ArticleScientific reports2024
Prediction model of weight control experience in men with obesity in their 30 s and 40 s using decision tree analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Trends in AI-based diagnosis and intervention of metabolic diseases: a bibliometric analysis of the literature from 2000 to 2024.Frontiers in medicine · 2025Pooled it
- N-salicyloyl tryptamine derivative ameliorates spermatogenic dysfunction in obese mice by attenuating insulin resistance, enhancing Sertoli cell glycolysis, and inhibiting apoptosis: anFrontiers in cell and developmental biology · 2026Article
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Abstract
Obesity is an abnormal and potentially dangerous condition caused by excess body fat accumulation. The number of people with obesity is increasing worldwide. Obesity is the primary cause of various diseases; therefore, it is crucial to make efforts to control body weight. Identifying the factors that influence men with obesity to attempt to control and not control their weight is essential. The objective of this study was to create a prediction model for weight control experience among Korean men in their 30 s and 40 s. We analyzed data from the 2022 Community Health Survey and included 12,311 men who were overweight or obese. The men were divided into two groups based on their weight control experience: (1) Yes group (n = 9405) and (2) No group (n = 2906). Chi-square and independent t-tests were used to compare general and health-related characteristics between the groups. Decision tree analysis was used to build a prediction model for weight control experience. A split-sample test was conducted to validate the model. From the results of this study, various models predicting weight control experience were derived. From the decision tree model without setting the first node, those who weighed below average, had a high school diploma or less, and did not know their blood sugar levels had the highest probability of not controlling their weight at 55.3%. In the prediction model where the first node was set to age, those in their 40 s who thought their weight was below average and were unaware of their blood sugar levels had the highest rate of not trying to control their weight at 50.1%. In the prediction model where the first node was set to BMI, those who were overweight but thought their weight was below average and had a high school diploma or less had the highest rate of not trying to control their weight at 51.5%. There is an urgent need to provide obesity prevention and management education to those who have no weight control experience, particularly those at high risk, as identified in this study.
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