PDF(Pubmed)
Abstract：
Numerous studies have reported adverse health effects of ambient air pollution on circulatory health outcomes mainly based on single-pollutant models. However, limited studies have focused on adjusted effect of multi-pollutant exposures on public health. This study aimed to examine short-term effects of three common air pollutants-ground-level ozone (ozone), nitrogen dioxide (NO2), and fine particulate matter (PM2.5)-through multi-pollutant models for mixed effect of adjustment. Daily data (circulatory hospitalization and mortality) and hourly data (air pollutants and temperature) were collected for 24 Canadian cities for 2001-2012. We applied generalized additive over-dispersion Poisson regression models with 1, 2, or 3 pollutants for city-specific risks, and Bayesian hierarchical models for national risks. This study found little mixed effect of adjustment through multi-pollutant models (ozone and/or NO2 and/or PM2.5) for circulatory hospitalization or mortality in Canada for 2001-2012, indicating that the 1-pollutant model did not result in considerable under- or over-estimates. It seemed weak-to-moderate correlations among air pollutants did not change the significant effect of one air pollutant after accounting for others. Inconsistent findings between other previous studies and this study indicate the need of comparable study design for multi-pollutant effect analysis.
摘要：
许多研究报告了主要基于单污染物模型的环境空气污染对循环健康结果的不利健康影响。然而,有限的研究集中在多污染物暴露对公共卫生的调整效应上。这项研究旨在研究三种常见的空气污染物-地面臭氧（臭氧）的短期影响。二氧化氮(NO2),和细颗粒物(PM2.5)-通过多污染物模型进行混合效应调节。收集了2001-2012年加拿大24个城市的每日数据（循环住院和死亡率）和每小时数据（空气污染物和温度）。我们应用了具有1、2或3种污染物的广义加性过分散泊松回归模型，用于城市特定风险，和国家风险的贝叶斯分层模型。这项研究发现，通过多污染物模型（臭氧和/或NO2和/或PM2.5）对2001-2012年加拿大的循环系统住院或死亡率的调整几乎没有混合效果，这表明1-污染物模型并没有导致相当多的低估或过度估计。空气污染物之间的弱至中度相关性似乎并没有改变一种空气污染物在考虑其他污染物后的显着影响。其他先前研究与本研究之间的不一致发现表明，需要对多污染物效应分析进行可比研究设计。
