Frequently Asked Questions


How should I cite County Health Rankings & Roadmaps?

The following citation should accompany any contents or graphics if used:   

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

How can I engage the County Health Rankings & Roadmaps team?

CHR&R serves as a curator of community health and equity improvement resources and connects program data, evidence and guidance to organizations engaged in local power-building and community health improvement efforts.  

Team members can help navigate the many resources available across the website to support users on their journey to create healthy, equitable communities. The team has also provided support for speaking engagements, presentations and media interviews that highlight these resources and tools. Click the Contact Us button at the bottom of any page on the website to get in touch with a CHR&R team member. 

How do I find my county's rank?

Health Outcome and Health Factor rankings are displayed in quartile graphics at the top of each county snapshot. Each quartile contains 25% of the ranked counties in the state, with healthier counties displayed further to the right on the graphic. These graphics provide an indication of where the county fares relative to other counties in the state. CHR&R encourages users to view a snapshot to reference the quartiles for overall comparison of counties within a state. Individual county ranks can be found in several places on the website:   

  • At the top of all county pages, just under the county name.
  • On any state page. Select "Health Outcomes" from the dropdown just above the large map at the top of the page. Once selected, a blue and yellow toggle will show the options "Map" and "Rankings." Select the "Rankings" option and a list of counties and their respective ranks will be displayed.  
  • Download the complete Rankings file for a state or the nation. 

Why did my county's rank change?

Ranks can change for one or more reasons:  

  • Your county experienced health gains or losses: Change in a rank can be due to change in the values of the underlying measures that comprise the rank.  
  • Other counties experienced health gains or losses: A county’s rank may also improve or worsen due to changes in other counties ranked just above or below.   
  • Random variation in measures: All measures experience some variation year-to-year and a fluctuation in county rank may be caused by random variation in the measures that comprise the rank.   
  • Changes in ranked measures or methods: Ranks can be influenced by the introduction of new ranked measures or a change in the methods for existing ranked measures.  

To better understand why a county’s rank may have changed from the previous year, the best place to start is by examining the individual measures that comprise the rank.   

For more information, see Measuring progress & change.

Where can I find out what years of data are included in the 2023 Rankings?

To see the years of data used for all measures please visit the 2023 measures page.

What should I know for 2023?

NEW! What measures are new in 2023?

In 2023, CHR&R introduced two new measures of civic health. These measures do not contribute to the ranks.  

  • Voter Turnout is the percentage of citizen population aged 18 or older who voted in the 2020 U.S. Presidential Election.
  • Census Participation is the percentage of households that self-responded to the 2020 census (by mail, internet or by phone). 

NEW! Are there changes to measures or methods in 2023?

Yes. In 2023, CHR&R retired the ranked measure of Violent Crime. The most recently available data for this measure were from 2014 & 2016 and did not reflect the current state in communities. The weight that Violent Crime previously contributed to the rank calculations was reassigned to the ranked measure of Injury Deaths. 

The unranked measures of Residential Segregation-(white/non-white) and COVID-19 Age Adjusted Mortality were also retired in 2023. 

Learn more about 2023 measure changes and comparability of measures across all years

    NEW! Why do some measures use the same data years as the 2022 release?

    Whenever possible, the most recently available data are used to calculate CHR&R measures.  

    Some data sources have not released new data in time to be included in the 2023 Rankings. In these cases, the measures feature data from previous years. For 2023, these measures include Juvenile Arrests, Alcohol-Impaired Driving Deaths, Reading Scores, Math Scores and % Rural.  

    For measures using mortality or natality data from the National Center for Health Statistics, changes in methodology for the 2020 census led to issues of comparability with data from previous years. The following measures feature data from previous years for reasons of comparability: Premature Death, Life Expectancy, Premature Age-Adjusted Mortality, Child Mortality, Infant Mortality, Limited Access to Healthy Foods, Drug Overdose Deaths, Homicides, Suicides, Firearm Fatalities, Motor Vehicle Crash Deaths, Teen Births and Low Birthweight. 

    Due to a reporting error, three counties in New Mexico (Bernalillo, Sandoval and Cibola) do not have updated data for the measure of Sexually Transmitted Infections. 

    To see the years of data used for all measures please visit the 2023 measures page.

    NEW! How did the 2020 census methodology impact County Health Rankings' data?

    The decennial census, an important source of data for monitoring population health, marked the 24th count of the U.S. population in 2020. Changes in methodology for the 2020 census resulted in population data that is not readily comparable to that of the 2010 census, which CHR&R has used in the calculation of a number of measures for the last decade. For example, 2020 was the first time that all households were invited to respond online. This census also introduced a new confidentiality protection called “differential privacy,” which is a mathematical transformation of the collected data with the goal of keeping individual’s information private. Another change to census methods in 2020 was the introduction of changes to the available options for reporting race and ethnicity.   

    These changes are a concern for CHR&R measures that rely on the census because we combine data from multiple years to provide reliable estimates for as many of the nation’s 3,143 counties as possible. Therefore, CHR&R has retained data for affected measures from the 2022 Rankings in the 2023 Rankings release. These measures include: Premature Death (YPLL), Premature Age-Adjusted Mortality, Life Expectancy, Child Mortality, Infant Mortality, Homicides, Suicides, Motor Vehicle Crash Deaths, Drug Overdose Deaths, Firearm Fatalities, Injury Deaths, Teen Births and Low Birthweight. 

    NEW! Are the 2020 congressional districts available on the state mapping feature?

    Yes. The new congressional district maps generated during the redistricting process based on the 2020 decennial census data are available for overlay on CHR&R state maps. For more information about redistricting and the availability of updated maps, please see the U.S. Census Bureau Redistricting Program page and this user note about Congressional and State Legislative Districts in Geographic Products.

    Are COVID-19 deaths included in the 2023 Rankings?

    Some COVID-19 deaths are included in the 2023 Rankings. The 2023 Rankings data communicate deaths recorded through the end of 2020, including deaths attributed to COVID-19. These deaths are reflected in the ranked measure of Premature Death (YPLL), and the unranked measures of Life Expectancy, Premature Age-Adjusted Mortality, Child Mortality and Infant Mortality. The 2023 Rankings do not include deaths attributed to COVID-19 during 2021 or 2022. To see the years of data used for all measures please visit the 2023 measures page

    Understanding the County Health Rankings Approach

    Where can I learn more about the County Health Rankings & Roadmaps model and frameworks?

    The County Health Rankings are based on a model of population health that emphasizes the many social, economic, physical, clinical and other factors that influence how long and how well we live.   

    The County Health Rankings model provides a graphical depiction of how we rank the health of communities. It also provides one way to think about the influence of various factors on health outcomes based on the best available evidence, while further serving as an important conversation starter about how to improve community health. This model is not intended to provide a complete picture of everything that influences health and equity. Find a downloadable graphic of the County Health Rankings model in English or Spanish in our Key Documents

    The Action Center - based on the Take Action model - provides a path to help your community move from data to action.

    The following citation should accompany these graphics if used:  

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

    Why rank counties' health?

    Ranking the health of counties using not only traditional health outcomes, but also the broad range of health factors, can mobilize action on the part of governmental public health and in many other sectors that can influence and are invested in community health. County rankings serve as a call to action for communities to: 

    1. Understand the health problems in their community.
    2. Encourage others to get involved in improving the health of communities.
    3. Recognize that factors outside health care influence health.

    Why are there separate rankings for Health Outcomes and Health Factors?

    We believe that there are two separate sets of messages to convey. One set (Health Outcomes) addresses how healthy a county currently is and the other (Health Factors) addresses how healthy a county might be in the future based on the many factors that influence health. When a single ranking of the “healthiest” counties is desired, we use the Health Outcomes rank.

    Why are counties ranked only within states?

    The purpose of the County Health Rankings is to provide actionable data at the county level with the goal of improving health outcomes for all and closing the health gaps between those with the most and least opportunities for good health. The County Health Rankings focus on state-specific county rankings and do not provide any county rankings across state boundaries. However, if a user would like to compare specific counties from different states, please visit the Compare Counties tool from the bottom of any state or county page. Users should refer to the 2023 Comparability Across States document to find measure-specific details. 

    How can I uncover disparities or inequities that may exist within a county?

    CHR&R data show that where you live matters to your health and that disparities exist within every state and county. We encourage communities to use the Rankings as a starting point to delve more deeply into data that can highlight disparities within counties and support dialogue on differences that are systemic, unfair and unjust. Learn more about how CHR&R defines race/ethnicity categories and which measures include data provide by race for American Indian, Asian, Black, Hispanic, and white populations. The disaggregated data do not provide an explanation for why differences exist between groups. Research increasingly demonstrates these gaps are due to structural racism. Communities can work to understand and highlight disparities by initiating a community health assessment or using the Rankings to draw attention to thorough assessments that have already been done.

    Our state already publishes county-level indicators - what is the value-added of the County Health Rankings?

    The County Health Rankings are designed as a call to action and users can link from any measure to related strategies in What Works for Health to learn about evidence-informed approaches to improve health and advance equity. Our Rankings follow this model built on published literature and follow our commitment to providing data on the many factors impacting health. The Rankings can serve as one of several data resources in state and local efforts to improve health and equity. 

    Representing People and Places in Data

    NEW! What happens when the names or boundaries for counties change?

    During the last decade, several counties have changed their name or boundary. These changes have occurred in Alaska, Connecticut, South Dakota and Virginia. Please Contact Us for more information about how this impacts CHR&R data and see this information from the U.S. Census Bureau: Substantial Changes to Counties and County Equivalent Entities

    County changes mean that data for these previous counties are no longer displayed on our website. However, data for these counties will continue to be available in the downloadable files for the years the counties existed.

    Where is residence reported for college students in census estimates?

    College students are encouraged to report their residence in the U.S. census as the place they live most of the time during the past year (>6 months of the year). Generally, this is the city/county where their college or university is located. Find more information and guidance on the Census here.

    Does County Health Rankings data include the experience of people living in the U.S. without documentation status?

    The inclusion of people living in the U.S. without documentation status is specific to each data source used in the CHR&R data. For example, data for births and deaths are provided by the National Center for Health Statistics registries and include all births and deaths in the United States. By contrast, the American Community Survey (ACS), another major data source included in CHR&R data, uses self-reported survey responses. The ACS is meant to include all persons with a usual residence in the U.S., however, as with all surveys the census is vulnerable to non-response bias and studies have found that questions of citizenship are sensitive and can be a reason someone may choose not to complete the ACS.

    If a county has a prison, are people who are incarcerated included in that county's Ranking?

    Are there similar platforms that provide data for smaller or larger geographic areas?

    Data at multiple geographic levels provides additional context and information.  

    Using County Health Rankings Data and Maps

    How are communities using the County Health Rankings?

    Community groups and leaders across the country are:

    1. Raising awareness in their community about the multiple factors that influence health via media interviews and follow-up conversations.
    2. Initiating community health assessment and planning efforts.
    3. Celebrating successes and promoting existing community health improvement efforts.
    4. Informing policy makers about the many factors that affect a community's health and about community health improvement planning.
    5. Revitalizing or refining existing community health improvement strategies.
    6. Citing the County Health Rankings as justification in securing grant funding to conduct community health improvement efforts and/or to address the determinants of health.

    Learn more about how to assess your community's needs and resources and focus on what's important via the Action Center


    How can the County Health Rankings help my community measure progress?

    A county’s rank tells a community how healthy it is today compared to other counties in the state, but a rank alone cannot fully capture progress. Because ranks are influenced by the health experiences of all counties within the state, they are not as helpful as a standalone measure of progress for a specific county. A county’s rank could get worse even though its health is getting better. For example, the Premature Death rate for Oklahoma County in Oklahoma improved by 2% between the 2017 Rankings and 2022 Rankings while its rank for Health Outcomes dropped by five places (from 23 to 28). People are living longer lives in Oklahoma County, but its rate of improvement has been outpaced by other counties in Oklahoma. 

    To examine progress, users could explore: 

    • Changes in specific measures over time: Look to the underlying measures to examine change over time. The trend graphs available for select measures illustrate how county trends compare to state and national trends. 
      Note: It is important to consider the error margins associated with each measure. When error margins overlap year-to-year, it is less likely that the county has experienced a change in health, even if the measure estimate has changed.  
    • Additional data sources and local information: Look for information from local data sources. These sources may contain data that can better capture the health needs and opportunities that are important for measuring progress in that community. 
    • A mixed-methods approach: Mixing qualitative and quantitative data can strengthen efforts to measure progress. Consider ways to collect additional information through interviews, focus groups or surveys, particularly for health factors or outcomes where changes happen more quickly, and trends can be more easily measured. These qualitative approaches can inform what should be measured and provide context to help interpret observed trends in quantitative measures. 

    How were Areas to Explore and Areas of Strength identified for my county?

    The Areas to Explore and Areas of Strength tool highlights measures that, respectively, are potential challenges that your community may want to examine more closely and measures where your community seems to be doing well. Accounting for the relative influence of each measure on health outcomes, the CHR&R team works to identify the Health Factor measures for your county that seem to have the greatest opportunity for improvement or are the assets your community might want to build on. We identified measures where there are meaningful differences between your county's values and either your state average, the national benchmark or the state average in the best state.

    As with your county’s ranks, these Areas to Explore are just one starting point for you to consider in your journey toward improving health in your community.

    How can I use the County Health Rankings mapping features?

    CHR&R maps provide optional overlays of large cities, state capitals and congressional districts. These layers provide additional information for users. Locating cities within counties can provide contextual information about the population density of a county and surrounding counties, and state capitals and congressional districts can help draw connections between places and power.

    Congressional district boundaries can help you identify who you may contact to help make policy changes in your area in addition to the county in which you reside. On each state page users have the option to overlay congressional districts on top of all ranked measures. Selecting this option will show the congressional districts for your state. You can then click a specific congressional district on the map (or select one from the pull-down menu) to zoom into the selected district and show the counties associated with that congressional district. The ranks or measure values of the counties associated with that congressional district appear in the box, sorted from lowest (best) to highest ranked. You can also see each county’s snapshot by clicking on the county name in the box.

    Users can also use this feature on the pages for individual measures: instead of seeing rank, you will be able to view the measure data in the selected congressional district. This information can be used to visualize health experiences within your congressional district and can be useful to share with your congressional representative or with other residents to identify geographic disparities within the district. Many congressional districts contain both high- and low-ranking counties. This information can be useful to improve health for all by identifying areas of high need and determining where to prioritize funding.

    What cities are displayed in the County Health Rankings maps?

    The cities displayed are those with a population of over 50,000 and those that are state capitals. The cities and state capitals that have a population of over 50,000 are included in the City Health Dashboard. Some smaller state capitals that have a population of less than 50,000 are not included in the City Health Dashboard.  

    City Health Dashboard provides health measures at the city level, which can complement CHR&R data.

      Understanding County Health Rankings Methodology

      How does County Health Rankings define rural and urban classifications?

      We define rural and urban classifications of urbanization as:

      • Rural (non-metropolitan counties with less than 50,000 people)
      • Smaller Metro (counties within a metropolitan statistical area ([MSA]) with between 50,000 and 1 million people)
      • Large Suburban Metro (non-central fringe counties within an MSA with more than 1 million people)
      • Large Urban Metro (central urban core counties within an MSA with more than 1 million people)

      How have changes to the BRFSS impacted the Rankings?

      We strive to provide our users with the most accurate and up-to-date data possible. As methods have improved from our data partners, we adapt to use their new estimates. The Behavioral Risk Factor Surveillance System (BRFSS) has been an important source of data since the inception of the Rankings, and we will continue to use their data moving forward. BRFSS has made updates to the methods used to create county-level estimates. We caution against using these estimates to compare to previous years or to track progress over time at the local level. A brief summary of BRFSS changes made over the years is below:

      • 2010-2015 Rankings: County estimates were derived from seven combined years of the most recent, unmodeled BRFSS survey data. The survey used only landlines for data collection at this time.
      • 2016-2020 Rankings: County estimates were derived from single-year, modeled BRFSS survey estimates, which included both cell phone and landline data for the first time. Compare different years of data from this time period with caution, as small area estimates are not designed for tracking progress.
      • 2021-Present Rankings: BRFSS has introduced a new multilevel regression and poststratification modeling system to produce their single-year modeled estimates. In addition, CHR&R began reporting age-adjusted measures for all BRFSS estimates in 2021, where previously only Health Outcome measures were age-adjusted.

      For measures based on several years of data, is recent data weighted more or is each year averaged equally?

      Each year's data are weighted equally.

      How are the ranks affected by lack of data?

      Some counties in the nation are too small to have reliable measurements for Health Outcome measures. These counties are not ranked. 

      If a county has data for enough measures to be ranked but is missing data for any other individual measure, we currently assign the county the same value as the state mean for that measure. One way to overcome unstable and unreliable estimates due to small numbers, such as with the measures from the National Center for Health Statistics, is to combine multiple years of data. This means that although the ranks are useful for differentiating between places that are more healthy or less healthy, ranks are not a good tool for setting objectives and tracking progress from year to year.

      How are race and ethnicity categories defined in County Health Rankings data?

      Race and ethnicity are different forms of identity but are sometimes categorized in non-exclusive ways. Race is a form of identity constructed by our society to give meaning to different groupings of observable physical traits. An individual may identify with more than one race group. Ethnicity is used to group individuals according to shared cultural elements. Racial and ethnic categorizations relate to health because our society groups individuals based on perceived identities. These categorizations have meaning because of social and political factors, including systems of power such as racism. Examining the variation among racial and ethnic groupings in health factors and outcomes is key to understanding and addressing historical and current context that underlie these differences. 

      Methods for defining and grouping race and ethnicity categories can differ between data sources and within data sources over time. To incorporate as much information as possible in our summaries, CHR&R race/ethnicity categories vary by data source. With a few exceptions, CHR&R adheres to the following nomenclature originally defined by The Office of Management and Budget (OMB)

      • American Indian & Alaska Native (AI/AN): includes people who identify as American Indian or Alaska Native and do not identify as Hispanic. 
      • Asian: includes people who identify as Asian or Pacific Islander and do not identify as Hispanic. 
      • Black: includes people who identify as Black or African American and do not identify as Hispanic. 
      • Hispanic: includes people who identify as Mexican, Puerto Rican, Cuban, Central or South American, other Hispanic, or Hispanic of unknown origin. 
      • White: includes people who identify as white and do not identify as Hispanic. 


      • Racial and ethnic categorization masks variation within groups. 
      • Individuals may identify with multiple races, indicating that none of the offered categories reflect their identity; these individuals are not included in our summaries. 
      • OMB categories have limitations and have changed over time, reflecting the importance of attending to contemporary racialization as a principle for examining approaches to measurement.  
      • For some data sources, race categories other than white also include people who identify as Hispanic.  

      Learn More: 

      The above definitions apply to all measures using data from the National Center for Health Statistics. For this data source, all race/ethnicity categories are exclusive so that each individual fits into only one category. 

      Other data sources offer slight nuances of the race/ethnicity categories listed above. The American Community Survey (ACS) only provides an exclusive race and ethnicity category for people who identify as non-Hispanic white. An individual who identifies as Hispanic and as Black would be included in both the Hispanic and Black race/ethnicity categories. Another difference with ACS data is the separate race categories for people who identify as Asian and people who identify as Hawaiian & Other Pacific Islander. For measures of Children in Poverty and Driving Alone to Work, CHR&R reports a combined estimate for the Asian & Other Pacific Islander categories, while we only report the Asian race category for Median Household Income. 

      Measures using data from the Center for Medicare and Medicaid Services (Mammography, Preventable Hospital Stays, Flu Vaccinations) follows the ACS categories with the exception of having a combined Asian/Pacific Islander category. For this data source, race and ethnicity are not self-reported. 

      The Stanford Education Data Archive used for the Reading and Math Scores measures follow the National Center for Education Statistics (NCES) definitions of Asian or Pacific Islander, American Indian & Alaska Native, non-Hispanic Black, non-Hispanic white, and Hispanic. 

      Which measures are missing data for my state?

      You may notice that some of the following measures do not appear in your snapshot. This could mean that data are not available for your state. The following 2023 measures do not have data available for the states listed:  

      • Drinking Water Violations (HI) 
      • HIV Prevalence (AK) 
      • High School Graduation (IL, TX) 
      • Reading Scores (AK, AZ, LA, MD, NM, NY, VT) 
      • Math Scores (AK, AZ, LA, MD, NY, VA, VT) 
      • School Funding Adequacy (HI, VT) 
      • Children Eligible for Free or Reduced Price Lunch (AK, AZ, DC, DE, IL, MA, MT, OH, OR, TN, VA) 
      • Juvenile Arrests (AZ, CT, ID, KS, KY, LA, MA, NC, ND, NH, NV, OK) 
      • Voter Turnout (AK)

      How are the trends for the trend graphs calculated?

      Our trends are estimated using linear regression for all years of data included in the graph. This sometimes creates unusual situations, particularly when a measure both improves and worsens over the time period. For example, in many counties, unemployment increased dramatically between 2007 and 2011. For the remainder of the decade, unemployment rates improved (i.e., rates declined) in many counties. However, the overall trend for the county reflects the average direction of change over the entire period.  

      For more information, see Measuring progress & change