Predictors of coronary atherosclerosis in middle-aged and older athletes: the MARC-2 study

Kristian Berge, Sylvan L J E Janssen, Birgitta K Velthuis, Peder Langeland Myhre, Arend Mosterd, Torbjørn Omland, Thijs M H Eijsvogels, Vincent L Aengevaeren

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Aims: Exercise improves cardiovascular health, but high-volume high-intensity exercise is associated with increased coronary artery calcification (CAC). We aimed to identify predictors of CAC in athletes. Methods and results: We assessed the association of traditional and non-traditional cardiovascular risk factors with CAC using linear and logistic regression. A total of 289 male athletes from the MARC-2 study were included, with a median age of 60 (Q1-3 56-66) years, lifelong weekly training load of 26 (17-35) metabolic equivalent of task hours, body mass index of 24.5 (22.9-26.6) kg/m2, systolic blood pressure of 139 ± 18mmHg, and reported 0.0 (0.0-8.0) smoking pack years. Thirty-one per cent had a CAC score > 100 and 13% > 400. Among traditional cardiovascular risk factors, higher age, systolic blood pressure, smoking pack years, and family history of coronary artery disease independently predicted greater CAC scores, while body mass index, low-density lipoprotein cholesterol, and diabetes mellitus did not. Among non-traditional risk factors, higher training loads, serum phosphate, and lower adjusted energy intake and fat percentage of energy intake independently predicted greater CAC scores. The full model with all traditional and non-traditional risk factors had higher accuracy in predicting CAC > 100 [receiver operating characteristic area under the curve 0.76, 95% confidence interval (0.70-0.82)] and CAC > 400 [0.85 (0.77-0.92)] than traditional cardiovascular risk factors alone [0.72 (0.65-0.78), P = 0.012, and 0.81 (0.74-0.90), P = 0.038, respectively]. Conclusion: Non-traditional risk factors, including training load, dietary patterns, and serum phosphate, were independently associated with CAC in aging male athletes. Prediction accuracy for CAC increased when including these variables in a prediction model with traditional risk factors.

Original languageEnglish
Pages (from-to)461-470
Number of pages10
JournalEuropean heart journal. Cardiovascular Imaging
Volume26
Issue number3
Early online date8 Dec 2024
DOIs
Publication statusPublished - 3 Mar 2025

Keywords

  • coronary artery disease
  • exercise
  • risk prediction
  • training

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