The analysis of the spatial distribution of cases could give important cues on putative environmental causes of a disease. We aimed to perform a spatial analysis of a 20-years period ALS cohort from the Piedmont and Aosta Valley ALS register (PARALS). METHODS:Address at the moment of diagnosis was considered for each ALS case. Municipalities' and census divisions' resident populations during the 1995-2014 period were obtained. Cluster analysis was performed adopting both Moran's Index and the Kulldorff's spatial scan statistic. RESULTS:A total of 2702 ALS patients were identified. Address was retrieved for 2671 (99%) patients. Moran's Index was -0.01 (p-value = 0.83) thus revealing no clusters. SatScan identified no statistically significant clusters. When census divisions were considered, Moran's Index resulted 0.13 (p-value = 0.45); SatScan revealed one statistically significant small cluster in the province of Alessandria. Here, 0.0099 cases were expected and 3 cases were observed (relative risk 304.60; 95% CI 109.83 - 845.88, p-value 0.03). DISCUSSION: Our study showed a substantial homogeneous distribution of ALS cases in Piedmont and Aosta Valley. The population-based setting and the adoption of proper statistical analyses strengthen the validity of our results. Such finding further suggests the involvement of multiple environmental and genetic factors in the ALS pathogenesis.
Spatial epidemiology of Amyotrophic Lateral Sclerosis in Piedmont and Aosta Valley, Italy: a population-based cluster analysis
Vasta, RFirst
;Calvo, A;Moglia, C;Cammarosano, S;Manera, U;Canosa, A;D'Ovidio, F;Chiò, A
2018-01-01
Abstract
The analysis of the spatial distribution of cases could give important cues on putative environmental causes of a disease. We aimed to perform a spatial analysis of a 20-years period ALS cohort from the Piedmont and Aosta Valley ALS register (PARALS). METHODS:Address at the moment of diagnosis was considered for each ALS case. Municipalities' and census divisions' resident populations during the 1995-2014 period were obtained. Cluster analysis was performed adopting both Moran's Index and the Kulldorff's spatial scan statistic. RESULTS:A total of 2702 ALS patients were identified. Address was retrieved for 2671 (99%) patients. Moran's Index was -0.01 (p-value = 0.83) thus revealing no clusters. SatScan identified no statistically significant clusters. When census divisions were considered, Moran's Index resulted 0.13 (p-value = 0.45); SatScan revealed one statistically significant small cluster in the province of Alessandria. Here, 0.0099 cases were expected and 3 cases were observed (relative risk 304.60; 95% CI 109.83 - 845.88, p-value 0.03). DISCUSSION: Our study showed a substantial homogeneous distribution of ALS cases in Piedmont and Aosta Valley. The population-based setting and the adoption of proper statistical analyses strengthen the validity of our results. Such finding further suggests the involvement of multiple environmental and genetic factors in the ALS pathogenesis.
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