Rural Health Mapping Tool

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Causes of Death

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INTRODUCTION HOW TO USE THE TOOL METHODOLOGY & DATA PROSPERITY INDEX ABOUT US/CONTACT

Example County

Example Text
Example Text
 21.8
26.6

The mortality rate for counties with fewer than 10 deaths during the time period is suppressed.

For each Prosperity Index component score: 1 = Lowest risk or highest resilience and 5 = Highest risk or lowest resilience

Click on a variable in the leftmost column of the data table to see it's definition.

Estimates for counties with small populations may be subject to large margins of error and should be interpreted with caution.

Prosperity Index Data Table
Component Score Indicator County Name State United States
Economic - Risk - - - -
- - -
- - -
- - -
Economic - Resilience - - - -
- - -
- - -
- - -
Social - Risk - - - -
- - -
- - -
- - -
Social - Resilience - - - -
- - -
- - -
- - -
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Methodology & Data Sources

Click here to download a Microsoft Excel file containing the data used in the Rural Health Mapping Tool.

The Rural Health Mapping Tool was developed using JavaScript and the Leaflet library. Data processing was conducted using SAS and R, and geographic files were converted from shapefile format to TopoJSON using the sf package in R.

The tables below provide data sources, definitions, and reference periods for all measures included in the tool. All data were obtained from publicly available sources. Rural and urban counties are classified using the 2023 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme for Counties.

Connecticut Data Considerations

Beginning with the 2022 American Community Survey (ACS), data for Connecticut are released at the Planning Region level rather than the county level. As a result, NCHS does not publish county-level population estimates or mortality rates for Connecticut counties beginning with 2022 data. Cause-of-death measures displayed in the tool for Connecticut counties are based on CDC WONDER data from 2020-2024. ACS-derived measures were estimated using a crosswalk linking Connecticut Planning Regions to census tracts and counties. All other Census-derived variables are based on the 2020–2024 5-year ACS release. Median household income, median gross rent, and median home value required a different estimation approach than other ACS-derived measures. Because median values cannot be directly aggregated across geographies, tract-level ACS data were aggregated within counties and used to recalculate county-specific median values. All other ACS-derived measures were estimated using the Planning Region-to-county crosswalk approach described above.
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Prosperity Index Methodology

What is the prosperity index?

NORC developed the Prosperity Index in 2019 with funding from the U.S. Department of Agriculture (USDA) Rural Development and guidance from a Technical Expert Panel. The Prosperity Index provides a composite measure of county-level prosperity for all U.S. counties. The index is designed to summarize economic and social factors associated with community well-being, resilience, and vulnerability.

For the overall Prosperity Index score:

  • 1 = Most prosperous
  • 5 = Least prosperous

For each component score:

  • 1 = Lowest risk or highest resilience
  • 5 = Highest risk or lowest resilience

The Prosperity Index is calculated using standardized values for 16 indicators organized into four component categories:

  • Economic Risk
  • Economic Resilience
  • Social Risk
  • Social Resilience

Each component comprises four indicators that capture distinct aspects of county-level prosperity. Indicator values are combined to produce component scores, which are then aggregated into the overall Prosperity Index score.

Diagram showing the Prosperity Index organized into four components: Economic Risk, Economic Resilience, Social Risk, and Social Resilience. The four components each contain four indicators and collectively contribute to the overall Prosperity Index score
How should the prosperity index be interpreted?

The Prosperity Index is intended to provide a broad assessment of conditions that may influence the health, well-being, and long-term prosperity of communities. The economic components measure factors that may increase vulnerability (Economic Risk) as well as factors that may help communities withstand and recover from challenges (Economic Resilience). Higher levels of resilience may help offset the effects of economic risk. Similarly, the social components measure factors associated with community vulnerability (Social Risk) and protective factors that support community well-being (Social Resilience). Taken together, these four dimensions provide a more comprehensive picture of county-level prosperity than any single indicator alone. Users can examine both overall scores and individual component scores to identify areas of strength and areas where additional resources, investments, or interventions may be beneficial. The Prosperity Index is intended as a screening and planning tool and should be used alongside local knowledge and additional data sources when assessing community needs.

What are the indicators?

Indicators were selected based on the following criteria:

  • Relevance to community-level prosperity and well-being
  • Availability of data at the county level for counties across the United States
  • Consistent collection and public availability of data
  • Potential usefulness for local planning, decision-making, and community development efforts

Several indicators were considered during development, but were not included because consistent county-level data were unavailable or did not meet data quality requirements. Examples include measures of transportation access, income inequality, and access to early childhood education.

Economic – Resilience
Indicator Data Source Time Period Definition
Number of Hospital Beds per 10,000 population HRSA Area Health Resources Files 2023 Number of hospital beds per 10,000 population
Business Establishments per 100 workers U.S. Census Bureau County Business Patterns 2023 Number distinct business establishments per workers 16 years and older
Median Household Income U.S. Census Bureau, ACS 5-year estimates 2020-2024 Median household income in the past 12 months (in 2024 inflation-adjusted dollars)
Self-employment Rate U.S. Census Bureau, ACS 5-year estimates 2020-2024 % of workers age 16 years and older who are self-employed in their own incorporated business
Economic – Risk
Indicator Data Source Time Period Definition
Industry Dependent (Yes/No) USDA Economic Research Service Economic Typology Codes 2025 Indicates whether a county is classified as economically dependent on a single dominant industry (farming, mining, manufacturing, government, or recreation). Counties identified as dependent on a single industry were coded as "Yes"; all other counties were coded as "No".
Net Migration per 100 people Census Population Totals and Components of Change 2025 Net migration rate was calculated by dividing the total net migration (domestic and international) between July 1, 2024, and July 1, 2025, by the county population on July 1, 2024.
Labor Force Participation Rate U.S. Census Bureau, ACS 5-year estimates 2020-2024 Among the civilian non-institutionalized population aged 25 to 54, the % that is working or actively looking for work
Poverty Rate U.S. Census Bureau, ACS 5-year estimates 2020-2024 % of persons below poverty threshold
Social – Resilience
Indicator Data Source Time Period Definition
Primary Care Providers per 10,000 population HRSA Area Health Resources Files 2023 Number of primary care physicians, nurse practitioners, and physician assistants per 10,000 population
501 c3 and c4s per 10,000 population Internal Revenue Service (IRS) 2025 Number of 501 c3 and c4 organizations per 10,000 population
Voter Participation Rate^ MIT Election Data and Science Lab 2024 % of eligible voters who cast a ballot in the 2024 presidential election, calculated using the U.S. Census Citizen Voting Age Population (CVAP) as the estimate of the eligible voting population
Educational Attainment – Bachelor's Degree or more U.S. Census Bureau, ACS 5-year estimates 2020-2024 % of population 25 years and older with a Bachelor's, Master's, Professional, or Doctorate degree
Social – Risk
Indicator Data Source Time Period Definition
Teen Birth Rate CDC National Center for Health Statistics 2020 Estimated teen birth rate, expressed as the number of births per 1,000 females aged 15 to 19 years
All-cause Mortality Rate per 100,000 population CDC WONDER 2020-2024 Number of deaths of all causes per 100,000 population (crude rate)
Digital Divide Index Purdue Center for Regional Development 2024 The Digital Divide Index or DDI ranges in value from 0 to 100, where 100 indicates the highest digital divide. It is composed of two scores, also ranging from 0 to 100: the infrastructure/adoption (INFA) score and the socioeconomic (SE) score.
High School Dropout Rate U.S. Census Bureau, ACS 5-year estimates 2020-2024 % of persons aged 16 to 19 years who neither graduated from, nor are currently enrolled in, high school


^The voter turnout indicator was not readily available for Alaska since the raw data included voter totals by Congressional House District. A proportional allocation method based on population overlap was devised to estimate the voter turnout for each county (borough) in Alaska.

How is the prosperity index calculated?

The Prosperity Index is calculated for each county in the United States using 16 indicators grouped into four components associated with prosperity: Economic Risk, Economic Resilience, Social Risk, and Social Resilience. Each component consists of four indicators that reflect different dimensions of community conditions related to risk or resilience. To ensure that indicators measured on different scales can be combined, each indicator is standardized to have a mean of 0 and a standard deviation of 1 across all U.S. counties. Standardized values allow the indicators to be compared and aggregated regardless of their original units of measurement. Before standardization, indicator values with exceptionally high observations are top-coded at approximately the 95th percentile. This approach limits the influence of outliers on each indicator's distribution and yields more stable standardized values for score calculations. Reported indicator values are not modified; this adjustment is applied only during the calculation of Prosperity Index scores. For each indicator, counties are grouped into five homogeneous categories based on their standardized values. These categories are assigned scores ranging from 1 to 5, where 1 represents the lowest risk or highest resilience and 5 represents the highest risk or lowest resilience. Within each component, the four standardized indicator values are summed to create a component value for each county. Counties are then grouped into five homogeneous categories based on these component values, resulting in component scores ranging from 1 to 5. The overall Prosperity Index is derived by summing the four component values to create a county-level prosperity value. Counties are then grouped into five categories based on their overall prosperity values. The final Prosperity Index score ranges from 1 (most prosperous) to 5 (least prosperous). The overall Prosperity Index provides a summary measure of county-level prosperity, while the component scores offer additional insight into the economic and social factors contributing to a county's overall score.

State and National Comparison Values

State and national comparison values are calculated separately from county-level Prosperity Index scores and are provided to support interpretation of county data. For most indicators, state and national values are derived using population-weighted calculations, typically by dividing the sum of indicator numerators by the sum of indicator denominators for the relevant geography. Indicators that do not have a numerator-denominator structure are aggregated using alternative methods consistent with their underlying data sources. For example, Industry Dependence is reported as the percentage of counties classified as industry dependent, while selected mortality measures use published state and national rates from the original data source.

Who participated in the Technical Expert Panel?

The Prosperity Index was developed with guidance from a Technical Expert Panel (TEP) representing a diverse group of experts in public health, rural health, community development, social determinants of health, and population health research.

The TEP included:

  • Anita Chandra, RAND Corporation
  • Courtney Cuthbertson, University of Illinois Urbana-Champaign
  • Alison Davis, University of Kentucky
  • Marjory Givens, Wisconsin Public Health Institute / County Health Rankings
  • Shannon Monnat, Syracuse University
  • Robert Pack, East Tennessee State University
  • Laura Palombi, University of Minnesota
  • Khary Rigg, University of South Florida
  • David Terrell, Indiana Communities Institute, Ball State University
  • Brian Smedley, National Collaborative for Health Equity
  • Sarah Willen, University of Connecticut
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About Us/Contact

This website is supported by the Centers for Disease Control and Prevention of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award totaling $500,000, with 100 percent funded by CDC/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement by, CDC/HHS, or the U.S. Government.

More About NORC at the University of Chicago

NORC at the University of Chicago conducts research and analysis that decision-makers trust. As a nonpartisan research organization and a pioneer in measuring and understanding the world, we have studied almost every aspect of the human experience and every major news event for more than eight decades. Today, we partner with government, corporate, and nonprofit clients around the world to provide the objectivity and expertise necessary to inform the critical decisions facing society.

www.norc.org

Contact

For more information please contact:

Megan Heffernan, MPH

Senior Research Scientist, Public Health Research, NORC at the University of Chicago

ruraltraining@norc.org

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Using the Rural Health Mapping Tool

The Rural Health Mapping Tool allows CDC staff, researchers, community organizations, local policymakers, and members of the public to create county-level maps that display health outcomes alongside socio-demographic and economic indicators across counties in the United States. The tool can be used to explore geographic patterns, identify areas of need, and examine relationships between community characteristics and health outcomes, particularly in rural areas.

Base-Layer Data

The base layer displays a selected health or prosperity measure for each county. Available measures include life expectancy, infant mortality rate, mortality rates for leading causes of death, and Prosperity Index scores. For health outcome and cause-of-death measures, darker-colored counties indicate higher rates and lighter-colored counties indicate lower rates. For Prosperity Index measures, green counties indicate higher resilience or prosperity, while orange counties indicate lower resilience or prosperity. Users may select a county directly from the map or use the “Search List of Counties” feature to navigate to a specific county.

County/State

Data can be viewed at either the county or state level using the “County/State” drop-down menu. When a state is selected using the “Filter by State” option, map shading is recalculated using quantiles for the selected state.

Rural vs. Urban

The Urban/Rural filter allows users to limit the displayed results to rural counties or urban counties.

Second-Layer Data: Socio-demographic and Economic Indicators by County

County-level socio-demographic and economic indicators can be displayed as a second layer over the selected base map measure. These indicators are shown as translucent circles whose size corresponds to the value of the selected indicator. This feature allows users to visually examine relationships between county characteristics and health outcomes. For example, displaying Median Household Income over a Heart Disease Mortality map may help illustrate how these measures vary across counties.

Correlation Graphs

When a second-layer indicator is added to a base map, users can select “Open Correlation Graph” to view a scatterplot and correlation coefficient describing the relationship between the two selected measures. Correlation coefficients range from -1 to +1 and indicate the strength and direction of the relationship between two variables. Values closer to -1 or +1 indicate stronger relationships, while values closer to 0 indicate weaker relationships. Positive values indicate that the variables tend to increase together, while negative values indicate that one variable tends to decrease as the other increases. The tool uses either Pearson's correlation coefficient or Spearman's correlation coefficient, depending on the characteristics of the selected variables.

  • Pearson's correlation coefficient - ranges from -1 to +1 and measures the strength and direction of a linear relationship between two continuous variables. A value of 0 indicates no linear relationship, while values near -1 and +1 indicate strong negative and positive linear relationships, respectively.
  • Spearman's correlation coefficient - ranges from -1 to +1 and measures the strength and direction of a monotonic relationship between two variables based on their ranks. Unlike Pearson's correlation coefficient, Spearman's correlation coefficient does not require the relationship to be linear.
Add Map Overlays

Additional geographic overlays can be added to the map using the “Add Map Overlay” drop-down. Available overlays include Native American reservations, persistent poverty counties, major highways, federally defined regions (such as Appalachia, the Delta Region, and the U.S.-Mexico border region), and HHS regions.

County Fact Sheets

A county fact sheet is available for every county in the United States. Fact sheets provide a summary of all measures included in the Rural Health Mapping Tool and compare county values with state and national averages. Fact sheets can be accessed by selecting “View Details” for a county on the main map page. County fact sheets also include information on local health care resources, such as pharmacies, primary care providers, National Health Service Corps sites, Federally Qualified Health Centers (FQHCs), and Rural Health Clinics.
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