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. 2021 Jan;28(3):2804-2809.
doi: 10.1007/s11356-020-10595-5. Epub 2020 Sep 7.

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

Roberto Bergamaschi  1 , Maria Cristina Monti  2 , Leonardo Trivelli  2 , Giulia Mallucci  3   4 , Leonardo Gerosa  1 , Enrico Pisoni  5 , Cristina Montomoli  2
Affiliations

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

Roberto Bergamaschi et al. Environ Sci Pollut Res Int. 2021 Jan.

Abstract

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 μg/m3). 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.

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

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Conflict of interest statement

Bergamaschi R has received funding for congress/travel/accommodation expenses for scientific meetings and honoraria for speaking from Almirall, Bayer Schering, Biogen-Idec, Merck Serono, Novartis, Sanofi-Genzyme and Teva; he has served on scientific Advisory Boards for Almirall, Biogen, Merck Serono, Novartis, Sanofi-Genzyme, Teva; he has received research grants for his department from Biogen, Merck Serono, Sanofi-Genzyme and Teva.

Mallucci G has received support for congress/travel/accommodation expenses related to scientific meetings from Biogen, Genzyme, Merck Serono, Novartis, Roche, Sanofi-Aventis and Teva; he has received research grants for his department from Biogen and has served on scientific advisory boards for Biogen, Genzyme and Merck Serono.

Monti MC, Trivelli L, Gerosa L, Pisoni E and Montomoli C. have nothing to disclose.

Figures

Fig. 1
Fig. 1
Average winter concentrations of PM2.5 across the 188 municipalities in the province of Pavia, divided into tertiles
Fig. 2
Fig. 2
a Map of the relative risk (RR) of developing MS in association with average winter PM2.5 levels, after adjustment for degree of urbanization and deprivation index, across the 188 municipalities in the province of Pavia. Darker areas have higher RR values (gradients of grey). b Posterior probabilities (PPs) in association with average winter PM2.5 levels. The highest PPs were consistently identified in the areas also characterized by the highest RRs
See this image and copyright information in PMC

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