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.

According to the 2011 census, the population density in the Indian state of Maharashtra was 365 individuals per square kilometer. Located on the Deccan Plateau, it is the second-most populous state in the country. A steady increase in the population of the state can be attributed to growing urban districts such as Mumbai and Pune, with diverse employment opportunities in several sectors.

India's economic powerhouse

With a contribution of over 22 trillion Indian rupees in the financial year 2017, the state of Maharashtra had the highest gross state domestic product in the country. A per capita income of over 175 thousand Indian rupees was estimated across the state for the preceding year. Based on its economic model, the state was a highly preferred destination for domestic and foreign investments.

The most populous Indian state

Mumbai, the capital city of Maharashtra, was the most populous city after Delhi. As the country's economic core, it serves as the financial and commercial capital while providing numerous job opportunities. Many are attracted to this dream city in search of a lucrative career and to make it big in the world-famous Bollywood film industry.

Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

Analysis of ‘Indian Census Data with Geospatial indexing’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sirpunch/indian-census-data-with-geospatial-indexing on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Dataset Description:

• This dataset has population data of each Indian district from 2001 and 2011 censuses.
• The special thing about this data is that it has centroids for each district and state.
• Centroids for a district are calculated by mapping border of each district as a polygon of latitude/longitude points in a 2D plane and then calculating their mean center.
• Centroids for a state are calculated by calculating the weighted mean center of all districts that constitutes a state. The population count is the weight assigned to each district.

Example Analysis:

• The complete code for calculating the centroids and web scraping for the data is shared on GitHub.

• The purpose of this project was to map population density center for each state.

• You can also read about the complete project here: https://medium.com/@sumit.arora/plotting-weighted-mean-population-centroids-on-a-country-map-22da408c1397

Output Screenshots: Indian districts mapped as polygons https://i.imgur.com/UK1DCGW.png" alt="Indian districts mapped as polygons">

Mapping centroids for each district https://i.imgur.com/KCAh7Jj.png" alt="Mapping centroids for each district">

Mean centers of population by state, 2001 vs. 2011 https://i.imgur.com/TLHPHjB.png" alt="Mean centers of population by state, 2001 vs. 2011">

National center of population https://i.imgur.com/yYxE4Hc.png" alt="National center of population">

--- Original source retains full ownership of the source dataset ---

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

The population density of the northern state of Uttar Pradesh in India recorded 829 people for every square kilometer in 2011, the latest available census. This was a doubling compared to the value in 1981.

The statistic displays the main states and union territories with the highest number of people living in urban areas in India in 2011. In that year, the state of Maharashtra had the highest population with over 50 million people living in urban areas. The population density in India from 2004 to 2014 can be seen here.

India population growth rate for 2023 was 0.88%, a 0.09% increase from 2022.

<ul style='margin-top:20px;'>

<li>India population growth rate for 2022 was <strong>0.79%</strong>, a <strong>0.03% decline</strong> from 2021.</li>
<li>India population growth rate for 2021 was <strong>0.82%</strong>, a <strong>0.15% decline</strong> from 2020.</li>
<li>India population growth rate for 2020 was <strong>0.97%</strong>, a <strong>0.07% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

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.

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

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.

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 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

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

Abstract

The India State-Level Disease Burden Initiative reported an unprecedented comprehensive assessment of the diseases causing the most premature deaths and ill-health in each state of the country, the risk factors responsible for this burden, and their trends spanning 26 years from 1990 to 2016. The burden from 333 disease conditions and injuries and 84 risk factors was computed for each state of India as part of the Global Burden of Disease Study 2016.

Documentation

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Methodology

The India State-Level Disease Burden Initiative was launched in October 2015. It is a collaboration between the Indian Council of Medical Research (ICMR), the Public Health Foundation of India (PHFI), Institute for Health Metrics and Evaluation (IHME), and senior experts and stakeholders currently from about 100 institutions across India. This Initiative reported an unprecedented comprehensive assessment of the diseases causing the most premature deaths and ill-health in each state of the country, the risk factors responsible for this burden, and their trends spanning 26 years from 1990 to 2016. The burden from 333 disease conditions and injuries and 84 risk factors was computed for each state of India as part of the Global Burden of Disease Study 2016.

The report “India: Health of the Nation's States — The India State-Level Disease Burden Initiative” details the main findings and is accompanied by the technical paper “Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study” published in The Lancet and an open access interactive visualization tool India GBD Compare to easily understand the disease burden trends over time across the states.

As of 2019, the south Indian state of Kerala had the highest density of doctors of about ** per ten thousand population in the country. However, Jharkhand had the least density of doctors in the country of about **** doctors per ten thousand people in the state.

Aim: Genetic diversity and forensic efficacy of 20 autosomal STR genetic markers were investigated in a highly diverse population of Rajasthan, a state in north-western India. Subjects and methods: In this study, 317 blood samples from unrelated healthy individuals were directly amplified using the PowerPlex® 21 multiplex system (Promega). Amplified products were separated by capillary electrophoresis using a Genetic Analyser –3500 XL (Thermo Fisher Scientific). The data thus obtained was statistically analysed using population genetic software. Results: The studied population showed genetic affinity with the geographically close populations. The locus Penta-E was found to be the most polymorphic with a value of 0.90 in the studied population. The combined discrimination power (CPD) and combined power of exclusion (CPE) were observed as >0.999999999 and 0.999999997, respectively, for all the studied 20 autosomal STR loci. The combined probability of match (CPm) was 1.39 × 10−25 and combined paternity index (CPI) was 3.66 × 108 for all the studied loci. Conclusion: The results conclusively support the hypothesis that the studied autosomal STR loci are polymorphic in nature and, besides being useful in forensic applications they can also be applied in anthropological and other population genetic studies. This study supports the ‘isolation-by-distance’ model. Genetic data obtained from this study will enrich the population data bank.

The COVID-19 pandemic has globally jeopardized food security, with heightened threats for the most vulnerable including smallholder farmers as well as rural, indigenous populations. A serial cross-sectional study was conducted to document effect of COVID-19 pandemic on food environment, agricultural practices, diets and food security, along with potential determinants of food systems resilience, among vulnerable smallholder farmer households in indigenous communities of Santhal, Munda, and Sauria Paharia of Jharkhand state, India. Telephonic household surveys were conducted in two phases i.e., lockdown and unlock phase to assess the impact of the pandemic on their food systems and agricultural practices. Market surveys were conducted during the unlock phase, to understand the impact on local informal markets. Secondary data on state and district level food production and Government food security programs were also reviewed. For data analysis purpose, a conceptual framework was developed which delineated possible pathways of impact of COVID-19 pandemic on food environment, food security and food consumption patterns along with factors that may offer resilience. Our findings revealed adverse effects on food production and access among all three communities, due to restrictions in movement of farm labor and supplies, along with disruptions in food supply chains and other food-related logistics and services associated with the pandemic and mitigation measures. The pandemic significantly impacted the livelihoods and incomes among all three indigenous communities during both lockdown and unlock phases, which were attributed to a reduction in sale of agricultural produce, distress selling at lower prices and reduced opportunity for daily wage laboring. A significant proportion of respondents also experienced changes in dietary intake patterns. Key determinants of resilience were identified; these included accessibility to agricultural inputs like indigenous seeds, labor available at household level due to back migration and access to diverse food environments, specifically the wild food environment. There is a need for programs and interventions to conserve and revitalize the bio-cultural resources available within these vulnerable indigenous communities and build resilient food systems that depend on shorter food supply chains and utilize indigenous knowledge systems and associated resources, thereby supporting healthy, equitable and sustainable food systems for all.

This study contains selected electoral and demographic national data for nine nations in the 1950s and 1960s. The data were prepared for the Data Confrontation Seminar on the Use of Ecological Data in Comparative Cross-National Research held under the auspices of the Inter-university Consortium for Political and Social Research on April 1-18, 1969. One of the primary concerns of this international seminar was the need for cooperation in the development of data resources in order to facilitate exchange of data among individual scholars and research groups. Election returns for two or more national and/or local elections are provided for each of the nine nations, as well as ecological materials for at least two time points in the general period of the 1950s and 1960s. While each dataset was received at a single level of aggregation, the data have been further aggregated to at least a second level of aggregation. In most cases, the data can be supplied at the commune or municipality level and at the province or district level as well. Part 1 (Germany, Regierungsbezirke), Part 2 (Germany, Kreise), Part 3 (Germany, Lander), and Part 4 (Germany, Wahlkreise) contain data for all kreise, laender (states), administrative districts, and electoral districts for national elections in the period 1957-1969, and for state elections in the period 1946-1969, and ecological data from 1951 and 1961. Part 5 (France, Canton), and Part 6 (France, Departemente) contain data for the cantons and departements of two regions of France (West and Central) for the national elections of 1956, 1962, and 1967, and ecological data for the years 1954 and 1962. Data are provided for election returns for selected parties: Communist, Socialist, Radical, Federation de Gauche, and the Fifth Republic. Included are raw votes and percentage of total votes for each party. Ecological data provide information on total population, proportion of total population in rural areas, agriculture, industry, labor force, and middle class in 1954, as well as urbanization, crime rates, vital statistics, migration, housing, and the index of "comforts." Part 7 (Japan, Kanagawa Prefecture), Part 8 (Japan, House of Representatives Time Series), Part 9 (Japan, House of (Councilors (Time Series)), and Part 10 (Japan, Prefecture) contain data for the 46 prefectures for 15 national elections between 1949 and 1968, including data for all communities in the prefecture of Kanagawa for 13 national elections, returns for 8 House of Representatives' elections, 7 House of Councilors' elections, descriptive data from 4 national censuses, and ecological data for 1950, 1955, 1960, and 1965. Data are provided for total number of electorate, voters, valid votes, and votes cast by such groups as the Jiyu, Minshu, Kokkyo, Minji, Shakai, Kyosan, and Mushozoku for the Communist, Socialist, Conservative, Komei, and Independent parties for all the 46 prefectures. Population characteristics include age, sex, employment, marriage and divorce rates, total number of live births, deaths, households, suicides, Shintoists, Buddhists, and Christians, and labor union members, news media subscriptions, savings rate, and population density. Part 11 (India, Administrative Districts) and Part 12 (India, State) contain data for all administrative districts and all states and union territories for the national and state elections in 1952, 1957, 1962, 1965, and 1967, the 1958 legislative election, and ecological data from the national censuses of 1951 and 1961. Data are provided for total number of votes cast for the Congress, Communist, Jan Sangh, Kisan Mazdoor Praja, Socialist, Republican, Regional, and other parties, contesting candidates, electorate, valid votes, and the percentage of valid votes cast. Also included are votes cast for the Rightist, Christian Democratic, Center, Socialist, and Communist parties in the 1958 legislative election. Ecological data include total population, urban population, sex distribution, occupation, economically active population, education, literate population, and number of Buddhists, Christians, Hindus, Jainis, Moslems, Sikhs, and other religious groups. Part 13 (Norway, Province), and Part 14 (Norway, Commune) consist of the returns for four national elections in 1949, 1953, 1957, and 1961, and descriptive data from two national censuses. Data are provided for the total number

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