In 2022, around 31.6 percent of the global population were identify as Christian. Around 25.8 percent of the global population identify as Muslims, followed by 15.1 percent of global populations as Hindu.

The World Religion Project (WRP) aims to provide detailed information about religious adherence worldwide since 1945. It contains data about the number of adherents by religion in each of the states in the international system. These numbers are given for every half-decade period (1945, 1950, etc., through 2010). Percentages of the states' populations that practice a given religion are also provided. (Note: These percentages are expressed as decimals, ranging from 0 to 1, where 0 indicates that 0 percent of the population practices a given religion and 1 indicates that 100 percent of the population practices that religion.) Some of the religions are divided into religious families. To the extent data are available, the breakdown of adherents within a given religion into religious families is also provided.

The project was developed in three stages. The first stage consisted of the formation of a religion tree. A religion tree is a systematic classification of major religions and of religious families within those major religions. To develop the religion tree we prepared a comprehensive literature review, the aim of which was (i) to define a religion, (ii) to find tangible indicators of a given religion of religious families within a major religion, and (iii) to identify existing efforts at classifying world religions. (Please see the original survey instrument to view the structure of the religion tree.) The second stage consisted of the identification of major data sources of religious adherence and the collection of data from these sources according to the religion tree classification. This created a dataset that included multiple records for some states for a given point in time. It also contained multiple missing data for specific states, specific time periods and specific religions. The third stage consisted of cleaning the data, reconciling discrepancies of information from different sources and imputing data for the missing cases.

The National Religion Dataset: The observation in this dataset is a state-five-year unit. This dataset provides information regarding the number of adherents by religions, as well as the percentage of the state's population practicing a given religion.

Census: Population: by Religion: Christian: Delhi data was reported at 146,093.000 Person in 03-01-2011. This records an increase from the previous number of 130,319.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Delhi data is updated decadal, averaging 138,206.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 146,093.000 Person in 03-01-2011 and a record low of 130,319.000 Person in 03-01-2001. Census: Population: by Religion: Christian: Delhi 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.GAE004: Census: Population: by Religion: Christian.

This study, designed and carried out by the "http://www.asarb.org/" Target="_blank">Association of Statisticians of American Religious Bodies (ASARB), compiled data on 372 religious bodies by county in the United States. Of these, the ASARB was able to gather data on congregations and adherents for 217 religious bodies and on congregations only for 155. Participating bodies included 354 Christian denominations, associations, or communions (including Latter-day Saints, Messianic Jews, and Unitarian/Universalist groups); counts of Jain, Shinto, Sikh, Tao, Zoroastrian, American Ethical Union, and National Spiritualist Association congregations, and counts of congregations and adherents from Baha'i, three Buddhist groupings, two Hindu groupings, four Jewish groupings, and Muslims. The 372 groups reported a total of 356,642 congregations with 161,224,088 adherents, comprising 48.6 percent of the total U.S. population of 331,449,281. Membership totals were estimated for some religious groups.

In January 2024, the ARDA added 21 religious tradition (RELTRAD) variables to this dataset. These variables start at variable #12 (TOTCNG_2020). Categories were assigned based on pages 88-94 in the original "https://www.usreligioncensus.org/index.php/node/1638" Target="_blank">2020 U.S. Religion Census Report.

Visit the "https://www.thearda.com/us-religion/sources-for-religious-congregations-membership-data" Target="_blank">frequently asked questions page for more information about the ARDA's religious congregation and membership data sources.

Census: Population: by Religion: Christian: Karnataka data was reported at 1,142,647.000 Person in 03-01-2011. This records an increase from the previous number of 1,009,164.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Karnataka data is updated decadal, averaging 1,075,905.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 1,142,647.000 Person in 03-01-2011 and a record low of 1,009,164.000 Person in 03-01-2001. Census: Population: by Religion: Christian: Karnataka 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.GAE004: Census: Population: by Religion: Christian.

Dear users,this dataset contains the 500m base grid for Central Germany as an ARCGIS shapefile in which all pixels have a uniqui ID.Please use this ID to link the spatial data (=grid) to the scenario tables, which are provided in the EXCEL file. Please read the read_me in the EXCEL file for more details on the data provided therein.Scenarios have been calculated with the SITE model using among other inputs 2 other figshare dadatsets:Population scenarios: https://figshare.com/articles/Population_scenarios_for_Central_Germany/3082183Spatial data Central Germany: https://figshare.com/articles/Central_Germany_GIS_dataset/1318765 Metadata to spatial data: https://figshare.com/articles/Centra_Germany_Dataset_Metadata/1319479Any questions welcome: joerg.priess@ufz.de (or the authors of the other datasets)

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.

Islam and Christianity form the two dominant religions in Nigeria. Since colonialism, approximately 90 percent of the Nigerian people identify themselves as Islamic or Christian. The northern region of Nigeria is predominately Islamic, while the southern region is predominately Christian.

Nigeria’s contact with Islam predated that of Christianity and European colonialism; its spread was facilitated into Sub-Saharan Africa through trade and commerce. The northern part of Nigeria is symbolic to the history of Islam, as it penetrated the area through the Kanem-Borno Empire in the 11th century before spreading to other predominately Hausa states. Islam was then introduced into the traditional societies of the Yoruba-speaking people of south-west Nigeria through their established commercial relationship with people of the north, particularly the Nupe and Fulani.

Christianity reached Nigeria in the 15th century with the visitation of Catholic missionaries to the coastal areas of the Niger-Delta region. Christianity soon recorded a boost in the southern region given its opposition to the slave trade and its promotion of Western education.

The distinct religious divide has instigated violence in present-day Nigeria, including the Sharia riot in Kaduna in 2000, ongoing ethno-religious violence in Jos since 2001, and the 2011 post-election violence that erupted in some northern states, particularly in the city of Maiduguri. Nigerians’ continued loyalty to religion compared to that of the country continues to sustain major political debate, conflict, and violent outbreaks between populations of the two faiths.

ISO3-International Organization for Standardization 3-digit country code

NAME-Name of religious institution

TYPE-Type of religious institution

CITY-City religious institution is located in

SPA_ACC-Spatial accuracy of site location 1- high, 2 – medium, 3 - low

SOURCE_DT-Source creation date

SOURCE-Primary source

SOURCE2_DT-Secondary source creation date

SOURCE2-Secondary source

Collection

This HGIS was created using information collected from the web sites GCatholic.org, Islamic Finder, Wikimapia, and BBBike.org, which uses OpenStreetMap, a crowd-source collaboration project that geo-locates sites throughout the world. After collection, all education institutions were geo-located.

The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe Analytics is not responsible for the accuracy and completeness of data compiled from outside sources.

Sources (HGIS)

BBBike, "Nigeria." Last modified 2013. Accessed March 19, 2013. http://extract.bbbike.org.

GCatholic.org, "Catholic Churches in Federal Republic of Nigeria." Last modified 2013. Accessed April 4, 2013. http://www.gcatholic.org/.

Islamic Finder, "Nigeria." Last modified 2013. Accessed April 4, 2013. http://islamicfinder.org/.

Olanrewaju, Timothy. The Sun, "oko Haram attacks church in Maiduguri." Last modified 2013. Accessed April 9, 2013. http://sunnewsonline.com/.

Wikimapia, "Nigeria:Mosques/Churches." Last modified 2013. Accessed April 4, 2013. http://wikimapia.org/

World Watch Monitor, "Muslim Threat to Attack Church Raises Tensions." Last modified 2012. Accessed April 9, 2013. http://www.worldwatchmonitor.org/.

Sources (Metadata)

Danjibo, N.D. "Islamic Fundamentalism and Sectarian Violence: The "Maitatsine" and "Boko Haram" Crises in Northern Nigeria." manuscript., University of Ibadan, 2010. http://www.ifra-nigeria.org.

Olanrewaju, Timothy. The Sun, "oko Haram attacks church in Maiduguri." Last modified 2013. Accessed April 9, 2013. http://sunnewsonline.com/.

Onapajo, Hakeem. "Politics for God: Religion, Politics, and Conflict in Democratic Nigeria." Journal of Pan African Studies. 4. no. 9 (2012): 42-66. http://web.ebscohost.com (accessed March 26, 2013).

World Watch Monitor, "Muslim Threat to Attack Church Raises Tensions." Last modified 2012. Accessed April 9, 2013. http://www.worldwatchmonitor.org/.

PerCapita_CO2_Footprint_InDioceses_FULLBurhans, Molly A., Cheney, David M., Gerlt, R.. . “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.MethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

Census: Population: by Religion: Christian: Sikkim data was reported at 60,522.000 Person in 03-01-2011. This records an increase from the previous number of 36,115.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Sikkim data is updated decadal, averaging 48,318.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 60,522.000 Person in 03-01-2011 and a record low of 36,115.000 Person in 03-01-2001. Census: Population: by Religion: Christian: Sikkim 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.GAE004: Census: Population: by Religion: Christian.

According to the population census data in 2010, 54.14 percent of the population in East Nusa Tenggara, Indonesia were Catholics. East Nusa Tenggara is the province with the least Muslim population in Indonesia. Indonesia has the largest Islamic population in the world. However, Indonesia is a multi-faith country that recognizes six official religions – Islam, Protestantism, Catholicism, Buddhism, Hinduism, and Confucianism.

Religious commitment during the pandemic.

Census: Population: by Religion: Christian: Himachal Pradesh data was reported at 12,646.000 Person in 03-01-2011. This records an increase from the previous number of 7,687.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Himachal Pradesh data is updated decadal, averaging 10,166.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 12,646.000 Person in 03-01-2011 and a record low of 7,687.000 Person in 03-01-2001. Census: Population: by Religion: Christian: Himachal Pradesh 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.GAE004: Census: Population: by Religion: Christian.

The purpose of the study: to explore the attitudes of Lithuanian population towards the development of European identity and citizenship in the context of EU change and enlargement. Major investigated questions: respondents were asked whether they support Lithuania's membership in the EU and how membership in this organisation brings benefits and disadvantages to Lithuania. They were asked whether they voted in the European Parliament elections and whether they often watch TV, listen to the radio or read daily newspapers to find out about political news. Next, they were asked to rate the influence of different people on important national issues (ordinary citizen; Member of the European Parliament - 11 choices in total). The survey went on to analyse whether it is more important to grow a competitive European economy within global markets or to ensure better social protection for all its citizens. They were asked to reveal the extent to which they associate themselves with their region, their country or Europe (EU). Given the block of questions, they were asked what it means to be Lithuanian (to be Christian; to follow Lithuanian cultural traditions - 8 choices in total). Given the list of threats, they were asked to rate the risk those threats pose to the EU (non-EU immigrants; EU expansion by including Turkey - 5 choices in total). Respondents had the opportunity to assess European unification and to indicate what it means to be European (being a Christian; following the European cultural traditions - 8 choices in total). Then, trust in the EU and in the ability of Lithuanian institutions to take the right decisions was assessed. The aim was to find out whether respondents felt that decision-makers at the EU level did not take Lithuania's interests into account sufficiently, and whether the interests of some EU Member States were given too much weight. The survey went on to analyse whether different policy areas should be dealt with at the national level or EU level (fight against unemployment; immigration policy [from non-EU countries] - 8 choices in total). Given the next set of questions, respondents were asked what the EU will look like in 10 years (unified EU tax system; mutual social security system - 4 choices in total). Next, they were asked how satisfied they are with the way democracy works in the EU and Lithuania. The survey went on to analyse whether the European Commission should be politically accountable to the European Parliament. Given another block of statements, respondents were asked whether or not different EU policies pose a risk to Lithuania (5 choices in total). Next, the survey went on to assess whether the redistribution of resources between EU Member States to protect the single currency is fair. Respondents were asked whether there should be a mutual EU army or whether each EU Member State should have its national army, and which institution is best suited to take care of Europe's security. Respondents were asked whether they were personally content with the introduction of the euro in Lithuania in 2015 and to describe their political views on a left-right scale. While having the future of the EU in mind, respondents were asked what the EU economy, the economic disparities between EU member states, the social disparities between EU citizens, the importance of the EU as a geopolitical power in the world and what the EU politically will be like in 10 years. The survey was concluded by asking whether or not Lithuania has benefited from EU membership. Socio-demographic characteristics: gender, age, nationality, education, marital status, occupation, income per household member per month, place of residence, lived, worked, studied abroad, religion, frequency of participation in religious services.

Census: Population: by Religion: Christian: Chandigarh data was reported at 8,720.000 Person in 03-01-2011. This records an increase from the previous number of 7,627.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Chandigarh data is updated decadal, averaging 8,173.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 8,720.000 Person in 03-01-2011 and a record low of 7,627.000 Person in 03-01-2001. Census: Population: by Religion: Christian: Chandigarh 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.GAE004: Census: Population: by Religion: Christian.

Philippines Population: RA: Tribal Religions data was reported at 243,704.000 Person in 2015. This records an increase from the previous number of 207,246.000 Person for 2010. Philippines Population: RA: Tribal Religions data is updated yearly, averaging 207,246.000 Person from Dec 2000 (Median) to 2015, with 3 observations. The data reached an all-time high of 243,704.000 Person in 2015 and a record low of 164,080.000 Person in 2000. Philippines Population: RA: Tribal Religions data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G003: Population: Religious: Affiliation.

Philippines Population: RA: Church of Christ data was reported at 319,987.000 Person in 2015. This records an increase from the previous number of 287,734.000 Person for 2010. Philippines Population: RA: Church of Christ data is updated yearly, averaging 303,860.500 Person from Dec 2010 (Median) to 2015, with 2 observations. The data reached an all-time high of 319,987.000 Person in 2015 and a record low of 287,734.000 Person in 2010. Philippines Population: RA: Church of Christ data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G003: Population: Religious: Affiliation.

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.

Philippines Population: RA: Crusaders of the Divine Church of Christ, Inc data was reported at 47,877.000 Person in 2015. This records a decrease from the previous number of 65,008.000 Person for 2010. Philippines Population: RA: Crusaders of the Divine Church of Christ, Inc data is updated yearly, averaging 56,442.500 Person from Dec 2010 (Median) to 2015, with 2 observations. The data reached an all-time high of 65,008.000 Person in 2010 and a record low of 47,877.000 Person in 2015. Philippines Population: RA: Crusaders of the Divine Church of Christ, Inc data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G003: Population: Religious: Affiliation.

Singapore Population: Religion: Female: Islam data was reported at 233.800 Person th in 2015. This records an increase from the previous number of 231.478 Person th for 2010. Singapore Population: Religion: Female: Islam data is updated yearly, averaging 231.478 Person th from Jun 2000 (Median) to 2015, with 3 observations. The data reached an all-time high of 233.800 Person th in 2015 and a record low of 185.804 Person th in 2000. Singapore Population: Religion: Female: Islam data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G002: Population by Religion .