The statistic displays the literacy rate in Punjab in India between 1991 and 2011, broken down by gender. In 2001, ** percent of the female population in Punjab knew how to read or write. India's literacy rate from 1981 through 2011 can be found here.
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Literacy Rate: Punjab data was reported at 75.800 % in 12-01-2011. This records an increase from the previous number of 69.650 % for 12-01-2001. Literacy Rate: Punjab data is updated decadal, averaging 58.510 % from Dec 1971 (Median) to 12-01-2011, with 5 observations. The data reached an all-time high of 75.800 % in 12-01-2011 and a record low of 34.120 % in 12-01-1971. Literacy Rate: Punjab data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Education Sector – Table IN.EDA001: Literacy Rate.
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The catalog contains the data related to Number of Scheduled Castes Population (male, female and total), Scheduled Castes as percentage to total population, Number of Literate Scheduled Castes and percentage Literacy of male, female and total in Punjab.
Literacy Ratio by District, The Punjab 1998 and 2017 Censuses (Percentage)
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Literacy Rate: Punjab在12-01-2011达75.800%,相较于12-01-2001的69.650%有所增长。Literacy Rate: Punjab数据按decadal更新,12-01-1971至12-01-2011期间平均值为58.510%,共5份观测结果。该数据的历史最高值出现于12-01-2011,达75.800%,而历史最低值则出现于12-01-1971,为34.120%。CEIC提供的Literacy Rate: Punjab数据处于定期更新的状态,数据来源于Office of the Registrar General & Census Commissioner, India,数据归类于India Premium Database的Education Sector – Table IN.EDA001: Literacy Rate。
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The catalog contains the data related to the number of convicts by age, sex and literacy in Punjab
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Census: Population: Punjab: Amritsar Cantt: Male data was reported at 6,255.000 Person in 03-01-2011. This records a decrease from the previous number of 7,621.000 Person for 03-01-2001. Census: Population: Punjab: Amritsar Cantt: Male data is updated decadal, averaging 5,695.500 Person from Mar 1961 (Median) to 03-01-2011, with 6 observations. The data reached an all-time high of 7,621.000 Person in 03-01-2001 and a record low of 1,722.000 Person in 03-01-1971. Census: Population: Punjab: Amritsar Cantt: Male data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAC029: Census: Population: By Towns and Urban Agglomerations: Punjab.
The PSLM Project is designed to provide Social & Economic indicators in the alternate years at provincial and district levels. The project was initiated in July 2004 and will continue up to June 2015. The data generated through surveys is used to assist the government In formulating the poverty reduction strategy as well as development plans at district level and for the rapid assessment of program in the overall context of MDGs. As such this survey is one of the main mechanisms for monitoring MDGs indicators. It provides a set of representative, population-based estimates of social indicators and their progress under the PRSP/MDGs. For Millennium Development Goals (MDGs), UN has set 18 targets for 48 indicators for its member countries to achieve by 2015. Pakistan has committed to implement 16 targets and 37 indicators out of which 6 targets and 13 indicators are monitored through PSLM Surveys. The PSLM surveys are conducted at district level and at Provincial level respectively at alternate years. PSLM District level survey collects information on key Social indicators whereas through provincial level surveys (Social & HIES) collects information on social indicators as well as on Income and Consumption while in specific sections also information is also collected about household size; the number of employed people and their employment status, main sources of income; consumption patterns; the level of savings; and the consumption of the major food items. However, Planning Commission also uses this data for Poverty analysis.
Another important objective of the PSLM Survey is to try to establish the distributional impact of development programs; whether the poor have benefited from the program or whether increased government expenditure on the social sectors has been captured by the better off. The sample size of PSLM surveys district level is approximately 80000 households and approximately 18000 at Provincial level.
Main Indicators: Indicators on Demographic characteristics, Education, Health, Employment, Household Assets, Household Amenities, Population Welfare and Water Supply & Sanitation are developed at National/Provincial /District levels.
National coverage
Households and Individuals
The universe of this survey consists of all urban and rural areas of all four provinces, AJK and Gilgit Baltistan. FATA and Military restricted areas have been excluded from the scope of the survey.
Sample survey data [ssd]
Sampling Frame: Pakistan Bureau of statistics PBS has developed its own urban area frame. Each city/town is divided into enumeration blocks. Each enumeration block is comprised to 200-250 households on the average with well-defined boundaries and maps .The list of enumeration blocks as updated from field on the prescribed Performa by Quick Count Technique in 2013 for urban and the list of villages/mouzas/dehs or its part (block), updated during House listing in 2011 for conduct of Population Census, are taken as sampling frame. Enumeration blocks and villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively. A project to update the rural blocks is currently in hand.
Stratification Plan
Urban Areas: Large sized cities having population five laces and above have been treated as independent stratum. Each of these cities has further been sub-stratified into low, middle and high income groups. The remaining cities/towns within each defunct administrative division have been grouped together to constitute an independent stratum.
Rural Areas: The entire rural domain of a district for Khyber Pakhtunkhwa, Punjab, and Sindh provinces has been considered as independent stratum, whereas in Balochistan province defunct administrative division has been treated as stratum.
Sample Size and its Allocation: To determine optimum sample size for this survey, 6 indicators namely Literacy rate, Net enrolment rate at primary level, Population 10+ that ever attended school, Contraceptive prevalence of women age 15-49 years, Children age 12-23 months who are fully immunized and post natal consultation for ever married women aged 15-49 years were taken into consideration. Keeping in view the prevalence of these indicators at different margin of errors, reliability of estimates and field resources available a sample of size 19620 households distributed over 1368 PSUs (567 urban and 801 rural) has been considered sufficient to produce reliable estimates in respect of all four provinces with urban rural breakdown, however data was collected from 1307 PSU’S by covering 17989 household.
Sample Design: A two-stage stratified sample design has been adopted for this survey.
Selection of primary sampling Units (PSUs): Enumeration blocks in urban and rural domains have been taken as PSUs. In urban and rural domains sample PSUs from each stratum have been selected by PPS method of sampling scheme; using households in each block as Measure of size (MOS).
Selection of Secondary Sampling Units (SSUs): Households within PSU have been considered as SSUs. 16 and 12 households have been selected from urban/rural domains respectively by systematic sampling scheme with a random start.
Out of 1368 PSUs, of all four provinces 61 PSUs (11 urban and 50 rural PSUs) of Balochistan were dropped due to bad law and order situation and the remaining 1307 PSUs (556 urban and 751 rural) comprising 17989 households were covered.
Computer Assisted Personal Interview [capi]
At both individual and household level, the PSLM Survey collects information on a wide range of topics using an integrated questionnaire. The questionnaire comprises a number of different sections, each of which looks at a particular aspect of household behavior or welfare. Data collected under Round IX includes education, diarrhea, immunization, reproductive health, pregnancy history, maternity history, family planning, pre and post-natal care and access to basic services.
Data quality in PSLM Survey has been ensured through a built in system of checking of field work by the supervisors in the field and by the in charge of the concerned Regional/Field offices. Teams from the headquarters also pay surprise visits and randomly check the work done by the enumerators. Regional/ Field offices ensured the data quality through preliminary editing at their office level. The entire data entry was carried at the PBS headquarter Islamabad and specially designed data entry programme had a number of built in consistency checks.
To determine the reliability of the estimates confidence interval and Standard error of important key indicators have been worked out and are attached at the end of each section of the survey report, provided under the 'Related Materials' tab
This polygon dataset shows village boundaries with socio-demographic and economic Census data for 1991 for the State of Punjab, India linked to the 1991 Census. Includes village socio-demographic and economic Census attribute data such as total population, population by sex, household, literacy and illiteracy rates, and employment by industry. This layer is part of the VillageMap dataset which includes socio-demographic and economic Census data for 1991 at the village level for all the states of India. This data layer is sourced from secondary government sources, chiefly Survey of India, Census of India, Election Commission, etc.
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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. SUMMARY OF FINDINGS POPULATION CHARACTERISTICS 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. 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, 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. 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. 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
Whether one is in favor of private education or not, it is here to stay and there is a critical need to understand this new environment. Unfortunately, little is known about the private sector and what its growth implies for the provision of education. There are important questions we need to answer before engaging in productive debate about how education can be best provided in the Pakistani context. For instance: a. Where are private schools setting up? Are they only being established in urban areas and only for the elite? b. What is the quality of education in private sector schools? How does it compare to public schools? c. Are the poor being left out? Is the private sector creating two classes of people in Pakistan—those who can afford private education and those who cannot? d. What is the effect of private schools on government schools?
Rural Punjab, Pakistan
How much a child learns depends on teachers, parents and the child herself. How these three coordinate and work together also depends on the head-teacher and the educational institutes that support the delivery of education. Our research strategy reflects this belief. We survey both schools and households and test children to assess how much they are learning. Here is a brief overview of the survey structure: a. Teachers: Rosters with basic information for all teachers in the schools and detailed interviews with the class-teachers of the children tested. b. Head-teachers: A detailed questionnaire with the head-teacher with basic information about his/her background and teaching experience. c. Schools: We also collected information on schools, the children who come, the fees charged (private schools) and their current needs. d. Children: For a random sample of 10 children from those tested the survey collects basic information on their households (parental education, assets and brothers and sisters), how far they travel to get to school, and their height and weight. e. Households: We complete household surveys for 16 households in every village, with information on what parents know and what parents do with regard to their children’s education. In addition, these surveys contain the basic information on expenditures, assets, education and health that will allow us to look at the relationship between these factors and educational performance. For instance, when the mother is sick, does the child perform worse in school?
Survey Data
The sample comprises 112 villages in 3 districts of Punjab-Attock, Faisalabad and Rahim Yar Khan. The districts represent an accepted stratification of the province into North (Attock), Central (Faisalabad) and South (Rahim Yar Khan). The 112 villages in these districts were chosen randomly from the list of all villages with an existing private school. This allows us to look at differences between private and public schools in the same village. Although these villages are thus bigger and richer than average villages in these districts, we believe this is a forward-looking strategy and the insights earned here will soon be applicable to a significant fraction of all villages in the country.
None.
The LEAPS project consists of a variety of questionnaires distributed to different groups in each village in order to obtain a complete picture of the educational environment.
School Survey: Head teachers and school ownders were asked a variety of questions about about infrastructure, prices, costs and other facilities available in the neighborhood of the school. Teacher surveys: The LEAPS project administered three sets of teacher surveys. A shorter roster was administered for all teachers in the school and for all teachers who had left the school in the previous two years. This roster yields information on above 5000 teachers in the LEAPS project schools. A longer questionnaire was administered to the teachers of the tested children. This questionnaire includes detailed socioeconomic information about the teacher and yields data on just above 800 teachers. In addition, a questionnaire was also administered to the head-teacher (where the head-teacher was different from the class teacher) with questions on management practices and bonus schemes, along with other modules.
Child Tests: All children in Class 3 (approximately 12,000) were tested in the LEAPS project schools with specially designed tests in Urdu, Mathematics and English. These tests were administered by the LEAPS team to ensure impartial test circumstances. Further, for a sample of 10 randomly selected children in every class (roughly 6000 in total), a short questionnaire was administered to the child with information on parental literacy, family structure and household assets (in classes with less than 10 children, all children were chosen).
Household surveys: Information on the educational inputs that children receive from home, a full-fledged household questionnaire was fielded for 1800 households in the sampled villages, with a special focus on covering those households with a child enrolled in class 3. To ensure that we could compare the activities of enrolled with out-of-school children we also sampled households with eligible kids who were not in school in a stratified fashion.
The attrition has been remarkably small, averaging 3-4 percent in each year.
This dataset is a cross-sectional survey collected from two provinces in Pakistan (Punjab) and India (State of Gujarat). The sample included both urban and rural parts of the two countries. The dataset mainly looks at children’s learning and general life experiences in the early years of childhood (at ages 4 to 8). We assessed 1,129 children on tasks of basic numeracy, literacy, and social-emotional learning using a standardised measure of assessment, implemented at two points in time with a gap of 12 months. Also, we collected data on household characteristics, children's learning performance and a parents' survey of children's activities and learning outcomes.
School enrolment of around 80% in India and Pakistan is lower than targets associated with Sustainable Development Goal 4 and functional levels of literacy and numeracy are inadequate even for many young children who are enrolled in school. This project, based on 1,500 young children from one province in Pakistan and one state in India, seeks to examine patterns of enrolment of children and school readiness by socio-economic group, family background, urban / rural locations and individual characteristics such as gender, disability and health. Attendance and progress at school will be analysed over one year, demonstrating how much of a difference school attendance can make to children’s cognitive development and health outcomes. The project aims to collect in-depth information from families and communities on their views of schools and any barriers to attendance, and conduct a systematic review of the evidence. The findings are expected to have policy implications on school enrolment, attendance and retention.
The team's final project report was published on 20 September 2022, and a foreword has been authored by Ziauddin Yousafzai (Malala Yousafzai’s father).
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.
SUMMARY OF FINDINGS
POPULATION CHARACTERISTICS
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.
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, 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.
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.
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
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The statistic displays the literacy rate in Punjab in India between 1991 and 2011, broken down by gender. In 2001, ** percent of the female population in Punjab knew how to read or write. India's literacy rate from 1981 through 2011 can be found here.