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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.
The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF.
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.
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 (
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.
Atrial fibrillation (AF) is the most common cardiac arrhythmia, and it is an important cause of stroke, heart failure, and death [
In recent years, researchers have investigated AF risk modification via lifestyle changes, such as decreased alcohol consumption, weight loss, smoking cessation, and other factors [
We hypothesized that a higher daily step count, as measured by wearable devices, is associated with a lower 5-year risk of AF, as predicted by the CHARGE-AF score.
The Framingham Heart Study (FHS), which originated in 1948 to investigate CVD, is a community-based cohort study that spans 3 generations of families [
This study was approved by the Institutional Review Board of Boston University Medical Center (approval number: H-36586). All participants provided written informed consent.
In this analysis, we selected eFHS participants, as displayed in Figure S1 in
The total number of hours of watch wear time per day and the number of days participants wore the watch were recorded. A
The primary dependent measure was participants’ 5-year risk of AF, which was estimated based on the CHARGE-AF risk scores that were calculated by using the clinical risk factors assessed when participants were examined at the FHS research center [
Participants were asked to complete a questionnaire during their FHS research examinations to determine their physical activity levels. This questionnaire, which has been used in other FHS studies, asked participants to estimate the number of hours in a typical day that they spent performing varying levels of physical activity over the past year [
Daily step count, watch wear time, and clinical variables were reported as means with SDs for continuous variables and as n values with percentages for dichotomous variables. When continuous variable distribution was skewed, medians with IQRs were reported.
The primary analysis examined the association between daily step count (independent measure) and the CHARGE-AF risk score (dependent measure) via linear regression, adjusting for age, sex, and average wear time per day. Both daily step count and the CHARGE-AF score were treated as continuous variables.
Secondary analyses tested for interactions between daily step count and sex and between daily step count and obesity (BMI≥30 kg/m2) in their association with the CHARGE-AF risk score, given that male sex and obesity are established independent risk factors for AF. For graphic purposes, we performed an analysis that examined the CHARGE-AF score, as a dependent variable, in high versus low physical activity groups (<7500 vs ≥7500 daily steps). High and low physical activity groups were determined by using the average step count of the study sample as the cutoff. The analysis was performed by using a Wilcoxon rank-sum test and adjusted for age.
Additional analyses examined the association between self-reported physical activity (PAI score) and CHARGE-AF risk via linear regression, adjusting for age and sex. Sensitivity analyses were performed by using different thresholds for watch wear time (5 vs 10 hours/day) and number of active days (30 vs 60 vs 90 days). A 2-sided
We included 923 participants in this study. The mean age of participants was 53 (SD 9) years, 563 (61%) participants were female, and 838 (90.8%) participants identified as White. The median daily step count was 7227 (IQR 5699-8970), and the median watch wear time was 13.6 (IQR 12.4-14.7) hours per day for 324 (IQR 137-563) active days. The median CHARGE-AF risk score was 1% for men and 0.5% for women (
Distribution of 5-year AF risk among participants. Most participants (823/923, 89.2%) had a 5-year AF risk of <2.5%, as determined by the CHARGE-AF score. AF: atrial fibrillation; CHARGE: Cohorts for Heart and Aging Research in Genomic Epidemiology.
Characteristics of the study participants.
Characteristicsa | Participants (N=923) | ||
Age (years), mean (SD) | 53 (9) | ||
Sex (female), n (%) | 563 (61) | ||
BMI (kg/m2), mean (SD) | 28.2 (5.5) | ||
Height (cm), mean (SD) | 169 (9) | ||
Weight (kg), mean (SD) | 81 (18) | ||
Systolic blood pressure (mm Hg), mean (SD) | 118 (14) | ||
Diastolic blood pressure (mm Hg), mean (SD) | 76 (9) | ||
History of heart failure, n (%) | 6 (0.7) | ||
History of myocardial infarction, n (%) | 12 (1.3) | ||
Current smoking, n (%) | 44 (4.8) | ||
Diabetes mellitus, n (%) | 53 (5.7) | ||
Antihypertensive medication use, n (%) | 193 (20.9) | ||
Self-reported physical activity index score, mean (SD) | 33.4 (4.7) | ||
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White | 838 (90.8) | |
|
Black | 21 (2.2) | |
|
Asian | 17 (1.8) | |
|
Hispanic | 27 (2.9) | |
|
Other | 20 (2.2) | |
Daily step count, median (IQR) | 7227 (5699-8970) | ||
Active hours per day, mean (SD) | 13.4 (1.9) | ||
Active days, median (IQR) | 324 (137-562) |
aPresented are means with SDs for continuous traits with a normal distribution, medians with IQRs for continuous traits with a skewed distribution, and n values with percentages for dichotomous traits.
After adjusting for age, sex, and watch wear time, our primary analysis, in which linear regression was performed, showed that daily step count and the CHARGE-AF score were inversely associated. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk score (
We observed significant interactions by sex and obesity; the association between the CHARGE-AF score and daily step count was stronger in men and participants with obesity. The CHARGE-AF risk score was 0.14% and 0.05% lower for every 1000 steps in men and women, respectively (interaction:
Participants’ self-reported physical activity levels, as determined by the PAI score, were not associated with the CHARGE-AF score.
Sensitivity analyses were conducted to investigate the association between daily step count and the CHARGE-AF score, using different device wear thresholds. The watch wear cutoff was increased to ≥60 days and ≥90 days from the cutoff of ≥30 days used in primary analysis. In a separate analysis, the wear time threshold was increased to 10 hours from the threshold of 5 hours used in the primary model. The inverse association between daily step count and the CHARGE-AF risk score remained significant in these subgroups (Tables S1 and S2 in
Association between average daily step count and the predicted 5-year atrial fibrillation (AF) riska.
|
Change in AF risk score per 1000 steps (%), βb (SE) | |
All participants | −0.08 (0.01) | <.001 |
Men | −0.14 (0.02) | <.001 |
Women | −0.05 (0.01) | .001 |
No obesity | −0.03 (0.01) | <.001 |
Obesityc | −0.10 (0.03) | <.001 |
aThe model was adjusted for age, sex (for the model including all participants), and wear time.
bβ represents the change in 5-year AF risk for every 1000-step increase in daily step count.
bObesity was defined as a BMI of ≥30 kg/m2.
Participants' 5-year AF risk by high versus low daily step count. Participants with lower daily step counts had higher CHARGE-AF scores (mean 1.3% for low daily step count vs mean 0.9% for high daily step count;
In our observational cross-sectional analysis of eFHS participants, the 5-year AF risk, as predicted by the CHARGE-AF score, was low (0.5% in women and 1% in men), and the score was 0.08% lower for every 1000 steps in a model adjusted for age, sex, and wear time. Interactions were significant for sex (
The overall benefits of increased physical activity have been well documented, including reductions in all-cause mortality, CVD-related mortality, and overall CVD risk [
The association between future AF risk and objectively measured physical activity has been investigated in both short-term accelerometer use and the long-term use of implantable devices (≥25 months). AF risk was either estimated with the CHARGE-AF score or calculated after monitoring for incident AF [
Our study also demonstrated that sex and obesity may modify the association between AF risk and daily step count, as a stronger association between AF risk and daily step count was noted in men and participants with obesity. The independently increased risk of AF in men and individuals with obesity may have contributed to the stronger association that we observed between step count and the CHARGE-AF score [
Finally, our study did not find evidence of an association between self-reported physical activity and predicted AF risk. This lack of association may be related to the inconsistent validity of self-reported physical activity [
The biological mechanisms behind the inverse association between step count, as an objective measure of physical activity, and estimated AF risk may be embedded within the shared risk factors between CVD and AF. On a cellular level, increased step counts have been associated with lower chronic inflammation and cardiac biomarkers, such as lipoproteins, white blood cell count, troponin, and N-terminal pro–brain natriuretic peptide [
Our study has several limitations. First, this study is limited by its observational and cross-sectional design, precluding the ability to establish causality, establish temporality, or rule out residual confounding. Additionally, the cross-sectional design precludes prospective follow-ups for the occurrence of incident AF. As such, the use of the estimated CHARGE-AF risk (as opposed to incident AF) as the primary outcome limits interpretations of clinical significance. However, CHARGE-AF risk has been extensively validated in large data sets with good predictive performance for incident AF [
Increasing daily steps can be a practical, lifestyle-modifying method for reducing an individual’s AF risk. Future studies could investigate a dose-dependent relation between step count and AF risk and examine this relation in more ethnically diverse, racially diverse, and age-diverse populations. Given the emerging relation between AF risk, objectively measured physical activity, and daily step count, assessing commercially available wearable devices for AF preventative risk reduction merits further investigation.
Supplementary figure and tables.
Graphic abstract.
atrial fibrillation
Cohorts for Heart and Aging Research in Genomic Epidemiology
cardiovascular disease
electronic Framingham Heart Study
Framingham Heart Study
physical activity index
We would like to warmly acknowledge Emily S Manders of Boston University’s Framingham Heart Study and the National Heart, Lung, and Blood Institute for her contribution to this project.
This study was supported by an award from the Robert Wood Johnson Foundation (number 74624) and a grant from the National Heart, Lung, and Blood Institute (R01HL141434). The Framingham Heart Study was supported by a contract from the National Heart, Lung, and Blood Institute (principal investigator [PI]: Vasan S Ramachandran 75N92019D00031). The investigators were supported by the following National Institutes of Health grants: R01HL126911 (EJB), R01HL092577 (EJB), R01 R01AG066010 (EJB), 18SFRN34110082 (EJB), U54HL120163 (EJB), R01HL126911 (DDM), R01HL137734 (DDM), R01HL137794 (DDM), R01HL13660 (DDM), U54HL143541 (DDM), and U01AG068221 (HL). This work was also supported by the American Heart Association (18SFRN34150007; PI: LT). JK received funding from the Marie Sklodowska-Curie Actions under the European Union’s Horizon 2020 research and innovation program (agreement number: 838259). The Apple watches were provided to Boston University by Apple Inc at no cost to the study.
NLS receives research support from Novo Nordisk for an investigator-initiated grant unrelated to this study. JMM was a guest lecturer at Merck, unrelated to this work. DDM has received honoraria, speaking, consulting, or editorial fees from the Heart Rhythm Society, Bristol-Myers Squibb, Pfizer, Samsung, Flexcon, Philips, Fitbit, Avania, and Venturewell; Data Safety Monitoring Boards including the Boston Biomedical Associates, Avania, and NAMSA. DDM also reports receiving research grants or support from Boehringer Ingelheim, Bristol-Myers Squibb, Philips, Samsung, Apple, Biotronik, Boehringer Ingelheim, Pfizer, Sanofi, Flexcon, Fitbit, and National Institutes of Health (NIH). EJB reports receiving grants from NIH.