Sensitivity analysis of the relationship between disease occurrence and distance from a putative source of pollution

Dreassi, Emanuela and Lagazio, Corrado and Maule M., Milena and Magnani, Corrado and Biggeri, Annibale (2008) Sensitivity analysis of the relationship between disease occurrence and distance from a putative source of pollution. Geospatial health , 2 (2). pp. 263-271. ISSN 1970-7096

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The relation between disease risk and a point source of pollution is usually investigated using distance from the source as a proxy of exposure. The analysis may be based on case-control data or on aggregated data. The definition of the function relating risk of disease and distance is critical, both in a classical and in a Bayesian framework, because the likelihood is usually very flat, even with large amounts of data. In this paper we investigate how the specification of the function relating risk of disease with distance from the source and of the prior distributions on the parameters of the function affects the results when case-control data and Bayesian methods are used. We consider different popular parametric models for the risk distance function in a Bayesian approach, comparing estimates with those derived by maximum likelihood. As an example we have analyzed the relationship between a putative source of environmental pollution (an asbestos cement plant) and the occurrence of pleural malignant mesothelioma in the area of Casale Monferrato (Italy) in 1987-1993. Risk of pleural malignant mesothelioma turns out to be strongly related to distance from the asbestos cement plant. However, as the models appeared to be sensitive to modeling choices, we suggest that any analysis of disease risk around a putative source should be integrated with a careful sensitivity analysis and possibly with prior knowledge. The choice of prior distribution is extremely important and should be based on epidemiological considerations

Item Type: Article
Uncontrolled Keywords: case-control study, environmental pollution, absestos, focused clustering, hierarchical Bayesian models, sensitivity to prior choice
Subjects: 300 Scienze sociali > 360 Problemi e servizi sociali; associazioni > 363 Altri problemi e servizi sociali > 363.7 Problemi ambientali (classificare qui la tutela ambientale; l’effetto dei rifiuti, dell’inquinamento, delle iniziative per controllarli) > 363.73 Inquinamento
Depositing User: Users 66 not found.
Date Deposited: 23 Jul 2010 09:42
Last Modified: 12 Oct 2010 10:08

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