CGMap: Characterizing continuous glucose monitor data in thousands of non-diabetic individuals

Despite its rising prevalence, diabetes diagnosis still relies on measures from blood tests. Technological ad-vances in continuous glucose monitoring (CGM) devices introduce a potential tool to expand our understanding of glucose control and variability in people with and without diabetes. Yet CGM data have not been character-ized in large-scale healthy cohorts, creating a lack of reference for CGM data research. Here we present CGMap, a characterization of CGM data collected from over 7,000 non-diabetic individuals, aged 40-70 years, between 2019 and 2022. We provide reference values of key CGM-derived clinical measures that can serve as a tool for future CGM research. We further explored the relationship between CGM-derived measures and diabetes -related clinical parameters, uncovering several significant relationships, including associations of mean blood glucose with measures from fundus imaging and sleep monitoring. These findings offer novel research direc-tions for understanding the influence of glucose levels on various aspects of human health.

Automated summary

Despite the increasing prevalence of diabetes, its diagnosis still relies on blood tests. Continuous glucose monitoring (CGM) devices provide a potential tool to better understand glucose control and variability in individuals with and without diabetes. This study presents CGMap, the characterization of CGM data collected from over 7,000 non-diabetic individuals, aged 40-70 years, between 2019 and 2022. The study provides reference values for key CGM-derived clinical measures and explores the relationship between CGM-derived measures and diabetes-related clinical parameters, revealing novel research directions for understanding the influence of glucose levels on various aspects of human health.