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The Aging Athlete: Paradigm of Healthy Aging

Gries, Kevin J., Trappe, Scott W.·2022·International Journal of Sports Medicine

Abstract

The Exercise Boom of the 1970’s resulted in the adoption of habitual exercise in a significant portion of the population. Many of these individuals are defying the cultural norms by remaining physically active and competing at a high level in their later years. The juxtaposition between masters athletes and non-exercisers demonstrate the importance of remaining physically active throughout the lifespan on physiological systems related to healthspan (years of healthy living). This includes ~50% improved maximal aerobic capacity (VO2max) and enhanced skeletal muscle health (size, function, as well as metabolic and communicative properties) compared to non-exercisers at a similar age. By taking a reductionist approach to VO2max and skeletal muscle health, we can gain insight into how aging and habitual exercise affects the aging process. Collectively, this review provides a physiological basis for the elite performances seen in masters athletes, as well as the health implications of lifelong exercise with a focus on VO2max, skeletal muscle metabolic fitness, whole muscle size and function, single muscle fiber physiology, and communicative properties of skeletal muscle. This review has significant public health implications due to the potent health benefits of habitual exercise across the lifespan.

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Cited by

Metadata

Authors
Gries, K. J., & Trappe, S. W.
Affiliations
  • Program in Exercise & Sports Science, Marian University, Indianapolis, Indiana, USA
  • Human Performance Laboratory, Ball State University, Muncie, Indiana, USA
Venue
International Journal of Sports Medicine
Published
2022-02-04
Volume
43
Issue
08
Pages
661-678
ISSN
  • 0172-4622
  • 1439-3964
Cited by
22
References
34
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.