BACKGROUND: Prior research on circadian rhythms have primarily focused on the risk of diabetes, with limited evidence on their impact in glycemic control among individuals with type 2 diabetes. This study investigated the association between Fitbit-derived circadian rhythm parameters and continuous glucose monitoring (CGM) metrics.
METHOD: Data were analyzed from 122 insulin-treated patients with type 2 diabetes who concurrently wore real-time CGM devices (Dexcom G6) and activity trackers (Fitbit Inspire 2) for 10 days. Cosinor analyses were used to derive circadian parameters from wearable-based heart rate data. Associations between time-of-day-specific activity metrics and CGM outcomes were evaluated using partial Spearman correlations and multivariable logistic regression.
RESULTS: Stronger circadian rhythmicity-characterized by greater amplitude and higher goodness-of-fit (R2)-was significantly associated with improved glycemic outcomes and reduced glucose variability. Higher daytime step counts and lower sedentary time were associated with reduced hyperglycemia and variability. Longer sleep duration was inversely associated with hypoglycemia (TBR <70) and glucose variability indices. Notably, circadian robustness (R2) and afternoon step counts emerged as independent predictors of achieving comprehensive CGM-based targets after adjusting for key clinical and behavioral confounders.
CONCLUSIONS: In this cross-sectional exploratory analysis, greater daytime physical activity and stronger circadian rhythmicity were associated with improved glycemic control and reduced glucose variability. These findings are hypothesis-generating and support the need for prospective trials testing circadian-aligned behavioral interventions.
