1. "Weekend Warrior" Physical Activity and Adipose Tissue Deposition.
- Author
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Kany S, Al-Alusi MA, Rämö JT, Pirruccello JP, Ajufo E, Churchill TW, Lubitz SA, Maddah M, Guseh JS, Ellinor PT, and Khurshid S
- Abstract
Background: Attaining guideline-recommended levels of physical activity is associated with substantially lower risk of cardiometabolic diseases., Objectives: Although physical activity commonly follows a weekend warrior pattern, in which most moderate-to-vigorous physical activity is concentrated in 1 to 2 days rather than spread more evenly across the week (regular), the effects of activity pattern on imaging-based biomarkers of cardiometabolic health are unknown., Methods: We analyzed 17,146 UK Biobank participants who wore accelerometers for 1 week, and later underwent cardiac magnetic resonance imaging. Activity was categorized as inactive, regular, or "weekend warrior". Associations between activity pattern and magnetic resonance imaging-derived visceral adipose tissue (VAT) and epicardial and pericardial adipose tissue (EPAT) were assessed using multiple linear regression adjusted for confounding factors., Results: Compared to inactive, VAT was progressively lower with weekend warrior (-0.71 L, 95% CI -0.78 to -0.64, P < 0.001) followed by regular activity (-0.96 L, 95% CI -1.04 to -0.88, P < 0.001). Observations were similar for EPAT (weekend warrior activity -2.84 cm
2 , 95% CI -3.20 to -2.49, P < 0.001; regular activity -3.62 cm2 , 95% CI -4.03 to -3.20, P < 0.001). When compared directly, weekend warriors had modestly higher adipose tissue than regular activity (VAT difference 0.25 L, 95% CI 0.17-0.32, P < 0.001; EPAT 0.78 cm2 , 95% CI 0.40-1.15, P < 0.001). No differences were observed after adjustment for total moderate-to-vigorous physical activity minutes (VAT 0.07 L, 95% CI -0.01 to 0.14, P = 0.09; EPAT 0.04 cm2 , 95% CI -0.35 to 0.43, P = 0.84)., Conclusions: Guideline-adherent physical activity is associated with favorable quantitative measures of cardiometabolic health, with no differences based on activity pattern for a given activity volume., Competing Interests: Funding support and author disclosures Dr Kany is supported by the Walter Benjamin Fellowship from the Deutsche Forschungsgemeinschaft (521832260). Dr Rämö is supported by a research fellowship from the Sigrid Jusélius Foundation. Dr Pirruccello is supported by the NIH (K08HL159346). Dr Churchill is supported by the National Institutes of Health (K23HL15926201A1). Dr Guseh is supported by the American Heart Association (19AMFDP34990046) and the President and Fellows of Harvard College (5KL2TR002542-04). Dr Ellinor is supported by grants from the National Institutes of Health (1RO1HL092577, 1R01HL157635, 5R01HL139731), from the American Heart Association (18SFRN34230127, 961045), and from the European Union (MAESTRIA 965286). Dr Lubitz previously received support from NIH grants R01HL139731 and R01HL157635, and American Heart Association18SFRN34250007. Dr Al-Alusi is supported by the NIH (T32-HL007208). Dr Khurshid is supported by the NIH (K23HL169839-01) and the American Heart Association (2023CDA1050571). Dr Ellinor receives sponsored research support from Bayer AG, IBM Research, Bristol Myers Squibb, Pfizer, and Novo Nordisk; he has also served on advisory boards or consulted for MyoKardia and Bayer AG. Dr Lubitz is an employee of Novartis as of July 2022; has received sponsored research support from Bristol Myers Squibb, Pfizer, Boehringer Ingelheim, Fitbit, Medtronic, Premier, and IBM; and has consulted for Bristol Myers Squibb, Pfizer, Blackstone Life Sciences, and Invitae. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.)- Published
- 2025
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