In 2020, around 28.8 percent of the global population were identified as Christian. Around 25.6 percent of the global population identify as Muslims, followed by 14.9 percent of global populations as Hindu. The number of Muslims increased by 347 million, when compared to 2010 data, more than all other religions combined.

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 (as detailed below) 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 Global Religion Dataset: This dataset uses a religion-by-five-year unit. It aggregates the number of adherents of a given religion and religious group globally by five-year periods.

Census: Population: by Religion: Christian: Madhya Pradesh: Female data was reported at 107,985.000 Person in 03-01-2011. This records an increase from the previous number of 85,025.000 Person for 03-01-2001. Census: Population: by Religion: Christian: Madhya Pradesh: Female data is updated decadal, averaging 96,505.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 107,985.000 Person in 03-01-2011 and a record low of 85,025.000 Person in 03-01-2001. Census: Population: by Religion: Christian: Madhya Pradesh: 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.GAE004: Census: Population: by Religion: Christian.

About this dataset

Context

The dataset tabulates the population of Pass Christian by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Pass Christian across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 51.08% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Pass Christian is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Pass Christian total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Pass Christian Population by Race & Ethnicity. You can refer the same here

This Religion and State-Minorities (RASM) dataset is supplemental to the Religion and State Round 2 (RAS2) dataset. It codes the RAS religious discrimination variable using the minority as the unit of analysis (RAS2 uses a country as the unit of analysis and, is a general measure of all discrimination in the country). RASM codes religious discrimination by governments against all 566 minorities in 175 countries which make a minimum population cut off. Any religious minority which is at least 0.25 percent of the population or has a population of at least 500,000 (in countries with populations of 200 million or more) are included. The dataset also includes all Christian minorities in Muslim countries and all Muslim minorities in Christian countries for a total of 597 minorities. The data cover 1990 to 2008 with yearly codings.

These religious discrimination variables are designed to examine restrictions the government places on the practice of religion by minority religious groups. It is important to clarify two points. First, these variables focus on restrictions on minority religions. Restrictions that apply to all religions are not coded in this set of variables. This is because the act of restricting or regulating the religious practices of minorities is qualitatively different from restricting or regulating all religions. Second, this set of variables focuses only on restrictions of the practice of religion itself or on religious institutions and does not include other types of restrictions on religious minorities. The reasoning behind this is that there is much more likely to be a religious motivation for restrictions on the practice of religion than there is for political, economic, or cultural restrictions on a religious minority. These secular types of restrictions, while potentially motivated by religion, also can be due to other reasons. That political, economic, and cultural restrictions are often placed on ethnic minorities who share the same religion and the majority group in their state is proof of this.

This set of variables is essentially a list of specific types of religious restrictions which a government may place on some or all minority religions. These variables are identical to those included in the RAS2 dataset, save that one is not included because it focuses on foreign missionaries and this set of variables focuses on minorities living in the country. Each of the items in this category is coded on the following scale:

0. The activity is not restricted or the government does not engage in this practice.
1. The activity is restricted slightly or sporadically or the government engages in a mild form of this practice or a severe form sporadically.
2. The activity is significantly restricted or the government engages in this activity often and on a large scale.

A composite version combining the variables to create a measure of religious discrimination against minority religions which ranges from 0 to 48 also is included.

ARDA Note: This file was revised on October 6, 2017. At the PIs request, we removed the variable reporting on the minority's percentage of a country's population after finding inconsistencies with the reported values. For detailed data on religious demographics, see the "/data-archive?fid=RCSREG2" Target="_blank">Religious Characteristics of States Dataset Project.

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.

This data set is part of the following publication:Jetten, M. (2018). Knowledge of interaction styles and dimensions of interpretation in interreligious adult education. An empirical study of the effects of a hermeneutic-communicative curriculum. Radboud University. Münster: LIT Verlag.This book reports on an evaluation study of a curriculum on interreligious dialogue among Christian and Muslims adults in the Netherlands. It was organized as a PhD-project between 2007 and 2013 at the Faculty of Philosophy, Theology and Religious Studies of Radboud University, financed by Stichting Nieuwegen.The primary aim of this research is to explain the contribution of a curriculum to knowledge of interaction styles and hermeneutic distinctions that are used to express and interpret the views on religious phenomena of adherents from different religious traditions. We consider knowledge of communication and interpretation conditional for mutual understanding between adherents of different religious traditions. We refer to this as hermeneutic-communicative learning. The focus of this dissertation is not solely religious phenomena, but the way that participants express and interpret these phenomena. Hence, the research goal of this study is: explaining the contribution of a hermeneutic-communicative curriculum using the method of mediated learning to the acquisition of knowledge of interaction styles and dimensions for interpreting religious phenomena.This study uses a quasi-experimental design with pre-test and post-test, based on two non-equivalent groups (“untreated non-equivalent control group design with pre-test and post-test”, Cook & Campbell 1979, 103-129). To study the effects of participation in our curriculum, we distinguish two research groups, an experimental group that participates in the intervention, and a control group that does not participate. In both groups a pre-test and a post-test is held, respectively before and after the intervention.Our research population are Christian and Muslim adults in the Netherlands who are interested in interreligious meetings. To be able to reliably estimate the characteristics of the research population, we required a sample of at least 400 respondents in total, with 200 participants in the experimental group and 200 in the control group. Regarding the experimental group, we aimed at 20 curriculum locations, each with about twelve participants, making sure that respondent still feel secure to exchange religious beliefs and practices in a personal and informal way. We sought a group distribution of at least a third Christians or a third Muslims at each location. Regarding religion, the relative number of Christians in the control group appeared to be higher than in the experimental group. Therefore, in the analyses, we randomly reduced the number of Christians in the control group by 40%, by deleting the third and fifth of each five Christian respondents in the control group. This resulted in a total number of 260 respondents in the experimental group and 132 respondents in the control group.Part of this research project of Radboud University is the material for an interreligious course. It has been developed for Christian and Muslim adults with interest in interreligious communication. Participants get acquainted with a practical method that eases interreligious dialogue, focused at both enriching one’s own religious identity as well as getting familiar with the religion of the other. Focus is learning to communicate from the personal perspective, applied to substantive themes from Christianity and Islam.You are welcome to re-use and adjust all available curriculum materials and guidance sheets. Feel free to use part of the material, split up the material in separate units, or adjust to materials to your own needs, as long as you respect the copyright. Please refer to this dataset and the aforementioned publication.The data set contains various types of files, which are further explained in the read me first file.- Read me first file- Data files (SPSS files)- Documentation on the data set (methodology and measuring instruments)- Documentation on the interreligious curriculum (including the full program and guidance sheets for educators)

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.

(UNCLASSIFIED) The Liberian population is religiously heterogeneous, comprised 85.6 percent Christian, 12.6 percent Muslim, 0.6 percent adherents of tribal or indigenous traditions, 1.5 percent non-religious, and less than 1 percent a combination of Bahais, Hindus, Sikhs, and Buddhists. Primary denominations within the country’s Christian majority include Lutheran, Baptist, Episcopal, Presbyterian, Roman Catholic, United Methodist, African Methodist Episcopal (AME), AME Zion, and Pentecostal. Many individuals identified as "Christian" retain a mix of Christian and indigenous (often animistic) beliefs. Both Christian and Muslim Liberians are dispersed throughout the country. Most Muslims belong to two distinct ethnic groups, the Mandingo—who are widely distributed—and the Vai who live mostly in western areas.Christianity reached Liberia in the 19th century with the arrival of freed slaves from the United States. Missionaries of various Protestant denominations started arriving in the 1820s, eventually forming what became one of the highest per capita missionary populations in the world. The first permanent Catholic mission in the country was established in the early 1900s. A Liberian Council of Churches composed of Lutheran, Episcopal, Methodist, and other similar groups now exists, and an evangelical association of churches and missions has operated on and off since 1966. Though religiously-motivated violence in Liberia is relatively uncommon, tensions between Christians and Muslims have escalated in the past. In October 2004, approximately 25 people were killed and several churches and mosques were destroyed in Monrovia during clashes between Christians of several ethnic groups and Mandingo Muslims. The Liberian constitution provides religious freedom for all inhabitants, and in practice, the government respects minority religious groups. According to a 2013 document published by the U.S. Department of State, the Liberian government does not discriminate based on religious affiliation, belief, or worship. Although there is no state religion in the country, government ceremonies commonly begin and end with prayers or hymns, the majority of which are Christian, though some are Muslim. Most private schools in the country are operated by churches or missions. The majority receive government funding, though non-religious schools are also heavily subsidized. Religious education is available as an elective in public schools, but is not required. Social welfare institutions are largely managed or affiliated with religious organizations, often in conjunction with international aid agencies. As regards the ongoing Ebola crisis in West Africa, some religious leaders in Liberia have cited “immoral acts” as the cause of the outbreak. In August 2014, Liberia’s Council of Churches agreed, “God is angry with Liberia,” and urged Liberians to seek forgiveness for corruption and immorality by staying indoors and fasting for three days.Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name ADM1_NAME - Administration level one identification / name ADM2_NAME - Administration level two identification / name NAME - Name of religious institution TYPE - Classification in the geodatabase (type of institution) CITY - City location available SPA_ACC - Spatial accuracy of site location (1 – high, 2 – medium, 3 – low) COMMENTS - Comments or notes regarding the religious institution SOURCE_DT - Source one creation date SOURCE - Source one SOURCE2_DT - Source two creation date SOURCE2 - Source two CollectionThe feature class was generated utilizing data from OpenStreetMap, Wikimapia, GeoNames and other sources. OpenStreetMap is a free worldwide map, created by crowd-sourcing. Wikimapia is open-content mapping focused on gathering all geographical objects in the world. GeoNames is a geographical places database maintained and edited by the online community. Consistent naming conventions for geographic locations were attempted but name variants may exist, which can include historical or less widespread interpretations.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 is not responsible for the accuracy and completeness of data compiled from outside sources.Metadata information was collected form U.S. Department of State publications as well as news media articles. Sources (HGIS)"Cathedral of St. Therese of The Child Jesus." GCatholic. July 2014. Accessed October 7, 2014. http://www.gcatholic.org.DigitalGlobe, "DigitalGlobe Imagery Archive." Accessed October 01, 2014. GeoNames, "Liberia." September 23, 2014. Accessed October 01, 2014. http://www.geonames.org.Google, September 2014. Accessed October 01, 2014. www.google.com.OpenStreetMap, "Liberia." September 2014. Accessed October 01, 2014. http://www.openstreetmap.org.Wikimapia, "Liberia." September 2014. Accessed October 01, 2014. http://wikimapia.org.Sources (Metadata)Baden, Joel and Candida Moss. “Ebola Is Not God’s Wrath: Religious leaders are perpetuating dangerous, dehumanizing beliefs about sin and disease.” Slate. August 20, 2014. Accessed October 01, 2014. http://www.slate.com.“Country Profile: Liberia.” Soudan Interior Mission. January 01, 2014. Accessed October 01, 2014. http://www.sim.org.“Education System in Liberia.” Classbase. January 01, 2012. Accessed October 01, 2014. http://www.classbase.com.“Liberia 2005 International Religious Freedom Report.” United States Department of State: Bureau of Democracy, Human Rights, and Labor. January 01, 2005. Accessed October 01, 2014. http://www.state.gov.“Liberia 2012 International Religious Freedom Report.” United States Department of State: Bureau of Democracy, Human Rights, and Labor. January 01, 2005. Accessed October 01, 2014. http://www.state.gov.“Liberia 2014 International Religious Freedom Report.” United States Department of State. January 01, 2014. Accessed October 01, 2014. http://www.state.gov.

The present study “shows the development of members of the protestant and the Roman Catholic Church in Germany and analyzes the importance of certain components of the membership development. The survey is based on data of the statistical office since the 1950s and on data of both churches (Protestant Church in Germany, Hannover, and German Bishops Conference, Bonn) on church life. The study aims to compile the membership development of both Christian churches in long time series, to analyze it systematically and to question, extent and quantify the thus far monocausal explanations for membership development. Since the late 1960s world trade and the related social changes, the immigration to Germany since the 1950s and the changes related to the German reunification and the European integration caused that both Christian churches in Germany got less important. Alternative religious communities emerged. Among those for example the Islam with about 4 Billion followers and small Free Church communities play a more and more important role. The official statistic has no or little data about those religious communities; therefor the survey concentrates on two National Christian Churches” (Eicken, J. /Schmitz-Veltin, A., 2010, a. a. O., p. 577). Compared to the discussion about leaving the church the public discussion pays little attention to demographic factors of membership development. The present study aims to show that the membership development is not only characterized by persons leaving, but that structure elements have an important impact, too. These “effects are not least based on the long term development of birth rates and the resulting surpluses of deaths as well as the changes of values concerning baptism. These processes together lead to a less important role of church in society.” (Eicken, J./Schmitz-Veltin, A., 2010, a. a. O., S. 576f). Data tables in HISTAT: A.1 Population in Germany by religious orientations and membership development of both National Churches (1956-2008) In der vorliegenden Untersuchung „wird die Mitgliederentwicklung der evangelischen sowie der römisch-katholischen Kirche in Deutschland dargestellt und analysiert, welches Gewicht den einzelnen Komponenten der Mitgliederentwicklung hierbei zukommt. Der Beitrag stützt sich auf Zahlen des Statistischen Bundesamtes seit den 1950er-Jahren beziehungsweise auf von den beiden Kirchen (Evangelische Kirche in Deutschland, Hannover, sowie Deutsche Bischofskonferenz, Bonn) zur Verfügung gestellte Daten zum „kirchlichen Leben“. Der Beitrag verfolgt das Ziel, die Mitgliederentwicklung in den beiden großen christlichen Volkskirchen als lange Zeitreihe synoptisch zusammenzustellen, systematisch aufzubereiten und zu analysieren und damit den bisher sehr stark monokausal ausgerichteten Erklärungsansatz zur Mitgliederentwicklung zu hinterfragen, zu erweitern und zu quantifizieren. Der seit den späten 1960er-Jahren zu beobachtende Wertewandel und die damit einhergehenden gesellschaftlichen Umbrüche, die Zuwanderung nach Deutschland seit den 1950er-Jahren sowie die Umwälzungen im Zuge der deutschen Vereinigung und der europäischen Integration haben dazu geführt, dass die beiden christlichen Volkskirchen in Deutschland an Bedeutung verloren haben. Neben die römisch-katholische und die evangelische Kirche sind zunehmend alternative Glaubensgemeinschaften getreten. Unter diesen spielen beispielsweise der Islam mit rund 4 Mill. Anhängern sowie kleinere freikirchliche oder charismatische Gemeinden zunehmend eine Rolle. Über diese Religionsgemeinschaften liegen in der amtlichen Statistik jedoch keine bzw. nur wenige Angaben vor, sodass sich der Beitrag im Folgenden auf die christlichen Volkskirchen konzentriert“ (Eicken, J./Schmitz-Veltin, A., 2010, a. a. O., S. 577). Im Gegensatz zu der Diskussion um Kirchenaustritt wird den demografischen Faktoren der Mitgliederentwicklung in der aktuellen Diskussion wenig Aufmerksamkeit geschenkt. Der vorliegende Beitrag möchte vor diesem Hintergrund aufzeigen, dass die Mitgliederentwicklung der großen Volkskirchen nicht nur durch Austritte geprägt ist, sondern altersstrukturelle Effekte ebenfalls als Ursache in Erwägung zu ziehen sind. Diese „Effekte sind nicht zuletzt auf die langfristige Entwicklung der Geburtenzahl und den hieraus resultierenden Überschüssen der Sterbefälle sowie auf Wertänderungen bezüglich Taufen zurückzuführen. Zusammengenommen führen diese Prozesse zu einer gesellschaftlichen Entkirchlichung. Unter Entkirchlichung wird in dem Beitrag das sich in zurückgehenden Mitgliederzahlen äußernde Nachlassen der Bindekräfte der gro0en Volksmassen verstanden“ (Eicken, J./Schmitz-Veltin, A., 2010, a. a. O., S. 576f). Datentabellen in HISTAT: A.1 Einwohnerzahl in Deutschland nach Religionszugehörigkeit und Mitgliederbewegungen in den beiden christlichen Volkskirchen (1956-2008)

This dataset provides data on the occurrence of 672 European bryophyte species in European countries or territories. All species which are considered threatened or near threatened according to the European Red List (Hodgetts et al. 2019) are included (553 species). Further, all species evaluated in the European Red List assessed as LC, DD, NE and EX, which at the same time are either endemic, near endemic or globally rare, are included (119 species). Therefore, the list contains not only all European bryophyte species that are threatened or near threatened, but also all species endemic or near endemic to Europe as well as all globally rare species occurring in Europe. For each of the 553 threatened or near threatened species, we provide a conservation a priority score which was calculated based the Red List status and the proportion of the European population of the global population or the global rarity of the species. For details on the prioritisation approach see Bisang et al. (2025).

Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species' ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability.

Already at the planning stage of the “Funerary Practices – A Study of Social Differences after Death” project, the fundamental idea was that the main data for the study would be provided by a broad survey of the large majority of all Church of Sweden funerals. It is well-known that the weakening of Christian customs related to service attendance and the use of other Christian practices (baptism, confirmation, and church weddings) is less pronounced when it comes to church funerals. The ritual form of the church funeral is largely defined through the order of service for funerals in Den svenska kyrkohandboken [approx. The Swedish Church Manual]. However, for several points in the service, the handbook offers alternative forms and the possibility of leaving them out, and the final part of the service mainly depends on whether there will be an earth burial or a cremation. There is hardly any information from previous studies regarding the formulation of the funeral service, and there is no individual information about what happens to the coffin with the deceased after the service. These facts alone are enough to warrant a study of funerary practices and their variations. The section on funerals in the church manual, which defines the ritual framework for funeral services, begins by observing that the funeral is part of a situation extending from the deathbed to the final leave-taking by the grave. A similar view informed the idea of a broad study of contemporary funerary practices in Sweden: not only - or mainly – would the study focus on the rituals of the church or chapel; it would also examine what goes on before and, to some extent, after the funeral service to the largest possible extent. Above all, it would address the social aspects (broadly interpreted) of funerals not regulated by the church manual or otherwise governed by established regulations. The raw data for the study is available from LUKA, the Church History Archive of Lund University. Purpose: During the second and third quarter of 1997 were an extensive survey material concerning funerals collected at the Department of Theology at University of Lund. The collection was part of a research project on "Funeral Customs - the study of social differences after death" conducted with funding from the Social Science Research Council (SFR). The survey forms provide information on many matters concerning funeral customs of modern Sweden. The questions sought to capture both the social events surrounding the funerals as well as the ritual events of the funeral church services. The dataset is comprised of an SPSS file, containing coded answers to the study's questionnaire. Redan då projektet "Begravningsseder - studier av sociala skillnader efter döden" började planeras var en grundtanke att en bred enkätundersökning om den stora majoritet av alla begravningar som Svenska kyrkan svarar för skulle utgöra ett huvudmaterial inom projektet. Det är välbekant att den försvagning av den kristna seden som kan iakttas både vad gällande gudstjänstbesök och utnyttjande av de övriga kyrkliga handlingarna (dop, konfirmation och kyrklig vigsel) inte i lika hög grad gjort sig gällande när det gäller de kyrkliga begravningarna. Den rituella formen för de kyrkliga begravningarna är i stort sett fastlagd i Den svenska kyrkohandbokens ordning för begravningsgudstjänster. Handboken erbjuder emellertid vid flera av momenten i gudstjänsten både alternativa former och möjligheter till utlämnande och vilken avslutning gudstjänsten får sammanhänger främst med om den döda skall jordbegravas eller kremeras. Beträffande begravningsgudstjänsternas utformning finns knappast några uppgifter från tidigare studier och när det gäller vad som efter gudstjänsten sker med kistan med den döda finns det inte några individuella uppgifter. Bara de nämnda förhållandena kunde motivera en undersökning av hur begravningssederna ter sig i praktiken och vilka variationer som finns. I den kyrkohandbok som anger de rituella ramarna för hur en begravningsgudstjänst skall utformas inleds avsnittet om "Begravning" med ett konstaterande att "Begravningen ingår i ett sammanhang som sträcker sig från dödsbädden till avskedet vid graven". Ett liknande synsätt låg bakom tankarna på en bred undersökning av hur begravningssederna gestaltar sig i dagens Sverige: den skulle inte bara eller främst koncentreras på det rituella skeendet i kyrkan eller gravkapellet utan den skulle också i görligaste mån uppmärksamma vad som händer före och i viss mån också efter begravningsgudstjänsten och den skulle framförallt ta upp de i bred mening sociala aspekterna på en begravning som inte regleras i Kyrkohandboken eller på annat sätt styrs av fastlagda regelverk. Studiens grundmaterial finns hos LUKA, Lunds kyrkohistoriska arkiv. Syfte: Under andra och tredje kvartalet 1997 insamlades vid Teologiska institutionen i Lund ett omfattande enkätmaterial rörande begravningar. Materialinsamlingen ingick som ett led i ett forskningsprojekt om "Begravningsseder - studier av sociala skillnader efter döden" som bedrevs med stöd från Socialvetenskapliga Forskningsrådet (SFR). Enkätformulären ger upplysningar om många förhållanden som rör begravningssederna i dagens Sverige. Frågorna avsåg att fånga såväl det i bred mening sociala skeendet kring begravningarna som det rituella skeendet vid begravningsgudstjänsterna. Datasetet utgörs av en SPSS-fil med kodade svar på studiens enkät. Seen as a survey of parish priests, the study would constitute a census. Accordingly, the questionnaire should have been sent to 3,132 priests. Those who stated that they were on leave, and thus could not be expected to officiate at funerals, were excluded from the population, giving a total of 3,035 priests. For a number of pastorates, the position as rector was reported to be vacant. All the letters with questionnaires were sent to individuals and not to someone holding a particular position. This was unproblematic to the extent that other active priests were substituting for a vacant position, but not when a retired priest did so. The result was that the funeral practices of a few pastorates in thinly populated areas, each with the position as rector vacant at the time of the survey, were not included. Whether “kontraksadjunkter” (approx. deanery curates) should be included in the population was doubtful. They appear to have somewhat different positions in the various dioceses. Apart from any special functions, many of them also have a parish connection; the Finnish-language parish work within the Church of Sweden is largely managed by “kontraktsadjunkter”, which is why this category of priests is included in the survey population. Another borderline category included was those who were listed as “Other priests”. This category includes priests who, for various reasons, have been hired for personal position; they are hired by the diocese without any diocesan functions but they are not connected to any particular pastorate. They can assume particular duties such as funerals, and are for that reason included in the survey population. Priests within the Swedish Evangelical Mission (Evangeliska Fosterlands-Stiftelsen, EFS) were not included in the survey population. The number of annual funerals for the roughly 150 EFS priests listed in the roster is considerably smaller than for priests with a “normal” parish position. A high response rate in this group could have given a somewhat skewed picture of how funerals according to the order of the Church of Sweden are carried out. Om man ser undersökningen som en enkät till präster med församlingstjänst är det fråga om en totalundersökning. Enligt denna princip skulle enkäten gått ut till 3132 präster. De som angav att de var tjänstlediga och alltså inte kunde förväntas ha några begravningar lämnades utanför populationen, varför antalet istället blev 3035. För ett antal pastorat uppgavs kyrkoherdetjänsten vara vakant. Alla brev med formulär hade som adressat en enskild person och inte någon som upprätthöll en viss tjänst. I den mån andra aktiva präster vikarierade på en vakant tjänst innebär förfarandet inga problem, däremot om en pensionerad präst gjorde det. Följden blev att från några få glesbygdspastorat som endast har en kyrkoherdetjänst vilken vid den aktuella tidpunkten var vakant, efterfrågades aldrig skeendet vid en begravning. Huruvida kontraktsadjunkterna skulle ingå i urvalet var tveksamt. Dessa förefaller ha något olika ställning inom de olika stiften. Många av dem har vid sidan om speciella funktioner också en församlingsanknytning, och det finskspråkiga församlingsarbetet inom Svenska kyrkan handhas i stor utsträckning av kontraktsadjunkter, varför också denna prästkategori inkluderades i undersökningspopulationen. En annan gränsgrupp som inkluderades var de som upptas som ”Övriga präster”. Det rör sig om präster som av skilda anledningar fått en personlig tjänst; de är alltså anställda av stiftet utan att ha några särskilda stiftsfunktioner men de är inte heller knutna till något speciella pastorat. Dessa kan ta på sig särskilda uppgifter som t ex begravningar och av detta skäl inkluderades de i undersökningspopulationen. Präster inom Evangeliska Fosterlands-Stiftelsen ansågs falla utanför undersökningspopulationen. Antalet begravningar under ett år på de drygt 150 EFS-präster som upptas i matrikeln är avsevärt lägre än bland präster med ”vanlig” församlingstjänst. Hade svarsfrekvensen inom gruppen blivit hög hade det funnits en risk för att totalbilden av hur begravningarna enligt Svenska kyrkans ordning gestaltar sig i någon mån blivit felaktig.

Genotypes and allele frequencies of the investigated six CR1 variants among world populations.

About this dataset

Context

The dataset tabulates the population of Christian County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Christian County. The dataset can be utilized to understand the population distribution of Christian County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Christian County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Christian County.

Key observations

Largest age group (population): Male # 55-59 years (1,361) | Female # 35-39 years (1,269). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Christian County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Christian County is shown in the following column.
• Population (Female): The female population in the Christian County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Christian County for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Christian County Population by Gender. You can refer the same here

About this dataset

Context

This list ranks the 18 cities in the Christian County, IL by Multi-Racial Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Multi-Racial Other Race Population: This column displays the rank of cities in the Christian County, IL by their Multi-Racial Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Other Race Population: The Multi-Racial Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Christian County Multi-Racial Other Race Population: This tells us how much of the entire Christian County, IL Multi-Racial Other Race population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

About this dataset

Context

The dataset tabulates the population of Christian County by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Christian County. The dataset can be utilized to understand the population distribution of Christian County by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Christian County. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Christian County.

Key observations

Largest age group (population): Male # 20-24 years (5,657) | Female # 0-4 years (3,325). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Christian County population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Christian County is shown in the following column.
• Population (Female): The female population in the Christian County is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Christian County for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Christian County Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Christian County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Christian County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 51.11% of total population being female. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Christian County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Christian County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Christian County Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Christian County by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Christian County across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 52.55% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Christian County is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Christian County total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Christian County Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

This list ranks the 18 cities in the Christian County, IL by Multi-Racial Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Multi-Racial Black Population: This column displays the rank of cities in the Christian County, IL by their Multi-Racial Black or African American population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Multi-Racial Black Population: The Multi-Racial Black population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Multi-Racial Black. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Christian County Multi-Racial Black Population: This tells us how much of the entire Christian County, IL Multi-Racial Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.