In 2022, India overtook China as the world's most populous country and now has almost 1.46 billion people. China now has the second-largest population in the world, still with just over 1.4 billion inhabitants, however, its population went into decline in 2023. Global population As of 2025, the world's population stands at almost 8.2 billion people and is expected to reach around 10.3 billion people in the 2080s, when it will then go into decline. Due to improved healthcare, sanitation, and general living conditions, the global population continues to increase; mortality rates (particularly among infants and children) are decreasing and the median age of the world population has steadily increased for decades. As for the average life expectancy in industrial and developing countries, the gap has narrowed significantly since the mid-20th century. Asia is the most populous continent on Earth; 11 of the 20 largest countries are located there. It leads the ranking of the global population by continent by far, reporting four times as many inhabitants as Africa. The Demographic Transition The population explosion over the past two centuries is part of a phenomenon known as the demographic transition. Simply put, this transition results from a drastic reduction in mortality, which then leads to a reduction in fertility, and increase in life expectancy; this interim period where death rates are low and birth rates are high is where this population explosion occurs, and population growth can remain high as the population ages. In today's most-developed countries, the transition generally began with industrialization in the 1800s, and growth has now stabilized as birth and mortality rates have re-balanced. Across less-developed countries, the stage of this transition varies; for example, China is at a later stage than India, which accounts for the change in which country is more populous - understanding the demographic transition can help understand the reason why China's population is now going into decline. The least-developed region is Sub-Saharan Africa, where fertility rates remain close to pre-industrial levels in some countries. As these countries transition, they will undergo significant rates of population growth

The statistic shows the Hindu population in India in 2011, by state and union territory. The region with the highest Hindu population was Uttar Pradesh, followed by the state of Maharashtra, with close to ** million Hindus. The region with the least Hindu population was Lakshadweep in that year. The countries with the largest number of Hindus in 2010 can be found here.

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

Abstract

The National Family Health Survey (NFHS) was carried out as the principal activity of a collaborative project to strengthen the research capabilities of the Population Reasearch Centres (PRCs) in India, initiated by the Ministry of Health and Family Welfare (MOHFW), Government of India, and coordinated by the International Institute for Population Sciences (IIPS), Bombay. Interviews were conducted with a nationally representative sample of 89,777 ever-married women in the age group 13-49, from 24 states and the National Capital Territoty of Delhi. The main objective of the survey was to collect reliable and up-to-date information on fertility, family planning, mortality, and maternal and child health. Data collection was carried out in three phases from April 1992 to September 1993. THe NFHS is one of the most complete surveys of its kind ever conducted in India.

The households covered in the survey included 500,492 residents. The young age structure of the population highlights the momentum of the future population growth of the country; 38 percent of household residents are under age 15, with their reproductive years still in the future. Persons age 60 or older constitute 8 percent of the population. The population sex ratio of the de jure residents is 944 females per 1,000 males, which is slightly higher than sex ratio of 927 observed in the 1991 Census.

The primary objective of the NFHS is to provide national-level and state-level data on fertility, nuptiality, family size preferences, knowledge and practice of family planning, the potentiel demand for contraception, the level of unwanted fertility, utilization of antenatal services, breastfeeding and food supplemation practises, child nutrition and health, immunizations, and infant and child mortality. The NFHS is also designed to explore the demographic and socioeconomic determinants of fertility, family planning, and maternal and child health. This information is intended to assist policymakers, adminitrators and researchers in assessing and evaluating population and family welfare programmes and strategies. The NFHS used uniform questionnaires and uniform methods of sampling, data collection and analysis with the primary objective of providing a source of demographic and health data for interstate comparisons. The data collected in the NFHS are also comparable with those of the Demographic and Health Surveys (DHS) conducted in many other countries.

Geographic coverage

National

Analysis unit

• Household
• Data collected for women 13-49, indicators calculated for women 15-49

Universe

The population covered by the 1992-93 DHS is defined as the universe of all women age 13-49 who were either permanent residents of the households in the NDHS sample or visitors present in the households on the night before the survey were eligible to be interviewed.

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN

The sample design for the NFHS was discussed during a Sample Design Workshop held in Madurai in Octber, 1991. The workshop was attended by representative from the PRCs; the COs; the Office of the Registrar General, India; IIPS and the East-West Center/Macro International. A uniform sample design was adopted in all the NFHS states. The Sample design adopted in each state is a systematic, stratified sample of households, with two stages in rural areas and three stages in urban areas.

SAMPLE SIZE AND ALLOCATION

The sample size for each state was specified in terms of a target number of completed interviews with eligible women. The target sample size was set considering the size of the state, the time and ressources available for the survey and the need for separate estimates for urban and rural areas of the stat. The initial target sample size was 3,000 completed interviews with eligible women for states having a population of 25 million or less in 1991; 4,000 completed interviews for large states with more than 25 million population; 8,000 for Uttar Pradesh, the largest state; and 1,000 each for the six small northeastern states. In States with a substantial number of backward districts, the initial target samples were increased so as to allow separate estimates to be made for groups of backward districts.

The urban and rural samples within states were drawn separetly and , to the extent possible, sample allocation was proportional to the size of the urban-rural populations (to facilitate the selection of a self-weighting sample for each state). In states where the urban population was not sufficiently large to provide a sample of at least 1,000 completed interviews with eligible women, the urban areas were appropriately oversampled (except in the six small northeastern states).

THE RURAL SAMPLE: THE FRAME, STRATIFICATION AND SELECTION

A two-stage stratified sampling was adopted for the rural areas: selection of villages followed by selection of households. Because the 1991 Census data were not available at the time of sample selection in most states, the 1981 Census list of villages served as the sampling frame in all the states with the exception of Assam, Delhi and Punjab. In these three states the 1991 Census data were used as the sampling frame.

Villages were stratified prior to selection on the basis of a number of variables. The firts level of stratification in all the states was geographic, with districts subdivided into regions according to their geophysical characteristics. Within each of these regions, villages were further stratified using some of the following variables : village size, distance from the nearest town, proportion of nonagricultural workers, proportion of the population belonging to scheduled castes/scheduled tribes, and female literacy. However, not all variables were used in every state. Each state was examined individually and two or three variables were selected for stratification, with the aim of creating not more than 12 strata for small states and not more than 15 strata for large states. Females literacy was often used for implicit stratification (i.e., the villages were ordered prior to selection according to the proportion of females who were literate). Primary sampling Units (PSUs) were selected systematically, with probaility proportional to size (PPS). In some cases, adjacent villages with small population sizes were combined into a single PSU for the purpose of sample selection. On average, 30 households were selected for interviewing in each selected PSU.

In every state, all the households in the selected PSUs were listed about two weeks prior to the survey. This listing provided the necessary frame for selecting households at the second sampling stage. The household listing operation consisted of preparing up-to-date notional and layout sketch maps of each selected PSU, assigning numbers to structures, recording addresses (or locations) of these structures, identifying the residential structures, and listing the names of the heads of all the households in the residentiak structures in the selected PSU. Each household listing team consisted of a lister and a mapper. The listing operation was supervised by the senior field staff of the concerned CO and the PRC in each state. Special efforts were made not to miss any household in the selected PSU during the listing operation. In PSUs with fewer than 500 households, a complete household listing was done. In PSUs with 500 or more households, segmentation of the PSU was done on the basis of existing wards in the PSU, and two segments were selected using either systematic sampling or PPS sampling. The household listing in such PSUs was carried out in the selected segments. The households to be interviewed were selected from provided with the original household listing, layout sketch map and the household sample selected for each PSU. All the selected households were approached during the data collection, and no substitution of a household was allowed under any circumstances.

THE RURAL URBAN SAMPLE: THE FRAME, STRATIFICATION AND SELECTION

A three-stage sample design was adopted for the urban areas in each state: selection of cities/towns, followed by urban blocks, and finally households. Cities and towns were selected using the 1991 population figures while urban blocks were selected using the 1991 list of census enumeration blocks in all the states with the exception of the firts phase states. For the first phase states, the list of urban blocks provided by the National Sample Survey Organization (NSSSO) served as the sampling frame.

All cities and towns were subdivided into three strata: (1) self-selecting cities (i.e., cities with a population large enough to be selected with certainty), (2) towns that are district headquaters, and (3) other towns. Within each stratum, the cities/towns were arranged according to the same kind of geographic stratification used in the rural areas. In self-selecting cities, the sample was selected according to a two-stage sample design: selection of the required number of urban blocks, followed by selection of households in each of selected blocks. For district headquarters and other towns, a three stage sample design was used: selection of towns with PPS, followed by selection of two census blocks per selected town, followed by selection of households from each selected block. As in rural areas, a household listing was carried out in the selected blocks, and an average of 20 households per block was selected systematically.

Mode of data collection

Face-to-face

Research instrument

Three types of questionnaires were used in the NFHS: the Household Questionnaire, the Women's Questionnaire, and the Village Questionnaire. The overall content

According to the latest census data, Lakshadweep, the island union territory had the highest share of Muslim population in the country, where 97 percent of its population identified as followers of the Islamic faith. Jammu & Kashmir ranked second at 68 percent during the same time period. With almost all major religions being practiced throughout the country, India is known for its religious diversity. Islam makes up the highest share among minority faiths in the country.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

India

Analysis unit

Household Individual

Universe

National Population, Both sexes,18 and more years

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 2002

As part of the India component of the World Values Survey, it was decided to conduct 2000 face-toface interviews. A rigorous scientific method was employed to generate the target sample for the study. The survey was conducted in 18 states of India, which covered nearly 97 % of the nations population.

40 districts in the country were identified for the purpose of the survey (a little less than 1/10 of the districts in the country: 466 districts as per 1991 census). The 40 districts were spread across the 18 states, in which the survey was conducted keeping in mind the population of the states, even while ensuring that the survey was conducted in at least one district in each of the sampled states.

Within each state, the district/s in which the survey was to be conducted was selected by circular sampling (PPS: Probability Proportion to Size). Once all the 40 districts were selected, the Lok Sabha (Lower House of the Indian Parliament)constituency that covered the district was identified. If the sampled district had more than one Lok Sabha constituency, the one, which had a larger proportion of the districts electorate, was selected.

The next stage in the sampling process was the selection of 2 State Assembly (Lower House of the State Legislature) constituencies in each of the sampled 40 Lok Sabha constituencies. Circular Sampling (PPS: Probability Proportion to Size) was once again employed. Thus, 80 Assembly Constituencies in 40 Lok Sabha constituencies (in 40 districts) were selected. Subsequently, a polling booth area in each of the 80 sampled Assembly constituencies was selected by simple circular sampling method.

The number of respondents to be interviewed in each state was determined on the basis of the proportion of the states share in the national population. This was equally divided among the polling booth areas that were sampled in a state. The number of respondents in the polling booth area was the same within a state, but varied from state to state. In a polling booth area, the respondents were selected from the electoral rolls (voters list) by circular sampling with a random first number.

While drawing up the random list of respondents to be interviewed in every sampled polling booth area, the number of target respondents was increased by nearly 20 %. This was done in view of the fact that the field investigators were required to interview only those respondents whose names were included in the sample list. No replacements or alteration in the list of sampled respondents was permitted. Previous survey experience has shown that it has never been possible for the investigator to interview all those included in the list of sampled respondents. A wide range of factors is responsible for the same. The investigators were told to make every effort to interview all those included in the list of respondents. In the event of the investigator not being able to complete an interview, they were asked to record the reason for the same. Such a rigorous method of sampling was followed in order to obtain as representative a national sample as possible. The analysis of the sample profile clearly indicates that the detailed and objective criteria employed has eminently served its purpose as the sample mirrors the nations social, economic, political, cultural and religious diversity.

Remarks about sampling: - Final numbers of clusters or sampling points: No clusters - Sample unit from office sampling: Named individual

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was translated into ten Indian languages by a specialist translator. A few modifications were undertaken in response categories for the scale answer questions. It was then back-translated to English. For each of the 10 languages the pre test was done on a sample of 5 each. There were several concepts and questions difficult to translate: more specifically v75/76/v103/v175/v208/v212/v229/. These problems were solved by developing new phrases close to the original statement or using it in the context of social reality The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 18 and there was not any upper age cut-off for the sample.

Response rate

The following table presents completion rate results: - Total number of starting names/addresses 2354 - Addresses which could not be traced at all 56 - Addresses established as empty, demolished or containing no private dwellings 39 - Selected respondent too sick/incapacitated to participate 29 - Selected respondent away during survey period 62 - Selected respondent had inadequate understanding of language of survey 27 - No contact at selected address 76 - No contact with selected person 31 - Refusal at selected address 34 - Full productive interviews 2002

Sampling error estimates

Estimated Error: 2,2

In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.

The dataset contains state-, region- and gender-wise NSS 78th round compiled data on Average Size and Total Number of Households, and Total Number of Persons (by Gender) in India

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

The statistic shows the total population of India from 2019 to 2029. In 2023, the estimated total population in India amounted to approximately 1.43 billion people.

Total population in India

India currently has the second-largest population in the world and is projected to overtake top-ranking China within forty years. Its residents comprise more than one-seventh of the entire world’s population, and despite a slowly decreasing fertility rate (which still exceeds the replacement rate and keeps the median age of the population relatively low), an increasing life expectancy adds to an expanding population. In comparison with other countries whose populations are decreasing, such as Japan, India has a relatively small share of aged population, which indicates the probability of lower death rates and higher retention of the existing population.

With a land mass of less than half that of the United States and a population almost four times greater, India has recognized potential problems of its growing population. Government attempts to implement family planning programs have achieved varying degrees of success. Initiatives such as sterilization programs in the 1970s have been blamed for creating general antipathy to family planning, but the combined efforts of various family planning and contraception programs have helped halve fertility rates since the 1960s. The population growth rate has correspondingly shrunk as well, but has not yet reached less than one percent growth per year.

As home to thousands of ethnic groups, hundreds of languages, and numerous religions, a cohesive and broadly-supported effort to reduce population growth is difficult to create. Despite that, India is one country to watch in coming years. It is also a growing economic power; among other measures, its GDP per capita was expected to triple between 2003 and 2013 and was listed as the third-ranked country for its share of the global gross domestic product.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household, enterprise

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: Persons without any normal residence, foreign nationals, and people in barracks of military and para-military forces, orphanages, rescue homes, ashram and vagrant houses are not covered by survey.

UNIT DESCRIPTIONS: - Households: A group of persons normally living together and taking food from a common kitchen will constitute a household. The members of a household may or may not be related by blood to one another.

Universe

All population in India, except for foreigners, the homeless, or people in barracks of military and para-military forces, orphanages, rescue homes, ashram, and vagrant houses.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Sample Survey Organization, Government of India

SAMPLE DESIGN: Two-stage, stratified samples drawn by the country, coupled with rotation sampling scheme for the central sample. (1) Stage 1: In the central sample, 10,384 first stage units (rural and urban combined) were selected from stratified states in proportion to poluation. Among them, 3,900 of which were revisted. (2) Stage 2: households and enterprises were selected from second-stage strata(hamlet-groups or sub-blocks) by circular systematic sampling with equal probability. (3) Under the rotation sampling scheme which was adopted for the first time in the National Sample Survey, 50% of the sample first stage units in the central sample were revisited in the subsequent three-month period. In state samples, the first stage units were only visited once.

SAMPLE UNIT: Household

SAMPLE FRACTION: .07%

SAMPLE SIZE (person records): 596,688

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 8 sections: 1) identification of sample household, 2) household characteristics, 3) demographic and migration particulars, 4) usual principal activity, 5) subsidiary activity, 6) current work activity during the preceding week, 5) follow-up questions for the unemployed, 6) availability for work to working persons, 7) job change of working persons, and 8) questions for females.

Response rate

COVERAGE: 100% of the Indian Union excepting (1) Ladakh and Kargil districts of Jammu and Kashmir, (2) interior villages of Nagaland situated beyond 5 kms. of a bus route, and (3) villages of Andaman and Nicobar Islands remaining inaccessible throughout the year. Also excluded were all the uninhabited villages according to 1991 census.

The 2019 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some states and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Abstract

The Employment and Unemployment surveys of National sample Survey (NSS) are primary sources of data on various indicators of labour force at National and State levels. These are used for planning, policy formulation, decision support and as input for further statistical exercises by various Government organizations, academicians, researchers and scholars. NSS surveys on employment and un-employment with large sample size of households have been conducted quinquennially from 27th. round(October'1972 - September'1973) onwards. Cotinuing in this series the fourth such all-india survey on the situation of employment and unemployment in India was carried out during the period july 1987 - june 1988 .

The working Group set up for planning of the entire scheme of the survey, among other things, examined also in detail some of the key results generated from the 38th round data and recommended some stream-lining of the 38th round schedule for the use in the 43rd round. Further, it felt no need for changing the engaging the easting conceptual frame work. However, some additional items were recommended to be included in the schedule to obtain the necessary and relevant information for generating results to see the effects on participation rates in view of the ILO suggestions.5.0.1. The NSSO Governing Council approved the recommendations of the working Group and also the schedule of enquiry in its 44th meeting held on 16 January, 1987. In this survey, a nation-wide enquiry was conducted to provide estimates on various characteristics pertaining to employment and unemployment in India and some characteristics associated with them at the national and state levels. Information on various facets of employment and unemployment in India was collected through a schedule of enquiry (schedule 10).

Geographic coverage

The survey covered the whole of Indian Union excepting i) Ladakh and Kargil districts of Jammu & Kashmir ii) Rural areas of Nagaland

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

It may be mentioned here that in order to net more households of the upper income bracket in the Sample , significant changes have been made in the sample design in this round (compares to the design of the 38th round).

SAMPLE DESIGN AND SAMPLE SIZE The survey had a two-stage stratified design. The first stage units (f.s.u.'s) are villages in the rural sector and urban blocks in the urban sector. The second stage units are households in both the sectors. Sampling frame for f.s.u.'s : The lists of 1981 census villages constituted the sampling frame for rural sector in most districts. But the 1981 census frame could not be used for a few districts because, either the 1981 census was not held there or the list of 1981 census villages could not be obtained or the lists obtained from the census authorities were found to be grossly incomplete. In such cases 1971 census frame were used. In the urban sector , the Urban Frame Survey (U.F.S.) blocks constituted the sampling frame. STRATIFICATION : States were first divided into agro-economic regions which are groups of contiguous districts , similar with respect to population density and crop pattern. In Gujarat, however , some districts have been split for the purpose of region formation In consideration of the location of dry areas and the distribution of the tribal population in the state. The composition of the regions is given in the Appendix. RURAL SECTOR: In the rural sector, within each region, each district with 1981Census rural population less 1.8 million formed a single stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils similar, as for as possible, in respect of rural population Density and crop pattern. (In Gujarat, however , in the case of districts extending over more than one region, even if the rural population was less than 1.8 million, the portion of a district falling in each region constituted a separate stratum. Further ,in Assam the old "basic strata" formed on the basis of 1971 census rural population exactly in the above manner, but with cut-off population as 1.5 million have been retained as the strata for rural sampling.) URBAN SECTOR : In the urban sector , strata were formed , again within NSS region , on the basis of the population size class of towns . Each city with population 10 lakhs or more is self-representative , as in the earlier rounds . For the purpose of stratification, in towns with '81 census population 4 lakhs or more , the blocks have been divided into two categories , viz . : One consisting of blocks in areas inhabited by the relatively affluent section of the population and the other consisting of the remaining blocks. The strata within each region were constituted as follows :

Table (1.2) : Composition of urban strata

Stratum population class of town

number

(1) (2)

1 all towns with population less than 50,000 2 -do- 50,000 - 199,999 3 -do- 200,000 - 399,999 4 -do- 400,000 - 999,999 ( affluent area) 5 (other area) 6 a single city with population 1 million and above (affluent area) 7 " (other area) 8 another city with population 1 million and above

9 " (other area)

Note : There is no region with more than one city with population 1 million and above. The stratum number have been retained as above even if in some regions some of the strata are empty. Allocation for first stage units : The total all-India sample size was allocated to the states /U.T.'s proportionate to the strength of central field staff. This was allocated to the rural and urban sectors considering the relative size of the rural and urban population. Now the rural samples were allocated to the rural strata in proportion to rural population. The urban samples were allocated to the urban strata in proportion to urban population with double weight age given to those strata of towns with population 4 lakhs or more which lie in area inhabited by the relatively affluent section. All allocations have been adjusted such that the sample size for stratum was at least a multiple of 4 (preferably multiple of 8) and the total sample size of a region is a multiple of 8 for the rural and urban sectors separately.
Selection of f.s.u.'s : The sample villages have been selected circular systematically with probability proportional to population in the form of two independent interpenetrating sub-samples (IPNS) . The sample blocks have been selected circular systematically with equal probability , also in the form of two IPNS' s. As regards the rural areas of Arunachal Pradesh, the procedure of 'cluster sampling' was:- The field staff will be supplied with a list of the nucleus villages of each cluster and they selected the remaining villages of the cluster according to the procedure described in Section Two. The nucleus villages were selected circular systematically with equal probability, in the form of two IPNS 's. Hamlet-group and sub-blocks : Large villages and blocks were sub- divided into a suitable number of hamlet-groups and sub-blocks respectively having equal population convent and one them was selected at random for surveys. Hamlet-group and sub-blocks : Large villages and blocks were sub- divided into a suitable number of hamlet-groups and sub-blocks respectively having equal population convent and one them was selected at random for surveys. Selection of households : rural : In order to have adequate number of sample households from the affluent section of the society, some new procedures were introduced for selection of sample households, both in the rural and urban sectors. In the rural sector , while listing households, the investigator identified the households in village/ selected hamlet- group which may be considered to be relatively more affluent than the rest. This was done largely on the basis of his own judgment but while exercising his judgment considered factors generally associated with rich people in the localitysuch as : living in large pucca house in well-maintained state, ownership/possession of cultivated/irrigated land in excess of certain norms. ( e.g.20 acres of cultivated land or 10 acres of irrigated land), ownership of motor vehicles and costly consumer durables like T.V. , VCR, VCP AND refrigerator, ownership of large business establishment , etc. Now these "rich" households will form sub-stratum 1. (If the total number of households listed is 80 or more , 10 relatively most affluent households will form sub-stratum 1. If it is below 80, 8 such households will form sub-stratum 1. The remaining households will 'constitute sub-stratum 2. At the time of listing, information relating to each household' s major sources of income will be collected, on the basis of which its means of livelihood will be identified as one of the following : "self-employed in non-agriculture " "rural labour" and "others" (see section Two for definition of these terms) . Also the area of land possessed as on date of survey will be ascertained from all households while listing. Now the households of sub-stratum 2 will be arranged in the order : (1)self-employed in non-agriculture, (2) rural labour, other households, with land possessed (acres) : (3) less than 1.00 (4) 1.00-2.49,(5)2.50-4.99, (6)

In 2024, Germany was the leading EU country in terms of population, with around 85 million inhabitants. In 2050, approximately 89.2 million people will live in Germany, according to the forecast. See the total EU population figures for more information. The global population The global population is rapidly increasing. Between 1990 and 2015, it increased by around 2 billion people. Furthermore, it is estimated that the global population will have increased by another 1 billion by 2030. Asia is the continent with the largest population, followed by Africa and Europe. In Asia,the two most populous nations worldwide are located, China and India. In 2014, the combined population in China and India alone amounted to more than 2.6 billion people. for comparison, the total population in the whole continent of Europe is at around 741 million people. As of 2014, about 60 percent of the global population was living in Asia, with only approximately 10 percent in Europe and even less in the United States. Europe is the continent with the second-highest life expectancy at birth in the world, only barely surpassed by Northern America. In 2013, the life expectancy at birth in Europe was around 78 years. Stable economies and developing and emerging markets in European countries provide for good living conditions. Seven of the top twenty countries in the world with the largest gross domestic product in 2015 are located in Europe.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

Excluded populations living in Northeast states and remote islands and Jammu and Kashmir. The excluded areas represent less than 10 percent of the total population.

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for India is 3000.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Abstract

The 2015-16 National Family Health Survey (NFHS-4), the fourth in the NFHS series, provides information on population, health, and nutrition for India and each state and union territory. For the first time, NFHS-4 provides district-level estimates for many important indicators. All four NFHS surveys have been conducted under the stewardship of the Ministry of Health and Family Welfare (MoHFW), Government of India. MoHFW designated the International Institute for Population Sciences (IIPS), Mumbai, as the nodal agency for the surveys. Funding for NFHS-4 was provided by the United States Agency for International Development (USAID), the United Kingdom Department for International Development (DFID), the Bill and Melinda Gates Foundation (BMGF), UNICEF, UNFPA, the MacArthur Foundation, and the Government of India. Technical assistance for NFHS-4 was provided by ICF, Maryland, USA. Assistance for the HIV component of the survey was provided by the National AIDS Control Organization (NACO) and the National AIDS Research Institute (NARI), Pune.

Geographic coverage

National coverage

Analysis unit

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The NFHS-4 sample was designed to provide estimates of all key indicators at the national and state levels, as well as estimates for most key indicators at the district level (for all 640 districts in India, as of the 2011 Census). The total sample size of approximately 572,000 households for India was based on the size needed to produce reliable indicator estimates for each district and for urban and rural areas in districts in which the urban population accounted for 30-70 percent of the total district population. The rural sample was selected through a two-stage sample design with villages as the Primary Sampling Units (PSUs) at the first stage (selected with probability proportional to size), followed by a random selection of 22 households in each PSU at the second stage. In urban areas, there was also a two-stage sample design with Census Enumeration Blocks (CEB) selected at the first stage and a random selection of 22 households in each CEB at the second stage. At the second stage in both urban and rural areas, households were selected after conducting a complete mapping and household listing operation in the selected first-stage units.

The figures of NFHS-4 and that of earlier rounds may not be strictly comparable due to differences in sample size and NFHS-4 will be a benchmark for future surveys. NFHS-4 fieldwork for Bihar was conducted in all 38 districts of the state from 16 March to 8 August 2015 by the Academic Management Studies (AMS) and collected information from 36,772 households, 45,812 women age 15-49 (including 7,464 women interviewed in PSUs in the state module), and 5,872 men age 15-54.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires - household, woman's, man's, and biomarker, were used to collect information in 19 languages using Computer Assisted Personal Interviewing (CAPI).

Abstract

Through this schedule, it is aimed to collect information relating to availability of some general facilities to the villagers like education, Facilities for cultural activities and health and Facilities for disabled persons. If a facility is available in general to the villagers, it is considered as a facility. The required information has been obtained by contacting the village officials and / or other knowledgeable person(s). In case they were not aware of the existence of a particular facility, the nearest Block Development Officer or other related Agencies were contacted for collection of the relevant information.

Geographic coverage

Geographical coverage: The survey covered the whole of the Indian Union except (i) Leh and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Randomly selected villages based on sampling procedure

Universe

The survey covered randomly selected rural villages of the country

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified two stage sample design was adopted for the NSS 47th round. The first stage units were in most cases 1981 census villages in rural areas. In some areas where either the 1981 census was not undertaken or the available list was incomplete, the list of 1971 census villages were used.

Stratification: States are first divided into agroeconomic regions by grouping contiguous districts which are similar in respect of population density and crop pattern. In Gujarat, however, some districts have been split for the purpose of region formation in consideration of the allocation of dry areas and distribution of tribal population in the state. In the rural sector, within each region each district with the 1981 census rural population less than 1.8 million formed a separate stratum. Districts with largest population are divided in to two or more strata depending on population, by grouping contiguous tehsils similar, as far as possible, in respect of rural population density and crop pattern.In Gujarat, however, in case of districts extending over more than one region, even if the rural population was less than 1.8 million , the portion of a district falling in each region constituted a separate stratum.

Selection of FSUs: The sample villages have been selected circular systematically with probability proportional to population in the form of two independent sub-samples. The sample blocks have been selected circular systematically with equal probability also in the form of two independent subsamples. The number of sample villages surveyed in this round were 4373, and the sample size for the Village Facilities Survey was 4298.

More information on sample design for this survey round is available in Section Two of the Report 391 NSS47 Round.pdf available under external resources.

Mode of data collection

Face-to-face [f2f]

Research instrument

Schedule 3.1 consists of the following blocks:

Block 1: identification of sample village Block 2: particulars of field operation Block 3: distance from nearest facility Block 4: remarks by investigator Block 5: comments by supervisory officer(s)

Blocks 3 is the main block of this schedule and is meant for recording the information relating to distance of specified facilities from the centre of the sample village. Blocks 1is meant for recording the identification particulars of the sample village. Block 2, 5 and 6 are used for official purposes to record the particulars relating to field operations, Remarks of the investigators and those of the supervisory officer(s) respectively.

India has the world’s second-largest HIV burden. Key populations of female sex workers (FSW), men who have sex with men (MSM), hijra/transgender (H/TG) people, and people who inject drugs (PWID), are disproportionately affected by the HIV epidemic. A community-led programmatic mapping and population size estimation (PMPSE) was carried out in 651 districts of 32 States and Union Territories of India. The goal was to identify the hotspots, network operators, and estimate the size of key population groups. This involved documenting the known hotspots, visiting them for rapid field assessment through key informants’/ network operators interviews, and identifying additional hotspots/ network operators through the snow-balling approach from the existing hotspots. For each identified hotspot, network operator, and village, size of each key population group was estimated after adjusting for the duplications and overlaps. These estimates were then aggregated to arrive at district, State, and ultimately national-level estimates. PMPSE estimated a total of 9,95,499 (9,02,277–10,88,712) FSWs, 3,51,020 (3,13,860–3,88,175) MSM, 2,88,717 (2,53,024-3,24,407) PWIDs, and 96,193 (85,206-1,07,174) H/TG individuals. The number of FSWs per 1000 adult women in different States/Union Territories (UT) varied from 0.34 to 17.25; MSM estimates ranged from 0.07 to 7.35 per 1000 adult men, H/TG persons ranged from 0.03 to 2.75 per 1000 adult men, and PWIDs ranged from 0.01 to 31.30 per 1000 adult men. Additionally, approximately 14% of FSWs, 7% of MSM, and 8% of H/TG individuals were estimated to operate exclusively through network operators. The community-led PMPSE has updated the size estimates for FSWs, MSM, PWIDs, and H/TG individuals at a granular level. This approach has emphatically quantified the presence of network operators. The methodological simplicity of the present round of PMPSE is likely to encourage and facilitate its periodic implementation for better tracking of population level changes in HIV burden based on more reliable denominators.

State/UT-wise distribution of districts by H/TG people size estimates categories from PMPSE 2020–22.

Geographic coverage

The survey covers the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

For Leh (Ladakh) and Kargil districts of Jammu & Kashmir there is no separate sample first-stage units (FSUs) for "central sample". For these two districts, sample FSUs drawn as "state sample" will also be treated as central sample. The state directorate of economics and statistics (DES) will provide a copy of the filled-in schedules to Data Processing Division of NSSO for processing.

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

Outline of sample design: A stratified multi-stage design has been adopted for the 66th round survey. The first stage units (FSU) are the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. In addition, two non-UFS towns of Leh and Kargil of Jammu & Kashmir are also treated as FSUs in the urban sector. The ultimate stage units (USU) are households in both the sectors. In case of large FSUs, one intermediate stage of sampling is the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each rural/ urban FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (henceforth the term "village" would mean Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of latest available UFS blocks is considered as the sampling frame. For non-UFS towns, frame consists of the individual towns (only two towns, viz., Leh & Kargil constitute this frame).

Stratification: Within each district of a State/ UT, generally speaking, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, wherever there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them forms a separate basic stratum and the remaining urban areas of the district are considered as another basic stratum.

Sub-stratification: There is no sub-stratification in the urban sector. However, to net adequate number of child workers, for all rural strata, each stratum has been divided into 2 sub-strata as follows: sub-stratum 1: all villages with proportion of child workers (p) >2P (where P is the average proportion of child workers for the sate/ UT as per Census 2001) sub-stratum 2: remaining villages

Total sample size (FSUs): 12784 FSUs for central sample and 15132 FSUs for state sample have been allocated at all-India level. Further, data of 24 state sample FSUs of Leh and Kargil districts of J & K surveyed by DES, J & K will be included in the central sample

Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to a minimum sample allocation to each State/ UT. While doing so, the resource availability in terms of number of field investigators has been kept in view.

Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample size is allocated between two sectors in proportion to population as per census 2001 with double weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 16 FSUs (to the extent possible) is allocated to each state/ UT separately for rural and urban areas. Further the State level allocations for both rural and urban have been adjusted marginally in a few cases to ensure that each stratum/ sub-stratum gets a minimum allocation of 4 FSUs.

Allocation to strata/ sub-strata: Within each sector of a State/ UT, the respective sample size is allocated to the different strata/ sub-strata in proportion to the population as per census 2001. Allocations at stratum/ sub-stratum level are adjusted to multiples of 4 with a minimum sample size of 4 and equal number of samples has been allocated among the four sub rounds.

Selection of FSUs: For the rural sector, from each stratum/ sub-stratum, required number of sample villages has been selected by probability proportional to size with replacement (PPSWR), size being the population of the village as per Census 2001. For urban sector, from each stratum FSUs have been selected by using Simple Random Sampling Without Replacement (SRSWOR). Both rural and urban samples have been drawn in the form of two independent sub-samples.

More information on sampling and estimation procedure is available in the document " Note on Sample Design and Estimation Procedure of NSS 66th Round". including information on: - Formation and selection of hamlet-groups/ sub-blocks - Listing of households - Formation of second stage strata and allocation of households - Selection of households - Estimation Procedure

Mode of data collection

Face-to-face [f2f]

Research instrument

During this round, the following schedules of enquiry were canvassed: - Schedule 0.0 : list of households
- Schedule 1.0 : consumer expenditure (Type 1 and Type 2) - Schedule 10 : employment and unemployment

In the present round, Schedule 10 on employment-unemployment consists of 16 blocks.

The first three blocks, viz. Blocks 0, 1 and 2, are used to record identification of sample households and particulars of field operations, as is the common practice in usual NSS rounds. The last two blocks, viz., Blocks 10 and 11 are to record the remarks of investigator and comments by supervisory officer(s), respectively.

Block 3 will be used for recording the household characteristics, like household size, religion, social group, land possessed, land cultivated, etc. For the rural households information will also be collected, in Block 3, on whether the household has NREG job card, whether got work in NREG works during the last 365 days, number of days got work in NREG works and mode of payment of the wages earned in NREG works. Besides, some particulars about holding of specified Post Office accounts and use of specified Postal services will also be collected in this block.

Block 3.1 is for recording particulars of indebtedness of rural labour households.

Block 4 will be used for recording the demographic particulars and attendance in educational institutions of the household members. Particulars of vocational training being received/received by the household members will also be collected in this block.

In Block 5.1, particulars of usual principal activity of all the household members will be recorded along with some particulars of the enterprises in which the usual status workers (excluding those in crop and plantation activities) are engaged. In this block information for all the workers about the location of workplace will also be collected. For the self-employed persons who are working under specifications (wholly or mainly), information will also be collected about "who provided credit/raw materials/equipments", "basis of payment" and "number of outlets of disposal". Information on informal employment will also be collected in Block 5.1. Similarly, the particulars of one subsidiary economic activity of the household members along with some particulars of the enterprises, informal employment and details of the self-employed persons in their subsidiary activity will be recorded in Block 5.2. The daily time disposition for the seven days preceding the date of survey along with the corresponding activity particulars will be recorded for each household member in Block 5.3. Besides this, the current weekly status (CWS) will be derived from the daily time disposition data and will be recorded in this block. As in the past, wage and salary earnings and mode of payment will also be collected for regular salaried/wage employees and for the casual labourers in this block. Block 6 will be used to record the responses to the probing questions to the persons who were unemployed on all the seven days of the reference week.

Blocks 7.1 and 7.2 contain the probing questions which are related to the under-utilisation of labour time and labour mobility, respectively.

For the members of the household classified as engaged in 'domestic duties' as per their usual principal status, some follow-up questions have been framed and listed in Block 8, with a view to collecting some additional information which might explain as to whether their usual attachment to domestic duties was voluntary or involuntary and also to throw light on their participation in some specified activities for family gain.

A worksheet to obtain the total monthly household consumer expenditure has been provided in Block 9.