Relation between Estimated Cardiorespiratory Fitness and Atrial Fibrillation (from the REasons for Geographic And Racial Differences in Stroke Study)

• Type of Material: Article
• Authors: Abhishek Bose, Wake Forest School of Medicine; Wesley T. O'Neal, Emory University; Aleena Bennett, University of Alabama Birmingham; Suzanne Judd, Emory University; Waqas T. Qureshi, Wake Forest School of Medicine; Xuemei Sui, University of South Carolina; Virginia J. Howard, University of Alabama Birmingham; George Howard, University of Alabama Birmingham; Elsayed Z. Soliman, Wake Forest School of Medicine
• Language: English
• Date: 2017-06-01
• Publisher: Elsevier
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2017 Elsevier Inc. All rights reserved.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.amjcard.2017.03.008
• Title of Journal or Parent Work: AMERICAN JOURNAL OF CARDIOLOGY
• Volume: 119
• Issue: 11
• Start Page: 1776
• End Page: 1780
• Grant/Funding Information: This research project is supported by a cooperative agreement U01 NS041588 from the National Institute of Neurological Disorders and Stroke, National Institutes of Health, Department of Health and Human Service. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Neurological Disorders and Stroke or the National Institutes of Health.
• Keywords: Atrial Fibrillation; REGARDS Study; Estimated Cardiorespiratory Fitness

Abstract

Estimated cardiorespiratory fitness (e-CRF) based on readily available clinical and self-reported data is a promising alternative to the costly traditional assessment of CRF using exercise equipment but its role as a predictor for incident atrial fibrillation (AF) is unclear. This study included 10,126 participants (54.5% women, 35% African American, mean age 63.2 years) from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study who were free of AF at baseline. Baseline (2003–2007) e-CRF was determined using a previously validated non-exercise algorithm. Incident AF cases were identified at a follow-up examination by electrocardiogram and self-reported medical history of prior physician diagnosis. After a median follow-up of 9.4 years, 906 (8.9%) participants developed AF. In a multivariable logistic regression model adjusted for socio-demographics and baseline cardiovascular disease (CVD) risk factors as well as incident coronary heart disease, heart failure, and stroke, each 1-MET increase in e-CRF was associated with a 5% lower risk of AF development (OR (95% CI) 0.95 (0.92, 0.99); p=0.0129). This association was stronger in women (OR (95% CI) 0.85 (0.79, 0.92) than men (OR (95% CI) 0.88 (0.84, 0.93), interaction p-value=0.05. No significant interactions by age, race, history of CVD, or physical limitations were observed. In conclusion, e-CRF using a non-exercise algorithm is a useful predictor of incident AF, which is consistent with prior reports using traditional CRF. This suggests that e-CRF using non-exercise algorithms may serve as a useful alternative to CRF measured by costly and time consuming exercise testing.