The association between triglyceride glucose-waist height ratio index and cardiometabolic multimorbidity among Chinese middle-aged and older adults: a national prospective cohort study

BACKGROUND: Cardiometabolic multimorbidity (CMM) imposes a progressively severe health burden worldwide. Triglyceride-glucose (TyG) index and waist-to-height ratio (WHtR), as indicators of insulin resistance and central adiposity, respectively, have been shown to be strongly associated with CMM. However, there is currently a lack of research combining the two for CMM risk assessment. This study aims to investigate the relationship between TyG-WHtR index and CMM. METHODS: This prospective cohort study analyzed data from Chinese adults aged ≥ 45 years participating in the 2011-2020 waves of the China Health and Retirement Longitudinal Study (CHARLS). We employed the Kaplan-Meier curves, multivariable Cox regression analysis, and restricted cubic spline (RCS) to examine the relationship between the TyG-WHtR index and the risk of CMM. Time-dependent receiver operating characteristic (ROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses were utilized to evaluate predictive performance. Additionally, subgroup analyses and sensitivity tests were conducted to assess the robustness of the findings. RESULTS: During a median follow-up of 9 years, 413 (9.4%) of the 4393 participants developed CMM. Multivariable Cox regression analysis revealed progressively higher risks of CMM across increasing TyG-WHtR quartiles. Compared to participants in the lowest quartile (Q1) of the TyG-WHtR index, the hazard ratios (HRs) and 95% confidence intervals (CIs) for those in quartiles Q2, Q3, and Q4 were 1.75 (1.18-2.6), 2.33 (1.58-3.43), and 3.13 (2.08-4.7), respectively. Consistently, elevated cumulative TyG-WHtR independently increased CMM risk. The RCS analysis indicated a positive linear relationship between the TyG-WHtR index and the incidence of CMM. Moreover, both baseline and cumulative TyG-WHtR significantly improved reclassification metrics (NRI/IDI) and discriminative ability (AUC). Sensitivity analyses corroborated these primary findings. CONCLUSION: This study suggests that TyG-WHtR independently predicts CMM risk. The linear dose-response relationship highlight the potential utility of TyG-WHtR in early risk assessment and prevention strategies for CMM.