Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan

Background: Few studies have explored the role of body composition linking air pollution to obstructive sleep apnea (OSA). Objective: To estimate the effects of air pollution on body composition and OSA, and that of body composition on OSA. Methods: This study included 3550 individuals. A spatiotemp...

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Main Authors: He, Yansu, Liu, Wen-Te, Lin, Shang-Yang, Li, Zhiyuan, Qiu, Hong, Yim, Steve Hung Lam, Chuang, Hsiao-Chi, Ho, Kin Fai
Other Authors: Asian School of the Environment
Format: Journal Article
Language:English
Published: 2023
Subjects:
Online Access:https://hdl.handle.net/10356/172066
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author He, Yansu
Liu, Wen-Te
Lin, Shang-Yang
Li, Zhiyuan
Qiu, Hong
Yim, Steve Hung Lam
Chuang, Hsiao-Chi
Ho, Kin Fai
author2 Asian School of the Environment
author_facet Asian School of the Environment
He, Yansu
Liu, Wen-Te
Lin, Shang-Yang
Li, Zhiyuan
Qiu, Hong
Yim, Steve Hung Lam
Chuang, Hsiao-Chi
Ho, Kin Fai
author_sort He, Yansu
collection NTU
description Background: Few studies have explored the role of body composition linking air pollution to obstructive sleep apnea (OSA). Objective: To estimate the effects of air pollution on body composition and OSA, and that of body composition on OSA. Methods: This study included 3550 individuals. A spatiotemporal model estimated personal exposure. Nocturnal changes in body composition were assessed through bioelectric impedance analysis. OSA was diagnosed using polysomnography. A generalized linear model was used to evaluate the absolute nocturnal changes in body composition associated with an interquartile range (IQR) increase in pollutants. A generalized logistic model was used to estimate odds ratios (ORs) of mild-OSA compared to non-OSA. Association between body composition and apnea–hypopnea index (AHI) was investigated through partial least squares (PLS) regression. Results: Nocturnal changes in lower-limb body composition were associated with NO2 and PM2.5 in all patients. In participants with AHI <15, both short- and long-term NO2 exposures affected body composition and mild-OSA, while PM2.5 was not associated with either outcome. In a PLS model incorporating eight NO2-associated lower-limb parameters, the variable importance projection scores (VIP) of left leg impedance (LLIMP), predicted muscle mass (LLPMM), fat-free mass (LLFFM), and right leg impedance (RLIMP) exceeded 1; the corresponding coefficients ranked in the top four for AHI prediction. The adjusted OR (mild vs. non-OSA) was 1.67 (95 % CI: 1.36–2.03) associated with an IQR increase in prediction value estimated from body compositions. Notably, the two-pollutant model investigating the effects of pollutants on body compositions revealed associations of four parameters (LLIMP, LLPMM, LLFFM, and RLIMP) with NO2 in all lags, which indicates their indispensability in the association between NO2 and AHI. Conclusions: NO2 exacerbates mild-OSA by disrupting nocturnal changes in lower-limb body composition of patients with AHI <15. PM2.5 was associated with nocturnal changes in lower-limb body composition but not with mild-OSA.
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spelling ntu-10356/1720662023-11-21T02:57:02Z Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan He, Yansu Liu, Wen-Te Lin, Shang-Yang Li, Zhiyuan Qiu, Hong Yim, Steve Hung Lam Chuang, Hsiao-Chi Ho, Kin Fai Asian School of the Environment Engineering::Environmental engineering::Environmental pollution Spatiotemporal Model Polysomnography Background: Few studies have explored the role of body composition linking air pollution to obstructive sleep apnea (OSA). Objective: To estimate the effects of air pollution on body composition and OSA, and that of body composition on OSA. Methods: This study included 3550 individuals. A spatiotemporal model estimated personal exposure. Nocturnal changes in body composition were assessed through bioelectric impedance analysis. OSA was diagnosed using polysomnography. A generalized linear model was used to evaluate the absolute nocturnal changes in body composition associated with an interquartile range (IQR) increase in pollutants. A generalized logistic model was used to estimate odds ratios (ORs) of mild-OSA compared to non-OSA. Association between body composition and apnea–hypopnea index (AHI) was investigated through partial least squares (PLS) regression. Results: Nocturnal changes in lower-limb body composition were associated with NO2 and PM2.5 in all patients. In participants with AHI <15, both short- and long-term NO2 exposures affected body composition and mild-OSA, while PM2.5 was not associated with either outcome. In a PLS model incorporating eight NO2-associated lower-limb parameters, the variable importance projection scores (VIP) of left leg impedance (LLIMP), predicted muscle mass (LLPMM), fat-free mass (LLFFM), and right leg impedance (RLIMP) exceeded 1; the corresponding coefficients ranked in the top four for AHI prediction. The adjusted OR (mild vs. non-OSA) was 1.67 (95 % CI: 1.36–2.03) associated with an IQR increase in prediction value estimated from body compositions. Notably, the two-pollutant model investigating the effects of pollutants on body compositions revealed associations of four parameters (LLIMP, LLPMM, LLFFM, and RLIMP) with NO2 in all lags, which indicates their indispensability in the association between NO2 and AHI. Conclusions: NO2 exacerbates mild-OSA by disrupting nocturnal changes in lower-limb body composition of patients with AHI <15. PM2.5 was associated with nocturnal changes in lower-limb body composition but not with mild-OSA. This study was supported by the Vice-Chancellors Discretionary Fund of The Chinese University of Hong Kong (project no.: 4930744). 2023-11-21T02:57:02Z 2023-11-21T02:57:02Z 2023 Journal Article He, Y., Liu, W., Lin, S., Li, Z., Qiu, H., Yim, S. H. L., Chuang, H. & Ho, K. F. (2023). Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan. Science of the Total Environment, 887, 163969-. https://dx.doi.org/10.1016/j.scitotenv.2023.163969 0048-9697 https://hdl.handle.net/10356/172066 10.1016/j.scitotenv.2023.163969 37164092 2-s2.0-85159376724 887 163969 en Science of the Total Environment © 2023 Elsevier B.V. All rights reserved.
spellingShingle Engineering::Environmental engineering::Environmental pollution
Spatiotemporal Model
Polysomnography
He, Yansu
Liu, Wen-Te
Lin, Shang-Yang
Li, Zhiyuan
Qiu, Hong
Yim, Steve Hung Lam
Chuang, Hsiao-Chi
Ho, Kin Fai
Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan
title Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan
title_full Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan
title_fullStr Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan
title_full_unstemmed Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan
title_short Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition: a cross-sectional study conducted in urban northern Taiwan
title_sort air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower limb body composition a cross sectional study conducted in urban northern taiwan
topic Engineering::Environmental engineering::Environmental pollution
Spatiotemporal Model
Polysomnography
url https://hdl.handle.net/10356/172066
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