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江门市居民亚健康状况及其影响因素分析 被引量:12

Sub-health and its influencing factors among residents of Jiangmen city
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摘要 目的了解广东省江门市居民亚健康状况及其影响因素,为采取有效的保健措施及制定健康促进策略提供参考依据。方法采用随机抽样方法抽取2010年10月—2011年5月在江门市疾病预防控制中心体检中心进行健康体检的5 896名体检者进行问卷调查。结果调查的5 896名体检者中,检出亚健康者2 136人,占36.23%;其中生理亚健康846人,占亚健康者总数的39.61%,心理亚健康623人,占亚健康者总数的29.17%,社会亚健康667人,占亚健康者总数的31.22%;多因素Logistic回归分析结果表明,女性、经常患病、工作时间>12 h/d、饮酒、经常饮食不正常、不注意和完全不理会饮食结构和营养是居民亚健康状况的危险因素;年龄30~49岁、除工人外的其他职业、文化程度高中/中专以上、混合型性格、工作时间5~6 h/d、心理状态和社会适应能力较好是江门市居民亚健康状况的保护因素。结论江门市亚健康人群比例较高,性别、年龄、职业、文化程度、患病情况、性格类型、工作时间、饮酒、饮食情况、饮食类型、心理状态和社会适应能力是居民亚健康状况发生的影响因素。 Objective To explore the prevalence and influencing factors of sub-health among residents of Jiangmen city for making effective health promotion strategy.Methods Physical examination and questionnaire survey were conducted among health physical examinees randomly selected at Physical Examination Center of Jiangmen Municipal Center for Disease Control and Preveation from October 2010 to May 2011.Results A total of 2 136 persons(36.23%) were sub-health(846[39.61%] with physiological sub-health,623[29.17%] with mental sub-health,and 667[31.22%] with social sub-health).Logistic regression analyses showed that female,frequent illness,working time longer than 12 hours per day,alcohol consumption,irregular diet structure,and unreasonable diet were risk factors of sub-health and at age of 30-49 years,occupation other than worker,education level higher than junior middle school,personality of mixed type,working time of 5-6 hours per day,good psychological status,and social adaptability were protective factor of sub-health in the residents of Jiangmen city.Conclusion A higher prevalence of sub-health is detected in the population of Jiangmen city.Disease prevalence,physical activity,working hours,diet,type of diet,smoking,alcohol consumption,psychological state,and social adaptability are influencing factors of sub-health in the residents.
出处 《中国公共卫生》 CAS CSCD 北大核心 2012年第6期844-847,共4页 Chinese Journal of Public Health
关键词 亚健康 影响因素 LOGISTIC回归分析 sub-health influencing factor logistic regression
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