Investigating the role of depression in obstructive sleep apnea and predicting risk factors for OSA in depressed patients: machine learning-assisted evidence from NHANES
In conclusion, our research indicates that depression is associated with OSA, highlighting the importance of early detection and management of depressive symptoms in individuals at risk of OSA.ML models were developed to predict OSA and were interpreted using SHAP. This method identified key factors associated with OSA, encompassing demographic, dietary, and health-related dimensions.
Authors
- Diansan Su (ORCID: https://orcid.org/0000-0001-9755-1025)
- Xuelai Zhong
- Xuwu Xiang
- Yong-Xing Yao (ORCID: https://orcid.org/0000-0002-5458-8298)
- Dong-Dong Tian
- Xiangyang Cheng (ORCID: https://orcid.org/0009-0001-7956-8701)
- Aijie Pei
- Xiao Chi Zhang (ORCID: https://orcid.org/0000-0002-0103-9594)
- Ye Liu (ORCID: https://orcid.org/0000-0003-1536-706X)
- Jiayi Guo (ORCID: https://orcid.org/0009-0004-9601-5887)
- Fang Liu (ORCID: https://orcid.org/0000-0002-5379-8816)
Institutions
- First Affiliated Hospital Zhejiang University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- BMC Psychiatry
- Published
- 2025-10-10
- DOI
- https://doi.org/10.1186/s12888-025-07414-x
- Citations
- 1
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 1.16
Funders
- Shanghai Municipal Health Commission
- National Natural Science Foundation of China
- Zhejiang University
- Natural Science Foundation of Zhejiang Province