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基于决策树模型和Logistic回归模型的2型糖尿病发生的影响因素分析

孟继娴 刘蕾 吴薇 王嘉钰 甄紫伊 傅一婷 马小慧 孙金菊

广西医学2024,Vol.46Issue(11):1656-1661,6.
广西医学2024,Vol.46Issue(11):1656-1661,6.DOI:10.11675/j.issn.0253-4304.2024.11.04

基于决策树模型和Logistic回归模型的2型糖尿病发生的影响因素分析

Influencing factors for the occurrence of type 2 diabetes mellitus based on decision tree and Logistic regression models:an analytic study

孟继娴 1刘蕾 2吴薇 3王嘉钰 2甄紫伊 1傅一婷 1马小慧 1孙金菊1

作者信息

  • 1. 沈阳医学院公共卫生学院,辽宁省沈阳市 110034
  • 2. 辽宁中医药大学护理学院,辽宁省沈阳市 116600
  • 3. 沈阳医学院全科医学院,辽宁省沈阳市 110034
  • 折叠

摘要

Abstract

Objective To explore the influencing factors for the occurrence of type 2 diabetes mellitus(T2DM)based on decision tree and Logistic regression models,so as to provide scientific basis for early screening of high-risk population.Methods A total of 3235 individuals with routine check-up were selected as the research subjects.The prediction model was established by employing the chi-square automatic interaction detector of decision tree and Logistic regression in SPSS 26.0 software.Area under the curve(AUC)of receiver operating characteristic,sensitivity,specificity,and Youden index were compared between the two models.Results A total of 186 patients suffered from T2DM.The results of decision tree model analysis revealed that age,body mass index,triglyceride,systolic blood pressure,concomitant hypertension,and gender were the influencing factors for the occurrence of T2DM.The results of Logistic regression model analysis indicated that gender,age,body mass index,systolic blood pressure,and triglyceride level were the influencing factors for the occurrence of T2DM.The results obtained by the two models were basically the same.AUC of decision tree model for predicting the occurrence risk of T2DM was 0.832,which was larger than that of Logistic regression model(0.800,P<0.05),and the prediction performance of the two models was favorable.The specificity(0.688)and Youden index(0.537)of decision tree model were higher than those of Logistic regression model(0.626,0.481),and the sensitivity(0.855)of Logistic regression model was higher than that of decision tree model(0.849).Conclusion The models of decision tree and Logistic regression established in this study can favorably predict the occurrence risk of T2DM.In practice,it is recommended to combine the two models to maximize the advantages of the two models and provide reference basis for the further prevention and treatment of T2DM.

关键词

2型糖尿病/影响因素/Logistic回归模型/决策树模型/预测效能

Key words

Type 2 diabetes mellitus/Influencing factors/Logistic regression model/Decision tree model/Prediction efficiency

分类

医药卫生

引用本文复制引用

孟继娴,刘蕾,吴薇,王嘉钰,甄紫伊,傅一婷,马小慧,孙金菊..基于决策树模型和Logistic回归模型的2型糖尿病发生的影响因素分析[J].广西医学,2024,46(11):1656-1661,6.

基金项目

沈阳医学院硕士研究生科技创新基金项目(Y20220515) (Y20220515)

广西医学

OACSTPCD

0253-4304

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