New risk-scoring system including non-alcoholic fatty liver disease for predicting incident type 2 diabetes in East China: Shanghai Baosteel Cohort

Abstract

Aims/Introduction: The present study aimed to explore the incidence of type 2 diabetes, and to develop a risk-scoring model for predicting diabetes among the adult health check-up population in East China. Materials and Methods: Participants from the Shanghai Baosteel Cohort (age ≥20 years) without diabetes at baseline were recruited in a 6-year follow-up study. In order to explore risk factors for diabetes, this cohort was categorized into two groups: new diabetes and no diabetes. Three models were developed by Cox regression analysis. The model accuracy was assessed using the area under the receiver operating characteristic curve. Results: A total of 6,542 individuals were included in the Shanghai Baosteel Cohort Study. Of them, 368 (5.6%) developed type 2 diabetes at the end of the follow-up period. Cox regression analysis found a close association between incident type 2 diabetes and several risk factors including non-alcoholic fatty liver diseases at baseline. The Shanghai Baosteel Score including advanced age (2 points), hypertriglyceridemia (2 points), obesity (2 points), non-alcoholic fatty liver diseases (2 points) and impaired fasting glucose (3 points) had a good diagnostic performance with estimated area under the receiver operating characteristic curve (0.724), sensitivity (57.9%) and specificity (72.2%) at a cut-off point of >3. Conclusions: A risk-scoring system including non-alcoholic fatty liver diseases can help identify individuals at a high risk of diabetes in the East Chinese population. It is a large-scale prospective cohort study, we established a new simple score system including NAFLD which can predict the onset of type 2 diabetes in China.