September 12, 2025Frontiers in NutritionOpen Access

Risk factors analysis and prediction models of obesity in college students based on dietary patterns

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Cross-sectional analysis identifies dietary patterns impacting obesity risk in college students, suggesting effective screening methods.

The developed PBF-based nomogram model achieved an area under the curve of 0.805, indicating good predictive ability.
Key predictors of obesity in the study include dietary patterns like vegetable meat grain, physical activity, and late-night snacking.
Application of principal component analysis and logistic regression helped identify significant dietary patterns associated with obesity risk.
The study highlights a pressing public health concern regarding obesity prevalence among college students, emphasizing comprehensive evaluation methods.

Bai et al. (2025) studied this question.

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September 12, 2025Frontiers in NutritionOpen Access

View Full Paper

Ask AI

Bookmark

Authors

Cross-sectional analysis identifies dietary patterns impacting obesity risk in college students, suggesting effective screening methods.

The developed PBF-based nomogram model achieved an area under the curve of 0.805, indicating good predictive ability.
Key predictors of obesity in the study include dietary patterns like vegetable meat grain, physical activity, and late-night snacking.
Application of principal component analysis and logistic regression helped identify significant dietary patterns associated with obesity risk.
The study highlights a pressing public health concern regarding obesity prevalence among college students, emphasizing comprehensive evaluation methods.

Bai et al. (2025) studied this question.

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