TY - JOUR
T1 - Air pollution exacerbates mild obstructive sleep apnea by disrupting nocturnal changes in lower-limb body composition
T2 - a cross-sectional study conducted in urban northern Taiwan
AU - He, Yansu
AU - Liu, Wen Te
AU - Lin, Shang Yang
AU - Li, Zhiyuan
AU - Qiu, Hong
AU - Yim, Steve Hung Lam
AU - Chuang, Hsiao Chi
AU - Ho, Kin Fai
N1 - Funding Information:
This study was supported by the Vice-Chancellor's Discretionary Fund of The Chinese University of Hong Kong (project no.: 4930744 ).
Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/8/20
Y1 - 2023/8/20
N2 - 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.
AB - 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.
KW - Bioelectric impedance analysis
KW - Nocturnal changes in body composition
KW - Partial least squares regression
KW - Polysomnography
KW - Spatiotemporal model
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U2 - 10.1016/j.scitotenv.2023.163969
DO - 10.1016/j.scitotenv.2023.163969
M3 - Article
C2 - 37164092
AN - SCOPUS:85159376724
SN - 0048-9697
VL - 887
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 163969
ER -