Daily eating window duration and dietary intake shape 24-hour glycemic patterns in type 2 diabetes: a functional data analysis approach
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Wenxin Xu1, Collin Sakal1,2, Wei Zhang1
1Department of Data Science, College of Computing, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong SAR, China.
Background:
The increasing prevalence of type 2 diabetes (T2D) highlights the need for effective glycemic control strategies. Time-restricted eating (TRE) shows promise for metabolic health, but its effectiveness in glucose management among individuals with type 2 diabetes, and its role in modulating glucose responses to dietary intake remain poorly understood. We aimed to identify temporal associations of TRE and dietary intake with 24-hour glucose dynamics. We further examined the interactions between eating windows and carbohydrate intake.
Methods:
Clinical information, dietary records, and continuous glucose monitoring data from 90 Chinese adults with type 2 diabetes were analyzed. Two digital biomarkers were developed to characterize duration and regularity of eating patterns: a binary indicator for eating windows < 10 h (TRE10) and a continuous measure of deviation from an individual's median eating window (TWD). Linear mixed-effects models and functional data analysis were used to examine independent and temporal associations of glucose levels with TRE and dietary intakes.
Results:
TRE10 was associated with reduced mean amplitude of glycemic excursions (MAGE) (β = -7.14, P = 0.031) and glucose standard deviation (SD) (β = -2.16, P = 0.035), with the strongest associations around 09:00. TWD was positively associated with glycemic coefficient of variation (CV) (β = 0.36, P = 0.050) and higher glucose levels between 07:00 and 08:00. Carbohydrate intake was significantly associated with time in range (TIR) and glycemic variability, with notable glucose changes at 10:00 and 21:00. Dietary vitamin D intake was linked to reduced glycemic area under the curve (AUC) (β = -0.29, P = 0.040), with pronounced effects at 12:00 and 20:00. Additionally, eating windows < 10 h were associated with lower carbohydrate-induced glucose spikes in the morning but higher glucose responses in the early afternoon.
Conclusions:
In adults with type 2 diabetes, eating windows < 10 h and consistent eating windows were associated with better glycemic control, with distinct time-of-day effects. These findings support integrating timing-based nutritional strategies into personalized diabetes management.
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