The population of India is divided into several groups based on social, educational, and financial statuses. The formation of these groups is a result of the historical social structure of the country. Between 2019 and 2021, Other Backward Class (OBC) constituted the largest part of Indian households accounting for about ** percent. On the other hand, Schedule Tribes formed about *** percent of households. How prosperous is India’s caste-based society? India suffers from extreme social and economic inequality. The combined share of Schedule Tribe and Schedule Caste in the affluent population of India was less than ** percent. Contrary to this, economically and socially stronger groups constituted the major part of the affluent population. Hence, indicating a strong relationship between caste and prosperity. India’s thoughts on caste-based reservation The constitution of India provides reservations to the weaker sections of the society for their upliftment and growth. However, the need for reservation has increased with time, making the whole situation even more complicated. People are divided over the existence of a system that provides preference to certain castes or sects. In a survey conducted in 2016 about providing employment reservation to young adults of Schedule Caste and Schedule Tribe, many people expressed opposition. More than ** percent of opposition came from upper Hindu caste. Minimum opposition was observed from the people belonging to Schedule Tribe and Schedule Caste.

India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

India Census: Population: by Religion: Hindu: Male data was reported at 498,306,968.000 Person in 2011. This records an increase from the previous number of 428,678,554.000 Person for 2001. India Census: Population: by Religion: Hindu: Male data is updated yearly, averaging 463,492,761.000 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 498,306,968.000 Person in 2011 and a record low of 428,678,554.000 Person in 2001. India Census: Population: by Religion: Hindu: Male data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

This statistic depicts the age distribution of India from 2013 to 2023. In 2023, about 25.06 percent of the Indian population fell into the 0-14 year category, 68.02 percent into the 15-64 age group and 6.92 percent were over 65 years of age. Age distribution in India India is one of the largest countries in the world and its population is constantly increasing. India’s society is categorized into a hierarchically organized caste system, encompassing certain rights and values for each caste. Indians are born into a caste, and those belonging to a lower echelon often face discrimination and hardship. The median age (which means that one half of the population is younger and the other one is older) of India’s population has been increasing constantly after a slump in the 1970s, and is expected to increase further over the next few years. However, in international comparison, it is fairly low; in other countries the average inhabitant is about 20 years older. But India seems to be on the rise, not only is it a member of the BRIC states – an association of emerging economies, the other members being Brazil, Russia and China –, life expectancy of Indians has also increased significantly over the past decade, which is an indicator of access to better health care and nutrition. Gender equality is still non-existant in India, even though most Indians believe that the quality of life is about equal for men and women in their country. India is patriarchal and women still often face forced marriages, domestic violence, dowry killings or rape. As of late, India has come to be considered one of the least safe places for women worldwide. Additionally, infanticide and selective abortion of female fetuses attribute to the inequality of women in India. It is believed that this has led to the fact that the vast majority of Indian children aged 0 to 6 years are male.

The literacy rate of the total population in the country was about ** percent in 2011, in comparison to about ** percent among the scheduled caste population. In India, scheduled caste and scheduled tribe and other backward class are officially recognized by the constitution as groups of disadvantaged indigenous people. They are the primary beneficiaries of reservation policies under the constitution.

The Socio Economic Caste Census (SECC) is a comprehensive exercise undertaken by the Government of India to gather detailed information about the socio-economic status and caste demographics of Indian households. Conducted in 2011, this census was distinct from the traditional decennial population census and aimed to provide a holistic understanding of the living conditions and deprivation levels of people across the country. The SECC data encompasses various parameters, including income, occupation, land ownership, and educational status. Additionally, it marked a significant effort to collect caste-wise population data, a feat not attempted since the pre-independence census of 1931. The findings from the SECC play a pivotal role in shaping targeted policy interventions and welfare schemes for the marginalized and underprivileged sections of society.

The data refers to State/UT-wise and caste-wise details of prison inmates at the end of the reference year. The prison inmates are categorised into male and female population. The age of inmates are grouped into 16-18 yrs, 18-30 yrs, 30-50 yrs and 50 & above yrs. Castes of jail inmates are further categorized as OBCs, SCs, STs & Others.

This dataset contains the State, Year, Caste, Level and Gender-wise Gross Enrolment Ratio (GER) in India. The Gross Enrolment Ratio (GER) compares the enrolment in a specific level of education to the population of the age-group which is most age-appropriate for that level of educationThe data is given for all caste categories, Scheduled Castes and Scheduled Tribes.

It was estimated that by 2050, India's Muslim population would grow by ** percent compared to 2010. For followers of the Hindu faith, this change stood at ** percent. According to this projection, the south Asian country would be home not just to the world's majority of Hindus, but also Muslims by this time period. Regardless, the latter would continue to remain a minority within the country at ** percent, with ** percent or *** billion Hindus at the forefront by 2050.

ObjectiveAlthough under-five mortality rate (U5MR) is declining in India, it is still high in a few selected states and among the scheduled caste (SC) and scheduled tribe (ST) population of the country. This study re-examines the association between caste and under-five deaths in high focus Indian states following the implementation of the country’s National Rural Health Mission (NRHM) program. In addition, we aim to quantify the contribution of socioeconomic determinants in explaining the gap in under-five death risk between the SC/ST population and non-SC/ST population in high focus states in India.Data and methodUsing data from the National Family Health Survey (NFHS), we calculated the U5MR by applying a synthetic cohort probability approach. We applied a binary logistic regression model to examine the association of under-five deaths with the selected covariates. Further, we used Fairlie's decomposition technique to understand the relative contribution of socioeconomic variables on under-five death risk between the caste groups.FindingsIn high focus Indian states, the under-five mortality risk between well-off and deprived caste children has declined in the post-NRHM period, indicating a positive impact in terms of reducing caste-based inequalities in the high focus states. Despite the reduction in under-five death risk, children belonging to the SC population experience higher mortality rates than children belonging to the non-SC/ST population from 1992 to 2016. Both macro level (district level mortality rates) and individual (regression analysis) analyses showed that children belonging to SCs experience the highest likelihood of dying before their fifth birthday. A decomposition analysis revealed that 83% of the caste-based gap in the under-five deaths is due to the distribution of women’s level of educational attainment and household wealth between the SC/ST and non-SC/ST population. Program indicators such as place of birth and number of antenatal care (ANC) visit also contributed significantly to widening caste-based gaps in U5MR.ConclusionThe study indicates that there is still room to improve access to health facilities for mothers and children belonging to deprived caste groups in India. Continuous efforts to raise the level of maternal education and the economic status of people belonging to deprived caste groups should be pursued simultaneously.

--- ### Context Basic Habitation Information: The data refers to the list of habitations, its population in different caste category (SC, ST and GENERAL) and status of availability of potable drinking water (Covered or Partially covered) all over India. Water Quality Affected Habitations: The data refers to the list of drinking water quality affected habitations all over India due to contamination such as Fluoride, Arsenic, Iron, Salinity and Nitrate. ### Content Basic Habitation Information from 2009 and 2012. Water Quality Affected Habitations from 2009 and 2012. ### Acknowledgements Ministry of Drinking Water and Sanitation (MDWS), Govt of India has shared this data in [Open Govt][1] [Data Platform India][2] portal under [Govt. Open Data License - India][3]. ---

Abstract

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.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 54

Universe

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.

Kind of data

Sample survey data [ssd]

Sampling procedure

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.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four survey schedules/questionnaires: Household, Woman, Man, and Biomarker were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI).

Cleaning operations

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.

Response rate

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 2010, Christianity was the religion with the most followers worldwide, followed by Islam (Muslims) and Hinduism. In the forty years between 2010 and 2050, it is projected that the landscape of world religions will undergo some noticeable changes, with the number of Muslims almost catching up to Christians. The changes in population sizes of each religious group is largely dependent on demographic development, for example, the rise in the world's Christian population will largely be driven by population growth in Sub-Saharan Africa, while Muslim populations will rise across various regions of Africa and South Asia. As India's population is set to grow while China's goes into decline, this will be reflected in the fact that Hindus will outnumber the unaffiliated by 2050. In fact, India may be home to both the largest Hindu and Muslim populations in the world by the middle of this century.

Abstract

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.

Geographic coverage

• National (29 states )
• Regional (for HIV Prevalence : Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu)
• Local (population and health indicators for slum and non-slum populations for eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur)

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Universe

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.

Kind of data

Sample survey data

Sampling procedure

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

A survey conducted across India in 2024 found that over 57 percent of the respondents agreed that the scope of reservations should be expanded to both Hindus and Muslims in the Scheduled caste (SC) category in government jobs. 19 percent believed that only Hindus should be given reservations in the category.