Identifying individuals at risk of type 2 diabetes using risk assessment tools: an overview

Abstract

Diabetes is a chronic disorder that arises mainly due to unhealthy lifestyles in genetically susceptible individuals and has affected over 460 million people worldwide. Hence, alternative ways of identifying individuals at risk for developing diabetes are needed. Risk assessment tools can be useful for identifying and segmenting those at higher risk. The goal of this article is to assess various diabetes risk models that have been established in general populations to predict future diabetes, and to compare the technology behind their development and validation. PubMed, Google Scholar and Scopus were searched from inception to 10th November 2021. Studies that reported the use of risk assessment tools to identify individuals at risk of diabetes were included. Of the 9045 articles identified, 28 were included. This study includes six diabetes risk assessment tools, all of which were developed using logistic regression analysis. The most commonly included variables were age and a family history of diabetes. All six tools were subjected to external validation. The risk scores exhibited an overall strong predictive capacity for the population it was developed. However, the external populations had a lower discriminatory performance, implying that risk scores may need to be verified within the group in which they are meant to be utilised. Further, developing the risk tools using modifiable diabetes risk factors and biochemical tests can be more useful for predicting future diabetes.