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.

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 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.

This feature layers contain demographics about age, gender, education, employment, assets & amenities as reported by Office of the Registrar General & Census Commissioner, India in the Census 2011. These attributes cover topics such as male and female population counts by age, literacy, occupation, and household characteristics.Census of India counts every resident in India at village level. It is mandated by The Census Act 1948 of the Constitution and takes place every 10 years.Other demographics layers are also available:Country DemographicsDistrict DemographicsSub-district DemographicsVillage DemographicsCombined DemographicsEach layer contains the same set of demographic attributes. Each geography level has a viewing range optimal for the geography size, and the map has increasing detail as you zoom in to smaller areas.Data source: Explore Census DataAdmin boundary source (country, states, and districts): Survey of India, 2020For more information: 2011 Census Demographic ProfileFor feedback please contact: content@esri.inData Processing notes:Country, State and District boundaries are simplified representations offered from the Survey of India database.Sub-districts and village boundaries are developed based on the census provided maps.Field names and aliases are processed by Esri India as created for the ArcGIS Platform.For a list of fields and alias names, access the following excel document.Disclaimer:The boundaries may not be perfectly align with AGOL imagery. The Census PDF maps are georeferenced using Survey of India boundaries and notice alignment issues with AGOL Imagery/ Maps. 33k villages are marked as point location on Census PDFs either because of low scale maps where small villages could not have been drawn or digitization has not been completed. These villages are marked as 100m circular polygons in the data.This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know via content@esri.in.

In 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

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

india - Population Growth for India was 0.88329 % Chg. at Annual Rate in January of 2023, according to the United States Federal Reserve. Historically, india - Population Growth for India reached a record high of 0.88329 in January of 2023 and a record low of 0.79020 in January of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for india - Population Growth for India - last updated from the United States Federal Reserve on June of 2025.

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

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)

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.

Abstract

The 44th round started from July 1988. The survey period of this round was July 1988 to June 1989. This round has been devoted to mainly three enquiries. First and foremost, there has been an enquiry on the living condition of the tribal population. Of the other two, one is concerned with the housing condition of the general population and the other is a survey on current building construction activity. For the purpose of this enquiry, “tribal population” mean the members of the Scheduled Tribes declared under the Article 342 of the Constitution of India. They are known to be the descendants of the earliest inhabitants of India (hence called “Adivasis”). At present, in most parts of India, they form one of the economically weakest sections of the society. So far there has not been any systematic study of their living conditions covering the whole country. Whatever data are available are derived from the decennial censuses, apart from some micro studies carried out by social anthropologists. In the NSS the tribal population has always been covered as part of the general population. In NSS 32nd and 33rd rounds special surveys had been carried out through an integrated schedule (schedule 16.4) in the North-Eastern region. The survey was conducted in the rural areas of the following States:- 32nd round : Arunachal Pradesh, Assam (N. Cachar and Karbi Anglong districts only), Manipur, Meghalaya and Tripura; 33rd round: In addition to the above States, Mizoram also. Even though this covered many aspects specially related to the life of the people of this region (who are mostly tribals), no such survey has so far been undertaken about the life of the tribals living in the main tribal belt stretching from West Bengal through Bihar, Orissa, Madhya Pradesh to Gujarat and Rajasthan. The scope of the enquiry is to understand the living condition of the tribals living in the main tribal belt stretching from West Bengal through Bihar, Orissa, Madhya Pradesh to Gujarat and Rajasthan.) The object of the enquiry in the this round is to throw light on as many aspects as possible of the tribal population of this country. This relates to aspects of their “level of the living” including demographic and activity particulars, family expenditure etc. as well as to their entrepreneurial activities.

Geographic coverage

The survey covered the whole of Indian Union except Ladakh and Kargil districts of Jammu and Kashmir state. The rural areas of Nagaland, so far outside NSS coverage up to the 43rd round, have also been brought in this round.

Analysis unit

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

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design is stratified two-stage with the census village as the first stage unit in the rural sector and UFS block as the first stage unit in the urban sector. The second stage units are households.

The sample design in the rural sector has been decided with a view to providing good estimates for the tribal enquiry. Except in the north-eastern region, the tribal population is concentrated in some districts within the states having considerable tribal population and even in those districts they are found to be unevenly distributed geographically. Therefore special stratification and selection procedures have been adopted not only to net sufficient number of tribal households in the sample but also to improve the design in general for the tribal enquiry.

While the rural design is oriented towards the tribal enquiry, the urban design is oriented towards the enquiry on construction. As building construction activity is found to be concentrated in some areas in the urban sector, attempts have been made in urban design to demarcate such areas in larger towns as separate strata. Detailed description of the rural and urban sample designs are as follows:

SAMPLE DESIGN : RURAL

Sampling frame of villages: The list of 1981 census villages constitute the sampling frame for selection of villages in most districts. However in Assam (where '81 census was not done) and a few districts of some other states (where the available lists of villages were not satisfactory), 1971 census village lists have been used as frame.

Stratification :
In Haryana, Jammu & Kashmir, Punjab, Chandigarh, Delhi, Goa, Daman & Diu and Pondicherry where there are practically no tribal population, the strata used in NSS 43rd round were retained. In Meghalaya, Mizoram, Nagaland, Arunachal Pradesh, Sikkim, Dadra and Nagar Haveli and Lakshadweep also the strata of 43rd round were retained because of the high percentage of ST population in these States/U.T.'s. (The strata of 43rd round have been retained in the case of Sikkim as the distribution of tribal population is more or less uniform over all the districts). In the remaining states fresh stratification was carried out as described below.

In these states all districts accounting for the bulk of the state's tribal population were selected for formation of strata with concentration of tribal population. Besides these districts, tribal concentration strata have been demarcated also in some other districts with relatively small tribal population in order to ensure coverage of as many different ethnic groups as possible.

Within each district so identified for formation of tribal concentration strata, the tehsils with relatively high concentration of tribal population, together constituted one stratum. These tehsils were selected in such a way that together they accounted for the bulk (70% or more) of the district tribal population and the proportion of tribal to total population in this stratum was significantly greater than that of the district as a whole. The strata so formed were not always geographically contiguous. These tribal concentration strata are called STRATUM TYPE -1. Further, all the strata of Meghalaya, Mizoram, Nagaland, Arunachal Pradesh, Dadra & Nagar Haveli, Lakshadweep and Sikkim are also considered as stratum type-1. All the remaining strata in the rural sector (in any State/U.T.) are called stratum type -2.

Sampling deviation

There was no deviation from the original sampling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

NSS Round 44 Schedule 29.2 consists of 17 blocks as enumerated below:

Block 1: identification of sample household Block 2: particulars of field operations Block 3: remarks by investigator Block 4: remarks by supervisory officer (s) Block 5: household characteristics Block 6: demographic particulars of household members Block 7: particulars of assistance received by the household during last 3 years Block 8: particulars of land owned and possessed Block 9: particulars of disposal of land during last 5 years Block 10: information on input items for cultivation during 1987-88 Block 11: particulars of crops produced during 1987-88 Block 12: particulars of wage employment in forest and forestry operation
Block 13: particulars of forest produce collected, consumed at home and sold by household members during last 30 days as self-employed Block 14: particulars of household enterprise (other than cultivation) during last 30 days Block 15: particulars of products (other than forest products) marketed during last 30 days Block 16 : inventory of assets owned on the date of survey Block 17 : cash dues and grain & other commodity dues payable by the household as on the date of survey and particulars of transaction of loans during last 365 days

The share of projected population increase in Uttar Pradesh, India from 2011 until 2036 is expected to grow by nearly ** percent. By contrast, the estimated population increase in Uttarakhand is expected to be less than *** percent during the same time period.

Why project population?
Population projections for a country are becoming increasingly important now than ever before. They are used primarily by government policy makers and planners to better understand and gauge future demand for basic services that predominantly include water, food and energy. In addition, they also support in indicating major movements that may affect economic development and in turn, employment and labour productivity. Consequently, this leads to amending policies in order to better adapt to the needs of society and to various circumstances.

Demographic projections and health interventions Demographic figures serve the foremost purpose of improving health and health related services among the population. Some of the government interventions include antenatal and neonatal care with the aim of reducing maternal and neonatal mortality and morbidity rates. In addition, it also focuses on improving immunization coverage across the country. Further, demographic estimates help in better preempting the needs of growing populations, such as the geriatric population within a country.

Abstract

The National Sample Survey Organisation (NSSO) has been set up by the Government of India in 1950 to collect socio-economic data employing scientific sampling methods. The NSSO conducts regular consumer expenditure surveys as part of its "rounds", each round being normally of a year's duration and covering more than one subject of study. The surveys are conducted through household interviews, using a random sample of households covering practically the entire geographical area of the country. Surveys on consumer expenditure are being conducted quinquennially on a large sample of households from the 27th round (October 1972 - September 1973) onwards. The fourth quinquennial survey on household consumer expenditure was carried out during July 1987 - June 1988. The three previous surveys of this series were carries out in the 27th (October-September 1973) , the 32nd (July 1977 to June 1978) and the 38th (January to December , 1983) rounds of the NSSO. The present survey like the previous one, covered the entire population. Expenditure incurred by the sample household for the purpose of domestic consumption were collected for the 30 days preceding the date of survey. No account has, however, been taken of any expenditure incurred towards the productive enterprises of the household. It may be mentioned here that in order to get more households of the upper income bracket in the Sample , significant changes have been made in the sample design in this round (compared to the design of the 38th round). The survey covered the whole of Indian Union excepting: i) Ladakh and Kargil districts of Jammu & Kashmir ii) Rural areas of Nagaland

The field work for the survey was conducted, as usual, by the Field Operations Division of the Organisation. The collected data were processed by the Data Processing Division of NSSO and tabulated by the Computer Centre of Department of Statistics. The reports have been prepared by Survey Design & Research Division (SDRD) of NSSO under the guidance of the Governing Council, NSSO.

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

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey will have a two-stage stratified design. The first stage units (f.s.u.s) or 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 constitute 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 have been used. In the urban sector , the Urban Frame Survey (U.F.S.) blocks constitute the sampling frame.

Stratification: States are 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.

RURAL SECTOR: In the rural sector, within each region, each district with 1981 Census rural population less 1.8 million forms 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 are 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 1981 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.

Allocation for first stage units: The total all-India sample size has been 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.

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.

Sample size (central sample): The all India sample in respect of the central sample consists of 8518 villages and 4648 blocks.

Sample size (state sample): All the states and Union Territories except Andaman & Nicobar Islands, Chandigarh, Dadra & Nagar Haveli and Lakshadweep are participating in this round at least on an equal matching basis.

Sampling deviation

There was no deviation from the original sampling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

The NSSO surveys on consumer expenditure aim to measure the household consumer expenditure in quantitative terms disaggregated by various household characteristics.

The data for this survey is collected in the NSS Schedule 1.0 used for household consumer expenditure. For this round, the schedule had 11 blocks.

Blocks 1 and 2 - are similar to the ones used in usual NSS rounds. These are used to record identification of sample households and particulars of field operations.

Block-3: Household characteristics like, household size, principal industry-occupation, social group, land possessed and cultivated, type of dwelling etc. are recorded in this block.

Block-4: In this block the detailed demographic particulars including age, sex, educational level, marital status, number of meals usually taken in a day etc. are recorded.

Block-5: In this block cash purchase and consumption of food, pan, tobacco, intoxicants and fuel & light during the last 30 days are recorded.

Block-6: Consumption of clothing during the last 30 and 365 days is recorded in this block.

Block-7: Consumption of footwear during the last 30 and 365 days is recorded in this block.

Block-8 : Expenditure on miscellaneous goods and services and rents and taxes during the last 30 days has been recorded in this block.

Block-9 : Expenditure for purchase and construction (including repairs) of durable goods for domestic use is recorded here.

Block-10 : Particulars of dwelling units are recorded in this block.

Block-11 : Summary of consumer expenditure during last 30 days is recorded in this block.

Census: Population: Punjab data was reported at 27,743,338.000 Person in 03-01-2011. This records an increase from the previous number of 24,358,999.000 Person for 03-01-2001. Census: Population: Punjab data is updated decadal, averaging 10,367,652.500 Person from Mar 1901 (Median) to 03-01-2011, with 12 observations. The data reached an all-time high of 27,743,338.000 Person in 03-01-2011 and a record low of 6,731,510.000 Person in 03-01-1911. Census: Population: Punjab data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAB002: Census: Population: by States.

Data set of a community based cross-sectional survey done to find the prevalence , its correlates and patterns in a population of a district in southern Kerala, IndiaBackground: Multi-morbidity is the coexistence of multiple chronic conditions in the same individual. With advancing epidemiological and demographic transitions, the burden of multi-morbidity is expected to increase India. The state of Kerala in India is also in an advanced phase of epidemiological transition. However, very limited data on prevalence of multi-morbidity are available in the Kerala population.

Methods: A cross sectional survey was conducted among 410 participants in the age group of 30-69 years. A multi-stage cluster sampling method was employed to identify the study participants. Every eligible participant in the household were interviewed to assess the household prevalence. A structured interview schedule was used to assess socio-demographic variables, behavioral risk factors and prevailing clinical conditions, PHQ-9 questionnaire for screening of depression and active measurement of blood sugar and blood pressure. Co-existence of two or more conditions out of 11 was used as multi-morbidity case definition. Bivariate analyses were done to understand the association between socio-demographic factors and multi-morbidity. Logistic regression analyses were performed to estimate the effect size of these variables on multi-morbidity.

Results: Overall, the prevalence of multi-morbidity was 45.4% (95% CI: 40.5-50.3%). Nearly a quarter of study participants (25.4%) reported only one chronic condition (21.3-29.9%). Further, 30.7% (26.3-35.5), 10.7% (7.9-14.2), 3.7% (2.1-6.0) and 0.2% reported two, three, four and five chronic conditions, respectively. Nearly seven out of ten households (72%, 95%CI: 65-78%) had at least one person in the household with multi-morbidity and one in five households (22%, 95%CI: 16.7-28.9%) had more than one person with multi-morbidity. With every year increase in age, the propensity for multi-morbidity increased by 10 percent (OR=1.1; 95% CI: 1.1-1.2). Males and participants with low levels of education were less likely to suffer from multi-morbidity while unemployed and who do recommended level of physical activity were significantly more likely to suffer from multi-morbidity. Diabetes and hypertension was the most frequent dyad.

Conclusion: One of two participants in the productive age group of 30-69 years report multi-morbidity. Further, seven of ten households have at least one person with multi-morbidity. Preventive and management guidelines for chronic non-communicable conditions should focus on multi-morbidity especially in the older age group. Health-care systems that function within the limits of vertical disease management and episodic care (e.g., maternal health, tuberculosis, malaria, cardiovascular disease, mental health etc.) require optimal re-organization and horizontal integration of care across disease domains in managing people with multiple chronic conditions.

Key words: Multi-morbidity, cross-sectional, household, active measurement, rural, India, pattern

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

Census: Population: Lakshadweep data was reported at 64,473.000 Person in 03-01-2011. This records an increase from the previous number of 60,650.000 Person for 03-01-2001. Census: Population: Lakshadweep data is updated decadal, averaging 22,571.500 Person from Mar 1901 (Median) to 03-01-2011, with 12 observations. The data reached an all-time high of 64,473.000 Person in 03-01-2011 and a record low of 13,637.000 Person in 03-01-1921. Census: Population: Lakshadweep data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAB002: Census: Population: by States.

Abstract

In order to have a comprehensive picture of the farming community and to analyze the impact of the transformation induced by public policy, investments and technological change on the farmers' access to resources and income as well as well-being of the farmer households it was decided to collect information on Indian farmers through “Situation Assessment Survey” (SAS). The areas of interest for conducting SAS would include economic well-being of farmer households as measured by consumer expenditure, income and productive assets, and indebtedness; their farming practices and preferences, resource availability, and their awareness of technological developments and access to modern technology in the field of agriculture. In this survey, detailed information would be collected on receipts and expenses of households' farm and non-farm businesses, to arrive at their income from these sources. Income from other sources would also be ascertained, and so would be the consumption expenditure of the households.

Geographic coverage

National, State, Rural, Urban

Analysis unit

Houdeholds

Universe

All Households of the type : 1-self-employed in agriculture 2-self-employed in non-agriculture 3-regular wage/salary earning 4-casual labour in agriculture 5-casual labour in non-agriculture 6-others

Kind of data

Sample survey data [ssd]

Sampling procedure

Total sample size (FSUs): 8042 FSUs have been allocated for the central sample at all-India level. For the state sample, there are 8998 FSUs allocated for all-India. sample design: A stratified multi-stage design has been adopted for the 70th round survey. The first stage units (FSU) are the census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks 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 updated by excluding the villages urbanised and including the towns de-urbanised after 2001 census (henceforth the term 'village' would mean Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the latest updated list of UFS blocks (2007-12) is considered as the sampling frame.

Stratification:

(a) Stratum has been formed at district level. 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 all the urban areas of the district. However, within the urban areas of a district, if there were one or more towns with population 10 lakhs or more as per population census 2011 in a district, each of them formed a separate basic stratum and the remaining urban areas of the district was considered as another basic stratum.

(b) However, a special stratum in the rural sector only was formed at State/UT level before district- strata were formed in case of each of the following 20 States/UTs: Andaman & Nicobar Islands, Andhra Pradesh, Assam, Bihar, Chhattisgarh, Delhi, Goa, Gujarat, Haryana, Jharkhand, Karnataka, Lakshadweep, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh and West Bengal. This stratum will comprise all the villages of the State with population less than 50 as per census 2001.

(c) In case of rural sectors of Nagaland one special stratum has been formed within the State consisting of all the interior and inaccessible villages. Similarly, for Andaman & Nicobar Islands, one more special stratum has been formed within the UT consisting of all inaccessible villages. Thus for Andaman & Nicobar Islands, two special strata have been formed at the UT level:

(i) special stratum 1 comprising all the interior and inaccessible villages (ii) special stratum 2 containing all the villages, other than those in special stratum 1, having population less than 50 as per census 2001.

Sub-stratification:

Rural sector: Different sub-stratifications are done for 'hilly' States and other States. Ten (10) States are considered as hilly States. They are: Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Sikkim, Meghalaya, Tripura, Mizoram, Manipur, Nagaland and Arunachal Pradesh.

(a) sub-stratification for hilly States: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed was 'r/2'. The villages within a district as per frame have been first arranged in ascending order of population. Then sub-strata 1 to 'r/2' have been demarcated in such a way that each sub-stratum comprised a group of villages of the arranged frame and have more or less equal population.

(b) sub-stratification for other States (non-hilly States except Kerala): The villages within a district as per frame were first arranged in ascending order of proportion of irrigated area in the cultivated area of the village. Then sub-strata 1 to 'r/2' have been demarcated in such a way that each sub-stratum comprised a group of villages of the arranged frame and have more or less equal cultivated area. The information on irrigated area and cultivated area was obtained from the village directory of census 2001.

(c) sub-stratification for Kerala: Although Kerala is a non-hilly State but because of non-availability of information on irrigation at FSU (Panchayat Ward) level, sub-stratification by proportion of irrigated area was not possible. Hence the procedure for sub-stratification was same as that of hilly States in case of Kerala.

Urban sector: There was no sub-stratification for the strata of million plus cities. For other strata, each district was divided into 2 sub-strata as follows:

 sub-stratum 1: all towns of the district with population less than 50000 as per census 2011 
 sub-stratum 2: remaining non-million plus towns of the district

Allocation of total sample to States and UTs: The total number of sample FSUs have been allocated to the States and UTs in proportion to population as per census 2011 subject to a minimum sample allocation to each State/ UT.
Allocation to strata: Within each sector of a State/ UT, the respective sample size has been allocated to the different strata in proportion to the population as per census 2011. Allocations at stratum level are adjusted to multiples of 2 with a minimum sample size of 2. Allocation to sub-strata:

1 Rural: Allocation is 2 for each sub-stratum in rural.

2 Urban: Stratum allocations have been distributed among the two sub-strata in proportion to the number of FSUs in the sub-strata. Minimum allocation for each sub-stratum is 2. Selection of FSUs: For the rural sector, from each stratum x sub-stratum, required number of sample villages has been selected by Simple Random Sampling Without Replacement (SRSWOR). For the urban sector, FSUs have been selected by using Simple Random Sampling Without Replacement (SRSWOR) from each stratum x sub-stratum. Both rural and urban samples were drawn in the form of two independent sub-samples and equal number of samples has been allocated among the two sub rounds.

For details reexternal refer to external resouce "Note on Sample Design and Estimation Procedure of NSS 70th Round" Page no.2

Sampling deviation

There was no deviation from the original sampling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

There are 17 blocks in visit 1. In Visits 1 & 2, Each sample FSU will be visited twice during this round. Since the workload of the first visit (i.e. visit 1) will be more, the first visit will continue till the end of July 2013. Thus, period of the first visit will be January - July 2013 and that of the second visit (i.e. visit 2) will be August - December 2013.

india - Employment to Population Ratio for India was 53.23% in January of 2024, according to the United States Federal Reserve. Historically, india - Employment to Population Ratio for India reached a record high of 53.23 in January of 2024 and a record low of 47.50 in January of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for india - Employment to Population Ratio for India - last updated from the United States Federal Reserve on June of 2025.

Census: Population: Punjab: Female data was reported at 13,103,873.000 Person in 03-01-2011. This records an increase from the previous number of 11,373,954.000 Person for 03-01-2001. Census: Population: Punjab: Female data is updated decadal, averaging 4,749,729.500 Person from Mar 1901 (Median) to 03-01-2011, with 12 observations. The data reached an all-time high of 13,103,873.000 Person in 03-01-2011 and a record low of 2,949,274.000 Person in 03-01-1911. Census: Population: Punjab: Female data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAB002: Census: Population: by States.