The Impact of Stay-at-Home Orders on Binge Drinking Patterns in the US

ABSTRACT

Objectives: This study aims to evaluate the impact of the stay-at-home orders, especially closing and reopening bars and other drinking establishments, on binge drinking patterns in US populations in Metropolitan Statistical Areas (MSAs). Method(s) Data on binge drinking and heavy binge drinking for this study was extracted from the 2018-2021 Behavioral Risk Factor Surveillance System (BRFSS). Data on regulations were collected by National Academy for State Health Policy. We used two staggered differences-in-differences strategies to account for monthly variations in bar regulations. We implemented a strategy that used never treated states as controls via the Stata package CSDID and a strategy that directly imputed counterfactuals for treated states via the Stata package FECT. The outcomes were measured by the number of binge drinkers or heavy binge drinkers per 1000 population. The treatment effect was estimated while controlling for age, income level, race, chronic conditions, gender, MSA fixed effects, and month fixed effects. Stay-at-home orders were coded as 1 in the first full month of implementation and were assumed to impact the entire state equally. Bars were assumed to reopen if the indoor service has been reactivated at any capacity. Result(s) For heavy binge drinking, the average treatment effect on the treated group was 4.86 per 1000 population (p=0.027) using FECT package and 6.74 per 1000 population (p = 0.025) using CSDID package. No significant effect was found for binge drinking. Conclusion(s) We provide suggestive evidence that stay-at-home orders may have increased heavy binge drinking in metropolitan areas. We estimated this led to a 3.38% (FECT) or 4.68% (CSDID) increase in heavy binge drinking during the pandemic. Future work will assess the characteristics of areas that saw the greatest increase in heavy binge drinking, and explore why heavy binge drinkers were more vulnerable than binge drinkers during the Covid.Copyright © 2023