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Cited by 158Mobile Health and mHealth ApplicationsNon-Invasive Vital Sign MonitoringPhysical Activity and Health

Use of wearable devices in individuals with or at risk for cardiovascular disease in the US, 2019 to 2020

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Dhingra, Lovedeep S., Aminorroaya, Arya, Oikonomou, Evangelos K., Nargesi, Arash Aghajani, Wilson, Francis Perry, Krumholz, Harlan M., Khera, Rohan·2023·JAMA Network Open
DOI 10.1001/jamanetworkopen.2023.16634PMC PMC10248745
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Abstract

Importance: Wearable devices may be able to improve cardiovascular health, but the current adoption of these devices could be skewed in ways that could exacerbate disparities. Objective: To assess sociodemographic patterns of use of wearable devices among adults with or at risk for cardiovascular disease (CVD) in the US population in 2019 to 2020. Design, Setting, and Participants: This population-based cross-sectional study included a nationally representative sample of the US adults from the Health Information National Trends Survey (HINTS). Data were analyzed from June 1 to November 15, 2022. Exposures: Self-reported CVD (history of heart attack, angina, or congestive heart failure) and CVD risk factors (≥1 risk factor among hypertension, diabetes, obesity, or cigarette smoking). Main Outcomes and Measures: Self-reported access to wearable devices, frequency of use, and willingness to share health data with clinicians (referred to as health care providers in the survey). Results: Of the overall 9303 HINTS participants representing 247.3 million US adults (mean [SD] age, 48.8 [17.9] years; 51% [95% CI, 49%-53%] women), 933 (10.0%) representing 20.3 million US adults had CVD (mean [SD] age, 62.2 [17.0] years; 43% [95% CI, 37%-49%] women), and 5185 (55.7%) representing 134.9 million US adults were at risk for CVD (mean [SD] age, 51.4 [16.9] years; 43% [95% CI, 37%-49%] women). In nationally weighted assessments, an estimated 3.6 million US adults with CVD (18% [95% CI, 14%-23%]) and 34.5 million at risk for CVD (26% [95% CI, 24%-28%]) used wearable devices compared with an estimated 29% (95% CI, 27%-30%) of the overall US adult population. After accounting for differences in demographic characteristics, cardiovascular risk factor profile, and socioeconomic features, older age (odds ratio [OR], 0.35 [95% CI, 0.26-0.48]), lower educational attainment (OR, 0.35 [95% CI, 0.24-0.52]), and lower household income (OR, 0.42 [95% CI, 0.29-0.60]) were independently associated with lower use of wearable devices in US adults at risk for CVD. Among wearable device users, a smaller proportion of adults with CVD reported using wearable devices every day (38% [95% CI, 26%-50%]) compared with overall (49% [95% CI, 45%-53%]) and at-risk (48% [95% CI, 43%-53%]) populations. Among wearable device users, an estimated 83% (95% CI, 70%-92%) of US adults with CVD and 81% (95% CI, 76%-85%) at risk for CVD favored sharing wearable device data with their clinicians to improve care. Conclusions and Relevance: Among individuals with or at risk for CVD, fewer than 1 in 4 use wearable devices, with only half of those reporting consistent daily use. As wearable devices emerge as tools that can improve cardiovascular health, the current use patterns could exacerbate disparities unless there are strategies to ensure equitable adoption.

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  • Novel AI applications have the potential for identification of digital signatures using multimodal inputs to phenotype patients with cardiovascular disease.

    “Novel AI applications have the potential for identification of digital signatures using multimodal inputs to phenotype patients with cardiovascular disease.8,9”

    From Unlocking Tomorrow’s Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence (2024) · cites this paper as [9]

  • The lower rate of use of wearable devices in individuals with health issues might be related in part to their perception that devices are more geared toward elite athletic performance, rather than monitoring of health status in those with disease.

    “The lower rate of use of wearable devices in individuals with health issues might be related in part to their perception that devices are more geared toward elite athletic performance, rather than monitoring of health status in those with disease.”

    From Unlocking Tomorrow’s Health Care: Expanding the Clinical Scope of Wearables by Applying Artificial Intelligence (2024) · cites this paper as [9]

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Authors
Dhingra, L. S., Aminorroaya, A., Oikonomou, E. K., Nargesi, A. A., Wilson, F. P., Krumholz, H. M., & Khera, R.
Affiliations
  • Yale University (US)
  • Brigham and Women's Hospital (US)
  • Yale New Haven Hospital (US)
Corresponding author
Khera, Rohan
ORCID
Venue
JAMA Network Open
Publisher
American Medical Association (AMA)
Published
2023-06-07
Volume
6
Issue
6
Pages
e2316634
ISSN
2574-3805 (ISSN-L)
DOI
10.1001/jamanetworkopen.2023.16634
PMC
PMC10248745
OpenAlex
W4379598831
Cited by
158
References
35
Citations by year
2026: 48 · 2025: 52 · 2024: 50 · 2023: 7 · 2022: 1
FWCI
55.60
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JAMA Network Open (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (UL1TR001863)
  • National Heart, Lung, and Blood Institute (K23HL153775)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
Keywords
wearable devices, cardiovascular disease, cardiovascular risk, health disparities, sociodemographic disparities, hypertension, diabetes mellitus, obesity, socioeconomic status, health equity, Health Information National Trends Survey, United States adults, technology adoption, digital health equity
MeSH terms
Adult, Cardiovascular Diseases, Cross-Sectional Studies, Female, Humans, Hypertension, Male, Middle Aged, Obesity, Risk Factors

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