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Combining multiple regression and principal component analysis to evaluate the effects of ambient air pollution on children’s respiratory diseases
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Combining multiple regression and principal component analysis to evaluate the effects of ambient air pollution on children’s respiratory diseases
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Journal Article
Combining multiple regression and principal component analysis to evaluate the effects of ambient air pollution on children’s respiratory diseases
2022
Overview
The aim of this study was to investigate the relationship between exposure to ambient air pollution (nitrogen dioxide, sulfur dioxide and particulate matter) and children’s respiratory diseases (asthma, pneumonia, chronic/acute upper/lower respiratory infections) in Casablanca, the largest city in Morocco, by combining principal component analysis and multiple regression method. The best environment-disease quantitative relationship model with 95% confidence interval was found between asthma and two air pollutants including sulfur dioxide and particulate matter. The current study showed that two ambient air pollutants, nitrogen dioxide and sulfur dioxide, were positively associated with childhood respiratory diseases in four major prefectures in the city of Casablanca. In contrast, particulate matter values do not appear to better reflect these health effects and were not significantly associated with respiratory emergency department visits to children during the study period. The strong positive correlations between sulfur dioxide and nitrogen dioxide indicate that the characteristics and origins of emission for these elements might be similar.
Publisher
Springer Nature B.V
Subject
