Reducing the number of retailers that sell tobacco products could benefit public health, but the strategies for doing so should be adjusted to account for differing community characteristics, according to new research from the Brown School at Washington University in St. Louis.
Researchers used a computational model they had developed, Tobacco Town, to simulate smokers’ buying behavior. They then studied the potential effects of four different types of retailer reduction policies: Capping the number of retailers, restricting the type of retailer that could sell tobacco (e.g., pharmacies), limiting proximity of retailers to schools, and limiting the proximity of retailers to each other.
They found that reducing retailer density can decrease accessibility of tobacco by driving up search and purchase costs. Proximity policies worked better in dense urban areas, while retailer type and random retail reduction worked better in suburban settings.
“There is not a ‘one size fits all’ retailer reduction policy,” wrote lead author Douglas A. Luke, professor and director of the Center for Public Health Systems Science at the Brown School. “Communities are far more likely to see public health benefits if they combine multiple retailer reduction strategies with strong traditional tobacco control efforts rather than relying on one policy to do everything.”
The study, “Tobacco Town: Computational Modeling of Policy Options to Reduce Tobacco Retailer Density,” was published in the May issue of the American Journal of Public Health.