Are FDA Compliance Checks Equitable? a Profile Analysis and Geospatial Analysis

Background: Although tobacco prevention and control efforts have tried to prevent minors from purchasing tobacco, tobacco continues to be a public health epidemic. One such effort is Food and Drug Administration (FDA) compliance checks. From previously published work on tobacco density, studies have found that tobacco density is high among areas of lower socioeconomic status (SES). This study hypothesized, that as tobacco density is higher among lower SES neighborhoods, these neighborhoods were more likely to be included in FDA compliance checks. To examine equity of FDA compliance check coverage, we created profiles to analyze if the FDA compliance checks were being conducted equitably across retailers based on neighborhood characteristics or having equal chance of being checked. This study also hypothesized that non-chain convenience stores will be cited for a violation after a FDA compliance check.

Method: This study used three sources of public data from New Jersey; 1) 2019 licensed tobacco retail outlets, 2) FDA compliance check data from 2019, 3) sociodemographic data from the American Community Survey (ACS). Once these data were matched together and cleaned, a Latent Profile Analysis (LPA) was conducted creating profiles based on tobacco density from census tracts. No previous study has used LPA to examine tobacco density or FDA compliance checks. Regression analyses predicted the likelihood that FDA compliance checks were conducted more in profiles with high tobacco density and in areas of lower socioeconomic demographics. Regression analysis also examined the relationship/predict that non-chain convenience stores are more likely to be cited for a violation from an FDA compliance check than chain convenience stores.

Results: Results of preliminary analysis suggests census tracts can be profiled based on the densities of different types of licensed tobacco retail outlets. And that there are certain profile types are stronger predictors suggesting the likelihood of being part of the FDA compliance checks. The preliminary results also show that profiles made of up census tracks of lower sociodemographics are also more likely to be part of the FDA compliance checks. When examining the likelihood of a violation by store type, preliminary results showed non-chain convenience stores are more likely to be cited for a violation as a result of a FDA compliance check than chain convenience stores.

Conclusions: The results of this study provide some policy implications; the first is to encourage the FDA to use their power to issue more civil money penalties and no-tobacco orders to restrict the access of tobacco among youth, truly exercising the compliance checks as a prevention tool. The second policy recommendation is to suggest that changes to FDA compliance checks to ensure that the FDA checks all areas of the state equally, as tobacco outlets are found across the states throughout multiple profiles regardless of sociodemographics.