4.6 Article

Continuous glucose monitoring reveals similar glycemic variability in individuals with obesity despite increased HOMA-IR

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FRONTIERS IN NUTRITION
卷 9, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fnut.2022.1070187

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continuous glucose monitoring; glycemic variability; insulin resistance; obesity; obesity management; HOMA-IR

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This study investigated glucose fluctuations and insulin resistance patterns in normoglycemic participants with and without obesity. The results suggest that fasting insulin and HOMA-IR values may be more clinically useful than continuous glucose monitoring data alone.
Background/aimsContinuous glucose monitoring is a well-tolerated and versatile tool for management of diabetes and metabolic disease. While its use appears to be feasible to monitor glycemic profiles in diabetics, there is a paucity of data in individuals with obesity and normal glucose tolerance. The aim of this study is to investigate glucose fluctuations and insulin resistance patterns in normoglycemic participants with obesity vs. without obesity and contextualize these results against leading models for obesity. Materials and methodsWe designed a prospective, observational pilot study of two cohorts including 14 normoglycemic participants with obesity and 14 normoglycemic participants without obesity. Participants were monitored with continuous glucose monitoring (CGM) for five consecutive days. Insulin resistance levels were measured and glucometric data were extracted from CGM for all participants. ResultsFasting serum insulin and homeostasis model assessment of insulin resistance (HOMA-IR) were significantly higher in the group with obesity (P < 0.05). While the group with obesity had a higher mean blood glucose (MBG), mean amplitude of glycemic excursions (MAGE), and continuous overall glycemic action-1 h (CONGA-1), these differences were not significant. On univariate linear regression, insulin resistance (HOMA-IR) was associated with body mass index (BMI), waist circumference (WC), cohort with obesity, cohort consuming a high glycemic diet, hemoglobin A1c (HbA1c), and fasting insulin levels. WC and fasting insulin levels remained predictors of HOMA-IR in our multivariable model. ConclusionWhile there is much excitement surrounding the use of commercial CGM products in obesity management, our results suggest that fasting insulin and HOMA-IR values may be more clinically useful than CGM data alone.

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