Frequently Asked Questions

What should I know for 2021?

NEW! Are COVID-19 deaths included in the 2021 Rankings?

No. The 2021 Rankings include all deaths through 2019. The first death attributed to COVID-19 in the US occurred in early 2020. We anticipate the 2022 Rankings will include mortality data from the year 2020 and will reflect deaths attributed to COVID-19 in that year. To see the years of data used for all measures please visit our 2021 Measures.

NEW! Does my 2021 rank reflect the impact COVID-19 has had on my county?

No. The data we used to calculate ranks for the 2021 Rankings are from 2019 and earlier. Therefore, the data in the latest Rankings are not yet reflective of the impact that COVID-19 has had on counties. However, the 2021 Rankings demonstrate the variation of health and opportunity by place and can highlight barriers to health which disproportionately affect communities of color and those with lower incomes. COVID-19 has likely worsened these disparities.COVID-19 will likely have an impact on measures such as unemployment, children in poverty, income inequality, premature age-adjusted mortality, food insecurity, and severe housing cost burden. We will continue to report these measures to focus on the entire impact COVID-19 has and will have on health in a community.

NEW! Were any data sources affected by COVID-19?

Our data represents time before the emergence of the COVID-19 pandemic (2019 and earlier). To see the years of data used for all measures, please visit our 2021 Measures.

NEW! Where are the Key Findings Report and State Reports for this year?

We have decided to forgo publishing the Key Findings Report and State Reports this year. The intent of this altered release is to offer public health partners an opportunity to access refreshed data, without pulling focus from the continuing COVID-19 response and recovery. The 2022 Rankings release will return to our usual Rankings approach complete with national and state reports.

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

Yes. Three changes are notable. First, the Behavioral Risk Factor Surveillance System (BRFSS) has made updates to the methods used to create their county-level estimates. This means that comparing years of data over time may be inappropriate. In addition, all BRFSS measures (both Health Outcomes and Health Factors) are now age-adjusted, whereas previously only measures included as Health Outcomes had been. See the FAQ on age-adjustment changes to learn more.

A second change introduced this year is the replacement of High School Graduation with High School Completion as a ranked measure. This change improves data quality and comparability across states. High School Graduation is still included as an additional measure. Learn more about our weights and how we calculate the rankings

A third change is for the measure of Children in Single-Parent Households. The American Community Survey now reports cohabitating households separate from single-parent households, so that cohabitating households are no longer reflected in this measure.

NEW! Why do some measures use the same data years as last year's release?

We use the most recently available data. Some of our data stewards have not released new data in time to be included in the 2021 Rankings. In these few cases, the measures are featured without new data, such as this year’s Access to Exercise Opportunities and Violent Crime.

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, we have introduced age-adjusted estimates for the following BRFSS measures this year: Adult Smoking, Excessive Drinking, and Insufficient Sleep. We have historically used age-adjusted estimates for the remaining BRFSS measures (i.e., Fair or Poor Health, Poor Physical Health Days, Poor Mental Health Days, Frequent Physical Distress, and Frequent Mental Distress).

NEW! Where can I find out what years of data are included in the 2021 Rankings?

The years of data used for each measure are all available on our website.

NEW! How do I find my county’s rank?

We encourage a focus on the data underlying the ranks, and not the ranks themselves. This year, we have displayed data in quartiles to support comparison of a county to a similar grouping in your state, instead of comparing difference in individual ranks which might not be statistically meaningful. Looking at the underlying data and how those data have changed over time provides a better picture of your county's progress. You can still find your county’s rank in several places on the website: 

  • Select the “Show Rankings” option from either a county snapshot or measure page. This option is available on the left side of the page, above where you see all the counties within a specific state listed alphabetically.
  • From your state page or county snapshot, select the Overview tab to see your state Health Outcome and Health Factors maps. Hover over a county to see its rank.
  • From your state page, select the Rankings tab to see your state Health Outcomes map. You can use the orange drop down on the left to find additional maps and ranks within Health Outcomes (i.e., Length of Life and Quality of Life) and within Health Factors (i.e., Health Behaviors, Clinical Care, Social & Economic Factors, and Physical Environment). In each case, hover over a county in the map to see its specific rank. 
  • Download the complete Rankings file for your state or the nation. 

NEW! What measures are new this year?

This year, we have introduced two new measures:

  1. Broadband Access is the percentage of households with a broadband internet connection. It is important because access to reliable, high-speed internet can improve health by supporting access to education, employment, and health care opportunities as well as fostering social connectedness.
  2. High School Completion is included as the percentage of the population ages 25 and over with at least a high school diploma or equivalent. High school completion replaces the measure of High School Graduation in the ranked measures and provides an improvement in data quality and comparability across states.

NEW! Why has CHR&R changed its approach to Action Learning Coaching?

RWJF decided to sunset funding for community coaching and increase funding for innovation regarding data and evidence to advance health equity. The County Health Rankings & Roadmaps will continue to serve as a curator of community health and equity improvement resources and will connect program data, evidence, guidance to organizations engaged in local power building and community health improvement efforts.

Our staff are available for speaking engagements, presentations and media interviews that highlight our resources and tools. And we can help you navigate the many resources we have available across our website to support you on your journey to create healthy, equitable communities. Click the Contact Us button on the bottom of any page on our site to get in touch with a CHR&R team member.

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

We encourage people to visit their state and local health department resources for the most up-to-date information on COVID-19. There are also helpful resources on the Rankings COVID-19 page that can be useful to community leaders, practitioners, and policymakers navigating the path to an inclusive and equitable recovery. You will find links to The US COVID Atlas - a robust data resource measuring everything from the number of COVID cases, deaths, vaccinations, and hospitalizations, to identifying where community clinics are. County Health Rankings measures are also featured to provide important community context about the conditions that contribute to health in a given community. Geographic overlays also showcase disproportionately impacted communities, such as hyper-segregated cities and Native American tribal lands, to draw attention to how these areas have also been routinely excluded from opportunity.

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 relative contributions of various factors to a specific set of 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 impacts or could potentially impact health or equity or their many interactions at the community level.

The Action Center was originally based on the Take Action model that provides a path to help your community move from data to action. However, it is important to keep in mind that action isn’t always linear. 

Click on the County Health Rankings model and our Take Action graphic to access these graphics. The following citation should accompany these graphics if used:

University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2021.

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. We don’t rank counties across the nation because we believe that a national report would only draw attention to the healthiest and least counties across the nation. The Rankings provide a tool for all communities in each state to identify opportunities for improvement.

We focus on state-specific county rankings and do not provide any county rankings across state boundaries. However, if you would like to compare specific counties from different states, please visit our Compare Counties tool by selecting a state and then the “Compare Counties” tab. Users should refer to our 2021 Comparability Across States document to find the differences that occur for some measures (e.g., high school graduation rates and violent crime).

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?

What are the counties recently added in Alaska, South Dakota and Virginia? What happened to the counties that no longer exist there?

During the last decade, several county definitions have changed due to mergers with another county, being dissolved and distributed into other counties, or undergoing a name change.

In the descriptions of the county changes below 'old' counties that no longer exist are italicized, while 'new' counties that are now included in the Rankings are bolded.

In Alaska:

  • Prince of Wales – Outer Ketchikan Census Area was dissolved and distributed into other counties including Ketchikan Gateway Borough, Prince of Wales-Hyder Census Area, and Wrangell City and Borough
  • Skagway-Hoonah-Angoon Census Area was split into Hoonah-Angoon Census Area and Skagway Municipality
  • Wrangell-Petersburg Census Area was split into Hoonah-Angoon Census Area, Petersburg Borough, and Skagway Municipality
  • Wade Hampton Census Area was renamed Kusilvak Census Area

In South Dakota:

  • Shannon County was renamed Oglala Lakota County

​In Virginia:

  • Bedford City was absorbed into Bedford County. The new Bedford County has the same name as when these counties were separate; however, measures over time may not be consistent since the county composition has changed.

These changes mean that data for these ‘old’ counties are no longer displayed on our website; therefore, if a county was ranked prior to 2017, there may appear to be a gap in ranks for that year on our website. However, data for these ‘old’ counties will continue to be available in the files available for download for the years these counties existed. For more detailed information on the county changes (and/or FIPS code changes) listed above, please see

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 your Rankings data, it is important to understand how the measures you are interested in are created and where the information comes from. Measures created from modeled estimates, such as BRFSS measures of adult smoking, can have specific drawbacks regarding their usefulness in tracking progress in communities. Modeled data like these are not particularly good at generating estimates that incorporate the effects of local conditions such as health promotion policies or unique population characteristics. Counties trying to measure the effects of programs and policies should take caution when using modeled estimates and look to other data sources, particularly local community information, that can help to understand the effects of interventions or changes over time. To explore how you can use individual measures to track progress in your community, visit the “Learn More About this Measure” link on each measure page in your county snapshot.

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.

Are immigrants who are documented and undocumented included in County Health Rankings estimates?

The inclusion of documented and undocumented immigrants is specific to each data source used in the County Health Rankings. Our data sources attempt to capture all individuals living in a community regardless of immigration status. For example, data for births and deaths include both documented and undocumented immigrants because the National Center for Health Statistics records virtually all births and deaths in the United States. By contrast, the American Community Survey, another major data source included in the County Health Rankings uses self-reported census information, which may not capture documented or undocumented immigrants in estimates produced by this data source.

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 disparities that may be masked at the county level.
  • Data for more refined or larger geographies, such as from America’s Health Rankings, can provide important context such as comparison values.
  • Data may be available at one level of geography, such as the county, and not for another, for example the census tract.

For more information see our Action Learning Guides:

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 you cannot compare your county's ranks with those for a county in a different state. However, you can compare the values for the Health Outcomes measures from one state to another. We advise caution in comparing the Health Factors measures across states because many of our measures for Health Factors are only uniform within states not across states. If you would like to compare specific counties from different states, please visit our Compare Counties tool by selecting a state and then the “Compare Counties” tab. Users should refer to our guidelines for comparing measures across states to find the differences that occur for some measures (e.g., high school graduation rates and violent crime).

Why did my county’s rank change?

Ranks can improve or worsen for one or more reason:

  • 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 rank may also improve or worsen not due to change in your own county’s measures, but rather because of changes in counties ranked just above or below your county within the state.
  • Random variation in measures: 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 current measures.

In order to better understand why your county’s rank may have changed from the previous year, the best place to start is by examining the individual measures and z-scores (that standardize each measure within each state to the average of counties in that state transforming them to the same metric—a mean (average) value of 0 and a standard deviation (measure of spread) of 1) that comprise the rank. When examining each of these underlying components, it is helpful to explore the following:

Your county’s measures over time;

Are measure values increasing, decreasing, or staying the same? For instance, take a look at the trend graph for your county’s premature death estimate. Is premature death in your county increasing, decreasing, or staying the same? How does your county’s  trend compare to the state or national trend? Looking more closely at changes over time in your county’s underlying estimates can help you better understand your county’s progress and potential influence on the change in your rank.

The error margins associated with your county’s estimates.

Another thing to consider is the error associated with the measures comprising the rank. Year-to-year, even if your county’s true rate does not change, there will be some fluctuation in the measure due to random variation. For instance, it is possible to see substantial change in your county’s premature death rate from the previous year, but if the rate is within the margin of error for the previous year’s premature death rate, the change may be partially or almost completely due to random fluctuation in measures from year-to-year.

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 its state, but a rank alone cannot fully capture progress. Because ranks are dependent on how other counties are doing, they are not as helpful as a standalone measure of progress. A county’s rank could actually 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 from our initial 2010 Rankings to 2015 while its rank for length of life dropped by 8 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, we suggest exploring:

Changes in Specific measures over time
Look to the underlying measures to examine change over time. For instance, take a look at the trend graph for your county’s premature death rate and see how your county trends compare to state and national trends. It is also important to consider the error margins associated with each measure. Even if a county’s true rate does not change, there may be some year-to-year fluctuation due to random variation in the estimate.

Diverse data sources and local information
Look for information from existing local data sources. These sources may contain measures that can better capture the health needs and opportunities that are important to measuring progress in your community.

Mixed methods approaches
You will probably not be able to measure progress fully with a simple quantitative approach. Consider ways to collect additional information through interviews, focus groups, or surveys, particularly for near-term progress measures. 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 new mapping features on

Screenshot of Health Outcomes & Factors of 15th Congressional District of Texas

On the homepage for each state, users have the option to overlay congressional districts on top of the county health outcome and health factor maps. Selecting this option will show the congressional districts for your state. You can then click on 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 of the counties associated with that congressional district appear in the box, sorted lowest (best) to highest ranked. You can also 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 for the selected measure in the congressional district you selected.

This information can be used to see how health differs within your congressional district. This information can be useful to share with your congressional representative or with other residents in order 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/or 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.

What’s Inside the Rankings? Understanding the Methodology

NEW! 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.

NEW! 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.

NEW! 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 2021: 

  • Juvenile arrests (CA, CT, ID, IN, KS, KY, LA, ME, MA, MI, NV, NH, ND, TN, WY)
  • Reading scores (AK, AZ, LA, MD, NM, NY, VT)
  • Math scores (AK, AZ, LA, MD, NY, VT, VA)
  • High school graduation (UT)

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 depends on the relative magnitude of worsening to improvement. For example, even if your county had improving rates after 2011, but had higher rates of worsening in the years prior, it might still show an overall worsening trend.