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.

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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
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article

Construction and validation of a risk prediction model for metabolic syndrome: a cross-sectional study based on randomized sampling

Xinhua An, L. D. Liu, Jiannan Zhao, Ling Liu et al.
Frontiers in Endocrinology
Diabetes, Cardiovascular Risks, and Lipoproteins
article

Construction and validation of a risk prediction model for metabolic syndrome: a cross-sectional study based on randomized sampling

Xinhua An, L. D. Liu, Jiannan Zhao, Ling Liu, Jia Meng, Yongliang Mu
article en

Abstract

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.

Frontiers in EndocrinologyVol. 16
Tianjin First Center Hospital (CN), Beijing Shijingshan Hospital (CN), Tianjin Medical University (CN)
Openalex Percentile: Top 87%
Diabetes, Cardiovascular Risks, and Lipoproteins
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