Collecting Long-Term Wearable Data in Older Adults: Atherosclerosis Risk in Communities Neurocognitive Study
Erin Spaulding, Jie Ding, Henry Zhao, Pamela Lutsey, B Gwen Windham, Katherine Ornstein, Josef Coresh, Seth Martin

TL;DR
This study shows that wearable devices like Fitbit can collect long-term health data from older adults with proper support, though some groups show more variability in usage.
Contribution
The study demonstrates successful long-term wearable data collection in older adults and identifies racial differences in wear time variability.
Findings
Approximately one-third of eligible older adults enrolled in the study and provided a median of 125 days of Fitbit data.
Median wear time was 99%, with Black participants showing greater variability in wear time compared to White participants.
Proper onboarding and ongoing support enabled consistent wearable use among adults aged 80 and older.
Abstract
Traditional cohort studies, relying on periodic visits, may introduce bias by capturing data largely when participants feel well. Wearables enable continuous data collection, potentially mitigating this bias, but low adoption among older adults could result in data gaps. Fitbit Charge 6 devices were used to collect long-term health data among Atherosclerosis Risk in Communities Neurocognitive Study (ARIC NCS) participants with a smartphone in 2024-2025. Staff provided Fitbit setup and training, encouraging daily wear and regular syncing, with ongoing technology support. Fitbit wear time, measured by heart rate data, was calculated as a percentage. Mann-Whitney U tests assessed differences in wear time by age, sex, and race. Approximately one-third of eligible participants offered a Fitbit chose to enroll. A total of 309 ARIC NCS participants (84.0±3.2 years [36% ≥85 years], 60% women,…
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Taxonomy
TopicsPhysical Activity and Health · Mobile Health and mHealth Applications · Digital Mental Health Interventions
