| Summary: | Diabetes is an increasing problem worldwide; almost 30 million people, nearly 10\% of the population, in the United States are diagnosed with diabetes. Another 86 million are estimated to be pre-diabetic and up to 70\% of these individuals are estimated to develop diabetes without intervention. We have used continuous glucose monitoring to investigate the frequency with which people have aberrant glucose control patterns, the types of patterns, and how these patterns are affected by nutrition. We developed an analytical framework for defining glucose variability that can group individuals into specific classes. We found a high incidence of glucose variability, particularly in response to certain foods, regardless of diagnosis. We find that variability is more common in the evening and post meals in pre-diabetics before becoming more continuous in diabetics. This variability appears earlier than clinical diagnosis of pre-diabetes and we find that it shows promise for predicting insulin resistance in a standardized setting. This study provides evidence that classification of glycemic signatures by variability shows promise for early intervention and personalized treatment of diabetes. Applying this metric in treatment and diagnosis will be critical in reducing the risk and prevalence of diabetes
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