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PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach
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 (PM(2.5)) concentrations with MS prevalence in the province of Pavia, Italy. The overall M...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788018/ https://www.ncbi.nlm.nih.gov/pubmed/32894443 http://dx.doi.org/10.1007/s11356-020-10595-5 |
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author | Bergamaschi, Roberto Monti, Maria Cristina Trivelli, Leonardo Mallucci, Giulia Gerosa, Leonardo Pisoni, Enrico Montomoli, Cristina |
author_facet | Bergamaschi, Roberto Monti, Maria Cristina Trivelli, Leonardo Mallucci, Giulia Gerosa, Leonardo Pisoni, Enrico Montomoli, Cristina |
author_sort | Bergamaschi, Roberto |
collection | PubMed |
description | 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 (PM(2.5)) 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 PM(2.5) gridded data were analysed, by municipality, for the period 2010–2016. Municipalities were grouped by tertiles according to PM(2.5) concentration. Ecological regression and Bayesian statistics were used to analyse the association between PM(2.5) concentrations, degree of urbanization, deprivation index and MS risk. MS risk was higher among persons living in areas with an average winter PM(2.5) concentration above the European annual limit value (25 μg/m(3)). The Bayesian map revealed sizeable MS high-risk clusters. The study found a relationship between low MS risk and lower PM(2.5) levels, strengthening the suggestion that air pollution may be one of the environmental risk factors for MS. |
format | Online Article Text |
id | pubmed-7788018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-77880182021-01-14 PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach Bergamaschi, Roberto Monti, Maria Cristina Trivelli, Leonardo Mallucci, Giulia Gerosa, Leonardo Pisoni, Enrico Montomoli, Cristina Environ Sci Pollut Res Int Research Article 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 (PM(2.5)) 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 PM(2.5) gridded data were analysed, by municipality, for the period 2010–2016. Municipalities were grouped by tertiles according to PM(2.5) concentration. Ecological regression and Bayesian statistics were used to analyse the association between PM(2.5) concentrations, degree of urbanization, deprivation index and MS risk. MS risk was higher among persons living in areas with an average winter PM(2.5) concentration above the European annual limit value (25 μg/m(3)). The Bayesian map revealed sizeable MS high-risk clusters. The study found a relationship between low MS risk and lower PM(2.5) levels, strengthening the suggestion that air pollution may be one of the environmental risk factors for MS. Springer Berlin Heidelberg 2020-09-07 2021 /pmc/articles/PMC7788018/ /pubmed/32894443 http://dx.doi.org/10.1007/s11356-020-10595-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Research Article Bergamaschi, Roberto Monti, Maria Cristina Trivelli, Leonardo Mallucci, Giulia Gerosa, Leonardo Pisoni, Enrico Montomoli, Cristina PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach |
title | PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach |
title_full | PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach |
title_fullStr | PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach |
title_full_unstemmed | PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach |
title_short | PM(2.5) exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach |
title_sort | pm(2.5) exposure as a risk factor for multiple sclerosis. an ecological study with a bayesian mapping approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788018/ https://www.ncbi.nlm.nih.gov/pubmed/32894443 http://dx.doi.org/10.1007/s11356-020-10595-5 |
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