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Predicting depressive symptoms from sleep quality in adolescents: a longitudinal study using the XGBoost algorithm
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Yuanzhong ZHU1, Yan GUO2, Qingya YU1, Sisi KE2, Chenchang XIAO3, Yinmei YANG4, Hong YAN1, Bin YU1
Chinese Journal of Public Health | 2026, 42(9) : 1072 - 1079
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Chinese Journal of Public Health | 2026, 42(9): 1072-1079
• Epidemiological Research •
Predicting depressive symptoms from sleep quality in adolescents: a longitudinal study using the XGBoost algorithm
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Yuanzhong ZHU1, Yan GUO2, Qingya YU1, Sisi KE2, Chenchang XIAO3, Yinmei YANG4, Hong YAN1, Bin YU1
Affiliations
  • 1Department of Epidemiology and Health Statistics, School of Public Health, Wuhan University, Wuhan 430071, China
  • 2Wuhan Center for Disease Control and Prevention, Wuhan 430024, China
  • 3Department of Medicine, City University of Wuhan, Wuhan 430083, China
  • 4College of Public Health, Zhengzhou University, Zhengzhou 450052, China
Published: 2026-09-10 doi: 10.11847/zgggws1149123
Outline
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Objective

To investigate the impacts of different dimensions of sleep quality on depressive symptoms among adolescents, thus providing evidence for the prevention of depressive symptoms among adolescents.

Methods

A baseline survey was conducted from September to November 2023 for 2 373 adolescents selected by stratified cluster sampling from two junior high schools, two senior high schools, and two vocational high schools in Wuhan city. A follow-up survey was conducted from September to November 2024. The Pittsburgh Sleep Quality Index (PSQI) and the Center for Epidemiologic Studies Depression Scale (CES-D) were used for the investigation. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to screen the influencing factors, and the eXtreme Gradient Boosting (XGBoost) algorithm was adopted to construct a prediction model. The prediction performance was evaluated by the area under the curve (AUC).

Results

The detection rates of depressive symptoms among adolescents in Wuhan were 31.73% at baseline and 32.28% at the one-year follow-up. The median (interquartile range) PSQI total score was 4 (2–6). Adolescents with depressive symptoms at follow-up had higher PSQI total score (5 vs. 3), sleep latency subscale score (1 vs. 0), and daytime dysfunction subscale score (2 vs. 1) than those without depressive symptoms (all P < 0.05). LASSO regression results indicated that baseline depressive symptoms (β = 0.15), daytime dysfunction (β = 0.04), sleep latency (β = 0.02), and sleep disturbances (β = 0.02) were influencing factors for follow-up depressive symptoms. The prediction model achieved an AUC of 0.775 (95%CI: 0.739–0.812). Baseline depressive symptoms and daytime dysfunction had the greatest impacts on follow-up depressive symptoms (with contributions of 0.36 and 0.20, respectively), and their interaction effect value was 0.022 (95%CI: 0.020–0.023).

Conclusions

Daytime dysfunction is a key sleep-related risk factor for future depressive symptoms among adolescents. It interacts with baseline depressive symptoms, significantly amplifying the risk of subsequent depression.

adolescents  /  sleep quality  /  depressive symptoms  /  machine learning  /  daytime dysfunction  /  CES-D  /  Wuhan city
朱元忠, 郭燕, 余清雅, 柯思思, 肖琛嫦, 杨银梅, 燕虹, 俞斌. 青少年睡眠质量与抑郁症状关系的随访研究:基于XGBoost模型预测. 中国公共卫生, 2026 , 42 (9) : 1072 -1079 . DOI: 10.11847/zgggws1149123
Yuanzhong ZHU, Yan GUO, Qingya YU, Sisi KE, Chenchang XIAO, Yinmei YANG, Hong YAN, Bin YU. Predicting depressive symptoms from sleep quality in adolescents: a longitudinal study using the XGBoost algorithm[J]. Chinese Journal of Public Health, 2026 , 42 (9) : 1072 -1079 . DOI: 10.11847/zgggws1149123
Year 2026 volume 42 Issue 9
141
67
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Article Info
doi: 10.11847/zgggws1149123
  • Receive Date:2025-10-21
  • Online Date:2026-10-23
  • Published:2026-09-10
Article Data
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History
  • Received:2025-10-21
  • Revised:2026-01-19
  • Accepted:2026-03-30
Affiliations
    1Department of Epidemiology and Health Statistics, School of Public Health, Wuhan University, Wuhan 430071, China
    2Wuhan Center for Disease Control and Prevention, Wuhan 430024, China
    3Department of Medicine, City University of Wuhan, Wuhan 430083, China
    4College of Public Health, Zhengzhou University, Zhengzhou 450052, China

Corresponding:

YU Bin, E-mail:
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