The northeast glucose drift: Stratification of post-breakfast dysglycemia among predominantly Hispanic/Latino adults at-risk or with type 2 diabetes.

Barua, Souptik; Sabharwal, Ashutosh; Glantz, Namino; Conneely, Casey; Larez, Arianna; Bevier, Wendy; Kerr, David · EClinicalMedicine · 2022

prospective_cohort · Level II

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Abstract

There is minimal experience in continuous glucose monitoring (CGM) among underserved racial/ethnic minority populations with or at risk of type 2 diabetes (T2D), and therefore a lack of CGM-driven insight for these individuals. We analyzed breakfast-related CGM profiles of free-living, predominantly Hispanic/Latino individuals at-risk of T2D, with pre-T2D, or with non-insulin treated T2D. Starting February 2019, 119 participants in Santa Barbara, CA, USA, (93 female, 87% Hispanic/Latino [predominantly Mexican-American], age 54·4 [±12·1] years), stratified by HbA<sub>1c</sub> levels into (i) at-risk of T2D, (ii) with pre-T2D, and (iii) with non-insulin treated T2D, wore blinded CGMs for two weeks. We compared valid CGM profiles from 106 of these participants representing glucose response to breakfast using four parameters. A "northeast drift" was observed in breakfast glucose responses comparing at-risk to pre-T2D to T2D participants. T2D participants had a significantly higher pre-breakfast glucose level, glucose rise, glucose incremental area under the curve (all <i>p</i> < 0·0001), and time to glucose peak (<i>p</i> < 0·05) compared to pre-T2D and at-risk participants. After adjusting for demographic and clinical covariates, pre-breakfast glucose and time to peak (<i>p</i> < 0·0001) were significantly associated with HbA<sub>1c</sub>. The model predicted HbA<sub>1c</sub> within (0·55 <math xmlns="http://www.w3.org/1998/Math/MathML"><mo>±</mo></math> 0·67)% of true laboratory HbA<sub>1c</sub> values. For predominantly Hispanic/Latino adults, the average two-week breakfast glucose response shows a progression of dysglycemia from at-risk of T2D to pre-T2D to T2D. CGM-based breakfast metrics have the potential to predict HbA<sub>1c</sub> levels and monitor diabetes progression. US Department of Agriculture (Grant #2018-33800-28404), a seed grant from the industry board fees of the NSF Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (Award #1648451), and the Elsevier foundation.