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Background <p>Weight-control behaviors are critical for managing metabolic syndrome (MetS); however, their influencing factors remain complex. This study aimed to identify key predictors of weight-control behavior in individuals with MetS.</p> Methods <p>A cross-sectional study design was employed. A secondary data analysis of 1282 adults with MetS was conducted using data from the 2022 Korea National Health and Nutrition Examination Survey. Univariate, logistic regression, and decision tree modeling was employed to explore the hierarchical predictors of self-reported weight-control efforts.</p> Results <p>Dietary therapy participation was the most significant predictor for engaging in weight control. Within each therapy stratum, body-image perception, alcohol consumption, and nutrition label awareness further differentiated the behavior. Perception of being overweight and nutrition label awareness were associated with higher engagement, whereas high-risk drinking was associated with lower engagement in weight control. The model exhibited a classification accuracy of 70.5% (area under the curve = 0.69).</p> Conclusion <p>Weight-control behaviors in individuals with MetS are influenced by structured interventions, self-perceived body image, and nutritional literacy. Tailored strategies that incorporate these factors may enhance behavioral engagement.</p>

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Weight-control behavior in individuals with metabolic syndrome: a decision tree model

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月21日

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  • Geumbo Ko,
  • Myoungjin Kwon,
  • Youngshin Song

摘要

Background

Weight-control behaviors are critical for managing metabolic syndrome (MetS); however, their influencing factors remain complex. This study aimed to identify key predictors of weight-control behavior in individuals with MetS.

Methods

A cross-sectional study design was employed. A secondary data analysis of 1282 adults with MetS was conducted using data from the 2022 Korea National Health and Nutrition Examination Survey. Univariate, logistic regression, and decision tree modeling was employed to explore the hierarchical predictors of self-reported weight-control efforts.

Results

Dietary therapy participation was the most significant predictor for engaging in weight control. Within each therapy stratum, body-image perception, alcohol consumption, and nutrition label awareness further differentiated the behavior. Perception of being overweight and nutrition label awareness were associated with higher engagement, whereas high-risk drinking was associated with lower engagement in weight control. The model exhibited a classification accuracy of 70.5% (area under the curve = 0.69).

Conclusion

Weight-control behaviors in individuals with MetS are influenced by structured interventions, self-perceived body image, and nutritional literacy. Tailored strategies that incorporate these factors may enhance behavioral engagement.