Relationship between visceral fat area and metabolic syndrome in the Chongqing population based on quantitative CT analysis

Chen Mengxue; Chen Yao; Wang Lihua; Chen Ying; Wang Lingyun; Li Xuan

doi:10.11986/j.issn.1673-873X.2025.03.04

Abstract：Objective To investigate the association between visceral fat area(VFA)and metabolic syndrome(MetS)using quantitative computed tomography(QCT)body-composition measurement.Methods We retrospectively reviewed the health-check data of 5,950 individuals(3,317 men and 2,633 women)who underwent QCT body-composition analysis at the Health Medicine Center of the Second Affiliated Hospital of Chongqing Medical University from July 2020 to July 2022.VFA and liver fat content(LFC)were measured by QCT,and clinical parameters including height,body weight,body mass index(BMI),waist circumference(WC),systolic and diastolic blood pressure(SBP,DBP),triglycerides(TG),total cho-lesterol(TC),high-density and low-density lipoprotein cholesterol(HDL-C,LDL-C),serum uric acid(SUA),and fasting blood glucose(FBG)were collected.We compared VFA between MetS and non-MetS groups stratified by sex,performed multivariable logistic regression with stepwise adjustment for confounders to construct three predictive models,and evalua-ted their performance using receiver operating characteristic(ROC)curves.Results The prevalence of MetS was signifi-cantly higher in men than in women(26.56%vs.9.99%).In both sexes,MetS patients were older and had higher BMI,WC,SBP,DBP,TG,SUA,FBG,and LFC,and lower HDL-C compared with non-MetS participants(P<0.05),while TC and LDL-C did not differ significantly between groups(P>0.05).VFA was markedly greater in the MetS group than in the non-MetS group,and higher VFA levels were associated with increased MetS risk;this trend persisted after sequential adjustment for confounders(P<0.05).VFA showed good predictive ability for MetS,with even stronger performance in women.Conclusion VFA appears to be an independent risk factor for MetS and may serve as a sensitive predictor for early MetS detection,demonstrating robust predictive efficacy.