Schwartz Joel, Sarnat Jeremy A, Coull Brent A, Wilson William E
Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA.
J Expo Sci Environ Epidemiol. 2007 Dec;17 Suppl 2:S2-10. doi: 10.1038/sj.jes.7500619.
Ascertaining the true risk associated with exposure to particulate matter (PM) is difficult, given the fact that pollutant components are frequently correlated with each other and with other gaseous pollutants; relationships between ambient concentrations and personal exposures are often not well understood; and PM, unlike its gaseous co-pollutants, does not represent a single chemical. In order to examine differences between observed versus true health risk estimate from epidemiologic studies, we conducted a simulation using data from a recent multi-pollutant exposure assessment study in Baltimore, MD. The objectives of the simulation were twofold: (a) to estimate the distribution of personal air pollutant exposures one might expect to observe within a population, given the corresponding ambient concentrations found in that location and; (b) using an assumed true health risk with exposure to one pollutant, to estimate the distribution of health risk estimates likely to be observed in an epidemiologic study using ambient pollutant concentrations as a surrogate of exposure as compared with actual personal pollutant exposures. Results from the simulations showed that PM2.5 was the only pollutant where a true association with its total personal exposures resulted in a significant observed association with its ambient concentrations. The simulated results also showed that true health risks associated with personal exposure to O3 and NO2 would result in no significant observed associations with any of their respective ambient concentrations. Conversely, a true association with PM2.5 would result in a significant, observed association with NO2 (beta=0.0115, 95% confidence interval (CI): 0.0056, 0.0185) and a true association with exposure to SO4(2-) would result in an observed significant association with O3 (beta=0.0035, 95% CI: 0.0021, 0.0051) given the covariance of the ambient pollutant concentrations. The results provide an indication that, in Baltimore during this study period, ambient gaseous concentrations may not have been adequate surrogates for corresponding personal gaseous exposures to allow the question to be investigated using central site monitors. Alternatively, the findings may suggest that in some locations, observed associations with the gaseous pollutants should be interpreted with caution, as they may be reflecting associations with PM or one of its chemical components.
鉴于污染物成分之间以及与其他气态污染物之间经常相互关联；环境浓度与个人暴露之间的关系往往尚未得到充分理解；而且与气态共同污染物不同，颗粒物并非单一化学物质，因此确定与接触颗粒物（PM）相关的真正风险很困难。为了研究流行病学研究中观察到的健康风险估计值与真实健康风险估计值之间的差异，我们利用来自马里兰州巴尔的摩市最近一项多污染物暴露评估研究的数据进行了模拟。模拟的目标有两个：（a）根据该地点相应的环境浓度，估计人群中个人空气污染物暴露可能观察到的分布；（b）假设暴露于一种污染物时的真实健康风险，估计在流行病学研究中，使用环境污染物浓度作为暴露替代指标与实际个人污染物暴露相比，可能观察到的健康风险估计值的分布。模拟结果表明，PM2.5是唯一一种其与个人总暴露的真实关联导致与环境浓度有显著观察关联的污染物。模拟结果还表明，个人暴露于O3和NO2的真实健康风险不会导致与它们各自的任何环境浓度有显著观察关联。相反，与PM2.5的真实关联会导致与NO2有显著的观察关联（β = 0.0115，95%置信区间（CI）：0.0056，0.0185），并且与暴露于SO4(2-)的真实关联会导致与O3有观察到的显著关联（β = 0.0035，95% CI：0.0021，0.0051），这是考虑到环境污染物浓度的协方差。结果表明，在本研究期间的巴尔的摩，环境气态浓度可能不足以作为相应个人气态暴露的替代指标，无法通过中心站点监测器来研究这个问题。或者，研究结果可能表明，在某些地点，与气态污染物的观察关联应谨慎解释，因为它们可能反映的是与PM或其化学成分之一的关联。
