Luo Yufang, Liu Lei, Liu Min, Tang Chenyi, Liu Hong, Wang Meng, Feng Guo, Wu Jinru, Wu Wei
Department of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Health Management Center, the Third Xiangya Hospital of Central South University, Changsha, China.
Clin Endocrinol (Oxf). 2025 Mar;102(3):264-272. doi: 10.1111/cen.15171. Epub 2024 Dec 1.
The triglyceride glucose (TyG) index, a novel and easily obtained marker of insulin resistance (IR), has been shown to predict metabolic diseases. Monitoring body composition is crucial in assessing disease states. This study aimed to investigate the relationship between body composition and IR as assessed by the TyG index.
Between January 2018 and December 2021, 12,186 individuals were initially enroled, with 4061 adults were ultimately included. Body composition, including fat mass (FM), fat mass index (FMI), fat-free mass (FFM), fat-free mass index (FFMI), and percent body fat (PBF), was measured using bioelectrical impedance analysis. Spearman analysis assessed correlations between body composition indices and the TyG index. Binary logistic regression identified independent predictors of IR.
Older women (≥ 50 years old) showed significantly higher BMI, PBF, FM, FMI, FFMI, HOMA-IR, and the TyG index, but lower FFM compared to younger women; Older men exhibited significantly lower BMI, FM, FFM, FFMI, HOMA-IR, and the TyG index than the younger men. FM, FMI, FFM, FFMI, and PBF were positively correlated with the TyG index. FFMI and PBF significantly predicted IR in both genders. Combined FFMI and PBF yielded an area under the ROC curves of 0.718 in women and 0.661 in men for IR diagnosis.
The TyG index correlates with body composition parameters of FFMI and PBF as well as HOMA-IR potentially making it a convenient marker of metabolic risk.
甘油三酯葡萄糖(TyG)指数是一种新型且易于获取的胰岛素抵抗(IR)标志物,已被证明可预测代谢性疾病。监测身体成分对于评估疾病状态至关重要。本研究旨在探讨通过TyG指数评估的身体成分与IR之间的关系。
在2018年1月至2021年12月期间,最初招募了12186人,最终纳入4061名成年人。使用生物电阻抗分析测量身体成分,包括脂肪量(FM)、脂肪量指数(FMI)、去脂体重(FFM)、去脂体重指数(FFMI)和体脂百分比(PBF)。Spearman分析评估身体成分指数与TyG指数之间的相关性。二元逻辑回归确定IR的独立预测因素。
与年轻女性相比,老年女性(≥50岁)的BMI、PBF、FM、FMI、FFMI、HOMA-IR和TyG指数显著更高,但FFM更低;老年男性的BMI、FM、FFM、FFMI、HOMA-IR和TyG指数显著低于年轻男性。FM、FMI、FFM、FFMI和PBF与TyG指数呈正相关。FFMI和PBF在两性中均显著预测IR。联合FFMI和PBF在女性中用于IR诊断的ROC曲线下面积为0.718,在男性中为0.661。
TyG指数与FFMI和PBF以及HOMA-IR的身体成分参数相关,可能使其成为代谢风险的便捷标志物。