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  • Title: Association between triglyceride-glucose related indices with the all-cause and cause-specific mortality among the population with metabolic syndrome.
    Author: Wei X, Min Y, Song G, Ye X, Liu L.
    Journal: Cardiovasc Diabetol; 2024 Apr 24; 23(1):134. PubMed ID: 38658993.
    Abstract:
    BACKGROUND: Triglyceride-glucose (TyG) index has been determined to play a role in the onset of metabolic syndrome (MetS). Whether the TyG index and TyG with the combination of obesity indicators are associated with the clinical outcomes of the MetS population remains unknown. METHOD: Participants were extracted from multiple cycles of the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018 years. Three indicators were constructed including TyG index, TyG combining with waist circumference (TyG-WC), and TyG combining with waist-to-height ratio (TyG-WHtR). The MetS was defined according to the National Cholesterol Education Program (NCPE) Adult Treatment Panel III. Kaplan-Meier (KM) curves, restricted cubic splines (RCS), and the Cox proportional hazard model were used to evaluate the associations between TyG-related indices and mortality of the MetS population. The sensitive analyses were performed to check the robustness of the main findings. RESULTS: There were 10,734 participants with MetS included in this study, with 5,570 females and 5,164 males. The median age of the study population was 59 years old. The multivariate Cox regression analyses showed high levels of TyG-related indices were significantly associated with the all-cause mortality of MetS population [TyG index: adjustedhazard ratio (aHR): 1.36, 95%confidence interval (CI): 1.18-1.56, p < 0.001; TyG-WHtR index: aHR = 1.29, 95%CI: 1.13-1.47, p < 0.001]. Meanwhile, the TyG-WC and TyG-WHtR index were associated with cardiovascular mortality of the MetS population (TyG-WC: aHR = 1.45, 95%CI: 1.13-1.85, p = 0.004; TyG-WHtR: aHR = 1.50 95%CI: 1.17-1.92, p = 0.002). Three TyG-related indices showed consistent significant correlations with diabetes mortality (TyG: aHR = 4.06, 95%CI: 2.81-5.87, p < 0.001; TyG-WC: aHR = 2.55, 95%CI: 1.82-3.58, p < 0.001; TyG-WHtR: aHR = 2.53 95%CI: 1.81-3.54, p < 0.001). The RCS curves showed a non-linear trend between TyG and TyG-WC indices with all-cause mortality (p for nonlinearity = 0.004 and 0.001, respectively). The sensitive analyses supported the positive correlations between TyG-related indices with mortality of the MetS population. CONCLUSION: Our study highlights the clinical value of TyG-related indices in predicting the survival of the MetS population. TyG-related indices would be the surrogate biomarkers for the follow-up of the MetS population.
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