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Article(id=1241036332290601340, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241036327177744706, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202502184, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1739376000000, receivedDateStr=2025-02-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815718958, onlineDateStr=2026-03-18, pubDate=1757433600000, pubDateStr=2025-09-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815718958, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815718958, creator=13701087609, updateTime=1773815718958, updator=13701087609, issue=Issue{id=1241036327177744706, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='17', pageStart='3073', pageEnd='3264', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815717738, creator=13701087609, updateTime=1773840080282, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241138511152206262, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241036327177744706, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241138511152206263, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241036327177744706, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3149, endPage=3153, ext={EN=ArticleExt(id=1241036332777140620, articleId=1241036332290601340, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Network analysis of adolescent biological rhythm disorders and symptoms of depression and anxiety, columnId=1228016568949474136, journalTitle=Modern Preventive Medicine, columnName=Child and Adolescent Health, Maternal and Child Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the relationships between different dimensions of biological rhythm disorders, depression and anxiety symptoms among adolescents, and to identify the key dimensions that have a greater impact on mental health, providing a basis for developing targeted interventions.

Methods

Conducted from September to November 2023 in Tianjin, this study recruited middle school students from urban and suburban areas using convenience and stratified cluster sampling methods, yielding 3 787 valid questionnaires. The Self-rating Questionnaire of Biological Rhythm Disorders for Adolescents (SQBRDA), the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) were employed to assess biological rhythm disorders, depression, and anxiety symptoms, respectively. Network analysis was utilized to examine the association strengths between dimensions and to calculate centrality indices to pinpoint key nodes.

Results

Activity rhythms showed higher centrality in the network (0.436), the edge weight between decreased interest and low mood was the largest in the depression symptom subnetwork (0.319), and the edge weight between persistent worry and excessive worry was the largest in the anxiety symptom subnetwork (0.446). In the biological rhythm subnetwork, the edge weight between activity rhythms and electronic product use rhythms was the largest (0.566). Females had stronger associations in the depression symptom network and the biological rhythm disorder network (0.194).

Conclusion

The study demonstrates a complex correlation network between adolescent biological rhythm disorders, depression and anxiety symptoms, especially activity rhythm and electronic product use rhythm.

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目的

探讨青少年生物节律紊乱各维度与抑郁、焦虑症状之间的关系，并识别对心理健康影响较大的关键节律维度，为制定针对性干预措施提供科学依据。

方法

本研究于2023年9—11月在天津市选取城区和郊区的中学生，采用方便抽样和分层随机整群抽样方法，共回收有效问卷3 787份。使用青少年生物节律紊乱评定问卷（SQBRDA）、患者健康问卷（PHQ-9）和广泛性焦虑障碍问卷（GAD-7）分别评估生物节律紊乱、抑郁症状和焦虑症状。采用网络分析方法分析各维度之间的关联强度，并计算中心性指标以识别关键节点。

结果

活动节律在总体网络中表现出较高的中心性（0.436），抑郁症状子网络中兴趣减退和情绪低落边线权值最大（0.319），焦虑症状子网络中持续担忧与担忧过多边线权重最大（0.446），生物节律子网络中活动节律和电子产品使用节律的边线权值最大（0.566）。女生在抑郁症状和生物节律紊乱的网络中表现出更强的关联性（0.194）。

结论

青少年生物节律紊乱与抑郁、焦虑症状存在复杂关联网络，特别是活动节律和电子产品使用节律。

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张献伟，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=DDCn2z9doFPaxNE0EOzx4g==, magXml=uI83gRuMkh5NEIHZqJQ5Jg==, pdfUrl=null, pdf=G+N01XKsKDm/ydqfhFRKsg==, pdfFileSize=976264, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=KPr//4AeQTnv+oBh6B9dNw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=1wBelEkVn4VGWDgxDAA/4w==, mapNumber=null, authorCompany=null, fund=null, authors=

张献伟（1992—），男，硕士，主管医师，研究方向：儿童青少年健康

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张献伟（1992—），男，硕士，主管医师，研究方向：儿童青少年健康

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注：节点间的连线表示各节点之间的相关系数，连线越粗代表系数越大；实线是正相关，虚线是负相关。

, figureFileSmall=ty8sH6Jpf05NIpUVdGjLag==, figureFileBig=VsKbx3UFTer3z8apkl/+Zg==, tableContent=null), ArticleFig(id=1241139378894991707, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241036332290601340, language=EN, label=Figure 2, caption=Standard estimates of the centrality of dimensions of network structures, figureFileSmall=hvIup25mayduuj4hcE/c9g==, figureFileBig=QDbWFvtT4oGEPqmCbclP+A==, tableContent=null), ArticleFig(id=1241139379012432228, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241036332290601340, language=CN, label=图2, caption=网络结构各维度中心性的标准估计, figureFileSmall=hvIup25mayduuj4hcE/c9g==, figureFileBig=QDbWFvtT4oGEPqmCbclP+A==, tableContent=null), ArticleFig(id=1241139379125678446, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241036332290601340, language=EN, label=Table 1, caption=

The score of each dimension of the scale ()

, figureFileSmall=null, figureFileBig=null, tableContent=
量表条目编码分量表/条目总样本（n=3 787）男（n=1 853）女（n=1 934）Z值P值
抑郁症状（PHQ-9）PHQ1兴趣减退1.40±0.811.37±0.791.42±0.82-2.400.050
PHQ2情绪低落1.37±0.761.33±0.731.40±0.79-2.910.005
PHQ3睡眠问题1.29±0.731.26±0.681.32±0.77-2.190.013
PHQ4容易疲倦1.42±0.811.37±0.771.46±0.85-3.63<0.001
PHQ5食欲改变1.31±0.731.28±0.701.34±0.76-2.650.015
PHQ6自信降低1.37±0.801.33±0.761.41±0.83-3.110.004
PHQ7专注困难1.28±0.711.26±0.681.30±0.74-1.420.093
PHQ8行动缓慢1.23±0.641.21±0.611.24±0.67-1.600.091
PHQ9意念杀伤1.24±0.691.21±0.631.28±0.73-3.500.001
焦虑症状（GAD-7）GAD1紧张焦虑1.35±0.771.31±0.731.39±0.80-3.550.002
GAD2持续担忧1.32±0.751.29±0.731.35±0.78-3.160.013
GAD3担忧过多1.33±0.761.31±0.741.36±0.78-2.950.036
GAD4难以放松1.31±0.741.30±0.731.32±0.75-1.470.302
GAD5难以静坐1.23±0.671.22±0.651.25±0.68-1.660.203
GAD6烦恼急躁1.28±0.721.25±0.681.31±0.75-3.310.005
GAD7担惊受怕1.26±0.691.23±0.671.28±0.71-3.120.027
生物节律紊乱（SQBRDA）BR1睡眠节律16.15±5.6715.17±5.7917.08±5.39-10.54<0.001
BR2饮食节律13.10±4.9312.75±5.1413.43±4.70-5.74<0.001
BR3活动节律16.90±7.2515.92±7.0417.84±7.33-8.49<0.001
BR4电子产品使用节律15.35±7.1015.07±7.1415.62±7.06-2.880.018
), ArticleFig(id=1241139379226341748, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241036332290601340, language=CN, label=表1, caption=

量表各维度的得分情况（）

, figureFileSmall=null, figureFileBig=null, tableContent=
量表条目编码分量表/条目总样本（n=3 787）男（n=1 853）女（n=1 934）Z值P值
抑郁症状（PHQ-9）PHQ1兴趣减退1.40±0.811.37±0.791.42±0.82-2.400.050
PHQ2情绪低落1.37±0.761.33±0.731.40±0.79-2.910.005
PHQ3睡眠问题1.29±0.731.26±0.681.32±0.77-2.190.013
PHQ4容易疲倦1.42±0.811.37±0.771.46±0.85-3.63<0.001
PHQ5食欲改变1.31±0.731.28±0.701.34±0.76-2.650.015
PHQ6自信降低1.37±0.801.33±0.761.41±0.83-3.110.004
PHQ7专注困难1.28±0.711.26±0.681.30±0.74-1.420.093
PHQ8行动缓慢1.23±0.641.21±0.611.24±0.67-1.600.091
PHQ9意念杀伤1.24±0.691.21±0.631.28±0.73-3.500.001
焦虑症状（GAD-7）GAD1紧张焦虑1.35±0.771.31±0.731.39±0.80-3.550.002
GAD2持续担忧1.32±0.751.29±0.731.35±0.78-3.160.013
GAD3担忧过多1.33±0.761.31±0.741.36±0.78-2.950.036
GAD4难以放松1.31±0.741.30±0.731.32±0.75-1.470.302
GAD5难以静坐1.23±0.671.22±0.651.25±0.68-1.660.203
GAD6烦恼急躁1.28±0.721.25±0.681.31±0.75-3.310.005
GAD7担惊受怕1.26±0.691.23±0.671.28±0.71-3.120.027
生物节律紊乱（SQBRDA）BR1睡眠节律16.15±5.6715.17±5.7917.08±5.39-10.54<0.001
BR2饮食节律13.10±4.9312.75±5.1413.43±4.70-5.74<0.001
BR3活动节律16.90±7.2515.92±7.0417.84±7.33-8.49<0.001
BR4电子产品使用节律15.35±7.1015.07±7.1415.62±7.06-2.880.018
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青少年生物节律紊乱与抑郁、焦虑症状的网络分析
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张献伟 1 , 王晓阳 2 , 李凤芹 3 , 赵赛赛 1 , 孙志颖 1 , 徐渴 1 , 刘忠慧 1
现代预防医学 | 儿少卫生与妇幼保健 2025,52(17): 3149-3153
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现代预防医学 | 儿少卫生与妇幼保健 2025, 52(17): 3149-3153
青少年生物节律紊乱与抑郁、焦虑症状的网络分析
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张献伟1 , 王晓阳2, 李凤芹3, 赵赛赛1, 孙志颖1, 徐渴1, 刘忠慧1
作者信息
  • 1.天津市疾病预防控制中心环境健康与公共卫生所，天津 300011
  • 2.天津市津南区疾病预防控制中心
  • 3.天津市和平区疾病预防控制中心

    • 张献伟（1992—），男，硕士，主管医师，研究方向：儿童青少年健康

通讯作者:

张献伟，E-mail:
Network analysis of adolescent biological rhythm disorders and symptoms of depression and anxiety
Xian-wei ZHANG1 , Xiao-yang WANG2, Feng-qin LI3, Sai-sai ZHAO1, Zhi-ying SUN1, Ke XU1, Zhong-hui LIU1
Affiliations
  • Institute of Environmental and Public Health, Tianjin Center of Disease Control and Prevention, Tianjin 300011, China
出版时间: 2025-09-10 doi: 10.20043/j.cnki.MPM.202502184
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摘要
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目的

探讨青少年生物节律紊乱各维度与抑郁、焦虑症状之间的关系，并识别对心理健康影响较大的关键节律维度，为制定针对性干预措施提供科学依据。

方法

本研究于2023年9—11月在天津市选取城区和郊区的中学生，采用方便抽样和分层随机整群抽样方法，共回收有效问卷3 787份。使用青少年生物节律紊乱评定问卷（SQBRDA）、患者健康问卷（PHQ-9）和广泛性焦虑障碍问卷（GAD-7）分别评估生物节律紊乱、抑郁症状和焦虑症状。采用网络分析方法分析各维度之间的关联强度，并计算中心性指标以识别关键节点。

结果

活动节律在总体网络中表现出较高的中心性（0.436），抑郁症状子网络中兴趣减退和情绪低落边线权值最大（0.319），焦虑症状子网络中持续担忧与担忧过多边线权重最大（0.446），生物节律子网络中活动节律和电子产品使用节律的边线权值最大（0.566）。女生在抑郁症状和生物节律紊乱的网络中表现出更强的关联性（0.194）。

结论

青少年生物节律紊乱与抑郁、焦虑症状存在复杂关联网络，特别是活动节律和电子产品使用节律。

青少年  /  生物节律  /  抑郁  /  焦虑  /  网络分析
Objective

To investigate the relationships between different dimensions of biological rhythm disorders, depression and anxiety symptoms among adolescents, and to identify the key dimensions that have a greater impact on mental health, providing a basis for developing targeted interventions.

Methods

Conducted from September to November 2023 in Tianjin, this study recruited middle school students from urban and suburban areas using convenience and stratified cluster sampling methods, yielding 3 787 valid questionnaires. The Self-rating Questionnaire of Biological Rhythm Disorders for Adolescents (SQBRDA), the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) were employed to assess biological rhythm disorders, depression, and anxiety symptoms, respectively. Network analysis was utilized to examine the association strengths between dimensions and to calculate centrality indices to pinpoint key nodes.

Results

Activity rhythms showed higher centrality in the network (0.436), the edge weight between decreased interest and low mood was the largest in the depression symptom subnetwork (0.319), and the edge weight between persistent worry and excessive worry was the largest in the anxiety symptom subnetwork (0.446). In the biological rhythm subnetwork, the edge weight between activity rhythms and electronic product use rhythms was the largest (0.566). Females had stronger associations in the depression symptom network and the biological rhythm disorder network (0.194).

Conclusion

The study demonstrates a complex correlation network between adolescent biological rhythm disorders, depression and anxiety symptoms, especially activity rhythm and electronic product use rhythm.

Adolescent  /  Biological rhythm  /  Depression  /  Anxiety  /  Network analysis
张献伟, 王晓阳, 李凤芹, 赵赛赛, 孙志颖, 徐渴, 刘忠慧. 青少年生物节律紊乱与抑郁、焦虑症状的网络分析. 现代预防医学, 2025 , 52 (17) : 3149 -3153 . DOI: 10.20043/j.cnki.MPM.202502184
Xian-wei ZHANG, Xiao-yang WANG, Feng-qin LI, Sai-sai ZHAO, Zhi-ying SUN, Ke XU, Zhong-hui LIU. Network analysis of adolescent biological rhythm disorders and symptoms of depression and anxiety[J]. Modern Preventive Medicine, 2025 , 52 (17) : 3149 -3153 . DOI: 10.20043/j.cnki.MPM.202502184
正文
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青少年期是生理心理发展的关键阶段，生物节律稳定性对其至关重要[1]。多维度生物节律紊乱（睡眠、饮食、活动及电子产品使用节律）与抑郁、焦虑症状的关联已被广泛证实[2-4]，且随社会发展日益普遍。然而，现有研究多聚焦单一维度（如睡眠）与心理健康的关系[5]，缺乏对多维度节律相互作用及其综合影响的系统探讨。
网络分析方法可量化变量间直接关联，识别核心节点与路径[6-7]。本研究运用该方法，旨在揭示多维度生物节律紊乱与抑郁/焦虑症状的网络关联特征，识别最具影响力的节律维度，为针对性干预提供依据[8-9]。
1　对象与方法
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1.1　对象
在2023年9—11月，本研究依据方便抽样的原则，在天津市城区与郊区分别选取了2所初中、2所高中以及1所职业高中。在抽样过程中，各学校均采用分层随机整群抽样的方法，以年级作为分层依据。对于初中和高中，每个年级通过产生随机数字法抽取5～7个班级，并且以年级为单位，确保每个年级抽取的学生数量不少于100名；职业高中方面，每个年级抽取的学生人数则不少于200人。共发放问卷3 927份，回收有效问卷3 787份，问卷有效率为96.4%。其中男生1 853名，女生1 934名；初中1 327名，高中2 460名；学生的年龄范围在12～18岁之间。本研究已经获得天津市疾病预防控制中心医学科研伦理委员会的批准（编号：TJCDC-R-2024-009），在开展调查之前，学生及其家长均已签署了知情同意书。
1.2　方法
1.2.1　青少年生物节律紊乱评定问卷[10]（Self -rating Questionnaire of Biological Rhythm Disorders for Adolescents, SQBRDA）
该问卷评估生物节律紊乱的四个维度，包括睡眠、饮食、活动、电子产品使用，共29个条目。采用李克特5级评分（1～5分），总分范围29～145分，维度得分与总分越高表明紊乱越严重。问卷具有良好信度，Cronbachα=0.94，是适用于我国青少年的有效工具[11]。
1.2.2　抑郁症状状况评估
采用9项患者健康问卷[12]（The Patient Health Questionnaire-9, PHQ-9）进行评估，该问卷被广泛用于青少年抑郁症状评估[13]，其内容涵盖了兴趣减退、情感低落、睡眠问题、容易疲劳、食欲改变、自信降低、专注困难、行动缓慢和意念杀伤等9个方面，采用0～3分四级评分（0=无，3=几乎每天）。本研究中量表的Cronbach α = 0.86。
1.2.3　焦虑症状状况评估
采用广泛焦虑障碍量表[14]（Generalized Anxiety Disorder-7, GAD-7），该量表是适用青少年广泛性焦虑障碍评估的常用工具[15]，共包含7个问题，主要评估受访者在过去两周内焦虑症状的频率和严重程度。量表涉及紧张焦虑、持续担忧、担忧过多、难以放松、难以静坐、烦恼急躁、担惊受怕等焦虑症状。每个条目采用4级评分，分别为：0分（没有或很少时间）、1分（几天）、2分（超过一半的时间）、3分（几乎每天）。本研究中量表的Cronbach α= 0.91。
1.3　质量控制
正式调查前，进行了预调查以优化问卷表述。所有调查员经过统一培训。采用双人录入数据并进行核查与清洗。
1.4　统计学分析
本研究采用SPSS 24.0软件进行描述性统计分析，以（均值±标准差）形式呈现数据。因部分变量不服从正态分布，采用Mann-Whitney U检验比较男、女两组在各条目得分差异，以Z值和P值衡量差异显著性，显著性水平设为P<0.05。网络分析使用R 4.4.0版本中的qgraph和bootnet包完成，检验水准α=0.05；基于扩展贝叶斯信息准则（参数λ=0.5）估计正则化偏相关网络。节点代表生物节律、抑郁及焦虑症状维度，连线表示节点间的偏相关系数。计算三个中心性指标以识别关键节点：强度中心性（strength），即节点所有边权绝对值的总和；接近中心性（closeness），即某一节点到其他所有节点的最短路径长度之和的倒数；中介中心性（betweenness），即某一节点在其他任意两个节点的最短路径中出现的频率。对于这些指标，其值越高，表明该节点的中心性越强，在网络中所起的作用也越关键。通过bootstrap抽样1 000次计算边权95%置信区间，并采用相关性稳定性系数（correlation stability coefficient,CS）评估中心性指标的稳定性（CS>0.25表示稳定性可接受）[16]。
2　结果
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2.1　描述性分析
本研究共纳入3 787名参与者，男1 853人，女1 934人。量表得分结果显示，被调查学生在抑郁症状、焦虑症状及生物节律紊乱方面均存在轻度表现。抑郁症状各条目平均得分在1.23～1.42分之间，其中兴趣减退和容易疲倦得分相对较高，分别为（1.40±0.81）和（1.42±0.81）分；焦虑症状各条目平均得分在1.23～1.35分之间，其中紧张焦虑、持续担忧、担忧过多得分相对较高，分别为（1.35±0.77）、（1.32±0.75）和（1.33±0.76）分；生物节律紊乱各维度得分差异较明显，活动节律紊乱程度最突出，为（16.90±7.25）分，其次是睡眠节律的（16.15±5.67）分和电子产品使用节律的（15.35±7.10）分，饮食节律紊乱相对较轻，为（13.10±4.93）分。性别比较分析显示，女生在大多数指标上的得分高于男生（P<0.05或P<0.01）。见表1。
2.2　总体网络估计
正则化网络结构包含20个节点，共190条边线，其中121条边的权值非零（平均权值0.080），见图1。各组内部联系强，同一组中的症状倾向于聚集在一起，其中活动节律与电子产品使用节律、兴趣减退和情绪低落、持续担忧与担忧过多分别在三个子网络中的多边线权重最大，分别为0.566、0.319、0.446，在跨越2个子网络间，行动缓慢和难以静坐、容易疲劳和睡眠节律紊乱、烦恼急躁和饮食节律紊乱的联系最强，分别为0.141、0.131、0.049。见图1A。
2.3　分性别网络估计
男生组：容易疲劳和食欲减退、持续担忧和担忧过多、活动节律和电子产品使用节律分别在三个子网络中的多边线权重最大，分别为0.346、0.388、0.573；跨越两个子网络间，行动缓慢和难以静坐、专注困难和活动节律紊乱、烦恼急躁和饮食节律紊乱的联系最强，分别为0.157、0.118、0.129；女生组：专注困难和行动缓慢、持续担忧和担忧过多、活动节律与电子产品使用节律分别在三个子网络中的多边线权重最大，分别为0.340、0.545、0.570；跨越两个子网络间，专注困难和难以静坐、容易疲劳和睡眠节律、烦恼急躁和活动节律紊乱的联系最强，分别为0.146、0.194、0.093。见图1B、C。
2.4　中心性指标
在总体网络结构中，活动节律强度中心性值最大，其次是容易疲倦；食欲改变的接近中心性值最大，其次是容易疲倦；中介中心性值最大的两项分别是容易疲倦、食欲改变。男生网络结构中，强度中心性、接近中心性、中介中心性最大值项分别是食欲改变、食欲改变和烦恼急躁，女生网络结构则分别是活动节律、自信降低、难以静坐。网络节点的中心性指标值见图2。
2.5　网络比较及准确性检验结果
不同性别组间网络结构不变性检验、网络总体强度不变性检验、中心性不变性检验不存在显著差异（P=0.95，P=0.97）。通过边权权重自举结果bootstrapped 95%置信区间可见，边缘权重的准确性相对准确和可靠。中心性指标的稳定性验证发现中心性指标较为稳定，其CS系数为0.75，表明网络稳定性良好。
3　讨论
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本研究基于天津市青少年样本的网络分析显示，生物节律紊乱与抑郁、焦虑症状之间存在特征性跨症状群连接。行动缓慢（抑郁症状）与难以静坐（焦虑症状）表现出最强的关联（边权=0.141），这种看似矛盾的行为模式可能共同源于生物节律紊乱与心理健康问题的共病效应[17]。睡眠节律紊乱与容易疲劳症状的紧密联系（边权=0.131）印证了睡眠质量下降导致躯体疲劳，进而加剧情绪功能障碍的病理机制[18-19]。饮食节律紊乱与烦恼急躁的关联（边权=0.049）则揭示了不规律饮食模式与焦虑情绪的双向作用关系[20-21]。既往研究指出电子产品的使用与青少年睡眠质量的下降密切相关，而睡眠质量的下降又与心理健康问题（如抑郁和焦虑）有关[22]。最新系统综述也强调了屏幕时间对中国青少年睡眠和心理健康的影响，与本研究中电子产品使用节律紊乱的发现相呼应[23]。
分性别网络分析显示性别特异性关联模式：男生组中，容易疲劳与食欲减退（边权=0.346）与持续担忧与担忧过多（边权=0.388）连接更强；女生组则以专注困难与行动缓慢（边权=0.340）和更强的持续担忧与担忧过多（边权=0.545）为特征。值得注意的是，活动节律与电子产品使用节律在两性中均呈高关联性（男生0.573/女生0.570），凸显其对心理健康的共同影响[24-25]。女生群体在抑郁症状与生物节律紊乱的交互网络中表现出更强关联性，这与女性更易因压力出现焦虑抑郁症状的既往研究一致[26]。这种差异可能与激素波动、社会角色压力及应对策略等生理心理因素相关[27]。
中心性指标分析表明，活动节律在总体网络中表现出最高的强度中心性，表明其在生物节律紊乱与心理健康症状之间的关联网络中具有核心地位，这与日常活动模式显著关联抑郁的研究一致[28-29]。性别差异分析发现：食欲改变呈现高中心性；女生：活动节律与难以静坐分别表现强度与中介中心性优势。这种差异印证了性别在生物节律—心理健康关联中的调节作用[30-31]，尤其女性更易通过内化情绪应对压力[32-33]，导致生物节律相关症状表现突出。
本研究存在一定的局限性：横断面设计难以推断生物节律紊乱与抑郁、焦虑症状的因果关系；地域样本（仅天津市）可能限制结果普适性；自我报告问卷存在回忆与社会期望偏差。未来研究可采用纵向设计扩大地域样本，结合客观测量（如睡眠监测）与生理指标（皮质醇、神经影像）深入探究因果机制。
本研究通过网络分析揭示青少年生物节律紊乱与抑郁、焦虑症状的多维度关联，其中活动节律与电子产品使用节律对心理健康影响尤为关键，且女生群体中二者关联性更强。建议干预措施需重视性别差异，开发针对性方案。未来需通过纵向设计验证因果机制，并基于网络分析结果推动个性化干预实践。
基金
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  • 天津市卫生健康科技项目(TJWJ2024QN089)
  • 天津市科学技术普及项目(24KPHDRC00310)
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doi: 10.20043/j.cnki.MPM.202502184
  • 接收时间：2025-02-13
  • 首发时间：2026-03-18
  • 出版时间：2025-09-10
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  • 收稿日期：2025-02-13
基金
天津市卫生健康科技项目(TJWJ2024QN089)
天津市科学技术普及项目(24KPHDRC00310)
作者信息
    1.天津市疾病预防控制中心环境健康与公共卫生所，天津 300011
    2.天津市津南区疾病预防控制中心
    3.天津市和平区疾病预防控制中心

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
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