Abstract
Background: Obesity is associated with metabolic disorders in clinical settings. We examined the relationship of adiposity indices and lipid-related indices with metabolic syndrome (MetS) among older adults in the coastal city of China.
Methods: In this population-based cross-sectional study, We used weight, height, waist circumference (WC), triglyceride, glucose, and uric acid (UA) to calculate 6 adiposity indices (body mass index [BMI], waist-to-height ratio [WHtR], body roundness index [BRI], Conicity Index [ConI], weight-adjusted-waist index [WWI], and A Body Shape Index [ABSI]) and 6 lipid-related indices (uric acid to high-density lipoprotein cholesterol [UHR], Chinese visceral adiposity index (CVAI), triglyceride–glucose [TyG] index and its correlation index [TyG-BMI, TyG-WC, and TyG-WHtR]). MetS were diagnosed following the international criteria. Data was analyzed with the restricted cubic splines (RCS) and logistic regression models.
Results: Of the 5840 participants, 3170 were diagnosed with MetS. The multivariable-adjusted logistic regression analysis showed that higher BMI, WHtR, BRI, ConI, WWI, UHR, CVAI, TyG index and its correlation index (TyG-BMI, TyG-WC, and TyG-WHtR) were significantly associated with increased likelihoods of MetS. RCS regression analysis revealed the association of BMI, WHtR, BRI, and TyG index, TyG-BMI, TyG-WC, TyG-WHtR, and CVAI with MetS presents a S shaped and -log shaped dose-response curve (P for non-linearity≤0.001). In addition, after comparison by ROC analysis, we found that TyG-WHtR had significantly higher predictive power for MetS than other indicators (P≤0.001). In addition, whether in female or male, TyG-WC is the best indicator to indicate MetS.
Conclusions: BMI, WHtR, BRI, CVAI, TyG index TyG-BMI, TyG-WC, and TyG-WHtR were non-linear associated with MetS. In addition, our study highlights the clinical value of lipid-related indices, especially TyG-related indices, in predicting the MetS.