Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/70626
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dc.contributor.authorWanwisa Chujiten_US
dc.contributor.authorPhongtape Wiwatanadateen_US
dc.contributor.authorAthavudh Deesomchoken_US
dc.contributor.authorKhajornsak Sopajareeen_US
dc.contributor.authorKamal Eldeirawien_US
dc.contributor.authorYing I. Tsaien_US
dc.date.accessioned2020-10-14T08:36:33Z-
dc.date.available2020-10-14T08:36:33Z-
dc.date.issued2020-01-01en_US
dc.identifier.issn20711409en_US
dc.identifier.issn16808584en_US
dc.identifier.other2-s2.0-85086764073en_US
dc.identifier.other10.4209/aaqr.2020.03.0092en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85086764073&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/70626-
dc.description.abstract© The Author(s). Asthmatics may suffer harmful health effects from air pollution. This year-long study, which was conducted from November 2015 till October 2016 and resulted in 12,045 data points from 33 participants, assessed the relationships (with a 95% confidence interval [CI]) between measured air pollutant (CO, NO2, O3, SO2, PM2.5 and PM10) concentrations and peak expiratory flow rates (PEFRs) among adults with asthma in the district of Mae Moh in Lampang, Thailand. A positive correlation was found between the mean daily concentration of NO2 from 4 days prior (“lag 4”) and the PEFR upon waking (“morning PEFR”), with an increase of 1 ppb in the former being associated with an increase of 1.34 L min–1 (95% CI: 0.25, 2.44) in the latter. Also, the interaction between NO2 (lag 4) and PM10 (lag 6) was multiplicatively associated with a decrease of –0.015 L min–1 in the morning PEFR, which was also negatively associated with the maximum daily concentration (“max”) of NO2 (lag 2) and that of PM10 (lag 6), with coefficients of –0.07 and –0.013, respectively. Furthermore, when including PM2.5 max in the generalized estimating equation model, only NO2 max (lag 2) and CO max (lag 6) were negatively associated with the morning PEFR, displaying coefficients of –0.08 and –1.71, respectively. O3 max (lag 3) and PM2.5 max exhibited positive relationships with the PEFR before sleeping (“evening PEFR”), with coefficients of 0.078 and 0.029, respectively. Additionally, the average daily PEFR was positively associated with the average daily concentration of NO2 (lag 4), with a coefficient of 0.15, but negatively associated with that of SO2, with a coefficient of –0.47. We also observed a negative relationship between the average daily PEFR and NO2 max (lag 2), with a coefficient of –0.05, but a positive one between the former and O3 max (lag 3), with a coefficient of 0.06. Our results indicate that the delayed—and, in some cases, negative—effects of these pollutants on PEFRs must be considered in health forecasting and that preventative measures should be implemented to control certain emissions at the source.en_US
dc.subjectEnvironmental Scienceen_US
dc.titleAir pollution levels related to peak expiratory flow rates among adult asthmatics in lampang, thailanden_US
dc.typeJournalen_US
article.title.sourcetitleAerosol and Air Quality Researchen_US
article.volume20en_US
article.stream.affiliationsUniversity of Illinois at Chicagoen_US
article.stream.affiliationsChia-Nan University of Pharmacy and Science Taiwanen_US
article.stream.affiliationsChiang Mai Universityen_US
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