2008
DOI: 10.1016/j.scitotenv.2008.01.065
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Multiple Sclerosis disease distribution and potential impact of environmental air pollutants in Georgia

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Cited by 49 publications
(43 citation statements)
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“…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 .…”
Section: Resultssupporting
confidence: 93%
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“…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 .…”
Section: Resultssupporting
confidence: 93%
“…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 .…”
Section: Materials and Methods O Meteorological Datamentioning
confidence: 99%
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“…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…”
Section: Discussionmentioning
confidence: 99%