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Updated: Jul 14, 2026

Assessment of Physical Activity Intensity with Accelerometers and Oxygen Consumption
Published on: June 20, 2025
The relationship between physical activity and metabolic syndrome risk: differential effects by exercise intensity
Woo Hyeon Son1,2, Min Seong Ha3, Yu Mi Jang4
1Institute of Design, Inje University, Gimhae, Republic of Korea.
Purpose:
Metabolic syndrome (MetS) is a major risk factor for cardiovascular disease and diabetes. However, ecological evidence regarding the differential effects of exercise intensity remains limited. In this study, we examined the associations between three types of exercise (high-intensity, moderate-intensity, and strength training) and five MetS components at the population level and developed a decision tree-based model to identify high-risk groups.
Methods:
Age group-level aggregate data (N = 150) from the National Health Screening Statistical Yearbook (2014-2023) were analyzed. Pearson's and age-adjusted partial correlations were used to assess associations between exercise frequency and the prevalence of metabolic conditions. A CART-based decision tree model was developed and evaluated using five-fold stratified cross-validation.
Results:
In simple correlation analyses, high-intensity exercise was negatively correlated with hypertension and hyperglycemia. After adjusting for age, moderate-intensity exercise was positively correlated with abdominal obesity, hypertension, and hyperglycemia, whereas strength training was positively correlated with hypertriglyceridemia and low HDL cholesterol (all p < 0.001). The decision tree model achieved an accuracy of 78.7% using high- and moderate-intensity exercise variables, which improved to 82.2% when all three exercise types were included. Under the MetS criterion (≥ 3 risk factors), accuracy reached 85.6% with a precision of 0.94.
Conclusion:
Partial correlations differed in direction from findings at the individual level, indicating a potential ecological fallacy. Nevertheless, the decision tree model demonstrated acceptable predictive performance, suggesting that exercise frequency may be a useful population-level screening indicator.
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