Percentage of adults aged 20 and above with diagnosed diabetes.

The 2019 County Health Rankings used data from 2015 for this measure.

Reason for Including

Diabetes is an important marker for a range of health behaviors. This can be a valuable source of data for communities in understanding the toll that risky health behaviors can take on their population and health care system.

Key Measure Methods

Diabetes Prevalence is a Percentage

Diabetes Prevalence is the percentage of adults aged 20 and above with diagnosed diabetes in a given county.

The Method for Calculating Diabetes Prevalence Changed

Data for Diabetes Prevalence are provided by the CDC Interactive Diabetes Atlas which uses BRFSS data to provide county-level estimates. Beginning with the 2015 County Health Rankings, Diabetes Prevalence estimates include both landline and cell phone users. Previously, only landline users were included in the data. This change was implemented in order to provide users with the most accurate estimates of health in their community as possible.

Diabetes Prevalence Estimates are Created Using Statistical Modeling

The calculation of Diabetes Prevalence uses three years of survey data to create a single-year estimate using a complex statistical model. The year the estimate represents is the middle year of the three years of data used.

Modeling generates more stable estimates for places with small numbers of residents or survey responses. There are also drawbacks to using modeled data. The smaller the population or sample size of a county, the more the estimates are derived from the model itself and the less they are based on survey responses. Models make statistical assumptions about relationships that may not hold in all cases. Finally, there is no perfect model and each model generally has limitations specific to their methods.

Caution Should Be Used When Comparing These Estimates Across State Lines

The model used to create these estimates includes a state-level factor that limits comparability between neighboring counties of adjacent states.


The numerator is the number of adults 20 years and older who responded "yes" to the question, "Has a doctor ever told you that you have diabetes?" Women who indicated that they only had diabetes during pregnancy were not considered to have diabetes.


The denominator is the total number of respondents (age 20 and older) in a county.

Can This Measure Be Used to Track Progress

This measure could be used to measure progress, but only after considering its substantial limitations. Methodological changes in the Behavioral Risk Factor Surveillance System, which are discussed above and were implemented in the 2015 Rankings, make comparisons with estimates prior to that release year difficult. In addition, current estimates are produced using sophisticated modeling techniques which make them difficult to use for tracking progress in small geographic areas.

Modeled estimates have specific drawbacks with regard to their usefulness in tracking progress in communities. Modeled data are not particularly good at incorporating the effects of local conditions, such as health promotion policies or unique population characteristics, into their estimates. Counties trying to measure the effects of programs and policies on the data should use great caution when using modeled estimates. In order to better understand and validate modeled estimates, confirming this data with additional sources of data at the local level is particularly valuable.

Data Source

Years of Data Used


CDC Diabetes Interactive Atlas

The National Diabetes Surveillance System provides county-level estimates of obesity, physical inactivity, and diabetes using three years of data from CDC's Behavioral Risk Factor Surveillance System (BRFSS) and data from the U.S. Census Bureau’s Population Estimates Program. The county-level estimates are based on indirect model-dependent estimates. Bayesian multilevel modeling techniques are used to obtain estimates.

Digging Deeper
Age 1
Gender 1
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Income 1
Subcounty Area 1

The 500 Cities project provides city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use, including diabetes prevalence, for the largest 500 cities in the United States.

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