TY - JOUR
T1 - Association between long-term exposure to ambient air pollutants and excessive daytime sleepiness in Chinese rural population
T2 - The Henan Rural Cohort Study
AU - Wang, Yan
AU - Mao, Zhenxing
AU - Chen, Gongbo
AU - Tu, Runqi
AU - Abdulai, Tanko
AU - Qiao, Dou
AU - Liu, Xue
AU - Dong, Xiaokang
AU - Luo, Zhicheng
AU - Wang, Yikang
AU - Li, Ruiying
AU - Huo, Wenqian
AU - Yu, Songcheng
AU - Guo, Yuming
AU - Li, Shanshan
AU - Wang, Chongjian
PY - 2020/6
Y1 - 2020/6
N2 - Background: Excessive daytime sleepiness is associated with many adverse consequences, including cardiovascular diseases and mortality. Although exposure to air pollution has been suggested in connection with excessive daytime sleepiness, evidence in China is scarce. The study aimed to explore the association between long-term exposure to air pollution and excessive daytime sleepiness in rural China. Methods: A lot of 27935 participants (60% females) from the Henan Rural Cohort Study were included in this analysis. A satellite-based spatiotemporal model estimated a 3-year average air pollution exposure to NO2 (nitrogen dioxide), PM1 (particulate matter with aerodynamic diameters not more than 1 μm) and PM2.5 (particulate matter with aerodynamic diameters not more than 2.5 μm) at the home address of participants before the baseline survey. Logistic regression was used to evaluate the odds ratio and 95% confidence interval between long-term air pollution and excessive daytime sleepiness. Results: The average concentrations of NO2, PM1 and PM2.5 during three years preceding baseline survey were 38.22 μg/m³, 56.29 μg/m³ and 72.30 μg/m³. Exposure to NO2, PM1 and PM2.5 were all associated with excessive daytime sleepiness. Each 1 μg/m³ increment of NO2, PM1 and PM2.5 were related to a 20% (OR: 1.20, 95% CI: 1.13–1.27), 10% (OR: 1.10, 95% CI: 1.05–1.16) and 17% (OR: 1.17, 95% CI: 1.10–1.23) increase of the prevalence of excessive daytime sleepiness. Conclusion: The study demonstrated that long-term exposure to NO2, PM1 and PM2.5 were all associated with excessive daytime sleepiness. The impact of air pollution should be considered when treating individuals with excessive daytime sleepiness.
AB - Background: Excessive daytime sleepiness is associated with many adverse consequences, including cardiovascular diseases and mortality. Although exposure to air pollution has been suggested in connection with excessive daytime sleepiness, evidence in China is scarce. The study aimed to explore the association between long-term exposure to air pollution and excessive daytime sleepiness in rural China. Methods: A lot of 27935 participants (60% females) from the Henan Rural Cohort Study were included in this analysis. A satellite-based spatiotemporal model estimated a 3-year average air pollution exposure to NO2 (nitrogen dioxide), PM1 (particulate matter with aerodynamic diameters not more than 1 μm) and PM2.5 (particulate matter with aerodynamic diameters not more than 2.5 μm) at the home address of participants before the baseline survey. Logistic regression was used to evaluate the odds ratio and 95% confidence interval between long-term air pollution and excessive daytime sleepiness. Results: The average concentrations of NO2, PM1 and PM2.5 during three years preceding baseline survey were 38.22 μg/m³, 56.29 μg/m³ and 72.30 μg/m³. Exposure to NO2, PM1 and PM2.5 were all associated with excessive daytime sleepiness. Each 1 μg/m³ increment of NO2, PM1 and PM2.5 were related to a 20% (OR: 1.20, 95% CI: 1.13–1.27), 10% (OR: 1.10, 95% CI: 1.05–1.16) and 17% (OR: 1.17, 95% CI: 1.10–1.23) increase of the prevalence of excessive daytime sleepiness. Conclusion: The study demonstrated that long-term exposure to NO2, PM1 and PM2.5 were all associated with excessive daytime sleepiness. The impact of air pollution should be considered when treating individuals with excessive daytime sleepiness.
KW - Air pollution
KW - Excessive daytime sleepiness
KW - Rural population
UR - https://www.scopus.com/pages/publications/85078900108
U2 - 10.1016/j.chemosphere.2020.126103
DO - 10.1016/j.chemosphere.2020.126103
M3 - Article
C2 - 32041074
AN - SCOPUS:85078900108
SN - 0045-6535
VL - 248
JO - Chemosphere
JF - Chemosphere
M1 - 126103
ER -