Spatiotemporal relationship between particle air pollution and respiratory emergency hospital admissions in Brisbane, Australia

被引:42
|
作者
Chen, Linping
Mengersen, Kerrie
Tong, Shilu
机构
[1] Queensland Univ Technol, Sch Publ Hlth, Brisbane, Qld, Australia
[2] Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld, Australia
[3] Queensland Univ Technol, Sch Math Sci, Brisbane, Qld, Australia
基金
澳大利亚研究理事会; 英国医学研究理事会;
关键词
particulate matter; respiratory emergency hospital admissions; poisson generalised linear model; meta-analysis;
D O I
10.1016/j.scitotenv.2006.10.050
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The nature of spatial variation in the relationship between air pollution and health outcomes within a city remains an open and important question. This study investigated the spatial variability of particle matter air pollution and its association with respiratory emergency hospital admissions across six geographic areas in Brisbane, Australia. Data on particles of 10 mu m or less in aerodynamic diameter per cubic metre (PM10), meteorological conditions, and daily respiratory emergency hospital admissions were obtained for the period of I January 1998 to 31 December 2001. A Poisson generalised linear model was used to estimate the specific effects of PM10 on respiratory emergency hospital admissions for each geographic area. A pooled effect of PM10 was then estimated using a meta-analysis approach for the whole city. The results of this study indicate that the magnitude of the association between particulate matter and respiratory emergency hospital admissions varied across different geographic areas in Brisbane. This relationship appeared to be stronger in areas with heavy traffic. We found an overall increase of 4.0% (95% confidence interval [CI]: 1.1-6.9%) in respiratory emergency hospital admissions associated with an increase of 10 mu g/m(3) in PM10 in the single pollutant model. The association was weaker but still statistically significant (an increase of 2.6%; 95% Cl: 1.0-5.5%) after adjusting for O-3, but did not appear to be affected by NO2. The effect estimates of PM10 were generally consistent for three spatial methods used in this study, but appeared to be underestimated if the spatial nature of the data was ignored. Therefore, the spatial variation in the relationship between PM10 and health outcomes needs to be considered when the health impact of air pollution is assessed, particularly for big cities. Crown Copyright (c) 2006 Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:57 / 67
页数:11
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