Using place-based characteristics to inform FDA tobacco sales inspections: results from a multilevel propensity score model

利用基于地点的特征指导FDA烟草销售检查:多级倾向评分模型的结果

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Abstract

BACKGROUND: Conducting routine inspections for compliance with age-of-sale laws is essential to reducing underage access to tobacco. We seek to develop a multilevel propensity score model (PSM) to predict retail violation of sales to minors (RVSM). METHODS: The Food and Drug Administration compliance check of tobacco retailers with minor-involved inspections from 2015 to 2019 (n=683 741) was linked with multilevel data for demographics and policies. Generalised estimating equation was used to develop the PSM using 2015-2016 data to predict the 2017 RVSM. The prediction accuracy of the PSM was validated by contrasting PSM deciles against 2018-2019 actual violation data. RESULTS: In 2017, 44.3% of 26 150 zip codes with ≥1 tobacco retailer had 0 FDA underage sales inspections, 11.0% had 1 inspection, 13.5% had 2-3, 15.3% had 4-9, and 15.9% had 10 or more. The likelihood of having an RVSM in 2017 was higher in zip codes with a lower number of inspections (adjusted OR (aOR)=0.988, 95% CI (0.987 to 0.990)) and penalties (aOR=0.97, 95% CI (0.95 to 0.99)) and a higher number of violations (aOR=1.07, 95% CI (1.06 to 1.08)) in the previous 2 years. Urbanicity, socioeconomic status, smoking prevalence and tobacco control policies at multilevels also predicted retail violations. Prediction accuracy was validated with zip codes with the highest 10% of the PSM 3.4 times more likely to have retail violations in 2019 than zip codes in the bottom decile. CONCLUSION: The multilevel PSM predicts the RVSM with a good rank order of retail violations. The model-based approach can be used to identify hot spots of retail violations and improve the sampling plan for future inspections.

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