100+ datasets found
  1. Vintage 2018 Population Estimates: Demographic Characteristics Estimates by...

    • catalog.data.gov
    • s.cnmilf.com
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Vintage 2018 Population Estimates: Demographic Characteristics Estimates by Age Groups [Dataset]. https://catalog.data.gov/dataset/vintage-2018-population-estimates-demographic-characteristics-estimates-by-age-groups
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Annual Resident Population Estimates by Age Group, Sex, Race, and Hispanic Origin: April 1, 2010 to July 1, 2018 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through June. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of 'Some Other Race' from the 2010 Census are modified. This results in differences between the population for specific race categories shown for the 2010 Census population in this file versus those in the original 2010 Census data. For more information, see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/modified-race-summary-file-method/mrsf2010.pdf. // The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2017) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.

  2. f

    Socio-demographic characteristics of people interviewed in the population.

    • datasetcatalog.nlm.nih.gov
    Updated Feb 25, 2025
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    Le Hesran, Jean-Yves; Atchadé, Aurore; Alfa, Daleb Abdoulaye; Yovo, Emmanuel; Hounsa, Sandrine; Massougbodji, Achille; Agossou, Anani; Fiogbé, Marc; Boko, Inès; Cottrell, Gilles (2025). Socio-demographic characteristics of people interviewed in the population. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001328706
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    Dataset updated
    Feb 25, 2025
    Authors
    Le Hesran, Jean-Yves; Atchadé, Aurore; Alfa, Daleb Abdoulaye; Yovo, Emmanuel; Hounsa, Sandrine; Massougbodji, Achille; Agossou, Anani; Fiogbé, Marc; Boko, Inès; Cottrell, Gilles
    Description

    Socio-demographic characteristics of people interviewed in the population.

  3. d

    Gridded Population of the World, Version 4 (GPWv4): Basic Demographic...

    • catalog.data.gov
    • earthdata.nasa.gov
    • +3more
    Updated Aug 23, 2025
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    SEDAC (2025). Gridded Population of the World, Version 4 (GPWv4): Basic Demographic Characteristics, Revision 11 [Dataset]. https://catalog.data.gov/dataset/gridded-population-of-the-world-version-4-gpwv4-basic-demographic-characteristics-revision
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    Dataset updated
    Aug 23, 2025
    Dataset provided by
    SEDAC
    Area covered
    World
    Description

    The Gridded Population of the World, Version 4 (GPWv4): Basic Demographic Characteristics, Revision 11 consists of estimates of human population by age and sex as counts (number of persons per pixel) and densities (number of persons per square kilometer), consistent with national censuses and population registers, for the year 2010. To estimate the male and female populations by age in 2010, the proportions of males and females in each 5-year age group from ages 0-4 to ages 85+ for the given census year were calculated. These proportions were then applied to the 2010 estimates of the total population to obtain 2010 estimates of male and female populations by age. In some cases, the spatial resolution of the age and sex proportions was coarser than the resolution of the total population estimates to which they were applied. The population density rasters were created by dividing the population count rasters by the land area raster. The data files were produced as global rasters at 30 arc-second (~1 km at the equator) resolution. To enable faster global processing, and in support of research commUnities, the 30 arc-second data were aggregated to 2.5 arc-minute, 15 arc-minute, 30 arc-minute and 1 degree resolutions.

  4. f

    Demographic characteristics of study participants–individuals and...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Feb 15, 2019
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    Dunn, Julia C.; Lwin, Aye Moe Moe; Maung, Nay Soe; Anderson, Roy M.; Bettis, Alison A.; Wyine, Nay Yee; Tun, Aung (2019). Demographic characteristics of study participants–individuals and households. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000108368
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    Dataset updated
    Feb 15, 2019
    Authors
    Dunn, Julia C.; Lwin, Aye Moe Moe; Maung, Nay Soe; Anderson, Roy M.; Bettis, Alison A.; Wyine, Nay Yee; Tun, Aung
    Description

    Demographic characteristics of study participants–individuals and households.

  5. Vintage 2016 Population Estimates: Demographic Characteristics Estimates by...

    • catalog.data.gov
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Vintage 2016 Population Estimates: Demographic Characteristics Estimates by Age Groups [Dataset]. https://catalog.data.gov/dataset/vintage-2016-population-estimates-demographic-characteristics-estimates-by-age-groups
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Annual Resident Population Estimates by Age Group, Sex, Race, and Hispanic Origin: April 1, 2010 to July 1, 2016 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through June. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of 'Some Other Race' from the 2010 Census are modified. This results in differences between the population for specific race categories shown for the 2010 Census population in this file versus those in the original 2010 Census data. For more information, see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/modified-race-summary-file-method/mrsf2010.pdf. // The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2015) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.

  6. Select socio-demographic characteristics of people who overdosed in Simcoe...

    • ouvert.canada.ca
    • www150.statcan.gc.ca
    • +1more
    csv, html, xml
    Updated Jan 17, 2023
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    Statistics Canada (2023). Select socio-demographic characteristics of people who overdosed in Simcoe Muskoka between 2018 and 2019 [Dataset]. https://ouvert.canada.ca/data/dataset/eb6d54f0-023f-4926-9a7a-b9b92b46d9d4
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    xml, csv, htmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    Characteristics from the 2016 Census of Population related to marital status, living arrangements, education, place of birth, housing, and health limitations among people who overdosed in Simcoe Muskoka between 2018 and 2019.

  7. f

    Demographic characteristics of the population studied.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Sep 28, 2016
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    Kamath, Asha; Kaur, Simar; Pandey, Deeksha (2016). Demographic characteristics of the population studied. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001569697
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    Dataset updated
    Sep 28, 2016
    Authors
    Kamath, Asha; Kaur, Simar; Pandey, Deeksha
    Description

    Demographic characteristics of the population studied.

  8. Year 2021: Summary of People data by gender, demographic characteristics and...

    • ine.es
    csv, html, json +4
    Updated Jun 2, 2025
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    INE - Instituto Nacional de Estadística (2025). Year 2021: Summary of People data by gender, demographic characteristics and type of ICT use [Dataset]. https://www.ine.es/jaxi/Tabla.htm?tpx=50895&L=1
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    json, text/pc-axis, csv, txt, html, xls, xlsxAvailable download formats
    Dataset updated
    Jun 2, 2025
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Variables measured
    Sex, Type of ICT use, Demographic characteristics
    Description

    Survey on Equipment and Use of Information and Communication Technologies in Households: Year 2021: Summary of People data by gender, demographic characteristics and type of ICT use. National.

  9. f

    Demographic characteristics of the population.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 2, 2023
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    Teresa Villarreal-Molina; Carlos Posadas-Romero; Sandra Romero-Hidalgo; Erika Antúnez-Argüelles; Araceli Bautista-Grande; Gilberto Vargas-Alarcón; Eric Kimura-Hayama; Samuel Canizales-Quinteros; Juan Gabriel Juárez-Rojas; Rosalinda Posadas-Sánchez; Guillermo Cardoso-Saldaña; Aída Medina-Urrutia; María del Carmen González-Salazar; Rocío Martínez-Alvarado; Esteban Jorge-Galarza; Alessandra Carnevale (2023). Demographic characteristics of the population. [Dataset]. http://doi.org/10.1371/journal.pone.0049285.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Teresa Villarreal-Molina; Carlos Posadas-Romero; Sandra Romero-Hidalgo; Erika Antúnez-Argüelles; Araceli Bautista-Grande; Gilberto Vargas-Alarcón; Eric Kimura-Hayama; Samuel Canizales-Quinteros; Juan Gabriel Juárez-Rojas; Rosalinda Posadas-Sánchez; Guillermo Cardoso-Saldaña; Aída Medina-Urrutia; María del Carmen González-Salazar; Rocío Martínez-Alvarado; Esteban Jorge-Galarza; Alessandra Carnevale
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data are expressed as means ± SD, log-transformed values were used for statistical analysis.*P values were estimated using ANOVA for continuous variables and Pearson’s Chisquare test for categorical values.CAD: coronary artery disease; SA: subclinical atherosclerosis.

  10. Year 2019: Summary of People data by gender, demographic characteristics and...

    • ine.es
    csv, html, json +4
    Updated May 27, 2025
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    INE - Instituto Nacional de Estadística (2025). Year 2019: Summary of People data by gender, demographic characteristics and type of ICT use [Dataset]. https://www.ine.es/jaxi/Tabla.htm?tpx=34947&L=1
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    txt, csv, html, xls, text/pc-axis, json, xlsxAvailable download formats
    Dataset updated
    May 27, 2025
    Dataset provided by
    National Statistics Institutehttp://www.ine.es/
    Authors
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Variables measured
    Sex, Type of ICT use, Demographic Characteristics
    Description

    Survey on Equipment and Use of Information and Communication Technologies in Households: Year 2019: Summary of People data by gender, demographic characteristics and type of ICT use. National.

  11. g

    Demographic Characteristics of the Population of Detroit, 1850-1880

    • datasearch.gesis.org
    • icpsr.umich.edu
    v1
    Updated Aug 5, 2015
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    Vinyard, Jo Ellen (2015). Demographic Characteristics of the Population of Detroit, 1850-1880 [Dataset]. http://doi.org/10.3886/ICPSR00031.v1
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    v1Available download formats
    Dataset updated
    Aug 5, 2015
    Dataset provided by
    da|ra (Registration agency for social science and economic data)
    Authors
    Vinyard, Jo Ellen
    Area covered
    Detroit
    Description

    This data collection provides information for native-born Americans, Irish Americans, and German Americans living in Detroit, Michigan, between 1850 and 1880. Demographic variables provide information on age, sex, occupation, marital status, marriage patterns, ethnic background, place of birth, and spouse's and parents' place of birth. Additional information is provided on family size, number of children of adults, number of individuals in the house beyond the immediate family, total number of individuals in the nuclear family, position of individuals within the family, number of children eligible to be in school, activities of school-age children, adult male skill level, literacy level, length of time the family had been in the United States, ownership and value of real estate, constitutional and legal status, and physical condition.

  12. l

    Census 2020 SRR and Demographic Characteristics

    • geohub.lacity.org
    • data.lacounty.gov
    • +2more
    Updated Dec 22, 2023
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    County of Los Angeles (2023). Census 2020 SRR and Demographic Characteristics [Dataset]. https://geohub.lacity.org/maps/lacounty::census-2020-srr-and-demographic-characteristics-1/about
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    Dataset updated
    Dec 22, 2023
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    For the past several censuses, the Census Bureau has invited people to self-respond before following up in-person using census takers. The 2010 Census invited people to self-respond predominately by returning paper questionnaires in the mail. The 2020 Census allows people to self-respond in three ways: online, by phone, or by mail.The 2020 Census self-response rates are self-response rates for current census geographies. These rates are the daily and cumulative self-response rates for all housing units that received invitations to self-respond to the 2020 Census. The 2020 Census self-response rates are available for states, counties, census tracts, congressional districts, towns and townships, consolidated cities, incorporated places, tribal areas, and tribal census tracts.The Self-Response Rate of Los Angeles County is 65.1% for 2020 Census, which is slightly lower than 69.6% of California State rate.More information about these data is available in the Self-Response Rates Map Data and Technical Documentation document associated with the 2020 Self-Response Rates Map or review FAQs.Animated Self-Response Rate 2010 vs 2020 is available at ESRI site SRR Animated Maps and can explore Census 2020 SRR data at ESRI Demographic site Census 2020 SSR Data.Following Demographic Characteristics are included in this data and web maps to visualize their relationships with Census Self-Response Rate (SRR).1. Population Density: 2020 Population per square mile,2. Poverty Rate: Percentage of population under 100% FPL,3. Median Household income: Based on countywide median HH income of $71,538.4. Highschool Education Attainment: Percentage of 18 years and older population without high school graduation.5. English Speaking Ability: Percentage of 18 years and older population with less or none English speaking ability. 6. Household without Internet Access: Percentage of HH without internet access.7. Non-Hispanic White Population: Percentage of Non-Hispanic White population.8. Non-Hispanic African-American Population: Percentage of Non-Hispanic African-American population.9. Non-Hispanic Asian Population: Percentage of Non-Hispanic Asian population.10. Hispanic Population: Percentage of Hispanic population.

  13. Vintage 2017 Population Estimates: Demographic Characteristics Estimates by...

    • catalog.data.gov
    Updated Jul 19, 2023
    + more versions
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    U.S. Census Bureau (2023). Vintage 2017 Population Estimates: Demographic Characteristics Estimates by Age Groups [Dataset]. https://catalog.data.gov/dataset/vintage-2017-population-estimates-demographic-characteristics-estimates-by-age-groups
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Annual Resident Population Estimates by Age Group, Sex, Race, and Hispanic Origin: April 1, 2010 to July 1, 2017 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through June. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of 'Some Other Race' from the 2010 Census are modified. This results in differences between the population for specific race categories shown for the 2010 Census population in this file versus those in the original 2010 Census data. For more information, see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/modified-race-summary-file-method/mrsf2010.pdf. // The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2017) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.

  14. Vintage 2015 Population Estimates: Demographic Characteristics Estimates by...

    • catalog.data.gov
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Vintage 2015 Population Estimates: Demographic Characteristics Estimates by Age Groups [Dataset]. https://catalog.data.gov/dataset/vintage-2015-population-estimates-demographic-characteristics-estimates-by-age-groups
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Annual Resident Population Estimates by Age Group, Sex, Race, and Hispanic Origin: April 1, 2010 to July 1, 2015 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through June. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of 'Some Other Race' from the 2010 Census are modified. This results in differences between the population for specific race categories shown for the 2010 Census population in this file versus those in the original 2010 Census data. For more information, see https://www.census.gov/popest/data/historical/files/MRSF-01-US1.pdf. // The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/popest/methodology/index.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2015) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/popest/index.html.

  15. f

    Demographic characteristics of the population study.

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Catarina Mateus; Raquel Lemos; Maria Fátima Silva; Aldina Reis; Pedro Fonseca; Bárbara Oliveiros; Miguel Castelo-Branco (2023). Demographic characteristics of the population study. [Dataset]. http://doi.org/10.1371/journal.pone.0055348.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Catarina Mateus; Raquel Lemos; Maria Fátima Silva; Aldina Reis; Pedro Fonseca; Bárbara Oliveiros; Miguel Castelo-Branco
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Note. FDT = Frequency Doubling Technology; LocSp = Local Speed Discrimination; 3D SFM = 3D Structure from Motion; CCT = Cambridge Color Test; ISF = Intermediate Spatial Frequency Perimetry; SEM = standard error of the mean.For each participant, only the dominant eye was performed, except for SFM that was tested binocularly.

  16. Decennial Census: Summary File 2 Demographic Profile

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • s.cnmilf.com
    • +1more
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Decennial Census: Summary File 2 Demographic Profile [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/decennial-census-summary-file-2-demographic-profile
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    Summary File 2 (SF 2) contains the data compiled from the questions asked of all people and about every housing unit. Summary File 2 (SF 2) contains the data compiled from the questions asked of all people and about every housing unit. SF 2 includes population characteristics, such as sex, age, average household size, household type, and relationship to householder such as nonrelative or child. The file includes housing characteristics, such as tenure (whether a housing unit is owner-occupied or renter-occupied), age of householder, and household size for occupied housing units. Selected aggregates and medians also are provided

  17. f

    Is Demography Destiny? Application of Machine Learning Techniques to...

    • plos.figshare.com
    • figshare.com
    docx
    Updated Jun 3, 2023
    + more versions
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    Wei Luo; Thin Nguyen; Melanie Nichols; Truyen Tran; Santu Rana; Sunil Gupta; Dinh Phung; Svetha Venkatesh; Steve Allender (2023). Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset [Dataset]. http://doi.org/10.1371/journal.pone.0125602
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    docxAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wei Luo; Thin Nguyen; Melanie Nichols; Truyen Tran; Santu Rana; Sunil Gupta; Dinh Phung; Svetha Venkatesh; Steve Allender
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

  18. f

    Data_Sheet_2_One Social Media Company to Rule Them All: Associations Between...

    • frontiersin.figshare.com
    xlsx
    Updated Jun 3, 2023
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    Davide Marengo; Cornelia Sindermann; Jon D. Elhai; Christian Montag (2023). Data_Sheet_2_One Social Media Company to Rule Them All: Associations Between Use of Facebook-Owned Social Media Platforms, Sociodemographic Characteristics, and the Big Five Personality Traits.xlsx [Dataset]. http://doi.org/10.3389/fpsyg.2020.00936.s002
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    xlsxAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    Frontiers
    Authors
    Davide Marengo; Cornelia Sindermann; Jon D. Elhai; Christian Montag
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Currently, 2.7 billion people use at least one of the Facebook-owned social media platforms – Facebook, WhatsApp, and Instagram. Previous research investigating individual differences between users and non-users of these platforms has typically focused on one platform. However, individuals typically use a combination of Facebook-owned platforms. Therefore, we aim (1) to identify the relative prevalence of different patterns of social media use, and (2) to evaluate potential between-group differences in the distributions of age, gender, education, and Big Five personality traits. Data collection was performed using a cross-sectional design. Specifically, we administered a survey assessing participants’ demographic variables, current use of Facebook-owned platforms, and Big Five personality traits. In N = 3003 participants from the general population (60.67% females; mean age = 35.53 years, SD = 13.53), WhatsApp emerged as the most widely used application in the sample, and hence, has the strongest reach. A pattern consisting of a combined use of WhatsApp and Instagram appeared to be most prevalent among the youngest participants. Further, individuals using at least one social media platform were generally younger, more often female, and more extraverted than non-users. Small differences in Conscientiousness and Neuroticism also emerged across groups reporting different combinations of social media use. Interestingly, when examined as control variables, we found demographic characteristics partially accounted for differences in broad personality factors and facets across different patterns of social media use. Our findings are relevant to researchers carrying out their studies via social media platforms, as sample characteristics appear to be different depending on the platform used.

  19. f

    Demographic characteristics of the study individuals.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Aug 23, 2019
    + more versions
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    Hoshiga, Masaaki; Ito, Takahide; Ukimura, Akira; Kanzaki, Yumiko; Akamatsu, Kanako; Fujita, Shu-ichi (2019). Demographic characteristics of the study individuals. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000148753
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    Dataset updated
    Aug 23, 2019
    Authors
    Hoshiga, Masaaki; Ito, Takahide; Ukimura, Akira; Kanzaki, Yumiko; Akamatsu, Kanako; Fujita, Shu-ichi
    Description

    Demographic characteristics of the study individuals.

  20. American Community Survey Artist Extracts 5-year Data

    • icpsr.umich.edu
    Updated May 16, 2025
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    United States. Bureau of the Census (2025). American Community Survey Artist Extracts 5-year Data [Dataset]. https://www.icpsr.umich.edu/web/NADAC/studies/39413
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    Dataset updated
    May 16, 2025
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of the Census
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/39413/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/39413/terms

    Description

    The American Community Survey (ACS), conducted by the U.S. Census Bureau, replaced the long form of the decennial census in 2000. The ACS allows researchers, policy makers, and others access to timely information about the U.S. population to make decisions about infrastructure and distribution of federal funds. The monthly survey is sent to a sample of approximately 3.5 million U.S. addresses, including the District of Columbia and Puerto Rico. The ACS includes questions on topics not included in the decennial census, such as those about occupations and employment, education, and key areas of infrastructure like internet access and transportation. When studying large geographic areas, such as states, researchers can use a single year's worth of ACS data to create population-level estimates. However, the study of smaller groups of the population, such as those employed in arts-related fields, requires additional data for more accurate estimation. Specifically, researchers often use 5-year increments of ACS data to draw conclusions about smaller geographies or slices of the population. Note, the Census Bureau produced 3-year estimates between 2005 and 2013 (resulting in seven files: 2005-2007, 2006-2008, 2007-2009, . . . 2011-2013), which remain available but no additional 3-year estimate files have been created. Individuals wishing to describe people working in occupations related to the arts or culture should plan to use at least five years' worth of data to generate precise estimates. When selecting data from the U.S. Census Bureau or IPUMS USA, users should select data collected over 60 months, such as 2020-2024. NADAC's Guide to Creating Artist Extracts and Special Tabulations of Artists from the American Community Survey provides information about the occupation codes used to identify artists.

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U.S. Census Bureau (2023). Vintage 2018 Population Estimates: Demographic Characteristics Estimates by Age Groups [Dataset]. https://catalog.data.gov/dataset/vintage-2018-population-estimates-demographic-characteristics-estimates-by-age-groups
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Vintage 2018 Population Estimates: Demographic Characteristics Estimates by Age Groups

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Dataset updated
Jul 19, 2023
Dataset provided by
United States Census Bureauhttp://census.gov/
Description

Annual Resident Population Estimates by Age Group, Sex, Race, and Hispanic Origin: April 1, 2010 to July 1, 2018 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through June. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of 'Some Other Race' from the 2010 Census are modified. This results in differences between the population for specific race categories shown for the 2010 Census population in this file versus those in the original 2010 Census data. For more information, see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/modified-race-summary-file-method/mrsf2010.pdf. // The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2017) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.

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