Association between bone mineral density and ground reaction force in male and female runners
Bibliographic record
Abstract
BACKGROUND: Bone responds to loading by accruing areal bone mineral density (BMD). Distance runners experience a ground reaction force (GRF) during exercise which contributes to bone loading. Sex differences in BMD reflect that males and females respond differently to running-imposed GRF. RESEARCH QUESTION: What is the relationship between GRF and BMD in male and female runners? METHODS: Forty participants (20 male; age=25.1 ± 4.5 years; height=1.7 ± 0.1 m; mass=67.2 ± 11.5 kg) who routinely participated in distance running (44.0 ± 26.1 km/week over 4.5 ± 1.5 weekly sessions for the past 6.9 ± 5.2 years) underwent dual x-ray absorptiometry to calculate BMD and ran on a force-instrumented treadmill to measure vertical GRF characteristics at a self-selected (SS) and at a standardized pace (SP; 3.33 m/s). Independent samples t-tests compared outcomes between males and females. Pearson correlation examined associations between GRF and BMD separately based on sex. RESULTS: Absolute GRF and BMD outcomes were consistently lower in females compared with males (all p < 0.05). At SS, greater BMD in some sites was associated with greater vertical GRF (r = 0.582-0.793, p < 0.001-0.007), vertical loading rate (r = 0.459-0.626, p = 0.003-0.042), and vertical impulse (r = 0.518-0.759, p < 0.001-0.019) in males. Greater BMD in some sites was also associated with greater vertical GRF (r = 0.550-0.736, p < 0.001-0.012), vertical loading rate (r = 0.495-0.718, p < 0.001-0.026), and vertical impulse (r = 0.478-0.755, p < 0.001-0.033) in males at SP. There were no associations between BMD and GRF in females at either pace (r = -0.095-0.360, p = 0.130-0.983). SIGNIFICANCE: The associations between GRF and BMD in runners differ between males and females. Supplemental training methods may be necessary for female runners to influence BMD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".