Frequent Mental Distress*

Data Source

Behavioral Risk Factor Surveillance System

The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based random digit dial (RDD) telephone survey that is conducted annually in all states, the District of Columbia, and U.S. territories. Data obtained from the BRFSS are representative of each state’s total non-institutionalized population over 18 years of age and have included more than 400,000 annual respondents with landline telephones or cellphones since 2011. Data are weighted using iterative proportional fitting (also called "raking") methods to reflect population distributions. For the County Health Rankings, data from the BRFSS are used to measure various health behaviors and health-related quality of life (HRQoL) indicators. HRQoL measures are age-adjusted to the 2000 U.S. standard population.

Prior to the 2016 County Health Rankings, up to seven survey years of landline only BRFSS data were aggregated to produce county estimates. However, even with multiple years of data, these did not provide reliable estimates for all counties, particularly those with smaller respondent samples. For the 2016 County Health Rankings and beyond, the CDC produced county estimates using single-year BRFSS data and a multilevel modeling approach based on respondent answers and their age, sex, and race/ethnicity, combined with county-level poverty, as well as county- and state-level contextual effects.¹ To produce estimates for those counties where there were no or limited data, the modeling approach borrowed information from the entire BRFSS sample as well as Census Vintage population estimates. CDC used a parametric bootstrapping method to produce standard errors and confidence intervals for those point estimates. This estimation methodology was validated for all U.S. counties, including those with no or small (< 50 respondents) samples.² This same method was used in constructing the 500 cities study, which includes BRFSS data for the 500 largest cities in the U.S. and can be found here: https://www.cdc.gov/500cities.

For the 2021 Rankings, the CDC has updated their modeling procedure for producing small-area estimates. With the PLACES project, a multilevel statistical modeling framework using multilevel regression and poststratification (MRP) is performed for small-area estimation that links BRFSS data with high spatial resolution population demographic and socioeconomic data from the Census’ American Community Survey (ACS). The CDC has performed internal and external validation studies, which confirm strong consistency between their model-based estimates and the direct BRFSS survey estimates at both the state and county levels. For more technical information on the PLACES modeling procedure, please see their website.³

¹Zhang X, Holt JB, Lu H, Wheaton AG, Ford ES, Greenlund K, Croft JB. Multilevel regression and poststratification for small-area estimation of population health outcomes: a case study of chronic obstructive pulmonary disease prevalence using the Behavioral Risk Factor Surveillance System. American Journal of Epidemiology 2014;179(8):1025–1033.

²Zhang X, Holt JB, Yun, S, Lu H, Greenlund K, Croft JB. Validation of multilevel regression and poststratification methodology for small area estimation of health outcomes. American Journal of Epidemiology 2015;182(2):127-137.

³PLACES Project. Centers for Disease Control and Prevention. Accessed March 9, 2021. https://www.cdc.gov/places.

Website to download data
For more detailed methodological information

Frequent Mental Distress is a percentage

Frequent Mental Distress is the percentage of adults who reported 14 or more days in response to the question, "Now, thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?"

Frequent Mental Distress is age-adjusted

Age is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. We report an age-adjusted rate in order to fairly compare counties with differing age structures.

The method for calculating Frequent Mental Distress has changed

The CDC provides single-year modeled county-level estimates that include both landline and cell phone users. Beginning with the 2021 Rankings, the CDC has updated their modeling procedure for producing small-area estimates. These changes were implemented in order to provide users with the most accurate estimates of health in their community as possible.

Frequent Mental Distress estimates are created using statistical modeling

Statistical modeling is used to obtain more informed and reliable estimates than survey data alone can provide. Modeling generates more stable estimates for places with small numbers of residents or survey responses. Frequent Mental Distress estimates are produced from one year of survey data and are created using complex statistical modeling. For more technical information on PLACES modeling using BRFSS data, please see their methodology.¹

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 assumptions about statistical relationships that may not hold in all cases. Finally, there is no perfect model and each model generally has limitations specific to their methods.

Numerator

The numerator is the number of adults who reported 14 or more days in response to the question, “Now, thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?”

Denominator

The denominator is the total number of adult respondents in a county.

This measure can be used to track progress, but only after considering its substantial limitations. Changes to the methodology to create the estimates were implemented in the 2021 Rankings, making 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, especially 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.

Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:

• Age
• Gender
• Race
• Education
• Income
• Subcounty Area

The PLACES Project provides county-, city-, census tract-, and zip code-level small-area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use, including Frequent Mental Distress, across the United States.

For larger counties, you can access county- or MSA-specific data from the CDC at http://www.cdc.gov/brfss/smart/smart_data.htm. However, using this data requires somewhat advanced analytic capabilities. In many states, you can access county-level BRFSS estimates, and in some cases you can stratify those estimates by age, gender, education, income, or race. You can find BRFSS resources for most states in our Data beyond the Rankings section.

¹ PLACES Project. Centers for Disease Control and Prevention. Accessed March 9, 2021. https://www.cdc.gov/places.