Evaluation for Performance of Body Composition Index Based on Quantitative Computed Tomography in the Prediction of Metabolic Syndrome

作者全名："Li, Cuihong; Xu, Bingwu; Chen, Mengxue; Zhang, Yong"

作者地址："[Li, Cuihong; Xu, Bingwu; Zhang, Yong] Chongqing Med Univ, Publ Hlth Coll, Chongqing, Peoples R China; [Chen, Mengxue; Zhang, Yong] Chongqing Med Univ, Hlth Med Ctr, Affiliated Hosp 2, Chongqing, Peoples R China; [Zhang, Yong] Chongqing Med Univ, Publ Hlth Coll, Chongqing 400016, Peoples R China"

通信作者："Zhang, Y (通讯作者)，Chongqing Med Univ, Publ Hlth Coll, Chongqing 400016, Peoples R China."

来源：METABOLIC SYNDROME AND RELATED DISORDERS

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001180947100002

JCR分区：Q4

影响因子：1.3

年份：2024

卷号：　

期号：　

开始页：　

结束页：　

文献类型：Article; Early Access

关键词：metabolic syndrome; quantitative computed tomography; abdominal fat; liver fat; abdominal muscle

摘要："Objective: We aimed to evaluate the performance of predicting metabolic syndrome (MS) using body composition indices obtained by quantitative computed tomography (QCT).Methods: In this cross-sectional study, data were collected from 4745 adults who underwent QCT examinations at a Chongqing teaching hospital between July 2020 and March 2022. Visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), total abdominal fat (TAT), abdominal muscle tissue (AMT), and liver fat content (LFC) were measured at the L2-L3 disc level using specialized software, and the skeletal muscle index (SMI) were calculated. The correlations between body composition indicators were analyzed using the Pearson correlation analysis. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) were used to assess these indicators' predictive potential for MS.Results: VAT and TAT exhibited the best predictive ability for MS, with AUCs of 0.797 [95% confidence interval (CI): 0.779-0.815] and 0.794 (95% CI: 0.775-0.812) in males, and 0.811 (95% CI: 0.785-0.836) and 0.802 (95% CI: 0.774-0.830) in females. The AUCs for VAT and TAT were the same but significantly higher than body mass index and other body composition measures. SAT also demonstrated good predictive power in females [AUC = 0.725 (95%CI: 0.692-0.759)] but fair power in males [AUC = 0.6673 (95%CI: 0.650-0.696)]. LFC showed average predictive ability, AMT showed average predictive ability in males but poor ability in females, and SMI had no predictive ability. Correlation analysis revealed a strong correlation between VAT and TAT (males: r = 0.95, females: r = 0.89). SAT was strongly correlated with TAT only in females (r = 0.89). In the male group, the optimal thresholds for VAT and TAT were 207.6 and 318.7 cm2, respectively; in the female group, the optimal thresholds for VAT and TAT were 128.0 and 269.4 cm2, respectively.Conclusions: VAT and TAT are the best predictors of MS. SAT and LFC can also be acceptable to make predictions, whereas AMT can only make predictions of MS in males."

基金机构：Intelligent Medicine Research Project of Chongqing Medical University [ZHYX202024]

基金资助正文：This research was funded by the Intelligent Medicine Research Project of Chongqing Medical University (Grant No: ZHYX202024).