Department of Economics, Statistics, Mathematics and Sociology, University of Messina, Via Tommaso Cannizzaro 278, Messina, Italy.
Int J Health Geogr. 2011 Jan 27;10:11. doi: 10.1186/1476-072X-10-11.
The analysis of risk for the population residing and/or working in contaminated areas raises the topic of commuting. In fact, especially in contaminated areas, commuting groups are likely to be subject to lower exposure than residents. Only very recently environmental epidemiology has started considering the role of commuting as a differential source of exposure in contaminated areas. In order to improve the categorization of groups, this paper applies a gravitational model to the analysis of residential risk for workers in the Gela petrochemical complex, which began life in the early 60s in the municipality of Gela (Sicily, Italy) and is the main source of industrial pollution in the local area.
A logistic regression model is implemented to measure the capacity of Gela "central location" to attract commuting flows from other sites. Drawing from gravity models, the proposed methodology: a) defines the probability of finding commuters from municipalities outside Gela as a function of the origin's "economic mass" and of its distance from each destination; b) establishes "commuting thresholds" relative to the origin's mass. The analysis includes 367 out of the 390 Sicilian municipalities. Results are applied to define "commuters" and "residents" within the cohort of petrochemical workers. The study population is composed of 5,627 workers. Different categories of residence in Gela are compared calculating Mortality Rate Ratios for lung cancer through a Poisson regression model, controlling for age and calendar period. The mobility model correctly classifies almost 90% of observations. Its application to the mortality analysis confirms a major risk for lung cancer associated with residence in Gela.
Commuting is a critical aspect of the health-environment relationship in contaminated areas. The proposed methodology can be replicated to different contexts when residential information is lacking or unreliable; however, a careful consideration of the territorial characteristics ("insularity" and its impact on transportation time and costs, in our case) is suggested when specifying the area of application for the mobility analysis.
对居住和/或工作在污染地区的人群进行风险分析提出了通勤的问题。事实上，特别是在污染地区，通勤人群的暴露水平可能低于居民。直到最近，环境流行病学才开始将通勤作为污染地区暴露的一个差异源来考虑。为了改进群体分类，本文应用引力模型分析了位于意大利西西里岛杰拉市的杰拉石化综合体工人的居住风险，该综合体于 20 世纪 60 年代初建成，是当地主要的工业污染源。
实施逻辑回归模型来衡量杰拉“中心位置”吸引来自其他地区通勤者的能力。从引力模型出发，提出的方法：a）定义来自杰拉以外城市的通勤者出现在目的地的概率为原点的“经济质量”和距离的函数；b）建立相对于原点质量的“通勤阈值”。该分析包括西西里岛 390 个城市中的 367 个。结果用于定义石化工人队列中的“通勤者”和“居民”。研究人群由 5627 名工人组成。通过泊松回归模型计算肺癌死亡率比，在控制年龄和日历期的情况下，比较了在杰拉的不同居住类别。该移动模型正确地对近 90%的观察结果进行了分类。其在死亡率分析中的应用证实了与居住在杰拉相关的肺癌的主要风险。
通勤是污染地区健康与环境关系的一个关键方面。当居住信息缺失或不可靠时，可以将所提出的方法复制到不同的环境中；然而，当指定移动性分析的应用区域时，建议对地域特征（“孤岛”及其对交通时间和成本的影响）进行仔细考虑。
