Article(id=1241035546626159317, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202408274, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1724083200000, receivedDateStr=2024-08-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815531641, onlineDateStr=2026-03-18, pubDate=1735056000000, pubDateStr=2024-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815531641, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815531641, creator=13701087609, updateTime=1773815531641, updator=13701087609, issue=Issue{id=1241035543589483182, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='24', pageStart='4417', pageEnd='4608', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815530917, creator=13701087609, updateTime=1773815686426, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241036195896029478, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241036195896029479, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4492, endPage=4498, ext={EN=ArticleExt(id=1241035547074949863, articleId=1241035546626159317, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Influencing factors of depressive symptoms in middle school students in Zhengzhou and construction of nomogram prediction model, columnId=null, journalTitle=Modern Preventive Medicine, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the associated factors affecting depressive symptoms in middle school students and to construct a risk prediction line graph model to assess the risk of developing depressive symptoms in middle school students.

Methods

A total of 1 088 middle school students were selected to participate in the monitoring and intervention project of common diseases and health influencing factors in Zhongmu County, Zhengzhou City, using the information collected from the questionnaires. A multivariate logistic regression analysis was employed to identify the factors that influenced the occurrence of depressive symptoms, and a column graph was established to predict the risk of depressive symptoms in middle school students.

Results

The prevalence of depressive symptoms among middle school students reached 28.50%. Female students (OR=2.051,95% CI:1.475-2.851), living in school (OR=1.496,95% CI:1.069-2.093), abnormal family (OR=1.615,95% CI:1.013-2.530), beaten and scolded by parents within one month (OR=3.516,95% CI:2.159-5.726), smoking (OR=2.044,95CI:1.298-3.219), serious injury within one year (OR=2.576,95CI:1.225-5.417), bullying(OR=3.276,95CI:1.113-9.643), internet addiction (OR=7.421,95CI:4.624-11.909) can increase the risk of depressive symptoms in middle school students. Average daily fruit intake in a week (<1time/day: OR=0.513,95% CI:0.306-0.863; ≥1time/day: OR=0.500,95% CI:0.290-0.863), reduce the risk of depressive symptoms in middle school students. The Nomogram model based on the above factors had good differentiation (AUC=0.752) and accuracy (Hosmer-Lemeshow test result χ2=3.657, P>0.05).

Conclusion

Middle school students who are girls, live in school, abnormal families, beaten by parents within one month, seriously hurt within one year, smoking, bullying and Internet addiction are more likely to have depressive symptoms. The column-chart can be used to predict the risk of depression symptoms in middle school students effectively, so as to take timely intervention measures for high-risk groups.

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目的

分析影响中学生抑郁症状的相关因素,构建风险预测列线图模型来评估中学生罹患抑郁症状的风险。

方法

选择中牟县参加学生常见病和健康影响因素监测与干预项目的中学生1088名,使用收集的问卷信息;采用多因素logistic回归分析抑郁症状的影响因素,建立列线图,预测中学生出现抑郁症状的风险。

结果

中学生抑郁症状检出率为28.50%。女生(OR=2.051,95% CI:1.475~2.851),住校(OR=1.496,95% CI:1.069~2.093),非常态家庭(OR=1.615,95% CI:1.013~2.530),被家长打骂(OR=3.516, 95% CI:2.159~5.726),吸烟(OR=2.044,95% CI:1.298~3.219),受到严重伤害(OR=2.576,95% CI:1.225~5.417),遭受校园欺凌(OR=3.276,95% CI:1.113~9.643),网络成瘾(OR=7.421, 95% CI:4.624~11.909)会增加中学生发生抑郁症状的风险。一周内平均水果摄入频率增加(<1次/天和≥1次/天OR值分别为0.513,95% CI:0.306~0.863;0.500,95% CI:0.290~0.863)会降低中学生发生抑郁症状的风险。基于以上因素建立的列线图模型具有较好的区分度(AUC=0.752)和准确度(Hosmer-Lemeshow,χ2=3.657,P>0.05)。

结论

女生、住校、非常态家庭、一月内被家长打骂、一年内受到严重伤害、吸烟、校园欺凌、网络成瘾的中学生出现抑郁症状风险增大,利用列线图能有效预测中学生出现抑郁症状的风险,从而对高危群体及时采取干预措施。

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王鲜,E-mail:
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张茜(1984—),女,硕士,副高,研究方向:学校卫生

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Journal of Affective Disorders, 2022, 299: 416-424., articleTitle=A bidirectional association between Internet addiction and depression: A large-sample longitudinal study among Chinese university students, refAbstract=null)], funds=[Fund(id=1241069989067813340, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, awardId=82003478, language=CN, fundingSource=国家自然科学基金青年科学基金项目(82003478), fundOrder=null, country=null), Fund(id=1241069989181059560, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, awardId=2022ZZUJG264, language=CN, fundingSource=郑州大学校级教学改革类项目(2022ZZUJG264), fundOrder=null, country=null), Fund(id=1241069989357220349, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, awardId=242102310031, language=CN, fundingSource=河南省科技攻关项目(242102310031), fundOrder=null, country=null), Fund(id=1241069989432717832, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, awardId=25A330009, language=CN, fundingSource=河南省高等学校重点科研项目(25A330009), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241069981052497956, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, xref=1., ext=[AuthorCompanyExt(id=1241069981060886565, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, companyId=1241069981052497956, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Centers for Disease Control and Prevention school, Zhengzhou, Henan 451450, China), AuthorCompanyExt(id=1241069981069275174, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, companyId=1241069981052497956, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.郑州市中牟县疾病预防控制中心学校卫生科,河南 郑州 451450)]), AuthorCompany(id=1241069981144772654, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, xref=2., ext=[AuthorCompanyExt(id=1241069981153161264, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, companyId=1241069981144772654, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.郑州大学公共卫生学院儿童少年卫生学教研室)])], figs=[ArticleFig(id=1241069986073080148, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=EN, label=Fig.1, caption=Line graph of predicted risk of depressive symptoms among middle school students, figureFileSmall=M0dgQ8lsEYSxfreQYYj9eg==, figureFileBig=h2LLXwMD7frTj4xnpFkcag==, tableContent=null), ArticleFig(id=1241069986211492196, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=CN, label=图1, caption=中学生抑郁症状风险预测列线图, figureFileSmall=M0dgQ8lsEYSxfreQYYj9eg==, figureFileBig=h2LLXwMD7frTj4xnpFkcag==, tableContent=null), ArticleFig(id=1241069986513482106, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=EN, label=Fig.2, caption=Line Chart Model Calibration Curves, figureFileSmall=QvTsza6aa1xLhyXLXa/ZTQ==, figureFileBig=AqXi4VJZ8Z0O829myPwZmA==, tableContent=null), ArticleFig(id=1241069986622534022, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=CN, label=图2, caption=列线图模型校准曲线图, figureFileSmall=QvTsza6aa1xLhyXLXa/ZTQ==, figureFileBig=AqXi4VJZ8Z0O829myPwZmA==, tableContent=null), ArticleFig(id=1241069986849026445, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=EN, label=Fig.3, caption=Column Line Chart Predictive Model ROC Curve, figureFileSmall=/8oVtoi1g5gv6RduRHu7zg==, figureFileBig=NqXGyBJBZ6tNyCCVjBk8UQ==, tableContent=null), ArticleFig(id=1241069986983244185, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=CN, label=图3, caption=列线图预测模型ROC曲线, figureFileSmall=/8oVtoi1g5gv6RduRHu7zg==, figureFileBig=NqXGyBJBZ6tNyCCVjBk8UQ==, tableContent=null), ArticleFig(id=1241069987075518881, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=EN, label=Table 1, caption=

Results of one-way analysis of depressive symptoms among middle school students[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
影响因素人数出现抑郁症状人数(%)χ2P
性别22.685<0.001
478101(21.1)
610209(34.3)
年级14.708<0.001
初中703173(24.6)
高中385137(35.6)
住校16.360<0.001
698170(24.4)
390140(35.9)
家庭类型4.4580.035
常态家庭965265(27.5)
非常态家庭12345(36.6)
一年内因病休学1.4360.231
1074304(28.3)
146(42.9)
一月内被家长打骂47.893<0.001
991253(25.5)
9757(58.8)
一年内受到严重伤害24.318<0.001
1044283(27.1)
4427(61.4)
一周内含糖饮料摄入(次/天)1.5940.451
从来不喝22156(25.3)
<1755219(29.0)
≥111235(31.3)
一周内油炸食物摄入(次/天)3.6520.161
从来不吃19151(26.7)
<1805225(28.0)
≥19234(37.0)
一周内水果摄入(次/天)12.4800.002
从来不吃8738(43.7)
<1580167(28.8)
≥1421105(24.9)
一周内蔬菜摄入(次/天)12.3810.002
从来不吃4818(37.5)
<124689(36.2)
≥1794203(25.6)
早餐摄入16.293<0.001
从来不吃218(38.1)
有时吃294109(37.1)
天天吃773193(25.0)
一周内体育课数(节)12.5060.002
≤134292(26.9)
2485162(33.4)
≥326156(21.5)
中高强度运动天数(天/周)2.4580.293
≤1547163(29.8)
222367(30.0)
≥331880(25.2)
吸烟15.413<0.001
958254(26.5)
13056(43.1)
饮酒20.655<0.001
806200(24.8)
282110(39.0)
校园欺凌21.564<0.001
1066294(27.6)
2216(72.7)
网络成瘾127.811<0.001
972225(23.1)
11685(73.3)
肥胖0.3370.562
896252(28.1)
19258(30.2)
), ArticleFig(id=1241069987188765099, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=CN, label=表1, caption=

中学生抑郁症状单因素分析结果[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
影响因素人数出现抑郁症状人数(%)χ2P
性别22.685<0.001
478101(21.1)
610209(34.3)
年级14.708<0.001
初中703173(24.6)
高中385137(35.6)
住校16.360<0.001
698170(24.4)
390140(35.9)
家庭类型4.4580.035
常态家庭965265(27.5)
非常态家庭12345(36.6)
一年内因病休学1.4360.231
1074304(28.3)
146(42.9)
一月内被家长打骂47.893<0.001
991253(25.5)
9757(58.8)
一年内受到严重伤害24.318<0.001
1044283(27.1)
4427(61.4)
一周内含糖饮料摄入(次/天)1.5940.451
从来不喝22156(25.3)
<1755219(29.0)
≥111235(31.3)
一周内油炸食物摄入(次/天)3.6520.161
从来不吃19151(26.7)
<1805225(28.0)
≥19234(37.0)
一周内水果摄入(次/天)12.4800.002
从来不吃8738(43.7)
<1580167(28.8)
≥1421105(24.9)
一周内蔬菜摄入(次/天)12.3810.002
从来不吃4818(37.5)
<124689(36.2)
≥1794203(25.6)
早餐摄入16.293<0.001
从来不吃218(38.1)
有时吃294109(37.1)
天天吃773193(25.0)
一周内体育课数(节)12.5060.002
≤134292(26.9)
2485162(33.4)
≥326156(21.5)
中高强度运动天数(天/周)2.4580.293
≤1547163(29.8)
222367(30.0)
≥331880(25.2)
吸烟15.413<0.001
958254(26.5)
13056(43.1)
饮酒20.655<0.001
806200(24.8)
282110(39.0)
校园欺凌21.564<0.001
1066294(27.6)
2216(72.7)
网络成瘾127.811<0.001
972225(23.1)
11685(73.3)
肥胖0.3370.562
896252(28.1)
19258(30.2)
), ArticleFig(id=1241069987327177146, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=EN, label=Table 2, caption=

Results of multi-factorial regression analysis of depressive symptoms in middle school students

, figureFileSmall=null, figureFileBig=null, tableContent=
影响因素β标准误Wald χ2POR值(95% CI
性别(ref:男)
0.7180.16818.275<0.0012.051(1.475~2.851)
住校(ref:否)
0.4030.1715.5190.0191.496(1.069~2.093)
家庭类型(ref:常态家庭)
非常态家庭0.4800.2294.3880.0361.615(1.013~2.530)
一周内水果摄入(ref:从来不吃)
<1次/天-0.6670.2656.3440.0120.513(0.306~0.863)
≥1次/天-0.6930.2796.1840.0130.500(0.290~0.863)
早餐摄入(ref:从来不吃)
有时吃0.0170.5220.0010.9731.018(0.366~2.829)
天天吃-0.7250.5141.9870.1590.484(0.177~1.327)
一月内被家长打骂(ref:否)
1.2570.24925.539<0.0013.516(2.159~5.726)
吸烟(ref:否)
0.7150.2329.5240.0022.044(1.298~3.219)
一年内受到严重伤害(ref:否)
0.9460.3796.2290.0132.576(1.225~5.417)
校园欺凌(ref:否)
1.1870.5514.6430.0313.276(1.113~9.643)
网络成瘾(ref:否)
2.0040.24168.960<0.0017.421(4.624~11.909)
), ArticleFig(id=1241069987444617669, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546626159317, language=CN, label=表2, caption=

中学生抑郁症状的多因素回归分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
影响因素β标准误Wald χ2POR值(95% CI
性别(ref:男)
0.7180.16818.275<0.0012.051(1.475~2.851)
住校(ref:否)
0.4030.1715.5190.0191.496(1.069~2.093)
家庭类型(ref:常态家庭)
非常态家庭0.4800.2294.3880.0361.615(1.013~2.530)
一周内水果摄入(ref:从来不吃)
<1次/天-0.6670.2656.3440.0120.513(0.306~0.863)
≥1次/天-0.6930.2796.1840.0130.500(0.290~0.863)
早餐摄入(ref:从来不吃)
有时吃0.0170.5220.0010.9731.018(0.366~2.829)
天天吃-0.7250.5141.9870.1590.484(0.177~1.327)
一月内被家长打骂(ref:否)
1.2570.24925.539<0.0013.516(2.159~5.726)
吸烟(ref:否)
0.7150.2329.5240.0022.044(1.298~3.219)
一年内受到严重伤害(ref:否)
0.9460.3796.2290.0132.576(1.225~5.417)
校园欺凌(ref:否)
1.1870.5514.6430.0313.276(1.113~9.643)
网络成瘾(ref:否)
2.0040.24168.960<0.0017.421(4.624~11.909)
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郑州市中学生抑郁症状影响因素分析及列线图预测模型构建
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张茜 1 , 赖娇龙 2 , 胡佳佳 2 , 张俊娜 2 , 周帆轲 2 , 娄晓民 2 , 王鲜 2
现代预防医学 | 儿少卫生与妇幼保健 2024,51(24): 4492-4498
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现代预防医学 | 儿少卫生与妇幼保健 2024, 51(24): 4492-4498
郑州市中学生抑郁症状影响因素分析及列线图预测模型构建
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张茜1, 赖娇龙2, 胡佳佳2, 张俊娜2, 周帆轲2, 娄晓民2, 王鲜2
作者信息
  • 1.郑州市中牟县疾病预防控制中心学校卫生科,河南 郑州 451450
  • 2.郑州大学公共卫生学院儿童少年卫生学教研室
  • 张茜(1984—),女,硕士,副高,研究方向:学校卫生

通讯作者:

王鲜,E-mail:
Influencing factors of depressive symptoms in middle school students in Zhengzhou and construction of nomogram prediction model
Qian ZHANG1, Jiao-long LAI2, Jia-jia HU2, Jun-na ZHANG2, Fan-ke ZHOU2, Xiao-min LOU2, Xian WANG2
Affiliations
  • Centers for Disease Control and Prevention school, Zhengzhou, Henan 451450, China
出版时间: 2024-12-25 doi: 10.20043/j.cnki.MPM.202408274
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目的

分析影响中学生抑郁症状的相关因素,构建风险预测列线图模型来评估中学生罹患抑郁症状的风险。

方法

选择中牟县参加学生常见病和健康影响因素监测与干预项目的中学生1088名,使用收集的问卷信息;采用多因素logistic回归分析抑郁症状的影响因素,建立列线图,预测中学生出现抑郁症状的风险。

结果

中学生抑郁症状检出率为28.50%。女生(OR=2.051,95% CI:1.475~2.851),住校(OR=1.496,95% CI:1.069~2.093),非常态家庭(OR=1.615,95% CI:1.013~2.530),被家长打骂(OR=3.516, 95% CI:2.159~5.726),吸烟(OR=2.044,95% CI:1.298~3.219),受到严重伤害(OR=2.576,95% CI:1.225~5.417),遭受校园欺凌(OR=3.276,95% CI:1.113~9.643),网络成瘾(OR=7.421, 95% CI:4.624~11.909)会增加中学生发生抑郁症状的风险。一周内平均水果摄入频率增加(<1次/天和≥1次/天OR值分别为0.513,95% CI:0.306~0.863;0.500,95% CI:0.290~0.863)会降低中学生发生抑郁症状的风险。基于以上因素建立的列线图模型具有较好的区分度(AUC=0.752)和准确度(Hosmer-Lemeshow,χ2=3.657,P>0.05)。

结论

女生、住校、非常态家庭、一月内被家长打骂、一年内受到严重伤害、吸烟、校园欺凌、网络成瘾的中学生出现抑郁症状风险增大,利用列线图能有效预测中学生出现抑郁症状的风险,从而对高危群体及时采取干预措施。

中学生  /  抑郁症状  /  列线图  /  影响因素
Objective

To analyze the associated factors affecting depressive symptoms in middle school students and to construct a risk prediction line graph model to assess the risk of developing depressive symptoms in middle school students.

Methods

A total of 1 088 middle school students were selected to participate in the monitoring and intervention project of common diseases and health influencing factors in Zhongmu County, Zhengzhou City, using the information collected from the questionnaires. A multivariate logistic regression analysis was employed to identify the factors that influenced the occurrence of depressive symptoms, and a column graph was established to predict the risk of depressive symptoms in middle school students.

Results

The prevalence of depressive symptoms among middle school students reached 28.50%. Female students (OR=2.051,95% CI:1.475-2.851), living in school (OR=1.496,95% CI:1.069-2.093), abnormal family (OR=1.615,95% CI:1.013-2.530), beaten and scolded by parents within one month (OR=3.516,95% CI:2.159-5.726), smoking (OR=2.044,95CI:1.298-3.219), serious injury within one year (OR=2.576,95CI:1.225-5.417), bullying(OR=3.276,95CI:1.113-9.643), internet addiction (OR=7.421,95CI:4.624-11.909) can increase the risk of depressive symptoms in middle school students. Average daily fruit intake in a week (<1time/day: OR=0.513,95% CI:0.306-0.863; ≥1time/day: OR=0.500,95% CI:0.290-0.863), reduce the risk of depressive symptoms in middle school students. The Nomogram model based on the above factors had good differentiation (AUC=0.752) and accuracy (Hosmer-Lemeshow test result χ2=3.657, P>0.05).

Conclusion

Middle school students who are girls, live in school, abnormal families, beaten by parents within one month, seriously hurt within one year, smoking, bullying and Internet addiction are more likely to have depressive symptoms. The column-chart can be used to predict the risk of depression symptoms in middle school students effectively, so as to take timely intervention measures for high-risk groups.

Middle school students  /  Depressive symptoms  /  Nomogram  /  Influencing factor
张茜, 赖娇龙, 胡佳佳, 张俊娜, 周帆轲, 娄晓民, 王鲜. 郑州市中学生抑郁症状影响因素分析及列线图预测模型构建. 现代预防医学, 2024 , 51 (24) : 4492 -4498 . DOI: 10.20043/j.cnki.MPM.202408274
Qian ZHANG, Jiao-long LAI, Jia-jia HU, Jun-na ZHANG, Fan-ke ZHOU, Xiao-min LOU, Xian WANG. Influencing factors of depressive symptoms in middle school students in Zhengzhou and construction of nomogram prediction model[J]. Modern Preventive Medicine, 2024 , 51 (24) : 4492 -4498 . DOI: 10.20043/j.cnki.MPM.202408274
抑郁症(Depression)是一种严重精神疾患,以情感或情绪障碍为特征,临床上主要表现为情绪低落、兴趣缺失、反应迟钝、注意力不集中、反复出现自杀念头等[1]。近年来青少年抑郁症状的患病率呈明显上升趋势,据世界卫生组织预测,至2030年,重度抑郁症预计将跃居为全球疾病负担的首要原因[2]。抑郁症状是一种心境负性情绪状态,尚未达到临床上抑郁症的诊断标准[3],但它是抑郁症的亚临床阶段,具有抑郁症状的青少年往往要面临一系列严峻的生活挑战,如发展为抑郁症、学习成绩下降等[4]。有关数据显示,2019年河南省开封市中学生抑郁症状检出率为14.51%[5];2020年郑州市青少年抑郁症状检出率为26.11%[6]。中学生出现抑郁症状不仅影响正常的学习生活,严重的还会导致其发生自伤或自杀行为[7]
抑郁症状的发生与性别、年级、日常饮食习惯、运动情况、家庭社会环境有着密切的联系[8]。青春期是个体由儿童转变为成人的关键发育阶段,在此期间,个体在成长过程中经历的躯体变化以及自我意识的觉醒和对社会更深层次的理解,均对个体的心理健康发展构成显著挑战。因此,本研究旨在探索郑州市中学生抑郁症状发生的相关因素,据此构建并验证列线图预警模型,从而实现郑州市中学生抑郁症状发生的辅助预警,为制订促进儿童青少年心理健康发展规划提供科学依据。
选择参加郑州市中牟县2022年学生常见病和健康影响因素监测与干预工作的3所中学(包括2所初中、1所高中)的学生作为研究对象。每个年级随机抽取2个及以上班级,以班为单位开展调查。研究共纳入1088人。本研究由郑州大学生命科学伦理审查委员会审查通过(编号:ZZUIRB2021-100),并已取得所有调查对象的知情同意。
使用《2022年全国学生常见病和健康影响因素监测与干预项目工作方案》编制的学生健康状况及影响因素调查表。调查表经历多轮专家评审和实地调研的检验,有效性和可靠性得到了充分的验证。
包含性别、年级、饮食情况、运动相关行为及伤害相关行为等信息。
根据体质量指数(BMI)的计算公式,即BMI=体重(kg)/[身高(m)]2,计算出BMI值。参照《学龄儿童青少年超重与肥胖筛查》(WS/T586—2018)[9],基于中学生的年龄和性别,对其是否肥胖进行判定。
主要分为常态家庭和非常态家庭两大类,常态家庭分为核心家庭和大家庭,非常态家庭分为单亲家庭、重组家庭和隔代家庭。
指会让人出现气喘吁吁或心跳加快的运动,例如跑步、足球、跳健身操等[11]
指需要到医院治疗,不能上学或影响日常活动一天及以上的伤害行为[11]
指吸过烟,喝过酒;即使只吸过一两口烟,喝过一整杯酒[11]
根据第5版《精神障碍与统计手册》(DSE-5)[12]提出的定义网络游戏成瘾的9个症状,在改编形成的9个测试问题中,存在≥4种者定义为存在网络成瘾行为[13]
询问学生在过去30天里,在校园或校园周边是否受到过欺侮,选项为“从未、有时、经常”,其中任意一项及以上内容选择“经常”即判定为曾遭受校园欺凌[14]
采用流调用中心抑郁量表(CES-D)[15],询问被测学生最近一周内各种症状出现的频率。评分系统采用四级制,具体为:“没有或偶尔”记作0分,“有时”记作1分,“时常”记作2分,“持续”记作3分。通过对每道题目获得的得分相加,得到抑郁总得分,将CES-D评分≥16分定义为可能存在抑郁症状[16]。量表的Cronbach α系数为0.88,具有较好的内部一致性和可靠性。
利用SPSS 21.0软件对数据进行χ2检验,将筛选得到的具有统计学意义的变量纳入多因素logistic回归分析(α剔除=0.05),分析前对相关变量进行赋值:性别(0-男;1-女);住校(0-否;1-是);家庭类型(0-常态家庭;1-非常态家庭);一周内水果摄入(0-从来不吃;1-<1次/天;2-≥1次/天);早餐摄入(0-从来不吃;1-有时吃;2-天天吃);一月内被家长打骂(0-否;1-是);吸烟(0-否;1-是);一年内受到严重伤害(0-否;1-是);校园欺凌(0-否;1-是);网络成瘾(0-否;1-是)。基于多因素分析结果,在R Studio软件(R版本:4.4.1)通过Nomogram函数对抑郁症状的风险进行预测并绘制列线图,采用Bootstrap法进行1 000次重复抽样,完成内部验证,绘制Calibration校准曲线用来评价模型的一致性。绘制ROC曲线,计算曲线下面积(AUC)评价模型的判别能力。通过Hosmer-Lemeshow检验结果,评价模型的拟合优度,P>0.05表明模型的拟合优度较好。
本次研究共调查中学生1 088人,其中男生478人(43.9%),初中生703人(64.6%),住校390人(35.8%),常态家庭965人(88.7%),一月内被家长打骂97人(8.9%),一周内水果摄入频率≥1次/天421人(38.7%),一周内蔬菜摄入频率≥1次/天794人(73.0%),每天吃早餐773人(71.0%),一周内体育课≥3节261人(24.0%)。吸烟130人(11.9%),饮酒282人(25.9%),遭受校园欺凌22人(2.0%),网络成瘾116人(10.7%),一年内受到过严重伤害44人(4.0%)。
调查对象中,检出抑郁症状310人,检出率为28.50%。女生的抑郁症状检出率(34.3%)明显高于男生(21.1%);高中生检出率(35.6%)高于初中生(24.6%)。住校、一年内存在因病休学、一月内存在被家长打骂、一年内受到严重伤害、非常态化家庭学生抑郁症状检出率分别为35.9%,42.9%,58.8%,61.4%,36.6%,均要高于不住校学生(24.4%),不存在因病休学情况的学生(28.3%),未被家长打骂的学生(25.5%),未受到严重伤害(27.1%)及常态化家庭学生(27.5%)。中学生抑郁症状检出率随着水果、蔬菜、早餐摄入频率增加而减少。吸烟、饮酒学生抑郁症状检出率43.1%,39.0%,要高于不吸烟、不饮酒学生。遭受校园欺凌的学生的抑郁症状检出率72.7%,显著高于未遭受校园欺凌的学生;网络成瘾学生的抑郁症状检出率73.3%,高于不存在网络成瘾学生。见表1
以抑郁症状作为因变量,单因素分析筛选出的有统计学意义的因素作为自变量,进行logistic回归分析。结果显示,女生、住校、非常态家庭、一月内被家长打骂、吸烟、一年内受到严重伤害、存在校园欺凌及存在网络成瘾会增加中学生抑郁症状发生风险;一周内平均每天水果摄入量增加会降低中学生抑郁症状发生风险。见表2
将经多因素分析筛选出来具有统计学意义的因素纳入预测模型绘制列线图。根据风险因素在列线图上的“单项得分”进行累加,可以计算出总分。总分与列线图底部的“抑郁症状发生风险”相对应,总分越高,意味着出现抑郁症状的风险也相应地增加,图1
使用Bootstrap法对列线图进行内部验证,绘制得到校准曲线。本次研究的校准曲线结果与对角线较为吻合,提示符合度高,如图2
本研究AUC=0.752(95% CI:0.719~0.785),AUC>0.5,说明本次研究模型具有一定的预测价值,如图3
将数据分成若干组比较每组内观测事件的平均预测概率和实际事件发生率来评估模型的拟合质量。本次研究的H-L检验结果为χ2=3.657,P=0.818>0.05,表明所构建模型拟合优度良好。
本研究结果显示,在所选调查地区中,中学生抑郁症状检出率为28.50%,与2022年一项对近20年全国各省中学生抑郁症状调查的meta分析结果28.40%[17]相接近,高于2019年大连市(24.12%)中学生检出率[18],低于2020年青岛市中学生检出率58.21%[19],这种差异可能由不同地域文化背景差异、调查时间不同及样本差异造成。
多因素分析结果显示,女生抑郁症状风险要高于男生,这一发现与既往研究结果相吻合[18]。可能是女性在青春期更容易受到外界伤害和社交媒体影响,更易出现心理健康问题。除此之外,青春期因素(如性类固醇激素的增加)与女生抑郁症状发病率增加也有关[20]。住校学生由于缺乏家庭父母支持,以及寄宿制学校硬件条件和日常管理方面的不完善,忽视学生的心理发展[6],抑郁症状风险要高于非住校学生。就家庭情况而言,非常态家庭与中学生抑郁症状呈正相关,可能是家庭结构的变化、家庭照顾缺失等影响到正常的亲子关系,导致孩子在家中缺乏安全感,加剧了孩子的心理健康问题[21]
校园欺凌,不仅会带来身体上的伤害,还可能引发精神方面的疾病。联合国教科文组织在2018年的报告指出,全球范围内约有三分之一的青少年曾经历过校园欺凌事件[22]。遭受校园欺凌的学生长期生活在自我压抑和否定当中,易产生各种消极人格和消极情绪,出现人际交往和学习困难等问题,进而增加抑郁的可能性[5]
过去一年内曾遭受过严重伤害的中学生更容易出现抑郁症状,身体健康下降,易出现沮丧、焦虑、脆弱等负性情绪,影响心理健康[23]。吸烟、网络成瘾均会增加抑郁症状发生风险。接触尼古丁会干扰神经系统,对认知功能产生负面影响[24],出现情绪恶化。研究表明,抑郁症状和网络过度使用具有双向作用[25],中学生在面对学习的重大压力时,会产生一系列的负性情绪,从而主动在网络上寻求放松,但长时间沉溺于网上交流,进一步加重了现实交流障碍,陷入恶性循环。而平均每天水果摄入增多,能有效减少抑郁症状发生的风险。可能是水果中含有丰富的维生素和各类矿物质,这些都在情绪调节中起关键作用[20]
本研究基于多因素logistic回归,将影响中学生抑郁症状的独立因素如性别、住校、吸烟等作为预测因子纳入抑郁症状列线图预测模型,将抑郁影响因素以分值形式直观地评估患抑郁症状的风险,实现个体层面的预测[18]。为教育工作者和学生家长及时识别高风险学生并采取干预措施提供科学依据。但研究采用横断面研究,无法准确验证抑郁症状与相关因素的因果关系;且调查对象仅为县城部分中学生,结论代表性有待提高;相关信息通过自我问卷收集,可能存在偏倚。因此,在以后的研究中,可以通过进一步拓宽研究的地理范畴,采纳前瞻性队列研究的方法,增强研究结果的代表性和准确性。
  • 国家自然科学基金青年科学基金项目(82003478)
  • 郑州大学校级教学改革类项目(2022ZZUJG264)
  • 河南省科技攻关项目(242102310031)
  • 河南省高等学校重点科研项目(25A330009)
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2024年第51卷第24期
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doi: 10.20043/j.cnki.MPM.202408274
  • 接收时间:2024-08-20
  • 首发时间:2026-03-18
  • 出版时间:2024-12-25
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  • 收稿日期:2024-08-20
基金
国家自然科学基金青年科学基金项目(82003478)
郑州大学校级教学改革类项目(2022ZZUJG264)
河南省科技攻关项目(242102310031)
河南省高等学校重点科研项目(25A330009)
作者信息
    1.郑州市中牟县疾病预防控制中心学校卫生科,河南 郑州 451450
    2.郑州大学公共卫生学院儿童少年卫生学教研室

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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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