Development Of Sex-Specific Risk Score Models For Diabetes Among Urban Chinese

The present study aimed to derivate and validate score models to predict the risk of diabetes among urban Chinese men and women. Participants included 26,600 men (47.64 +/- 7.86 years) and 9,600 women (47.89 +/- 8.30 years), and were respectively divided into derivation and validation cohorts. Multivariate logistic regression analysis was used to select and weigh variables in the derivation cohorts. The validity of the models was tested by the area under the receiver operating characteristic curve (AUC) in validation cohorts, and compared with the Chinese Diabetes Risk Score (CDRS) and Finnish Diabetes Risk Score (FINDRISC) models. Both male and female mathematical models were established to calculate the diabetes risk-score in urban Chinese. The estimated AUC for the male model was 0.920 (95% CI 0.909-0.930) at a cut-off point of >1871. The performance of the male model was superior to the CDRS and FINDRISC models. The estimated AUC for the female model was 0.924 (95% CI 0.905-0.940) at a cut-off point of >2127. The performance of the female model was superior to the CDRS, but slightly inferior to the FINDRISC. The male and female models could help determine individuals at high risk of diabetes in the urban Chinese population.