Expanding continuous glucose monitoring's potential from real-time safety to lifestyle support in type 1 diabetes exercise: a proof-of-concept study among adults with low baseline exercise levels.

Authors

Young In Chung, Garrett I Ash, Sangchoon Jeon, Reshma Ramachandran, Matthew Stults-Kolehmainen, Elias K Spanakis, Lisa M Fucito

Published in

Human factors in healthcare. Volume 10. Pages 100154. Epub Aug 06, 2026.

Abstract

This proof-of-concept study sought to explore how data from CGM and exercise can be aggregated and analyzed to capture clinically meaningful glycemic patterns and actionable feedback. To this end, we examined how exercise days were associated with glucose outcomes derived from continuous glucose monitoring (CGM) among adults with type 1 diabetes (T1D) who had low baseline exercise levels.
Secondary analyses were conducted on data from a 10-week digital app-based exercise intervention. Participants (N = 17; 52.9% Female; M [SD] age = 43.4 years [13.5]; M [SD] diabetes duration = 23.1 years [15.2]) received an exercise app with videos, text-based exercise coaching, a web-based self-monitoring diary, and a monthly session with personalized integrated feedback of CGM and other psychosocial data (exercise, mood, and sleep). To identify meaningful post-exercise periods, glucose patterns were examined across the 24-hour period, followed by iterative testing of different analytic windows. The final models focused on evening and overnight periods (18:00-06:00) to capture immediate and delayed glycemic effects. CGM-derived outcomes - mean glucose, time in range (TIR; 70-180 mg/dL), time in hyperglycemia (≥250 mg/dL), and time in hypoglycemia (≤70 mg/dL) - were analyzed using generalized linear mixed models. Logistic mixed models estimated odds of hyperglycemia and hypoglycemia, adjusting for age, diabetes duration, BMI, weekday, and HbA1c.
Relative to non-exercise days, exercise days were associated with lower mean glucose (-3.13 mg/dL, p = .001) and higher TIR (3.36%, p < .001), corresponding to ~25 additional minutes per night in range. Exercise days were associated with reduced time in hyperglycemia (-2.16%, p < .001) and lower odds of hyperglycemia (OR = 0.68 [0.58-0.78], p < .001). Exercise was associated with a small but statistically significant increase in percent time below 70 mg/dL (0.81%, p = .002); however, the interval-level odds model did not show a statistically significant increase in hypoglycemia risk (OR = 0.85 [0.71-1.00], p = .057).
In this exploratory study, exercise was associated with greater evening and overnight glucose stability among adults with T1D who were physically inactive at baseline (i.e., 0 min of recorded exercise per week). These preliminary findings suggest the analytic feasibility of linking CGM and exercise data to identify clinically meaningful glycemic patterns. This lays the groundwork for an integrated behavioral support system that provides interpretable, actionable feedback to support patients' diabetes self-management.

PMID:
42840788
Bibliographic data and abstract were imported from PubMed on 07 Oct 2026.

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