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Wearable-Derived Training Load and Coronary Atherosclerosis in Middle-Aged and Older Athletes and Physically Active
Rik Pauwels1,2,3,4, Christophe Dausin5, Sergio Ruiz-Carmona6,7
1Department of Cardiology, Hartcentrum (R.P., J.D.P., Y.B., B.D., L.H., G.C.), Jessa Ziekenhuis, Hasselt, Belgium.
Background:
Middle-aged and older endurance athletes have increased prevalence of coronary artery disease (CAD) on coronary computed tomography angiography compared with healthy controls, despite similarly low cardiovascular risk. Previous studies relied on self-reported data to quantify training load (TL), which poorly correlates with objective wearable-derived TL and may bias outcomes. The effect of objective TL on CAD risk remains unknown.
Methods:
In this observational, cross-sectional analysis of the Master@Heart study, 222 men (median age, 54 [49-59] years) were included: 77 lifelong athletes, 98 late-onset athletes, and 47 controls. TL was assessed using objective wearable-derived training duration and intensity (12 consecutive months), as well as self-reported training measures. Coronary computed tomography angiography-derived CAD prevalence was compared across TL quartiles (Q) using a global unadjusted chi-square test and logistic regression, adjusted for cardiovascular risk factors and years of endurance exercise, to estimate odds ratios between Q4 and Q1. In addition, adjusted logistic regression models were fitted with continuous TL, using smoothing splines to capture potential nonlinear associations.
Results:
Across quartiles of objective Edwards training impulse (training duration × heart rate-weighted intensity), unadjusted global differences were observed for ≥1 plaque (P<0.001), coronary artery calcification (CAC)>0 (P=0.002), and CAC>100 (P=0.012). Q4 participants had significantly higher adjusted odds of ≥1 plaque (odds ratio, 5.85; 95% CI, 2.33-14.71), CAC>0 (odds ratio, 5.03; 95% CI, 2.04-12.35), and CAC>100 (odds ratio, 3.50; 95% CI, 1.22-10.00) versus Q1. Similar associations were found for objective training duration, whereas no clear associations were observed for relative time spent in high-intensity zones. In continuous analyses, Edwards training impulse and objective training duration showed significant positive associations with ≥1 plaque and CAC>100 (P<0.05), whereas self-reported training duration was only significantly associated with CAC>100 (P<0.05). Metabolic equivalent of task-minutes per week based on self-reported TL was not associated with CAD (P>0.05).
Conclusions:
High training duration (hours/week), particularly when combined with cumulative high-intensity TL (Edwards training impulse), was independently associated with increased prevalence of subclinical CAD in middle-aged and older athletes and physically active controls. Exercise intensity alone, in the absence of high duration, was not clearly linked to CAD. These findings underscore the potential of objectively measured TL for understanding associations with subclinical CAD in endurance athletes.
Registration:
URL: https://www.clinicaltrials.gov; Unique identifier: NCT03711539.
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