25 datasets found
  1. County Health Rankings

    • open.piercecountywa.gov
    • internal.open.piercecountywa.gov
    Updated Jun 13, 2023
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    Robert Wood Johnson Foundation (2023). County Health Rankings [Dataset]. https://open.piercecountywa.gov/Health-and-Human-Services/County-Health-Rankings/mzcd-rv3c
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    csv, application/rdfxml, xml, tsv, kml, application/geo+json, application/rssxml, kmzAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset authored and provided by
    Robert Wood Johnson Foundationhttp://www.rwjf.org/
    Description

    Data from County Health Rankings and Roadmaps, a Robert Wood Johnson Foundation program. The County Health Rankings & Roadmaps program is a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute.

    The goals of the program are to: - Build awareness of the multiple factors that influence health
    - Provide a reliable, sustainable source of local data and evidence to communities to help them identify opportunities to improve their health - Engage and activate local leaders from many sectors in creating sustainable community change, and - Connect & empower community leaders working to improve health.

  2. v

    County Health Rankings 2020

    • anrgeodata.vermont.gov
    • covid-hub.gio.georgia.gov
    • +4more
    Updated Apr 24, 2023
    + more versions
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    cf2977oe (2023). County Health Rankings 2020 [Dataset]. https://anrgeodata.vermont.gov/datasets/4fdb2c0e7753484a81e16482dbe2429b
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    Dataset updated
    Apr 24, 2023
    Dataset authored and provided by
    cf2977oe
    Area covered
    Description

    The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. This feature layer contains 2020 County Health Rankings data for nation, state, and county levels. The Rankings are compiled using county-level measures from a variety of national and state data sources. Some example measures are:adult smokingphysical inactivityflu vaccinationschild povertydriving alone to workTo see a full list of variables, as well as their definitions and descriptions, explore the Fields information by clicking the Data tab here in the Item Details. These measures are standardized and combined using scientifically-informed weights."By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Some new features of the 2020 Rankings data compared to previous versions:More race/ethnicity categories, including Asian/Pacific Islander and American Indian/Alaska NativeReliability flags that to flag an estimate as unreliable5 new variables: math scores, reading scores, juvenile arrests, suicides, and traffic volumeData Processing Notes:Data downloaded March 2020Slight modifications made to the source data are as follows:The string " raw value" was removed from field labels/aliases so that auto-generated legends and pop-ups would only have the measure's name, not "(measure's name) raw value" and strings such as "(%)", "rate", or "per 100,000" were added depending on the type of measure.Percentage and Prevalence fields were multiplied by 100 to make them easier to work with in the map.For demographic variables only, the word "numerator" was removed and the word "population" was added where appropriate.Fields dropped from analytic data file: yearall fields ending in "_cihigh" and "_cilow"and any variables that are not listed in the sources and years documentation.Analytic data file was then merged with state-specific ranking files so that all county rankings and subrankings are included in this layer.

  3. County Health Rankings 2022

    • atlas-connecteddmv.hub.arcgis.com
    Updated Aug 29, 2022
    + more versions
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    Esri (2022). County Health Rankings 2022 [Dataset]. https://atlas-connecteddmv.hub.arcgis.com/maps/3a684a0851e74ff1b55225dbdfde78b4
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    Dataset updated
    Aug 29, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. This feature layer contains 2022 County Health Rankings data for nation, state, and county levels. The Rankings are compiled using county-level measures from a variety of national and state data sources. Some example measures are:adult smokingphysical inactivityflu vaccinationschild povertydriving alone to workTo see a full list of variables, as well as their definitions and descriptions, explore the Fields information by clicking the Data tab here in the Item Details. These measures are standardized and combined using scientifically-informed weights."By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Counties are ranked within their state on both health outcomes and health factors. Counties with a lower (better) health outcomes ranking than health factors ranking may see the health of their county decline in the future, as factors today can result in outcomes later. Conversely, counties with a lower (better) factors ranking than outcomes ranking may see the health of their county improve in the future.Some new variables in the 2022 Rankings data compared to previous versions:COVID-19 age-adjusted mortalitySchool segregationSchool funding adequacyGender pay gapChildcare cost burdenChildcare centersLiving wage (while the Living wage measure was introduced to the CHRR dataset in 2022 from the Living Wage Calculator, it is not available in the Living Atlas dataset and user’s interested in the most up to date living wage data can look that up on the Living Wage Calculator website).Data Processing Notes:Data downloaded April 2022Slight modifications made to the source data are as follows:The string " raw value" was removed from field labels/aliases so that auto-generated legends and pop-ups would only have the measure's name, not "(measure's name) raw value" and strings such as "(%)", "rate", or "per 100,000" were added depending on the type of measure.Percentage and Prevalence fields were multiplied by 100 to make them easier to work with in the map.Ratios were set to null if negative to make them easier to work with in the map.For demographic variables, the word "numerator" was removed and the word "population" was added where appropriate.Fields dropped from analytic data file: yearall fields ending in "_cihigh" and "_cilow"and any variables that are not listed in the sources and years documentation.Analytic data file was then merged with state-specific ranking files so that all county rankings and subrankings are included in this layer.2010 US boundaries were used as the data contain 2010 US census geographies, for a total of 3,142 counties.

  4. T

    2022 County Health Rankings Ranked Measures

    • data.countyofnapa.org
    application/rdfxml +5
    Updated Dec 29, 2022
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    (2022). 2022 County Health Rankings Ranked Measures [Dataset]. https://data.countyofnapa.org/Health-Outcomes-and-Health-Behaviors/2022-County-Health-Rankings-Ranked-Measures/mhir-22m3
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    csv, xml, tsv, application/rssxml, json, application/rdfxmlAvailable download formats
    Dataset updated
    Dec 29, 2022
    Description

    County Health Ranking and Roadmap

  5. e

    Country

    • coronavirus-resources.esri.com
    Updated Mar 25, 2020
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    Esri (2020). Country [Dataset]. https://coronavirus-resources.esri.com/maps/esri::country-9
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    Dataset updated
    Mar 25, 2020
    Dataset authored and provided by
    Esri
    Area covered
    Description

    The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. This feature layer contains 2020 County Health Rankings data for nation, state, and county levels. The Rankings are compiled using county-level measures from a variety of national and state data sources. Some example measures are:adult smokingphysical inactivityflu vaccinationschild povertydriving alone to workTo see a full list of variables, as well as their definitions and descriptions, explore the Fields information by clicking the Data tab here in the Item Details. These measures are standardized and combined using scientifically-informed weights."By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Some new features of the 2020 Rankings data compared to previous versions:More race/ethnicity categories, including Asian/Pacific Islander and American Indian/Alaska NativeReliability flags that to flag an estimate as unreliable5 new variables: math scores, reading scores, juvenile arrests, suicides, and traffic volumeData Processing Notes:Data downloaded March 2020Slight modifications made to the source data are as follows:The string " raw value" was removed from field labels/aliases so that auto-generated legends and pop-ups would only have the measure's name, not "(measure's name) raw value" and strings such as "(%)", "rate", or "per 100,000" were added depending on the type of measure.Percentage and Prevalence fields were multiplied by 100 to make them easier to work with in the map.For demographic variables only, the word "numerator" was removed and the word "population" was added where appropriate.Fields dropped from analytic data file: yearall fields ending in "_cihigh" and "_cilow"and any variables that are not listed in the sources and years documentation.Analytic data file was then merged with state-specific ranking files so that all county rankings and subrankings are included in this layer.

  6. a

    Children in Poverty in the US

    • hub.arcgis.com
    Updated May 17, 2018
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    Urban Observatory by Esri (2018). Children in Poverty in the US [Dataset]. https://hub.arcgis.com/maps/UrbanObservatory::children-in-poverty-in-the-us
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    Dataset updated
    May 17, 2018
    Dataset authored and provided by
    Urban Observatory by Esri
    Area covered
    Description

    This map shows the percent of children living within poverty by county in the United States. The popup shows the breakdown of children within poverty by race, if the data is available. According to the National Center for Children in Poverty, 21% of all children live within poverty. The map uses this figure to show areas that are above or below the national average. Areas in orange represent areas that have a higher amount of children living within poverty.The data comes from the County Health Rankings 2018 layer. The report is from a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute.According to the County Health Rankings & Roadmaps site "By ranking the health of nearly every county in the nation, the County Health Rankings help communities understand what influences how healthy residents are and how long they will live. These comparisons among counties provide context and demonstrate that where you live, and many other factors including race/ethnicity, can deeply impact your ability to live a healthy life. The Rankings not only provide this snapshot of your county’s health, but also are used to drive conversations and action to address the health challenges and gaps highlighted in these findings."Download the Excel file here: 2018 County Health Rankings

  7. Access to Mental Health

    • share-open-data-njtpa.hub.arcgis.com
    • hub.arcgis.com
    Updated Dec 4, 2018
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    Urban Observatory by Esri (2018). Access to Mental Health [Dataset]. https://share-open-data-njtpa.hub.arcgis.com/items/07f70065653b4386b5c87cbe9b50b314
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    Dataset updated
    Dec 4, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map shows the access to mental health providers in every county and state in the United States according to the 2024 County Health Rankings & Roadmaps data for counties, states, and the nation. It translates the numbers to explain how many additional mental health providers are needed in each county and state. According to the data, in the United States overall there are 319 people per mental health provider in the U.S. The maps clearly illustrate that access to mental health providers varies widely across the country.The data comes from this County Health Rankings 2024 layer. An updated layer is usually published each year, which allows comparisons from year to year. This map contains layers for 2024 and also for 2022 as a comparison.County Health Rankings & Roadmaps (CHR&R), a program of the University of Wisconsin Population Health Institute with support provided by the Robert Wood Johnson Foundation, draws attention to why there are differences in health within and across communities by measuring the health of nearly all counties in the nation. This map's layers contain 2024 CHR&R data for nation, state, and county levels. The CHR&R Annual Data Release is compiled using county-level measures from a variety of national and state data sources. CHR&R provides a snapshot of the health of nearly every county in the nation. A wide range of factors influence how long and how well we live, including: opportunities for education, income, safe housing and the right to shape policies and practices that impact our lives and futures. Health Outcomes tell us how long people live on average within a community, and how people experience physical and mental health in a community. Health Factors represent the things we can improve to support longer and healthier lives. They are indicators of the future health of our communities.Some example measures are:Life ExpectancyAccess to Exercise OpportunitiesUninsuredFlu VaccinationsChildren in PovertySchool Funding AdequacySevere Housing Cost BurdenBroadband AccessTo see a full list of variables, definitions and descriptions, explore the Fields information by clicking the Data tab here in the Item Details of this layer. For full documentation, visit the Measures page on the CHR&R website. Notable changes in the 2024 CHR&R Annual Data Release:Measures of birth and death now provide more detailed race categories including a separate category for ‘Native Hawaiian or Other Pacific Islander’ and a ‘Two or more races’ category where possible. Find more information on the CHR&R website.Ranks are no longer calculated nor included in the dataset. CHR&R introduced a new graphic to the County Health Snapshots on their website that shows how a county fares relative to other counties in a state and nation. Data Processing:County Health Rankings data and metadata were prepared and formatted for Living Atlas use by the CHR&R team. 2021 U.S. boundaries are used in this dataset for a total of 3,143 counties. Analytic data files can be downloaded from the CHR&R website.

  8. o

    Data from: Identifying characteristics of high-poverty counties in the...

    • openicpsr.org
    delimited, stata
    Updated Sep 15, 2020
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    Anita Arora (2020). Identifying characteristics of high-poverty counties in the United States with high well-being: an observational cross-sectional study [Dataset]. http://doi.org/10.3886/E121690V1
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    stata, delimitedAvailable download formats
    Dataset updated
    Sep 15, 2020
    Dataset provided by
    Yale University
    Authors
    Anita Arora
    License

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

    Time period covered
    Jan 1, 2010 - Dec 31, 2010
    Area covered
    United States
    Description

    In this study of high-poverty counties in the USA, we used a unique and validated measure of population well-being, the Gallup-Sharecare Well-being Index. We described high-poverty counties with high and low well-being using 29 characteristics from the Robert Wood Johnson Foundation County Health Rankings and Roadmaps, a well-established model of population health. Our study examined associations by county, due to lack of well-being data at the city or neighbourhood level, and both poverty and well-being are likely to be heterogeneous at the county level.

  9. C

    Low Birth-Weight Rate

    • data.ccrpc.org
    csv
    Updated Dec 1, 2023
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    Champaign County Regional Planning Commission (2023). Low Birth-Weight Rate [Dataset]. https://data.ccrpc.org/ar/dataset/low-birth-weight-rate
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    csvAvailable download formats
    Dataset updated
    Dec 1, 2023
    Dataset authored and provided by
    Champaign County Regional Planning Commission
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    The low birth-weight rate measures the percentage of live births with weights below 2500 grams. A low birth-weight can affect health outcomes later in life, and is an illustrative indicator for the overall health of the measured population.

    The low birth-weight rate in Champaign County has been above 8 percent since 2011, the earliest Reporting Year available in the dataset. This is close to the statewide rate, which returned to 8.4 percent from Reporting Year 2021 through present after a slight decrease in recent years. The lowest county low birth-weight rate in the state is 5.6 percent (Carroll County in the northwest corner of the state), while the highest county low birth-weight rate in the state is 11.9 percent (Pulaski County in southernmost Illinois).

    This data was sourced from the University of Wisconsin's Population Health Institute's and the Robert Wood Johnson Foundation’s County Health Rankings & Roadmaps. Each year’s County Health Rankings uses data from years prior. Therefore, the 2023 County Health Rankings (“Reporting Year” in the table) uses data from 2014-2020 (“Data Years” in the table).

    Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2023.

  10. C

    Adult Obesity Rate

    • data.ccrpc.org
    csv
    Updated Dec 11, 2024
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    Champaign County Regional Planning Commission (2024). Adult Obesity Rate [Dataset]. https://data.ccrpc.org/ca/dataset/adult-obesity-rate
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    csvAvailable download formats
    Dataset updated
    Dec 11, 2024
    Dataset authored and provided by
    Champaign County Regional Planning Commission
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Description

    The adult obesity rate, or the percentage of the county population (age 18 and older*) that is obese, or has a Body Mass Index (BMI) equal to or greater than 30 [kg/m2], is illustrative of a serious health problem, in Champaign County, statewide, and nationally.

    The adult obesity rate data shown here spans from Reporting Years (RY) 2015 to 2024. Champaign County’s adult obesity rate fluctuated during this time, peaking in RY 2022. The adult obesity rates for Champaign County, Illinois, and the United States were all above 30% in RY 2024, but the Champaign County rate was lower than the state and national rates. All counties in Illinois had an adult obesity rate above 30% in RY 2024, but Champaign County's rate is one of the lowest among all Illinois counties.

    Obesity is a health problem in and of itself, and is commonly known to exacerbate other health problems. It is included in our set of indicators because it can be easily measured and compared between Champaign County and other areas.

    This data was sourced from the University of Wisconsin’s Population Health Institute’s and the Robert Wood Johnson Foundation’s County Health Rankings & Roadmaps. Each year’s County Health Rankings uses data from the most recent previous years that data is available. Therefore, the 2024 County Health Rankings (“Reporting Year” in the table) uses data from 2021 (“Data Year” in the table). The survey methodology changed in Reporting Year 2015 for Data Year 2011, which is why the historical data shown here begins at that time. No data is available for Data Year 2018. The County Health Rankings website notes to use caution if comparing RY 2024 data with prior years.

    *The percentage of the county population measured for obesity was age 20 and older through Reporting Year 2021, but starting in Reporting Year 2022 the percentage of the county population measured for obesity was age 18 and older.

    Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2024. www.countyhealthrankings.org.

  11. Predominant Race for Teen Birth in the U.S.

    • gis-for-racialequity.hub.arcgis.com
    Updated May 11, 2018
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    Urban Observatory by Esri (2018). Predominant Race for Teen Birth in the U.S. [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/515638d5a34d403f996e0f6da8839dbb
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    Dataset updated
    May 11, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map shows the predominant race of mothers who have given birth between the ages of 15-19. This is shown by county, state, and country from the 2022 County Health Rankings. The data comes from the County Health Rankings 2022 layer. The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. "By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Counties are ranked within their state on both health outcomes and health factors. Counties with a lower (better) health outcomes ranking than health factors ranking may see the health of their county decline in the future, as factors today can result in outcomes later. Conversely, counties with a lower (better) factors ranking than outcomes ranking may see the health of their county improve in the future.

  12. 3C dataverse: Community capitals, cover crops, & conservation agriculture in...

    • zenodo.org
    bin
    Updated Apr 24, 2025
    + more versions
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    Jacob Miller-Klugesherz; Jacob Miller-Klugesherz (2025). 3C dataverse: Community capitals, cover crops, & conservation agriculture in the U.S. corn-soybean belt, version 2.1 [Dataset]. http://doi.org/10.5281/zenodo.14595668
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    binAvailable download formats
    Dataset updated
    Apr 24, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Jacob Miller-Klugesherz; Jacob Miller-Klugesherz
    License

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

    Time period covered
    Jan 3, 2025
    Description

    What?

    A dataset containing 313 total variables from 33 secondary sources. There are 261 unique variables, and 52 variables that have the same measurement but are reported for a different year; e.g. average farm size in 2017 (CapitalID: N27a) and 2022 (N27b). Variables were grouped by the community capital framework's seven capitals—Natural (96 total variables), Cultural (38), Human (39), Social (40), Political (18), Financial (67), & Built (15)—and temporally and thematically ordered. The geographic boundary is NOAA NCEI's corn and soybean belt (figure below), which stretches across 18 states and includes N=860 counties/observations. Cover crop data for the 80 Crop Reporting Districts in the boundary are also included for 2015-2021.

    Why?

    Comprehensively assessing how community capital clustered variables, for both farmers and nonfarmers, impact conservation practices (and perennial groundcover) over time helps to examine county-level farm conservation agriculture practices in the context of community development. We contribute to the robust U.S. cover crop literature a better understanding of how overarching cultural, social, and human factors influence conservation agriculture practices to encourage better farm management practices. Analyses of this Dataverse will be presented as recomendations for farmers, nonfarmers, ag-adjacent stakeholders, and community leaders.

    How?

    Variables used in this dataset range 20 years, from 2004-2023, though primary analyses focus on data collected between 2017-2024, primarily 2017 and 2022 (NASS Ag Census years). First, JAM-K requested, accessed, and downloaded data, most of which was already publically available. Next, JAM-K cleaned the data and aggregated into one dataset, and made it publically available on Google Drive and Zenodo.

    What is 'new' or corrected in version 2?

    Edited/amended: Carroll, KY is now spelled correctly (two 'l's, not one); variable names, full and abbreviated, were updated to include the data year; Pike County's (IL) FIPS has been corrected from its wrong 17153 (same as Pulaski County) to 17149 (correct fips), and all Pike County (IL) data has been correctly amended; Farming dependent (ERS) updated for all variables; Data for built capital variables irrCorn17, irrSoy17, irrHcrp17, tractor17, and combine17 were incorrect for v.1, but were corrected for v.2; Several variable labels aggregated by Wisconsin University's Population Health Institute's County Health Rankings and Roadmaps were corrected to have the data's original source and years included, rather than citing CHR&R as the source (except for CHR&R's originally-produced values such as quartiles or rank scores); variables were reorganized by hypothesized community capital clusters (Natural -> Built), and temporally within each cluster.

    Added: 55 variables, mostly from the 2022 Ag Census, and v2.1 added a .pdf file with descriptives of data sources and years, and a .sav file.

    Omitted: Four variables deemed irrelevant to the study; V1 codebook's "years internally available" column.

    CRediT: conceptualization, CBF, JAM-K; methodology, JAM-K; data aggregation and curation, JAM-K; formal analysis, JAM-K; visualization, JAM-K; supervision, CBF; funding acquisition, CBF; project administration, CBF; resources, CBF, JAM-K

    Acknowledgements: This research was funded by the Agriculture and Food Research Initiative Competitive Grant No. 2021-68012-35923 from the United States Department of Agriculture National Institute for Food and Agriculture. Any opinions, findings, conclusions, or recommendations expressed in this presentation are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture. Much thanks to Corteva for granting data access of OpTIS 2.0 (2005-2019), and Austin Landini for STATA code and visualization assistance.

  13. Country

    • gis-for-racialequity.hub.arcgis.com
    • covid-gagio.hub.arcgis.com
    Updated Mar 25, 2020
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    Esri (2020). Country [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/esri::country-9
    Explore at:
    Dataset updated
    Mar 25, 2020
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. This feature layer contains 2020 County Health Rankings data for nation, state, and county levels. The Rankings are compiled using county-level measures from a variety of national and state data sources. Some example measures are:adult smokingphysical inactivityflu vaccinationschild povertydriving alone to workTo see a full list of variables, as well as their definitions and descriptions, explore the Fields information by clicking the Data tab here in the Item Details. These measures are standardized and combined using scientifically-informed weights."By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Some new features of the 2020 Rankings data compared to previous versions:More race/ethnicity categories, including Asian/Pacific Islander and American Indian/Alaska NativeReliability flags that to flag an estimate as unreliable5 new variables: math scores, reading scores, juvenile arrests, suicides, and traffic volumeData Processing Notes:Data downloaded March 2020Slight modifications made to the source data are as follows:The string " raw value" was removed from field labels/aliases so that auto-generated legends and pop-ups would only have the measure's name, not "(measure's name) raw value" and strings such as "(%)", "rate", or "per 100,000" were added depending on the type of measure.Percentage and Prevalence fields were multiplied by 100 to make them easier to work with in the map.For demographic variables only, the word "numerator" was removed and the word "population" was added where appropriate.Fields dropped from analytic data file: yearall fields ending in "_cihigh" and "_cilow"and any variables that are not listed in the sources and years documentation.Analytic data file was then merged with state-specific ranking files so that all county rankings and subrankings are included in this layer.

  14. How many females aged 15-19 have given birth?

    • livingatlas-dcdev.opendata.arcgis.com
    Updated May 11, 2018
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    Urban Observatory by Esri (2018). How many females aged 15-19 have given birth? [Dataset]. https://livingatlas-dcdev.opendata.arcgis.com/datasets/5842fc4518704c848bea7567de950661
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    Dataset updated
    May 11, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map shows teen birth rates in the US. This is shown by county, state, and country from the 2022 County Health Rankings. The average is 19 births per 1,000 women aged 15-19.The data comes from the County Health Rankings 2022 layer. The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. "By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Counties are ranked within their state on both health outcomes and health factors. Counties with a lower (better) health outcomes ranking than health factors ranking may see the health of their county decline in the future, as factors today can result in outcomes later. Conversely, counties with a lower (better) factors ranking than outcomes ranking may see the health of their county improve in the future.

  15. High School Graduation Rate in the U.S.

    • atlas-connecteddmv.hub.arcgis.com
    Updated May 3, 2018
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    Urban Observatory by Esri (2018). High School Graduation Rate in the U.S. [Dataset]. https://atlas-connecteddmv.hub.arcgis.com/maps/11f7fbf1bf864abcae3d13109b413792
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    Dataset updated
    May 3, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map shows high school graduations within the US by graduation rate. This is shown by county, state, and country from the 2022 County Health Rankings. The national average of students who graduate high school is 86%.The data comes from the County Health Rankings 2022 layer. The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. "By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Counties are ranked within their state on both health outcomes and health factors. Counties with a lower (better) health outcomes ranking than health factors ranking may see the health of their county decline in the future, as factors today can result in outcomes later. Conversely, counties with a lower (better) factors ranking than outcomes ranking may see the health of their county improve in the future.

  16. Stratified Analysis: Cox Proportional Hazard Model for Associations Between...

    • plos.figshare.com
    xls
    Updated Jul 10, 2025
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    Shenghui Wu; Sarah Ulrich; Tinghao Feng; Yanning Liu; Leilani Tseng (2025). Stratified Analysis: Cox Proportional Hazard Model for Associations Between Food Environment Index and Overall Cancer Survival (NC Cancer Registry 2000–2022). [Dataset]. http://doi.org/10.1371/journal.pone.0326597.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 10, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Shenghui Wu; Sarah Ulrich; Tinghao Feng; Yanning Liu; Leilani Tseng
    License

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

    Area covered
    North Carolina
    Description

    Stratified Analysis: Cox Proportional Hazard Model for Associations Between Food Environment Index and Overall Cancer Survival (NC Cancer Registry 2000–2022).

  17. Data from: Infant Mortality in the U.S.

    • gis-for-racialequity.hub.arcgis.com
    Updated May 10, 2018
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    Urban Observatory by Esri (2018). Infant Mortality in the U.S. [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/UrbanObservatory::infant-mortality-in-the-u-s-/about
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    Dataset updated
    May 10, 2018
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Urban Observatory by Esri
    Area covered
    Description

    This map shows the infant mortality rate and total number of infant deaths. This is shown by county, state, and country from the 2022 County Health Rankings. The national average is 5.7 deaths per 1,000.The data comes from the County Health Rankings 2022 layer. The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. "By ranking the health of nearly every county in the nation, County Health Rankings & Roadmaps (CHR&R) illustrates how where we live affects how well and how long we live. CHR&R also shows what each of us can do to create healthier places to live, learn, work, and play – for everyone."Counties are ranked within their state on both health outcomes and health factors. Counties with a lower (better) health outcomes ranking than health factors ranking may see the health of their county decline in the future, as factors today can result in outcomes later. Conversely, counties with a lower (better) factors ranking than outcomes ranking may see the health of their county improve in the future.

  18. Cox Proportional Hazards Regression Analyses of the Associations Between...

    • plos.figshare.com
    xls
    Updated Jul 10, 2025
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    Shenghui Wu; Sarah Ulrich; Tinghao Feng; Yanning Liu; Leilani Tseng (2025). Cox Proportional Hazards Regression Analyses of the Associations Between Food Environment Index and Overall Cancer Survival (NC Cancer Registry 2000–2022). [Dataset]. http://doi.org/10.1371/journal.pone.0326597.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 10, 2025
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Shenghui Wu; Sarah Ulrich; Tinghao Feng; Yanning Liu; Leilani Tseng
    License

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

    Area covered
    North Carolina
    Description

    Cox Proportional Hazards Regression Analyses of the Associations Between Food Environment Index and Overall Cancer Survival (NC Cancer Registry 2000–2022).

  19. a

    CVIData Free or Reduced Price Lunch

    • superfund-gis-data-tamu.hub.arcgis.com
    Updated Nov 22, 2023
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    shiyun@tamu.edu_tamu (2023). CVIData Free or Reduced Price Lunch [Dataset]. https://superfund-gis-data-tamu.hub.arcgis.com/maps/9d1f6d4f194e413a85aee22b31788db7
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    Dataset updated
    Nov 22, 2023
    Dataset authored and provided by
    shiyun@tamu.edu_tamu
    Area covered
    Description

    Percentage of children enrolled in public schools that are eligible for free or reduced price lunch, 2019-2020.Source: County Health Rankings & Roadmaps (CHR&R), a program of the University of Wisconsin Population Health Institute. 2022.

  20. a

    IdahoVoterTurnout

    • uidaho.hub.arcgis.com
    Updated Nov 22, 2023
    + more versions
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    University of Idaho (2023). IdahoVoterTurnout [Dataset]. https://uidaho.hub.arcgis.com/maps/uidaho::idahovoterturnout-1
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    Dataset updated
    Nov 22, 2023
    Dataset authored and provided by
    University of Idaho
    Area covered
    Description

    This county-level map shows. Voter Turnout for the 2020 U.S. Presidential election Data from County Health Rankings.Voter turnout is the percentage of citizen population aged 18 or older who voted in the 2020 U.S. Presidential election.Areas in dark blue indicate a lower voter turnout, while areas in light blue indicate a higher voter turnout. Data comes from County Health Rankings, a program of the University of Wisconsin Population Health Institute with support provided by the Robert Wood Johnson Foundation.Voting collectively influences the health of our communities and healthier communities are more likely to vote. Studies show that communities with higher voter turnout tend to also have better self-reported general health, fewer chronic health conditions, a lower overall mortality rate, and less depression. Learn more about voter turnout from County Health Rankings & Roadmaps.A number of different policies can affect voter turnout, such as voter id laws, early voting, and mail-in ballots. Learn more about voter turnout strategies and initiatives.

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Robert Wood Johnson Foundation (2023). County Health Rankings [Dataset]. https://open.piercecountywa.gov/Health-and-Human-Services/County-Health-Rankings/mzcd-rv3c
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County Health Rankings

Explore at:
csv, application/rdfxml, xml, tsv, kml, application/geo+json, application/rssxml, kmzAvailable download formats
Dataset updated
Jun 13, 2023
Dataset authored and provided by
Robert Wood Johnson Foundationhttp://www.rwjf.org/
Description

Data from County Health Rankings and Roadmaps, a Robert Wood Johnson Foundation program. The County Health Rankings & Roadmaps program is a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute.

The goals of the program are to: - Build awareness of the multiple factors that influence health
- Provide a reliable, sustainable source of local data and evidence to communities to help them identify opportunities to improve their health - Engage and activate local leaders from many sectors in creating sustainable community change, and - Connect & empower community leaders working to improve health.

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