@Article{info:doi/10.2196/65368,
author="Jospe, Michelle R
and Kendall, Martin
and Schembre, Susan M
and Roy, Melyssa",
title="Real-World Effectiveness of Glucose-Guided Eating Using the Data-Driven Fasting App Among Adults Interested in Weight and Glucose Management: Observational Study",
journal="JMIR Form Res",
year="2025",
month="May",
day="8",
volume="9",
pages="e65368",
keywords="precision health; digital health; metabolic health; personalized nutrition; blood glucose self-monitoring; biological feedback; glucose; blood glucose; monitoring; self monitoring; dietary intervention; diet; app engagement; glucose monitoring",
abstract="Background: The Data-Driven Fasting (DDF) app implements glucose-guided eating (GGE), an innovative dietary intervention that encourages individuals to eat when their glucose level, measured via glucometer or continuous glucose monitor, falls below a personalized threshold to improve metabolic health. Clinical trials using GGE, facilitated by paper logging of glucose and hunger symptoms, have shown promising results. Objective: This study aimed to describe user demographics, app engagement, adherence to glucose monitoring, and the resulting impact on weight and glucose levels. Methods: Data from 6197 users who logged at least 2 days of preprandial glucose readings were analyzed over their first 30 days of app use. App engagement and changes in body weight and fasting glucose levels by baseline weight and diabetes status were examined. Users rated their preprandial hunger on a 5-point scale. Results: Participants used the app for a median of 19 (IQR 9-28) days, with a median of 7 (IQR 3-13) weight entries and 52 (IQR 25-82) glucose entries. On days when the app was used, it was used a median of 1.8 (IQR 1.4-2.1) times. A significant inverse association was observed between perceived hunger and preprandial glucose concentrations, with hunger decreasing by 0.22 units for every 1 mmol/L increase in glucose (95{\%} CI −0.23 to −0.21; P<.001). Last observation carried forward analysis resulted in weight loss of 0.7 (95{\%} CI −0.8 to −0.6) kg in the normal weight category, 1 (95{\%} CI −1.1 to −0.9) kg in the overweight category, and 1.2 (95{\%} CI −1.3 to −1.1) kg in the obese category. All weight changes nearly doubled when analyzed using a per-protocol (completers) analysis. Fasting glucose levels increased by 0.11 (95{\%} CI 0.09-0.12) mmol/L in the normal range and decreased by 0.14 (95{\%} CI −0.16 to −0.12) mmol/L in the prediabetes range and by 0.5 (95{\%} CI −0.58 to −0.42) mmol/L in the diabetes range. Per-protocol analysis showed fasting glucose reductions of 0.26 (SD 4.7) mg/dL in the prediabetes range and 0.94 (16.9) mg/dL in the diabetes range. Conclusions: The implementation of GGE through the DDF app in a real-world setting led to consistent weight loss across all weight categories and significant improvements in fasting glucose levels for users with prediabetes and diabetes. This study underscores the potential of the GGE to facilitate improved metabolic health. ",
issn="2561-326X",
doi="10.2196/65368",
url="https://formative.jmir.org/2025/1/e65368",
url="https://doi.org/10.2196/65368"
}