The association between physical activity during growth and bone microarchitecture at peak bone mass
Bibliographic record
Abstract
Childhood and adolescence are critical periods for skeletal development in establishing peak bone mass (PBM), an important determinant of lifelong fracture risk. This study investigates the relationship between cumulative physical activity during growth and bone density and microarchitecture attained surrounding PBM. BMD and microarchitecture properties were obtained in 226 individuals (142 females; 84 males) surrounding PBM (aged 18-35 years) using HR-pQCT at the distal radius and tibia, and DXA at the lumbar spine and femoral neck. Physical activity during growth up to PBM was captured with the bone-specific physical activity questionnaire (BPAQ). Spearman's partial correlations, adjusted for age, height, and weight were used to determine sex-specific associations between bone properties and physical activity during growth. Higher physical activity during growth quantified by the BPAQ (gBPAQ) was associated with higher tibia failure load and femoral neck areal BMD, in both sexes (ρ = 0.27-0.38, p ≤ .02). Higher gBPAQ scores were also associated with better trabecular BMD and bone volume fraction at the tibia in both sexes, where associations were stronger in males (ρ = 0.40-0.41, p < .01) than in females (ρ = 0.24-0.26, p < .05). Males additionally had significant associations with trabecular bone microarchitecture properties, including number, separation, and inhomogeneity at both the radius (ρ = 0.30-0.34, p ≤ .01) and tibia (ρ = 0.31-0.42, p ≤ .02). In contrast, gBPAQ scores were not associated with cortical bone properties at PBM for either sex or site. Physical activity during growth is associated with greater BMD and failure load at PBM, 2 predictors of lifelong fracture risk. However, compartment-specific differences indicate that trabecular bone, as opposed to cortical bone, is more responsive to physical activity during growth.
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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 | 0.000 | 0.000 |
| 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".