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一种用于估算空气污染对大伦敦地区呼吸科住院长期影响的时空模型。

A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London.

作者信息

Rushworth Alastair, Lee Duncan, Mitchell Richard

机构信息

School of Mathematics and Statistics, University Gardens, University of Glasgow, Glasgow G12 8QW, UK.

School of Mathematics and Statistics, University Gardens, University of Glasgow, Glasgow G12 8QW, UK.

出版信息

Spat Spatiotemporal Epidemiol. 2014 Jul;10:29-38. doi: 10.1016/j.sste.2014.05.001. Epub 2014 Jul 15.

Abstract

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.

摘要

长期以来,人们都知道空气污染对人类健康有害,因为已经进行了许多关于其影响的流行病学研究。总体而言,这些研究调查了污染的急性和慢性影响,后者通常基于个体水平队列设计,实施起来可能成本高昂。由于小区域统计数据的可得性不断提高,生态时空研究设计也在被使用,与之相关的一个关键统计问题是如何考虑在去除协变量效应后仍存在的残余时空自相关性。我们提出了一种用于估计空气污染对人类健康影响的新模型,该模型考虑了残余时空自相关性,并对英国大伦敦地区空气污染对人类健康的长期影响进行了研究。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个体和联合效应。

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