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The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China
Background: Rising levels of air pollution in Beijing, China have become a serious environmental issue affecting human health, and young adults are experiencing high rates of insufficient sleep duration or a lack of sleep. Gaps in previous research remain regarding the relationship between air pollu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766077/ https://www.ncbi.nlm.nih.gov/pubmed/31514480 http://dx.doi.org/10.3390/ijerph16183362 |
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author | Yu, Hongjun Chen, Panpan Paige Gordon, Shelby Yu, Miao Wang, Yangyang |
author_facet | Yu, Hongjun Chen, Panpan Paige Gordon, Shelby Yu, Miao Wang, Yangyang |
author_sort | Yu, Hongjun |
collection | PubMed |
description | Background: Rising levels of air pollution in Beijing, China have become a serious environmental issue affecting human health, and young adults are experiencing high rates of insufficient sleep duration or a lack of sleep. Gaps in previous research remain regarding the relationship between air pollution and sleep duration among young adults. The purpose of this study is to assess the associations between air pollution and sleep duration among college students living in Beijing, China. Methods: We conducted follow-up health surveys on 16,889 freshman students enrolled at Tsinghua University over a five-year study period (2013–2018). Sleep duration was measured using the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), which has been validated in China to measure sleep duration. Corresponding levels of the average hourly air quality index (AQI), PM(2.5) (µg/m(3)), PM(10) (µg/m(3)), and NO(2) (µg/m(3)) were gathered from data provided by the Beijing Municipal Ecological Environment Bureau in a closed site at Tsinghua University. Multilevel mixed-effects linear regression models were used to analyze the data. Results: One standard deviation increase in air pollution concentration in AQI, PM(2.5), PM(10), and NO(2) was associated with a reduction in daily hours of sleep by 0.68 (95% confidence interval (CI) = 0.63, 0.73), 0.55 (95% CI = 0.51, 0.59), 0.70 (95% CI = 0.64, 0.76), and 0.51 (95% CI = 0.47, 0.54), respectively. Conclusions: Air pollution was associated with a reduction in sleep duration among freshman students living in Beijing, China. Replication of this study is warranted among various populations within China. |
format | Online Article Text |
id | pubmed-6766077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67660772019-09-30 The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China Yu, Hongjun Chen, Panpan Paige Gordon, Shelby Yu, Miao Wang, Yangyang Int J Environ Res Public Health Article Background: Rising levels of air pollution in Beijing, China have become a serious environmental issue affecting human health, and young adults are experiencing high rates of insufficient sleep duration or a lack of sleep. Gaps in previous research remain regarding the relationship between air pollution and sleep duration among young adults. The purpose of this study is to assess the associations between air pollution and sleep duration among college students living in Beijing, China. Methods: We conducted follow-up health surveys on 16,889 freshman students enrolled at Tsinghua University over a five-year study period (2013–2018). Sleep duration was measured using the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI), which has been validated in China to measure sleep duration. Corresponding levels of the average hourly air quality index (AQI), PM(2.5) (µg/m(3)), PM(10) (µg/m(3)), and NO(2) (µg/m(3)) were gathered from data provided by the Beijing Municipal Ecological Environment Bureau in a closed site at Tsinghua University. Multilevel mixed-effects linear regression models were used to analyze the data. Results: One standard deviation increase in air pollution concentration in AQI, PM(2.5), PM(10), and NO(2) was associated with a reduction in daily hours of sleep by 0.68 (95% confidence interval (CI) = 0.63, 0.73), 0.55 (95% CI = 0.51, 0.59), 0.70 (95% CI = 0.64, 0.76), and 0.51 (95% CI = 0.47, 0.54), respectively. Conclusions: Air pollution was associated with a reduction in sleep duration among freshman students living in Beijing, China. Replication of this study is warranted among various populations within China. MDPI 2019-09-11 2019-09 /pmc/articles/PMC6766077/ /pubmed/31514480 http://dx.doi.org/10.3390/ijerph16183362 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yu, Hongjun Chen, Panpan Paige Gordon, Shelby Yu, Miao Wang, Yangyang The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China |
title | The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China |
title_full | The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China |
title_fullStr | The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China |
title_full_unstemmed | The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China |
title_short | The Association between Air Pollution and Sleep Duration: A Cohort Study of Freshmen at a University in Beijing, China |
title_sort | association between air pollution and sleep duration: a cohort study of freshmen at a university in beijing, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6766077/ https://www.ncbi.nlm.nih.gov/pubmed/31514480 http://dx.doi.org/10.3390/ijerph16183362 |
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