The School of public health, Inner Mongolia University of Science and Technology Baotou Medical College, Baotou, China.
The School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Cardiovasc Diabetol. 2024 Aug 16;23(1):304. doi: 10.1186/s12933-024-02373-1.
Insulin resistance is linked to an increased risk of frailty, yet the comprehensive relationship between the triglyceride glucose-body mass index (TyG-BMI), which reflects weight, and frailty, remains unclear. This relationship is investigated in this study.
Data from 9135 participants in the China Health and Retirement Longitudinal Study (2011-2020) were analysed. Baseline TyG-BMI, changes in the TyG-BMI and cumulative TyG-BMI between baseline and 2015, along with the frailty index (FI) over nine years, were calculated. Participants were grouped into different categories based on TyG-BMI changes using K-means clustering. FI trajectories were assessed using a group-based trajectory model. Logistic and Cox regression models were used to analyse the associations between the TyG-BMI and FI trajectory and frail incidence. Nonlinear relationships were explored using restricted cubic splines, and a linear mixed-effects model was used to evaluate FI development speed. Weighted quantile regression was used to identify the primary contributing factors.
Four classes of changes in the TyG-BMI and two FI trajectories were identified. Individuals in the third (OR = 1.25, 95% CI: 1.10-1.42) and fourth (OR = 1.83, 95% CI: 1.61-2.09) quartiles of baseline TyG-BMI, those with consistently second to highest (OR = 1.49, 95% CI: 1.32-1.70) and the highest (OR = 2.17, 95% CI: 1.84-2.56) TyG-BMI changes, and those in the third (OR = 1.20, 95% CI: 1.05-1.36) and fourth (OR = 1.94, 95% CI: 1.70-2.22) quartiles of the cumulative TyG-BMI had greater odds of experiencing a rapid FI trajectory. Higher frail risk was noted in those in the fourth quartile of baseline TyG-BMI (HR = 1.42, 95% CI: 1.28-1.58), with consistently second to highest (HR = 1.23, 95% CI: 1.12-1.34) and the highest TyG-BMI changes (HR = 1.58, 95% CI: 1.42-1.77), and those in the third (HR = 1.10, 95% CI: 1.00-1.21) and fourth quartile of cumulative TyG-BMI (HR = 1.46, 95% CI: 1.33-1.60). Participants with persistently second-lowest to the highest TyG-BMI changes (β = 0.15, 0.38 and 0.76 respectively) and those experiencing the third to fourth cumulative TyG-BMI (β = 0.25 and 0.56, respectively) demonstrated accelerated FI progression. A U-shaped association was observed between TyG-BMI levels and both rapid FI trajectory and higher frail risk, with BMI being the primary factor.
A higher TyG-BMI is associated with the rapid development of FI trajectory and a greater frail risk. However, excessively low TyG-BMI levels also appear to contribute to frail development. Maintaining a healthy TyG-BMI, especially a healthy BMI, may help prevent or delay the frail onset.
胰岛素抵抗与虚弱风险增加有关,但是反映体重的甘油三酯-葡萄糖-体重指数(TyG-BMI)与虚弱之间的综合关系尚不清楚。本研究对此进行了调查。
分析了来自中国健康与退休纵向研究(2011-2020 年)的 9135 名参与者的数据。计算了基线 TyG-BMI、基线与 2015 年之间 TyG-BMI 的变化以及累积 TyG-BMI,以及九年期间的虚弱指数(FI)。使用 K-均值聚类根据 TyG-BMI 的变化将参与者分为不同类别。使用基于群组的轨迹模型评估 FI 轨迹。使用逻辑和 Cox 回归模型分析 TyG-BMI 与 FI 轨迹和虚弱发生率之间的关联。使用受限立方样条探索非线性关系,并使用线性混合效应模型评估 FI 发展速度。使用加权分位数回归确定主要贡献因素。
确定了 TyG-BMI 的四种变化类别和两种 FI 轨迹。基线 TyG-BMI 处于第三(OR=1.25,95%CI:1.10-1.42)和第四(OR=1.83,95%CI:1.61-2.09)四分位的个体,那些 TyG-BMI 变化始终处于第二高(OR=1.49,95%CI:1.32-1.70)和最高(OR=2.17,95%CI:1.84-2.56)四分位的个体,以及那些 TyG-BMI 处于第三(OR=1.20,95%CI:1.05-1.36)和第四(OR=1.94,95%CI:1.70-2.22)四分位的个体,更有可能出现快速 FI 轨迹。基线 TyG-BMI 处于第四四分位的个体(HR=1.42,95%CI:1.28-1.58)虚弱风险更高,TyG-BMI 变化始终处于第二高(HR=1.23,95%CI:1.12-1.34)和最高(HR=1.58,95%CI:1.42-1.77)四分位的个体,以及那些 TyG-BMI 处于第三(HR=1.10,95%CI:1.00-1.21)和第四四分位的个体(HR=1.46,95%CI:1.33-1.60)。那些 TyG-BMI 变化持续处于第二低至高的个体(β=0.15、0.38 和 0.76)和经历第三至第四累积 TyG-BMI 的个体(β=0.25 和 0.56)的 FI 进展加速。TyG-BMI 水平与快速 FI 轨迹和更高的虚弱风险之间呈 U 形关联,BMI 是主要因素。
较高的 TyG-BMI 与 FI 轨迹的快速发展和更高的虚弱风险相关。然而,过低的 TyG-BMI 水平似乎也会导致虚弱的发生。保持健康的 TyG-BMI,尤其是健康的 BMI,可能有助于预防或延迟虚弱的发生。