Associations of cumulative exposure and dynamic trajectories of the triglyceride–total cholesterol–body weight index with new-onset cardiometabolic multimorbidity in middle-aged and older Chinese adults: evidence from a nationwide prospective cohort

The global prevalence of cardiometabolic multimorbidity (CMM) has created a substantial health burden. The triglyceride–total cholesterol–body weight index (TCBI), a novel and easily computed metabolic indicator, has shown a robust association with stroke and cardiovascular disease (CVD). However, research on the risk assessment of CMM remains limited. This study aims to investigate the relationships between cumulative exposure to the TCBI (CumTCBI) and its longitudinal trajectories with the risk of incident CMM in middle-aged and older adults, as well as to develop a survival-based risk prediction model. Data from the China Health and Retirement Longitudinal Study (CHARLS) were utilized. Cox proportional hazards models and restricted cubic spline (RCS) analyses were applied to evaluate the associations between CumTCBI and the risk of CMM. Trajectory patterns of TCBI were discerned through K-means clustering. Subgroup and interaction analyses were conducted. Extensive sensitivity analyses were performed, including lag analysis, complete-case analysis, trimmed RCS analysis, interval-censored survival analysis, and Fine-Gray competing risk models. The proportional hazards assumption was verified using Schoenfeld residuals test. Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) were calculated to assess incremental predictive value. A survival nomogram prediction model based on Cox regression was developed, with discrimination assessed using the time-dependent area under the receiver operating characteristic curve (ROC) and clinical utility evaluated through decision curve analysis (DCA). Among 5068 participants, 424 individuals (8.4%) developed incident CMM during the follow-up period. Following multivariable adjustment, each 1-SD increase in CumTCBI was associated with an 18% higher risk of CMM (HR = 1.18, 95%CI 1.09-1.28), and the highest tertile was linked to an increased risk of CMM compared to the lowest tertile (HR = 1.90, 95% CI 1.43-2.52). A significant nonlinear dose-response relationship between CumTCBI and the riks of CMM (P for nonlinearity < 0.001). Three distinct trajectories are identified (low-stable, moderate-stable, and high-stable), with participants in the high-stable group facing a 61% greater risk of CMM than those with consistently low TCBI (HR = 1.61, 95% CI 1.10-2.36). These associations remained consistent across subgroups and were robust in all sensitivity. The proportional hazards assumption was satisfied (global P = 0.86). NRI and IDI analyses confirmed that TCBI provided incremental predictive value beyond its individual components (NRI = 0.158, P < 0.001). The nomogram prediction model exhibited acceptable discrimination (AUC: 0.715 in the training cohort and 0.694 in the validation cohort), and DCA indicated a favorable clinical net benefit. Higher cumulative TCBI exposure and unfavorable TCBI trajectories are independently associated with increased CMM risk in middle-aged and older Chinese adults. The Cox-based nomogram provides a practical tool for early risk stratification, supporting targeted preventino and personalized management of CMM.