College of Nursing, Wenzhou Medical University, Wenzhou, China.
Department of Global Health, School of Public Health, Wuhan University of Science and Technology, Wuhan, China.
J Diabetes. 2024 Aug;16(8):e13595. doi: 10.1111/1753-0407.13595.
To estimate glucose disposal rate (eGDR) as a newly validated surrogate marker of insulin resistance. Few studies have explored the association between changes in eGDR levels and stroke incidence. This study aims to explore the effect of the level of eGDR control on stroke and events.
Data were obtained from the China Longitudinal Study on Health and Retirement (CHARLS). The eGDR control level was classified using K-means cluster analysis. Logistic regression analysis was used to explore the association between different eGDR control levels and incident stroke. Restrictive cubic spline regression was used to test the potential nonlinear association between cumulative eGDR and stroke incidence.
Of the 4790 participants, 304 (6.3%) had a stroke within 3 years. The odds ratio (OR) was 2.34 (95% confidence interval [CI], 1.42-3.86) for the poorly controlled class 4 and 2.56 (95% CI, 1.53-4.30) for the worst controlled class 5 compared with class 1 with the best controlled eGDR. The OR for well-controlled class 2 was 1.28 (95% CI, 0.79-2.05), and the OR for moderately controlled class 3 was 1.95 (95% CI, 1.14-3.32). In restrictive cubic spline regression analysis, eGDR changes are linearly correlated with stroke occurrence. Weighted quartile and regression analysis identified waist circumference and hypertension as key variables of eGDR for predicting incident stroke.
Poorly controlled eGDR level is associated with an increased risk of stroke in middle-aged and elderly people. Monitoring changes in eGDR may help identify individuals at high risk of stroke early.
评估葡萄糖处置率（eGDR）作为新验证的胰岛素抵抗替代标志物。很少有研究探讨 eGDR 水平变化与卒中发病之间的关系。本研究旨在探讨 eGDR 控制水平对卒中及事件的影响。
数据来自中国健康与养老追踪调查（CHARLS）。采用 K 均值聚类分析对 eGDR 控制水平进行分类。采用 Logistic 回归分析探讨不同 eGDR 控制水平与卒中发病的关系。采用限制性立方样条回归检验累积 eGDR 与卒中发病之间的潜在非线性关系。
在 4790 名参与者中，304 人（6.3%）在 3 年内发生卒中。与 eGDR 控制最佳的第 1 类相比，控制较差的第 4 类（OR=2.34，95%CI：1.42-3.86）和控制最差的第 5 类（OR=2.56，95%CI：1.53-4.30）的比值比（OR）更高。与 eGDR 控制最佳的第 1 类相比，控制较好的第 2 类（OR=1.28，95%CI：0.79-2.05）的 OR 较低，控制适度的第 3 类（OR=1.95，95%CI：1.14-3.32）的 OR 较高。在限制性立方样条回归分析中，eGDR 变化与卒中发生呈线性相关。加权四分位数和回归分析确定腰围和高血压是预测卒中发生的 eGDR 的关键变量。
控制不佳的 eGDR 水平与中老年人卒中风险增加相关。监测 eGDR 的变化可能有助于早期识别卒中风险较高的个体。
