title: A Bayesian analysis of the impact of air pollution episodes on cardio-respiratory hospital admissions in the Greater London area.
abstract: 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.
authors.affiliation: 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
authors.forename: Marta
authors.initials: M
authors.lastname: Blangiardo
authors.forename: Sylvia
authors.initials: S
authors.lastname: Richardson
authors.forename: John
authors.initials: J
authors.lastname: Gulliver
authors.forename: Anna
authors.initials: A
authors.lastname: Hansell
mesh_terms: 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