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Structured Meal-Logging and Glycemic Outcomes in Adults with Type 1 Diabetes on Automated Insulin Delivery: Longitudinal Observational Study
ABSTRACT
Background:
Despite advances in automated insulin delivery (AID) systems, many individuals with type 1 diabetes (T1D) fail to achieve recommended glycemic targets. Whether structured meal-logging paired with wearable monitoring can drive clinically meaningful glycemic improvement in this population remains insufficiently examined.
Objective:
To examine whether structured meal-logging paired with wearable monitoring is associated with clinically meaningful glycemic improvement in adults with T1D using AID systems, and whether any observed benefit persists after monitoring tools are removed.
Methods:
We conducted a three-phase prospective observational study involving 19 adults with T1D using AID systems. Phase 1 established each participant's natural glycemic baseline; Phase 2 introduced structured meal-logging via the ExActHealth™ mobile application and smartwatch-based wearable monitoring; Phase 3 assessed glycemic outcomes after monitoring tools were removed. Participants were stratified using a two-step framework based on baseline time in range (TIR) and glycemic response magnitude.
Results:
Stratification yielded four groups: Clinically Improved (Group 1, n=4), High-Baseline Improver (Group 2, n=2), Ceiling Effect (Group 3, n=7), and No Consistent Pattern (Group 4, n=6). Group 1 improved mean TIR from 65.0% to 76.2% during Phase 2, with postprandial TIR improving from 50.9% to 64.7%; both measures partially reversed following tool removal, with mean TIR declining to 69.5% in Phase 3. Groups 3 and 4 showed no clinically meaningful change in TIR across any phase (Δ <2 pp). Correlation analysis across participants with baseline TIR <80% showed that greater Phase 2 improvement was associated with higher variability in postprandial TIR (ρ=0.770, p=0.009) and time above range (ρ=0.733, p=0.016). Usability ratings were favorable, with 87% of participants reporting that the application was easy to use.
Conclusions:
In this preliminary study, structured meal-logging combined with wearable monitoring was associated with clinically meaningful glycemic improvement in a subset of adults with T1D using AID systems, particularly those with baseline TIR <80% and higher day-to-day glycemic variability. Improvements were most evident in postprandial glucose control and diminished after the monitoring tools were removed, suggesting that continued structured monitoring may be required to sustain the benefit.
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