1. Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study
- Author
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Tommaso Filippini, Marco Vinceti, Jessica Mandrioli, Sofia Costanzini, A Cherubini, Carlotta Malagoli, and Giuseppe Maffeis
- Subjects
medicine.medical_specialty ,amyotrophic lateral sclerosis ,case-control study ,environmental factors ,geographical information system ,particulate matter ,vehicular traffic ,Health, Toxicology and Mutagenesis ,lcsh:Medicine ,Pilot Projects ,010501 environmental sciences ,Logistic regression ,01 natural sciences ,Article ,03 medical and health sciences ,0302 clinical medicine ,Air Pollution ,Internal medicine ,Humans ,Medicine ,Amyotrophic lateral sclerosis ,0105 earth and related environmental sciences ,Air Pollutants ,business.industry ,lcsh:R ,Public Health, Environmental and Occupational Health ,Absolute risk reduction ,Case-control study ,Neurodegenerative Diseases ,Environmental Exposure ,Odds ratio ,medicine.disease ,Confidence interval ,Quartile ,Case-Control Studies ,Etiology ,business ,030217 neurology & neurosurgery - Abstract
(1) Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with still unknown etiology. Some occupational and environmental risk factors have been suggested, including long-term air pollutant exposure. We carried out a pilot case-control study in order to evaluate ALS risk due to particulate matter with a diameter of &le, 10 µ, m (PM10) as a proxy of vehicular traffic exposure. (2) Methods: We recruited ALS patients and controls referred to the Modena Neurology ALS Care Center between 1994 and 2015. Using a geographical information system, we modeled PM10 concentrations due to traffic emissions at the geocoded residence address at the date of case diagnosis. We computed the odds ratio (OR) and 95% confidence interval (CI) of ALS according to increasing PM10 exposure, using an unconditional logistic regression model adjusted for age and sex. (3) Results: For the 132 study participants (52 cases and 80 controls), the average of annual median and maximum PM10 concentrations were 5.2 and 38.6 µ, g/m3, respectively. Using fixed cutpoints at 5, 10, and 20 of the annual median PM10 levels, and compared with exposure <, 5 µ, g/m3, we found no excess ALS risk at 5&ndash, g/m3 (OR 0.87, 95% CI 0.39&ndash, 1.96), 10&ndash, 20 µ, g/m3 (0.94, 95% CI 0.24&ndash, 3.70), and &ge, g/m3 (0.87, 95% CI 0.05&ndash, 15.01). Based on maximum PM10 concentrations, we found a statistically unstable excess ALS risk for subjects exposed at 10&ndash, g/m3 (OR 4.27, 95% CI 0.69&ndash, 26.51) compared with those exposed <, g/m3. However, risk decreased at 20&ndash, 50 µ, g/m3 (OR 1.49, 95% CI 0.39&ndash, 5.75) and &ge, g/m3 (1.16, 95% CI 0.28&ndash, 4.82). ALS risk in increasing tertiles of exposure showed a similar null association, while comparison between the highest and the three lowest quartiles lumped together showed little evidence for an excess risk at PM10 concentrations (OR 1.13, 95% CI 0.50&ndash, 2.55). After restricting the analysis to subjects with stable residence, we found substantially similar results. (4) Conclusions: In this pilot study, we found limited evidence of an increased ALS risk due to long-term exposure at high PM10 concentration, though the high statistical imprecision of the risk estimates, due to the small sample size, particularly in some exposure categories, limited our capacity to detect small increases in risk, and further larger studies are needed to assess this relation.
- Published
- 2021