Predictive models of post‐prandial glucose response in persons with prediabetes and early onset type 2 diabetes: A pilot study

Abstract Objective Post‐prandial glucose response (PPGR) is a risk factor for cardiovascular disease. Meal carbohydrate content is an important predictor of PPGR, but dietary interventions to mitigate PPGR are not always successful. A personalized approach, considering behaviour and habitual pattern of glucose excursions assessed by continuous glucose monitor (CGM), may be more effective. Research Design and Methods Data were collected under free‐living conditions, over 2 weeks, in older adults (age 60 ± 7, BMI 33.0 ± 6.6 kg/m 2 ), with prediabetes ( n = 35) or early onset type 2 diabetes ( n = 3), together with sleep and physical activity by actigraphy. We assessed the predictive value of habitual CGM glucose excursions and fasting glucose on PPGR after a research meal (hereafter MEAL‐PPGR) and during an oral glucose tolerance test (hereafter OGTT‐PPGR). Results Mean amplitude of glucose excursions (MAGE) and fasting glucose were highly predictive of all measures of OGTT‐PPGR (AUC, peak, delta, mean glucose and glucose at 120 min; R 2 between 0.616 and 0.786). Measures of insulin sensitivity and β‐cell function (Matsuda index, HOMA‐B and HOMA‐IR) strengthened the prediction of fasting glucose and MAGE ( R 2 range 0.651 to 0.832). Similarly, MAGE and premeal glucose were also strong predictors of MEAL‐PPGR ( R 2 range 0.546 to 0.722). Meal carbohydrates strengthened the prediction of 3 h AUC ( R 2 increase from 0.723 to 0.761). Neither anthropometrics, age nor habitual sleep and physical activity added to the prediction models significantly. Conclusion These data support a CGM‐guided personalized nutrition and medicine approach to control PPGR in older individuals with prediabetes and diet and/or metformin‐treated type 2 diabetes.