The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based system of health surveys that collects information on health risk behaviors, preventive health practices, and health care access primarily related to chronic disease and injury. For many states, the BRFSS is the only available source of timely, accurate data on health-related behaviors.

In 1984, the Centers for Disease Control and Prevention (CDC) initiated the state-based Behavioral Risk Factor Surveillance System (BRFSS)--a cross-sectional telephone survey that state health departments conduct monthly over landline telephones and cellular telephones with a standardized questionnaire and technical and methodologic assistance from CDC. BRFSS is used to collect prevalence data among adult U.S. residents regarding their risk behaviors and preventive health practices that can affect their health status. Respondent data are forwarded to CDC to be aggregated for each state, returned with standard tabulations, and published at year's end by each state. In 2011, more than 500,000 interviews were conducted in the states, the District of Columbia, and participating U.S. territories and other geographic areas.The files in this deposit were downloaded from the CDC website by Julia Dennett, Yale University, and Toby Chaiken, J-PAL North America, and archived by Travis Donahoe, Harvard University. Additional information edited by Michael Darisse and Lars Vilhuber, Cornell University and American Economic Association.

These BRFSS datasets were downloaded prior to them being taken offline on January 31st, 2025. Special thanks to James Bailey & Doug Livingston who made earlier years of BRFSS data available!

Data 2000-2023 are provided in SAS, Stata, and R formats. Data for 1987-1999 are provided in CSV format.

This repository has a DOI assigned if you need to cite it.

analyze the behavioral risk factor surveillance system (brfss) with r and monetdb experimental. the behavioral risk factor surveillance system (brfss) aggregates behavioral health data from 400,000 adults via telephone every year. it's um clears throat the largest telephone survey in the world and it's gotta lotta uses, here's a list neato. state health departments perform the actual d ata collection (according to a nationally-standardized protocol and a core set of questions), then forward all responses to the centers for disease control and prevention (cdc) office of surveillance, epidemiology, and laboratory services (osels) where the nationwide, annual data set gets constructed. independent administration by each state allows them to tack on their own questions that other states might not care about. that way, florida could exempt itself from all t he risky frostbite behavior questions. in addition to providing the most comprehensive behavioral health data set in the united states, brfss also eeks out my worst acronym in the federal government award - onchit a close second. annual brfss data sets have grown rapidly over the past half-decade: the 1984 data set contained only 12,258 respondents from 15 states, all states were participating by 1994, and the 2011 file has surpassed half a million interviews. if you're examining trends over time, do your homework and review the brfss technical documents for the years you're looking at (plus any years in between). what might you find? well for starters, the cdc switched to sampling cellphones in their 2011 methodology. unlike many u.s. government surveys, brfss is not conducted for each resident at a sampled household (phone number). only one respondent per phone number gets interviewed. did i miss anything? well if your next question is frequently asked, you're in luck. all brfss files are available in sas transport format so if you're sittin' pretty on 16 gb of ram, you could potentially read.xport a single year and create a taylor-series survey object using the sur vey package. cool. but hear me out: the download and importation script builds an ultra-fast monet database (click here for speed tests, installation instructions) on your local hard drive. after that, these scripts are shovel-ready. consider importing all brfss files my way - let it run overnight - and during your actual analyses, code will run a lot faster. the brfss generalizes to the u.s. adult (18+ ) (non-institutionalized) population, but if you don't have a phone, you're probably out of scope. this new github repository contains four scripts: 1984 - 2011 download all microdata.R create the batch (.bat) file needed to initiate the monet database in the future download, unzip, and import each year specified by the user create and save the taylor-series linearization complex sample designs create a well-documented block of code to re-initiate the monetdb server in the future 2011 single-year - analysis examples.R run the well-d ocumented block of code to re-initiate the monetdb server load the r data file (.rda) containing the taylor-series linearization design for the single-year 2011 file perform the standard repertoire of analysis examples, only this time using sqlsurvey functions 2010 single-year - variable recode example.R run the well-documented block of code to re-initiate the monetdb server copy the single-year 2010 table to maintain the pristine original add a new drinks per month category variable by hand re-create then save the sqlsurvey taylor-series linearization complex sample design on this new table close everything, then load everything back up in a fresh instance of r replicate statistics from this table , pulled from the cdc's web-enabled analysis tool replicate cdc weat - 2010.R run the well-documented block of code to re-initiate the monetdb server load the r data file (.rda) containing the taylor-series linearization design for the single-year 2010 file replicate statistics from this table, pulled from the cdc's web-enabled analysis tool click here to view these four scripts for more detail about the behavioral risk factor surveillance system, visit: the centers for disease control and prevention beh avioral risk factor surveillance system homepage the behavioral risk factor surveillance system wikipedia entry notes: if you're just scroungin' around for a few statistics, the cdc's web-enabled analysis tool (weat) might be all your heart desires. in fact , on slides seven, eight, nine of my online query tools video, i demonstrate how to use this table creator. weat's more advanced than most web-based survey analysis - you can run a regression. but only seven (of eighteen) years can currently be queried online. since data types in sql are not as plentiful as they are in the r language, the definition of a monet database-backed complex design object requires a cutoff be specified between the categorical variables and the linear ones. that cut point gets...

This dataset contains model-based Census tract level estimates for the PLACES project by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. It represents a first-of-its kind effort to release information uniformly on this large scale. Data sources used to generate these model-based estimates include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 or 2014–2018 estimates. The 2021 release uses 2019 BRFSS data for 22 measures and 2018 BRFSS data for 7 measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours a night). Seven measures are based on the 2018 BRFSS data because the relevant questions are only asked every other year in the BRFSS. This data only covers the health of adults (people 18 and over) in East Baton Rouge Parish. All estimates lie within a 95% confidence interval.

Download the latest version of the Glossary and Methodology File

2011 to present. BRFSS combined land line and cell phone prevalence data. BRFSS is a continuous, state-based surveillance system that collects information about modifiable risk factors for chronic diseases and other leading causes of death. Data will be updated annually as it becomes available. Detailed information on sampling methodology and quality assurance can be found on the BRFSS website (http://www.cdc.gov/brfss). Methodology: http://www.cdc.gov/brfss/factsheets/pdf/DBS_BRFSS_survey.pdf Glossary: http://apps.nccd.cdc.gov/BRFSSQuest/index.asp

The Synthetic BRFSS Health Behaviour and Condition Dataset is a large-scale, anonymized synthetic dataset designed for educational and research purposes to analyze behavioral risk factors and chronic health conditions. It simulates data typically collected by the Behavioral Risk Factor Surveillance System (BRFSS), enabling investigation of lifestyle, demographic, and health status indicators influencing cardiovascular and related diseases.

Dataset Features

• HeartDisease: Presence of heart disease (Yes/No).
• Smoking: Current smoking status (Yes/No).
• AlcoholDrinking: Regular alcohol consumption status (Yes/No).
• Stroke: History of stroke (Yes/No).
• PhysicalHealth: Number of days physical health was not good in the past month (integer).
• DiffWalking: Difficulty walking or climbing stairs (Yes/No).
• Sex: Biological sex of the respondent (Male/Female).
• AgeCategory: Age group category (e.g., 18-24, 40-44).
• Race: Self-reported race category.
• Diabetic: Diabetes status (Yes/No/Borderline/During pregnancy).
• PhysicalActivity: Engagement in physical activity (Yes/No).
• GenHealth: Self-rated general health (e.g., Excellent, Very good, Fair).
• SleepTime: Average hours of sleep per day (integer).
• Asthma: Presence of asthma (Yes/No).
• KidneyDisease: Presence of kidney disease (Yes/No).
• SkinCancer: Presence of skin cancer (Yes/No).

Distribution

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Usage

This dataset can be used for the following applications:

• Public Health Research: Analyze associations between lifestyle factors and chronic disease outcomes.
• Predictive Modeling: Develop classifiers to predict heart disease or stroke risk based on behavioural and demographic indicators.
• Health Informatics: Study patterns in self-reported health status and risk factor prevalence across age and race groups.
• Educational Purposes: Offer students and researchers a realistic dataset to practice data cleaning, visualisation, and modelling in epidemiology.

Coverage

The data is fully anonymised and synthetically generated to protect privacy while maintaining realistic feature distributions, allowing safe use in academic and data science projects related to health risk assessment.

License

CC0 (Public Domain)

Who Can Use It

• Public Health Researchers and Epidemiologists: To explore risk factors and disease correlations.
• Data Scientists and Machine Learning Practitioners: To build and evaluate health risk prediction models.
• Healthcare Educators and Students: As a comprehensive dataset for training and education in health data analysis.

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) level estimates. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 40 measures: 12 for health outcomes, 7 for preventive services use, 4 for chronic disease-related health risk behaviors, 7 for disabilities, 3 for health status, and 7 for health-related scocial needs. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population data, and American Community Survey 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

This dataset contains model-based county-level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. Project was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2022 county population estimates, and American Community Survey (ACS) 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the census 2022 county boundary file in a GIS system to produce maps for 40 measures at the county level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. This table displays the percentage of adults meeting Aerobic Physical Activity guidelines in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by the Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. The column percentages are weighted to the 2010 California Department of Finance (DOF) population statistics. Population estimates were obtained from the CA DOF for age, race/ethnicity, and sex. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

Download the current cigarette use among adults slides. These slides are available in PowerPoint format.

This dataset contains model-based census tract level estimates in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. These data can be joined with the Census tract 2022 boundary file in a GIS system to produce maps for 40 measures at the census tract level. An ArcGIS Online feature service is also available for users to make maps online or to add data to desktop GIS software. https://cdcarcgis.maps.arcgis.com/home/item.html?id=3b7221d4e47740cab9235b839fa55cd7

This dataset contains model-based census tract estimates. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 40 measures: 12 for health outcomes, 7 for preventive services use, 4 for chronic disease-related health risk behaviors, 7 for disabilities, 3 for health status, and 7 for health-related social needs. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2020 population data, and American Community Survey 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

This is a source dataset for a Let's Get Healthy California indicator at "https://letsgethealthy.ca.gov/." This table displays the proportion of adults who were ever told they had a depressive disorder in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. This indicator is based on the question: "“Has a doctor, nurse or other health professional EVER told you that you have a depressive disorder (including depression, major depression, dysthymia, or minor depression)?” NOTE: Denominator data and weighting was taken from the California Department of Finance, not U.S. Census. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

This is a source dataset for a Let's Get Healthy California indicator at "https://letsgethealthy.ca.gov/. This table displays the prevalence of diabetes in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. This prevalence rate does not include pre-diabetes, or gestational diabetes. This is based on the question: "Has a doctor, or nurse or other health professional ever told you that you have diabetes?" The sample size for 2014 was 8,832. NOTE: Denominator data and weighting was taken from the California Department of Finance, not U.S. Census. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

2015-2022. This data set contains data from BRFSS.