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.

The 2011 BRFSS data reflects a change in weighting methodology (raking) and the addition of cell phone only respondents. Shifts in observed prevalence from 2010 to 2011 for BRFSS measures will likely reflect the new methods of measuring risk factors, rather than true trends in risk-factor prevalence. A break in trend lines after 2010 is used to reflect this change in methodolgy. Percentages are weighted to population characteristics. Data are not available if it did not meet BRFSS stability requirements. For more information on these requirements, as well as risk factors and calculated variables, see the Technical Documents and Survey Data for a specific year - http://www.cdc.gov/brfss/annual_data/annual_data.htm. Recommended citation: Centers for Disease Control and Prevention (CDC). Behavioral Risk Factor Surveillance System. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, [appropriate year].

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...

1984-2023. Centers for Disease Control and Prevention (CDC). BRFSS Survey Data. The BRFSS is a continuous, state-based surveillance system that collects information about modifiable risk factors for chronic diseases and other leading causes of death. Detailed information on sampling methodology and quality assurance can be found on the BRFSS website (http://www.cdc.gov/brfss).

2011 to present. BRFSS combined land line and cell phone age-adjusted prevalence data. The 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: https://data.cdc.gov/Behavioral-Risk-Factors/Behavioral-Risk-Factor-Surveillance-System-BRFSS-H/iuq5-y9ct

This dataset contains model-based place (incorporated and census-designated places) 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.

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: https://data.cdc.gov/Behavioral-Risk-Factors/Behavioral-Risk-Factor-Surveillance-System-BRFSS-H/iuq5-y9ct

Originally, the dataset come from the CDC and is a major part of the Behavioral Risk Factor Surveillance System (BRFSS), which conducts annual telephone surveys to gather data on the health status of U.S. residents. As the CDC describes: "Established in 1984 with 15 states, BRFSS now collects data in all 50 states as well as the District of Columbia and three U.S. territories. BRFSS completes more than 400,000 adult interviews each year, making it the largest continuously conducted health survey system in the world.". The most recent dataset (as of February 15, 2022) includes data from 2020. It consists of 401,958 rows and 279 columns. The vast majority of columns are questions asked to respondents about their health status, such as "Do you have serious difficulty walking or climbing stairs?" or "Have you smoked at least 100 cigarettes in your entire life? [Note: 5 packs = 100 cigarettes]".

To improve the efficiency and relevance of our analysis, we removed certain attributes from the original BRFSS dataset. Many of the 279 original attributes included administrative codes, metadata, or survey-specific variables that do not contribute meaningfully to heart disease prediction—such as respondent IDs, timestamps, state-level identifiers, and detailed lifestyle questions unrelated to cardiovascular health. By focusing on a carefully selected subset of 18 attributes directly linked to medical, behavioral, and demographic factors known to influence heart health, we streamlined the dataset. This not only reduced computational complexity but also improved model interpretability and performance by eliminating noise and irrelevant information. All predicting variables could be divided into 4 broad categories:

1. Demographic factors: sex, age category (14 levels), race, BMI (Body Mass Index)

2. Diseases: weather respondent ever had such diseases as asthma, skin cancer, diabetes, stroke or kidney disease (not including kidney stones, bladder infection or incontinence)

3. Unhealthy habits:

   • Smoking - respondents that smoked at least 100 cigarettes in their entire life (5 packs = 100 cigarettes)
   • Alcohol Drinking - heavy drinkers (adult men having more than 14 drinks per week and adult women having more than 7 drinks per week

4. General Health:

   • Difficulty Walking - weather respondent have serious difficulty walking or climbing stairs
   • Physical Activity - adults who reported doing physical activity or exercise during the past 30 days other than their regular job
   • Sleep Time - respondent’s reported average hours of sleep in a 24-hour period
   • Physical Health - number of days being physically ill or injured (0-30 days)
   • Mental Health - number of days having bad mental health (0-30 days)
   • General Health - respondents declared their health as ’Excellent’, ’Very good’, ’Good’ ,’Fair’ or ’Poor’

Below is a description of the features collected for each patient:

This dataset contains model-based census tract level estimates for the PLACES 2021 release in GIS-friendly format. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 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 (RWJF) in conjunction with the CDC Foundation. 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. These data can be joined with the census tract 2015 boundary file in a GIS system to produce maps for 29 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=024cf3f6f59e49fe8c70e0e5410fe3cf

2013-2016. This dataset is a de-identified summary table of vision and eye health data indicators from BRFSS, stratified by all available combinations of age group, race/ethnicity, gender, risk factor and state. BRFSS is a system of telephone surveys conducted by CDC that collect state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. BRFSS completes more than 400,000 adult interviews each year across 50 states, the District of Columbia, and three U.S. territories. BRFSS data for VEHSS includes one question from the core component related to Visual Function. Data were suppressed for cell sizes less than 30 persons, or where the relative standard error more than 30% of the mean. Data will be updated as it becomes available. Detailed information on VEHSS BRFSS analyses can be found on the VEHSS BRFSS webpage (link). General information about BRFSS can be found on the BRFSS website (https://www.cdc.gov/brfss). The VEHSS BRFSS dataset was last updated in June 2018.

This layer represents the Percent of Adults who are Obese calculated from the 2014-2017 Colorado Behavioral Risk Factor Surveillance System (County or Regional Estimates) data set. These data represent the estimated prevalence of being Obese among adults (Age 18+) for each county in Colorado. Obese is defined as a BMI of 30 or greater. BMI is calculated from self-reported height and weight. Regional estimates were used if there was not enough sample size to calculate a single county estimate. The estimate for each county was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2014-2017).

This dataset contains model-based place (incorporated and census designated places) level estimates for the PLACES 2022 release in GIS-friendly format. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 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 include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population estimates, and American Community Survey (ACS) 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. These data can be joined with the 2019 Census TIGER/Line place boundary file in a GIS system to produce maps for 29 measures at the place 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

Analysis of ‘CDC Places Data by ZIP Code’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/93493d26-ac78-465d-8197-ba486cc07ed7 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains model-based ZIP Code Tabulation Area (ZCTA) 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.

--- Original source retains full ownership of the source dataset ---

This layer represents the Percent of Adults who used Marijuana 1+ days out of the past 30 days calculated from the 2014-2017 Colorado Behavioral Risk Factor Surveillance System (County or Regional Estimates) data set. These data represent the estimated prevalence of adult (Age 18+) Marijuana use for each county in Colorado. Marijuana use is defined as using marijuana or hashish 1 or more days out of the past 30 days. Regional estimates were used if there was not enough sample size to calculate a single county estimate. The estimate for each county was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2014-2017).

This dataset contains model-based place (incorporated and census-designated places) level estimates for the PLACES 2022 release. PLACES covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at 4 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 29 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, and 3 for health status. 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 include Behavioral Risk Factor Surveillance System (BRFSS) 2020 or 2019 data, Census Bureau 2010 population data, and American Community Survey 2015–2019 estimates. The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

This layer represents the Percent of Adults with Frequent Mental Distress calculated from the 2014-2017 Colorado Behavioral Risk Factor Surveillance System (County or Regional Estimates) data set. These data represent the estimated prevalence of Frequent Mental Distress among adults (Age 18+) for each county in Colorado. Frequent Mental Distress is defined as experiencing more than 14 mentally unhealthy days within the past 30 days in which mental health was "not good." Health conditions for measuring mental health include stress, depression, and problems with emotions. Regional estimates were used if there was not enough sample size to calculate a single county estimate. The estimate for each county was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2014-2017).

This is the complete dataset for the 500 Cities project 2017 release. This dataset includes 2015, 2014 model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of 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 measures include Behavioral Risk Factor Surveillance System (BRFSS) data (2015, 2014), Census Bureau 2010 census population data, and American Community Survey (ACS) 2011-2015, 2010-2014 estimates. Because some questions are only asked every other year in the BRFSS, there are 7 measures from the 2014 BRFSS that are the same in the 2017 release as the previous 2016 release. More information about the methodology can be found at www.cdc.gov/500cities.

This layer represents the Percent of Adults who Binge Drink calculated from the 2014-2017 Colorado Behavioral Risk Factor Surveillance System (County or Regional Estimates) data set. These data represent the estimated prevalence of Binge Drinking among adults (Age 18+) for each county in Colorado. Binge Drinking is defined for males as having five or more drinks on one occasion and for females as having four or more drinks on one occasion within the past 30 days. Binge Drinking is calculated from the number of days alcohol was consumed in the past 30 days, and the average number of drinks consumed on those days. Regional estimates were used if there was not enough sample size to calculate a single county estimate. The estimate for each county was derived from multiple years of Colorado Behavioral Risk Factor Surveillance System data (2014-2017).

This dataset contains model-based census tract-level estimates for the PLACES 2021 release. PLACES is the expansion of the original 500 Cities project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 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 (RWJF) in conjunction with the CDC Foundation. The dataset includes estimates for 29 measures: 4 chronic disease-related health risk behaviors, 13 health outcomes, 3 health status, and 9 on use of preventive services. 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 include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2010 population data, and American Community Survey (ACS) 2015–019 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 because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

Abstract

Dataset quality ***: High quality dataset that was quality-checked by the EIDC team

This dataset contains model-based county-level estimates for the PLACES 2021 and 2022 release. PLACES is the expansion of the original 500 Cities Project and covers the entire United States—50 states and the District of Columbia (DC)—at county, place, census tract, and ZIP Code Tabulation Area (ZCTA) levels. It represents a first-of-its kind effort to release information uniformly on this large scale for local areas at 4 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 (RWJF) in conjunction with the CDC Foundation.

Methodology

The dataset includes estimates for 29 measures: 4 chronic disease-related health risk behaviors, 13 health outcomes, 3 health status, and 9 on using preventive services. 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 include Behavioral Risk Factor Surveillance System (BRFSS) 2019 or 2018 data, Census Bureau 2019 or 2018 county population estimate data, 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 because the relevant questions are only asked every other year in the BRFSS. More information about the methodology can be found at www.cdc.gov/places.

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• The 2022 release uses 2020 BRFSS data for 25 measures and 2019 BRFSS data for 4 measures (high blood pressure, taking high blood pressure medication, high cholesterol, and cholesterol screening) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places

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