Association of Baseline, Cumulative Exposure, and Dynamic Changes of VLR with the Risk of Incident CMM in Individuals with MASLD: A Longitudinal Cohort Study from CHARLS

Background and Aims: Cardiometabolic multimorbidity (CMM) significantly increases mortality and long-term disease burden. The metabolic dysfunction-associated steatotic liver disease (MASLD) population is often accompanied by insulin resistance, dyslipidemia, visceral fat accumulation, and chronic low-grade inflammation, making it a high-risk population for the occurrence of multisystem cardiometabolic disease clustering. The visceral lipoprotein risk (VLR) index is a novel comprehensive lipid-visceral fat indicator integrating low-density lipoprotein cholesterol (LDL-C) and the Chinese visceral adiposity index (CVAI), but the relationship of its dynamic trajectories and cumulative exposure with incident CMM in the MASLD population remains unclear. Materials and Methods: This study is based on the China Health and Retirement Longitudinal Study (CHARLS). The K-means clustering algorithm was used to identify the longitudinal evolution patterns of the VLR index in the MASLD population. Cox proportional hazards models were used to evaluate the associations between various VLR indicators (dynamic changes, baseline levels, and cumulative values) and CMM risk. Restricted cubic splines (RCS) were used to explore the nonlinear relationships between variables, and the predictive values of the cumulative VLR index and baseline VLR index were compared through time-dependent receiver operating characteristic curves, C-index, integrated discrimination improvement, and net reclassification improvement. Results: A total of 2472 MASLD participants were ultimately included, with a median follow-up of 5 years, and a total of 255 (10.32%) incident CMM cases occurred. The incidence rates of CMM in the Low, Medium, and High VLR trajectory groups were 7.37%, 10.26%, and 17.76%, respectively. In the fully adjusted model, compared with the Low trajectory group, the risk of CMM was significantly elevated in the High trajectory group [hazard ratio (HR) 1.97, 95% confidence interval (CI): 1.41–2.76]. Compared with the lowest tertile of cumulative VLR, the risk in the highest tertile increased (HR 1.57, 95% CI: 1.14–2.17; P for trend = 0.004); the highest tertile of baseline VLR was similarly associated with a higher risk (HR 1.44, 95% CI: 1.06–1.97; P for trend = 0.011). Each 1-standard deviation increase in cumulative VLR and baseline VLR corresponded to a 28% and 26% increase in CMM risk, respectively. RCS showed that the overall association was significant, and no obvious nonlinearity was observed. Sensitivity analyses supported the robustness of the results. Compared with baseline VLR, CVAI, and LDL-C, cumulative VLR demonstrated better clinical value in the predictive ability for evaluating 5-year CMM risk (area under the curve = 0.622); after adding cumulative VLR to the adjusted model, the C-index improved from 0.693 to 0.714. Conclusions: In the middle-aged and elderly MASLD population, the High trajectory, higher cumulative exposure, and higher baseline levels of the VLR index are all independently associated with the risk of incident CMM. Compared with a single baseline measurement, dynamic and cumulative VLR provide more complete metabolic risk information, which can be used for long-term risk stratification in the MASLD population.