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

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.

Associations between body size and visual impairment of first-year university students in Chongqing: A cross-sectional study.

The relationship between body size and visual impairment (VI) presents a controversial topic in the health sciences. This study aims to evaluate and clarify the potential associations between these 2 variables. We conducted a cross-sectional study on first-year students enrolled in 2022 at the Southwest University of Political Science & Law. The students underwent a series of physical examinations and visual acuity tests. Visual impairment was classified into 3 categories: mild, moderate, or severe. We used logistic regression analysis to examine the association between body size and VI. Our findings indicated a high prevalence of VI among first-year university students; more than 80% of them were affected. In bivariate analysis, height and weight were negatively related to the presence of VI. However, BMI (body mass index) was not related to VI. By adjusting all available confounders, no associations between BMI (OR = 1.002, 95% CI = 0.974-1.032, P = .877), height (OR = 0.998, 95% CI = 0.967-1.010, P = .298), weight (OR = 0.999, 95% CI = 989-1.009, P = .860), and mild-severe VI were found in females. For males, the ORs were 0.988 (95% CI = 0.955-1.021, P = .459), 0.980 (95% CI = 0.954-1.006, P = .135), and 0.995 (95% CI = 0.985-1.004, P = .285) for BMI, height, and weight, respectively. Among young adults demonstrating high academic performance in high schools, the cessation of physical growth, combined with potential eye strain resulting from overuse, may mitigate any previously observed positive associations between physical status and VI in younger children.