中学生生活方式与抑郁焦虑症状的网络分析

王春艳; 江小玉; 林秀金; 吴俊端

doi:10.16835/j.cnki.1000-9817.2025200

中学生生活方式与抑郁焦虑症状的网络分析

doi: 10.16835/j.cnki.1000-9817.2025200

王春艳¹,
江小玉²,
林秀金^3, ,,
吴俊端^{1, 4, ,}

1.
广西医科大学公共卫生学院, 南宁 530021
2.
广西医科大学第二附属医院心理卫生科
3.
广州大学教育学院青少年心理与行为研究中心
4.
广西卫生职业技术学院临床医学院

基金项目:

广西自然基金重点项目 2022GXNSFDA035077

广西哲学社会科学研究项目 23FSH027

详细信息

作者简介:
王春艳(1998-), 女, 河北邢台人, 在读硕士, 主要研究方向为儿少卫生与妇幼保健学、儿童青少年心理健康与精神卫生

通讯作者:
林秀金, E-mail: Lin.Xiujin00@gzhu.edu.cn

吴俊端, E-mail: wujunduan@gxmu.edu.cn

利益冲突声明 所有作者声明无利益冲突。
中图分类号: R179 B844.2 D432.7
计量
- 文章访问数: 21
- HTML全文浏览量: 8
- PDF下载量: 2
- 被引次数: 0
出版历程
- 收稿日期: 2025-01-24
- 修回日期: 2025-04-22
- 网络出版日期: 2025-08-02
- 刊出日期: 2025-07-25

A network analysis study of middle school students' lifestyle with depressive and anxiety symptoms

WANG Chunyan¹,
JIANG Xiaoyu²,
LIN Xiujin^{3
, ,},
WU Junduan^{1, 4
, ,}

1.
School of Public Health, Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China

摘要

摘要: 目的探讨中学生生活方式与抑郁及焦虑症状的交互作用机制，为构建中学生心理健康精准预防体系提供依据。方法 2024年10—12月，采用分层整群随机抽样方法选取广西6 251名中学生为研究对象，应用生活方式问卷、9项患者健康问卷(PHQ-9)和广泛性焦虑障碍量表(GAD-7)分别调查中学生生活方式、抑郁和焦虑症状情况。通过二元Logistic回归分析中学生生活方式与抑郁焦虑症状的关系；通过网络分析构建中学生生活方式与抑郁及焦虑症状之间的网络结构。结果存在抑郁症状中学生1 690名(27.0%)，焦虑症状者1 071名(17.1%)。二元Logistic回归分析结果表明，吸烟、饮酒、含糖饮料摄入过多、蔬菜摄入不足、不每天吃早餐、吃外卖快餐、学习日及休息日久坐时间过长、睡眠时间不足、学习日视屏时间过长均是中学生抑郁(OR=1.19~2.07)及焦虑(OR=1.20~1.91)症状的相关因素，休息日视屏时间过长仅是抑郁症状的相关因素(OR=1.35)(P值均 < 0.05)。生活方式-抑郁症状群间的连接主要通过“早餐”与“自杀念头”实现(权重为0.31)，生活方式-焦虑症状群间的连接主要通过“学习日久坐时间”与“无法控制的担忧”实现(权重为0.34)。在抑郁症状网络中, “情绪低落”表现出最高的节点强度; 在焦虑症状网络中, “无法控制的担忧”表现出最高的节点强度。“自杀念头”是生活方式与抑郁及焦虑症状网络的关键桥梁节点。结论不良生活方式是中学生抑郁焦虑症状的重要可调控风险因素，应将早餐规律性摄入和久坐行为管理作为重要的干预切入点。
- 生活方式 /
- 抑郁 /
- 焦虑 /
- 精神卫生 /
- 回归分析 /
- 青少年
Abstract: Objective To explore the interactive mechanisms of middle school students' lifestyle with depressive and anxiety symptoms, so as to provide a basis for constructing a precise prevention system of middle school students' mental health. Methods From October to December in 2024, a stratified cluster random sampling method was used to select 6 251 middle school students from Guangxi. The Lifestyle Questionnaire, Patient Health Questionnaire-9 (PHQ-9), and Generalized Anxiety Disorder-7 (GAD-7) were used to investigate middle school students' lifestyle, depressive symptoms and anxiety symptoms. The relationship of adolescent lifestyle with depressive and anxiety symptoms was analyzed through binary Logistic regression. The network analysis method was used to construct the network of middle school students' lifestyle with depressive and anxiety symptoms. Results A total of 1 690 individuals (27.0%) exhibited depressive symptoms, and 1 071 individuals (17.1%) exhibited anxiety symptoms. Binary Logistic regression analysis revealed that smoking, alcohol consumption, excessive intake of sugary drinks, insufficient vegetable intake, not eating breakfast daily, frequent consumption of fast food, prolonged sedentary time on both weekdays and weekends, insufficient sleep duration on weekdays and weekends, and excessive screen time on weekdays were all associated with depressive symptom (OR=1.19-2.07) and anxiety symptom (OR=1.20-1.91) in middle school students(all P < 0.05). Additionally, excessive screen time on weekends was associated only with depressive symptoms (OR=1.35, P < 0.05). The connection between the lifestyle-depressive symptom cluster was mainly through "breakfast" and "suicidal ideation" (weight=0.31); the connection between the lifestyle-anxiety symptom cluster was mainly through "sedentary time on weekdays" and "uncontrollable worry" (weight=0.34). In the depressive symptom network, "depressed mood" had the highest node strength; in the anxiety symptom network, "uncontrollable worry" had the highest node strength. "Suicidal ideation" was a key bridge node between lifestyle and depressive and anxiety symptoms. Conclusions Unhealthy lifestyles are significant modifiable risk factors for depressive and anxiety symptoms among middle school students. Regular breakfast intake and management of sedentary behavior should be prioritized as important intervention entry points.
- Life style /
- Depression /
- Anxiety /
- Mental health /
- Regression analysis /
- Adolescent
注释:

1) 利益冲突声明 所有作者声明无利益冲突。

HTML全文

图 1 中学生生活方式与抑郁焦虑症状的网络结构

注：图中线越粗表示相关性越强；生活方式包括吸烟(b1)、饮酒(b2)、含糖饮料(b3)、蔬菜(b4)、水果(b5)、早餐(b6)、外卖快餐(b7)、学习日久坐时间(b8)、休息日久坐时间(b9)、学习日睡眠时间(b10)、休息日睡眠时间(b11)、学习日视屏时间(b12)、休息日视屏时间(b13)；PHQ包括快感缺失(PHQ1)、情绪低落(PHQ2)、睡眠(PHQ3)、疲劳(PHQ4)、食欲(PHQ5)、内疚感(PHQ6)、注意力(PHQ7)、动作(PHQ8)、自杀念头(PHQ9)；GAD-7包括紧张(GAD1)、无法控制的担忧(GAD2)、过度担忧(GAD3)、难以放松(GAD4)、烦躁(GAD5)、易怒(GAD6)、感到害怕(GAD7)。

Figure 1. Network structure of lifestyles with depressive and anxiety symptoms among middle school students

下载: 全尺寸图片幻灯片

图 2 中学生生活方式与抑郁焦虑症状网络中心性特征

注：生活方式包括吸烟(b1)、饮酒(b2)、含糖饮料(b3)、蔬菜(b4)、水果(b5)、早餐(b6)、外卖快餐(b7)、学习日久坐时间(b8)、休息日久坐时间(b9)、学习日睡眠时间(b10)、休息日睡眠时间(b11)、学习日视屏时间(b12)、休息日视屏时间(b13)；PHQ包括快感缺失(PHQ1)、情绪低落(PHQ2)、睡眠(PHQ3)、疲劳(PHQ4)、食欲(PHQ5)、内疚感(PHQ6)、注意力(PHQ7)、动作(PHQ8)、自杀念头(PHQ9)；GAD-7包括紧张(GAD1)、无法控制的担忧(GAD2)、过度担忧(GAD3)、难以放松(GAD4)、烦躁(GAD5)、易怒(GAD6)、感到害怕(GAD7)。

Figure 2. Centrality characteristics of the network between lifestyles and depressive and anxiety symptoms among middle school students

下载: 全尺寸图片幻灯片

表 1 不同生活方式中学生抑郁及焦虑症状检出率比较

Table 1. Comparison of detection rates of depression and anxiety symptoms among middle school students with different lifestyles

生活方式	选项	人数	抑郁症状		焦虑症状
生活方式	选项	人数	检出人数	χ²值	检出人数	χ²值
每月吸烟/d	< 1	5 840	1 524(26.1)	39.77	960(16.4)	30.21
	≥1	411	166(40.4)		111(27.0)
每月饮酒/d	< 1	5 618	1 399(24.9)	128.03	875(15.6)	94.89
	≥1	633	291(46.0)		196(31.0)
每周喝含糖	≤1	2 449	484(19.8)	107.96	317(12.9)	49.77
饮料/次	>1	3 802	1 206(31.7)		754(19.8)
每天蔬菜	>1	4 011	991(24.7)	30.77	608(15.2)	30.75
摄入/份	≤1	2 240	699(31.2)		463(20.7)
每天水果	>1	2 883	703(24.4)	19.07	440(15.3)	13.20
摄入/份	≤1	3 368	987(29.3)		631(18.7)
每周吃早餐/d	7	3 675	736(20.0)	222.05	449(12.2)	151.77
	< 7	2 576	954(37.0)		622(24.1)
每周吃外卖	< 1	5 081	1 256(24.7)	73.82	762(15.0)	87.25
快餐/次	≥1	1 170	434(37.1)		309(26.4)
学习日平均每天	< 9	4 484	995(22.2)	188.82	609(13.6)	140.93
久坐时间/h	≥9	1 767	695(39.3)		462(26.1)
休息日平均每天	< 9	5 192	1 239(23.9)	156.32	764(14.7)	126.24
久坐时间/h	≥9	1 059	451(42.6)		307(29.0)
学习日平均每天	≥8	1 967	301(15.3)	200.30	165(8.4)	154.59
睡眠时间/h	< 8	4 284	1 389(32.4)		906(21.1)
休息日平均每天	≥8	3 463	734(21.2)	134.25	448(12.9)	96.31
睡眠时间/h	< 8	2 788	956(34.3)		623(22.3)
学习日平均每天	≤2	4 855	1 216(25.0)	43.61	771(15.9)	24.03
视屏时间/h	>2	1 396	474(34.0)		300(21.5)
休息日平均每天	≤2	3 021	629(20.8)	114.47	416(13.8)	46.57
视屏时间/h	>2	3 230	1 061(32.8)		655(20.3)
注：()内数字为检出率/%；P值均 < 0.01。

下载: 导出CSV

表 2 中学生抑郁及焦虑症状的二元Logistic回归分析[OR值(95%CI)，n=6 251]

Table 2. Binary Logistic regression analysis of depressive and anxiety symptoms in middle school students [OR(95%CI), n=6 251]

自变量	选项	抑郁症状	焦虑症状
每月吸烟/d	< 1	1.00	1.00
	≥1	1.44(1.12~1.85)^**	1.45(1.10~1.91)^**
每月饮酒/d	< 1	1.00	1.00
	≥1	2.07(1.69~2.54)^**	1.91(1.53~2.39)^**
每周喝含糖饮料/次	≤1	1.00	1.00
	>1	1.40(1.23~1.61)^**	1.20(1.03~1.41)^**
每天蔬菜摄入/份	>1	1.00	1.00
	≤1	1.19(1.04~1.37)^*	1.25(1.07~1.46)^**
每天水果摄入/份	>1	1.00	1.00
	≤1	1.11(0.97~1.27)	1.07(0.91~1.25)
每周吃早餐/d	7	1.00	1.00
	< 7	1.89(1.67~2.14)^**	1.83(1.59~2.11)^**
每周吃外卖	< 1	1.00	1.00
快餐/次	≥1	1.33(1.14~1.54)^**	1.56(1.32~1.83)^**
学习日平均每天久坐时间/h	< 9	1.00	1.00
	≥9	1.53(1.32~1.76)^**	1.53(1.30~1.80)^**
休息日平均每天久坐时间/h	< 9	1.00	1.00
	≥9	1.47(1.25~1.73)^**	1.52(1.27~1.82)^**
学习日平均每天睡眠时间/h	≥8	1.00	1.00
	< 8	1.86(1.59~2.18)^**	2.05(1.69~2.49)^**
休息日平均每天睡眠时间/h	≥8	1.00	1.00
	< 8	1.42(1.25~1.63)^**	1.36(1.17~1.58)^**
学习日平均每天视屏时间/h	≤2	1.00	1.00
	＞2	1.31(1.13~1.53)^**	1.29(1.08~1.53)^**
休息日平均每天视屏时间/h	≤2	1.00	1.00
	＞2	1.35(1.17~1.54)^**	1.14(0.97~1.33)
注：因变量以无抑郁、焦虑症状为参照；模型调整了性别、年龄等变量；^* P < 0.05，^** P < 0.01。

下载: 导出CSV

参考文献(32)

[1]	SHAW J W, JOHNSON J A, COONS S J. US valuation of the EQ-5D health states: development and testing of the D1 valuation model[J]. Med Care, 2005, 43(3): 203-220.
[2]	SILVA S A, SILVA S U, RONCA D B, et al. Common mental disorders prevalence in adolescents: a systematic review and Meta-analyses[J]. PLoS One, 2020, 15(4): e0232007.
[3]	TIAN Y E, COLE J H, BULLMORE E T, et al. Brain, lifestyle and environmental pathways linking physical and mental health[J]. Nat Ment Health, 2024, 2(10): 1250-1261.
[4]	EPSKAMP S, BORSBOOM D, FRIED E I. Estimating psychological networks and their accuracy: a tutorial paper[J]. Behav Res Methods, 2018, 50(1): 195-212.
[5]	BRENER N D, MPOFU J J, KRAUSE K H, et al. Overview and methods for the youth risk behavior surveillance system-United States, 2023[J]. MMWR Suppl, 2024, 73(4): 1-12.
[6]	王陈芳. 昼夜节律紊乱与青少年聚集性健康危害行为关联方向性的队列研究[D]. 合肥: 安徽医科大学, 2023. WANG C F. A cohort study on the directivity of association between circadian rhythm disturbances and clustered health risk behaviors among adolescents[D]. Hefei: Anhui Medical University, 2023. (in Chinese)
[7]	张一. 社会生态学风险因素与多基因风险评分的交互作用对青少年健康危害行为聚集的影响[D]. 合肥: 安徽医科大学, 2022. ZHANG Y. The effect of interaction between social ecological risk factors and polygenic risk score on clustering of health risk behaviors in adolescents[D]. Hefei: Anhui Medical University, 2022. (in Chinese)
[8]	杨瑞君, 吕书红, 刘志业, 等. 中国5省初中生视屏时间和饮食行为与抑郁症状的关联[J]. 上海交通大学学报(医学版), 2024, 44(3): 358-364. doi: 10.3969/j.issn.1674-8115.2024.03.008 YANG R J, LV S H, LIU Z Y, et al. Relationship of screen time and dietary behaviors with depressive symptoms in junior high school students in five provinces in China[J]. J Shanghai Jiaotong Univ (Med Sci), 2024, 44(3): 358-364. (in Chinese) doi: 10.3969/j.issn.1674-8115.2024.03.008
[9]	张云婷, 马生霞, 陈畅, 等. 中国儿童青少年身体活动指南[J]. 中国循证儿科杂志, 2017, 12(6): 401-409. doi: 10.3969/j.issn.1673-5501.2017.06.001 ZHANG Y T, MA S X, CHEN C, et al. Physical activity guidelines for Chinese children and adolescents[J]. Chin J Evid Based Pediatr, 2017, 12(6): 401-409. (in Chinese) doi: 10.3969/j.issn.1673-5501.2017.06.001
[10]	袁亚运. 中国中小学生睡眠状况及其与抑郁症状的关联[J]. 中国学校卫生, 2024, 45(10): 1465-1470, 1475. doi: 10.16835/j.cnki.1000-9817.2024301 YUAN Y Y. Association between sleep and depressive symptoms among primary and secondary school students[J]. Chin J Sch Health, 2024, 45(10): 1465-1470, 1475. (in Chinese) doi: 10.16835/j.cnki.1000-9817.2024301
[11]	BARBOSA B C R, MENEZES-JUNIOR L A A D E, DE PAULA W, et al. Sedentary behavior is associated with the mental health of university students during the COVID-19 pandemic, and not practicing physical activity accentuates its adverse effects: cross-sectional study[J]. BMC Public Health, 2024, 24(1): 1860.
[12]	KROENKE K, SPITZER R L, WILLIAMS J B W. The PHQ-9: validity of a brief depression severity measure[J]. J Gen Intern Med, 2001, 16(9): 606-613.
[13]	ANAND P, BHURJI N, WILLIAMS N, et al. Comparison of PHQ-9 and PHQ-2 as screening tools for depression and school related stress in inner city adolescents[J]. J Prim Care Commun Health, 2021, 12: 21501327211053750.
[14]	SEKHAR D L, SCHAEFER E W, WAXMONSKY J G, et al. Screening in high schools to identify, evaluate, and lower depression among adolescents a randomized clinical trial[J]. JAMA Netw Open, 2021, 4(11): e2131836.
[15]	SPITZER R L, KROENKE K, WILLIAMS J B W, et al. A brief measure for assessing generalized anxiety disorder: the GAD-7[J]. Arch Intern Med, 2006, 166(10): 1092.
[16]	WANG H, ZHOU Y, DAI P, et al. Anxiety symptoms and associated factors among school students after 2 years of the COVID-19 pandemic: a cross-sectional study in Zhejiang Province, China[J]. BMJ Open, 2023, 13(12): e079084.
[17]	ROMANO I, FERRO M A, PATTE K A, et al. Measurement invariance of the GAD-7 and CESD-R-10 among adolescents in Canada[J]. J Pediatr Psychol, 2022, 47(5): 585-594.
[18]	CAI H, BAI W, LIU H, et al. Network analysis of depressive and anxiety symptoms in adolescents during the later stage of the COVID-19 pandemic[J]. Transl Psychiatry, 2022, 12(1): 98.
[19]	COSTANTINI G, EPSKAMP S, BORSBOOM D, et al. State of the aRt personality research: a tutorial on network analysis of personality data in R[J]. J Res Pers, 2015, 54: 13-29.
[20]	EPSKAMP S, FRIED E I. A tutorial on regularized partial correlation networks[J]. Psychol Methods, 2018, 23(4): 617-634.
[21]	莫敏, 张莉梅, 印德娇, 等. 重庆市某区青少年不良健康行为与焦虑抑郁的相关分析[J]. 健康教育与健康促进, 2024, 19(3): 234-236, 283. MO M, ZHANG L M, YIN D J, et al. Correlation analysis of unhealthy behaviors and anxiety and depression among adolescents in a district of Chongqing[J]. J Health Educ Health Promot, 2024, 19(3): 234-236, 283. (in Chinese)
[22]	MOHD S N Z, HANAWI S A, HANAFIAH H, et al. Relationship of screen time with anxiety, depression, and sleep quality among adolescents: a cross-sectional study[J]. Front Public Health, 2024, 12: 1459952.
[23]	CAAMAÑO-NAVARRETE F, SAAVEDRA-VALLEJOS E, GUZMÁN-GUZMÁN I P, et al. Unhealthy lifestyle contributes to negative mental health and poor quality of life in young university students[J]. Healthcare (basel), 2024, 12(22): 2213.
[24]	LIU D, YU M, ZHANG X, et al. Adolescent anxiety and depression: perspectives of network analysis and longitudinal network analysis[J]. BMC Psychiatry, 2024, 24: 619.
[25]	MISHRA A K, VARMA A R. A comprehensive review of the generalized anxiety disorder[J]. Cureus, 2023, 15(9): e46115.
[26]	NIU C, JIANG Y, LI Y, et al. A network analysis of the heterogeneity and associated risk and protective factors of depression and anxiety among college students[J]. Sci Reports, 2025, 15(1): 6699.
[27]	FRIED E I, EPSKAMP S, NESSE R M, et al. What are "good" depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis[J]. J Affect Disord, 2016, 189: 314-320.
[28]	仲伟莹, 徐岚, 潘习, 等. 桥梁症状在精神疾病患者症状管理中的应用及其研究进展[J]. 中华现代护理杂志, 2023, 29(36): 5030-5034. ZHONG W Y, XU L, PAN X, et al. Research progress on bridge symptoms in symptom management of mental illness patients[J]. Chin J Mod Nurs, 2023, 29(36): 5030-5034. (in Chinese)
[29]	CHOPRA C, MANDALIKA S, KINGER N. Does diet play a role in the prevention and management of depression among adolescents? A narrative review[J]. Nutr Health, 2021, 27(2): 243-263.
[30]	KESKI-RAHKONEN P, KOLEHMAINEN M, LAPPI J, et al. Decreased plasma serotonin and other metabolite changes in healthy adults after consumption of wholegrain rye: an untargeted metabolomics study[J]. Am J Clin Nutr, 2019, 109(6): 1630-1639.
[31]	姚娇, 杨岩涛, 艾启迪, 等. 神经递质功能与抑郁症发病的研究进展[J]. 中国药理学通报, 2023, 39(7): 1217-1221. YAO J, YANG Y T, AI Q D, et al. Review of research progress on neurotransmitter function and depression[J]. Chin Pharmacol Bull, 2023, 39(7): 1217-1221. (in Chinese)
[32]	RODRIGUEZ-AYLLON M, CADENAS-SÁNCHEZ C, ESTÉVEZ-LÓPEZ F, et al. Role of physical activity and sedentary behavior in the mental health of preschoolers, children and adolescents: a systematic review and Meta-analysis[J]. Sports Med, 2019, 49(9): 1383-1410.