High objective training load (Q4 vs Q1) was associated with significantly higher odds of having ≥1 coronary plaque (OR 5.85; 95% CI 2.33-14.71) in middle-aged and older males.
Cross-Sectional (n=222)
Does high objective wearable-derived training load increase the prevalence of subclinical coronary atherosclerosis in middle-aged and older athletes and physically active controls?
High objectively measured training duration and intensity are independently associated with an increased prevalence of subclinical coronary atherosclerosis in middle-aged and older male athletes.
Effect estimate: OR 5.85 (95% CI 2.33-14.71)
p-value: p=<0.001
Background: Middle-aged and older endurance athletes have increased prevalence of coronary artery disease (CAD) on coronary CT angiography (CCTA) compared to healthy controls, despite similarly low cardiovascular risk. Prior studies relied on self-reported data to quantify training load (TL), which poorly correlates with objective wearable-derived TL and may bias outcomes. The impact of objective TL on CAD risk remains unknown. Methods: In this observational, cross-sectional analysis of the Master@Heart study, 222 males (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. CCTA-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 (ORs) between Q4 and Q1. Additionally, adjusted logistic regression models were fitted with continuous TL, using smoothing splines to capture potential non-linear associations. Results: Across quartiles of objective eTRIMP (training duration x heart rate-weighted intensity), unadjusted global differences were observed for ≥1 plaque (p0 (p=0.002), and CAC>100 (p=0.012). Q4 participants had significantly higher adjusted odds of ≥1 plaque (OR 5.85, 95% CI 2.33–14.71), CAC>0 (OR 5.03, 95% CI 2.04–12.35), and CAC>100 (OR 3.50, 95% CI 1.22–10.00) versus Q1. Similar associations were found for objective training duration, while no clear associations were observed for relative time spent in high-intensity zones. In continuous analyses, eTRIMP and objective training duration showed significant positive associations with ≥1 plaque and CAC>100 (p100 (p0.05). Conclusions: High training duration (hours/week) , particularly when combined with cumulative high-intensity TL (eTRIMP) , 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.
Pauwels et al. (Thu,) conducted a cross-sectional in Coronary atherosclerosis (n=222). High objective training load (Quartile 4) vs. Low objective training load (Quartile 1) was evaluated on Presence of ≥1 coronary plaque (OR 5.85, 95% CI 2.33-14.71, p=<0.001). High objective training load (Q4 vs Q1) was associated with significantly higher odds of having ≥1 coronary plaque (OR 5.85; 95% CI 2.33-14.71) in middle-aged and older males.