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

India Census: Population: by Religion: Hindu: Male data was reported at 498,306,968.000 Person in 2011. This records an increase from the previous number of 428,678,554.000 Person for 2001. India Census: Population: by Religion: Hindu: Male data is updated yearly, averaging 463,492,761.000 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 498,306,968.000 Person in 2011 and a record low of 428,678,554.000 Person in 2001. India Census: Population: by Religion: Hindu: Male data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.

Census: Population: by Religion: Muslim: Uttarakhand data was reported at 1,406,825.000 Person in 03-01-2011. This records an increase from the previous number of 1,012,141.000 Person for 03-01-2001. Census: Population: by Religion: Muslim: Uttarakhand data is updated decadal, averaging 1,209,483.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 1,406,825.000 Person in 03-01-2011 and a record low of 1,012,141.000 Person in 03-01-2001. Census: Population: by Religion: Muslim: Uttarakhand 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.

Get details on population by religious community. It also provides the information on State Code, District Code, Tehsil Code, Area Name, Persons, Males, Females, Religious communities, Hindu, Muslim, Christian, Sikh, Buddhist and Jain etc.

The second National Family Health Survey (NFHS-2), conducted in 1998-99, provides information on fertility, mortality, family planning, and important aspects of nutrition, health, and health care. The International Institute for Population Sciences (IIPS) coordinated the survey, which collected information from a nationally representative sample of more than 90,000 ever-married women age 15-49. The NFHS-2 sample covers 99 percent of India's population living in all 26 states. This report is based on the survey data for 25 of the 26 states, however, since data collection in Tripura was delayed due to local problems in the state. IIPS also coordinated the first National Family Health Survey (NFHS-1) in 1992-93. Most of the types of information collected in NFHS-2 were also collected in the earlier survey, making it possible to identify trends over the intervening period of six and one-half years. In addition, the NFHS-2 questionnaire covered a number of new or expanded topics with important policy implications, such as reproductive health, women's autonomy, domestic violence, women's nutrition, anaemia, and salt iodization. The NFHS-2 survey was carried out in two phases. Ten states were surveyed in the first phase which began in November 1998 and the remaining states (except Tripura) were surveyed in the second phase which began in March 1999. The field staff collected information from 91,196 households in these 25 states and interviewed 89,199 eligible women in these households. In addition, the survey collected information on 32,393 children born in the three years preceding the survey. One health investigator on each survey team measured the height and weight of eligible women and children and took blood samples to assess the prevalence of anaemia. SUMMARY OF FINDINGS POPULATION CHARACTERISTICS Three-quarters (73 percent) of the population lives in rural areas. The age distribution is typical of populations that have recently experienced a fertility decline, with relatively low proportions in the younger and older age groups. Thirty-six percent of the population is below age 15, and 5 percent is age 65 and above. The sex ratio is 957 females for every 1,000 males in rural areas but only 928 females for every 1,000 males in urban areas, suggesting that more men than women have migrated to urban areas. The survey provides a variety of demographic and socioeconomic background information. In the country as a whole, 82 percent of household heads are Hindu, 12 percent are Muslim, 3 percent are Christian, and 2 percent are Sikh. Muslims live disproportionately in urban areas, where they comprise 15 percent of household heads. Nineteen percent of household heads belong to scheduled castes, 9 percent belong to scheduled tribes, and 32 percent belong to other backward classes (OBCs). Two-fifths of household heads do not belong to any of these groups. Questions about housing conditions and the standard of living of households indicate some improvements since the time of NFHS-1. Sixty percent of households in India now have electricity and 39 percent have piped drinking water compared with 51 percent and 33 percent, respectively, at the time of NFHS-1. Sixty-four percent of households have no toilet facility compared with 70 percent at the time of NFHS-1. About three-fourths (75 percent) of males and half (51 percent) of females age six and above are literate, an increase of 6-8 percentage points from literacy rates at the time of NFHS-1. The percentage of illiterate males varies from 6-7 percent in Mizoram and Kerala to 37 percent in Bihar and the percentage of illiterate females varies from 11 percent in Mizoram and 15 percent in Kerala to 65 percent in Bihar. Seventy-nine percent of children age 6-14 are attending school, up from 68 percent in NFHS-1. The proportion of children attending school has increased for all ages, particularly for girls, but girls continue to lag behind boys in school attendance. Moreover, the disparity in school attendance by sex grows with increasing age of children. At age 6-10, 85 percent of boys attend school compared with 78 percent of girls. By age 15-17, 58 percent of boys attend school compared with 40 percent of girls. The percentage of girls 6-17 attending school varies from 51 percent in Bihar and 56 percent in Rajasthan to over 90 percent in Himachal Pradesh and Kerala. Women in India tend to marry at an early age. Thirty-four percent of women age 15-19 are already married including 4 percent who are married but gauna has yet to be performed. These proportions are even higher in the rural areas. Older women are more likely than younger women to have married at an early age: 39 percent of women currently age 45-49 married before age 15 compared with 14 percent of women currently age 15-19. Although this indicates that the proportion of women who marry young is declining rapidly, half the women even in the age group 20-24 have married before reaching the legal minimum age of 18 years. On average, women are five years younger than the men they marry. The median age at marriage varies from about 15 years in Madhya Pradesh, Bihar, Uttar Pradesh, Rajasthan, and Andhra Pradesh to 23 years in Goa. As part of an increasing emphasis on gender issues, NFHS-2 asked women about their participation in household decisionmaking. In India, 91 percent of women are involved in decision-making on at least one of four selected topics. A much lower proportion (52 percent), however, are involved in making decisions about their own health care. There are large variations among states in India with regard to women's involvement in household decisionmaking. More than three out of four women are involved in decisions about their own health care in Himachal Pradesh, Meghalaya, and Punjab compared with about two out of five or less in Madhya Pradesh, Orissa, and Rajasthan. Thirty-nine percent of women do work other than housework, and more than two-thirds of these women work for cash. Only 41 percent of women who earn cash can decide independently how to spend the money that they earn. Forty-three percent of working women report that their earnings constitute at least half of total family earnings, including 18 percent who report that the family is entirely dependent on their earnings. Women's work-participation rates vary from 9 percent in Punjab and 13 percent in Haryana to 60-70 percent in Manipur, Nagaland, and Arunachal Pradesh. FERTILITY AND FAMILY PLANNING Fertility continues to decline in India. At current fertility levels, women will have an average of 2.9 children each throughout their childbearing years. The total fertility rate (TFR) is down from 3.4 children per woman at the time of NFHS-1, but is still well above the replacement level of just over two children per woman. There are large variations in fertility among the states in India. Goa and Kerala have attained below replacement level fertility and Karnataka, Himachal Pradesh, Tamil Nadu, and Punjab are at or close to replacement level fertility. By contrast, fertility is 3.3 or more children per woman in Meghalaya, Uttar Pradesh, Rajasthan, Nagaland, Bihar, and Madhya Pradesh. More than one-third to less than half of all births in these latter states are fourth or higher-order births compared with 7-9 percent of births in Kerala, Goa, and Tamil Nadu. Efforts to encourage the trend towards lower fertility might usefully focus on groups within the population that have higher fertility than average. In India, rural women and women from scheduled tribes and scheduled castes have somewhat higher fertility than other women, but fertility is particularly high for illiterate women, poor women, and Muslim women. Another striking feature is the high level of childbearing among young women. More than half of women age 20-49 had their first birth before reaching age 20, and women age 15-19 account for almost one-fifth of total fertility. Studies in India and elsewhere have shown that health and mortality risks increase when women give birth at such young ages?both for the women themselves and for their children. Family planning programmes focusing on women in this age group could make a significant impact on maternal and child health and help to reduce fertility. INFANT AND CHILD MORTALITY NFHS-2 provides estimates of infant and child mortality and examines factors associated with the survival of young children. During the five years preceding the survey, the infant mortality rate was 68 deaths at age 0-11 months per 1,000 live births, substantially lower than 79 per 1,000 in the five years preceding the NFHS-1 survey. The child mortality rate, 29 deaths at age 1-4 years per 1,000 children reaching age one, also declined from the corresponding rate of 33 per 1,000 in NFHS-1. Ninety-five children out of 1,000 born do not live to age five years. Expressed differently, 1 in 15 children die in the first year of life, and 1 in 11 die before reaching age five. Child-survival programmes might usefully focus on specific groups of children with particularly high infant and child mortality rates, such as children who live in rural areas, children whose mothers are illiterate, children belonging to scheduled castes or scheduled tribes, and children from poor households. Infant mortality rates are more than two and one-half times as high for women who did not receive any of the recommended types of maternity related medical care than for mothers who did receive all recommended types of care. HEALTH, HEALTH CARE, AND NUTRITION Promotion of maternal and child health has been one of the most important components of the Family Welfare Programme of the Government of India. One goal is for each pregnant woman to receive at least three antenatal check-ups plus two tetanus toxoid injections and a full course of iron and folic acid supplementation. In India, mothers of 65 percent of the children born in the three years preceding NFHS-2 received at least one antenatal

This data set contains experimental data collected as part of the field experiments conducted in West Bengal. These experiments study the effect of religious identity and religious fragmentation on cooperation, rent-seeking and income distribution among Hindu and Muslim groups. We study the effect of religious identity among Hindu and Muslim groups by varying the way our subjects are matched with each other. We implement in-group/in-group treatments where Muslim subjects play with fellow Muslim subjects and Hindu subjects play with fellow Hindu subjects; we also implement in-group/out-group treatments where Hindu subjects play with Muslim subjects. Finally, we have a control treatment where the identity of a subject's match is uncertain. To study the effect of fragmentation, we resort to a quasi-experimental approach. We take religious composition of villages as fixed, based on the village-level survey on religious fragmentation by Das et al. (2011). We select villages in two districts in West Bengal which conform to one of three categories: Muslim-dominated, where over 90% of the population is Muslim; Hindu-dominated, where over 90% of the population is Hindu; and fragmented, where the Muslim and Hindu communities are roughly equal. Our experimental design combines identity treatments with village types to understand how social identity interacts with fragmentation. For more details on the analysis of the data, please see the link to the first working paper to have come out of this project, which can be found in the "Related Resources" section. Tackling increasing resource scarcity is one of the major challenges to policy-makers in developing countries. An important aspect of resource scarcity involves public goods. Lack of public goods, like health and education, can significantly reduce the welfare of individuals and households and often this affects the poorest the most. In India, these issues are amplified by the existence of a long-standing social structure based around caste and religion. Such social fragmentation can result in social exclusion and/or lower public good provision. This project investigates the behavioural foundations of inter-group discrimination on economic performance in rural West Bengal, India. It builds on existing household survey work on religious- and caste-based social exclusion in villages in West Bengal by conducting a series of field experiments. Field experiments study the decisions of agents who in their daily lives are affected by poverty, and help determine the extent to which their preferences regarding caste, ethnicity and religion determine their willingness to socially exclude others or themselves to be excluded. This project‘s findings will help policy-makers to the extent that they facilitate the identification of the right policy response to social exclusion and lower economic performance, which in turn are key determinants of poverty. The data collection method employed experimental economics. The description of the recruitment of participants and experimental procedures is taken from section 3.4 of Chakravarty, S., Fonseca, M.A., Ghosh, S. and Marjit, S. (2015) "Religious fragmentation, social identity and cooperation: Evidence from a artefactual field experiment in India", University of Exeter Economics Department Discussion Paper Series 15/01. which is the first paper based on this project. A link to this paper is provided in this submission. Please see this paper for more details on the experimental procedures. We employed a mixed-gender, mixed-religion team of local research assistants to recruit participants and conduct the sessions, so as to minimize any possible experimenter demand effect. A week ahead of a planned session, our research assistants travelled to the village where that session would take place. A set of neighborhoods were randomly selected, and within each neighborhood, recruitment was done on a door-by-door basis. On a given street, every two consecutive houses were skipped and the third house would be approached and those who agreed to participate would be signed up. Participants were reminded about the session the day before it took place. Participants did not know the purpose of the experiment: when approached, they were informed that the research team would be conducting decision- making sessions. We conducted one session per village. In the H-H and M-M sessions, all subjects in the room shared the same religion. In the H-M sessions, subjects of both religious were present; Hindu subjects played a Muslim counterpart in every game and vice versa. This was common knowledge. Finally, in the MIX sessions, Hindu and Muslim subjects were present in the session, but they did not know the religion of the person with whom they were playing. Sessions were split in three parts. In the first part, participants played three games: the Prisoners' Dilemma, the Stag-Hunt game and the Tullock contest (in that specific order). In the second part of the session, participants played a series of individual decision-making tasks. In the third part, participants individually responded to a survey in a separate room, got feedback on the decisions made in the experiment, and received their corresponding payment. An experimenter standing in the middle of the room read the instructions aloud, using visual aids to explain the incentive structure of each game (see Appendix for the experimental materials). We did not employ written instructions since about a third of our subjects was unable to read or write. As such, we denoted payoffs in INR and used images of Indian notes and coins to represent payoffs. See materials for details. Prior to the start of each session, an experimenter informed subjects that all decisions taken would be anonymous, there would be no identifying information collected as part of the experiment. Subjects were also told that they had the right to abandon the session; they also had the right to opt out of the study without detriment to their payment for participation. Again, this information was announced orally, as a large proportion of participants were not able to read or write.

Census: Population: by Religion: Muslim: West Bengal: Female data was reported at 12,014,733.000 Person in 03-01-2011. This records an increase from the previous number of 9,770,137.000 Person for 03-01-2001. Census: Population: by Religion: Muslim: West Bengal: Female data is updated decadal, averaging 10,892,435.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 12,014,733.000 Person in 03-01-2011 and a record low of 9,770,137.000 Person in 03-01-2001. Census: Population: by Religion: Muslim: West Bengal: 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.GAE003: Census: Population: by Religion: Muslim.

Non-syndromic hearing loss (NSHL) is one of the most frequent auditory deficits in humans characterized by high clinical and genetic heterogeneity. Very few studies have reported the relationship between OTOF (Locus: DFNB9) and hereditary hearing loss in India. We aimed to decipher the genetic cause of prelingual NSHL in a large affected Muslim consanguineous families using whole-exome sequencing (WES). The study was performed following the guidelines and regulations of the Indian Council of Medical Research (ICMR), New Delhi. The population was identified from Jammu and Kashmir, the Northernmost part of India. Near about 100 individuals were born deaf-mute in the village of 3,000 inhabitants. A total of 103 individuals (with 52 cases and 51 controls) agreed to participate in this study. Our study revealed a rare non-sense homozygous mutation NC_000002.11:g.2:26702224G>A; NM_001287489.2:c.2122C>T; NP_001274418.1:p.(Arg708∗) in the 18th exon of the OTOF gene. Our study provides the first insight into this homozygous condition, which has not been previously reported in ExAC, 1,000 Genome and genomAD databases. Furthermore, the variant was confirmed in the population cohort (n = 103) using Sanger sequencing. In addition to the pathogenic OTOF variant, the WES data also revealed novel and recurrent mutations in CDH23, GJB2, MYO15A, OTOG, and SLC26A4 genes. The rare pathogenic and the novel variants observed in this study have been submitted to the ClinVar database and are publicly available online with the accessions SCV001448680.1, SCV001448682.1 and SCV001448681.1. We conclude that OTOF-related NSHL hearing loss is prevalent in the region due to successive inbreeding in its generations. We recommend premarital genetic testing and genetic counseling strategies to minimize and control the disease risk in future generations.