苏州市高中生青春发动时相与抑郁症状的关系

胡佳乐; 张俪叶; 凌睿哲; 韩迪; 王希; 胡佳; 沈蕙

doi:10.16835/j.cnki.1000-9817.2025315

苏州市高中生青春发动时相与抑郁症状的关系

doi: 10.16835/j.cnki.1000-9817.2025315

胡佳乐¹,
张俪叶²,
凌睿哲²,
韩迪²,
王希¹,
胡佳^{1, 2, 3, ,},
沈蕙^{1, 2, 3, ,}

1.
南京医科大学公共卫生学院, 江苏 211166
2.
苏州市疾病预防控制中心学校卫生科
3.
南京医科大学姑苏学院苏州市公共卫生高等研究院

基金项目:

国家自然科学基金-青年项目 82204070

苏州市姑苏卫生人才计划培养项目 GSWS2020100

苏州市“科教强卫”青年项目 QNXM2024059

详细信息

作者简介:
胡佳乐(2001-)，女，浙江衢州人，在读硕士，主要研究方向为儿童青少年发育与健康

通讯作者:
胡佳，E-mail：hujia200606@163.com

沈蕙，E-mail：791675633@qq.com

利益冲突声明 所有作者声明无利益冲突。
中图分类号: R179 G444 R339.3⁺⁵
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出版历程
- 收稿日期: 2025-06-23
- 修回日期: 2025-09-04
- 刊出日期: 2025-10-25

Association between pubertal timing and depressive symptoms among high school students in Suzhou City

HU Jiale¹,
ZHANG Liye²,
LING Ruizhe²,
HAN Di²,
WANG Xi¹,
HU Jia^{1, 2, 3
, ,},
SHEN Hui^{1, 2, 3
, ,}

1.
School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu Province, China

摘要

摘要: 目的探讨苏州市高中生青春发动时相与抑郁症状的关系，为促进青少年心理健康提供科学依据。方法于2023年10月至2024年1月，采用分层整群随机抽样方法从苏州市20所高中抽取3 369名学生，进行体格检查和问卷调查。通过Preece & Baines生长模型1计算学生的身高突增开始年龄(ATO)和身高速度高峰年龄(APHV)，将学生分为青春发动时相提前组(< P₁₅)、适时组(P₁₅~P₈₅)、延迟组(>P₈₅)，采用二元Logistic回归分析其与抑郁症状的关联。结果苏州市高中男生和女生的ATO分别为(9.35±1.23)(8.12±1.52)岁，APHV分别为(12.35±0.74)(10.91±0.82)岁。抑郁症状的总检出率为34.22%，性别间差异无统计学意义(χ²=0.42，P=0.52)；不同年级、早餐频率、每周中高强度运动天数、睡眠时长、是否遭受校园欺凌以及是否存在网络成瘾的学生抑郁症状检出率差异均有统计学意义(χ²=5.03~69.21，P值均 < 0.05)。调整年龄、体质量指数、地区、是否住校、早餐频率、每周中高强度运动天数、每天睡眠时长、遭受校园欺凌和存在网络成瘾协变量后，Logistic回归分析结果显示，ATO评价青春发动时相时，男生延迟组抑郁症状检出风险是适时组的1.65倍(95%CI=1.24~2.19)；APHV评价青春发动时相时，男生提前组和延迟组抑郁症状检出风险分别是适时组的1.43(95%CI=1.07~1.91)和1.41倍(95%CI=1.05~1.88)(P值均 < 0.05)；女生中的关联均无统计学意义(P值均>0.05)。结论苏州市高中生抑郁症状检出率较高，男生青春发动时相提前或延迟与抑郁症状检出有关。
- 青春期发育 /
- 抑郁 /
- 精神卫生 /
- 回归分析 /
- 学生
Abstract: Objective To investigate the relationship between pubertal timing and depressive symptoms among high school students in Suzhou, so as to provide scientific evidence for promoting adolescents mental health. Methods From October 2023 to January 2024, 3 369 students were selected from 20 high schools in Suzhou using stratified cluster random sampling method. Physical examinations and questionnaire surveys were conducted. The Preece & Baines growth Model 1 was used to calculate the age at take-off of height velocity (ATO) and age at peak height velocity (APHV), categorizing students into three groups: early pubertal timing group (< P₁₅), on-time group (P₁₅-P₈₅), and delayed group (>P₈₅). Binary Logistic regression was used to analyze its association with depressive symptoms. Results The ATO for male and female high school students in Suzhou was (9.35±1.23) and (8.12±1.52) years old, respectively. The mean APHV was (12.35±0.74) years old for boys and (10.91±0.82) years old for girls. The overall prevalence of depressive symptoms was 34.22%, with no statistically significant gender difference (χ²=0.42, P=0.52). Significant differences in depressive symptom prevalence were observed across grade levels, breakfast frequency, weekly days of moderate-to-vigorous physical activity, daily sleep duration, history of school bullying, and the presence of Internet addiction (χ²=5.03-69.21, all P < 0.05). After adjusting for age, body mass index, region, boarding status, breakfast frequency, weekly moderate-to-vigorous physical activity days, sleep duration, campus bullying, and presence of Internet addiction, Logistic regression analysis revealed that when ATO was used to evaluate pubertal timing, the risk of depressive symptoms in the delayed group of boys was 1.65 times that of the on-time group (95%CI=1.24-2.19); when APHV was used to evaluate pubertal timing, the risks of depressive symptoms in the early pubertal timing group and delayed group of boys were 1.43 times (95%CI=1.07-1.91) and 1.41 times (95%CI=1.05-1.88) of that of the on-time group, respectively (all P < 0.05). No statistically significant associations were found among females (all P>0.05). Conclusion The prevalence of depressive symptoms among high school students in Suzhou is relatively high, and both early and delayed puberty timing in boys are associated with depressive symptoms.
- Adolescent development /
- Depression /
- Mental health /
- Regression analysis /
- Students
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表 1 苏州市高中生抑郁症状检出率单因素分析

Table 1. Univariate analysis of depression detection rate among high school students in Suzhou

组别	选项	人数	抑郁症状	χ²值	P值
性别	男	1 753	591(33.71)	0.42	0.52
	女	1 616	562(34.78)
年级	高一	1 191	393(33.00)	12.38	< 0.01
	高二	1 166	370(31.73)
	高三	1 012	390(38.54)
地区	城区	1 678	562(33.49)	0.80	0.37
	郊县	1 691	591(34.95)
住校	是	1 105	401(36.29)	3.12	0.08
	否	2 264	752(33.22)
早餐频率	天天吃	2 815	879(31.23)	69.21	< 0.01
	有时吃	486	237(48.77)
	从来不吃	68	37(54.41)
每周中高强度运动天数/d	≥3	1 198	365(30.47)	11.65	< 0.01
	< 3	2 171	788(36.30)
每天睡眠时长/h	≥8	261	67(25.67)	9.20	< 0.01
	< 8	3 108	1 086(34.94)
遭受校园欺凌	是	102	71(69.61)	58.50	< 0.01
	否	3 267	1 082(33.12)
存在网络成瘾	是	129	56(43.41)	5.03	0.03
	否	3 240	1 097(33.86)
合计		3 369	1 153(34.22)
注：()内数字为检出率/%。

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表 2 不同性别高中生ATO分组与抑郁症状的Logistic回归分析

Table 2. Logistic regression analysis of the association between ATO grouping and depressive symptom among high school students by genders

性别	组别	β值	标准误	Wald χ²值	P值	OR值(95%CI)
男	提前组	0.20	0.15	1.80	0.18	1.22(0.91~1.63)
(n=1 753)	延迟组	0.50	0.15	11.68	< 0.01	1.65(1.24~2.19)
	常量	-2.80	1.15	5.91	0.02	0.06
女	提前组	-0.11	0.16	0.51	0.48	0.90(0.66~1.22)
(n=1 616)	延迟组	0.06	0.15	0.17	0.68	1.06(0.80~1.43)
	常量	-1.58	1.26	1.59	0.21	0.21
注：模型调整了年龄、BMI、地区、是否住校、早餐频率、每周中高强度运动天数、睡眠时长、遭受校园欺凌和存在网络成瘾。

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表 3 不同性别高中生APHV分组与抑郁症状的Logistic回归分析

Table 3. Logistic regression analysis of the association between APHV grouping and depressive symptom among high school students by genders

性别	组别	β值	标准误	Wald χ²值	P值	OR值(95%CI)
男	提前组	0.36	0.15	5.74	0.02	1.43(1.07~1.91)
(n=1 753)	延迟组	0.34	0.15	5.22	0.02	1.41(1.05~1.88)
	常量	-2.72	1.15	5.55	0.02	0.07
女	提前组	-0.31	0.16	3.81	0.05	0.73(0.54~1.00)
(n=1 616)	延迟组	-0.13	0.15	0.69	0.41	0.88(0.65~1.19)
	常量	-1.56	1.26	1.55	0.21	0.21
注：模型调整了年龄、BMI、地区、是否住校、早餐频率、每周中高强度运动天数、睡眠时长、遭受校园欺凌和存在网络成瘾。

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参考文献(23)

[1]	CLAYBORNE Z M, VARIN M, COLMAN I. Systematic review and Meta-analysis: adolescent depression and long-term psychosocial outcomes[J]. J Am Acad Child Adolesc Psychiatry, 2019, 58(1): 72-79.
[2]	MARSHALL W A, TANNER J M. Variations in pattern of pubertal changes in girls[J]. Arch Dis Child, 1969, 44(235): 291-303.
[3]	陶芳标. 儿童少年卫生学[M]. 8版. 北京: 人民卫生出版社, 2017. TAO F B. Child and adolescent health[M]. 8th ed. Beijing: People's Medical Publishing House, 2017. (in Chinese)
[4]	RUDOLPH K D, TROOP-GORDON W, LAMBERT S F, et al. Long-term consequences of pubertal timing for youth depression: identifying personal and contextual pathways of risk[J]. Dev Psychopathol, 2014, 26(4 Pt 2): 1423-1444.
[5]	KALTIALA-HEINO R, MARTTUNEN M, RANTANEN P, et al. Early puberty is associated with mental health problems in middle adolescence[J]. Soc Sci Med, 2003, 57(6): 1055-1064.
[6]	COPELAND W, SHANAHAN L, MILLER S, et al. Outcomes of early pubertal timing in young women: a prospective population-based study[J]. Am J Psychiatry, 2010, 167(10): 1218-1225.
[7]	苏州市卫生健康委员会, 苏州市教育局, 苏州市疾病预防控制中心. 2023年苏州市学生常见病和健康影响因素监测及干预工作手册[Z]. 苏州: 苏州市疾病预防控制中心, 2023. Suzhou Municipal Health Commission, Suzhou Municipal Education Bureau, Suzhou Center for Disease Prevention and Control. Handbook for monitoring and intervention of common diseases and health influencing factors among students in Suzhou City in 2023[Z]. Suzhou: Suzhou Center for Disease Prevention and Control, 2023. (in Chinese)
[8]	SAYERS A, BAINES M, TILLING K. A new family of mathematical models describing the human growth curve-erratum: direct calculation of peak height velocity, age at take-off and associated quantities[J]. Ann Hum Biol, 2013, 40(3): 298-299.
[9]	MENDLE J, BELTZ A M, CARTER R, et al. Understanding puberty and its measurement: ideas for research in a new generation[J]. J Res Adolesc, 2019, 29(1): 82-95.
[10]	RADLOFF L S. The CES-D scale: a self-report depression scale for research in the general population[J]. Appl Psychol Meas, 1977, 1(3): 385-401.
[11]	陈咏梅, 范明明. 开封市中学生抑郁状况及影响因素分析[J]. 中国学校卫生, 2021, 42(10): 1520-1523. doi: 10.16835/j.cnki.1000-9817.2021.10.018 CHEN Y M, FAN M M. Analysis of depressive symptoms and associated factors among middle school students in Kaifeng City[J]. Chin J Sch Health, 2021, 42(10): 1520-1523. (in Chinese) doi: 10.16835/j.cnki.1000-9817.2021.10.018
[12]	袁琳琳, 张喆, 周欣怡, 等. 上海市中学生压力与网络成瘾的关联性[J]. 中国学校卫生, 2024, 45(12): 1757-1760, 1765. YUAN L L, ZHANG Z, ZHOU X Y, et al. Correlation between stress and Internet addiction among middle school students in Shanghai[J]. Chin J Sch Health, 2024, 45(12): 1757-1760, 1765. (in Chinese)
[13]	胥思宇, 杨文漪. 江苏省中学生抑郁状况及其影响因素分析[J]. 江苏预防医学, 2023, 34(2): 163-167. XU S Y, YANG W Y. Prevalence and influencing factors of depression among high school students in Jiangsu Province[J]. Jiangsu J Prev Med, 2023, 34(2): 163-167. (in Chinese)
[14]	奉琪, 陈艳, 吴鑫. 长沙市中学生抑郁症状流行状况及其影响因素分析[J]. 实用预防医学, 2023, 30(8): 949-954. FENG Q, CHEN Y, WU X. Prevalence of depressive symptoms and its influencing factors among middle school students in Changsha City[J]. Pract Prev Med, 2023, 30(8): 949-954. (in Chinese)
[15]	孙力菁, 罗春燕, 周月芳, 等. 上海市中学生抑郁症状和网络成瘾行为的相关性[J]. 中国学校卫生, 2019, 40(3): 445-447. doi: 10.16835/j.cnki.1000-9817.2019.03.035 SUN L J, LUO C Y, ZHOU Y F, et al. Correlation between depressive symptoms and Internet addiction behavior of middle school students in Shanghai[J]. Chin J Sch Health, 2019, 40(3): 445-447. (in Chinese) doi: 10.16835/j.cnki.1000-9817.2019.03.035
[16]	陈国平, 王志强, 孙莹, 等. 安徽省中学生校园欺凌与焦虑抑郁症状共患的关联性[J]. 中国学校卫生, 2024, 45(8): 1115-1119. doi: 10.16835/j.cnki.1000-9817.2024250 CHEN G P, WANG Z Q, SUN Y, et al. Association of school bullying with the comorbidity of anxiety and depressive symptoms among middle school students in Anhui Province[J]. Chin J Sch Health, 2024, 45(8): 1115-1119. (in Chinese) doi: 10.16835/j.cnki.1000-9817.2024250
[17]	BELTZ A M. Gendered mechanisms underlie the relation between pubertal timing and adult depressive symptoms[J]. J Adolesc Health, 2018, 62(6): 722-728.
[18]	GAYSINA D, RICHARDS M, KUH D, et al. Pubertal maturation and affective symptoms in adolescence and adulthood: evidence from a prospective birth cohort[J]. Dev Psychopathol, 2015, 27(4 Pt 1): 1331-1340.
[19]	GE X, NATSUAKI M N. In search of explanations for early pubertal timing effects on developmental psychopathology[J]. Curr Dir Psychol Sci, 2009, 18(6): 327-331.
[20]	TARIF D, HERON J, FRASER A, et al. Pubertal timing, depressive symptoms, and depression in adolescent males: a prospective cohort study[J]. Psychol Med, 2025, 55: e3.
[21]	GE X, BRODY G H, CONGER R D, et al. Pubertal maturation and African American children's internalizing and externalizing symptoms[J]. J Youth Adolesc, 2006, 35(4): 528-537.
[22]	ZHANG C, YANG J, YANG W, et al. Age at menarche and depression: an updated systematic review and Meta-analysis[J]. Arch Womens Ment Health, 2025, 28(5): 983-995.
[23]	龚纯, 方姣, 万宇辉, 等. 青春期发育时相和速度对儿童抑郁症状影响的6年随访研究[J]. 中华预防医学杂志, 2020, 54(7): 747-752. GONG C, FANG J, WAN Y H, et al. Six-year follow-up study on the influence of puberty development stage and speed on children's depressive symptoms[J]. Chin J Prev Med, 2020, 54(7): 747-752. (in Chinese)