What Are the Effects of Recreational Marijuana Laws on Nutrition and Physical Activity?

Wilk, Deza, Hodge, and Danagoulian (2026) ask whether recreational marijuana laws change adults’ eating habits and physical activity. They examine grocery purchase data from the NielsenIQ Consumer Panel, self-reported exercise from the Behavioral Risk Factor Surveillance System, and time-use data from the American Time Use Survey. They find that recreational marijuana laws increase spending on junk food by about 1.8 percent and raise the likelihood that a grocery trip includes junk food by roughly 0.5 percentage points, with notable increases in ice cream, chips, and candy. At the same time, they find a 1.1 percentage point decline in exercise participation and a 2.0 percentage point drop in cardio activity.

Why This Article Was Selected for The Policy Scientist

This article addresses a policy issue of broad importance as recreational marijuana laws continue to expand and normalize adult marijuana use across many jurisdictions. As legalization matures, the policy focus necessarily shifts from criminal justice outcomes to population-level health behaviors that affect long-run health and health care costs. The study is timely because diet- and lifestyle-related chronic conditions already impose substantial social costs, making even modest behavioral changes consequential at scale. The authors build on a growing literature linking marijuana access to consumption but extend it in an important way by examining downstream behaviors using multiple large, high-quality datasets. The findings are likely to generalize to other settings with similar legalization frameworks. Methodologically, the use of modern causal inference techniques for staggered policy adoption represents a clear strength relative to earlier regression-based work.

Full Citation and Link to Article

Wilk, T., Deza, M., Hodge, T., & Danagoulian, S. (2026). Couch-Locked With the Munchies: Effects of Recreational Marijuana Laws on Exercise and Nutrition. Journal of Policy Analysis and Management, 45(1), 000–000. https://doi.org/10.1002/pam.70080 

Central Research Question

This article examines whether the adoption of recreational marijuana laws alters two key health-related behaviors among adults: unhealthy food consumption and physical activity. Specifically, the authors ask whether expanded legal access to marijuana increases purchases of calorie-dense, low-nutrition foods commonly associated with “the munchies” and whether it reduces exercise and out-of-home activity consistent with “couch-lock.” The core question is not whether individuals consume marijuana, but whether population-level legalization produces measurable downstream behavioral changes that plausibly affect long-run health. By focusing on diet and exercise rather than marijuana use itself, the study reframes legalization as a policy intervention with indirect but potentially consequential health effects.

Previous Literature

Prior research on marijuana and health behaviors falls into two broad strands. Clinical and experimental studies document short-term physiological effects of cannabis, including increased appetite, altered taste preferences, and fatigue, often based on small samples or laboratory settings. These studies establish biological plausibility but offer limited insight into sustained behavioral change. A second literature uses survey or aggregate data to examine associations between marijuana use and diet or physical activity, though results are mixed and often confounded by selection into use. More recent policy-based studies exploit medical or recreational marijuana laws to study consumption, crime, or labor outcomes, with relatively little attention to lifestyle behaviors. A small number of papers link legalization to food spending or fast-food consumption, but typically rely on aggregate sales or narrow outcomes. This article builds on that work by jointly analyzing nutrition and physical activity using individual- and household-level data and by applying modern causal inference methods to address staggered policy adoption.

Data

The authors draw on four large, complementary data sources. Grocery purchasing behavior is measured using the NielsenIQ Consumer Panel, which tracks millions of household grocery trips across the United States with detailed information on spending, product categories, and timing. Physical activity is measured using the Behavioral Risk Factor Surveillance System, a large nationally representative survey that includes questions on recent exercise and cardio activity. Time allocation and location are analyzed using the American Time Use Survey, which provides diary-based measures of daily activities and where they occur. Finally, mobile device data from Advan are used to examine visits to food-related retail locations such as grocery stores and fast-food outlets. Together, these datasets allow the authors to examine food purchases, self-reported exercise, and broader patterns of time use before and after recreational marijuana laws take effect.

Methods

The empirical strategy exploits variation in the timing of recreational marijuana law implementation across states. Rather than relying on conventional two-way fixed effects models, the authors use an imputation-based difference-in-differences estimator designed for staggered treatment adoption. This approach estimates counterfactual outcomes using untreated observations and avoids biases associated with heterogeneous treatment timing. Models include rich geographic and temporal fixed effects and control for medical marijuana laws and pandemic-related restrictions. Event-study analyses are used to assess pre-trends and dynamic effects. Outcomes are tailored to each dataset, including household-week measures of food spending, individual-level exercise indicators, and daily minutes spent in various locations. Standard errors are clustered at the state level. This design is well suited to isolating the average effect of legalization on treated states over time.

Findings/Size Effects

The study finds consistent evidence that recreational marijuana laws increase unhealthy food purchasing and reduce physical activity. Grocery spending on junk food rises by approximately 1.8 percent following legalization, with increases observed at both the extensive and intensive margins of purchasing. The probability that a grocery trip includes junk food increases by about 0.5 percentage points, and the number of trips involving junk food rises by roughly 0.8 percent. Category-specific results show statistically significant increases in spending on ice cream, chips, and candy. Importantly, total grocery trips and total grocery spending do not change, indicating a shift in composition rather than overall consumption.

On the activity side, legalization is associated with a 1.1 percentage point decline in the likelihood of exercising in the past month, relative to a baseline participation rate of roughly 74 percent. Cardio-intensive exercise declines by about 2.0 percentage points, corresponding to a sizable proportional reduction. Time-use data show reduced minutes spent at the gym and outdoors, coupled with an increase of approximately eight additional minutes per day spent at home. Time spent at work and in restaurants also declines modestly. Mobile device data show no corresponding increase in visits to fast-food outlets, suggesting that increased unhealthy eating is concentrated in grocery purchases rather than restaurant consumption.

Conclusion

This article provides evidence that recreational marijuana laws have meaningful, though modest, effects on adult lifestyle behaviors that are relevant for long-term health. By combining multiple high-quality datasets and applying contemporary causal inference methods, the study advances the literature beyond narrow consumption outcomes and toward broader behavioral consequences of legalization. The findings suggest that increased access to marijuana shifts dietary choices toward less nutritious foods and reduces physical activity, even in the absence of changes in total food purchasing or restaurant visits. While the estimated effects are small in isolation, their population-level implications are potentially important given the scale of legalization. The analysis is well positioned to generalize to other jurisdictions with similar retail legalization regimes and contributes a rigorous empirical foundation for future research on the health externalities of drug policy.