Risk scores for predicting incidence of type 2 diabetes in the Chinese population: the Kailuan prospective study

Few risk scores have been specifically developed to identify individuals at high risk of type 2 diabetes in China. In the present study, we aimed to develop such risk scores, based on simple clinical variables. We studied a population-based cohort of 73,987 adults, aged 18 years and over. After 5.35 ± 1.59 years of follow-up, 4,726 participants (9.58%) in the exploration cohort developed type 2 diabetes and 2,327 participants (9.44%) in the validation cohort developed type 2 diabetes. Age, gender, body mass index, family history of diabetes, education, blood pressure, and resting heart rate were selected to form the concise score with an area under the receiver operating characteristic curve (AUC) of 0.67. The variables in the concise score combined with fasting plasma glucose (FPG), and triglyceride (TG) or use of lipid-lowering drugs constituted the accurate score with an AUC value of 0.77. The utility of the two scores was confirmed in the validation cohort with AUCs of 0.66 and 0.77, respectively. In summary, the concise score, based on non-laboratory variables, could be used to identify individuals at high risk of developing diabetes within Chinese population; the accurate score, which also uses FPG and TG data, is better at identifying such individuals.