Association between the cumulative exposure to metabolic score for visceral fat and cardiovascular disease incidence in individuals with dysglycemia: insights from CHARLS

Previous studies have established that individuals with dysglycemia represent a high-risk population for cardiovascular disease (CVD), in which visceral fat plays a significant role.The metabolic score for visceral fat (METS-VF) has emerged as a novel surrogate indicator for assessing visceral fat. However, evidence regarding the association between cumulative METS-VF exposure and cardiovascular outcomes in patients with abnormal glucose metabolism remains limited, and it remains unclear whether cumulative METS-VF burden can provide additional risk information for cardiovascular outcomes in this high-risk metabolic subgroup. All data were derived from the China Health and Retirement Longitudinal Study (CHARLS). Cumulative METS-VF served as the exposure variable and was calculated based on METS-VF values obtained from the baseline and follow-up surveys (Wave 1 in 2011–2012 and Wave 3 in 2015). It was defined as the average METS-VF across these two waves multiplied by the 4-year interval between them (2015 − 2011) .The maximal selected rank statistics method was applied to determine the optimal cut-off value of cumulative average METS-VF associated with CVD, which was subsequently used to define high METS-VF exposure. Multivariable Cox proportional hazards regression models were employed to assess the risk of CVD between 2015 and 2020. Among 1,791 participants (mean age 59 ± 8 years; 47% male), 382 (21.3%) incident CVD events occurred. After adjusting for potential covariates, compared with the Q1 group, participants in the highest quartile (Q4) exhibited a hazard ratio (HR) of 1.70 (95% CI, 1.26–2.31) for CVD risk. The optimal cut-off value of cumulative average METS-VF for incident CVD was determined to be ≥ 7.15. The HR for CVD increased progressively with greater burden and high METS-VF at both assessments. Fully adjusted restricted cubic spline (RCS) regression analysis demonstrated a positive and approximately linear relationship between cumulative METS-VF and CVD risk (P for overall < 0.001; P for nonlinear = 0.052) . Among individuals with dysglycemia, higher cumulative METS-VF estimated from two assessments was associated with a higher risk of subsequent CVD after adjustment for measured covariates. These observational findings do not establish causality.