These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: Spatiotemporal relationship between particle air pollution and respiratory emergency hospital admissions in Brisbane, Australia.
    Author: Chen L, Mengersen K, Tong S.
    Journal: Sci Total Environ; 2007 Feb 01; 373(1):57-67. PubMed ID: 17175007.
    Abstract:
    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 microm 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. 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 microg /m3 in PM10 in the single pollutant model. The association was weaker but still statistically significant (an increase of 2.6%; 95% CI: 1.0-5.5%) after adjusting for O3, 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.
    [Abstract] [Full Text] [Related] [New Search]