4.6 Article

Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index

Journal

PLOS ONE
Volume 18, Issue 10, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0291923

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This study found a correlation between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. Prediabetes and underweight individuals had higher GV, possibly due to irregular eating habits and low activity levels. On the other hand, overweight individuals had longer periods of elevated blood sugar, potentially due to dietary habits and lack of exercise.
BackgroundThere are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults.MethodsThis cross-sectional study was carried out within our ethics committee-approved study called Exploring the impact of nutrition advice on blood sugar and psychological status using continuous glucose monitoring (CGM) and wearable devices. Prediabetes was defined by the HbA1c level of 5.7-6.4% and /or fasting glucose level of 100-125 mg/dL. Glucose levels and daily steps were measured for 40 participants using Free Style Libre and Fitbit Inspire 2 under normal conditions for 14 days. Dietary intakes and eating behaviors were assessed using a brief-type self-administered dietary history questionnaire and a modified questionnaire from the Obesity Guidelines.ResultsResults: All indices of GV were higher in the prediabetes group than in the healthy group, but a significant difference was observed only in mean amplitude of glycemic excursions (MAGE). In the multivariate analysis, only the presence of prediabetes showed a significant association with the risk of higher than median MAGE (Odds, 6.786; 95% CI, 1.596-28.858; P = 0.010). Additionally, the underweight (BMI < 18.5) group had significantly higher value in standard deviation (23.7 +/- 3.5 vs 19.8 +/- 3.7 mg/dL, P = 0.038) and coefficient variability (22.6 +/- 4.6 vs 18.4 +/- 3.2%, P = 0.015), compared to the normal group. This GV can be partially attributed to irregularity of eating habits. On the contrary, the overweight (BMI >= 25) group had the longest time above the 140 or 180 mg/dL range, which may be due to eating style and taking fewer steps (6394 +/- 2337 vs 9749 +/- 2408 steps, P = 0.013).ConclusionsConcurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.

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