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| Factors affecting microvascular complications among patients with type 2 diabetes mellitus |
| WU Yaxing1, LIU Hong1, FENG Jian2, YANG Guimao3, CHENG Xuebing3, XU Qian3, SUN Xiaodong3, REN Yanfeng1
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1. School of Public Health, Weifang Medical University, Weifang, Shandong 261053, China;
2. Weifang People's Hospital Health Management Center, Weifang, Shandong 261044, China;
3. Affiliated Hospital of Weifang Medical College, Weifang, Shandong 261031, China |
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Abstract Objective To identify the factors affecting microvascular complications among patients with type 2 diabetes (T2DM), so as to provide insights into the management of microvascular complications of T2DM. Methods T2DM patients hospitalized in the Department of Endocrinology of a tertiary hospital in Weifang City, Shandong Province from January 2021 to January 2022 were enrolled, and subjects' basic information, lifestyle and medical history were collected using questionnaire surveys. Fasting insulin, fasting blood glucose and glycated hemoglobin were measured, and factors affecting microvascular complications were identified among T2DM patients using a multivariable logistic regression model and a decision tree model. Results Totally 1 003 T2DM inpatients were enrolled, including 515 men (51.35%) and 488 women (48.65%), and the prevalence of microvascular complications was 40.18%. Multivariable logistic regression analysis showed that age of 60 years and older (OR=2.510, 95%CI: 1.441-4.374), T2DM duration of 10 years and longer (OR=3.205, 95%CI: 2.242-4.581), fasting insulin of lower than 3.21 μIU/mL (OR=1.749, 95%CI: 1.239-2.469), using of agents or insulin to control blood glucose (OR=1.880, 95%CI: 1.143-3.092), glycated hemoglobin level of 7% and higher (OR=1.751, 95%CI: 1.172-2.615) as factors affecting microvascular complications among T2DM patients. Decision tree analysis identified course of T2DM as a major factor affecting the risk of microvascular complications among T2DM patients, and the prevalence of microvascular complications was 70.22% among T2DM patients with disease course of 10 years and longer and fasting insulin of lower than 3.21 μIU/mL or 16.32 μIU/mL and higher, 44.23% among T2DM patients with disease course of 5 to 10 years and at ages of 60 years and older, and 43.10% among T2DM patients with disease course of less than 5 years and fasting insulin of lower than 3.21 μIU/mL. Conclusion Advanced age, long course of T2DM, low fasting insulin and high glycated hemoglobin may increase the risk of microvascular complications among T2DM patients.
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Received: 26 June 2023
Revised: 21 October 2023
Published: 22 November 2023
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[1] 石杰,高艳均,王倩.2型糖尿病患者糖尿病肾病患病率及其危险因素分析[J]. 华南预防医学,2021,47(2):228-231.
[2] 万文萃,龙洋. 糖尿病视网膜病变的流行病学、病因学与发病机制研究现状[J]. 眼科新进展,2022,42(9):673-679.
[3] 中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2020年版)[J]. 中华糖尿病杂志,2021,13(4):13-107.
[4] 刘兵,李苹,朱玫烨,等. 决策树模型与logistic回归模型在胃癌高危人群干预效果影响因素分析中的应用[J]. 中国卫生统计,2018,35(1):70-73.
[5] 陈文鑫,晋聪,王婷,等. 基于决策树模型与logistic回归模型的HBV宫内传播影响因素分析[J]. 中华流行病学杂志,2022,43(1):85-91.
[6] 吴梦怡,胡劲松,黄霜,等.湖南省30岁及以上社区居民高血压、糖尿病、高血脂共病的影响因素分析[J]. 预防医学,2021,33(2):157-161.
[7] 关云琦,梁明斌,潘劲,等. 浙江省成年人睡眠时间与高血压的关联研究[J]. 预防医学,2022,34(7):681-686.
[8] 诸骏仁,高润霖,赵水平,等.中国成人血脂异常防治指南(2016年修订版)[J]. 中国循环杂志,2016,31(10):937-953.
[9] 阙霜,曾雁冰,方亚. 基于logistic回归与决策树模型的社会资本对老年人自评健康的影响研究[J]. 中国卫生统计,2022,39(2):186-191.
[10] 潘恩春,缪丹丹,张芹,等. 2型糖尿病人群肾功能异常影响因素分析[J]. 中华疾病控制杂志,2017,21(9):913-916,920.
[11] 胡利,李东豪,陈慧. 糖尿病患者血糖控制相关因素与糖尿病视网膜病变发生的关系[J]. 中华眼底病杂志,2011,27(3):210-213.
[12] HUANG L,WU P,ZHANG Y,et al.Relationship between onset age of type 2 diabetes mellitus and vascular complications based on propensity score matching analysis[J]. J Diabetes Investig,2022,13(6):1062-1072.
[13] HOSSEINI S S M,ESTEGHAMATI A,HEMMATABADI M,et al. Predicting diabetic nephropathy in type 2 diabetic patients using machine learning algorithms[J]. J Diabetes Metab Disord,2022,21(2):1433-1441.
[14] 郭雅丽,周泽宸,田峰,等.年龄分层下不同血糖控制水平与糖尿病视网膜病变的关联[J]. 中国慢性病预防与控制,2020,28(3):161-164,170.
[15] 任艳艳. 2018—2021年郑州市2型糖尿病微血管并发症的流行病学特点及危险因素分析[J]. 现代疾病预防控制,2023,34(5):392-395,402.
[16] 崔竞文,姚丽君,席巍. 海安地区人群2型糖尿病肾脏病变流行特征分析[J]. 实用预防医学,2023,30(10):1247-1250.
[17] 柏旭,苏洁,李凤,等.我国成人糖尿病视网膜病变影响因素的Meta分析[J]. 预防医学,2023,35(7):595-601.
[18] 杨洪燕,夏淼,刘赞朝,等.2型糖尿病视网膜病变临床预测模型的构建与评价[J]. 中国慢性病预防与控制,2023,31(1):2-7.
[19] YAPRAK B,KESKIN L.Evaluation of microvascular complications in patients with new diagnosis type 2 diabetes[J]. Eur Rev Med Pharmacol Sci,2023,27(4):1601-1608.
[20] 姜佳佳,李峰,房冬冬,等.2型糖尿病患者非增殖型糖尿病性视网膜病变的影响因素分析[J]. 预防医学,2023,35(1):17-20.
[21] 邬闻文,谭晓东,孙东晗,等. Logistic回归分析模型和决策树分析在高血压糖尿病共患病预警指标中的应用[J]. 中华疾病控制杂志,2022,26(7):827-833,844. |
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