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Updated: Jan 24, 2026

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Associations Between Objective Sleep Characteristics From Wearable Physiologic Monitors and Incident Atrial

Mohammad Hosein Yazdanpanah1, Farhan Naeem1, Mohamed Doma1

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Summary

Objectively measured sleep duration and stages, particularly prolonged total sleep and increased light sleep, are linked to higher atrial fibrillation risk. Reduced deep and REM sleep also correlate with increased AF incidence.

Keywords:
All of Usatrial fibrillationepidemiologysleep architecturesleep durationwearable devices

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Area of Science:

  • Cardiology
  • Sleep Medicine
  • Epidemiology

Background:

  • Existing research suggests a connection between sleep and atrial fibrillation (AF).
  • Prior studies often relied on self-reported sleep data, lacking detailed sleep architecture information.
  • The predictive value of objectively measured sleep for incident AF is not well understood.

Purpose of the Study:

  • To investigate the relationship between objectively measured sleep parameters and the incidence of AF.
  • To analyze associations between total sleep duration, sleep stages, and new-onset AF in a large, diverse population.

Main Methods:

  • Utilized wearable-derived sleep data from 52,952 participants in the All of Us Research Program.
  • Excluded individuals with baseline AF or extreme sleep durations (under 3 or over 16 hours).
  • Employed Cox proportional hazards models to assess the risk of incident AF over a median follow-up of 935 days.

Main Results:

  • Incident AF was associated with older age, male sex, White race, smoking, and comorbidities.
  • Longer total sleep duration (>9 hours) was linked to a 47% increased AF risk compared to 6-9 hours.
  • Increased light sleep and prolonged nonmain sleep were associated with higher AF risk, while deeper sleep stages showed an inverse association.

Conclusions:

  • Objectively measured sleep parameters independently predict AF risk.
  • Prolonged total sleep, increased light sleep, and reduced deep/REM sleep are associated with incident AF.
  • These findings suggest sleep parameters could aid in AF risk stratification and prevention strategies.