Associations between body composition, hydration status, and sleep architecture in obstructive sleep apnea
Ya-Min Chuang1, Wen-Te Liu2,3,4, Cheng-Yu Tsai2,5
1Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taipei, Taiwan.
Introduction:
Obstructive sleep apnea (OSA) is linked to increased cardiovascular and metabolic risks. Although body mass index is a recognized risk factor, the roles of fat mass, muscle mass, and hydration status in influencing OSA severity and sleep architecture remain unclear. This study examined the associations between body composition and apnea-hypopnea index, sleep efficiency, and sleep stages across sex, age, and BMI strata.
Materials And Methods:
In this cross-sectional study, data from 5,381 adults undergoing overnight polysomnography and bioimpedance analysis were analyzed. Multivariable linear regression, adjusted for age, sex, and BMI were used, with additional analyses stratified by sex, age, and BMI.
Results:
A unit increase in fat percentage (FATP) and fat mass (FATM) were associated with increasing AHI, whereas increase in bone mass, and FFM were associated with decreasing AHI, particularly in younger adults. Intracellular and total body water associated with increasing AHI. Stratified analyses revealed stronger associations in females and individuals with obesity. A unit increase in adiposity associated with increasing WASO, while bone mass (BONEM) reduced WASO. A unit increase in BMI and water content were linked to increasing N1 stage, whereas increase in PMM and BONEM associated with increasing deeper stages. Age- and sex-specific analyses showed stronger adiposity-AHI associations in younger adults, while these including hydration parameters, tend to attenuate with age.
Conclusion:
Body composition and hydration status were significantly associated with sleep architecture and AHI. These findings support a personalized approach to sleep health and OSA management, emphasizing not only weight control but also muscle preservation and fluid balance optimization.
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