ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Adolescent and Young Adult Psychiatry
Volume 16 - 2025 | doi: 10.3389/fpsyt.2025.1594074
The Burden of Depressive disorder Among the Global 10-24 Age Group and the Construction of an Early Risk Factors Model
Provisionally accepted
- Third Hospital of Longyan, Longyan, China
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Objective: To understand the global trends in depression and identify potential early risk factors for its detection.This study is the first to integrate the 2021 Global Burden of Disease (GBD) data with machine learning techniques to explore the risk factors of adolescent depression. A machine learning-based model was constructed, and SHAP (SHapley Additive exPlanations) plots were utilized for interpretive analysis.Results: From 1990 to 2021, the incidence and Disability-Adjusted Life Years (DALYs) of depression continued to rise globally among the 10-24 age group, particularly in high Socio-demographic Index(SDI) regions. Greenland, the United States of America, and Palestine had the highest rates of depression globally. Among the eight machine learning models evaluated, Random Forest (RF) proved to be the most reliable. SHAP analysis revealed that elevated levels of S100β (0.330), NSE (0.060), and PLT (0.031) significantly increased the risk of depression.Our study shows an increasing trend of depression in the global 10-24 age group. Additionally, elevated S100β, NSE, and PLT are identified as key risk factors for depression.
Keywords: Depressive Disorder, machine learning, S100β, NSE, GBD
Received: 15 Mar 2025; Accepted: 27 May 2025.
Copyright: © 2025 Guo, Lu, Chen, Guo, Lai and Lu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Zhengyou Lu, Third Hospital of Longyan, Longyan, China
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