Cardiometabolic multimorbidity (CMM) poses a growing public health challenge, calling for better primary prevention strategies. While both elevated LDL-C and visceral adiposity (assessed by Chinese visceral adiposity index (CVAI)) are established risk factors, their combined utility for risk stratification is unclear. This prospective analysis included 8813 CMM-free adults from the China Health and Retirement Longitudinal Study (CHARLS). We proposed a novel integrated metric, the Visceral Lipoprotein Risk (VLR) index, defined as CVAI × LDL-C (mg/dL). Its association with incident CMM was evaluated using Cox regression, Kaplan-Meier analysis, and restricted cubic spline (RCS). The incremental predictive value of VLR was assessed via receiver operating characteristic (ROC) analysis, with robustness examined through sensitivity analyses. Mediation analysis explored underlying pathways. Over a median follow-up of 9 years, 729 (8.27%) participants developed CMM. After multivariable adjustment, each standard deviation (SD) increase in VLR was associated with an 31% higher risk of CMM (HR: 1.31, 95%CI 1.24–1.39). Participants in the highest VLR quartile had a 3.12-fold increased risk (95%CI 2.39–4.08) compared to the lowest quartile. Kaplan-Meier curves (log-rank P < 0.001) and RCS models confirmed a strong, positive, and non-linear dose-response relationship. The VLR index demonstrated good discriminative ability (AUC: 0.78). Subgroup analyses revealed effect heterogeneity, which mediation analysis attributed to distinct underlying pathways: while Triglyceride-Glucose Index (TyG) and Atherogenic Index of Plasma (AIP) were key mediators in the overall population, white blood cell (WBC) count emerged as a significant but minor mediator (proportion mediated 3.17%) in individuals free of any baseline cardiometabolic disease (CMD), whereas HbA1c remained the predominant mediator in the obese subgroup. The VLR index, its non-linear association and mediation mechanisms underscore biological plausibility and utility for refined risk stratification, offering a practical tool for early identification and targeted primary prevention in middle-aged and older adults.
Shao et al. (Sun,) studied this question.