Construction and validation of a risk prediction model for metabolic syndrome: a cross-sectional study based on randomized sampling
The metabolic syndrome column-line diagram risk prediction model constructed in this study, based on multivariate logistic regression analysis, has good discriminative ability and high prediction accuracy. The model shows that a large proportion of the current risk factors for metabolic syndrome are modifiable, and that the risk of metabolic syndrome in high-risk groups, such as the elderly, men, people with marital/cohabitation histories, and people with specific occupations, can be reduced through behavioral and lifestyle interventions. This model can provide a scientific basis for the early identification of high-risk groups for metabolic syndrome and has an important guiding value for targeted preventive interventions.
Authors
- Xinhua An
- L. D. Liu
- Jiannan Zhao
- Ling Liu
- Jia Meng
- Yongliang Mu
Institutions
- Tianjin First Center Hospital (CN)
- Beijing Shijingshan Hospital (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Frontiers in Endocrinology
- Published
- 2026-01-16
- DOI
- https://doi.org/10.3389/fendo.2025.1761342
- Primary Topic
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Type
- article
- Field-Weighted Citation Impact
- 0.00