Survival of the fittest: retrospective cohort study of the longevity of Olympic medallists in the modern era
Bibliographic record
Abstract
OBJECTIVE: To determine whether Olympic medallists live longer than the general population. DESIGN: Retrospective cohort study, with passive follow-up and conditional survival analysis to account for unidentified loss to follow-up. SETTING AND PARTICIPANTS: 15 174 Olympic athletes from nine country groups (United States, Germany, Nordic countries, Russia, United Kingdom, France, Italy, Canada, and Australia and New Zealand) who won medals in the Olympic Games held in 1896-2010. Medallists were compared with matched cohorts in the general population (by country, age, sex, and year of birth). MAIN OUTCOME MEASURES: Relative conditional survival. RESULTS: More medallists than matched controls in the general population were alive 30 years after winning (relative conditional survival 1.08,95% confidence interval 1.07 to1.10). Medallists lived an average of2.8 years longer than controls. Medallists in eight of the nine country groups had a significant survival advantage compared with controls. Gold, silver, and bronze medallists each enjoyed similar sized survival advantages. Medallists in endurance sports and mixed sports had a larger survival advantage over controls at 30 years (1.13, 1.09 to 1.17; 1.11,1.09 to 1.13) than that of medallists in power sports (1.05,1.01 to 1.08). CONCLUSIONS: Olympic medallists live longer than the general population, irrespective of country, medal, or sport. This study was not designed to explain this effect, but possible explanations include genetic factors, physical activity, healthy lifestyle, and the wealth and status that come with international sporting glory.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".