| Title: | Investigating the comparability of wearable accelerometer methods in the association between physical activity and cardiovascular disease: a cohort study using UK Biobank |
| Journal: | Preventive Medicine |
| Published: | 15 May 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42142761/ |
| DOI: | https://doi.org/10.1016/j.ypmed.2026.108603 |
Publication 20021
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Abstract
OBJECTIVE: The selection of accelerometer processing methods may influence the shape of the dose-response association between wearable-measured physical activity and health outcomes. We aimed to compare the association of stroke and myocardial infarction with Moderate-Vigorous Physical Activity (MVPA) assessed by three accelerometer-generated metrics: Low-pass Filtered Euclidean Norm Minus One (LFENMO), machine-learning, and activity counts.</p>
METHODS: We computed MVPA durations in the UK Biobank accelerometer sub-cohort recruited between 2013 and 2015 in the UK. The outcomes, incident stroke and myocardial infarction, were followed up until December 2022. We used Cox regression and a restricted cubic spline to estimate the dose-response association for each of the three MVPA metrics.</p>
RESULTS: There were 90,237 cardiovascular disease-free participants at baseline. We observed 1298 incident strokes and 2031 myocardial infarctions. For stroke, a linear decrease in hazard ratio was observed with machine-learning, but not with LFENMO and activity counts. For myocardial infarction, machine-learning and LFENMO showed a curvilinear decrease in hazard ratios, whereas activity counts showed a linear decrease.</p>
CONCLUSIONS: The dose-response associations between MVPA and cardiovascular disease varied markedly across the three accelerometer-derived MVPA metrics. Research using a single accelerometer metric may caution about the interpretation of the association.</p>
6 Authors
- Yacine Lapointe
- Aayush Kapur
- Abhinav Sharma
- Jenna Panter
- Daniel Fuller
- Hiroshi Mamiya
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