Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA.
Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond, VA 23298, USA.
Int J Environ Res Public Health. 2022 Jan 20;19(3):1134. doi: 10.3390/ijerph19031134.
Tobacco causes 29% of cancer-related deaths while alcohol causes 5.5% of cancer-related deaths. Reducing the consumption of these cancer-causing products is a special priority area for the National Cancer Institute. While many factors are linked to tobacco and alcohol use, the placement and density of retail outlets within neighborhoods may be one community-level risk factor contributing to greater use of these products. To elucidate associations between tobacco, alcohol, and tobacco and alcohol retail outlets (TRO, ARO, and TARO) and neighborhood disadvantage over a large geographic area, we employed a novel Bayesian index modeling approach to estimate a neighborhood disadvantage index (NDI) and its associations with rates of the three types of retailers across block groups in the state of North Carolina. We used a novel extension of the Bayesian index model to include a shared component for the spatial pattern common to all three types of outlets and NDI effects that varied by outlet type. The shared component identifies areas that are elevated in risk for all outlets. The results showed significant positive associations between neighborhood disadvantage and TROs (relative risk (RR) = 1.12, 95% credible interval (CI = 1.09, 1.14)) and AROs (RR = 1.15, 95% CI = 1.11, 1.17), but the association was greatest for TAROs (RR = 1.21, 95% CI = 1.18, 1.24). The most important variables in the NDI were percent renters (i.e., low home ownership), percent of homes built before 1940 (i.e., old housing stock), and percent without a high school diploma (i.e., low education).
烟草导致 29%的癌症相关死亡,而酒精导致 5.5%的癌症相关死亡。减少这些致癌产品的消费是国家癌症研究所的一个特别优先领域。虽然许多因素与烟草和酒精使用有关,但社区内零售店的位置和密度可能是导致这些产品使用增加的一个社区层面的风险因素。为了阐明在广大地理区域内,烟草、酒精以及烟草和酒精零售点(TRO、ARO 和 TARO)与邻里劣势之间的关联,我们采用了一种新颖的贝叶斯指数建模方法来估计邻里劣势指数(NDI)及其与北卡罗来纳州街区组内三种零售商类型的比率之间的关联。我们使用了贝叶斯指数模型的一个新颖扩展,包括了所有三种类型的零售商和 NDI 效应的共同空间模式的共享组件,这些效应因零售商类型而异。共享组件确定了所有零售商风险升高的区域。结果表明,邻里劣势与 TRO(相对风险 (RR) = 1.12,95%置信区间 (CI) = 1.09, 1.14) 和 ARO(RR = 1.15,95% CI = 1.11, 1.17)之间存在显著正相关,但 TARO 的相关性最大(RR = 1.21,95% CI = 1.18, 1.24)。NDI 中最重要的变量是租客比例(即低住房拥有率)、建于 1940 年以前的房屋比例(即旧住房存量)和没有高中文凭的比例(即低教育水平)。