Fig. 2

Nomogram for the diagnosis of pre-sarcopenia. A All-subset regression analysis. The importance of variates was calculated as adjusted r-square value. The optimal model owns the highest adjusted r-square value. Y-axis presented the adjusted r-square value, and X-axis presented the potential predictive factors. The adjusted r-square value was calculated as the sum of colored variate, and higher adjusted r-square value means the better prediction. In this study, the adjusted r-square value of race and height was 0.25, waist circumference, race and height were 0.33. B Predictive nomogram model for pre-sarcopenia in young diabetic people. The nomogram model was based on gender, height, and waist circumference. And each predictive factor has a scoring point, the total score points of those three factors may indicate the risk of pre-sarcopenia in young diabetic people