% Disability: Functional Limitations*

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 United States 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. Data from the BRFSS are used to measure various health behaviors and health-related quality of life (HRQoL) indicators in the Health Snapshots and downloadable datasets. HRQoL measures are age-adjusted to the 2000 U.S. standard population.

Prior to the 2016 Annual Data Release, 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 Annual Data Release 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.

For the 2021 Annual Data Release, 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

% Disability: Functional Limitations is a percentage

% Disability - Functional Limitations is the percentage of the population aged 18 and over who reported difficulty in hearing, vision, cognition, mobility, self-care, or independent living.

% Disability: Functional Limitations estimates are created using statistical modeling

Surveys collect information about a limited portion of a population. Statistical modeling can be used to predict how people who share certain characteristics with those surveyed may have responded to the survey. Modeling can increase the power of survey data by generating more stable estimates for places with small numbers of residents or survey responses. The % Disability: Functional Limitations 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.

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 its methods.

Caution should be used when comparing these estimates across states

BRFSS survey data are collected independently by each state, which could result in data collection differences.

% Disability: Functional Limitations should be compared with caution across counties

Disability as measured by functional limitations becomes more likely with aging. This measure is not age-adjusted which means that these data may not be comparable across counties if the age distribution of the county populations are different from each other.

Measure limitations

These data collected in the BRFSS survey underestimate the true number of people with disabilities because the questions emphasize “serious” difficultly doing functions, asks only about specific types of tasks or activities and may incorrectly represent people with temporary disabilities. This measure also uses functional limitations to define disability, which does not capture the full range of people with disabilities; especially those with psychiatric disabilities, developmental disabilities and chronic conditions.²

Numerator

The numerator is the number of respondents who answered ‘yes’ to at least one of the six following questions:

• “Are you deaf or do you have serious difficulty hearing?”
• “Are you blind or do you have serious difficulty seeing, even when wearing glasses?”
• “Because of a physical, mental, or emotional condition, do you have serious difficulty concentrating, remembering, or making decisions?”
• “Do you have serious difficulty walking or climbing stairs?”
• “Do you have difficulty dressing or bathing?”
• “Because of a physical, mental, or emotional condition, do you have difficulty doing errands alone such as visiting a doctor´s office or shopping?”

Denominator

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

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

There are several methods to try to get more specific data than the county level. For larger counties, you can access county- or MSA-specific data from the CDC. However, using these data requires somewhat advanced analytic capabilities.

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 % Disability - Functional Limitations, across the United States.

In many states, you can access county-level BRFSS estimates, and in some cases, you can stratify those estimates by age, gender, income, education, or race.

1. Centers for Disease Control and Prevention. Disability and health data system. Behavioral Risk Factor Surveillance System data. 2024.
2. Swenor B, Landes S, Hall J. Millions of people are missing from U.S. disability data. STAT. September 9, 2024.