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Masters Athletes: Exemplars of Successful Aging?
Abstract
Global population aging has raised academic interest in successful aging to a public policy priority. Currently there is no consensus regarding the definition of successful aging. However, a synthesis of research shows successful aging can be defined as a late-life process of change characterized by high physical, psychological, cognitive, and social functioning. Masters athletes systematically train for, and compete in, organized forms of team and individual sport specifically designed for older adults. Masters athletes are often proposed as exemplars of successful aging. However, their aging status has never been examined using a comprehensive multidimensional successful aging definition. Here, we examine the successful aging literature, propose a successful aging definition based on this literature, present evidence which suggests masters athletes could be considered exemplars of successful aging according to the proposed definition, and list future experimental research directions.
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“This may further contribute to a reduced risk of lean tissue loss, sarcopenia, and functional decline in combination with the benefits of ongoing exercise [3,10].”
From Dietary Intake of Masters Athletes: A Systematic Review (2023) · cites this paper as [10]
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“studying master endurance runners will remain methodologically valuable because this cohort provides a well-established human model of “successful/healthy ageing”, allowing for the investigation of age-related physiological decline under conditions of sustained high training exposure, thereby reducing confounding by the typical age-related reduction in physical activity [55,72,79].”
From Ageing, Sex Differences, and REDs Risk in Endurance Runners: An Integrated Cross-Sectional Study Protocol (2026) · cites this paper as [79]
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Metadata
- Authors
- Geard, D., Reaburn, P. R. J., Rebar, A. L., & Dionigi, R. A.
- Venue
- Journal of Aging and Physical Activity
- Publisher
- Human Kinetics
- Published
- 2017-07
- Volume
- 25
- Issue
- 3
- Pages
- 490-500
- ISSN
- 1063-8652
- 1543-267X
- Cited by
- 67
- References
- 26
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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.
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.