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

Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Original Publication: San Francisco, CA : Public Library of Science

Prediabetic State* ; Diabetes Mellitus, Type 2*; Adult ; Humans ; Blood Glucose/analysis ; Body Mass Index ; Blood Glucose Self-Monitoring ; Cross-Sectional Studies ; Glycated Hemoglobin ; Life Style

Background: There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults.
Methods: This 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.
Results: 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).
Conclusions: Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.
Competing Interests: The Institutional ethics committees approving thi original study comply with the Declaration of Helsinki. The identity of the patient has been protected. The authors also declared the following potential conflicts of interest: KK, SK, and TK have been members of Hills Joint Research Laboratory for Future Preventive Medicine and Wellness, supported by Mori Building Co., Ltd. The sponsor had no control over the interpretation, writing, or publication of this study. This does not alter our adherence to PLOS ONE policies on sharing data and materials
(Copyright: © 2023 Kashiwagi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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0 (Blood Glucose)
0 (Glycated Hemoglobin)

Date Created: 20231004 Date Completed: 20231101 Latest Revision: 20231102

20231215

PMC10550127

10.1371/journal.pone.0291923

37792730