Development and validation of a predictive model for depression risk in Chinese obese adults

The model constructed in this study has good efficacy in predicting the occurrence of depression in the obese population and can be used for the early identification of high-risk groups and the adoption of targeted preventive measures to reduce the risk of depression.

Authors

Institutions

Publication Details

Journal
Frontiers in Public Health
Published
2025-05-14
DOI
https://doi.org/10.3389/fpubh.2025.1574386
Citations
2
Primary Topic
Cardiac Health and Mental Health
Type
article
Field-Weighted Citation Impact
2.78
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and validation of a predictive model for depression risk in Chinese obese adults

Wenguang Chen, Jing Cao, Cong Yu, Ensi Hong
2 citations
Frontiers in Public Health
Cardiac Health and Mental Health
2.78
article

Development and validation of a predictive model for depression risk in Chinese obese adults

Wenguang Chen, Jing Cao, Cong Yu, Ensi Hong
article en
2 citations

Abstract

The model constructed in this study has good efficacy in predicting the occurrence of depression in the obese population and can be used for the early identification of high-risk groups and the adoption of targeted preventive measures to reduce the risk of depression.

Frontiers in Public HealthVol. 13
Jiangxi University of Traditional Chinese Medicine (CN), Nanchang Normal University (CN), Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine (CN), Jiangxi Normal University (CN)
Openalex Percentile: Top 10%
Cardiac Health and Mental Health
2.78
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.