Journal of Shandong University (Health Sciences) ›› 2026, Vol. 64 ›› Issue (9): 88-99.doi: 10.6040/j.issn.1671-7554.0.2025.1017

• Public Health and Preventive Medicine • Previous Articles    

Disease burden trends and risk factors of depressive disorders among children and adolescents in China: an explainable machine learning analysis based on SHAP

JIANG Xiuyu1, ZHENG Fengjia2, LIU Xuan3, LI Suyun4, LYU Cuixia4, LIU Zhaolu4, ZHENG Shoujuan4, ZHOU Han5, YU Lianlong3,6   

  1. 1. Health Management Center, Central Hospital Affiliated to Shandong First Medical University, Jinan 250013, Shandong, China;
    2. Institute of Health Inspection and Testing, Shandong Provincial Center for Disease Control and Prevention, Jinan 250014, Shandong, China;
    3. School of Public Health, Shandong Second Medical University, Weifang 261053, Shandong, China;
    4. Institute of Health Management, Shandong Provincial Center for Disease Control and Prevention, Jinan 250014, Shandong, China;
    5. Institute of Food and Nutrition, Shandong Provincial Center for Disease Control and Prevention, Jinan 250014, Shandong, China;
    6. Institute of Public Health Monitoring and Evaluation, Shandong Provincial Center for Disease Control and Prevention, Jinan 250014, Shandong, China
  • Published:2026-09-09

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Abstract: Objective To analyze the long-term trends and age- and sex-specific differences in the burden of depressive disorders among children and adolescents aged <20 years in China from 1990 to 2021, and to explore the contributions of relevant exposure features to model predictions. Methods Data were obtained from the Global Burden of Disease Study 2021. The estimated annual percentage change(EAPC)and Joinpoint regression were used to analyze long-term trends in incidence, prevalence, and disability-adjusted life years(DALYs). A Bayesian age-period-cohort(BAPC)model was used to project changes in incidence from 2021 to 2049. Light gradient boosting machine(LightGBM), combined with Shapley additive explanations(SHAP)and negative binomial regression, was used to explore relevant summary exposure value(SEV)features and the strengths of their associations. Results From 1990 to 2021, the incidence, prevalence, and DALYs of depressive disorders among children and adolescents in China decreased overall, whereas the corresponding global indicators increased. In China, the disease burden increased with age and was higher among females than among males. The burden of depressive disorders increased among children aged ≤9 years but decreased among those aged 15-19 years. SHAP analysis showed that childhood underweight made the greatest contribution to model predictions, while iron deficiency, sexual violence against children, and occupational exposure to particulate matter, gases, and fumes also showed relatively high contributions. Negative binomial regression showed that sexual violence against children had the strongest association(RR=2.212, 95%CI: 2.099-2.331). Conclusion The burden of depressive disorders among children and adolescents in China has decreased overall, but younger children and females remain priority populations. These findings support strengthening early screening and implementing comprehensive interventions targeting violence prevention, nutritional improvement, and living environments.

Key words: Children and adolescents, Depressive disorders, Disease burden, Explainable machine learning, Summary exposure value

CLC Number: 

  • R179
[1] Thapar A, Eyre O, Patel V, et al. Depression in young people[J]. Lancet, 2022, 400(10352): 617-631
[2] GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability(YLDs), disability-adjusted life-years(DALYs), and healthy life expectancy(HALE)for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021[J]. Lancet, 2024, 403(10440): 2133-2161. DOI:10.1016/S0140-6736(24)00757-8[PubMed]
[3] Kieling C, Buchweitz C, Caye A, et al. Worldwide prevalence and disability from mental disorders across childhood and adolescence: evidence from the global burden of disease study[J]. JAMA Psychiatry, 2024, 81(4): 347-356.
[4] Piao J M, Huang Y Q, Han C, et al. Alarming changes in the global burden of mental disorders in children and adolescents from 1990 to 2019: a systematic analysis for the Global Burden of Disease study[J]. Eur Child Adolesc Psychiatry, 2022, 31(11): 1827-1845.
[5] Deng Y, Sun S W, Wu S X, et al. Burden and trends of mental disorders in China from 1990 to 2019: findings from the Global Burden of Disease Study 2019[J]. Soc Psychiatry Psychiatric Epidemiol, 2024, 59(9): 1563-1576.
[6] Zhu F Y, Yang Y, Yin T L, et al. The Burdenof adolescent depression and the impact of COVID-19 across 204 countries and regions from 1990 to 2021: results from the 2021 global burden of disease study[J]. Sci Rep, 2025, 15: 5658. DOI:10.1038/s41598-024-84843-w
[7] Liu X Z, Cang R, Zhang Z H, et al. Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features[J]. BMC Public Health, 2025, 25(1): 264. DOI:10.1186/s12889-025-21506-z
[8] Yoo A, Li F Z, Youn J, et al. Prediction of adolescent depression from prenatal and childhood data from ALSPAC using machine learning[J]. Sci Rep, 2024, 14(1): 23282. DOI:10.1038/s41598-024-72158-9
[9] Patel J, Hung C, Katapally T R. Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review[J]. Psychiatry Res, 2025, 343: 116277. DOI:10.1016/j.psychres.2024.116277
[10] Brauer M, Roth G A, Aravkin A Y, et al. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021[J]. Lancet, 2024, 403(10440): 2162-2203.
[11] 曾四清, 李艳, 刘珺, 等. 两组序列数据趋势变化特征对比分析的Joinpoint回归模型方法及应用[J]. 中国卫生统计, 2021, 38(2): 307-311.
[12] Riebler A, Held L. Projecting the future burden of cancer: Bayesian age-period-cohort analysis with integrated nested Laplace approximations[J]. Biom J, 2017, 59(3): 531-549.
[13] Steare T, Gutiérrez Muñoz C, Sullivan A, et al. The association between academic pressure and adolescent mental health problems: a systematic review[J]. J Affect Disord, 2023, 339: 302-317. DOI:10.1016/j.jad.2023.07.028
[14] Fassi L, Thomas K, Parry D A, et al. Social media use and internalizing symptoms in clinical and community adolescent samples: a systematic review and meta-analysis[J]. JAMA Pediatr, 2024, 178(8): 814-822.
[15] 中共中央国务院印发《“健康中国2030”规划纲要》[J]. 中华人民共和国国务院公报, 2016(32):5-20.
[16] 国务院办公厅. 国务院办公厅关于转发卫生计生委等部门全国精神卫生工作规划(2015—2020年)的通知[EB/OL].(2015-06-18)[2026-03-21]. https://www.gov.cn/zhengce/content/2015-06/18/content_9860.htm
[17] 吴霞民, 马宁, 陈润滋, 等. 中国内地精神卫生防治技术管理机构现状调查[J]. 中国公共卫生, 2023, 39(4): 485-488. Wu Xiamin, Ma Ning, Chen Runzi, et al. Mental health prevention and control management facilities and personnel in the mainland of China, 2020: a cross-sectional survey[J]. Chinese Journal of Public Health, 2023, 39(4): 485-488.
[18] Liu Z, Kuai M N. The global burden of depression in adolescents and young adults, 1990-2021: systematic analysis of the global burden of disease study[J]. BMC Psychiatry, 2025, 25(1): 767. DOI:10.1186/s12888-025-07201-8
[19] Cagney J, Spencer C, Flor L, et al. Prevalence of sexual violence against children and age at first exposure: a global analysis by location, age, and sex(1990-2023)[J]. Lancet, 2025, 405(10492): 1817-1836.
[20] Spencer C N, Khalil M, Herbert M, et al. Health effects associated with exposure to intimate partner violence against women and childhood sexual abuse: a Burden of Proof study[J]. Nat Med, 2023, 29(12): 3243-3258.
[21] Yu Z Y, Cao Y H, Shang T, et al. Depression in youths with early life adversity: a systematic review and meta-analysis[J]. Front Psychiatry, 2024, 15: 1378807. DOI:10.3389/fpsyt.2024.1378807
[22] Song QQ, Yuan T S, Hu Y Y, et al. The effect of peer victimization during adolescence on depression and gender differences: a systematic review and meta-analysis[J]. Trauma Violence Abuse, 2024, 25(4): 2862-2876.
[23] Newbury J B, Heron J, Kirkbride J B, et al. Air and noise pollution exposure in early life and mental health from adolescence to young adulthood[J]. JAMA Netw Open, 2024, 7(5): e2412169. DOI:10.1001/jamanetworkopen.2024.12169
[24] Shoari N, Blangiardo M, Pirani M. Neighborhood characteristics and mental health from childhood to adolescence[J]. JAMA Netw Open, 2025, 8(4): e254470. DOI:10.1001/jamanetworkopen.2025.4470
[25] Zeng J, Xu Y B. The impact of family socioeconomic status on depression in Chinese adolescents: a comparison of life course models[J]. J AffectDisord, 2024, 356: 97-104. DOI:10.1016/j.jad.2024.04.010
[26] Talib M,Rachdi M, Papazova A, et al. The role of dietary patterns and nutritional supplements in the management of mental disorders in children and adolescents: an umbrella review of meta-analyses[J]. Can J Psychiatry, 2024, 69(8): 567-589.
[27] Fiani D, Chahine S, Zaboube M, et al. Psychiatric and cognitive outcomes of iron supplementation in non-anemic children, adolescents, and menstruating adults: a meta-analysis and systematic review[J]. Neurosci Biobehav Rev, 2025, 178: 106372. DOI:10.1016/j.neubiorev.2025.106372
[28] 况利, 徐何雁. 从精准评估到整合干预: 儿童青少年心理健康问题诊疗范式的革新与展望[J]. 山东大学学报(医学版), 2026, 64(3): 10-16. Kuang Li, Xu Heyan. From precision assessment to integrated intervention: innovations and future perspectives in the diagnostic and therapeutic paradigm for child and adolescent mental health disorders[J]. Journal of Shandong University(Health Science), 2026, 64(3): 10-16.
[29] Zhang Q Y, Wang J, Neitzel A. School-based mental health interventions targeting depression or anxiety: a meta-analysis of rigorous randomized controlled trials for school-aged children and adolescents[J]. J Youth Adolesc, 2023, 52(1): 195-217.
[30] Piantadosi S,Byar D P, Green S B. The ecological fallacy[J]. Am J Epidemiol, 1988, 127(5): 893-904.
[31] Stevens G A, Alkema L, Black R E, et al. Guidelines for accurate and transparent health estimatesreporting: the GATHER statement[J]. Lancet, 2016, 388(10062): 19-23.
[32] Collins G S, Moons K G M, Dhiman P, et al. TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods[J]. BMJ, 2024: e078378. DOI:10.1136/bmj-2023-078378
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