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首页> 外文期刊>Environmental Health: A Global Access Science Source >Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies
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Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies

机译:PM 2.5 健康影响研究中的暴露测量误差:八项个人暴露验证研究的汇总分析

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摘要

Background Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures. Methods Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5. Conclusions Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies.
机译:背景暴露量度测量误差是使用环境浓度作为暴露量的长期PM2.5健康研究中的一个问题。我们通过将校准系数作为验证研究中的个人PM2.5暴露量与通常可用的替代暴露量之间的关联性来估计误差值。方法每天收集个人和周围的PM2.5,并在可用硫酸盐的情况下,在2到12天内对9个城市进行测量。真实暴露定义为个人暴露于环境PM2.5。由于只能确定五个城市的环境PM2.5浓度,因此还考虑了个人暴露于PM2.5的总量。代理人的暴露被估计为最近的监视器处的环境PM2.5或预测的室外被摄对象的家。我们通过对随机效应模型中的替代暴露量进行真实回归来估算校准系数。结果当使用每月平均的周围环境个人PM2.5作为真实暴露时,最近的显示器的校准系数等于0.31(95%CI:0.14,0.47),而对于室外房屋的预测则等于0.54(95%CI:0.42,0.65) 。两次曝光均未发现户外家用PM2.5的城市间异质性。对于最近的监控器PM2.5而言​​,对于两次真实曝光而言,异质性都很显着,但在针对个人总PM2.5调整城市平均机动车数量之后,异质性并不明显。结论校准系数<1,与先前报道的慢性健康风险一致,因为当环境浓度为目标暴露量时,最近的监测器暴露量被低估了。对于户外房屋预测,校准系数接近于1,可能反映出较小的空间误差。需要进一步的研究,以确定如何将我们的发现纳入未来的健康研究。

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