An Interview with Prof. Jordan Weiss, NYU Grossman School of Medicine

The Behavioral Risk Factor Surveillance System (BRFSS) is a CDC survey conducted annually across all 50 U.S. states and territories, tracking chronic disease, health behaviors, healthcare access, and mental health. It is one of the largest ongoing public health surveys in the country, with decades of data available for researchers studying trends over time.

The catch is that questions change over time, fields get renamed, and optional modules vary by state and year. That means researchers often spend more time preparing BRFSS data than analyzing it.

In a recent conversation hosted by Briya, Dr. April Chan spoke with Prof. Jordan Weiss of NYU Grossman School of Medicine about his experience using BRFSS, the research questions it can answer, and how AI is changing how quickly researchers can get to publication-ready evidence.

Key takeaways

Q: Why is BRFSS useful for public health research?

Jordan Weiss: BRFSS is extremely large, covers every state, is collected annually, and includes a wide range of health topics in one survey. That makes it especially valuable for studying changes over time, comparing states, or examining population groups that may be too small in other national surveys.

 

Q: How have you used BRFSS in your own research?

JW: My first experience with BRFSS was during my dissertation, when I was projecting the burden of dementia in the United States through 2050. I used it to examine trends in major dementia risk factors, including diabetes, obesity, and cardiovascular health.

More recently, I have used it to explore cognitive decline, chronic disease, and quality of life, particularly among older adults.

 

Q: What makes BRFSS difficult to work with?

JW: The biggest challenge is often determining whether variables are genuinely comparable across years. Variable names, response options, survey methods, and definitions can change.

Researchers need to resolve those questions before they can trust the analysis. I have worked on projects where most of the effort went into preparing and validating the data, only to discover that the original research question could not be answered reliably.

 

Q: How long does BRFSS data preparation take?

JW: Even a relatively short prompt can represent half a day or a full day of downloading files, merging them, and putting the dataset together. But those are often the easy steps. The bigger challenge is reading through the codebooks and checking whether variable names, definitions, or response options have changed.

 

Q: How does Briya AIRE simplify BRFSS data analysis?

JW: One example is our analysis of depression trends among adults aged 65 and older across 14 years of BRFSS data. To make those years comparable, we had to account for changes in weighting methods, race and ethnicity categories, and how key variables were defined and coded over time.

This harmonization process doesn’t just make the data easier to use, it makes the results more credible, because people can trust that they’re comparing like with like. With AIRE, much of that work is already handled. It changes how much of researchers’ time can go toward the science instead of what my advisors used to call “the plumbing.”

 

Making BRFSS More Accessible

As Prof. Jordan Weiss’s experience shows, Briya AIRE makes BRFSS research faster and more accessible by providing harmonized, analysis-ready data that is already loaded into the platform. Researchers can now spend less time preparing data and more time actually answering meaningful research questions.

Learn more about the BRFSS survey methodology on the CDC’s BRFSS page.

Explore BRFSS Data With Briya AIRE

Joseph Schwartz