Strand Matthew, Vedal Sverre, Rodes Charles, Dutton Steven J, Gelfand Erwin W, Rabinovitch Nathan
Division of Biostatistics, National Jewish Medical and Research Center, Denver, CO, USA.
J Expo Sci Environ Epidemiol. 2006 Jan;16(1):30-8. doi: 10.1038/sj.jea.7500434.
Most air pollution and health studies conducted in recent years have examined how a health outcome is related to pollution concentrations from a fixed outdoor monitor. The pollutant effect estimate in the health model used indicates how ambient pollution concentrations are associated with the health outcome, but not how actual exposure to ambient pollution is related to health. In this article, we propose a method of estimating personal exposures to ambient PM(2.5) (particulate matter less than 2.5 microm in diameter) using sulfate, a component of PM(2.5) that is derived primarily from ambient sources. We demonstrate how to use regression calibration in conjunction with these derived values to estimate the effects of personal ambient PM(2.5) exposure on a continuous health outcome, forced expiratory volume in 1 s (FEV(1)), using repeated measures data. Through simulation, we show that a confidence interval (CI) for the calibrated estimator based on large sample theory methods has an appropriate coverage rate. In an application using data from our health study involving children with moderate to severe asthma, we found that a 10 microg/m3 increase in PM(2.5) was associated with a 2.2% decrease in FEV(1) at a 1-day lag of the pollutant (95% CI: 0.0-4.3% decrease). Regressing FEV(1) directly on ambient PM(2.5) concentrations from a fixed monitor yielded a much weaker estimate of 1.0% (95% CI: 0.0-2.0% decrease). Relatively small amounts of personal monitor data were needed to calibrate the estimate based on fixed outdoor concentrations.
近年来开展的大多数空气污染与健康研究，都考察了健康结果与固定室外监测器所测污染浓度之间的关系。所用健康模型中的污染物效应估计值，表明了环境污染浓度与健康结果之间的关联，但并未表明实际接触环境污染物与健康之间的关系。在本文中，我们提出一种利用硫酸盐来估算个人对环境细颗粒物（直径小于2.5微米的颗粒物）暴露量的方法，硫酸盐是细颗粒物的一种成分，主要来源于环境源。我们展示了如何结合这些推导值使用回归校准，来利用重复测量数据估算个人环境细颗粒物暴露对连续健康结果（1秒用力呼气量，FEV₁）的影响。通过模拟，我们表明基于大样本理论方法的校准估计量的置信区间（CI）具有适当的覆盖率。在一项应用中，我们利用来自针对中重度哮喘儿童的健康研究的数据发现，细颗粒物每增加10微克/立方米，在污染物滞后1天时，FEV₁会降低2.2%（95%置信区间：降低0.0 - 4.3%）。直接将FEV₁对固定监测器所测环境细颗粒物浓度进行回归，得到的估计值要弱得多，为1.0%（95%置信区间：降低0.0 - 2.0%）。校准基于固定室外浓度的估计值所需的个人监测数据量相对较少。
