1901-P: Association of Wearable Physiological Signals and Glucose Biosensor Data in 46,000 Adults without Self-Reported Diabetes

Introduction and Objective: The use of continuous glucose monitors (CGMs) has expanded to people without diabetes, offering actionable insights that support healthy behavior and lifestyle change. Integrating CGM data with other wearable signals may clarify how glucose interacts with sleep, activity, and cardiovascular physiology. We sought to characterize these associations and evaluate the utility of multimodal wearable data. Methods: We analyzed de-identified data from 46,033 adults (67% female, age range 18-90), who wore an Oura Ring and used a Dexcom Stelo glucose biosensor for at least 7 days, for a total of 1,353,416 days. Outcomes were daily mean glucose, glucose variability (coefficient of variation, CV), and time above range >140 mg/dL (TAR). Oura Ring metrics included nighttime heart rate (HR), heart-rate variability (HRV), cardiovascular age (CVA), sleep duration and efficiency, activity (steps). We modeled these associations using cubic B-spline regressions adjusted for age, sex, and BMI. Results: The median daily mean glucose in the sample was 109 mg/dL, median CV 12.7%, median TAR 55 min. Higher HRV, sleep efficiency, and more steps per day were associated with lower glucose (Fig 1). Conversely, higher HR and CVA were associated with higher glucose. Conclusion: Oura physiological metrics show associations with glucose biosensor data, supporting the utility of research for their use in scalable metabolic health assessment and interventions. Disclosure A. Kluge: Employee; Current; Oura Health Oy. M. Karsikas: Employee; Current; Oura Health. T. Kinnunen: Employee; Current; Oura Health Oy. P. Ohukainen: Employee; Current; Oura Health oy.