Frequently Asked Questions

COVID-19 and the County Health Rankings

NEW! Are COVID-19 deaths included in the 2022 Rankings?

Yes. The 2022 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, infant mortality, and COVID-19 age-adjusted mortality. The 2022 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 2022 Measures page.

NEW! Where can I find the number of COVID-19 deaths in my county in 2020?

County Health Rankings has introduced two options for viewing COVID-19 deaths in the 2022 Rankings county snapshots. 

  1. Premature death: click on the measure title in your county snapshot to open the measure drawer. There you will find a table that contains the five leading causes of death before age 75 from 2020. Deaths attributed to COVID-19 before age 75 will also be displayed in this table. Please note that the categories in this table are mutually exclusive – deaths attributed to COVID-19 are not included in any other category of leading causes of death. 
  2. COVID-19 age-adjusted mortality: An unranked measure of all COVID-19 mortality from 2020 has been added to the county snapshot. This measure is an age-adjusted rate which allows for comparisons across counties with differing age-structures; the absolute number of deaths attributed to COVID-19 in 2020 is accessible in the data table for this measure. This measure will remain available for as long as COVID-19 persists as an important focus of community health.  

NEW! Does my 2022 rank reflect the impact COVID-19 has had on my county?

No. The 2022 Ranks do not reflect the full impact of COVID-19. However, the data show initial signs of the pandemic's influence. As in previous rankings, years of potential life lost before age 75 (YPLL-75) accounts for 50% of the CHR&R Health Outcomes rank. COVID-19 deaths occurring before age 75 during 2020 contribute to this metric. Although an explicit COVID-19 death measure is not ranked, the impact of COVID-19 is captured through YPLL-75.  

In addition to deaths, the pandemic impacted many Health Factors. Please visit the 2022 Measures page to review the data years used for each. Certain measures such as Unemployment, Children in poverty, and Median household income are based on a single year of data (2020 data in the 2022 Rankings) and may reflect pandemic-induced changes.  

NEW! Were any data sources affected by the pandemic?

The American Community Survey was delayed and received fewer responses due to the pandemic. Following the pandemic-related data collection disruptions, the Census Bureau revised its methodology to reduce nonresponse bias in data collected in 2020. After evaluating the effectiveness of this methodology, the Census Bureau determined the resulting data are fit for public release, government and business uses, and understanding the social and economic characteristics of the U.S. population and economy. Visit the Census Bureau updates for more information

NEW! Why aren’t COVID-19 deaths from 2021 and 2022 included in the 2022 Rankings?

The County Health Rankings include death data from the finalized National Center for Health Statistics (NCHS) dataset, which is released annually at the end of the following year (e.g., 2020 death data was released at the end of 2021) after careful review of all death records for completeness and quality. Data platforms reporting more real-time death data use provisional death data, which are subject to change as data become more complete. As a result, provisional death data are expected to differ from the final data. Final data are the most accurate and complete data available and are also comparable across states with different data reporting practices. More information on COVID-19 data from NCHS is available here.

NEW! Where should I go for the latest COVID-19 data?

County Health Rankings encourages users to visit their state and local health department resources, which can also be found on the Find More Data page, for the most up-to-date information on COVID-19.  

There are also helpful resources on the County Health Rankings COVID-19 page that can be useful to community leaders, practitioners, and policymakers navigating the path to an inclusive and equitable recovery including: 

  • The US COVID Atlas – provides robust data summarizing everything from the number of COVID-19 cases, deaths, vaccinations, and hospitalizations, to information such as the locations of community clinics. The tool connects COVID-19 case data and community indicators nationwide, including data from CHR&R, from the beginning of the pandemic to today. 
  • A searchable list of evidence-informed strategies from What Works for Health to help communities respond to and recover from COVID-19.

What should I know for 2022?

What are the suggested citations?

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

University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2022. 

NEW! What measures are new this year?

CHR&R has introduced seven new measures which can be found among the Additional Measures and do not contribute to the Ranks.  

  • COVID-19 age-adjusted mortality measures all deaths occurring between January 1, 2020 and December 31, 2020 due to COVID-19, and is reported as the age-adjusted rate per 100,000 population. 
  • Living wage is the hourly wage needed to cover basic household expenses plus all relevant taxes for a household of one adult and two children.  
  • Childcare cost burden represents childcare costs for a household with two children as a percent of median household income. 
  • Childcare centers is the number of childcare centers per 1,000 population under 5 years old. 
  • Gender pay gap is a ratio of women's median earnings to men's median earnings for all full-time, year-round workers, presented as "cents on the dollar" (i.e., women's median earnings in cents compared to every dollar, or 100 cents, of men's median earnings). 
  • School funding adequacy is the average gap in dollars between actual and required spending per pupil among public school districts. Required spending is an estimate of dollars needed to achieve U.S. average test scores in each district. 
  • School segregation is the extent to which students within different race and ethnicity groups are unevenly distributed across schools when compared with the racial and ethnic composition of the local population. The index ranges from 0 to 1 with lower values representing a school composition that approximates race and ethnicity distributions in the student populations within the county, and higher values representing more segregation. 

Six measures fall into the Social and Economic Health Factor areas with School segregation and School funding belonging to Education, Living wage to Employment, Childcare cost burden and Childcare centers to Family and Social Support, and Gender pay gap to Income. COVID-19 age-adjusted mortality is a Length of Life measure included in Health Outcomes.  

NEW! Are there changes to data sources or methods this year?

In 2022, the data source for the measures of Adult obesity, Diabetes prevalence, and Physical inactivity changed from the United States Diabetes Surveillance System to the Behavioral Risk Factor Surveillance System (BRFSS). These measures have also changed from crude to age-adjusted in the 2022 Rankings. The measures of Adult obesity and Physical inactivity are ranked and the measure of Diabetes prevalence is unranked. 

NEW! Why do some measures use the same data years as the 2021 release?

The most recently available data is used to calculate CHR&R measures. Some of the data sources have not released new data in time to be included in the 2022 Rankings. In these few cases, the measures feature data from previous years. For 2022, these include Insufficient sleep, Violent crime, Traffic volume, Math scores, Reading scores, and % rural. To see the years of data used for all measures please visit the 2022 Measures page

NEW! Why do BRFSS measures use different data years for New Jersey counties in the 2022 Rankings?

The 2019 Behavioral Risk Factors Survey (BRFSS) did not include estimates for New Jersey. The state did not collect enough BRFSS data to meet the minimum requirements for inclusion in the 2019 aggregate BRFSS dataset. The affected Rankings measures are listed below and use 2018 BRFSS data for New Jersey counties (all other counties use 2019 BRFSS data for these measures). 

  • Poor and fair health 
  • Adult smoking 
  • Adult obesity 
  • Poor physical health days 
  • Poor mental health days 
  • Excessive drinking 
  • Diabetes prevalence 
  • Physical inactivity 
  • Frequent physical distress 
  • Frequent mental distress 

NEW! Are the 2020 Congressional districts available on the CHR&R maps?

The new congressional district maps generated during the redistricting process based on the 2020 Decennial Census data are not yet available. As of April 2022, these maps were not yet finalized for all states. 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.  

NEW! Where can I find out what years of data are included in the 2022 Rankings?

To see the years of data used for all measures please visit the 2022 Measures page

How do I find my county's rank?

Health Outcome and Health Factor rankings are displayed in quartiles graphics at the top of each county snapshot. Each quartile contains 25% of the 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 without direct comparison of individual county ranks. County Health Rankings encourages users viewing a snapshot to reference the quartiles for overall comparison of counties within a state. County ranks can still be found in several places on the website:  

  • At the top of all county pages, just under the county name. 
  • On your 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. 

NEW! Have any measures been changed from crude to age-adjusted this year?

Yes. To make data more comparable across counties with different age structures, age-adjusted measures have been introduced for the following BRFSS measures this year: Adult obesity, Physical inactivity, and Diabetes prevalence. Age-adjusted measures have historically been used for the remaining BRFSS measures (e.g., Fair or poor health, Poor physical health days, Poor mental health days, Frequent physical distress, Frequent mental distress). The COVID-19 age-adjusted mortality measure introduced this year is also age-adjusted.  

NEW! How can I engage the CHR&R team?

The County Health Rankings & Roadmaps 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. 

NEW! Why does the National Findings Report use white men as a comparison group for equal pay when Asian men are the highest earners?

Though gender and racial diversity has increased among working adults over time, white men continue to make up the majority of the U.S. workforce. This has influenced workplace cultures and policies that tend to center the issues and opportunities of most importance to white men. In this context, white men have a social and economic advantage. Comparing the experiences of other groups to the experiences of white men supports health equity goals by providing a way to better understand how social advantage may impact earning potential and other opportunities for health. 

Even though Asian men are the highest earners in the U.S., their numbers and influence are small when compared with white men. Additionally, minoritized groups, including Asian men and women have experienced forms of marginalization and social disadvantage in society and in the workforce. Social disadvantage holds important relevance for health.  

It is also important to note that categorizing minoritized groups, such as Asian and Pacific Islander people does not represent the wide range of experiences, including those of native-born Americans, immigrants, and refugees, and also lumps together those who identify as Laotian, Taiwanese, Chinese, and Indian (along with many other identities) into the same race group. While the overall median of Asian male earners is higher than the median of white male earners, this doesn’t represent the experience of the entire group. 

NEW! Why does CHR&R use a household structure of one adult and two children for the Living wage measure?

The basic needs budget and living wage is characterized according to a one adult, two children household to better reflect how societal structures such as gender pay gap and minimum wages close opportunities for single adults, especially women, to provide support for children. Data and documentation for more household compositions can be found on the Living Wage Calculator

Understanding the County Health Rankings Approach

What and where are the frameworks on which the County Health Rankings & Roadmaps are based?

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 does not provide a complete picture of everything that influences health and equity. 

The Action Center - based on the Take Action model - provides a path to help your community move from data to action. To download model graphics, click on the County Health Rankings model and Take Action model.  

The following citation should accompany these graphics if used: 

University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2022. 

Why rank counties' health?

We rank counties to 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 medical care influence 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.

Why do you report two sets of rankings? Wouldn’t one set of rankings be clearer?

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. However, when a single ranking of the “healthiest” counties is desired, we use the Health Outcomes rank.

Why don't we rank counties across the nation as well as 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 focuses on state-specific county rankings and does 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 by selecting a state and then the “Compare Counties” tab. Users should refer to the 2022 Comparability Across States document to find measure-specific details. 

Why don’t you rank states as well as counties within states?

America’s Health Rankings ranks the health of states -- we have worked to align our measures as closely as possible with these Rankings.

Don't county-level rankings hide disparities that may exist within counties?

The County Health Rankings 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 may highlight disparities within counties. For example, the Dig Deeper section lists the measures where we provide data broken down by race for American Indian, Asian, Black, Hispanic, and white populations. The disaggregated data do not provide an explanation for why there are such wide differences 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. We have provided information in our guide to Using the Rankings Data for communities that need help getting started. 

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 – the use of ranks can often serve as a more effective tool for drawing attention to community health issues than lengthy listings of indicators. We encourage any community that has not already done so to use the Rankings as a tool to engage community members in a more detailed community health assessment, using whatever additional data sources they have available. The Rankings can be used to inform areas where more in-depth analysis might be helpful.

What is Included in the County Health Rankings?

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

During the last decade, several county definitions have changed. These changes have occurred in Alaska, South Dakota, and Virginia, and include county name and boundary changes and the deletion of some counties. Please Contact Us for more information about how this impacts County Health Rankings 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 ‘old’ counties are no longer displayed on our website.  However, data for ‘old’ counties will continue to be available in the downloadable files for the years the counties existed.  


Can local communities use the County Health Rankings measures that come from modeled estimates to track progress?

To make the best, most appropriate use of the Rankings data, it is important to understand how the measures are created and how the underlying data were collected and processed. Measures created from modeled estimates, such as the BRFSS measure of adult smoking, can have specific drawbacks regarding their usefulness in tracking progress in communities. Modeled data like these are not particularly good at capturing the effects of local conditions such as health promotion policies or unique population characteristics. Evaluation of local health promotion efforts can benefit from the use of additional data sources, particularly local community information, to measure effects of interventions or changes over time. Visit Measuring Progress to learn more.  

Where is residence reported for college students in Census estimates?

College students are encouraged to report their residence in the US 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. For more information on the Census, see their guidance.

Do the 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 County Health Rankings. 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 the County Health Rankings, uses self-reported census information. The ACS is meant to include all persons with a usual residence in the U.S., however, as with all surveys the census is prone to non-response bias and studies have found that immigration concerns can be a reason someone may choose not to complete the census.   

If a county has a prison, are prison inmates included in that county's Rankings?

How to Use 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 the general community about the multiple factors that influence health via media interviews and follow-up conversations.
  2. Initiating community health assessment and planning efforts where none previously existed.
  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.

Visit the Community Stories section to learn more.

Should counties primarily work on the areas where their rankings are lowest?

There is not one formula for where communities should put their efforts. Because the County Health Rankings are based on broad measures and include multiple years of data, it is important for communities to look at further information prior to making a decision about next steps. Learn more about how to assess your community's needs and resources and focus on what’s important via the Action Center.

How can data at varying geographic levels be helpful?

Data at multiple geographic levels provides additional context and information. 

  • Data for smaller geographies, such as from City Health Dashboard, can provide important information on local patterns which may not be visible at the county level. 
  • Data summarized by typology or larger geographies, such as from America’s Health Rankings, can provide important context about health experiences shared across similar places or larger geographies. 

Can I compare my county's ranks and measures with those for a county in a different state?

Each county's ranks are calculated within a specific state so a county's rank cannot be compared with the rank for a county in a different state. However, the values for the Health Outcomes measures can be compared from one state to another. Caution should be taken in comparing the Health Factors measures across states because many of the measures for Health Factors are only uniform within states and not across states. To compare specific counties from different states, please visit the Compare Counties tool by selecting a state and then the “Compare Counties” tab. Users should refer to the guidelines for comparing measures across states for measure-specific details

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 actual 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 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 their methods: Ranks can be influenced by the introduction of new measures or a change in the methods for existing 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 Why Ranks Change

You can contact us through the ‘Contact Us’ button on the website with any specific questions regarding why your county’s rank changed. 

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 Bexar County in Texas (home to San Antonio) improved by 6 percent between the initial 2010 Rankings and 2015 while its rank for Length of life dropped by eight places (from 58 to 66). People are living longer lives in Bexar, but its rate of improvement has been outpaced by other counties in Texas. 

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.  
  • Diverse 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. 
  • 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 selected for my county?

The Areas to Explore and Areas of Strength highlight 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 County Health Rankings team works to identify the Health Factor measures for your county that seem to have the greatest potential 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. Using the Data provides suggestions for other sources of state and local data that you can use to examine these measures more closely.

How can I use the mapping features on

Map of Texas with a congressional district selected

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 have 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 layer features are available in the County Health Rankings maps?

The County Health Rankings maps provide optional overlays of the 500 most populous cities as well as congressional districts. Both layers provide additional information for users. Locating cities within counties can provide contextual information about the population density of a county and surrounding counties. Congressional district boundaries can help you identify who you may contact to help make policy changes in your area in additional to the county in which you reside.

What cities are displayed in the County Health Rankings maps?

The cities displayed are those with populations over 66,000 population. These cities correspond to those included in City Health Dashboard. City Health Dashboard provides health measures at the city level which can complement data from County Health Rankings.

Understanding the Methodology

NEW! How does CHR&R define levels of urbanization?

We define levels 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 BRFSS has been an important source of data since the inception of the Rankings, and we will continue to use their data moving forward. Behavioral Risk Factor Surveillance System (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 the changes they have made over the years is summarized below:

  • 2010-2015 Rankings: County estimates were derived from the 7 most recent years of direct BRFSS survey data.
  • 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. Even during this timeframe comparing different years of data should be done with caution, as small area estimates are not designed for tracking progress.
  • 2021 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, where previously only Health Outcome measures were age-adjusted.

Did the County Health Rankings team calculate all the measures in these reports?

No, although we calculate many of the measures used in the Rankings with raw data provided by our partners (e.g., National Center for Health Statistics) many measures are also calculated by partner organizations. For example, the Behavioral Risk Factor Surveillance System estimates are calculated by staff at the Center for Disease Control and Prevention and the Preventable Hospital Stays measure is calculated by staff at the Centers for Medicare & Medicaid Services. 

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.

Are the Rankings affected by lack of data?

Some counties in the nation are too small to have reliable measurements for health outcome measures. Those counties are not ranked. If a county has data for enough measures to be ranked but is missing data for any 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 (NCHS), is to combine multiple years of data. This means that although the Rankings are useful for differentiating between places that are and are not healthy, they 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?

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 sorts groups of 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.

Data sources differ in methods for defining and grouping race and ethnicity categories. 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 (AIAN): 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 for Median Household Income we only report the Asian race category.

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.

How do crude and age-adjusted rates differ?

County Health Rankings includes both crude and age-adjusted rates. Age-adjustment is a useful strategy for a more ‘apples to apples’ comparison of health measures between counties because it accounts for potential age group differences in the makeup of communities. However, it can also mask the true burden of a health need in a county, regardless of age. Due to these considerations, only some measures in the Rankings are age-adjusted. The following Health Outcome measures are age-adjusted: Premature Death (YPLL), Fair or Poor Health, Physically Unhealthy Days, and Mentally Unhealthy Days. The Health Factor measures of Adult Smoking, Excessive Drinking, and Insufficient Sleep, Preventable Hospital Stays, Flu Vaccinations, and Suicides are also age-adjusted.

Why is a measure missing from my snapshot?

You may notice that some of the following measures may not show up in your snapshot. This is because data are not available for your state. The following states do not have data for the respective measures in 2022:  

  • Drinking water violations (HI) 
  • HIV prevalence (AK) 
  • High school graduation (IL, UT) 
  • 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 (DC, DE, MA) 
  • Juvenile arrests (AZ, CT, ID, KS, KY, LA, MA, NC, ND, NH, NV, OK) 

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 Understanding Trend Over Time