In 2009, the Family Smoking Prevention and Tobacco Control Act gave the Food and Drug Administration the authority to regulate the manufacturing, marketing, and distribution of tobacco products in the United States. Through the FDA Center for Tobacco Products (FDACTP), the government undertakes a range of actions to promote public health by reducing harm from tobacco products, including setting tobacco product standards, requiring labeling, and making decisions on whether new tobacco products can be marketed.  In January 2025, the FDA has proposed a rule to set a maximum nicotine level in cigarettes to make them minimally or non-addictive, which is part of the agency’s broader goal to reduce smoking-related disease and death. However, given the wide variety of tobacco products and the size and complexity of the U.S. population, it can be difficult to estimate the impact of potential FDA rules and regulations using data collected from randomized clinical trials alone.

To improve this process, researchers with the University of Minnesota School of Public Health (SPH) are developing statistical methods to better estimate the impact of tobacco-product regulation from multiple data sources. With a $3.15 million grant from  the National Institutes of Health and FDACTP, SPH researchers are developing novel statistical methods that integrate diverse data sources in order to more precisely estimate the population-level impact of tobacco product regulations. The research will be led by Joe Koopmeiners, Mayo Professor and head of the Division of Biostatistics & Health Data Science, and Associate Professor David Vock.

While randomized controlled trials completed over the last decade show that a low nicotine standard will decrease cigarette use and dependence, there are still many nuanced questions remaining as to the effect of a nicotine standard. For example, will the effect of a nicotine standard be the same across the population of people who smoke? How do effects on individual people who smoke affect population health? Are our conclusions robust to a potential illicit market? Answering these questions will require integrating data from multiple sources, which in turn requires new statistical methods to translate these data into answers.

“Capturing the full impact of a new tobacco-product standard requires researchers to capture and analyze numerous complex data resources, and the existing statistical methods are either inefficient or simply incapable of providing the answers FDACTP needs,” says Koopmeiners. “Our work represents a significant contribution to the fields of tobacco regulatory science and biostatistics through the development of innovative statistical methods that will result in more precise estimates of the impact of potential FDA

regulatory action. Using these new statistical methods, federal regulators will be able to understand the full impact of a low nicotine-product standard for cigarettes on populations across the U.S.”

The five-year research project will focus on four key aims:

• Developing techniques to synthesize data from multiple trials, ensuring that regulatory impact estimates reflect the broader U.S. smoking population.
• Introducing a statistical approach that allows researchers to pool information from multiple studies and enhance the precision of regulatory effect estimates.
• Developing methods to understand individual treatment effects to better understand disparities in the impact of tobacco regulations across various populations and demographic groups.
• Creating sensitivity analysis methods to account for unmeasured factors, such as illicit markets, that could influence regulatory outcomes.