Predicting metabolic syndrome risk in Chinese adults using integrated features of movement behaviors and dietary intake: a machine learning approach

Machine learning provides a robust and complementary approach for capturing the complex, multi-dimensional nature of MetS risk factors. The findings highlight a conditional association between carbohydrate intake and sedentary behavior associated with metabolic risk in China's urbanizing population.