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1.
Environ Res ; 145: 68-73, 2016 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-26624240

RESUMO

BACKGROUND: Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating disease of the central nervous system, characterized by recurrent relapses of inflammation that cause mild to severe disability. Exposure to airborne particulate matter (PM) has been associated with acute increases in systemic inflammatory responses and neuroinflammation. In the present study, we hypothesize that exposure to PM<10µm in diameter (PM10) might increase the occurrence of MS-related hospitalizations. METHODS: We obtained daily concentrations of PM10 from 53 monitoring sites covering the study area and we identified 8287 MS-related hospitalization through hospital admission-discharge records of the Lombardy region, Italy, between 2001 and 2009. We used a Poisson regression analysis to investigate the association between exposure to PM10 and risk of hospitalization. RESULTS: A higher RR of hospital admission for MS relapse was associated with exposure to PM10 at different time intervals. The maximum effect of PM10 on MS hospitalization was found for exposure between days 0 and 7: Hospital admission for MS increased 42% (95%CI 1.39-1.45) on the days preceded by one week with PM10 levels in the highest quartile. The p-value for trend across quartiles was<0.001. CONCLUSIONS: These data support the hypothesis that air pollution may have a role in determining MS occurrence and relapses. Our findings could open new avenues for determining the pathogenic mechanisms of MS and potentially be applied to other autoimmune diseases.


Assuntos
Poluentes Atmosféricos/análise , Hospitalização/estatística & dados numéricos , Exposição por Inalação/análise , Esclerose Múltipla/epidemiologia , Material Particulado/análise , Adulto , Poluentes Atmosféricos/toxicidade , Feminino , Humanos , Exposição por Inalação/efeitos adversos , Itália , Masculino , Pessoa de Meia-Idade , Esclerose Múltipla/etiologia , Tamanho da Partícula , Material Particulado/efeitos adversos , Distribuição de Poisson , Risco , Estações do Ano , População Suburbana/estatística & dados numéricos , População Urbana/estatística & dados numéricos , Tempo (Meteorologia)
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