基于智能健康监测系统的社区居民健康状况及影响因素分析
摘要：
目的 旨在调查社区居民健康状况,分析影响健康的相关因素。 方法 2019年4月—5月,采用描述性横断面研究,便利获取来自全国不同地区4 311例居民为研究对象,通过智能健康监测系统获取研究对象的健康数据,包括一般特征、健康行为及健康状况、广泛性焦虑障碍量表和抑郁症筛查量表测评结果。 结果 研究对象年龄为（29.25±11.88）岁,慢性病患病率为13.8%。存在焦虑者有1 480例（34.3%）,存在抑郁症状者有1 620例（37.6%）。吸烟率、饮酒率分别为12.2%、32.3%。年龄、文化程度、已婚、饮食规律性、上午加餐情况、以肉食为主、饮食偏咸、其他特殊饮食、饮酒频率、是否剧烈运动、焦虑程度、抑郁程度是慢性病患病情况的影响因素。结论 社区居民健康状况良好,普遍存在焦虑、抑郁,需重视心理健康。老年、已婚、进餐不规律、以肉食为主、饮食偏咸、其他特殊饮食、经常饮酒、无剧烈运动、抑郁和焦虑的社区居民易患慢性病,建议参考慢性病影响因素制订社区居民健康促进措施。
关键词: 智能健康监测系统, 社区居民, 社区保健护理, 健康状况, 影响因素分析
Abstract:
Objective To investigate the health status of community residents and to analyze related influencing factors. Methods A descriptive cross-sectional study was conducted to obtain data of 4 311 community residents in China from April to May,2019. Intelligent health monitoring system,including their general characteristics,health behavior,health status,results of generalized anxiety disorder scale-7（GAD-7） and patient health questionnair-9（PHQ-9）,was used as the suvery tool. Descriptive statistics,chi square test and logistic regression were used for data analysis. Results The average age of the participants was（29.25±11.88） years old,and the prevalence of chronic diseases was 13.8%. There were 1 480（34.3%） patients with anxiety and 1 620（37.6%） with depression. The smoking rate and drinking rate were 12.2% and 32.3% respectively. Age,education level,being married,meal regularity,additional meal in the morning,eating dinner,meat-based diet,salty diet,other special diet,drinking alcohol,taking vigorous exercise,anxiety and depression were the influencing factors of chronic diseases. Conclusion The health condition of community residents was generally good,while the symptoms of anxiety and depression were common,which implies that much attention should be paid on the emotional health. The risk factors of chronic diseases were old age,being married,irregular meal,meat-based diet,salty diet,other special diet,drinking alcohol,no vigorious exercise,depression and anxiety. These findings can provide suggestions for the community to develop interventions to promote residents’ health.
Key words: Intelligent Health Monitoring System, Community Residents, Community Health Nursing, Health Status, Root Cause Analysis
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