LAUSR

To develop a noninvasive screening tool for diagnosing type 2 diabetes among young and middle-aged people in Chinese community. In total, 1432 participants without diabetes diagnosis were enrolled from Chinese communities. Diabetes was defined as fasting plasma glucose (FPG) ≥ 126 mg/dL (≥ 7.0 mmol/L) or glycated hemoglobin (HbA1c) ≥ 6.5%. The noninvasive diabetes screening model score was developed using the coefficients of the final multivariable logistic regression model. Undiagnosed diabetes was detected using a receiver-operating characteristic curve and the area under the curve (AUC). Of the 1432 participants, 142 (9.9%) were newly diagnosed with diabetes through FPG or HbA1c, 67 (4.7%) through FPG alone, and 121 (8.4%) through HbA1c alone. The noninvasive diabetes screening model was developed using significant risk factors, namely age, family history of diabetes, hypertension, waist circumference, body mass index, smoking, daily consumption of vegetables, and daily consumption of fruits. The cutoff score of 22.5 was the optimum to detect undiagnosed diabetes with an AUC of 0.758 (95% confidence interval 0.714–0.803), sensitivity of 83.1%, and specificity of 60.0%. We developed a practical and effective noninvasive screening tool for detecting undiagnosed diabetes among young and middle-aged people in Chinese community.