Baseline triglyceride–cholesterol–body weight index and risk of incident cardiovascular disease: evidence from the CHARLS and ELSA cohorts

Background: The triglyceride-cholesterol-body weight index (TCBI) has been proposed as a composite indicator of nutritional-metabolic status, yet evidence regarding its association with incident CVD in general aging populations and across different modeling strategies remains limited. Methods: We analyzed harmonized data from the China Health and Retirement Longitudinal Study (CHARLS: 2011-2018) and the English Longitudinal Study of Aging (ELSA: 2002-2018). Community-dwelling adults aged 45 years and older and free of CVD at baseline were included. Baseline TCBI was calculated as triglycerides × total cholesterol × body weight /1,000 and primarily analyzed as a log-transformed continuous variable. Incident CVD was defined as physician-diagnosed heart disease or stroke during follow-up. Cox proportional hazards models, restricted cubic spline analyses, and prespecified subgroup analyses were conducted separately in each cohort. Results: = 0.025) when modeled as a continuous variable. Quartile-based analyses were broadly consistent, although the pattern was not entirely monotonic, particularly in ELSA. Restricted cubic spline analyses showed a significant overall association without evidence of non-linearity in CHARLS, whereas neither the overall nor the non-linear association was statistically significant in ELSA. The results remained robust in lag analyses. However, the incremental predictive value of TCBI beyond conventional risk factors was minimal, with no significant improvement in discrimination or reclassification in either cohort. Conclusions: Higher baseline TCBI was associated with incident CVD in two large aging cohorts, especially when modeled as a continuous exposure. However, its incremental predictive value beyond conventional cardiovascular risk factors was minimal. TCBI may therefore serve as a complementary metabolic and nutritional indicator rather than a stand-alone predictive tool.