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Spatial epidemiology of amyotrophic lateral sclerosis in Piedmont and Aosta Valley, Italy: a population‐based cluster analysis
Author(s) -
Vasta R.,
Calvo A.,
Moglia C.,
Cammarosano S.,
Manera U.,
Canosa A.,
D'Ovidio F.,
Mazzini L.,
Chiò A.
Publication year - 2018
Publication title -
european journal of neurology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.881
H-Index - 124
eISSN - 1468-1331
pISSN - 1351-5101
DOI - 10.1111/ene.13586
Subject(s) - amyotrophic lateral sclerosis , scan statistic , demography , confidence interval , medicine , epidemiology , population , cluster (spacecraft) , census , statistic , geography , cartography , environmental health , disease , statistics , pathology , mathematics , sociology , computer science , programming language
Background and purpose The analysis of the spatial distribution of cases could give important cues on putative environmental causes of a disease. Our aim was to perform a spatial analysis of an amyotrophic lateral sclerosis (ALS) cohort from the Piedmont and Aosta Valley ALS register (PARALS) over a 20‐year period. Methods The 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. A cluster analysis was performed adopting both Moran's index and the Kulldorff spatial scan statistic. Results A total of 2702 ALS patients were identified. An 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 was 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 three cases were observed (relative risk 304.60; 95% confidence interval 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 a finding further suggests the involvement of multiple environmental and genetic factors in ALS pathogenesis.