A Bayesian analysis of the impact of air pollution episodes on cardio-respiratory hospital admissions in the Greater London area.
In this paper, we present a Bayesian hierarchical model to evaluate the effect of long-range and local range PM(10) during air pollution episodes on hospital admissions for cardio-respiratory diseases in Greater London. These episodes in 2003 are matched with the same periods during the previous year, used as a control. A baseline dose-response function is estimated for the controls and carried forward in the episodes, which are characterised by an additional component that estimates their specific effect on the health outcome.
Blangiardo
Marta
M
MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK. m.blangiardo@imperial.ac.uk
Richardson
Sylvia
S
Gulliver
John
J
Hansell
Anna
A
D000397:Air Pollution / Q000009:adverse effects* / Q000706:statistics & numerical data*; D001499:Bayes Theorem; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008131:London / Q000453:epidemiology; D008297:Male; D015233:Models, Statistical; D012140:Respiratory Tract Diseases / Q000453:epidemiology*; D018570:Risk Assessment / Q000706:statistics & numerical data