Biological vs. Chronological Overnight Fasting: Influence of Last Evening Meal on Morning Glucose in Dysglycemia
Diana A Diaz-Rizzolo1,2, Haley Yao1, Leinys S Santos-Báez1
1Division of Endocrinology, Diabetes Research Center, Columbia University Irving Medical Center, New York, NY 10032, USA.
Abstract:
Background/Objectives: Nocturnal glucose regulation is a critical but underexplored determinant of next-day fasting glucose (FG), particularly in individuals with dysglycemia. This study examined the role of glucose levels after the last eating occasion (LEO) and during the overnight fast in predicting FG, considering the potential influence of carbohydrate content in LEO and insulin sensitivity. Methods: In a controlled 24 h protocol, 33 adults (50-75 years) with prediabetes or diet-controlled type 2 diabetes followed a standardized feeding schedule with meals at fixed times, including a LEO at 10:00 p.m. Continuous glucose monitoring was used to assess glucose during the 3 h postprandial period (LEO-PPGR) and two fasting intervals: chronological overnight fast (COF) and biological overnight fast (BOF). Associations with FG were tested using general linear models, adjusting for carbohydrate intake and insulin sensitivity (Matsuda index). Results: Glucose responses during LEO-PPGR-assessed by mean glucose, peak, and AUC-were strongly correlated with FG the next morning (r = 0.704, 0.535, and 0.708, p < 0.001). Similarly, glucose levels during COF and BOF were also correlated with FG (r = 0.878, p < 0.001 for both), but these associations weakened after adjustment for LEO carbohydrate content. The Matsuda index was positively correlated with glucose in all three periods (p < 0.05), yet its inclusion in the model attenuated all previously significant associations with FG. Conclusions: These findings suggest that the glycemic response to the last meal and subsequent overnight glucose levels contribute to next-day FG, but their impact is modulated by carbohydrate content and individual insulin sensitivity. Understanding nocturnal glycemic dynamics may inform strategies for improving metabolic outcomes in dysglycemia.
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