653-P: Post-Breakfast Glycemic Profiles in Hispanic/Latino Adults with or at Risk of Type 2 Diabetes

Abstract

Hispanic/Latinos in the U.S. bear an excess burden of type 2 diabetes (T2D) . In type 1 diabetes and insulin-treated T2D, continuous glucose monitoring (CGM) is an established technology to guide therapy, yet CGM use and studies are rare in people with/at-risk of non-insulin treated T2D and ethnic minorities. In this study, CGM was used to assess breakfast glycemic response in free-living adults with or at risk of non-insulin treated T2D. For 9-14 days, 35 Hispanic/Latino adults (28 female, median HbA1c 6.0% [IQR 5.5%, 6.8%]) wore blinded Abbott Freestyle Libre CGM and logged food via the MyFitnessPal app. Start and peak time of glycemic responses associated with a glucose rise ≥20 mg/dL between 5-a.m. were manually annotated. Median variation between annotated and logged time was 39 [20, 78] minutes. Participants were stratified using HbA1c into at risk for T2D, pre-T2D, and T2D. Median starting glucose (SG) ; maximum glucose rise (Max GR) ; time-to-peak (TTP) ; and incremental area under the curve over 2, 3, and 4 hours (iAUC2hr, iAUC3hr, iAUC4hr) were computed (Table 1) . The T2D group had significantly higher post-breakfast glycemic measures than the at-risk group for all measures. The T2D group also had higher measures than pre-T2D for all but Max GR. Increases in response from at-risk to pre- to T2D in Hispanic/Latino adults suggest post-breakfast glycemic profiles may potentially be used to monitor diabetes progression. Disclosure A.Pai: Employee; Apple. R.F.Santiago: Research Support; Abbott. W.C.Bevier: Research Support; Abbott Diabetes. N.M.Glantz: Research Support; Abbott. S.Barua: None. A.Sabharwal: None. D.Kerr: Advisory Panel; Abbott Diabetes, Novo Nordisk A/S, Sanofi, Consultant; Evidation Health, Research Support; Novo Nordisk A/S, Stock/Shareholder; Glooko, Inc., Hi.Health. Funding Elsevier Foundation

Technology and health inequities in diabetes care: How do we widen access to underserved populations and utilize technology to improve outcomes for all?

“…Because diabetes outcomes are impacted by multiple factors, including physical activity, diet, and medications, any insights and storytelling must account for all factors relevant to the user. Recent work has demonstrated the ability to extract patterns from user data that take complex streams of data and convert them into relevant bio‐behavioural information for the users, 21 for example, helping users decide on how much postprandial physical activity will lead to desirable mealtime glycaemic outcomes. Recommendation : New data summarization and storytelling techniques should be tested in PWD (and those with prediabetes) to determine the ability of this approach to reach diverse populations at their health literacy levels and present culturally appropriate, actionable information.…”