Use of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020

Abstract

ImportanceWearable devices may be able to improve cardiovascular health, but the current adoption of these devices could be skewed in ways that could exacerbate disparities.ObjectiveTo 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 ParticipantsThis 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.ExposuresSelf-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 MeasuresSelf-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).ResultsOf 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 RelevanceAmong 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.

Application of wearables for remote monitoring of oncology patients: A scoping review

“…More strict data privacy and security regulations in the EU complicate research in this sensitive field, both from researchers’ and from participants’ points of view, who might be skeptical concerning the adaption of new technologies and especially concerning the processing of sensitive personal health data. 71 One-third of the adult US population is estimated to use wearables 72 and more than 80% of US wearable users report willingness to share wearable information with HCPs. 73 In contrast, only 19% of the EU population between 16 and 74 years reported to use wearables in 2020.…”

Deep Learning-enabled Detection of Aortic Stenosis from Noisy Single Lead Electrocardiograms

“…Consequently, our model's proposed use on portable device-acquired ECGs represents an accessible approach for detecting moderate/severe AS in the community, as these portable devices are widely available, and easily deployable. 15,21 Finally, our model incorporates realworld noise during the model training, which enhances the model's ability to identify the pathological disease signature even in the presence of noise in portable ECG acquisition. 13,16 The morbidity and mortality arising from AS is treatable with recent advances in transcatheter aortic valve replacement, making AS management safer and more feasible.…”

“…Using portable and wearable devices capable of capturing single lead ECGs can facilitate large-scale cardiovascular screening. [15][16][17] However, these devices are often prone to the introduction of noise during ECG acquisition. 16,18 Thus, the advancement of scalable strategies for AS detection requires development of noise-resilient AI-ECG models capable of detecting AS from single-lead ECGs.…”

Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System

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