This study aims to explore the predictive value of adiposity measures and lipid-related indices for metabolic syndrome (MetS) in Chinese elderly people at high risk of stroke. A total of 7,693 community-dwelling individuals aged 60 years and older in Shanghai were included. Through ROC curve analysis, it was found that indices such as triglyceride glucose-waist circumference (TyG-WC), triglyceride glucose-waist-to-height-ratio (TyG-WHtR), and Lipid accumulation product (LAP) showed excellent performance in predicting MetS, with TyG-WC being the strongest predictor in both males (AUC = 0.90) and females (AUC = 0.90). These indices integrate information on both lipid metabolism and body fat distribution, allowing for more accurate identification of MetS. The study also revealed that ABSI had poor predictive performance. These findings suggest that the combined use of these indices may help identify MetS earlier and more accurately in elderly people at high risk of stroke, providing a basis for clinical intervention. Future research should validate the generalizability of these indicators in more diverse populations and explore their potential integration into clinical workflows.
Chen et al. (Tue,) studied this question.