Harvard School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA 02215, USA.
Int J Environ Res Public Health. 2011 Sep;8(9):3688-711. doi: 10.3390/ijerph8093688. Epub 2011 Sep 13.
Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors.
基于社区的累积风险评估需要对多种化学和非化学应激因素进行特征描述，并考虑非化学应激因素可能如何影响化学应激因素的风险。由于住宅氡的归因风险较大、与吸烟相互作用以及氡浓度和吸烟模式的显著差异，因此它为这一问题提供了一个有趣的案例。尽管如此，迄今为止，尚无研究以允许将氡纳入基于社区的累积风险评估的方式来估计氡和吸烟的地理和社会人口统计学模式。在这项研究中，我们应用多层次回归模型来解释基于住房特征和地质变量的氡变异性，并使用美国人口普查数据构建一个预测住房特征的回归模型。基于与住房模型共有的预测因子的吸烟多层次回归模型使我们能够将暴露情况联系起来。我们估计，全县平均终生肺癌风险从每 100 人中 0.15 到 1.8 不等，在预测氡和吸烟率较高的地区和亚人群中存在高风险集群。我们的研究结果表明，通过一种可以推广到多种化学和非化学应激因素的方法，进行筛选水平评估以描述氡引起的肺癌风险模式是可行的。
