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

ABSTRACT

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.