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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 16, 2025
Open Peer Review Period: May 19, 2025 - Jul 14, 2025
Date Accepted: Sep 15, 2025
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Digital Biometrics in Predicting Risk for Obstructive Sleep Apnea and Hypertension: Decentralized, Prospective Cohort Study

Orendain N, Bagsic SS, Ramos E, Pandit J, Owens RL, Jaiswal S

Digital Biometrics in Predicting Risk for Obstructive Sleep Apnea and Hypertension: Decentralized, Prospective Cohort Study

J Med Internet Res 2025;27:e77641

DOI: 10.2196/77641

PMID: 41340392

PMCID: 12675995

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Digital biometrics in predicting risk for obstructive sleep apnea and hypertension: A decentralized, prospective cohort study

  • Natalia Orendain; 
  • Samantha Spierling Bagsic; 
  • Edward Ramos; 
  • Jay Pandit; 
  • Robert L Owens; 
  • Stuti Jaiswal

ABSTRACT

Background:

Sleep is an important component of human health and can be measured longitudinally using digital activity trackers. Further, decentralized digital research data collection has the potential to provide a real-world picture of sleep in large populations. We hypothesized that longitudinal sleep patterns from activity trackers could predict risk of obstructive sleep apnea (OSA) similar to the Berlin questionnaire and risk for hypertension based on self-report.

Objective:

To test the ability of biometric to predict risk for human disease.

Methods:

We recruited adults ≥18 years nationwide to join our sleep-focused smartphone-based study, called the Research Framework for Exploring Sleep Health (REFRESH). Participants were asked to fill out health-related surveys including the Berlin questionnaire, which also includes self-reported hypertension, and the Horne-Ostberg questionnaire for chronotype. Participants were asked to optionally link their own activity tracker to the application to collect longitudinal sleep data.

Results:

We analyzed sleep data from 391 participants, 67.9% of which were women, and 40.4% of whom demonstrated an evening chronotype. Collinearity testing showed that OSA risk and self-reported hypertension could be considered independently. Increased sleep variability predicted risk of both OSA and hypertension in this decentralized cohort, when using data from the Berlin questionnaire as the ground truth.

Conclusions:

Decentralized sleep research could provide important information regarding risk for some health outcomes. Sleep variability is gaining increasing importance in the context of sleep health. Clinical Trial: NCT05197738


 Citation

Please cite as:

Orendain N, Bagsic SS, Ramos E, Pandit J, Owens RL, Jaiswal S

Digital Biometrics in Predicting Risk for Obstructive Sleep Apnea and Hypertension: Decentralized, Prospective Cohort Study

J Med Internet Res 2025;27:e77641

DOI: 10.2196/77641

PMID: 41340392

PMCID: 12675995

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