Stratified analysis of the age-related waist circumference cut-off model for the screening of dysglycemia at zero-cost

Aims: We perform a stratified analysis of the recently published age-related waist circumference cut-off model to validate its performance in the screening of dysglycemia in the US population. Methods: We use NHANES data as representative of the US population. Data were subdivided into sex, ethnic and glycemia groups. We evaluate the performance of the model separately in each group through the AUC. We also discuss the calibration of the model. Results: For the sex-stratified analysis, we obtain AUC = 0.69–0.71 (95% C.I.) for male individuals and AUC = 0.75–0.78 (95% C.I.) for female individuals. The stratified analysis is performed in different ethnic groups, namely “Mexican American”, “Other Hispanic”, “Non-Hispanic White”, “Non-Hispanic Black” and “Other Race – Including Multi-Racial. We obtain, respectively, AUC = 0.74–0.75, AUC = 0.76–0.78, AUC = 0.73–0.75, AUC = 0.74–0.77 and AUC = 0.71–0.73 (95% C.I.). The model achieves AUC = 0.70–0.73 (95% C.I.) in the identification of individuals with prediabetes and AUC = 0.70–0.80 (95% C.I.) in the identification of individuals with diabetes. Conclusions: The accuracy of the model turns out to be similar in each group considered in the stratified analysis, indicating that the model is suitable to be used as a screening tool for dysglycemia in the US population.