100+ datasets found
  1. US Census Bureau States And Counties Health Insurance Estimates

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
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    John Snow Labs (2021). US Census Bureau States And Counties Health Insurance Estimates [Dataset]. https://www.johnsnowlabs.com/marketplace/us-census-bureau-states-and-counties-health-insurance-estimates/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Time period covered
    2020
    Area covered
    United States
    Description

    This dataset contains estimates of health insured and uninsured population for 2020 at county and state level based on US Census Bureau program, The Small Area Health Insurance Estimates (SAHIE) program. For every state and county for each demographic group, defined by age, gender, race/ethnicity and income relative to poverty, the estimated number of persons insured and uninsured is given along with the margin of error.

  2. Time Series Small Area Health Insurance Estimates

    • catalog.data.gov
    Updated Sep 30, 2025
    + more versions
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    U.S. Census Bureau (2025). Time Series Small Area Health Insurance Estimates [Dataset]. https://catalog.data.gov/dataset/small-area-health-insurance-estimates-small-area-health-insurance-estimates
    Explore at:
    Dataset updated
    Sep 30, 2025
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The U.S. Census Bureau's Small Area Health Insurance Estimates program produces the only source of data for single-year estimates of health insurance coverage status for all counties in the U.S. by selected economic and demographic characteristics. This program is partially funded by the Centers for Disease Control and Prevention's (CDC) Division of Cancer Prevention and Control (DCPC). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the National Breast and Cervical Cancer Early Detection Program (NBCCEDP). For estimation, SAHIE uses statistical models that combine survey data from the American Community Survey (ACS) with administrative records data and Census 2020 data.

  3. Health Insurance Coverage 2018-2022 - STATES

    • covid19-uscensus.hub.arcgis.com
    • hub.arcgis.com
    • +2more
    Updated Feb 4, 2024
    + more versions
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    US Census Bureau (2024). Health Insurance Coverage 2018-2022 - STATES [Dataset]. https://covid19-uscensus.hub.arcgis.com/maps/91d772d271644a15b59a5c97ead2917a
    Explore at:
    Dataset updated
    Feb 4, 2024
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    US Census Bureau
    Area covered
    Description

    This layer shows Health Insurance Coverage. This is shown by state and county boundaries. This service contains the 2018-2022 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 Percent of Population with No Health Insurance Coverage. 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: 2018-2022ACS Table(s): B27010, DP03Data downloaded from: Census Bureau's API for American Community SurveyDate of API call: January 18, 2024National 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.

  4. F

    Health Insurance Coverage: Coverage Rate in the United States (DISCONTINUED)...

    • fred.stlouisfed.org
    json
    Updated Sep 17, 2013
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    (2013). Health Insurance Coverage: Coverage Rate in the United States (DISCONTINUED) [Dataset]. https://fred.stlouisfed.org/series/USHICCOVPCT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 17, 2013
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Health Insurance Coverage: Coverage Rate in the United States (DISCONTINUED) (USHICCOVPCT) from 1999 to 2012 about coverage rate, health, insurance, rate, and USA.

  5. p

    Uninsured Population Census Data CY 2009-2014 Human Services

    • data.pa.gov
    csv, xlsx, xml
    Updated Jul 25, 2018
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    Small Area Health Insurance Estimates Program, U.S. Census Bureau (2018). Uninsured Population Census Data CY 2009-2014 Human Services [Dataset]. https://data.pa.gov/w/s782-mpqp/33ch-zxdi?cur=NpQjDR1nV-g&from=root
    Explore at:
    csv, xml, xlsxAvailable download formats
    Dataset updated
    Jul 25, 2018
    Dataset authored and provided by
    Small Area Health Insurance Estimates Program, U.S. Census Bureau
    License

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

    Description

    This data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions

    The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties.

    For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64

    •3 sex categories: both sexes, male, and female

    •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold

    •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race).

    In addition, estimates for age category 0-18 by the income categories listed above are published.

    Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured.

    This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges.

    We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response.

    The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010

    Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.

  6. e

    ACS Health Insurance Coverage Variables - Centroids

    • coronavirus-resources.esri.com
    • covid-hub.gio.georgia.gov
    • +4more
    Updated Dec 7, 2018
    + more versions
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    Esri (2018). ACS Health Insurance Coverage Variables - Centroids [Dataset]. https://coronavirus-resources.esri.com/maps/7c69956008bb4019bbbe67ed9fb05dbb
    Explore at:
    Dataset updated
    Dec 7, 2018
    Dataset authored and provided by
    Esri
    Area covered
    Description

    This layer shows health insurance coverage by type and by age group. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released 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 the count and percent uninsured. 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: 2019-2023ACS Table(s): B27010 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National 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. For more information about ACS layers, visit the FAQ. 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:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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 RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).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 file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  7. F

    Health Insurance Coverage: Coverage Rate in the West Census Region...

    • fred.stlouisfed.org
    json
    Updated Sep 17, 2013
    + more versions
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    (2013). Health Insurance Coverage: Coverage Rate in the West Census Region (DISCONTINUED) [Dataset]. https://fred.stlouisfed.org/series/CWSTHICCOVPCT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 17, 2013
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Health Insurance Coverage: Coverage Rate in the West Census Region (DISCONTINUED) (CWSTHICCOVPCT) from 1999 to 2012 about coverage rate, West Census Region, health, insurance, rate, and USA.

  8. Data from: Health Insurance Coverage in the United States

    • kaggle.com
    zip
    Updated Dec 6, 2019
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    US Census Bureau (2019). Health Insurance Coverage in the United States [Dataset]. https://www.kaggle.com/census/health-insurance-coverage-in-the-united-states
    Explore at:
    zip(888 bytes)Available download formats
    Dataset updated
    Dec 6, 2019
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    US Census Bureau
    Area covered
    United States
    Description

    Content

    This dataset has no description from FRED.

    Context

    This is a dataset from the U.S. Census Bureau hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according the amount of data that is brought in. Explore the U.S. Census Bureau using Kaggle and all of the data sources available through the U.S. Census Bureau organization page!

    • Update Frequency: This dataset is updated daily.

    • Observation Start: 1999-01-01

    • Observation End : 2012-01-01

    Acknowledgements

    This dataset is maintained using FRED's API and Kaggle's API.

  9. a

    Health Insurance (census tract)

    • equity-lacounty.hub.arcgis.com
    • data.lacounty.gov
    • +3more
    Updated Sep 21, 2021
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    County of Los Angeles (2021). Health Insurance (census tract) [Dataset]. https://equity-lacounty.hub.arcgis.com/datasets/health-insurance-census-tract
    Explore at:
    Dataset updated
    Sep 21, 2021
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    For the original data source: https://data.census.gov/table/ACSST5Y2023.S2701. Layer published for the Equity Explorer, a web experience developed by the LA County CEO Anti-Racism, Diversity, and Inclusion (ARDI) initiative in collaboration with eGIS and ISD. Visit the Equity Explorer to explore health insurance status and other equity related datasets and indices, including the COVID Vulnerability and Recovery Index. Health insurance status for census tracts in LA County from the US Census American Communities Survey (ACS), 2023. Estimates are based on 2020 census tract boundaries, and tracts are joined to 2021 Supervisorial Districts, Service Planning Areas (SPA), and Countywide Statistical Areas (CSA). For more information about this dataset, please contact egis@isd.lacounty.gov.

  10. d

    HEALTH INSURANCE BY EMPLOYMENT STATUS (B27011)

    • catalog.data.gov
    Updated Jan 31, 2025
    + more versions
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    City of Seattle ArcGIS Online (2025). HEALTH INSURANCE BY EMPLOYMENT STATUS (B27011) [Dataset]. https://catalog.data.gov/dataset/health-insurance-by-employment-status-b27011
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    City of Seattle ArcGIS Online
    Description

    Table from the American Community Survey (ACS) B27011 health insurance coverage status and type by employment status. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2015 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2015, 2020, 2021, 2022, 2023ACS Table(s): B27011Data downloaded from: Census Bureau's Explore Census Data <div s

  11. Health Insurance and Socioeconomic Status by Census Tracts 2014-2018

    • johnsnowlabs.com
    csv
    Updated Jan 20, 2021
    + more versions
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    John Snow Labs (2021). Health Insurance and Socioeconomic Status by Census Tracts 2014-2018 [Dataset]. https://www.johnsnowlabs.com/marketplace/health-insurance-and-socioeconomic-status-by-census-tracts-2014-2018/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jan 20, 2021
    Dataset authored and provided by
    John Snow Labs
    Time period covered
    2014 - 2018
    Area covered
    US
    Description

    This dataset offers census tract level estimates for the number of uninsured noninstitutionalized civilians, number of persons below poverty line, unemployed population, number of persons with no high school diploma, which are socioeconomic characteristics with a negative impact on the access to healthcare services.

  12. ACS Health Insurance by Age by Race Variables - Boundaries

    • hub.arcgis.com
    • mapdirect-fdep.opendata.arcgis.com
    Updated Nov 17, 2020
    + more versions
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    Esri (2020). ACS Health Insurance by Age by Race Variables - Boundaries [Dataset]. https://hub.arcgis.com/maps/0bdb1479d3554ae59337a0eb47b17afb
    Explore at:
    Dataset updated
    Nov 17, 2020
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released 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. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black)This layer is symbolized to show the percent of population with no health insurance coverage. 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: 2019-2023ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National 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. For more information about ACS layers, visit the FAQ. 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:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. 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 RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).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 file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations: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.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.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  13. F

    Health Insurance Coverage: Coverage Rate in the Northeast Census Region...

    • fred.stlouisfed.org
    json
    Updated Sep 17, 2013
    + more versions
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    (2013). Health Insurance Coverage: Coverage Rate in the Northeast Census Region (DISCONTINUED) [Dataset]. https://fred.stlouisfed.org/series/CNERHICCOVPCT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 17, 2013
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Northeastern United States
    Description

    Graph and download economic data for Health Insurance Coverage: Coverage Rate in the Northeast Census Region (DISCONTINUED) (CNERHICCOVPCT) from 1999 to 2012 about coverage rate, Northeast Census Region, health, insurance, rate, and USA.

  14. 2019 American Community Survey: S2701 | SELECTED CHARACTERISTICS OF HEALTH...

    • data.census.gov
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    ACS, 2019 American Community Survey: S2701 | SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES (ACS 1-Year Estimates Subject Tables) [Dataset]. https://data.census.gov/cedsci/table?q=virginia%20uninsured&g=0400000US51&tid=ACSST1Y2019.S2701&hidePreview=true
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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
    2019
    Area covered
    United States
    Description

    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..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..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations 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 delineations due to differences in the effective dates of the geographic entities..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..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, or the margin of error associated with a median was larger than the median itself.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.

  15. 2017 American Community Survey: C27001H | HEALTH INSURANCE COVERAGE STATUS...

    • data.census.gov
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    ACS, 2017 American Community Survey: C27001H | HEALTH INSURANCE COVERAGE STATUS BY AGE (WHITE ALONE, NOT HISPANIC OR LATINO) (ACS 5-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT5Y2017.C27001H
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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..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled ."Health Insurance Table Updates".. for further details..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see .https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html.. for more details. The 2008 data table in American FactFinder does not incorporate these edits. Therefore, the estimates that appear in these tables are not comparable to the estimates in the 2009 and later tables. Select geographies of 2008 data comparable to the 2009 and later tables are available at .https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html... The health insurance coverage category names were modified in 2010. See .https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18.. for a list of the insurance type definitions..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

  16. z

    Health Insurance Coverage

    • zipatlas.com
    Updated Dec 18, 2023
    + more versions
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    Zip Atlas Inc (2023). Health Insurance Coverage [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
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    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    Health Insurance Coverage Report based on US Census and American Community Survey Data.

  17. a

    Health Insurance Coverage Ages 0 - 17 By Zipcode

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 9, 2018
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    Santa Clara County Public Health (2018). Health Insurance Coverage Ages 0 - 17 By Zipcode [Dataset]. https://hub.arcgis.com/datasets/c605b29814da4d06a48a527025c342aa
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    Dataset updated
    Feb 9, 2018
    Dataset authored and provided by
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Health insurance coverage among children ages 0-17, Santa Clara County, 2009-2013. U.S. Census Bureau; American Community Survey, 2009-13 American Community Survey 5-Years Estimates, Table B27001;http://factfinder2.census.gov; 19 October 2015.

  18. D

    Indicators of Health Insurance Coverage at the Time of Interview

    • data.cdc.gov
    • data.virginia.gov
    • +4more
    csv, xlsx, xml
    Updated Oct 4, 2024
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    NCHS/DHIS (2024). Indicators of Health Insurance Coverage at the Time of Interview [Dataset]. https://data.cdc.gov/w/jb9g-gnvr/tdwk-ruhb?cur=l9_88DmmwnF
    Explore at:
    csv, xml, xlsxAvailable download formats
    Dataset updated
    Oct 4, 2024
    Dataset authored and provided by
    NCHS/DHIS
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    The U.S. Census Bureau, in collaboration with five federal agencies, launched the Household Pulse Survey to produce data on the social and economic impacts of Covid-19 on American households. The Household Pulse Survey was designed to gauge the impact of the pandemic on employment status, consumer spending, food security, housing, education disruptions, and dimensions of physical and mental wellness.

    The survey was designed to meet the goal of accurate and timely weekly estimates. It was conducted by an internet questionnaire, with invitations to participate sent by email and text message. The sample frame is the Census Bureau Master Address File Data. Housing units linked to one or more email addresses or cell phone numbers were randomly selected to participate, and one respondent from each housing unit was selected to respond for him or herself. Estimates are weighted to adjust for nonresponse and to match Census Bureau estimates of the population by age, sex, race and ethnicity, and educational attainment. All estimates shown meet the NCHS Data Presentation Standards for Proportions.

  19. F

    Health Insurance Coverage: Coverage Rate in the Pacific Census Division...

    • fred.stlouisfed.org
    json
    Updated Sep 17, 2013
    + more versions
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    (2013). Health Insurance Coverage: Coverage Rate in the Pacific Census Division (DISCONTINUED) [Dataset]. https://fred.stlouisfed.org/series/CPACHICCOVPCT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 17, 2013
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Health Insurance Coverage: Coverage Rate in the Pacific Census Division (DISCONTINUED) (CPACHICCOVPCT) from 1999 to 2012 about Pacific Census Division, coverage rate, health, insurance, rate, and USA.

  20. Health Insurance (by Census Tract) 2019

    • hub.arcgis.com
    • opendata.atlantaregional.com
    Updated Feb 26, 2021
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    Georgia Association of Regional Commissions (2021). Health Insurance (by Census Tract) 2019 [Dataset]. https://hub.arcgis.com/maps/8de7f155971245bfaef85a64931bdf2a_134/about
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    Dataset updated
    Feb 26, 2021
    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 dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau.For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.Naming conventions:Prefixes: None Countp Percentr Ratem Mediana 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)s Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed Suffixes: _e19 Estimate from 2014-19 ACS_m19 Margin of Error from 2014-19 ACS_00_v19 Decennial 2000, re-estimated to 2019 geography_00_19 Change, 2000-19_e10_v19 2006-10 ACS, re-estimated to 2019 geography_m10_v19 Margin of Error from 2006-10 ACS, re-estimated to 2019 geography_e10_19 Change, 2010-19The 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 2015-2019). 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.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2015-2019Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the manifest: https://www.arcgis.com/sharing/rest/content/items/3d489c725bb24f52a987b302147c46ee/data

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John Snow Labs (2021). US Census Bureau States And Counties Health Insurance Estimates [Dataset]. https://www.johnsnowlabs.com/marketplace/us-census-bureau-states-and-counties-health-insurance-estimates/
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US Census Bureau States And Counties Health Insurance Estimates

Explore at:
csvAvailable download formats
Dataset updated
Jan 20, 2021
Dataset authored and provided by
John Snow Labs
Time period covered
2020
Area covered
United States
Description

This dataset contains estimates of health insured and uninsured population for 2020 at county and state level based on US Census Bureau program, The Small Area Health Insurance Estimates (SAHIE) program. For every state and county for each demographic group, defined by age, gender, race/ethnicity and income relative to poverty, the estimated number of persons insured and uninsured is given along with the margin of error.

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