4.7 Article

PM2.5 exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 28, Issue 3, Pages 2804-2809

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-020-10595-5

Keywords

Multiple sclerosis; Epidemiology; PM2.5; Air pollution; Bayesian mapping; Ecological study

Funding

  1. Universita degli Studi di Pavia within the CRUI-CARE Agreement

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This study investigated the association between PM2.5 concentrations and the prevalence of multiple sclerosis (MS) in the province of Pavia, Italy. It found that living in areas with high PM2.5 concentrations was associated with higher MS risk, and Bayesian maps revealed significant clusters of high-risk areas for MS.
Some environmental factors are associated with an increased risk of multiple sclerosis (MS). Air pollution could be a main one. This study was conducted to investigate the association of particulate matter 2.5 (PM2.5) concentrations with MS prevalence in the province of Pavia, Italy. The overall MS prevalence in the province of Pavia is 169.4 per 100,000 inhabitants. Spatial ground-level PM2.5 gridded data were analysed, by municipality, for the period 2010-2016. Municipalities were grouped by tertiles according to PM2.5 concentration. Ecological regression and Bayesian statistics were used to analyse the association between PM2.5 concentrations, degree of urbanization, deprivation index and MS risk. MS risk was higher among persons living in areas with an average winter PM2.5 concentration above the European annual limit value (25 mu g/m(3)). The Bayesian map revealed sizeable MS high-risk clusters. The study found a relationship between low MS risk and lower PM2.5 levels, strengthening the suggestion that air pollution may be one of the environmental risk factors for MS.

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