中国中老年人胰岛素抵抗代谢评分与新发脑卒中相关性研究

摘要
图/表
参考文献
相关文章 (2)

全文: PDF (1905 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要 目的：探讨中老年人胰岛素抵抗代谢评分（METS-IR）与新发脑卒中之间的关系。方法：数据来源于2011年至2018年的中国健康与养老追踪调查（CHARLS）的数据。建立回归模型探究METS-IR与新发脑卒中之间的关联,同时采用限制立方样条模型来检查可能的非线性关联,并且采用亚组分析探究可能的潜在的调节变量。结果：研究共纳入6706名研究对象,其中新发脑卒中381人,回归模型结果发现METS-IR每上升一个四分位数,新发生脑卒中的患病风险增加67.3%（OR=1.673,95%CI：1.440~1.944）。使用限制性三次样条回归分析显示METS-IR与新发脑卒中患病率之间存在线性的相关关系,分层分析结果发现METS-IR与新发脑卒中的关系在不同亚组中一致。结论：METS-IR与新发脑卒中患病率密切相关,高METS-IR的人群需要更加警惕发生脑卒中的风险。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	沙鸥
	于洋

关键词 ：胰岛素抵抗代谢评分, 脑卒中, 相关性研究, 中国健康与养老追踪调查

Abstract：Objective Stroke is a major cause of cardiovascular mortality and may have a correlative relationship with insulin resistance. To investigate the relationship between the metabolic score for insulin resistance (METS-IR) and new-onset stroke in middle-aged and elderly people based on a large cohort study. Methods Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) in 2011 and 2018. Regression models were developed to explore the association between METS-IR and new-onset stroke, while restricted cubic spline models were used to examine possible nonlinear associations and subgroup analyses were used to explore possible potential moderating variables. Results A total of 6706 study subjects were included in the study, including 381 with new-onset stroke. The regression model results found a 67.3% increase in the risk of new-onset stroke for each quartile increase in the METS-IR (OR=1.673, 95% CI: 1.440-1.944). A linear relationship between the METS-IR and the prevalence of new-onset stroke was shown using restricted three-sample regression analysis, and stratified analysis revealed that the relationship between METS-IR and new-onset stroke was consistent across subgroups. Conclusion The METS-IR is strongly associated with the prevalence of new-onset stroke, and people with high METS-IR need to be more alert to the risk of stroke.

Key words： METS-IR stroke association study CHARLS

收稿日期: 2023-07-30

中图分类号:

R743.3

基金资助:辽宁省教育厅2020年度科学研究经费资助项目（FWZR2020004）

通讯作者: 于洋,E-mail：yuyang@cmu1h.com

引用本文:

沙鸥, 于洋. 中国中老年人胰岛素抵抗代谢评分与新发脑卒中相关性研究[J]. 金宝搏官方188学报(医学版), 2023, 20(5): 70-74. SHA Ou, YU Yang. Association study between Metabolic Insulin Resistance Score and New-Onset Stroke in middle-aged and elderly Chinese population. HuNan ShiFan DaXue XueBao(YiXueBan), 2023, 20(5): 70-74.

链接本文:

http://yxb.hunnu.edu.cn/CN/ 或 http://yxb.hunnu.edu.cn/CN/Y2023/V20/I5/70

[1] Global, regional,national burden of stroke, 1990-2016: a systematic analysis for the Global Burden of DiseaseStudy 2016[J]. Lancet Neurol, 2019, 18(5): 439-458.
[2] Ma Q, Li R, Wang L, et al.Temporal trend and attributable risk factors of stroke burden in China, 1990-2019: an analysis for the Global Burden of Disease Study 2019[J]. Lancet Public Health, 2021, 6(12): e897-e906.
[3] 于洗河, 高尚, 贾欢欢, 等.1999年、2009年、2019年我国与全球脑卒中疾病负担研究[J]. 中国卫生经济, 2021, 40(6): 58-61.
[4] Ghasemi R, Haeri A, Dargahi L, et al.Insulin in the brain: sources, localization and functions[J]. Mol Neurobiol, 2013, 47(1): 145-171.
[5] Rehni AK, Cho S, Dave KR.Ischemic brain injury in diabetes and endoplasmic reticulum stress[J]. Neurochem Int, 2022, 152: 105219.
[6] Lee JE, Shin DW, Yun JM, et al.Insulin Resistance Is a Risk Factor for Silent Lacunar Infarction[J]. Stroke, 2016, 47(12): 2938-2944.
[7] Arvanitakis Z, Capuano AW, Wang HY, et al.Brain insulin signaling and cerebrovascular disease in human postmortem brain[J]. Acta Neuropathol Commun, 2021, 9(1): 71.
[8] Bello-Chavolla OY, Almeda-Valdes P, Gomez-Velasco D, et al.METS-IR, a novel score to evaluate insulin sensitivity, is predictive of visceral adiposity and incident type 2 diabetes[J]. Eur J Endocrinol, 2018, 178(5): 533-544.
[9] Zhou X, Kang C, Hu Y, et al.Study on insulin resistance and ischemic cerebrovascular disease: A bibliometric analysis via CiteSpace[J]. Front Public Health, 2023, 11: 1021378.
[10] 陈韵, 陈坤, 王桂斌, 等. 急性缺血性脑卒中患者卒中后抑郁发病率与危险因素分析[J]. 金宝搏官方188学报 (医学版), 2021, 18(2): 20-23.
[11] Radaelli T, Farrell KA, Huston-Presley L, et al.Estimates of insulin sensitivity using glucose and C-Peptide from the hyperglycemia and adverse pregnancy outcome glucose tolerance test[J]. Diabetes Care, 2010, 33(3): 490-494.
[12] Hong S, Han K, Park CY.The insulin resistance by triglyceride glucose index and risk for dementia: population-based study[J]. Alzheimers Res Ther, 2021, 13(1): 9.
[13] Zhang X, Yu C, Ye R, et al.Correlation between non-insulin-based insulin resistance indexes and the risk of prehypertension: A cross-sectional study[J]. J Clin Hypertens (Greenwich), 2022, 24(5): 573-581.
[14] Bello-Chavolla OY, Antonio-Villa NE, Vargas-Vázquez A, et al.Prediction of incident hypertension and arterial stiffness using the non-insulin-based metabolic score for insulin resistance (METS-IR) index[J]. J Clin Hypertens (Greenwich), 2019, 21(8): 1063-1070.
[15] Yang W, Cai X, Hu J, et al.The Metabolic Score for Insulin Resistance (METS-IR) Predicts Cardiovascular Disease and Its Subtypes in Patients with Hypertension and Obstructive Sleep Apnea[J]. Clin Epidemiol, 2023, 15: 177-189.
[16] Cai X, Hu J, Zhu Q, et al.Relationship of the metabolic score for insulin resistance and the risk of stroke in patients with hypertension: A cohort study[J]. Front Endocrinol (Lausanne), 2022, 13: 1049211.
[17] Frosch OH, Yau PL, Osorio RS, et al.Insulin resistance among obese middle-aged is associated with decreased cerebrovascular reactivity[J]. Neurology, 2017, 89(3): 249-255.
[18] Oikonomou EK, Antoniades C.The role of adipose tissue in cardiovascular health and disease[J]. Nat Rev Cardiol, 2019, 16(2): 83-99.
[19] Scherer T, Sakamoto K, Buettner C.Brain insulin signalling in metabolic homeostasis and disease[J]. Nat Rev Endocrinol, 2021, 17(8): 468-483.
[20] Georgakis MK, Harshfield EL, Malik R, et al.Diabetes Mellitus, Glycemic Traits, and Cerebrovascular Disease: A Mendelian Randomization Study[J]. Neurology, 2021, 96(13): e1732-e1742.
[21] Bornfeldt KE, Tabas I.Insulin resistance, hyperglycemia, and atherosclerosis[J]. Cell Metab, 2011, 14(5): 575-585.
[22] Hierons SJ, Marsh JS, Wu D, et al.The Interplay between Non-Esterified Fatty Acids and Plasma Zinc and Its Influence on Thrombotic Risk in Obesity and Type 2 Diabetes[J]. Int J Mol Sci, 2021, 22(18): 10140.
[23] Xu S, Ilyas I, Little PJ, et al.Endothelial Dysfunction in Atherosclerotic Cardiovascular Diseases and Beyond: From Mechanism to Pharmacotherapies[J]. Pharmacol Rev, 2021, 73(3): 924-967.
[24] Athyros VG, Doumas M, Imprialos KP, et al.Diabetes and lipid metabolism[J]. Hormones (Athens), 2018, 17(1): 61-67.
[25] Heeren J, Scheja L.Metabolic-associated fatty liver disease and lipoprotein metabolism[J]. Mol Metab, 2021, 50: 101238.
[26] Jin A, Wang S, Li J, et al.Mediation of Systemic Inflammation on Insulin Resistance and Prognosis of Nondiabetic Patients With Ischemic Stroke[J]. Stroke, 2023, 54(3): 759-769.
[27] Ding PF, Zhang HS, Wang J, et al.Insulin resistance in ischemic stroke: Mechanisms and therapeutic approaches[J]. Front Endocrinol (Lausanne), 2022, 13: 1092431.