Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China

Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China

Abstract Background Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiovascular system, chronic kidney disease, and metabolic risk factors. In China, the prevalence of CKM in middle-aged and elderly patients is rela...

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Bibliographic Details
Main Authors: Xinyi Xu, Xinru Li, Xiyan Li, Benli Xue, Xiao Zheng, Shujuan Xiao, Lingli Yang, Xinyi Zhang, Chengyu Chen, Ting Zheng, Yuyang Li, Yanan Wang, Jianan Han, Haoran Wu, Mengjie Zhang, Yanming Liao, Siyi Bai, Nan Zeng, Chichen Zhang
Format: Article
Language:English
Published: BMC 2025-06-01
Series:Journal of Health, Population and Nutrition
Subjects:
Cardiovascular-Kidney-Metabolic syndrome
Random forest
Mediation analysis
Health management
Online Access:https://doi.org/10.1186/s41043-025-00897-0
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