Do Elite Athletes Live Longer? A Systematic Review of Mortality and Longevity in Elite Athletes
Bibliographic record
Abstract
BACKGROUND: Understanding of an athlete's lifespan is limited with a much more sophisticated knowledge of their competitive careers and little knowledge of post-career outcomes. In this review, we consider the relationship between participation at elite levels of sport and mortality risk relative to other athletes and age- and sex-matched controls from the general population. Our objective was to identify, collate, and disseminate a comprehensive list of risk factors associated with longevity and trends and causes of mortality among elite athletes. METHODS: were used to locate research articles. Seventeen additional articles were retrieved from reference lists found in these papers and a general web search. The inclusion criteria were the following: (1) publication year 1980 or later; (2) the study examined elite-level athletes; and (3) outcome data measured mortality/longevity trends and/or causes. RESULTS: Fifty-four peer-reviewed publications and three articles from online sources met the criteria for inclusion. Baseball, football, soccer, basketball, and cycling had the most reported data on elite athletes' lifespan longevities. A variety of mechanisms have attempted to explain mortality risk (e.g., handedness, playing position, achievement, etc.). Considerable support was found for superior longevity outcomes for elite athletes, particularly those in endurance and mixed sports. CONCLUSIONS: Future research into the mechanisms that may affect mortality risk is important for a better understanding of life expectancies in both eminent and non-eminent populations. Participation in elite sport is generally favorable to lifespan longevity. KEY POINTS: A majority of studies included in this review reported superior lifespan longevity outcomes for elite athletes compared to age- and sex-matched controls from the general population and other athletes.Several mechanisms within and between sports may have powerful effects on the overall lifespan longevities of players (e.g., type of sport, playing position, race, and energy system).Future research on mortality in elite athletes would benefit from more comprehensive statistical measures and reliable databases to determine potential mechanisms that may influence mortality trends and causes in both athlete and non-athlete samples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".