Liu Xue, Zhang Yuhao, Chai Yuwei, Li Yuchen, Yuan Jie, Zhang Li, Zhang Haiqing
Department of Endocrinology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, 250021, China.
Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China.
J Clin Endocrinol Metab. 2025 Feb 18;110(3):677-684. doi: 10.1210/clinem/dgae558.
Evidence on the link between iron status markers and insulin resistance (IR) is limited.
We aimed to explore the relationship between iron status and IR among US adults.
This study involved 2993 participants from the National Health and Nutrition Examination Survey (NHANES) 2003-2006, 2017-2020. IR is characterized by a homeostatic model assessment (HOMA)-IR value of ≥2.5. Weighted linear and multivariable logistic regression analyses were used to examine the linear relationships between iron status and IR. Furthermore, restricted cubic splines (RCS) were used to identify the nonlinear dose-response associations. Stratified analyses by age, sex, body mass index, and physical activity were also performed. Last, a receiver operating characteristic (ROC) curve was used to evaluate the predictive value of iron status in IR.
In weighted linear analyses, serum iron (SI) exhibited a negative correlation with HOMA-IR (β -0.03, 95% CI -0.05, -0.01, P = .01). In weighted multivariate logistic analyses, iron intake and the serum transferrin receptor (sTfR) were positively correlated with IR (OR 1.02, 95% CI 1.00-1.04, P = .04; OR 1.07, 95% CI 1.02-1.13, P = .01). Also, SI and transferrin saturation (TSAT) were negatively correlated with IR (OR 0.96, 95% CI 0.94-0.98, P < .0001; OR 0.98, 95% CI 0.97-0.99, P < .001) after adjusting for confounding factors. RCS depicted a nonlinear dose-response relationship between sTfR and TSAT and IR. This correlation remained consistent across various population subgroups. The ROC curve showed that TSAT performed better than iron intake, SI and sTfR in ROC analyses for IR prediction.
All biomarkers demonstrated significantly lower risk of IR with increasing iron levels, which will contribute to a more comprehensive and in-depth understanding of the relationship between the 2 and provide a solid foundation for future exploration of the mechanisms underlying their relationship.
关于铁状态标志物与胰岛素抵抗(IR)之间联系的证据有限。
我们旨在探讨美国成年人中铁状态与IR之间的关系。
本研究纳入了2003 - 2006年、2017 - 2020年国家健康与营养检查调查(NHANES)的2993名参与者。IR的特征是稳态模型评估(HOMA)-IR值≥2.5。采用加权线性和多变量逻辑回归分析来检验铁状态与IR之间的线性关系。此外,使用受限立方样条(RCS)来识别非线性剂量反应关联。还按年龄、性别、体重指数和身体活动进行了分层分析。最后,使用受试者工作特征(ROC)曲线来评估铁状态在IR中的预测价值。
在加权线性分析中,血清铁(SI)与HOMA-IR呈负相关(β -0.03,95%CI -0.05,-0.01,P = 0.01)。在加权多变量逻辑分析中,铁摄入量和血清转铁蛋白受体(sTfR)与IR呈正相关(OR 1.02,95%CI 1.00 - 1.04,P = 0.04;OR 1.07,95%CI 1.02 - 1.13,P = 0.01)。此外,在调整混杂因素后,SI和转铁蛋白饱和度(TSAT)与IR呈负相关(OR 0.96,95%CI 0.94 - 0.98,P < 0.0001;OR 0.98,95%CI 0.97 - 0.99,P < 0.001)。RCS描绘了sTfR、TSAT与IR之间的非线性剂量反应关系。这种相关性在各个人口子组中保持一致。ROC曲线显示,在IR预测的ROC分析中,TSAT的表现优于铁摄入量、SI和sTfR。
所有生物标志物均显示随着铁水平升高,IR风险显著降低,这将有助于更全面深入地理解两者之间的关系,并为未来探索其关系背后的机制提供坚实基础。