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.

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.

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.

Census: Population: by Religion: Muslim: Gujarat data was reported at 5,846,761.000 Person in 03-01-2011. This records an increase from the previous number of 4,592,854.000 Person for 03-01-2001. Census: Population: by Religion: Muslim: Gujarat data is updated decadal, averaging 5,219,807.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 5,846,761.000 Person in 03-01-2011 and a record low of 4,592,854.000 Person in 03-01-2001. Census: Population: by Religion: Muslim: 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.GAE003: Census: Population: by Religion: Muslim.

Census: Population: by Religion: Muslim: Gujarat: Male data was reported at 3,007,221.000 Person in 03-01-2011. This records an increase from the previous number of 2,370,832.000 Person for 03-01-2001. Census: Population: by Religion: Muslim: Gujarat: Male data is updated decadal, averaging 2,689,026.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 3,007,221.000 Person in 03-01-2011 and a record low of 2,370,832.000 Person in 03-01-2001. Census: Population: by Religion: Muslim: Gujarat: Male 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.GAE003: Census: Population: by Religion: Muslim.

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.

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.

According to the 76th round of the NSO survey conducted between July and December 2018, Gujarat had a higher percentage of disabled men with a certificate of disability at 34.5 percent. The disability certificate was issued by the medical board to persons with more than 40 percent of any disability. This provides eligibility to apply for facilities, concessions and other benefits provided under various schemes.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for village level demographic analysis within basic applications to support graphical overlays and analysis with other spatial data.

Census: Population: Gujarat: Rural: Female data was reported at 16,895,450.000 Person in 03-01-2011. This records an increase from the previous number of 15,422,996.000 Person for 03-01-2001. Census: Population: Gujarat: Rural: Female data is updated decadal, averaging 16,159,223.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 16,895,450.000 Person in 03-01-2011 and a record low of 15,422,996.000 Person in 03-01-2001. Census: Population: Gujarat: Rural: Female data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAB003: Census: Population: by Stratum.

Vital Statistics: Death Rate: per 1000 Population: Gujarat: Urban data was reported at 5.000 NA in 2020. This records a decrease from the previous number of 5.200 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: Gujarat: Urban data is updated yearly, averaging 5.600 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 6.400 NA in 1998 and a record low of 5.000 NA in 2020. Vital Statistics: Death Rate: per 1000 Population: Gujarat: Urban 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.GAH003: Vital Statistics: Death Rate: by States.

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 ******** states of India. Of these, the lowest sex ratio is expected to be seen in the national capital region of Delhi with *** in 2036.

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.

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.

Abstract

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

Geographic coverage

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

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

SAMPLE DESIGN : RURAL

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

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

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

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

Sampling deviation

There was no deviation from the original sampling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

Census: Population: Gujarat: Bavla: Female data was reported at 17,103.000 Person in 03-01-2011. This records an increase from the previous number of 14,503.000 Person for 03-01-2001. Census: Population: Gujarat: Bavla: Female data is updated decadal, averaging 10,203.000 Person from Mar 1951 (Median) to 03-01-2011, with 7 observations. The data reached an all-time high of 17,103.000 Person in 03-01-2011 and a record low of 4,057.000 Person in 03-01-1951. Census: Population: Gujarat: Bavla: Female data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAC011: Census: Population: By Towns and Urban Agglomerations: Gujarat.

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

The Enterprise Surveys of Micro firms (ESM) conducted by the World Bank Group's (WBG) Enterprise Analysis Unit (DECEA) in India. The survey covers nine cities: Hyderabad, Telangana; Jaipur, Rajasthan; Kochi, Kerala; Ludhiana, Punjab; Mumbai, Maharashtra; Sehore, Madhya Pradesh; Surat, Gujarat; Tezpur, Assam; and Varanasi, Uttar Pradesh.

The primary objectives of the ESM are to: i) understand demographics of the micro enterprises in the covered cities, ii) describe the environment within which these enterprises operate, and iii) enable data analysis based on the samples that are representative at each city level.

Geographic coverage

Nine cities in India: Hyderabad, Telangana; Jaipur, Rajasthan; Kochi, Kerala; Ludhiana, Punjab; Mumbai, Maharashtra; Sehore, Madhya Pradesh; Surat, Gujarat; Tezpur, Assam; and Varanasi, Uttar Pradesh.

Analysis unit

• Firms

Universe

The universe of ESM includes formally registered businesses in the sectors covered by the ES and with less than five employees. The definition of formal registration can vary by country. The universe table for each of the nine cities covered by ESM in India was obtained from the 6th Economic Census (EC) of India (conducted between January 2013 and April 2014), which has its own well-defined definition of registration. Generally, this entails registration with any central/government agency, under Shops & Establishment Act, Factories Act etc.

In terms of sectors, the survey covers all non-agricultural and non-extractive sectors. In particular, according to the group classification of ISIC Revision 4.0, it includes: all manufacturing sectors (group D), construction (group F), wholesale and retail trade (group G), transportation and storage (group H), accommodation and food service activities (group I), a subset of information and communications (group J), some administrative and support service activities (codes 79) and other service activities (codes 95). Notably, the ESM universe excludes the following sectors: financial and insurance activities (group K), real estate activities (group L), and all public or utilities-sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Enterprise Survey of Micro firms in India 2022 was selected using stratified random sampling, following the methodology explained in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling was preferred over simple random sampling for several reasons, including: a. To obtain unbiased estimates for different subdivisions of the population with some known level of precision, along with the unbiased estimates for the whole population. b. To make sure that the final total sample includes establishments from all different sectors and that it is not concentrated in one or two of industries/sizes/regions. c. To exploit the benefits of stratified sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e., lower standard errors, other things being equal.) d. Stratification may produce a smaller bound on the error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are homogeneous. e. The cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.

Two levels of stratification were used in this survey: industry and region. For stratification by industry, two groups were used: Manufacturing (combining all the relevant activities in ISIC Rev. 4.0 codes 10-33) and Services (remainder of the universe, as outlined above). Regional stratification was done across nine cities included in the study, namely: Hyderabad, Jaipur, Kochi, Ludhiana, Mumbai, Sehore, Surat, Tezpur and Varanasi.

Mode of data collection

Face-to-face [f2f]

Census: Population: Gujarat: Halol data was reported at 64,265.000 Person in 03-01-2011. This records an increase from the previous number of 44,473.000 Person for 03-01-2001. Census: Population: Gujarat: Halol data is updated decadal, averaging 14,629.000 Person from Mar 1921 (Median) to 03-01-2011, with 9 observations. The data reached an all-time high of 64,265.000 Person in 03-01-2011 and a record low of 3,810.000 Person in 03-01-1921. Census: Population: Gujarat: Halol 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.GAC011: Census: Population: By Towns and Urban Agglomerations: Gujarat.

Vitiligo is an autoimmune skin disorder defined by the destruction of functional epidermal melanocytes. It is a multifactorial and polygenic disorder caused due to oxidative stress, endoplasmic reticulum (ER) stress, and autoimmunity, among other factors. In the present study, we aimed to investigate the association of X-box Binding Protein 1 (XBP1) and Interleukin-17A (IL-17A) polymorphisms and monitor their systemic as well as skin expression levels in vitiligo patients from Gujarat population in India. XBP1 rs2269577 G/C, IL17A rs2275913 G/A and IL17A rs8193036 C/T polymorphisms were genotyped by Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) method in 312 controls and 276 vitiligo patients. Transcript levels of spliced (sXBP1), unspliced XBP1 (uXBP1) and IL17A from peripheral blood mononuclear cells (PBMCs) as well as spliced and unspliced XBP1 from skin samples were analyzed by qPCR. IL-17A protein levels in suction-induced blister fluid (SBF) from the skin of study subjects were estimated by ELISA. The results revealed that genotype (p=0.010) and allele (p=0.014) frequencies of XBP1 rs2269577 G/C polymorphism were significantly different, however, no significant difference was observed in frequencies of IL17A rs2275913 G/A and IL17A rs8193036 C/T polymorphisms in control and patient population. Gene expression analysis revealed that sXBP1 and IL17A levels were significantly higher in PBMCs of generalized (p=0.030 and p=0.039, respectively) and active (p=0.024 and p=0.017, respectively) vitiligo patients. Moreover, we observed a significantly elevated sXBP1 expression (p=0.037) as well as IL-17A protein levels (p=0.009) in perilesional skin of vitiligo patients as compared to controls. Overall, these findings suggest XBP1 and IL17A play an important role in vitiligo and further substantiate the involvement of ER stress in exacerbating immune-mediated vitiligo pathogenesis.