Estimating the effects of environmental exposures using a weighted mean of monitoring stations
Date
2012
Authors
Barnett, Adrian
Vaneckova, P
Clements, Archie
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Publisher
Elsevier BV
Abstract
The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.
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Keywords
Keywords: air pollution; article; Australia; Bayes theorem; death; environmental exposure; hospital admission; priority journal; Air Pollution; Australia; Bayes Theorem; Environmental Exposure; Environmental Monitoring; Hospitalization; Humans; Mortality; Particula Air pollution; Spatial analysis; Temperature; Time series
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Source
Spatial and Spatio-temporal Epidemiology
Type
Journal article
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Restricted until
2037-12-31
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