title: Investigating trends in asthma and COPD through multiple data sources: A small area study.
abstract: This paper investigates trends in asthma and COPD by using multiple data sources to help understanding the relationships between disease prevalence, morbidity and mortality. GP drug prescriptions, hospital admissions, and deaths are analysed at clinical commissioning group (CCG) level in England from August 2010 to March 2011. A Bayesian hierarchical model is used for the analysis, which takes into account the complex space and time dependencies of asthma and COPD, while it is also able to detect unusual areas. Main findings show important discrepancies across the different data sources, reflecting the different groups of patients that are represented. In addition, the detection mechanism that is provided by the model, together with inference on the spatial, and temporal variation, provide a better picture of the respiratory health problem.
authors.affiliation: Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK. Electronic address: a.boulieri@imperial.ac.uk.
authors.forename: Areti
authors.initials: A
authors.lastname: Boulieri
authors.affiliation: UK Small Area Health Statistics Unit, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK; Imperial College Healthcare NHS Trust, London, UK.
authors.forename: Anna
authors.initials: A
authors.lastname: Hansell
authors.affiliation: Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK.
authors.forename: Marta
authors.initials: M
authors.lastname: Blangiardo
mesh_terms: D000397:Air Pollution / Q000009:adverse effects; D001249:Asthma / Q000453:epidemiology* / Q000209:etiology / Q000401:mortality / Q000517:prevention & control; D001499:Bayes Theorem; D004739:England; D006801:Humans; D015995:Prevalence; D029424:Pulmonary Disease, Chronic Obstructive / Q000453:epidemiology* / Q000209:etiology / Q000401:mortality / Q000517:prevention & control; D012621:Seasons; D062211:Spatio-Temporal Analysis; D013222:State Medicine / Q000706:statistics & numerical data
keywords: Asthma and COPD; Detection; Space-time analysis