Bibliographic record
Abstract
PURPOSE: To quantify the relationship between musculoskeletal fitness and all-cause mortality in the Canadian population. METHODS: The sample consisted of 8116 people (3933 men and 4183 women), aged 20-69 yr, who participated in the 1981 Canada Fitness Survey. Measures of musculoskeletal fitness included sit-ups, push-ups, grip strength, and sit-and-reach trunk flexibility. In the 13 yr after the Canada Fitness Survey, there were 238 deaths and a total of 101,685 person-years. Proportional hazards regression was used to estimate the risk of mortality across baseline age- and sex-specific quartiles of the musculoskeletal fitness measures. All models included the effects of age, smoking status, body mass, and estimated VO2max as covariates, and the upper quartile was set as the reference group. RESULTS: There was no pattern of increased risk of mortality across quartiles of trunk flexibility or push-ups; however, there was a significantly higher risk in the lower quartile of sit-ups in both men (relative risk (RR) = 2.72, 95% CI 1.56-4.64) and women (RR = 2.26, 95% CI 1.15-4.43). Grip strength was not predictive of mortality in women, although there was a 49% increased risk of death in the lower quartile of grip strength in males (RR = 1.49, 95% CI 0.86-2.59). CONCLUSION: The results suggest that some components of musculoskeletal fitness, particularly sit-ups (abdominal muscular endurance), are predictive of mortality in the Canadian population.
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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 | 0.000 | 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) | 0.002 | 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".