摘要
目的了解新冠感染疫情流行期间长沙市中学生抑郁症状流行状况及其主要危险因素。方法采用横断面调查方法,对分层整群随机抽取的6307名中学生进行问卷调查。结果流调中心用抑郁量表(The Center for Epidemiological Studies Depression Scale,CES-D)平均得分为(11.19±8.88)分。存在抑郁症状人数为978人,检出率为15.15%(95%CI:14.61%~16.40%)。多因素logistic回归模型分析显示,女生、职业高中、住校、单亲/重组家庭、每天睡眠时间不足、静坐时间过长、缺乏运动、不规律早餐行为、遭受家庭暴力、遭受校园欺凌、尝试吸烟、饮酒、其他物质成瘾、网络成瘾行为等因素均是中学生抑郁危险因素(P值均<0.05)。结论中学生抑郁症状与学校、家庭环境、生活方式、伤害相关行为以及成瘾行为相关,应采取相应措施加强对抑郁症状学生的心理干预。
Objective To study the prevalence of depressive symptoms and its main risk factors among middle school students in Changsha City during the SARS-Cov-2 epidemic.Methods A cross-sectional questionnaire survey was conducted among 6,307 middle school students selected by stratified cluster random sampling.Results The mean score of the Center for Epidemiological Studies Depression Scale(CES-D)was(11.19±8.88).The number of students with depressive symptoms was 978,with the detection rate being 15.51%(95%CI:14.61-16.40).Multivariate logistic regression model analysis showed that female students,vocational high school,residential schools,single-parent or reorganized families,insufficient sleep time per day,sitting for long periods of time every day,lack of physical exercise,irregular breakfast behavior,suffering from domestic violence,suffering from school bullying,attempt at smoking,alcohol consumption,other substance addiction and Internet addiction behavior were all risk factors for depression in the middle school students(all P<0.05).Conclusion The middle school students’depressive symptoms are correlated with schools,family environment,lifestyle,injury-related behaviors and addictive behavior;and hence,corresponding measures should be taken to enhance psychological interventions for students with depressive symptoms.
作者
奉琪
陈艳
吴鑫
FENG Qi;CHEN Yan;WU Xin(Changsha Municipal Center for Disease Control and Prevention(Changsha Public Health Testing and Inspection Center),Changsha,Hunan 410001,China)
出处
《实用预防医学》
CAS
2023年第8期949-954,共6页
Practical Preventive Medicine
关键词
抑郁
中学生
心理健康
因素分析
depression
middle school student
mental health
factor analysis