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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Amyotrophic lateral sclerosis in Piedmont (Italy): a Bayesian spatial analysis of the incident cases
Giuseppe Migliaretti1, Paola Berchialla, Paola Dalmasso
1Department of Public Health and Microbiology, University of Turin, Turin, Italy. giuseppe.migliaretti@unito.it
Abstract:
In the analysis of risk factors in amyotrophic lateral sclerosis (ALS), few ecological studies, based on the relationship between the distribution of the patients in a given area and the environmental exposures, have been performed. The aim of our study was to depict the spatial risk distribution of ALS in Piedmont's resident population during the period 1995-2004. Data were collected from the Piedmont and Aosta Valley Register for ALS, which is a prospective epidemiological archive for gathering all the ALS incident cases in north-western Italy. Only cases from Piedmont were considered. The Besag, York and Molliè model was used to estimate smoothed standardized incidence ratios (SIR) by municipalities either overall or stratified by gender and age class. Results demonstrated that excess of risk was particularly evident in the area of Cuneo, Alessandria and Vercelli (SIR > 1.2). The results were evident for both genders, but in particular for males aged 35-60 years. Given the geographic distribution of rural areas, our results suggest that the environmental exposure to agricultural chemicals could be possibly linked to this pattern. Despite some limits of the spatial analysis in the study of rare diseases, results appear coherent with literature data, stimulating other in-depth analysis in this field of research.
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