Dynamic sleep-derived HRV features from a consumer wearable differed significantly between higher- and lower-glycemic-risk groups (p<0.05; Cohen's |d|>1.1).
Observational (n=18)
Are dynamic sleep-derived heart rate and heart rate variability features from consumer wearables associated with glucose metabolism status in free-living adults?
Dynamic sleep-derived HRV features from consumer wearables can identify autonomic instability associated with impaired glucose metabolism, highlighting their potential for continuous cardiometabolic health monitoring.
Effect estimate: Cohen's |d| > 1.1
p-value: p=<0.05
Impaired glucose metabolism, a known precursor to type 2 diabetes, is associated with dysregulation of the autonomic nervous system. To assess such autonomic states, consumer wearable devices provide continuous, non-invasive physiological monitoring and may capture autonomic signatures related to metabolic status. This exploratory study examined whether dynamic features of heart rate (HR) and heart rate variability (HRV) during sleep—derived from a consumer wrist-worn device (Fitbit)—are associated with glucose metabolism status in free-living adults. We analyzed 189 nights from 18 participants (7 participants in the higher-glycemic-risk group, estimated glycated hemoglobin (HbA1c) ≥ 5.5%; 11 participants in the lower-glycemic-risk group, estimated HbA1c 1.1). Specifically, the lower-glycemic-risk group exhibited decreasing overnight trends in HRV variability, consistent with progressive autonomic stabilization during sleep. In contrast, the higher-glycemic-risk group showed increasing variability trends, suggestive of persistent autonomic instability. These directional patterns are consistent with prior evidence linking autonomic dysfunction to impaired glucose metabolism. We characterize these findings as hypothesis-generating. The identified dynamic HR/HRV features represent physiologically plausible candidate correlates of glycemic status and warrant confirmatory investigation in larger, independent cohorts with laboratory-measured HbA1c. More broadly, this work highlights the potential of widely available, consumer-grade wearable devices to move beyond activity tracking and support continuous, real-world assessment of cardiometabolic health, thereby expanding their utility in everyday health monitoring and preventive medicine.
Li et al. (2026) conducted an observational in Impaired glucose metabolism (n=18). Consumer wrist-worn device (Fitbit) monitoring vs. Lower-glycemic-risk group was evaluated on Differences in dynamic HRV features between lower- and higher-glycemic-risk groups (Cohen's |d| > 1.1, p=<0.05). Dynamic sleep-derived HRV features from a consumer wearable differed significantly between higher- and lower-glycemic-risk groups (p<0.05; Cohen's |d|>1.1).