At A Glance
Noteworthy Characteristics
- Annual data collection.
- Random sample.
- Has large sample sizes nationally and for many states.
- Large sample sizes are available for American Indians/Alaska Natives (AI/ANs) and Native Hawaiian/Pacific Islanders (NH/PIs).
- State-specific modules cover different topics (e.g., sleep) in select years.
- Includes state-level and selected metropolitan statistical area-level data.
Website
Purpose
To collect state-specific data about preventive health practices and risk behaviors linked to chronic disease, injuries, and preventable infectious disease for adults in the United States (U.S.).
Target Population
Adults living in households in all 50 U.S. states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, Guam, American Samoa, and Palau.
Conducted
Began in 1984. Conducted annually. Most recent year conducted was 2017. Data are available for all years through 2018. Questions may vary over time.
Sponsor
Centers for Disease Control and Prevention, U.S. Department of Health and Human Services
Special Note(s)
Data are available for states and select cities and communities. Because BRFSS is conducted individually by state health departments, the questionnaire can vary from state to state. However, there is a standard data collection method.
BRFSS uses telephone interviews only. Data may not be representative of individuals without telephones (which is about 3% of the U.S. population). Starting in 2011, BRFSS implemented several modifications to its weighting methods and modes of data collection, including the addition of cellular telephone surveys. Additional information on these changes and potential implications are available here: Methodologic Changes in the Behavioral Risk Factor Surveillance System in 2011 and Potential Effects on Prevalence Estimates.
The 2018 BRFSS data continues to reflect the changes initially made in 2011 in weighting methodology (raking) and the addition of cell phone only respondents.
Contact information for BRFSS state coordinators.
Sampling
Sample Design
Cross-sectional survey with probability sampling.
Learn more about the sampling design.
Sample Size
Approximately 432,600 records in 2009.
There are 437,436 records for 2018.
Special Note(s)
To provide adequate sample sizes for smaller geographically defined populations of interest, however, many states sample disproportionately from strata that correspond to sub-state regions. In 2018, the 48 states with geographic stratification were Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Pennsylvania, Puerto Rico, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, Wisconsin, and U.S. Virgin Islands.
Key Variables
Demographic
| Name | Methods of Assessment |
|---|---|
| Age of respondent and child in household | Interview/questionnaire |
| Disability (cognitive; equipment use; general; vision) | Interview/questionnaire |
| Household income | Interview/questionnaire |
| Marital status of respondent | Interview/questionnaire |
| Number of children in household | Interview/questionnaire |
| Race/ethnicity of respondent and child in household | Interview/questionnaire |
| Sex of respondent and child in household | Interview/questionnaire |
Diet-Related
| Name | Methods of Assessment |
|---|---|
| Cholesterol awareness | Interview/questionnaire |
| Food security status | Interview/questionnaire |
| Fruit and vegetable consumption (including juice, carrots, and salad) and number of servings | Interview/questionnaire |
| Sugar sweetened beverage consumption (select states) | Interview/questionnaire |
Physical Activity-Related
| Name | Methods of Assessment |
|---|---|
| Frequency of moderate- and vigorous-intensity physical activity | Self report |
| Occupational physical activity | Self report |
| Physical inactivity during leisure time | Self report |
Sleep-Related
| Name | Methods of Assessment |
|---|---|
| Involuntary falling asleep | Interview/Questionnaire |
| Sleep continuity: Other | Interview/Questionnaire |
| Sleep disordered breathing: Observed breathing pauses while sleeping | Interview/Questionnaire |
| Sleep disordered breathing: Snoring | Interview/Questionnaire |
| Sleep disturbances and quality: Other | Interview/Questionnaire |
| Sleep duration and quantity | Interview/Questionnaire |
| Sleep as a symptom of a health condition (i.e., assess severity of health condition such as asthma, anxiety, depression) | Interview/Questionnaire |
Weight-Related
| Name | Methods of Assessment |
|---|---|
| Height, weight (used to calculate body mass index) | Self report |
| Select obesity-related health conditions | Interview/questionnaire |
Geocode/Linkage
| Name | Methods of Assessment |
|---|---|
| Public use: County, state, indicator of residence within or outside a metropolitan statistical area. Restricted access: zip code | N/A |
Other
| Name | Methods of Assessment |
|---|---|
| Quality of life | Interview/questionnaire |
Special Note(s)
The BRFSS Sugar-Sweetened Beverage (SSB) Module, either included as an Optional Module
or as State-Added Questions, was introduced in 2011 to monitor consumption of SSBs at the state level.
Data Access and Cost
Data Availability
Obtain data online.
Cost
Free of charge.
Special Note(s)
The most recent year for which data are available is not necessarily the most recent year this survey was conducted. Please note that a statistical software program such as SAS or SUDAAN may be needed to analyze downloaded data.
Geocode/Linkage
Geocode Variable(s)
Public use: County, state, indicator of residence within or outside a metropolitan statistical area. Restricted access: zip code.
Existing Linkages
BRFSS data on fruit and vegetable consumption and physical activity have been linked to Nevada built environment data on land use mix, continuation of streets and sidewalks, safety, and the food environment (e.g., number and types of food retail outlets and availability of fruits and vegetables) using address. Learn more.
Selected Publications
Diet-Related
Grimm KA, Blanck HM, Scanlon KS, Moore LV, Grummer-Strawn LM, Foltz JL. State-specific trends in fruit and vegetable consumption among adults—United States, 2000–2009. Morbidity and Mortality Weekly Report 2010;59(35):1125-1130.
Park S, Pan L, Sherry B, Blanck HM. Consumption of sugar-sweetened beverages among U.S. adults in 6 states: Behavioral Risk Factor Surveillance System, 2011. Prev Chronic Dis. 2014 Apr 24;11:E65.
Sullivan KM, Ford ES, Azrak MF, Mokdad AH. Multivitamin use in pregnant and nonpregnant women: Results from the Behavioral Risk Factor Surveillance System. Public Health Reports 2009;124(3):384-390.
Tichenor N, Conrad Z. Inter- and independent effects of region and race/ethnicity on variety of fruit and vegetable consumption in the U.S.A.: 2011 Behavioral Risk Factor Surveillance System (BRFSS). Public Health Nutr. 2015 Mar 6:1-10.
Physical Activity-Related
Carlson SA, Fulton JE, Galuska DA, Kruger J, Lobelo F, Loustalot FV. Prevalence of self-reported physically active adults—United States, 2007. Morbidity and Mortality Weekly Report 2008;57(48):1297-1300.
Weight-Related
Bish CL, Chu SY, Shapiro-Mendoza CK, Blanck HM, Sharma AJ. Trying to lose or maintain weight during pregnancy—United States, 2003. Maternal & Child Health Journal 2008;13(2):286-292.
Henderson VR. Longitudinal associations between television viewing and body mass index among white and black girls. Journal of Adolescent Health 2007;41(6):544-550.
Krishna A, Razak F, Lebel A, Smith GD, Subramanian SV. Trends in group inequalities and interindividual inequalities in BMI in the United States, 1993-2012. Am J Clin Nutr. 2015 Mar;101(3):598-605.
Whetstone LM, Morrissey SL, Cummings DM. Children at risk: The association between perceived weight status and suicidal thoughts and attempts in middle school youth. Journal of School Health 2007;77(2):59-66.
Xie D, Raghunathan TE, Lepkowski JM. Estimation of the proportion of overweight individuals in small areas—a robust extension of the Fay-Herriot model. Statistics in Medicine 2007;26(13):2699-2715.
Methods
Fahimi M, Link M, Schwartz DA, Levy P, Mokdad A. Tracking chronic disease and risk behavior prevalence as survey participation declines: Statistics from the Behavioral Risk Factor Surveillance System and other national surveys. Preventing Chronic Disease 2008;5(3):A80.
Resources
Data Query System
Data query systems also are available at various state BRFSS Web sites.
City and county level data for some areas are available online through SMART BRFSS.
Documentation/Codebook(s)
http://www.cdc.gov/brfss/data_documentation/pdf/userguidejune2013.pdf
Tools
Maps showing frequency of responses by state and metropolitan statistical area.
