Background: Body composition is a crucial factor associated with the incidence of type 2 diabetes mellitus. However, no study on this relationship has been performed in the Chinese population. This study aimed to investigate the relationship between body composition indicators and risk of type 2 diabetes mellitus among Chinese adults undergoing medical examination.
Methods: Between January 2018 and July 2018, a retrospective cross-sectional study was performed on 3367 (2307 male and 1060 female) participants aged ≥18 years undergoing medical examination in Zhengzhou. Logistic regression analysis was performed to explore the relationship between body composition indicators and risk of type 2 diabetes mellitus. A receiver operating characteristic curve was used to calculate cutoff points and the predictive power of each indicator.
Results: Among the 3367 participants, 12.53% were diagnosed with type 2 diabetes mellitus. Multivariate logistic analysis indicated that male participants (odds ratio [OR] = 1.68, 95% confidence interval [CI]: 1.29-2.19), older participants (OR = 1.05, 95% CI: 1.04-1.06), participants with a waist-to-hip ratio above the reference value (OR = 1.56, 95% CI: 1.18-2.07), participants with body fat percentage above the reference value (OR = 1.62, 95% CI: 1.01-2.68), and participant with a large visceral fat area (OR = 1.01, 95% CI: 1.01-1.02) had a high risk of type 2 diabetes mellitus. Waist-to-hip ratio, body fat percentage, and visceral fat area were the best indicators of type 2 diabetes mellitus (P < 0.001) with cutoff values of 0.90, 25.02%, and 92.00 cm2, respectively.
Conclusion: This study suggests a predictive relationship between type 2 diabetes mellitus and body composition indicators of waist-to-hip ratio, body fat percentage, and visceral fat area, which are valuable for screening diabetes and providing effective health education and behavioral intervention for high-risk populations.
Keywords: Body composition; Indicators; Predictive value; Type 2 diabetes mellitus; Visceral fat area.