Despite an extensive research on the adverse effects of air pollution on human health, little was known about the mechanism by which air pollutants may affect sleep. Particularly for adults, it was proposed that particles influence sleep because they cause damages to the upper airways and because they have dangerous effects on the central nervous system. It was also suggested that environmental tobacco smoke exposure (active or passive) may be a cause of poor sleep and of sleep health disparities. In this study we present the application of the Multiple Correspondence Analysis (MCA) to analyze qualitative data regarding lifestyles of patients and the analysis of results obtained combining qualitative e quantitative data. In particular, Cluster Analysis (CA), and Principal Component Analysis (PCA) were used in order to investigate the potential relationships between PM10 concentrations and the occurrence of the Obstructive Sleep Apnoea Syndrome (OSAS), a particular respiratory disease consisting in a form of sleep disordered breathing. We used a database composed of polisomnography test performed on 295 patients living in Rome urban area, data about the lifestyles related to OSAS risk factors of the patients and PM10 daily concentrations measured by Air Quality Monitoring Network of Rome urban area in 11 sampling sites from 2008 to 2011.

APPLICATION OF MCA FOR STUDYING AS THE LIFESTYLE AND THE AIR QUALITY CAN AFFECT FORMS OF SLEEP DISORDERED BREATHING

Ragosta, M
;
2019

Abstract

Despite an extensive research on the adverse effects of air pollution on human health, little was known about the mechanism by which air pollutants may affect sleep. Particularly for adults, it was proposed that particles influence sleep because they cause damages to the upper airways and because they have dangerous effects on the central nervous system. It was also suggested that environmental tobacco smoke exposure (active or passive) may be a cause of poor sleep and of sleep health disparities. In this study we present the application of the Multiple Correspondence Analysis (MCA) to analyze qualitative data regarding lifestyles of patients and the analysis of results obtained combining qualitative e quantitative data. In particular, Cluster Analysis (CA), and Principal Component Analysis (PCA) were used in order to investigate the potential relationships between PM10 concentrations and the occurrence of the Obstructive Sleep Apnoea Syndrome (OSAS), a particular respiratory disease consisting in a form of sleep disordered breathing. We used a database composed of polisomnography test performed on 295 patients living in Rome urban area, data about the lifestyles related to OSAS risk factors of the patients and PM10 daily concentrations measured by Air Quality Monitoring Network of Rome urban area in 11 sampling sites from 2008 to 2011.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/136328
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