Objectives. To identify the behavioral mechanisms and effects of tobacco control policies designed to reduce tobacco retailer density.Methods. We developed the Tobacco Town agent-based simulation model to examine 4 types of retailer reduction policies: (1) random retailer reduction, (2) restriction by type of retailer, (3) limiting proximity of retailers to schools, and (4) limiting proximity of retailers to each other. The model examined the effects of these policies alone and in combination across 4 different types of towns, defined by 2 levels of population density (urban vs suburban) and 2 levels of income (higher vs lower).Results. Model results indicated that reduction of retailer density has the potential to decrease accessibility of tobacco products by driving up search and purchase costs. Policy effects varied by town type: proximity policies worked better in dense, urban towns whereas retailer type and random retailer reduction worked better in less-dense, suburban settings.Conclusions. Comprehensive retailer density reduction policies have excellent potential to reduce the public health burden of tobacco use in communities.
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机译：目标。确定旨在降低烟草零售商密度的烟草控制政策的行为机制和效果。我们开发了基于Tobacco Town Agent的模拟模型，以研究4种减少零售商的政策：（1）随机减少零售商；（2）限制零售商的类型；（3）限制零售商与学校的距离；以及（4）限制零售商彼此之间的距离。该模型单独检查了这些政策的效果，并结合了4种不同类型城镇的效果，分别定义为2个人口密度水平（城市与郊区）和2个收入水平（较高与较低）。模型结果表明，零售商密度的降低有可能通过提高搜索和购买成本来降低烟草产品的可及性。政策效果因城镇类型而异：在人口密集的城镇中，就近政策效果更好，而在密度较低的郊区环境中，零售商类型和随机零售商减少效果更好。全面的零售商密度降低政策在减少社区烟草使用的公共卫生负担方面具有巨大潜力。
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