...
首页> 外文期刊>Inhalation toxicology >Vehicular traffic effects on survival within the Washington University-EPRI veterans cohort: new estimates and sensitivity studies.
【24h】

Vehicular traffic effects on survival within the Washington University-EPRI veterans cohort: new estimates and sensitivity studies.

机译:华盛顿大学-EPRI退伍军人队列中的车辆交通对生存的影响:新估计和敏感性研究。

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

We analyzed survival patterns among approximately 70,000 U.S. male military veterans relative to vehicular traffic density in their counties of residence, by mortality period and type of exposure model. Previous analyses show traffic density to be a better predictor than concentrations of criteria air pollutants. We considered all subjects and also the subset defined by availability of air quality monitoring data from the U.S. EPA PM(2.5) Speciation Trends Network (STN). Traffic density is a robust predictor of mortality in this cohort; statistically significant estimates of deaths associated with traffic range from 1.3% to 4.4%, depending on the method of analysis. This range of uncertainty is larger than the traditional 95% confidence intervals for each estimate (1-2%). Our best estimate of the relative risk for the entire follow-up period is 1.03. These deaths occurred mainly before 1997 in counties with STN air quality data, which tend to be more urban. We identified a threshold in mortality responses to traffic density, corresponding to county-average traffic flow rates of about 4000 vehicles/day. Relative risks were significantly higher in the more urban (STN) counties in the early subperiods, but this gradient appears to have diminished over time. We found larger risks by pooling results from separate portions of the overall follow-up period, relative to considering the entire period at once, which suggests temporal changes in confounding risk factors such as smoking cessation, for example. These results imply that the true uncertainties in cohort studies may exceed those indicated by the confidence intervals from a single modeling approach.
机译:我们根据死亡率和暴露模型的类型,分析了其居住县中约70,000名美国男性退伍军人相对于车辆交通密度的生存模式。先前的分析表明,交通密度比标准空气污染物的浓度更好。我们考虑了所有主题以及由美国EPA PM(2.5)物种趋势网络(STN)的空气质量监测数据的可用性定义的子集。交通密度是该队列中死亡率的有力预测指标。根据分析方法的不同,与交通相关的死亡人数具有统计学意义的估计范围为1.3%至4.4%。对于每个估计,此不确定性范围都大于传统的95%置信区间(1-2%)。我们对整个随访期的相对风险的最佳估计是1.03。这些死亡主要发生在1997年之前具有STN空气质量数据的县,这些县的城市人口更多。我们确定了对交通密度的死亡率响应阈值,对应于约4000辆/天的县平均交通流量。在早期亚市区中,相对城市县(STN)的相对风险明显更高,但是随着时间的流逝,这种梯度似乎有所减少。通过汇总整个随访期间各部分的结果,相对于同时考虑整个时期,我们发现了更大的风险,例如,这提示了混杂风险因素(例如戒烟)的时间变化。这些结果表明,队列研究中的真正不确定性可能超过单一建模方法的置信区间所表明的不确定性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号