2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      PM 2.5 exposure as a risk factor for multiple sclerosis. An ecological study with a Bayesian mapping approach

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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 (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.

          Related collections

          Most cited references23

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria

          New evidence and consensus has led to further revision of the McDonald Criteria for diagnosis of multiple sclerosis. The use of imaging for demonstration of dissemination of central nervous system lesions in space and time has been simplified, and in some circumstances dissemination in space and time can be established by a single scan. These revisions simplify the Criteria, preserve their diagnostic sensitivity and specificity, address their applicability across populations, and may allow earlier diagnosis and more uniform and widespread use. Ann Neurol 2011
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Multiple sclerosis

            Multiple sclerosis continues to be a challenging and disabling condition but there is now greater understanding of the underlying genetic and environmental factors that drive the condition, including low vitamin D levels, cigarette smoking, and obesity. Early and accurate diagnosis is crucial and is supported by diagnostic criteria, incorporating imaging and spinal fluid abnormalities for those presenting with a clinically isolated syndrome. Importantly, there is an extensive therapeutic armamentarium, both oral and by infusion, for those with the relapsing remitting form of the disease. Careful consideration is required when choosing the correct treatment, balancing the side-effect profile with efficacy and escalating as clinically appropriate. This move towards more personalised medicine is supported by a clinical guideline published in 2018. Finally, a comprehensive management programme is strongly recommended for all patients with multiple sclerosis, enhancing health-related quality of life through advocating wellness, addressing aggravating factors, and managing comorbidities. The greatest remaining challenge for multiple sclerosis is the development of treatments incorporating neuroprotection and remyelination to treat and ultimately prevent the disabling, progressive forms of the condition.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Bayesian image restoration, with two applications in spatial statistics

                Bookmark

                Author and article information

                Contributors
                giulia.mallucci@mondino.it
                Journal
                Environ Sci Pollut Res Int
                Environ Sci Pollut Res Int
                Environmental Science and Pollution Research International
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0944-1344
                1614-7499
                7 September 2020
                7 September 2020
                2021
                : 28
                : 3
                : 2804-2809
                Affiliations
                [1 ]Multiple Sclerosis Centre, IRCCS Mondino Foundation, via Mondino 2, 27100 Pavia, Italy
                [2 ]GRID grid.8982.b, ISNI 0000 0004 1762 5736, Department of Public Health, Experimental and Forensic Medicine, , University of Pavia, ; Pavia, Italy
                [3 ]GRID grid.8982.b, ISNI 0000 0004 1762 5736, Department of Brain and Behavioural Sciences, , University of Pavia, ; Pavia, Italy
                [4 ]GRID grid.434554.7, ISNI 0000 0004 1758 4137, European Commission, Joint Research Centre (JRC), ; Ispra, Italy
                Author notes

                Responsible Editor: Lotfi Aleya

                Author information
                http://orcid.org/0000-0002-0031-9594
                Article
                10595
                10.1007/s11356-020-10595-5
                7788018
                32894443
                d84c947a-4eeb-47d2-a341-7e6fed5505d4
                © 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/.

                History
                : 28 April 2020
                : 23 August 2020
                Funding
                Funded by: Università degli Studi di Pavia
                Categories
                Research Article
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2021

                General environmental science
                multiple sclerosis,epidemiology,pm2.5,air pollution,bayesian mapping,ecological study

                Comments

                Comment on this article