Population intervention models to estimate ambient NO2 health effects in children with asthma.

Population intervention models to estimate ambient NO2 health effects in children with asthma.
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DOI:
10.1038/jes.2014.60
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发表时间:
2015-11
影响因子:
4.5
通讯作者:
Tager IB
Tager IB
中科院分区:
医学3区
文献类型:
--
作者:
Snowden JM;Mortimer KM;Kang Dufour MS;Tager IB

文献摘要

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环境空气污染对健康的影响在个别研究中最常表示为对空气污染变化的标准化单位的响应(例如,四分位数间隔),这被认为能够比较研究之间的结果。然而,这种方法并不一定会在现实世界的空气污染情况下传达健康影响。在本研究中,我们采用人口干预模型来估计空气污染干预的效果,明确参考观察到的暴露数据,并在这些数据中识别。我们计算了加州弗雷斯诺一组哮喘儿童夏季环境NO2与用力肺活量(FEF 25 -75)25%-75%之间用力呼气流量之间的关系。我们缩放效应大小,以反映夏季大部分时间的NO2减排。效应估计值较小,不精确,并且始终表明肺功能改善,NO2降低。效应范围为平均FEF 25 -75的−0.8%(95%置信区间:−3.4,1.7)至−3.3%(95%置信区间:−7.5,0.9)。最后,我们讨论的性质和可行性的暴露变化分析在这里观察到的空气污染概况,我们提出了额外的应用程序的人口干预模型在环境流行病学。
Health effects of ambient air pollution are most frequently expressed in individual studies as responses to a standardized unit of air pollution changes (e.g., an interquartile interval), which is thought to enable comparison of findings across studies. However, this approach does not necessarily convey health effects in terms of a real-world air pollution scenario. In the present study, we employ population intervention modeling to estimate the effect of an air pollution intervention that makes explicit reference to the observed exposure data and is identifiable in those data. We calculate the association between ambient summertime NO2 and forced expiratory flow between 25% and 75% of forced vital capacity (FEF25–75) in a cohort of children with asthma in Fresno, California. We scale the effect size to reflect NO2 abatement on a majority of summer days. The effect estimates were small, imprecise, and consistently indicated improved pulmonary function with decreased NO2. The effects ranged from −0.8% of mean FEF25–75 (95% Confidence Interval: −3.4 , 1.7) to −3.3% (95% CI: −7.5, 0.9). We conclude by discussing the nature and feasibility of the exposure change analyzed here given the observed air pollution profile, and we propose additional applications of the population intervention model in environmental epidemiology.