Abstract
The aim of this study is to quantitatively analyze the influence of risk factors on the blood glucose level, and to provide theory basis for understanding the characteristics of blood glucose change and confirming the intervention index for type 2 diabetes. The quantitative method is proposed to analyze the influence of risk factors on blood glucose using back propagation (BP) neural network. Ten risk factors are screened first. Then the cohort is divided into nine groups by gender and age. According to the minimum error principle, nine BP models are trained respectively. The quantitative values of the influence of different risk factors on the blood glucose change can be obtained by sensitivity calculation. The experiment results indicate that weight is the leading cause of blood glucose change (0.2449). The second factors are cholesterol, age and triglyceride. The total ratio of these four factors reaches to 77% of the nine screened risk factors. And the sensitivity sequences can provide judgment method for individual intervention. This method can be applied to risk factors quantitative analysis of other diseases and potentially used for clinical practitioners to identify high risk populations for type 2 diabetes as well as other disease.