Hest, Robert
Stewart, Andrea

Survey Data Season Essentials: What Is the BRFSS and How Can Researchers Use It?

This post is a part of our Survey Data Season series where we examine data from various surveys that are released annually from the summer through early fall. Find all of the Survey Data Season series posts on our Survey Data Season 2024 page here.

Each year, SHADAC covers the data releases of multiple federal surveys from a variety of agencies, beginning with the National Health Interview Survey (NHIS) in June continuing through the release of American Community Survey (ACS) and Current Population Survey (CPS) data products in September through January. 

While our focus has traditionally been on the health insurance coverage data that found in these surveys, we have also looked at factors related to coverage, including ‘access to care’ via measures of adults without primary doctors, for example, and ‘cost of care’ via measures such as adults who forgo needed medical care (because of cost). Both of those measures come from the BRFSS, a survey that is both part of our overall Survey Data Season coverage and is used in our annual “Comparing Federal Surveys that Count the Uninsured” brief, but is not typically used as our main source of data when analyzing health insurance coverage.*

This blog post will provide an overview of the BRFSS, answer some common questions about this survey, walk through a few examples of how we at SHADAC use BRFSS data, and review how other researchers and analysts can use it, too.

What Does “BRFSS” Stand For?

BRFSS stands for Behavioral Risk Factor Surveillance System. “BRFSS” can be treated as either an acronym and pronounced “BUR-fiss” or an initialism with each letter read out individually.

Which Federal Agency Conducts the BRFSS?

Conducted since 1984, the BRFSS is a partnership between the Centers for Disease Control (CDC) and state health departments in U.S. states and territories, which are responsible for data collection in their area. 

How Are BRFSS Data Collected?

BRFSS is an annual, telephone-based survey of U.S. adults (18 years or older) that calls landlines and cell phones via random digit dialing. 

The survey questionnaire has three parts:

1. The core component, which includes demographic questions and asks about health-related perceptions, conditions, and behaviors. The core is composed of a “standard” core of questions that states ask every year, and also includes a “rotating” core of alternating and emerging content (e.g., questions related to COVID were added in 2021) that is asked in even and odd years. 
2. The optional modules, which focus on specific health conditions and additional risk factors and that states can optionally choose to ask.
3. The state-added questions, which are additional questions added by individual states to their own questionnaire that can be used to learn more about a specific topic, or can be used to oversample groups of interest.

All participating states and territories (50 states, District of Columbia, Guam, the Commonwealth of Puerto Rico, and the U.S. Virgin Islands) are required to ask the survey questions contained in the core component, but are not required to ask anything from the optional or state-added question sections. This can make it difficult to compare data across all states or analyze trends over time, depending on the health topic area of interest.

What Kind of Information Is Found in the BRFSS? 

BRFSS collects state-level data about adult “health-related risk behaviors and events, chronic health conditions, and use of preventive services.” 

When Does the BRFSS Release Data?

Data from the BRFSS is released annually, but the exact timeframe can vary. Unlike the American Community Survey (ACS) and Current Population Survey (CPS) - which are scheduled to come out on September 10 and September 12 this year, respectively - the BRFSS does not release data on a specific date. Rather, data usually come out in August, but can be released anytime from July to September. Researchers can check the BRFSS Annual Survey Data page to see when the data becomes available.

This year's data released on August 29th - you can find that here.

Can You Pool or Combine Multiple Years of BRFSS Data?

BRFSS data can generally be pooled (i.e., combined) across multiple years of data. This is usually done to increase both sample sizes and the statistical reliability of estimates for small populations or uncommon events.

Survey questions, measures, and variable names can change across data years, though, so care should be taken to appropriately harmonize variables when pooling multiple years of BRFSS data. For example, BRFSS’ usual source of care measure changed substantially in 2021, creating a “break in series” in that year. Survey weights can generally be divided by the number of pooled data years to produce accurate weighted counts.

Important to note for combining multiple years of BRFSS data specifically: There was a break in the BRFSS series in 2011 when the survey began including cell phones in addition to landlines. Thus, data before 2011 should not be pooled with data from 2011 forward. 

How Does SHADAC Use BRFSS Data?

SHADAC draws on data from the BRFSS to produce key resources like our Comparing Federal Government Surveys That Count the Uninsured, which looks at trends in rates of uninsurance across time and across five different federal surveys, helping researchers understand how and when to most appropriately use each one.

The BRFSS is a rich source of 50-state data on health outcomes and behaviors, and thus offers researchers and analysts a venue for tracking the effects of health reforms for persons of varying income levels. Since the BRFSS income categories do not always match those set by the federal government for calculating poverty levels, SHADAC produced a helpful brief detailing Four Methods for Calculating Income as a Percent of the Federal Poverty Guidelines (FPG) in the Behavioral Risk Factor Surveillance System (BRFSS) in order to assist with this analytic process.

Choosing Between Federal Surveys That Measure Rent Affordability is another resource produced by SHADAC researchers that uses data from multiple federal surveys, including the BRFSS, to help researchers better understand ways to measure the effect of a rising housing affordability crisis across varying populations and across states in the U.S. We also use a variety of data from BRFSS measures on our State Health Compare tool.

Take a look at the BRFSS measures that are available on our State Health Compare site!

Access, Cost, and Quality of Care

Adults Who Forgo Needed Medical Care contains estimates of adults who could not get needed medical care due to cost. Uniquely for this measure, our demographic subgroups are organized not only by racial and ethnic categories and educational attainment, but also by chronic disease status. See more on this measure in this recent resource.

Adults Who Have No Personal Doctor is a measure of adults who do not have a doctor or care provider that they regularly interact with or schedule visits with for routine health care. SHADAC pulls this measure from the BRFSS and has used it in several past analyses, including this blog. 

Adult Cancer Screenings provides users with the rate of adults receiving recommended cancer screenings, including pap smears (cervical cancer screening), colorectal cancer screenings, and mammograms (breast cancer screening). Check out this recent SHADAC blog for more detail on this measure and analysis by available demographics.

Adult Flu Vaccinations are a gauge for adults in the United States who received their annual vaccine to protect against influenza. Tracking flu vaccination rates can help in estimating broader vaccination trends - such as in this analysis - and help detect gaps in vaccination coverage across different demographic groups.

Health Behaviors and Outcomes

Adult Excessive Alcohol Consumption is newer measure on state health compare that provides the rate of adult excessive alcohol consumption, which in turn is defined as binge drinking (4 or more drinks for women or 5 or more drinks for men on one occasion) and/or heavy drinking (7 or more drinks per week for women or 15 or more drinks per week for men).

Adult Smoking and Adult E-Cigarette Use are two related measures that track annual state-level rates of adults who smoke traditional tobacco cigarettes and those who smoke e-cigarettes, respectively. SHADAC researchers used this data from the BRFSS to produce a series of blogs on health behaviors, including this one. 

Chronic Disease Prevalence looks at the percent of the adult population who report having one or more of the following specific chronic disease types: diabetes, cardiovascular disease (CVD), heart attack, stroke and asthma.

Adult Unhealthy Days is a self-reported measure of the number of days within a month (30 days) that an individual does not have good health, either mentally or physically. Recently, SHADAC produced a 50-state resource which takes a closer look at this measure.

Activities Limited due to Health Difficulty provides a look at rates on the average number of days in the past 30 days that a person reports limited activity due to mental or physical health difficulties.

Stay Updated on the BRFSS Data Release and More with SHADAC’s Survey Data Season Series

We hope that this blog helps you to better understand what the BRFSS is, what kinds of information we can get from the data, and how SHADAC and other researchers can use BRFSS data to understand health care use, cost, quality, and access in each of the states and the nation as a whole.

But Survey Data Season doesn’t stop with the BRFSS. Through September, SHADAC will be covering the release of various major survey data from important federal survey sources, including the NHIS, MEPS, ACS, CPS, and, of course, the BRFSS. Stay up to date on our Survey Data Season series, with more Essentials blogs like this one along with other products analyzing newly released data, by signing up for our newsletter and following us on LinkedIn.

Want to see what we’ve already made for our Survey Data Season series? Check out the Survey Data Season archive page for a full list of everything we’ve created so far, including a blog on recently released 2023 NHIS data. Check back often for updates and new additions.

Notes

*The BRFSS has included a question about current health insurance coverage within the standard core component since 1991. However, the question simply asked whether the respondent had coverage, and not about the type of health insurance coverage a respondent might have. 

Question: “Do you have any kind of health care coverage, including health insurance, prepaid plans such as HMOs, or government plans such as Medicare, or Indian Health Service?” 

Answers: Yes; No; Don’t Know/Not Sure; Refused

Recently, in 2021, the BRFSS added a primary source of coverage question, making it possible to understand what portions of the national and state populations have different types of coverage. 

Question: “What is the current primary source of your health insurance?” 

Answers: A plan purchased through an employer or union (including plans purchased through another person's employer); A private nongovernmental plan that you or another family member buys on your own; Medicare; Medigap; Medicaid; Children's Health Insurance Program (CHIP); Military related health care: TRICARE (CHAMPUS) / VA health care / CHAMP- VA; Indian Health Service; State sponsored health plan; Other government program; No coverage of any type; Don’t Know/Not Sure; Refused

BRFSS’ measure of health insurance coverage is substantially different from those found in other federal surveys (e.g., ACS, CPS or NHIS) that allow respondents to choose multiple sources of health insurance coverage, rather than requiring respondents to select one “primary” source of coverage. Though BRFSS coverage data are generally reliable, by preventing respondents from selecting multiple sources of coverage, they present a less nuanced picture of health insurance compared to other surveys. Further, because BRFSS only surveys adults and has lower response rates than other surveys, other surveys are typically better sources of information about health insurance coverage, per se.

Walsh, Elliot
Research Dissemination Coordinator

e wals0421@umn.edu

LGBT Health Equity: Sexual Orientation and Gender Identity Data Resources and Information from SHADAC

• Less likely to have health insurance coverage 
• Less likely to have a regular health care provider
• More likely to delay care
• More likely to report poor quality care and unfair treatment from providers

Sexual Orientation and Gender Identity Data: New and Updated Information on Federal Guidance and Medicaid Data Collection Practices (SHVS Brief) 

State Health Compare: Explore Health Data with SOGI Data Breakdowns

• Adults Who Forgo Needed Medical Care Due to Cost
• Adult Smoking
• Adult Excessive Alcohol Consumption
• Adult E-Cigarette Use
• Chronic Disease Prevalence
• Adult Unhealthy Days
• Activities Limited Due to Health Difficulty
• Adults with No Personal Doctor
• Adult Cancer Screenings
• Adult Flu Vaccinations

Gender Based Discrimination in Health Care by Gender Identity in Minnesota

• Over half (57.1%) of trans and non-binary people reported forgone care—more than double the overall average of 26.2%
• Nearly one-third of trans and non-binary adults had low confidence in getting necessary health care—compared to the overall average of 11.8%

Examining Discrimination and Health Care Access by Sexual Orientation in Minnesota

• Both lesbian/gay and bisexual/pansexual people were more likely to report barriers to health care access
• Bisexual/pansexual people were more likely to report having low confidence in the ability to get needed health care
• Both lesbian/gay or bisexual/pansexual people had significantly higher rates of forgone care

SHADAC Response to 2023 Request for Comments on American Community Survey SOGI Questions

Stay Up to Date on the Latest in SOGI and LGBT Health Data

• Medicaid Equity Monitoring Tool Project
• Affordable Housing and Health: Unaffordable Rents Infographics
• Collection of Self-Reported Disability Data in Medicaid Applications: A Fifty-State Review of the Current Landscape (SHVS Brief)

Comparing Federal Government Surveys That Count the Uninsured: 2023

How many Americans are uninsured? The exact answer is unclear, but general estimates can be obtained by comparing various federal government surveys that estimate uninsurance.

SHADAC has recently updated our annual “Comparing Federal Government Surveys that Count the Uninsured” brief following the release of new insurance coverage estimates from surveys conducted by the US Census Bureau, the Agency for Healthcare Research and Quality (AHRQ), and the Centers for Disease Control and Prevention (CDC).

Accurate estimates of the number of people that do not have insurance coverage (also referred to as uninsured or uninsurance) are important in understanding trends and the impacts of actions (policy changes), events (like public health emergencies), or shifts in the economic landscape (like periods of recession) that may affect health insurance coverage.

The brief provides an annual update to comparisons of uninsurance estimates from five federal surveys. As in prior years, we have included estimates from:

• The American Community Survey (ACS)
• The Current Population Survey (CPS)
• The Medical Expenditure Panel Survey - Household Component (MEPS-HC)
• The National Health Interview Survey (NHIS)

This year we have included data from an additional source:

• The Behavioral Risk Factor Surveillance System (BRFSS)

In this brief, SHADAC provides up-to-date and past national uninsurance estimates, as well as the latest state-level estimates from surveys (where feasible). 

 

We also analyze the primary factors contributing to variations in these estimates among surveys, along with potential reasons for their incomparability both within and across surveys.

View and download the Comparing Federal Government Surveys 2023 Brief to learn more about our findings and analysis.

Interested in insurance coverage trends? Learn more with the following SHADAC products:

• Comparing Federal Surveys That Count the Uninsured 2022 (last year’s version of this brief) 
• Tracking Health Insurance Coverage During the Unwinding: Monthly Data from the Household Pulse Survey
• Unemployment Rate Trends of the Past 5 Years: Pre-, Mid-, and Post-Pandemic

SHADAC Staff

p 612.624.4802
e shadac@umn.edu

Household Pulse Survey (HPS) Insurance Coverage Trend Analysis: How Does It Compare?

Introduction

The U.S. Census Bureau’s Household Pulse Survey (HPS) is an online survey that provides up-to-date monthly data on emergent issues and the social and economic wellbeing of U.S. adults. As one of the only sources of publicly available rapid response data, the HPS is a critical tool for monitoring how policies such as the “unwinding” of the Medicaid continuous coverage requirement are affecting the landscape of health insurance coverage in near real time, hopefully providing actionable information for those making and implementing policy.

However, data validation of the Household Pulse Survey is crucial, especially given its short track record and novel methods. Even while offering near-real-time data, the HPS also faces several other challenges, including a notably low response rate (6.8% as of September 2023); underrepresentation of harder-to-reach demographic groups, such as adults with lower levels of education and young adults; a lack of editing and imputation for most variables; and likely some degree of nonresponse bias.

As researchers at the State Health Access Data Assistance Center (SHADAC) utilize the subannual HPS data to monitor changes in insurance coverage, we wanted to compare the HPS’ ability to detect insurance coverage changes over time against other more established surveys that also provide subannual estimates.

To this end, we compared subannual estimates of Medicaid/CHIP coverage, private coverage, and uninsurance among U.S. civilian noninstitutionalized nonelderly adults (age 18–64) in the HPS to similar estimates in the National Health Interview Survey (NHIS) [quarterly estimates from 2021–2022] and the Behavioral Risk Factor Surveillance System (BRFSS) [monthly estimates from 2022]. Below you'll find our insurance trend analysis findings using survey data.

Key Findings

Our analysis reveals that HPS estimates of coverage among adults follow similar trends as found with BRFSS and NHIS estimates. However, the exact estimates tend to deviate from each other.

Medicaid/CHIP

HPS estimates of Medicaid coverage almost exactly follow the trend of NHIS estimates of Medicaid coverage. The HPS estimates were consistently greater than the NHIS estimates with the HPS estimating that around 18% of adults were covered by Medicaid in 2021 and around 19% in 2022. The NHIS estimates were approximately 4 percentage points lower at around 14% in 2021 and 15% in 2022.

Private

Similar to estimates of Medicaid coverage among adults, the HPS estimates of private insurance coverage among adults were consistently higher than NHIS estimates, but both followed the same overall trend. HPS estimates for private insurance coverage hovered around 75% in 2021 and 2022. The gap between HPS estimates and NHIS estimates widened slightly between 2021 and 2022, increasing from an approximately 6 percentage point difference to an approximately 8 percentage point difference – NHIS estimates were around 69% in 2021 and 67% in 2022.

Uninsured

Similarly to both Medicaid and private coverage estimates, HPS estimates of uninsurance among adults closely mirrored the trends observed in both NHIS and BRFSS data. In a change from Medicaid and private coverage estimates, though, HPS estimates of uninsurance consistently fall between the estimates from BRFSS and NHIS, with HPS figures consistently greater than those from BRFSS but lower than NHIS’. This pattern persists through the first quarter of 2022.

Following this point, HPS estimates of uninsurance among adults decrease while BRFSS estimates increase and NHIS estimates stay more or less consistent.

Data and Methods

This analysis utilizes publicly available data from three household surveys: the Household Pulse Survey (HPS), the National Health Interview Survey (NHIS), and the Behavioral Risk Factor Surveillance System (BRFSS). All three surveys provide national representation of the civilian, noninstitutionalized population, with data collected on either a quarterly basis (NHIS) or a monthly basis (HPS and BRFSS). In order to have comparable time periods, HPS data was pooled both at the quarterly level and at the monthly level prior to analysis.

In the Household Pulse Survey, coverage was defined as having any sort of coverage (e.g. Medicaid or private) at the time of the survey. Uninsured was allocated to those that did not answer yes to being currently covered by some sort of health insurance or health coverage plan.

In the National Health Interview Survey (NHIS), Medicaid coverage among adults was defined as currently having either Medicaid coverage or CHIP coverage. Private coverage was defined as currently having any private coverage. Uninsurance was designated to those who answered they did not currently have health insurance.

The Behavioral Risk Factor Surveillance System (BRFSS) has a unique method of ascertaining health insurance coverage. As opposed to asking which health insurance coverage an individual has, BRFSS only has asks for a primary source of insurance, and individuals are only allowed to select one type of coverage. So, while BRFSS does include data on Medicaid coverage and private coverage, these estimates were not provided in this analysis as this type of instrument is not sufficiently comparable with the questions used by the HPS and NHIS to include estimates of coverage. Uninsurance among adults in BRFSS was defined as not having coverage of any type at the time of survey or being covered by Indian Health Service. 

Hest, Robert
Senior Research Fellow

p 612-624-5507
e hestx005@umn.edu

Analyzing Forgone Care by Coverage Type: New on State Health Compare

For most Americans, having health insurance is an important first step to being able to access and afford health care when it is needed.

As shown in recent data published on SHADAC’s State Health Compare, adults with health insurance coverage were at least 79% less likely to report having forgone (gone without) medical care when they needed it because of cost than adults without health insurance coverage. Whereas 63 percent of adults without health coverage reported forgone care, no more than 14 percent of those with coverage reported forgone care. This statistic illustrates the ability of health insurance coverage to protect against unexpected health care costs.

However, these data indicate that health insurance coverage’s ability to protect against unexpected health care costs varies by state and by type of health insurance coverage. The chart below shows the percent of adults (age 18+) who could not get medical care when needed due to cost by state and source of health insurance coverage. In the U.S., adults with some types of coverage such as Medicare (5 percent) or employer/military coverage (6 percent) were less likely to have gone without care because of cost compared with other types of coverage, such as individual coverage (10 percent) or Medicaid/CHIP coverage (14 percent).

It is important to note that the size of these differences in the protective power of health insurance coverage varied substantially by state. For example, where 11 percent of Georgia adults with employer coverage went without care, just 3 percent of employer-covered adults in the District of Columbia went without care. And similar state differences existed for other types of coverage:

• For adults with Medicare coverage, 9 percent of Louisianans had forgone care versus 3 percent of Vermonters.
   
• For adults with individual coverage, 16 percent of Nevadans had forgone care versus 3 percent of Vermonters.
   
• For adults with Medicaid/CHIP coverage, 25 percent of Oklahomans had forgone care versus 7 percent of South Dakotans.
   
• For adults with no health insurance coverage, 77 percent of Nevadans had forgone care versus 44 percent of South Dakotans.

These state differences highlight the inconsistency in the quality of health insurance coverage across the U.S., often related to differences in states’ markets for private health insurance coverage (e.g., individual coverage or employer coverage), differences in state Medicaid and CHIP programs, and differences in health care costs across the states.

Differences by coverage type call attention to variation in the ability of different types of health insurance coverage to protect covered adults from the risks of expensive or unexpected health care needs. However, these differences also highlight disparities in the underlying economic and health vulnerabilities of adults covered by different types of coverage.

Accessing BRFSS Coverage Data on State Health Compare

The data presented here come from SHADAC analysis of the 2021 Behavioral Risk Factor Surveillance System (BRFSS), a survey conducted in partnership between states and the Centers for Disease Control, and are available on SHADAC’s State Health Compare web tool. 

Data on detailed health insurance coverage types were collected among all participating states in the BRFSS for the first time in 2021. These new data have allowed State Health Compare to include breakdowns by detailed coverage type for all eight BRFSS measures that feature 2021 data and are the first source of information about these important measures of access and affordability of care, outcomes, and health behaviors for adults with specific types of coverage (e.g., Medicaid/CHIP).

BRFSS measures to explore further:

Notes: All differences described in this analysis are statistically significant at the 95% confidence level. Estimates are representative of the civilian non-institutionalized population 18 years and over and are based on SHADAC analysis of the 2021 Behavioral Risk Factor Surveillance System public use files. Florida data are not available in 2021 because the state was unable to collect sufficient data, and 2021 national data do not include Florida. Other state-level data were not available due to suppression where the number of sample cases was too small.