Data Sheet 1_Association between the triglyceride-glucose-waist-to-height ratio and cardiovascular disease in Chinese adults with sarcopenia or probable sarcopenia.docx

IntroductionSarcopenia, an age-related syndrome characterized by decreased muscle mass and performance, has been increasingly linked to high cardiovascular disease (CVD) risk. In this study, sarcopenia and probable sarcopenia were diagnosed according to the Asian Working Group for Sarcopenia (AWGS) 2019 criteria. However, specific biomarkers underlying this association, such as the triglyceride-glucose-waist-to-height ratio (TyG-WHtR), remain unclear.
MethodsA cohort of 2,521 adults ≥45 years with sarcopenia or probable sarcopenia (2011-2020) were stratified by TyG-WHtR tertiles: T1 (≤4.30), T2 (4.30–5.01), and T3 (>5.01). To quantify the predictive utility of TyG-WHtR for CVD, methods such as Cox proportional hazards models, restricted cubic splines, and threshold regression analyses were utilized.
ResultsOver 7.3 years (median), incident CVD was documented in 727 individuals, including 258 patients who had a stroke and 560 patients who had heart diseases. Adjusted Cox models revealed that higher TyG-WHtR was independently associated with increased CVD risk: each one-unit increase corresponded to an 11% higher CVD risk (HR 1.11, 95% CI 1.01–1.22) and a 25% higher stroke risk (HR 1.25, 95% CI 1.06–1.47). Tertile analyses showed graded associations, with individuals in the highest tertile (T3) having a 51% higher risk of CVD, 90% higher risk of stroke, and 42% higher risk of heart diseases compared with T1. Threshold regression revealed a nonlinear relationship: when TyG-WHtR exceeded 3.76, CVD risk rose markedly (HR 1.22, p <.001), while below this threshold, lower TyG-WHtR levels were associated with reduced CVD risk (HR 0.80, p = .037).
DiscussionIn individuals with sarcopenia or probable sarcopenia, high TyG-WHtR is independently associated with higher CVD risk, demonstrating a distinct threshold effect. TyG-WHtR may be a valuable marker for predicting CVD risk in this population, thus enabling early cardiovascular risk stratification and personalized interventions for this group. However, these findings still require further validation through large-scale studies.