The Census 2011 is the 15th National census survey conducted by the Census Organization of India. Mr. C. Chandramouli is the Commissioner & Registrar General of the Indian 2011 Census. The 2011 Indian National Census has been conducted in 2 phases - house listing and population. The national census survey covered all the 28 states of the country and 7 Union territories including 640 districts, 497 cities, 5767 tehsils & over 6 lakh villages. Census demographic data contains information like Households, Population enumeration, Literacy, Sex ratio, Child sex ratio (0–6 age group), etc.Source links for the Data are given below:Census of India, 2011This 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.

The Primary Census Abstract (PCA) for ‘Others’ give Total population, Population in the age group 0- 6, Scheduled Caste population, Scheduled Tribe population, Literates, Illiterates, Total workers, Main workers by the four broad industrial categories namely (i) Cultivators, (ii) Agricultural labourers, (iii) Household industry and (iv) Other work, Marginal workers classified by periodicity of work in two categories i.e. worked for 0-3 months and 3-6 months by four fold classification and also Non-workers at India/State/Union Territory level by residence i.e Total, Rural and Urban. It therefore, indicates the basic socio-economic characteristics of ‘Others’

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

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.

In 2011, 12.48 percent of the disabled population in Bihar were children up to six years old, making Bihar the region with the highest prevalence of disability among children. Meanwhile, children accounted for 11.41 percent of the population with disability in Meghalaya. In comparison, Kerala had the lowest prevalence of disability among children aged 0 to six years, at only 3.44 percent of the total disabled population in this region.

Abstract

This schedule is designed to collect the information on (a) participation of persons aged 5-29 years in the pursuit of education, (b) private expenditure incurred on the education of household members including those who are resident of Students' hostel at the time of survey, (c) examining the extent of educational wastage and their causes in terms of dropout and discontinuance and (d) IT literacy of persons aged 14 years and above. However, inclusions and exclusions, in a nutshell, are mentioned below.

Inclusions: I.School education commencing from class I to X or XII, as the case may be, irrespective of the recognition status of the educational institution, II.Higher secondary / Pre-university education leading to award of certificate/ diploma/ degree etc. including enrolment in private unrecognised institutions, which are authorised to sponsor students for public examinations as private or external candidates, III.General University education in Universities which are recognised by University Grant Commission(UGC), IV.Correspondence or distance learning courses conducted by Universities, Deemed Universities or Institutions, authorised by competent authorities for awarding regular degrees or diplomas or certificates, V.Technical or Professional courses, conducted by Universities, Deemed Universities or institutes like, National Institute of Fashion Technology, National School of Drama, Satyajit Ray Film and Television Institute, Film and Television Institute of India, Lok Nayak Jayaprakash Narayan National Institute of Criminology and Forensic Science, etc. or Institutions, authorised by competent authorities like All India Council of Technical Education (AICTE), Medical Council of India (MCI), The Institute of Chartered Accountants of India, The Institute of Cost and Works Accountants of India, The Institute of Company Secretaries of India, Actuarial Society of India, etc., leading to award of degree/diploma/certificates VI.All types of courses of duration three months or more, conducted by Institutions like Industrial Training Institute (ITI), National Vocational Training Institute, Regional Vocational Training Institutes, etc., authorised by competent authorities VII.Any course at primary level and above conducted by recognised educational institution not covered above.

Exclusions: I.Art, music and similar type of courses conducted by individuals in their houses or by unrecognised/ unaffiliated institutions, II.Classes taken by Private tutors, III.Education in nursery/Kindergartens/Preparatory levels except for their enrolment statuses and dropout / discontinuance statuses . IV.The non-formal system of education being implemented through various programmes by government or other agencies except for their enrolment statuses and discontinuance / dropout statuses.

Summary description of the schedule: In the present round, Schedule 25.2 on education and IT literacy consists of 10 blocks. The first three blocks, viz., Block 0, Block 1 and Block 2 have used for recording identification of sample households and particulars of field operations, as practised in previous rounds. The last two blocks, viz., Block 8 and Block 9 have used to record the remarks/comments of investigator and supervisory officer(s) respectively. Block 3 is used for recording the household characteristics like household size, principal industry and principal occupation of household, household type, religion, social group, distance from nearest school having primary/upper primary/secondary level classes, whether the household has a computer/ any access to internet and household's usual consumer expenditure in a month etc. Block 4 is used for recording the demographic and other particulars of all the household members satisfying the modified definition of household. Particulars of IT literacy for household members aged 14 & above and the particulars of current educational attendance and current enrolment status for household member aged 5-29 years are also collected in Block 4. The education particulars of the household members, aged 5 years to 29 years, who are currently attending educational institutions at primary level and above are recorded in Block 5. In this block, information on course, level, class/grade/year, type of institution, medium of instruction, etc., are collected on basic course. Block 6 is designed to collect particulars of private expenditure on education of the household members, whose educational particulars are collected in block 5. Here, the break-up of expenditure of the basic course of each such member is collected in detail. Particulars of household members, aged 5 years to 29 years, who are currently not attending any educational institution, are collected in Block 7. In this block, information like whether ever enrolled, age at entry in school, age of discontinuation / dropping, etc. have also recorded.

Geographic coverage

National, States, Urban, Rural

Analysis unit

Households Indivisuals

Universe

Households, persons aged 5-29 years in the pursuit of education

Kind of data

Sample survey data [ssd]

Sampling procedure

Outline of sample design: A stratified multi-stage design has been adopted for the 71st 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 2011 census villages (henceforth the term 'village' would mean Panchayat wards for Kerala) constitutes the sampling frame. In case of Kerala, due to the non-availability of Panchayat wards based on census 2011, the available list of Panchayat wards based on census 2001 is used as the rural frame. For the urban sector, the latest updated list of UFS blocks (phase 2007-12) is considered as the sampling frame.

Stratification: 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 of all the urban areas of the district. However, within the urban areas of a district, if there are one or more towns with population 1 lakh or more as per Census 2011, each of them formed a separate basic stratum and the remaining urban areas of the district has been considered as another basic stratum.

Special stratum in the rural sector: There are some villages in Nagaland and Andaman & Nicobar Islands which reamins difficult to access. As in earlier rounds, a special stratum has been formed at State/UT level comprising these villages in the two State/UTs.

Sub-stratification:

Rural sector: 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 had more or less equal population. Urban sector: If 'u' be the sample size allocated for an urban stratum, the number of sub-strata formed was 'u/2'. For all strata, if u/2 >1, implying formation of 2 or more sub-strata, all the UFS blocks within the stratum have been first arranged in ascending order of total number of households in the UFS Blocks as per UFS phase 2007-12. Then sub-strata 1 to 'u/2' have been demarcated in such a way that each sub-stratum had more or less equal number of households.

Total sample size (FSUs): 8300 FSUs have been allocated for the central sample at all-India level. For the state sample, there are 9274 FSUs allocated for all-India. State wise allocation of sample FSUs is given in Table 1.

Allocation of total sample to States and UTs: The total number of sample FSUs heve 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. While doing so, the resource availability in terms of number of field investigators has been kept in view.

Allocation of State/ UT level sample to rural and urban sectors: State/UT level sample size has been allocated between two sectors in proportion to population as per Census 2011 with double weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. do not exceed the rural sample size. A minimum of 16 FSUs (minimum 8 each for rural and urban sector separately) is allocated 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. Stratum level allocation has been adjusted to multiples of 2 with a minimum sample size of 2.

For special strata in the rural areas of Nagaland and A & N Islands, 4 FSUs has been allocated to each.

Allocation to sub-strata: Allocation for each sub-stratum has been 2 in both rural and urban sectors.

Selection of FSUs:

For the rural sector, from each stratum/sub-stratum, required number of sample villages have been selected by Probability Proportional to Size With Replacement (PPSWR), size being the population of the village as per Census 2011. For the urban sector, from each stratum/sub-stratum, FSUs have been selected by Probability Proportional to Size With Replacement (PPSWR), size being the number of households of the UFS Blocks. Both rural and urban samples have been drawn

In 1800, the population of the region of present-day India was approximately 169 million. The population would grow gradually throughout the 19th century, rising to over 240 million by 1900. Population growth would begin to increase in the 1920s, as a result of falling mortality rates, due to improvements in health, sanitation and infrastructure. However, the population of India would see it’s largest rate of growth in the years following the country’s independence from the British Empire in 1948, where the population would rise from 358 million to over one billion by the turn of the century, making India the second country to pass the billion person milestone. While the rate of growth has slowed somewhat as India begins a demographics shift, the country’s population has continued to grow dramatically throughout the 21st century, and in 2020, India is estimated to have a population of just under 1.4 billion, well over a billion more people than one century previously. Today, approximately 18% of the Earth’s population lives in India, and it is estimated that India will overtake China to become the most populous country in the world within the next five years.

This data package includes spatial environmental and social layers for Shivamogga District, Karnataka, India that were considered as potential predictors of patterns in human cases of Kyasanur Forest Disease (KFD). KFD is a fatal tick-borne viral haemorrhagic disease of humans, that is spreading across degraded forest ecosystems in India. The layers encompass a range of fifteen metrics of topography, land use and land use change, livestock and human population density and public health resources for Shivamogga District across 1km and 2km study grids. These spatial proxies for risk factors for KFD that had been jointly identified between cross-sectoral stakeholders and researchers through a co-production approach. Shivamogga District is the District longest affected by KFD in south India. The layers are distributed as 1km and 2km GeoTiffs in Albers equal area conic projection. For KFD, spatial models incorporating these layers identified characteristics of forest-plantation landscapes at higher risk for human KFD. These layers will be useful for modelling spatial patterns in other environmentally sensitive infectious diseases and biodiversity within the district.

Methods Processing of environmental predictors of Kyasanur Forest Disease distribution

This file details the sources and processing of environmental predictors offered to the statistical analysis in the paper. All processing was performed in the raster package [1] of the R program [2] unless otherwise specified, with function names as specified below.

Topography predictors

Elevation data was extracted in tiles from Shuttle Radar Topography Mission data version 4 [3] an original resolution of 0.000833 degrees Latitude and Longitude resolution (approximately 90m by 90m grid cells). Tiles were mosaicked across the study region using the merge function. A slope value for each pixel was calculated (in degrees) using the terrain function of the raster package, and a focal window of 3 by 3 cells. Both the resulting elevation and slope rasters were cropped to the administrative boundaries of the Shivamogga District (raster package: crop function) and re-projected to an equal area projection (Albers equal area conic projection) using the projectRaster function (method=”bilinear”). Mean elevation and slope values were then calculated across the study 1km and 2km grid cells, using the aggregate function to average values across the appropriate number of ~90m grid cells and then the resample function to align the resulting grid to the study grids.

Landscape predictors

Metrics of the current availability (and fragmentation) of forest, agricultural and built-up land use types as well as that of water-bodies were extracted from the MonkeyFeverRisk Land Use Land Cover map of Shimoga. The latter was produced from classification of earth observation data from 2016 to 2018 using the methods described in the Supplementary information S3 file of the paper linked to this dataset. The LULC map had an original grid square resolution of 0.000269 degrees Latitude and Longitude resolution (or 30m x 28m grid cells) and nine different LULC classes. It was cropped to the administrative boundaries of the Shimoga District (raster package: crop function) and re-projected to the equal area projection (Albers equal area conic projection) using the projectRaster function (method=”ngb” for categorical data). The agriculture and fallow land classes were combined before landscape analysis (due to the difficulty of separating them accurately in the classification process).

An algorithm was developed in R to identify which of the pixels in the LULC map coincided with each 1km and 2km grid cell of the study area. The ClassStat function of the SDM Tools package [4] was used to calculate the proportional area of each 1km or 2km grid cell landscape that was made up of a particular land class, as well patch density and edge density metrics for the forest classes as indicators of fragmentation and forest-agriculture interface habitat respectively (Fig. S2B). The proportional area values (pi) of the n different forest classes (wet evergreen forest, moist deciduous forest, dry deciduous forest and plantation) were used to calculate an index of forest type diversity per grid cell as follows, after Shannon & Weaver (1949) [5]:

H'= -1npi(lognpi)

Metrics of longer term forest changes in Shimoga since 2000 were derived from a global product by Hansen et al. (2013) [6] available at a spatial resolution of 1 arc-second per pixel, (~ 30 meters per pixel at equator). Forest loss during the period 2000–2014, is defined as a stand-replacement disturbance, or a change from a forest to non-forest state, encoded as either 1 (loss) or 0 (no loss). Forest gain during the period 2000–2012, is defined as a non-forest to forest change entirely within the study period, encoded as either 1 (gain) or 0 (no gain).These layers were again cropped to the administrative boundaries of the Shimoga District (raster package: crop function) and re-projected to an equal area projection (Albers equal area conic projection) using the projectRaster function (method=”ngb”) in R. An algorithm was developed in R to identify which of the pixels in the loss and gain rasters coincided with each 1km and 2km grid cell of the study area. The ClassStat function of the SDM Tools package [4] was used to calculate the proportional area of each 1km or 2km grid cell that was made up of loss pixels or gain pixels. Forest gain and loss are very highly correlated (r=0.986) and occur in similar places in the landscape (Fig. S2C). Forest loss was a much more common transition than a forest gain affecting 1.2% of land pixels rather than 0.16% of land pixels for forest gain.

To assess how forest loss or gain from a global product like Hansen et al. (2013) should be interpreted locally in south India, we analysed how the loss and gain pixels from Hansen et al. 2013 coincided with classes in the MonkeyFeverRisk LULC map (by extracting the value of the LULC map for the centroids of loss or gain pixels).

The distribution of loss and gain pixels across forest classes from the MonkeyFeverRisk LULC map is shown in Table 1. Locations categorised as a loss by Hansen et al. were most commonly classified currently as plantation, followed by moist evergreen forest, followed by

moist or dry deciduous forest by the MonkeyFeverRisk LULC map. The pattern was similar for the gain pixels. Since not all forest loss pixels were non-forest in the current day and not all forest gain pixels were forest in the current day, the precise meaning of the Hansen et al. (2013) forest loss layer was unclear for south India, though we expect that it is at least indicative of areas where the forest has undergone a larger degree of change since 2000.

Table 1: Percentage of loss (n= 108398) and gain (n= 14646) land pixels from the global Hansen et al. (2013) product that fall into different forest classes according to the MonkeyFeverRisk LULC map

    Land use class


    Gain


    Loss




    moist evergreen


    30.4


    26.1




    moist deciduous


    6.5


    16.2




    dry deciduous


    3.0


    9.7




    plantation


    46.2


    37.2




    Non-forest classes


    14.0


    10.9

Host and public health predictors

Livestock host density data, namely buffalo and indigenous cattle densities in units of total head per village were obtained from Department of Animal Husbandry, Dairying and Fisheries, Government of India Census from 2011 at village level. These were linked to village boundaries from the Survey of India using the village census codes in R. The village areas were calculated from the spatial polygons dataframe of villages using the rgeos package in R, so that the total head per village metrics could be convert into an areal density of buffalo and indigenous cattle per km and then rasterized at 1km and 2km using the rasterize function of the raster package.

The human population size and public health metrics were obtained from the Government of India Population Census 2011. The human population size (census field TOT_P) was again linked to the spatial polygon village boundaries using the census village code (census field VCT_2011) and converted to an areal metric of population density per km and rasterized at 1km and 2km as above. The number of medics per head of population was derived by summing all doctors and para-medicals “in position” across all types of health centres, clinics and dispensaries per village and dividing by the total population of the village (TOT_P) and then linked to village boundaries and rasterized as above. The proximity to health centres was a categorical variable derived from the “Primary.Health.Centre..Numbers” field, where 1 = Primary Health Centre (PHC) within village boundary, 2 = PHC within 5km of village, 3=PHC within 5-10km of village, 4= PHC further than 10km from village. It was linked to village boundaries and rasterized as above.

The resulting raster layers for all predictors were saved in GeoTiff format.

References

Robert J. Hijmans (2017). raster: Geographic Data Analysis and Modeling. R package version 2.6-7. https://CRAN.R-project.org/package=raster
R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.URL https://www.R-project.org/ 
Jarvis, A., Reuter, I., Nelson, A., Guevara, E. Hole-filled SRTM for the globe Version 4. 2008.
VanDerWal, J., Falconi, L., Januchowski, S., Shoo, L., & Storlie, C. (2014). SDMTools: Species Distribution Modelling Tools: Tools for processing data associated with species distribution modelling exercises. R

Abstract

Household consumer expenditure (HCE) is expenditure incurred by households on consumption of goods and services. Household consumer expenditure (HCE) during a specified period, called the reference period, may be defined as the following: (a) expenditure incurred by households on 'consumption goods and services' during the reference period (b) imputed value of goods and services produced as outputs of household (proprietary or partnership) enterprises owned by households and used by their members themselves during the reference period (c) imputed value of goods and services received by households as remuneration in kind during the reference period (d) imputed value of goods and services received by households through social transfers in kind received from government units or non-profit institutions serving households (NPISHs) and used by households during the reference period. The survey will cover the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Period of survey and work programme: The period of survey will be of one year duration starting on 1st July 2011 and ending on 30th June 2012. The survey period of this round will be divided into four sub-rounds of three months' duration each as follows:

sub-round 1 : July - September 2011
sub-round 2 : October - December 2011 sub-round 3 : January - March 2012
sub-round 4 : April - June 2012

Objective of the consumer expenditure survey (CES): Firstly, as an indicator of level of living, monthly per capita expenditure (MPCE) is both simple and universally applicable. Average MPCE of any sub-population of the country (any region or population group) is a single number that summarises the level of living of that population.Apart from these major uses of the CES, the food (quantity) consumption data are used to study the level of nutrition of different regions, and disparities therein. Further, the budget shares of a commodity at different MPCE levels are used by economists and market researchers to determine the elasticity (responsiveness) of demand to income increases.

Geographic coverage

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

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

Sample Design

Outline of sample design: A stratified multi-stage design has been adopted for the 68th round survey. The first stage units (FSU) are the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In case of large FSUs, one intermediate stage of sampling is the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each rural/ urban FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (henceforth the term 'village' would include also Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of UFS blocks (2007-12) is considered as the sampling frame.

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

Sub-stratification:

Rural sector r: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed would be 'r/4'. The villages within a district as per frame were first arranged in ascending order of population. Then sub-strata 1 to 'r/4' 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.

Urban sector: If 'u' be the sample size for an urban stratum, 'u/4' number of sub-strata have been formed. In case u/4 is more than 1, implying formation of 2 or more sub-strata, this is done by first arranging the towns in ascending order of total number of households in the town as per UFS phase 2007-12 and then arranging the IV units of each town and blocks within each IV unit in ascending order of their numbers. From this arranged frame of UFS blocks of all the towns/million plus city of a stratum, 'u/4' number of sub- strata formed in such a way that each sub-stratum has more or less equal number of households as per UFS 2007-12.

Total sample size (FSUs): 12784 FSUs have been allocated for the central sample at all-India level and 14772 FSUs have been allocated for state sample. Statewise allocation of sample FSUs has been given in Appendix Table-1.

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

Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample size has been allocated between two sectors in proportion to population as per census 2001 with double weightage to urban sector. However, if such weighted allocation resulted in too high sample size for the urban sector, the allocation for bigger states like Maharashtra, Tamil Nadu, etc. was restricted to that of the rural sector. A minimum of 16 FSUs (minimum 8 each for rural and urban sector separately) is allocated to each state/ UT.

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

Selection of FSUs:

For the rural sector, from each stratum/ sub-stratum, required number of sample villages has been selected by probability proportional to size with replacement (PPSWR), size being the population of the village as per Census 2001.

For the urban sector, UFS 2007-12 phase has been used for all towns and cities and FSUs have been selected from each stratum/sub-stratum by using Simple Random Sampling Without Replacement (SRSWOR).

Both rural and urban samples are to be drawn in the form of two independent sub-samples and equal number of samples have been allocated among the four sub rounds.

Selection of hamlet-groups/ sub-blocks - important steps

Criterion for hamlet-group/ sub-block formation: After identification of the boundaries of the FSU, it is first determined whether listing is to be done in the whole sample FSU or not. In case the population of the selected FSU is found to be 1200 or more, it has to be divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector by more or less equalising the population as stated below.

approximate present population of the sample FSU no. of hg's/sb's to be formed

less than 1200 (no hamlet-groups/sub-blocks) 1
1200 to 1799 3
1800 to 2399 4
2400 to 2999 5
3000 to 3599 6
…………..and so on

For rural areas of Himachal Pradesh, Sikkim, Uttarakhand (except four districts Dehradun (P), Nainital (P), Hardwar and Udham Singh Nagar), Poonch, Rajouri, Udhampur, Doda, Leh (Ladakh), Kargil districts of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups are formed as follows:

approximate present population of the sample village no. of hg's to be formed

less than 600 (no hamlet-groups) 1
600 to 899 3
900 to 1199 4
1200 to 1499 5
.………..and so on

Formation and selection of hamlet-groups/ sub-blocks: In case hamlet-groups/ sub-blocks are formed in the sample FSU, the same is done by more or less equalizing population.

Two hamlet-groups (hg)/ sub-blocks (sb) are selected from a large FSU wherever hamlet-groups/ sub-blocks have been formed in the following manner - one hg/ sb with maximum percentage share of population is always selected and termed as hg/ sb 1; one more hg/ sb is selected from the remaining hg's/ sb's by simple random sampling (SRS) and termed as hg/ sb 2. Listing and selection of the households is done independently in the two selected hamlet-groups/ sub-blocks. The FSUs without hg/ sb formation are treated as sample hg/ sb number 1. It is to be noted that if more than one hg/ sb have same maximum percentage share of population, the one among them which is listed first in block 4.2 of schedule 0.0 is treated as hg/ sb 1.

Selection of households: From each SSS the sample households for each of the schedules are selected by SRSWOR. If a household is selected for more than one schedule, only one schedule is canvassed in that household in the priority order of Schedule 1.0 (Type 1), Schedule 1.0 (Type 2) and Schedule 10 and in

Geographic coverage

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

Analysis unit

Enterprise

Kind of data

Sample survey data [ssd]

Sampling procedure

Outline of sample design:

A stratified multi-stage design has been adopted for the 67th round survey. The first stage units (FSU) is 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) is enterprises in both the sectors. In case of large FSUs, one intermediate stage of sampling will be the selection of three hamlet-groups (hgs)/ sub-blocks (sbs) from each large rural/ urban FSU.

Sampling frame to be used for selection of first stage units

Census 2001 list of villages is used as the sampling frame for rural areas. Auxiliary information such as number of enterprises, number of workers, type of enterprises, activities of enterprises, etc. available from EC-2005 frame is used for stratification, sub-stratification and selection of enterprises.

In Kerala, list of panchayat wards as per Census 2001 will be used as frame since list of such wards is not available as per EC 2005 frame.

In the urban sector, EC-2005 frame is used for 26 cities with population more than a million as per census 2001. Although Mumbai is a million plus city, EC-2005 frame is not used for Mumbai because of identification problem for IV unit/blocks in the EC for the city. For other cities/towns (including Mumbai), UFS frame (2002-07 phase or latest available phase prior to 2002-07 if it is not available) is used.

Stratification:

Each district is a basic stratum in both rural and urban areas. However, in case of urban, each city with population of 1 million or more as per Census 2001 forms a separate stratum and all other cities/towns of a district is grouped to form another stratum.

Sub-stratification:

(i) Rural: There is three sub-strata in the rural sector: (1) Villages with at least 5 establishments (NDE/DE) (see para 1.4.17 and 1.4.18 for definition of NDE/DE) under coverage in the manufacturing sector as per EC-2005 information; (2) Remaining villages having at least 5 NDE/DE under coverage in the services sector including trade as per EC-2005 information; (3) Remaining villages of the stratum.

For the State(s) where EC-2005 information cannot be used as auxiliary information for stratification/sub-stratification due to limitations of EC 2005 frame, each district is sub-stratified into 'r/4' sub-strata with a sample allocation of 4 per sub-stratum where 'r' is the sample allocation for the district/stratum. The sub-strata is formed by arranging the villages in terms of population so that total population of each sub-stratum is approximately the same.

(ii) Urban, Million plus cities (excluding Mumbai) : For each stratum / million plus city, 20 sub-strata will be formed as under: Sub-stratum 1: Blocks with one or more establishment in insurance & pension funding;
Sub-stratum 2: Remaining blocks with one or more establishment in storage & warehousing;
Sub-stratum 3: Remaining blocks with one or more establishment in accommodation;
Sub-strata 4-8: Remaining blocks with one or more establishment in broad activities of manufacturing (as per SSS formation discussed subsequently under para 1.3.10);
Sub-strata 9-12: Remaining blocks with one or more establishment in broad activities of trade (as per SSS formation in para 1.3.10);
Sub-strata 13-19: Remaining blocks with one or more establishment in broad activities of other services (as per SSS formation in para 1.3.10) excluding the activities covered under sub-strata 1-3.
Sub-strata 20: All remaining blocks of the stratum.

(iii) Urban, Other cities and towns (including Mumbai): Two sub-strata is formed: Sub-stratum 1: UFS block types: Bazaar area (BA)/ Industrial area (IA)/ Hospital area/ (HA)/ Slum area (SA) which are likely to contain relatively higher number of enterprises;
Sub-stratum 2: Remaining UFS blocks of the stratum.

If the number of FSUs in the frame of a rural or urban sub-stratum is found to be less than 8, then separate sub-stratum is formed and it is merged with the adjacent sub-stratum. There is only one town (Leh) in Leh district and one town (Kargil) in Kargil district of J & K. These two towns are out of UFS coverage. These are treated as sub-stratum 2 and the entire town is treated as one FSU.

Total Sample size (FSUs):

A sample of 16000 FSUs for central sample and 17176 FSUs for state sample have been allocated at all-India level.

Allocation of total sample FSUs:

(i) All-India allocation over States: All-India sample size (FSUs) have been allocated to different State/UTs taking into account the minimum allocations required for a State/UT and the proportion of non-agricultural workers as per EC-2005 in the State/UT.

(ii) State/UT allocation over rural/urban sectors: State/UT sample sizes is allocated to rural and urban sectors of the State/UT in proportion to number of non-agricultural workers as per EC-2005 with the constraint that urban allocation should not be too high compared to rural allocation and both rural and urban allocations is in multiples of 8.

(iii) State × sector allocation over strata: Stratum allocations of State/UT sample sizes for each sector is made in proportion to number of non-agricultural workers as per EC-2005. For the States/UTs where census 2001 frame was used in the rural sector, allocations to strata are made in proportion to population as per census.

(iv) Stratum allocation over sub-strata: Allocations to sub-strata are made: (a) In proportion to number of non-agricultural workers as per EC-2005 in rural sector as well as in million plus cities (after assuming the number as 1 for those villages/blocks where number of non-agricultural workers is 0); (b) In proportion to number of blocks with a double weight to sub-stratum 1 for other than million plus cities.

Minimum allocation for a sub-stratum is 4.

Selection of FSUs: (a) Rural & million plus cities: From each sub-stratum, required number of sample villages/blocks will be selected by probability proportional to size with replacement (PPSWR), size being the number of total non-agricultural workers under coverage in the village/block as per EC-2005. For the State(s) where EC-2005 information cannot be used as auxiliary information for selection of FSUs due to limitations of EC 2005 frame, size for PPSWR selection is the population of the village as per Census 2001.

(b) Urban (other than million plus cities): From each sub-stratum FSUs are selected by using Simple Random Sampling Without Replacement (SRSWOR). However, for Leh and Kargil towns, each town is selected 4 times, once in each sub-round. Both rural and urban samples is drawn in the form of two independent sub-samples and equal number of samples is allocated among the four sub rounds.

Formation of segment 9 and selection of hamlet-groups/ sub-blocks

Proper identification of the FSU boundaries: The first task of the field investigators is to ascertain the exact boundaries of the sample FSU as per its identification particulars given in the sample list. For urban samples, the boundaries of each FSU may be identified by referring to the map corresponding to the frame code specified in the sample list (even though map of the block for a latter period of the UFS might be available).

Formation of Segment 9: Having determined the boundaries of the sample FSU, all non-agricultural enterprises having 20 or more workers in the entire FSU and having operated at least one day during last 365 days preceding the day of survey (hereinafter to be called as 'big enterprises') are listed and all the eligible units under coverage are surveyed. All the listed big units (whether under coverage or not) constitute segment 9. All eligible enterprises under coverage were surveyed in segment 9.

Criterion for hamlet-group/ sub-block formation: Having constituted segment 9 as stated above, it is to be determined whether listing is done in the whole sample FSU or not. For this, approximate present population (P) and approximate total number of non-agricultural enterprises (E) for the whole FSU may be ascertained first from knowledgeable persons. Depending upon the values of 'P' and 'E', it is divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector as stated below. Final value of 'D' is the higher of the two values 'P' and 'E' based on the dual criteria. While considering enterprise criteria, segment 9 enterprises, if any, may be excluded from the count of 'E', if possible.

For rural areas of Himachal Pradesh, Sikkim, Uttarakhand (except four districts Dehradun (P), Nainital (P), Hardwar and Udham Singh Nagar), Poonch, Rajouri, Udhampur, Doda, Leh (Ladakh), Kargil districts of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups is formed as follows: population (P) | no. of hgs/ sbs to be formed | no. of non-agricultural enterprises (E) | no. of hgs/ sbs to be formed
less than 600 | 1 | less than 120 | 1
600 - 799 | 4 | 120 - 159 | 4
800 - 899 | 5 | 160 - 199 | 5
1000 - 1199 | 6 | 200 - 239 | 6
and so on | … | and

Abstract

Household consumer expenditure (HCE) is expenditure incurred by households on consumption of goods and services. Household consumer expenditure (HCE) during a specified period, called the reference period, may be defined as the following: (a) expenditure incurred by households on 'consumption goods and services' during the reference period (b) imputed value of goods and services produced as outputs of household (proprietary or partnership) enterprises owned by households and used by their members themselves during the reference period (c) imputed value of goods and services received by households as remuneration in kind during the reference period (d) imputed value of goods and services received by households through social transfers in kind received from government units or non-profit institutions serving households (NPISHs) and used by households during the reference period. The survey will cover the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Period of survey and work programme: The period of survey will be of one year duration starting on 1st July 2011 and ending on 30th June 2012. The survey period of this round will be divided into four sub-rounds of three months' duration each as follows:

sub-round 1 : July - September 2011
sub-round 2 : October - December 2011 sub-round 3 : January - March 2012
sub-round 4 : April - June 2012

Objective of the consumer expenditure survey (CES): Firstly, as an indicator of level of living, monthly per capita expenditure (MPCE) is both simple and universally applicable. Average MPCE of any sub-population of the country (any region or population group) is a single number that summarises the level of living of that population.Apart from these major uses of the CES, the food (quantity) consumption data are used to study the level of nutrition of different regions, and disparities therein. Further, the budget shares of a commodity at different MPCE levels are used by economists and market researchers to determine the elasticity (responsiveness) of demand to income increases.

Geographic coverage

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

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

Sample Design

Outline of sample design: A stratified multi-stage design has been adopted for the 68th round survey. The first stage units (FSU) are the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In case of large FSUs, one intermediate stage of sampling is the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each rural/ urban FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (henceforth the term 'village' would include also Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of UFS blocks (2007-12) is considered as the sampling frame.

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

Sub-stratification:

Rural sector r: If 'r' be the sample size allocated for a rural stratum, the number of sub-strata formed would be 'r/4'. The villages within a district as per frame were first arranged in ascending order of population. Then sub-strata 1 to 'r/4' 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.

Urban sector: If 'u' be the sample size for an urban stratum, 'u/4' number of sub-strata have been formed. In case u/4 is more than 1, implying formation of 2 or more sub-strata, this is done by first arranging the towns in ascending order of total number of households in the town as per UFS phase 2007-12 and then arranging the IV units of each town and blocks within each IV unit in ascending order of their numbers. From this arranged frame of UFS blocks of all the towns/million plus city of a stratum, 'u/4' number of sub- strata formed in such a way that each sub-stratum has more or less equal number of households as per UFS 2007-12.

Total sample size (FSUs): 12784 FSUs have been allocated for the central sample at all-India level and 14772 FSUs have been allocated for state sample. Statewise allocation of sample FSUs has been given in Appendix Table-1.

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

Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample size has been allocated between two sectors in proportion to population as per census 2001 with double weightage to urban sector. However, if such weighted allocation resulted in too high sample size for the urban sector, the allocation for bigger states like Maharashtra, Tamil Nadu, etc. was restricted to that of the rural sector. A minimum of 16 FSUs (minimum 8 each for rural and urban sector separately) is allocated to each state/ UT.

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

Selection of FSUs:

For the rural sector, from each stratum/ sub-stratum, required number of sample villages has been selected by probability proportional to size with replacement (PPSWR), size being the population of the village as per Census 2001.

For the urban sector, UFS 2007-12 phase has been used for all towns and cities and FSUs have been selected from each stratum/sub-stratum by using Simple Random Sampling Without Replacement (SRSWOR).

Both rural and urban samples are to be drawn in the form of two independent sub-samples and equal number of samples have been allocated among the four sub rounds.

Selection of hamlet-groups/ sub-blocks - important steps

Criterion for hamlet-group/ sub-block formation: After identification of the boundaries of the FSU, it is first determined whether listing is to be done in the whole sample FSU or not. In case the population of the selected FSU is found to be 1200 or more, it has to be divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector by more or less equalising the population as stated below.

approximate present population of the sample FSU no. of hg's/sb's to be formed

less than 1200 (no hamlet-groups/sub-blocks) 1
1200 to 1799 3
1800 to 2399 4
2400 to 2999 5
3000 to 3599 6
…………..and so on

For rural areas of Himachal Pradesh, Sikkim, Uttarakhand (except four districts Dehradun (P), Nainital (P), Hardwar and Udham Singh Nagar), Poonch, Rajouri, Udhampur, Doda, Leh (Ladakh), Kargil districts of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups are formed as follows:

approximate present population of the sample village no. of hg's to be formed

less than 600 (no hamlet-groups) 1
600 to 899 3
900 to 1199 4
1200 to 1499 5
.………..and so on

Formation and selection of hamlet-groups/ sub-blocks: In case hamlet-groups/ sub-blocks are formed in the sample FSU, the same is done by more or less equalizing population.

Two hamlet-groups (hg)/ sub-blocks (sb) are selected from a large FSU wherever hamlet-groups/ sub-blocks have been formed in the following manner - one hg/ sb with maximum percentage share of population is always selected and termed as hg/ sb 1; one more hg/ sb is selected from the remaining hg's/ sb's by simple random sampling (SRS) and termed as hg/ sb 2. Listing and selection of the households is done independently in the two selected hamlet-groups/ sub-blocks. The FSUs without hg/ sb formation are treated as sample hg/ sb number 1. It is to be noted that if more than one hg/ sb have same maximum percentage share of population, the one among them which is listed first in block 4.2 of schedule 0.0 is treated as hg/ sb 1.

Selection of households: From each SSS the sample households for each of the schedules are selected by SRSWOR. If a household is selected for more than one schedule, only one schedule is canvassed in that household in the priority order of Schedule 1.0 (Type 1), Schedule 1.0 (Type 2) and Schedule 10 and in

Abstract

The survey on health aims to generate basic quantitative information on the health sector. A vital component is the information relevant to the determination of the prevalence rate of morbidity among various age-sex groups in different regions of the country. Further, measurement of the extent of use of health services provided by the government is an indispensable part of the exercise. Special attention is given to hospitalisation, or medical care received as in-patient of medical institutions. The ailments for which such medical care is sought, the extent of use of government hospitals, and the expenditure incurred on treatment received from public and private sectors, are all to be investigated by the survey. Break-up of expenditure by various heads is to be estimated for expenses on medical care received both as in-patient and otherwise.

Reference period : July 2017-June 2018

Period of survey and work programme: The survey period of the round will be divided into four sub-rounds of three months' duration each as follows: sub-round 1 : July - September 2017 sub-round 2 : October - December 2017 sub-round 3 : January - March 2018 sub-round 4 : April - June 2018

For the first time in NSS health survey, the data collected will enable assessment of population who are affected by some widespread communicable diseases. Like previous round, data will be collected on alternative schools of medicine as well, which enable to derive the role of these types of medicines inrespective of prevalence of use, cost of treatment and type of ailments covered. Besides, the survey will ascertain the extent of use of private and public hospitals for childbirth, the cost incurred, and the extent of receipt of pre-natal and post-natal care by women who undergo childbirth. Moreover, status of immunisation of children age 0-5 years will be estimated as on date of survey. Finally, information on certain aspects of the condition of the 60-plus population will be obtained which have a bearing on their state of health, economic independence, and degree of isolation. Primarily, indicators on morbidity (proportion of ailing persons during last 15 days), hospitalization rates, the utilization of both public and private health care institutions, proportion of institutional childbirth etc will be attempted to be derived from this survey data with special emphasis on ‘out of pocket expenses’ as well as on access to government financed health insurance programmes.

Geographic coverage

The survey cover's the whole of the Indian Union except except the villages in Andaman and Nicobar Islands which are difficult to access.

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.

Sampling procedure

Sample Design

1.1 Outline of sample design: A stratified multi-stage design has been adopted for the 75th round survey. The first stage units (FSU) are the Census villages (Panchayat wards for 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 the 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.

1.2 Sampling Frame for First Stage Units: For the rural sector, the list of 2011 Population Census villages constitutes the sampling frame. However, for Kerala, the latest available updated list of Panchayat wards constitutes the sampling frame. For the urban sector, the latest available list of UFS blocks has been considered as the sampling frame.

1.3 Stratification: (a) Each district is a stratum. Within each district of a State/UT, generally speaking, two basic strata have been formed: (i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, if there are one or more towns with population one million or more as per Census 2011, each of them formed as a separate basic stratum and the remaining urban areas of the district have been considered as another basic stratum. (b) In the case of rural sectors of Nagaland another special stratum has been formed within the State consisting of all the villages which are difficult to access.

1.4 Sub-stratification:

1.4.1 Rural sector: If 'r' be the sample size allocated for a rural stratum, 'r/4' sub-strata are formed in that stratum. The villages within a stratum (district) as per frame are first arranged in ascending order of population. Then sub-strata 1 to 'r/4' have been demarcated in such a way that each substratum comprises a group of villages of the arranged frame and has more or less equal population.

1.4.2 Urban sector: Each urban stratum has been divided into two parts - 'Affluent part' consisting of UFS blocks identified as 'Affluent Area' and 'Non-Affluent part' consisting of the remaining UFS blocks within the stratum. Sample allocation of a stratum is then allocated to Affluent and Non-Affluent parts in proportion to total number of households in the UFS blocks with double weightage to Affluent part subject to a maximum of 8 FSUs in 'Affluent part' of any stratum. If 'u' be the sample size allocated for an urban stratum consisting of both affluent area UFS Blocks and non affluent area UFS Blocks. 'u/4' sub-strata are formed within each stratum. Out of these 'u/4' substrata, the first two sub-strata '01' and '02' are earmarked for those UFS blocks which are identified as 'Affluent Area' and the remaining sub-strata, '03', '04',…... and so on, are assigned to the nonaffluent UFS blocks. If any stratum does not have any Affluent Area UFS block then also the substratum number starts from '03' for that stratum. For all strata, if u/4 >1, implying formation of 2 or more sub-strata, all the UFS blocks within the stratum are first arranged in ascending order of total number of households in the UFS Blocks as per the latest UFS phase. Then sub-strata 1 to 'u/4' are demarcated in such a way that each sub-stratum has more or less equal number of households. This procedure has been done separately for Affluent-part and Non-Affluent part of the stratum (if two sub-strata are required to be formed in the Affluent part). The following three cases arise while doing the sub-stratification: i) If there is no 'Affluent Area' UFS block in the stratum, all the UFS blocks are divided into 'u/4' sub-strata and numbered as '03', '04', ….., '(u/4)+2'. ii) If only one sub-stratum is formed with the 'Affluent Area' UFS blocks, then all the remaining non-affluent blocks are divided into '(u-4)/4' sub-strata and numbered as '03', '04', ….., '(u/4)+1'. iii) If two sub-strata are formed with the 'Affluent Area' blocks, then all the remaining non-affluent UFS blocks are divided into '(u-8)/4' sub-strata and numbered as '03', '04', ….., 'u/4'.

1.5 Total sample size (FSUs): 14300 FSUs have been allocated for the central sample at all-India level. For the state sample, there are 16492 FSUs allocated for all-India.

1.6 Allocation of total sample to States and UTs: The total number of sample FSUs has 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.

1.7 Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample size has been allocated between two sectors in proportion to population as per Census 2011 with 1.5 weightage to urban sector depending on population share. A minimum of 16 FSUs (minimum 8 each for rural and urban sector separately) have been allocated to each State/ UT.

1.8 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. Stratum level allocation has been adjusted to multiples of 4 with a minimum sample size of 4. For special stratum formed in rural areas of Nagaland as discussed in para 1.3 (b), 12 FSUs have been allocated.

1.9 Allocation to sub-strata: Allocation for each sub-stratum has been made as 4 in both rural and urban sectors.

1.10 Selection of FSUs:

1.10.1 For the rural sector, from each stratum/sub-stratum, required number of sample villages has been selected by Probability Proportional to Size With Replacement (PPSWR), size being the population of the village as per Census 2011.

1.10.2 For the urban sector, from each stratum/sub-stratum, FSUs have been selected by Probability Proportional to Size With Replacement (PPSWR), size being the number of households of the UFS Block. Both rural and urban samples are drawn in the form of two independent sub-samples.

1.11 Selection of hamlet-groups/ sub-blocks - important steps

1.11.1 Criterion for hamlet-group/ sub-block formation: After identification of the boundaries of the FSU, it is to be determined whether listing is to be done in the whole sample FSU or not. In case the approximate present population of the selected FSU is found to be 1200 or more, it is divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector by more or less equalising the population as stated below. approximate present population of the sample FSU no. of hgs/sbs formed less than 1200 (no hamlet-group/sub-block) 1 1200 to 1799 3 1800 to 2399 4 2400 to 2999 5 3000 to 3599 6 …...and so on - For rural areas of Himachal Pradesh, Sikkim, Andaman & Nicobar Islands, Uttarakhand (except four districts Dehradun, Nainital, Hardwar and Udham Singh Nagar), Punch, Rajouri, Udhampur, Reasi, Doda,

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