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Evaluating how licensing-law strategies will impact disparities in tobacco retailer density: a simulation in Ohio


Objectives To assess tobacco licensing-law strategies (eg, restricting the sale of tobacco near schools, banning the sale of tobacco in pharmacies) in terms of the equity of their impact and ability to correct existing disparities in tobacco retailer density.

Methods We geocoded all 11 392 tobacco retailers in Ohio, categorised neighbourhoods based on their demographic characteristics and calculated current disparities in tobacco retailer density. We next simulated the four main types of licensing-law strategies (capping-based, declustering-based, school-based and pharmacy-based), as well as strategy combinations. Finally, using statistical methods that account for residual spatial dependence, we evaluated how each strategy would impact density disparities.

Findings The most impactful licensing-law strategy depended on the type of community. School-based reductions were equitable for low-income, African–American and urban neighbourhoods (eg, eliminating retailers from 1000 feet of all schools produced a 9.2% reduction in the log retailer rate for neighbourhoods with a low prevalence of African–Americans and a 17.7% reduction for neighbourhoods with a high prevalence of African–Americans). Conversely, capping-based reductions were equitable for rural neighbourhoods. Pharmacy-based reductions demonstrated inequitable impacts.

Conclusion Licensing-law strategies could be a central tobacco control effort that benefits both the overall population and vulnerable communities. Policymakers will need to consider their community’s characteristics when selecting licensing-law strategies to correct (rather than inadvertently widen) density disparities. But when matched with the appropriate strategy, high-risk communities could remove over 20% of their tobacco retailers.

  • disparities
  • public policy
  • environment

Data availability statement

Data are available upon reasonable request. Data are publicly available; the cleaned dataset used by the authors is available from the authors upon request.

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