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重庆市居民超重与肥胖现状及影响因素分析
引用本文:杨小伶,刘先锋,刘达伟,张华东,向新志,赵舰. 重庆市居民超重与肥胖现状及影响因素分析[J]. 中国公共卫生, 2007, 23(7): 778-779
作者姓名:杨小伶  刘先锋  刘达伟  张华东  向新志  赵舰
作者单位:1. 重庆市疾病预防控制中心,400042
2. 重庆医科大学公共卫生学院
摘    要:
目的了解重庆市居民超重与肥胖现状及主要影响因素。方法运用分层整群随机抽样方法及面对面询问调查,获得18岁及以上居民个人基本情况,体检获取身高、体重数据。采用多因素Logistic回归分析方法筛选超重肥胖相关影响因素。结果共调查4 183人,重庆市18岁及以上居民超重、肥胖率分别为27.0%,8.2%,超重、肥胖率均城市高于农村,女性高于男性。多因素Logistic逐步回归分析显示,城乡、性别、年龄、家庭人均年收入和体力活动是超重和肥胖的相关影响因素。结论重庆市居民超重、肥胖率较高,必须采取平衡膳食、增加体力活动和开展健康教育等措施进行综合防治。

关 键 词:超重  肥胖  Logistic回归分析
文章编号:1001-0580(2007)07-0778-02
修稿时间:2006-10-14

Analysis on situation and relative risk factors of overweight and obesity in Chongqing
YANG Xiao-ling, LIU Xian-feng, LIU Da-wei,et al.. Analysis on situation and relative risk factors of overweight and obesity in Chongqing[J]. Chinese Journal of Public Health, 2007, 23(7): 778-779
Authors:YANG Xiao-ling   LIU Xian-feng   LIU Da-wei  et al.
Affiliation:Chongying Center for Disease Control and Prevention ( Chongqing 400042, China
Abstract:
Objective To learn the situation and main relative risk factors of overweight and obesity in Chongqing. Methods The population aged above 18 years old was sampled by randomized cluster sampling. Background information was collected by face - to - face interview. Data on weight and height was obtained through physical check - ups. The relative risk factors were screened by Logistic regression analysis. Results There were 4183 subjects were interviewed and physically measured. The prevalence rates of overweight and obesity were 27.0 % and 8.2 %. Both the rate of overweight and the rate of obesity in cities and females were all higher than that in rural areas and males. The results of Logistic regression analysis showed that major risk factors influencing overweight and obesity were residence, sex, age, household income and physical activity. Conclusion Many citizens in Chongqing were considered to be overweight and obesity, which became an important public health problem. Integrated measures must be taken for prevention and control.
Keywords:overweight    obesity   Logistic regression analysis
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