This predictive model shows that Body Roundness Index improves obstructive sleep apnea detection in Chinese adults, implying better assessment of severity.
Background: Obesity is a key factor in obstructive sleep apnea (OSA), though Body Mass Index (BMI) may not fully capture this risk as it ignores visceral fat distribution. The Body Roundness Index (BRI), which uses waist circumference and height to better reflect visceral adiposity, has not been widely validated for OSA screening. This study assesses a BRI-based model for predicting severe OSA. Methods: Patients undergoing polysomnography (PSG) were retrospectively enrolled from January 2022 to March 2025 and prospectively enrolled from March 2025 to June 2025. Least absolute shrinkage and selection operator (LASSO) regression was used to identify optimal predictors of severe OSA. A predictive model for severe OSA (Apnea–Hypopnea Index [AHI] ≥ 30 events/h) was developed using BRI and other relevant factors. Subgroup analyses were performed by sex and age. Results: A total of 7579 patients were included in the final analysis, of whom 3864 (51%) were diagnosed with severe OSA. Univariable logistic regression revealed that each unit increase in BRI was associated with a significantly elevated risk of severe OSA (OR 2.01, 95% CI 1.93–2.10; p < 0.001). The predictive severe OSA model incorporating BRI yielded higher area under the receiver operating characteristic curve (AUC) values (Training: 0.762 vs. 0.747; Test: 0.820 vs. 0.803; DeLong test p < 0.05). Subgroup analyses by sex and age revealed higher AUCs across all groups, with the most pronounced improvements in sensitivity observed in women (84.3% vs. 73.0%) and individuals aged ≤ 50 years (75.6% vs. 60.2%). Conclusions: BRI is more strongly correlated with severe OSA than BMI and may enhance screening efficacy in Chinese adults.
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Tang et al. (2025) studied this question.
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