diverge early in the transition and reconverge (though rarely completely) towards the end of the transition as fertility approaches the replacement level. India as a whole still has fairly large fertility differentials. Figure 4.3 Total Fertility Rate by State 0 1 2 3 4 5 Meghalaya Uttar Pradesh Rajasthan Nagaland Bihar Madhya Pradesh Manipur Mizoram Haryana INDIA Sikkim Gujarat Jammu & Kashmir Maharashtra Arunachal Pradesh Orissa Delhi Assam West Bengal Andhra Pradesh Punjab Tamil Nadu Himachal Pradesh Karnataka Kerala Goa Total Fertility Rate Note: Rates are for the three years preceding the survey (1996–98) NFHS-2, India, 1998–99 91 Overall, 6 percent of women age 15–49 report that they are currently pregnant. Differentials in the percentage of women who are currently pregnant do not always parallel differentials in the TFR. In Table 4.4, for example, Sikhs have a slightly lower TFR than Christians but a higher percentage currently pregnant. Such apparent inconsistencies can occur because the TFR is not affected by age structure, whereas the percentage currently pregnant is affected by age structure, which can vary from one group to the next. In most cases in the table, however, the direction of differentials in the percentage currently pregnant parallels the direction of differentials in the TFR. Table 4.4 Fertility by background characteristics Total fertility rate for the three years preceding the survey, percentage of all women age 15–49 currently pregnant, and mean number of children ever born to ever-married women age 40–49 by selected background characteristics, India, 1998–99 Background characteristic Total fertility rate1 Percentage currently pregnant2 Mean number of children ever born to ever- married women age 40–49 years Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 2.27 4.4 3.78 3.07 6.1 4.73 3.47 6.2 4.98 2.64 5.4 4.06 2.26 5.1 3.41 1.99 4.7 2.66 2.78 5.5 4.34 3.59 6.9 5.72 2.44 4.3 3.47 2.26 4.8 3.59 1.90 * 3.32 2.13 3.7 4.05 2.33 5.0 4.33 3.91 * (5.62) 3.15 6.1 4.85 3.06 6.8 4.74 2.83 5.6 4.43 2.66 5.1 4.20 3.37 6.4 4.81 2.85 5.8 4.67 2.10 4.1 3.61 2.85 5.6 4.45 Note: Total includes women with missing information on education, religion, caste/tribe, and the standard of living index, who are not shown separately. ( ) Based on 25–49 unweighted cases *Percentage not shown; based on fewer than 25 unweighted cases 1Rate for women age 15–49 years 2For this calculation, it is assumed that women who are never married, widowed, divorced, separated, or deserted are not currently pregnant. 92 The last column of Table 4.4 shows the mean number of children ever born to ever- married women age 40–49 at the time of the survey. The average number of children ever born for these women, who are at the end of their childbearing years, is 4.5. The substantial decline in fertility in India over time is evident from the difference of 1.6 children between the average number of children for women who are currently in their forties and the number of children women would have in their lifetime if they were subject to the current age-specific fertility rates (the last column and first column of Table 4.4). In almost every case, the pattern of differentials in the mean number of children ever born parallels the pattern of differentials in the TFR. The differentials by religion are again a partial exception. Exceptions can occur because the mean number of children ever born at age 40–49 reflects fertility in the past, whereas the TFR only reflects fertility in the three years preceding the survey. The preceding section already discussed fertility trends based on estimates from NFHS-1 and NFHS-2 for the three-year period preceding each survey. Table 4.5 shows fertility trends for five-year time periods preceding NFHS-2, estimated solely from NFHS-2 birth histories. It is not possible to show TFRs because of progressively greater age truncation as one goes back in time. In NFHS-2, birth histories were collected only for women age 15–49. This means, for example, that for the period 5–9 years preceding the survey it is not possible to compute an ASFR for age 45–49. Similarly, for the period 10–14 years preceding the survey, it is not possible to compute ASFRs for the oldest two age groups, and for the period 15–19 years preceding the survey, it is Figure 4.4 Total Fertility Rate by Selected Background Characteristics 2.3 3.1 3.5 2.6 2.0 3.4 2.9 2.1 2.3 0 1 2 3 4 RESIDENCE Urban Rural EDUCATION Illiterate Literate, < Middle School Complete Middle School Complete High School Complete and Above STANDARD OF LIVING INDEX Low Medium High Total Fertility Rate Note: Rates are for the three years preceding the survey (1996–98) NFHS-2, India, 1998–99 93 not possible to compute ASFRs for the oldest three age groups. Thus Table 4.5 shows only the truncated trends in ASFRs. Results are shown separately for urban and rural areas as well as for the entire country. These results show very substantial fertility declines in every age group over a 15-year period in both urban and rural areas. In many cases, age-specific fertility declined by half or more. The proportionate decline tends to be somewhat greater at the older reproductive ages. For the periods 0–4 years and 5–9 years before the survey, it is possible to calculate truncated TFRs (more appropriately called cumulative fertility rates, or CFRs) for the age range 15–39, based on the ASFRs shown in Table 4.5. This is done by summing ASFRs for the age groups 15–19 through 35–39 and multiplying the sum by five. For India as a whole, CFR(15–39) declined from 3.8 to 2.9 over the five-year period, a decline of 0.9 child. The decline was 0.6 for urban areas and 1.0 for rural areas, indicating that fertility fell slightly more rapidly in rural areas than in urban areas during the 10 years before the survey. This is to be expected because the practice of family limitation tends to start in urban areas and spread to rural areas. It should be noted that these estimated fertility declines may exaggerate to some degree the magnitude of the decline between these two five-year periods, because there is considerable age misreporting in India which could result in displacement of births from the first five-year period into the second five-year period before the survey (Narasimhan et al., 1997). Table 4.5 Fertility trends Age-specific fertility rates for five-year periods preceding the survey by residence, India, 1998–99 Years preceding survey Age 0–4 5–9 10–14 15–19 URBAN 15–19 20–24 25–29 30–34 35–39 40–44 45–49 0.072 0.101 0.125 0.138 0.186 0.221 0.253 0.268 0.132 0.162 0.183 0.210 0.059 0.071 0.101 [0.132] 0.019 0.031 [0.047] U 0.004 [0.008] U U [0.001] U U U RURAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 0.132 0.182 0.198 0.190 0.231 0.282 0.295 0.298 0.157 0.197 0.222 0.242 0.079 0.111 0.136 [0.175] 0.036 0.057 [0.075] U 0.012 [0.025] U U [0.004] U U U TOTAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 0.116 0.160 0.177 0.174 0.218 0.264 0.282 0.289 0.150 0.186 0.210 0.232 0.073 0.099 0.125 [0.162] 0.031 0.049 [0.066] U 0.010 [0.020] U U [0.003] U U U Note: Age-specific fertility rates are expressed per woman. U: Not available [ ] Truncated, censored 94 Another way of looking at fertility is to calculate fertility rates by the number of years since the first cohabitation with the husband. These rates are measures of marital fertility, i.e., fertility within marriage. Table 4.6 shows fertility rates by duration since first cohabitation for ever-married women for four five-year periods preceding the survey1. Fertility has declined at all durations, but more so at the longer durations. The limited decline of fertility at duration 0–4 years since first cohabitation is typical of populations in which contraception is initiated only after the first birth or later, as is the case in India (see Table 5.8). The large overall declines in fertility rates by duration since first cohabitation confirm the earlier observation that fertility within marriage has declined substantially in India. It is also evident from Table 4.6 that marital fertility is lower in urban areas than in rural areas at most durations for most time periods. 1Because NFHS-2 collected information only on a woman’s age at the time of first cohabitation and not the year and month when she first began cohabiting with her husband, the exact number of months since first cohabitation cannot be calculated. For this reason, the first year since cohabitation contains only six months, on average, and the first five years since cohabitation contain only 4.5 years, on average. Table 4.6 Fertility by marital duration Fertility rates for ever-married women by duration since first cohabitation with husband (in years) and residence for five-year periods preceding the survey, India, 1998–99 Years preceding surveyDuration since first cohabitation (in years) 0–4 5–9 10–14 15–19 URBAN < 5 5–9 10–14 15–19 20–24 25–29 0.307 0.324 0.340 0.335 0.161 0.202 0.233 0.271 0.073 0.100 0.135 0.183 0.031 0.047 0.082 0.123 0.010 0.026 0.057 * 0.004 0.007 * U RURAL < 5 5–9 10–14 15–19 20–24 25–29 0.302 0.331 0.332 0.310 0.220 0.275 0.285 0.298 0.126 0.166 0.197 0.227 0.065 0.097 0.127 0.172 0.030 0.053 0.081 (0.118) 0.010 0.029 (0.086) U TOTAL < 5 5–9 10–14 15–19 20–24 25–29 0.303 0.329 0.335 0.317 0.205 0.256 0.271 0.290 0.112 0.148 0.180 0.216 0.056 0.083 0.115 0.162 0.025 0.046 0.076 0.115 0.009 0.025 0.078 U Note: Duration-specific fertility rates are per woman. The duration since first cohabitation with husband is defined as the difference between the woman’s age at the specific time period and her age when she began living with her husband. U: Not available ( ) Based on 125–249 woman-years of exposure *Rate not shown; based on fewer than 125 woman-years of exposure 95 4.4 Pregnancy Outcomes Table 4.7 shows the percent distribution of all pregnancies of ever-married women age 15–49 by their outcome, for all India and states. The possible outcomes considered are spontaneous abortion, induced abortion, stillbirth, and live birth. Information on pregnancies that did not result in a live birth is collected on the birth history. For each interval between births, as well as the interval before the first birth and after the last birth, the respondent was asked whether she had any stillbirths, spontaneous abortions, or induced abortions (and, if yes, how many she had). This information is summed to obtain the total number of non-live births of each type she has had in her lifetime. In most countries, the reporting of non-live births (particularly induced Table 4.7 Outcome of pregnancy by state Percent distribution of all pregnancies of ever-married women by their outcome, according to state, India, 1998–99 State Spontaneous abortion Induced abortion Stillbirth Live birth Total percent India–Urban India–Rural India–Total North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 5.2 3.4 1.5 89.9 100.0 4.2 1.1 2.1 92.6 100.0 4.4 1.7 2.0 91.9 100.0 5.8 4.7 1.3 88.2 100.0 5.7 1.4 3.0 90.0 100.0 4.5 1.6 2.6 91.3 100.0 5.1 2.6 1.8 90.5 100.0 4.1 3.0 2.9 90.0 100.0 5.0 0.9 2.1 91.9 100.0 3.8 1.0 1.8 93.4 100.0 4.5 1.4 1.8 92.4 100.0 3.2 0.3 2.1 94.4 100.0 5.4 1.6 2.1 90.9 100.0 4.0 2.2 1.8 91.9 100.0 2.6 0.7 3.1 93.5 100.0 6.1 3.3 3.2 87.4 100.0 6.6 6.3 1.2 85.8 100.0 5.2 0.7 3.3 90.9 100.0 5.3 0.6 2.3 91.8 100.0 5.8 2.3 2.3 89.5 100.0 2.1 0.9 2.9 94.0 100.0 7.1 3.9 1.1 87.9 100.0 4.9 2.1 1.4 91.6 100.0 3.8 1.9 1.5 92.8 100.0 4.0 0.8 2.3 92.9 100.0 4.0 0.9 2.3 92.8 100.0 5.7 1.9 1.2 91.2 100.0 6.2 5.2 2.5 86.2 100.0 96 abortions) is inadequate, so it is likely that there is some underreporting of these events in NFHS-2. In India, 92 percent of pregnancies resulted in a live birth, 4 percent in a spontaneous abortion, 2 percent in an induced abortion, and 2 percent in a stillbirth. The proportion resulting in a spontaneous abortion is one percentage point higher in urban areas than in rural areas, the proportion resulting in an induced abortion is two percentage points higher in urban areas than in rural areas, and the proportion resulting in a stillbirth is one percentage point lower in urban areas than in rural areas. The reported rate of induced abortion in urban areas, though higher than in rural areas, is quite low. By state, the proportion of pregnancies resulting in a spontaneous abortion ranges from 2 percent in Sikkim to 7 percent in Goa and Manipur, and the proportion of pregnancies resulting in an induced abortion ranges from 0.3 percent in Bihar to 6 percent in Manipur. In addition to Manipur, Delhi and Tamil Nadu stand out as having a relatively high proportion (5 percent) of pregnancies resulting in an induced abortion. The proportion of pregnancies resulting in a stillbirth ranges from 1.1 percent in Goa to 3.3 percent in Meghalaya. 4.5 Children Ever Born and Living The number of children a woman has ever borne is a cohort measure of fertility. Because it reflects fertility in the past, it provides a somewhat different picture of fertility levels, trends, and differentials than do period measures of fertility such as the CBR and the TFR. Table 4.8 shows the percent distribution of all women and currently married women by the number of children ever born (CEB). The table shows these distributions by the age of the woman at the time of the survey and also shows the mean number of children ever born and living children. Among women age 15–49 in India, the mean number of children ever born is 2.4 for all women irrespective of marital status, and 3.0 for currently married women. The mean number of children ever born increases steadily with age, reaching a high of 4.6 children for all women age 45–49 and 4.8 children for currently married women age 45–49. The table also shows that early childbearing is fairly common in India. Sixteen percent of all women age 15–19 and nearly half of currently married women age 15–19 have already had a child. For women age 45–49, the number of children ever born is of particular interest because these women have virtually completed their childbearing. For all women in this age group, the modal number of children is four. Eighteen percent of these women have reached the end of childbearing with four children ever born. Among currently married women age 45–49, the modal number of children is also four; 18 percent of these women have also reached the end of childbearing with four children ever born. More than one-third of currently married women in this age group (35 percent) have had six or more live births, and half have had five or more live births. Only two percent of currently married women age 45–49 have never given birth. This suggests that primary infertility (which is the proportion of couples who are unable to have any children) is very low in India. Table 4.8 Children ever born and living Percent distribution of all women and of currently married women by number of children ever born (CEB) and mean number of children ever born and living, according to age, India, 1998–99 Children ever born Age 0 1 2 3 4 5 6 7 8 9 10+ Total percent Number of women Mean number of CEB Mean number of living children ALL WOMEN 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 83.6 11.9 3.8 0.6 0.1 0.0 0.0 0.0 0.0 0.0 35.8 23.4 23.7 12.0 3.8 0.9 0.2 0.0 0.0 0.0 12.2 12.4 26.6 23.9 14.5 6.6 2.7 0.7 0.2 0.0 6.1 7.3 20.9 23.4 17.6 11.4 7.1 3.7 1.5 0.7 4.5 5.3 16.9 22.4 18.3 12.6 8.8 5.5 2.9 1.6 3.8 4.4 13.4 18.6 18.1 14.9 10.2 6.9 4.4 2.6 3.8 4.0 10.7 16.7 17.7 14.0 12.3 8.1 5.4 3.6 28.7 11.5 16.8 15.4 10.9 6.9 4.4 2.6 1.4 0.8 0.0 100.0 23,735 0.21 0.19 0.0 100.0 21,006 1.28 1.16 0.0 100.0 18,954 2.52 2.27 0.3 100.0 15,481 3.36 2.96 1.3 100.0 13,287 3.84 3.33 2.7 100.0 10,625 4.31 3.62 3.7 100.0 8,249 4.62 3.79 0.7 100.0 111,336 2.40 2.08 CURRENTLY MARRIED WOMEN 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 52.2 34.8 11.1 1.7 0.2 0.0 0.0 0.0 0.0 0.0 17.3 29.9 30.5 15.7 5.0 1.2 0.3 0.0 0.0 0.0 5.8 12.7 28.5 25.9 15.8 7.2 3.0 0.8 0.3 0.1 3.0 6.8 21.4 24.4 18.3 12.1 7.4 4.0 1.6 0.7 2.2 4.5 17.1 22.9 19.2 13.0 9.2 5.8 3.2 1.7 2.1 3.9 12.9 18.7 18.8 15.4 10.6 7.3 4.6 2.8 2.3 3.2 10.3 16.6 18.2 14.6 13.0 8.5 5.6 3.9 10.7 14.1 21.1 19.4 13.7 8.6 5.5 3.2 1.8 1.0 0.0 100.0 8,014 0.63 0.57 0.0 100.0 15,930 1.66 1.50 0.0 100.0 17,055 2.73 2.45 0.3 100.0 14,286 3.51 3.10 1.3 100.0 12,052 3.99 3.47 2.9 100.0 9,363 4.46 3.75 4.0 100.0 6,948 4.79 3.94 0.9 100.0 83,649 3.00 2.62 98 For all women age 15–49, the average number of dead children per woman is 0.32. For currently married women it is 0.38, implying that 13 percent of children ever born to currently married women have died. The proportion of children ever born who have died increases with women’s age. For currently married women, the proportion of children ever born who have died increases from 10 percent for women age 20–24 to 18 percent for women age 45–49. 4.6 Birth Order The distribution of births by birth order is yet another way to view fertility. Table 4.9 shows the distribution of births during the three-year period before the survey by birth order for selected background characteristics. Overall, as expected, the proportion of births at each order is larger than the proportion at the next higher order. Twenty-nine percent of all births are first-order births, 26 percent are second-order births, 18 percent are third-order births, and 28 percent are births of order four or higher. Over 70 percent of births to mothers age 15–19 are of order one; by contrast, over 70 percent of births to mothers age 30–39 are of order four or higher. The proportion of births that are of order four or higher is 19 percent in urban areas and 30 percent in rural areas. The proportion of births of order four or higher is relatively large for births to illiterate women, Muslim women, and scheduled-tribe women. By work status, 34–36 percent of births to women who work are of order four or higher compared with 24 percent of births to women who did not work in the past 12 months. This finding may be partly explained by the fact that working women come disproportionately from rural areas, where fertility is relatively high. For women living in households with a low standard of living, the proportion of births of order four or higher is 37 percent, compared with only 12 percent for women living in households with a high standard of living. Table 4.10 shows how the percent distribution of births by birth order varies among the various states of India. The proportion of births that are of order four or higher ranges from 7 percent in Kerala to 47 percent in Meghalaya. In all of the seven states with a total fertility rate of 3.0 or higher, at least 30 percent of recent births are of order four or higher. In the two states with the lowest level of fertility (Goa and Kerala), only 7–8 percent of births are of order four or higher. 4.7 Birth Intervals A birth interval, defined as the length of time between two successive live births, indicates the pace of childbearing. Short birth intervals may adversely affect a mother’s health and her children’s chances of survival. Past research has shown that children born too close to a previous birth are at increased risk of dying, especially if the interval between the births is less than 24 months (Pandey et al., 1998; Govindasamy et al., 1993). Table 4.11 shows the percent distribution of births during the five years preceding the survey by birth interval according to selected demographic and socioeconomic background characteristics. In India, 13 percent of births occur within 18 months of a previous birth and 28 percent occur within 24 months. Thirty-eight percent of births occur after an interval of three years or more. 99 Table 4.9 Birth order Percent distribution of births during the three years preceding the survey by birth order, according to selected background characteristics, India, 1998–99 Birth order Background characteristic 1 2 3 4+ Total percent Number of births Mother’s current age 15–19 20–29 30–39 40–49 Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Mother’s work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living index Low Medium High Total 73.3 22.9 3.5 0.4 100.0 4,209 27.5 30.8 21.8 20.0 100.0 22,147 4.5 10.3 13.3 71.9 100.0 5,658 0.3 2.2 4.6 92.9 100.0 483 35.4 29.6 15.8 19.2 100.0 7,215 27.1 24.7 18.2 29.9 100.0 25,282 21.5 21.4 18.9 38.2 100.0 19,132 31.9 29.0 19.5 19.6 100.0 5,832 41.7 33.7 15.3 9.3 100.0 2,948 48.5 35.1 11.9 4.6 100.0 4,580 29.7 26.3 17.9 26.2 100.0 25,730 24.2 22.3 16.3 37.3 100.0 5,140 35.2 29.9 16.1 18.8 100.0 755 32.8 30.8 20.6 15.8 100.0 451 36.2 41.1 16.5 6.2 100.0 76 34.4 26.2 22.1 17.3 100.0 199 22.9 24.4 25.0 27.7 100.0 87 17.4 19.7 15.9 47.0 100.0 24 26.6 24.1 17.9 31.5 100.0 6,505 24.1 23.5 18.5 34.0 100.0 3,091 29.7 26.4 17.7 26.2 100.0 10,431 31.2 27.0 17.2 24.5 100.0 12,086 22.0 22.5 19.9 35.6 100.0 4,203 23.4 23.4 19.4 33.8 100.0 4,808 25.3 23.1 16.1 35.5 100.0 1,102 31.7 27.1 17.0 24.3 100.0 22,373 22.9 21.9 18.4 36.7 100.0 11,844 30.0 26.5 17.8 25.7 100.0 15,131 39.7 33.1 15.5 11.7 100.0 5,125 29.0 25.8 17.7 27.5 100.0 32,496 Note: Total includes 5, 33, 383, 9, and 397 births with missing information on mother’s education, religion, caste/tribe, mother’s work status, and the standard of living index, respectively, which are not shown separately. 100 The median closed birth interval in India is 31 months. The median closed birth interval for women age 15–19 is 24 months, which is substantially less than the median interval of 36 months for women age 30–39. The relatively short birth interval for women age 15–19 at the time of the survey may result partly from a selection effect: Only women who have had two or more births are included in the table, and women age 15–19 with more than one birth are likely to be more fecund than average. Given the finding that the median birth interval increases with mother’s age, it is surprising that it does not also increase substantially with the order of the previous birth. Perhaps this is due to the absence of the selection effect just noted in the case of age. There may also be another type of selection effect operating: Mothers of higher-order births may be more fecund, on average, than mothers of lower-order births. Table 4.10 Birth order by state Percent distribution of births during the three years preceding the survey by birth order, according to state, India, 1998–99 Birth order State 1 2 3 4+ Total percent India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 29.0 25.8 17.7 27.5 100.0 31.5 29.1 17.8 21.6 100.0 29.0 29.3 16.8 24.9 100.0 35.8 30.9 19.3 14.0 100.0 25.8 23.9 18.1 32.2 100.0 31.7 28.6 21.2 18.5 100.0 24.7 22.5 18.0 34.8 100.0 25.1 22.2 17.7 35.0 100.0 21.7 20.3 18.1 39.9 100.0 23.2 22.1 17.4 37.3 100.0 29.0 28.1 18.4 24.5 100.0 34.5 29.0 16.6 19.9 100.0 27.2 26.6 16.5 29.7 100.0 31.0 25.2 16.3 27.5 100.0 28.6 24.3 16.7 30.4 100.0 19.8 20.2 13.5 46.5 100.0 29.1 25.0 23.2 22.7 100.0 20.8 19.6 16.4 43.2 100.0 37.2 20.9 14.7 27.3 100.0 45.9 29.3 17.0 7.8 100.0 31.2 27.9 20.1 20.8 100.0 33.0 27.9 21.1 18.0 100.0 36.4 32.2 16.5 15.0 100.0 36.1 30.3 14.9 18.8 100.0 40.0 39.0 14.3 6.7 100.0 42.9 34.0 14.0 9.1 100.0 101 Table 4.11 Birth interval Percent distribution of births during the five years preceding the survey by interval since previous birth, according to selected demographic and background characteristics, India, 1998–99 Months since previous birth Demographic/ background characteristic < 12 12–17 18–23 24–35 36–47 48+ Total percent Median open birth interval1 Median closed birth interval2 Number of births Mother’s current age 15–19 20–29 30–39 40–49 Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Order of previous birth 1 2 3 4+ Sex of previous birth Male Female 4.0 21.2 23.5 36.7 12.2 2.5 100.0 10.0 24.3 1,193 2.6 11.0 17.2 36.2 19.5 13.5 100.0 20.3 29.3 26,305 2.0 7.1 11.9 30.2 20.8 28.0 100.0 29.5 35.5 11,183 3.3 7.1 11.9 24.8 17.5 35.5 100.0 38.4 37.3 1,215 2.2 11.0 16.2 31.8 17.7 21.0 100.0 25.1 30.9 8,017 2.5 9.8 15.6 34.8 20.0 17.2 100.0 22.3 30.8 31,878 2.6 9.9 15.0 34.7 20.2 17.6 100.0 22.4 31.0 26,674 2.1 10.3 17.6 35.2 18.7 16.1 100.0 24.0 29.6 6,779 2.2 10.1 19.0 33.8 17.3 17.6 100.0 22.6 29.6 2,728 1.9 10.9 15.0 29.5 18.4 24.3 100.0 24.3 32.5 3,706 2.4 9.7 15.5 34.2 20.0 18.1 100.0 23.0 31.1 31,277 2.8 11.3 16.3 34.3 17.6 17.6 100.0 21.9 29.7 6,777 1.7 9.5 18.0 33.3 18.8 18.8 100.0 22.6 30.9 824 3.1 14.5 17.9 32.2 17.5 14.8 100.0 26.7 28.2 529 2.7 12.0 12.2 25.9 22.7 24.6 100.0 19.8 33.3 75 0.6 10.8 18.0 39.4 15.1 16.2 100.0 21.8 29.6 230 1.7 11.9 11.7 41.7 19.4 13.6 100.0 23.9 30.1 115 6.8 6.3 17.1 35.1 12.7 22.0 100.0 24.6 27.6 31 2.6 9.8 14.9 35.2 20.5 17.1 100.0 21.4 30.7 8,106 2.8 10.5 16.0 35.7 19.4 15.6 100.0 22.5 29.9 4,133 2.2 9.6 15.9 34.3 19.8 18.2 100.0 23.2 31.1 12,686 2.5 10.5 16.1 33.3 18.7 18.9 100.0 23.9 30.7 14,384 2.6 9.5 15.1 35.0 20.0 17.8 100.0 22.4 31.0 16,073 2.4 10.2 16.3 34.7 19.6 16.7 100.0 22.8 30.4 18,212 2.2 11.3 15.8 29.7 18.4 22.6 100.0 24.9 31.7 5,149 2.5 11.0 16.4 32.8 18.6 18.7 100.0 21.4 30.7 14,325 2.1 9.4 16.2 35.2 19.9 17.2 100.0 22.3 30.8 9,713 1.8 9.4 15.7 35.3 20.3 17.4 100.0 24.4 31.0 6,102 3.2 9.8 14.3 34.6 20.2 17.9 100.0 25.1 30.8 9,756 2.4 9.9 15.6 34.1 20.0 18.0 100.0 24.1 31.1 19,526 2.5 10.3 15.8 34.4 19.2 17.9 100.0 21.8 30.6 20,369 Contd… 102 The median birth interval is shorter if the previous child was a girl than if it was a boy, but the difference is only 0.5 months. This pattern may result from the shorter duration of breastfeeding for girls, which is indicative of son preference (see Table 7.12). Birth intervals are much shorter if the previous child died (25 months) than if the previous child survived (32 months). In part, this reflects the shortening of postpartum amenorrhoea that occurs when the preceding child dies in infancy and breastfeeding stops prematurely. Women are also less likely to use temporary methods of contraception to postpone fertility if the previous child died and they want to replace the dead child. Very few women in India use temporary methods of contraception, however, so that the main effect is probably through prematurely terminated breastfeeding. Birth intervals are virtually the same in urban areas and rural areas. Birth intervals are somewhat longer for illiterate mothers and mothers with at least a high school education than for mothers with intermediate levels of education. The median interval between births is slightly shorter for Muslim and Sikh mothers than for Hindu and Christian mothers. Birth intervals show little variation by caste/tribe or the standard of living. The median open birth interval (the interval between the most recent birth and the time of the survey) is 23 months. The median open birth interval rises dramatically with age from only 10 months for teenage mothers to 38 months for mothers in their forties. For women in all other subgroups (except for Sikh women), the median open birth interval varies between only 20 months and 25 months. Table 4.12 shows how birth intervals vary among the states of India. The median closed birth interval ranges from 27.5 months in Nagaland to 38.1 months in Kerala. States with a median closed birth interval of 33 months or longer are Kerala, Goa, Delhi, and West Bengal. In Kerala, 36 percent of births have an interval since the preceding birth of at least 48 months (compared with a national average of 18 percent of births). Table 4.11 Birth interval (contd.) Percent distribution of births during the five years preceding the survey by interval since previous birth, according to selected demographic and background characteristics, India, 1998–99 Months since previous birth Demographic/ background characteristic < 12 12–17 18–23 24–35 36–47 48+ Total percent Median open birth interval1 Median closed birth interval2 Number of births Survival of previous birth Living Dead Total 1.9 8.8 15.5 34.8 20.3 18.8 100.0 23.0 31.6 35,278 6.9 20.1 17.7 30.0 13.9 11.4 100.0 21.8 25.2 4,618 2.5 10.1 15.7 34.2 19.6 17.9 100.0 22.9 30.8 39,896 Note: Table includes only second- and higher-order births except for the median open birth interval, which is based on all births. The interbirth interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. Total includes 10, 38, 587, and 461 births with missing information on mother's education, religion, caste/tribe, and the standard of living index, respectively, which are not shown separately. 1Median number of months between the date of interview and the most recent birth 2Median number of months between the most recent birth and the previous birth 103 4.8 Age at First and Last Birth The ages at which women start and stop childbearing are important demographic determinants of fertility. A higher median age at first birth and a lower median age at last birth are indicators of lower fertility. Table 4.13 shows the median age at first birth for various age groups by selected background characteristics. The median age at first birth for any group of women is defined in this table as the age by which half of all women in the group have had a first birth, rather than the Table 4.12 Birth interval by state Percent distribution of births during the five years preceding the survey by interval since previous birth, according to state, India, 1998–99 Months since previous birth State < 12 12–17 18–23 24–35 36–47 48+ Total percent Median open birth interval1 Median closed birth interval2 India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 2.5 10.1 15.7 34.2 19.6 17.9 100.0 22.9 30.8 3.2 12.0 13.1 26.4 20.4 24.9 100.0 24.6 33.6 2.1 11.0 16.3 34.4 20.1 16.1 100.0 22.6 30.0 1.3 13.4 17.3 36.0 16.6 15.3 100.0 24.4 29.4 1.8 8.6 14.5 33.8 20.4 21.0 100.0 23.2 32.5 3.6 14.7 17.4 32.0 16.6 15.5 100.0 26.1 28.0 3.1 11.0 15.9 36.3 19.3 14.4 100.0 21.5 29.5 3.2 9.4 15.8 36.1 19.9 15.5 100.0 22.2 30.2 3.2 11.1 14.8 33.7 20.6 16.6 100.0 20.8 30.4 2.4 8.2 14.6 34.4 21.2 19.2 100.0 22.2 32.3 1.9 9.1 13.8 31.6 21.6 21.9 100.0 24.0 32.9 1.6 8.0 13.4 31.9 20.5 24.5 100.0 25.1 33.6 1.5 13.0 15.8 35.2 20.3 14.2 100.0 28.8 29.9 2.1 10.3 15.7 34.9 19.2 17.7 100.0 26.3 30.6 0.1 11.0 15.7 35.5 18.7 18.8 100.0 22.2 31.8 1.2 12.8 17.9 36.9 16.3 14.9 100.0 19.6 28.5 0.5 11.3 21.1 35.5 15.8 15.7 100.0 22.5 28.4 0.7 11.4 20.0 40.5 17.3 10.1 100.0 19.8 27.5 2.0 11.7 15.9 30.4 17.3 22.6 100.0 22.7 32.6 0.6 8.7 13.7 30.8 16.5 29.6 100.0 25.8 34.8 1.8 12.3 17.8 35.9 16.6 15.6 100.0 20.7 29.0 1.7 9.0 19.9 36.0 17.8 15.5 100.0 23.2 29.0 2.4 10.1 14.8 35.0 19.1 18.5 100.0 24.2 31.1 1.1 9.9 19.3 35.5 18.4 15.8 100.0 24.8 29.7 1.2 8.4 11.7 24.4 18.1 36.2 100.0 25.3 38.1 1.7 11.3 17.3 33.0 16.5 20.3 100.0 25.4 30.5 Note: Table includes only second- and higher-order births except for the median open birth interval, which is based on all births. The interbirth interval for multiple births is the number of months since the preceding pregnancy that ended in a live birth. 1Median number of months between the date of interview and the most recent birth 2Median number of months between the most recent birth and the previous birth 104 age by which half of all mothers in the group have had a first birth. If the median age at first birth calculated for an age group lies above the lower limit of that age group, it is not valid because some younger women in the age group who have not yet had a first birth will not have reached the median age by the time of the survey. In such cases, the estimate of the median is not shown. As shown in the last row of the table, the median age at first birth in India as a whole appears to have increased slightly in recent years, from 19.3 years for women age 30–34 to 19.6 years for women age 25–29. Among all women age 25–49, the median age at first birth is 1.6 years higher in urban areas than in rural areas. The median increases especially sharply between the 30–34 and 25–29 age cohorts in urban areas and between the 25–29 and 20–24 age cohorts in rural areas. The median age at first birth is almost five years higher for women who have completed at least high school than for illiterate women. The median is 0.5 year higher for Table 4.13 Median age at first birth Median age at first birth among women age 20–49 years by current age and selected background characteristics, India, 1998–99 Current age Background characteristic 20–24 25–29 30–34 35–39 40–44 45–49 20–49 25–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total NC 21.3 20.6 20.3 20.3 20.3 NC 20.6 19.7 19.0 18.8 19.0 18.9 19.2 19.1 19.0 18.5 18.2 18.3 18.6 18.6 18.9 18.5 18.5 19.8 19.4 19.2 19.4 19.4 19.7 19.5 19.4 NC 20.8 20.7 20.8 20.5 20.5 NC 20.7 NC 23.5 23.1 23.2 23.2 23.2 NC 23.3 NC 19.5 19.3 19.3 19.2 19.5 19.6 19.4 19.8 19.2 18.8 18.9 18.8 18.8 19.1 18.9 NC 23.1 22.1 21.9 22.6 21.3 NC 22.2 NC 21.3 21.4 21.5 21.7 22.5 NC 21.5 NC 22.5 20.7 21.0 (21.1) 20.9 NC 21.2 NC 19.4 18.4 18.7 19.6 18.5 19.5 19.1 NC 19.5 18.6 19.9 19.3 20.0 19.9 19.5 NC (19.6) (19.2) (20.7) * * NC 19.7 19.8 18.9 18.5 18.6 18.6 18.8 18.9 18.7 19.4 18.8 18.6 18.9 18.9 19.1 18.9 18.8 NC 19.5 19.3 19.3 19.1 19.4 19.5 19.3 NC 20.1 19.9 19.9 19.8 20.0 NC 20.0 18.7 18.3 18.3 18.7 18.7 18.8 18.5 18.5 NC 19.6 19.2 19.1 19.0 19.4 19.5 19.3 NC 22.0 21.3 21.1 20.7 20.5 NC 21.2 NC 19.6 19.3 19.4 19.3 19.5 19.6 19.4 Note: Total includes women with missing information on education, religion, caste/tribe, and the standard of living index, who are not shown separately. NC: Not calculated because less than 50 percent of women had their first birth by age 20 ( ) Based on 25–49 unweighted cases *Median not shown; based on fewer than 25 unweighted cases 105 Hindus than for Muslims. Christians, Sikhs, and Jains all have a median age at first birth that is considerably higher than that of either Hindus or Muslims. By caste/tribe, women from other backward classes have a median age at first birth that is about half a year higher than that of scheduled-caste women or scheduled-tribe women, and women belonging to none of these caste/tribe groups have a median that is more than one year higher than that of schedule-caste women or scheduled-tribe women. The median age at first birth increases steadily with standard of living and is almost three years higher for women living in households with a high standard of living than for women living in households with a low standard of living. For older women the age at last childbirth is an indicator of cessation of childbearing. Table 4.14 presents the distribution of ever-married women age 40–49 by age at last birth, as well as the median age at last birth. Although a few of these women may have another birth later on, the very low fertility rates for women in this age group suggest that childbearing is virtually complete by these ages. More than half of women (54 percent) had their last birth by age 30, and 80 percent by age 35. The median age at last birth in India for women age 40–49 is 29.3 years (28.7 for women age 40–44 and 30.2 for women age 45–49). Table 4.15 shows how median age at first and last birth (for women with at least one birth) varies among states. The median age at first birth ranges from 17.7 in Andhra Pradesh to 22.8 in Goa. States with a median age at first birth of 21 years or higher are Goa, Mizoram, Sikkim, Punjab, Delhi, Manipur, Nagaland, Arunachal Pradesh, and Kerala. The median age at last birth ranges from 27.0 in Andhra Pradesh to 35.7 in Meghalaya. States with a median age at last birth below 28 years are Andhra Pradesh, Maharashtra, Tamil Nadu, Karnataka, and Kerala. Table 4.14 Age at last birth Percent distribution of ever-married women age 40–49 years by age at last birth and median age at last birth, according to current age and residence, India, 1998–99 Age at last birth Current age No birth < 20 20–24 25–29 30–34 35–39 40–44 45–49 Total percent Median age at last birth Number of women URBAN 40–44 45–49 40–49 3.1 3.1 23.9 36.8 23.3 8.7 1.1 NA 100.0 28.0 3,135 3.1 2.7 18.1 36.6 25.3 12.1 2.0 0.2 100.0 28.8 2,473 3.1 2.9 21.3 36.7 24.2 10.2 1.5 0.1 100.0 28.4 5,608 RURAL 40–44 45–49 40–49 2.7 3.8 19.1 33.6 24.2 13.9 2.7 NA 100.0 29.0 7,387 2.9 3.3 13.9 27.5 29.6 15.8 6.2 0.7 100.0 30.7 5,706 2.8 3.6 16.8 31.0 26.6 14.7 4.2 0.3 100.0 29.8 13,092 TOTAL 40–44 45–49 40–49 2.8 3.6 20.5 34.6 23.9 12.4 2.2 NA 100.0 28.7 10,521 2.9 3.1 15.2 30.3 28.3 14.7 4.9 0.6 100.0 30.2 8,179 2.9 3.4 18.2 32.7 25.9 13.4 3.4 0.2 100.0 29.3 18,701 NA: Not applicable 106 The difference between the median age at first birth and the median age at last birth provides a rough estimate of the typical reproductive age span. Among women age 40–49 in India, this estimated reproductive age span is the difference between 19.2 and 29.1, or 9.9 years. Thus, reproduction in India begins at a fairly early age and is concentrated in a span of about 10 years. The difference between the median age at last birth and median age at first birth ranges from only 6.8 years in Kerala to 14.9 years in Meghalaya. In addition to Meghalaya, states with a span of 12 or more years are Uttar Pradesh, Bihar, and Nagaland. Table 4.15 Median age at first and last birth by state Median age at first birth and median age at last birth for women age 40–49 who have had at least one birth, by state, India, 1998–99 State Median age at first birth for women with at least one birth Median age at last birth for women with at least one birth Difference India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 19.2 29.1 9.9 21.3 28.9 7.6 20.4 29.4 9.0 20.0 28.2 8.3 19.5 30.3 10.9 21.5 29.2 7.6 19.5 30.7 11.2 18.5 29.9 11.3 19.0 32.5 13.4 18.8 31.6 12.9 19.1 29.0 9.9 19.0 28.6 9.6 21.1 30.5 9.4 19.1 28.7 9.6 21.3 33.0 11.6 20.7 35.7 14.9 22.1 31.4 9.3 21.3 34.1 12.8 21.7 32.1 10.4 22.8 30.2 7.5 20.1 28.1 8.1 18.8 27.1 8.4 17.7 27.0 9.3 18.5 27.7 9.1 21.1 27.9 6.8 19.6 27.6 8.1 107 4.9 Postpartum Amenorrhoea, Abstinence, Insusceptibility, and Menopause Among the factors that influence the risk of pregnancy following a birth are breastfeeding and sexual abstinence. Breastfeeding prolongs postpartum protection from conception through its effect on the period of amenorrhoea (the period prior to the return of menses) following a birth. Delaying the resumption of sexual relations following a birth also prolongs the period of postpartum protection. Women are defined as insusceptible to pregnancy following a birth if they are not at risk of conception because they are amenorrhoeic, are abstaining from sexual relations, or both. Table 4.16 shows the percentage of births occurring during the three years preceding the survey whose mothers are postpartum amenorrhoeic, abstaining, or insusceptible, by the number of months since childbirth. These distributions are based on current status information, i.e., on the proportion of births occurring within the 36 months before the survey whose mothers were amenorrhoeic, abstaining, or insusceptible at the time of the survey. In other words, the table is based on cross-sectional data and does not represent the experience of a real cohort of births over time. Median and mean durations of amenorrhoea, abstinence, and insusceptibility are also shown in the table. The prevalence/incidence mean is obtained by dividing the number of mothers who are amenorrhoeic, abstaining, or insusceptible by the average number of births per month over the 36-month period. Ninety-four percent of mothers are still amenorrhoeic within the first month after a birth, and 82 percent are still amenorrhoeic two months after a birth. The proportion amenorrhoeic gradually decreases as the number of months since the last birth increases. Half of mothers are still amenorrhoeic eight months after a birth, but the proportion then drops off fairly rapidly and is only 9 percent 24 months after a birth. The proportion of mothers abstaining from sexual intercourse within the first month after a birth is almost the same as the proportion amenorrhoeic at this same duration, but at later durations the proportion abstaining is substantially lower than the proportion amenorrhoeic. Twenty percent of women still abstain from sexual intercourse 8 months after a birth, and 12 percent are still abstinent 12 months after a birth. Overall, when amenorrhoea and abstinence are considered together, half of mothers are still insusceptible to pregnancy nine months after a birth. The median and mean durations of insusceptibility are 10 and 12 months, respectively. The median duration of amenorrhoea (almost 9 months) is almost three times as high as the median duration of abstinence (just over 3 months). The table indicates that women in India remain insusceptible to conception for almost one year after a birth, primarily due to the effect of postpartum amenorrhoea. Menopause is a primary limiting factor of fertility. It is the culmination of a gradual decline in fecundity with increasing age. After age 30, the risk of pregnancy declines with age as an increasing proportion of women become infecund. In NFHS-2, menopause is defined as the absence of menstruation for six or more months preceding the survey among currently married women. Women who report that they are menopausal or that they have had a hysterectomy are also included in this category. Women who are pregnant or postpartum amenorrhoeic are assumed not to be menopausal. 108 Table 4.17 presents data on menopause for women age 30–49 in the whole country and individual states. In India, 19 percent of women age 40–41 have already reached menopause, and the incidence of menopause increases rapidly after age 41. By age 48–49, two-thirds of women are in menopause. The onset of menopause appears to occur somewhat later in urban areas than in rural areas. Table 4.16 Postpartum amenorrhoea, abstinence, and insusceptibility Percentage of births during the three years preceding the survey whose mothers are postpartum amenorrhoeic, abstaining, or insusceptible by number of months since birth, and median and mean durations, India, 1998–99 Percentage of births whose mothers are: Months since birth Amenorrhoeic Abstaining Insusceptible Number of births < 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Median1 Mean Prevalence/incidence mean 94.3 95.5 99.1 469 92.8 82.5 97.5 1,010 82.3 60.2 90.4 1,139 73.6 44.1 80.5 1,087 70.7 36.2 77.4 1,040 64.6 30.8 70.2 1,049 56.0 22.1 62.2 1,024 56.4 20.7 62.3 968 49.0 19.6 55.9 863 44.9 13.1 50.5 841 40.8 13.9 47.2 755 38.4 15.5 43.4 724 35.9 11.8 42.2 827 33.0 9.0 37.3 1,016 25.0 9.7 30.2 1,075 22.8 6.8 25.2 1,029 18.6 6.3 21.9 1,072 15.4 5.9 19.7 1,002 11.6 5.3 15.8 959 11.2 5.3 15.3 795 8.8 4.6 11.9 747 8.7 3.6 10.8 756 11.4 4.5 14.0 726 9.9 5.8 14.2 701 8.5 4.8 12.0 750 4.5 4.2 7.8 947 3.4 2.9 5.9 966 3.0 3.0 5.6 988 3.4 2.3 5.0 939 2.5 2.8 5.1 1,015 3.5 2.9 5.9 1,019 2.4 3.3 5.2 891 1.3 2.0 3.0 796 3.1 2.6 5.0 744 2.0 3.6 5.4 793 2.5 2.5 4.8 762 8.6 3.3 9.8 NA 10.7 6.2 12.2 NA 10.3 5.6 11.8 NA Note: Median and mean durations are based on current status. Insusceptible is defined as amenorrhoeic, abstaining, or both. NA: Not applicable 1Based on a three-period moving average of percentages 109 There is a surprising amount of variability among the states in the proportion of women who are menopausal at each age. At age 48–49, this proportion ranges from 48 percent in West Bengal to 82 percent in Andhra Pradesh. At age 35–39, it ranges from 2 percent in Nagaland to 22 percent in Andhra Pradesh. Since menopause is a heavily biologically-influenced characteristic, the wide variations by state are somewhat unexpected. However, it is interesting to note that in both NFHS-1 and NFHS-2, Andhra Pradesh had much higher reported levels of menopause than any other state. Table 4.17 Menopause by state Percentage of currently married women age 30–49 years who are in menopause by age and state, India, 1998–99 Age State 30–34 35–39 40–41 42–43 44–45 46–47 48–49 Total India–Urban India–Rural India–Total North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 2.2 7.0 15.1 23.1 35.4 50.0 67.3 3.5 8.5 20.6 28.1 40.9 55.6 66.4 3.1 8.0 19.0 26.5 39.3 53.9 66.6 1.5 3.4 11.4 20.9 31.9 35.4 73.4 1.7 4.8 10.7 23.3 37.0 43.6 66.7 0.9 5.0 9.6 22.4 32.1 46.0 72.0 2.1 6.6 16.7 31.9 33.9 52.4 62.9 1.4 4.4 20.8 20.6 35.4 52.5 63.3 2.3 4.6 13.5 19.9 35.1 39.3 61.2 2.9 7.3 15.1 23.5 32.6 44.8 51.9 2.1 7.3 20.2 31.3 42.3 58.5 68.8 2.9 9.2 23.6 35.2 51.1 60.7 75.8 1.7 5.3 19.5 23.8 31.7 50.6 62.4 1.5 4.3 12.8 22.1 34.9 46.1 48.4 1.0 3.8 6.9 * (8.2) * * 1.6 6.2 22.5 30.4 43.6 55.7 73.4 0.8 4.8 9.6 14.4 21.8 (31.8) (48.9) 1.4 2.9 (4.1) (13.9) (21.7) * * 1.1 2.3 7.6 10.1 (8.1) (9.2) * 2.9 1.5 (7.6) (20.1) (39.4) * * 2.1 5.8 12.2 7.8 28.8 * (68.9) 1.7 4.7 15.0 17.0 27.6 40.9 66.1 3.1 10.7 24.0 27.5 42.3 55.5 62.7 4.3 7.8 16.6 21.5 40.5 62.9 64.8 12.8 22.1 37.6 35.9 55.0 65.4 82.2 1.6 10.6 22.7 26.6 45.8 58.3 76.1 1.2 3.7 8.2 12.5 21.1 37.4 53.0 2.0 4.5 12.6 26.1 30.5 49.8 69.7 16.1 18.3 17.7 11.8 14.6 15.0 15.6 15.2 13.1 14.2 17.8 21.7 15.6 12.8 6.1 17.0 10.7 10.8 5.4 11.6 11.6 16.1 19.9 16.9 31.4 20.2 11.6 16.0 Note: Percentage menopausal is defined as the percentage of currently married women who are not pregnant, not amenorrhoeic, and reported that their last menstrual period occurred six or more months preceding the survey or that they are menopousal or have had a hysterectomy. ( ) Based on 25–49 unweighted cases *Percentage not shown; based on fewer than 25 unweighted cases 110 Table 4.18 Fertility preferences Percent distribution of currently married women by desire for children and preferred sex of additional child, according to number of living children and residence, India, 1998–99 Number of living children1 Desire for children 0 1 2 3 4+ Total URBAN Desire for additional child Wants another soon2 Wants another later3 Wants another, undecided when Undecided Up to God Wants no more Sterilized Declared infecund Missing Total percent Number of women Preferred sex of additional child 4 Boy Girl Doesn’t matter Up to God Total percent Number of women wanting more4 68.8 21.0 4.7 1.9 1.2 11.6 13.4 40.9 6.7 2.9 1.4 11.5 6.3 3.9 1.1 0.7 0.5 1.8 0.4 2.0 0.9 0.7 0.6 0.9 1.3 0.8 0.6 0.5 1.0 0.7 2.0 24.2 43.5 30.7 36.1 32.2 0.7 4.6 40.1 60.1 54.1 37.9 6.8 2.7 2.4 2.2 5.0 3.3 0.3 0.1 0.1 0.1 0.1 0.1 100.0 100.0 100.0 100.0 100.0 100.0 1,811 3,972 6,465 4,711 4,929 21,888 22.5 33.2 57.9 66.2 73.0 36.4 4.6 19.0 15.5 12.9 6.2 13.5 56.2 34.3 16.8 13.0 9.9 36.5 16.7 13.5 9.8 7.9 10.8 13.6 100.0 100.0 100.0 100.0 100.0 100.0 1,632 2,615 817 261 153 5,478 RURAL Desire for additional child Wants another soon2 Wants another later3 Wants another, undecided when Undecided Up to God Wants no more Sterilized Declared infecund Missing Total percent Number of women Preferred sex of additional child 4 Boy Girl Doesn’t matter Up to God Total percent Number of women wanting more4 71.9 30.5 11.0 5.2 2.5 16.0 12.1 45.1 14.5 6.9 2.9 13.9 5.7 5.2 2.2 1.1 0.7 2.3 0.6 0.8 1.1 0.8 0.9 0.9 2.0 2.0 1.5 1.4 2.3 1.8 0.9 8.8 27.0 27.3 40.9 25.9 0.9 4.8 40.2 54.6 44.5 35.4 5.7 2.6 2.4 2.6 5.2 3.6 0.1 0.1 0.1 0.1 0.1 0.1 100.0 100.0 100.0 100.0 100.0 100.0 5,809 9,659 14,371 13,469 18,273 61,761 38.6 42.6 60.6 75.7 71.9 49.8 1.9 14.9 14.2 8.4 6.8 10.3 39.1 27.7 13.7 6.7 9.4 25.0 20.5 14.8 11.4 9.2 11.9 15.0 100.0 100.0 100.0 100.0 100.0 100.0 5,282 7,812 4,001 1,816 1,111 20,023 111 4.10 Desire for More Children In order to obtain information on fertility preferences, NFHS-2 asked nonsterilized, currently married, nonpregnant women: ‘Would you like to have (a/another) child or would you prefer not to have any (more) children?’ Pregnant women were asked, ‘After the child you are expecting, would you like to have another child or would you prefer not to have any more children?’ Women who expressed a desire for additional children were asked how long they would like to wait before the birth of their next child. The survey also collected information on the preferred sex of the next child and the ideal number of children by sex. Table 4.18 and Figure 4.5 show future fertility preferences of currently married women. Overall, 28 percent of currently married women say that they do not want any more children, an additional 36 percent cannot have another child because either the wife or the husband has been sterilized, and 4 percent of women say that they cannot get pregnant (that is, they are ‘declared infecund’). Thirty percent of the women say they would like to have another child (15 percent within two years, 13 percent after waiting at least two years, and 2 percent undecided when). The desire to stop childbearing increases rapidly with the number of living children. Only 2 percent of women with no living children do not want any children (the woman or her husband is sterilized Table 4.18 Fertility preferences (contd.) Percent distribution of currently married women by desire for children and preferred sex of additional child, according to number of living children and residence, India, 1998–99 Number of living children1 Desire for children 0 1 2 3 4+ Total TOTAL Desire for additional child Wants another soon2 Wants another later3 Wants another, undecided when Undecided Up to God Wants no more Sterilized Declared infecund Missing Total percent Number of women Preferred sex of additional child 4 Boy Girl Doesn’t matter Up to God Total percent Number of women wanting more4 71.1 27.7 9.0 4.4 2.2 14.8 12.4 43.9 12.1 5.9 2.6 13.3 5.9 4.8 1.9 1.0 0.7 2.2 0.6 1.2 1.0 0.8 0.8 0.9 1.8 1.7 1.2 1.2 2.0 1.5 1.2 13.3 32.1 28.2 39.9 27.5 0.9 4.8 40.2 56.0 46.5 36.1 6.0 2.6 2.4 2.5 5.2 3.5 0.1 0.1 0.1 0.1 0.1 0.1 100.0 100.0 100.0 100.0 100.0 100.0 7,620 13,631 20,836 18,359 23,202 83,649 34.8 40.3 60.2 74.5 72.0 46.9 2.5 15.9 14.4 9.0 6.8 11.0 43.1 29.4 14.3 7.5 9.4 27.5 19.6 14.5 11.1 9.0 11.8 14.7 100.0 100.0 100.0 100.0 100.0 100.0 6,914 10,427 4,818 2,077 1,264 25,501 1Includes current pregnancy, if any 2Wants next birth within 2 years 3Wants to delay next birth for 2 or more years 4Excludes currently pregnant women 112 or the woman says she wants no more children), compared with 72 percent of women with two living children and 86 percent or more of women with four or more living children. Two percent of the women say that the decision about having any (more) children is up to God. Overall, 77 percent of women want to either space their next birth or do not want any more children. This proportion is 82 percent in urban areas and 75 percent in rural areas. The desire to have a child within two years drops rapidly with the number of living children, from 71 percent for women without any living children to 9 percent or less for women with two or more living children. Forty-four percent of women with one living child (41 percent in urban areas and 45 percent in rural areas) would like to wait at least two years before having the next child. And yet, as will be seen in the next chapter, very few women in India use any temporary method of contraception. These findings suggest that encouraging the use of temporary methods would lower overall fertility and population growth, as well as provide health benefits to mothers and their children through increased birth spacing. Forty-seven percent of women who want another child say they want the next child to be a boy, only 11 percent say they want the child to be a girl, and the rest say that the sex of the child does not matter (28 percent) or that it is up to God (15 percent). Irrespective of their number of living children, women are much more likely to express a desire for a son than for a daughter, and the proportion of women expressing a desire specifically for a son generally increases with the number of living children. Among women who have no living children, only a few women express a specific desire for a daughter (3 percent), but 43 percent say it does not matter whether they have a son or a daughter. Even among this group, one in every three women say they would like their first child to be a boy. Table 4.19 shows how fertility preferences vary by state. The proportion of currently married women who want to have another child at any time in the future ranges from 20 percent Figure 4.5 Fertility Preferences Among Currently Married Women Wants Another After 2 Years 13% Wants Another, Undecided When 2% Wants No More 28% Sterilized 36% Other 6% Missing 0.1% Wants Another Within 2 Years 15% Note: Percents add to more than 100 due to rounding NFHS-2, India, 1998–99 113 in Himachal Pradesh and Punjab to 46 percent in Meghalaya. A majority of women who want another child would like to wait at least two years before having that child in Jammu and Kashmir, West Bengal, and five states in the Northeast Region (Arunachal Pradesh, Manipur, Meghalaya, Mizoram, and Sikkim). The proportion who want no more children, including those who are sterilized or whose husbands are sterilized, ranges from 39 percent in Meghalaya to 79 percent in Himachal Pradesh. The proportion of women who believe that decisions pertaining to childbearing are ‘up to God’ is 6 percent in Assam, 4 percent in Bihar and Uttar Pradesh, and 2 percent or less in other states. Table 4.19 Fertility preferences by state Percent distribution of currently married women by desire for children, according to state, India, 1998–99 State Wants another soon1 Wants another later2 Wants another, undecided when Unde- cided Up To God Wants no more Steril- ized Declared infecund Miss- ing Total percent India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 14.8 13.3 2.2 0.9 1.5 27.5 36.1 3.5 0.1 100.0 9.9 10.2 2.2 1.1 1.5 45.6 28.6 0.7 0.1 100.0 15.4 9.6 0.5 0.3 0.2 32.8 40.8 0.4 0.1 100.0 10.9 8.9 0.1 0.6 0.0 26.2 52.4 0.8 0.0 100.0 11.1 12.4 0.9 0.9 1.5 38.6 30.7 3.8 0.0 100.0 11.8 9.1 0.3 0.2 0.3 46.6 30.9 0.7 0.1 100.0 17.3 14.6 1.4 1.1 1.3 27.6 32.3 4.3 0.1 100.0 17.1 16.5 2.2 0.7 0.8 23.4 38.0 1.2 0.1 100.0 17.0 17.8 2.0 1.2 3.6 38.1 15.6 4.5 0.2 100.0 17.3 15.8 6.3 0.8 3.8 30.2 20.1 5.6 0.0 100.0 17.3 15.3 0.6 0.6 0.8 27.7 35.6 2.0 0.0 100.0 10.5 13.4 0.6 0.8 0.5 39.2 33.8 1.0 0.1 100.0 15.2 18.8 3.3 9.9 1.3 26.3 20.7 4.1 0.4 100.0 15.4 12.8 1.6 1.1 6.2 43.0 16.7 2.6 0.6 100.0 13.8 21.9 1.2 8.2 0.6 36.5 15.5 2.2 0.0 100.0 8.3 33.4 4.3 6.6 2.3 32.0 6.5 6.5 0.1 100.0 10.4 22.3 2.8 4.3 1.4 12.4 45.4 1.2 0.0 100.0 13.2 14.8 3.8 12.7 1.3 35.0 12.3 6.9 0.0 100.0 6.9 12.5 1.2 1.2 0.4 51.2 24.7 1.6 0.3 100.0 17.4 12.0 1.3 0.8 0.6 32.8 28.2 6.9 0.0 100.0 15.1 11.2 1.4 1.1 0.6 20.1 45.3 5.2 0.0 100.0 9.8 9.5 4.9 1.0 0.3 19.8 52.2 2.5 0.1 100.0 17.0 7.5 1.6 0.5 0.7 10.5 57.0 5.1 0.1 100.0 12.8 11.7 1.2 1.0 0.3 15.3 52.2 5.4 0.0 100.0 14.3 12.0 1.8 1.0 0.6 17.1 51.0 2.1 0.0 100.0 13.5 11.8 0.2 0.3 0.4 23.0 45.9 4.7 0.1 100.0 1Wants next birth within 2 years 2Wants to delay next birth for 2 or more years 114 Table 4.20 Desire to have no more children by background characteristics Percentage of currently married women who want no more children by number of living children and selected background characteristics, India, 1998–99 Number of living children1 Background characteristic 0 1 2 3 4+ Total Age 15–24 25–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Number of living sons2 0 1 2 3+ Number of living daughters2 0 1 2 3+ Total 0.4 6.5 52.4 65.2 79.8 26.2 2.4 27.4 77.3 83.9 84.2 72.2 13.4 62.5 88.2 91.6 88.2 85.6 2.7 28.8 83.6 90.9 90.2 70.0 1.9 13.6 67.2 81.8 85.4 61.3 2.6 13.4 59.8 79.7 84.7 62.7 2.5 17.0 78.2 88.9 91.7 68.3 0.6 15.5 80.7 90.7 91.9 60.1 1.3 28.4 87.1 93.9 93.1 62.9 2.1 19.1 73.8 85.2 87.9 64.4 2.3 10.0 51.3 72.8 80.0 56.5 3.2 14.2 80.3 83.2 80.2 62.5 0.8 24.4 88.7 93.6 96.1 75.4 (0.0) (26.5) 85.9 92.5 100.0 73.5 (0.1) 23.2 79.1 96.2 95.5 78.0 (0.0) 13.3 56.6 77.3 85.0 57.2 * * * (63.7) 41.0 39.8 2.1 14.7 63.4 83.6 87.6 62.1 3.2 11.2 55.8 75.1 82.3 55.8 1.8 14.8 72.4 83.9 86.3 62.7 2.1 23.8 78.5 87.1 87.3 67.0 2.6 13.6 61.5 78.8 83.3 59.2 1.8 15.0 71.2 84.3 87.1 63.5 2.0 29.6 85.1 92.3 92.4 70.6 2.1 17.1 46.8 50.1 57.0 19.5 NA 23.4 76.4 80.8 83.1 66.0 NA NA 82.6 92.9 90.8 89.3 NA NA NA 89.6 87.9 88.2 2.1 23.4 82.6 89.6 87.8 40.9 NA 17.1 76.4 92.9 90.0 71.5 NA NA 46.8 80.8 91.1 78.8 NA NA NA 50.1 83.1 79.6 2.1 18.1 72.3 84.2 86.5 63.6 Note: Women who have been sterilized or whose husbands have been sterilized are considered to want no more children. Total includes women with missing information on education, religion, caste/tribe, and the standard of living index, who are not shown separately. NA: Not applicable ( ) Based on 25–49 unweighted cases *Percentage not shown; based on fewer than 25 unweighted cases 1Includes current pregnancy, if any 2Excludes pregnant women 115 Table 4.20 provides information about differentials in the desire to limit family size by selected background characteristics. Women who are sterilized (or whose husbands are sterilized) are included among those who say they want no more children. As expected, older women are much more likely than younger women to want no more children. Already by age 25– 34, 72 percent of women want no more children. The proportion who want no more children is somewhat higher among urban women (70 percent) than among rural women (61 percent). For mothers, the desire to stop childbearing tends to increase steadily with the level of education within each parity, although that progression does not show up clearly in the percentages for all women taken together. The proportion who want no more children is higher among Hindus (64 percent) and Christians (63 percent) than among Muslims (57 percent), but the desire to stop childbearing is particularly strong among Buddhists, Sikhs, and Jains. By caste/tribe, the proportion who want no more children is highest for women in the ‘other’ category (67 percent) and lowest for scheduled-tribe women (56 percent). The proportion who want no more increases with the standard of living, from 59 percent for women living in households with a low standard of living to 71 percent for women living in households with a high standard of living. The proportion who want no more children is highest for women with two living sons (89 percent) and is very low for women with no living sons (20 percent). Differences associated with the number of living daughters are also large but not as large as differences associated with the number of living sons, indicating a preference for sons. The proportion who want no more children is highest for women with three or more living daughters (80 percent) and lowest for women with no living daughters (41 percent). Despite the existence of son preference, it is interesting to note that 47 percent of women with two daughters and no sons do not want to have a third child. Overall, the table shows that, in every socioeconomic subgroup, a majority of women with two or more living children want no more children. It also shows that within each subgroup, the proportion who want no more children rises sharply with the number of living children. 4.11 Ideal Number of Children To assess women’s ideal number of children, NFHS-2 asked each woman the number of children she would like to have if she could start over again. Women with no children were asked, ‘If you could choose exactly the number of children to have in your whole life, how many would that be?’ Women who already had children were asked, ‘If you could go back to the time you did not have any children and could choose exactly the number of children to have in your whole life, how many would that be?’ Some women had difficulty in answering these hypothetical questions, and hence the question often had to be repeated to ensure that the meaning was understood. Table 4.21 shows that almost half (47 percent) of ever-married women in India consider two to be the ideal number of children, and 72 percent consider two or three to be ideal. Only 21 percent have an ideal number that differs from two or three children. Seven percent were unable to give a numeric response to the question. Among all women who gave a numeric response, the average number of children considered ideal is 2.7, ranging from 2.4 for women who have no children to 3.3 for women who have four or more children. 116 Asking a question on ideal family size is sometimes criticized on the grounds that women tend to adjust their ideal family size upward as the number of their living children increases, in a process of rationalizing previously unwanted children as wanted. It is argued that the question on ideal family size prompts many women to state the actual number of children they already have as their ideal. It is evident from Table 4.21, however, that this is not so for many women in India. Among women with four or more living children, for example, 51 percent state that fewer than four children would be ideal. Similarly, among women with three living children, 43 percent state that their ideal family size is smaller than three children. It is evident that a large proportion of women already have more children than they now consider ideal. This proportion may be taken as another indicator of surplus or unwanted fertility. Table 4.21 Ideal and actual number of children Percent distribution of ever-married women by ideal number of children, and mean ideal number of children, by number of living children and residence, India, 1998–99 Number of living children1 Ideal number of children 0 1 2 3 4+ Total URBAN 0 1 2 3 4 5 6+ Non-numeric response Total percent Number of women Mean ideal number2 Number of women giving numeric response 0.1 0.1 0.0 0.1 0.2 0.1 17.0 21.6 6.7 3.7 1.4 8.5 63.5 64.6 76.9 52.7 35.0 58.8 10.2 8.6 10.1 32.1 25.9 18.1 2.8 1.7 2.7 5.4 20.3 7.1 0.5 0.3 0.3 0.8 3.1 1.1 0.2 0.0 0.1 0.3 2.3 0.6 5.6 3.1 3.2 4.9 11.8 5.7 100.0 100.0 100.0 100.0 100.0 100.0 2,005 4,271 6,796 5,010 5,287 23,370 2.0 1.9 2.1 2.4 3.0 2.3 1,893 4,139 6,578 4,765 4,666 22,041 RURAL 0 1 2 3 4 5 6+ Non-numeric response Total percent Number of women Mean ideal number2 Number of women giving numeric response 0.1 0.1 0.0 0.1 0.3 0.1 5.8 7.0 3.1 2.0 0.7 3.0 52.1 57.4 61.6 36.7 21.4 42.8 24.2 21.2 21.4 40.2 25.9 27.1 8.5 6.8 7.5 12.0 28.6 14.7 1.8 1.4 1.2 1.7 6.5 3.0 0.7 1.0 0.6 1.0 4.7 2.0 6.8 5.0 4.6 6.4 11.9 7.4 100.0 100.0 100.0 100.0 100.0 100.0 6,576 10,456 15,212 14,341 19,243 65,829 2.5 2.4 2.4 2.8 3.4 2.8 6,130 9,933 14,515 13,422 16,956 60,956 117 Table 4.22 shows the mean ideal number of children for ever-married women by age according to selected background characteristics. The mean ideal family size increases gradually from 2.5 children for women age 15–24 to 2.9 children for women age 45–49. Ideal family size is 2.3 children in urban areas and 2.8 children in rural areas. The average ideal number of children ranges from 2.1 for women with at least a high school education to 2.9 for illiterate women. Among religious groups, it ranges from 2.2 for Sikh and Jain women to 3.1 for Muslim women. By caste/tribe, the ideal ranges from 2.5 children for the ‘other’ category to 3.0 children for scheduled-tribe women. The ideal number of children does not vary much by the work status of the woman. The ideal family size ranges from 2.3 children for women living in households with a high standard of living to 2.9 children for women living in households with a low standard of living. Women whose husbands are illiterate have a much higher ideal number of children (3.0) than women whose husbands have at least completed higher secondary school (2.2). Table 4.23 shows how ideal family size varies by state. The mean ideal number of children ranges from 2.0 in Tamil Nadu to 4.7 in Meghalaya. A majority of states have a mean ideal family size between 2.0 and 2.7 children. Meghalaya, Mizoram, and Nagaland all have a mean ideal number of children of 4.0 or higher. Other states with a mean ideal family size of more than 3.0 children are Manipur, Bihar, Arunachal Pradesh, and Uttar Pradesh. Table 4.21 Ideal and actual number of children (contd.) Percent distribution of ever-married women by ideal number of children, and mean ideal number of children, by number of living children and residence, India, 1998–99 Number of living children1 Ideal number of children 0 1 2 3 4+ Total TOTAL 0 1 2 3 4 5 6+ Non-numeric response Total percent Number of women Mean ideal number2 Number of women giving numeric response 0.1 0.1 0.0 0.1 0.2 0.1 8.4 11.2 4.2 2.4 0.9 4.5 54.8 59.5 66.3 40.8 24.3 47.0 20.9 17.6 17.9 38.1 25.9 24.7 7.2 5.4 6.0 10.3 26.8 12.7 1.5 1.1 0.9 1.5 5.8 2.5 0.6 0.8 0.5 0.8 4.2 1.6 6.5 4.4 4.2 6.0 11.9 7.0 100.0 100.0 100.0 100.0 100.0 100.0 8,581 14,727 22,009 19,352 24,531 89,199 2.4 2.3 2.3 2.7 3.3 2.7 8,023 14,072 21,093 18,187 21,622 82,996 1Includes current pregnancy, if any 2Means are calculated excluding women who gave non-numeric responses. 118 Table 4.22 Ideal number of children by background characteristics Mean ideal number of children reported by ever-married women, according to current age and selected background characteristics, India, 1998–99 Current age Background characteristic 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living index Low Medium High Husband’s education Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Total 2.2 2.2 2.2 2.3 2.4 2.4 2.5 2.3 2.6 2.6 2.7 2.8 2.9 3.0 3.1 2.8 2.8 2.8 2.9 3.0 3.0 3.1 3.2 2.9 2.3 2.3 2.4 2.5 2.5 2.6 2.7 2.5 2.2 2.2 2.2 2.2 2.3 2.4 2.4 2.2 2.1 2.0 2.0 2.0 2.1 2.1 2.2 2.1 2.5 2.4 2.5 2.6 2.7 2.8 2.9 2.6 2.8 2.8 3.0 3.1 3.3 3.4 3.6 3.1 2.4 2.6 2.5 2.6 2.8 2.8 3.1 2.7 2.2 2.1 2.1 2.2 2.3 2.4 2.5 2.2 * (1.9) 2.1 2.0 2.1 (2.3) 2.6 2.2 (2.2) 2.2 2.2 2.3 2.5 2.6 2.6 2.3 (2.8) 2.6 2.6 3.2 2.8 3.4 (3.3) 2.9 * (3.8) (3.4) (4.3) (5.5) * * 4.0 2.6 2.5 2.7 2.7 2.9 2.9 3.1 2.7 2.8 2.8 3.0 3.2 3.2 3.2 3.4 3.0 2.5 2.5 2.6 2.6 2.7 2.8 2.9 2.6 2.5 2.4 2.4 2.5 2.6 2.7 2.8 2.5 2.5 2.6 2.7 2.9 2.9 3.0 3.2 2.8 2.5 2.5 2.6 2.6 2.7 2.7 2.7 2.6 2.6 2.5 2.5 2.6 2.7 2.6 2.9 2.6 2.5 2.5 2.5 2.6 2.7 2.8 3.0 2.6 2.7 2.7 2.8 3.0 3.0 3.0 3.2 2.9 2.5 2.5 2.6 2.7 2.8 2.9 3.0 2.7 2.2 2.1 2.1 2.2 2.3 2.4 2.6 2.3 2.7 2.8 2.9 3.0 3.1 3.1 3.2 3.0 2.6 2.6 2.7 2.8 2.9 2.9 3.1 2.8 2.5 2.5 2.7 2.7 2.7 2.8 2.9 2.7 2.5 2.5 2.5 2.6 2.7 2.7 2.9 2.6 2.4 2.3 2.4 2.5 2.5 2.6 2.6 2.5 2.3 2.2 2.2 2.2 2.3 2.4 2.5 2.2 2.5 2.5 2.6 2.7 2.7 2.8 2.9 2.7 Note: Means are calculated excluding women who gave non-numeric responses. Total includes women with missing information on education, religion, caste/tribe, work status, the standard of living index, and husband’s education, who are not shown separately. ( ) Based on 25–49 unweighted cases *Mean not shown; based on fewer than 25 unweighted cases 119 4.12 Sex Preference for Children A strong preference for sons has been found to be pervasive in Indian society, affecting both attitudes and behaviour with respect to children (Arnold et al., 1998; Arnold, 1996; Basu, 1989; Das Gupta, 1987; Kishor, 1995; Koenig and Foo, 1992; Murthi et al., 1995; Nag, 1991; Parasuraman et al., 1994). In NFHS-2, women who gave a numerical response to the question on ideal number of children were also asked how many of these children they would like to be boys, how many they would like to be girls, and for how many the sex would not matter. Table 4.24 shows the mean ideal number of sons and daughters, the percentage who desire more sons than Table 4.23 Ideal number of children by state Mean ideal number of children reported by ever-married women, according to current age and state, India, 1998–99 Current age State 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 2.5 2.5 2.6 2.7 2.7 2.8 2.9 2.7 2.3 2.2 2.2 2.4 2.4 2.5 2.5 2.4 2.1 2.3 2.4 2.5 2.6 2.8 3.1 2.5 2.0 2.1 2.1 2.1 2.2 2.3 2.4 2.2 2.4 2.5 2.5 2.7 2.8 2.8 2.9 2.7 2.1 2.1 2.2 2.2 2.3 2.4 2.5 2.3 2.5 2.6 2.7 2.8 3.0 3.0 3.2 2.8 2.7 2.7 2.9 3.0 3.0 3.1 3.3 2.9 2.9 2.9 3.1 3.2 3.3 3.4 3.5 3.1 2.9 3.0 3.2 3.4 3.4 3.5 3.7 3.3 2.5 2.5 2.6 2.7 2.8 2.8 3.0 2.7 2.2 2.1 2.3 2.4 2.5 2.5 2.9 2.4 2.9 3.0 3.1 3.2 3.5 3.7 3.5 3.2 2.6 2.6 2.8 2.9 3.1 3.3 3.3 2.9 (2.9) 3.2 3.4 3.6 3.8 3.9 4.1 3.6 (4.6) 4.4 4.3 4.9 5.0 4.8 5.5 4.7 (3.2) 3.5 3.7 4.1 4.3 4.5 4.8 4.0 (3.7) 3.5 3.7 3.8 4.3 4.6 4.9 4.0 (2.0) 1.9 2.1 2.2 2.5 2.5 2.8 2.2 * 2.3 2.1 2.1 2.3 2.6 2.6 2.3 2.4 2.4 2.4 2.4 2.6 2.6 2.6 2.5 2.2 2.2 2.3 2.3 2.4 2.4 2.5 2.3 2.2 2.1 2.3 2.4 2.6 2.8 3.0 2.4 2.2 2.2 2.1 2.2 2.2 2.3 2.3 2.2 2.9 2.4 2.4 2.4 2.6 2.7 2.7 2.5 2.0 2.0 2.0 2.0 2.0 2.1 2.2 2.0 Note: Means are calculated excluding women who gave non-numeric responses. ( ) Based on 25–49 unweighted cases *Mean not shown; based on fewer than 25 unweighted cases 120 Table 4.24 Indicators of sex preference Mean ideal number of sons, daughters, and children of either sex for ever-married women, percentage who want more sons than daughters, percentage who want more daughters than sons, percentage who want at least one son, and percentage who want at least one daughter by selected background characteristics, India, 1998–99 Mean ideal number of: Background characteristic Sons Daughters Either sex Percentage who want more sons than daughters Percentage who want more daughters than sons Percentage who want at least one son Percentage who want at least one daughter Number of women Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living index Low Medium High 1.1 0.8 0.4 22.6 2.5 76.9 72.7 22,027 1.5 1.0 0.3 37.0 2.1 88.1 82.8 60,911 1.6 1.1 0.3 41.7 2.0 90.2 84.8 47,104 1.2 0.9 0.4 27.7 2.2 83.2 78.7 16,289 1.0 0.8 0.4 21.5 2.1 80.0 75.6 7,135 0.8 0.7 0.5 14.6 3.0 71.0 67.0 12,401 1.3 0.9 0.3 33.6 2.0 85.3 80.1 68,574 1.6 1.1 0.4 34.4 2.8 85.3 82.2 9,582 1.2 1.0 0.5 20.0 5.2 77.6 74.1 2,036 1.2 0.8 0.3 30.1 0.8 86.7 76.1 1,393 1.0 0.8 0.4 18.3 1.5 81.1 75.7 326 1.1 0.9 0.3 25.1 2.1 83.2 78.2 654 1.6 1.2 0.2 32.5 3.9 93.5 89.0 259 2.0 1.9 0.1 22.1 15.6 87.1 89.3 42 1.5 1.0 0.3 37.9 1.8 87.3 82.1 15,232 1.6 1.2 0.2 38.0 3.6 91.5 86.6 7,313 1.3 0.9 0.4 32.5 1.9 83.7 79.4 27,169 1.3 0.9 0.3 30.0 2.3 83.6 78.2 32,455 1.5 1.0 0.3 39.6 2.1 89.2 83.0 11,861 1.3 0.9 0.4 30.8 2.6 82.8 78.0 16,051 1.3 1.0 0.3 30.7 3.4 83.1 78.6 4,153 1.4 1.0 0.3 32.6 2.0 85.0 80.3 50,855 1.5 1.1 0.3 38.4 2.3 89.0 84.1 26,517 1.4 1.0 0.3 34.3 2.0 85.7 80.7 38,378 1.0 0.8 0.4 22.5 2.5 77.5 72.8 17,067 Contd… 121 daughters, the percentage who desire more daughters than sons, the percentage who desire at least one son, and the percentage who desire at least one daughter, according to selected background characteristics. The table shows a consistent preference for sons over daughters. Overall, the average ideal family size of 2.7 children consists of 1.4 sons, 1.0 daughters, and 0.3 children of either sex. Thirty-three percent of women want more sons than daughters, but only 2 percent want more daughters than sons. The indicator on the percentage who want at least one son and at least one daughter exhibits the weakest son preference. Eighty-five percent want at least one son among their children, and nearly as many (80 percent) want at least one daughter. One reason that a substantial proportion of women want to have at least one daughter despite having a preference for sons is to fulfil the Hindu religious obligation of kanyadan (giving a daughter away at the time of her marriage), which is one of the acts that enable the parents to acquire the highest level of merit (punya). Son preference is relatively weak in urban areas, among literate women, among women with more education and whose husbands have more education, and among women living in households with a high standard of living. Son preference is somewhat weaker among Christian and Jain women than among women of other religions. Son preference does not vary much by caste/tribe or woman’s work status. Table 4.25 shows how son preference varies by state. According to these measures, son preference is evident in every state. Son preference tends to be stronger in the northern part of the country than elsewhere, especially in Uttar Pradesh, Rajasthan, Bihar, Haryana, Madhya Pradesh, Orissa, and Arunachal Pradesh. The weakest son preference is found in Meghalaya, Mizoram, Tamil Nadu, Kerala, Karnataka, and Goa. The proportion who want more sons than daughters Table 4.24 Indicators of sex preference (contd.) Mean ideal number of sons, daughters, and children of either sex for ever-married women, percentage who want more sons than daughters, percentage who want more daughters than sons, percentage who want at least one son, and percentage who want at least one daughter by selected background characteristics, India, 1998–99 Mean ideal number of: Background characteristic Sons Daughters Either sex Percentage who want more sons than daughters Percentage who want more daughters than sons Percentage who want at least one son Percentage who want at least one daughter Number of women Husband’s education Illiterate Literate, < primary school complete Primary school complete Middle school complete High school complete Higher secondary complete and above Total 1.6 1.1 0.3 40.2 2.1 89.4 84.2 24,572 1.4 1.0 0.3 34.9 2.7 87.5 82.7 7,395 1.4 1.0 0.3 33.3 2.1 85.3 80.3 13,558 1.3 0.9 0.3 33.7 2.0 86.1 80.9 11,348 1.2 0.9 0.3 28.8 2.1 83.3 78.1 12,290 1.0 0.8 0.4 23.0 2.5 76.6 72.4 13,545 1.4 1.0 0.3 33.2 2.2 85.1 80.1 82,939 Note: Table excludes women who gave non-numeric responses to the questions on ideal number of children or ideal number of sons or daughters. Total includes 11, 73, 770, 18, 976, and 230 women with missing information on education, religion, caste/tribe, work status, the standard of living index, and husband’s education, respectively, who are not shown separately. 122 ranges from 10 percent in Tamil Nadu to 53 percent in Uttar Pradesh. In all states except Meghalaya and Mizoram, the proportion wanting more daughters than sons is 6 percent or lower. This proportion is 19 percent in Mizoram and 17 percent in Meghalaya. 4.13 Fertility Planning For each child born in the three years before the survey and for each current pregnancy, NFHS-2 asked women whether the pregnancy was wanted at that time (planned), wanted at a later time Table 4.25 Indicators of sex preference by state Mean ideal number of sons, daughters, and children of either sex for ever-married women, percentage who want more sons than daughters, percentage who want more daughters than sons, percentage who want at least one son, and percentage who want at least one daughter, according to state, India, 1998–99 Mean ideal number of: State Sons Daughters Either sex Percentage who want more sons than daughters Percentage who want more daughters than sons Percentage who want at least one son Percentage who want at least one daughter India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 1.4 1.0 0.3 33.2 2.2 85.1 80.1 1.2 0.9 0.3 23.1 2.6 85.5 82.0 1.4 0.9 0.3 37.5 0.5 89.8 80.9 1.1 0.8 0.3 25.9 0.6 87.5 79.4 1.4 1.0 0.3 38.0 2.7 87.6 82.5 1.2 0.8 0.3 29.1 0.4 86.2 78.0 1.6 1.1 0.1 47.5 1.3 95.7 89.4 1.5 1.0 0.3 42.5 2.9 87.8 82.4 1.8 1.1 0.2 53.3 1.4 94.1 89.3 1.9 1.3 0.1 47.9 2.1 97.2 93.6 1.5 1.0 0.2 37.6 2.1 92.8 85.3 1.1 0.9 0.4 20.7 3.4 79.9 75.5 1.8 1.3 0.1 41.9 2.5 93.5 90.5 1.6 1.2 0.1 38.2 2.9 94.5 91.0 1.9 1.6 0.1 36.5 4.8 96.2 93.0 2.3 2.2 0.2 20.9 16.9 94.7 93.6 2.0 1.9 0.1 26.0 19.0 97.6 97.1 2.0 1.7 0.3 32.7 6.3 91.6 88.7 1.1 0.9 0.3 22.4 3.1 83.4 77.6 0.9 0.8 0.7 17.0 5.1 67.9 64.9 1.2 0.8 0.5 33.2 1.8 78.9 68.1 1.2 0.9 0.3 27.1 1.9 84.5 79.3 1.0 0.8 0.5 19.8 2.7 76.0 71.3 0.9 0.8 0.5 13.0 1.9 70.0 67.5 1.0 0.8 0.7 14.6 5.2 72.6 70.7 0.8 0.7 0.6 9.6 1.9 66.3 63.9 Note: Table excludes women who gave non-numeric responses to the questions on ideal number of children or ideal number of sons or daughters. 123 (mistimed), or not wanted at all. Because a woman may retrospectively describe an unplanned pregnancy as one that was wanted at that time, responses to these questions may lead to an underestimation of unplanned childbearing. Nevertheless, this information provides a potentially powerful indicator of the degree to which couples successfully control childbearing. It should be noted that the proportion unplanned is influenced not only by whether, and how effectively, couples use contraception, but also by the couple’s ideal family size. Table 4.26 shows the percent distribution of births during the three years preceding the survey and current pregnancies according to fertility planning status. Twenty-one percent of all pregnancies that resulted in live births in the three years preceding the survey (including current pregnancies) were unplanned (that is, unwanted at the time the woman became pregnant). Twelve percent were wanted later and 9 percent were not wanted at all. The proportion of births that were unplanned is highest for births to women age 45–49 (47 percent) and lowest for births to women below age 20 (15 percent). Within the unplanned category, the proportion of births that were wanted later goes down and the proportion that were not wanted at all goes up with the age of the mother. The proportion of births that were unplanned is almost the same in urban areas and rural areas. By education, the proportion unplanned is slightly lower for births to women with at least a high school education (19 percent) than for births to women in the other education groups (21–23 percent). Among the religions, the proportion unplanned ranges from 15 percent for Sikhs to 28 percent for Buddhists. For the two largest religions, it is 20 percent for Hindus and 27 percent for Muslims. Scheduled-tribe women have a slightly lower proportion of unplanned births than women do in other caste/tribe groups. The proportion of pregnancies that are unplanned ranges from 19 percent for births to women living in households with a high standard of living to 22 percent for births to women living in households with a medium or low standard of living. Large variations in the planning status of births are seen by the birth order of the child. Unplanned pregnancies range from 14 percent for first-order births to 33 percent for births of order four or higher. The impact of unwanted fertility can be measured by comparing the total wanted fertility rate with the total fertility rate (TFR). The total wanted fertility rate represents the level of fertility that theoretically would result if all unwanted births were prevented. A comparison of the TFR with the total wanted fertility rate indicates the potential demographic impact of the elimination of all unwanted births. The total wanted fertility rates presented in Table 4.27 are calculated in the same way as the TFR except that unwanted births are excluded from the numerator. In this case, a birth is considered unwanted if the number of living children at the time of conception was greater than or equal to the ideal number of children reported by the respondent at the time of the survey. Women who did not give a numeric response to the question on ideal number of children are assumed to have wanted all the births they had. Overall, the total wanted fertility rate of 2.13 is lower by 0.72 child (i.e., by 25 percent) than the total fertility rate of 2.85. This means that if unwanted births could be eliminated, the TFR would drop to the replacement level of fertility (approximately 2.1 children per woman). Women living in urban areas, literate women, Sikh, Jain, and Buddhist women, and women living in households with a high standard of living would have well under two children, on average, under these circumstances. The difference between the total fertility rate and the total wanted fertility rate is somewhat larger for rural women (0.79 children) than for urban women (0.54 children). The difference is also relatively large for illiterate women, Muslims, scheduled- caste women, and women living in households with a low standard of living. 124 Table 4.26 Fertility planning Percent distribution of births during the three years preceding the survey and current pregnancies by fertility planning status, according to selected background characteristics, India, 1998–99 Planning status of pregnancy Background characteristic Wanted then Wanted later Not wanted at all Missing Total percent Number of births and current pregnancies Mother’s age at birth 1 < 20 20–24 25–29 30–34 35–39 40–44 45–49 Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Birth order 2 1 2 3 4+ Total 84.4 13.8 1.5 0.3 100.0 8,972 81.0 13.5 5.2 0.2 100.0 15,217 76.1 10.3 13.3 0.3 100.0 9,203 68.1 7.3 24.3 0.2 100.0 3,674 58.9 5.4 35.1 0.5 100.0 1,262 52.3 4.5 41.9 1.2 100.0 289 53.1 4.8 42.1 0.0 100.0 46 77.6 13.1 9.1 0.2 100.0 8,590 78.6 11.5 9.5 0.3 100.0 30,072 78.5 9.7 11.4 0.3 100.0 22,596 76.8 14.8 8.2 0.2 100.0 7,003 76.5 16.9 6.4 0.3 100.0 3,539 81.3 13.8 4.8 0.1 100.0 5,518 79.6 11.3 8.8 0.3 100.0 30,604 72.4 14.3 13.0 0.2 100.0 6,122 77.2 15.8 6.7 0.3 100.0 890 85.1 7.5 7.1 0.3 100.0 541 78.2 19.3 2.4 0.0 100.0 100 72.0 17.4 10.6 0.0 100.0 233 71.1 21.6 3.8 3.5 100.0 106 65.6 20.6 13.8 0.0 100.0 28 77.2 11.5 11.0 0.4 100.0 7,687 81.6 10.2 7.7 0.4 100.0 3,726 79.1 11.8 8.9 0.2 100.0 12,435 77.8 12.5 9.5 0.2 100.0 14,345 77.9 10.9 10.9 0.4 100.0 13,970 78.2 12.1 9.4 0.2 100.0 18,111 80.5 13.1 6.2 0.2 100.0 6,095 86.2 10.9 2.6 0.2 100.0 13,565 80.7 16.0 3.0 0.3 100.0 9,199 76.6 13.1 10.0 0.3 100.0 6,234 66.4 8.7 24.7 0.3 100.0 9,664 78.4 11.9 9.4 0.3 100.0 38,662 Note: Table includes only the two most recent births in the three years preceding the survey. Total includes 6, 39, 469, and 487 births with missing information on mother’s education, religion, caste/tribe, and the standard of living index, respectively, which are not shown separately. 1For current pregnancy, estimated maternal age at birth 2Includes current pregnancy, if any 125 Table 4.28 shows how the total wanted fertility rate varies by state. Total wanted fertility ranges from a very low level of 1.47 children per woman in Goa to 3.83 in Meghalaya. Among the major states, total wanted fertility is highest in Uttar Pradesh, at 2.83 children per woman. The difference between the total fertility rate and the total wanted fertility rate ranges from 0.15 child in Kerala to 1.21 children in Rajasthan. Besides Rajasthan, the difference is more than one child in Uttar Pradesh and Sikkim. Both the TFR and the wanted TFR decreased between NFHS-1 and NFHS-2, but the difference between the two rates has remained virtually unchanged. Table 4.27 Wanted fertility rates Total wanted fertility rate and total fertility rate for the three years preceding the survey by selected background characteristics, India, 1998–99 Background characteristic Total wanted fertility rate Total fertility rate Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 1.73 2.27 2.28 3.07 2.54 3.47 1.99 2.64 1.81 2.26 1.68 1.99 2.08 2.78 2.54 3.59 2.07 2.44 1.62 2.26 1.70 1.90 1.57 2.13 1.70 2.33 3.21 3.91 2.26 3.15 2.30 3.06 2.15 2.83 2.00 2.66 2.42 3.37 2.13 2.85 1.70 2.10 2.13 2.85 Note: Rates are based on births in the period 1–36 months preceding the survey to women age 15–49. The total fertility rates are the same as those presented in Table 4.4. Total includes women with missing information on education, religion, caste/tribe, and the standard of living index, who are not shown separately. 126 Table 4.28 Wanted fertility rates by state Total wanted fertility rate and total fertility rate for the three years preceding the survey by state, India, 1998–99 State Total wanted fertility rate Total fertility rate India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 2.13 2.85 1.72 2.40 2.10 2.88 1.50 2.14 1.74 2.71 1.55 2.21 2.57 3.78 2.40 3.31 2.83 3.99 2.58 3.49 1.90 2.46 1.78 2.29 1.74 2.52 1.75 2.31 2.50 3.04 3.83 4.57 2.66 2.89 2.98 3.77 1.65 2.75 1.47 1.77 2.08 2.72 1.87 2.52 1.88 2.25 1.56 2.13 1.81 1.96 1.71 2.19 Note: Rates are based on births in the period 1–36 months preceding the survey to women age 15–49. The total fertility rates are the same as those presented in Table 4.3. CHAPTER 5 FAMILY PLANNING The National Family Welfare Programme in India has traditionally sought ‘to promote responsible and planned parenthood through voluntary and free choice of family planning methods best suited to individual acceptors’ (Ministry of Health and Family Welfare, 1998a). In April 1996, the programme was renamed the Reproductive and Child Health Programme and given a new orientation to meet the health needs of women and children more completely. The programme now aims to cover all aspects of women’s reproductive health throughout their lives. With regard to family planning, the new approach emphasizes the target-free promotion of contraceptive use among eligible couples, the provision to couples of a choice of contraceptive methods (including condoms, oral pills, IUDs, and male and female sterilization), and the assurance of high-quality care. An important component of the programme is the encouragement of adequate spacing of births, with at least three years between births (Ministry of Health and Family Welfare, n.d.). The new National Population Policy, 2000, adopted by the Government of India has set as its immediate objective the task of addressing unmet need for contraception in order to achieve the medium-term objective of bringing the total fertility rate down to replacement level by the year 2010. One of the 14 national socio-demographic goals identified for this purpose is to achieve universal access to information/counselling and services for fertility regulation and contraception with a wide range of choices (Ministry of Health and Family Welfare, 2000). Information about knowledge and use of contraceptive methods provided in this chapter is designed to be of practical relevance to programme administrators and policymakers responsible for monitoring existing programmes and formulating new strategies to meet the health and family planning needs of the population. The chapter begins with an appraisal of women’s knowledge of contraceptive methods and then discusses women’s past and present use of contraception and sources of supply of modern contraceptive methods. Special attention is focused on reasons for discontinuation and nonuse of contraception and on intentions to use family planning methods in the future. The chapter also contains information on exposure to family planning messages through the media and on discussions about family planning with relatives and friends. 5.1 Knowledge of Family Planning Methods Lack of knowledge of contraceptive methods can be a major obstacle to their use. In NFHS-2, interviewers obtained information on knowledge and ever use of contraceptive methods by asking each respondent the following question: ‘Now I would like to talk about family planning—the various ways or methods that a couple can use to delay or avoid a pregnancy. For each method I mention, please tell me if you have ever heard of the method and whether you have ever used the method at any time in your life?’ If a respondent did not recognize the name of a method, a short description was read. In this way, the survey assesses women’s knowledge and ever use of seven contraceptive methods, namely the pill, condom, IUD, female sterilization, male sterilization, rhythm or safe-period method, and withdrawal. In addition, the survey 128 collected information on respondents’ knowledge and ever use of any other contraceptive methods (modern, traditional, or folkloric). Table 5.1 shows the extent of knowledge of contraceptive methods among currently married women by specific method and urban-rural residence. Knowledge of contraceptive methods is nearly universal in India, with 99 percent of currently married women recognizing at least one method of contraception and at least one modern method of contraception. Female sterilization is the most widely known method of contraception in India, followed by male sterilization. Overall, 98 percent of currently married women know about female sterilization and 89 percent know about male sterilization. There is little difference by residence in knowledge of female sterilization, but 94 percent of urban women know about male sterilization compared with 88 percent of rural women. Knowledge of the officially-sponsored spacing methods (pill, IUD, and condom) is much less widespread. The best-known spacing method is the pill, which is known by 80 percent of currently married women, followed by the condom and IUD (71 percent each). Although knowledge of these spacing methods is lower than knowledge of sterilization, the results indicate that knowledge of spacing methods has increased since NFHS-1. At the time of NFHS-1, only 66 percent of currently married women knew about the pill, 61 percent knew about IUDs, and 58 percent knew about condoms. There are large differences in knowledge of spacing methods by residence. Seventy-five percent of rural women know about pills compared with 92 percent of urban women. For IUDs and condoms, the corresponding proportions are 65 and 88 percent. Traditional methods of contraception are less well known than modern methods. Forty- nine percent of currently married women report knowledge of a traditional method, with the rhythm/safe period method being better known (45 percent) than withdrawal (31 percent). Knowledge of traditional methods is much higher in urban areas (60 percent) than in rural areas Table 5.1 Knowledge of contraceptive methods Percentage of currently married women who know any contraceptive method by specific method and residence, India, 1998–99 Method Urban Rural Total Any method Any modern method Pill IUD Condom Female sterilization Male sterilization Any traditional method Rhythm/safe period Withdrawal Other method1 Number of women 99.7 98.7 99.0 99.7 98.6 98.9 91.5 75.2 79.5 87.8 64.6 70.6 88.0 64.9 71.0 99.3 97.8 98.2 93.6 87.8 89.3 60.3 44.9 48.9 56.7 41.0 45.1 41.1 27.7 31.2 3.1 2.6 2.7 21,888 61,761 83,649 1Includes both modern and traditional methods that are not listed separately 129 (45 percent). Between NFHS-1 and NFHS-2, knowledge of traditional methods increased from 39 percent to 49 percent. Interstate Variations in Knowledge Interstate variations in knowledge of contraception are shown in Table 5.2. Knowledge of any method of contraception as well as any modern method is nearly universal in all states except Meghalaya and Nagaland, where the proportion of currently married women knowing any method or any modern method is 88 percent. Knowledge of female sterilization is also nearly universal, except in Meghalaya, where the proportion knowing the method is 79 percent, and Nagaland, where it is 83 percent. The proportion knowing about male sterilization ranges from 48 percent in Meghalaya to nearly 100 percent in Himachal Pradesh. States with less than 80 percent reporting knowledge of male sterilization are Meghalaya, Nagaland, Arunachal Pradesh, Karnataka, Goa, and Mizoram. There are wide variations among the states in the extent of knowledge of temporary modern methods. For pills the proportion with knowledge varies from 60 percent in Andhra Pradesh to 99 percent in Delhi. For IUDs it varies from 50 percent in Madhya Pradesh to 97 percent in Punjab. For condoms it varies from 48 percent in Andhra Pradesh to 97 percent in Delhi and Punjab. Knowledge of any traditional method exceeds 70 percent in Himachal Pradesh, Punjab, Kerala, Haryana, West Bengal, Delhi, and Sikkim. 5.2 Contraceptive Use Ever Use of Family Planning Methods NFHS-2 asked respondents if they had ever used each of the methods they knew about. Women who said they had not used any of the methods were asked further if they had ‘ever used anything or tried in any way to delay or avoid getting pregnant’. Table 5.3 presents the pattern of ever use of family planning methods for currently married women by age and residence. Although nearly all currently married women know at least one method of contraception, only 55 percent have ever used a method, up from 47 percent in NFHS-1. Forty-nine percent of currently married women have ever used a modern method, and 12 percent have ever used a traditional method. Ever use of any method is higher in urban areas (67 percent) than in rural areas (51 percent). Ever use of both modern methods and traditional methods is also higher in urban areas. The most commonly used method is female sterilization, which has been adopted by 34 percent of currently married women, compared with 2 percent who have adopted male sterilization. Six to 8 percent have ever used each modern spacing method (the pill, condom, or IUD). Ever use of each method of family planning is higher in urban than in rural areas, except for ever use of male sterilization, which shows almost no variation by place of residence. Ever use of IUDs and condoms is more than three times higher among urban women than among rural women. 130 Ever use of any modern method increases with women’s age up to age 35–39 (peaking at 67 percent) and declines at older ages. The increase in contraceptive use with age up to 35–39 reflects a life-cycle effect, with women increasingly adopting contraception as their fertility goals are met. Declining ever use of modern methods by older women reflects, at least in part, larger family size norms and lower levels of contraceptive prevalence in the past. The pattern of ever use by age is similar for urban and rural areas, although urban women are more likely to have used contraception than rural women at every age. Table 5.2 Knowledge of contraceptive methods by state Percentage of currently married women who know any contraceptive method by specific method and state, India, 1998–99 State Any method Any modern method Pill IUD Con- dom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 99.0 98.9 79.5 70.6 71.0 98.2 89.3 48.9 45.1 31.2 2.7 99.7 99.7 98.7 95.3 97.4 99.2 99.1 73.1 69.2 54.2 2.1 99.9 99.8 93.9 90.3 92.1 99.5 97.1 77.5 70.6 65.5 2.8 100.0 100.0 93.9 92.3 93.6 100.0 99.8 90.9 87.9 68.3 1.4 98.8 98.8 81.8 77.0 76.9 98.3 94.0 54.2 37.0 42.6 8.0 100.0 100.0 96.5 96.9 97.1 99.9 98.8 78.3 72.7 63.1 2.1 98.8 98.7 79.0 69.3 74.4 97.8 90.7 32.2 29.5 17.3 1.8 97.8 97.8 67.0 50.1 55.5 96.6 80.6 31.1 29.5 13.6 2.3 98.4 98.3 84.7 73.5 83.1 97.4 92.5 60.2 54.8 33.0 3.0 99.2 99.2 74.9 58.7 64.3 98.9 97.3 39.5 36.2 24.4 3.4 98.6 98.3 75.4 55.3 53.1 97.7 90.2 52.0 46.3 43.0 3.5 99.6 99.4 92.5 72.7 78.9 98.3 83.7 74.7 67.5 61.6 3.0 98.1 98.1 84.9 75.1 68.9 96.9 63.3 33.4 32.6 17.4 4.2 98.4 98.3 87.3 70.3 71.2 96.3 85.0 65.8 61.5 50.3 5.9 95.1 94.9 82.3 85.3 74.6 93.4 90.1 67.2 55.2 56.9 7.7 88.4 87.9 75.9 62.4 67.8 78.6 47.9 48.2 45.0 33.7 14.4 97.8 97.8 88.1 86.8 91.2 96.8 78.5 54.6 52.2 40.1 0.5 88.0 87.5 73.7 77.1 68.3 83.0 59.3 67.0 64.5 58.4 1.1 99.4 99.4 89.4 89.7 79.4 98.4 91.3 70.3 67.1 41.7 2.4 99.7 99.7 89.7 79.6 86.7 98.8 76.7 56.8 51.4 37.7 5.7 98.5 98.3 72.0 76.2 68.2 97.8 81.9 56.8 54.2 35.3 5.9 99.4 99.4 84.1 79.9 71.7 98.9 87.6 34.5 32.4 18.6 1.7 98.9 98.9 60.1 50.7 48.3 98.5 90.9 15.3 14.4 7.4 1.2 99.4 99.3 69.0 74.4 51.1 99.0 76.5 41.9 41.5 8.4 1.1 99.7 99.7 90.4 89.2 91.5 99.0 94.0 78.1 71.4 61.4 0.5 99.9 99.9 82.8 86.5 79.4 99.8 93.7 51.3 48.1 35.3 3.6 1Includes both modern and traditional methods that are not listed separately 131 Current Use of Family Planning Methods Table 5.4 and Figure 5.1 provide information on current use of family planning methods for currently married women in India. Forty-eight percent of currently married women were currently using some method of contraception at the time of the survey. This level compares with 83 percent for China and 62 percent for Asia as a whole (Population Reference Bureau, 2000). The NFHS-2 estimates of current use, both overall use and use of specific methods, are close to those obtained by the national Reproductive and Child Health Household Survey, which was carried out at about the same time (International Institute for Population Sciences, 2000). Table 5.3 Ever use of contraception Percentage of currently married women who have ever used any contraceptive method by specific method, according to age and residence, India, 1998–99 Age Any method Any modern method Pill IUD Condom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 Number of women URBAN 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 15.8 11.7 4.5 1.6 5.4 1.6 0.2 6.0 3.8 3.3 0.1 1,181 43.3 37.3 10.2 7.8 16.0 10.7 0.2 11.6 8.4 6.7 0.9 3,689 68.9 62.7 13.6 13.5 21.0 31.8 0.5 14.7 10.1 8.3 1.4 4,453 79.0 72.5 13.7 15.6 21.0 44.7 0.8 17.6 12.5 9.5 1.7 4,078 81.8 76.1 12.5 14.6 17.9 51.5 2.4 17.4 13.0 8.7 1.4 3,601 77.6 70.4 9.9 9.9 13.1 50.2 4.8 17.2 13.0 9.0 1.1 2,804 73.0 66.6 8.2 6.9 10.5 46.9 6.6 15.2 11.4 7.4 1.0 2,081 67.2 61.0 11.4 11.4 16.8 36.0 1.9 15.1 10.9 8.0 1.2 21,888 RURAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 13.0 7.6 3.4 0.6 2.9 1.5 0.0 6.8 4.7 3.7 0.1 6,833 32.9 26.2 7.8 2.8 5.2 14.1 0.2 10.5 7.5 5.3 0.4 12,241 53.5 47.5 9.2 4.8 6.4 34.2 0.7 11.6 8.6 5.9 1.0 12,602 64.8 59.4 9.7 5.5 6.1 46.7 1.3 12.1 9.4 5.5 1.4 10,208 68.3 63.4 7.7 4.4 4.7 51.6 3.1 11.3 8.7 5.1 1.4 8,451 66.8 61.8 5.6 2.4 2.8 51.1 5.3 10.5 8.3 4.8 1.3 6,559 61.2 56.1 4.2 1.7 2.1 43.0 9.0 9.1 7.0 3.9 1.6 4,867 50.8 45.2 7.4 3.5 4.8 33.5 2.1 10.6 7.9 5.1 1.0 61,761 TOTAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 13.4 8.2 3.6 0.7 3.3 1.5 0.0 6.7 4.6 3.6 0.1 8,014 35.3 28.8 8.3 3.9 7.7 13.3 0.2 10.8 7.7 5.6 0.5 15,930 57.5 51.5 10.4 7.1 10.2 33.5 0.7 12.4 9.0 6.5 1.1 17,055 68.9 63.1 10.8 8.4 10.4 46.1 1.1 13.7 10.3 6.7 1.4 14,286 72.3 67.2 9.1 7.5 8.6 51.6 2.9 13.1 9.9 6.2 1.4 12,052 70.0 64.4 6.9 4.6 5.9 50.8 5.1 12.5 9.7 6.0 1.2 9,363 64.7 59.2 5.4 3.2 4.6 44.2 8.3 10.9 8.3 5.0 1.4 6,948 55.1 49.3 8.4 5.6 7.9 34.2 2.0 11.8 8.7 5.9 1.0 83,649 1Includes both modern and traditional methods that are not listed separately Table 5.4 Current use of contraception Percent distribution of currently married women by contraceptive method currently used, according to age and residence, India, 1998–99 Age Any method Any modern method Pill IUD Condom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 Not using any method Total percent Number of women URBAN 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 9.9 7.4 2.1 1.1 2.5 1.6 0.2 2.5 1.3 1.2 0.0 90.1 100.0 1,181 31.7 26.0 3.7 4.1 7.4 10.7 0.2 5.3 2.8 2.5 0.4 68.3 100.0 3,689 58.0 51.2 3.9 5.4 9.7 31.8 0.4 6.4 3.7 2.8 0.3 42.0 100.0 4,453 71.4 63.2 3.0 4.6 10.2 44.6 0.7 7.9 4.5 3.4 0.4 28.6 100.0 4,078 75.3 66.9 2.1 3.3 7.8 51.5 2.2 8.2 5.0 3.2 0.2 24.7 100.0 3,601 70.8 61.9 1.4 1.6 4.0 50.2 4.6 8.6 5.1 3.5 0.3 29.2 100.0 2,804 60.7 56.0 0.4 0.6 1.7 46.9 6.4 4.6 2.7 1.9 0.2 39.3 100.0 2,081 58.2 51.2 2.7 3.5 7.2 36.0 1.8 6.7 3.9 2.8 0.3 41.8 100.0 21,888 RURAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 7.7 4.2 1.2 0.4 1.2 1.5 0.0 3.5 1.7 1.7 0.0 92.3 100.0 6,833 24.3 19.8 2.5 1.1 1.9 14.1 0.2 4.4 2.7 1.8 0.1 75.7 100.0 12,241 46.2 41.2 2.5 1.5 2.4 34.1 0.6 4.6 3.0 1.7 0.4 53.8 100.0 12,602 59.2 53.5 2.3 1.4 2.0 46.7 1.1 5.2 3.2 2.0 0.6 40.8 100.0 10,208 64.0 58.2 1.7 0.9 1.2 51.6 2.8 5.1 3.2 1.9 0.6 36.0 100.0 8,451 62.4 57.8 0.7 0.4 0.7 51.1 4.9 4.1 2.7 1.4 0.4 37.6 100.0 6,559 55.7 52.5 0.3 0.3 0.3 42.9 8.7 2.7 1.8 0.9 0.5 44.3 100.0 4,867 44.7 39.9 1.9 1.0 1.6 33.5 1.9 4.4 2.7 1.7 0.4 55.3 100.0 61,761 TOTAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 8.0 4.7 1.3 0.5 1.4 1.5 0.0 3.3 1.7 1.7 0.0 92.0 100.0 8,014 26.0 21.2 2.8 1.8 3.2 13.3 0.2 4.6 2.7 1.9 0.2 74.0 100.0 15,930 49.3 43.8 2.9 2.5 4.3 33.5 0.6 5.1 3.2 1.9 0.4 50.7 100.0 17,055 62.7 56.2 2.5 2.3 4.4 46.1 1.0 6.0 3.6 2.4 0.5 37.3 100.0 14,286 67.4 60.8 1.9 1.6 3.2 51.6 2.6 6.1 3.7 2.3 0.5 32.6 100.0 12,052 64.9 59.1 1.0 0.8 1.7 50.8 4.8 5.4 3.4 2.0 0.4 35.1 100.0 9,363 57.2 53.5 0.3 0.4 0.7 44.1 8.0 3.3 2.1 1.2 0.4 42.8 100.0 6,948 48.2 42.8 2.1 1.6 3.1 34.2 1.9 5.0 3.0 2.0 0.4 51.8 100.0 83,649 1Includes both modern and traditional methods that are not listed separately 133 Table 5.4 also shows that current use of any method is considerably higher in urban areas (58 percent) than in rural areas (45 percent). Country-wide, 87 percent of ever users of contraception are current users, and 89 percent of current users are using a modern method. Thirty-four percent of currently married women are sterilized, accounting for 71 percent of total current contraceptive prevalence. Only 2 percent of currently married women reported that their husbands are sterilized. Female sterilization and male sterilization together account for 75 percent of current contraceptive prevalence. No other individual method of family planning is used by more than 4 percent of currently married women. Less than 7 percent of currently married women are currently using any of the three officially-sponsored spacing methods. By residence, female and male sterilization together account for 65 percent of contraceptive prevalence in urban areas and 79 percent in rural areas. Current use of all modern methods except male sterilization is higher in urban areas than in rural areas, and the gap for condoms is especially wide (urban use is more than four times rural use). By age, current contraceptive use increases from 8 percent for women age 15–19 to a peak of 67 percent for women age 35–39 and then decreases for older women. The pattern of variation by age is similar in urban areas and rural areas. Figure 5.1 Current Use of Contraceptive Methods Condom 3% IUD 2%Pill 2% Not Using Any Method 52% Any Traditional Method/ Other Method 5% Male Sterilization 2% Female Sterilization 34% NFHS-2, India, 1998–99 134 Comparison of NFHS-2 results for current contraceptive use with NFHS-1 results reveals an 18 percent increase in contraceptive prevalence since NFHS-1, when prevalence was 41 percent (Figure 5.2). The share of female sterilization in contraceptive prevalence increased slightly from 67 to 71 percent over the period. Since the share of male sterilization declined from 9 to 4 percent, however, the share of female and male sterilization together remained almost the same in NFHS-1 and NFHS-2 at about 75 percent. In rural areas it remained about 80 percent, and in urban areas it remained at about 65 percent. The proportion of currently married women using the officially-sponsored spacing methods—pill, IUD, and condom—was 6 percent in NFHS-1 and 7 percent in NFHS-2, indicating almost no change between the two surveys. Current use of traditional methods increased slightly between the two surveys, from 4 percent of currently married women in NFHS-1 to 5 percent in NFHS-2. These results indicate that, despite the increased emphasis on contraceptive choice and on spacing methods in the Reproductive and Child Health Programme, female sterilization continues to dominate the method mix in India, and, despite improvement in the knowledge of spacing methods, spacing methods still account for only a small fraction of contraceptive use. Socioeconomic Differentials in Current Use of Family Planning Methods Table 5.5 shows differences in contraceptive use by background characteristics. Current contraceptive use among currently married women generally increases with education, from 43 Figure 5.2 Current Use of Family Planning by Residence NFHS-1 and NFHS-2 37 45 51 58 41 48 0 10 20 30 40 50 60 70 TOTAL NFHS-2 NFHS-1 URBAN AREAS NFHS-2 NFHS-1 RURAL AREAS NFHS-2 NFHS-1 Percent Sterilization Other methods India 135 percent among illiterate women to 57 percent among women with at least a high school education. There is, however, little difference in contraceptive use between literate women who have and have not completed middle school. In the case of spacing methods, use also tends to increase with education. Modern spacing methods account for 6 percent of contraceptive use by illiterate women and 35 percent of contraceptive use by women with at least a high school education. On the other hand, use of female sterilization declines sharply with education among literate women. Illiterate women, however, have a somewhat lower prevalence of sterilization than literate women who have not completed middle school. Female and male sterilization account for 85 percent of contraceptive use by illiterate women but only 48 percent of contraceptive use by women with at least a high school education. Contraceptive use increased between NFHS-1 and NFHS-2 among women of every educational level. The increase, however, was much more rapid among illiterate women than among literate women. Various studies based on NFHS-1 data have shown that even after controlling the effects of other factors, education is a key factor influencing contraceptive use (Retherford and Ramesh, 1996; Ramesh et al., 1996). By religion, contraceptive prevalence among Hindus (49 percent) is higher than among Muslims (37 percent) but lower than among women belonging to most other religions (52–65 percent). Use of the pill is highest among Muslims and Sikhs (4 percent), use of the IUD is highest among Sikhs (7 percent), and use of condoms is highest among Sikhs and Jains (10–12 percent). Male sterilization is rare for all religious groups except Buddhists/Neo-Buddhists. Use of female sterilization is lowest among Muslims (20 percent) and highest among Buddhists/Neo- Buddhists (53 percent). Since NFHS-1, contraceptive prevalence has increased for all religious groups, but the largest increases have been for Buddhists/Neo-Buddhists and Muslims. By caste/tribe, contraceptive prevalence is highest among women who do not belong to a scheduled caste, scheduled tribe, or other backward class (54 percent), followed by women belonging to other backward classes (47 percent), scheduled castes (45 percent), and scheduled tribes (39 percent). The use of male sterilization and each of the modern temporary methods is very low for all caste/tribe groups. By the standard of living index (SLI), contraceptive prevalence ranges from 40 percent among women living in households with a low SLI to 61 percent among women living in households with a high SLI. The use of officially-sponsored spacing methods is also much higher among women with a high SLI (16 percent) than among women with a medium (6 percent) or low SLI (3 percent). Table 5.5 also shows differences in current use by number and sex of living children. Contraceptive use increases sharply from 5 percent for women with no living children to 68 percent for women with three living children and then falls to 57 percent for women with four or more living children. A similar pattern is evident for female and male sterilization. The results also indicate strong preference for sons over daughters. At each parity, current use of family planning is lower among women with no sons than among women with one or more sons, with a maximum differential at parity 3. Son preference is not, however, an insuperable barrier to contraceptive use. At parities 2, 3, and 4+, the percentage of women with no sons who are currently using sterilization (female or male) is 23, 27, and 30 percent, respectively. An earlier study based on NFHS-1 data has shown that son preference is an important factor influencing contraceptive use in India and that the national contraceptive prevalence rate would be 5 percentage points higher if there were no son preference (Arnold et al., 1998). Table 5.5 Current use by background characteristics Percent distribution of currently married women by contraceptive method currently used, according to selected background characteristics, India, 1998–99 Background characteristic Any method Any modern method Pill IUD Con- dom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 Not using any method Total percent Number of women Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High 58.2 51.2 2.7 3.5 7.2 36.0 1.8 6.7 3.9 2.8 0.3 41.8 100.0 21,888 44.7 39.9 1.9 1.0 1.6 33.5 1.9 4.4 2.7 1.7 0.4 55.3 100.0 61,761 42.9 39.2 1.2 0.5 0.9 34.4 2.2 3.3 2.1 1.2 0.4 57.1 100.0 48,018 55.5 49.7 3.3 1.5 2.3 40.8 1.8 5.4 3.1 2.4 0.3 44.5 100.0 16,257 52.2 44.6 3.7 2.9 5.0 32.1 0.9 7.4 4.0 3.4 0.2 47.8 100.0 7,073 57.0 47.1 3.0 5.7 11.2 25.8 1.4 9.6 5.9 3.7 0.3 43.0 100.0 12,291 49.2 44.3 1.8 1.5 2.7 36.2 2.1 4.7 2.9 1.8 0.3 50.8 100.0 68,443 37.0 30.2 4.1 1.5 4.2 19.6 0.8 6.4 3.6 2.8 0.4 63.0 100.0 10,477 52.4 44.9 1.2 2.3 2.8 36.5 2.1 7.1 4.9 2.3 0.4 47.6 100.0 2,072 65.2 54.7 3.7 7.4 11.8 30.2 1.6 10.1 4.6 5.5 0.4 34.8 100.0 1,365 65.1 58.1 0.2 4.3 10.0 42.3 1.4 6.4 4.6 1.8 0.6 34.9 100.0 316 64.7 63.9 2.5 1.4 2.5 52.5 5.0 0.8 0.4 0.4 0.0 35.3 100.0 601 48.6 35.2 2.8 3.9 1.3 26.1 1.0 9.1 4.9 4.3 4.2 51.4 100.0 259 30.1 28.6 3.3 6.3 2.4 16.7 0.0 1.4 1.0 0.4 0.0 69.9 100.0 38 44.6 40.1 1.5 0.7 1.6 34.4 1.9 4.2 2.7 1.6 0.3 55.4 100.0 15,178 39.1 35.2 1.6 0.9 0.8 28.8 3.1 3.2 2.3 1.0 0.7 60.9 100.0 7,176 46.8 43.4 1.1 1.5 2.0 37.2 1.6 3.1 2.0 1.1 0.3 53.2 100.0 27,529 53.5 45.8 3.3 2.4 5.1 33.1 1.9 7.3 4.2 3.1 0.4 46.5 100.0 32,957 39.5 35.5 1.5 0.4 0.6 31.0 2.0 3.6 2.3 1.3 0.4 60.5 100.0 26,505 48.4 43.3 2.2 1.2 2.2 36.0 1.7 4.8 2.9 1.9 0.3 51.6 100.0 38,999 61.2 53.1 2.7 4.5 8.7 35.0 2.2 7.8 4.5 3.2 0.3 38.8 100.0 17,173 Contd… Table 5.5 Current use by background characteristics (contd.) Percent distribution of currently married women by contraceptive method currently used, according to selected background characteristics, India, 1998–99 Background characteristic Any method Any modern method Pill IUD Con- dom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 Not using any method Total percent Number of women Number and sex of living children No children 1 child 1 son No sons 2 children 2 sons 1 son No sons 3 children 3 sons 2 sons 1 son No sons 4+ children 2+ sons 1 son No sons Total 4.6 2.1 0.4 0.0 1.0 0.4 0.3 2.5 1.3 1.2 0.0 95.4 100.0 9,792 23.7 15.8 3.1 2.9 4.9 4.2 0.7 7.7 4.5 3.2 0.2 76.3 100.0 13,215 25.3 16.9 3.2 3.3 5.2 4.8 0.5 8.2 4.8 3.4 0.3 74.7 100.0 7,062 21.9 14.6 3.1 2.5 4.5 3.6 0.9 7.1 4.1 3.0 0.2 78.1 100.0 6,153 58.1 51.9 2.7 3.0 4.7 39.4 2.1 5.9 3.4 2.5 0.3 41.9 100.0 20,184 66.8 61.6 2.4 2.9 3.5 50.5 2.3 4.8 2.7 2.1 0.3 33.2 100.0 6,185 58.9 52.2 3.0 3.2 5.4 38.5 2.2 6.4 3.8 2.6 0.2 41.1 100.0 10,621 39.7 33.1 2.4 2.6 5.0 21.9 1.3 6.3 3.4 3.0 0.2 60.3 100.0 3,378 67.5 63.1 1.7 1.2 2.5 54.8 2.8 4.1 2.5 1.6 0.4 32.5 100.0 17,840 73.8 69.7 0.9 0.7 1.7 63.8 2.5 3.7 2.2 1.5 0.5 26.2 100.0 2,381 74.9 71.0 1.6 1.0 2.0 63.3 3.2 3.5 2.2 1.3 0.4 25.1 100.0 8,131 61.6 56.5 2.0 1.8 3.6 46.4 2.8 4.8 3.0 1.8 0.3 38.4 100.0 5,975 37.9 32.8 2.8 1.1 2.4 25.5 1.0 4.8 3.0 1.9 0.2 62.1 100.0 1,354 57.4 52.2 1.9 0.7 1.8 45.3 2.4 4.5 3.0 1.5 0.7 42.6 100.0 22,617 58.5 53.5 1.9 0.6 1.6 46.9 2.4 4.4 2.9 1.4 0.7 41.5 100.0 17,488 56.2 50.4 2.3 1.1 2.7 41.7 2.6 5.1 3.4 1.7 0.7 43.8 100.0 4,423 37.3 33.0 0.8 0.1 2.2 28.8 1.1 3.7 2.2 1.5 0.6 62.7 100.0 705 48.2 42.8 2.1 1.6 3.1 34.2 1.9 5.0 3.0 2.0 0.4 51.8 100.0 83,649 Note: Total includes 11, 77, 809, and 971 women with missing information on education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. 1Includes both modern and traditional methods that are not listed separately 138 Table 5.6, which classifies contraceptive use rates by both religion and education, sheds further light on religious differentials in contraceptive use. When contraceptive prevalence by religion is examined among women at the same educational level, it is seen that prevalence differentials by religion are still large. In other words, religion has a substantial effect on contraceptive use even after education is controlled by holding it constant. It is noteworthy that among literate women, use varies little by level of education for Hindus, Muslims, Sikhs, and Jains. Among literate women belonging to these religions, religion has a bigger effect on use than education does. Earlier studies based on analysis of NFHS-1 data also suggest that religion has a substantial effect on contraceptive use, even after controlling for education, and that Muslims have lower use rates than Hindus (Ramesh et al., 1996; Moulasha and Rama Rao, 1999). Interstate Variations in Current Use of Family Planning Methods Table 5.7 and Figure 5.3 show variations in the current use of contraception by state. The current use of any method among states varies widely from 20 percent in Meghalaya to 68 percent in Himachal Pradesh. Among the major states, Bihar and Uttar Pradesh have the lowest level of current use (25 and 28 percent, respectively), followed by Rajasthan (40 percent), Assam (43 percent), and Madhya Pradesh (44 percent). Low rates in these states have important implications for future population growth in India because these states together account for more than 40 percent of India’s population. Orissa and all the northeastern states except Mizoram and Sikkim also have current contraceptive use rates below the national average. Interestingly, Goa, which is at an advanced stage of fertility transition, has a current use rate very close to the national average, as was also the case in NFHS-1, suggesting that later-than-average marriage accounts for a substantial amount of Goa’s low fertility. The eight top-ranking states in current use are Himachal Pradesh, Punjab, West Bengal, Delhi, Kerala, Haryana, Maharashtra, and Andhra Pradesh (60–68 percent). When the rankings of states in NFHS-2 are compared with those in NFHS-1, it is seen that Andhra Pradesh, Haryana, Himachal Pradesh, Karnataka, and Nagaland have risen in relative rank, while Mizoram, Tamil Nadu, and Kerala have fallen. Sterilization continues to be the mainstay of the family planning programme in all except a few small northeastern states. The method mix in Andhra Pradesh continues to be highly skewed, with 96 percent of users sterilized, compared with 95 percent in NFHS-1. In all other southern states, as well as in Maharashtra, Madhya Pradesh, Bihar, and Rajasthan, 80–90 percent of users have adopted sterilization. At the other extreme are Delhi, Punjab, and the northeastern states (except Arunachal Pradesh and Mizoram), where sterilization accounts for 32–46 percent of current use. Table 5.6 Current use by religion and education Percentage of currently married women currently using any method, any modern method, and any modern temporary method of contraception, by religion and education, India 1998–99 Any method Any modern method1 Any modern temporary method2 Religion Illit- erate Literate, < middle school complete Middle school complete High school complete and above Illit- erate Literate, < middle school complete Middle school complete High school complete and above Illit- erate Literate, < middle school complete Middle school complete High school complete and above Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion 44.2 57.2 52.2 57.5 41.0 51.8 44.7 47.7 1.9 6.0 10.7 19.5 31.3 45.1 46.4 46.1 25.1 37.4 38.5 38.8 6.6 11.7 16.6 21.0 45.7 50.0 57.4 58.7 43.1 44.5 49.9 44.8 1.4 3.8 9.5 11.5 66.5 66.5 61.7 63.9 57.0 57.8 50.4 51.2 10.0 20.0 29.0 39.2 * 68.0 (64.2) 63.8 * 67.0 (61.7) 52.1 * 5.0 (10.3) 21.5 65.3 74.4 53.2 58.3 64.9 74.3 52.6 55.3 2.5 6.6 7.5 15.7 43.0 51.7 72.1 65.0 29.6 40.1 50.4 59.8 3.3 9.5 24.2 30.0 15.6 (17.3) * * 14.8 (13.3) * * 1.2 (8.1) * * ( ) Based on 25–49 unweighted cases *Percentage not shown; based on fewer than 25 unweighted cases 1Includes female sterilization, male sterilization, pill, IUD, and condom 2Includes the pill, IUD, and condom Table 5.7 Current use by state Percent distribution of currently married women by contraceptive method currently used, according to state and residence, India, 1998–99 State Any method Any modern method Pill IUD Condom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 Not using any method Total percent URBAN India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 58.2 51.2 2.7 3.5 7.2 36.0 1.8 6.7 3.9 2.8 0.3 41.8 100.0 64.0 56.4 4.0 6.2 18.2 25.7 2.3 7.3 4.8 2.5 0.3 36.0 100.0 67.2 53.4 2.3 5.9 14.8 28.0 2.5 13.5 5.9 7.5 0.2 32.8 100.0 74.3 63.9 1.5 6.3 17.8 34.1 4.1 10.4 5.6 4.8 0.0 25.7 100.0 68.0 59.7 3.2 4.1 9.6 37.5 5.4 7.9 2.0 5.9 0.5 32.0 100.0 71.8 54.0 3.1 8.8 23.2 17.9 0.9 17.6 8.1 9.5 0.2 28.2 100.0 50.4 46.9 2.4 2.1 7.6 33.0 1.9 2.9 1.9 1.0 0.5 49.6 100.0 55.2 52.5 2.0 2.1 8.1 37.9 2.3 2.5 1.4 1.1 0.2 44.8 100.0 44.8 36.6 2.3 2.6 12.6 18.0 1.0 7.3 4.3 2.9 0.9 55.2 100.0 38.9 35.4 2.9 1.2 3.0 26.6 1.7 3.2 1.5 1.7 0.3 61.1 100.0 54.0 45.2 6.4 3.0 3.0 30.9 1.8 7.6 5.0 2.6 1.2 46.0 100.0 73.4 46.4 9.1 2.0 7.1 27.0 1.2 26.6 11.6 15.1 0.4 26.6 100.0 47.3 42.7 9.2 4.6 1.5 27.5 0.0 4.6 3.8 0.8 0.0 52.7 100.0 53.4 30.6 6.0 1.9 4.5 17.9 0.3 22.2 13.0 9.3 0.6 46.6 100.0 44.9 31.4 2.6 8.0 2.1 17.5 1.1 13.5 8.1 5.4 0.0 55.1 100.0 45.3 38.9 5.9 8.9 3.5 20.6 0.0 6.4 6.4 0.0 0.0 54.7 100.0 65.1 64.7 6.4 6.4 1.3 50.6 0.0 0.4 0.4 0.0 0.0 34.9 100.0 46.7 37.8 3.8 10.0 4.4 19.6 0.0 9.0 7.7 1.2 0.0 53.3 100.0 56.8 47.2 7.2 5.6 3.2 31.2 0.0 9.6 8.0 1.6 0.0 43.2 100.0 52.7 39.4 0.8 2.2 7.0 28.7 0.7 12.2 7.2 5.0 1.1 47.3 100.0 61.8 53.3 2.2 5.1 6.4 37.6 2.0 8.3 6.8 1.4 0.2 38.2 100.0 58.5 56.7 2.5 3.5 5.6 43.6 1.5 1.7 1.4 0.3 0.1 41.5 100.0 63.4 62.3 1.4 1.6 1.8 52.4 5.0 1.0 1.0 0.0 0.1 36.6 100.0 59.9 56.4 1.0 5.0 2.4 47.1 0.9 3.4 3.1 0.3 0.1 40.1 100.0 65.5 57.4 0.2 1.6 4.4 48.5 2.7 8.1 3.8 4.3 0.0 34.5 100.0 58.2 55.1 0.4 5.0 3.1 46.0 0.6 3.0 2.2 0.9 0.0 41.8 100.0 Table 5.7 Current use by state (contd.) Percent distribution of currently married women by contraceptive method currently used, according to state and residence, India, 1998–99 State Any method Any modern method Pill IUD Condom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 Not using any method Total percent RURAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 44.7 39.9 1.9 1.0 1.6 33.5 1.9 4.4 2.7 1.7 0.4 55.3 100.0 60.8 55.5 4.8 5.8 9.6 32.7 2.6 5.2 1.6 3.7 0.0 39.2 100.0 60.4 53.1 2.0 2.6 3.4 43.0 2.0 7.0 3.9 3.1 0.4 39.6 100.0 67.0 60.5 1.3 1.6 3.7 46.1 7.6 6.4 4.2 2.2 0.2 33.0 100.0 43.9 36.8 3.3 2.7 3.5 25.3 2.0 6.5 1.8 4.7 0.6 56.1 100.0 64.4 53.8 3.1 4.9 9.5 34.3 1.9 10.1 5.3 4.8 0.5 35.6 100.0 37.1 35.3 1.2 0.9 1.7 30.1 1.3 1.6 1.2 0.4 0.2 62.9 100.0 40.7 39.3 0.6 0.4 1.1 35.0 2.2 1.0 0.8 0.2 0.3 59.3 100.0 23.9 18.3 1.0 0.6 2.1 14.1 0.6 5.3 4.0 1.3 0.3 76.1 100.0 22.9 20.9 0.8 0.4 0.4 18.3 0.9 1.4 0.8 0.6 0.6 77.1 100.0 45.9 39.7 2.6 0.5 0.7 34.2 1.7 5.4 3.7 1.7 0.8 54.1 100.0 64.5 47.5 9.2 1.2 1.6 33.5 2.0 15.9 7.8 8.1 1.0 35.5 100.0 33.3 31.0 6.9 4.1 0.5 19.3 0.1 2.0 1.0 0.9 0.3 66.7 100.0 42.3 26.3 6.3 1.9 1.5 15.5 1.1 15.2 10.9 4.3 0.9 57.7 100.0 35.6 23.1 2.0 6.2 0.9 12.8 1.1 12.2 5.7 6.5 0.2 64.4 100.0 13.8 9.5 4.1 1.9 0.7 2.9 0.0 3.6 2.2 1.4 0.6 86.2 100.0 49.7 48.7 4.3 4.3 0.5 39.4 0.2 1.0 1.0 0.0 0.0 50.3 100.0 26.1 20.9 2.2 7.1 1.1 10.5 0.0 5.1 3.6 1.5 0.2 73.9 100.0 53.3 40.4 9.9 5.6 1.2 20.9 2.8 12.7 10.5 2.2 0.2 46.7 100.0 43.9 33.4 1.0 1.7 3.4 27.2 0.1 8.9 4.8 4.2 1.6 56.1 100.0 57.0 53.3 1.0 1.6 1.3 47.0 2.4 3.6 3.2 0.4 0.0 43.0 100.0 62.7 62.1 1.2 0.8 2.9 51.9 5.3 0.4 0.2 0.2 0.1 37.3 100.0 58.3 57.8 0.3 0.3 0.3 52.8 4.1 0.3 0.2 0.1 0.3 41.7 100.0 57.4 56.6 0.4 1.5 0.3 53.9 0.5 0.7 0.6 0.1 0.1 42.6 100.0 63.2 55.7 0.5 1.6 2.6 48.6 2.4 7.5 3.8 3.6 0.0 36.8 100.0 48.8 47.6 0.3 1.1 0.7 44.7 0.9 1.1 0.8 0.3 0.1 51.2 100.0 Table 5.7 Current use by state (contd.) Percent distribution of currently married women by contraceptive method currently used, according to state and residence, India, 1998–99 State Any method Any modern method Pill IUD Condom Female ster- ilization Male ster- ilization Any traditional method Rhythm/ safe period With- drawal Other method1 Not using any method Total percent TOTAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 48.2 42.8 2.1 1.6 3.1 34.2 1.9 5.0 3.0 2.0 0.4 51.8 100.0 63.8 56.3 4.0 6.2 17.5 26.3 2.3 7.1 4.5 2.6 0.3 36.2 100.0 62.4 53.2 2.1 3.6 6.8 38.7 2.1 8.9 4.5 4.4 0.3 37.6 100.0 67.7 60.8 1.3 2.1 5.0 45.1 7.3 6.8 4.4 2.4 0.2 32.3 100.0 49.1 41.7 3.3 3.0 4.8 28.0 2.7 6.8 1.8 4.9 0.6 50.9 100.0 66.7 53.8 3.1 6.1 13.8 29.3 1.6 12.4 6.2 6.3 0.4 33.3 100.0 40.3 38.1 1.5 1.2 3.1 30.8 1.5 1.9 1.3 0.6 0.3 59.7 100.0 44.3 42.6 1.0 0.8 2.9 35.7 2.2 1.4 1.0 0.4 0.3 55.7 100.0 28.1 22.0 1.2 1.0 4.2 14.9 0.7 5.7 4.1 1.6 0.4 71.9 100.0 24.5 22.4 1.0 0.5 0.7 19.2 1.0 1.6 0.9 0.7 0.5 75.5 100.0 46.8 40.3 3.0 0.8 0.9 33.9 1.7 5.6 3.8 1.8 0.9 53.2 100.0 66.6 47.3 9.2 1.4 2.9 32.0 1.8 18.5 8.7 9.8 0.9 33.4 100.0 35.4 32.8 7.3 4.2 0.7 20.6 0.1 2.4 1.5 0.9 0.3 64.6 100.0 43.3 26.6 6.3 1.9 1.8 15.7 1.0 15.8 11.1 4.7 0.8 56.7 100.0 38.7 25.9 2.2 6.8 1.3 14.4 1.1 12.7 6.5 6.1 0.2 61.3 100.0 20.2 15.5 4.5 3.3 1.3 6.5 0.0 4.2 3.1 1.1 0.5 79.8 100.0 57.7 57.1 5.4 5.4 0.9 45.2 0.1 0.7 0.7 0.0 0.0 42.3 100.0 30.3 24.2 2.5 7.7 1.8 12.3 0.0 5.9 4.5 1.4 0.1 69.7 100.0 53.8 41.4 9.5 5.6 1.5 22.4 2.4 12.3 10.1 2.1 0.2 46.2 100.0 47.5 35.9 0.9 1.9 4.9 27.8 0.4 10.3 5.8 4.5 1.4 52.5 100.0 59.0 53.3 1.5 3.1 3.5 43.0 2.3 5.6 4.8 0.8 0.1 41.0 100.0 60.9 59.9 1.7 1.9 4.0 48.5 3.7 1.0 0.7 0.3 0.1 39.1 100.0 59.6 58.9 0.5 0.6 0.7 52.7 4.3 0.5 0.4 0.1 0.2 40.4 100.0 58.3 56.5 0.6 2.8 1.0 51.5 0.7 1.7 1.5 0.2 0.1 41.7 100.0 63.7 56.1 0.4 1.6 3.1 48.5 2.5 7.6 3.8 3.8 0.0 36.3 100.0 52.1 50.3 0.3 2.5 1.5 45.2 0.8 1.8 1.3 0.5 0.1 47.9 100.0 1Includes both modern and traditional methods that are not listed separately 143 Modern temporary methods of contraception are most prevalent in Delhi, Punjab, West Bengal, Haryana, Jammu and Kashmir, and the northeastern states. Their use among currently married women in these states ranges from 9 to 28 percent. About one-quarter of currently married women in Punjab and Delhi use modern temporary methods, accounting for 34 and 43 percent of current use in these states, respectively. Although the level of use of modern temporary methods is about the same (2–6 percent of currently married women) in the four better-performing southern states (Kerala, Andhra Pradesh, Karnataka, and Tamil Nadu) and the five large poor-performing states (Bihar, Uttar Pradesh, Rajasthan, Madhya Pradesh, and Orissa), use of these methods constitutes only 3–8 percent of current use in the southern states while in the other group it accounts for 9–23 percent of current use. In Uttar Pradesh, about one out of every four users uses a modern temporary method. Traditional methods are used most in West Bengal, Assam, Manipur, Punjab, Sikkim, and Goa, where 10–19 percent of currently married women use a traditional method. Traditional methods account for 19–36 percent of current use in these states. About one-third of users in Assam and Manipur use traditional methods. Since NFHS-1, use of traditional methods has Figure 5.3 Current Use of Family Planning by State 0 10 20 30 40 50 60 70 80 H im acha l P radesh P unjab W est B enga l De lh i K era la Ha ryana M aharashtra A ndhra P radesh G ujara t K arnataka M izo ram S ikk im Tam il N adu Jam m u & K ashm ir INDIA G oa O rissa M adhya P radesh A ssam Ra jasthan M anipur A runacha l P radesh Nagaland Uttar P radesh B ihar M eghalaya P ercent NFHS-2, India, 1998–99 144 increased most (by 5–6 percentage points) in Nagaland and Punjab, but declined substantially in Assam (from 22 to 16 percent). The rhythm method is most prevalent in Assam and Sikkim, where it is used by 10–11 percent of currently married women, and withdrawal is most prevalent in West Bengal, where it is used by 10 percent of currently married women. There are considerable urban-rural differentials in current use in almost all states. Maharashtra is the only state where prevalence is higher in rural areas (63 percent) than in urban areas (59 percent), and the gap has widened slightly since NFHS-1. Urban-rural differentials are small in Sikkim and all the southern and western states except Goa and Tamil Nadu. They are large in Meghalaya, Jammu and Kashmir, Uttar Pradesh, and Nagaland. Number of Living Children at First Use of Contraception In order to examine the timing of initial family planning use, NFHS-2 included a question on how many living children women had when they first used a method. Table 5.8 shows the distribution of ever-married women by the number of living children at the time of first contraceptive use, according to current age and residence. Only 4 percent of ever-married women (7 percent of ever-married women who have ever used contraception) began using contraception when they did not have any children, and another 10 percent (19 percent of ever users) began using when they had one living child. Although early use of contraception is rare, 39 percent of ever-married women (73 percent of ever users) began when they had three or fewer living children. This pattern of first acceptance at low parities means that family planning has a larger demographic impact than it would if contraceptive use were initiated later. A similar age pattern is observed among women in urban and rural areas, but urban users are more likely than rural users to begin using when they have two or fewer living children. Fifty-nine percent of urban users and 44 percent of rural users start using contraception when they have two or fewer children. Because of the dominance of sterilization in the contraceptive mix, women usually begin contraceptive use only after achieving their desired family size. Clearly, spacing methods need to be promoted if reductions are sought in the parity at which women first accept contraception. Problems with Current Method Women who were using a contraceptive method were asked if they had experienced any problem with their current method. Table 5.9 presents the percentage of current contraceptive users who report specific problems. Overall, four out of every five current users report having no problem with their method. This may be an underestimate of the extent of problems, however, because women who have experienced problems with spacing methods may have stopped using contraception altogether, and these women are not represented in the table. 145 The analysis of method-specific problems reveals that 75 percent of sterilized women and 87 percent of women whose husbands are sterilized report having no problem with their method. The most common problems experienced by sterilized women are headache, bodyache, or backache (13 percent), abdominal pain (8 percent), weakness or tiredness (7 percent), and white discharge (4 percent). Among women whose husbands are sterilized and who report problems with this method, the two most common complaints are headache, bodyache, or backache and weakness or tiredness. These results point to a continuing need to strengthen post-operative care and counselling for sterilization acceptors. The two most common problems reported by pill users are weakness/tiredness and headache/bodyache/backache. Too much bleeding, abdominal pain, and headache/bodyache/backache are reported as problems by 5–6 percent of IUD users. Table 5.8 Number of living children at first use Percent distribution of ever-married women by number of living children at the time of first use of contraception, according to current age and residence, India, 1998–99 Number of living children at the time of first use Current age Never used 0 1 2 3 4+ Missing Total percent Number of women URBAN 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 84.5 6.3 6.8 2.0 0.1 0.2 0.1 100.0 1,201 57.4 8.9 17.6 11.1 3.9 1.2 0.0 100.0 3,779 32.4 7.3 22.4 19.2 12.8 5.7 0.0 100.0 4,620 23.0 4.9 21.4 19.8 17.4 13.5 0.0 100.0 4,274 21.1 3.5 16.7 18.9 18.2 21.6 0.0 100.0 3,888 25.7 2.9 13.1 16.2 16.9 25.2 0.0 100.0 3,135 30.6 2.5 12.0 12.4 15.0 27.4 0.1 100.0 2,473 34.4 5.3 17.3 16.0 13.3 13.7 0.0 100.0 23,370 RURAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 87.2 6.4 4.4 1.7 0.3 0.0 0.0 100.0 6,981 67.6 4.5 10.7 10.5 5.2 1.4 0.0 100.0 12,610 47.6 3.1 10.4 15.9 14.2 8.7 0.0 100.0 13,124 36.7 2.1 8.7 15.1 18.4 19.0 0.1 100.0 10,820 34.4 1.5 6.9 13.1 18.4 25.6 0.0 100.0 9,201 35.8 1.1 4.8 9.3 16.6 32.3 0.1 100.0 7,387 42.3 1.0 3.8 7.3 12.9 32.6 0.0 100.0 5,706 50.2 2.9 7.8 11.4 12.4 15.2 0.0 100.0 65,829 TOTAL 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Total 86.8 6.4 4.7 1.8 0.2 0.0 0.0 100.0 8,182 65.2 5.5 12.3 10.7 4.9 1.4 0.0 100.0 16,389 43.7 4.2 13.5 16.8 13.9 7.9 0.0 100.0 17,745 32.8 2.9 12.3 16.4 18.1 17.5 0.0 100.0 15,094 30.5 2.1 9.8 14.9 18.4 24.4 0.0 100.0 13,089 32.8 1.6 7.3 11.4 16.7 30.2 0.1 100.0 10,521 38.8 1.5 6.3 8.9 13.6 31.0 0.0 100.0 8,179 46.1 3.6 10.3 12.6 12.7 14.8 0.0 100.0 89,199 146 5.3 Sterilization Timing of Sterilization Table 5.10 shows how many years before the survey women or their husbands were sterilized and how old the women were when the sterilization took place. Of 30,167 sterilizations reported, 95 percent are female sterilizations. Thirty-eight percent of female sterilizations took place less than 6 years before the survey, another 22 percent took place 6–9 years before the survey, and the remaining 40 percent took place 10 or more years before the survey. By contrast, 75 percent of male sterilizations took place 10 or more years before the survey. The median age of the wife at the time of sterilization was 25.7 years, with 44 percent of sterilized couples undergoing sterilization before the wife was age 25. Seventy-nine percent of sterilizations took place before the wife was age 30, and less than 1 percent took place when the wife was in her forties. Table 5.9 Problems with current method Percentage of current users of specific contraceptive methods who have had problems in using the method, India, 1998–99 Contraceptive method Problem Pill IUD Condom Female steri- lization Male steri- lization Rhythm/ safe period With- drawal Other methods1 Total No problem Weight gain Weight loss Too much bleeding Hypertension Headache/bodyache/ backache Nausea/vomiting No menstruation Weakness/tiredness Dizziness Fever Cramps Spotting Inconvenient to use Abdominal pain White discharge Irregular periods Breast tenderness Allergy Reduced sexual satisfaction Other Number of users 82.8 81.5 97.1 75.4 87.2 99.4 98.5 91.7 80.3 0.8 1.3 0.2 1.1 0.3 0.1 0.0 0.0 0.9 1.0 1.0 0.0 1.2 1.1 0.0 0.0 0.0 0.9 1.5 5.8 0.1 2.4 0.5 0.0 0.0 1.0 2.0 0.7 0.1 0.0 0.3 0.1 0.0 0.2 0.8 0.3 5.5 4.7 0.3 12.7 6.3 0.1 0.2 2.4 9.7 1.6 0.2 0.0 0.7 0.3 0.0 0.1 0.7 0.6 0.4 0.3 0.0 0.2 0.0 0.0 0.0 0.0 0.2 6.2 3.1 0.3 7.0 4.6 0.1 0.6 3.6 5.6 2.1 1.0 0.0 1.3 0.4 0.0 0.1 1.0 1.1 1.2 0.2 0.0 1.7 0.6 0.0 0.0 1.8 1.3 0.8 0.5 0.1 0.9 0.2 0.0 0.0 0.6 0.7 0.1 0.4 0.0 0.2 0.0 0.0 0.0 0.0 0.1 0.0 0.2 0.3 0.1 0.0 0.0 0.0 0.0 0.1 1.5 4.9 0.2 7.6 1.9 0.1 0.3 1.7 5.7 0.6 2.7 0.5 4.0 0.3 0.1 0.2 2.7 3.0 1.7 2.4 0.2 2.0 0.1 0.2 0.0 0.8 1.6 0.1 0.2 0.0 0.3 0.1 0.0 0.0 0.0 0.2 0.5 0.4 0.8 0.4 0.3 0.0 0.0 0.0 0.4 0.0 0.1 0.3 0.1 0.1 0.1 0.5 0.0 0.1 1.2 0.4 0.3 2.2 1.6 0.0 0.3 0.5 1.7 1,735 1,371 2,568 28,580 1,587 2,526 1,664 296 40,327 Note: Percentages add to more than 100.0 because multiple problems could be recorded. 1Includes both modern and traditional methods that are not listed separately 147 Male sterilization is not as common as it was 10 or more years ago. Only 2 percent of sterilizations during the 10 years preceding the survey were male sterilizations, compared with 10 percent of sterilizations 10 or more years before the survey. The median age of women at the time of sterilization has declined marginally, from age 26.1 during the period 8–9 years before the survey to age 25.7 in more recent years. From NFHS-2 data it is not possible to assess the trend in the median age at sterilization for more than 10 years before the survey because only women age 15–49 years were interviewed. Women in their forties 10 or more years before the survey would have been 50–59 years at the time of the survey and would therefore not have been interviewed. A comparison with NFHS-1 data, however, suggests that the decline in women’s age at sterilization began more than 10 years ago. Women’s median age at sterilization declined by one and one-half years between about 1983–84 (8–9 years before NFHS-1) and the mid-to-late 1990s. Table 5.10 Timing of sterilization Percent distribution of currently married, sterilized women and wives of sterilized men by age at the time of sterilization, and median age of the woman at the time of sterilization, according to the number of years since sterilization, India, 1998–99 Woman’s age at the time of sterilization Years since sterilization < 20 20–24 25–29 30–34 35–39 40–44 45–49 Total percent Number sterilized Median age1 STERILIZED WOMEN < 2 2–3 4–5 6–7 8–9 10+ Total 6.3 37.2 34.4 14.9 5.4 1.5 0.4 100.0 3,615 25.7 6.4 37.1 34.5 16.2 4.4 1.2 0.1 100.0 3,430 25.7 7.3 37.2 32.8 16.2 5.1 1.4 0.0 100.0 3,894 25.6 8.3 36.0 32.2 16.8 5.6 1.0 U 100.0 3,277 25.7 7.8 34.9 35.0 16.2 5.6 0.4 U 100.0 3,050 26.0 7.4 36.0 38.1 16.0 2.5 U U 100.0 11,315 NC 7.3 36.3 35.5 16.0 4.1 0.7 0.1 100.0 28,580 25.7 WIVES OF STERILIZED MEN < 10 10+ Total 4.9 25.9 27.9 20.4 16.2 3.8 U 100.0 394 27.8 10.0 35.6 39.4 13.1 2.0 U U 100.0 1,193 NC 8.7 33.2 36.5 14.9 5.5 0.9 0.2 100.0 1,587 25.8 STERILIZED WOMEN AND WIVES OF STERILIZED MEN < 2 2–3 4–5 6–7 8–9 10+ Total 6.3 36.8 34.4 14.8 5.6 1.5 0.5 100.0 3,687 25.7 6.3 37.0 34.4 16.2 4.7 1.3 0.1 100.0 3,484 25.7 7.2 37.2 32.6 16.3 5.2 1.5 0.0 100.0 3,958 25.6 8.3 35.6 32.1 17.1 5.9 1.1 U 100.0 3,362 25.8 7.8 34.6 34.7 16.4 6.0 0.4 U 100.0 3,168 26.1 7.6 36.0 38.2 15.8 2.4 U U 100.0 12,508 NC 7.3 36.2 35.5 16.0 4.2 0.7 0.1 100.0 30,167 25.7 NC: Not calculated due to censoring U: Not available 1To avoid censoring, median age is calculated only for sterilizations that took place when the woman was less than 40 years old. 148 Interstate Variations in Timing of Sterilization Table 5.11 shows state differentials in the median age of currently married, sterilized women and wives of sterilized men at the time of sterilization by the number of years since the operation. The median age varies from a low of 23.6 years in Andhra Pradesh to a high of 30.5 in Manipur. Among major states, the highest median age is 28.3 in Uttar Pradesh. The median age is relatively low in the southern states, except Kerala, and in West Bengal and Maharashtra. According to Table 5.11, in recent years the largest declines in the median age at sterilization Table 5.11 Timing of sterilization by state Median age of currently married, sterilized women and wives of sterilized men at the time of sterilization by number of years since sterilization, according to state, India, 1998–99 Years since sterilization State <2 2–3 4–5 6–7 8–9 Total India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 25.7 25.7 25.6 25.8 26.1 25.7 29.0 28.9 29.1 27.7 27.7 27.8 26.4 25.6 26.4 26.3 26.6 26.5 26.2 25.4 25.9 26.0 25.8 26.2 29.8 29.2 28.4 27.9 28.2 28.2 26.6 27.3 27.0 27.2 26.8 27.1 26.6 27.1 26.6 27.2 27.1 27.0 26.6 26.2 26.7 26.4 26.9 26.4 27.9 28.0 27.9 28.9 29.6 28.3 27.5 27.8 27.0 28.1 28.3 27.7 27.2 26.4 26.3 26.0 26.3 26.3 24.7 25.0 25.4 25.4 25.5 25.1 * (26.8) (26.2) (26.8) * 26.2 (28.4) 27.0 25.7 27.4 26.7 26.7 * * * * * 30.5 * * * * * 28.6 29.7 29.6 30.4 29.7 (28.2) 29.3 * * * * * 29.0 (25.9) (26.1) * (27.8) (26.1) 26.7 (29.8) (27.8) (29.5) (29.0) * 28.5 26.3 26.6 26.5 27.1 27.0 26.5 25.3 25.1 24.8 24.7 24.6 25.0 23.5 22.9 23.2 23.3 24.2 23.6 23.9 23.9 24.0 23.8 23.9 24.2 27.4 27.1 26.6 26.4 26.1 26.4 25.3 25.8 24.8 25.3 24.9 25.3 Note: Medians are not shown for persons sterilized 10 or more years before the survey, and median ages are calculated only for persons sterilized at less than age 40 to avoid problems of censoring. ( ) Based on 25–49 unweighted cases *Median not shown; based on fewer than 25 unweighted cases 149 (calculated as the difference between columns 1 and 5) occurred in Uttar Pradesh, Bihar, and West Bengal. During the same period, the median age increased in almost half the states. Methods Used before Sterilization Because sterilization is a terminal method, it is essential for policymakers to know whether couples use any temporary methods before they finally adopt sterilization. Table 5.12 shows that, in India as a whole, 82 percent of sterilization users never used any other method before sterilization, the same percentage as in NFHS-1. Six percent each used the pill or rhythm method before sterilization, while 5 percent each used the IUD or condom. The extent of prior use of temporary methods before sterilization is substantial in Sikkim (53 percent), Manipur and Kerala (42–43 percent), and West Bengal (40 percent). It is lowest in Andhra Pradesh and Bihar (6–8 percent). Prior use of the pill by 10 percent or more of sterilized couples is found in Sikkim, West Bengal, Manipur, and Jammu and Kashmir. Prior use of the IUD by 10 percent or more of sterilized couples is found in Manipur, Sikkim, Delhi, Mizoram, Kerala, and Goa. Condoms were previously used by 10 percent or more of sterilized couples in Delhi, Punjab, Kerala, and Jammu and Kashmir. 5.4 Sources of Contraceptive Methods Family planning methods and services in India are provided primarily through a network of government hospitals and urban family welfare centres in urban areas and Primary Health Centres (PHC) and sub-centres in rural areas. Family planning services are also provided by private hospitals and clinics, as well as nongovernmental organizations (NGOs). Sterilizations and IUD insertions are carried out mostly in government hospitals and PHCs. Sterilization camps, organized from time to time, also provide sterilization services. Modern spacing methods such as the IUD, pill, and condom are available through both the government and private sectors. It is expected that since levels of urbanization and education in India are rapidly increasing, reliance on private sector family planning services is likely to expand in the future (Nair et al., 1999). To assess the relative importance of various sources of contraceptive methods, NFHS-2 included a question on where current contraceptive users obtained their methods. Table 5.13 and Figure 5.4 show the percent distribution of current modern contraceptive users by the most recent source, according to specific method and residence. The public medical sector, consisting of government/municipal hospitals, government dispensaries, Primary Health Centres, and other governmental health infrastructure, is the source of contraception for 76 percent of current users of modern methods, down from 79 percent in NFHS-1. The role of the private medical sector, including private hospitals or clinics, private doctors, private mobile clinics, private paramedics, vaidyas, hakims, homeopaths, traditional birth attendants, and pharmacies or drugstores, as the source for current users has increased marginally from 15 percent in NFHS-1 to 17 percent in NFHS-2. Five percent of current users obtain their methods from other sources such as shops, friends, and relatives, and 1 percent from NGOs. Government/municipal hospitals are the main source (53 percent) for female sterilization, followed by community health centres, rural hospitals, or Primary Health Centres (22 percent), and private hospitals or clinics (12 percent). Government hospitals, community health centres, and Primary Health Centres are the source for 75 percent of male sterilizations. In contrast, private shops and pharmacies/drugstores are the main source for condoms (68 percent) and pills (62 percent). 150 Table 5.12 Methods used before sterilization by state Percentage of sterilized persons who used specific contraceptive methods before sterilization by state, India, 1998–99 Method used before sterilization State None Pill IUD Condom Rhythm/ safe period With- drawal Other method1 India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 81.9 5.8 5.1 4.7 5.5 3.1 0.6 62.0 8.4 13.2 20.0 8.0 5.8 0.3 81.2 5.1 4.0 5.3 6.7 4.2 0.2 70.7 4.2 5.4 7.4 14.8 4.4 0.2 69.6 10.1 8.6 11.0 5.5 9.0 1.3 66.8 6.6 8.6 14.0 8.1 4.7 0.1 84.9 4.5 4.9 5.9 4.3 2.7 0.1 85.5 5.8 4.0 4.7 4.0 1.2 0.6 82.3 5.4 5.0 6.9 5.0 2.1 0.2 92.5 2.7 0.8 1.9 2.5 1.3 0.2 85.7 5.8 3.4 1.8 4.3 3.4 0.4 59.6 16.5 4.5 5.0 18.3 11.1 0.7 83.7 9.8 5.8 1.4 0.8 1.2 0.0 74.9 7.7 1.9 2.7 11.5 9.5 0.5 56.6 12.3 24.2 9.9 14.9 11.4 0.5 85.5 7.0 3.8 0.0 3.7 0.0 0.0 79.7 9.9 12.4 1.7 0.5 0.0 0.2 82.7 3.1 9.1 0.0 5.1 3.1 0.0 47.2 21.6 18.2 4.4 23.0 8.6 0.0 72.8 8.3 10.0 7.1 5.9 3.7 0.3 75.9 5.9 7.5 4.1 12.7 4.5 2.0 82.8 6.7 5.9 7.0 1.9 0.7 0.1 94.4 2.9 2.0 1.5 0.5 0.2 0.3 90.0 2.9 5.6 1.4 1.9 0.3 0.3 57.9 5.0 11.9 11.8 17.8 14.5 0.2 87.8 4.2 7.1 1.2 0.8 0.7 2.9 Note: Percentages may add to more than 100.0 because all prior methods are included. 1Includes both modern and traditional methods that are not listed separately 151 Table 5.13 Source of modern contraceptive methods Percent distribution of current users of modern contraceptive methods by most recent source, according to specific method and residence, India, 1998–99 Contraceptive method Source Pill IUD Condom Female sterilization Male sterilization All modern methods URBAN Public medical sector Government/municipal hospital Government dispensary UHC/UHP/UFWC CHC/rural hospital/PHC Sub-centre Government mobile clinic Government paramedic Camp Other public medical sector NGO or trust Hospital/clinic NGO worker Private medical sector Private hospital/clinic Private doctor Private mobile clinic Private paramedic Vaidya/hakim/homeopath Pharmacy/drugstore Dai (TBA) Other private medical sector Other source Shop Other Don’t know1 Missing Total percent Number of users 13.1 44.8 8.7 74.5 78.2 60.1 7.8 31.8 5.3 58.6 54.5 46.5 1.5 2.4 0.9 0.0 0.0 0.4 1.0 2.7 0.4 1.4 2.2 1.3 0.8 5.9 1.0 8.2 10.2 6.7 1.1 0.5 0.3 0.0 0.0 0.1 0.0 0.2 0.0 0.1 0.8 0.1 0.0 0.0 0.4 0.0 0.0 0.1 0.0 0.3 0.2 4.1 5.9 3.1 0.9 1.1 0.3 2.2 4.6 1.9 0.3 2.4 0.2 1.9 0.8 1.5 0.1 2.4 0.1 1.9 0.8 1.5 0.3 0.0 0.1 0.0 0.0 0.0 45.0 52.2 43.0 23.2 19.9 29.0 4.7 39.4 4.1 21.9 18.4 19.5 3.2 12.5 2.0 1.0 0.7 2.0 0.0 0.0 0.2 0.0 0.0 0.0 2.5 0.0 2.8 0.0 0.0 0.5 0.1 0.0 0.0 0.0 0.0 0.0 33.6 0.0 33.2 0.0 0.0 6.4 0.0 0.0 0.2 0.0 0.0 0.0 0.9 0.3 0.3 0.3 0.8 0.3 38.3 0.6 40.3 0.3 0.9 7.9 37.8 0.0 39.8 0.0 0.0 7.6 0.5 0.6 0.5 0.3 0.9 0.4 3.0 0.0 7.3 0.0 0.0 1.2 0.3 0.0 0.4 0.2 0.2 0.3 100.0 100.0 100.0 100.0 100.0 100.0 584 765 1,580 7,887 398 11,213 152 Table 5.13 Source of modern contraceptive methods (contd.) Percent distribution of current users of modern contraceptive methods by most recent source, according to specific method and residence, India, 1998–99 Contraceptive method Source Pill IUD Condom Female sterilization Male sterilization All modern methods RURAL Public medical sector Government/municipal hospital Government dispensary UHC/UHP/UFWC CHC/rural hospital/PHC Sub-centre Government mobile clinic Government paramedic Camp Other public medical sector NGO or trust Hospital/clinic NGO worker Private medical sector Private hospital/clinic Private doctor Private mobile clinic Private paramedic Vaidya/hakim/homeopath Pharmacy/drugstore Dai (TBA) Other private medical sector Other source Shop Other Don’t know1 Missing Total percent Number of users 24.4 65.9 22.2 89.4 92.1 83.2 5.3 30.5 4.9 50.8 47.9 46.2 2.6 4.1 3.3 0.0 0.0 0.4 0.4 1.1 0.3 0.8 1.0 0.8 8.0 22.9 7.6 26.6 31.0 25.1 6.6 5.9 4.3 0.0 0.0 0.6 0.0 0.0 0.1 0.4 1.0 0.4 0.6 0.0 0.4 0.0 0.0 0.0 0.2 1.1 0.0 10.4 10.5 9.3 0.7 0.3 1.2 0.4 0.8 0.5 0.5 0.5 0.3 0.8 0.6 0.8 0.2 0.5 0.3 0.8 0.6 0.8 0.3 0.0 0.1 0.0 0.0 0.0 38.4 31.5 33.3 9.3 5.3 12.0 4.8 23.5 2.6 8.8 4.7 8.6 5.0 7.7 1.9 0.4 0.4 0.8 0.1 0.1 0.0 0.0 0.0 0.0 1.3 0.0 2.2 0.0 0.0 0.1 1.9 0.0 0.0 0.0 0.0 0.1 25.0 0.0 26.4 0.0 0.0 2.2 0.1 0.0 0.1 0.0 0.0 0.0 0.3 0.2 0.1 0.1 0.1 0.1 33.4 1.5 33.5 0.1 1.4 3.1 32.6 0.0 32.7 0.0 0.0 2.8 0.9 1.5 0.9 0.1 1.4 0.3 2.9 0.0 10.6 0.0 0.0 0.6 0.4 0.6 0.2 0.3 0.6 0.4 100.0 100.0 100.0 100.0 100.0 100.0 1,151 606 988 20,693 1,189 24,628 153 Table 5.13 Source of modern contraceptive methods (contd.) Percent distribution of current users of modern contraceptive methods by most recent source, according to specific method and residence, India, 1998–99 Contraceptive method Source Pill IUD Condom Female sterilization Male sterilization All modern methods TOTAL Public medical sector Government/municipal hospital Government dispensary UHC/UHP/UFWC CHC/rural hospital/PHC Sub-centre Government mobile clinic Government paramedic Camp Other public medical sector NGO or trust Hospital/clinic NGO worker Private medical sector Private hospital/clinic Private doctor Private mobile clinic Private paramedic Vaidya/hakim/homeopath Pharmacy/drugstore Dai (TBA) Other private medical sector Other source Shop Other Don’t know1 Missing Total percent Number of users 20.6 54.1 13.9 85.3 88.6 76.0 6.1 31.2 5.1 53.0 49.5 46.3 2.2 3.1 1.8 0.0 0.0 0.4 0.6 2.0 0.3 1.0 1.3 1.0 5.5 13.4 3.6 21.5 25.7 19.3 4.8 2.8 1.9 0.0 0.0 0.5 0.0 0.1 0.0 0.3 0.9 0.3 0.4 0.0 0.4 0.0 0.0 0.0 0.1 0.7 0.1 8.7 9.3 7.4 0.8 0.8 0.6 0.9 1.8 0.9 0.4 1.5 0.2 1.1 0.7 1.0 0.1 1.5 0.2 1.1 0.7 1.0 0.3 0.0 0.1 0.0 0.0 0.0 40.6 43.1 39.3 13.1 8.9 17.3 4.7 32.4 3.5 12.4 8.2 12.0 4.4 10.4 2.0 0.5 0.5 1.2 0.1 0.0 0.1 0.0 0.0 0.0 1.7 0.0 2.6 0.0 0.0 0.3 1.3 0.0 0.0 0.0 0.0 0.1 27.9 0.0 30.6 0.0 0.0 3.5 0.0 0.0 0.2 0.0 0.0 0.0 0.5 0.3 0.2 0.2 0.3 0.2 35.1 1.0 37.7 0.1 1.3 4.6 34.3 0.0 37.0 0.0 0.0 4.3 0.7 1.0 0.7 0.1 1.3 0.3 2.9 0.0 8.6 0.0 0.0 0.8 0.4 0.3 0.3 0.3 0.5 0.3 100.0 100.0 100.0 100.0 100.0 100.0 1,735 1,371 2,568 28,580 1,587 35,841 UHC: Urban health centre; UHP: Urban health post; UFWC: Urban family welfare centre; CHC: Community health centre; PHC: Primary Health Centre; NGO: Nongovernmental organization; TBA: Traditional birth attendant 1For the pill and condom, this category includes women who say their husband or a friend or other relative obtained the method, but they do not know the original source of supply. 154 Eighty-three percent of rural users obtain their contraceptives from the public medical sector compared with 60 percent of urban users. The role of the private medical sector in providing sterilization services in urban areas and services for IUD insertion in both rural and urban areas is especially notable. About one-quarter of female sterilizations and one-fifth of male sterilizations in urban areas as well as nearly one-third of IUD insertions in rural areas and more than half of IUD insertions in urban areas are performed in the private sector. Interstate Variations in the Role of the Public Sector Table 5.14 provides information on the extent to which urban, rural, and all current users of modern contraceptive methods used a public-sector source as their most recent source of contraception, by specific method and by state. In Himachal Pradesh, Orissa, Madhya Pradesh, Rajasthan, and Karnataka, 85–92 percent of users used a public-sector source. On the other hand, in Meghalaya, Delhi, Nagaland, Assam, Punjab, and Kerala, less than two-thirds of users used a public-sector source. The proportion who used a public-sector source is lower in urban areas than in rural areas. In 14 out of 24 states, 90 percent or more of sterilizations of rural women were performed in the public medical sector. In 13 out of 25 states, 80 percent or more of sterilizations of urban women were performed in the public medical sector. Figure 5.4 Sources of Family Planning Among Current Users of Modern Contraceptive Methods Public Medical Sector 76% Other Source 5% Don't Know/Missing 1% Private Medical Sector 17% NGO or Trust 1% NFHS-2, India, 1998–99 155 Table 5.14 Public sector as source of modern contraceptives by state Percentage of current users of modern contraceptive methods for whom the most recent source of contraceptives was the public sector, according to specific method, residence, and state, India, 1998–99 Contraceptive method State Pill IUD Condom Female sterilization Male sterilization All modern methods URBAN India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 13.1 44.8 8.7 74.5 78.2 60.1 15.9 56.3 11.4 80.2 79.2 50.8 * (45.7) 7.5 90.7 * 59.2 * 56.0 14.8 97.8 (100.0) 68.4 * (38.7) 2.7 79.8 (83.0) 60.7 (16.7) 35.5 5.9 88.2 * 40.3 (23.4) (62.5) 15.1 89.7 (96.0) 73.3 (28.9) (59.4) 8.9 84.7 (83.2) 69.8 (13.4) (65.8) 4.4 81.9 * 49.8 * * * 65.6 * 56.0 19.3 * * 91.2 * 74.2 6.0 (56.8) 3.6 79.9 * 52.6 * * * (77.8) * 64.3 (6.3) * (8.3) 68.1 * 46.8 * (51.1) * 90.9 * 69.7 * * * (43.2) * 33.5 (55.4) (64.1) * 76.8 * 72.8 * * * (90.5) * 59.5 * * * (89.7) * 76.3 * * (12.4) 79.3 * 62.8 (11.7) 30.3 8.0 64.1 (68.7) 52.2 10.6 28.1 14.4 69.4 (77.0) 59.1 * * * 68.7 (69.5) 64.9 * 50.2 (9.3) 77.1 * 70.7 * * (8.5) 68.1 * 63.4 * 43.7 15.6 70.8 * 65.0 156 Table 5.14 Public sector as source of modern contraceptives by state (contd.) Percentage of current users of modern contraceptive methods for whom the most recent source of contraceptives was the public sector, according to specific method, residence, and state, India, 1998–99 Contraceptive method State Pill IUD Condom Female sterilization Male sterilization All modern methods RURAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 24.4 65.9 22.2 89.4 92.1 83.2 * * * 88.6 * 63.7 (35.1) 63.5 21.6 96.6 (100.0) 87.9 (59.3) (85.3) 36.1 99.2 100.0 94.2 19.3 (59.3) 9.0 87.5 (89.1) 72.0 28.1 53.0 14.6 98.0 (100.0) 75.2 56.4 (74.5) 40.9 96.9 86.4 91.8 (33.9) * 28.5 97.2 98.9 94.2 22.9 (73.3) 21.0 94.2 98.0 81.7 (15.9) (55.6) (11.6) 86.0 79.2 80.9 26.3 * * 97.8 96.5 91.6 15.7 (96.3) (21.5) 92.3 (78.7) 74.6 33.1 (72.0) * 90.6 * 74.2 31.9 (85.8) (16.4) 79.7 (92.2) 65.5 * 72.2 * 94.7 * 81.7 (44.2) * * * * 61.8 * * * 94.2 * 92.8 * (43.2) * 80.7 * 56.8 52.9 67.0 * 93.8 (87.9) 78.2 * * * 82.9 * 72.9 * (56.1) (37.2) 89.3 98.0 86.7 (28.6) * 27.3 89.9 96.4 85.5 * * * 83.5 89.5 83.4 * (60.0) * 94.9 * 93.3 * (83.6) 12.0 69.5 (84.7) 67.4 * (32.0) * 81.0 * 78.9 157 Table 5.14 Public sector as source of modern contraceptives by state (contd.) Percentage of current users of modern contraceptive methods for whom the most recent source of contraceptives was the public sector, according to specific method, residence, and state, India, 1998–99 Contraceptive method State Pill IUD Condom Female sterilization Male sterilization All modern methods TOTAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 20.6 54.1 13.9 85.3 88.6 76.0 14.4 57.0 11.2 81.0 79.3 51.9 27.4 54.9 12.6 95.4 96.8 79.5 (53.1) 77.2 29.2 99.1 100.0 91.7 15.3 53.2 6.3 85.3 86.5 68.5 24.5 45.3 10.0 96.1 (100.0) 64.3 43.7 69.4 25.8 95.1 89.3 86.3 31.3 (66.5) 14.7 93.9 94.8 86.6 19.4 69.3 11.0 91.2 94.5 71.1 16.2 (48.5) (11.1) 83.1 78.3 76.9 24.6 (73.3) (21.7) 97.2 96.1 89.5 13.4 82.7 11.1 89.8 78.7 69.5 28.3 (76.7) * 88.0 * 72.2 29.8 83.5 14.7 78.6 (92.3) 63.7 (24.2) 63.9 * 93.1 * 76.8 (32.3) (67.0) * 52.4 * 47.3 72.3 73.6 * 84.1 * 81.0 * 44.3 * 83.8 * 57.7 49.6 69.7 * 93.0 (87.9) 77.9 * * 12.5 81.3 * 68.3 27.2 37.8 14.4 79.9 86.8 72.0 18.1 29.8 19.9 82.3 93.1 75.2 * * (15.3) 79.8 83.8 78.5 * 53.7 (12.4) 89.1 (80.7) 85.3 * (76.3) 10.8 69.2 83.8 66.4 * 40.3 14.7 77.3 (95.5) 73.5 ( ) Based on 25–49 unweighted cases *Percentage not shown; based on fewer than 25 unweighted cases 158 5.5 Reasons for Discontinuation/Non-Use of Contraception Currently married, nonpregnant women who were not using a contraceptive method at the time of the survey fall into two categories with respect to their contraceptive experience: those who used contraception in the past and those who never used contraception. NFHS-2 asked women who had discontinued contraceptive use their main reason for discontinuing. The survey also asked women who had never used contraception the main reason they were not currently using a method. Table 5.15 shows that only 4,588 nonpregnant women who ever used family planning methods—10 percent of ever users—have discontinued use. Because 66 percent of ever users are sterilized, only 34 percent of ever users even have the option of discontinuing use. Among the small group who discontinued contraception, the most commonly mentioned reasons for discontinuing are that they wanted to have a child (29 percent) or that the method created a health problem or a menstrual problem (21 percent). There are no sharp urban-rural differentials in the reasons given for discontinuation, except that the percentage of those who discontinued because the husband was away is somewhat higher in rural areas (13 percent) than in urban areas (8 percent). Among the 32,464 currently married nonpregnant women who never used contraception, the most commonly mentioned reason for not currently using a method is the desire for more children (45 percent). Another 12 percent of women say they are not currently using contraception because they are menopausal, have had a hysterectomy, or are infecund or subfecund. Only 7 percent mention a health-related problem (health concerns or worry about side effects). Another 7 percent mention opposition to family planning. Although knowledge of family planning methods is found to be almost universal, only 4 percent of women mention lack of knowledge as their main reason for not currently using contraception. Three percent say they are not currently using contraception because they are afraid of sterilization (thereby implicitly equating family planning with sterilization). There are no substantial urban-rural differences in reasons for not currently using contraception among women who never used contraception. 5.6 Future Intentions Regarding Contraceptive Use Currently married women who were not using any contraceptive method at the time of the survey (including those who were pregnant at that time) were asked about their intentions to use a method in the future. If they intended to use a method, they were asked about their preferred method. This type of information can help managers of family planning programmes to identify potential groups of users and to provide the types of contraception that are likely to be in demand. Table 5.16 gives women’s responses to the questions on future use according to residence and number of living children. Sixty percent of currently married women who are not currently using any contraceptive method express an intention to use a method in the future, which is double the corresponding percentage in NFHS-1. Among women who intend to use contraception, only one-third intend to use a method within the next 12 months. The proportion of women who intend to use contraception any time in the future increases from 60 percent of women with no living children to 71 percent of women with one living child, and then declines to 68 percent of women with two living children and 60 percent of women with three living children. Fifty-three percent of women with four or more living children say they have no intention of using contraception at any time in the future. 159 Table 5.15 Reasons for discontinuation/non-use Percent distribution of nonpregnant, currently married women who stopped using contraception by main reason for stopping use, and percent distribution of nonpregnant, currently married women who never used contraception by main reason for not currently using, according to residence, India, 1998–99 Reason Urban Rural Total REASON FOR STOPPING USE Method failed/got pregnant Lack of sexual satisfaction Created menstrual problem Created health problem Inconvenient to use Hard to get method Gained weight Did not like the method Wanted to have a child Wanted to replace dead child Lack of privacy for use Husband away Costs too much Others Missing Total percent Number of women 3.6 4.7 4.3 1.7 1.8 1.8 9.2 6.9 7.7 14.4 12.7 13.3 2.2 1.5 1.7 0.5 1.9 1.4 0.3 0.1 0.2 4.2 5.1 4.8 29.8 29.2 29.4 0.6 0.5 0.5 0.8 0.7 0.7 8.2 13.4 11.6 0.9 2.3 1.8 23.2 18.3 20.0 0.4 0.9 0.8 100.0 100.0 100.0 1,578 3,010 4,588 REASON FOR NOT CURRENTLY USING Husband away Fertility-related reasons Not having sex Infrequent sex Menopausal/had hysterectomy Subfecund/infecund Postpartum/breastfeeding Wants more children Opposition to use Opposed to family planning Husband opposed Other people opposed Against religion Lack of knowledge Knows no method Knows no source Method-related reasons Health concerns Worry about side effects Hard to get method Costs too much Inconvenient to use Afraid of sterilization Doesn’t like existing methods Other Don’t know/missing Total percent Number of women 3.1 2.8 2.9 68.8 66.4 66.8 2.0 1.1 1.3 1.6 1.0 1.1 9.4 7.9 8.2 5.4 3.8 4.1 6.6 7.8 7.6 43.8 44.8 44.6 7.9 7.3 7.4 0.8 0.9 0.9 4.0 3.7 3.8 0.8 0.7 0.7 2.3 2.0 2.0 1.6 4.5 4.0 0.6 1.5 1.3 1.0 3.0 2.6 13.7 14.4 14.3 3.9 3.2 3.4 4.1 3.3 3.4 0.2 0.5 0.4 0.3 1.1 1.0 0.3 0.3 0.3 1.4 3.0 2.7 3.5 3.0 3.1 3.5 2.6 2.7 1.4 2.0 1.9 100.0 100.0 100.0 6,172 26,292 32,464 160 The expressed timing of future use also varies by number of living children. The proportion of women who say that they intend to use contraception after 12 or more months falls steadily with the number of living children from 55 percent among women with no living children to 16 percent among those with four or more children. The proportion expressing an intention to use contraception within the next 12 months increases from 5 percent among those with no children to 29 percent among those with three living children and then falls slightly to 26 percent among those with four or more children. The overall proportion of women who intend to use contraception at some time in the future does not differ greatly by residence, but the timing of intended future use is somewhat different for women in rural and urban areas. Twenty percent of women in rural areas intend to use contraception in the next 12 months compared with 24 percent in urban areas. Among women with one or more children, the proportion intending to use contraception after 12 months is higher in rural areas than in urban areas at each number of living children. One-third of rural as well as urban women who are currently non-users have no intention of using contraception any time in the future. Table 5.16 Future use of contraception Percent distribution of currently married women who are not currently using any contraceptive method by intention to use in the future, according to number of living children and residence, India, 1998–99 Number of living children1 Intention to use in the future 0 1 2 3 4+ Total URBAN Intends to use in next 12 months Intends to use later Intends to use, unsure when Unsure as to intention Does not intend to use Missing Total percent Number of women 5.3 22.6 34.0 31.2 25.5 23.8 57.1 48.7 30.2 24.9 13.4 36.5 1.5 2.3 1.7 1.0 0.4 1.5 11.2 4.7 2.9 2.4 2.2 4.7 24.6 21.7 31.0 40.1 58.4 33.4 0.2 0.0 0.1 0.3 0.1 0.1 100.0 100.0 100.0 100.0 100.0 100.0 1,655 2,525 2,154 1,176 1,639 9,149 RURAL Intends to use in next 12 months Intends to use later Intends to use, unsure when Unsure as to intention Does not intend to use Missing Total percent Number of women 4.3 14.7 24.5 28.9 26.2 20.1 53.8 53.2 41.8 29.9 16.6 38.3 1.0 1.9 1.5 1.6 1.1 1.4 10.6 6.1 4.0 3.6 3.6 5.4 30.0 23.9 28.0 35.7 52.0 34.6 0.2 0.2 0.2 0.3 0.3 0.2 100.0 100.0 100.0 100.0 100.0 100.0 5,519 7,972 6,954 5,139 8,588 34,173 TOTAL Intends to use in next 12 months Intends to use later Intends to use, unsure when Unsure as to intention Does not intend to use Missing Total percent Number of women 4.6 16.6 26.8 29.3 26.1 20.9 54.6 52.1 39.1 28.9 16.1 37.9 1.1 2.0 1.6 1.5 1.0 1.5 10.8 5.8 3.7 3.3 3.4 5.3 28.8 23.4 28.7 36.5 53.0 34.3 0.2 0.2 0.2 0.3 0.3 0.2 100.0 100.0 100.0 100.0 100.0 100.0 7,174 10,497 9,109 6,314 10,227 43,322 1Includes current pregnancy, if any 161 Interstate Variations in Intentions to Use Contraception in the Future Table 5.17 shows considerable interstate variation in intentions to use contraception in the future among women who were not using contraception at the time of the survey. The proportion of currently married women not using contraception but intending to use it in the future ranges from 34 percent in Meghalaya to 86 percent in Himachal Pradesh. The proportion is 75 percent or higher in Himachal Pradesh, Haryana, Punjab, and Maharashtra. Table 5.17 Future use of contraception by state Percentage of currently married women not currently using contraception who intend to use any time in the future by number of living children, according to state, India, 1998–99 Number of living children1 State 0 1 2 3 4+ Total India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 60.2 70.7 67.4 59.8 43.3 60.2 59.6 74.5 61.7 60.2 48.1 62.1 85.1 90.2 86.0 77.4 56.8 80.2 89.7 94.5 88.1 82.8 59.9 85.6 63.9 74.9 74.5 62.9 49.5 63.6 86.2 87.3 76.3 65.2 48.2 75.1 59.2 67.2 67.0 62.2 43.2 58.5 78.8 85.8 80.7 70.6 53.7 73.5 55.0 65.4 61.5 57.9 45.1 55.1 63.1 68.3 65.5 58.0 42.7 57.0 47.4 67.6 63.2 57.8 42.4 57.5 42.0 63.3 66.0 63.5 42.9 56.5 53.2 60.2 56.3 46.1 47.6 52.9 25.7 45.7 45.5 42.3 32.6 38.6 40.5 61.9 62.6 59.7 35.8 50.8 (13.5) 40.2 34.7 38.0 32.1 34.1 (37.0) 64.0 66.7 59.4 50.8 58.6 (23.8) 57.7 54.8 51.2 47.4 49.0 (73.9) 81.4 79.2 61.0 55.5 70.3 56.5 58.3 51.1 34.0 31.1 50.2 76.9 83.6 68.9 72.1 50.4 72.1 70.9 81.6 78.6 73.1 56.8 74.5 62.3 72.1 70.5 57.8 28.9 62.9 64.0 73.5 69.7 52.9 23.9 60.8 37.8 50.4 54.0 38.2 17.8 44.5 47.5 68.0 63.3 38.2 18.5 54.7 ( ) Based on 25–49 unweighted cases 1Includes current pregnancy, if any 162 From these results it is evident that the proportion intending to use is not highly correlated with the level of fertility. This is possible because a high proportion currently using contraception and a low fertility rate are compatible with a residual group of non-users who are highly resistant to the idea of using contraception or who do not feel the need to use contraception. In most states the proportion intending to use in the future is highest among women with one or two living children. Reasons for Not Intending to Use Contraception The survey asked currently married women who were not using any method of contraception and who said that they did not intend to use a method at any time in the future why they did not intend to use contraception. This type of information is crucial for understanding the obstacles to further increases in contraceptive use and for designing effective information programmes. Table 5.18 shows that 54 percent of women mention a fertility-related reason for not intending to use contraception in the future, 22 percent mention a method-related reason, and 18 percent mention a reason related to opposition to use or lack of knowledge. Table 5.18 Reasons for not intending to use contraception Percent distribution of currently married women who are not using any contraceptive method and who do not intend to use any method in the future by main reason for not intending to use contraception, according to current age, India, 1998–99 Current age Reason 15–29 30–49 Total Fertility-related reasons Not having sex Infrequent sex Menopausal/had hysterectomy Subfecund/infecund Wants as many children as possible Opposition to use Opposed to family planning Husband opposed Other people opposed Against religion Lack of knowledge Knows no method Knows no source Method-related reasons Health concerns Worry about side effects Hard to get method Costs too much Inconvenient Afraid of sterilization Doesn’t like existing methods Other Don’t know/missing Total percent Number of women 43.5 59.1 54.0 0.6 4.6 3.2 0.4 2.3 1.7 2.1 32.9 22.8 3.0 12.0 9.0 37.4 7.5 17.3 21.4 11.0 14.4 1.9 1.6 1.7 6.4 3.7 4.6 1.1 0.4 0.6 12.1 5.2 7.5 7.0 2.2 3.8 5.2 1.4 2.6 1.8 0.8 1.1 22.0 21.8 21.9 3.2 4.9 4.3 6.6 5.1 5.6 0.1 0.3 0.2 1.2 0.7 0.9 0.1 0.3 0.2 5.0 5.5 5.3 5.9 5.1 5.3 1.8 4.2 3.4 4.3 1.7 2.5 100.0 100.0 100.0 4,876 9,993 14,868 163 The most frequently mentioned single reason given for not intending to use contraception is that the woman is menopausal or has undergone a hysterectomy (23 percent). Other reasons given by sizeable proportions of women are that the woman wants as many children as possible (17 percent) or that the couple is subfecund or infecund (9 percent). Thirty-seven percent of women below age 30 mention the desire to have as many children as possible as the main reason for not intending to use contraception, compared with 8 percent of women age 30–49. By contrast, 45 percent of older women mention reasons related to menopause, hysterectomy, infecundity, or subfecundity, compared with only 5 percent of younger women. Since women below age 30 account for more than 80 percent of total current fertility in India, the reasons they give for not intending to use contraception are extremely important from a policy perspective. Among the 52 percent of younger women who give reasons not related to fertility, 19 percent mention health concerns or concerns about side effects, 24 percent give other method-related reasons, and another 13 percent mention lack of knowledge. This suggests that improved information and improved quality of services could enhance the acceptance of the government’s family welfare programme. Nevertheless, among younger women who are not using contraception, the desire to have as many children as possible remains the major reason for not intending to use contraception in the future. Preferred Future Method of Contraception NFHS-2 asked currently married women who were not using contraception but intended to use a method in the future which method of family planning they would prefer to use. Table 5.19 shows the results according to the timing of intended use. A large majority (65 percent) of women who intend to use contraception say they intend to use female sterilization, up from 59 percent in NFHS-1. The next most preferred method is the pill, which was the preference of 16 percent of women, down from 19 percent in NFHS-1. Less than 1 percent of the women prefer that their husbands get sterilized, and 3 percent each prefer to use the condom or IUD. There are important differences in the choice of preferred methods by timing of intended use. Women who intend to use within the next 12 months show a much greater preference for modern spacing methods (38 percent) than women who intend to use later (14 percent). Among women who intend to use in the next 12 months, the pill is the spacing method mentioned most often (25 percent), followed by the IUD and the condom (6 percent each). A negligible percentage of women from either group mention male sterilization as the preferred method. Results are similar for urban and rural areas with some exceptions. Among women who intend to use a method within the next 12 months, a higher proportion of rural women than urban women prefer the pill (28 percent compared with 18 percent), whereas a higher proportion of urban women than rural women prefer the condom (11 percent vs. 5 percent) and IUD (9 percent vs. 5 percent). Overall, the mix of contraceptive methods that intended future users say they would prefer to use is not very different from the methods currently being used, with heavy reliance on female sterilization. However, the fact that 38 percent of the women intending to use contraception within the next year plan to use a spacing method suggests that there is a significant potential demand for spacing methods that will need to be met. 164 Table 5.19 Preferred method Percent distribution of currently married women who are not currently using a contraceptive method but who intend to use a method in the future by preferred method, according to timing of intended use and residence, India, 1998–99 Timing of intended use Preferred method Next 12 months Later Unsure about timing Total URBAN Pill IUD Condom Female sterilization Male sterilization Rhythm/safe period Withdrawal Other Unsure Total percent Number 18.4 7.4 2.7 11.5 9.2 3.1 0.9 5.4 11.0 4.0 2.3 6.6 48.2 74.1 75.2 64.1 0.6 0.4 1.3 0.5 2.7 1.2 0.6 1.8 0.9 0.4 0.4 0.6 1.0 0.7 1.1 0.8 8.1 8.8 15.5 8.7 100.0 100.0 100.0 100.0 2,179 3,339 138 5,655 RURAL Pill IUD Condom Female sterilization Male sterilization Rhythm/safe period Withdrawal Other Unsure Total percent Number 27.5 11.7 13.3 17.0 5.0 1.4 0.8 2.6 4.7 1.2 2.2 2.4 48.4 74.4 67.4 65.5 1.0 0.7 0.9 0.8 3.6 1.2 3.5 2.1 1.1 0.3 0.7 0.5 2.0 1.1 0.1 1.4 6.7 8.0 11.1 7.6 100.0 100.0 100.0 100.0 6,857 13,080 492 20,429 TOTAL Pill IUD Condom Female sterilization Male sterilization Rhythm/safe period Withdrawal Other Unsure Total percent Number 25.3 10.8 11.0 15.9 6.0 1.7 0.8 3.2 6.2 1.8 2.2 3.3 48.4 74.3 69.1 65.2 0.9 0.6 1.0 0.7 3.4 1.2 2.9 2.0 1.0 0.3 0.6 0.5 1.8 1.0 0.3 1.3 7.0 8.2 12.1 7.9 100.0 100.0 100.0 100.0 9,035 16,419 630 26,084 165 5.7 Exposure to Family Planning Messages For many years, the family planning programme has been using electronic and other mass media to promote family planning. Studies have confirmed that even after controlling the effect of residence and education the exposure to electronic mass media has a substantial effect on contraceptive use (Ramesh et al., 1996). It is also found to strengthen women’s motivation to prevent unwanted fertility (Kulkarni and Choe, 1998). In order to explore the reach of family planning messages through various mass media, NFHS-2 asked women whether they had heard or seen any message about family planning in the past few months. Table 5.20 shows the proportion of ever-married women who report having heard or seen a family planning message in the past few months, according to various background characteristics. Results indicate that messages disseminated through the mass media reach 60 percent of ever-married women in India. The most common source of exposure to family planning messages is television. Forty- four percent of ever-married women report having seen a family planning message on television, followed by radio (38 percent), wall paintings or hoardings (31 percent), newspapers or magazines (18 percent), and cinema/film shows (13 percent). Only 4 percent were exposed to a message through a drama, folk dance, or street play. Overall exposure to mass media messages on family planning does not vary much by age, but exposure is much higher in urban areas than in rural areas. Eighty-three percent of urban ever-married women report seeing or hearing a family planning message from at least one media source, compared with 52 percent of women in rural areas. Urban women are more likely than rural women to have been exposed to a message through each form of mass media. Exposure to family planning messages varies greatly by education. More than 75 percent of women who are literate have heard or seen a family planning message from at least one media source in the past few months, compared with only 42 percent of women who are illiterate. This proportion reaches 94 percent among women with at least a high school education. Exposure to family planning messages through some specific media sources is even more closely linked to education than is exposure in general. For example, 86 percent of women with at least a high school education have heard or seen a family planning message on television, compared with only 26 percent of illiterate women. Exposure to family planning messages also differs by religion. Fifty-nine percent of Hindu women and 57 percent of Muslim women say they have heard or seen a family planning message through the media, compared with 70–90 percent of Buddhist, Christian, Sikh, or Jain women. Muslim women report less exposure through television, newspapers or magazines, and wall paintings or hoardings than do women from any of the other five religions. Sixty-eight percent of ever-married women not belonging to scheduled castes/tribes or other backward classes have seen or heard a family planning message, followed by 60 percent of women from other backward classes, 53 percent of women from scheduled castes, and 39 percent of women from scheduled tribes. This pattern of differential exposure by caste/tribe is also observed for all specific media sources except cinema/film shows. Exposure to family planning messages rises steadily as the standard of living increases, both for media in general and for each specific media source. Only 38 percent of women living in households with a low standard of living are exposed to family planning messages, compared with 89 percent of women living in households with a high standard of living. 166 Table 5.20 Exposure to family planning messages Percentage of ever-married women who have heard or seen any message about family planning in the past few months, by specific media source and selected background characteristics, India, 1998–99 Source of family planning message Background characteristic Radio Television Cinema/ film show News- paper/ magazine Wall painting/ hoarding Drama/ folk dance/ street play Any source Number of women Age 15–24 25–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Use of contraception Ever used Never used Total 37.9 42.2 13.9 16.9 30.1 4.4 59.4 24,571 39.4 45.4 13.8 19.5 32.8 4.7 61.5 32,839 37.1 43.6 11.5 17.6 29.4 4.1 58.6 31,789 49.0 75.9 24.5 38.1 47.3 5.6 83.4 23,370 34.3 32.5 8.9 11.0 25.0 4.0 51.6 65,829 25.9 25.8 5.8 1.2 14.7 2.5 42.4 51,871 48.2 56.0 14.7 21.6 42.6 5.1 76.4 17,270 55.8 70.5 21.8 41.0 54.1 7.1 85.9 7,328 64.4 86.0 34.8 69.0 67.4 9.8 94.0 12,719 38.2 43.6 13.5 17.8 30.7 4.7 59.2 72,903 35.1 38.8 8.8 13.8 25.9 2.5 57.1 11,190 51.9 50.8 19.3 37.3 48.0 5.1 75.4 2,263 34.4 75.6 6.1 28.3 39.3 1.1 82.7 1,427 48.3 82.2 28.9 55.4 59.1 7.4 89.6 331 38.2 55.9 14.9 24.8 43.3 8.8 69.5 676 32.1 20.4 6.1 8.5 23.5 4.1 49.8 285 31.6 33.2 7.0 24.5 32.4 1.7 51.6 44 33.4 35.7 10.0 9.6 24.6 3.9 53.2 16,301 25.2 20.6 4.9 7.0 18.2 3.3 38.8 7,750 38.6 43.4 15.3 17.2 33.1 4.5 60.2 29,383 43.0 53.7 14.4 25.7 35.1 4.9 67.9 34,904 24.1 18.6 6.4 3.4 17.8 2.8 38.0 29,033 40.2 44.5 12.1 15.1 30.4 4.2 62.6 41,289 55.9 83.2 25.8 48.8 53.2 7.4 89.1 17,845 43.4 52.7 15.7 23.3 37.2 5.2 68.8 48,092 32.0 33.6 9.9 12.1 23.5 3.4 49.5 41,107 38.1 43.9 13.0 18.1 30.9 4.4 59.9 89,199 Note: Total includes 11, 79, 862, and 1,032 women with missing information on education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. 167 Finally, as expected, women who have ever used contraception are more likely (69 percent) to report hearing or seeing a media message on family planning than are women who have never used contraception (50 percent). These differentials are likely to reflect some combination of greater access to broadcast signals in urban areas, the greater ability of higher- income households to own radios and televisions, and variations in attentiveness to media messages associated with differing levels of education, leisure, and interest. 5.8 Discussion of Family Planning Irrespective of whether they had ever used contraception, all currently married women were asked whether they had discussed family planning with their husband, friends, neighbours, or other relatives in the past few months. Information on whether women talk about family planning at all, and with whom they discuss it, sheds light on their level of interest in family planning, their familial and other sources of family planning information, and the possibility of communication with others on such a personal topic. Table 5.21 shows that only 25 percent of women discussed family planning with their husband, friends, neighbours, or other relatives in the past few months. Only 18 percent of currently married women discussed family planning with their husbands and 11 percent discussed family planning with friends or neighbours. Discussions with other relatives were rare. Women age 15–34 years are more likely to have discussed family planning with someone (27–29 percent) than women age 35–49 (17 percent). In general, the proportion of women who have discussed family planning varies predictably by most other background characteristics. Urban women are somewhat more likely (29 percent) than rural women (23 percent) to have discussed family planning. The proportion of women reporting such discussions rises with women’s education (from 20 among illiterate women to 36 percent among women with at least a high school education), husband’s education (from 19 to 31 percent), and the standard of living index (from 19 percent among women living in households with a low standard of living to 33 percent among women living in households with a high standard of living). By religion, about one-quarter of women from each religion have discussed family planning with others, except the percentage is almost double (49 percent) among Sikh women. Discussions about family planning are slightly lower for scheduled-tribe women than for other caste/tribe groups, but the differences are small. Women who have ever used contraception are more likely to have discussed family planning (28 percent) than women who have never used contraception (20 percent). Interstate Variations in Exposure to Family Planning Messages and Discussions about Family Planning The three indicators shown in Table 5.22 summarize state differentials in the situation of women regarding their exposure to family planning messages through media and their discussions with their husbands and others about family planning. Women’s media exposure to family planning messages varies from 36 percent in Rajasthan to 92 percent in Delhi. Exposure also exceeds 80 percent in Himachal Pradesh, Sikkim, Goa, Punjab, Karnataka, Manipur, and Kerala. At the other extreme are four large states with low levels of contraception—Rajasthan, Bihar, Uttar Pradesh, and Madhya Pradesh—with exposure ranging from 36 percent in Rajasthan to 49 percent in Madhya Pradesh. 168 Table 5.21 Discussion of family planning Percentage of currently married women who discussed family planning with their husbands, friends, neighbours, or other relatives in the past few months by selected background characteristics, India, 1998–99 Person with whom discussed family planning Background characteristic Husband Mother Sister Daughter Mother- in-law Sister- in-law Friend/ neighbour Other relative Any of these persons Number of women Age 15–24 25–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Use of contraception Ever used Never used Husband’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Total 21.7 2.5 1.2 0.1 3.1 2.2 9.8 0.3 27.4 23,944 21.8 1.9 1.7 0.2 2.0 2.6 12.3 0.4 29.3 31,342 10.1 0.5 0.9 1.1 0.5 1.5 9.1 0.2 17.2 28,363 21.8 2.0 1.8 0.5 1.9 2.2 11.5 0.4 29.3 21,888 16.4 1.4 1.1 0.4 1.8 2.1 10.1 0.3 23.0 61,761 13.8 1.1 0.8 0.5 1.4 1.6 8.7 0.2 19.7 48,018 19.1 2.0 1.7 0.6 2.2 2.4 11.8 0.4 27.1 16,257 24.0 2.4 1.8 0.3 2.7 2.9 13.7 0.4 32.3 7,073 27.9 2.5 2.3 0.2 2.4 3.4 14.1 0.5 36.3 12,291 17.1 1.6 1.2 0.5 1.9 2.1 10.5 0.3 24.1 68,443 19.3 1.3 1.3 0.2 1.3 1.9 9.4 0.4 24.9 10,477 17.2 1.5 1.7 0.5 1.0 1.5 10.6 0.2 24.9 2,072 40.7 2.7 3.4 0.1 4.0 7.3 21.3 0.0 48.9 1,365 18.7 1.8 1.5 0.4 2.0 1.9 10.0 0.5 24.8 316 21.4 1.8 0.8 0.0 2.4 0.5 8.0 1.2 25.2 601 18.9 1.4 1.1 0.0 1.8 1.9 7.6 1.0 24.9 259 19.4 1.4 0.4 0.0 4.5 0.2 11.0 0.2 24.8 38 17.4 1.5 1.0 0.6 1.9 1.7 10.7 0.2 24.1 15,178 15.1 0.9 0.7 0.2 1.3 1.2 8.5 0.3 20.8 7,176 16.4 1.9 1.4 0.6 2.0 2.2 11.0 0.3 23.9 27,529 19.8 1.6 1.4 0.4 1.7 2.5 10.5 0.4 26.4 32,957 13.6 1.4 0.8 0.3 1.2 1.3 8.9 0.3 19.3 26,505 17.8 1.6 1.3 0.5 2.0 2.0 10.3 0.3 24.7 38,999 24.2 1.9 2.1 0.6 2.5 3.7 13.4 0.4 32.7 17,173 20.0 1.6 1.7 0.7 1.8 2.7 12.7 0.3 28.4 46,115 15.1 1.5 0.8 0.2 1.9 1.5 7.8 0.3 19.9 37,534 12.7 1.2 0.8 0.6 1.2 1.4 8.5 0.2 18.6 24,965 15.8 1.5 1.3 0.5 1.6 1.9 10.0 0.3 22.7 21,298 19.7 1.7 1.3 0.3 2.1 2.2 10.8 0.3 26.3 11,330 23.5 2.0 1.7 0.4 2.5 3.0 12.7 0.4 31.3 25,847 17.8 1.6 1.3 0.5 1.8 2.1 10.5 0.3 24.6 83,649 Note: Total includes 11, 77, 809, 971, and 209 women with missing information on education, religion, caste/tribe, the standard of living index, and husband’s education, respectively, who are not shown separately. 169 Table 5.22 Exposure to messages and discussion of family planning by state Percentage of ever-married women who have been exposed to a family planning message in the past few months, and percentage of currently married women who know a contraceptive method who have discussed family planning with their husbands, friends, neighbours, or other relatives by state, India, 1998–99 State Exposed to family planning message1 Discussed family planning with husband Discussed family planning with anyone2 India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 59.9 17.8 24.6 91.7 23.6 27.5 76.6 47.4 57.0 88.4 44.4 54.5 60.6 22.0 28.9 84.8 49.7 58.8 35.9 17.7 22.6 48.9 16.4 23.7 47.1 18.5 22.7 39.7 13.9 19.8 58.9 24.4 31.1 56.5 17.8 25.2 67.9 19.3 27.7 60.8 20.5 25.4 80.8 18.5 23.5 62.8 27.4 30.6 77.7 32.6 40.0 64.4 29.8 35.4 88.0 12.4 20.3 85.7 25.1 33.4 62.5 11.4 20.6 62.2 17.5 20.5 75.9 10.0 22.7 84.4 14.8 21.8 80.6 17.8 23.8 75.7 13.1 23.8 1Women who have heard or seen any message about family planning on the radio or television, in a cinema, film show, newspaper, or magazine, on a wall painting or hoarding, or in a drama, folk dance, or street play in the past few months 2Husband, friends, neighbours, or other relatives 170 Women in Andhra Pradesh, Gujarat, Sikkim, and Tamil Nadu (10–13 percent) are less likely than women in other states to have discussed family planning with their husbands. Comparable estimates for Punjab and Haryana are 50 percent and 47 percent, respectively. Discussions of family planning with anyone range from 20 percent in Bihar and Sikkim to 59 percent in Punjab. Surprisingly, women in the southern states, despite high levels of media exposure to family planning messages, are about as likely to have discussed family planning with their husbands or with anyone as women in the states with low media exposure to family planning messages. 5.9 Need for Family Planning Currently married women who are not using any method of contraception but who do not want any more children or want to wait two or more years before having another child are defined as having an unmet need for family planning. Current contraceptive users are said to have a met need for family planning. The total demand for family planning is the sum of the met need and the unmet need. Table 5.23 shows the unmet need, met need, and total demand for family planning, according to whether the need is for spacing or limiting births, by background characteristics of women. The footnotes in the table provide detailed definitions of these concepts. According to these definitions, 16 percent of currently married women in India have an unmet need for family planning. The unmet need for spacing births is the same as the unmet need for limiting births (8 percent). If all of the women who say they want to space or limit their births were to use family planning, the contraceptive prevalence rate would increase from 48 percent to 64 percent of currently married women, implying that 25 percent of total family planning need is not being met. Comparison with NFHS-1 indicates that the proportion of women with unmet need for family planning declined from 20 to 16 percent during the six and one-half years between the two surveys. The proportion of total demand for family planning that is met increased from 68 percent to 75 percent. Unmet need is highest (27 percent) among women below age 20; the unmet need in this age group is almost entirely for spacing rather than for limiting. Unmet need is also relatively high for women age 20–24 (24 percent), with 75 percent of the need being for spacing. Among women age 25–29, 19 percent have an unmet need, and more than half of this need is for limiting. Only 23 percent of the total demand for family planning is being met for married women age 15–19. This proportion rises sharply to 52 percent for women age 20–24, to 73 percent for women age 25–29, and to 82–95 percent for women age 30–49. Both met need and unmet need for contraception among women age 30 years and above are mostly for limiting. Unmet need for family planning is higher in rural areas than in urban areas, and the proportion of total demand for family planning that is satisfied is lower in rural areas than in urban areas. Unmet need for family planning varies by women’s education, but only within a narrow range of 14 to 17 percent. The percentage of demand satisfied rises with education from 73 percent among illiterate women to 79 percent among women with at least a high school education. 171 Table 5.23 Need for family planning services Percentage of currently married women with unmet need, met need, and total demand for family planning (FP) services and percentage of total demand satisfied by selected background characteristics, India, 1998–99 Unmet need for FP1 Met need (currently using)2 Total demand for FP Background characteristic For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Percentage of demand satisfied Age 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High 25.6 1.6 27.1 5.6 2.4 8.0 31.2 4.0 35.2 22.8 18.4 5.9 24.4 7.7 18.3 26.0 26.1 24.3 50.4 51.6 8.1 10.5 18.6 4.9 44.4 49.3 13.0 54.8 67.9 72.7 3.1 11.1 14.1 2.1 60.6 62.7 5.2 71.7 76.8 81.6 1.1 9.1 10.2 0.7 66.7 67.4 1.7 75.8 77.5 86.9 0.2 5.5 5.7 0.2 64.7 64.9 0.5 70.1 70.6 91.9 0.1 3.0 3.1 0.0 57.2 57.2 0.1 60.2 60.3 94.8 6.7 6.7 13.4 5.2 53.0 58.2 11.9 59.7 71.6 81.3 8.9 7.8 16.7 2.9 41.8 44.7 11.8 49.6 61.3 72.8 7.8 8.5 16.2 1.6 41.3 42.9 9.4 49.8 59.2 72.6 8.4 6.1 14.4 3.5 52.0 55.5 11.8 58.1 69.9 79.3 11.1 6.1 17.1 6.8 45.4 52.2 17.9 51.5 69.3 75.3 8.8 6.3 15.1 9.1 47.9 57.0 17.9 54.2 72.1 79.0 8.0 7.1 15.1 3.1 46.1 49.2 11.1 53.2 64.3 76.5 11.0 11.0 22.0 5.2 31.8 37.0 16.1 42.8 59.0 62.7 8.7 6.1 14.8 5.2 47.2 52.4 13.9 53.3 67.2 78.0 3.6 5.1 8.6 5.6 59.6 65.2 9.2 64.7 73.9 88.3 5.9 3.6 9.5 6.0 59.1 65.1 12.0 62.6 74.6 87.2 7.4 5.3 12.7 2.7 62.0 64.7 10.1 67.3 77.4 83.6 6.9 5.4 12.3 8.7 39.9 48.6 15.6 45.3 60.9 79.8 14.2 11.4 25.6 5.1 24.9 30.1 19.4 36.3 55.7 54.0 8.6 8.2 16.8 2.7 42.0 44.6 11.2 50.2 61.4 72.7 8.8 7.0 15.9 2.5 36.7 39.1 11.3 43.7 55.0 71.1 8.6 7.1 15.7 2.5 44.3 46.8 11.2 51.3 62.5 74.8 7.7 7.5 15.2 5.0 48.5 53.5 12.7 56.0 68.7 77.8 9.0 8.8 17.9 1.9 37.5 39.5 11.0 46.4 57.4 68.8 8.5 7.2 15.6 3.3 45.2 48.4 11.7 52.3 64.0 75.6 6.7 6.1 12.8 6.3 54.9 61.2 13.0 61.0 74.0 82.7 Contd… 172 Hindu and Christian women have a lower unmet need for family planning (15 percent) than Muslim women (22 percent) but a higher unmet need than women from other religious groups (8–13 percent). The percentage of total demand satisfied is higher for Hindu and Christian women (77–78 percent) than for Muslims (63 percent), but less than that of other religious groups (80–88 percent). There are no notable differentials in the extent of unmet need by caste/tribe, but the percentage of demand satisfied is somewhat higher for women who do not belong to a scheduled caste or tribe or other backward class. Unmet need declines steadily from 18 to 13 percent, and the percentage of demand satisfied increases from 69 to 83 percent as the standard of living index rises from low to high. Unmet need is much higher for women with one living child and for women with 6 or more living children (23 percent) than for women with either no children (14 percent) or two to five children (12–17 percent). Among women with no children or one child, unmet need is almost exclusively for spacing. The proportion of unmet need that is for limiting then rises from 47 percent among women with two living children to 91 percent among women with six or more living children. Among women with no living children, only 24 percent of total demand for family planning is satisfied. Half of total demand is satisfied among women with one living child. The proportion of demand satisfied rises sharply to 80–85 percent for women with two to four living children and then declines to 65 percent for women with six or more children. These results indicate that the family planning programme’s strong emphasis on sterilization results in failure to meet the spacing needs of young women who are still in the process of forming their families. Table 5.23 Need for family planning services (contd.) Percentage of currently married women with unmet need, met need, and total demand for family planning (FP) services and percentage of total demand satisfied by selected background characteristics, India, 1998–99 Unmet need for FP1 Met need (currently using)2 Total demand for FP Background characteristic For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Percentage of demand satisfied Number of living children 0 1 2 3 4 5 6+ Total 13.8 0.2 14.1 3.8 0.7 4.6 17.7 1.0 18.6 24.4 20.6 2.6 23.2 12.4 11.4 23.7 32.9 14.0 46.9 50.6 7.9 7.1 15.0 3.0 55.1 58.1 10.8 62.2 73.1 79.5 4.1 7.8 11.9 1.1 66.4 67.5 5.2 74.2 79.4 85.0 2.9 9.7 12.5 0.7 65.1 65.8 3.5 74.8 78.3 84.0 2.4 14.2 16.6 0.3 56.4 56.7 2.8 70.5 73.3 77.3 2.0 20.5 22.5 0.3 41.1 41.4 2.4 61.6 63.9 64.8 8.3 7.5 15.8 3.5 44.7 48.2 11.8 52.2 64.0 75.3 1Unmet need for spacing includes pregnant women whose pregnancy was mistimed, amenorrhoeic women whose last birth was mistimed, and women who are neither pregnant nor amenorrhoeic and who are not using any method of family planning and who say they want to wait two or more years for their next birth. Also included in unmet need for spacing are women who are unsure whether they want another child or who want another child but are unsure when to have the birth. Unmet need for limiting refers to pregnant women whose pregnancy was unwanted, amenorrhoeic women whose last child was unwanted, and women who are neither pregnant nor amenorrhoeic who are not using any method of family planning and who want no more children. 2Met need for spacing refers to women who are using some method of family planning and say they want to have another child or are undecided whether to have another. Met need for limiting refers to women who are using some method and who want no more children. Note that spacing and limiting refer to the reason for using contraception rather than to the particular method used. 173 These findings on unmet need from NFHS-2 corroborate similar findings from NFHS-1 (Radha Devi et al., 1996). Interstate Variations in Unmet Need Table 5.24 and Figure 5.5 show that unmet need for family planning services ranges from 7 percent in Punjab to 25 percent in Uttar Pradesh and Bihar (among major states) to 36 percent in the small northeastern state of Meghalaya. In Uttar Pradesh unmet need declined from 30 to 25 percent between NFHS-1 and NFHS-2. In Bihar it remained unchanged at 25 percent. In Rajasthan, Madhya Pradesh, and Orissa, unmet need declined from 20–22 percent in NFHS-1 to 16–18 percent in NFHS-2. Haryana, Karnataka, Himachal Pradesh, Punjab, West Bengal, Assam, and Gujarat are the other states that have achieved a considerable decline in unmet need since NFHS-1. Unmet need increased in all the northeastern states except Assam. The percentage of demand satisfied increased in all states except Meghalaya, Mizoram, Goa, and Kerala. The percentage of unmet need that is for spacing ranges from 37 percent in Jammu and Kashmir to 75 percent in Mizoram. In summary, NFHS-2 results show that although current use of contraception has increased and the extent of unmet need has declined in most of the states in India, there is a need for considerable improvement in the coverage and quality of family planning services, especially in the four large states of Uttar Pradesh, Bihar, Madhya Pradesh, and Rajasthan, as well as in Orissa. The findings underscore the need for appropriate state-specific strategies with emphasis on universal education, imaginative use of electronic mass media for IEC programmes, intensified promotion of temporary methods, and improvement in the quality of services. 174 Table 5.24 Need for family planning services by state Percentage of currently married women with unmet need, met need, and total demand for family planning (FP) services, and percentage of total demand satisfied, according to state, India, 1998–99 Unmet need for FP1 Met need (currently using)2 Total demand for FP State For spacing For limiting Total For spacing For limiting Total For spacing For limiting Total Percentage of demand satisfied India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 8.3 7.5 15.8 3.5 44.7 48.2 11.8 52.2 64.0 75.3 5.9 7.5 13.4 7.8 56.0 63.8 13.7 63.5 77.1 82.7 2.9 4.7 7.6 4.1 58.3 62.4 7.0 62.9 69.9 89.2 3.6 4.9 8.6 3.5 64.2 67.7 7.1 69.2 76.3 88.8 7.4 12.6 20.0 4.5 44.6 49.1 11.9 57.1 69.0 71.1 2.8 4.5 7.3 5.2 61.5 66.7 8.0 66.0 74.0 90.1 8.7 8.9 17.6 2.4 37.9 40.3 11.1 46.8 57.9 69.6 8.9 7.3 16.2 2.2 42.1 44.3 11.1 49.4 60.5 73.2 11.8 13.4 25.1 3.0 25.1 28.1 14.7 38.5 53.2 52.8 12.6 11.9 24.5 1.4 23.1 24.5 14.0 35.0 49.1 50.0 8.7 6.8 15.5 2.4 44.4 46.8 11.1 51.2 62.3 75.1 6.3 5.5 11.8 9.8 56.9 66.6 16.0 62.4 78.4 85.0 17.2 9.3 26.5 6.4 29.1 35.4 23.6 38.4 61.9 57.2 7.0 10.0 17.0 7.9 35.3 43.3 14.9 45.3 60.2 71.8 13.6 10.0 23.6 8.9 29.8 38.7 22.5 39.8 62.3 62.1 23.4 12.1 35.5 4.5 15.6 20.2 27.9 27.8 55.7 36.3 11.7 3.7 15.5 8.2 49.5 57.7 20.0 53.3 73.2 78.9 18.3 11.9 30.2 2.5 27.7 30.3 20.8 39.6 60.5 50.0 9.9 13.2 23.1 6.4 47.4 53.8 16.3 60.6 76.9 70.0 7.3 9.8 17.1 7.1 40.4 47.5 14.4 50.2 64.6 73.5 4.8 3.7 8.5 4.9 54.2 59.0 9.7 57.8 67.5 87.4 8.1 4.9 13.0 3.1 57.8 60.9 11.2 62.7 74.0 82.4 5.2 2.5 7.7 0.7 58.9 59.6 5.9 61.4 67.3 88.5 8.3 3.2 11.5 2.1 56.2 58.3 10.4 59.4 69.8 83.5 6.9 4.9 11.7 6.2 57.5 63.7 13.1 62.4 75.5 84.4 6.6 6.4 13.0 2.2 49.9 52.1 8.8 56.3 65.1 80.1 1Unmet need for spacing includes pregnant women whose pregnancy was mistimed, amenorrhoeic women whose last birth was mistimed, and women who are neither pregnant nor amenorrhoeic and who are not using any method of family planning and who say they want to wait two or more years for their next birth. Also included in unmet need for spacing are women who are unsure whether they want another child or who want another child but are unsure when to have the birth. Unmet need for limiting refers to pregnant women whose pregnancy was unwanted, amenorrhoeic women whose last child was unwanted, and women who are neither pregnant nor amenorrhoeic who are not using any method of family planning and who want no more children. 2Met need for spacing refers to women who are using some method of family planning and say they want to have another child or are undecided whether to have another. Met need for limiting refers to women who are using some method and who want no more children. Note that spacing and limiting refer to the reason for using contraception rather than to the particular method used. 175 Figure 5.5 Unmet Need for Family Planning by State 0 5 10 15 20 25 30 35 40 M eghalaya Nagaland A runacha l P radesh Uttar P radesh B ihar M anipur S ikkim Jam m u & K ashm ir Ra jasthan G oa A ssam M adhya P radesh INDIA O rissa M izoram De lh i Tam il N adu M aharashtra W est B enga l K era la K arnataka H im acha l P radesh G ujara t A ndhra P radesh Haryana P unjab P ercentage o f Currently M arried W om en NFHS-2, India, 1998–99 CHAPTER 6 MORTALITY, MORBIDITY, AND IMMUNIZATION This chapter presents mortality rates, particularly for infants and young children, and data on the prevalence of certain diseases (morbidity). It also presents information on the prevention and treatment of diseases, especially those that are life-threatening to young children. The chapter ends with data on women’s knowledge of AIDS. This type of information is relevant both to an assessment of the demographic situation and to the design of appropriate health policies and programmes. Mortality estimates are also useful for projecting the future size of the population. Detailed information on mortality and morbidity (by demographic and socioeconomic characteristics) can be used to identify population groups that are at high risk and in need of health services. This chapter primarily presents information on child health, while other chapters of this report, particularly Chapter 8, present information on maternal and reproductive health. The Government of India has repeatedly taken steps to strengthen maternal and child health services in India, starting during the First and Second Five-Year Plans (1951–56 and 1956–61) under the Ministry of Health, and continuing with the Minimum Needs Programme initiated during the Fifth Five-Year Plan (1974–79). More recently, efforts to improve maternal and child health have been enhanced by activities of the Family Welfare Programme and by the introduction of the Child Survival and Safe Motherhood Programme (Ministry of Health and Family Welfare, 1992). The Ministry of Health and Family Welfare has also sponsored special projects under the Maternal and Child Health Programme, including the Oral Rehydration Therapy (ORT) programme, the establishment of Regional Institutes of Maternal and Child Health in states where infant mortality rates are high, the Universal Immunization Programme, and the Maternal and Child Health Supplemental Programme within the Postpartum Programme (Ministry of Health and Family Welfare, 1992). These programmes are now integrated into the Reproductive and Child Health Programme launched in 1996. Maternal and child health services in rural areas of India are delivered mainly by government-run Primary Health Centres and sub-centres. In urban areas, such services are available mainly through government or municipal hospitals, urban health posts, hospitals and nursing homes operated by nongovernmental organizations (NGOs), and private nursing homes and maternity homes. The second National Family Health Survey (NFHS-2) includes questions on mortality and morbidity on both the Household Questionnaire and the Woman’s Questionnaire. The Household Questionnaire has questions on individuals in the household suffering from asthma, tuberculosis, jaundice, and malaria, plus questions on deaths occurring to usual residents of the household during the two years preceding the survey. The Woman’s Questionnaire collects information on the survival status of all births and the age at death of children who died. The Woman’s Questionnaire also contains questions on child immunization coverage and sources; vitamin A supplementation for children; prevalence of acute respiratory infections, fever, and diarrhoea among children and the treatment of these illnesses; and mothers’ knowledge of oral rehydration therapy. 178 The information on child health and health-care practices was collected from mothers for children born since 1 January 1995 (in states where the fieldwork started in 1998) or 1 January 1996 (in states where the fieldwork started in 1999). If a woman had more than two live births during the three years preceding the survey, the information was collected for only the two most recent births. The information on child health presented in this chapter pertains to children born during the three years preceding the survey. 6.1 Crude Death Rates and Age-Specific Death Rates Table 6.1 shows crude death rates (CDR) and age-specific death rates by sex and by residence for the usual resident (de jure) population of India from NFHS-2 and the Sample Registration System (SRS). The SRS death rates are based on deaths to the usual resident population in 1997. The NFHS-2 death rates are based on the average annual number of deaths occurring to usual residents of the household during the two-year period preceding the survey (approximately 1997–98). The denominators for the NFHS-2 death rates are obtained by projecting the number of usual residents at the time of the survey backwards to the midpoint of the time period on the basis of the intercensal population growth rate in the country. The intercensal growth rate is assumed to be the same for all age and sex groups. Similarly, the rural intercensal growth rate is applied to all rural age and sex groups and the urban intercensal growth rate is applied to all urban age and sex groups. Questions on the number of deaths occurring to usual residents in each household during a particular time period have been included in demographic surveys in many countries and have often resulted in a substantial underreporting of deaths. The Sample Registration System (SRS), maintained by the Office of the Registrar General of India, provides a useful comparison. The most recent report on mortality estimates by age for India is for 1997 (Office of the Registrar General, 1999a). Table 6.1 shows an estimated average annual CDR for India of 9.7 deaths per 1,000 population based on NFHS-2 data (covering roughly 1997–98) compared with 8.9 from the 1997 SRS. Thus, contrary to expectations, the CDR estimated from NFHS-2 is slightly higher than the corresponding SRS estimate. NFHS-2 estimates of the CDR are also higher than the SRS estimates in both urban and rural areas. This suggests that reporting of deaths in NFHS-2 may be better than that in the SRS. The urban CDR estimated by NFHS-2 is 25 percent lower than the rural CDR. NFHS-2 age-specific death rates are higher than the SRS rates for most of the age groups. The most notable exception is the age group 0–4, where the NFHS-2 estimate is considerably lower than the SRS estimate. In most countries, male death rates are higher than female death rates at nearly all ages. South Asia generally has been an exception in this respect, with higher death rates for females over much of the age span (Tabutin and Willems, 1995; Preston, 1989; Ghosh, 1987). According to both NFHS-2 and the SRS, the male CDR in India is higher than the female CDR, but the age- specific death rates are slightly higher for females than for males through age 30, after which males generally have higher rates. 179 Table 6.1 Age-specific death rates and crude death rates Age-specific death rates and crude death rates (CDR) from NFHS-2 and the SRS by sex and residence, India NFHS-2 (1997–98) SRS (1997) Age Male Female Total Male Female Total URBAN 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+ CDR 13.1 11.3 12.2 0.9 1.4 1.2 1.2 0.9 1.1 1.7 1.9 1.8 1.4 1.5 1.4 3.0 2.3 2.6 4.0 2.1 3.1 2.9 2.7 2.8 5.5 2.3 4.0 8.8 4.4 6.7 13.1 9.3 11.4 16.1 8.7 12.3 24.5 20.9 22.8 34.1 30.2 32.1 103.2 103.4 103.3 8.3 7.3 7.8 12.5 13.8 13.1 1.0 1.2 1.1 0.9 0.7 0.8 1.0 1.5 1.2 1.8 2.0 1.9 2.1 2.1 2.1 2.9 1.9 2.4 3.5 2.0 2.8 4.4 3.6 4.0 7.5 5.5 6.6 12.5 7.3 10.1 18.2 11.2 14.8 28.2 18.2 23.2 46.2 30.8 38.2 88.4 73.7 80.7 7.0 6.0 6.5 RURAL 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+ CDR 19.5 20.6 20.0 2.1 2.4 2.2 1.0 1.5 1.2 1.8 2.7 2.2 3.2 4.7 4.0 2.9 3.5 3.2 4.3 2.8 3.5 4.2 3.8 4.0 6.3 4.0 5.2 9.0 7.1 8.1 15.1 11.8 13.6 16.3 11.9 13.9 29.8 27.3 28.6 40.9 27.8 34.6 99.5 111.3 104.5 10.7 10.0 10.4 24.2 27.2 25.6 2.0 2.7 2.3 1.2 1.3 1.3 1.4 2.4 1.9 2.3 3.1 2.7 2.8 2.9 2.9 3.5 3.2 3.3 4.0 3.2 3.6 6.6 4.2 5.4 9.6 5.8 7.8 14.7 11.0 12.9 20.1 14.9 17.5 33.4 23.1 28.1 46.4 35.3 40.7 90.0 78.6 84.2 9.8 9.4 9.6 TOTAL 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+ CDR 18.1 18.5 18.3 1.8 2.2 2.0 1.0 1.4 1.2 1.8 2.5 2.1 2.7 3.8 3.2 2.9 3.2 3.1 4.2 2.6 3.4 3.8 3.5 3.7 6.1 3.5 4.9 8.9 6.3 7.7 14.6 11.1 13.0 16.3 11.1 13.5 28.5 25.9 27.2 39.2 28.4 34.0 100.3 109.1 104.2 10.1 9.3 9.7 21.8 24.5 23.1 1.8 2.4 2.1 1.1 1.2 1.2 1.4 2.1 1.7 2.2 2.8 2.5 2.6 2.7 2.7 3.4 2.8 3.1 3.9 2.9 3.4 6.0 4.0 5.0 9.0 5.8 7.5 14.2 10.2 12.2 19.7 14.1 16.9 32.3 22.1 27.1 46.3 34.4 40.2 89.7 77.6 83.5 9.2 8.6 8.9 Note: Age-specific death rates and crude death rates (CDR) from NFHS-2 are based on the annual number of deaths reported for the de jure population during the two years preceding the survey. The SRS rates are also de jure, based on deaths during 1997. Rates are specified on a per-thousand basis. Source for SRS: Office of the Registrar General, 1999b 180 Table 6.2 provides comparisons among NFHS-1, NFHS-2, and SRS estimates of the CDR by state. For India as a whole, the CDR has remained at 9.7 per 1,000 since NFHS-1. The CDR from NFHS-2 ranges from 6.0 per 1,000 in Kerala to 12.9 per 1,000 in Orissa. Estimates for urban Nagaland and Sikkim seem low, perhaps mainly due to the small size of the samples. The CDR is higher in rural areas than in urban areas for all states except Delhi, Jammu and Kashmir, and Manipur. A comparison of NFHS-1 and NFHS-2 estimates by state shows that the CDR has declined in only 9 of the 23 states where data are available from both surveys. The CDR appears to have increased most markedly in the smaller northeastern states between the two surveys. It should be pointed out that the sampling errors are relatively large in these states due to the small size of the samples in both surveys. Table 6.2 Crude death rates by state Crude death rates (CDR) from NFHS-1, NFHS-2, and the SRS by residence and state, India NFHS-1 (1991–92) NFHS-2 (1997–98) SRS (1997) State Urban Rural Total Urban Rural Total Urban Rural Total India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 7.6 10.4 9.7 8.0 4.1 7.8 8.1 9.3 9.0 6.5 8.6 8.4 U U U 7.2 7.0 7.1 7.2 7.9 7.8 9.1 10.7 10.3 7.7 13.0 11.9 9.0 12.0 11.5 7.4 11.6 11.0 8.6 10.2 9.7 0.8 9.1 8.2 7.0 11.9 11.3 5.3 6.1 5.8 6.6 6.1 6.2 4.2 2.7 3.4 1.7 2.0 1.9 U U U 5.9 7.1 6.5 7.2 10.2 9.1 7.3 8.1 7.7 7.4 9.2 8.7 6.2 8.1 7.5 6.1 6.3 6.2 7.3 11.0 9.7 7.8 10.4 9.7 7.9 6.8 7.8 7.4 8.4 8.1 7.4 8.3 8.3 9.1 8.0 8.3 7.1 9.0 8.4 8.8 10.6 10.2 8.7 10.7 10.2 7.9 10.8 10.2 8.3 11.6 11.2 9.2 13.4 12.9 7.3 8.7 8.3 12.1 12.5 12.4 6.1 9.7 9.4 9.8 8.7 9.0 7.6 10.4 9.9 6.0 8.7 7.3 4.3 7.6 6.9 3.3 6.8 6.3 8.7 11.1 10.1 7.6 8.3 8.0 7.8 9.9 9.0 7.7 11.7 10.7 6.9 8.4 7.9 5.7 6.1 6.0 8.1 12.2 10.8 6.5 9.6 8.9 5.4 5.4 5.4 6.9 8.3 8.0 5.9 8.3 8.1 U U U 6.1 7.8 7.4 9.4 9.3 8.9 7.7 11.7 11.0 8.2 10.7 10.3 6.8 10.4 10.0 7.5 11.3 10.9 7.2 7.9 7.7 2.0 6.1 5.8 5.9 10.3 9.9 6.2 5.8 5.9 4.4 9.7 8.8 3.7 5.7 4.8 2.7 U U 3.5 6.6 6.5 7.2 8.0 7.7 6.2 8.3 7.6 5.4 8.6 7.3 5.9 9.1 8.3 5.4 8.5 7.6 6.1 6.3 6.2 6.7 8.7 8.0 Note: Crude death rates (CDR) from NFHS-1 and NFHS-2 are based on the annual number of deaths reported for the de jure population during the two years preceding the survey. The SRS rates are also de jure, based on deaths during 1997. Rates are specified on a per-thousand basis. U: Not available Source for SRS: Office of the Registrar General, 1999a 181 Table 6.2 also shows the CDRs for the year 1997 from the SRS for 23 states for which the SRS has published statewise estimates. The SRS estimates are lower than the NFHS-2 estimates in 18 of the 23 states. This may reflect greater underestimation of deaths in the SRS than in NFHS-2. 6.2 Infant and Child Mortality Infant and child mortality rates reflect a country’s level of socioeconomic development and quality of life and are used for monitoring and evaluating population and health programmes and policies. NFHS-2 asked all ever-married women age 15–49 to provide a complete history of their births including, for each live birth, the sex, month and year of birth, survival status, and age at the time of the survey or age at death. Age at death was recorded in days for children dying in the first month of life, in months for other children dying before their second birthday, and in years for children dying at later ages. This information was used to calculate the following direct estimates of infant and child mortality1: Neonatal mortality: The probability of dying in the first month of life Postneonatal mortality: The probability of dying after the first month of life but before the first birthday Infant mortality (1q0): The probability of dying before the first birthday Child mortality (4q1): The probability of dying between the first and fifth birthdays Under-five mortality (5q0): The probability of dying before the fifth birthday Assessment of Data Quality The reliability of mortality estimates calculated from retrospective birth histories depends upon the completeness with which deaths of children are reported and the extent to which birth dates and ages at death are accurately reported and recorded. Estimated rates of infant and child mortality are subject to both sampling and nonsampling errors. While sampling errors for various mortality estimates are provided in Appendix C, this section describes the results of various checks for nonsampling errors—in particular, underreporting of deaths in early childhood (which would result in an underestimate of mortality) and misreporting of the date of birth or age at death (which could distort the age pattern of under-five mortality). Both problems are likely to be more pronounced for children born further in the past than for children born recently. Underreporting of infant deaths is usually most serious for deaths that occur very early in infancy. If deaths in the early neonatal period are selectively underreported, there will be an abnormally low ratio of deaths under seven days to all neonatal deaths and an abnormally low ratio of neonatal to infant mortality. Changes in these ratios over time can be examined to test the 1A detailed description of the method for calculating the probabilities presented here is given in Rutstein (1984). The mortality estimates are not rates, but are true probabilities, calculated according to the conventional life-table approach. Deaths and exposure in any calendar period are first tabulated for the age intervals 0, 1–2, 3–5, 6–11, 12–23, 24–35, 36–47, and 48–59 months. Then age-interval-specific probabilities of survival are calculated. Finally, probabilities of mortality for larger age segments are produced by multiplying the relevant age-interval survival probabilities together and subtracting the product from one: i=x+n nqx = 1–Π (1 – qi) i=x 182 hypothesis that underreporting of early infant deaths is more common for births that occurred further in the past than for births that occurred more recently. Failure to report deaths will result in mortality figures that are too low and if underreporting is more severe for children born longer ago than children born recently, any decline in mortality will tend to be understated. Results from Table D.5 (Appendix D) suggest that early neonatal deaths have not been seriously underreported in India as a whole in NFHS-2, since the ratios of deaths under seven days to all neonatal deaths are consistently high (between 70 and 74 percent) for the different time periods preceding the survey (a ratio of less than 25 percent is often used as a guideline to indicate underreporting of early neonatal deaths). The ratios decline slightly over time, from 74 in the five years preceding the survey to 70 in the period 10–14 years preceding the survey, indicating that some early infant deaths may not have been reported by older women. The ratios of infant deaths that occurred during the neonatal period (Appendix Table D.6) are also consistently high (between 64 and 67 percent) for the different time periods preceding the survey, and again they increase slightly over time. Another problem inherent in most retrospective surveys is heaping of age at death on certain digits, e.g., 6, 12, and 18 months. If the net result of age misreporting is the transference of deaths between age segments for which the rates are calculated, misreporting of the age at death will bias estimates of the age pattern of mortality. For instance, an overestimate of child mortality relative to infant mortality may result if children dying during the first year of life are reported as having died at age one year or older. Thus, heaping at 12 months can bias the mortality estimates because a certain fraction of these deaths, which are reported to have occurred after infancy (i.e., at ages 12–23 months), may have actually occurred during infancy (i.e., at ages 0–11 months). In such cases, heaping would bias infant mortality (1q0) downward and child mortality (4q1) upward. In NFHS-2, there appears to be some preference for reporting age at death at 3, 5, 8, 10, 12, 15, 20, and 25 days (Table D.5 in Appendix D). An examination of the distribution of deaths under age two years during the 15 years preceding the survey by month of death (Appendix Table D.6) indicates some heaping of deaths at 6, 12, and 18 months of age. Heaping at 12 months and reporting of the age at death as ‘one year’ are substantial despite the strong emphasis on this problem during the training of interviewers for the NFHS-2 fieldwork2. Nevertheless, even if one-third of the deaths reported at age 12 months or age one year actually occurred at less than 12 months of age, the infant mortality rate for the five years before the survey would be underestimated by only 2 percent. An examination of the distribution of births and deaths since 1988 (Table D.4 in Appendix D) suggests that there may be some underreporting of deaths in the most recent five- year period. The proportion of deaths to births decreases from 11 percent in 1988 to 6 percent in 1998. Some of this decrease undoubtedly reflects a real reduction in mortality during that period and some reflects the fact that younger children have had less exposure to the risk of mortality. However, the sharp disjuncture in the proportion of deaths between 1994 and 1995 may be due partly to underreporting of deaths relative to births during the most recent period. 2Interviewers were trained to probe for the exact number of months lived by the child if the age at death was reported as ‘one year’. 183 It is seldom possible to establish mortality levels with confidence for a period of more than 15 years before a survey. Even within the recent 15-year period considered here, apparent trends in mortality rates should be interpreted with caution for several reasons. First, there may be differences in the completeness of death reporting related to the length of time before the survey. Second, the accuracy of reports of age at death and of date of birth may deteriorate with time. Third, sampling variability of mortality rates tends to be high, especially for groups with relatively few births. Fourth, mortality rates are truncated as they go back in time because women currently age 50 or above who were bearing children during earlier periods were not included in the survey. This truncation affects mortality trends, in particular. For example, for the period 10–14 years before the survey, the rates do not include any births for women age 40–49 since these women were over age 50 at the time of the survey and were not eligible to be interviewed. Since these excluded births to older women were likely to be at a somewhat greater risk of dying than births to younger women, the mortality rates for the period may be slightly underestimated. Estimates for more recent periods are less affected by truncation bias since fewer older women are excluded. The extent of this bias depends on the proportion of births omitted. Table 4.26 (Chapter 4) shows that less than 5 percent of the children born in the three years before the survey were born to women age 35 and above. Given the small proportion of births excluded, selection bias for infant and child mortality statistics as far back as 15 years before the survey should be negligible. Levels, Trends, and Differentials in Infant and Child Mortality Table 6.3 and Figure 6.1 present various measures of infant and child mortality by residence for the three five-year periods preceding the survey. Infant mortality in India declined from 86 deaths per 1,000 live births during 1984–88 (10–14 years before the survey) to 68 deaths per 1,000 live births during 1994–98 (0–4 years before the survey), an average rate of decline of nearly 2 infant deaths per 1,000 live births per year. A comparison of the infant mortality rate for the period 0–4 years before NFHS-2 (68 deaths per 1,000 live births) with the infant mortality rate 0–4 years before NFHS-1 (79 deaths per 1,000 live births) suggests a similar rate of decline of 11 deaths per 1,000 live births over the six and one-half years between the two surveys. The NFHS-2 infant mortality rate for the period 5–9 years before the survey (78) is slightly lower than the NFHS-1 infant mortality rate for the period 0–4 years before the survey, so the results from the two surveys are quite compatible for these years. All other measures of infant and child mortality presented in Table 6.3 have also declined during the past 15 years. Despite the overall decline in infant and child mortality, however, 1 in every 15 children born during the five years before NFHS-2 died within the first year of life, and 1 in every 11 children died before reaching age five. Clearly, child survival programmes in India need to be intensified to achieve further reductions in infant and child mortality. Rural mortality rates are considerably higher than urban mortality rates. Child mortality is almost twice as high in rural areas as in urban areas, neonatal mortality is 47 percent higher in rural areas, postneonatal mortality is 73 percent higher in rural areas, and infant mortality is 56 percent higher in rural areas. Under-five mortality is 64 percent higher in rural areas than in urban areas. 184 Table 6.3 Infant and child mortality Neonatal, postneonatal, infant, child, and under-five mortality rates for five-year periods preceding the survey by residence, India, 1998–99 Years preceding the survey Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) URBAN 0–4 5–9 10–14 31.7 15.4 47.0 16.9 63.1 35.1 16.1 51.2 17.2 67.5 42.1 22.9 65.1 23.1 86.7 RURAL 0–4 5–9 10–14 46.7 26.6 73.3 32.8 103.7 56.3 29.2 85.5 36.4 118.8 58.4 34.2 92.6 45.0 133.4 TOTAL 0–4 5–9 10–14 43.4 24.2 67.6 29.3 94.9 51.7 26.4 78.0 31.9 107.4 54.5 31.4 85.9 39.3 121.9 Note: The first five-year period preceding the survey does not include the month in which the interview took place. Rates are specified on a per-thousand basis. See text for definition of rates. 1Computed as the difference between the infant and neonatal mortality rates Figure 6.1 Infant Mortality Rates for Five-Year Periods by Residence 86 73 65 86 93 51 78 47 68 0 10 20 30 40 50 60 70 80 90 100 Total Urban Rural P e r 1 ,0 0 0 B ir th s 10-14 years ago 5-9 years ago 0-4 years ago Note: Rates are for five-year periods preceding the survey NFHS-2, India, 1998–99 185 All infant and child mortality rates declined steadily in both urban and rural areas of India during the 15 years preceding NFHS-2. Infant mortality in rural areas declined from 93 deaths per 1,000 live births during 1984–88 to 73 deaths per 1,000 live births during 1994–98. Neonatal mortality declined by 20 percent and postneonatal mortality declined by 22 percent in rural areas over the same period. In urban areas, infant mortality declined from 65 deaths per 1,000 live births during 1984–88 to 47 deaths per 1,000 live births during 1994–98. Neonatal and postneonatal mortality in urban areas declined by 25 percent and 33 percent, respectively. A comparison with corresponding figures from NFHS-1 shows a decline in every rural and urban estimate of infant and child mortality for the five-year period before each survey. The estimated NFHS-2 infant mortality rate of 68 deaths per 1,000 live births during 1994–98 is somewhat lower than the SRS value of 73 deaths per 1,000 live births averaged for the period 1994–98. This difference between NFHS-2 and the average SRS infant mortality rates is significant statistically (the lower and upper confidence limits for the NFHS-2 estimate are 64.7 and 70.4, respectively (Appendix Table C.2)). The NFHS-2 estimate of the infant mortality rate for rural areas is also lower than the average SRS estimate over the same period (73 deaths per 1,000 live births from NFHS-2 compared with 78 deaths per 1,000 live births from the SRS). The NFHS-2 estimate for urban areas is the same as the average SRS estimate for urban areas (47 deaths per 1,000 live births). Socioeconomic Differentials in Infant and Child Mortality The probability of dying in early childhood is higher in some population groups than in others. Table 6.4 and Figure 6.2 present differentials in infant and child mortality rates for the 10-year period preceding the survey by selected background characteristics. Children in rural areas of India experience a 70 percent higher probability of dying before their fifth birthday than urban children, slightly more than the 64 percent differential in the most recent five-year period shown in Table 6.3. The overall infant mortality rate declines sharply with increasing education of mothers, as expected, ranging from a high of 87 deaths per 1,000 live births for illiterate mothers to a low of 33 deaths per 1,000 live births for mothers who have at least completed high school. Other mortality indicators shown in the table vary similarly with mother’s education. As one would expect, mother’s education has a stronger negative effect on postneonatal and child mortality than on neonatal mortality (which is strongly affected by biological factors). All the infant and child mortality rates are much higher for Hindus than for Muslims. The infant mortality rate is 31 percent higher and the child mortality rate is 28 percent higher for Hindu children than for Muslim children. These findings are consistent with those of NFHS-1, which also recorded much higher rates of infant and child mortality for Hindus than Muslims in India. Mortality differentials by religion presumably reflect influences other than religion alone. For example, a larger proportion of Muslims than Hindus in India live in urban areas, where mortality rates are generally low. This is confirmed by a study based on NFHS-1 data, which noted that the difference in infant and child mortality rates between Hindu and Muslim children is reduced considerably when other demographic and socioeconomic variables are controlled statistically (Pandey et al., 1998). 186 Table 6.4 Infant and child mortality by background characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey by selected background characteristics and residence, India, 1998–99 Background characteristic Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) URBAN Mother’s education Illiterate Literate, < middle complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 44.1 23.8 67.8 28.8 94.7 30.8 11.8 42.6 14.7 56.7 29.5 13.3 42.8 9.2 51.6 22.2 8.2 30.4 3.7 34.0 36.6 16.7 53.3 17.2 69.6 25.9 14.0 39.8 18.8 57.9 29.6 8.0 37.5 10.9 48.0 21.8 18.8 40.6 13.1 53.1 (44.5) (4.7) (49.2) (0.0) (49.2) (17.5) (9.2) (26.7) (6.1) (32.6) (2.0) (8.7) (10.7) (5.9) (16.6) * * * * * 40.1 20.2 60.4 25.2 84.0 35.6 22.1 57.6 23.4 79.6 35.3 15.8 51.2 16.3 66.6 29.8 13.7 43.5 14.1 57.0 48.8 27.3 76.1 39.1 112.2 34.6 16.9 51.5 17.6 68.2 24.1 8.9 33.0 6.6 39.4 33.5 15.8 49.2 17.0 65.4 RURAL Mother’s education Illiterate Literate, < middle complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 57.0 32.4 89.4 41.5 127.2 44.0 20.3 64.3 20.0 82.9 36.1 15.0 51.1 11.4 61.9 26.9 8.8 35.7 5.6 41.1 53.8 29.1 82.8 36.3 116.2 43.6 23.8 67.5 28.6 94.1 30.0 24.0 53.9 23.3 76.0 42.5 14.3 56.8 12.0 68.2 * * * * * 58.7 18.2 76.9 20.9 96.2 63.6 27.4 91.0 23.4 112.2 (48.5) (36.0) (84.5) (83.0) (160.5) 56.2 31.9 88.1 43.0 127.3 55.1 31.8 86.9 48.8 131.4 54.7 27.6 82.2 32.7 112.2 45.1 24.2 69.3 25.6 93.1 56.5 33.7 90.2 45.8 131.8 50.7 25.3 76.0 28.8 102.6 37.4 14.7 52.1 11.7 63.2 51.7 28.0 79.7 34.6 111.5 187 Children of women belonging to scheduled castes and scheduled tribes have higher rates of infant and child mortality than children of women belonging to other backward classes or ‘other’ women. Children of ‘other’ women have by far the lowest rates of infant and child mortality. As expected, all indicators of infant and child mortality decline substantially with increases in the household standard of living. For example, for children in households with a high standard of living the infant mortality rate is 43 deaths per 1,000 live births and the under- five mortality rate is 52 deaths per 1,000 live births; the corresponding rates for children in households with a low standard of living are more than twice as high at 89 and 130, respectively. The postneonatal mortality rate is almost three times as high in households with a low standard of living as in households with a high standard of living, the child mortality rate is almost five times as high, and the neonatal mortality rate is almost twice as high. Similar differentials in infant and child mortality by mothers’ education, religion, caste/tribe, and living standard are observed in both urban and rural areas. Table 6.4 Infant and child mortality by background characteristics (contd.) Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey by selected background characteristics and residence, India, 1998–99 Background characteristic Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) TOTAL Mother’s education Illiterate Literate, < middle complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 55.3 31.2 86.5 39.7 122.8 40.5 18.0 58.5 18.4 75.8 33.7 14.4 48.1 10.5 58.1 24.3 8.5 32.8 4.4 37.1 50.4 26.7 77.1 32.4 107.0 38.0 20.8 58.8 25.4 82.7 29.8 19.4 49.2 19.7 68.0 38.0 15.3 53.3 12.3 64.9 (36.3) (10.5) (46.7) (11.3) (57.5) 39.5 14.0 53.6 14.1 66.9 55.5 24.7 80.3 20.9 99.4 (45.4) (32.1) (77.6) (77.2) (148.8) 53.2 29.8 83.0 39.5 119.3 53.3 30.9 84.2 46.3 126.6 50.8 25.2 76.0 29.3 103.1 40.7 21.1 61.8 22.2 82.6 55.8 33.1 88.8 45.2 130.0 47.0 23.4 70.3 26.1 94.6 30.9 11.8 42.7 9.1 51.5 47.7 25.3 73.0 30.6 101.4 Note: The 10-year period preceding the survey does not include the month in which the interview took place. Rates are specified on a per-thousand basis. See text for definition of rates. Total includes children with missing information on mother’s education, religion, caste/tribe, and the standard of living index, whose mortality rates are not shown separately. ( ) Based on 250–499 children surviving to the beginning of the age interval *Rates not shown; based on fewer than 250 children surviving to the beginning of the age interval 1Computed as the difference between the infant and neonatal mortality rates 188 Demographic Differentials in Infant and Child Mortality This section examines differentials in early childhood mortality by demographic characteristics of the child and the mother. Table 6.5 and Figure 6.3 present various indicators of infant and child mortality for the 10 years preceding the survey by sex of the child, mother’s age at childbirth, birth order, length of the previous birth interval, medical care received by the mother during pregnancy, delivery, and the early postpartum period, and size of the child at the time of birth. Table 6.5 shows that the female mortality rate below age five years is slightly higher than the male mortality rate (105 deaths per 1,000 live births for females compared with 98 deaths per 1,000 live births for males). This pattern is evident in rural areas, but not in urban areas. Excess female mortality occurs mainly after the first year of life. The infant mortality rate during the 10- year period before the survey is slightly higher for boys (75 deaths per 1,000 live births) than for girls (71 deaths per 1,000 live births), but the child mortality rate (4q1) is considerably higher for girls (37 deaths per 1,000) than for boys (25 deaths per 1,000). This reversal of sex differentials in mortality with increasing age has been observed in other studies in South Asia and is thought to reflect the relative medical and nutritional neglect of the girl-child (Das Gupta, 1987; Basu, 1989). Figure 6.2 Infant Mortality Rates by Selected Background Characteristics 87 59 48 33 77 59 49 53 47 54 80 78 89 70 43 MOTHER'S EDUCATION Illiterate Literate, < Middle School Complete Middle School Complete High School Complete and Above RELIGION Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No Religion STANDARD OF LIVING INDEX Low Medium High Infant Mortality Rate 0 10 20 30 40 50 60 70 80 90 100 NFHS-2, India, 1998–99 189 Table 6.5 Infant and child mortality by demographic characteristics Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey by selected demographic characteristics and residence, India, 1998–99 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under- five mortality (5q0) URBAN Sex of child Male Female Mother’s age at birth < 20 20–29 30–39 40–49 Birth order 1 2 3 4 5 6+ Previous birth interval < 24 months 24–47 months 48+ months Medical care2 No care One or two types of care All three types of care Birth size3 Large Average Small Very small 37.8 16.0 53.8 14.6 67.6 28.8 15.5 44.3 19.7 63.1 48.4 19.3 67.7 21.3 87.5 28.1 14.4 42.4 14.2 56.0 36.6 17.1 53.7 23.5 75.9 * * * * * 34.3 13.7 48.1 9.1 56.8 32.3 12.6 44.8 14.3 58.5 26.8 15.7 42.5 19.5 61.1 36.6 19.4 56.0 25.7 80.3 29.9 21.1 50.9 21.0 70.8 47.9 27.4 75.4 37.5 110.0 49.4 23.1 72.6 27.8 98.3 26.9 15.4 42.2 19.6 61.0 17.9 7.9 25.9 8.8 34.4 46.2 20.0 66.2 U U 35.8 19.3 55.1 U U 21.8 8.2 30.1 U U 31.0 9.3 40.3 U U 21.5 13.9 35.4 U U 43.5 23.1 66.6 U U (106.5) (17.5) (124.0) U U 190 Table 6.5 Infant and child mortality by demographic characteristics (contd.) Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey by selected demographic characteristics and residence, India, 1998–99 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under- five mortality (5q0) RURAL Sex of child Male Female Mother’s age at birth < 20 20–29 30–39 40–49 Birth order 1 2 3 4 5 6+ Previous birth interval < 24 months 24–47 months 48+ months Medical care2 No care One or two types of care All three types of care Birth size3 Large Average Small Very small 54.3 26.4 80.7 27.9 106.4 49.0 29.7 78.6 41.7 117.0 66.1 31.8 97.9 33.1 127.7 44.7 25.3 70.0 33.5 101.2 52.0 30.9 83.0 41.4 121.0 60.8 47.5 108.4 53.3 155.9 58.8 25.4 84.2 22.4 104.7 47.5 25.0 72.6 29.5 100.0 41.6 25.2 66.8 38.0 102.2 46.5 30.4 76.9 39.5 113.3 52.4 28.8 81.2 46.6 124.1 65.0 40.6 105.6 52.3 152.4 77.4 41.6 119.0 55.1 167.5 37.5 24.3 61.9 34.4 94.2 26.0 16.5 42.5 15.2 57.0 54.2 36.8 90.9 U U 35.8 19.0 54.7 U U 22.4 14.5 36.9 U U 33.4 21.1 54.6 U U 32.4 21.6 54.0 U U 48.5 29.7 78.2 U U 111.2 42.6 153.8 U U 191 Table 6.5 Infant and child mortality by demographic characteristics (contd.) Neonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year period preceding the survey by selected demographic characteristics and residence, India, 1998–99 Demographic characteristic Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under- five mortality (5q0) TOTAL Sex of child Male Female Mother’s age at birth < 20 20–29 30–39 40–49 Birth order 1 2 3 4 5 6+ Previous birth interval < 24 months 24–47 months 48+ months Medical care2 No care One or two types of care All three types of care Birth size3 Large Average Small Very small 50.7 24.2 74.8 24.9 97.9 44.6 26.6 71.1 36.7 105.2 63.1 29.7 92.7 31.0 120.8 40.7 22.6 63.3 28.7 90.2 48.7 27.9 76.7 37.4 111.2 61.9 44.3 106.2 57.2 157.4 52.4 22.4 74.9 18.9 92.3 43.8 22.0 65.7 25.7 89.8 38.5 23.2 61.7 33.9 93.5 44.7 28.4 73.1 36.8 107.3 48.7 27.5 76.2 42.0 115.0 62.5 38.6 101.1 49.8 145.9 71.7 37.8 109.5 49.2 153.3 35.5 22.6 58.1 31.4 87.7 24.1 14.4 38.5 13.6 51.5 53.6 35.5 89.1 U U 35.8 19.0 54.8 U U 22.2 11.8 34.0 U U 32.8 18.1 50.9 U U 30.0 19.9 49.9 U U 47.5 28.3 75.9 U U 110.1 37.0 147.2 U U Note: The period preceding the survey does not include the month in which the interview took place. Rates are specified on a per-thousand basis. See text for definition of rates. U: Not available ( ) Based on 250–499 children surviving to the beginning of the age interval *Rates not shown; based on fewer than 250 children surviving to the beginning of the age interval 1Computed as the difference between the infant and neonatal mortality rates 2Medical care includes (i) antenatal care received from a health worker, (ii) delivery assistance given by a doctor, nurse, trained midwife, or other health professional, and (iii) postnatal care received in a health facility or at home within two months of delivery; rates are for the three-year period preceding the survey. 3Birth size as reported by the mother; rates are for the three-year period preceding the survey. 192 The lower female than male infant mortality rate in India results from considerably higher neonatal mortality among boys (51 deaths per 1,000) than among girls (45 deaths per 1,000) coupled with slightly higher female than male mortality rates during the postneonatal period. For both social and biological reasons, infant mortality rates and child mortality rates often exhibit a U-shaped pattern with respect to the mother’s age at childbirth, with children of the youngest and oldest mothers experiencing higher mortality rates than children whose mothers are in their prime reproductive ages. Children born to young mothers are more likely to be of low birth weight, which is probably an important factor contributing to their higher neonatal mortality rate. Similarly, children born to mothers above age 30 are at a relatively high risk of experiencing congenital problems. The expected U-shaped pattern of mortality by mother’s age is observed for all indicators of infant and child mortality in India. Birth order also tends to have a U-shaped relationship to infant deaths, with first births and high-order births having elevated mortality rates. In Table 6.5 and Figure 6.3, birth order shows the expected U-shaped pattern for neonatal and infant mortality rates. This association is likely to reflect not only the effect of birth order but also the effect of the age of the mother at childbirth. Postneonatal mortality and child mortality rates tend to increase with birth order. The Figure 6.3 Infant Mortality Rates by Selected Demographic Characteristics 39 58 110 101 76 73 62 66 75 106 77 63 93 71 75 SEX OF CHILD Male Female MOTHER'S AGE AT BIRTH < 20 20–29 30–39 40–49 BIRTH ORDER 1 2 3 4 5 6+ PREVIOUS BIRTH INTERVAL < 24 Months 24–47 Months 48+ Months Infant Mortality Rate 0 20 40 60 80 100 120 Note: Based on births in the 10 years preceding the survey (1989–98) NFHS-2, India, 1998–99 193 under-five mortality rate declines slightly from the first birth order to the second birth order and then increases steadily with birth order. The increase in the child mortality rate with birth order may reflect a more intense competition faced by higher birth-order children for the caregiver’s time, for medical resources, and for nutritious food when children are weaned. It is also likely that higher birth-order children are disproportionately from lower socioeconomic groups, in which mortality tends to be higher. The timing of successive births has a powerful effect on the survival chances of children in India. Infant and child mortality rates decrease sharply as the length of the previous birth interval increases, and all measures are especially high for children born less than 24 months after a previous birth. The infant mortality rate is almost three times as high for children with a previous birth interval of less than 24 months as for children with a previous interval of 48 months or more (110 deaths compared with 39 deaths per 1,000 live births). The previous birth interval has a similar effect on all other indicators of infant and child mortality shown in Table 6.5. Although the length of the previous birth interval is likely to affect mortality risks directly, a substantial portion of the association between birth intervals and mortality risks may reflect the effect of factors that are correlated with birth intervals. For example, shorter birth intervals are likely to occur in large families, and large families tend to come from lower socioeconomic groups and are more likely than other families to live in rural areas where medical facilities and other survival-enhancing resources are less readily available. Nevertheless, multivariate analyses of birth-interval effects and child survival commonly find an association between short birth intervals (less than 24 months) and increased mortality even after controlling for other demographic and socioeconomic characteristics (Retherford et al., 1989). Antenatal, delivery, and postnatal care are usually associated with lower infant mortality. Table 6.5 shows that children of women who receive all three types of care have considerably lower risk of neonatal and postneonatal mortality than those with only one or two types of care. Mortality rates are highest for children of mothers who receive none of the three types of pregnancy-related care. Another important determinant of the survival chances of children is the baby’s weight at the time of birth. Many studies have found that low birth weight babies (under 2,500 grams) have a substantially increased risk of mortality. Because most babies in India are not weighed at the time of birth, in addition to birth weight, mothers were asked whether babies born during the three years preceding the survey were “large, average, small, or very small” at birth. The last panel in Table 6.5 shows neonatal, postneonatal, and infant mortality rates by birth size. Children who are perceived by their mothers to be smaller than average at birth experience much higher mortality risks than children perceived to be of average size or larger. Mortality among children perceived to be very small is markedly higher. Table 6.5 also shows demographic differentials in infant and child mortality separately for urban and rural areas. In both urban and rural areas, the pattern of demographic differentials is similar to that for the country as a whole. Table 6.6 and Figure 6.4 present variations in infant and child mortality rates by state. Infant mortality rates vary dramatically from one state to another, ranging from 16 in Kerala to more than 86 in Meghalaya, Uttar Pradesh, and Madhya Pradesh. Other states with infant mortality rates above the national average are Orissa (81), Rajasthan (80), Bihar (73), and Assam 194 (70). The child mortality rate (4q1) also varies considerably in India, ranging from 3 in Kerala to 56 in Madhya Pradesh. Other states with child mortality above the national average are Uttar Pradesh, Rajasthan, Arunachal Pradesh, Meghalaya, and Bihar. Table 6.6 Infant and child mortality by state Neonatal, postneonatal, infant, child, and under-five mortality rates for the five-year period preceding the survey by state, India, 1998–99 State Neonatal mortality (NN) Postneonatal mortality1 (PNN) Infant mortality (1q0) Child mortality (4q1) Under-five mortality (5q0) India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 43.4 24.2 67.6 29.3 94.9 29.5 17.4 46.8 9.0 55.4 34.9 21.9 56.8 21.2 76.8 22.1 12.3 34.4 8.3 42.4 40.3 24.7 65.0 16.1 80.1 34.3 22.8 57.1 15.9 72.1 49.5 30.9 80.4 37.6 114.9 54.9 31.2 86.1 56.4 137.6 53.6 33.1 86.7 39.2 122.5 46.5 26.4 72.9 34.7 105.1 48.6 32.3 81.0 25.5 104.4 31.9 16.8 48.7 19.9 67.6 41.8 21.3 63.1 37.4 98.1 44.6 24.9 69.5 21.4 89.5 18.6 18.4 37.0 19.9 56.1 50.7 38.3 89.0 36.2 122.0 18.8 18.2 37.0 18.4 54.7 20.1 22.0 42.1 22.7 63.8 26.3 17.6 43.9 28.4 71.0 31.2 5.5 36.7 10.5 46.8 39.6 23.0 62.6 24.0 85.1 32.0 11.7 43.7 15.0 58.1 43.8 22.1 65.8 21.0 85.5 37.1 14.4 51.5 19.3 69.8 13.8 2.5 16.3 2.6 18.8 34.8 13.3 48.2 15.9 63.3 1Computed as the difference between the infant and neonatal mortality rates 195 6.3 Maternal Mortality Worldwide, about 500,000 women die every year from pregnancy and childbirth related causes and most of these deaths occur in developing countries (World Health Organization, 1999). Although reliable national estimates of maternal mortality are not available for most countries, South Asia is thought to have among the highest maternal mortality rates in the world. Most demographic surveys do not have samples that are large enough to produce reliable direct estimates of maternal mortality. The NFHS samples, however, are large enough to estimate maternal mortality at the national level for the two-year period preceding each survey. The NFHS estimates are based on a series of questions in the Household Questionnaire about deaths occurring to usual residents of the household since January of the second calendar year preceding the start of the survey in each state. In the case of deaths to women age 15–49 (13–49 in NFHS-1), a series of follow-up questions was asked about whether the women was pregnant when she died, whether the death occurred during childbirth, whether she died within two months after the end of a pregnancy or childbirth, and whether the death was due to a complication of the pregnancy or childbirth. Figure 6.4 Infant Mortality Rate by State 0 10 20 30 40 50 60 70 80 90 100 Meghalaya Uttar Pradesh Madhya Pradesh Orissa Rajasthan Bihar Assam INDIA Andhra Pradesh Jammu & Kashmir Arunachal Pradesh Gujarat Punjab Haryana Karnataka West Bengal Tamil Nadu Delhi Sikkim Maharashtra Nagaland Mizoram Manipur Goa Himachal Pradesh Kerala Infant Mortality Rate Note: Based on births in the five years preceding the survey (1994–98) NFHS-2, India, 1998–99 196 On the basis of this information, it is possible to calculate the maternal mortality ratio (MMR), which is defined here as the number of maternal deaths to women age 15–49 per 100,000 live births. This measure is based on the annual number of female deaths to usual residents of the sample households that occurred during childbirth or within two months after the end of a pregnancy or childbirth. The average maternal mortality ratio at the national level for the two-year period preceding NFHS-2 is 540 deaths per 100,000 live births. The corresponding value for the two-year period preceding NFHS-1 was 424 deaths per 100,000 live births (revised using a two-year general fertility rate as in the calculation of the NFHS-2 maternal mortality ratio), suggesting a considerable increase in the maternal mortality ratio in the country. However, it should be noted that despite the large size of the NFHS-1 and NFHS-2 samples, sampling errors for the maternal mortality estimates are quite large. The 95 percent confidence interval for the maternal mortality ratio ranges from 428 to 653 per 100,000 live births for NFHS-2 and from 324 to 524 per 100,000 live births for NFHS-1. There is considerable overlap in the confidence intervals from the two surveys, indicating that the difference between the NFHS-1 and NFHS-2 estimates of MMR is not significant statistically. In both NFHS-1 and NFHS-2, the rural MMR is much higher than urban MMR (434 compared with 385 in NFHS-1 and 619 compared with 267 in NFHS-2). The confidence intervals are even wider for the urban and rural estimates. Because of large sampling errors, there is no easy way to assess the completeness and accuracy of these estimates, and reliable maternal mortality ratios cannot be calculated for individual states or population subgroups. Other estimates of the maternal mortality ratio for India range from 407 for 1998 from the Sample Registration System (Office of the Registrar General, 2000) to 570 for 1990 from the World Health Organization (WHO, 1999). The two NFHS estimates—424 from NFHS-1 for 1991–92 and 540 from NFHS-2 for 1997–98—are of the same order of magnitude as these other estimates. All of these estimates imply that more than 100,000 women in India die every year from causes related to pregnancy and childbirth. This finding reinforces the urgency of ensuring that all pregnant women receive adequate antenatal care during pregnancy and that deliveries take place under hygienic conditions with the assistance of trained medical practitioners. 6.4 Morbidity There is limited experience in collecting morbidity data from population-based demographic sample surveys. NFHS-1 collected data on five major morbidity conditions—partial and complete blindness, tuberculosis, leprosy, physical impairment of the limbs, and malaria— among all persons in the sampled households. The results were found to be generally plausible and useful. For these reasons, it was decided to include similar morbidity questions in NFHS-2. In NFHS-2, questions on blindness, leprosy, and physical impairment of the limbs were replaced by questions on asthma and jaundice. The questions on tuberculosis and malaria were retained, and a question on medical treatment of tuberculosis was added to get a better measure of the prevalence of tuberculosis. The household head or other knowledgeable adult in the household reported morbidity for all household members, and no effort was made to do clinical tests for any of the disease conditions. Table 6.7 shows the prevalence of asthma, tuberculosis, jaundice, and malaria in the household population by age, sex, and place of residence. There are several reasons why the results of NFHS-2 may understate the prevalence of these conditions. Respondents may 197 underreport diseases carrying a stigma, such as tuberculosis, due to intentional concealment. Underestimation may also occur because the household respondents are unaware that they or other members of the household have the condition. It is also possible that the respondents know that a household member suffers from a given condition but fail to report it because they do not recognize the term used by the enumerator to describe the condition. On the other hand, a factor contributing to a possible overestimation of prevalence without clinical verification is that some other disease can be mistaken by the respondent as one of the listed diseases; for example, chronic bronchitis may be reported as asthma or tuberculosis, or common flu may be reported as malaria. Table 6.7 Morbidity Number of persons per 100,000 usual household residents suffering from asthma, tuberculosis, jaundice, or malaria by age, sex, and residence, India, 1998–99 Number of persons per 100,000 suffering from: Age and sex Asthma Tuberculosis1 Medically treated tuberculosis Jaundice during the past 12 months Malaria during the past 3 months Number of usual residents URBAN Age < 15 15–59 60+ Sex Male Female Total 829 144 106 1,555 2,112 40,908 1,795 426 338 1,132 2,207 79,941 8,304 1,141 913 583 1,913 9,488 1,955 446 350 1,354 2,133 67,586 1,978 330 262 1,085 2,180 62,750 1,966 390 307 1,225 2,156 130,336 RURAL Age < 15 15–59 60+ Sex Male Female Total 986 155 106 1,503 3,990 134,529 2,517 776 630 1,423 4,343 196,498 11,036 1,448 1,141 903 4,858 29,737 2,784 690 558 1,675 4,320 184,367 2,508 507 391 1,134 4,184 176,397 2,649 600 476 1,410 4,254 360,764 TOTAL Age < 15 15–59 60+ Sex Male Female Total 950 153 106 1,515 3,552 175,437 2,309 675 545 1,339 3,725 276,439 10,375 1,374 1,086 826 4,146 39,224 2,561 624 502 1,589 3,734 251,953 2,369 460 357 1,121 3,658 239,147 2,468 544 432 1,361 3,697 491,100 1Includes medically treated tuberculosis 198 Asthma Asthma is a chronic respiratory disease characterized by sudden attacks of laboured breathing, chest constriction, and coughing. There has been a rapid increase in asthma cases in recent years in many parts of the world. In India, 2,468 persons per 100,000 population were reported to be suffering from asthma at the time of the survey. The prevalence of asthma is considerably higher in rural areas (2,649 per 100,000 population) than in urban areas (1,966 per 100,000 population), and is slightly higher among males (2,561 per 100,000) than among females (2,369 per 100,000). Age differences are marked, with the prevalence of asthma increasing from 950 per 100,000 at age 0–14 to 10,375 per 100,000 at age 60 and over. Tuberculosis Tuberculosis, which is also resurgent worldwide, is an infectious disease that affects the lungs and other body tissues. Tuberculosis of the lungs, the most commonly known form, is characterized by coughing up mucus and sputum, fever, weight loss, and chest pain. According to NFHS-2, the overall prevalence of tuberculosis in India is 544 per 100,000 population. This is 16 percent higher than the prevalence recorded in NFHS-1 (467 per 100,000), indicating that tuberculosis may be on the rise in India. The prevalence of tuberculosis is much higher in rural areas (600 per 100,000) than in urban areas (390 per 100,000). The prevalence rate is much higher for males (624 per 100,000) than for females (460 per 100,000). The sex differential in the prevalence of tuberculosis is about the same in urban and rural areas. Probable reasons for the much higher prevalence of tuberculosis among males than females are that men are more likely than women to come in contact with people who suffer from active tuberculosis and that men in India smoke more than women. The prevalence of tuberculosis increases rapidly with age. It is substantially higher among persons age 60 and above (1,374 per 100,000) than among those age 15–59 (675 per 100,000) or age 0–14 (153 per 100,000). Medically treated tuberculosis is expected to give a more reliable measure of the prevalence of active tuberculosis than the measure based on all reported cases considered in the preceding paragraph. As expected, the prevalence of medically treated tuberculosis is considerably lower (432 per 100,000) than the prevalence based on all reported cases (544 per 100,000). Differentials in the prevalence of medically treated tuberculosis by residence, age, and sex are similar to differentials in the prevalence of all reported cases. Jaundice Jaundice is characterized by yellowish discolouration of the eyes and skin, fever, liver enlargement, and abdominal pain. NFHS-2 asked household respondents if any member of the household had suffered from jaundice at any time during the 12 months preceding the survey. In India as a whole, 1,361 persons per 100,000 population were reported to have suffered from jaundice during the 12 months preceding the survey. People living in rural areas were somewhat more likely to have suffered from jaundice (1,410 per 100,000) than those living in urban areas (1,225 per 100,000). Males were 42 percent more likely to have suffered from jaundice than females. Jaundice is the only condition measured that decreases with age. The prevalence of jaundice was highest for the age group 0–14 (1,515 per 100,000), followed by the age groups 15–59 (1,339 per 100,000) and 60 years and above (826 per 100,000). The age and sex differentials in the prevalence of jaundice are similar in urban and rural areas. 199 Malaria Malaria is characterized by recurrent high fever with shivering. NFHS-2 asked household respondents whether any member of their household suffered from malaria any time during the three months preceding the survey. In India, 3,697 persons per 100,000 population were reported to have suffered from malaria during the three months preceding the survey. Since the prevalence of malaria is known to vary considerably by season, the NFHS-2 estimates should not be interpreted as representative of the level throughout the year. It would also be misleading to compare this estimate with the lower NFHS-1 estimate because the months of the year comprising the reference period for the malaria estimates from the two surveys are different. Rural residents are almost twice as likely to suffer from malaria (4,254 per 100,000) as are urban residents (2,156 per 100,000). The reported prevalence of malaria is slightly higher for males than for females. The prevalence of malaria during the past three months increases with age, from 3,552 per 100,000 in the population under age 15 to 4,146 per 100,000 in the population age 60 years and above. The steady increase with age occurs in rural areas but not in urban areas. Comparisons by State Table 6.8 shows comparisons of prevalence rates for morbidity by state. The prevalence of asthma varies considerably by state, from a low of 1,204 per 100,000 in Delhi to a high of 5,995 per 100,000 in Meghalaya. Other states with relatively low levels of asthma prevalence are Punjab and Himachal Pradesh, and other states with relatively high prevalence rates are Nagaland, Kerala, Sikkim, and Andhra Pradesh. State variations in the prevalence rate of tuberculosis are also large. Tuberculosis prevalence ranges from 207 per 100,000 in Punjab to 1,654 per 100,000 in Nagaland. All states in the Northeast Region except Assam have prevalence rates above 1,000 per 100,000. Tuberculosis prevalence rates are also noticeably high in Bihar and Orissa. Variations in the prevalence of medically treated tuberculosis are generally in line with the variations in all reported cases of tuberculosis. State differentials are also substantial for jaundice. Jaundice is most common in Nagaland, but it is also a substantial problem in most other northeastern states and in West Bengal and Goa. The prevalence of malaria varies widely across the states, at least partly because of seasonal variations in the timing of the survey fieldwork. Malaria was most often reported in Meghalaya, Nagaland, Arunachal Pradesh, and Madhya Pradesh, where 10–17 percent of the population were reported to have malaria during the three months preceding the survey. On the other hand, there were very few reports of malaria in Kerala, Himachal Pradesh, and Tamil Nadu. Four states (Arunachal Pradesh, Meghalaya, Nagaland, and Andhra Pradesh) have a higher prevalence of all these diseases than the national average, and six states (Haryana, Himachal Pradesh, Jammu and Kashmir, Punjab, Karnataka, and Tamil Nadu) consistently have a lower prevalence than the national average. 200 Table 6.8 Morbidity by state Number of persons per 100,000 usual household residents suffering from asthma, tuberculosis, jaundice, or malaria by state and residence, India, 1998–99 Number of persons per 100,000 suffering from: State Asthma Tuberculosis1 Medically treated tuberculosis Jaundice during the past 12 months Malaria during the past 3 months URBAN India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 1,966 390 307 1,225 2,156 1,216 548 483 946 592 1,545 305 284 885 1,217 841 200 177 575 177 1,158 320 320 977 199 1,112 200 164 1,057 949 2,573 329 290 808 3,007 1,737 405 326 1,318 5,240 1,667 490 347 1,037 1,441 1,430 629 558 1,551 1,833 3,000 819 652 1,152 4,571 2,410 357 170 1,892 918 1,451 1,055 792 1,451 11,346 1,931 583 345 2,716 1,910 1,900 1,086 1,086 1,324 847 2,798 580 506 1,306 5,533 2,112 1,096 907 1,837 4,438 4,343 1,723 1,546 6,972 14,447 3,197 1,151 128 2,046 1,535 2,003 445 329 1,989 1,267 1,304 279 242 1,141 3,378 2,172 342 282 1,618 3,551 3,525 299 199 1,456 2,613 1,442 216 190 372 280 3,901 348 301 165 47 1,318 431 366 1,185 346 201 Table 6.8 Morbidity by state (contd.) Number of persons per 100,000 usual household residents suffering from asthma, tuberculosis, jaundice, or malaria by state and residence, India, 1998–99 Number of persons per 100,000 suffering from: State Asthma Tuberculosis1 Medically treated tuberculosis Jaundice during the past 12 months Malaria during the past 3 months RURAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 2,649 600 476 1,410 4,254 1,068 92 92 639 725 2,074 379 327 1,037 2,447 1,389 265 240 437 394 1,870 455 455 933 706 1,391 210 210 942 1,140 3,237 420 358 1,070 4,458 2,457 669 587 2,134 11,646 2,061 566 444 943 4,103 2,103 1,035 868 1,510 4,034 3,288 835 714 1,265 7,770 2,654 537 330 2,544 1,669 3,371 1,302 1,164 1,703 12,814 3,394 721 358 2,773 3,066 2,108 1,118 988 1,924 2,551 6,793 1,679 683 2,996 19,433 2,190 1,027 708 4,630 10,623 6,076 1,637 961 4,940 16,597 4,938 980 742 2,432 1,044 1,971 480 304 2,417 688 2,451 550 438 1,087 5,199 2,788 236 191 1,471 4,509 4,560 695 532 1,611 5,633 1,888 297 237 374 770 5,084 581 434 640 58 1,667 505 455 1,118 399 202 6.5 Child Immunization The vaccination of children against six serious but preventable diseases (tuberculosis, diphtheria, pertussis, tetanus, poliomyelitis, and measles) has been a cornerstone of the child health care system in India. As part of the National Health Policy, the National Immunization Programme is being implemented on a priority basis. The Expanded Programme on Immunization (EPI) was initiated by the Government of India in 1978 with the objective of reducing morbidity, mortality, and disabilities from these six diseases by making free vaccination services easily available to all eligible children. Immunization against poliomyelitis was introduced in 1979–80, and tetanus toxoid for school children was added in 1980–81. Immunization against tuberculosis (BCG) was Table 6.8 Morbidity by state (contd.) Number of persons per 100,000 usual household residents suffering from asthma, tuberculosis, jaundice, or malaria by state and residence, India, 1998–99 Number of persons per 100,000 suffering from: State Asthma Tuberculosis1 Medically treated tuberculosis Jaundice during the past 12 months Malaria during the past 3 months TOTAL India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 2,468 544 432 1,361 3,697 1,204 511 451 921 603 1,922 358 314 993 2,093 1,339 259 234 450 374 1,725 428 428 942 602 1,308 207 197 976 1,082 3,073 397 342 1,005 4,099 2,273 602 520 1,927 10,015 1,979 551 424 963 3,552 2,028 989 833 1,515 3,788 3,255 833 707 1,253 7,414 2,593 492 290 2,381 1,482 3,117 1,270 1,115 1,669 12,619 3,278 710 357 2,768 2,974 2,040 1,107 1,020 1,728 1,995 5,995 1,459 648 2,658 16,656 2,149 1,063 813 3,155 7,359 5,729 1,654 1,078 5,348 16,166 4,711 1,002 662 2,382 1,108 1,984 466 314 2,245 920 1,979 438 357 1,109 4,449 2,524 282 230 1,534 4,098 4,292 592 446 1,571 4,851 1,733 269 221 373 600 4,806 526 403 528 56 1,546 479 424 1,142 380 1Includes medically treated tuberculosis 203 brought under the EPI in 1981–82. The latest addition to the Programme was vaccination against measles in 1985–86 (Ministry of Health and Family Welfare, 1991). The Universal Immunization Programme (UIP) was introduced in 1985–86 with the following objectives: to cover at least 85 percent of all infants against the six vaccine- preventable diseases by 1990 and to achieve self-sufficiency in vaccine production and the manufacture of cold-chain equipment (Ministry of Health and Family Welfare, 1991). This scheme has been introduced in every district of the country and the target now is to achieve 100 percent immunization coverage. Pulse Polio Immunization Campaigns began in December 1995 as part of a major national effort to eliminate polio. The standard immunization schedule developed for the child immunization programme specifies the age at which each vaccine is to be administered, the number of doses to be given, and the route of vaccination (intramuscular, oral, or subcutaneous). Routine vaccinations received by infants and children are usually recorded on a vaccination card that is issued for the child. NFHS-2 asked mothers in India whether they had a vaccination card for each child born since January 1995 (or since January 1996 in states in which the survey began in 1999). If a card was available, the interviewer was required to copy carefully the dates when the child received vaccinations against each disease. For vaccinations not recorded on the card, the mother’s report that the vaccination was or was not given was accepted. If the mother could not show a vaccination card, she was asked whether the child had received any vaccinations. If any vaccinations had been received, the mother was asked whether the child had received a vaccination against tuberculosis (BCG); diphtheria, whooping cough (pertussis), and tetanus (DPT); poliomyelitis (polio); and measles. For DPT and polio, information was obtained on the number of doses of the vaccine given to the child. Mothers were not asked the dates of vaccinations. To distinguish Polio 0 (polio vaccine given at the time of birth) from Polio 1 (polio vaccine given about six weeks after birth), mothers were also asked whether the first polio vaccine was given just after birth or later3. Table 6.9 gives the percentages of urban and rural children age 12–23 months who received specific vaccinations at any time before the interview and before 12 months of age, according to whether a vaccination card was shown to the interviewer or the mother was the source of all vaccination information. The 12–23 month age group was chosen for analysis because both international and Government of India guidelines specify that children should be fully immunized by the time they complete their first year of life. Because the date of vaccination was not asked of the mother if she could not show a vaccination card, for children whose information is based on the mother’s report, the proportion of vaccinations given during the first year of life is assumed to be the same as the proportion of vaccinations given during the first year of life among children with an exact date of vaccination on the card. 3Because mothers sometimes report that the first dose was given just after birth even if it was given several weeks later, an adjustment was made to the estimates of the number of polio vaccinations given, based on reports of the number of DPT vaccinations. This adjustment is based on the fact that when children receive a DPT vaccination, they are almost always given a polio vaccination at the same time. Thus, if the number of polio vaccinations was reported to be less than the number of DPT vaccinations and the first polio vaccination was reported to be given just after birth, then Polio 0 is assumed to really be Polio 1, Polio 1 is assumed to be Polio 2, etc. For comparative purposes, this same adjustment was made to the NFHS-1 vaccination estimates. 204 In NFHS-2, children who received BCG, measles, and three doses each of DPT and polio (excluding Polio 0) are considered to be fully vaccinated. Based on information obtained from a card or reported by the mother (‘either source’), 42 percent of children age 12–23 months are fully vaccinated and 14 percent have not received any vaccinations. Coverage for BCG, DPT, and polio (except Polio 0) vaccinations is much higher than the percentage fully vaccinated. BCG, the first dose of DPT, and the first and second doses of polio vaccine have each been received by at least 71 percent of children. Fifty-five percent of children have received three doses of DPT and 63 percent have received three doses of polio vaccine. Although DPT and polio vaccinations are given at the same time as part of the routine immunization programme, the coverage rates are higher for polio than for DPT (especially for the first two doses), undoubtedly because of the Pulse Polio campaigns. Not all children who begin with the DPT and polio vaccination series go on to complete them. The difference between the percentages of children receiving the first and third doses is 16 percentage points for DPT and 21 percentage points for polio. Fifty-one percent of children age 12–23 months have been vaccinated against measles. Table 6.9 Childhood vaccinations by source of information Percentage of children age 12–23 months who received specific vaccinations at any time before the interview and before 12 months of age by source of information on vaccination history and residence, India, 1998–99 Percentage vaccinated DPT Polio Source of information BCG Polio 0 1 2 3 1 2 3 Measles All1 None Number of children URBAN Vaccinated at any time before the interview Vaccination card Mother’s report Either source Vaccinated by 12 months of age2 96.6 33.0 98.9 96.4 91.1 98.5 96.0 90.8 81.0 77.5 0.1 1,048 78.4 14.9 75.3 69.5 58.3 86.9 83.7 67.5 59.2 46.0 11.7 1,233 86.8 23.3 86.1 81.9 73.4 92.2 89.4 78.2 69.2 60.5 6.4 2,282 85.1 23.3 83.6 79.1 70.6 89.4 86.1 74.9 59.7 51.9 8.6 2,282 RURAL Vaccinated at any time before the interview Vaccination card Mother’s report Either source Vaccinated by 12 months of age2 94.5 19.8 98.4 91.4 83.0 97.9 91.1 83.0 69.7 65.4 0.1 2,344 55.3 5.9 53.7 46.6 35.5 73.8 68.0 47.7 34.8 24.3 23.9 5,450 67.1 10.1 67.1 60.1 49.8 81.1 75.0 58.3 45.3 36.6 16.7 7,795 64.3 10.1 64.4 57.0 46.6 77.5 71.1 54.4 36.2 29.3 20.2 7,795 TOTAL Vaccinated at any time before the interview Vaccination card Mother’s report Either source Vaccinated by 12 months of age2 95.2 23.9 98.6 92.9 85.5 98.1 92.6 85.4 73.2 69.1 0.1 3,393 59.6 7.6 57.6 50.8 39.7 76.2 70.9 51.3 39.3 28.3 21.6 6,684 71.6 13.1 71.4 65.0 55.1 83.6 78.2 62.8 50.7 42.0 14.4 10,076 69.1 13.1 68.8 62.1 52.1 80.3 74.6 59.2 41.7 34.5 17.5 10,076 Note: Table includes only surviving children from among the two most recent births in the three years preceding the survey. 1BCG, measles, and three doses each of DPT and polio vaccines (excluding Polio 0) 2For children whose information was based on the mother’s report, the proportion of vaccinations given by 12 months of age is assumed to be the same as for children with a written record of vaccination. 205 The relatively low percentage vaccinated against measles is partly responsible for the fact that the percentage fully vaccinated is not higher than it is. There has been considerable improvement in vaccination coverage in India since the time of NFHS-1 when the proportion of children fully vaccinated was 36 percent and the proportion who had received no vaccinations was 30 percent (Figure 6.5). The coverage of each specific vaccination has also improved considerably since NFHS-1. Nonetheless, these data indicate that achievement of the goal of universal immunization coverage for children in India is far from complete. Government of India statistics suggest a much higher level of vaccination coverage than NFHS-2 estimates. According to government statistics for 1997–98, 61 percent of children age 12–23 months are fully vaccinated and coverage is 79 percent for BCG, 73 percent for the third dose of DPT, 73 percent for the third dose of polio vaccine, and 66 percent for measles (Ministry of Health and Family Welfare, 1999). According to the immunization schedule, all primary vaccinations, including measles, should be completed by the time a child is 12 months old. Table 6.9 shows that only 35 percent Figure 6.5 Percentage of Children Age 12–23 Months Who Have Received Specific Vaccinations, NFHS-1 and NFHS-2 62 72 52 55 54 63 42 51 36 42 30 14 0 10 20 30 40 50 60 70 80 BCG NFHS-1 NFHS-2 DPT 3 NFHS-1 NFHS-2 POLIO 3 NFHS-1 NFHS-2 MEASLES NFHS-1 NFHS-2 ALL NFHS-1 NFHS-2 NONE NFHS-1 NFHS-2 Percent India 206 of all children (or 82 percent of fully vaccinated children) were fully vaccinated by age 12 months. The percentages of children who received BCG, each dose of DPT, and each dose of polio by age 12 months are only slightly lower than the percentages who received these vaccines at any time before the survey. For measles vaccination, however, which is supposed to be given when the child is nine months old, the gap is wider (51 percent at any time before the survey compared with 42 percent by age 12 months). Eighteen percent of children who were vaccinated against measles received the vaccination after their first birthday. The analysis of vaccine-specific data indicates much higher coverage for each type of vaccine in urban areas than in rural areas. Sixty-one percent of children age 12–23 months in urban areas had received all of the recommended vaccinations by the time of the survey, compared with 37 percent in rural areas. The proportion fully vaccinated during the first year of life is also much higher in urban areas (52 percent) than in rural areas (29 percent). Dropout rates for both DPT and polio are lower in urban areas than in rural areas. Table 6.10 and Figure 6.6 present vaccination coverage rates (according to the vaccination card or the mother) for children age 12–23 months by selected background characteristics. The table also shows the percentage of children with vaccination cards that were shown to the interviewer. Mothers could show vaccination cards for 34 percent of children age 12–23 months, up slightly from 31 percent in NFHS-1. Vaccination cards were shown for 46 percent of children in urban areas and 30 percent in rural areas. As expected, vaccination coverage is much higher for children for whom a vaccination card was shown than for other children (see Table 6.9). Boys (43 percent) are slightly more likely than girls (41 percent) to be fully vaccinated. Boys are also somewhat more likely than girls to have received each of the individual vaccinations. Mothers showed vaccination cards for 34 percent of boys and 33 percent of girls. In NFHS-1, vaccination coverage was also slightly higher for boys than for girls and a vaccination card was shown for a higher proportion of boys than girls. It is noteworthy that the male-female difference in the percentage fully immunized and in the percentage showing a vaccination card is small and diminishing over time, indicating that discrimination against female children in India with regard to immunizations is not a major problem. The relationship between vaccination coverage and birth order is consistently negative for almost all vaccinations. A large majority of first-order births occur to younger women who are more likely than older women to utilize maternal and child health care services. As with the use of maternal health care services, there is a strong positive relationship between mother’s education and children’s vaccination coverage. Only 28 percent of children of illiterate mothers are fully vaccinated compared with 73 percent of children of mothers who have at least completed high school. Muslim children (33 percent) are less likely to be fully vaccinated than are Hindu (42 percent), Christian (61 percent), Sikh (70 percent), Buddhist/Neo-Buddhist (73 percent), or ‘other’ (60 percent) children. By caste/tribe, scheduled-tribe children (26 percent) are less likely to be fully vaccinated than are scheduled-caste (40 percent), other backward class (43 percent), or ‘other’ (47 percent) children. Household standard of living has a strong positive relationship with vaccination coverage, as expected. Only 30 percent of children from households with a low standard of living are fully vaccinated compared with 65 percent of children from households with a high standard of living. Differentials in immunization coverage for individual vaccines are similar to those just reported for full immunization. Table 6.10 Childhood vaccinations by background characteristics Percentage of children age 12–23 months who received specific vaccinations at any time before the interview (according to the vaccination card or the mother) and percentage with a vaccination card that was shown to the interviewer by selected background characteristics, India, 1998–99 Percentage vaccinated DPT Polio Background characteristic BCG Polio 0 1 2 3 1 2 3 Measles All1 None Percentage showing vaccination card Number of children Sex of child Male Female Birth order 1 2 3 4+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Buddhist/Neo-Buddhist Other Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 72.8 13.2 73.2 66.6 56.3 84.5 79.3 63.4 70.3 13.0 69.5 63.3 54.0 82.7 77.1 62.2 79.8 19.2 80.1 74.9 66.9 88.6 84.5 72.7 79.0 15.8 78.7 72.9 63.0 89.2 84.4 69.8 72.0 9.7 70.0 63.0 51.4 82.2 75.9 59.3 54.6 5.9 55.3 47.4 36.8 73.3 66.6 47.2 86.8 23.3 86.1 81.9 73.4 92.2 89.4 78.2 67.1 10.1 67.1 60.1 49.8 81.1 75.0 58.3 59.1 7.1 58.7 51.0 40.2 76.3 69.4 50.9 82.8 15.2 82.6 76.8 66.7 90.4 85.9 72.8 90.5 23.0 91.1 85.8 77.6 94.0 90.9 79.5 95.2 27.9 95.6 92.7 86.0 97.4 95.5 87.1 72.5 13.1 72.1 65.6 55.7 84.7 79.3 63.5 62.3 9.9 63.2 56.0 45.7 76.3 70.0 54.0 84.0 32.1 84.5 81.4 72.8 88.5 86.8 76.5 86.4 14.0 86.8 84.5 77.6 87.9 86.9 80.5 94.6 15.6 94.1 94.0 88.7 94.4 94.3 90.1 88.1 11.4 89.4 88.9 75.2 90.1 89.8 67.2 69.6 11.7 68.4 62.9 52.7 82.6 77.8 61.3 60.0 4.5 57.0 48.6 37.5 73.9 66.9 49.0 71.6 18.7 72.4 66.0 56.7 86.6 81.3 65.6 76.1 11.6 76.4 69.9 60.4 84.6 79.4 65.6 59.3 9.0 59.2 52.2 42.7 76.4 69.8 51.9 74.1 12.9 74.0 67.4 56.9 85.3 80.0 64.8 91.2 22.6 91.0 86.3 78.0 94.6 91.8 81.2 71.6 13.1 71.4 65.0 55.1 83.6 78.2 62.8 51.6 43.1 13.5 34.4 5,163 49.8 40.9 15.3 32.9 4,913 61.8 54.0 9.8 42.3 2,957 56.7 48.9 9.1 38.5 2,663 49.4 38.8 15.0 29.9 1,805 33.1 24.1 24.4 21.7 2,651 69.2 60.5 6.4 45.9 2,282 45.3 36.6 16.7 30.1 7,795 35.8 27.8 21.2 24.2 5,867 61.8 52.3 8.0 41.4 1,782 71.8 62.7 4.6 49.0 921 82.8 72.7 1.4 52.2 1,505 51.5 42.4 13.3 33.7 7,941 40.4 32.7 21.0 30.6 1,605 66.2 61.1 11.0 42.3 264 75.7 69.5 11.1 45.9 138 77.3 73.0 1.1 39.9 58 69.8 59.7 9.1 41.6 31 47.6 40.2 15.1 31.3 2,031 34.3 26.4 24.2 24.5 935 50.7 43.0 11.6 33.4 3,217 57.1 46.8 13.3 38.1 3,770 37.6 30.4 20.8 26.2 3,637 51.6 43.2 13.1 35.2 4,680 77.2 64.7 4.0 45.8 1,649 50.7 42.0 14.4 33.7 10,076 Note: Table includes only surviving children from among the two most recent births in the three years preceding the survey. Total includes 21 children belonging to the Jain religion, 7 children with no religion, and 1, 10, 124, and 109 children with missing information on mother’s education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. 1BCG, measles, and three doses each of DPT and polio vaccines (excluding Polio 0) 208 Table 6.11 and Figure 6.7 show vaccination coverage rates for each type of vaccination and the percentage of mothers showing a vaccination card for children age 12–23 months in each state. There are considerable interstate differentials in the coverage rates for different vaccinations and for children receiving all vaccinations. The percentage of children who are fully vaccinated ranges from 11 percent in Bihar to 89 percent in Tamil Nadu. Among major states, Bihar (11 percent), Assam (17 percent), Rajasthan (17 percent), Uttar Pradesh (21 percent), and Madhya Pradesh (22 percent) stand out as having a much lower percentage of children fully vaccinated than the national average of 42 percent. As these states account for more than 40 percent of the total population of the country, their low coverage for vaccination pulls down the coverage rate for the country as a whole. All northern states except Rajasthan, and all southern and western states, have fared relatively well with regard to full coverage of vaccinations. Most of the northeastern states have a relatively poor record on vaccination coverage. A similar picture emerges with respect to individual vaccinations. Tamil Nadu, Goa, Maharashtra, Himachal Pradesh, and Kerala are approaching universal coverage for BCG and three doses of DPT and polio. In most states, there is a considerable drop from the second to the third dose for both DPT and polio, and in almost every state fewer children have received measles vaccine than any of the other vaccinations. Dropouts for DPT and polio and relatively low levels of coverage for measles are major factors in the failure to achieve full immunization coverage. Figure 6.6 Percentage of Children Age 12–23 Months Who Have Received All Vaccinations 61 37 28 52 63 73 43 41 RESIDENCE Urban Rural MOTHER'S EDUCATION Illiterate Literate, < Middle School Complete Middle School Complete High School Complete and Above SEX OF CHILD Male Female Percent 0 10 20 30 40 50 60 70 80 NFHS-2, India, 1998–99 209 The percentage of children with a vaccination card that was shown to the interviewer varies considerably by state, from 15 percent in Rajasthan to 70 percent in Goa. These differentials reflect both differences in the proportion who have a vaccination card for their young children in each state and, among those who have cards, differences in the ability or willingness to find the card and show it to the interviewer. Table 6.12 shows the percentage of children age 12–35 months with a vaccination card that was shown to the interviewer and the percentage who received various vaccinations during the first year of life by current age of the child and place of residence. The table shows a considerable improvement in vaccination coverage over a short period of time. The proportion vaccinated during the first year of life is estimated separately for children in each age group. The Table 6.11 Childhood vaccinations by state Percentage of children age 12–23 months who received specific vaccinations at any time before the interview (according to the vaccination card or the mother) and percentage with a vaccination card that was shown to the interviewer by state, India, 1998–99 Percentage vaccinated DPT Polio State BCG Polio 0 1 2 3 1 2 3 Measles All1 None Percentage showing vaccination card India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 71.6 13.1 71.4 65.0 55.1 83.6 78.2 62.8 92.0 36.9 90.8 88.3 79.9 93.8 91.7 81.0 86.8 6.1 89.5 84.5 71.1 90.1 87.4 74.3 94.6 4.2 96.7 96.1 88.8 97.2 97.2 89.8 85.6 4.8 85.7 83.6 72.3 88.3 85.4 74.3 88.7 11.2 88.4 87.3 82.0 90.5 88.5 83.6 53.9 3.2 47.8 40.2 26.1 75.5 67.3 44.6 64.9 10.1 62.8 52.3 37.0 85.4 79.0 56.7 57.5 4.7 57.3 46.5 33.9 66.5 60.3 42.3 37.7 3.6 39.7 33.4 24.2 81.3 71.7 41.0 84.7 14.6 80.1 74.8 61.9 88.7 84.8 68.4 76.5 2.1 77.9 70.1 58.3 83.9 76.5 61.7 54.2 4.5 57.4 52.7 41.8 67.6 62.5 43.3 53.5 3.1 57.4 48.5 37.5 61.8 53.6 37.9 71.0 32.1 76.4 71.0 59.1 81.3 76.9 62.5 46.1 11.5 44.8 36.8 25.4 51.8 43.8 27.6 88.2 4.6 86.9 83.9 69.5 88.3 83.5 71.9 46.1 5.5 48.1 40.9 29.6 66.6 60.3 41.8 76.5 8.2 75.7 71.7 62.5 79.8 75.7 63.5 99.2 31.6 97.6 95.2 93.4 99.2 98.4 95.8 84.7 5.3 83.1 75.4 64.1 90.2 82.5 68.6 93.7 8.3 94.9 91.7 89.4 97.2 94.7 90.8 90.2 5.3 89.8 86.9 79.5 93.8 90.9 81.6 84.8 26.4 87.0 84.8 75.2 91.9 89.0 78.3 96.2 60.6 96.0 94.4 88.0 96.9 95.2 88.4 98.6 85.5 98.6 97.5 96.7 99.7 99.5 98.0 50.7 42.0 14.4 33.7 77.5 69.8 5.1 43.7 72.2 62.7 9.9 24.4 89.1 83.4 2.8 54.6 68.9 56.7 10.4 51.1 76.5 72.1 8.7 43.0 27.1 17.3 22.5 14.7 35.5 22.4 13.9 25.1 34.6 21.2 29.5 20.4 16.6 11.0 16.8 17.4 54.0 43.7 9.4 46.2 52.4 43.8 13.6 58.0 33.6 20.5 28.7 24.6 24.6 17.0 33.2 32.5 45.8 42.3 17.2 43.4 17.7 14.3 42.3 20.6 71.0 59.6 10.5 41.1 19.6 14.1 32.7 18.4 58.9 47.4 17.6 47.0 84.3 82.6 0.0 69.7 63.6 53.0 6.6 31.8 84.3 78.4 2.0 48.9 64.7 58.7 4.5 41.3 67.3 60.0 7.7 41.2 84.6 79.7 2.2 63.2 90.2 88.8 0.3 45.8 Note: Table includes only surviving children from among the two most recent births in the three years preceding the survey. 1BCG, measles, and three doses each of DPT and polio vaccines (excluding Polio 0) 210 row labelled ‘No vaccinations’ indicates the percentage of children who have not received any vaccination by 12 months of age. The proportion of children whose vaccination status was determined from a vaccination card declines with the age of children. This may reflect an upward trend in the use of vaccination cards as well as an upward trend in overall vaccination coverage. On the other hand, vaccination cards may have been lost or discarded, especially for older children who have received all their vaccinations. The proportion of children fully vaccinated by age 12 months is about the same for children age 12–23 months (35 percent) as for children age 24–35 months (34 percent). A similar pattern is observed in both urban and rural areas. However, a decline in coverage with increasing children’s age is observed for BCG, DPT, and the first two doses of polio, indicating that there has been some progress for individual vaccines. However, because the percentage vaccinated by 12 months of age declines only marginally for measles, the extent of progress for individual vaccines is not fully seen in the very small decline in the percentage receiving all vaccinations. Figure 6.7 Percentage of Children Age 12–23 Months Who Have Received All Vaccinations by State 0 10 20 30 40 50 60 70 80 90 100 Tam il N adu H im acha l P radesh G oa K era la M aharashtra P un jab De lh i Ha ryana K arnataka M izoram A ndhra P radesh Jam m u & K ashm ir G ujara t S ikk im W est B enga l O rissa M anipur INDIA M adhya P radesh Uttar P radesh A runacha l P radesh Ra jasthan A ssam M eghalaya Nagaland B ihar P ercent NHS-2, India, 1998–99 211 Table 6.13 and Figure 6.8 give the percent distribution of children under age three years who have received any vaccinations by the source of most of the vaccinations, according to selected background characteristics. The public sector is the primary provider of childhood vaccinations in India. Eighty-two percent of all children who have received any vaccinations received most of them from a public-sector medical source and only 13 percent received them from a private-sector medical source. The percentage of children receiving vaccinations from the private sector is considerably lower in rural areas (9 percent) than in urban areas (24 percent), where private-sector services tend to be concentrated. Even in urban areas, however, 72 percent of children received their vaccinations from the public sector. Children of more educated mothers and those belonging to households with a high standard of living are more likely than other children to receive vaccinations from the private sector. Christian and Jain children are much more likely to receive vaccinations from the private sector than children belonging to other religions. Children from scheduled tribes and scheduled castes are much less likely than other children to receive vaccinations from the private sector. Table 6.12 Childhood vaccinations received by 12 months of age Percentage of children age 12–23 months and 24–35 months with a vaccination card that was shown to the interviewer and percentage who received specific vaccinations by 12 months of age, according to residence and child's current age, India, 1998–99 Urban Rural Total Vaccination status 12–23 months 24–35 months 12–23 months 24–35 months 12–23 months 24–35 months Vaccination card shown to interviewer Percentage vaccinated by 12 months of age1 BCG Polio 0 DPT 1 2 3 Polio 1 2 3 Measles All vaccinations2 No vaccinations Number of children 45.9 32.7 30.1 21.4 33.7 24.0 85.1 82.4 64.3 59.9 69.1 65.2 23.3 21.5 10.1 9.0 13.1 11.9 83.6 81.3 64.4 58.7 68.8 64.1 79.1 77.6 57.0 53.2 62.1 59.0 70.6 69.2 46.6 43.5 52.1 49.6 89.4 87.3 77.5 71.8 80.3 75.7 86.1 84.6 71.1 68.7 74.6 72.6 74.9 75.2 54.4 54.5 59.2 59.6 59.7 59.2 36.2 35.7 41.7 41.3 51.9 51.4 29.3 28.6 34.5 33.9 8.6 12.1 20.2 25.6 17.5 22.2 2,282 2,277 7,795 7,536 10,076 9,813 Note: Table includes only surviving children from among the two most recent births in the three years preceding the survey. 1Information was obtained either from the vaccination card or from the mother if there was no written record. For children whose information was based on the mother’s report, the proportion of vaccinations given by 12 months of age is assumed to be the same as for children with a written record of vaccinations. 2BCG, measles, and three doses each of DPT and polio vaccines (excluding Polio 0) 212 Table 6.13 Source of childhood vaccinations Percent distribution of children under age 3 who have received any vaccinations by source of most of the vaccinations, according to selected background characteristics, India, 1998–99 Source Background characteristic Public medical sector NGO or trust hospital/ clinic Private medical sector Other Total percent Number of children Age of child < 12 months 12–23 months 24–35 months Sex of child Male Female Birth order 1 2 3 4+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 79.9 0.8 14.1 5.2 100.0 7,432 82.7 0.5 12.1 4.7 100.0 8,622 83.0 0.6 11.4 5.0 100.0 8,384 81.7 0.6 12.9 4. 8 100.0 12,824 82.3 0.6 12.0 5.1 100.0 11,614 77.8 0.7 17.3 4.1 100.0 7,589 81.4 0.7 13.5 4.4 100.0 6,683 83.0 0.5 10.0 6.5 100.0 4,331 87.2 0.5 6.8 5.5 100.0 5,835 72.3 1.2 24.3 2.3 100.0 6,176 85.2 0.4 8.5 5.9 100.0 18,262 87.1 0.5 6.5 5.9 100.0 12,886 83.3 0.6 10.5 5.5 100.0 4,783 81.2 0.8 13.6 4.4 100.0 2,548 65.2 0.8 32.3 1.7 100.0 4,219 82.2 0.5 11.9 5.4 100.0 19,546 82.6 0.6 13.7 3.0 100.0 3,545 72.8 3.5 22.3 1.4 100.0 625 84.7 0.1 14.3 0.9 100.0 369 71.6 0.0 23.5 4.9 100.0 69 70.8 0.0 13.0 16.2 100.0 184 85.9 0.9 11.6 1.6 100.0 62 93.8 0.0 6.2 0.0 100.0 13 87.2 0.6 7.9 4.2 100.0 4,746 86.3 0.8 5.5 7.3 100.0 2,053 83.0 0.4 13.1 3.5 100.0 8,110 77.3 0.7 15.9 6.1 100.0 9,315 87.6 0.7 5.3 6.5 100.0 8,060 84.0 0.5 10.7 4.8 100.0 11,547 67.4 0.7 29.5 2.4 100.0 4,551 82.0 0.6 12.5 5.0 100.0 24,438 Note: Table includes only surviving children from among the two most recent births in the three years preceding the survey. Total includes 2, 26, 214, and 281 children with missing information on mother’s education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. NGO: Nongovernmental organization 213 6.6 Vitamin A Supplementation Vitamin A deficiency is one of the most common nutritional deficiency disorders in the world, affecting more than 250 million children worldwide (Bloem et al., 1997). The National Programme on Prevention of Blindness targets children under age five years and administers oral doses of vitamin A every six months starting at age nine months. NFHS-2 asked mothers of children born during the three years before the survey whether their children ever received a dose of vitamin A. Those who said that their child had received at least one dose of vitamin A were asked how long ago the last dose of vitamin A was given. Table 6.14 shows the percentage of children age 12–35 months who received at least one dose of vitamin A and who received a dose of vitamin A within the past six months by selected background characteristics. In the country as a whole, only 3 out of 10 children age 12–35 months received at least one dose of vitamin A, and only 17 percent received a dose within the past six months. This indicates that a large majority of children in India have not received vitamin A supplementation at all and even fewer children receive vitamin A supplementation regularly. Children living in urban areas, children of more educated mothers, and children living in high standard of living households are considerably more likely than other children to receive vitamin A supplementation (Table 6.14). Children of birth order 4 or above are much less likely than children of birth orders 1, 2, or 3 to have received any vitamin A supplementation. Muslim, Hindu, and Christian children are less likely to receive vitamin A than other children. Similarly, children from schedule castes, schedule tribes, and other backward classes are less likely to receive vitamin A than other children. As is the case with immunizations, boys have a slight edge in vitamin A coverage. In general, children from groups that are less likely to have received at least one dose of vitamin A supplementation are also less likely to have received a dose in the past six months. Figure 6.8 Source of Childhood Vaccinations by Residence Urban NGO or Trust Hospital/ Clinic 1% Other Source 2% Private Medical Sector 24% Public Medical Sector 72% Rural NGO or Trust Hospital/ Clinic 0. 4% Public Medical Sector 85% Private Medical Sector 9% Other Source 6% Note: Percents do not add to 100 due to rounding NFHS-2, India, 1998–99 214 Table 6.14 Vitamin A supplementation for children Percentage of children age 12–35 months who received at least one dose of vitamin A and who received at least one dose of vitamin A within the six months preceding the survey by selected background characteristics, India, 1998–99 Percentage who received vitamin A Background characteristic At least one dose At least one dose within the past six months Number of children Age of child 12–23 months 24–35 months Sex of child Male Female Birth order 1 2 3 4+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 28.4 20.4 10,076 31.0 13.8 9,813 30.8 18.1 10,251 28.4 16.1 9,638 35.7 20.2 5,680 33.4 19.4 5,215 29.8 17.0 3,556 19.6 11.8 5,439 38.7 21.2 4,559 27.0 15.9 15,331 20.4 12.6 11,541 39.1 21.2 3,625 41.9 22.4 1,829 47.0 27.0 2,892 29.7 17.1 15,621 24.1 14.5 3,226 33.0 20.0 484 55.3 31.7 301 (57.1) (34.0) 45 67.5 28.2 119 57.3 23.3 58 43.5 20.0 17 27.1 15.6 3,956 26.0 15.1 1,819 26.8 15.4 6,347 34.8 20.1 7,545 21.7 12.7 7,138 30.9 17.9 9,251 43.3 24.2 3,271 29.7 17.1 19,889 Note: Table includes only surviving children from among the two most recent births in the three years preceding the survey. Total includes 2, 19, 222, and 229 children with missing information on mother’s education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. ( ) Based on 25–49 unweighted cases 215 State variations in the percentage of children who received at least one dose of vitamin A and the percentage who received at least one dose within the six months preceding the survey are shown in Table 6.15. The percentage of children age 12–35 who received at least one dose of vitamin A supplementation ranges from 7 percent in Nagaland to 78 percent in Goa. In addition to Nagaland, Bihar (10 percent), Uttar Pradesh (14 percent), Assam (15 percent), Tamil Nadu (16 percent), and Rajasthan (18 percent) stand out as having very low proportions of children receiving at least one dose of vitamin A. In addition to Goa, Himachal Pradesh (71 percent) and Maharashtra (65 percent) stand out as having relatively successful vitamin A supplementation programmes. State variations in the percentage of children receiving at least one dose of vitamin A supplementation within the past six months follow closely the variations in the percentage of children receiving at least one dose at any time in the past. Table 6.15 Vitamin A supplementation for children by state Percentage of children age 12–35 months who received at least one dose of vitamin A and who received at least one dose of vitamin A within the six months preceding the survey by state, India, 1998–99 Percentage who received vitamin A State At least one dose At least one dose within the past six months India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 29.7 17.1 32.7 17.4 45.2 21.4 71.1 35.1 36.0 22.8 56.5 30.2 17.6 12.5 24.4 14.7 13.9 9.5 10.2 6.8 42.0 26.4 43.4 23.5 20.9 9.6 15.4 8.9 38.4 18.8 24.7 10.7 70.6 41.8 6.8 4.4 45.8 22.0 78.0 52.3 51.9 26.3 64.7 36.6 24.8 14.0 48.4 22.8 43.6 28.2 16.2 10.0 Note: Table includes only surviving children from among the two most recent births in the three years preceding the survey. 216 6.7 Child Morbidity and Treatment This section discusses the prevalence and treatment of acute respiratory infection (ARI), fever, and diarrhoea. Mothers of children born during the three years preceding the survey were asked if their children suffered from cough, fever, or diarrhoea during the two weeks preceding the survey, and if so, the type of treatment given. Accuracy of all these measures is affected by the reliability of the mother’s recall of when the disease episode occurred. The two-week recall period is thought to be most suitable for ensuring that there will be an adequate number of cases to analyze and that recall errors will not be too serious. Table 6.16 shows the percentage of children with cough accompanied by fast breathing (symptoms of acute respiratory infection), fever, and diarrhoea during the two weeks preceding the survey and the percentage with acute respiratory infection who were taken to a health facility or provider, by selected background characteristics. Acute Respiratory Infection Acute respiratory infection, primarily pneumonia, is a major cause of illness among infants and children and the leading cause of childhood mortality throughout the world (Murray and Lopez, 1996). Early diagnosis and treatment with antibiotics can prevent a large proportion of ARI/pneumonia deaths. NFHS-2 found that 19 percent of children under age three in India suffered from acute respiratory infection (cough accompanied by short, rapid breathing) at some time during the two-week period before the survey (Table 6.16). A comparison with NFHS-1 ARI data is not meaningful since the two surveys took place at different times of the year and rates of ARI are affected by the time of the year when the measurements are taken. Table 6.16 shows that there is little variation in the prevalence of ARI by most of the background characteristics included in the table. ARI is somewhat more common among boys than girls and among children living in rural areas than urban areas. Children of mothers who have at least completed high school have a lower occurrence of ARI than other children. The prevalence of ARI is higher among scheduled-tribe children than among other children, and children living in lower standard of living households also have a higher prevalence of ARI. Children living in households that use piped drinking water and in households that use a water filter for the purification of water have a lower prevalence of ARI than do other children. The small variation in the prevalence of ARI by most socioeconomic characteristics indicates that respiratory infections affect children from all strata in India irrespective of their socioeconomic background. Table 6.16 also shows the percentage of children suffering from ARI symptoms in the two weeks before the survey who were taken to a health facility or provider. Sixty-four percent of children received some advice or treatment from a health facility or health provider when ill with ARI. This percentage, as expected, is relatively low for children whose mothers are illiterate or who live in households with a low standard of living. The percentage is relatively high for children whose mothers do not belong to a scheduled caste or scheduled tribe. Notably, boys, urban children, and children of birth order one are also more likely than other children to have been taken to a health facility or provider for advice or treatment. 217 Table 6.16 Prevalence of acute respiratory infection, fever, and diarrhoea Percentage of children under age 3 who were ill with a cough accompanied by fast breathing (symptoms of acute respiratory infection— ARI), fever, or diarrhoea during the two weeks preceding the survey and percentage with ARI who were taken to a health facility or provider by selected background characteristics, India, 1998–99 Percentage of children suffering in past two weeks from: Diarrhoea Background characteristic Cough accompanied by fast breathing (ARI) Fever Any diarrhoea1 Diarrhoea with blood Number of children Percentage with ARI taken to a health facility or provider Number of children with ARI Age of child 1–5 months 6–11 months 12–23 months 24–35 months Sex of child Male Female Birth order 1 2 3 4+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High 17.4 20.9 16.9 0.9 5,074 55.7 884 23.7 33.6 25.1 2.8 4,901 66.9 1,161 20.0 33.4 21.3 2.9 10,076 65.1 2,019 17.5 27.8 15.1 3.0 9,813 64.8 1,716 20.7 30.3 19.4 2.5 15,515 66.5 3,214 17.9 28.5 18.9 2.6 14,349 60.8 2,564 19.7 30.0 18.5 2.0 8,630 70.1 1,700 18.3 27.7 17.8 2.4 7,785 65.0 1,424 19.3 29.5 20.1 2.3 5,316 62.8 1,023 20.1 30.6 20.5 3.6 8,134 57.4 1,631 16.2 28.8 19.6 1.6 6,768 75.1 1,096 20.3 29.7 19.0 2.9 23,096 61.4 4,682 20.6 29.5 20.1 3.3 17,273 58.3 3,550 20.3 31.5 19.8 2.0 5,457 69.5 1,105 18.8 28.9 18.6 2.0 2,753 76.3 517 13.8 27.2 15.0 0.9 4,377 77.0 604 19.1 28.3 19.0 2.5 23,568 62.9 4,502 20.8 34.5 20.7 2.9 4,773 66.8 994 20.3 32.8 16.5 2.9 705 57.1 143 13.8 25.8 10.1 1.3 425 90.5 59 12.0 28.3 23.8 2.7 72 * 9 18.8 41.9 23.2 0.7 189 93.0 35 31.6 34.1 27.5 1.2 81 69.5 26 19.1 21.7 11.1 1.0 22 (69.5) 4 19.6 29.4 19.8 2.9 5,894 60.3 1,153 22.4 31.4 21.1 3.7 2,810 50.4 631 19.1 28.1 18.3 2.6 9,573 67.9 1,826 18.7 30.4 19.1 2.1 11,257 67.2 2,108 21.0 29.8 19.9 3.2 10,710 55.1 2,245 19.4 30.1 19.7 2.6 13,906 67.4 2,694 15.7 26.7 16.1 1.3 4,889 76.9 768 Contd… 218 There is considerable variation in the prevalence of ARI by state (Table 6.17). The percentage of children under age three who suffered from ARI during the two weeks preceding the survey ranges from 8 percent in Karnataka to 30 percent in Sikkim. Interstate variations in the prevalence of ARI, fever, or diarrhoea should be interpreted with caution, however, because these conditions vary throughout the year and the fieldwork was conducted at different times of the year in different states. Fever In Table 6.16, fever is the most common of the three conditions examined, with 30 percent of children suffering from fever during the two weeks before the survey. The prevalence of fever is lower among children under age six months (21 percent) than among older children (28–34 percent). In general, the prevalence of fever does not vary widely or in a predictable way with most of the remaining demographic and socioeconomic characteristics. As with acute respiratory infection, fever tends to strike young children irrespective of their demographic and socioeconomic background. The prevalence of fever varies from 21 percent in Gujarat to 42 percent in Kerala (Table 6.17). Table 6.16 Prevalence of acute respiratory infection, fever, and diarrhoea (contd.) Percentage of children under age 3 who were ill with a cough accompanied by fast breathing (symptoms of acute respiratory infection— ARI), fever, or diarrhoea during the two weeks preceding the survey and percentage with ARI who were taken to a health facility or provider by selected background characteristics, India, 1998–99 Percentage of children suffering in past two weeks from: Diarrhoea Background characteristic Cough accompanied by fast breathing (ARI) Fever Any diarrhoea1 Diarrhoea with blood Number of children Percentage with ARI taken to a health facility or provider Number of children with ARI Source of drinking water Piped water Hand pump Well water Surface water Other Purification of water2 Straining by cloth Alum Water filter Boiling Electronic purifier Other Nothing Total 15.1 28.4 19.3 1.8 9,697 75.7 1,461 21.7 29.6 19.2 3.2 13,343 60.1 2,902 21.1 30.9 18.5 2.5 5,834 61.1 1,230 19.3 30.0 22.1 3.8 783 47.3 151 17.6 34.6 16.8 1.4 200 (66.3) 35 18.6 29.0 22.0 2.3 5,151 71.2 957 20.3 29.0 18.8 1.6 323 76.1 65 12.2 25.4 15.2 0.9 1,159 78.9 142 16.9 31.2 16.5 1.8 2,054 75.7 348 20.8 24.2 18.0 0.1 69 * 14 23.3 30.3 25.2 3.3 216 80.0 50 19.9 29.6 19.0 2.8 21,673 61.1 4,321 19.3 29.5 19.2 2.6 29,864 64.0 5,778 Note: Table includes only surviving children age 1–35 months from among the two most recent births in the three years preceding the survey. Total includes children with missing information on mother’s education, religion, caste/tribe, the standard of living index, and source of drinking water, who are not shown separately. ( ) Based on 25–49 unweighted cases *Percentage not shown; based on fewer than 25 unweighted cases 1Includes diarrhoea with blood 2Number of children and number of children with ARI add to more than the respective totals because multiple methods of purification of water could be recorded. 219 Table 6.17 Prevalence of acute respiratory infection, fever, and diarrhoea by state Percentage of children under age 3 who were ill with a cough accompanied by fast breathing (symptoms of acute respiratory infection—ARI), fever, or diarrhoea during the two weeks preceding the survey and percentage with ARI who were taken to a health facility or provider by state, India, 1998–99 Percentage of children suffering in past two weeks from: Diarrhoea State Cough accompanied by fast breathing (ARI) Fever Any diarrhoea1 Diarrhoea with blood Percentage with ARI taken to a health facility or provider India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 19.3 29.5 19.2 2.6 64.0 16.9 35.7 30.1 1.6 83.3 11.8 23.7 13.9 1.8 87.9 10.8 29.9 31.3 4.5 95.6 22.2 39.4 32.8 4.1 76.2 14.4 24.9 9.8 0.6 93.8 22.0 25.8 19.8 3.4 60.6 29.2 31.0 23.4 4.3 57.9 21.1 27.8 23.3 3.8 61.3 21.7 31.0 17.7 2.9 58.2 22.5 36.0 28.1 4.5 57.1 24.8 29.9 8.3 1.0 52.4 25.4 38.5 23.4 3.0 49.2 17.8 28.4 8.2 2.2 41.7 26.9 36.8 16.6 4.1 45.0 28.8 41.2 21.8 6.1 48.7 11.2 35.9 23.0 3.5 51.0 18.4 34.0 21.7 2.6 28.0 30.0 31.3 31.0 2.5 41.3 17.1 34.4 18.7 0.6 98.2 11.0 20.7 19.7 1.3 71.2 13.5 37.4 25.4 1.7 84.6 19.3 28.6 15.0 1.5 69.4 7.9 25.9 13.9 0.7 77.4 22.8 41.5 11.6 0.9 82.8 10.3 22.3 14.4 1.7 82.9 Note: Table includes only surviving children age 1–35 months from among the two most recent births in the three years preceding the survey. 1Includes diarrhoea with blood 220 Diarrhoea Diarrhoea is the second most important killer of children under age five worldwide, following acute respiratory infection. Deaths from acute diarrhoea are most often caused by dehydration due to loss of water and electrolytes. Nearly all dehydration-related deaths can be prevented by prompt administration of rehydration solutions. Because deaths from diarrhoea are a significant proportion of all child deaths, the Government of India has launched the Oral Rehydration Therapy Programme as one of its priority activities for child survival. One major goal of this programme is to increase awareness among mothers and communities about the causes and treatment of diarrhoea. Oral rehydration salt (ORS) packets are made widely available and mothers are taught how to use them. NFHS-2 asked mothers of children born during the three years preceding the survey a series of questions about episodes of diarrhoea suffered by their children in the two weeks before the survey, including questions on feeding practices during diarrhoea, the treatment of diarrhoea, and their knowledge and use of ORS. Table 6.16 shows that 19 percent of children under age three suffered from diarrhoea in the two-week period before the survey. There are seasonal variations in the prevalence of diarrhoea, however, so that the percentages shown in Table 6.16 cannot be assumed to reflect the situation throughout the year. Among children age 1–35 months, those age 6–11 months are most susceptible to diarrhoea (as is the case with ARI and fever). Differentials by sex of child, birth order, place of residence, and caste/tribe are small. Sikh children are considerably less likely to suffer from diarrhoea than children belonging to other religions. As expected, children of mothers with high school or more education and children in high standard of living households are somewhat less likely to suffer from diarrhoea than other children. Also consistent with expectations, diarrhoea is somewhat less common among children living in households that boil water or use a water filter for purification of drinking water than among other children. Children living in households that use surface water for drinking are more vulnerable to diarrhoea than children living in households that use other sources for drinking water. Three percent of all children age 1–35 months (14 percent of children who suffered from diarrhoea in the two weeks before the survey) suffered from diarrhoea with blood, a symptom of dysentery. Children under age six months had the lowest prevalence of diarrhoea with blood (less than 1 percent). Children of birth order four or higher, children living in rural areas, children whose mothers are illiterate, scheduled-tribe children, children living in low standard of living households, children living in households using surface water for drinking, and children living in households using ‘other’ means of water purification or using unpurified water for drinking all had an elevated risk of having diarrhoea with blood. Prevalence of diarrhoea also varies considerably by state (Table 6.17). Prevalence of any diarrhoea among children age 1–35 months during the two weeks preceding the survey ranges from 8 percent in Assam and West Bengal to 33 percent in Jammu and Kashmir. Prevalence of diarrhoea with blood was highest in Meghalaya (6 percent). 221 Table 6.18 shows that 62 percent of mothers with births during the three years preceding the survey know about ORS packets, up from 43 percent among women who gave birth during the three years before NFHS-1. Knowledge of ORS packets is somewhat lower among mothers age 15–19 and among mothers age 35 years or older than among mothers in the middle age groups. As expected, knowledge is considerably higher among urban mothers (76 percent) than rural mothers (59 percent), and among more educated mothers, especially literate mothers as compared with illiterate mothers. Knowledge of ORS is higher among Sikh, Jain, and Christian mothers than among mothers belonging to other religions. Mothers belonging to scheduled tribes are less likely to know about ORS packets than mothers belonging to other caste/tribe groups. Among all the groups shown in the table, knowledge of ORS packets is lowest among mothers who are not regularly exposed to any mass media (48 percent). In order to assess mothers’ knowledge of children’s need for extra fluids during episodes of diarrhoea, all mothers of children born in the three years preceding the survey were asked: ‘When a child has diarrhoea, should he/she be given less to drink than usual, about the same amount, or more than usual?’ Table 6.18 shows the response of mothers to this question by selected background characteristics. In India as a whole, only 29 percent of mothers report that children should be given more to drink than usual during an episode of diarrhoea and, contrary to the standard recommendation, 34 percent report that children should be given less to drink. This suggests that mothers in India need much more education in the proper management of diarrhoea. The proportion reporting correctly that children with diarrhoea should be given more to drink is particularly low among rural mothers, illiterate mothers, mothers belonging to a scheduled tribe, and mothers not regularly exposed to any mass media. The proportion reporting correctly that children with diarrhoea should be given more to drink is much higher among Sikh and Christian mothers than among mothers belonging to other religions. Mothers age 15–19 and 35 years or older are less likely to answer correctly than mothers age 20–34. To assess whether mothers are aware of one or more signs associated with diarrhoea which suggest the need for medical treatment, mothers were also asked: ‘When a child is sick with diarrhoea, what signs of illness would tell you that he or she should be taken to a health facility or health worker?’ All answers given by the respondent were recorded. The signs warranting medical treatment include repeated watery stools, repeated vomiting, blood in the stools, fever, marked thirst, not eating or not drinking well, getting sicker or very sick, and not getting better. Table 6.18 shows that only 37 percent of mothers were able to name two or more signs of diarrhoea that indicate that a child with diarrhoea should be given medical treatment. The percentage who know two or more signs for medical treatment of diarrhoea does not vary much by socioeconomic characteristics. Contrary to expectations, there is no difference in the percentage by place of residence. Literate mothers and mothers exposed to mass media are slightly more likely to know the danger signs. Notably, however, knowledge of two or more signs of diarrhoea that suggest the need for medical treatment is universally low across all demographic and socioeconomic groups. This suggests a need for further educating mothers with regard to children’s diarrhoea so that they are better able to recognize the danger signs of diarrhoea for which a health provider should be consulted. 222 Table 6.18 Knowledge of diarrhoea care Among mothers with births during the three years preceding the survey, percentage who know about oral rehydration salt (ORS) packets, percent distribution by quantity to be given to drink during diarrhoea, and percentage who know two or more signs of diarrhoea that indicate the need for medical treatment by selected background characteristics, India, 1998–99 Reported quantity to be given to drink Background characteristic Percentage who know about ORS packets Less Same More Don’t know/ missing Total percent Percentage who know two or more signs for medical treatment of diarrhoea1 Number of mothers Age 15–19 20–24 25–29 30–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Exposure to media Exposed to any media Watches television weekly Listens to radio weekly Visits cinema/theatre monthly Reads newspaper/magazine weekly Not regularly exposed to any media Total 55.7 39.5 29.8 21.0 9.7 100.0 33.9 3,691 64.6 34.5 29.7 28.9 6.9 100.0 37.0 10,691 64.8 32.8 28.4 32.7 6.1 100.0 38.8 8,432 62.0 32.0 27.1 33.1 7.8 100.0 37.5 3,741 53.1 32.8 30.1 26.5 10.6 100.0 35.0 1,900 75.8 30.9 28.4 36.8 3.9 100.0 37.1 6,291 58.6 35.2 29.2 27.3 8.4 100.0 37.1 22,163 51.2 37.9 30.1 22.2 9.7 100.0 34.9 16,757 72.3 34.2 29.0 32.0 4.8 100.0 38.3 5,028 77.2 30.5 28.9 36.0 4.6 100.0 42.1 2,539 86.5 21.5 24.5 51.1 2.9 100.0 41.4 4,125 61.5 34.3 29.7 28.6 7.4 100.0 36.8 22,566 63.4 36.1 26.0 29.7 8.2 100.0 36.4 4,454 74.1 26.3 30.3 39.8 3.7 100.0 46.8 674 81.9 19.2 24.7 50.0 6.1 100.0 37.1 388 75.7 31.0 32.0 33.1 3.9 100.0 39.8 68 66.7 36.3 26.1 32.1 5.5 100.0 46.0 173 57.6 49.9 19.9 24.4 5.8 100.0 39.3 80 54.6 16.7 50.3 25.3 7.7 100.0 44.8 22 59.3 36.9 28.9 26.5 7.6 100.0 37.5 5,658 51.3 35.1 34.9 22.0 7.9 100.0 35.1 2,709 62.4 33.3 29.9 29.2 7.6 100.0 38.9 9,169 66.9 33.1 26.9 33.1 6.9 100.0 35.8 10,586 74.6 31.9 28.6 35.0 4.6 100.0 39.0 15,255 77.7 30.5 28.8 36.5 4.1 100.0 38.3 11,205 75.8 30.7 28.0 36.5 4.9 100.0 41.8 9,254 79.7 31.7 30.6 33.9 3.8 100.0 37.7 2,804 83.2 24.0 27.0 45.8 3.3 100.0 42.3 5,234 48.3 36.9 29.5 22.9 10.7 100.0 34.8 13,199 62.4 34.2 29.0 29.4 7.4 100.0 37.1 28,454 Note: Total includes 5, 30, and 332 mothers with missing information on education, religion, and caste/tribe, respectively, who are not shown separately. 1Percentage who know two or more signs of illness that indicate that a child should be taken to a health facility or health worker 223 Table 6.19 shows differentials in the knowledge of diarrhoea care by state. Knowledge of ORS packets is almost universal in Mizoram (96 percent), Himachal Pradesh (93 percent), and Manipur (92 percent) and it also exceeds 80 percent in Kerala, Goa, Tamil Nadu, and Punjab. Knowledge of ORS packets is lowest in Bihar, Assam, and Rajasthan, where most mothers do not know about ORS packets. Women in Meghalaya, Madhya Pradesh, and Uttar Pradesh also have relatively low levels of knowledge of ORS packets. The proportion reporting correctly that children with diarrhoea should be given more to drink also varies considerably across states, from only 14 percent in Nagaland to 86 percent in Kerala. Tamil Nadu and Maharashtra are the only other states where less than 20 percent of Table 6.19 Knowledge of diarrhoea care by state Among mothers with births during the three years preceding the survey, percentage who know about oral rehydration salt (ORS) packets, percent distribution by quantity to be given to drink during diarrhoea, and percentage who know two or more signs of diarrhoea that indicate the need for medical treatment by state, India, 1998–99 Reported quantity to be given to drink State Percentage who know about ORS packets Less Same More Don’t know/ missing Total percent Percentage who know two or more signs for medical treatment of diarrhoea1 India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 62.4 34.2 29.0 29.4 7.4 100.0 37.1 73.9 15.0 15.8 64.9 4.4 100.0 33.2 71.7 20.2 24.9 49.7 5.2 100.0 31.9 92.7 18.8 29.5 49.1 2.5 100.0 26.8 72.9 30.1 24.4 41.1 4.4 100.0 40.7 81.8 19.6 28.9 47.2 4.4 100.0 38.6 44.8 43.2 29.7 21.0 6.1 100.0 17.9 55.5 29.5 36.9 28.1 5.5 100.0 30.9 59.1 35.2 28.8 25.3 10.7 100.0 36.4 37.5 32.1 24.7 27.6 15.5 100.0 49.6 72.9 10.3 24.5 62.1 3.2 100.0 44.4 76.0 57.6 16.9 21.2 4.2 100.0 34.4 77.1 24.4 37.8 28.4 9.5 100.0 28.6 42.9 21.7 17.9 40.4 20.0 100.0 43.9 91.6 10.8 36.3 39.5 13.3 100.0 47.3 51.9 31.2 33.2 23.4 12.2 100.0 57.3 96.0 3.1 22.0 66.3 8.6 100.0 36.3 58.6 18.0 64.6 13.8 3.7 100.0 63.0 63.8 17.5 13.9 66.6 1.9 100.0 36.8 85.8 36.0 24.3 32.4 7.3 100.0 43.1 61.5 38.0 33.4 27.7 0.9 100.0 29.3 65.1 42.4 35.4 17.6 4.6 100.0 41.2 73.0 36.8 35.3 22.5 5.5 100.0 29.6 78.9 23.8 31.7 39.5 4.9 100.0 28.6 88.9 3.2 8.9 85.5 2.5 100.0 52.3 83.1 42.3 37.8 16.6 3.3 100.0 50.7 1Percentage who know two or more signs of illness that indicate that a child should be taken to a health facility or health worker 224 mothers know that children with diarrhoea should be given more to drink than before the diarrhoea. Knowledge of two or more signs of diarrhoea requiring medical treatment is lowest in Rajasthan (18 percent) and highest in Nagaland (63 percent), followed by Meghalaya, Kerala, and Tamil Nadu. Table 6.20 shows the percentage of children under age three with diarrhoea during the two weeks preceding the survey who were taken to a health facility or provider, the percentage who received various types of oral rehydration therapy (ORT), and the percentage who received other types of treatment, by selected background characteristics. Among children who suffered from diarrhoea during the two weeks preceding NFHS-2, 63 percent were taken to a health facility or provider (almost the same percentage that were taken for medical advice or treatment for ARI). Twenty-seven percent of children with diarrhoea did not receive any treatment at all. The percentage taken to a health facility or provider for diarrhoea is slightly higher for boys than for girls and much higher for urban children than for rural children and for children of more educated mothers. The percentage is particularly low for scheduled-tribe children and for children living in households with a low standard of living. Twenty-seven percent of the children age 1–35 months who suffered from diarrhoea during the two weeks preceding the survey were treated with a solution made from ORS packets. This is up from 18 percent in NFHS-1, indicating some improvement in the use of ORS packets for the treatment of childhood diarrhoea in India. As expected, use of ORS packets is relatively high among urban children, children of more educated mothers, and children living in high standard of living households. Use of ORS packets is lower among Hindu and Muslim children than among children belonging to other religions. Scheduled-tribe children were less likely than any other group to be taken to a health facility or provider, but they were more likely than any other caste/tribe group to receive ORS during their diarrhoea. More than half (52 percent) of children did not receive any of the various types of oral rehydration therapy when sick with diarrhoea. Only 22 percent received increased fluids when sick with diarrhoea and only 15 percent received gruel. The youngest children (age 1–11 months), children living in rural areas, children whose mothers are illiterate, and children belonging to households with a low standard of living are less likely than other children to receive any of the various types of oral rehydration therapy. The use of antibiotics and other antidiarrhoeal drugs is not generally recommended for the treatment of childhood diarrhoea. Yet 53 percent of the children who had diarrhoea in the two weeks before NFHS-2 were treated with pills or syrup, and 15 percent received an injection. These figures indicate poor knowledge about the proper treatment of diarrhoea not only among mothers but also among health-care providers. The results underscore the need for informational programmes for mothers and supplemental training for health-care providers that emphasizes the importance of ORT, increased fluid intake, and continued feeding and discourages the use of drugs to treat childhood diarrhoea. The use of unnecessary antidiarrhoeal drugs is widespread across most socioeconomic groups, and is particularly common for children of more educated mothers and for children belonging to higher standard of living households. Table 6.20 Treatment of diarrhoea Among children under age 3 who had diarrhoea in the past two weeks, the percentage taken to a health facility or provider, the percentage who received various types of oral rehydration therapy (ORT), and the percentage who received other treatments by selected background characteristics, India, 1998–99 Oral rehydration Other treatment Background characteristic Taken to a health facility or provider Oral rehydration salt (ORS) packets Gruel Homemade sugar-salt- water solution Increased fluids ORT not given Pill or syrup Injec- tion Intrave- nous (IV/drip/ bottle) Home remedy/ herbal medicine Other No treat- ment Number of children with diarrhoea Age of child 1–11 months 12–23 months 24–35 months Sex of child Male Female Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Buddhist/Neo-Buddhist Other Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 60.7 21.2 8.9 3.0 17.9 62.2 66.6 31.6 18.3 3.2 23.5 46.7 62.6 27.7 18.4 3.6 26.3 46.7 64.8 26.8 15.6 3.4 22.3 52.4 61.9 26.8 14.1 3.1 22.1 52.2 75.2 32.7 20.2 5.2 25.5 42.9 59.9 25.0 13.3 2.6 21.2 55.2 58.5 22.8 12.1 2.6 18.9 57.9 65.2 28.8 15.9 3.8 22.6 48.8 74.2 34.7 20.5 2.8 26.0 44.7 78.2 38.6 23.7 6.2 35.7 34.6 62.0 26.3 14.5 3.0 21.7 53.5 67.7 26.8 15.7 4.2 21.8 50.3 62.3 34.9 23.2 3.2 34.1 40.2 89.7 43.4 21.6 3.9 45.7 29.3 84.1 30.5 16.1 4.9 18.2 43.5 55.6 36.6 2.2 2.8 29.4 46.5 64.6 25.3 15.8 1.9 23.4 52.5 52.2 31.9 13.2 3.5 18.6 50.6 63.8 25.2 14.2 2.8 21.9 55.0 66.1 27.6 15.7 4.2 22.6 50.4 55.5 24.2 12.9 2.6 19.1 56.0 65.1 27.3 14.7 3.4 22.2 52.6 77.2 32.6 20.7 4.5 30.7 41.4 63.4 26.8 14.9 3.2 22.2 52.3 47.8 13.1 3.2 4.8 0.3 33.8 2,087 56.4 16.7 3.9 2.9 0.5 23.3 2,149 54.0 14.4 3.8 3.5 0.9 24.2 1,485 53.7 14.4 3.7 3.4 0.5 26.8 3,015 51.5 15.3 3.5 4.1 0.7 28.0 2,706 59.6 12.7 5.5 3.7 0.9 18.4 1,324 50.6 15.4 3.0 3.8 0.4 30.1 4,397 50.8 15.0 3.4 3.1 0.6 31.4 3,473 50.4 14.8 3.5 4.7 0.6 26.0 1,078 59.3 14.2 3.1 5.5 0.4 18.0 513 61.1 14.1 5.3 4.1 0.2 15.6 658 51.5 14.9 3.1 3.7 0.6 28.7 4,476 59.0 13.5 4.4 3.8 0.4 21.9 989 36.4 22.4 9.2 7.9 1.5 24.8 117 70.0 19.5 0.0 2.3 0.0 14.7 43 54.7 20.9 14.8 0.1 0.0 21.5 44 44.9 0.3 18.9 0.8 0.0 49.6 22 52.0 17.4 4.1 2.5 0.4 27.6 1,168 44.1 9.6 2.8 4.7 0.3 36.3 592 52.5 16.4 3.8 4.3 0.6 28.2 1,750 55.7 13.5 3.6 3.6 0.7 23.8 2,145 45.1 14.7 2.9 3.1 0.6 33.2 2,126 56.0 15.2 4.0 4.2 0.5 25.6 2,745 61.1 13.5 4.4 4.3 0.8 17.9 786 52.7 14.8 3.6 3.8 0.5 27.4 5,721 Note: Table includes only surviving children age 1–35 months from among the two most recent births in the three years preceding the survey. Total includes 17 Jain children, 2 children having no religion, and 11, 66, and 64 children with missing information on religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. 226 Table 6.21 shows state differentials in the percentage of children under age three with diarrhoea during the two weeks preceding the survey who were taken to a health facility or provider, the percentage who received various types of oral rehydration therapy, and the percentage who received other types of treatment. The percentage of children taken to a health facility or provider when sick with diarrhoea is considerably higher in the northern states (with the exception of Rajasthan) than in other states. Kerala and Maharashtra also have a relatively high percentage of children receiving medical attention when sick with diarrhoea. The northeastern and eastern states, on the other hand, have the lowest percentage of children taken to a health facility or provider for diarrhoea treatment. Use of oral rehydration therapy for children with diarrhoea is quite limited in Rajasthan and Uttar Pradesh where almost two-thirds of the children who had diarrhoea during the two weeks preceding the survey were not given ORT. In Kerala, on the other hand, 9 out of 10 children received ORT. Use of antidiarrhoeal drugs or injections is most widespread in the contiguous states of Haryana, Punjab, and Himachal Pradesh. Jammu and Kashmir and Maharashtra also have a relatively high percentage of children receiving pills, syrup, or injections when they are sick with diarrhoea. Table 6.22 shows the percent distribution of children who were treated with ORS for diarrhoea in the two weeks before NFHS-2 by the source of the ORS packets. For 38 percent of children who were treated with ORS, the packets were obtained from public-sector medical sources, for 40 percent the packets were obtained from private-sector medical sources, for less than 1 percent the packets were obtained from an NGO or trust, and for the remaining 21 percent the packets were obtained from other sources. Among the public-sector sources, government or municipal hospitals are mentioned most often, followed by community health centres (CHC), rural hospitals, or Primary Health Centres (PHC), sub-centres, and government dispensaries. Among the private-sector medical sources, ORS packets were usually obtained from a private doctor or a private hospital or clinic. The pharmacy or drugstore category accounts for 9 percent of all cases. If this category is added to the shop category, the proportion purchasing ORS packets from shops, pharmacies, or drugstores becomes 26 percent. State differentials in feeding practices during diarrhoea compared with feeding practices before diarrhoea are shown in Table 6.23. In India as a whole, only 22 percent of children who were sick with diarrhoea were given more to drink and only 10 percent were given more to eat. On the other hand, 30 percent of the children were given less to drink and 44 percent of the children were given less food to eat or no food at all. This is contrary to the recommendations for proper management of diarrhoea and suggests the need for public education programmes on proper feeding practices during diarrhoea. Kerala stands out among the states as having the highest percentage of children given more to drink during a diarrhoea episode than before (73 percent). In every other state, no more than 44 percent of women give children more to drink when they are sick with diarrhoea. Assam, Rajasthan, Maharashtra, and Tamil Nadu have very small proportions (below 15 percent) of children receiving more to drink when sick with diarrhoea. With regard to the amount given to eat during diarrhoea, Haryana, Punjab, Himachal Pradesh, and Mizoram stand out as having relatively high proportions of children given more or the same amount to eat. Kerala, Goa, Manipur, West Bengal, and Orissa are at the other end of the spectrum. In these states, more than 55 percent of the children were given less food or no food to eat when sick with diarrhoea. Table 6.21 Treatment of diarrhoea by state Among children under age 3 who had diarrhoea in the past two weeks, the percentage taken to a health facility or provider, the percentage who received various types of oral rehydration therapy (ORT), and the percentage who received other treatments by state, India, 1998–99 Oral rehydration Other treatment State Taken to a health facility or provider Oral rehydration salt (ORS) packets Gruel Homemade sugar-salt- water solution Increased fluids ORT not given Pill or syrup Injec- tion Intrave- nous (IV/drip/ bottle) Home remedy/ herbal medicine Other No treat- ment India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 63.4 26.8 14.9 3.2 22.2 52.3 80.1 39.1 27.2 12.1 38.1 32.4 92.6 25.7 14.0 3.0 41.1 41.9 91.6 45.6 26.2 0.6 35.0 32.4 81.2 47.5 13.6 6.5 32.0 33.3 91.7 42.3 20.5 7.4 42.0 34.6 58.2 20.3 9.2 1.5 13.9 65.9 59.4 29.8 14.2 1.6 21.0 54.3 62.1 15.8 10.5 2.0 18.8 63.8 50.3 15.4 16.5 2.1 25.0 59.0 46.9 35.1 14.4 9.1 41.9 32.8 54.2 40.5 35.0 4.3 15.6 27.4 52.8 40.2 14.8 9.1 34.1 35.2 48.2 37.1 19.7 2.7 11.1 46.2 44.8 50.7 33.5 4.7 22.1 30.2 44.1 22.4 29.5 4.0 23.2 48.1 33.7 44.7 23.6 0.0 43.6 31.5 23.3 29.7 35.0 9.8 19.2 38.4 31.8 27.0 22.8 3.6 39.4 34.9 65.4 55.6 37.2 3.5 15.5 24.1 63.1 28.9 4.9 3.7 17.4 57.8 77.2 33.2 11.9 4.4 14.4 48.5 69.0 39.6 20.3 3.9 21.5 44.8 67.9 34.3 22.2 3.6 29.7 41.7 77.8 47.9 49.2 4.7 72.8 10.0 67.3 27.9 14.7 1.2 14.9 54.6 52.7 14.8 3.6 3.8 0.5 27.4 52.7 10.7 0.8 10.2 0.0 18.3 82.2 30.9 3.7 4.5 0.0 6.6 80.9 18.9 4.4 1.2 0.0 5.4 68.4 13.6 2.6 5.1 0.3 10.2 77.7 29.4 2.3 1.1 0.0 11.1 49.3 7.5 2.5 4.2 2.2 36.3 54.4 16.3 3.1 2.7 0.0 30.3 58.8 14.6 2.7 2.5 0.2 30.2 42.4 23.4 6.0 4.2 0.0 38.8 23.9 4.8 0.3 6.5 0.2 34.5 30.6 5.3 3.9 0.0 1.3 26.7 26.4 1.0 3.2 2.3 0.0 36.8 22.1 12.6 7.3 3.5 0.0 38.8 59.0 5.7 8.6 1.9 0.9 15.2 44.0 4.4 0.0 7.7 0.0 33.2 54.5 0.8 0.0 2.7 0.0 25.7 11.5 4.7 0.0 12.2 0.0 37.1 23.4 0.7 5.0 5.7 0.0 39.3 38.6 3.2 0.0 4.9 5.1 14.1 58.2 3.3 1.6 4.2 2.0 29.8 64.3 14.3 9.1 1.9 0.4 17.0 53.0 17.0 1.2 5.1 0.6 20.6 45.7 21.3 1.2 3.7 0.6 19.8 56.4 3.7 2.3 9.7 0.0 12.1 41.3 27.7 2.5 9.2 2.0 21.6 Note: Table includes only surviving children age 1–35 months from among the two most recent births in the three years preceding the survey. 228 Table 6.22 Source of ORS packets Among children under age 3 who were treated with a solution made from oral rehydration salt (ORS) packets for diarrhoea in the two weeks preceding the survey, the percent distribution of children by source of ORS packets, India, 1998–99 Source Percent Public medical sector Government/municipal hospital Government dispensary UHC/UHP/UFWC CHC/rural hospital/PHC Sub-centre Government mobile clinic Government paramedic Other public medical sector NGO or trust Hospital/clinic NGO worker Private medical sector Private hospital/clinic Private doctor Private mobile clinic Private paramedic Vaidya/hakim/homeopath Pharmacy/drugstore Dai (TBA) Other private medical sector Other source Shop Husband Other relative/friend Other Total percent Number of children treated with ORS 37.6 13.5 2.5 0.7 12.7 4.3 0.2 1.0 2.5 0.8 0.6 0.3 40.2 13.0 14.7 0.1 1.9 0.6 9.2 0.0 0.8 21.4 17.2 2.0 0.2 1.9 100.0 1,528 Note: Table includes only surviving children age 1–35 months from among the two most recent births in the three years preceding the survey. Table excludes children with missing information on source of ORS packets. UHC: Urban health centre; UHP: Urban health post; UFWC: Urban family welfare centre; CHC: Community health centre; PHC: Primary Health Centre; NGO: Nongovernmental organization; TBA: Traditional birth attendant Table 6.23 Feeding practices during diarrhoea by state Percent distribution of children under age 3 who had diarrhoea in the past two weeks by amount given to drink and eat during diarrhoea by state, India, 1998–99 Amount given to drink during diarrhoea compared with amount given before diarrhoea Amount given to eat during diarrhoea compared with amount given before diarrhoea State Less Same More Don’t know Missing Total percent Less Same More Stopped completely Don’t know Missing Total percent India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 29.8 46.0 22.2 1.9 0.1 100.0 16.6 44.1 38.1 1.3 0.0 100.0 17.0 41.2 41.1 0.7 0.0 100.0 16.5 47.6 35.0 0.9 0.0 100.0 22.5 45.1 32.0 0.3 0.0 100.0 19.2 38.7 42.0 0.0 0.0 100.0 27.9 57.5 13.9 0.7 0.0 100.0 27.0 49.0 21.0 2.8 0.2 100.0 34.2 42.9 18.8 3.9 0.2 100.0 28.9 43.6 25.0 2.6 0.0 100.0 19.3 38.0 41.9 0.6 0.3 100.0 46.8 37.6 15.6 0.0 0.0 100.0 23.3 32.7 34.1 8.5 1.3 100.0 32.8 53.3 11.1 2.8 0.0 100.0 28.6 47.5 22.1 1.9 0.0 100.0 28.1 47.2 23.2 1.5 0.0 100.0 13.1 42.1 43.6 1.1 0.0 100.0 21.2 58.6 19.2 1.0 0.0 100.0 21.6 38.2 39.4 0.8 0.0 100.0 40.3 44.2 15.5 0.0 0.0 100.0 26.4 55.4 17.4 0.8 0.0 100.0 36.2 48.0 14.4 1.4 0.0 100.0 33.0 45.5 21.5 0.0 0.0 100.0 21.6 47.6 29.7 1.2 0.0 100.0 8.6 18.6 72.8 0.0 0.0 100.0 30.8 54.3 14.9 0.0 0.0 100.0 37.4 42.8 10.1 6.5 2.9 0.3 100.0 41.3 35.2 18.0 1.3 3.8 0.4 100.0 20.6 39.1 36.0 3.7 0.7 0.0 100.0 27.3 48.8 21.9 1.0 0.9 0.0 100.0 37.6 44.3 7.3 8.3 2.5 0.0 100.0 25.5 37.9 35.3 1.3 0.0 0.0 100.0 32.6 52.7 5.8 6.4 2.6 0.0 100.0 34.1 45.3 8.4 7.3 4.9 0.0 100.0 36.1 40.3 9.7 8.4 4.5 0.9 100.0 34.9 41.2 10.2 8.6 5.2 0.0 100.0 48.2 37.9 5.7 7.3 0.9 0.0 100.0 52.6 27.9 15.5 4.0 0.0 0.0 100.0 36.2 35.6 15.1 4.8 8.2 0.0 100.0 36.5 39.5 12.7 8.6 2.7 0.0 100.0 42.2 36.9 3.9 16.0 0.9 0.0 100.0 48.3 39.4 3.9 4.6 3.8 0.0 100.0 20.6 40.4 29.8 3.8 5.3 0.0 100.0 26.3 61.5 7.4 3.7 1.0 0.0 100.0 46.3 32.5 16.8 3.6 0.7 0.0 100.0 54.3 35.8 3.4 5.1 1.5 0.0 100.0 35.2 54.1 5.8 3.3 1.3 0.4 100.0 40.0 43.0 9.5 5.2 2.2 0.0 100.0 37.4 43.6 14.0 5.0 0.0 0.0 100.0 27.3 50.4 14.0 6.6 1.8 0.0 100.0 57.7 31.6 6.4 4.2 0.0 0.0 100.0 47.4 43.4 4.2 5.0 0.0 0.0 100.0 Note: Table includes only surviving children age 1–35 months from among the two most recent births in the three years preceding the survey. 230 6.8 HIV/AIDS Acquired Immune Deficiency Syndrome (AIDS) is an illness caused by the HIV virus, which weakens the immune system and leads to death through secondary infections such as tuberculosis or pneumonia. The virus is generally transmitted through sexual contact, through the placenta of HIV-infected women to their unborn children, or through contact with contaminated needles (injections) or blood. HIV and AIDS prevalence in India have been on the rise for more than a decade and have reached alarming proportions in recent years. The Government of India established a National AIDS Control Organization (NACO) under the Ministry of Health and Family Welfare in 1989 to deal with the epidemic. Since then there have been various efforts to prevent HIV transmission, such as public health education through the media and the activities of many nongovernmental organizations (NGOs). NFHS-2 included a set of questions on knowledge of AIDS and AIDS prevention. Ever- married women age 15–49 were first asked if they had ever heard of an illness called AIDS. Respondents who had heard of AIDS were asked further questions about their sources of information on AIDS, whether they believe that AIDS is preventable, and if so, what precautions, if any, a person can take to avoid infection. Knowledge of AIDS Table 6.24 shows the percentage of women who have heard about AIDS by background characteristics. Sixty percent of women in India have never heard of AIDS. Knowledge of AIDS varies little by women’s age, but it is somewhat higher among women age 25–34. Urban residence, education, and the standard of living all have a very strong positive association with AIDS knowledge. Seventy percent of urban women in India have heard about AIDS compared with only 30 percent of rural women. Knowledge of AIDS increases from only 18 percent among illiterate women to 92 percent among women who have at least completed high school. Similarly, knowledge of AIDS increases from 20 percent among women in households with a low standard of living to 74 percent among women in households with a high standard of living. Jain (83 percent), Christian (78 percent), Buddhist/Neo-Buddhist (69 percent), and Sikh (54 percent) women are much more likely to know about AIDS than Hindus, Muslims, or women belonging to other religions (28–39 percent). Only 17 percent of scheduled-tribe women have heard about AIDS compared with 32 percent of scheduled-caste women, 42 percent of women belonging to other backward classes, and 48 percent of ‘other’ women. Exposure to mass media increases women’s knowledge about AIDS substantially. Eighty-five percent of women who read a newspaper or magazine at least once a week know about AIDS compared with only 10 percent of women who are not regularly exposed to any mass media (newspapers, magazines, radio, television, cinema, or theatre). Table 6.24 Source of knowledge about AIDS The percentage of ever-married women who have heard about AIDS and among women who have heard about AIDS, the percentage who received information from specific sources by selected background characteristics, India, 1998–99 Among those who have heard about AIDS, percentage who received information from: Background characteristic Percentage who have heard about AIDS Number of women Radio Television Cinema News- paper/ magazine Poster/ hoarding Health worker Adult education programme Friend/ relative School/ teacher Other source Number of women who have heard about AIDS Age 15–24 25–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other 37.2 24,571 42.4 80.0 8.2 23.5 12.6 3.3 0.4 29.5 1.4 5.4 9,131 42.7 32,839 42.7 79.6 8.8 28.6 13.2 4.0 0.5 30.7 0.9 6.3 14,007 40.3 31,789 39.7 77.1 7.2 27.2 11.6 3.4 0.5 32.1 0.9 7.3 12,808 70.3 23,370 36.4 91.1 10.6 34.0 16.0 2.8 0.5 23.2 1.0 4.8 16,424 29.7 65,829 45.9 68.5 6.0 20.8 9.5 4.3 0.5 37.3 1.0 7.8 19,522 18.4 51,871 33.6 61.7 3.7 1.2 2.3 3.0 0.2 44.0 0.5 9.1 9,564 53.8 17,270 39.9 76.3 5.8 15.7 10.3 3.0 0.3 33.6 0.4 5.4 9,296 74.0 7,328 44.3 83.7 8.1 30.2 15.7 3.7 0.2 26.3 0.7 4.3 5,421 91.7 12,719 48.1 92.7 13.5 55.1 21.0 4.5 0.9 20.1 2.1 6.0 11,661 39.2 72,903 42.3 79.8 8.7 26.0 12.4 3.5 0.4 30.7 1.0 6.6 28,591 35.4 11,190 37.2 75.0 4.9 23.5 8.4 2.9 0.7 30.0 1.1 3.1 3,963 77.6 2,263 51.1 64.6 9.3 42.1 15.6 5.1 1.2 40.8 1.6 11.4 1,756 54.2 1,427 28.5 94.6 4.1 35.3 20.4 3.0 0.5 21.0 0.7 3.1 773 83.1 331 31.3 89.2 6.9 50.6 22.8 2.3 0.2 15.0 0.6 7.7 275 68.6 676 23.8 80.7 3.2 20.0 21.2 7.7 0.0 32.6 1.0 9.9 464 28.4 285 41.7 51.6 7.2 24.9 9.6 10.4 0.4 42.7 0.3 15.3 81 37.0 44 50.6 71.1 2.4 43.9 24.2 2.4 2.4 46.2 0.0 4.9 16 32.4 16,301 39.4 72.5 6.2 15.5 9.6 4.2 0.4 36.6 1.0 8.1 5,288 17.2 7,750 41.0 57.0 3.7 21.4 14.1 7.5 0.4 42.1 2.1 11.2 1,335 41.9 29,383 46.5 76.6 9.5 25.0 12.2 3.6 0.5 37.4 1.0 6.6 12,314 48.4 34,904 38.7 84.2 8.0 32.2 13.5 3.1 0.5 23.4 1.0 5.4 16,878 Contd… Table 6.24 Source of knowledge about AIDS (contd.) The percentage of ever-married women who have heard about AIDS and among women who have heard about AIDS, the percentage who received information from specific sources by selected background characteristics, India, 1998–99 Among those who have heard about AIDS, percentage who received information from: Background characteristic Percentage who have heard about AIDS Number of women Radio Television Cinema News- paper/ magazine Poster/ hoarding Health worker Adult education programme Friend/ relative School/ teacher Other source Number of women who have heard about AIDS Standard of living index Low Medium High Exposure to mass media Exposed to any media Listens to radio weekly Watches television weekly Goes to cinema/theatre monthly Reads newspaper/ magazine weekly Not regularly exposed to any media Total 19.6 29,033 40.4 51.5 5.1 8.3 6.1 3.8 0.4 50.1 0.9 10.2 5,682 40.1 41,289 42.5 76.1 6.7 19.9 10.4 3.9 0.4 32.7 0.8 6.4 16,559 74.3 17,845 40.9 93.9 11.2 43.4 17.7 3.2 0.6 20.6 1.4 4.9 13,267 60.7 53,224 43.3 83.5 8.7 29.2 13.2 3.5 0.5 27.9 1.1 5.8 32,316 61.6 32,547 59.2 81.1 9.9 32.0 13.0 3.7 0.6 28.4 1.2 6.0 20,040 68.1 40,788 40.2 90.9 9.2 30.4 13.9 3.4 0.5 25.5 1.1 5.4 27,776 71.9 9,457 48.8 84.6 19.6 33.1 14.3 3.8 0.7 32.4 1.4 6.3 6,795 85.1 18,567 47.9 89.4 12.2 51.1 19.6 4.1 0.8 22.4 1.6 5.7 15,809 10.1 35,975 26.2 37.3 2.4 5.3 5.8 4.4 0.2 57.6 0.9 12.0 3,630 40.3 89,199 41.5 78.8 8.1 26.8 12.5 3.6 0.5 30.9 1.0 6.4 35,946 Note: Total includes women with missing information on education, religion, caste/tribe, and the standard of living index, who are not shown separately. 233 State variations in the percentage of ever-married women who have heard about AIDS are shown in Table 6.25 and Figure 6.9. Knowledge of AIDS ranges from a low of only 12 percent in Bihar to 93 percent in Manipur and Mizoram. Bihar, Uttar Pradesh, Rajasthan, and Madhya Pradesh all have very low levels of AIDS awareness (below 23 percent). On the other hand, Tamil Nadu, Kerala, Delhi, Goa, and Nagaland (in addition to Manipur and Mizoram) have relatively high levels of AIDS awareness (above 72 percent). In NFHS-1, AIDS-awareness questions were asked in only 13 states so it is not possible to assess trends in AIDS awareness between NFHS-1 and NFHS-2 for India as a whole. However, in all of the 12 states with comparable information currently available, awareness of AIDS increased substantially between the two surveys. Particularly dramatic increases in AIDS knowledge have taken place in Tamil Nadu (from 23 to 87 percent), Delhi (from 36 percent to 79 percent), Maharashtra (from 19 to 61 percent), and Goa (from 42 percent to 76 percent). Source of Knowledge about AIDS As part of the AIDS prevention programme, the Government of India has been using mass media, especially electronic media, extensively to create awareness among the general public about AIDS and its prevention. NFHS-2 asked women who had heard of AIDS about their sources of AIDS information. Table 6.24 shows the percentage of ever-married women who have heard about AIDS from specific sources. Television is the most important source of information about AIDS among ever-married women in India. Seventy-nine percent of women report television as a source of their information about AIDS. Other important sources are the radio (42 percent), friends or relatives (31 percent), and newspapers or magazines (27 percent). Only 4 percent report that they received information about AIDS from a health worker. Television is the most important source of information about AIDS in both urban and rural areas, followed by the radio. Rural women are more likely than urban women to have learned about AIDS from the radio, a health worker, or a friend or relative. On the other hand, urban women are more likely to have learned about AIDS from television, cinema, newspapers or magazines, or posters or hoardings. More educated women are less likely than less educated women to have learned about AIDS from a friend or relative, but they are more likely to have learned about AIDS from each of the other sources. Scheduled-tribe women are less likely than other women to have learned about AIDS from television or cinema, but are more likely than other women to have learned about it from a health worker or a friend or relative. Women in households with a high standard of living are more likely than other women to have learned about AIDS from television, cinema, newspapers or magazines, or posters or hoardings; they are less likely to have learned about AIDS from a friend or relative. Finally, women who are not regularly exposed to mass media are much less likely to have learned about AIDS from any media sources, but they are more likely to have learned about AIDS from a friend or relative, as might be expected. Among ever-married women who have heard about AIDS, television is the primary source of information in most states, followed by the radio (Table 6.25). Newspapers and magazines are also important sources of information about AIDS in most states. The percentage who received AIDS information from a health worker is much higher in Mizoram, Sikkim, Himachal Pradesh, and Goa than in other states, but even in those states only 10–13 percent of women mention health workers as a source of information. Friends and relatives are a relatively Table 6.25 Source of knowledge about AIDS by state The percentage of ever-married women who have heard about AIDS and among women who have heard about AIDS, the percentage who received information from specific sources by state, India, 1998–99 Among those who have heard about AIDS, percentage who received information from: State Percentage who have heard about AIDS Radio Television Cinema Newspaper/ magazine Poster/ hoarding Health worker Adult education programme Friend/ relative School/ teacher Other source India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 40.3 41.5 78.8 8.1 26.8 12.5 3.6 0.5 30.9 1.0 6.4 79.2 36.1 96.9 13.2 38.8 21.6 2.4 0.4 14.2 0.6 3.1 44.3 32.2 90.5 3.6 26.3 17.8 3.2 0.6 24.4 2.4 2.6 60.9 33.3 89.8 2.7 28.0 31.9 10.4 0.5 21.7 0.8 3.7 31.9 45.9 86.4 2.2 16.4 4.0 2.2 0.4 17.9 0.9 1.0 54.6 25.2 94.6 3.9 34.2 23.0 3.1 0.7 24.2 0.6 2.8 20.8 28.1 87.4 4.5 26.7 12.6 3.3 0.2 13.0 1.3 4.0 22.7 27.8 93.8 5.3 29.9 7.0 3.4 0.3 10.7 0.8 2.0 20.2 39.4 90.4 7.4 22.4 6.3 1.2 0.0 11.1 0.3 1.9 11.7 55.4 82.9 13.8 22.1 2.9 1.2 0.4 16.4 1.1 3.2 39.0 61.8 74.4 5.1 16.7 7.0 2.2 0.4 40.2 0.8 2.9 26.4 31.3 84.8 5.2 25.8 6.0 1.8 0.0 16.3 0.3 4.2 60.4 30.8 62.7 5.0 9.3 8.1 1.7 0.5 65.3 1.4 4.5 33.7 63.2 63.6 15.5 27.9 17.0 3.1 0.2 38.5 0.9 5.1 92.9 73.2 34.5 4.1 23.1 12.5 6.1 0.1 57.4 0.8 17.9 44.2 54.9 60.6 4.5 42.9 21.0 6.0 1.4 57.4 1.1 4.8 93.2 67.4 30.4 1.7 60.1 44.4 12.9 1.6 59.3 2.8 16.0 72.4 39.8 40.0 1.2 25.8 27.1 3.1 1.0 72.3 1.0 23.4 53.6 57.1 70.7 4.6 21.2 24.3 10.7 0.5 40.3 0.9 4.5 76.3 26.5 82.5 2.4 34.7 18.5 10.2 1.8 32.9 2.5 13.0 29.8 15.2 85.9 5.2 46.4 37.6 3.8 0.3 11.9 1.5 5.4 61.1 22.2 76.8 2.7 23.0 16.6 6.5 0.2 32.8 1.5 13.6 55.3 33.7 74.3 14.7 15.9 6.8 2.9 0.3 40.6 0.9 7.7 58.1 68.3 80.6 12.0 26.9 10.9 4.4 0.4 33.4 0.9 3.4 86.9 66.8 57.3 4.3 60.6 7.2 3.9 2.5 34.6 2.0 5.0 87.3 52.4 75.1 11.8 19.2 14.3 3.4 0.4 50.9 0.9 8.9 235 important source of AIDS information in the northeastern and southern states, as well as in Orissa, Goa, and Maharashtra. Knowledge of Ways to Avoid AIDS Respondents who have heard of AIDS were asked if a person can do anything to avoid becoming infected. Those who reported that something could be done were asked what a person could do to avoid AIDS. Table 6.26 shows the percentage of ever-married women who know of no way to avoid AIDS and the percentages who report that AIDS can be avoided in specific ways, by selected background characteristics. Among women who have heard about AIDS, 33 percent do not know any way to avoid infection. As expected, this percentage is higher among rural women than among urban women and among women not regularly exposed to mass media than among other women. The percentage who do not know any way to avoid becoming infected with AIDS decreases sharply with increasing levels of education and household standard of living, as expected. This percentage is also considerably higher among Muslim women (40 percent) than among women Figure 6.9 Percentage Who Have Heard About AIDS by State 0 10 20 30 40 50 60 70 80 90 100 M izoram M anipur Tam il N adu K era la De lh i G oa Nagaland M aharashtra H im acha l P radesh A runacha l P radesh K arnataka A ndhra P radesh P unjab S ikk im Haryana M eghalaya INDIA O rissa A ssam Jam m u & K ashm ir G ujara t W est B enga l M adhya P radesh Ra jasthan Uttar P radesh B ihar P ercent NFHS-2, India, 1998–99 Table 6.26 Knowledge about avoidance of AIDS Among ever-married women who have heard about AIDS, the percentage who believe AIDS can be avoided in specific ways by selected background characteristics, India, 1998–99 Percentage who believe AIDS can be avoided by: Background characteristic Abstaining from sex Using condoms Having only one sex partner Avoiding sex with commercial sex workers Avoiding sex with homo- sexuals Avoiding blood transfusions Avoiding injections/ using clean needles Avoiding IV drug use Other ways Knows no way to avoid AIDS Number of women Age 15–24 25–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other 6.3 20.3 37.8 23.8 2.9 17.3 28.6 1.3 5.7 34.7 9,131 7.3 22.1 42.2 27.1 3.1 20.0 31.1 1.7 6.3 30.0 14,007 6.2 16.9 39.5 24.5 3.3 18.8 29.1 1.5 6.4 34.4 12,808 7.7 26.2 42.0 28.7 3.9 22.5 34.4 1.8 6.3 28.4 16,424 5.8 14.4 38.6 22.5 2.4 15.9 25.8 1.3 6.1 36.5 19,522 3.5 5.6 31.4 18.7 1.8 8.1 15.9 0.7 4.2 48.9 9,564 5.0 12.8 35.3 24.0 1.9 14.2 25.2 0.9 6.1 38.6 9,296 6.7 20.8 43.5 26.4 2.5 19.4 31.8 1.6 6.0 28.7 5,421 10.6 36.6 49.5 31.4 5.5 31.3 43.8 2.7 8.0 16.9 11,661 6.6 19.9 40.4 25.5 3.1 18.9 30.0 1.5 6.3 32.1 28,591 4.9 15.9 36.8 23.3 2.4 14.7 23.1 0.9 4.9 40.4 3,963 5.2 16.5 45.7 31.4 4.4 29.1 39.2 2.8 7.7 27.4 1,756 22.0 34.5 40.3 11.1 2.6 23.6 29.4 3.3 4.7 30.8 773 9.5 30.7 42.3 22.6 5.1 18.7 32.7 0.3 6.6 26.0 275 3.2 23.2 34.8 34.4 3.4 12.8 31.4 1.4 8.2 33.3 464 3.0 22.9 26.2 18.0 3.3 23.4 23.6 4.5 7.9 41.8 81 7.9 23.5 44.5 25.6 0.5 23.2 24.1 7.2 0.0 42.1 16 5.0 14.1 39.7 23.3 2.3 15.1 24.1 1.0 5.6 37.0 5,288 6.3 16.3 25.7 21.0 3.7 15.4 26.4 2.8 8.0 44.6 1,335 4.5 15.3 47.2 29.0 3.1 20.8 30.2 1.4 5.6 28.2 12,314 8.8 25.1 36.5 23.7 3.4 19.1 31.5 1.7 6.7 33.6 16,878 Contd… Table 6.26 Knowledge about avoidance of AIDS (contd.) Among ever-married women who have heard about AIDS, the percentage who believe AIDS can be avoided in specific ways by selected background characteristics, India, 1998–99 Percentage who believe AIDS can be avoided by: Background characteristic Abstaining from sex Using condoms Having only one sex partner Avoiding sex with commercial sex workers Avoiding sex with homo- sexuals Avoiding blood transfusions Avoiding injections/ using clean needles Avoiding IV drug use Other ways Knows no way to avoid AIDS Number of women Standard of living index Low Medium High Exposure to mass media Exposed to any media Listens to radio weekly Watches television weekly Goes to cinema/theatre monthly Reads newspaper/magazine weekly Not regularly exposed to any media Total 2.9 5.5 36.5 21.5 1.3 9.4 17.8 0.5 4.6 43.5 5,682 5.0 15.0 38.3 24.9 2.7 16.3 27.3 1.2 5.8 36.1 16,559 10.3 31.8 44.0 27.3 4.4 26.3 38.0 2.4 7.4 24.2 13,267 6.9 21.4 41.2 26.5 3.3 20.2 31.6 1.6 6.4 30.6 32,316 7.4 22.1 42.8 27.5 4.0 22.6 34.0 1.7 6.8 28.3 20,040 7.3 23.3 41.8 26.9 3.4 21.3 32.8 1.7 6.5 29.4 27,776 6.9 25.5 44.8 29.1 4.4 24.7 37.1 1.9 7.1 25.4 6,795 9.0 31.4 47.3 31.1 4.7 27.9 40.7 2.2 7.6 20.6 15,809 4.1 5.5 30.1 15.3 1.3 7.1 13.3 0.7 4.3 52.0 3,630 6.7 19.8 40.1 25.3 3.1 18.9 29.7 1.5 6.2 32.8 35,946 Note: Total includes 3, 26, 131, and 438 women with missing information on education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. 238 from almost all other religious groups. Scheduled-tribe women are less likely to know any way to avoid AIDS than other women. Among women who report that something can be done to prevent AIDS, the most commonly mentioned ways of avoiding AIDS are having only one sex partner (40 percent) and avoiding injections or using clean needles (30 percent). Avoiding sex with commercial sex workers, using condoms, and avoiding blood transfusions are also mentioned as ways to avoid AIDS by substantial proportions of women (25, 20, and 19 percent, respectively). Only 7 percent mention abstaining from sex, 3 percent mention avoiding sex with homosexuals, and 2 percent mention avoiding intravenous drug use. The percentage reporting each means of avoiding AIDS is lower among rural than among urban women and among women not regularly exposed to mass media than among other women. The level of education and the household standard of living are strongly and positively associated with women mentioning each of these ways of avoiding AIDS. Table 6.27 shows state variations in specific ways to avoid AIDS. Even among women who have heard about AIDS, about one-half of women or more do not know of any way to avoid getting AIDS in Sikkim, Arunachal Pradesh, Jammu and Kashmir, Assam, West Bengal, and Bihar. On the other hand, in Mizoram, Tamil Nadu, and Orissa a large majority of women (84 percent or more) know of at least one way to avoid AIDS. The percentage mentioning the use of condoms as a way to avoid AIDS ranges 3 percent in Nagaland to 52 percent in Delhi. Other states where condoms are rarely mentioned as a way to avoid infection include Karnataka (9 percent), Tamil Nadu (11 percent), and Kerala (12 percent). ‘Having only one sex partner’ is mentioned more often than ‘avoiding injections or using clean needles’ in 16 out of 25 states. ‘Abstaining from sex’ is mentioned much less frequently as a way to avoid AIDS in the southern and western states than in other states. The lack of knowledge of AIDS, its modes of transmission, and ways to avoid infection among women in India is a major challenge to efforts to avoid the spread of AIDS. Most ever- married women in their childbearing years have never heard of AIDS, and many of those who have heard of AIDS do not know even one way to avoid infection. It is clear that AIDS prevention organizations need to strengthen the educational components of their programmes, in addition to trying to reduce high-risk behaviour, since even basic information about AIDS is seriously deficient, at least among women in India. 239 Table 6.27 Knowledge about avoidance of AIDS by state Among ever-married women who have heard about AIDS, the percentage who believe AIDS can be avoided in specific ways by state, India, 1998–99 Percentage who believe AIDS can be avoided by: State Abstaining from sex Using con- doms Having only one sex partner Avoiding sex with commercial sex workers Avoiding sex with homo- sexuals Avoiding blood trans- fusions Avoiding injections/ using clean needles Avoiding IV drug use Other ways Knows no way to avoid AIDS India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 6.7 19.8 40.1 25.3 3.1 18.9 29.7 1.5 6.2 32.8 17.4 52.0 54.4 21.0 7.0 30.2 42.2 1.3 4.1 23.7 23.0 36.5 43.4 8.4 1.0 20.7 31.6 2.0 4.0 28.5 21.9 39.8 44.9 11.4 0.9 15.3 30.1 0.9 2.4 26.7 6.7 15.9 26.7 8.4 2.8 12.6 20.4 2.4 6.5 51.8 25.2 34.8 40.3 10.6 1.8 23.2 29.9 4.0 5.4 32.1 10.7 33.7 36.0 4.1 1.5 9.7 19.0 1.4 5.3 40.5 10.1 26.4 21.6 7.3 2.0 11.4 23.2 1.2 3.0 44.9 10.0 24.8 27.9 11.2 2.8 14.8 22.5 1.5 4.6 45.0 18.8 23.7 25.7 11.8 3.2 9.8 16.8 4.5 12.1 49.6 16.9 14.5 39.5 34.5 2.8 27.1 61.8 4.9 25.2 15.7 6.7 21.1 18.9 15.2 2.1 10.7 20.4 1.0 5.4 50.5 1.9 20.7 21.1 9.1 5.3 21.2 16.8 2.9 4.9 52.5 15.2 26.5 23.2 13.8 3.7 18.7 18.6 2.7 3.3 51.7 7.2 15.4 26.5 39.8 2.7 36.9 51.5 10.2 5.9 29.0 11.8 18.9 33.6 10.5 2.3 22.6 25.6 8.1 5.1 47.8 20.7 39.8 42.8 34.9 8.8 25.3 63.7 9.8 9.0 6.2 10.6 3.2 12.9 42.7 3.3 40.5 55.2 20.7 25.5 25.3 2.3 23.6 22.5 4.3 1.4 11.7 18.2 0.5 7.3 62.6 2.9 15.0 33.7 36.6 1.1 28.7 40.7 2.0 9.5 25.1 1.8 27.2 33.0 34.6 2.6 18.7 25.6 0.8 6.0 35.4 2.2 20.1 37.6 33.3 1.8 10.9 27.3 0.8 6.9 33.3 3.9 16.1 32.2 26.0 2.1 20.8 38.2 1.5 6.0 36.8 3.0 8.6 25.3 37.6 13.8 30.2 38.7 1.1 7.5 36.0 0.7 12.0 57.8 26.2 2.0 23.8 24.5 0.5 4.6 26.6 1.2 11.0 74.7 37.6 1.5 22.5 28.6 0.7 3.5 11.5 CHAPTER 7 NUTRITION AND THE PREVALENCE OF ANAEMIA This chapter focuses on the nutrition of women and young children, examining both the types of food consumed and the consequences of inadequate nutrition and poor feeding practices. NFHS-1 included basic information about feeding practices and the nutritional status of young children. NFHS-2 contains more comprehensive information on these topics, and, for the first time, information on the diet of women. Measurement of height and weight has been expanded to include ever-married women as well as young children. Two additional tests have been included for the first time—anaemia testing for women and young children and the testing of cooking salt to determine the extent of iodization. A specially trained health investigator attached to each interviewing team conducted height and weight measurements and anaemia testing. 7.1 Women’s Food Consumption The consumption of a wide variety of nutritious foods is important for women’s health. Adequate amounts of protein, fat, carbohydrates, vitamins, and minerals are required for a well- balanced diet. Meat, fish, eggs, and milk, as well as pulses and nuts, are rich in protein. Green, leafy vegetables are a rich source of iron, folic acid, vitamin C, carotene, riboflavin, and calcium. Many fruits are also good sources of vitamin C. Bananas are rich in carbohydrates. Papayas, mangoes, and other yellow fruits contain carotene, which is converted to vitamin A. Vitamin A is also present in milk and milk products, as well as egg yolks (Gopalan et al., 1996). NFHS-2 asked ever-married women how often they consume various types of food (daily, weekly, occasionally, or never). Women consume vegetables (other than green, leafy vegetables) most often (Table 7.1). Almost two-thirds of women consume these vegetables every day and 93 percent of women eat these vegetables at least once a week. Pulses and beans, as well as green, leafy vegetables, are also an important part of the diet. Almost half of women (47 percent) eat pulses or beans every day and 42 percent eat green, leafy vegetables every day. Milk or curd is a common part of the diet for a majority of women, but 45 percent of women consume milk or curd only occasionally or never. Fruits are eaten daily by only 8 percent of women and only one-third of women eat fruits at least once a week. Almost one-third of women in India never eat chicken, meat, or fish and very few women (only 6 percent) eat chicken, meat, or fish every day. Eggs are consumed slightly less often than chicken, meat, or fish. Table 7.2 shows that there are substantial differentials in food consumption patterns by selected background characteristics. Age does not play an important role in women’s consumption patterns. Women in urban areas are more likely than women in rural areas to include every type of food in their diet, particularly nutritious foods such as fruits and milk or curd. Illiterate women have poorer and less varied diets than literate women, and their diet is particularly deficient in the consumption of fruits. Hindus are less likely than Muslims or Christians to eat eggs, chicken, meat, or fish at least once a week. Sikhs and Jains rarely eat chicken, meat, fish, or eggs, but they are more likely than women in any other religious group to consume milk or curd, as well as pulses or beans. Jains are more likely than women in any other religious group to eat fruits at least once a week. 242 Table 7.1 Women’s food consumption Percent distribution of ever-married women by frequency of consumption of specific foods, India, 1998–99 Frequency of consumption Type of food Daily Weekly Occasionally Never Missing Total percent Milk or curd Pulses or beans Green, leafy vegetables Other vegetables Fruits Eggs Chicken, meat, or fish 37.5 17.4 34.1 10.9 0.0 100.0 46.9 40.8 11.6 0.6 0.0 100.0 41.8 43.4 14.3 0.4 0.0 100.0 65.1 28.0 6.6 0.2 0.0 100.0 8.1 24.9 62.2 4.7 0.1 100.0 2.8 25.0 37.9 34.2 0.0 100.0 5.8 26.1 37.3 30.8 0.0 100.0 Table 7.2 Women’s food consumption by background characteristics Percentage of ever-married women consuming specific foods at least once a week by selected background characteristics, India, 1998–99 Type of food Background characteristic Milk or curd Pulses or beans Green, leafy vegetables Other vegetables Fruits Eggs Chicken, meat, or fish Number of women Age 15–24 25–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 53.3 88.1 85.5 92.7 30.8 28.2 31.3 24,571 55.4 87.7 85.5 93.2 34.0 28.6 32.5 32,839 55.8 87.6 84.8 93.3 33.7 26.7 31.8 31,789 65.3 92.8 88.4 95.0 53.9 39.7 41.7 23,370 51.3 86.0 84.1 92.4 25.6 23.6 28.5 65,829 46.5 85.0 83.8 91.6 20.8 22.5 25.9 51,871 57.3 90.1 85.6 94.5 37.6 34.4 41.2 17,270 65.4 91.8 87.8 95.3 47.5 35.9 41.5 7,328 80.2 93.8 89.3 96.3 68.4 36.1 38.5 12,719 55.7 88.5 85.1 93.0 31.9 24.9 27.5 72,903 46.8 83.7 85.8 93.8 32.9 44.1 55.7 11,190 53.7 78.2 76.5 93.6 53.0 49.7 70.1 2,263 91.0 98.7 97.3 97.9 48.2 11.8 5.1 1,427 82.3 94.7 88.2 87.9 70.9 2.3 2.3 331 43.4 92.1 93.4 88.9 41.0 48.1 51.2 676 23.3 74.0 91.6 87.4 27.8 31.7 43.8 285 31.3 67.0 94.5 87.9 40.7 32.7 64.3 44 44.9 85.6 84.5 93.2 24.5 27.5 32.6 16,301 34.4 80.6 81.5 87.6 20.9 21.9 25.7 7,750 57.8 89.4 84.7 93.9 33.5 29.8 31.8 29,383 62.1 89.0 86.9 93.6 39.7 27.8 33.4 34,904 35.0 81.4 82.1 91.6 17.0 23.8 29.1 29,033 58.1 89.4 85.3 93.1 31.5 28.6 33.1 41,289 80.0 94.3 90.0 95.7 62.0 32.3 33.6 17,845 55.0 87.8 85.2 93.1 33.0 27.8 31.9 89,199 Note: Total includes 11, 79, 862, and 1,032 women with missing information on education, religion, caste/tribe, and the standard of living index, respectively, who are not shown separately. 243 Women from scheduled tribes have a relatively poor diet that is particularly deficient in fruits and milk or curd. In fact, scheduled-tribe women are less likely than women in any other caste/tribe group to consume each of the food items shown. Women from scheduled castes and other backward classes also have relatively poor diets compared with women in the ‘other’ category. As expected, poverty has a strong negative effect on the consumption of nutritious types of food. Women in households with a low standard of living are less likely than other women to eat each type of food listed, and their diet is particularly deficient in fruits and milk or curd. Table 7.3 provides information on the regular consumption of specific foods by state. More than 90 percent of women in Haryana and Punjab consume milk or curd at least once a week, whereas less than 20 percent of women in Manipur and Arunachal Pradesh consume milk or curd regularly. Pulses and beans are eaten regularly by a majority of women in every state except Manipur. Green, leafy vegetables are eaten regularly by at least 70 percent of women in every state except Kerala, where only 55 percent of women eat green, leafy vegetables on a regular basis. Regular consumption of other vegetables is common everywhere, ranging from less than 80 percent in Arunachal Pradesh and Rajasthan to more than 99 percent in Punjab, Haryana, and Gujarat. The regular consumption of fruits varies widely from less than 20 percent in Uttar Pradesh and the three eastern states to 72 percent in Himachal Pradesh. The consumption of eggs is well below average in all of the northern and central states, as well as in Gujarat, Manipur, Orissa, and Bihar. The regular consumption of chicken, meat, or fish is very low throughout Northern and Central India (with the exception of Jammu and Kashmir), as well as Gujarat. Not more than 15 percent of women in any of these states eat chicken, meat, or fish at least once a week. The regular consumption of these foods is relatively high throughout the Northeast, as well as West Bengal, Goa, and most states in the South. 7.2 Nutritional Status of Women In NFHS-2, ever-married women age 15–49 were weighed using a solar-powered digital scale with an accuracy of ±100 grams. Their height was measured using an adjustable wooden measuring board specially designed to provide accurate measurements (to the nearest 0.1 cm) of women and children in a field situation. The weight and height data were used to calculate several indicators of women’s nutritional status as shown in Table 7.4. The height of an adult is an outcome of several factors including nutrition during childhood and adolescence. A woman’s height can be used to identify women at risk of having a difficult delivery, since small stature is often related to small pelvic size. The risk of having a baby with a low birth weight is also higher for mothers who are short. The cutoff point for height, below which a woman can be identified as nutritionally at risk, varies among populations, but it is usually considered to be in the range of 140–150 centimetres (cm). NFHS-2 found a mean height for women in India of 151 cm. The mean height varies only slightly (between 150 and 155 cm) for women in different population groups, as shown in Table 7.4. Sikh women and Jain women are taller, on average, than women in any other group. Thirteen percent of women are under 145 cm in height. The percentage of women who are below 145 cm does not vary much by age, marital status, or residence, but there is a strong negative relationship between this measure of height and both education and the standard of living index. The percentage of women who are short varies most by religion, ranging from 244 4–8 percent for Sikhs and Jains to 24–25 percent for women with ‘other’ religions and no religion. By caste/tribe, scheduled caste women are most likely to be short (17 percent). Table 7.4 also shows several measures of an index that relates a woman’s weight to her height. The body mass index (BMI) can be used to assess both thinness and obesity. The BMI is defined as the weight in kilograms divided by the height in metres squared (kg/m2). This index excludes women who were pregnant at the time of the survey or women who had given birth during the two months preceding the survey. The mean BMI for women in India is 20.3 (varying within the narrow range of 19–23 for the different groups shown in the table). Chronic energy deficiency is usually indicated by a BMI of less than 18.5. More than one-third (36 percent) of women have a BMI below 18.5, indicating a high prevalence of nutritional deficiency. Nutritional problems are particularly serious for rural women, illiterate women, women from ‘other’ religions, scheduled-caste and scheduled-tribe women, working women who are not self- employed, and women who live in households with a low standard of living. Table 7.3 Women’s food consumption by state Percentage of ever-married women consuming specific foods at least once a week by state, India, 1998–99 Type of food State Milk or curd Pulses or beans Green, leafy vegetables Other vegetables Fruits Eggs Chicken, meat, or fish India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 55.0 87.8 85.2 93.1 33.0 27.8 31.9 73.3 91.2 86.8 92.8 57.8 21.2 15.1 93.2 99.3 99.2 99.2 54.8 7.7 3.8 87.0 99.1 94.3 98.8 71.7 14.7 6.2 72.1 68.5 85.5 88.3 44.0 14.2 31.1 91.1 99.2 99.1 99.5 50.7 10.8 3.6 70.7 81.4 77.8 78.9 20.5 6.1 7.8 32.5 79.9 80.9 86.1 22.7 11.7 11.2 57.2 88.0 90.0 90.7 19.0 9.9 8.7 46.7 88.7 96.0 96.1 18.3 22.1 21.5 20.7 80.7 90.9 95.8 14.4 15.6 28.2 25.0 76.3 91.4 98.7 15.0 43.5 69.0 19.9 51.2 95.6 72.7 28.9 33.5 57.4 41.7 85.3 87.6 94.9 33.3 58.4 57.7 15.3 37.3 96.9 93.2 34.3 14.8 47.4 23.7 61.5 88.9 91.8 40.3 32.6 61.8 22.9 64.5 99.2 87.1 61.6 42.5 59.3 82.7 59.6 96.3 80.6 40.9 30.2 72.3 72.4 82.9 94.9 87.5 28.8 26.8 57.1 65.0 76.5 74.6 82.5 65.8 36.6 89.0 80.0 97.0 74.1 99.2 44.4 14.0 12.4 47.3 94.5 87.9 91.1 44.7 34.4 38.2 72.0 92.3 72.7 95.7 47.6 59.7 56.7 75.5 98.6 93.3 91.8 53.7 39.9 33.9 45.3 69.8 54.8 90.9 56.5 27.3 82.8 66.5 94.6 77.6 98.7 46.2 52.7 52.6 245 Table 7.4 Nutritional status of women Among ever-married women, mean height, percentage with height below 145 cm, mean body mass index (BMI), and percentage with specified levels of BMI by selected background characteristics, India, 1998–99 Height Weight-for-height1 Background characteristic Mean height (cm) Percent- age below 145 cm Number of women for height Mean body mass index (BMI) Percent- age with BMI below 18.5 kg/m2 Percent- age with BMI of 25.0 kg/m2 or more Percent- age with BMI of 30.0 kg/m2 or more Number of women for BMI Age 15–19 20–24 25–29 30–34 35–49 Marital status Currently married Not currently married Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living index Low Medium High Total 150.6 14.7 7,480 19.3 38.8 1.7 0.1 6,707 151.2 13.0 15,185 19.3 41.8 3.6 0.4 12,928 151.4 12.4 16,618 19.8 39.1 7.3 1.2 15,030 151.5 12.3 14,051 20.4 35.0 11.7 2.4 13,399 151.2 13.7 29,451 21.1 31.1 16.8 3.9 29,056 151.3 13.1 77,737 20.3 35.6 10.6 2.2 72,093 150.8 14.8 5,049 20.1 39.3 10.3 2.1 5,026 151.6 12.0 21,690 22.1 22.6 23.5 5.8 20,563 151.1 13.6 61,095 19.6 40.6 5.9 0.9 56,556 150.6 15.4 47,773 19.5 42.6 5.1 0.9 44,251 151.4 12.2 16,253 20.6 32.6 12.9 2.7 15,234 152.0 9.8 6,908 21.1 28.0 15.7 3.2 6,447 152.9 7.7 11,840 22.5 17.8 26.0 6.4 11,178 151.1 13.5 67,895 20.1 36.9 9.6 2.0 63,394 151.5 12.3 10,108 20.5 34.1 12.4 2.8 9,207 152.1 10.3 2,100 21.4 24.6 17.6 3.4 1,981 155.0 3.9 1,358 23.0 16.4 30.1 8.0 1,280 153.6 7.6 300 23.4 15.8 33.7 9.8 286 149.9 17.3 638 20.4 33.3 10.5 2.8 607 149.5 24.6 270 19.2 49.4 7.0 0.4 261 149.8 24.1 42 20.6 34.5 13.8 3.4 37 150.3 17.0 15,234 19.5 42.1 5.8 0.9 14,040 150.8 13.5 7,175 19.1 46.3 3.3 0.5 6,590 151.0 13.5 27,295 20.2 35.8 9.4 1.7 25,474 152.0 10.9 32,334 21.0 30.5 15.4 3.7 30,345 151.5 11.4 11,877 19.5 41.9 5.2 0.8 11,114 150.8 14.7 16,301 19.5 44.3 6.4 1.2 15,512 150.8 15.4 4,133 20.5 35.0 12.1 2.5 3,955 151.3 12.9 50,450 20.7 31.6 13.1 2.9 46,514 150.0 17.7 26,687 18.9 48.1 2.6 0.3 24,589 151.3 12.5 38,451 20.1 35.6 8.6 1.5 35,732 153.0 7.5 16,706 22.7 17.3 27.2 6.8 15,938 151.2 13.2 82,785 20.3 35.8 10.6 2.2 77,119 Note: Total includes women with missing information on education, religion, caste/tribe, work status, and the standard of living index, who are not shown separately. 1Excludes women who are pregnant and women with a birth in the preceding two months. The body mass index (BMI) is the ratio of the weight in kilograms to the square of the height in metres (kg/m2). 246 Obesity is becoming a substantial problem among several groups of women in India, particularly women living in urban areas, women who are well educated, and women from households with a high standard of living. Approximately one-quarter of women in each of these groups have a BMI of 25 or more and 6–7 percent have a BMI of 30 or more. In addition to being relatively tall, Sikh and Jain women are more likely than women in any other group to be obese. State differentials in the mean height of women are not large, but women in the Northern Region are 1–3 cm taller than average (Table 7.5). The shortest women are from the Eastern Region, as well as Uttar Pradesh and parts of the Northeast. A similar pattern is evident for the percentage of women below 145 cm. The mean body mass index also varies within a narrow range, from 19.2 in Orissa to 23.7 in Delhi. Arunachal Pradesh, Sikkim, and Delhi have the Table 7.5 Nutritional status of women by state Among ever-married women, mean height, percentage with height below 145 cm, mean body mass index (BMI), and percentage with specified levels of BMI by state, India, 1998–99 Height Weight-for-height1 State Mean height (cm) Percentage below 145 cm Mean body mass index (BMI) Percentage with BMI below 18.5 kg/m2 Percentage with BMI of 25.0 kg/m2 or more Percentage with BMI of 30.0 kg/m2 or more India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 151.2 13.2 20.3 35.8 10.6 2.2 152.5 9.9 23.7 12.0 33.8 9.2 154.3 4.6 21.3 25.9 16.6 3.9 152.7 6.1 20.8 29.7 13.1 2.3 153.5 6.7 21.0 26.4 13.8 3.0 154.5 4.1 23.0 16.9 30.2 9.1 153.7 5.6 19.9 36.1 7.1 1.6 151.7 10.8 19.8 38.2 6.1 1.2 150.3 16.4 20.0 35.8 7.5 1.5 149.5 19.5 19.4 39.3 3.7 0.5 150.5 14.9 19.2 48.0 4.4 0.6 150.0 19.2 19.7 43.7 8.6 1.3 150.8 11.9 21.0 10.7 5.1 0.6 149.9 17.3 20.1 27.1 4.2 0.7 151.5 10.3 21.1 18.8 10.8 1.2 150.6 21.1 20.3 25.8 5.8 1.2 151.6 10.7 20.4 22.6 5.3 0.5 151.6 10.6 20.9 18.4 8.2 0.7 150.2 14.8 22.0 11.2 15.7 2.5 151.8 12.3 21.6 27.1 21.2 4.3 151.8 10.2 20.7 37.0 15.8 4.4 151.4 11.9 20.2 39.7 11.7 2.9 151.2 12.7 20.3 37.4 12.0 2.2 152.0 9.6 20.4 38.8 13.6 2.9 152.6 8.8 22.0 18.7 20.6 3.8 151.5 12.0 21.0 29.0 14.7 2.7 1Excludes women who are pregnant and women with a birth in the preceding two months. The body mass index (BMI) is the ratio of the weight in kilograms to the square of the height in metres (kg/m2). 247 lowest percentage of women with a low BMI (11–12 percent) and Orissa has the highest percentage (48 percent). The level of obesity is much higher in Delhi and Punjab than in any other state. Over 30 percent of women in these two states have a BMI of at least 25 and 9 percent have a BMI of at least 30. Other states with particularly high levels of obesity are Goa and Kerala (21 percent each). Obesity is least common (less than 10 percent) in all parts of Central and Eastern India, most states in the Northeast, and Rajasthan. 7.3 Anaemia Among Women Anaemia is characterized by a low level of haemoglobin in the blood. Haemoglobin is necessary for transporting oxygen from the lungs to other tissues and organs of the body. Anaemia usually results from a nutritional deficiency of iron, folate, vitamin B12, or some other nutrients. This type of anaemia is commonly referred to as iron-deficiency anaemia. Iron deficiency is the most widespread form of malnutrition in the world, affecting more than two billion people (Stolzfus and Dreyfuss, 1998). In India, anaemia affects an estimated 50 percent of the population (Seshadri, 1998). Anaemia may have detrimental effects on the health of women and children and may become an underlying cause of maternal mortality and perinatal mortality. Anaemia also results in an increased risk of premature delivery and low birth weight (Seshadri, 1997). Early detection of anaemia can help to prevent complications related to pregnancy and delivery, as well as child- development problems. Information on the prevalence of anaemia can be useful for the development of health-intervention programmes designed to prevent anaemia, such as iron- fortification programmes. In India, under the Government’s Reproductive and Child Health Programme, iron and folic acid tablets are provided to pregnant women in order to prevent anaemia during pregnancy. Because anaemia is such a serious health problem in India, NFHS-2 undertook direct measurement of the haemoglobin levels of all ever-married women age 15–49 and their children under three years of age. Measurements were taken in the field using the HemoCue system1. This system uses a single drop of blood from a finger prick (or heel prick in the case of infants under six months old), which is drawn into a cuvette and then inserted into a portable, battery-operated instrument2. In less than one minute, the haemoglobin concentration is indicated on a digital read-out. Before the anaemia testing was undertaken in a household, the health investigator read a detailed informed consent statement to the respondent, informing her about anaemia, describing the procedure to be followed for the test, and emphasizing the voluntary nature of the test. She was then asked whether or not she would consent to have the test done for herself and her young children, if any. The health investigator then signed the questionnaire at the bottom of the statement to indicate that it had been read to the respondent and recorded her agreement or lack 1The HemoCue instrument has been used extensively throughout the world for estimating the concentration of haemoglobin in capillary blood in field situations. The HemoCue has been found to give accurate results on venous blood samples, comparable to estimates from more sophisticated laboratory instruments (Von Schenk et al., 1986; McNulty et al., 1995; Krenzicheck and Tanseco, 1996). A recent small-scale study in India (Prakash et al., 1999), however, found that the HemoCue provided slightly higher estimates of haemoglobin than the standard blood cell counter (BCC) method. 2Because the first 2–3 drops of blood are wiped away to be sure that the sample used for analysis consists of fresh capillary blood, it is actually the third or fourth drop of blood that is drawn into the cuvette. 248 of agreement to the testing. If the test was conducted, at the end of the test the respondent was given a written record of the results for herself and each of her young children. In addition, the health investigator described to her the meaning of the results and advised her if medical treatment was necessary. In cases of severe anaemia, the respondent was read an additional statement asking whether or not she would give her permission for the survey organization to inform a local health official about the problem. For each Primary Sampling Unit, a local health official was given a list of severely anaemic women (and children) who had consented to the referral. Table 7.6 and Figure 7.1 show anaemia levels for ever-married women age 15–49. Three levels of severity of anaemia are distinguished: mild anaemia (10.0–10.9 grams/decilitre for pregnant women and 10.0–11.9 g/dl for nonpregnant women), moderate anaemia (7.0–9.9 g/dl), and severe anaemia (less than 7.0 g/dl). Appropriate adjustments in these cutoff points were made for women living at altitudes above 1,000 metres and women who smoke, since both of these groups require more haemoglobin in their blood (Centers for Disease Control and Prevention, 1998). In India, haemoglobin levels were tested for 88 percent of women (see Table D.3 in Appendix D). Overall, 52 percent of women have some degree of anaemia3. Thirty-five percent of women are mildly anaemic, 15 percent are moderately anaemic, and 2 percent are severely anaemic. There are some differences in the prevalence of anaemia by background characteristics, but anaemia is substantial for women in every population group. The prevalence of anaemia is slightly higher for younger women less than age 25 than for older women and for women who are not currently married than for currently married women. It is considerably higher for rural women (54 percent) than for urban women (46 percent). Anaemia decreases steadily with increases in the level of educational attainment, from 56 percent among illiterate women to 40 percent among women who have completed at least high school. Anaemia also decreases steadily with increases in the standard of living index. About half of Hindu, Muslim, and Buddhist women are anaemic. Anaemia is slightly lower among Christians and substantially lower among Sikhs and Jains. The highest levels of anaemia are evident for women from ‘other’ religions and women with no religion. By caste/tribe, scheduled-tribe women have the highest levels of anaemia (65 percent), followed by scheduled-caste women (56 percent) and women from other backward classes (51 percent). Women who are not in any of these three groups have the lowest level of anaemia (48 percent). The prevalence of anaemia does not vary much by work status, but women who do not work have slightly less anaemia than working women. The prevalence of anaemia is slightly higher for breastfeeding women than for other groups, but there is no difference in the prevalence of anaemia between pregnant women and nonpregnant women who are not breastfeeding. Since anaemia is often considered to be particularly problematic for pregnant women, it is noteworthy that these women have slightly lower than average levels of anaemia. The provision of iron and folic acid supplements to pregnant women has undoubtedly reduced the overall prevalence of anaemia in pregnant women (58 percent of pregnant women received IFA tablets or syrup during pregnancy for births in the 3If the hemoglobin measurements are not adjusted for smoking and for the altitude of the enumeration area, the estimated prevalence of anaemia is slightly lower (51 percent of women would be defined as anaemic instead of 52 percent). The small impact of the adjustment factor is to be expected since, in India, less than 3 percent of women age 15 and over smoke (see Table 2.16), and 90 percent of the sample PSUs (2,836 of the 3,165 PSUs) are at an altitude below 1,000 metres. 249 three years preceding the survey—see Table 8.6). However, by far the highest levels of moderate anaemia are experienced by pregnant women (25 percent), and pregnant women also are subject to a somewhat higher level of severe anaemia. For this reason, anaemia remains a serious problem among pregnant women. Table 7.6 Anaemia among women Percentage of ever-married women classified as having iron-deficiency anaemia by degree of anaemia, according to selected background characteristics, India, 1998–99 Percentage of women with: Background characteristic Percentage of women with any anaemia Mild anaemia Moderate anaemia Severe anaemia Number of women Age 15–19 20–24 25–29 30–34 35–49 Marital status Currently married Not currently married Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living Index Low Medium High 56.0 36.2 17.9 1.9 7,117 53.8 34.8 17.0 2.0 14,560 51.4 34.8 14.7 1.9 15,965 50.5 34.8 13.7 1.9 13,595 50.5 35.1 13.6 1.9 28,426 51.5 34.9 14.8 1.8 74,830 55.5 36.6 15.7 3.1 4,833 45.7 32.0 12.2 1.5 20,872 53.9 36.1 15.8 2.0 58,791 55.8 36.7 16.8 2.3 45,818 50.1 34.4 13.8 1.9 15,735 48.0 34.0 12.6 1.3 6,718 40.3 29.7 9.7 0.9 11,381 52.4 35.5 15.0 2.0 65,507 49.6 34.2 14.2 1.3 9,545 47.1 30.7 14.4 2.0 2,007 39.6 26.6 11.8 1.2 1,315 42.5 30.8 10.9 0.8 290 48.6 30.1 15.3 3.1 630 75.7 47.3 24.6 3.8 265 59.5 34.2 24.9 0.4 40 56.0 37.2 16.5 2.3 14,657 64.9 41.2 21.4 2.3 6,908 50.7 34.3 14.5 2.0 26,246 47.6 33.3 12.9 1.5 31,112 53.1 35.7 15.2 2.2 11,450 54.9 35.8 16.2 3.0 15,671 52.2 35.0 15.3 2.0 3,974 50.4 34.6 14.3 1.5 48,543 60.2 38.9 18.6 2.7 25,620 50.3 34.5 14.1 1.7 37,107 41.9 30.1 10.7 1.1 16,034 Contd… 250 Figure 7.1 Anaemia Among Women 52 35 15 2 0 10 20 30 40 50 60 Any Anaemia Mild Anaemia Moderate Anaemia Severe Anaemia P e rc e n t NFHS-2, India, 1998–99 Table 7.6 Anaemia among women (contd.) Percentage of ever-married women classified as having iron-deficiency anaemia by degree of anaemia, according to selected background characteristics, India, 1998–99 Percentage of women with: Background characteristic Percentage of women with any anaemia Mild anaemia Moderate anaemia Severe anaemia Number of women Pregnancy/breastfeeding status Pregnant Breastfeeding (not pregnant) Nonpregnant/non-breastfeeding Height < 145 cm ≥ 145 cm Body mass index < 18.5 kg/m2 ≥ 18.5 kg/m2 Fruit and vegetable consumption1 Fruit and vegetables Fruit only Vegetables only Neither Total 49.7 21.8 25.4 2.5 5,654 56.4 38.9 15.8 1.6 19,054 50.4 35.1 13.4 1.9 54,954 56.2 36.5 17.2 2.5 10,515 51.1 34.8 14.5 1.8 68,987 56.8 37.0 17.1 2.7 27,743 49.1 34.0 13.7 1.5 51,336 46.7 32.2 12.9 1.7 23,740 42.9 30.9 10.9 1.2 2,554 55.1 36.9 16.1 2.0 44,207 51.5 34.7 14.7 2.0 9,142 51.8 35.0 14.8 1.9 79,663 Note: The haemoglobin levels are adjusted for altitude of the enumeration area and for smoking when calculating the degree of anaemia. Total includes 10, 65, 741, 26, 902, 161, 584, and 20 women with missing information on education, religion, caste/tribe, work status, the standard of living index, height, body mass index, and fruit and vegetable consumption, respectively, who are not shown separately. 1Based on consumption at least weekly. Vegetables include only green, leafy vegetables. 251 Shorter women and women with a low body mass index have a somewhat higher prevalence of anaemia than other women. The diet of women also plays a role in the likelihood that they have anaemia. Consumption of iron-rich foods can reduce the prevalence or severity of anaemia, and the absorption of iron from the diet can be enhanced (for example, by vitamin C) or inhibited (for example, by tea or coffee) if particular items are consumed around the time that a meal is eaten. Women who eat fruit at least once a week are less likely to be anaemic than women who eat fruit less often or not at all. The consumption of green, leafy vegetables, however, does not appear to have any protective effect against anaemia. In fact, women who regularly consume green, leafy vegetables, but not fruit, have the highest prevalence of anaemia (55 percent). Levels of anaemia are substantial in every state in India (Table 7.7). The lowest prevalence of anaemia is found in Kerala (23 percent), Manipur (29 percent), Goa (36 percent), and Nagaland (38 percent). The majority of women are anaemic in 10 states, and anaemia is particularly pronounced in the Eastern Region and in many of the states in the Northeastern Region. More than one-quarter of women suffer from moderate to severe anaemia in Meghalaya and Assam. In interpreting state differentials in anaemia, it is important to note that anaemia has multiple causes in addition to the low intake of iron-rich foods. These include the low dietary intake of enhancers of iron absorption, the presence in the diet of inhibitors of iron absorption, overcooking of food, and parasitic infestations. More research is needed on these and other factors to better understand the underlying causes of high anaemia levels and the differentials across states and population subgroups. 7.4 Infant Feeding Practices Infant feeding practices have significant effects on both mothers and children. Mothers are affected through the influence of breastfeeding on the period of postpartum infertility, and hence on fertility levels and the length of birth intervals. These effects vary by both the duration and intensity of breastfeeding. Proper infant feeding, starting from the time of birth, is important for the physical and mental development of the child. Breastfeeding improves the nutritional status of young children and reduces morbidity and mortality. Breast milk not only provides important nutrients but also protects the child against infection. The timing and type of supplementary foods introduced in an infant’s diet also have significant effects on the child’s nutritional status. The Baby Friendly Hospitals Initiative, launched by the United Nations Children’s Fund (UNICEF), recommends initiation of breastfeeding immediately after childbirth. The World Health Organization (WHO) and UNICEF recommend that infants should be given only breast milk for about the first six months of their life. Under the Reproductive and Child Health Programme, the Government of India recommends that infants should be exclusively breastfed from birth to age four months (Ministry of Health and Family Welfare, n.d.). Most babies do not require any other foods or liquids during this period. By age seven months, adequate and appropriate complementary foods should be added to the infant’s diet in order to provide sufficient nutrients for optimal growth. It is recommended that breastfeeding should continue, along with complementary foods, through the second year of life or beyond. It is further recommended that a feeding bottle with a nipple should not be used at any age, for reasons related mainly to sanitation and the prevention of infections. 252 WHO has suggested several indicators of breastfeeding practices to guide countries in gathering information for measuring and evaluating infant feeding practices. These indicators include the ever breastfed rate, the exclusive breastfeeding rate, the timely complementary feeding rate, the continued breastfeeding rate, and the bottle feeding rate. The exclusive breastfeeding rate is defined as the proportion of infants under age four months who receive only breast milk. The timely complementary feeding rate is the proportion of infants age 6–9 months who receive both breast milk and solid or semi-solid food. The continued breastfeeding rate through one year of age is the proportion of children age 12–15 months who are still breastfed. The continued breastfeeding rate until two years of age is the proportion of children age 20–23 months who are still breastfed. The bottle feeding rate is the proportion of infants who are fed using a bottle with a nipple. These indicators of breastfeeding and other feeding practices are presented in this section. Table 7.7 Anaemia among women by state Percentage of ever-married women classified as having iron-deficiency anaemia by degree of anaemia, according to state, India, 1998–99 Percentage of women with: State Percentage of women with any anaemia Mild anaemia Moderate anaemia Severe anaemia India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 51.8 35.0 14.8 1.9 40.5 29.6 9.6 1.3 47.0 30.9 14.5 1.6 40.5 31.4 8.4 0.7 58.7 39.3 17.6 1.9 41.4 28.4 12.3 0.7 48.5 32.3 14.1 2.1 54.3 37.6 15.6 1.0 48.7 33.5 13.7 1.5 63.4 42.9 19.0 1.5 63.0 45.1 16.4 1.6 62.7 45.3 15.9 1.5 62.5 50.6 11.3 0.6 69.7 43.2 25.6 0.9 28.9 21.7 6.3 0.8 63.3 33.4 27.5 2.4 48.0 35.2 12.1 0.7 38.4 27.8 9.6 1.0 61.1 37.3 21.4 2.4 36.4 27.3 8.1 1.0 46.3 29.5 14.4 2.5 48.5 31.5 14.1 2.9 49.8 32.5 14.9 2.4 42.4 26.7 13.4 2.3 22.7 19.5 2.7 0.5 56.5 36.7 15.9 3.9 Note: The haemoglobin levels are adjusted for altitude of the enumeration area and for smoking when calculating the degree of anaemia. 253 In NFHS-2, data on breastfeeding and complementary feeding were obtained from a series of questions in the Woman’s Questionnaire. These questions pertain to births since January of the third calendar year before the survey, but the tables are restricted to children born in the three years preceding the survey. For any given woman, information was obtained for a maximum of two births. Initiation of breastfeeding immediately after childbirth is important because it benefits both the mother and the infant. As soon as the infant starts suckling at the breast, the hormone oxytocin is released, resulting in uterine contractions that facilitate expulsion of the placenta and reduce the risk of postpartum haemorrhage. It is also recommended that the first breast milk (colostrum) should be given to the child rather than squeezed from the breast and discarded, because it provides natural immunity to the child. Table 7.8 shows the percentage of children born during the three years before the survey who started breastfeeding within one hour and one day of birth. It also gives the percentage of children whose mothers squeezed the first milk from the breast before breastfeeding, which is not the recommended practice. Although breastfeeding is nearly universal in India, very few children are put to the breast immediately after birth. Only 16 percent of children began breastfeeding within one hour of birth, and only 37 percent began breastfeeding within one day. Nearly two-thirds of women (63 percent) squeezed the first milk from the breast before they began breastfeeding. Differentials in the early initiation of breastfeeding and in squeezing the first milk from the breast are also shown in Table 7.8. With the exception of women in the ‘other religion’ category, no more than 30 percent of children in any group were put to the breast within one hour of birth. Between one-quarter and two-thirds of children were first breastfed in the first day of their life. The early initiation of breastfeeding is relatively high for urban women, women with at least a middle school education, women from several religious groups (Christian, Jain, Buddhist, ‘other’, and none), women from scheduled tribes, and women from households with a high standard of living. The circumstances surrounding delivery of the baby can have an important effect on the early initiation of breastfeeding. Children whose delivery was assisted by a health professional, as well as children born in health facilities, tend to initiate breastfeeding relatively early. Mizoram and Tamil Nadu are the only states in which a majority of children were breastfed within one hour of birth (Table 7.9). Less than 10 percent of children were breastfed within one hour of birth in Rajasthan, Punjab, Bihar, Uttar Pradesh, and Madhya Pradesh. In those five states plus Haryana, only one-third of children or less were first put to the breast within one day of birth. The custom of squeezing the first milk from the breast before breastfeeding a child is widely practised in India, but it is more common in rural areas and for children whose mothers are illiterate, scheduled-tribe children, Sikhs and those with no religion, children whose mothers work on the family farm or in a family business, children living in households with a low to medium standard of living, children born at home, and children born without the assistance of a health professional. It should be stressed, however, that contrary to recommendations for feeding infants, mothers squeeze the first milk from the breast before breastfeeding for a majority of children in all groups. In 20 of the 25 states, the mothers of most children squeeze the first milk from the breast before breastfeeding (Table 7.9). The only exceptions are Tamil Nadu, Manipur, Bihar, Goa, and Arunachal Pradesh. 254 Table 7.8 Initiation of breastfeeding Percentage of children born during the three years preceding the survey who started breastfeeding within one hour and within one day of birth and percentage whose mother squeezed the first milk from her breast before breastfeeding by selected background characteristics, India, 1998–99 Background characteristic Percentage started breastfeeding within one hour of birth Percentage started breastfeeding within one day of birth1 Percentage whose mother squeezed first milk from breast Number of children Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Mother’s work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living index Low Medium High Assistance during delivery Health professional2 Dai (TBA) Other Place of delivery Public health facility NGO or trust hospital/clinic Private health facility Own home Parents’ home Other Total 19.2 45.0 58.8 7,191 14.8 34.8 64.0 25,202 12.7 29.9 66.6 19,061 18.3 43.5 62.0 5,818 21.3 48.2 56.7 2,935 22.2 51.6 52.4 4,574 15.0 36.0 62.5 25,650 17.4 37.6 64.4 5,120 29.4 65.8 50.2 753 8.7 23.6 83.4 450 17.4 47.3 57.2 76 29.6 59.1 66.4 199 41.2 66.2 54.4 87 27.6 65.7 75.7 24 15.3 34.5 64.3 6,478 19.7 45.6 67.8 3,080 15.9 36.7 56.6 10,404 15.3 37.2 65.7 12,050 12.7 32.8 67.8 4,198 17.9 38.5 63.1 4,792 15.1 42.1 61.9 1,099 16.0 37.3 61.9 22,295 15.1 34.1 63.9 11,804 15.8 37.4 63.4 15,080 16.8 42.7 58.5 5,112 21.5 49.4 55.4 13,715 11.0 27.9 65.7 11,323 12.8 28.6 73.3 7,252 27.1 59.0 55.6 5,247 16.0 52.1 55.5 234 20.7 48.1 50.6 5,409 12.2 28.7 68.6 17,224 10.9 29.8 66.3 3,945 8.6 32.4 66.0 225 15.8 37.1 62.8 32,393 Note: Table includes only the two most recent births during the three years preceding the survey, whether living or dead at the time of interview. Total includes 5, 33, 380, 9, 397, 103, and 108 children with missing information on mother’s education, religion, caste/tribe, mother’s work status, the standard of living index, assistance during delivery, and place of delivery, respectively, who are not shown separately. TBA: Traditional birth attendant; NGO: Nongovernmental organization 1Includes children who started breastfeeding within one hour of birth 2Includes doctor, auxiliary nurse midwife, nurse, midwife, lady health visitor, and other health professionals 255 Mothers of children born in the three years before the survey were asked if the child had been given plain water, other liquids, or solid or mushy (semi-solid) food at any time during the day or night before the interview. Results are shown in Tables 7.10 and 7.11. Children who received nothing but breast milk during that period are defined as being exclusively breastfed. The introduction of supplementary foods before four months of age may put infants at risk of malnutrition because other liquids and solid foods are nutritionally inferior to breast milk. Consumption of liquids and solid or mushy foods at an early age also increases children’s exposure to pathogens and consequently puts them at a greater risk of getting diarrhoea. However, a recent study based on findings from NFHS-1 (Anandaiah and Choe, 2000) concluded that breastfeeding with supplements is more beneficial than exclusive breastfeeding Table 7.9 Initiation of breastfeeding by state Percentage of children born during the three years preceding the survey who started breastfeeding within one hour and within one day of birth and percentage whose mother squeezed the first milk from her breast before breastfeeding by state, India, 1998–99 State Percentage started breastfeeding within one hour of birth Percentage started breastfeeding within one day of birth1 Percentage whose mother squeezed first milk from breast India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 15.8 37.1 62.8 23.8 51.2 59.9 11.7 31.1 76.5 20.7 42.3 86.2 20.8 59.2 77.1 6.1 19.5 87.3 4.8 33.6 69.1 9.9 29.3 71.1 6.5 13.4 75.6 6.2 20.7 42.1 24.9 63.2 58.1 25.0 50.6 76.3 49.0 77.1 49.5 44.7 77.6 64.1 27.0 47.5 39.9 26.7 71.6 66.9 54.0 78.2 60.7 24.5 70.2 59.8 31.4 73.4 74.5 34.4 61.8 47.4 10.1 36.6 61.1 22.8 47.7 66.4 10.3 37.3 52.4 18.5 41.5 61.4 42.9 92.0 52.8 50.3 78.7 21.5 Note: Table includes only the two most recent births during the three years preceding the survey, whether living or dead at the time of interview. 1Includes children who started breastfeeding within one hour of birth 256 even for children at very young ages (less than four months). That report suggests that mothers who are not well nourished and who are in poor health themselves may not be able to provide adequate breast milk for their infants. In India, only 55 percent of children under four months of age are exclusively breastfed, 23 percent receive breast milk plus water, and 20 percent receive supplements along with breast milk (Table 7.10). The percentage of infants exclusively breastfed drops steadily from 72 percent for children under one month of age to 6 percent for children who are nine months old. Very few older children are exclusively breastfed. The proportion of children receiving breast milk and Table 7.10 Breastfeeding status by child’s age Percent distribution of children under age 3 years by breastfeeding status, according to child’s age in months, India, 1998–99 Breastfeeding status Breastfeeding and: Age in months Not breastfeeding Exclusively breastfeeding Receiving plain water only Receiving supplements Don’t know if fed supplements Total percent Number of living children < 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 < 4 months 4–6 months 7–9 months 3.7 72.0 14.4 9.9 0.0 100.0 452 1.2 61.0 21.1 16.7 0.0 100.0 973 2.2 54.2 23.3 20.3 0.0 100.0 1,087 1.7 43.3 27.5 27.5 0.0 100.0 1,023 1.6 37.0 25.9 35.4 0.0 100.0 986 2.2 25.3 28.8 43.6 0.2 100.0 1,006 2.9 19.4 28.2 49.4 0.0 100.0 968 3.9 13.1 24.8 57.9 0.2 100.0 922 4.8 10.0 19.1 66.0 0.2 100.0 821 6.5 6.3 20.0 67.2 0.0 100.0 791 6.1 6.3 15.7 71.4 0.5 100.0 719 6.6 3.4 12.6 77.3 0.1 100.0 681 7.7 2.7 8.8 80.8 0.0 100.0 797 10.3 2.3 9.9 77.4 0.1 100.0 961 13.3 1.6 6.8 77.7 0.6 100.0 1,008 12.5 1.4 6.4 79.8 0.0 100.0 960 13.6 1.6 6.4 78.0 0.3 100.0 1,006 15.6 0.9 4.2 79.0 0.3 100.0 939 21.2 0.7 5.0 73.1 0.0 100.0 906 23.2 0.6 5.1 70.9 0.1 100.0 741 30.1 0.7 3.5 65.1 0.6 100.0 706 28.9 1.1 4.6 65.3 0.0 100.0 717 32.2 0.5 4.4 62.9 0.0 100.0 682 33.6 0.2 4.9 60.8 0.4 100.0 652 41.0 0.3 2.6 55.8 0.2 100.0 699 47.8 0.3 3.4 48.3 0.3 100.0 886 47.4 0.3 1.8 50.3 0.3 100.0 903 51.6 0.0 1.5 46.5 0.4 100.0 920 54.0 0.1 0.9 44.5 0.4 100.0 869 58.4 0.1 0.5 40.8 0.2 100.0 935 55.6 0.1 1.7 42.6 0.0 100.0 934 57.5 0.2 0.8 41.5 0.0 100.0 827 63.5 0.2 0.1 36.2 0.0 100.0 714 61.4 0.0 0.7 37.8 0.2 100.0 679 62.7 0.1 1.1 35.9 0.2 100.0 741 60.2 0.1 2.0 37.4 0.3 100.0 706 2.0 55.2 22.8 20.0 0.0 100.0 3,535 2.2 27.3 27.6 42.8 0.1 100.0 2,959 5.0 10.0 21.4 63.4 0.1 100.0 2,534 Note: Table includes only surviving children from among the two most recent births during the three years preceding the survey. Breastfeeding status refers to the day or night before the interview. Children classified as ‘breastfeeding and receiving plain water only’ receive no supplements. 257 supplements increases from 10 percent for children in the first month of life to 81 percent for children age 12 months, and declines thereafter as children are weaned from the breast and their food consumption no longer supplements breast milk. However, breastfeeding generally continues for a long period. Ninety-two percent of children are still being breastfed at 12 months of age, as are 59 percent of children at 24 months of age. For the majority of children in India, breastfeeding usually stops at about 26–27 months of age, but 40 percent of children are still breastfed at age 35 months. Table 7.11 and Figure 7.2 show in more detail the types of food consumed by children under age three years the day or night before the interview. Because of the small number of non- breastfeeding children, one-month age categories have been combined into two-month groups for the youngest children. Powdered milk is rarely given to young children at any age, but other milk (such as cow’s milk or buffalo’s milk) is given to young children more often. Except for children under two months of age, more than 60 percent of non-breastfeeding children in each age group were given these other types of milk the day or night before the interview. About one-third to one-half of breastfeeding children age 6–35 months received non-powdered milk in addition to breast milk. For all children under age three years, milk is given more often than other liquids, although the differences are not large for children once they become two years old. The consumption of green, leafy vegetables generally increases with age, from less than 3 percent for children age 6 months or less to 50 percent or more at age 24–35 months. The consumption of fruits is negligible for children less than six months old, but it increases rapidly thereafter, reaching a plateau of about one-third of children age 18–35 months. Even among non- breastfeeding children, the majority did not eat any fruit the day or night before the interview. From about six months of age, the introduction of complementary food is critical for meeting the protein, energy, and micronutrient needs of children. However, in India the introduction of complementary food is delayed for a substantial proportion of children. Only 24 percent of breastfeeding children who are 6 months old consume solid or mushy foods. This proportion rises to only 46 percent at 9 months of age. Even at 12 months of age, more than one- quarter of breastfeeding children did not eat any solid or mushy food the day or night before the interview. Only 35 percent of breastfeeding children age 6–9 months receive solid or mushy food, as recommended. Bottle feeding has a direct effect on the mother’s exposure to the risk of pregnancy because the period of amenorrhoea may be shortened when breastfeeding is reduced or replaced by bottle feeding. Because it is often difficult to sterilize the nipple properly, the use of bottles with nipples also exposes children to an increased risk of getting diarrhoea and other diseases. For children who are being breastfed, the use of bottles with nipples is not common in India. In every age group, less than 18 percent of breastfeeding children drank anything from a bottle with a nipple during the day or night before the interview (Table 7.11). The use of a bottle with a nipple is much more common for children who are not being breastfed, particularly during the first year of life. 258 Table 7.11 Type of food received by children Percentage of children under age 3 years who received specific types of food the day or night before the interview and percentage using a bottle with a nipple by current breastfeeding status and child’s age in months, India, 1998–99 Type of food received Age in months Powdered milk Any other milk Any other liquid Green, leafy vegetables Fruits Any solid or mushy food1 Using bottle with a nipple Number of living children BREASTFEEDING CHILDREN < 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 < 4 months 4–5 months 6–9 months 1.3 6.5 3.1 0.7 0.9 1.4 3.7 436 2.0 13.1 3.9 0.5 1.1 2.2 7.5 962 3.6 14.4 4.1 0.5 0.4 1.9 9.8 1,063 6.0 18.9 6.1 0.5 0.7 3.7 15.4 1,005 5.1 22.9 8.1 1.1 3.2 10.7 14.5 970 7.6 28.9 12.7 1.4 2.7 14.8 16.8 984 4.6 32.5 17.7 2.2 6.9 23.6 16.2 940 6.3 36.2 20.6 4.9 9.7 30.9 14.8 886 8.0 41.5 26.8 10.8 13.5 43.6 17.7 782 6.1 43.0 28.1 10.4 13.8 45.5 15.7 739 4.4 42.8 32.6 13.8 17.2 57.3 16.3 675 8.0 45.1 35.2 18.7 20.9 64.8 14.4 636 3.9 50.0 39.5 25.8 24.2 71.1 14.3 735 5.1 43.9 42.0 26.1 20.9 72.1 11.4 862 3.6 48.7 41.6 29.0 20.2 77.4 11.6 874 5.3 49.8 43.6 33.7 26.4 81.7 9.7 841 3.6 47.9 44.3 35.6 23.7 76.6 11.2 869 3.2 50.6 48.1 37.8 26.9 84.1 8.8 792 6.1 52.1 48.2 38.9 27.7 82.2 9.1 714 2.6 51.5 46.6 36.8 26.6 80.7 8.4 570 5.0 53.3 46.2 37.2 32.4 85.4 12.4 494 2.9 47.7 51.7 40.2 26.3 79.7 6.4 510 3.4 49.2 48.0 37.4 30.5 83.8 8.5 462 3.8 42.2 43.9 38.7 27.6 81.8 7.8 433 5.2 48.5 50.7 47.1 27.4 87.9 5.7 412 4.1 42.8 45.9 45.0 27.0 86.9 6.1 463 5.2 50.5 49.3 51.3 24.3 89.4 7.0 475 3.1 52.2 50.4 52.4 30.1 88.9 4.8 446 5.3 56.2 55.1 51.3 25.7 90.8 7.1 399 3.2 56.3 53.7 53.6 22.9 90.6 8.7 389 3.9 53.4 54.1 52.6 29.8 90.3 6.0 415 5.8 47.5 53.0 57.6 30.9 91.3 6.9 352 2.5 51.2 58.1 51.2 27.7 91.0 7.2 261 3.6 46.2 61.2 53.9 30.6 92.4 8.0 262 4.8 42.1 45.0 56.5 27.2 91.0 4.9 276 1.7 46.1 54.1 49.1 27.0 87.6 6.7 281 3.6 14.4 4.5 0.6 0.7 2.5 10.0 3,466 6.4 25.9 10.4 1.3 2.9 12.8 15.6 1,953 6.2 37.9 22.9 6.8 10.7 35.0 16.1 3,346 259 Table 7.11 Type of food received by children (contd.) Percentage of children under age 3 years who received specific types of food the day or night before the interview and percentage using a bottle with a nipple by current breastfeeding status and child’s age in months, India, 1998–99 Type of food received Age in months Powdered milk Any other milk Any other liquid Green, leafy vegetables Fruits Any solid or mushy food1 Using bottle with a nipple Number of living children NON-BREASTFEEDING CHILDREN < 2 2–3 4–5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 < 4 months 4–5 months 6–9 months (13.0) (42.3) (6.1) (4.7) (0.1) (5.2) (40.0) 28 (22.4) (62.2) (12.8) (0.0) (0.0) (11.7) (87.0) 41 (46.6) (70.2) (32.9) (8.0) (8.6) (30.5) (86.6) 38 (15.7) (89.9) (44.7) (18.0) (17.4) (41.1) (58.4) 28 (26.6) (69.7) (36.5) (14.8) (18.8) (49.1) (75.3) 36 (30.2) (83.5) (29.8) (11.5) (21.7) (64.4) (91.5) 39 38.6 66.8 45.2 15.8 21.2 59.4 81.1 52 32.9 77.9 34.3 16.1 23.8 75.9 85.6 44 27.7 72.3 35.4 26.8 35.5 81.0 71.5 45 4.2 93.4 51.9 24.9 47.5 78.2 54.4 61 14.2 80.8 55.1 42.0 39.2 88.2 55.0 99 11.7 90.4 53.8 42.7 33.8 86.1 52.4 134 8.3 85.1 53.4 45.1 46.0 90.7 37.2 120 11.3 78.7 55.1 46.5 37.5 87.3 45.4 137 9.8 85.0 56.7 45.0 46.0 92.3 37.6 147 11.0 74.8 55.9 37.9 46.0 89.9 25.3 192 3.0 78.9 57.1 51.0 54.4 93.1 28.0 172 4.6 72.3 53.0 40.9 35.1 85.8 26.6 212 6.8 71.7 61.5 46.8 41.5 89.9 20.9 208 6.6 74.4 50.2 46.1 59.5 91.3 22.0 219 8.1 74.2 56.0 52.6 54.0 92.3 25.6 219 3.7 73.1 58.6 53.8 42.2 92.9 22.0 286 5.1 67.9 63.7 58.0 35.8 93.7 14.6 423 4.9 68.6 61.6 55.2 44.6 93.8 13.7 428 5.0 65.2 61.2 51.8 34.2 90.5 15.9 475 2.3 66.9 62.0 57.3 37.8 94.7 12.8 469 3.6 69.7 61.0 57.2 41.2 92.4 15.2 547 3.9 67.4 66.8 55.1 39.7 91.9 15.6 519 2.8 70.0 61.2 55.9 40.9 92.9 9.8 475 4.1 69.5 60.8 56.7 38.0 91.4 13.3 454 5.2 64.5 60.3 57.9 41.7 93.2 12.8 417 4.1 60.6 62.1 57.3 42.3 93.9 11.2 464 4.8 64.9 58.3 60.0 42.8 95.8 9.2 425 18.6 54.1 10.1 1.9 0.0 9.0 67.9 69 (46.6) (70.2) (32.9) (8.0) (8.6) (30.5) (86.6) 38 29.5 75.9 39.2 14.9 20.1 54.9 78.3 155 260 Table 7.11 Type of food received by children (contd.) Percentage of children under age 3 years who received specific types of food the day or night before the interview and percentage using a bottle with a nipple by current breastfeeding status and child’s age in months, India, 1998–99 Type of food received Age in months Powdered milk Any other milk Any other liquid Green, leafy vegetables Fruits Any solid or mushy food1 Using bottle with a nipple Number of living children ALL CHILDREN < 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 < 4 months 4–5 months 6–9 months 1.5 7.5 3.4 0.8 0.9 1.5 4.2 452 2.3 13.6 3.8 0.6 1.0 2.3 8.3 973 4.0 15.4 4.2 0.5 0.4 2.2 11.3 1,087 6.3 19.7 6.3 0.5 0.7 3.8 16.8 1,023 6.1 23.7 8.2 1.1 3.3 11.0 15.8 986 8.2 29.8 13.4 1.6 2.8 15.2 18.2 1,006 4.9 34.1 18.5 2.7 7.2 24.1 17.4 968 7.1 37.5 21.2 5.3 10.1 31.6 17.2 922 9.0 43.5 27.0 10.8 13.9 44.5 21.2 821 8.2 44.6 29.3 10.7 14.3 46.4 20.0 791 6.2 45.0 32.7 13.9 17.6 58.4 20.5 719 9.3 46.9 35.2 19.2 21.9 65.9 18.1 681 3.9 53.3 40.5 25.7 26.0 71.6 17.4 797 6.1 47.7 43.4 27.7 22.8 73.8 15.9 961 4.7 54.2 43.2 30.8 22.0 78.6 17.0 1,008 5.7 54.2 44.8 35.1 28.8 82.8 13.1 960 4.7 52.1 45.8 37.1 25.6 78.0 15.8 1,006 4.2 56.0 49.5 38.9 29.9 85.4 13.3 939 7.1 56.9 49.8 38.7 31.6 83.8 12.6 906 2.7 57.9 49.1 40.1 33.1 83.5 13.0 741 4.9 59.0 48.3 38.3 33.2 85.6 16.6 706 4.0 54.6 54.5 42.1 30.7 82.7 10.6 717 4.4 57.3 48.7 40.2 39.8 86.2 12.9 682 5.2 52.9 48.0 43.4 36.5 85.3 13.8 652 4.6 58.6 54.0 49.8 33.4 89.9 12.4 699 4.6 54.8 54.4 51.2 31.2 90.1 10.1 886 5.1 59.1 55.1 53.1 33.9 91.5 10.1 903 4.1 58.9 56.0 52.1 32.2 89.7 10.5 920 3.7 62.0 58.8 54.5 32.3 92.9 10.2 869 3.4 64.1 58.0 55.7 33.6 91.7 12.5 935 3.9 61.2 61.1 54.0 35.3 91.2 11.3 934 4.0 60.5 57.7 56.7 36.7 92.2 8.6 827 3.5 62.9 59.8 54.7 34.2 91.2 11.1 714 4.6 57.4 60.6 56.3 37.4 92.9 11.0 679 4.4 53.7 55.8 57.0 36.7 92.8 8.8 741 3.6 57.4 56.6 55.6 36.5 92.5 8.2 706 3.9 15.2 4.6 0.6 0.7 2.6 11.2 3,535 7.1 26.8 10.8 1.4 3.0 13.1 17.0 1,991 7.2 39.6 23.6 7.1 11.1 35.9 18.8 3,501 Note: Table includes only surviving children from among the two most recent births during the three years preceding the survey. Percents by type of food may sum to more than 100.0 because children may have received more than one type of food. ( ) Based on 25–49 unweighted cases 1Includes green, leafy vegetables and fruits 261 Table 7.12 shows several statistics that describe the duration of breastfeeding. Estimates of both means and medians are based on the current proportions of children breastfeeding in each age group because information on current status is usually more accurate than information based on mother’s recall. The median length of any breastfeeding is slightly more than two years (25.4 months). Supplementation begins relatively early, however. The median length of exclusive breastfeeding is 1.9 months and the median length of exclusive breastfeeding or breastfeeding with water only is 5.3 months. The mean durations of any breastfeeding, exclusive breastfeeding, and exclusive breastfeeding or breastfeeding with water only are 25.2 months, 4.0 months, and 7.2 months, respectively. The mean durations are slightly longer than the median durations for the last two measures, but are about the same for the overall duration of breastfeeding. An alternative measure of the duration of breastfeeding is the prevalence-incidence mean, which is calculated as the ‘prevalence’ of breastfeeding divided by its ‘incidence’. In this case, prevalence is defined as the number of children whose mothers were breastfeeding at the time of the survey, and incidence is defined as the average number of births per month (averaged over a 36–month period to overcome problems of seasonality of births and possible reference-period errors). For each measure of breastfeeding, the prevalence-incidence mean is about the same as the mean calculated in the conventional manner. Figure 7.2 Percentage of Breastfeeding Children Given Milk, Other Liquid, or Solid/Mushy Food the Day or Night Before the Interview 0 20 40 60 80 100 0 3 6 9 12 15 18 21 24 27 30 33 Age (months) Milk Other liquid Solid/Mushy food NFHS-2, India, 1998–99 262 Table 7.12 Median duration of breastfeeding Median duration of breastfeeding among children under age 3 years by selected background characteristics, and mean duration of breastfeeding, India, 1998–99 Median duration (months)1 Background characteristic Any breastfeeding Exclusive breastfeeding Exclusive breastfeeding or breastfeeding plus water only Number of children Sex of child Male Female Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Mother’s work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living index Low Medium High Place of delivery Public health facility NGO or trust hospital/clinic Private health facility Own home Parents’ home Other Median duration Mean duration (months)1 Prevalence/incidence mean 26.4 1.8 5.2 16,805 24.6 2.0 5.5 15,588 21.8 0.9 3.7 7,191 26.3 2.2 5.7 25,202 27.1 2.4 6.6 19,061 24.2 1.5 4.4 5,818 23.7 0.7 3.8 2,935 21.4 1.3 3.2 4,574 25.8 2.0 5.5 25,650 24.5 1.8 5.1 5,120 23.1 1.6 3.1 753 21.7 0.6 4.2 450 16.9 1.0 2.4 76 25.6 2.5 4.7 199 27.1 5.7 8.6 87 ≥ 36.0 0.4 0.5 24 26.4 2.2 5.9 6,478 27.7 3.1 7.3 3,080 24.3 2.1 5.6 10,404 24.8 1.3 4.2 12,050 26.8 2.4 6.1 4,198 28.2 2.5 6.0 4,792 ≥ 36.0 2.2 4.5 1,099 24.7 1.7 5.1 22,295 28.5 2.5 6.6 11,804 24.8 1.9 5.2 15,080 22.0 0.8 3.3 5,112 23.9 1.2 3.6 5,247 23.2 1.8 5.0 234 21.3 1.6 3.8 5,409 27.3 2.2 6.3 17,224 25.3 2.4 6.2 3,945 27.6 2.5 3.5 225 25.4 1.9 5.3 32,393 25.2 4.0 7.2 32,393 24.8 3.5 6.9 32,393 Note: Table includes only the two most recent births during the three years preceding the survey. Total includes 5, 33, 380, 9, 397, and 108 children with missing information on mother’s education, religion, caste/tribe, mother’s work status, the standard of living index, and place of delivery, respectively, who are not shown separately. The median duration of any breastfeeding is shown as ≥ 36 months for groups in which the exact median cannot be calculated because the proportion of breastfeeding children does not drop below 50 percent in any age group for children under 36 months of age. NGO: Nongovernmental organization 1Based on current status 263 The median duration of breastfeeding is two months shorter for girls than for boys. This pattern is often observed in societies where there is a strong preference for sons, since the parents may stop breastfeeding a girl at a younger age to increase their chances of having another child earlier (with the hope that the next child will be a boy). The median length of breastfeeding is five months longer in rural areas than in urban areas. Most children living in rural areas are breastfed for more than two years. Children in urban areas are exclusively breastfed for a very short median period of less than one month. The median duration of breastfeeding decreases steadily with increasing educational attainment and increasing standard of living. The duration of breastfeeding is particularly short for Jains and particularly long for children in the ‘no religion’ category, but both of these estimates are based on a small number of children. Working women breastfeed their children for a longer time than women who do not work, a pattern that was also observed in NFHS-1. Children who are born at home tend to be breastfed for several more months than children who are born in health facilities. The median duration of breastfeeding is at least 20 months in every state except Tamil Nadu, where it is only 16 months (Table 7.13). There are five states (mostly in the Eastern Region), where the exact median duration of breastfeeding cannot be calculated because the proportion of breastfeeding children does not drop below 50 percent in any age group for children under 36 months of age. In these states, the median duration of breastfeeding is 36 months or longer. Andhra Pradesh is the only state where the median duration of exclusive breastfeeding is more than four months. The median duration of exclusive breastfeeding or breastfeeding plus water only is eight months or less in every state. The recommended feeding indicators for young children are summarized for every state in Table 7.14. Just over half of children in India (55 percent) are exclusively breastfed for the recommended period of four months. This percentage varies widely from less than 20 percent in Delhi, Meghalaya, Sikkim, and Himachal Pradesh to 75 percent in Andhra Pradesh. As noted earlier, the introduction of solid or mushy food in addition to breast milk is much later than recommended for the majority of children in India. The worst performing states in this respect are Bihar, Uttar Pradesh, and Rajasthan, where less than 20 percent of children receive timely complementary feeding. Children in Kerala and several states in the Northeastern Region are most likely to receive timely complementary feeding. Prolonged breastfeeding is common throughout India, with 89 percent of children still being breastfed at age 12–15 months and 69 percent being breastfed at age 20–23 months. In every state except Tamil Nadu, at least 70 percent of children are breastfed at age 12–15 months and at least 45 percent are breastfed at age 20–23 months. More than 80 percent of children age 20–23 months are breastfed in the contiguous states of Assam, West Bengal, Sikkim, Bihar, and Orissa. Bottle feeding of infants is most common in Goa (63 percent), Delhi (41 percent), and Tamil Nadu (34 percent). These are states that also exhibited unusually high levels of bottle feeding in NFHS-1. 7.5 Nutritional Status of Children Nutritional status is a major determinant of the health and well-being of children. Inadequate or unbalanced diets and chronic illness are associated with poor nutrition among children. To assess their nutritional status, measurements of weight and height/length were obtained for children born in the three years preceding the survey. Children were weighed and measured with the same type of scales and measuring boards used for women. Children under two years of age were 264 measured lying down and older children were measured standing up. Data on weight and height/length were used to calculate the following three summary indices of nutritional status: • weight-for-age • height-for-age • weight-for-height Table 7.13 Median duration of breastfeeding by state Median duration of any, exclusive, and full breastfeeding among children under age 3 years by state, India, 1998–99 Median duration (months)1 State Any breastfeeding Exclusive breastfeeding Exclusive breastfeeding or breastfeeding plus water only India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 25.4 1.9 5.3 22.6 0.5 1.7 24.3 1.2 3.9 24.1 0.6 2.8 29.5 1.5 3.8 21.2 0.7 2.9 25.5 1.8 6.2 ≥ 36.0 2.6 6.6 25.8 2.2 5.7 ≥ 36.0 1.9 7.5 ≥ 36.0 1.8 5.3 ≥ 36.0 1.1 2.9 30.8 0.6 2.3 ≥ 36.0 1.2 3.2 29.3 3.1 3.8 22.6 0.5 0.7 21.8 0.7 4.3 23.1 0.7 3.7 27.3 0.5 0.7 23.3 0.5 0.7 22.0 3.0 5.9 23.8 1.0 5.9 25.0 4.6 5.1 20.0 3.2 5.6 24.5 2.8 3.4 16.1 1.8 3.5 Note: Table includes only the two most recent births during the three years preceding the survey. The median duration of any breastfeeding is shown as ≥ 36 months for states in which the exact median cannot be calculated because the proportion of breastfeeding children does not drop below 50 percent in any age group for children under 36 months of age. 1Based on current status 265 The nutritional status of children calculated according to these three measures is compared with the nutritional status of an international reference population recommended by the World Health Organization (Dibley et al., 1987a; 1987b). The use of this reference population is based on the empirical finding that well-nourished children in all population groups for which data exist follow very similar growth patterns (Martorell and Habicht, 1986). A scientific report from the Nutrition Foundation of India (Agarwal et al., 1991) has concluded that the WHO standard is generally applicable to Indian children. Table 7.14 Recommended feeding indicators by state Recommended feeding indicators for children age 0–23 months by state, India, 1998–99 Recommended feeding indicators State Percentage of children 0–3 months who are exclusively breastfed Percentage of children 6–9 months who receive breast milk and solid/mushy food Percentage of children 12–15 months who are breastfed Percentage of children 20–23 months who are breastfed Percentage of children <12 months who are bottle fed India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 55.2 33.5 88.9 68.9 15.9 13.2 37.0 70.4 59.9 41.0 47.2 41.8 88.3 77.5 15.9 17.5 61.3 73.1 60.2 30.8 41.5 38.9 90.0 69.5 32.3 36.3 38.7 76.0 53.8 30.2 53.7 17.5 91.5 76.3 12.1 64.2 27.3 91.4 73.2 11.4 56.9 17.3 87.9 78.6 16.8 55.2 15.0 95.1 85.1 10.3 58.0 30.1 94.6 89.7 13.8 48.8 46.3 95.8 86.9 21.1 (33.9) (60.2) (94.1) (76.0) 6.6 42.5 58.5 96.1 83.5 12.5 69.7 86.8 90.8 67.9 13.0 16.1 77.1 91.2 63.2 30.9 40.7 (74.2) (89.9) 47.4 18.4 43.9 81.3 83.7 (61.4) 23.1 16.3 87.3 89.6 (82.0) 20.0 * (65.4) (76.0) (56.5) 63.2 65.2 46.5 86.2 56.1 6.3 38.5 30.8 89.0 63.7 14.7 74.6 59.4 84.6 60.6 13.2 66.5 38.4 86.5 44.9 11.4 68.5 72.9 95.5 61.8 20.4 48.3 55.4 69.4 29.0 34.1 Note: Table includes only the two most recent births in the three years preceding the survey. ( ) Based on 25–49 unweighted cases *Percentage not shown; based on fewer than 25 unweighted cases 266 The three indices of nutritional status are expressed in standard deviation units (z-scores) from the median for the international reference population. Children who are more than two standard deviations below the reference median on any of the indices are considered to be undernourished, and children who fall more than three standard deviations below the reference median are considered to be severely undernourished. Each of these indices provides somewhat different information about the nutritional status of children. Weight-for-age is a composite measure that takes into account both chronic and acute undernutrition. Children who are more than two standard deviations below the reference median on this index are considered to be underweight. The height-for-age index measures linear growth retardation. Children who are more than two standard deviations below the median of the reference population in terms of height-for-age are considered short for their age or stunted. The percentage in this category indicates the prevalence of chronic undernutrition, which often results from a failure to receive adequate nutrition over a long period of time or from chronic or recurrent diarrhoea. Height-for-age, therefore, does not vary appreciably by the season in which data are collected. The weight-for-height index examines body mass in relation to body length. Children who are more than two standard deviations below the median of the reference population in terms of weight-for-height are considered too thin or wasted. The percentage in this category Table 7.15 Nutritional status of children by demographic characteristics Percentage of children under age 3 years classified as undernourished on three anthropometric indices of nutritional status, according to selected demographic characteristics, India, 1998–99 Weight-for-age Height-for-age Weight-for-height Demographic characteristic Percentage below –3 SD Percentage below –2 SD1 Percentage below –3 SD Percentage below –2 SD1 Percentage below –3 SD Percentage below –2 SD1 Number of children Age of child < 6 months 6–11 months 12–23 months 24–35 months Sex of child Male Female Birth order 1 2–3 4–5 6+ Previous birth interval2 First birth < 24 months 24–47 months 48+ months Total 2.0 11.9 4.2 15.4 1.9 9.3 4,203 11.8 37.5 11.3 30.9 2.8 13.2 4,116 23.1 58.5 29.8 57.5 4.1 21.9 8,295 24.1 58.4 32.0 56.5 1.9 13.2 7,986 16.9 45.3 21.8 44.1 2.9 15.7 12,822 19.1 48.9 24.4 47.0 2.7 15.2 11,778 13.6 40.9 17.8 39.6 2.8 14.5 7,111 16.3 46.2 21.8 44.4 2.5 15.0 10,893 23.8 52.9 28.5 52.3 3.2 16.8 4,287 28.5 58.6 35.2 56.2 3.3 18.2 2,309 13.6 41.0 17.9 39.7 2.8 14.5 7,144 21.3 52.2 27.9 50.8 3.1 15.8 3,908 19.8 50.0 25.6 48.9 2.5 15.6 9,753 18.0 45.1 21.2 42.4 3.2 16.5 3,794 18.0 47.0 23.0 45.5 2.8 15.5 24,600 Note: Each index is expressed in standard deviation units (SD) from the median of the International Reference Population. 1Includes children who are below –3 SD from the International Reference Population median 2First-born twins (triplets, etc.) are counted as first births because they do not have a previous birth interval. 267 indicates the prevalence of acute undernutrition. Wasting is associated with a failure to receive adequate nutrition in the period immediately before the survey and may be the result of seasonal variations in food supply or recent episodes of illness. The validity of these indices is determined by many factors, including the coverage of the population of children and the accuracy of the anthropometric measurements. The survey was not able to measure the height and weight of all eligible children, usually because the child was not at home at the time of the health investigator’s visit or because the mother refused to allow the child to be weighed and measured. In India, NFHS-2 did not measure 13 percent of children under age three (see Table D.3 in Appendix D). Also excluded from the analysis are children whose month and year of birth were not known and those with grossly improbable height or weight measurements. In addition, two of the three indices (weight-for-age and height-for-age) are sensitive to misreporting of children’s ages, including heaping on preferred digits. Table 7.15 shows the percentage of children classified as undernourished by selected demographic characteristics. Almost half of children under three years of age (47 percent) are underweight, and a similar percentage (46 percent) are stunted. The proportion of children who are severely undernourished is also notable—18 percent according to weight-for-age and 23 percent according to height-for-age. Wasting is also quite evident in India, affecting 16 percent of children under three years of age. The proportion of children under three years of age who are underweight decreased from 52 percent in NFHS-1 to 47 percent in NFHS-2 (Figure 7.3), and the proportion severely underweight decreased from 20 percent to 18 percent. A similar comparison cannot be made at the national level for stunting and wasting because children’s height was not measured in five states in NFHS-1. Figure 7.3 Percentage of Children Under Age 3 Who Are Underweight NFHS-1 and NFHS-2 52 20 47 18 0 10 20 30 40 50 60 Underweight Severely Underweight P e rc e n t NFHS-1 NFHS-2 India 268 The proportion of children who are undernourished increases rapidly with the child’s age through age 12–23 months, where it peaks at 22 percent for wasting and 58–59 percent for the other two measures. Even during the first six months of life, when most babies are breastfed, 9–15 percent of children are undernourished according to the three nutritional indices. It is notable that at age 24–35 months, when most children have been weaned from breast milk, almost one-third of children are severely stunted and almost one-quarter are severely underweight. Overall, girls and boys are about equally undernourished, but girls are slightly more likely than boys to be underweight and stunted, whereas boys are slightly more likely to be wasted. Undernutrition generally increases with increasing birth order. Young children in families with six or more children are nutritionally the most disadvantaged. First births have lower than average levels of undernutrition on almost all the measures, and children born after a short birth interval are more likely than other children to be stunted or underweight. Table 7.16 shows the nutritional status of children by selected background characteristics. Undernutrition is substantially higher in rural areas than in urban areas. Even in urban areas, however, more than one-third of children are underweight or stunted. Children whose mothers are illiterate are about twice as likely to be undernourished as children whose mothers have completed at least high school (see Figure 7.4) and the differentials are even larger in the case of severe undernutrition. Figure 7.4 Percentage of Children Under Age 3 Who Are Stunted by Mother’s Education and SLI 29 45 54 54 41 34 25 0 10 20 30 40 50 60 MOTHER'S EDUCATION Illiterate Literate, < Middle School Complete Middle School Complete High School Complete and Above STANDARD OF LIVING INDEX Low Medium High Percent NFHS-2, India, 1998–99 269 Hindu and Muslim children are equally likely to be undernourished, but Christian, Sikh, and Jain children are considerably better nourished. Children belonging to scheduled castes, scheduled tribes, or other backward classes have relatively high levels of undernutrition according to all three measures. Children from scheduled tribes have the poorest nutritional Table 7.16 Nutritional status of children by background characteristics Percentage of children under age 3 years classified as undernourished on three anthropometric indices of nutritional status, according to selected background characteristics, India, 1998–99 Weight-for-age Height-for-age Weight-for-height Background characteristic Percent- age below –3 SD Percent- age below –2 SD1 Percent- age below –3 SD Percent- age below –2 SD1 Percent- age below –3 SD Percent- age below –2 SD1 Number of children Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Mother’s work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Mother’s height < 145 cm ≥ 145 cm Mother’s body mass index < 18.5 kg/m2 ≥ 18.5 kg/m2 Standard of living index Low Medium High Total 11.6 38.4 15.4 35.6 2.2 13.1 5,757 19.9 49.6 25.4 48.5 3.0 16.2 18,842 24.1 55.0 30.2 54.4 3.4 17.1 13,878 13.1 44.6 18.3 40.7 2.0 15.3 4,634 10.8 36.6 13.4 34.0 2.5 13.3 2,400 5.8 26.6 8.2 25.4 1.6 11.0 3,685 18.4 47.7 23.3 46.0 2.9 16.0 19,572 18.6 48.3 24.8 47.1 2.5 14.1 3,745 9.6 30.8 14.0 30.6 2.5 13.4 582 8.4 26.8 16.0 35.4 1.1 7.0 365 1.3 20.9 0.8 13.2 0.0 11.9 60 7.5 43.7 8.7 32.5 0.9 11.9 168 19.1 49.6 11.2 44.0 0.4 17.7 68 20.1 44.1 26.9 54.4 0.0 5.0 17 21.2 53.5 27.5 51.7 3.0 16.0 4,919 26.0 55.9 27.6 52.8 4.4 21.8 2,236 18.3 47.3 23.1 44.8 3.4 16.6 7,941 13.8 41.1 19.4 40.7 1.8 12.8 9,265 22.9 56.0 29.3 52.8 3.3 17.7 3,134 24.6 55.5 26.9 51.8 3.8 19.6 3,602 21.4 51.7 24.7 47.7 2.8 19.3 838 15.5 43.3 21.0 42.7 2.5 14.0 17,018 28.3 59.8 36.8 60.7 2.9 17.1 3,100 16.5 45.1 21.1 43.3 2.8 15.2 21,458 23.4 57.2 25.9 50.3 3.0 19.6 9,824 14.4 40.2 21.2 42.3 2.7 12.7 14,698 25.3 56.9 29.8 53.7 3.9 19.7 8,548 16.5 46.8 22.4 45.3 2.4 14.3 11,636 6.7 26.8 10.7 28.5 1.5 10.2 4,137 18.0 47.0 23.0 45.5 2.8 15.5 24,600 Note: Each index is expressed in standard deviation units (SD) from the median of the International Reference Population. Total includes 3, 23, 239, 7, 42, 78, and 278 children with missing information on mother’s education, religion, caste/tribe, mother’s work status, mother’s height, mother’s body mass index, and the standard of living index, respectively, who are not shown separately. 1Includes children who are below –3 SD from the International Reference Population median 270 status, and the high prevalence of wasting in this group (22 percent) is of particular concern. Interestingly, undernutrition is relatively low for children whose mothers have not worked in the past 12 months. The nutritional status of children is strongly related to maternal nutritional status. Undernutrition is much more common for children of mothers whose height is less than 145 centimetres or whose body mass index is below 18.5 than for other children. All of the measures of undernutrition are strongly related to the household’s standard of living. Children from households with a low standard of living are twice as likely to be undernourished as children from households with a high standard of living. Table 7.17 Nutritional status of children by state Percentage of children under age 3 years classified as undernourished on three anthropometric indices of nutritional status, according to state, India, 1998–99 Weight-for-age Height-for-age Weight-for-height State Percent- age below –3 SD Percent- age below –2 SD1 Percent- age below –3 SD Percent- age below –2 SD1 Percent- age below –3 SD Percent- age below –2 SD1 India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 18.0 47.0 23.0 45.5 2.8 15.5 10.1 34.7 18.0 36.8 4.1 12.5 10.1 34.6 24.3 50.0 0.8 5.3 12.1 43.6 18.1 41.3 3.3 16.9 8.3 34.5 17.3 38.8 1.2 11.8 8.8 28.7 17.2 39.2 0.8 7.1 20.8 50.6 29.0 52.0 1.9 11.7 24.3 55.1 28.3 51.0 4.3 19.8 21.9 51.7 31.0 55.5 2.1 11.1 25.5 54.4 33.6 53.7 5.5 21.0 20.7 54.4 17.6 44.0 3.9 24.3 16.3 48.7 19.2 41.5 1.6 13.6 7.8 24.3 11.9 26.5 2.0 7.9 13.3 36.0 33.7 50.2 3.3 13.3 5.3 27.5 11.2 31.3 1.8 8.2 11.3 37.9 24.5 44.9 1.0 13.3 5.0 27.7 13.9 34.6 2.8 10.2 7.4 24.1 11.7 33.0 2.4 10.4 4.2 20.6 9.7 31.7 0.8 4.8 4.7 28.6 4.8 18.1 0.7 13.1 16.2 45.1 23.3 43.6 2.4 16.2 17.6 49.6 14.1 39.9 2.5 21.2 10.3 37.7 14.2 38.6 1.6 9.1 16.5 43.9 15.9 36.6 3.9 20.0 4.7 26.9 7.3 21.9 0.7 11.1 10.6 36.7 12.0 29.4 3.8 19.9 Note: Each index is expressed in standard deviation units (SD) from the median of the International Reference Population. 1Includes children who are below –3 SD from the International Reference Population median 271 Inadequate nutrition is a problem throughout India, but the situation is considerably better in some states. Table 7.17 shows that undernutrition is most pronounced in Bihar, Madhya Pradesh, Orissa, Uttar Pradesh, and Rajasthan. In addition, Maharashtra, Karnataka, and Tamil Nadu are all characterized by high levels of wasting among children. Nutritional problems are least evident in Sikkim, Arunachal Pradesh, Goa, and Kerala. Even in these states, however, levels of undernutrition are unacceptably high. 7.6 Anaemia Among Children Anaemia is a serious concern for young children because it can result in impaired cognitive performance, behavioural and motor development, coordination, language development, and scholastic achievement, as well as increased morbidity from infectious diseases (Seshadri, 1997). One of the most vulnerable groups is children age 6–24 months (Stoltzfus and Dreyfuss, 1998). Table 7.18 and Figure 7.5 show anaemia levels for children age 6–35 months. Overall, nearly three-quarters (74 percent) of these children have some level of anaemia4, including 23 percent who are mildly anaemic (10.0–10.9 g/dl), 46 percent who are moderately anaemic (7.0–9.9 g/dl), and 5 percent who are severely anaemic (less than 7.0 g/dl). Notably, a much larger proportion of children than women are anaemic and the difference is particularly pronounced in the case of moderate to severe anaemia. 4If the hemoglobin measurements are not adjusted for the altitude of the enumeration area, the estimated prevalence of anaemia is only slightly lower (73.7 percent instead of 74.3 percent). Figure 7.5 Anaemia Among Children 74 23 46 5 0 20 40 60 80 100 Any Anaemia Mild Anaemia Moderate Anaemia Severe Anaemia P e rc e n t NFHS-2, India, 1998–99 272 Table 7.18 Anaemia among children Percentage of children age 6–35 months classified as having iron-deficiency anaemia by selected background characteristics, India, 1998–99 Percentage of children with: Background characteristic Percentage of children with anaemia Mild anaemia Moderate anaemia Severe anaemia Number of children Age of child 6–11 months 12–23 months 24–35 months Sex of child Male Female Birth order 1 2–3 4–5 6+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Mother’s work status Working in family farm/business Employed by someone else Self-employed Not worked in past 12 months Standard of living index Low Medium High Mother’s anaemia status Not anaemic Mildly anaemic Moderately anaemic Severely anaemic Total 71.7 27.0 41.5 3.2 3,923 77.7 22.0 49.4 6.3 8,215 72.0 21.9 44.5 5.6 7,877 75.1 22.2 47.0 5.9 10,477 73.3 23.7 44.8 4.8 9,539 70.7 23.6 42.5 4.6 5,759 74.9 22.7 46.4 5.8 8,896 76.4 22.7 48.0 5.7 3,459 78.4 22.4 50.3 5.7 1,902 70.8 23.7 42.0 5.1 4,642 75.3 22.7 47.1 5.5 15,374 78.2 21.7 50.0 6.4 11,255 74.6 24.4 45.1 5.1 3,866 69.7 25.2 40.2 4.3 1,959 61.9 24.0 35.1 2.8 2,935 74.6 22.4 46.7 5.5 15,982 74.2 26.0 43.0 5.2 2,952 61.0 23.7 34.1 3.3 500 76.5 18.0 52.8 5.7 304 (69.4) (20.7) (48.7) (0.0) 44 73.3 27.9 41.9 3.5 139 88.9 16.9 57.0 15.0 60 (55.1) (11.9) (40.7) (2.5) 16 78.3 22.0 49.7 6.6 4,048 79.8 22.8 50.1 6.9 1,921 72.0 22.8 44.4 4.8 6,487 72.7 23.6 44.1 5.0 7,373 75.8 21.8 49.3 4.7 2,669 76.9 21.7 48.7 6.6 3,067 74.8 20.6 48.6 5.5 707 73.3 23.6 44.5 5.3 13,566 78.7 23.1 50.0 5.7 7,064 73.5 22.7 45.2 5.7 9,444 67.3 23.5 39.6 4.2 3,292 67.8 23.2 40.7 3.9 9,172 76.8 23.4 48.4 5.1 7,235 85.6 21.6 55.5 8.5 3,212 86.8 18.0 45.3 23.6 323 74.3 22.9 45.9 5.4 20,016 Note: Haemoglobin levels are adjusted for altitude when calculating the degree of anaemia. Total includes 2, 20, 187, 7, 215, and 73 children with missing information on mother’s education, religion, caste/tribe, mother’s work status, the standard of living index, and mother’s anaemia status, respectively, who are not shown separately. ( ) Based on 25–49 unweighted cases 273 Several groups of children have particularly high levels of anaemia. These include children age 12–23 months, children of higher birth orders, rural children, children whose mothers are illiterate, Sikh children and children of ‘other’ religions, children from scheduled castes and scheduled tribes, and children from poor families. As expected, there is a strong positive relationship between the haemoglobin levels of mothers and prevalence of anaemia among children. Almost one-quarter of children whose mothers are severely anaemic are severely anaemic themselves. Table 7.19 and Figure 7.6 show the level of anaemia by state. Nagaland, Kerala, and Manipur are the only states where less than half of the children are anaemic. The highest prevalence of anaemia is found in Haryana, Rajasthan, Bihar, and Punjab, where at least 80 percent of children are anaemic. In these four states, 54–66 percent of children are moderately or severely anaemic. Table 7.19 Anaemia among children by state Percentage of children age 6–35 months classified as having iron-deficiency anaemia by state, India, 1998–99 Percentage of children with: State Percentage of children with anaemia Mild anaemia Moderate anaemia Severe anaemia India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 74.3 22.9 45.9 5.4 69.0 22.2 42.9 3.9 83.9 18.0 58.8 7.1 69.9 28.7 39.0 2.2 71.1 29.1 38.5 3.5 80.0 17.4 56.7 5.9 82.3 20.1 52.7 9.5 75.0 22.0 48.1 4.9 73.9 19.4 47.8 6.7 81.3 26.9 50.3 4.1 72.3 26.2 43.2 2.9 78.3 26.9 46.3 5.2 54.5 29.1 24.7 0.7 63.2 31.0 32.2 0.0 45.2 22.6 21.7 0.9 67.6 23.4 39.8 4.3 57.2 32.2 22.7 2.3 43.7 22.0 18.7 3.0 76.5 28.4 40.7 7.5 53.4 23.5 27.9 2.0 74.5 24.2 43.7 6.7 76.0 24.1 47.4 4.4 72.3 23.0 44.9 4.4 70.6 19.6 43.3 7.6 43.9 24.4 18.9 0.5 69.0 21.9 40.2 6.9 Note: Haemoglobin levels are adjusted for altitude when calculating the degree of anaemia. 274 7.7 Iodization of Salt Iodine is an important micronutrient. A lack of iodine in the diet can lead to Iodine Deficiency Disorders (IDD), which, according to the World Health Organization, can cause miscarriages, brain disorders, cretinism, and retarded psychomotor development. Iodine deficiency is the single most important and preventable cause of mental retardation worldwide. It has been estimated that 200 million people in India are exposed to the risk of iodine deficiency and 70 million suffer from goitre and other IDDs (IDD & Nutrition Cell, 1998). In addition, about one-fifth of pregnant women are at considerable risk of giving birth to children who will not reach their optimum physical and mental potential because of maternal iodine deficiency (Vir, 1995). Iodine deficiency can be avoided by using salt that has been fortified with iodine. In 1983–84, the Government of India adopted a policy to achieve universal iodization of edible salt by 1992. In 1988, the Prevention of Food Adulteration Act was amended to fix the minimum iodine content of salt at 30 parts per million (ppm) at the manufacturing level and 15 ppm at the Figure 7.6 Anaemia Among Children by State 0 10 20 30 40 50 60 70 80 90 Haryana Ra jasthan B ihar P un jab W est B enga l S ikkim M aharashtra M adhya P radesh G ujara t INDIA Uttar P radesh O rissa A ndhra P radesh Jam m u & K ashm ir K arnataka H im acha l P radesh Tam il N adu De lh i M egha laya A ssam M izoram A runacha l P radesh G oa M anipur K era la Nagaland P ercent NFHS-2, India, 1998–99 275 consumer level (MOHFW, 1994). The Government of India has advised all states and union territories to issue notifications banning the sale of edible salt that is not iodized. However, the ban on non-iodized salt was lifted in September, 2000. NFHS-2, with its representative sample of households throughout the country, is an ideal vehicle for measuring the degree of iodization of salt used in households in India. Iodine levels in salt can be measured in the laboratory using a standard titration test or in the field using a rapid-test kit. In NFHS-2, interviewers measured the iodine content of cooking salt in each interviewed household using a rapid-test kit. The test kit consists of ampoules of a stabilized starch solution and of a weak acid-based solution. The interviewer squeezes one drop of the starch solution onto a sample of cooking salt obtained from the household. If the colour changes (from light blue through dark violet), the interviewer matches the colour of the salt as closely as possible to a colour chart on the test kit and records the iodine level as 7, 15, or 30 ppm. If the initial test is negative (no change in colour), the interviewer is required to conduct a second confirmatory test on a new salt sample, using the acid-based solution in addition to the starch solution. This test is necessary because the starch solution will not show any colour change even on iodized salt if the salt is alkaline or is mixed with alkaline free-flow agents. If the colour of the salt does not change even after the confirmatory test, the salt is not iodized. Because of uncertainties and subjective judgement in the matching process, the rapid test should not be seen as giving an exact quantitative estimate of salt iodization, but it does provide useful information on whether or not salt is iodized, as well as the extent of iodization. A recent multicentric study in eight centres in India concluded that the rapid test kit can be used for semi-quantitative estimation of the iodine content of salt to monitor the quality of salt being used in a community (Kapil et al., 1999). Table 7.20 shows the extent of salt iodization at the household level. Overall, despite government regulations in effect at the time of the survey, only 49 percent of households use cooking salt that is iodized at the recommended level of 15 ppm or more. More than one-quarter of households (28 percent) use salt that is not iodized at all and 22 percent use salt that is inadequately iodized (less than 15 ppm). Differentials in salt iodization by background characteristics are pronounced. Seventy-seven percent of households in large cities use salt with 15 ppm or more of iodine compared with 67–68 percent of households in small cities and towns and only 42 percent of households in rural areas. Among religious groups, households with Jain or Sikh heads are most likely to use adequately iodized salt. The use of iodized salt is relatively low in households headed by persons from scheduled castes, scheduled tribes, or other backward classes. The widest differentials are observed for the standard of living index. Seventy-eight percent of households with a high standard of living use adequately iodized salt compared with only 35 percent of households with a low standard of living. 276 The use of iodized salt varies dramatically from one state to another. The variations are due to a number of factors, including the scale of salt production, transportation requirements, enforcement efforts, the pricing structure, and storage patterns. In particular, salt iodization is likely to be more common in states where salt is transported exclusively by railways, at least partly because the Salt Department monitors the iodine content of salt shipped by railways. The use of adequately iodized salt is uniformly high throughout the Northeastern Region and in most states in the Northern Region, reaching a high of 91 percent in Himachal Pradesh and Mizoram (Table 7.21). All of the states in the Southern Region have low levels of use of adequately iodized salt, ranging from only 21 percent in Tamil Nadu to 43 percent in Karnataka. Outside of the Southern Region, Orissa is the only state where less than 40 percent of households use adequately iodized salt. It is clear that in many states the lax enforcement of salt iodization regulations in effect at the time of NFHS-2 was thwarting efforts to eliminate Iodine Deficiency Disorders in India. Table 7.20 Iodization of salt Percent distribution of households by degree of iodization of salt, according to selected background characteristics, India, 1998–99 Background characteristic Not iodized 7 ppm 15 ppm 30 ppm Missing Total percent Number of households Type of place of residence Large city Small city Town Rural area Religion of household head Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe of household head Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 14.8 7.8 11.1 65.7 0.7 100.0 6,745 17.7 14.1 12.5 55.2 0.5 100.0 7,393 19.3 13.6 13.7 52.8 0.6 100.0 11,106 32.5 25.3 18.3 23.2 0.7 100.0 65,953 29.3 22.1 16.3 31.6 0.7 100.0 74,699 23.1 23.0 21.2 32.1 0.6 100.0 10,662 33.3 16.5 12.2 37.9 0.1 100.0 2,716 17.1 8.2 15.7 58.7 0.3 100.0 1,556 12.6 6.2 13.0 68.1 0.0 100.0 363 26.4 9.1 16.1 47.5 0.9 100.0 749 19.7 22.2 20.3 37.7 0.0 100.0 306 28.9 19.2 14.1 37.6 0.3 100.0 59 32.0 25.5 17.4 24.4 0.8 100.0 17,051 34.0 22.1 18.6 24.7 0.6 100.0 8,337 33.9 23.2 15.9 26.5 0.5 100.0 29,543 20.7 18.2 16.7 43.7 0.7 100.0 35,386 36.0 28.1 18.6 16.5 0.8 100.0 33,064 28.6 21.5 17.5 31.7 0.6 100.0 40,434 12.8 9.2 11.6 66.0 0.4 100.0 16,640 28.4 21.6 16.8 32.6 0.7 100.0 91,196 Note: Total includes 87, 880, and 1,057 households with missing information on religion, caste/tribe, and the standard of living index, respectively, which are not shown separately. ppm: Parts per million 277 Table 7.21 Iodization of salt by state Percent distribution of households by degree of iodization of salt, according to state, India, 1998–99 State Not iodized 7 ppm 15 ppm 30 ppm Missing Total percent India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 28.4 21.6 16.8 32.6 0.7 100.0 6.1 4.5 13.5 75.7 0.1 100.0 19.5 9.2 13.9 57.1 0.2 100.0 3.2 6.2 14.9 75.6 0.1 100.0 24.8 22.3 27.5 25.4 0.0 100.0 16.7 7.8 13.7 61.6 0.3 100.0 37.1 15.3 21.9 24.4 1.3 100.0 25.0 16.3 14.4 42.3 2.1 100.0 22.7 26.9 19.6 29.2 1.6 100.0 22.9 30.1 26.6 20.4 0.0 100.0 29.6 35.1 18.2 16.8 0.4 100.0 11.3 26.5 25.8 36.0 0.5 100.0 0.8 15.0 46.9 37.2 0.1 100.0 1.8 18.2 32.7 46.9 0.3 100.0 2.3 9.7 15.4 72.5 0.1 100.0 6.7 30.0 24.9 38.1 0.3 100.0 0.7 8.0 27.9 63.3 0.0 100.0 10.9 21.2 25.5 41.7 0.7 100.0 3.1 17.5 31.8 47.3 0.3 100.0 37.3 20.2 4.0 37.9 0.6 100.0 29.5 14.2 14.9 41.2 0.2 100.0 32.0 6.9 11.0 49.1 1.0 100.0 36.8 35.7 10.2 17.2 0.1 100.0 24.1 32.4 12.9 30.5 0.1 100.0 47.6 13.2 5.6 33.7 0.0 100.0 62.7 15.8 8.1 13.1 0.3 100.0 ppm: Parts per million CHAPTER 8 MATERNAL AND REPRODUCTIVE HEALTH Promotion of maternal and child health has been one of the most important objectives of the Family Welfare Programme in India. The Government of India took steps to strengthen maternal and child health services as early as the First and Second Five-Year Plans (1951–56 and 1956– 61). As part of the Minimum Needs Programme initiated during the Fifth Five-Year Plan (1974– 79), maternal health, child health, and nutrition services were integrated with family planning services. The primary aim at that time was to provide at least a minimum level of public health services to pregnant women, lactating mothers, and preschool children (Kanitkar, 1979). In 1992–93, the Child Survival and Safe Motherhood Programme continued the process of integration by bringing together several key child survival interventions with safe motherhood and family planning activities (Ministry of Health and Family Welfare, 1992). In 1996, safe motherhood and child health services were incorporated into the Reproductive and Child Health Programme. This new programme seeks to integrate maternal health, child health, and fertility regulation interventions with reproductive health programmes for both women and men. With regard to maternal and reproductive health (Ministry of Health and Family Welfare, 1997; 1998b), the important elements of the programme include: • Provision of antenatal care, including at least three antenatal care visits, iron prophylaxis for pregnant and lactating mothers, two doses of tetanus toxoid vaccine, detection and treatment of anaemia in mothers, and management and referral of high-risk pregnancies • Encouragement of institutional deliveries or home deliveries assisted by trained health personnel • Provision of postnatal care, including at least three postnatal visits • Identification and management of reproductive tract and sexually transmitted infections In rural areas, the government delivers reproductive and other health services through its network of Primary Health Centres (PHCs), sub-centres, and other government health facilities. In addition, pregnant women and children can obtain services from private maternity homes, hospitals, private practitioners, and in some cases, nongovernmental organizations (NGOs). In urban areas, reproductive health services are available mainly through government or municipal hospitals, urban health posts, hospitals and nursing homes operated by NGOs, and private nursing and maternity homes. In rural areas, a female paramedical worker, called an auxiliary nurse midwife (ANM), is posted at a sub-centre to provide basic maternal health, child health, and family welfare services to women and children either in their homes or in the health clinic. Her work is overseen by the lady health visitor (LHV) posted at the PHC. With regard to safe motherhood, the ANM is responsible for registering pregnant women, motivating them to obtain antenatal and postnatal care, assessing their health throughout pregnancy and in the postpartum period, and referring women with high-risk pregnancies. The ANM is assisted by a male health worker whose duties 280 include motivating men to participate in the family welfare programme and educating men about reproductive tract and sexually transmitted infections. The ANM and LHV also assist the medical officer at the PHC where health services including antenatal and postnatal care are provided (Ministry of Health and Family Welfare, 1997; 1998b). The National Population Policy adopted by the Government of India in 2000 (Ministry of Health and Family Welfare, 2000) reiterates the government’s commitment to the safe motherhood programmes within the wider context of reproductive health. Among the national sociodemographic goals for 2010 specified by the policy, several goals pertain to safe motherhood, namely that 80 percent of all deliveries should take place in institutions by 2010, 100 percent of deliveries should be attended by trained personnel, and the maternal mortality ratio should be reduced to a level below 100 per 100,000 live births. Empowering women for improved health and nutrition is 1 of the 12 strategic themes identified in the policy to be pursued in stand alone or intersectoral programmes. An important objective of NFHS-2 is to provide information on the use of safe- motherhood services provided by the public and private sectors. In addition, the survey included questions on the prevalence and treatment of reproductive health problems. Relevant questions on safe motherhood were included in the Woman’s Questionnaire. The topics covered include pregnancy complications, antenatal and postnatal care, place of and assistance during delivery, delivery characteristics, and postpartum complications. Although NFHS-2 obtained this information for the two most recent live births since 1 January 1995 for the states surveyed in the first phase and 1 January 1996 for the states surveyed in the second phase, the information presented in this chapter pertains only to the subset of those births that took place during the three years preceding the woman’s interview. With regard to reproductive health, all women were asked about their experience of specific symptoms of reproductive health problems, and if problems were reported, whether and where treatment was received. 8.1 Antenatal Problems and Care Antenatal care (ANC) refers to pregnancy-related health care provided by a doctor or a health worker in a medical facility or at home. The Safe Motherhood Initiative proclaims that all pregnant women must receive basic, professional antenatal care (Harrison, 1990). Ideally, antenatal care should monitor a pregnancy for signs of complications, detect and treat pre- existing and concurrent problems of pregnancy, and provide advice and counselling on preventive care, diet during pregnancy, delivery care, postnatal care, and related issues. The Reproductive and Child Health Programme recommends that as part of antenatal care, women receive two doses of tetanus toxoid vaccine, adequate amounts of iron and folic acid tablets or syrup to prevent and treat anaemia, and at least three antenatal check-ups that include blood pressure checks and other procedures to detect pregnancy complications (Ministry of Health and Family Welfare, 1997; 1998b). NFHS-2 collected information from women on specific problems they may have had during their pregnancies and whether they received any antenatal check-ups. Women who did not receive antenatal check-ups were asked why they did not. Women who received antenatal check-ups were asked about the care provider, the timing of the first antenatal check-up, the total number of check-ups, the procedures conducted during the check-ups, and the advice given. In addition, the survey asked women whether they received tetanus toxoid injections and iron and 281 folic acid tablets or syrup during the pregnancy. Results from each of these questions are discussed in this chapter. Problems During Pregnancy For each of the two most recent births in the three years preceding the survey, the mother was asked if at any time during the pregnancy she experienced any of the following pregnancy-related problems: night blindness, blurred vision, convulsions (not from fever), swelling (of the legs, body or face), excessive fatigue, anaemia, or vaginal bleeding. Night blindness, or difficulty seeing at dusk, is the result of chronic vitamin A deficiency and is often seen in pregnant women in areas where vitamin A deficiency is endemic. Convulsions accompanied by signs of hypertension can be symptomatic of eclampsia, a potentially fatal condition. The potential health risk posed by vaginal bleeding during pregnancy varies by when in the pregnancy the bleeding takes place. Although documenting the prevalence of the symptoms of pregnancy complications is vital for planning services to reduce maternal morbidity and mortality, the information presented here is based on women’s self reports and should be interpreted with care. As shown in Table 8.1 and Figure 8.1, the pregnancy-related health problems most commonly reported are excessive fatigue (43 percent), followed by anaemia (27 percent), swelling of the legs, body, or face (26 percent), and blurred vision (22 percent). Fourteen percent reported convulsions that were not from fever and 12 percent reported night blindness. Only 4 percent reported any vaginal bleeding. The reported prevalence of both kinds of vision problems and of convulsions that were not from fever are higher in rural than in urban areas. There is little urban-rural difference in the prevalence of the other pregnancy-related health problems. Antenatal Check-Ups A pregnant woman can have an antenatal check-up by visiting a doctor or another health professional in a medical facility, receiving a home visit from a health worker, or both. NFHS-2 asked women who had a birth during the three years preceding the survey whether any health worker had visited them at home to provide antenatal check-ups. The survey also asked whether Table 8.1 Health problems during pregnancy Among births during the three years preceding the survey, percentage of mothers experiencing specific health problems during pregnancy by residence, India, 1998–99 Problem during pregnancy Urban Rural Total Night blindness Blurred vision Convulsions not from fever Swelling of the legs, body, or face Excessive fatigue Anaemia Vaginal bleeding Number of births 6.4 13.7 12.1 17.0 23.2 21.8 11.0 15.2 14.3 28.2 25.8 26.3 43.6 43.3 43.4 27.1 26.3 26.5 3.1 3.6 3.5 7,191 25,202 32,393 Note: Table includes only the two most recent births during the three years preceding the survey. 282 women had gone for antenatal check-ups outside the home, and if they had, what type of service provider gave them the check-ups. Table 8.2 and Figure 8.2 show the percent distribution of births in the three years preceding the survey by the source of antenatal check-ups received during pregnancy according to selected background characteristics. Women who received antenatal check-ups both at home and outside the home are categorized as having received care outside the home. If a woman received check-ups from more than one type of health provider, only the provider with the highest qualification is considered. NFHS-2 results show that mothers in India received antenatal check-ups for only 65 percent of births during the three years preceding the survey, almost unchanged from 64 percent in NFHS-1. Mothers received antenatal check-ups from doctors for 49 percent of births and from other health professionals (such as ANMs, nurses, midwives, or LHVs) for 11 percent of births. Mothers received antenatal check-ups exclusively at home from a health worker for 6 percent of births. Older women (age 35–49) are much less likely than younger women to have received antenatal check-ups for their births and the likelihood that an antenatal check-up was received declines sharply with birth order. Mothers of 78 percent of first order births received an antenatal check-up compared with only 37 percent of mothers of births of order six or higher. As expected, antenatal check-ups from doctors are much more common in urban areas than in rural areas. At least four out of five births to literate women received antenatal check-ups compared with half of the births to illiterate women. The proportion of births whose mothers received antenatal check-ups from a doctor increases sharply with education, from 32 percent for illiterate mothers to 62 percent for mothers who are literate but have not completed middle school and 85 percent Figure 8.1 Problems During Pregnancy 43 27 26 22 14 12 4 0 5 10 15 20 25 30 35 40 45 50 Excessive Fatigue Anaemia Swelling of Legs, Body, or Face Blurred Vision Convulsions Not from Fever Night B lindness Vaginal B leeding Percent Note: Based on births in the three years preceding the survey (1996–98) NFHS-2, India, 1998–99 283 Table 8.2 Antenatal check-ups Percent distribution of births during the three years preceding the survey by source of antenatal check-up, according to selected background characteristics, India, 1998–99 Antenatal check-up outside home1 from: Background characteristic Antenatal check-up only at home from health worker Doctor Other health professional Traditional birth attendant, other No antenatal check-up Missing Total percent Number of births Mother’s age at birth < 20 20–34 35–49 Birth order 1 2–3 4–5 6+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 6.3 48.7 12.4 0.4 31.7 0.6 100.0 7,589 5.3 49.5 10.7 0.2 33.6 0.6 100.0 23,469 5.7 32.1 6.1 0.1 54.9 1.2 100.0 1,335 3.8 63.1 10.4 0.3 21.7 0.6 100.0 9,365 5.9 51.4 12.0 0.2 30.0 0.6 100.0 14,104 7.1 32.7 11.2 0.2 48.2 0.5 100.0 5,644 6.8 22.9 7.3 0.2 62.0 0.9 100.0 3,279 2.0 74.8 8.8 0.2 13.6 0.6 100.0 7,191 6.6 41.2 11.5 0.3 39.8 0.6 100.0 25,202 7.3 32.1 11.2 0.3 48.4 0.7 100.0 19,061 4.8 62.1 12.9 0.3 19.3 0.7 100.0 5,818 3.0 71.8 11.2 0.1 13.5 0.4 100.0 2,935 1.2 85.4 7.2 0.1 5.8 0.3 100.0 4,574 6.2 47.2 11.2 0.2 34.5 0.6 100.0 25,650 3.3 50.7 8.5 0.4 36.4 0.7 100.0 5,120 3.0 73.4 7.5 0.2 15.4 0.4 100.0 753 1.3 44.7 29.0 0.0 24.9 0.1 100.0 450 3.1 84.7 6.5 0.0 5.7 0.0 100.0 76 1.4 74.9 9.2 0.0 14.5 0.0 100.0 199 0.3 59.9 15.7 0.1 19.7 4.2 100.0 87 10.0 53.7 0.7 0.0 35.6 0.0 100.0 24 5.9 41.7 13.3 0.2 38.2 0.6 100.0 6,478 10.0 34.7 11.5 0.3 43.1 0.4 100.0 3,080 5.9 48.9 9.6 0.2 34.8 0.6 100.0 10,404 4.0 56.5 10.6 0.2 27.9 0.7 100.0 12,050 7.3 35.8 11.0 0.2 45.1 0.7 100.0 11,804 5.1 50.1 11.1 0.3 32.8 0.7 100.0 15,080 2.8 73.7 10.5 0.2 12.4 0.4 100.0 5,112 5.6 48.6 10.9 0.2 34.0 0.6 100.0 32,393 Note: Table includes only the two most recent births during the three years preceding the survey. Total includes 5, 33, 380, and 397 births with missing information on mother’s education, religion, caste/tribe, and the standard of living index, respectively, which are not shown separately. 1Includes all births for which the mothers received an antenatal check-up outside the home, even if they also received an antenatal check-up at home from a health worker. If more than one type of antenatal check-up provider was mentioned, only the provider with the highest qualifications is shown. 284 for mothers who have completed at least high school. Conversely, the percentage of births for which mothers received home visits only from a health worker decreases with mothers’ education. The majority of women in all religious groups receive antenatal check-ups; nonetheless, there is substantial variation in the likelihood of women receiving an antenatal check-up by religion. Antenatal check-ups were received for only 63–65 percent of births to Hindu and Muslim women compared with 84–86 percent of births to Christian and Buddhist/Neo-Buddhist women and 94 percent of births to Jain women. Jain women, followed by Buddhist/Neo-Buddhist and Christian women, are also most likely to have received check-ups from a doctor; but Sikh women are much more likely than women of any other religion to have received check-ups from health professionals other than doctors. By caste/tribe, the likelihood of having received any antenatal check-up and a check-up from a doctor is lowest for births to scheduled-tribe mothers and highest for births to mothers who do not belong to a scheduled caste, scheduled tribe, or other backward class. The likelihood of having received antenatal check-ups at all, as well as from a doctor, increases sharply with the household’s standard of living. Among births to mothers living in households with a low standard of living, 54 percent received antenatal check-ups and 36 percent received antenatal check-ups from doctors. By contrast, among births to mothers living in households with a high standard of living, 87 percent received antenatal check-ups and 74 percent received check-ups from doctors. In summary, more than one out of every three women in India did not receive an antenatal check-up for births in the three years preceding the survey. Women not receiving antenatal check-ups tend disproportionately to be older women, women of high parity, women from scheduled tribes, illiterate women, and poor women. This suggests that improving the coverage of antenatal programmes requires special efforts to reach older and high-parity women and women who are socioeconomically disadvantaged. Figure 8.2 Source of Antenatal Check-Ups During Pregnancy No Antenatal Check-Up 34% Other Health Professional 11% Traditional Birth Attendant, Other 0.2% Doctor 49% Missing 1% Antenatal Check-Ups Only at Home from Health Worker 6% Note: Percents add to more than 100 due to rounding NFHS-2, India, 1998–99 285 Reasons for Not Receiving Antenatal Check-Ups Table 8.3 shows the percent distribution of births in the three years preceding the survey whose mothers did not receive any antenatal check-ups in a health facility or at home by the main reason for not receiving check-ups. For almost three-quarters of the births to mothers who did not have any antenatal check-ups, mothers did not consider having a check-up to be necessary (60 percent) or customary (4 percent) or were not allowed by their families to have one (9 percent). Costs account for another 15 percent of cases and lack of knowledge, distance, and lack of transport account for the majority of the remaining reasons. These results suggest the need to inform mothers and families about the availability and benefits of antenatal check-ups to help overcome traditional attitudes and other hurdles that prevent mothers from seeking antenatal care for their pregnancies. In addition, since about one-fifth of the reasons reported deal with problems of accessibility, quality, and cost of services, utilization of antenatal care services could also be increased by lowering direct and indirect costs, improving quality, and making services more accessible. Number and Timing of Antenatal Check-Ups The number of antenatal check-ups and the timing of the first check-up are important for the health of the mother and the outcome of the pregnancy. The conventional recommendation for normal pregnancies is that once pregnancy is confirmed, antenatal check-ups should be scheduled at four-week intervals during the first seven months, then every two weeks until the last month, and weekly thereafter (MacDonald and Pritchard, 1980). Four antenatal check-ups—one each during the third, sixth, eighth, and ninth months of pregnancy—have been recommended as the minimum necessary (Park and Park, 1989). The conventional recommendation is to schedule the first check-up within six weeks of a woman’s last menstrual period. Studies on the timing of the Table 8.3 Reason for not receiving an antenatal check-up Percent distribution of births during the three years preceding the survey to mothers who did not receive an antenatal check-up by the main reason for not receiving an antenatal check-up, according to residence, India, 1998–99 Reason for not receiving an antenatal check-up Urban Rural Total Not necessary Not customary Costs too much Too far/no transport Poor quality service No time to go Family did not allow Lack of knowledge No health worker visited Other Total percent Number of births 63.4 59.1 59.5 3.8 4.3 4.3 11.3 15.0 14.7 0.9 3.9 3.7 1.6 0.8 0.8 2.6 1.7 1.8 11.3 8.2 8.5 3.2 4.2 4.1 0.2 1.6 1.5 1.7 1.1 1.2 100.0 100.0 100.0 978 10,040 11,018 Note: Table includes only the two most recent births during the three years preceding the survey. 286 initial antenatal check-up, however, show that even when antenatal care is initiated as late as the third trimester, there is a substantial reduction in perinatal mortality (Ramachandran, 1992). In India, the Reproductive and Child Health Programme includes the provision of at least three antenatal care visits for pregnant women. Guidelines of the programme require that each pregnancy be registered in the first 12–16 weeks (Ministry of Health and Family Welfare, 1997). Accordingly, the first antenatal check-up should take place at the latest during the second trimester of pregnancy. NFHS-2 asked women who received antenatal check-ups for births in the three years preceding the survey about the total number of check-ups they received and when in their pregnancies they received their first check-up. Table 8.4 and Figure 8.3 show the percent distribution of births in the three years preceding the survey by the number and timing of antenatal check-ups. In India, mothers of 44 percent of births received at least three antenatal check-ups (unchanged from NFHS-1) and 30 percent had four or more check-ups. The median number of check-ups was 2.8. There are substantial differences in the number of antenatal check-ups by residence. At least three antenatal Table 8.4 Number and timing of antenatal check-ups and stage of pregnancy Percent distribution of births during the three years preceding the survey by number of antenatal check-ups and by the stage of pregnancy at the time of the first check-up, according to residence, India, 1998–99 Number and timing of check-ups Urban Rural Total Number of antenatal check-ups 0 1 2 3 4+ Don’t know/missing Total percent Median number of check-ups (for those who received at least one antenatal check-up) Stage of pregnancy at the time of the first antenatal check-up No antenatal check-up First trimester Second trimester Third trimester Don’t know/missing Total percent Median months pregnant at first antenatal check-up (for those who received at least one antenatal check-up) Number of births 13.6 39.8 34.0 6.0 8.8 8.2 10.5 14.1 13.3 14.5 14.2 14.3 54.7 22.4 29.5 0.7 0.8 0.7 100.0 100.0 100.0 4.2 2.5 2.8 13.6 39.8 34.0 55.1 26.6 33.0 24.2 25.5 25.2 6.9 7.6 7.4 0.2 0.4 0.4 100.0 100.0 100.0 3.0 3.9 3.5 7,191 25,202 32,393 Note: Table includes only the two most recent births during the three years preceding the survey. 287 check-ups were received for 69 percent of births to mothers living in urban areas, but for only 37 percent of births to mothers living in rural areas. The median number of check-ups is also higher in urban areas (4.2) than in rural areas (2.5). The shorter distances to antenatal-care services and the comparative ease of travelling in urban areas, as well as the higher educational attainment of mothers in urban areas, could be important factors for the larger number of check-ups received by mothers in urban areas. One-third of the births that took place in the three years preceding the survey were to mothers who received their first antenatal check-up in the first trimester of pregnancy (up from one-quarter of births in NFHS-1), and another one-quarter were to mothers who received their first check-up in the second trimester (Table 8.4 and Figure 8.3). Check-ups during the first trimester were about twice as common in urban areas (55 percent) as in rural areas (27 percent). The first check-up was rarely received as late as the third trimester. Among births for which the mother received at least one antenatal check-up, the median timing of the first antenatal check-up is 3.5 months for India as a whole and is about one month later in rural areas (3.9) than in urban areas (3.0). Components of Antenatal Check-Ups The effectiveness of antenatal check-ups in ensuring safe motherhood depends in part on the tests and measurements done and the advice given during the check-ups. NFHS-2 collected information on this important aspect of antenatal care for the first time by asking mothers who received antenatal check-ups whether they received each of several components of antenatal check-ups at least once during any of their check-ups during pregnancy. For births during the three years preceding the survey for which antenatal check-ups were received, Table 8.5 presents the percentage whose mothers received specific components of check-ups by residence. Except Figure 8.3 Number and Timing of Antenatal Check-Ups 34 8 13 14 30 1 34 33 25 7 0 0 5 10 15 20 25 30 35 40 NUMBER OF CHECK-UPS 0 1 2 3 4+ Don't Know/Missing TIMING OF FIRST CHECK-UP No Antenatal Check-Up First Trimester Second Trimester Third Trimester Don't Know/Missing Percent Note: Based on births in the three years preceding the survey (1996–98) NFHS-2, India, 1998–99 288 for X-rays (which are not recommended as a standard component of antenatal care), all of the measurements and tests are part of essential obstetric care or are required for monitoring high- risk pregnancies. Among all births for which mothers received antenatal check-ups, mothers had an abdominal examination in 75 percent of these cases and had their blood pressure checked in 63 percent of these cases. Other common components of antenatal check-ups were blood tests (59 percent), measurement of weight (56 percent), and urine tests (56 percent). Mothers of only 38 percent of births had an internal examination during any antenatal check-up, 27 percent had their height measured, and 18 percent had a sonogram or ultrasound. X-rays and amniocentesis were rarely performed. Most of these measurements or tests were performed at least 1.5 times more often during antenatal check-ups for births to mothers living in urban areas than for those living in rural areas. The differentials by residence are greatest for sonography or ultrasound (which is about three times as likely to be performed in urban areas as in rural areas). Table 8.5 also shows the type of advice received by mothers who had antenatal check-ups for births in the three years preceding the survey. Dietary advice was given to mothers most often (in 68 percent of cases). Mothers were much less likely to receive advice on delivery care (41 percent), newborn care (38 percent), the danger signs of pregnancy (36 percent), and family planning (28 percent). The proportion receiving advice on each of these topics is consistently higher in urban areas than in rural areas. Table 8.5 Components of antenatal check-ups Among births during the three years preceding the survey for which an antenatal check-up was received, the percentage receiving specific components of antenatal check-ups by residence, India, 1998–99 Components of antenatal check-ups Urban Rural Total Antenatal measurements/tests Weight measured Height measured Blood pressure checked Blood tested Urine tested Abdomen examined Internal examination X-ray Sonography or ultrasound Amniocentesis Antenatal advice Diet Danger signs of pregnancy Delivery care Newborn care Family planning Number of births for which the mother received at least one antenatal check-up 74.7 48.3 56.0 37.1 22.2 26.5 80.1 55.5 62.7 78.1 51.4 59.2 76.2 46.9 55.5 87.6 70.2 75.3 55.2 31.4 38.3 6.9 3.5 4.5 34.4 11.8 18.4 3.4 1.9 2.3 76.7 63.9 67.6 45.5 31.7 35.7 51.0 37.4 41.3 47.7 34.0 38.0 33.8 26.1 28.3 6,171 15,002 21,173 Note: Table includes only the two most recent births during the three years preceding the survey. 289 Tetanus Toxoid Vaccination In India, an important cause of death in infancy is neonatal tetanus, which is caused by newborn infants becoming infected by tetanus organisms, usually at the umbilical stump. Neonatal tetanus is most common among children who are delivered in unhygienic environments and when unsterilized instruments are used to cut the umbilical cord. Tetanus typically develops during the first or second week of life and is fatal in 70–90 percent of cases (Foster, 1984). If neonatal tetanus infection occurs where expert medical help is not available, as is common in many rural areas in India, death is almost certain. Neonatal tetanus, however, is a preventable disease. Two doses of tetanus toxoid vaccine given one month apart during early pregnancy are nearly 100 percent effective in preventing tetanus among both newborn infants and their mothers. Immunity against tetanus is transferred to the foetus through the placenta when the mother is vaccinated. In India, the tetanus toxoid immunization programme for expectant mothers was initiated in 1975–76 and was integrated with the Expanded Programme on Immunization (EPI) in 1978 (Ministry of Health and Family Welfare, 1991). To step up the pace of the immunization programme, the Government of India initiated the Universal Immunization Programme (UIP) in 1985–86. An important objective of the UIP was to vaccinate all pregnant women against tetanus by 1990. In 1992–93, the UIP was integrated into the Child Survival and Safe Motherhood Programme, which in turn has been integrated into the Reproductive and Child Health Programme. According to the National Immunization Schedule, a pregnant woman should receive two doses of tetanus toxoid injection, the first when she is 16 weeks pregnant and the second when she is 20 weeks pregnant (Central Bureau of Health Intelligence, 1991). Re- inoculation is recommended every three years. If two doses were received less than three years earlier, a single booster injection is recommended. For each of the two most recent births during the three years preceding the survey, NFHS-2 asked mothers whether they were given an injection in the arm to prevent them and their baby from getting tetanus. Women who said they had received a tetanus injection were asked how many times they had received the injection during pregnancy. Table 8.6 shows the distribution of births by the number of tetanus toxoid injections given to mothers, according to selected background characteristics. Tetanus toxoid coverage in India is far from complete. For births in the three years preceding the survey, 24 percent of the mothers did not receive any tetanus toxoid injections during pregnancy, and another 8 percent received only one injection. The proportion of mothers who received two or more tetanus toxoid injections during their pregnancies rose from 55 percent to 67 percent between NFHS-1 and NFHS-2. Tetanus toxoid injections are more common in urban areas than in rural areas. Tetanus toxoid coverage (two or more injections) is much higher for births to women under age 35 (68 percent) than for the small number of births to older women (47 percent). Coverage varies inversely by birth order. At least two tetanus toxoid injections were received by mothers for 78 percent of first births compared with 56 percent of fourth and fifth births and less than half (42 percent) of higher-order births. Tetanus toxoid coverage is similar for Hindus (67 percent) and Muslims (66 percent), but coverage is much higher for births to mothers who are Jain or Sikh (both 88 percent). Coverage is substantially lower for births to scheduled-tribe mothers (46 percent) than for births to mothers in other caste and class groups (65–72 percent). 290 Table 8.6 Tetanus toxoid vaccination and iron and folic acid tablets or syrup Percent distribution of births during the three years preceding the survey by the number of tetanus toxoid injections received by the mother, percentage of births for which the mothers were given iron and folic acid (IFA) tablets or syrup during pregnancy, and among those who received iron and folic acid tablets or syrup, percentage who received enough for three months or longer and percentage who consumed all the supply given, according to selected background characteristics, India, 1998–99 Number of tetanus toxoid injections Background characteristic None One Two or more Don’t know/ missing Total percent Percent- age given iron and folic acid tablets or syrup Number of births Percent- age who received supply for 3+ months1 Percent- age who consumed all the supply1 Number of births whose mothers received IFA Mother’s age at birth < 20 20–34 35–49 Birth order 1 2–3 4–5 6+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Total 23.1 8.4 67.6 0.8 100.0 58.8 7,589 79.9 78.5 4,460 23.4 8.2 67.6 0.8 100.0 58.4 23,469 83.5 81.1 13,715 43.3 8.3 47.0 1.5 100.0 36.6 1,335 77.6 80.6 488 15.5 5.9 77.7 0.9 100.0 68.7 9,365 84.8 82.8 6,435 20.4 9.2 69.7 0.8 100.0 61.4 14,104 83.1 80.3 8,664 33.8 9.5 55.8 0.9 100.0 45.8 5,644 78.4 77.8 2,584 48.1 8.6 42.2 1.0 100.0 29.9 3,279 73.8 74.3 980 9.9 7.3 81.9 1.0 100.0 75.7 7,191 87.5 83.2 5,440 28.2 8.5 62.5 0.8 100.0 52.5 25,202 80.5 79.4 13,222 35.3 9.1 54.7 0.9 100.0 43.6 19,061 77.4 76.3 8,304 12.5 8.4 78.4 0.7 100.0 70.4 5,818 83.0 80.7 4,094 7.5 7.5 84.2 0.7 100.0 78.5 2,935 86.4 81.5 2,304 3.0 5.0 91.2 0.8 100.0 86.5 4,574 90.4 88.7 3,958 24.5 8.2 66.5 0.8 100.0 57.5 25,650 82.5 80.1 14,748 25.8 7.7 65.6 0.8 100.0 51.7 5,120 80.8 80.9 2,649 14.8 10.3 74.0 1.0 100.0 77.3 753 87.9 81.3 582 7.9 4.5 87.5 0.2 100.0 79.4 450 80.7 93.5 357 3.9 8.2 87.9 0.0 100.0 90.3 76 85.5 74.8 68 17.0 16.6 65.3 1.1 100.0 82.6 199 90.8 78.0 165 18.7 22.1 52.0 7.1 100.0 69.9 87 89.0 94.1 61 43.0 13.5 43.5 0.0 100.0 61.8 24 86.6 94.5 15 25.8 8.6 64.8 0.8 100.0 54.6 6,478 80.7 76.2 3,538 38.7 13.6 46.4 1.3 100.0 48.6 3,080 81.6 82.0 1,496 23.8 7.1 68.4 0.7 100.0 56.8 10,404 84.9 81.4 5,910 19.2 7.7 72.2 0.9 100.0 63.0 12,050 82.0 81.6 7,587 34.1 9.5 55.4 1.0 100.0 46.0 11,804 79.1 77.1 5,433 22.3 8.2 68.7 0.8 100.0 59.4 15,080 81.8 80.2 8,956 6.4 5.6 87.5 0.6 100.0 79.2 5,112 88.4 86.1 4,050 24.1 8.2 66.8 0.8 100.0 57.6 32,393 82.5 80.5 18,663 Note: Table includes only the two most recent births during the three years preceding the survey. Total includes births with missing information on mother’s education, religion, caste/tribe, and the standard of living index, which are not shown separately. 1Among births whose mother received iron and folic acid tablets or syrup 291 For 39 percent of their births, scheduled-tribe mothers did not receive any tetanus toxoid vaccine. Illiterate mothers received at least two tetanus toxoid injections for 55 percent of their births, whereas literate mothers received at least two tetanus toxoid injections for 78 percent or more of their births. Tetanus toxoid coverage increases with an increasing standard of living of the household. Notably, among births to mothers living in households with a low standard of living in only about half (55 percent) of the cases did the mother receive the recommended two doses of tetanus toxoid. These results suggest that despite generally improving coverage of tetanus toxoid vaccinations, the coverage for socioeconomically disadvantaged women lags far behind the level for the country as a whole. Iron and Folic Acid Supplementation Nutritional deficiencies in women are often exacerbated during pregnancy because of the additional nutrient requirements of foetal growth. Iron deficiency anaemia is the most common micronutrient deficiency in the world. It is a major threat to safe motherhood and to the health and survival of infants because it contributes to low birth weight, lowered resistance to infection, impaired cognitive development, and decreased work capacity. Studies in different parts of India have estimated that the proportion of births with a low birth weight (less than 2,500 grams) ranges from 15 percent in Trivandrum to 46 percent in Baroda (Nutrition Foundation of India, 1993). Overall, about one-third of newborn children in India are of low birth weight, indicating that many pregnant women in India suffer from nutritional deficiencies. Improvement in a woman’s nutritional status, coupled with proper health care during pregnancy, can substantially increase her child’s birth weight (Ramachandran, 1992). To this end, the provision of iron and folic acid (IFA) tablets to pregnant women to prevent nutritional anaemia forms an integral part of the safe-motherhood services offered as part of the MCH activities of the Family Welfare Programme (Ministry of Health and Family Welfare, 1991), and now offered as part of the Reproductive and Child Health Programme. The programme recommendation is that pregnant women consume 100 tablets of iron and folic acid during pregnancy. For each birth during the three years preceding the survey, NFHS-2 collected information on whether the mother received IFA tablets or syrup during pregnancy. IFA syrup was included in the question along with IFA tablets since IFA syrup is sometimes prescribed in the private sector and may even be prescribed in the public sector when and where tablets are not available. Table 8.6 shows that mothers in India received IFA supplements for more than half (58 percent) of the births. As with tetanus toxoid coverage, however, IFA coverage is well below average for births to older women, illiterate women, women with a low standard of living, scheduled-tribe women, and mothers of higher-order births. IFA coverage is also lower in rural areas (53 percent) than in urban areas (76 percent) and is much lower for births to Hindu and Muslim mothers (52– 58 percent) than for births to mothers of any other religion (70–90 percent). For India as a whole, IFA coverage improved slightly from 52 percent in NFHS-1 to 58 percent in NFHS-2. However, some of this improvement may be due to the fact that IFA syrup was included in the measurement of IFA coverage in NFHS-2 but not in NFHS-1. Not all mothers who received IFA received the recommended three-month supply of tablets or syrup. Among births to mothers who received IFA during pregnancy, for 83 percent mothers received at least a three-month supply and for 81 percent mothers consumed all the supplements that were given to them. Differentials by background characteristics in the proportion that received at least a three-month supply and the proportion that consumed the 292 supply received are similar, except by religion and caste/tribe. Both indicators are negatively related to birth order and positively related to mother’s education level and the standard of living, and both are relatively low in rural areas and for higher order births. Consumption of the supply received is relatively low for Jain and Buddhist/Neo-Buddhist mothers, and for scheduled-caste mothers, whereas the proportion who received at least a three-month supply is slightly lower than average for Muslims and Sikhs and does not vary much by caste/tribe. Thus, despite some success in ensuring that pregnant women receive the recommended dosage of IFA, many women are not actually consuming an adequate amount of IFA during their pregnancies. This suggests that the Reproductive and Child Health Programme needs to do a better job of informing pregnant women about the advantages of IFA, trying to understand why many women do not consume all the IFA they receive, and overcoming resistance to the consumption of IFA. Antenatal Care Indicators by State Table 8.7 shows the percentage of live births during the three years preceding the survey whose mothers received different types of antenatal care by state. Six summary indicators of utilization of antenatal care services are presented: the percentage who received at least one antenatal check-up, the percentage who received three or more antenatal check-ups, the percentage who received an antenatal check-up in the first trimester of pregnancy, the percentage who received two or more tetanus toxoid injections, the percentage given any iron and folic acid tablets or syrup, and the percentage who received a supply of iron and folic acid tablets or syrup for three or more months. The utilization of antenatal care services differs greatly by state; however, with a few exceptions, states that do well on any one indicator of antenatal care also perform well on the other indicators. Goa, Kerala, and Tamil Nadu consistently rank in the top five states in the country in terms of their performance on all six indicators. In these three states, mothers of 99 percent of births received at least one antenatal check-up, 91–98 percent received three or more antenatal check-ups, 60–81 percent received a check-up in the first trimester of pregnancy, 86–95 percent received two or more tetanus toxoid injections, 93–95 percent received any iron and folic acid tablets or syrup, and 84–89 percent received at least a three months supply. Kerala ranks highest on four of the six indicators. Goa is slightly ahead of Kerala in the percentage with at least one antenatal check-up and Tamil Nadu ranks highest in coverage by two or more tetanus toxoid injections. Although Andhra Pradesh is never in the top three, it is the only other state that performs consistently well on almost all indicators. Only a few states perform relatively well on one or more but not all of the antenatal care indicators. For example, Mizoram performs well in terms of the percentage who received at least one antenatal check-up (92 percent) and also in terms of the percentage who received three or more antenatal check-ups (76 percent) but does not perform as well on any of the other indicators. Other states that perform relatively well on only some indicators include Karnataka, Maharashtra, West Bengal, Punjab, Delhi, and Himachal Pradesh. 293 Uttar Pradesh, Bihar, and Rajasthan perform consistently poorly on all antenatal care indicators. Compared with Kerala for example, where mothers of 98 percent of births received three or more antenatal check-ups, mothers of only 35–36 percent of births in Bihar and Uttar Pradesh received at least one antenatal check-up and only 15–18 percent received three or more check-ups. In Rajasthan, mothers of 48 percent of births received at least one antenatal check-up and 23 percent received three or more. In addition, in Bihar, Rajasthan, and Uttar Pradesh mothers of less than one in five births received an antenatal check-up in the first trimester of pregnancy. These three states also fall well below the national average in terms of the percentage Table 8.7 Antenatal care indicators by state Percentage of births during the three years preceding the survey for which mothers received different types of antenatal care by state, India, 1998–99 State Percentage that received at least one antenatal check-up Percentage that received three or more antenatal check-ups Percentage that received an antenatal check-up in the first trimester of pregnancy Percentage that received two or more tetanus toxoid injections Percentage given any iron and folic acid tablets or syrup Percentage that received supply of iron and folic acid tablets or syrup for 3+ months India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 65.4 43.8 33.0 66.8 57.6 47.5 83.5 68.2 49.0 84.9 77.8 69.5 58.1 37.4 32.8 79.7 67.0 53.3 86.8 60.9 48.2 66.2 85.6 70.9 83.2 66.0 47.9 77.7 70.8 55.8 74.0 57.0 42.6 89.9 79.6 64.2 47.5 22.9 19.2 52.1 39.3 30.6 61.0 28.1 26.1 55.0 48.9 38.4 34.6 14.9 16.9 51.4 32.4 20.6 36.3 17.8 15.1 57.8 24.1 19.8 79.5 47.3 33.7 74.3 67.6 62.2 90.0 57.0 35.1 82.4 71.6 56.4 61.6 40.5 24.5 45.6 56.3 47.6 60.1 30.8 30.7 51.7 55.0 45.3 80.2 54.4 45.0 64.2 50.0 38.0 53.6 31.3 20.6 30.8 49.5 40.6 91.8 75.8 39.6 37.8 72.7 62.0 60.4 23.1 23.8 50.9 42.5 26.7 69.9 42.6 30.2 52.7 62.4 50.4 99.0 95.7 73.4 86.1 94.7 87.8 86.4 60.2 35.8 72.7 78.0 66.6 90.4 65.4 46.7 74.9 84.8 71.6 92.7 80.1 52.5 81.5 81.2 70.7 86.3 71.4 52.7 74.9 78.0 74.2 98.8 98.3 81.1 86.4 95.2 88.6 98.5 91.4 59.5 95.4 93.2 84.1 Note: Table includes only the two most recent births during the three years preceding the survey. 294 receiving iron and folic acid tablets or syrup. Only 24 percent of women in Bihar, 32 percent in Uttar Pradesh, and 39 percent in Rajasthan received any iron and folic acid tablets or syrup compared with an all-India average of 58 percent. With respect to tetanus toxoid injections, Meghalaya, Mizoram, and Arunachal Pradesh perform even worse than Bihar, Rajasthan, and Uttar Pradesh. While at least half of all women in the latter three states received two or more tetanus toxoid injections, only 31 percent in Meghalaya, 38 percent in Mizoram, and 46 percent in Arunachal Pradesh did so. Meghalaya also performs relatively poorly on most other antenatal care indicators, as does Nagaland. Manipur performs relatively well in terms of the percentage receiving antenatal check-ups but not in the percentage receiving iron and folic acid tablets or syrup. Notably, Madhya Pradesh, the only other large state in North India, though performing below the national average, performs better than Bihar, Rajasthan, and Uttar Pradesh on all antenatal care indicators other than the provision of tetanus toxoid vaccine. In summary, antenatal care utilization in India varies greatly by state and for some indicators the variation ranges from only marginal coverage to almost complete coverage. For example, the percentage that received three or more antenatal check-ups ranges from only 15 percent in Uttar Pradesh to 98 percent in Kerala. In general, the southern and western states and some of the northern states perform uniformly well and the central states plus Bihar and Rajasthan perform uniformly poorly. The performance of the Northeastern states on most of the antenatal care indicators is mixed; notably, however, the percentage receiving tetanus toxoid injections is below the national average in all of these states. The majority of states improved their performance with respect to antenatal care indicators between NFHS-1 and NFHS-2. The states with the largest absolute gains in the percentage of births for which the mother received at least one antenatal check-up were Nagaland, Orissa, Manipur, and Rajasthan (all of which increased by at least 15 percentage points). Large decreases in this indicator (12–17 percentage points) occurred in Haryana, Uttar Pradesh, and Punjab. All but three states (Kerala, Mizoram, and Meghalaya) improved coverage of tetanus toxoid vaccinations. Coverage increased by more than 20 percentage points in Bihar and Rajasthan. The percentage of births for which the mother received any iron and folic acid tablets or syrup increased in every state except Meghalaya. The increase was 15 percent or higher in Nagaland, Orissa, West Bengal, and Manipur. 8.2 Delivery Care Place of Delivery Another important thrust of the Reproductive and Child Health Programme is to encourage deliveries under proper hygienic conditions under the supervision of trained health professionals. For each birth during the three years preceding the survey, NFHS-2 asked the mother where she gave birth and who assisted during the delivery. Table 8.8 and Figure 8.4 show that one-third (34 percent) of births in India took place in health facilities, more than half took place in the women’s own homes, and one in eight took place in their parents’ homes. Births taking place in health facilities were about equally divided between those that took place in a private health facility and those that took place in public institutions (such as government-operated district, 295 Table 8.8 Place of delivery Percent distribution of births during the three years preceding the survey by place of delivery, according to selected background characteristics, India, 1998–99 Place of delivery Health facility/institution Home Background characteristic Public NGO/trust Private Own home Parents’ home Other1 Total percent Number of births Mother’s age at birth < 20 20–34 35–49 Birth order 1 2–3 4–5 6+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Number of antenatal check-ups 0 1 2 3 4+ Total 16.7 0.7 14.4 46.0 21.0 1.1 100.0 7,589 16.4 0.8 17.8 54.2 9.8 1.0 100.0 23,469 9.5 0.5 9.9 75.3 3.1 1.7 100.0 1,335 23.2 1.0 26.4 32.6 15.8 1.0 100.0 9,365 16.4 0.7 16.7 51.5 13.6 1.1 100.0 14,104 9.6 0.6 7.3 73.7 7.9 1.0 100.0 5,644 6.4 0.3 5.1 83.7 3.2 1.2 100.0 3,279 29.1 1.5 34.5 27.6 6.3 1.0 100.0 7,191 12.5 0.5 11.6 60.5 13.8 1.0 100.0 25,202 10.2 0.4 6.8 68.1 13.4 1.1 100.0 19,061 23.3 1.1 19.0 42.3 13.4 0.9 100.0 5,818 28.5 1.0 25.6 32.8 11.1 1.1 100.0 2,935 24.2 1.5 49.3 17.9 6.4 0.7 100.0 4,574 16.4 0.6 15.9 53.5 12.5 1.1 100.0 25,650 14.1 0.9 16.5 55.7 11.8 1.0 100.0 5,120 19.8 2.6 32.0 35.0 10.2 0.4 100.0 753 10.8 0.9 35.3 45.4 7.3 0.4 100.0 450 12.4 1.6 57.6 25.5 3.0 0.0 100.0 76 38.9 0.0 16.3 30.5 14.0 0.4 100.0 199 24.2 2.5 5.2 57.6 6.3 4.2 100.0 87 7.9 0.0 11.1 78.5 2.6 0.0 100.0 24 16.0 0.5 10.3 60.1 12.0 1.1 100.0 6,478 10.7 0.7 5.7 70.4 11.4 1.1 100.0 3,080 16.3 0.8 19.0 49.8 13.0 1.1 100.0 10,404 17.9 0.9 21.3 47.1 11.9 0.9 100.0 12,050 11.9 0.4 6.2 66.1 14.2 1.2 100.0 11,804 18.1 0.8 16.0 51.8 12.3 1.0 100.0 15,080 20.3 1.1 43.2 27.6 7.0 0.7 100.0 5,112 4.2 0.1 3.0 80.5 11.5 0.8 100.0 11,018 11.2 0.2 6.8 67.3 13.5 1.0 100.0 2,641 15.7 0.4 10.7 57.0 15.3 0.9 100.0 4,293 21.8 0.7 15.0 45.7 16.0 0.7 100.0 4,628 29.2 1.7 39.0 20.2 9.5 0.5 100.0 9,571 16.2 0.7 16.7 53.2 12.2 1.0 100.0 32,393 Note: Table includes only the two most recent births during the three years preceding the survey. Total includes 5, 33, 380, 397, and 242 births with missing information on mother’s education, religion, caste/tribe, the standard of living index, and number of antenatal check-ups, respectively, which are not shown separately. NGO: Nongovernmental organization 1Includes missing 296 tehsil/taluk, town, or municipal hospitals and Primary Health Centres). Only 1 percent of births took place in facilities operated by nongovernmental organizations or trusts. About two-thirds of deliveries in urban areas and one-quarter of deliveries in rural areas took place in health facilities. The Sample Registration System (SRS) estimated that a slightly lower percentage of births took place in institutions in 1997 (25 percent of total births, 60 percent of births in urban areas, and 18 percent of births in rural areas). Deliveries in health facilities in India rose from 26 percent at the time of NFHS-1 to 34 percent at the time of NFHS-2. The proportion of births occurring in health facilities is higher for mothers under age 35 (32–35 percent) than for mothers age 35–49 (20 percent). Births to Hindu mothers (33 percent) and Muslim mothers (32 percent) are about equally likely to take place in a health facility; births to Jain mothers (72 percent), followed by births to Buddhist/Neo-Buddhist and Christian mothers (54–55 percent), are more likely than births to mothers of all other religions to take place in a health facility. Only 17 percent of births to scheduled-tribe mothers are institutional deliveries, compared with 40 percent of births to mothers who do not belong to a scheduled caste, scheduled tribe, or other backward class. The proportion of births that were delivered in a health facility decreases as birth order increases from order one (51 percent) to order six and over (12 percent). Institutional deliveries, particularly in private facilities, increase sharply with education and with the standard of living. Institutional deliveries are about two to four times as common among births to mothers who had four or more antenatal check-ups (70 percent) than to mothers who had 1–3 antenatal check-ups (18–38 percent). Institutional deliveries are least prevalent (7 percent) among births to mothers who did not receive any antenatal check-ups. Several factors are likely to contribute to the positive relationship between antenatal check-ups and delivery in a health facility. Women who receive antenatal check-ups are more likely than other women to deliver in a health facility because their antenatal care providers are likely to have advised them to do so. Conversely, women who register with a health facility for delivery may be called for regular check-ups by the facility. Another important factor may be pregnancy complications, because women with Figure 8.4 Place of Delivery and Assistance During Delivery Note: Percents for assistance during delivery add to less than 100 due to rounding NFHS-2, India, 1998–99 Place of Delivery Own Home 53% Public Institution 16% NGO or Trust Hospital/ Clinic 1% Private Institution 17% Other 1%Parents' Home 12% ��� ��� ��� ��� ��� Assistance During Delivery Other 22% Other Health Professional 1% ANM/Nurse/ Midwife/LHV 11% Doctor 30% Missing 0. 3% Dai (TBA) 35% 297 complications are more likely than other women to have antenatal check-ups and to deliver in a health facility. Another contributing factor may be the growing awareness of the benefits of professional medical care during both pregnancy and delivery, especially among urban, young, and educated women. With regard to deliveries at home, the proportion of deliveries in a woman’s own home increases and the proportion in her parents’ home decreases with age and birth order. Mother’s education and standard of living are both negatively associated with deliveries at home. Assistance During Delivery Table 8.9 and Figure 8.4 provide information on assistance during delivery by selected background characteristics. If more than one type of attendant assisted at delivery, only the most qualified attendant is shown. Forty-two percent of births in the three years before the survey were attended by a health professional, including 30 percent by a doctor and 11 percent by an ANM, nurse, midwife, or LHV. More than one-third of births (35 percent) were attended by a traditional birth attendant (TBA), and almost one-quarter (22 percent) were attended only by friends, relatives, and other persons. The proportion of deliveries attended by a health professional increased substantially from 33 percent in NFHS-1 to 42 percent in NFHS-2. Eighty-seven percent of deliveries in private institutions were attended by a doctor compared with 71 percent of deliveries in public institutions. Among deliveries at home (the respondents’ or their parents’ homes), more than half were attended by a TBA and fewer than one in seven were attended by a health professional. The percentage of births attended by a doctor is lower for mothers age 35–49 than for younger mothers and decreases steadily by birth order. First-order births (46 percent) are more than four times as likely as births of order six or above (11 percent) to be attended by a doctor. Deliveries are much more likely to be attended by a doctor in urban areas (56 percent) than in rural areas (23 percent). The proportion of deliveries attended by doctors also increases sharply with mother’s education and household standard of living. Seventy percent of births to mothers who have completed at least high school were attended by a doctor compared with only 16 percent of births to illiterate mothers. Among religious groups, Jain women (73 percent), followed by Christian women (50 percent), are most likely to have a delivery attended by a doctor. By contrast, only 29–30 percent of births to Muslim and Hindu women were attended by a doctor. Only 15 percent of births to women who belong to scheduled tribes and 24 percent to women who belong to scheduled castes were attended by a doctor compared with 37 percent of births to women who do not belong to a scheduled caste, scheduled tribe, or other backward class. As with deliveries in health facilities, the likelihood of having a birth attended by a doctor increases with the number of antenatal check-ups that the mother had during pregnancy. Only 8 percent of births to mothers who did not have any antenatal check-up were attended by a doctor; this proportion increases steadily to 33 percent for mothers who had three antenatal check-ups and 62 percent for mothers who had four or more antenatal check-ups. Among births to mothers who did not have any antenatal check-up, more than half (51 percent) were attended by a TBA and more than one-third (35 percent) only by friends, relatives, or others. 298 Table 8.9 Assistance during delivery Percent distribution of births during the three years preceding the survey by attendant assisting during delivery, according to selected background characteristics, India, 1998–99 Attendant assisting during delivery1 Background characteristic Doctor ANM/nurse/ midwife/ LHV Other health profes- sional Dai (TBA) Other Missing Total percent Number of births Mother’s age at birth < 20 20–34 35–49 Birth order 1 2–3 4–5 6+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Number of antenatal check-ups 0 1 2 3 4+ 28.2 12.6 0.8 34.7 23.4 0.3 100.0 7,589 31.5 11.3 0.6 34.6 21.7 0.3 100.0 23,469 19.7 6.7 1.0 42.5 29.5 0.7 100.0 1,335 46.1 13.7 0.7 25.2 14.0 0.3 100.0 9,365 30.1 11.9 0.6 35.0 22.0 0.3 100.0 14,104 15.9 9.0 0.7 44.3 29.8 0.3 100.0 5,644 10.5 6.8 0.6 46.7 35.0 0.4 100.0 3,279 55.8 17.2 0.3 18.8 7.6 0.2 100.0 7,191 23.0 9.8 0.7 39.6 26.6 0.3 100.0 25,202 15.6 9.0 0.8 44.7 29.6 0.4 100.0 19,061 37.3 15.4 0.4 28.4 18.1 0.3 100.0 5,818 49.5 17.1 0.3 21.0 11.7 0.3 100.0 2,935 70.3 12.9 0.2 11.8 4.7 0.1 100.0 4,574 29.5 11.5 0.6 34.7 23.3 0.3 100.0 25,650 29.0 9.6 0.6 40.0 20.5 0.2 100.0 5,120 50.4 12.2 1.3 18.7 17.1 0.3 100.0 753 43.0 25.5 0.2 31.0 0.3 0.0 100.0 450 73.2 11.2 0.0 14.2 1.5 0.0 100.0 76 43.4 19.2 0.0 18.3 19.1 0.0 100.0 199 30.0 6.1 0.0 22.1 37.5 4.2 100.0 87 10.6 10.9 0.0 50.8 27.6 0.0 100.0 24 23.5 12.1 1.2 37.7 25.1 0.5 100.0 6,478 14.5 8.3 0.2 44.4 32.2 0.5 100.0 3,080 31.8 12.3 0.8 34.9 19.9 0.3 100.0 10,404 37.3 11.3 0.3 31.4 19.5 0.2 100.0 12,050 15.8 8.5 1.1 43.5 30.7 0.5 100.0 11,804 31.1 12.8 0.4 34.3 21.1 0.3 100.0 15,080 60.9 14.5 0.3 17.5 6.8 0.1 100.0 5,112 7.6 5.2 0.9 50.9 35.4 0.1 100.0 11,018 15.7 11.0 0.7 41.5 31.0 0.0 100.0 2,641 23.9 13.5 0.7 38.1 23.8 0.0 100.0 4,293 32.8 15.7 0.7 32.9 17.9 0.0 100.0 4,628 62.3 15.9 0.3 14.7 6.8 0.0 100.0 9,571 Contd… 299 Delivery Characteristics Table 8.10 shows the percentage of births during the three years preceding the survey that were delivered by caesarian section and the percent distribution of births by weight and the mother’s estimate of the baby’s size at birth. Based on mothers’ reports, 7 percent of children born in India in the past three years were delivered by caesarian section. The proportion of deliveries by caesarian section was three times as high in urban areas (15 percent) as in rural areas (5 percent). Among births delivered by health professionals, 20 percent in urban areas and 15 percent in rural areas were delivered by caesarian section. The proportion of all births delivered by caesarian section increased substantially from NFHS-1 to NFHS-2, from 3 percent to 7 percent for India as a whole. A rapid increase took place in both urban areas (from 6 percent to 15 percent) and rural areas (from 2 percent to 5 percent). Low birth weight babies face substantially higher risks of dying than do babies of normal birth weight. For each birth that took place in the three years preceding the survey, respondents were asked the baby’s birth weight. Since babies delivered at home are unlikely to be weighed, the survey also asked mothers about the size of each baby at birth (large, average, small, or very small). In India, 70 percent of babies born in the three years preceding the survey were not weighed at birth. The proportion not weighed is 40 percent in urban areas and 79 percent in rural areas. Even for babies that were weighed, some mothers did not remember the weight. Therefore, the resulting sample of births for which weights are reported is subject to a potentially large selection bias, and the results should be interpreted with caution. Among children for whom birth weights were reported, 23 percent weighed less than 2.5 kilograms. The proportion weighing less than 2.5 kilograms is slightly higher in rural areas (24 percent) than in urban areas (21 percent). Table 8.9 Assistance during delivery (contd.) Percent distribution of births during the three years preceding the survey by attendant assisting during delivery, according to selected background characteristics, India, 1998–99 Attendant assisting during delivery1 Background characteristic Doctor ANM/nurse/ midwife/ LHV Other health profes- sional Dai (TBA) Other Missing Total percent Number of births Place of delivery Public health facility NGO or trust hospital/clinic Private health facility Own home Parents’ home Other2 Total 70.6 28.6 0.1 0.3 0.4 0.0 100.0 5,247 82.7 17.3 0.0 0.0 0.0 0.0 100.0 234 87.2 12.3 0.1 0.2 0.2 0.0 100.0 5,409 4.7 6.3 0.8 53.4 34.7 0.0 100.0 17,224 9.3 9.4 1.4 50.7 29.3 0.0 100.0 3,945 6.3 10.5 0.0 27.6 25.3 30.3 100.0 333 30.3 11.4 0.6 35.0 22.4 0.3 100.0 32,393 Note: Table includes only the two most recent births during the three years preceding the survey. Total includes 5, 33, 380, 397, and 242 births with missing information on mother’s education, religion, caste/tribe, the standard of living index, and number of antenatal check-ups, respectively, which are not shown separately. ANM: Auxiliary nurse midwife; LHV: Lady health visitor; TBA: Traditional birth attendant; NGO: Nongovernmental organization 1If the respondent mentioned more than one attendant, only the most qualified attendant is considered. 2Includes missing 300 According to mothers’ estimates, 61 percent of births in the three years preceding the survey were of average size, 14 percent were large, 19 percent were small, and 5 percent were very small. The proportion of babies reported as small or very small was similar in urban (23 percent) and rural (25 percent) areas. 8.3 Postnatal Care The health of a mother and her newborn child depends not only on the health care she receives during her pregnancy and delivery, but also on the care she and the infant receive during the first few weeks after delivery. Postpartum check-ups within two months after the delivery are particularly important for births that take place in noninstitutional settings. Recognizing the importance of postpartum check-ups, the Reproductive and Child Health Programme recommends three postpartum visits (Ministry of Health and Family Welfare, 1998b). Table 8.11 gives the percentage of noninstitutional births in the three years preceding the survey that were followed by a postpartum check-up within two months of delivery. Among births that were followed by a postpartum check-up, the table also shows the percentage with a check-up within two days of delivery (which is the most crucial period) and within one week of delivery, and the percentage whose mothers received specific recommended components of care during the check-up. Table 8.10 Characteristics of births Percentage of births during the three years preceding the survey that were delivered by caesarian section and percent distribution of births by birth weight and by the mother’s estimate of the baby’s size at birth, according to residence, India, 1998–99 Characteristic of births Urban Rural Total Percentage delivered by caesarian section Birth weight < 2.5 kg 2.5 kg or more Don’t know/missing Not weighed Total percent Size at birth Large Average Small Very small Don’t know/missing Total percent Number of births 14.7 4.9 7.1 10.8 4.2 5.7 40.3 13.4 19.4 8.7 3.7 4.8 40.2 78.6 70.1 100.0 100.0 100.0 16.0 13.3 13.9 61.2 61.4 61.4 17.6 19.9 19.4 4.9 5.0 5.0 0.3 0.4 0.4 100.0 100.0 100.0 7,191 25,202 32,393 Note: Table includes only the two most recent births during the three years preceding the survey. 301 Only 17 percent of noninstitutional births were followed by a check-up within two months of the delivery. Among births that were followed by a check-up, few check-ups took place shortly after birth (only 14 percent within two days and 31 percent within one week). Births to urban mothers were slightly more likely to be followed by a postpartum check-up than births to rural mothers. The likelihood of a birth being followed by a postpartum check-up was higher for literate mothers than illiterate mothers and for mothers in households with a high standard of Table 8.11 Postpartum check-ups Percentage of noninstitutional births during the three years preceding the survey for which a postpartum check-up was received within two months of birth and among those receiving a postpartum check-up, percentage seen within two days and one week of birth and percentage receiving specific components of check-ups by selected background characteristics, India, 1998–99 Among those with a postpartum check-up Components of postpartum check-up (%) Background characteristic Percentage with a postpartum check-up within two months of birth Number of births Percent- age seen within two days of birth Percent- age seen within one week of birth Abdominal examination Family planning advice Breast- feeding advice Baby care advice Number of births followed by a post- partum check-up Mother’s age at birth < 20 20–34 35–49 Birth order 1 2–3 4–5 6+ Residence Urban Rural Mother’s education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High 18.1 5,148 14.7 30.3 34.8 19.3 43.2 47.8 930 16.4 15,184 13.7 30.6 38.7 30.4 42.6 45.8 2,491 10.5 1,059 22.5 38.9 32.8 25.5 36.3 33.1 112 19.9 4,590 16.1 31.5 35.8 14.0 49.0 50.0 915 18.0 9,283 13.1 30.5 41.2 32.3 43.3 48.1 1,669 14.3 4,643 14.5 29.9 36.0 35.1 37.0 39.9 662 10.0 2,875 14.1 32.4 24.6 23.1 30.3 34.5 286 19.6 2,495 14.3 32.3 42.1 31.8 44.9 47.9 489 16.1 18,896 14.2 30.5 36.7 26.6 42.2 45.6 3,042 13.6 15,665 14.5 31.9 33.8 26.7 38.4 42.8 2,126 24.0 3,276 12.8 28.9 37.4 25.7 43.9 47.1 788 23.2 1,310 19.7 31.1 50.5 29.7 56.4 57.1 304 27.4 1,135 10.0 26.7 50.3 33.1 53.9 53.0 311 16.4 17,111 13.2 29.6 37.9 28.0 42.8 46.7 2,807 15.7 3,491 20.4 36.3 32.3 23.6 40.6 42.4 549 24.4 341 4.8 23.6 32.6 34.9 38.9 40.6 83 19.8 239 30.5 49.7 81.4 28.8 57.0 51.9 47 20.5 89 3.3 41.9 54.4 26.1 66.0 71.9 18 16.7 56 * * * * * * 9 25.1 19 * * * * * * 5 17.0 4,709 15.5 32.5 32.8 27.7 42.6 45.3 800 14.1 2,542 5.0 17.0 35.9 27.7 34.0 41.0 358 15.6 6,615 11.2 31.5 39.3 33.2 44.4 50.4 1,035 18.3 7,185 18.4 32.9 39.1 22.6 43.4 44.1 1,314 15.5 9,565 14.4 30.5 31.2 26.8 39.0 43.4 1,486 16.5 9,768 13.6 29.4 40.0 26.9 44.2 47.9 1,613 20.5 1,798 15.8 37.6 52.3 32.9 49.7 48.3 368 Contd… 302 living than for mothers in households with a medium or low standard of living. This likelihood decreases by mother’s age and birth order, and varies little by caste or tribe. Births to Hindu and Muslim women are equally likely to be followed by a postpartum check-up, whereas births to Christian women are more likely than births to women of other religions to be followed by a postpartum check-up. The likelihood that a birth was followed by a postpartum check-up increases steadily from 7 percent if the mother did not receive an antenatal check-up to 32 percent if the mother received three or more antenatal check-ups. Births delivered with the assistance of a health professional were more likely to be followed by a postpartum check-up (29 percent) than were births delivered with the assistance of a TBA (15 percent) or an other person (13 percent). These results clearly indicate that women are more likely to have a postpartum check-up if they have had continuous interaction with health providers through their pregnancy and delivery, even if they did not give birth in a health facility. Mothers who did not deliver in a health facility but who received a postpartum check-up were asked whether they had received specific components of postpartum care, including an abdominal examination and advice on family planning, breastfeeding, and baby care. For 38 percent of births, mothers who received a postpartum check-up said that their abdomen was examined during the check-up, and for 27 percent mothers said that they received family planning advice. Advice on breastfeeding and baby care was considerably more common (given in 43 and 46 percent of cases, respectively). Urban mothers, mothers who had completed at least middle school, mothers belonging to households with a high standard of living, and mothers who had received two or more antenatal check-ups, as well as mothers whose births were assisted by a Table 8.11 Postpartum check-ups (contd.) Percentage of noninstitutional births during the three years preceding the survey for which a postpartum check-up was received within two months of birth and among those receiving a postpartum check-up, percentage seen within two days and one week of birth and percentage receiving specific components of check-ups by selected background characteristics, India, 1998–99 Among those with a postpartum check-up Components of postpartum check-up (%) Background characteristic Percentage with a postpartum check-up within two months of birth Number of births Percent- age seen within two days of birth Percent- age seen within one week of birth Abdominal examination Family planning advice Breast- feeding advice Baby care advice Number of births followed by a post- partum check-up Number of antenatal check-ups 0 1 2 3+ Assistance during delivery Doctor/nurse/midwife/LHV1 Dai (TBA) Other Total 7.1 10,213 19.6 34.0 23.2 12.9 28.7 39.4 724 13.1 2,159 18.8 34.0 30.1 16.7 28.2 35.1 282 21.1 3,138 9.9 26.3 39.1 30.5 41.0 43.5 663 32.1 5,777 12.9 30.6 43.5 33.4 50.7 51.0 1,856 29.3 2,882 21.5 42.3 48.9 34.2 54.2 53.4 844 15.3 11,295 10.9 27.7 36.4 26.4 42.3 45.5 1,724 13.4 7,211 13.7 26.2 29.4 22.8 32.8 40.2 964 16.5 21,391 14.2 30.8 37.5 27.3 42.6 45.9 3,532 Note: Table includes only the two most recent births during the 2–35 months preceding the survey. Total includes births to mothers belonging to the Jain religion and births with missing information on mother’s education, religion, caste/tribe, the standard of living index, number of antenatal check-ups, and assistance during delivery, which are not shown separately. *Percentage not shown; based on fewer than 25 unweighted cases LHV: Lady health visitor; TBA: Traditional birth attendant 1Includes other health professionals 303 health professional, were more likely to receive each of the components of a postpartum check-up. Older women (age 35–49) and women having births of order six and above were less likely than other women to have received an abdominal examination and advice on breastfeeding and baby care. Younger women (age less than 20), women having their first birth, and women with no or only one antenatal check-up were less likely than other women to receive advice on family planning. Notably, mothers received advice about family planning during postpartum check-ups for only 14 percent of first births, although these women are particularly likely to need advice on birth spacing and contraception. Even among births attended by health professionals, advice on family planning was given to only one-third of mothers who had a postpartum check- up. Women belonging to other backward classes were more likely than women in any other caste/tribe category to receive each component of postpartum care and Hindu women were more likely to receive each component of postpartum care than Muslim women. Postpartum Complications Every woman who had a birth in the three years preceding the survey was asked if she had massive vaginal bleeding or a very high fever—both symptoms of possible postpartum complications—at any time during the two months after delivery (Table 8.12). Mothers in India reported massive vaginal bleeding for 11 percent of births and a very high fever in the postpartum period for 13 percent of births. Both complications were slightly more common among rural than urban mothers. While the likelihood of massive vaginal bleeding did not vary much by mother’s age and birth order, very high fever was somewhat more likely to be reported for births to older mothers (age 35–49) and for births at higher orders (four or above). The likelihood of having massive vaginal bleeding did not vary much by place of delivery and assistance during delivery. The only exceptions are in the case of the few deliveries that took place in NGO or trust hospitals/clinics (which had a relatively low likelihood of being followed by massive vaginal bleeding) and the few that were delivered by a health professional other than a doctor, auxiliary nurse midwife, nurse, midwife, or lady health visitor (which had a lower likelihood of being followed by massive vaginal bleeding). Mothers of births delivered in their own home or in their parents’ home were more likely, however, to have had a very high fever in the postpartum period (14 percent) than were mothers of births delivered elsewhere (11 percent or less). 304 8.4 Summary of Maternal Care Indicators by State Table 8.13 shows five different maternal care indicators for births during the three years preceding the survey by state. These indicators together summarize the extent to which different states have progressed towards achieving safe motherhood goals at all three stages of the birth process: antenatal, delivery, and postnatal. The first indicator is a summary antenatal care indicator which shows the percentage of births whose mothers received all of the following: three or more antenatal check-ups (with the first check-up within the first trimester of pregnancy), two or more tetanus toxoid injections, and iron and folic acid tablets or syrup for three or more months. The next two indicators pertain to care during delivery and show the percentage of births delivered in medical institutions and deliveries assisted by a health professional. The last two Table 8.12 Symptoms of postpartum complications Among births during the three years preceding the survey, the percentage for which the mother had massive vaginal bleeding or very high fever within two months after the delivery by selected background characteristics, India, 1998–99 Background characteristic Massive vaginal bleeding Very high fever Number of births Residence Urban Rural Mother’s age at birth < 20 20–34 35–49 Birth order 1 2–3 4–5 6+ Place of delivery Public health facility NGO or trust hospital/clinic Private health facility Own home Parents’ home Other1 Assistance during delivery Doctor ANM/nurse/midwife/LHV Other health professional Dai (TBA) Other1 Total 9.3 10.0 6,888 11.4 13.4 24,014 12.2 13.3 7,311 10.5 12.3 22,329 11.2 15.9 1,262 11.8 11.4 8,952 10.5 11.8 13,434 10.9 14.6 5,395 10.5 16.4 3,121 11.1 10.4 5,016 7.3 11.1 220 10.6 9.4 5,185 10.9 14.3 16,410 11.9 13.6 3,754 8.4 8.1 316 11.5 10.3 9,365 9.5 11.3 3,534 18.1 21.5 188 11.3 14.0 10,780 10.3 14.2 7,035 11.0 12.6 30,902 Note: Table includes only the two most recent births during the 2–35 months preceding the survey. NGO: Nongovernmental organization; ANM: Auxiliary nurse midwife; LHV: Lady health visitor; TBA: Traditional birth attendant 1Includes missing 305 indicators pertain to postnatal care and show the percentage of noninstitutional deliveries with a postpartum check-up within two months of birth and within two days of birth. For India as a whole, mothers of only 20 percent of births received all of the required components of antenatal care. This indicator ranges from a high of 65 percent in Kerala and 61 percent in Goa to a low of only 4 percent in Uttar Pradesh. Other states that perform almost as poorly as Uttar Pradesh on this indicator include Bihar, Rajasthan, and Nagaland, where only 6–9 Table 8.13 Maternal care indicators by state Maternal care indicators for births during the three years preceding the survey by state, India, 1998–99 State Percentage who received all recommended types of antenatal care1 Percentage of births delivered in a medical institution Percentage of deliveries assisted by a health professional2 Percentage of non- institutional deliveries with a postpartum check-up within two months of birth3 Percentage of non- institutional deliveries with a postpartum check-up within two days of birth3 India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 20.0 33.6 42.3 16.5 2.3 32.8 59.1 65.9 19.5 2.1 20.8 22.4 42.0 15.7 2.5 30.2 28.9 40.2 21.2 2.9 30.7 35.6 42.4 27.6 1.1 31.7 37.5 62.6 20.3 5.7 8.3 21.5 35.8 6.4 0.5 10.9 20.1 29.7 10.0 0.5 4.4 15.5 22.4 7.2 1.5 6.4 14.6 23.4 10.0 1.4 21.4 22.6 33.4 19.2 2.2 19.7 40.1 44.2 31.6 7.1 17.3 31.2 31.9 10.5 0.3 15.8 17.6 21.4 25.5 0.5 18.3 34.5 53.9 27.1 1.4 10.4 17.3 20.6 20.8 0.0 13.5 57.7 67.5 20.9 0.9 8.9 12.1 32.8 4.3 0.0 15.3 31.5 35.1 38.0 0.7 60.6 90.8 90.8 41.0 6.9 25.0 46.3 53.5 10.4 1.6 31.0 52.6 59.4 29.8 6.9 35.6 49.8 65.2 44.9 1.6 41.5 51.1 59.1 35.3 3.6 64.9 93.0 94.0 27.4 7.5 50.8 79.3 83.8 53.0 10.1 Note: Table includes only the two most recent births during the three years preceding the survey. 1Three or more antenatal check-ups (with the first check-up within the first trimester of pregnancy), two or more tetanus toxoid injections, and iron and folic acid tablets or syrup for three or more months 2Doctor, auxiliary nurse midwife, nurse, midwife, lady health visitor, or other health professional 3Based on births in the 2–35 months preceding the survey 306 percent of women received the required components of antenatal care. Kerala, followed closely by Goa, also outperform all other states in terms of delivery care, with over 90 percent of deliveries taking place in medical institutions and a similarly high percentage of deliveries assisted by a health professional (Figure 8.5). Tamil Nadu, with 79 percent of births delivered in medical institutions and 84 percent of deliveries assisted by a health professional, ranks third among the states on these delivery care indicators. By contrast, in Nagaland, Bihar, and Uttar Pradesh, only 12–16 percent of births were delivered in medical institutions and in Meghalaya, Assam, Uttar Pradesh, and Bihar, only 21–23 percent of deliveries were assisted by a health professional. Tamil Nadu, with 53 percent of noninstitutional deliveries with a postpartum check-up within two months of birth and 10 percent within two days, tops the list of states with regard to both of the postnatal care indicators. What is particularly notable, however, is the poor performance of almost all states on the two indicators of postpartum care, both in absolute terms as well as relative to their performance on the antenatal care and delivery care indicators. There is no state other than Tamil Nadu where more than half of the noninstitutional deliveries in the three years preceding the survey were followed by a postpartum check-up within two months, and there are only six states where this percentage was 30–45 percent. In 19 states, less than 5 Figure 8.5 Percentage of Deliveries Assisted by a Health Professional by State 0 10 20 30 40 50 60 70 80 90 100 Kerala Goa Tamil Nadu Mizoram Delhi Andhra Pradesh Punjab Maharashtra Karnataka Manipur Gujarat West Bengal Jammu & Kashmir INDIA Haryana Himachal Pradesh Rajasthan Sikkim Orissa Nagaland Arunachal Pradesh Madhya Pradesh Bihar Uttar Pradesh Assam Meghalaya Percent NFHS-2, India, 1998–99 307 percent of noninstitutional deliveries were followed by a postpartum check within two days, including 2 states where the percentage receiving such check-ups was zero. An examination of the performance of each state on the different safe motherhood indicators shows that several states consistently perform well below the national average on each of the five indicators. This list includes Arunachal Pradesh, Bihar, Madhya Pradesh, Nagaland, Rajasthan, and Uttar Pradesh. Assam, Meghalaya, and Sikkim also perform poorly on the indicators although the percentage of noninstitutional deliveries with a postpartum check-up within two months after birth in these states is higher than the national average. Haryana, Himachal Pradesh, and Orissa perform poorly on one or both of the delivery care indicators, whereas Mizoram performs much better on the delivery care indicators than it does on the other indicators. Gujarat performs particularly poorly on the provision of postpartum care but performs above the national average on the other indicators. Nonetheless, in Gujarat, the mothers of only 25 percent of births received all the recommended components of antenatal care. Between NFHS–1 and NFHS–2, the percentage of births delivered in a health institution and the percentage of deliveries assisted by a health professional increased in every state except Meghalaya. 8.5 Reproductive Health Problems Absence of reproductive tract infections (RTIs) is essential for the reproductive health of both women and men and is critical for their ability to meet their reproductive goals. There are three different types of reproductive tract infections for women: endogenous infections that are caused by the multiplying of organisms normally present in the vagina; iatrogenic infections caused by the introduction of bacteria or other infection-causing micro-organisms through medical procedures such as an IUD insertion; and sexually transmitted infections (STIs). Endogenous infections and several of the iatrogenic and sexually transmitted infections are often easily cured if detected early and given proper treatment. If left untreated, RTIs can cause pregnancy-related complications, congenital infections, infertility, and chronic pain. They are also a risk factor for pelvic inflammatory disease and HIV (Population Council, 1999). A number of studies (Bang et al., 1989; Bang and Bang, 1991; Pachauri and Gittlesohn, 1994; Jeejeebhoy and Rama Rao, 1992) have shown that many Indian women suffer from RTIs. Several researchers have also shown that women in India often bear the symptoms of RTIs silently without seeking health care. RTIs and their sequellae are an important component of programmes for family planning, child survival, women’s health, safe motherhood, and HIV prevention. RTIs have profound implications for the success of each of these initiatives, and conversely, these initiatives provide a critical opportunity for the prevention and control of RTIs (Germain et al., 1992). Studies have demonstrated that RTIs are an important reason for the poor acceptance and low continuation rates of contraceptive methods such as the IUD. Bhatia and Cleland (1995) found a higher incidence of gynaecological symptoms among women who had undergone a tubectomy than among other women. The Government of India recognized the importance of RTIs and STIs in undermining the health and welfare of individuals and couples in a policy statement on the Reproductive and Child Health Programme, which states that couples should be ‘able to have sexual relations free of fear of pregnancy and contracting diseases’ (Ministry of Health and Family Welfare, 1997:2). The Reproductive and Child Health Programme includes the following relevant interventions: establishment of RTI/STI clinics at district hospitals (where not already available), provision of technicians for laboratory diagnosis 308 of RTIs/STIs, and in selected districts, screening and treatment of RTIs/STIs (Ministry of Health and Family Welfare, 1997). NFHS-2 collected information from women on some common symptoms of RTIs, namely problems with abnormal vaginal discharge or urinary tract infections in the three months preceding the survey, and intercourse-related pain (often) and bleeding (ever). Specifically, the prevalence of reproductive health problems among ever-married women is estimated from women’s self-reported experience with each of the following problems: vaginal discharge accompanied by itching, by irritation around the vaginal area, by bad odour, by severe lower abdominal pain, by fever, or by any other problem; pain or burning while urinating or frequent or difficult urination; and (among currently married women only) painful intercourse or bleeding after intercourse. Women who experience one or more of these reproductive health problems could either have or be at risk of getting an RTI/STI. However, since information on health problems is based on self-reports rather than clinical tests or examinations, the results should be interpreted with caution. Table 8.14 shows the prevalence of different reproductive health problems among women in India during the three months preceding the survey by background characteristics. Thirty percent of ever-married women report at least one type of problem related to vaginal discharge, and 18 percent report symptoms of a urinary tract infection. Overall, 36 percent of women report either problems with vaginal discharge or symptoms of a urinary tract infection. Among problems related to vaginal discharge, severe lower abdominal pain (19 percent) is mentioned most frequently, followed by itching or irritation (17 percent). Since a large majority of ever- married women are also currently married, there is almost no difference in the estimates of prevalence of problems related to vaginal discharge and symptoms of urinary tract infections for currently married women and ever-married women. Table 8.14 and Figure 8.6 show that two out of five currently married women (39 percent) report that they have at least one reproductive health problem. Thirty-six percent have problems with vaginal discharge or urinary tract infections, 13 percent report painful intercourse, and 2 percent report bleeding after intercourse. The prevalence of reproductive health problems by age among currently married women first increases slightly from 38 percent for women age 15–19 to 42 percent for women age 25–34 and then declines to 30 percent for women age 45–49. The prevalence of reproductive health problems varies little between illiterate women (41 percent) and literate women who have completed at most middle school (39–40 percent) but it is lower for women who have completed at least high school (32 percent). Muslim women (49 percent), followed by Buddhist/Neo-Buddhist women (47 percent), are more likely than women of all other religions (with the exception of women who do not belong to any religion) to have reproductive health problems, and Sikh women (28 percent) and Jain women (33 percent) are least likely to have problems. The prevalence of reproductive health problems is slightly higher for scheduled-tribe women (42 percent) than for other women (38–40 percent), and women in households with a medium or low standard of living (40–41 percent) are more likely to have reproductive health problems than women in households with a high standard of living (34 percent). Women who are self-employed (44 percent) are more likely than nonworking women (38 percent), as well as other employed women (40 percent), to have reproductive health problems. Table 8.14 Symptoms of reproductive health problems Percentage of ever-married women reporting abnormal vaginal discharge or symptoms of a urinary tract infection during the three months preceding the survey and percentage of currently married women reporting painful intercourse or bleeding after intercourse by selected background characteristics, India, 1998–99 Ever-married women Vaginal discharge accompanied by: Currently married women Background characteristic Any abnormal vaginal discharge Itching or irritation Bad odour Severe lower ab- dominal pain1 Fever Other problem Symptoms of a urinary tract infec- tion2 Any abnormal vaginal discharge or symptoms of a urinary tract infection2 Number of ever- married women Painful inter- course (often) Bleeding after inter- course (ever)1 Any repro- ductive health problem Number of currently married women Age 15–19 20–24 25–29 30–34 35–39 40–44 45–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion 26.2 14.4 10.2 17.3 7.1 5.8 16.1 32.1 8,182 16.9 3.7 37.9 8,014 29.3 16.7 11.0 18.1 7.4 7.3 17.1 35.0 16,389 15.1 3.0 39.7 15,930 32.5 18.6 12.5 20.5 8.5 9.1 18.3 38.0 17,745 14.0 2.1 41.6 17,055 33.2 18.8 12.8 20.8 9.0 9.8 18.6 38.9 15,094 12.9 2.0 41.9 14,286 32.2 18.9 12.3 20.0 9.5 8.9 18.1 37.5 13,089 10.9 2.2 40.5 12,052 27.3 16.3 10.5 17.0 8.0 7.4 18.0 33.5 10,521 8.4 1.4 35.7 9,363 20.7 12.3 7.5 12.6 5.7 5.6 15.5 27.8 8,179 5.9 1.3 30.3 6,948 27.8 15.9 8.7 16.5 6.3 8.6 15.4 33.1 23,370 11.5 1.8 36.7 21,888 30.4 17.5 12.3 19.3 8.7 7.8 18.4 36.4 65,829 12.9 2.4 40.1 61,761 31.3 18.2 13.0 20.3 9.7 8.5 19.3 37.3 51,871 12.8 2.4 40.8 48,018 30.3 16.9 10.2 18.7 7.5 8.4 17.4 36.2 17,270 13.1 2.2 39.9 16,257 29.1 16.9 10.0 17.0 6.2 7.1 15.1 34.3 7,328 12.7 2.4 38.6 7,073 22.8 13.2 6.7 12.6 3.5 6.1 12.6 28.0 12,719 10.7 1.9 32.4 12,291 28.7 16.6 10.9 17.6 7.7 7.8 16.9 34.3 72,903 11.7 2.2 37.9 68,443 37.2 20.6 14.3 25.4 11.8 10.3 23.2 44.1 11,190 18.5 3.0 48.6 10,477 29.5 14.8 10.1 18.9 5.9 6.6 15.3 35.0 2,263 14.9 2.5 40.0 2,072 22.4 14.7 11.0 13.3 2.0 3.4 9.5 25.7 1,427 7.5 1.5 28.3 1,365 26.2 13.2 6.5 13.2 4.1 6.4 11.4 30.4 331 8.7 0.2 33.1 316 34.6 20.7 11.6 20.5 8.6 11.0 24.5 41.6 676 14.3 2.4 46.8 601 35.0 22.7 14.1 24.3 9.6 6.6 25.6 42.1 285 11.7 1.9 45.2 259 51.5 35.5 30.2 22.6 12.9 12.7 37.2 57.5 44 5.3 0.0 59.0 38 Contd… Table 8.14 Symptoms of reproductive health problems (contd.) Percentage of ever-married women reporting abnormal vaginal discharge or symptoms of a urinary tract infection during the three months preceding the survey and percentage of currently married women reporting painful intercourse or bleeding after intercourse by selected background characteristics, India, 1998–99 Ever-married women Vaginal discharge accompanied by: Currently married women Background characteristic Any abnormal vaginal discharge Itching or irritation Bad odour Severe lower ab- dominal pain1 Fever Other problem Symptoms of a urinary tract infec- tion2 Any abnormal vaginal discharge or symptoms of a urinary tract infection2 Number of ever- married women Painful inter- course (often) Bleeding after inter- course (ever)1 Any repro- ductive health problem Number of currently married women Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Work status Working in family farm/ business Employed by someone else Self-employed Not worked in past 12 months Number of children ever born 0 1 2–3 4–5 6+ All ever-married women All currently married women 30.1 17.2 11.8 18.8 7.8 8.0 17.9 36.1 16,301 13.2 2.1 39.9 15,178 33.4 18.9 14.8 22.3 10.3 7.3 20.4 39.2 7,750 12.6 3.4 42.0 7,176 27.8 16.0 9.9 17.6 7.8 7.7 17.4 33.8 29,383 11.9 2.3 37.7 27,529 30.6 17.7 11.6 18.6 7.9 8.5 17.0 36.1 34,904 12.7 2.1 39.6 32,957 31.2 17.3 12.8 20.7 9.6 8.1 19.5 37.4 29,033 13.5 2.5 41.3 26,505 30.5 17.7 11.5 18.9 8.4 8.3 18.0 36.3 41,289 13.0 2.3 40.1 38,999 25.6 15.3 8.7 14.5 5.0 7.0 13.7 30.6 17,845 10.1 1.7 34.0 17,173 31.3 19.1 12.4 19.4 9.8 8.4 19.3 37.0 12,849 12.0 2.6 40.1 12,062 30.6 16.6 10.7 20.0 9.4 9.0 18.5 36.5 17,571 12.6 2.4 40.4 15,403 32.7 18.4 11.3 20.5 9.6 10.0 19.2 39.2 4,483 14.7 2.3 43.5 3,891 28.8 16.7 11.3 17.8 7.1 7.4 16.8 34.5 54,271 12.5 2.1 38.3 52,269 29.4 16.5 11.0 19.6 7.8 7.2 18.7 35.9 9,807 19.3 4.5 42.5 8,980 26.2 14.6 9.6 15.7 6.1 6.2 14.9 31.5 12,752 12.7 2.1 35.8 11,823 29.7 16.6 10.7 18.5 7.5 8.0 16.8 35.1 35,858 11.8 2.1 38.5 33,861 31.8 18.6 12.8 20.0 9.8 9.1 19.1 37.8 19,743 11.7 2.0 40.6 18,618 30.5 19.5 12.9 18.9 9.6 8.9 19.7 37.2 11,039 10.6 1.7 39.6 10,368 29.7 17.1 11.3 18.6 8.1 8.0 17.6 35.5 89,199 NA NA NA NA 30.0 17.3 11.5 18.7 8.1 8.1 17.8 35.9 83,649 12.5 2.3 39.2 83,649 Note: Total includes women with missing information on education, religion, caste/tribe, the standard of living index, and work status, who are not shown separately. NA: Not applicable 1Not related to menstruation 2Includes pain or burning while urinating or more frequent or difficult urination 311 Women with no children are slightly more likely than women with one or more children to have reproductive health problems. Among women with at least one child, women with two or more children are somewhat more likely to have reproductive health problems (39–41 percent) than are women with only one child (36 percent). Overall, however, the prevalence of reproductive health problems is very similar for women with almost all background characteristics. Notably, with the exception of the much larger variation by religion, prevalence ranges only between 30 percent and 44 percent for all other currently married women. Among women who report any reproductive health problems, almost two-thirds have not seen anyone for advice or treatment (Table 8.15). The proportion of women who have not obtained advice or treatment is higher in rural areas (69 percent) than in urban areas (55 percent). Overall, more than three-quarters of women who have obtained advice or treatment were seen by someone in the private medical sector and less than one-third sought advice or treatment from someone in the public medical sector. Among women who sought advice or treatment, 64 percent saw a private doctor and 22 percent saw a government doctor. A private doctor was seen by 69 percent of these women in urban areas and 62 percent in rural areas, whereas a government doctor was seen by less than one-quarter of both urban women (23 percent) and rural women (21 percent). Reproductive Health Problems by State Table 8.16 shows the prevalence of any reproductive health problem, as well as the prevalence of different types of reproductive health problems, among currently married women by state. Since these prevalence rates are based on self-reports and because the willingness of women to talk about and report reproductive health problems may vary by state, considerable caution should be used in interpreting differences in prevalence between states. Overall, the percentage of currently married women with any reproductive health problem varies from 19 percent in Karnataka to 67 percent in Meghalaya. Other states where more than half of currently married women had at least Figure 8.6 Reproductive Health Problems Among Currently Married Women 39 30 18 13 2 0 5 10 15 20 25 30 35 40 45 Any Reproductive Health Problem TYPE OF PROBLEM Any Abnormal Vaginal Discharge Symptoms of a Urinary Tract Infection Painful Intercourse Bleeding After Intercourse Percent NFHS-2, India, 1998–99 312 one reproductive health problem are Jammu and Kashmir, Manipur, Mizoram, and Assam. In all but five states, at least one-third of women report one or more reproductive health problems. In all states, women are much more likely to report problems with vaginal discharge than to report symptoms of a urinary tract infection or problems related to intercourse. Nonetheless, there is substantial variation by state in the prevalence of each of these different reproductive health problems. The percentage of currently married women with any abnormal vaginal discharge ranges from 14 percent in Karnataka to 64 percent in Meghalaya; the percentage with symptoms of a urinary tract infection ranges from 7 percent in Karnataka to 31 percent in Jammu and Kashmir; the percentage who often experience painful intercourse ranges from 3 percent in Karnataka to 22 percent in Jammu and Kashmir; and the percentage who ever experienced bleeding after intercourse ranges from 0.3 percent in Karnataka to 5 percent in Nagaland. The states where the prevalence of all four kinds of reproductive health problems is consistently high are Jammu and Kashmir, Madhya Pradesh, Andhra Pradesh, and all the northeastern states except Arunachal Pradesh and Mizoram. Jammu and Kashmir has high levels of all the reproductive health problems except bleeding after intercourse. Prevalence of all of the different reproductive health problems is lowest in Karnataka. Other states where the reported prevalence of Table 8.15 Treatment of reproductive health problems Among women with a reproductive health problem, the percentage who sought advice or treatment from specific providers by residence, India, 1998–99 Provider Urban Rural Total Public medical sector Government doctor Public health nurse ANM/LHV Male MPW/supervisior Anganwadi worker Village health guide Other public medical sector NGO worker Private medical sector Private doctor Private nurse Compounder/pharmacist Vaid/hakim/homeopath Dai (TBA) Traditional healer Other private medical sector Other None Number of women 12.0 10.0 10.5 10.2 6.7 7.5 0.4 0.8 0.7 1.0 1.9 1.7 0.0 0.1 0.1 0.0 0.1 0.1 0.0 0.1 0.1 0.4 0.2 0.3 0.2 0.1 0.1 35.6 24.1 26.9 30.9 19.3 22.2 1.4 1.1 1.2 0.3 0.3 0.3 2.2 1.9 2.0 0.3 0.5 0.5 0.3 0.7 0.6 0.1 0.3 0.3 0.9 1.2 1.1 55.3 68.8 65.5 8,462 25,989 34,451 Note: Table includes currently married women who report abnormal vaginal discharge, symptoms of a urinary tract infection, painful intercourse or bleeding after intercourse and women who are ever married but not currently married who report abnormal vaginal discharge or symptoms of a urinary tract infection. Percentages add to more than 100.0 because women could report treatment from multiple providers. ANM: Auxiliary nurse midwife; LHV: Lady health visitor; MPW: Multipurpose health worker; NGO: Nongovernmental organization; TBA: Traditional birth attendant 313 reproductive health problems is consistently low are Gujarat, Orissa, Punjab, Tamil Nadu, and Himachal Pradesh. In summary, NFHS-2 results show that although more than one-third of ever-married women in India report at least one reproductive health problem related to vaginal discharge or urination, and two-fifths of currently married women report at least one reproductive health problem related to vaginal discharge, urination, or intercourse that could be symptomatic of a more serious reproductive tract infection, the majority of them bear the problems silently without Table 8.16 Symptoms of reproductive tract infections by state Percentage of currently married women reporting various symptoms of reproductive tract infections by state, India, 1998–99 State Percentage with any abnormal vaginal discharge Percentage with symptoms of a urinary tract infection1 Percentage with any abnormal vaginal discharge or symptoms of a urinary tract infection1 Percentage with painful intercourse (often) Percentage with bleeding after intercourse (ever)2 Percentage with any reproductive health problem India North Delhi Haryana Himachal Pradesh Jammu & Kashmir Punjab Rajasthan Central Madhya Pradesh Uttar Pradesh East Bihar Orissa West Bengal Northeast Arunachal Pradesh Assam Manipur Meghalaya Mizoram Nagaland Sikkim West Goa Gujarat Maharashtra South Andhra Pradesh Karnataka Kerala Tamil Nadu 30.0 17.8 35.9 12.5 2.3 39.2 29.9 13.9 34.0 9.3 1.3 36.5 32.2 12.6 35.9 8.3 1.0 38.2 26.5 14.3 30.8 8.6 0.7 33.7 50.5 31.0 56.5 21.7 2.3 60.5 23.9 8.5 26.3 5.6 0.9 28.3 36.8 19.1 41.3 11.1 1.8 43.2 34.8 22.5 41.2 16.7 4.2 44.9 28.0 17.9 33.9 16.4 2.4 38.1 33.7 25.7 42.2 11.4 2.4 44.2 18.2 11.0 22.9 11.0 1.9 27.5 35.8 18.4 41.8 14.6 1.9 45.3 29.5 23.6 39.8 10.5 1.3 42.1 41.2 20.6 47.3 14.7 4.1 50.6 41.3 29.5 51.7 19.8 3.2 56.0 64.2 24.5 66.2 20.2 3.6 66.9 44.7 21.6 50.7 10.7 2.0 52.5 40.8 24.4 44.4 20.3 4.6 45.6 37.5 20.1 44.5 14.0 3.1 48.6 26.2 17.4 35.3 11.3 1.0 40.2 23.0 10.3 26.3 6.9 1.6 28.6 30.7 20.1 37.1 10.4 1.8 40.0 38.2 18.8 44.0 16.9 2.9 48.5 13.5 7.2 17.7 2.7 0.3 18.8 26.3 19.8 35.7 16.8 3.7 42.4 18.6 12.3 24.2 8.5 2.2 27.8 1Includes pain or burning while urinating or more frequent or difficult urination 2Not related to menstruation 314 seeking advice or treatment. There does not appear to be any systematic variation in reports of reproductive health problems by the level of development of the state: women in both less developed and more developed states report a high prevalence of at least one reproductive health problem. Given the silence that surrounds reproductive health problems, this consistently high self-reported prevalence suggests that reproductive health problems are widespread among all groups of women and in almost all states. Moreover, women who seek advice or treatment for reproductive health problems do not usually go to government health professionals. These findings highlight the need to educate women regarding the symptoms and consequences of reproductive health problems and the urgent need to expand counselling and reproductive health services in both rural and urban areas, particularly through the public sector. CHAPTER 9 QUALITY OF CARE The historic International Conference on Population and Development in Cairo in 1994 brought about a paradigm shift in population-related policies. The conference helped focus the attention of governments on making programmes more client-oriented with an emphasis on the quality of services and care. In line with the conference recommendations, the Government of India acknowledged the need to abandon the use of targets for monitoring its family welfare programme. It recognized that the top-down target approach does not reflect user needs and preferences and de-emphasizes the quality of care provided (Ministry of Health and Family Welfare, 1998b). Recent research on the different aspects of service delivery, especially at the grass-roots level, including programme coverage, client-provider interactions, and informed choice, also endorses the need to take a different approach to meeting the reproductive and health needs of the Indian population (Koenig and Khan, 1999). This research suggests that inadequate attention to the quality of care has contributed to the inability of the government’s family welfare programme to meet its goals. In 1996, the existing family welfare programme was transformed into the new Reproductive and Child Health (RCH) Programme. This new programme integrates all family welfare and women and child health services with the explicit objective of providing beneficiaries with ‘need based, client centred, demand driven, high quality integrated RCH services’ (Ministry of Health and Family Welfare, 1998b:6). The strategy for the RCH Programme shifts the policy emphasis from achieving demographic targets to meeting the reproductive needs of individual clients (Ministry of Health and Family Welfare, 1996). NFHS-2 included several questions on the quality of care of health and family welfare services provided in the public sector and the private sector. In this chapter, sources of health care for households are described first. The chapter then examines different aspects of home visits by health and family planning workers and visits by respondents to health facilities, including frequency, source, and quality for each state and for all-India. Finally, information is presented on state differentials in the quality of care for family planning services. 9.1 Source of Health Care for Households To examine the role of different health providers in meeting the health-care needs of households, the NFHS-2 Household Questionnaire included the question, ‘When members of your household get sick, where do they generally go for treatment?’ Table 9.1 shows the use of services from various types of health providers. More than two-thirds of households (69 percent) normally use the private medical sector when a household member gets sick. Only 29 percent normally use public-sector medical services. Reliance on the private medical sector is higher in urban areas than in rural areas. In the public medical sector, hospitals are the most popular source of health care, whereas in the private medical sector, private doctors are visited slightly more often than hospitals for health care. Use of health-care services is strongly influenced by the standard of living of the household. As the standard of living increases, use of private-sector services increases. Seventy- 316 nine percent of households with a high standard of living use the private medical sector compared with 63 percent of households with a low standard of living. Yet, even among households with a low standard of living, only one-third typically use public-sector services for their health care. 9.2 Contacts at Home with Health and Family Planning Workers Under the family welfare programme, health or family planning workers are required to regularly visit each household in their assigned area. During these contacts the female health or family planning worker is required to monitor various aspects of the health of women and children, provide information related to health and family planning, counsel and motivate women to adopt appropriate health and family planning practices, and deliver other selected services. These contacts are also important for enhancing the credibility of services and establishing necessary rapport with the clients. Only 13 percent of women in India, however, report that they received a Table 9.1 Source of health care Percent distribution of households by main source of health care when household members get sick, according to residence and the standard of living index, India, 1998–99 Residence Standard of living index Source Urban Rural Low Medium High Total Public medical sector Government/municipal hospital Government dispensary UHC/UHP/UFWC CHC/rural hospital/PHC Sub-centre Government mobile clinic Government paramedic Other public medical sector NGO or trust Hospital/clinic NGO worker Private medical sector Private hospital/clinic Private doctor Private mobile clinic Private paramedic Vaidya/hakim /homeopath Traditional healer Pharmacy/drugstore Dai (TBA) Other private medical sector Other source Shop Home treatment Other Total percent Number of households 23.5 30.6 34.0 28.3 19.0 28.7 17.0 11.3 13.5 13.2 10.9 12.9 1.3 1.4 1.1 1.5 1.5 1.3 0.9 0.2 0.3 0.5 0.4 0.4 2.6 15.4 16.7 11.0 4.5 11.9 0.1 1.9 2.0 1.4 0.4 1.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.0 0.1 1.5 0.3 0.3 0.7 1.3 0.6 0.8 0.6 0.7 0.6 0.8 0.7 0.8 0.6 0.6 0.6 0.8 0.6 0.0 0.0 0.1 0.0 0.0 0.0 74.8 66.2 62.5 69.3 78.8 68.6 34.1 27.3 24.0 30.0 37.8 29.2 38.4 35.0 33.7 36.3 38.7 35.9 0.2 0.2 0.2 0.1 0.2 0.2 0.3 1.0 1.0 0.7 0.5 0.8 1.1 1.1 1.2 0.9 1.1 1.1 0.0 0.6 0.7 0.4 0.1 0.4 0.3 0.3 0.3 0.3 0.1 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.9 1.3 0.5 0.3 0.8 1.0 2.5 2.8 1.7 1.3 2.1 0.3 0.3 0.5 0.3 0.2 0.3 0.5 0.4 0.4 0.3 0.7 0.4 0.2 1.8 1.9 1.2 0.5 1.3 100.0 100.0 100.0 100.0 100.0 100.0 25,243 65,953 33,064 40,434 16,640 91,196 Note: Total includes 1,057 households with missing information on the standard of living index, which are not shown separately. UHC: Urban health centre; UHP: Urban health post; UFWC: Urban family welfare centre; CHC: Community health centre; PHC: Primary Health Centre; NGO: Nongovernmental organization; TBA: Traditional birth attendant 317 home visit from a health or family planning worker during the 12 months preceding the survey (Table 9.2). Differentials in home visits by background characteristics are generally small. In fact, among all the subgroups shown in Table 9.2, there is no group in which more than one-fifth of women received a home visit from a health or family planning worker in the 12 months preceding the survey. Younger women are slightly more likely to report a home visit than are older women. Rural women (14 percent) are more likely than urban women (10 percent) to have had a home visit from a health or family planning worker. Women who have a moderate level of education were more likely to have a home visit than women who are illiterate or have completed at least high school. The likelihood of a home visit from a health or family planning worker decreases as the standard of living of the household increases. Only 2 percent of Sikh women received a home visit, whereas between 11 to 19 percent of women belonging to all the other religions reported a home visit during the past 12 months. Home visits are more common among scheduled-tribe women than among scheduled-caste or other backward class women and least common among other women. Women without any children are least likely and women with one child are most likely to receive a home visit. As the number of children increases the likelihood of a home visit declines. Home visits are slightly less common for nonusers of contraception than for users. Women who reported a home visit from a health or family planning worker during the 12 months preceding the survey were asked the frequency of the visits during the past 12 months and the number of months since the most recent visit. These women, on average, received three home visits during the year with the median duration since the last visit of 1.8 months (Table 9.2). The median number of home visits and the duration since the last visit do not vary substantially according to the background characteristics measured, except for religion. For example, the median number of home visits reported by Sikh women is less than two compared with five reported by women belonging to ‘other’ religions. Similarly, the median duration since the visit was 3.2 months for Sikh women and only 1.1 months for women belonging to ‘other’ religions. These results should be interpreted carefully because of the small sample size of these groups. Nevertheless, although some groups are much more likely to be visited by a health or family planning worker than others, among women who were visited the frequency of visits does not vary widely. 9.3 Quality of Home Visits The quality of the care provided during home visits can be assessed in terms of client satisfaction with the services received during the visit. Each woman who reported that a health or family planning worker had visited her during the 12 months preceding the survey was asked about the quality of care received. Questions were asked with reference only to the most recent home visit. The questions covered how the worker talked to the woman during the visit and whether the worker spent enough time with her. Table 9.3 provides this information by the type of services received and whether the worker was from the private or public sector. Public-sector health or family planning workers provided almost all recent home visits (96 percent). A large majority of women who were visited at home (82 percent) reported that they received services related to health; only 11 percent reported that they received family planning services. 318 Table 9.2 Home visits by a health or family planning worker Percentage of ever-married women who had at least one home visit by a health or family planning worker in the 12 months preceding the survey and, among women who had home visits, median number of visits and median number of months since the most recent visit by selected background characteristics, India, 1998–99 Background characteristic Percent- age with at least one visit Number of women Median number of visits1 Median months since the most recent visit1 Number of women with home visit Age 15–24 25–34 35–49 Residence Urban Rural Education Illiterate Literate, < middle school complete Middle school complete High school complete and above Religion Hindu Muslim Christian Sikh Jain Buddhist/Neo-Buddhist Other No religion Caste/tribe Scheduled caste Scheduled tribe Other backward class Other Standard of living index Low Medium High Number of children ever born 0 1 2 3 4 5+ Family planning status Sterilized Using method other than sterilization Nonuser Total 16.5 24,571 2.6 1.7 4,054 14.0 32,839 2.7 1.8 4,599 9.1 31,789 3.0 1.8 2,909 10.0 23,370 2.6 2.0 2,338 14.0 65,829 2.8 1.7 9,223 11.5 51,871 2.8 1.7 5,961 15.9 17,270 2.7 1.8 2,747 17.0 7,328 2.7 1.9 1,246 12.6 12,719 2.4 1.9 1,606 13.3 72,903 2.8 1.7 9,709 11.3 11,190 2.3 2.1 1,262 15.1 2,263 2.4 2.1 343 1.7 1,427 (1.7) (3.2) 24 12.0 331 (2.0) (2.7) 40 17.4 676 2.3 1.9 118 18.7 285 (4.5) (1.1) 53 12.4 44 * * 5 13.4 16,301 2.8 1.6 2,189 17.9 7,750 3.3 1.5 1,386 13.6 29,383 2.8 1.8 4,004 11.3 34,904 2.5 1.9 3,931 14.2 29,033 2.8 1.7 4,114 13.3 41,289 2.8 1.8 5,498 10.3 17,845 2.6 1.9 1,845 7.0 9,807 2.4 1.6 686 17.3 12,752 2.6 1.8 2,211 15.8 18,720 2.6 1.8 2,955 14.0 17,139 2.9 1.8 2,401 12.1 12,116 2.8 1.8 1,469 9.9 18,666 2.9 1.7 1,841 14.1 30,167 3.0 1.7 4,251 14.2 10,160 2.6 1.8 1,439 12.0 48,872 2.6 1.8 5,872 13.0 89,199 2.7 1.8 11,561 Note: Total includes women with missing information on education, religion, caste/tribe, and the standard of living index, who are not shown separately. ( ) Based on 25–49 unweighted cases *Median not shown; based on fewer than 25 unweighted cases 1For women who received at least one visit Table 9.3 Quality of home visits Quality of care indicators for the most recent home visit by a health or family planning worker during the 12 months preceding the survey, according to type of worker and type of services received during the visit, India, 1998–99 Type of worker and type of services received Public-sector worker Private-sector/NGO/trust worker Total Quality indicator Family planning Health Family planning or health Neither family planning nor health Family planning Health Family planning or health Neither family planning nor health Family planning Health Family planning or health Neither family planning nor health Percentage who said worker spent enough time with them Percentage who said worker talked to them: Nicely Somewhat nicely Not nicely Missing Total percent Number of women visited at home 89.7 90.4 90.2 85.8 * 92.9 91.9 * 89.4 90.5 90.2 85.9 77.4 79.0 78.9 77.6 * 69.8 69.8 * 77.0 78.6 78.6 77.3 21.4 19.3 19.4 18.8 * 27.6 27.2 * 21.7 19.7 19.7 19.2 1.2 1.6 1.6 3.6 * 2.0 2.4 * 1.3 1.6 1.6 3.6 0.0 0.1 0.0 0.0 * 0.6 0.6 * 0.0 0.1 0.1 0.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1,258 8,919 9,636 1,326 25 393 405 19 1,284 9,312 10,041 1,345 Note: Cases where the source of service was neither the public sector nor the private sector/NGO/trust are excluded from the table. *Percentage not shown; based on fewer than 25 unweighted cases NGO: Nongovernmental organization 320 Irrespective of the type of service received, 90 percent of the women who received health or family planning services at home were satisfied that the worker had spent enough time with them. The proportion of women satisfied with the time the worker spent with them was slightly lower for visits by a public-sector health or family planning worker (90 percent) than a private- sector worker (92 percent). In general, women had only a few complaints about the way that the worker talked to them. About four-fifths (79 percent) of the women who received family planning or health services reported that the worker talked to them nicely; and less than 2 percent said that the worker did not talk to them nicely. A higher proportion of women who received the services from the public sector (79 percent) than from the private sector (70 percent) reported that the worker talked to them nicely. 9.4 Matters Discussed during Home Visits or Visits to Health Facilities Women who were visited at home by a health or family planning worker, as well as those who visited a health facility during the 12 months preceding the survey, were asked about the different topics discussed with the workers during any of these visits. Table 9.4 shows the percentage of women who discussed specific topics during all home visits or visits to a health facility during the past 12 months. The major focus of home visits was immunization and treatment of health problems. In addition, 21 percent of women reported that childcare was discussed, 15 percent mentioned that family planning was discussed, 14 percent discussed disease prevention, and 11 percent reported having discussions about antenatal care during home visits. Although family planning is not often discussed during a home visit, discussions about family planning are more common for women who were pregnant or had children under age three years than for other women. Eighteen percent of these women mentioned having discussions about family planning during home visits. Women who were pregnant or women with children under age three were also much more likely than other women to have talked about immunizations and somewhat more likely to have talked about antenatal, delivery, postpartum, and childcare, but less likely to have discussed health problems or disease prevention. Visits to health facilities are largely for treatment of health problems (66 perc