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

  • Chen, Linping
  • Mengersen, Kerrie L.
  • Tong, Shilu
Publication Date
Feb 01, 2007
Queensland University of Technology ePrints Archive
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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 by different exposure measurements. Data on particles of 10 microns or less in aerodynamic diameter per cubic metre (PM10), meteorological conditions, and daily respiratory emergency hospital admissions were obtained for the period of 1 January 1998 to 31 December 2001. 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 10µg /m3 in PM10 in the single pollutant model. The association became weaker (an increase of 2.6%; 95% CI: 1.05.5%) after adjusting for O3, but did not appear to be confounded by NO2. Our study also indicated that the estimated effects of PM10 were quite similar for three spatial methods used in this study, but may be underestimated if the spatial nature of the data is ignored (for example, by using the average levels of air pollutants from a few monitoring stations or from a single monitoring station). The spatial variation in the relationship between PM10 and health outcomes needs to be taken into consideration for big cities.

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