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中国上海每日细颗粒物污染对脑血管病死亡率的急性影响:一项基于人群的时间序列研究。

Acute effect of daily fine particulate matter pollution on cerebrovascular mortality in Shanghai, China: a population-based time series study.

机构信息

Department of Applied Statistics, School of Business, Örebro University, Örebro, Sweden.

Center for Assessment of Medical Technology in Örebro, Örebro University Hospital, Örebro, Sweden.

出版信息

Environ Sci Pollut Res Int. 2019 Sep;26(25):25491-25499. doi: 10.1007/s11356-019-05689-8. Epub 2019 Jul 1.

Abstract

Numerous studies have investigated the impacts of ambient fine particulate matter (PM) on human health. In this study, we examined the association of daily PM concentrations with the number of deaths for the cerebrovascular disease on the same day, using the generalized additive model (GAM) controlling for temporal trend and meteorological variables. We used the data between 2012 and 2014 from Shanghai, China, where the adverse health effects of PM have been of particular concern. Three different approaches (principal component analysis, shrinkage smoothers, and the least absolute shrinkage and selection operator regularization) were used in GAM to handle multicollinear meteorological variables. Our results indicate that the average daily concentration of PM in Shanghai was high, 55 μg/m, with an average daily death for cerebrovascular disease (CVD) of 62. There was 1.7% raised cerebrovascular disease deaths per 10 μg/m increase in PM concentration in the unadjusted model. However, PM concentration was no longer associated with CVD deaths after controlling for meteorological variables. The results were consistent in the three modelling techniques that we used. As a large number of people are exposed to air pollution, further investigation with longer time period including individual-level information is needed to examine the association.

摘要

大量研究已经调查了环境细颗粒物(PM)对人类健康的影响。在这项研究中,我们使用广义加性模型(GAM)控制时间趋势和气象变量,检查了每日 PM 浓度与同一天脑血管病死亡人数之间的关联。我们使用了 2012 年至 2014 年期间中国上海的数据,其中 PM 的不良健康影响尤其受到关注。在 GAM 中使用了三种不同的方法(主成分分析、收缩平滑器和最小绝对收缩和选择算子正则化)来处理多共线性气象变量。我们的结果表明,上海的 PM 平均日浓度较高,为 55 μg/m,平均每日脑血管病(CVD)死亡人数为 62 人。在未调整模型中,PM 浓度每增加 10 μg/m,脑血管病死亡率升高 1.7%。然而,在控制气象变量后,PM 浓度与 CVD 死亡之间不再相关。我们使用的三种建模技术的结果是一致的。由于大量人暴露于空气污染,需要进行进一步的调查,包括更长的时间周期和个体层面的信息,以检查这种关联。

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