ArticlePloS one2023
Assessment of glycemic variability and lifestyle behaviors in healthy nondiabetic individuals according to the categories of body mass index.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Inflammatory markers and blood glucose are higher after morning vs afternoon exercise in type 2 diabetes.Diabetologia · 2025Trial
- Cruciferous vegetables improve glycaemic control compared to root/squash vegetables in a randomized, controlled, crossover trial: The VEgetableS for vaScular hEaLth (VESSEL) study.Diabetes, obesity & metabolism · 2025Trial
- Mulberry leaf extract combined with tryptophan improves sleep and post wake mood in adults with sleep complaints - A randomized cross-over study.European journal of nutrition · 2025Trial
- The Effect of Hunger on the Likelihood of Glucose Excursions in Adults with Overweight or Obesity: Continuous Glucose Monitoring and Ecological Momentary Assessment Observational Study.JMIR formative research · 2026Observational
- Differences in Continuous Glucose Monitoring Metrics Between Prediabetes and Normoglycemia: A Systematic Review and Meta-Analysis.Journal of diabetes science and technology · 2026Review
- Risk of Hypoglycemia and Associated Factors Among In-Hospital Chinese Patients With Latent Autoimmune Diabetes in Adults (LADA): A Multicenter Retrospective Cohort Study.Journal of diabetes research · 2026Article
- Continuous Glucose Monitoring Metrics in Asians Without Diabetes: Differentiating Prediabetes From Normoglycemia.Journal of diabetes science and technology · 2025Article
- Continuous Glucose Monitoring for Prediabetes: What Are the Best Metrics?Journal of diabetes science and technology · 2024Review
- Assessment of Stress and Well-Being of Japanese Employees Using Wearable Devices for Sleep Monitoring Combined With Ecological Momentary Assessment: Pilot Observational Study.JMIR formative research · 2024Article
- Associations between glycemic variability, sleep quality, and daily steps in subjects without diabetes using wearable devices.Metabolism open · 2023Article
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
resultsAll 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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.