Longitudinal Association of Cumulative Visceral Fat Metabolic Score with New-Onset Stroke in Chinese Middle-Aged and Elderly Adults: A Prospective Study Based on the CHARLS Database

• Each 1-SD rise in cumulative METS-VF increased stroke risk by 29% (HR=1.29, 95% CI: 1.08–1.54, P<0.01). • A METS-VF threshold of 6.84 optimally stratified stroke risk (Log-rank P<0.001). • KM curves showed a 3.4-fold higher 60-month stroke rate in Q4 (17.0%) vs. Q1 (5.0%), diverging from 12 months. • Cumulative METS-VF best predicted stroke risk (AUC=0.606) vs. BMI, ABSI, METS-IR. Each 1-SD rise in cumulative METS-VF increased stroke risk by 29% (HR=1.29, 95% CI: 1.08–1.54, P<0.01). A METS-VF threshold of 6.84 optimally stratified stroke risk (Log-rank P<0.001). KM curves showed a 3.4-fold higher 60-month stroke rate in Q4 (17.0%) vs. Q1 (5.0%), diverging from 12 months. Cumulative METS-VF best predicted stroke risk (AUC=0.606) vs. BMI, ABSI, METS-IR. Stroke is a leading cause of death and disability worldwide, influenced by complex metabolic and lifestyle factors. The Metabolic Visceral Fat Index (METS-VF) has recently gained attention as a key measure of metabolic burden. This study examines the relationship between cumulative METS-VF and stroke risk. This study used the China Health and Retirement Longitudinal Study (CHARLS) database and a multivariate Cox regression model to explore the relationship between cumulative METS-VF and stroke risk. Kaplan-Meier (KM) curves, restricted cubic splines (RCS), and receiver operating characteristic (ROC) analysis were utilized to assess dose-response relationships and predictive performance. The research also examined the effects of cumulative exposure duration and burden on stroke risk, with subgroup and sensitivity analyses to confirm robustness. In a study of 4,069 participants, 347 strokes (8.5%) occurred. Multivariate Cox regression revealed that the highest exposure group (Q4) had more than double the stroke risk of the lowest group (Q1), with a hazard ratio (HR) of 2.12. A one standard deviation increase in cumulative METS-VF raised stroke risk by 29%. The optimal threshold was 6.84, above which stroke risk significantly increased. KM survival analysis supported this link, and ROC analysis indicated that cumulative METS-VF was a predictor of stroke risk, with an area under the curve (AUC) of 0.606. Subgroup and sensitivity analyses validated these findings. This study identifies cumulative METS-VF as an independent stroke risk factor, with both its duration and cumulative burden affecting risk, providing new insights for prevention and intervention.