A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London
A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London
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DOI：
10.1016/j.sste.2014.05.001
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发表时间：
2014-07-01
影响因子：
3.4
通讯作者：
Mitchell, Richard
中科院分区：
文献类型：
--
作者：
Rushworth, Alastair;Lee, Duncan;Mitchell, Richard
空气污染对人体健康的危害早已为人们所知，因为许多流行病学研究已经对其影响进行了研究。总的来说，这些研究调查了污染的急性和慢性影响，后者通常基于个人水平的队列设计，实施起来可能很昂贵。由于小面积统计数据的可得性越来越大，生态时空研究设计也在使用，其中一个关键的统计问题是允许在去除协变量效应后仍然存在的残余时空自相关。我们提出了一个新的模型来估计空气污染对人类健康的影响，它允许残留的时空自相关，并在英国大伦敦的空气污染对人类健康的长期影响的研究。通过使用单一污染物模型和多种污染物指数，探讨了不同污染物的单独和联合影响。(C)2014作者爱思唯尔有限公司出版
It has long been known that air pollution is harmful to human health, as many epidemiological studies have been conducted into its effects. Collectively, these studies have investigated both the acute and chronic effects of pollution, with the latter typically based on individual level cohort designs that can be expensive to implement. As a result of the increasing availability of small-area statistics, ecological spatio-temporal study designs are also being used, with which a key statistical problem is allowing for residual spatio-temporal autocorrelation that remains after the covariate effects have been removed. We present a new model for estimating the effects of air pollution on human health, which allows for residual spatio-temporal autocorrelation, and a study into the long-term effects of air pollution on human health in Greater London, England. The individual and joint effects of different pollutants are explored, via the use of single pollutant models and multiple pollutant indices. (C) 2014 The Authors. Published by Elsevier Ltd.