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Associations between summertime ambient pollutants and respiratory morbidity in New York City: Comparison of results using ambient concentrations versus predicted exposures

机译:纽约市夏季环境污染物与呼吸系统疾病之间的关系:使用环境浓度与预计暴露量的结果比较

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Epidemiological analyses of air quality often estimate human exposure from ambient monitoring data, potentially leading to exposure misclassification and subsequent bias in estimated health risks. To investigate this, we conducted a case-crossover study of summertime ambient ozone and fine particulate matter (PM 2.5) levels and daily respiratory hospitalizations in New York City during 2001-2005. Comparisons were made between associations estimated using two pollutant exposure metrics: observed concentrations and predicted exposures from the EPA's Stochastic Human Exposure and Dose Simulation (SHEDS) model. Small, positive associations between interquartile range mean ozone concentrations and hospitalizations were observed and were strongest for 0-day lags (hazard ratio (HR)=1.013, 95% confidence interval (CI): 0.998, 1.029) and 3-day lags (HR=1.006, 95% CI: 0.991, 1.021); applying mean predicted ozone exposures yielded similar results. PM 2.5 was also associated with admissions, strongest at 2-and 4-day lags, with few differences between exposure metrics. Subgroup analyses support recognized sociodemographic differences in concentration- related hospitalization risk, whereas few inter-stratum variations were observed in relation to SHEDS exposures. Predicted exposures for these spatially homogenous pollutants were similar across sociodemographic strata, therefore SHEDS predictions coupled with the case-crossover design may have masked observable heterogeneity in risks. However, significant effect modification was found for subjects in the top exposure-to-concentration ratio tertiles, suggesting risks may increase as a consequence of infiltration or greater exposure to outdoor air.
机译:空气质量的流行病学分析通常根据环境监测数据来估计人体暴露,这可能导致暴露分类错误以及随后对估计的健康风险造成偏见。为了对此进行调查,我们对2001-2005年纽约市的夏季环境臭氧和细颗粒物(PM 2.5)水平以及日常呼吸道住院情况进行了病例交叉研究。在使用两种污染物暴露指标进行估算的关联之间进行了比较:EPA随机人体暴露和剂量模拟(SHEDS)模型的观察浓度和预测暴露。观察到四分位数间距平均臭氧浓度与住院之间存在较小的正相关性,并且在0天滞后(危险比(HR)= 1.013,95%置信区间(CI):0.998,1.029)和3天滞后(HR = 1.006,95%CI:0.991,1.021);应用平均预测的臭氧暴露量得出相似的结果。 PM 2.5也与入院有关,在2天和4天的滞后时间中表现最强,暴露指标之间的差异很小。亚组分析支持与浓度有关的住院风险的公认的社会人口统计学差异,而与SHEDS暴露相关的层间差异很少。在社会人口统计各层中,这些空间均质污染物的预计暴露程度相似,因此,SHEDS预测与案例交叉设计相结合可能掩盖了可观察到的风险异质性。但是,对于暴露于浓度最高的三分位数中的受试者,发现了明显的效果改变,这表明由于渗透或更多地暴露于室外空气,风险可能会增加。

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