Background: Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk.
Objective: The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF.
Methods: Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m2), as well as the relation between self-reported physical activity and predicted 5-year AF risk.
Results: We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk.
Conclusions: Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation.
Keywords: atrial fibrillation; cardiology; cardiovascular epidemiology; cross-sectional analysis; exercise; fitness; fitness tracker; heart; physical activity; risk; smartwatch; step count; tracker; walk; wearable.
©Ayelet Shapira-Daniels, Jelena Kornej, Nicole L Spartano, Xuzhi Wang, Yuankai Zhang, Chathurangi H Pathiravasan, Chunyu Liu, Ludovic Trinquart, Belinda Borrelli, David D McManus, Joanne M Murabito, Emelia J Benjamin, Honghuang Lin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.03.2023.