| Exhaustive CHAID分类树与logistic回归在脑卒中危险因素中的应用 |
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| 引用本文： | 张芬,余金明,王家宏,毛勇,张李军,李社昌,战义强,胡大一.Exhaustive CHAID分类树与logistic回归在脑卒中危险因素中的应用[J].中国预防医学杂志,2011(7):573-576. |
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| 作者姓名： | 张芬 余金明 王家宏 毛勇 张李军 李社昌 战义强 胡大一 |
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| 作者单位： | 复旦大学公共卫生学院临床流行病学研究中心公共卫生安全教育部重点实验室;北京大学人民医院心内科;昆明医学院公共卫生学院流行病与卫生统计学系; |
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| 基金项目： | 北京市科委科技攻关项目社区居民胆固醇教育和控制(D0906002040191) |
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| 摘 要： | 目的应用exhaustive CHAID分类树模型与logistic回归分析来分析北京社区居民脑卒中危险因素以及不同特征人群的重点干预因素,为加强北京市居民脑卒中的干预提供科学依据。方法于2007年6月至8月,采用整群抽样方法,对北京10 108名社区居民进行问卷调查、体格检查及检测空腹血糖、血脂。采用logistic回归与exhaustive CHAID分类树分析相结合来探讨影响北京市居民脑卒中的因素。结果 logistic回归分析和exhaustive CHAID分类树分析显示年龄、性别、踝臂指数(ABI)、高血压、腹型肥胖、高密度脂蛋白胆固醇、吸烟状况、工作强度为脑卒中的危险因素;Exhaustive CHAID分类树分析揭示老年者ABI贡献大,不容忽视中年者糖尿病。Logistic回归分析和exhaustive CHAID分类树分析的ROC曲线下面积分别为0.803和0.778,模型可靠。结论对脑卒中的防治,要在总体把握的情况下,对不同的高危人群应采取不同的防制措施。
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| 关 键 词： | 脑卒中 Logistic 分类树 危险因素 预防 |
Exhaustive CHAID decision tree and logistic regression analyses of risk factors for stroke |
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| ZHANG Fen,YU Jin-ming,WANG Jia-hong,MAO Yong,ZHANG Li-jun,LI She-chang,ZHAN Yi-qiang,HU Da-yi.Clinical Research Institute , Key Laboratory of Public Health Safety,Ministry of Education,School of Public Health,Fudan University,Shanghai ,China.Exhaustive CHAID decision tree and logistic regression analyses of risk factors for stroke[J].China Preventive Medicine,2011(7):573-576. |
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| Authors: | ZHANG Fen YU Jin-ming WANG Jia-hong MAO Yong ZHANG Li-jun LI She-chang ZHAN Yi-qiang HU Da-yiClinical Research Institute Key Laboratory of Public Health Safety Ministry of Education School of Public Health Fudan University Shanghai China |
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| Institution: | ZHANG Fen,YU Jin-ming,WANG Jia-hong,MAO Yong,ZHANG Li-jun,LI She-chang,ZHAN Yi-qiang,HU Da-yi.Clinical Research Institute and Key Laboratory of Public Health Safety,Ministry of Education,School of Public Health,Fudan University,Shanghai 200032,China |
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| Abstract: | Objective To analyze risk factors for stroke by logistic regression model and exhaustive CHAID decision tree methods.Methods A total of 10 108 community residents were recruited for study by a cluster sampling method.Data were collected by questionnaire,physical examination and blood testing for fasting plasma lipids and glucose concentrations.The risk factors were determined by logistic regression model and exhaustive CHAID decision tree methods.Results Stroke was significantly associated with age,sex,abdo... |
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| Keywords: | Stroke Logistic regression Decision tree Risk factors Prevention |
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