A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population

Abstract

Background: Currently available tools for identifying individuals at high risk of 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 of 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 35-74 years. The diabetes risk level (DRL) was assessed by classification and regression tree (CART) analysis using four predictors: age, body mass index, waistehip 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 eight DRL and men into five DRL. The prevalence of type 2 diabetes increased with the increase in DRL in both women and men. A DRL of 6 or greater predicted type 2 diabetes status with a sensitivity of 0.61 (95% CI 0.55 to 0.67), a specificity of 0.71 (95% CI 0.70 to 0.73) in women, and a DRL of 3 or greater predicted type 2 diabetes status with a sensitivity of 0.59 (95% CI 0.52 to 0.65) and a specificity of 0.63 (95% CI 0.62 to 0.65) in men. Conclusions: This study demonstrates that application of the DRL has identified a substantial proportion of individuals with type 2 diabetes in the Chinese general population. It suggests that there is a great potential for applying the self-assessment tool in healthcare-limited settings.