As of 2021, India recorded a higher nationwide literacy rate among men than women, at respectively **** percent of male population and **** percent of female population. The gender literacy gap was more evident in rural India, with only ** percent of women aged between 15 and 49 years being literate, compared to over ** percent of their male counterparts in the region.
Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.
In the year *******, a total of **** percent females were literate in the urban areas in India. In the same year, a total of only **** percent females were literate in the rural areas. The total female literacy rate in India grew from **** percent to **** percent from 2005 to 2016.
Description and codebook for subset of harmonized variables:
Guide to datasets:
Full Project Name: The Impact of Mother Literacy and Participation Programs on Child Learning in India
Unique ID: 458
PIs: Rukmini Banerji, James Berry, Marc Shotland
Location: Indian states of Bihar and Rajasthan
Sample: Around 9,000 households in 480 villages
Timeline: 2010 to 2012
Target Group: Children Parents Rural population Women and girls
Outcome of Interest: Employment, Student learning ,Women’s/girls’ decision-making, Gender attitudes and norms
Intervention Type: Early childhood development, Tracking and remedial education, Empowerment training
Associated publications: https://www.aeaweb.org/articles?id=10.1257/app.20150390
More information: https://www.povertyactionlab.org/evaluation/impact-mother-literacy-and-participation-programs-child-learning-india
Dataverse: Banerji, Rukmini; Berry, James; Shotland, Marc, 2017, “The Impact of Maternal Literacy and Participation Programs: Evidence from a Randomized Evaluation in India”, https://doi.org/10.7910/DVN/19PPE7, Harvard Dataverse, V1
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This dataset was created on 2021-10-06 20:35:41.921
by merging multiple datasets together. The source datasets for this version were:
Maternal Literacy in India Baseline: Modified from ml_merged : contains data with variables only from baseline surveys
Maternal Literacy in India Endline: Modified from ml_merged : contains data with variables only from endline surveys
Maternal Literacy in India Raw Administrative Statistics: ml_admin_stats_raw: Contains administrative statistics from the 2011 census and aser surveys used in online Appendix Table 1 in the paper; this is merged with some of the survey data to create ml_admin_stats
In the year *******, a total of **** percent females from the highest wealth group were literate in India. In the same year, a total of only **** percent females from the lowest wealth group were literate. The total female literacy rate in India grew from **** percent to **** percent from 2005 to 2016.
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This dataset presents national-level literacy rates, compiled from multiple official sources, including the National Sample Survey (NSS), Periodic Labour Force Survey (PLFS), Population Census, National Family Health Survey (NFHS), and data published by the Ministry of Statistics and Programme Implementation (MoSPI).
It provides literacy rates disaggregated by gender, region (urban and rural), and age group. The inclusion of age groups is essential, as the criteria for calculating literacy rates have changed over time. To allow consistent comparisons across sources and years, an ‘age group’ column is included in the dataset. In general, literacy is assessed based on whether a person above a specified age can read and write a simple message with understanding in at least one language. The age specified as per these sources is as follows:
Census: Population aged 7 years and above (used since 1981; previously, it was 5 years and above). Data is available for 1951, 1961, 1971, 1981, 1991, 2001, and 2011 NSS: Population aged 5 years and above. Data is available for 2005, 2007-08, 2010, 2011-12, 2014, and 2017-18 PLFS: Survey typically covers population aged 15 years and above, but literacy data is also available for 5 years and above and 7 years and above. Data is available for 2017-18 to 2023-24. NFHS: Covers population aged 15–49 years only. Literacy rate refers to women and men who have completed standard 6, 9, or higher, or those who can read a full or partial sentence among individuals assumed to be literate. Data is available for 2005-06, 2015-16, and 2019-21. MoSPI: Follows the NSS age criteria, usually 5 years and above. Data is available for 2003, 2004, 2006, 2007, and 2011
In the year *******, a total of about ** percent Sikh females were literate in India. In comparison, a total of only ** percent Muslim females were literate during the same time period. The total female literacy rate in India grew from **** percent to **** percent from 2005 to 2016.
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Abstract: This study critically examines how digital empowerment has catalyzed the rise of women entrepreneurs across India’s diverse socio-economic spectrum. Drawing from feminist economic theory, digital sociology, and intersectional analysis, the paper explores how access to digital platforms, financial inclusion tools, and policy innovations has enabled women to transcend structural barriers and redefine enterprise. Through a detailed discussion of digital literacy, grassroots entrepreneurship, ethical leadership, and the digital gender divide, it highlights how women are not only participating in but actively reshaping the digital economy. By mapping personal narratives and case studies across urban and rural settings, the paper positions women as ethical innovators, social disruptors, and architects of an inclusive entrepreneurial ecosystem. It argues for a feminist digital economy rooted in empathy, equity, and sustainable development. Keywords: Women Entrepreneurship, Digital Empowerment, Inclusive Innovation, Tech-Driven Financial Inclusion, Intersectionality, Ethical Leadership, Digital Gender Divide. Introduction: The digital revolution in India has unfolded as a transformative force, particularly for women seeking economic agency in a historically patriarchal society. With the widespread adoption of mobile technologies, fintech innovations, and digital platforms, women are reimagining traditional business paradigms and carving out entrepreneurial identities. These digital shifts, supported by state initiatives and global networks, have lowered entry barriers and fostered new models of inclusive, decentralized, and socially conscious entrepreneurship. More than a technological shift, this transformation is a cultural and epistemic one—where women, once peripheral to the business narrative, now emerge as producers of value, knowledge, and leadership. However, their journeys remain shaped by complex intersections of caste, class, geography, and education. By analyzing this nuanced terrain, this study seeks to highlight how digital empowerment is not just a tool but a terrain of struggle, negotiation, and innovation for women entrepreneurs in India. • Digital Literacy and Tech-Readiness: The Foundational Layer: At the heart of digital empowerment lies digital literacy—the capacity to navigate, evaluate, and create information using digital technologies. For women entrepreneurs, digital literacy is not merely a skill set; it is an emancipatory tool. In India, where digital literacy among women remains uneven across rural-urban and socio-economic lines, targeted efforts like ‘Digital India’, ‘Pradhan Mantri Gramin Digital Saksharta Abhiyan’, and private initiatives like Google’s ‘Internet Saathi’ have attempted to bridge the gap. Tech-readiness, particularly among first-generation female entrepreneurs, empowers them to harness platforms like WhatsApp Business, Shopify, Instagram Reels, or UPI-based payment systems.....
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Full Project Name: Impact of Female Leadership on Aspirations and Educational Attainment for Teenage Girls in India
Unique ID: 498
PIs: Lori Beaman, Esther Duflo, Rohini Pande, Petia Topalova
Location: Birbhum District, West Bengal, India
Sample: 495 villages
Timeline: 2006 to 2007
Target Group: Parents Men and boys Rural population Women and girls Youth
Outcome of Interest: Discrimination Enrollment and attendance Women’s/girls’ decision-making Self-esteem/self-efficacy Aspirations Gender attitudes and norms
Associated publications: http://science.sciencemag.org/content/335/6068/582
More information: https://www.povertyactionlab.org/evaluation/impact-female-leadership-aspirations-and-educational-attainment-teenage-girls-india
Dataverse: Lori Beaman; Raghabendra Chattopadhyay; Esther Duflo; Rohini Pande; Petia Topalova, 2012, “Powerful women and aspirations in India”, https://doi.org/10.7910/DVN/O3UKFO, Harvard Dataverse, V3.
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This dataset was created on 2021-10-06 20:34:42.626
by merging multiple datasets together. The source datasets for this version were:
Powerful Women in India Adult Survey: Adult survey data, excluding section F5 on education; Only one round of data collection
Powerful Women in India Adult Education: Adult survey data from section F5 on education; Only one round of data collection
Powerful Women in India:
Powerful Women in India Facilities Anganwadi: Data collected from facilities survey on school facility quality only from the Anganwadi section
Powerful Women in India Facilities Math Test: Data collected from facilities survey on school facility quality only from the Math Test section
Powerful Women in India Facilities School Details: Data collected from facilities survey on school facility quality only from the School Details section
Powerful Women in India Household Roster: Data collected from household survey section A1 - household roster
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This dataset was created on 2021-10-06 18:52:27.489
by merging multiple datasets together. The source datasets for this version were:
Powerful Women in India Facilities Survey: Data collected from facilities survey on school facility quality, excluding the following sections: -Anganwadi -Math test -Reading test -School Details
Powerful Women in India Facilities Reading Test: Data collected from facilities survey on school facility quality only from the Reading Test section
Powerful Women in India Household Survey: Data collected from household survey, excluding section A1
Powerful Women in India Participatory Resource Appraisal: Data from the assessment of village resources through a participatory resource appraisal exercise
Powerful Women in India Pradhan Survey: Data from current and previous Pradhans and their spouses about economic condition and political activities
Powerful Women in India Pradhan Seats Reserved for Women: Data at community/village level regarding current and previous Pradhan seats
Powerful Women in India Teenager Survey: Data from teenagers interviewed (children aged 11-16 years)
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License information was derived automatically
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
Goal 5: Achieve gender equality and empower all women and girlIn Southern Asia, only 74 girls were enrolled in primary school for every 100 boys in 1990. By 2012, the enrolment ratios were the same for girls and for boys.In sub-Saharan Africa, Oceania and Western Asia, girls still face barriers to entering both primary and secondary school.Women in Northern Africa hold less than one in five paid jobs in the non-agricultural sector.In 46 countries, women now hold more than 30% of seats in national parliament in at least one chamber.India is on track to achieve gender parity at all education levels, having already achieved it at the primary level. The ratio of female literacy to male literacy for 15- 24 year olds is 0.91.As of August 2015, in India the proportion of seats in National Parliament held by women is only 12% against the target of 50%.This map layer is offered by Esri India, for ArcGIS Online subscribers, If you have any questions or comments, please let us know via content@esri.in.
In the year *******, a total of **** percent females from scheduled castes were literate in India. In the same year, a total of only ** percent females from scheduled tribes were literate. The total female literacy rate in India grew from **** percent to **** percent from 2005 to 2016.
The National Family Health Surveys (NFHS) programme, initiated in the early 1990s, has emerged as a nationally important source of data on population, health, and nutrition for India and its states. The 2005-06 National Family Health Survey (NFHS-3), the third in the series of these national surveys, was preceded by NFHS-1 in 1992-93 and NFHS-2 in 1998-99. Like NFHS-1 and NFHS-2, NFHS-3 was designed to provide estimates of important indicators on family welfare, maternal and child health, and nutrition. In addition, NFHS-3 provides information on several new and emerging issues, including family life education, safe injections, perinatal mortality, adolescent reproductive health, high-risk sexual behaviour, tuberculosis, and malaria. Further, unlike the earlier surveys in which only ever-married women age 15-49 were eligible for individual interviews, NFHS-3 interviewed all women age 15-49 and all men age 15-54. Information on nutritional status, including the prevalence of anaemia, is provided in NFHS3 for women age 15-49, men age 15-54, and young children.
A special feature of NFHS-3 is the inclusion of testing of the adult population for HIV. NFHS-3 is the first nationwide community-based survey in India to provide an estimate of HIV prevalence in the general population. Specifically, NFHS-3 provides estimates of HIV prevalence among women age 15-49 and men age 15-54 for all of India, and separately for Uttar Pradesh and for Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu, five out of the six states classified by the National AIDS Control Organization (NACO) as high HIV prevalence states. No estimate of HIV prevalence is being provided for Nagaland, the sixth high HIV prevalence state, due to strong local opposition to the collection of blood samples.
NFHS-3 covered all 29 states in India, which comprise more than 99 percent of India's population. NFHS-3 is designed to provide estimates of key indicators for India as a whole and, with the exception of HIV prevalence, for all 29 states by urban-rural residence. Additionally, NFHS-3 provides estimates for the slum and non-slum populations of eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur. NFHS-3 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOHFW), Government of India, and is the result of the collaborative efforts of a large number of organizations. The International Institute for Population Sciences (IIPS), Mumbai, was designated by MOHFW as the nodal agency for the project. Funding for NFHS-3 was provided by the United States Agency for International Development (USAID), DFID, the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and MOHFW. Macro International, USA, provided technical assistance at all stages of the NFHS-3 project. NACO and the National AIDS Research Institute (NARI) provided technical assistance for the HIV component of NFHS-3. Eighteen Research Organizations, including six Population Research Centres, shouldered the responsibility of conducting the survey in the different states of India and producing electronic data files.
The survey used a uniform sample design, questionnaires (translated into 18 Indian languages), field procedures, and procedures for biomarker measurements throughout the country to facilitate comparability across the states and to ensure the highest possible data quality. The contents of the questionnaires were decided through an extensive collaborative process in early 2005. Based on provisional data, two national-level fact sheets and 29 state fact sheets that provide estimates of more than 50 key indicators of population, health, family welfare, and nutrition have already been released. The basic objective of releasing fact sheets within a very short period after the completion of data collection was to provide immediate feedback to planners and programme managers on key process indicators.
The population covered by the 2005 DHS is defined as the universe of all ever-married women age 15-49, NFHS-3 included never married women age 15-49 and both ever-married and never married men age 15-54 as eligible respondents.
Sample survey data
SAMPLE SIZE
Since a large number of the key indicators to be estimated from NFHS-3 refer to ever-married women in the reproductive ages of 15-49, the target sample size for each state in NFHS-3 was estimated in terms of the number of ever-married women in the reproductive ages to be interviewed.
The initial target sample size was 4,000 completed interviews with ever-married women in states with a 2001 population of more than 30 million, 3,000 completed interviews with ever-married women in states with a 2001 population between 5 and 30 million, and 1,500 completed interviews with ever-married women in states with a population of less than 5 million. In addition, because of sample-size adjustments required to meet the need for HIV prevalence estimates for the high HIV prevalence states and Uttar Pradesh and for slum and non-slum estimates in eight selected cities, the sample size in some states was higher than that fixed by the above criteria. The target sample was increased for Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland, Tamil Nadu, and Uttar Pradesh to permit the calculation of reliable HIV prevalence estimates for each of these states. The sample size in Andhra Pradesh, Delhi, Maharashtra, Tamil Nadu, Madhya Pradesh, and West Bengal was increased to allow separate estimates for slum and non-slum populations in the cities of Chennai, Delhi, Hyderabad, Indore, Kolkata, Mumbai, Meerut, and Nagpur.
The target sample size for HIV tests was estimated on the basis of the assumed HIV prevalence rate, the design effect of the sample, and the acceptable level of precision. With an assumed level of HIV prevalence of 1.25 percent and a 15 percent relative standard error, the estimated sample size was 6,400 HIV tests each for men and women in each of the high HIV prevalence states. At the national level, the assumed level of HIV prevalence of less than 1 percent (0.92 percent) and less than a 5 percent relative standard error yielded a target of 125,000 HIV tests at the national level.
Blood was collected for HIV testing from all consenting ever-married and never married women age 15-49 and men age 15-54 in all sample households in Andhra Pradesh, Karnataka, Maharashtra, Manipur, Tamil Nadu, and Uttar Pradesh. All women age 15-49 and men age 15-54 in the sample households were eligible for interviewing in all of these states plus Nagaland. In the remaining 22 states, all ever-married and never married women age 15-49 in sample households were eligible to be interviewed. In those 22 states, men age 15-54 were eligible to be interviewed in only a subsample of households. HIV tests for women and men were carried out in only a subsample of the households that were selected for men's interviews in those 22 states. The reason for this sample design is that the required number of HIV tests is determined by the need to calculate HIV prevalence at the national level and for some states, whereas the number of individual interviews is determined by the need to provide state level estimates for attitudinal and behavioural indicators in every state. For statistical reasons, it is not possible to estimate HIV prevalence in every state from NFHS-3 as the number of tests required for estimating HIV prevalence reliably in low HIV prevalence states would have been very large.
SAMPLE DESIGN
The urban and rural samples within each state were drawn separately and, to the extent possible, unless oversampling was required to permit separate estimates for urban slum and non-slum areas, the sample within each state was allocated proportionally to the size of the state's urban and rural populations. A uniform sample design was adopted in all states. In each state, the rural sample was selected in two stages, with 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 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. In the final stage, households were randomly selected within each selected CEB.
SAMPLE SELECTION IN RURAL AREAS
In rural areas, the 2001 Census list of villages served as the sampling frame. The list was stratified by a number of variables. 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: village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. In addition to these variables, an external estimate of HIV prevalence, i.e., 'High', 'Medium' or 'Low', as estimated for all the districts in high HIV prevalence states, was used for stratification in high HIV prevalence states. Female literacy was used for implicit stratification (i.e., villages were
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The women's magazine market, while facing challenges from digital media, remains a significant sector with a robust, albeit evolving, landscape. The market size in 2025 is estimated at $15 billion, reflecting a compound annual growth rate (CAGR) of approximately 3% from 2019 to 2024. This relatively moderate growth is indicative of a market undergoing a transition. While print circulation continues to decline, the market is showing resilience through diversification. Growth drivers include the continued demand for targeted content in niche areas like women's health, parenting, and social issues, leading to specialized magazine formats. Furthermore, the successful integration of digital platforms, including online subscriptions and e-magazines, is helping to offset print losses. Key trends include the increasing importance of personalized content, interactive experiences, and a shift towards building communities around shared interests among readers. However, restraints include stiff competition from free online content, the rising cost of print production, and changing consumer media habits. Segmentation within the market reveals significant potential: the fashion and health segments lead in revenue generation, while segments like entertainment news and social issues are exhibiting stronger growth potential due to increasing reader engagement and willingness to pay for quality journalism. The leading players, such as Condé Nast, Hearst Corporation, and Martha Stewart Living Omnimedia, are adapting their strategies by creating engaging multi-platform content to reach a wider audience. Geographic distribution reveals a concentration of market share in North America and Europe, primarily driven by established publishing houses and higher disposable incomes. However, growth is anticipated in Asia Pacific, particularly in countries like China and India, due to increasing urbanization, female empowerment, and rising literacy rates. The future success of women's magazines hinges on their ability to provide readers with exclusive, high-quality content that cannot be easily replicated online, coupled with effective digital strategies that leverage social media and other digital platforms to foster community engagement and broaden readership. The focus should shift towards building strong reader relationships and offering unique and valuable experiences beyond just print.
The National Family Health Survey 2019-21 (NFHS-5), the fifth in the NFHS series, provides information on population, health, and nutrition for India, each state/union territory (UT), and for 707 districts.
The primary objective of the 2019-21 round of National Family Health Surveys is to provide essential data on health and family welfare, as well as data on emerging issues in these areas, such as levels of fertility, infant and child mortality, maternal and child health, and other health and family welfare indicators by background characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, noncommunicable diseases, and the use of emergency contraception.
The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas.
The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements.
National coverage
The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-54, and all children aged 0-5 resident in the household.
Sample survey data [ssd]
A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs.
For further details on sample design, see Section 1.2 of the final report.
Computer Assisted Personal Interview [capi]
Four survey schedules/questionnaires: Household, Woman, Man, and Biomarker were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI).
Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized.
Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required.
A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent.
In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent.
As of 2021, India recorded a higher nationwide share of men with at least 10 years of schooling than that of women. Around half of the male population age between 15 and 49 years stayed in school for at least 10 years, compared to only ** percent of their female counterparts. The gender education gap also remained evident in rural India, with only *** out of three women in this region receiving at least 10 years of schooling.
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The use of biomass fuel is associated with the deterioration of human health and women are more likely to develop health conditions due to their exposure to indoor air pollution during cooking. This study was conducted to assess the pattern of fuel used for cooking in households as well as to determine the association between the types of fuel used with respect to socio-demographic characteristics and health status of women. A community based cross-sectional survey was conducted between August 2016 and September 2018 in four rural areas and one semi-urban area of Udupi district, Karnataka, India. The study comprised 587 families including 632 women. A pre-tested semi-structured questionnaire was used to collect data on the type of fuel as well as self-reported health conditions. Overall, 72.5% of the families used biomass, where 67.2% families were currently using both biomass and liquefied petroleum gas while only biomass was used in 5.3% of the families for cooking. Among women, being ever exposed to biomass fuel was significantly associated with their age, literacy level, occupation and socio-economic status (p < 0.001). Those who were exposed to biomass fuel showed a significant association with self-reported ophthalmic (AOR = 3.85; 95% CI: 1.79–8.29), respiratory (OR = 5.04; 95% CI: 2.52–10.07), cardiovascular (OR = 6.07; 95% CI: 1.88–19.67), dermatological symptoms /conditions (AOR = 3.67; 95% CI: 1.07–12.55) and history of adverse obstetric outcomes (AOR = 2.45; 95% CI: 1.08–5.57). A positive trend was observed between cumulative exposure to biomass in hour-years and various self-reported health symptoms/conditions (p < 0.001). It was observed that more than two-thirds of women using biomass fuel for cooking were positively associated with self-reported health symptoms. Further longitudinal studies are essential to determine the level of harmful air pollutants in household environment and its association with various health conditions among women in this region.
The statistic shows the degree of adult literacy in China from 1982 to 2020. In 2020, the literacy rate, which is defined as people aged 15 and above who can read and write, had reached about 97.15 percent in China.
Global literacy rates
By 2020, around 86.8 percent of the world population aged 15 years and above had been able to read and write. While in developed regions this figure ranged a lot higher, only around 67 percent of the population in Sub-Saharan Africa was literate. Countries with the lowest literacy rates are also the most underdeveloped worldwide. According to UNESCO, literacy is a human right, especially in a fast-changing and technology-driven world. In China, the literacy rate has developed from 79 percent in 1982 to 97 percent in 2020, indicating that almost one million people per year had become literate over three decades. In India, the situation was entirely different. The second most populous country in the world displayed a literacy rate of merely 76 percent in 2022.
Literacy in China
The dramatic increase in literacy in China has a lot to do with the efficacy of numerous political, economic and educational policies. In 1982, compulsory education was written into the Chinese constitution, postulating a nine-year compulsory education funded by the government. As is shown by the graph above, there was a large gender gap in literacy rate in China as of 1982. Though this gap still existed in 2020, it was narrowed down to three percent, starting from 28 percent in 1982. Since 1990, the national education policy was directed at females, especially from poor and/or minority families. Over the past years, China has achieved gender parity in primary schooling.
However, regional literacy disparities in China should not to be overlooked. Regions with a strong economic background tend to display illiteracy rates below national average. In contrast, economically underdeveloped regions have a much larger share of people who cannot read nor write. Tibet for instance, a region where 92 percent of the population belong to an ethnic minority, showed the highest illiterate rate nationwide, with around 34 percent in 2022.
The statistic displays the literacy rate within the slum population in India in 2001 and 2011, distributed by gender. In 2001, more than ** percent of the male population living in slum households were able to read or write. The male literacy rate has increased by 2011 to just under ** percent. A high share of females living in slum households were illiterate.
The statistic depicts the literacy rate in the rural and urban areas of Bihar in India in 2011, by gender. In that year, the literacy rate for females living in rural areas in Bihar was just over 49 percent. India's literacy rate from 1981 through 2011 can be found here.
As of 2021, India recorded a higher nationwide literacy rate among men than women, at respectively **** percent of male population and **** percent of female population. The gender literacy gap was more evident in rural India, with only ** percent of women aged between 15 and 49 years being literate, compared to over ** percent of their male counterparts in the region.