Delamater Paul L, Herbert Lily, Golden Shelley D, Kong Amanda Y
Department of Geography and Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Nicotine Tob Res. 2025 Jan 22;27(2):217-224. doi: 10.1093/ntr/ntae190.
Tobacco retailer density and distance to tobacco retailers are understood to influence tobacco-related behaviors; however, there is no general agreement on how to best characterize or measure the tobacco retail environment (TRE). In this data-driven analysis, we examine similarities among neighborhood-level measures of the TRE and assess how the geographic resolution of the neighborhood units may affect them.
We used locations of likely tobacco retailers in the United States to calculate multiple retailer count, density, and distance measures. Measures were calculated at the Census block group, tract, and county (including county equivalents) levels of geographic aggregation. Spearman's correlation was used to evaluate the similarity among the TRE measures.
At the block group and tract level, correlation among all TRE measures ranged from slightly negative (ρ = -0.03) to nearly perfect (ρ = 0.99). At both levels of aggregation, distance-based TRE measures were highly correlated (ρ > 0.76). At the block group level, the simple count of retailers was highly correlated with the density measures (ρ > 0.83), and at the tract level, simple count was moderately to highly correlated with the density measures (ρ > 0.5). Findings were generally similar at the county level; a notable deviation was that retailers per person were negatively correlated with all other TRE measures (range from ρ = -0.08 to ρ = -0.32).
Some common measures were not correlated, suggesting they capture different aspects of the TRE; similarity among the various measures also varied by level of geographic aggregation.
Because the TRE shapes people's tobacco-related behaviors, using appropriate measures to characterize it at a neighborhood level is paramount. Our work highlights both the similarities and differences among a set of common measures, thereby suggesting the measures may be capturing different aspects of the overall retail environment. Our findings regarding geographic level of aggregation underscore the importance of neighborhood definition in any TRE analysis.
烟草零售商密度以及到烟草零售商的距离被认为会影响与烟草相关的行为；然而，对于如何最好地描述或衡量烟草零售环境（TRE），目前尚无普遍共识。在这项数据驱动的分析中，我们研究了邻里层面TRE衡量指标之间的相似性，并评估邻里单元的地理分辨率可能如何影响这些指标。
我们利用美国可能的烟草零售商位置来计算多个零售商数量、密度和距离指标。这些指标在人口普查街区组、普查区和县级（包括县级同等区域）地理聚合层面进行计算。使用斯皮尔曼相关性来评估TRE指标之间的相似性。
在街区组和普查区层面，所有TRE指标之间的相关性范围从略为负相关（ρ = -0.03）到几乎完全相关（ρ = 0.99）。在这两个聚合层面，基于距离的TRE指标高度相关（ρ > 0.76）。在街区组层面，零售商的简单计数与密度指标高度相关（ρ > 0.83），而在普查区层面，简单计数与密度指标呈中度到高度相关（ρ > 0.5）。在县级层面的结果总体上相似；一个显著的偏差是人均零售商数量与所有其他TRE指标呈负相关（范围从ρ = -0.08到ρ = -0.32）。
一些常见指标不相关，这表明它们捕捉到了TRE的不同方面；各种指标之间的相似性也因地理聚合层面而异。
由于TRE塑造了人们与烟草相关的行为，在邻里层面使用适当的指标来描述它至关重要。我们的工作突出了一组常见指标之间的异同，从而表明这些指标可能捕捉到了整体零售环境的不同方面。我们关于地理聚合层面的研究结果强调了在任何TRE分析中邻里定义的重要性。
