A risk assessment model for type 2 diabetes in Chinese.

Abstract

To develop a risk assessment model for persons at risk from type 2 diabetes in Chinese. The model was generated from the cross-sectional data of 16246 persons aged from 20 years old and over. C4.5 algorithm and multivariate logistic regression were used for variable selection. Relative risk value combined with expert decision constructed a comprehensive risk assessment for evaluating the individual risk category. The validity of the model was tested by cross validation and a survey performed six years later with some participants. Nine variables were selected as risk variables. A mathematical model was established to calculate the average probability of diabetes in each cluster's group divided by sex and age. A series of criteria combined with relative RR value (2.2) and level of risk variables stratified individuals into four risk groups (non, low, medium and high risk). The overall accuracy reached 90.99% evaluated by cross-validation inside the model population. The incidence of diabetes for each risk group increased from 1.5 (non-risk group) to 28.2(high-risk group) per one thousand persons per year with six years follow-up. The model could determine the individual risk for type 2 diabetes by four risk degrees. This model could be used as a technique tool not only to support screening persons at different risk, but also to evaluate the result of the intervention.