Linking Metabolic Health with Sleep Efficiency in Adolescents and Adults

Introduction and Objective: This study aimed to investigate the association between various metabolic indicators and sleep efficiency in a sample of adolescents and adults. Methods: We analyzed data from 207 individuals with a BMI>24kg/m2. Participants were grouped by sleep efficiency (≤74% and >74%), measured using polysomnography (PSG). Univariate and multivariate logistic regression analyzed the relationship between anthropometric indicators and sleep efficiency. Receiver operating characteristic (ROC) analysis was used to assess the area under the curve (AUC) of triglycerides (TG) and other indicators in classifying individuals with poor sleep efficiency. Stratified multivariate logistic regression (by quartiles) evaluated the association between TG, prealbumin (PAB), and albumin (ALB) levels and low sleep efficiency. Results: Low sleep efficiency was significantly associated with higher BMI, TG, TG/HDL ratio, and TyG, and lower ALB levels. Female gender was found to cause low sleep efficiency (OR: 2.928; 95% CI: 1.541-5.563; P = 0.001). The TG as a predictor of low sleep efficiency was clearly evident with an AUC of 0.636, improving to 0.739 when adjusted for sex, age, BMI, TG/HDL, PAB, and ALB. Conclusion: Various independent risk factors have been identified for poor sleep efficiency, including higher BMI, female gender, lower ALB, higher TG, higher TG/HDL ratio, and higher Prealbumin. Notably, triglycerides are a significant diagnostic marker for low sleep efficiency, with an adjusted accuracy rate of 73.82%. These findings highlight the link between anthropometric markers and sleep quality, providing a basis for further research and targeted interventions. Disclosure: Y. Fang: None. S. Bashyal: None. K. Mutailipu: None. L. Lu: None. Y. Wang: None. X. Wang: None. S. Qu: None. L. Bu: None.