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Updated: May 22, 2025

Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea
Published on: December 6, 2016
Cross-sectional study of the association between triglyceride glucose-body mass index and obstructive sleep apnea
Li Gong1, Ming Su2, Jing-Han Xu3
1Department of Diabetes, Shenzhen Bao'an Chinese Medicine Hospital Guangzhou University of Chinese Medicine, Shenzhen 518100, Guangdong Province, China.
Background:
The triglyceride glucose-body mass index (TyG-BMI) is a novel indicator of insulin resistance (IR). Obstructive sleep apnea (OSA) is a prevalent disorder characterized by recurrent complete or partial collapse of the pharyngeal airway during sleep; however, the relationship between these two conditions remains unexplored. We hypothesized that a higher TyG-BMI is associated with the occurrence of OSA.
Aim:
To assess the association between TyG-BMI and OSA in adults in the United States.
Methods:
A cross-sectional study was conducted utilizing data from the National Health and Nutrition Examination Surveys spanning from 2005-2008 to 2015-2018. TyG-BMI was calculated as Ln [triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI. Restricted cubic splines were used to analyze the risk of TyG-BMI and OSA occurrence. To identify potential nonlinear relationships, we combined Cox proportional hazard regression with smooth curve fitting. We also conducted sensitivity and subgroup analyses to verify the robustness of our findings.
Results:
We included 16794 participants in the final analysis. Multivariate regression analysis showed that participants with a higher TyG-BMI had a higher OSA incidence. After adjusting for all covariates, TyG-BMI was positively correlated with the prevalence of OSA (odds ratio: 1.28; 95% confidence interval: 1.17, 1.40; P < 0.001); no significant nonlinear relationship was observed. Subgroup analysis showed no strong correlation between TyG-BMI and OSA in patients with diabetes. The correlation between TyG-BMI and OSA was influenced by age, sex, smoking status, marital status, hypertensive stratification, and obesity; these subgroups played a moderating role between TyG-BMI and OSA. Even after adjusting for all covariates, there was a positive association between TYG-BMI and OSA prevalence.
Conclusion:
A higher TyG-BMI index is linked to higher chances of developing OSA. As TyG-BMI is an indicator of IR, managing IR may help reduce the risk of OSA.
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