100+ datasets found
  1. Disability prevalence rates in MENA by country 2017

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Disability prevalence rates in MENA by country 2017 [Dataset]. https://www.statista.com/statistics/914966/mena-disability-prevalence-rates-by-country/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    MENA
    Description

    This statistic describes the disability prevalence rates across the Middle East and North Africa in 2017, by country. As of 2017, the disability prevalence rate in Morocco was about **** percent compared to *** percent in Qatar.

  2. Annual Statistical Report on the Social Security Disability Insurance...

    • s.cnmilf.com
    • catalog.data.gov
    Updated Feb 1, 2023
    + more versions
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    Social Security Administration (2023). Annual Statistical Report on the Social Security Disability Insurance Program - 2017 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/annual-statistical-report-on-the-social-security-disability-insurance-program-2017
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    Dataset updated
    Feb 1, 2023
    Dataset provided by
    Social Security Administrationhttp://ssa.gov/
    Description

    This annual report provides program and demographic information on the people who receive Social Security Disability Insurance Program benefits. This edition presents a series of detailed tables on the three categories of beneficiaries: disabled workers, disabled widowers, and disabled adult children. Numbers presented in these tables may differ slightly from other published statistics because all tables, except those using data from the Survey of Income and Program Participation, are based on 100 percent data files. Report for 2017.

  3. d

    Disability - ACS 2017-2021 - Tempe Tracts

    • catalog.data.gov
    • datasets.ai
    • +9more
    Updated Sep 20, 2024
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    City of Tempe (2024). Disability - ACS 2017-2021 - Tempe Tracts [Dataset]. https://catalog.data.gov/dataset/disability-acs-2017-2021-tempe-tracts-daad6
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    Dataset updated
    Sep 20, 2024
    Dataset provided by
    City of Tempe
    Description

    This layer shows six different types of disability. Data is from US Census American Community Survey (ACS) 5-year estimates.This layer is symbolized to show the percent of population with a disability. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). To view only the census tracts that are predominantly in Tempe, add the expression City is Tempe in the map filter settings.Layer includes percent of population with a disability categorized as:an independent living difficultya hearing difficultyan ambulatory difficultya vision difficultya cognitive difficultya selfcare difficultyA ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2017-2021ACS Table(s): S1810 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data table downloaded and joined with Census Tract boundaries that are within or adjacent to the City of Tempe boundaryDate of Census update: December 8, 2022National Figures: data.census.gov

  4. Prevalence of disability in Canada in 2017 and 2022, by age

    • statista.com
    Updated May 29, 2024
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    Statista (2024). Prevalence of disability in Canada in 2017 and 2022, by age [Dataset]. https://www.statista.com/statistics/1469601/disability-prevalence-in-canada-by-age/
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    Dataset updated
    May 29, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Canada
    Description

    In 2022, some 27 percent of Canadians aged 15 years and over, equivalent to roughly 8 million people, had one or more disabilities that limited them in their daily activities. This includes various types of disabilities such as pain-related, mental health-related, hearing, etc. The prevalence of disability has increased in Canada compared to 2017, when the disability rate was 22.3 percent. While seniors were more likely to have a disability compared to youths, the rate of disability among youths increased the most in the five-year period shown. This statistic shows the percentage of people in Canada with a disability in 2017 and 2022, by age.

  5. O

    2017 San Diego County Demographics - Percent of the Population with a...

    • data.sandiegocounty.gov
    application/rdfxml +5
    Updated Feb 26, 2020
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    County of San Diego (2020). 2017 San Diego County Demographics - Percent of the Population with a Disability by Age Group [Dataset]. https://data.sandiegocounty.gov/Demographics/2017-San-Diego-County-Demographics-Percent-of-the-/nj44-amv2
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    csv, json, tsv, application/rssxml, application/rdfxml, xmlAvailable download formats
    Dataset updated
    Feb 26, 2020
    Dataset authored and provided by
    County of San Diego
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    San Diego County
    Description

    This indicator provides number and percentage of persons with a disability (one or more) within each age group. Disability status is determined for the civilian non-institutionalized population who responded to questions regarding six types of difficulty and may vary by age. For children under 5 years old, hearing and vision difficulty are used to determine disability status. For children between the ages of 5 and 14, disability status is determined from hearing, vision, cognitive, ambulatory, and self-care difficulties. For people aged 15 years and older, they are considered to have a disability if they have difficulty with any one of the six difficulty types. *Refers to the percent of those with a disability within the specific age group.

    Source: U.S. Census Bureau; 2013-2017 American Community Survey 5-Year Estimates, Table S1810.

  6. P

    Population with Disability - 2017

    • data.pompanobeachfl.gov
    Updated May 20, 2020
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    External Datasets (2020). Population with Disability - 2017 [Dataset]. https://data.pompanobeachfl.gov/dataset/population-with-disability-2017
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    arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    May 20, 2020
    Dataset provided by
    RBENSADOUN_BCGIS
    Authors
    External Datasets
    Description

    The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

    Source: U.S. Census Bureau, Table S1810 DISABILITY CHARACTERISTICS, 2013 – 2017 ACS 5-Year Estimates

    Effective Date: December 2018

    Last Update: December 2019

    Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.


  7. Levels of access to care Americans experience by disability status 2017-2019...

    • statista.com
    Updated Jul 8, 2025
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    Statista (2025). Levels of access to care Americans experience by disability status 2017-2019 [Dataset]. https://www.statista.com/statistics/1350974/levels-of-access-to-care-americans-experience-by-disability/
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    Dataset updated
    Jul 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    According to various measures of access to care, Americans experienced different levels of access to care depending on their disability status. From 2017 to 2019, disabled individuals experienced better access to care than individuals with no disabilities for roughly ** percent of measures. However, disabled individuals faced worse access to care for the same share of measures.

  8. P

    2017 Population with Disability

    • data.pompanobeachfl.gov
    Updated May 20, 2020
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    External Datasets (2020). 2017 Population with Disability [Dataset]. https://data.pompanobeachfl.gov/dataset/2017-population-with-disability
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    html, geojson, arcgis geoservices rest api, zip, kml, csvAvailable download formats
    Dataset updated
    May 20, 2020
    Dataset provided by
    RBENSADOUN_BCGIS
    Authors
    External Datasets
    Description

    The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

    Source: U.S. Census Bureau, Table S1810 DISABILITY CHARACTERISTICS, 2013 – 2017 ACS 5-Year Estimates

    Effective Date: December 2018

    Last Update: December 2019

    Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.


  9. 2017 Types of Pending Disability Cases, 2nd Quarter

    • catalog.data.gov
    Updated May 5, 2022
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    Social Security Administration (2022). 2017 Types of Pending Disability Cases, 2nd Quarter [Dataset]. https://catalog.data.gov/dataset/2017-types-of-pending-disability-cases-quarter-2nd
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    Dataset updated
    May 5, 2022
    Dataset provided by
    Social Security Administrationhttp://ssa.gov/
    Description

    This file contains the number of pending disability cases by types from Social Security Administration nationally for the 2nd quarter of FY 2017.

  10. d

    Learning Disability Services Monthly Statistics - England Commissioner...

    • digital.nhs.uk
    csv, pdf, xls, xlsx
    Updated Jan 30, 2018
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    (2018). Learning Disability Services Monthly Statistics - England Commissioner Census (Assuring Transformation) - December 2017, Provisional Statistics [Dataset]. https://digital.nhs.uk/data-and-information/publications/statistical/learning-disability-services-statistics
    Explore at:
    pdf(651.7 kB), pdf(1.4 MB), xls(586.8 kB), csv(16.2 kB), pdf(224.3 kB), xlsx(79.8 kB)Available download formats
    Dataset updated
    Jan 30, 2018
    License

    https://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions

    Time period covered
    Mar 1, 2015 - Dec 31, 2017
    Area covered
    England
    Description

    This statistical release published by NHS Digital makes available the most recent data relating to patients with learning disabilities and/or autistic spectrum disorder receiving inpatient care commissioned by the NHS in England. The release comprises: •A report which presents England level analysis of key measures. •A monthly CSV file which presents key measures at England level. •A metadata file to accompany the CSV file, which provides contextual information for each measure. •An excel reference data tables showing data as reported and total patient counts retrospectively updated from March 2015 onwards. •An easy read version of the report highlighting key findings in an easy-to-understand way

  11. HBAI, 1994/95 to 2016/17: disability data tables

    • gov.uk
    Updated Mar 22, 2018
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    Department for Work and Pensions (2018). HBAI, 1994/95 to 2016/17: disability data tables [Dataset]. https://www.gov.uk/government/statistics/hbai-199495-to-201617-disability-data-tables
    Explore at:
    Dataset updated
    Mar 22, 2018
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Work and Pensions
    Description

    The HBAI report presents information on living standards in the United Kingdom year-on-year from 1994/1995 to 2016/2017.

    These additional data tables include the following information.

    Charts

    This shows the distribution of household incomes for individuals in families where someone is disabled compared to all individuals.

    Time series

    This includes the proportions of children or people on low incomes or children in material deprivation by disability, if a range of disability-related benefits are excluded from income.

    Further disability time series are available in the HBAI summary spreadsheets.

    Additional data tables

    The following additional data tables are also available:

  12. 2017 American Community Survey: C18108 | AGE BY NUMBER OF DISABILITIES (ACS...

    • data.census.gov
    + more versions
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    ACS, 2017 American Community Survey: C18108 | AGE BY NUMBER OF DISABILITIES (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5Y2017.C18108
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available...Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2013-2017 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the .Evaluation Report Covering Disability....Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .Accuracy of the Data..). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates

  13. 2017 American Community Survey: K201803 | TYPES OF DISABILITIES (ACS 1-Year...

    • data.census.gov
    Updated Apr 1, 2018
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    ACS (2018). 2017 American Community Survey: K201803 | TYPES OF DISABILITIES (ACS 1-Year Supplemental Estimates) [Dataset]. https://data.census.gov/table/ACSSE2017.K201803
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    Dataset updated
    Apr 1, 2018
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2017 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2017 American Community Survey 1-Year Estimates

  14. u

    Infographic: Developmental Disabilities or Disorders in Canada - Highlights...

    • data.urbandatacentre.ca
    • beta.data.urbandatacentre.ca
    Updated Oct 1, 2024
    + more versions
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    (2024). Infographic: Developmental Disabilities or Disorders in Canada - Highlights from the 2017 Canadian Survey on Disability - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-4036ebe9-3897-4598-a908-29dbc5cd2bff
    Explore at:
    Dataset updated
    Oct 1, 2024
    License

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

    Area covered
    Canada
    Description

    This infographic uses data from the 2017 Canadian Survey on Disability (CSD), a national survey of Canadians aged 15+ years living in private dwellings whose daily activities are limited due to a long-term condition or health related problem, to profile individuals with a diagnosed developmental disability or disorder.

  15. Health and Care of People with Learning Disabilities: 2016 to 2017

    • gov.uk
    Updated Dec 12, 2017
    + more versions
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    NHS Digital (2017). Health and Care of People with Learning Disabilities: 2016 to 2017 [Dataset]. https://www.gov.uk/government/statistics/health-and-care-of-people-with-learning-disabilities-2016-to-2017
    Explore at:
    Dataset updated
    Dec 12, 2017
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    NHS Digital
    Description

    These are aggregated data on key health issues for people who are recorded by their GP as having a learning disability, and comparative data about a control group who are not recorded by their GP as having a learning disability.

  16. Persons with and without disabilities aged 15 years and over, census...

    • www150.statcan.gc.ca
    • open.canada.ca
    Updated Mar 24, 2025
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    Government of Canada, Statistics Canada (2025). Persons with and without disabilities aged 15 years and over, census metropolitan areas [Dataset]. http://doi.org/10.25318/1310075001-eng
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    Dataset updated
    Mar 24, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Differences in the number and proportion of persons with and without disabilities, aged 15 years and over, by census metropolitan areas.

  17. a

    Disability (by Strong, Prosperous, And Resilient Communities Challenge) 2017...

    • opendata.atlantaregional.com
    Updated Jun 24, 2019
    + more versions
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    Georgia Association of Regional Commissions (2019). Disability (by Strong, Prosperous, And Resilient Communities Challenge) 2017 [Dataset]. https://opendata.atlantaregional.com/datasets/disability-by-strong-prosperous-and-resilient-communities-challenge-2017/api
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    Dataset updated
    Jun 24, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show counts and percentages of the civilian noninstitutionalized population with disabilities by age group by Strong, Prosperous, And Resilient Communities Challenge in the Atlanta region.

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Naming conventions:

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    Suffixes:

    None

    Change over two periods

    _e

    Estimate from most recent ACS

    _m

    Margin of Error from most recent ACS

    _00

    Decennial 2000

    Attributes:

    SumLevel

    Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

    GEOID

    Census tract Federal Information Processing Series (FIPS) code

    NAME

    Name of geographic unit

    Planning_Region

    Planning region designation for ARC purposes

    Acres

    Total area within the tract (in acres)

    SqMi

    Total area within the tract (in square miles)

    County

    County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

    CountyName

    County Name

    CivNonInstPopTotal_e

    # Civilian non-institutionalized population, 2017

    CivNonInstPopTotal_m

    # Civilian non-institutionalized population, 2017 (MOE)

    WithDisabilityTotal_e

    # Civilian non-institutionalized population with a disability, 2017

    WithDisabilityTotal_m

    # Civilian non-institutionalized population with a disability, 2017 (MOE)

    pWithDisabilityTotal_e

    % Civilian non-institutionalized population with a disability, 2017

    pWithDisabilityTotal_m

    % Civilian non-institutionalized population with a disability, 2017 (MOE)

    CivNonInstPopU18_e

    # Civilian non-institutionalized population under age 18, 2017

    CivNonInstPopU18_m

    # Civilian non-institutionalized population under age 18, 2017 (MOE)

    WithDisabilityU18_e

    # Civilian non-institutionalized population under age 18 with a disability, 2017

    WithDisabilityU18_m

    # Civilian non-institutionalized population under age 18 with a disability, 2017 (MOE)

    pWithDisabilityU18_e

    % Civilian non-institutionalized population under age 18 with a disability, 2017

    pWithDisabilityU18_m

    % Civilian non-institutionalized population under age 18 with a disability, 2017 (MOE)

    CivNonInstPop1864_e

    # Civilian non-institutionalized population ages 18-64, 2017

    CivNonInstPop1864_m

    # Civilian non-institutionalized population ages 18-64, 2017 (MOE)

    WithDisability1864_e

    # Civilian non-institutionalized population ages 18-64 with a disability, 2017

    WithDisability1864_m

    # Civilian non-institutionalized population ages 18-64 with a disability, 2017 (MOE)

    pWithDisability1864_e

    % Civilian non-institutionalized population ages 18-64 with a disability, 2017

    pWithDisability1864_m

    % Civilian non-institutionalized population ages 18-64 with a disability, 2017 (MOE)

    CivNonInstPop65P_e

    # Civilian non-institutionalized population ages 65 and over, 2017

    CivNonInstPop65P_m

    # Civilian non-institutionalized population ages 65 and over, 2017 (MOE)

    WithDisability65P_e

    # Civilian non-institutionalized population ages 65 and over with a disability, 2017

    WithDisability65P_m

    # Civilian non-institutionalized population ages 65 and over with a disability, 2017 (MOE)

    pWithDisability65P_e

    % Civilian non-institutionalized population ages 65 and over with a disability, 2017

    pWithDisability65P_m

    % Civilian non-institutionalized population ages 65 and over with a disability, 2017 (MOE)

    last_edited_date

    Last date the feature was edited by ARC

    Source: U.S. Census Bureau, Atlanta Regional Commission

    Date: 2013-2017

    For additional information, please visit the Census ACS website.

  18. Application Outcomes for Disability Benefits, 2017

    • catalog.data.gov
    Updated Jul 21, 2021
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    Railroad Retirement Board (2021). Application Outcomes for Disability Benefits, 2017 [Dataset]. https://catalog.data.gov/dataset/application-outcomes-for-disability-benefits-2017
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    Dataset updated
    Jul 21, 2021
    Dataset provided by
    Railroad Retirement Board
    Description

    Data on the disability application outcomes for railroad employees and the survivors of deceased railroad employees.

  19. a

    Disability Status of the Civilian Noninstitutionalized Population 2017-2021...

    • mce-data-uscensus.hub.arcgis.com
    • covid19-uscensus.hub.arcgis.com
    Updated Mar 24, 2023
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    US Census Bureau (2023). Disability Status of the Civilian Noninstitutionalized Population 2017-2021 - STATES [Dataset]. https://mce-data-uscensus.hub.arcgis.com/datasets/disability-status-of-the-civilian-noninstitutionalized-population-2017-2021-states
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    Dataset updated
    Mar 24, 2023
    Dataset authored and provided by
    US Census Bureau
    Area covered
    Description

    This layer shows Disability Status of the Civilian Noninstitutionalized Population. This is shown by state and county boundaries. This service contains the 2017-2021 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show Total Civilian Noninstitutionalized Population - with a disability 65 and over. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2017-2021ACS Table(s): DP02, S2201, S1810Data downloaded from: Census Bureau's API for American Community Survey Date of API call: February 16, 2023National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

  20. 2017 American Community Survey: C18120 | EMPLOYMENT STATUS BY DISABILITY...

    • data.census.gov
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    ACS, 2017 American Community Survey: C18120 | EMPLOYMENT STATUS BY DISABILITY STATUS (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5Y2017.C18120
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Description

    Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution..An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution..An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An "(X)" means that the estimate is not applicable or not available...Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2013-2017 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the .Evaluation Report Covering Disability....Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .Accuracy of the Data..). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2013-2017 American Community Survey 5-Year Estimates

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Statista (2025). Disability prevalence rates in MENA by country 2017 [Dataset]. https://www.statista.com/statistics/914966/mena-disability-prevalence-rates-by-country/
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Disability prevalence rates in MENA by country 2017

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Dataset updated
Jul 9, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2017
Area covered
MENA
Description

This statistic describes the disability prevalence rates across the Middle East and North Africa in 2017, by country. As of 2017, the disability prevalence rate in Morocco was about **** percent compared to *** percent in Qatar.

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