{"title":"Body Composition Analysis in Obstructive Sleep Apnea: A Cross-Sectional Study Using Bioelectrical Impedance Analysis","authors":"Mucahit Yetim, Macit Kalçık, Lütfü Bekar, Yusuf Karavelioğlu, Yasemin Arı Yılmaz","doi":"10.1111/crj.70123","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Introduction</h3>\n \n <p>Obstructive sleep apnea (OSA) is a prevalent disorder characterized by recurrent upper airway collapse, resulting in intermittent hypoxia and sleep fragmentation. While obesity is a major risk factor, traditional markers such as body mass index (BMI) inadequately reflect the complex interplay of body composition in OSA pathogenesis. This study aimed to investigate the predictive value of body composition parameters assessed by bioelectrical impedance analysis (BIA) for OSA.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>In this cross-sectional single-center study, 78 patients diagnosed with OSA by polysomnography (PSG) and 78 age-, gender-, and BMI-matched controls without OSA were analyzed. BIA was used to assess fat distribution, muscle mass, and body water composition. Logistic regression analyses were performed to identify independent predictors of OSA.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Compared to controls, the OSA group had significantly higher lean mass, trunk fat percentage, and total body water. Multivariable logistic regression identified body fat mass (OR = 1.06), visceral fat area (OR = 0.83), and total body water (OR = 1.10) as independent predictors of OSA. Notably, total body water had the strongest association with OSA risk, independent of traditional obesity metrics.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>BIA-derived body composition analysis provides nuanced insights beyond BMI, highlighting the roles of central fat distribution and fluid balance in OSA pathophysiology. These findings underscore the clinical utility of incorporating detailed body composition assessment into the routine evaluation of patients at risk for OSA.</p>\n </section>\n </div>","PeriodicalId":55247,"journal":{"name":"Clinical Respiratory Journal","volume":"19 9","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/crj.70123","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Respiratory Journal","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/crj.70123","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction
Obstructive sleep apnea (OSA) is a prevalent disorder characterized by recurrent upper airway collapse, resulting in intermittent hypoxia and sleep fragmentation. While obesity is a major risk factor, traditional markers such as body mass index (BMI) inadequately reflect the complex interplay of body composition in OSA pathogenesis. This study aimed to investigate the predictive value of body composition parameters assessed by bioelectrical impedance analysis (BIA) for OSA.
Methods
In this cross-sectional single-center study, 78 patients diagnosed with OSA by polysomnography (PSG) and 78 age-, gender-, and BMI-matched controls without OSA were analyzed. BIA was used to assess fat distribution, muscle mass, and body water composition. Logistic regression analyses were performed to identify independent predictors of OSA.
Results
Compared to controls, the OSA group had significantly higher lean mass, trunk fat percentage, and total body water. Multivariable logistic regression identified body fat mass (OR = 1.06), visceral fat area (OR = 0.83), and total body water (OR = 1.10) as independent predictors of OSA. Notably, total body water had the strongest association with OSA risk, independent of traditional obesity metrics.
Conclusion
BIA-derived body composition analysis provides nuanced insights beyond BMI, highlighting the roles of central fat distribution and fluid balance in OSA pathophysiology. These findings underscore the clinical utility of incorporating detailed body composition assessment into the routine evaluation of patients at risk for OSA.
期刊介绍:
Overview
Effective with the 2016 volume, this journal will be published in an online-only format.
Aims and Scope
The Clinical Respiratory Journal (CRJ) provides a forum for clinical research in all areas of respiratory medicine from clinical lung disease to basic research relevant to the clinic.
We publish original research, review articles, case studies, editorials and book reviews in all areas of clinical lung disease including:
Asthma
Allergy
COPD
Non-invasive ventilation
Sleep related breathing disorders
Interstitial lung diseases
Lung cancer
Clinical genetics
Rhinitis
Airway and lung infection
Epidemiology
Pediatrics
CRJ provides a fast-track service for selected Phase II and Phase III trial studies.
Keywords
Clinical Respiratory Journal, respiratory, pulmonary, medicine, clinical, lung disease,
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