Abstract
Background
The Life’s Essential 8 (LE8) metric is a well-validated tool to assess cardiovascular health. The tool relies on self-reported physical activity (PA) and sleep data which may be subject to recall bias when compared with objective device-derived data. We used objectively captured device data from Fitbit devices linked to the electronic health record (EHR) from the All of Us Research Program (AoURP) to examine the association between LE8 and incident cardiovascular disease (CVD).
Methods
We analyzed AoURP participants with ≥6 months of Fitbit-derived PA and sleep data from 2009 to 2023. Remaining LE8 components were obtained via EHR and combined with Fitbit components to calculate LE8 scores. Cox proportional hazards models analyzed the association between LE8 scores and a composite CVD outcome (myocardial infarction, coronary artery disease, heart failure, stroke, and peripheral artery disease). Relative explained variation (REV) assessed the contribution of each LE8 component to model performance. We modeled the impact of plausible changes in weekly activity and sleep on the composite CVD outcome.
Results
11,542 participants were included (50.1 years [IQR: 35.9, 61.7], 74% female, 81% white) with a median monitoring duration of 4.48 years [2.00, 6.87]. The median LE8 score was 68.1 [60.6, 74.4]. Higher LE8 score was linearly associated with lower CVD risk (HR = 0.74; CI, 0.69-0.80) per 10-point increase. Risk of MI, CAD, HF, PAD, and stroke showed similar independent associations with LE8 scores. Among LE8 components, physical activity had the highest median REV 0.35 [0.21, 0.47], followed by blood pressure (0.23, CI = 0.11-0.36) and blood glucose (0.14, CI = 0.05-0.24). Increasing weekly moderate to vigorous physical activity by 30 minutes (120min to 150min) decreased the risk of incident CVD by 23% (HR=0.77; CI, 0.721-0.81), and increasing sleep duration from 4-5 hours to 7-9 hours decreased the risk of incident CVD by 35% (HR=0.65; CI, 0.50-0.84).
Conclusion
These results underscore the potential of calculating the LE8 score using objective PA and sleep data from consumer devices and highlight the disproportionate impact of lifestyle behaviors on CVD risk among patients seeking care. Consumer wearable devices offer valuable information when included in cardiovascular risk assessment.
Full Text Availability
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