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Geographic distribution of amyotrophic lateral sclerosis through motor neuron disease mortality data

TitoloGeographic distribution of amyotrophic lateral sclerosis through motor neuron disease mortality data
Tipo di pubblicazioneArticolo su Rivista peer-reviewed
Anno di Pubblicazione2007
AutoriUccelli, Raffaella, Binazzi A., Altavista P., Belli S., Comba P., Mastrantonio Marina, and Vanacore N.
RivistaEuropean Journal of Epidemiology
Volume22
Paginazione781-790
Parole chiaveadult, aged, amyotrophic lateral sclerosis, article, cluster analysis, data base, Female, Geographic distribution, geography, human, Humans, international classification of diseases, Italy, male, methodology, Mortality, Motor Neuron Disease, Risk assessment
Abstract

Amyotrophic lateral sclerosis (ALS) is a rare and devastating neurological disorder of the adult age with a prognosis of about 2-3 years from the onset of the disease. No clear cause has been identified but it seems to be a multifactorial disease with genetic and environmental components involved. Increments of mortality rates were observed since 1980 both in Italy and in many other countries. The objective of the present study is to describe the distribution of ALS mortality in Italy in the period 1980-2001 detecting single municipalities or clusters with high mortality levels for motor neuron disease (MND). ALS represents the main part (85%) of the MND group which is globally identified by the IX ICD (International Classification of Diseases and Causes of Death) 335.2 code. Death numbers and standardized mortality ratios (SMR) for MND were calculated for all Italian municipalities through the ENEA mortality database system (data source: National Institute of Statistics-ISTAT), using national mortality rates as reference. Subsequently, in order to detect municipal clusters, spatial analysis was performed. Out of the 8,099 Italian municipalities, 132 where characterized by SMR values higher than expected. Moreover 16 clusters with significant high relative risk values (RR) were identified, 12 out of them including only a single municipality. Only 22 of the municipalities with high SMR were included in the clusters. In conclusion, the two different epidemiological methodologies demonstrated to be widely complementary in detecting the geographical distribution of the disease in terms of risk for populations. A first selection of the priority areas where analytical studies should be carried on, in order to identify risk factors associated to ALS, is tentatively suggested. © 2007 Springer Science+Business Media B.V.

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-36148984645&doi=10.1007%2fs10654-007-9173-7&partnerID=40&md5=948e61d9d93ebb8ef8cf85e6f7450a8b
DOI10.1007/s10654-007-9173-7
Citation KeyUccelli2007781