Background: Current available tools for identifying individuals at high risk for type 2 diabetes can be invasive, costly and time-consuming. This study aims to develop and validate a self-assessment tool for identifying individuals at high risk for type 2 diabetes in the Chinese general population.
Methods: A cross-sectional survey was conducted from 2000 to 2001 in a nationally representative sample of 15, 540 Chinese adults aged 35 to 74 years. The diabetes risk level (DRL) was assessed by classification and regression tree (CART) analysis using four predictors: age, body mass index, waist-hip ratio (WHR) and waist circumference (WC).
Results: The significant predictors for type 2 diabetes were WHR and age for women, and WC and age for men. The categories generated by CART analysis stratified women into 8 DRLs and men into 5 DRLs. The prevalence of type 2 diabetes increased with the increasing of DRLs in both women and men. A DRL ≥ 6 predicted type 2 diabetes status with a sensitivity of 0.61 (95% confidence interval [CI]: 0.55, 0.67), specificity of 0.71 (95% CI: 0.70, 0.73) in women, and a DRL ≥ 3 predicted type 2 diabetes status with a sensitivity of 0.59 (95% CI: 0.52, 0.65), specificity of 0.63 (95% CI: 0.62, 0.65) in men.
Conclusions: This study demonstrates that application of the DRLs has identified a substantial proportion of individuals with type 2 diabetes in the Chinese general population. It suggests that there is a great potential of applying the self-assessment tool in health care limited settings.