Time-Restricted Eating and Dietary Intake Shape 24-Hour Glycemic Patterns in Type 2 Diabetes: A Functional Data Analysis
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Background
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.
Objective
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 hours (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 = −7.15, 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 hours attenuated carbohydrate-induced glucose spikes in the morning but amplified glucose responses in the early afternoon.
Conclusions
In adults with type 2 diabetes, eating windows <10 hours and consistent eating windows improved glycemic control, with distinct time-of-day effects. These findings support integrating timing-based nutritional strategies into personalized diabetes management.
