[The role of body roundness index and a body size index in the assessment of obstructive sleep apnea-hypopnea syndrome].

Objective:To investigate the role of the body roundness index（BRI） and a body shape index（ABSI） in the assessment of Obstructive Sleep Apnea-Hypopnea Syndrome（OSAHS）. Methods:A retrospective analysis was performed on the medical records of 256 adult patients with suspected OSAHS who underwent polysomnography（PSG） in the Department of Otorhinolaryngology, Peking University Third Hospital, from March 2024 to February 2025. The collected data included gender, age, Body Mass Index（BMI）, waist circumference（WC）, Apnea-Hypopnea Index（AHI）, and the lowest oxygen saturation（LSaO2）. Non-parametric correlation analysis, Receiver Operating Characteristic（ROC） curve analysis, and multiple logistic regression analysis were employed to explore the relationships between WC, BMI, BRI, ABSI, age and other indicators, as well as AHI and LSaO2. Results:Non-parametric correlation analysis showed that, among males, the indicators most strongly correlated with AHI, in descending order, were WC（r=0.476, P<0.001）, BMI（r=0.458, P<0.001）, and BRI（r=0.456, P<0.001）. Among females, the order was BRI（r=0.567, P<0.001）, WC（r=0.484, P<0.001）, BMI（r=0.449, P<0.001）, and age（r=0.352, P=0.004）. For the correlation with LSaO2, in males, the order was BMI（r=-0.445, P<0.001）, WC（r=-0.426, P<0.001）, and BRI（r=-0.415, P<0.001）; in females, it was BRI（r=-0.482, P<0.001）, BMI（r=-0.468, P<0.001）, and WC（r=-0.373, P<0.001）. ROC curve analysis indicated that the indicators of predictive performance for AHI>15/h from strongest to weakest（area under the curve, AUC） were WC（AUC=0.655, P<0.001）, BRI（AUC=0.646, P=0.001）, and BMI（AUC=0.646, P=0.001） in males; in females they were BRI（AUC=0.836, P<0.001）, WC（AUC=0.799, P<0.001）, and BMI（AUC=0.766, P=0.001）. Predictors of LSaO2<80% from strongest to weakest performance were BMI（AUC=0.701, P<0.001）, WC（AUC=0.689, P<0.001）, and BRI（AUC=0.689, P<0.001） in men; in females they were BRI（AUC=0.744, P=0.007）, BMI（AUC=0.724, P=0.013）, and WC（AUC=0.680, P=0.046）. Multifactor logistic regression analysis shows that in men WC（OR=1.049, 95%CI1.009-1.091） was an independent risk factor for AHI>15/h, and WC（OR=1.075, 95%CI1.038-1.114） was an independent risk factor for LSaO2<80%; in women BRI（OR=2.899, 95%CI 1.528-5.550） was an independent risk factor for AHI>15/h, and BMI（OR=1.276, 95%CI1.067-1.527） was an independent risk factor for LSaO2<80%. Conclusion:BRI is closely correlated with the severity of OSAHS in both adult male and female populations, with a more pronounced correlation in females. BRI may have advantages over other anthropometric measures in predicting the risk of OSAHS, playing a decisive role in predicting OSAHS in adult females, and may serve as a novel indicator for predicting the severity of OSAHS in adult women.