A predictive model for metabolic syndrome in a community-based population with sleep apnea: a secondary prevention screening tool using simple and accessible indicators
This study successfully developed a MetS prediction model based on community environment. The model relies solely on simple, easily obtainable self-reported indicators and demonstrates good predictive performance. This model, as a primary screening tool, enables residents to assess their MetS risk status independently, without relying on complex biochemical tests or the assistance of specialized medical personnel.
Authors
- Yaoda Hu (ORCID: https://orcid.org/0000-0002-3713-3208)
- Huijing He (ORCID: https://orcid.org/0000-0002-2922-752X)
- Guangliang Shan (ORCID: https://orcid.org/0000-0002-4535-8941)
- Tong Feng (ORCID: https://orcid.org/0000-0003-3037-783X)
- Q. Ou (ORCID: https://orcid.org/0000-0003-4821-4828)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Deyang Stomatological Hospital (CN)
- Guangdong Academy of Medical Sciences (CN)
Publication Details
- Journal
- Frontiers in Nutrition
- Published
- 2025-11-05
- DOI
- https://doi.org/10.3389/fnut.2025.1667055
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China