Reproducibility of continuous glucose monitoring-derived postprandial glucose features and their association with glycemic control in type 2 diabetes
Open Access
- 17 June 2026
- journal article
- research article
- Published by Springer Nature in Nutrition & Diabetes
- Vol. 16 (1)
Abstract
Background/objectives Targeting postprandial glucose response (PPGR) is more effective than lowering fasting plasma glucose in improving glycemic control and reducing cardiovascular risk in individuals with type 2 diabetes (T2D). Continuous glucose monitoring (CGM) has the potential to uncover time-related features of PPGR. This study evaluates the within-subject reproducibility of dynamic PPGR parameters obtained by CGM and explores their potential as independent predictors of glycemic control in T2D. Subjects/methods A total of 102 individuals with T2D underwent a 7-day CGM and consumed a standardized breakfast twice to assess the 4-h glucose response, described by the following parameters: glucose peak—the highest glucose value; time to peak—time of peak occurrence; delta glucose max—the difference between the peak and fasting glucose; nadir—the lowest post-peak glucose value; incremental area under the glucose curve; mean postprandial glucose—the average interstitial glucose concentration. Intraclass correlation coefficients (ICCs) for both single and average measurements with their 95% confidence intervals (CIs), were calculated for PPGR parameters to estimate their within-subject reproducibility. Multivariable linear regression models assessed the independent predictive contribution of PPGR parameters, fasting glucose, and 2-h postprandial glucose on 7-day CGM metrics and HbA1c. Results Moderate to good reproducibility for single measurements was observed for mean glucose (ICC: 0.78, 95%CI 0.69–0.84), glucose peak (ICC: 0.69, 95% CI 0.57–0.78), and nadir (0.74, 95% CI 0.64–0.82). Mean postprandial glucose was the strongest predictor of 7-day time in range (β = −0.772, p < 0.001), 7-day mean glucose (β = 0.800, p < 0.001) and HbA1c (β = 0.434, p < 0.001), whereas the glucose peak was the main predictor of short-term glycemic variability, as reflected by the 7-day coefficient of variation (β = 0.258, p = 0.006) and mean amplitude of glucose excursions (β = 0.613, p < 0.001). Conclusion In individuals with T2D, CGM-derived parameters of PPGR are reproducible and could represent a practical tool to uncover meaningful information about glucose control, which 2-h postprandial glucose fails to predict.Keywords
This publication has 27 references indexed in Scilit:
- Enhancing Type 2 Diabetes Care With CGM Integration: Insights From an Italian Expert GroupDiabetes/Metabolism Research and Reviews, 2025
- Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021The Lancet, 2023
- Reproducibility and determinants of the metabolic responses during a mixed‐meal tolerance testObesity, 2023
- Human postprandial responses to food and potential for precision nutritionNature Medicine, 2020
- Glycaemic variability in diabetes: clinical and therapeutic implicationsThe Lancet Diabetes & Endocrinology, 2019
- Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variablesThe Lancet Diabetes & Endocrinology, 2018
- Atherogenicity of postprandial hyperglycemia and lipotoxicityReviews in Endocrine and Metabolic Disorders, 2016
- Postprandial and basal hyperglycaemia in type 2 diabetes: Contributions to overall glucose exposure and diabetic complicationsDiabetes & Metabolism, 2015
- Personalized Nutrition by Prediction of Glycemic ResponsesCell, 2015
- Activation of Oxidative Stress by Acute Glucose Fluctuations Compared With Sustained Chronic Hyperglycemia in Patients With Type 2 DiabetesJAMA, 2006