Effects of particulate matter exposure on multiple sclerosis hospital admission in Lombardy region, Italy

Abstract

Background Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating disease of the central nervous system, characterized by recurrent relapses of inflammation that cause mild to severe disability. Exposure to airborne particulate matter (PM) has been associated with acute increases in systemic inflammatory responses and neuroinflammation. In the present study, we hypothesize that exposure to PM < 10 µm in diameter (PM10) might increase the occurrence of MS-related hospitalizations. Methods We obtained daily concentrations of PM10 from 53 monitoring sites covering the study area and we identified 8287 MS-related hospitalization through hospital admission-discharge records of the Lombardy region, Italy, between 2001 and 2009. We used a Poisson regression analysis to investigate the association between exposure to PM10 and risk of hospitalization. Results A higher RR of hospital admission for MS relapse was associated with exposure to PM10 at different time intervals. The maximum effect of PM10 on MS hospitalization was found for exposure between days 0 and 7: Hospital admission for MS increased 42% (95%CI 1.39–1.45) on the days preceded by one week with PM10 levels in the highest quartile. The p-value for trend across quartiles was < 0.001. Conclusions These data support the hypothesis that air pollution may have a role in determining MS occurrence and relapses. Our findings could open new avenues for determining the pathogenic mechanisms of MS and potentially be applied to other autoimmune diseases.

Influence of particulate matter and meteorological conditions on multiple sclerosis relapse: a preliminary study in São Paulo, Brazil

“…Regarding the meteorological variables, the air temperature showed a negative correlation with hospitalizations and the relative humidity a positive correlation with admissions of patients between 30 and 50 years and of male gender. These results agree with others studies, such as that of Angelici et al 16 , which demonstrated a positive relation between PM 10 and MS admissions in Lombardy, Italy, and that of Gregory et al 3 , which showed a positive relation between PM 10 and female patient admissions. o Adjustments of the multiple linear regression model with the stepwise method Before the development of multiple linear regression, residual analysis was performed to verify the adjustment of hospitalization data and PM 10 to the model, since residuals should follow a normal distribution for the model 11,17,24 .…”

“…After the Kolmogorov-Smirnov test indicated normal distribution of data, the variables PM 10 , relative humidity, air temperature, and hospital admissions due to MS were correlated using Pearson's model 14,15 . Although many studies that correlate air pollution and meteorological variables with diseases use the Poisson family of generalized linear models (MLG), in this study we used multiple linear regression 3,16,17 . This model was chosen because the variables have a normal distribution and, according to the residue analysis, the model was adequate for our data 11,13,17 .…”

Urban air quality and associations with pediatric multiple sclerosis

“…To our knowledge, the current study is the first to have looked at potential sources through industrial output and examine childhood exposure and MS risk. In other adult MS studies, increased exposure to larger particulate matter (PM 10 ) was related to both increased risk for MS in adults20, 23 and MS relapse using hospitalization records 18, 19, 24…”

“…Although some adult MS studies have suggested a relationship between air constituents and MS,18, 19, 20 not all of the Environmental Protection Agency (EPA) criteria air pollutants have been assessed, including fine PM 2.5 , ground level ozone precursors, and lead. Furthermore, the proximity of MS patients to industrial facilities that release toxic chemicals into the air has yet to be explored.…”

Upgrading the Estimation of Daily PM10 Concentrations Utilizing Prediction Variables Reflecting Atmospheric Processes

“…The connection of outdoor particulate air pollution with adverse health effects, has been highlighted in multiple recent publications worldwide (Cruz et al, 2015;Dai et al, 2015, Kim et al, 2015Angelici et al, 2016;Tsangari et al, 2016). Hence, the European Union (EU) has established upper concentration limits for PM 10 (Particulate Matter with diameter less than 10 µm) and PM 2.5 (Particulate Matter with diameter less than 2.5 µm), in order to protect the European population from being exposed to excessive levels of inhalable aerosols (Council Directive 1999/30/EC).…”