Association between METS-VF and hypertension in U.S.: a cross-sectional analysis of NHANES data

Visceral fat accumulation is a key factor in the onset of cardiometabolic diseases, including hypertension. Metabolic Score for Visceral Fat (METS-VF) is an innovative, non-invasive metric developed to estimate visceral fat based on commonly accessible clinical parameters. A total of 13,822 participants were included in this cross-sectional analysis. METS-VF was calculated using a validated formula incorporating age, sex, metabolic score for insulin resistance, waist-to-height ratio. Hypertension was defined based on measured blood pressure or self-reported physician diagnosis. Logistic regression models were used to estimate the association between METS-VF and hypertension, adjusting for sociodemographic, clinical, and dietary covariates. Subgroup, threshold effect, and ROC analyses were conducted to assess robustness and predictive ability. External validation was conducted using 8400 fasting participants from the China Health and Retirement Longitudinal Study (CHARLS) 2011 baseline cohort. METS-VF was positively associated with hypertension. In model 3, participants in the highest METS-VF quartile had substantially higher odds of hypertension (OR: 5.82, 95% CI 4.76-7.11, P < 0.001). A threshold effect was observed at a METS-VF value of 6.42. Subgroup analyses confirmed the consistency of associations across various demographic and clinical strata. Notably, high intake of protein and unsaturated fatty acids attenuated this association. ROC analysis showed METS-VF had the best discriminatory power for hypertension (AUC = 0.749) compared to BMI, WHtR and METS-IR. In the CHARLS external validation cohort, METS-VF also showed the highest AUC among the evaluated indices (AUC = 0.668), and logistic regression confirmed a consistent positive association with hypertension. METS-VF was significantly associated with prevalent hypertension and showed better discriminatory performance than traditional adiposity indices. External validation in CHARLS supports the robustness of these findings, although prospective validation is still warranted.