Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Hubei Provincial Clinical Research Center for Diabetes and Metabolic Disorders, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Lipids Health Dis. 2023 Feb 14;22(1):24. doi: 10.1186/s12944-023-01790-7.
Studies have reported that lipid-derived indicators are associated with type 2 diabetes (T2D) in various populations; however, it is unclear which lipid-derived indicators could effectively predict T2D risk. Therefore, this study aimed to explore the association between four lipid-derived indicators and T2D risk.
This was a post-hoc analysis from a large cohort that included data from 114,700 Chinese individuals aged 20 years and older from 11 cities and 32 sites. The association between four lipid-derived indicators and T2D risk was determined using Kaplan-Meier (KM) survival curves, Cox regression, and restricted cubic spline analyses. This study used receiver operating characteristic (ROC) curves for assessing the ability of four lipid-derived indicators to accurately predict the development of T2D during follow-up.
This study included a total of 114,700 participants, with a mean age of 44.15. These individuals were followed up for 3.1 years, of which 2668 participants developed T2D. ROC curve analysis showed that TyG was the most robust predictor of 3-year [aera under the ROC (AUC) = 0.77, 95% CI: 0.768, 0.772] and 5-year T2D risk (AUC = 0.763, 95% CI: 0.760, 0.765). In addition, sensitivity analysis showed an association between TyG and an increased incidence of T2D.
The results suggest that TyG was a superior for predicting the risk of developing T2D in the general Chinese population.
研究报告称，脂源性指标与 2 型糖尿病（T2D）在不同人群中相关；然而，目前尚不清楚哪些脂源性指标能够有效预测 T2D 风险。因此，本研究旨在探讨四种脂源性指标与 T2D 风险之间的关联。
这是一项来自大型队列的事后分析，该队列包括来自 11 个城市和 32 个地点的 114700 名年龄在 20 岁及以上的中国个体的数据。使用 Kaplan-Meier（KM）生存曲线、Cox 回归和限制性立方样条分析来确定四种脂源性指标与 T2D 风险之间的关联。本研究使用受试者工作特征（ROC）曲线来评估四种脂源性指标在随访期间准确预测 T2D 发展的能力。
本研究共纳入 114700 名参与者，平均年龄为 44.15 岁。这些参与者的随访时间为 3.1 年，其中 2668 名参与者发生了 T2D。ROC 曲线分析表明，TyG 是预测 3 年（ROC 下面积（AUC）=0.77，95%CI：0.768，0.772）和 5 年 T2D 风险（AUC=0.763，95%CI：0.760，0.765）最稳健的预测指标。此外，敏感性分析表明 TyG 与 T2D 发生率的增加之间存在关联。
结果表明，TyG 是预测中国一般人群发生 T2D 风险的较好指标。
