The western state of Gujarat in India recorded a population density of 308 people for every square kilometer according to the country's latest census in 2011. This was a significant increase compared to a decade earlier where the figure stood at 258.

According to the 76th round of the NSO survey conducted between July and December 2018, the share of males with disability was the highest in rural Gujarat at 1.8 percent. Disability was less prevalent among female residents of Gujarat. The National Statistical Office (NSO) is the statistical wing of the Ministry of Statistics and Programme Implementation (MOSPI), mainly responsible for laying down standards for statistical analysis, data collection, and implementation.

Worker Population Ratio: Usual Status: Education: Middle: Gujarat: Rural: Female data was reported at 59.500 % in 2024. This records an increase from the previous number of 50.000 % for 2023. Worker Population Ratio: Usual Status: Education: Middle: Gujarat: Rural: Female data is updated yearly, averaging 37.100 % from Jun 2018 (Median) to 2024, with 7 observations. The data reached an all-time high of 59.500 % in 2024 and a record low of 17.000 % in 2018. Worker Population Ratio: Usual Status: Education: Middle: Gujarat: Rural: Female data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Labour Market – Table IN.GBA029: Periodic Labour Force Survey: Annual: Worker Population Ratio: Usual Status: by State: Education Level: Middle.

Worker Population Ratio: Usual Status: Education: Gujarat: Urban data was reported at 54.100 % in 2024. This records an increase from the previous number of 52.100 % for 2023. Worker Population Ratio: Usual Status: Education: Gujarat: Urban data is updated yearly, averaging 49.000 % from Jun 2018 (Median) to 2024, with 7 observations. The data reached an all-time high of 54.100 % in 2024 and a record low of 45.100 % in 2018. Worker Population Ratio: Usual Status: Education: Gujarat: Urban data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Labour Market – Table IN.GBA026: Periodic Labour Force Survey: Annual: Worker Population Ratio: Usual Status: by State: Education Level.

POPULATION PROIECTIONS FOR INDIA AND STATES 2011 – 2036 (Downscaled to District, Sub-Districts and Villages/Towns by Esri India)REPORT OF THE TECHNICAL GROUP ON POPULATION PROIECTTONSJuly, 2020The projected population figures provided by the Registrar General of India forms the basis for planning and implementation of various health interventions including RMNCH+A, which are aimed at improving the overall health outcomes by ensuring quality service provision to all the health beneficiaries. These interventions focus on antenatal, intranatal and neonatal care aimed at reducing maternal and neonatal morbidity and mortality; improving coverage and quality of health care interventions and improving coverage for immunization against vaccine preventable diseases. Further, these estimates would also enable us to tackle the special health care needs of various population age groups, thus gearing the system for necessary preventive, promotive, curative, and rehabilitative services for the growing population to this report. PREETI SUDAN, IAS SecretaryThe Cohort Component Method is the universally accepted method of making population projections because of the fact that the growth of population is determined by fertility, mortality, and migration rates. In this exercise, 20 States and two UTs have been applied the Cohort Component method. These are Andhra Pradesh, Assam, Bihar, Gujarat, Haryana, Himachal Pradesh, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, West Bengal, Jharkhand, Chhattisgarh, Uttarakhand, Jammu & Kashmir (UT) and NCT of Delhi. Based on the residual of the projected population of Jammu & Kashmir (State) and Jammu & Kashmir (UT), for which Cohort Component method has applied, projection of the Ladakh UT have been made. For the projections of Jammu & Kashmir (UT), SRS fertility and mortality estimates of Jammu & Kashmir (State) are used. The projection of the seven northeastern states (excluding Assam) has also been carried out as a whole using the Cohort Component Method. Separate projections for Andhra Pradesh and Telangana were done using the re-casted populations of these states. For the projections, for the years before 2014, combined SRS estimates of Andhra Pradesh and year 2014 onwards, separate SRS estimates of fertility and mortality of Andhra Pradesh and Telangana are used. For the remaining States and Union territories, Mathematical Method has been applied. The sources of data used are 2011 Census and Sample Registration System (SRS). SRS provides time series data of fertility and mortality, which has been used for predicting their future levelsEsri India Efforts:The Population Projections Report published by MoHFW contains output summary tables from series Table 8 to Table 14. Example: TABLE – 8: Projected total population by sex as on 1st March, 2011-2036: India, States and Union territories, TABLE – 9: Projected urban population by sex as on 1st March, 2011-2036: India, States and Union territories, etc. The parameters available with these census data tables are Census Year, Projected Total Persons with Gender categorization and Projected Urban Population from 2011 to 2036.By subtracting “Projected Urban Population” from “Projected Total Population”, a new data column has been added as “Projected Rural Population”. The data is available for all Union Territory and States for 25 years.A factor has been calculated by taking projected population and the base year population (2011). Subsequently, the factor is calculated for each year using the projected values provided by census of India. Projected Population by Sex as on 1st March - 2011 - 2036: India, States and Union Territories* ('000)YearGUJARAT GUJARAT URBANGUJARAT RURALPersonsMaleFemalePersonMaleFemalePersonMaleFemale2011 60,440 (A) 31,49128,94825,74513,69412,05134,69517,79716,8972012 61,383 (B)32,00729,37626,47214,08112,39134,91117,92616,985Factor has been applied below State level- Projected Population by Sex as on 1st March - 2011 - 2036: India, States and Union Territories* ('000)YearGUJARAT GUJARAT URBANGUJARAT RURALPersonsMaleFemalePersonMaleFemalePersonMaleFemale20121.01560225 (B/A)1.0163856341.0147851321.0282384931.0282605521.0282134261.0062256811.0072484131.005208025Esri India has access to SOI admin boundaries up-to district level and developed village, town and sub-district boundaries using census maps. The calculated factors have been applied to smallest geography at villages and towns and upscaled back to sub-district, district, state, and country. The derived values have been compared with the original values provided by census at state level and no deviation is confirmed.Data Variables: Year (2011-2036)Total Population MaleFemaleTotal Population UrbanMale UrbanFemale UrbanTotal Population RuralMale RuralFemale RuralData source: https://main.mohfw.gov.in/sites/default/files/Population Projection Report 2011-2036 - upload_compressed_0.pdfOther related contents are also available:Village Population Projections for India 2011-2036Sub-district Population Projections for India 2011-2036District Population Projections for India 2011-2036State Population Projections for India 2011-2036Country Population Projections for India 2011-2036This 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.

Worker Population Ratio: Usual Status: Education: Higher Secondary: Gujarat: Female data was reported at 32.000 % in 2024. This records an increase from the previous number of 26.700 % for 2023. Worker Population Ratio: Usual Status: Education: Higher Secondary: Gujarat: Female data is updated yearly, averaging 19.500 % from Jun 2018 (Median) to 2024, with 7 observations. The data reached an all-time high of 32.000 % in 2024 and a record low of 10.100 % in 2018. Worker Population Ratio: Usual Status: Education: Higher Secondary: Gujarat: Female data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Labour Market – Table IN.GBA032: Periodic Labour Force Survey: Annual: Worker Population Ratio: Usual Status: by State: Education Level: Higher Secondary.

Owing to its high copy number and its small size, mtDNA analysis is the most reliable choice when biological materials from crime scenes are degraded or have mixed STR profiles. To examine the occurrence of heteroplasmy along with its frequency and pattern in both HV1 and HV2 regions of the mtDNA among unrelated individuals from India. Mitochondrial DNA control region [hypervariable region one (HV1) and hypervariable region two (HV2)] were analysed in blood and buccal tissues of 104 unrelated individuals from the Indian state of Gujarat. A high frequency of point heteroplasmy (PH) and length heteroplasmy (LH) was revealed. PH was detected in 7.69% of the population, with a higher frequency observed in blood than in buccal samples. However, there were no statistically significant differences in PH between the two tissues (Chi-square = 0.552, p ≥ 0.05). A total of six PH positions were detected: three at HV1, and another three at HV2. The studied population showed 46.15% LH in the HV1 and HV2 regions of both tissues. The LH positions observed in the Gujarat population were the same as those previously reported at HV1 np16184–16193 and HV2 np303–315. Our findings suggest that differences in the pattern of heteroplasmy found in different tissues can complicate the forensic analysis, on the other hand, the probability of a match between the questioned and reference samples increases when the heteroplasmy is identical in both tissues. Variability of PH among persons and even within tissues recommends analysing multiple tissue samples before drawing a conclusion in forensic mtDNA analyses.

The share of males was the highest for multiple disabilities at 1.7 percent, followed by locomotor disability at one percent in the western state of Gujarat in 2018. According to the 76th round of the NSO survey conducted between July and December 2018, a higher percentage of disabled men than disabled women were present in India. The National Statistical Office (NSO) is the statistical wing of the Ministry of Statistics and Programme Implementation (MOSPI), mainly responsible for laying down standards for statistical analysis, data collection, and implementation.

Worker Population Ratio: Usual Status: Education: Post Graduate and Above: Gujarat data was reported at 67.300 % in 2024. This records a decrease from the previous number of 67.800 % for 2023. Worker Population Ratio: Usual Status: Education: Post Graduate and Above: Gujarat data is updated yearly, averaging 59.800 % from Jun 2018 (Median) to 2024, with 7 observations. The data reached an all-time high of 67.800 % in 2023 and a record low of 55.800 % in 2020. Worker Population Ratio: Usual Status: Education: Post Graduate and Above: Gujarat data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Labour Market – Table IN.GBA035: Periodic Labour Force Survey: Annual: Worker Population Ratio: Usual Status: by State: Education Level: Post Graduate and Above.

The urban region of the Indian state of Gujarat had over 288 thousand people per police station as of January 2022. By contrast, rural Arunachal Pradesh had almost nine thousand people per police station.

The statistic gives the literacy rate in rural and urban regions of Gujarat in India in 2011, with a breakdown by gender. The literacy rate among females living in rural areas in Gujarat was around 61 percent in that year. India's literacy rate from 1981 through 2011 can be found here.

Worker Population Ratio: Usual Status: Education: Middle: Gujarat: Urban: Female data was reported at 28.600 % in 2024. This records an increase from the previous number of 26.000 % for 2023. Worker Population Ratio: Usual Status: Education: Middle: Gujarat: Urban: Female data is updated yearly, averaging 16.600 % from Jun 2018 (Median) to 2024, with 7 observations. The data reached an all-time high of 28.600 % in 2024 and a record low of 11.400 % in 2018. Worker Population Ratio: Usual Status: Education: Middle: Gujarat: Urban: Female data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Labour Market – Table IN.GBA029: Periodic Labour Force Survey: Annual: Worker Population Ratio: Usual Status: by State: Education Level: Middle.

In India, the projected sex ratio for the population in 2036 is expected to see more females than males in comparison to the population as of 2011. Apart from Kerala, Karnataka, Maharashtra and Gujarat, the sex ratio is expected to increase in eighteen states of India. Of these, the lowest sex ratio is expected to be seen in the national capital region of Delhi with 899 in 2036.

The statistic shows the literacy rate in the state of Gujarat in India between 1991 and 2011, broken down by gender. In 2001, some 80 percent of the male population living in Gujarat knew how to read or write. India's literacy rate from 1981 through 2011 can be found here.

Worker Population Ratio: Usual Status: Education: Secondary: Gujarat: Rural: Male data was reported at 78.000 % in 2024. This records an increase from the previous number of 74.100 % for 2023. Worker Population Ratio: Usual Status: Education: Secondary: Gujarat: Rural: Male data is updated yearly, averaging 70.000 % from Jun 2018 (Median) to 2024, with 7 observations. The data reached an all-time high of 78.000 % in 2024 and a record low of 66.400 % in 2019. Worker Population Ratio: Usual Status: Education: Secondary: Gujarat: Rural: Male data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under India Premium Database’s Labour Market – Table IN.GBA030: Periodic Labour Force Survey: Annual: Worker Population Ratio: Usual Status: by State: Education Level: Secondary.

Comprehensive population and demographic data for Balambhadi Village

Abstract

A nationwide survey on "Particulars of Slums" was carried-out by the National Sample Survey Organisation (NSSO) during the period January-June, 1993 in its 49th round to ascertain the extent of civic facilities available in the slums. The 49th round survey among other objectives also collected data on the condition of slum dwellings as well as on some general particulars of slum areas. Apart from formulating the sampling design with an emphasis to obtain an adequate number of slum households for the survey on housing condition and migration, surveyed the slum areas and collected information on slums. The schedule 0.21 was canvassed in both the rural and urban areas. All the slums, both the declared ones as well as the others (undeclared), found in the selected first stage units were surveyed even if hamlet-group/sub-block selection was resorted to in some of then. To ascertain the extent of civic facilities available in the slums as well as the information regarding the improvement of slum condition during a period of last five years was also collected. Information was collected by contacting one or more knowledgeable persons in the FSU on the basis of predominant criterion in both declared and undeclared slums, and not through household approach.

Geographic coverage

The geographical coverage of the survey was the whole of the Indian Union except Ladakh & Kargil districts of Jammu & Kashmir, 768 interior villages of Nagaland and 172 villages in Andaman & Nicobar islands which remain inaccessible throughout the year. However, certain districts of Jammu & Kashmir viz. Doda, Anantanag, Pulwama, Srinagar, Badgam, Barmula & Kupwara, as well as Amritsar district in Punjab, had to be excluded from the survey coverage due to unfavourable field conditions.

Sampling procedure

Sample Design : The first stage units in the rural sector and urban sector were census villages and urban frame survey (UFS) blocks respectively. However for newly declared towns of the 1991 census,for which UFS frames were not available, census EBs were used as first stage units.

Sampling frame for fsu's : In the rural sector, the sampling frame in most of the districts was the 1981 census list of villages. However, in Assam and in 8 districts of Madhya Pradesh, 1971 Census lists of villages were used. For Nagaland, the villages situated within 5 kms of a bus route constituted the sampling frame. For the Andaman & Nicobar islands the list of accessible villages was used as sampling frame. In the urban sector, the lists of NSS urban frame survey (UFS) blocks were the sampling frames used in most cases. However, 1991 Census house - listing enumeration blocks were considered as the sampling units for some of the newly declared towns of the 1991 population census, for which UFS frames were not available.

Stratification : Each state/u.t. was divided into one or more agro-economic regions by grouping contiguous districts which are similar with respect to population density and crop pattern. In Gujarat, however, some districts were subdivided for the purpose of region formation on the basis of location of dry areas and the distribution of tribal population in the state. The total number of regions formed in the whole of India was 78.

In the rural sector, within each region, each district with a rural population of less than 1.8 million according to the 1981 Census formed a single basic stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils, similar as far as possible in respect of rural population density & crop pattern. In Gujarat, however, in the case of districts extending over more than one region, the portion of a district falling in each region constituted a separate stratum even if the rural population of the district as a whole was less than 1.8 million. Further, in Assam, the strata formed for the earlier NSS round on the basis of 1971 Census rural population exactly in the above manner, but with a cutoff point of 1.5 million population, were retained as the strata for rural sampling.

In the urban sector, strata were formed, within NSS regions, on the basis of 1981 (1991 in some of the new towns) Census population. Each city with a population of 10 lakhs or more formed a separate stratum itself. The remaining towns of each region were grouped to form three different strata on the basis of 1981 (1991 in a few cases) census population.

Sub stratification of urban strata : In order to be able to allocate a large proportion of the first stage sample to slum-dominated areas than would otherwise be possible, each stratum in the urban sector was divided into two "sub-strata" a s follows. Sub-stratum 1 was constituted of the UFS blocks in the stratum with a "slum area" indicated in the frame. Substratum 2 was constituted of the remaining blocks of the stratum.

Allocation of sample : A total all-India sample of 8000 first stage units (5072 villages and 2928 urban blocks) determined on the basis of investigator strength in different state/u.t's and the expected workload per investigator was first allocated to the states/u.t's in proportion to Central Staff available. The sample thus obtained for each state/u.t. was then allocated to its rural & urban sectors considering the relative sizes of the rural & urban population with double weightage for the urban sector. Within each sector of a state/u.t., the allotted sample size was reallocated to the different strata in proportion to stratum population. Stratum-level allocations were adjusted so that the sample size for a stratum (rural or urban) was at least a multiple of 4. This was done in order to have equal sized samples in each sub-sample and sub-round.

In the urban sector, stratum-level allocations were further allocated to the two sub-strata in proportion to the number of UFS blocks in the sub-strata, with double weightage to sub-stratum 1, with a minimum sample size of 4 blocks to sub-stratum 1 (2 if stratum allocation was only 4). Sub-stratum level allocations were made even in number.

Selection of fsu's : Sample villages except in Arunachal Pradesh were selected by pps systematic sampling with population as the size variable and sample blocks by simple random sampling without replacement. In both sectors the sample of fsu's was drawn in the form of two independent sub-samples. (In Arunachal Pradesh the sample of villages was drawn by a cluster sampling procedure. The field staff were supplied with a list of sample "nucleus" villages and were advised to select cluster of villages building up each cluster around a nucleus village according to prescribed guidelines. The nucleus villages were selected circular-systematically with equal probability in the form of two ) independent sub-samples.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire consisted of 6 blocks (including 0) as given below : Block - 0 : descriptive identification of sample village/block having slum Block - 1 : identification of sample village/block having slum. Block - 3 : Remarks by investigator. Block - 4 : Comments by Supervisory Officer(s). Block - 5 : Particulars about slum.

Response rate

1572 slums spread over 5072 villages and 2928 urban blocks in the sample have been surveyed.

Vital Statistics: Birth Rate: per 1000 Population: Gujarat data was reported at 19.300 NA in 2020. This records a decrease from the previous number of 19.500 NA for 2019. Vital Statistics: Birth Rate: per 1000 Population: Gujarat data is updated yearly, averaging 22.300 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 25.500 NA in 1998 and a record low of 19.300 NA in 2020. Vital Statistics: Birth Rate: per 1000 Population: Gujarat data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH002: Vital Statistics: Birth Rate: by States.

There were over 26 million registered vehicles across the Indian state of Gujarat at the end of fiscal year 2020. The south Asian country's transport sector accounted for a 4.59 percent share of the GVA with road transport accounting for over three percent of it. The GVA from railways was about 0.74 percent and air transport accounted for about 0.12 percent during the same time period.

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.