Sex differences in bone mineral content and bone geometry accrual: a review of the Paediatric Bone Mineral Accural Study (1991–2017)
Bibliographic record
Abstract
Context Girls’ and boys’ growth patterns differ in timing and tempo, and they have different lifestyles with regards to diet and physical activity. These factors have all been linked with bone mineral accrual.Objective To identify the associations of boys’ and girls’ growth, maturation, and lifestyle choices relating to parameters of bone geometry and mineral accrual.Methods Between 1991 and 1993, 251 children aged 8–15 years were recruited into a mixed-longitudinal cohort study (The Paediatric Bone Mineral Accrual Study (PBMAS)) and followed repeatedly over 26 years.Results It was found that girls matured approximately two years earlier than boys (11.8 vs. 13.4 years) but on average were shorter, had less lean mass and had greater fat mass (p < 0.05). There was a dissociation between the growth of bone and its mineralisation in both sexes. Boys had greater bone mass and bone geometry (p < 0.05). Both a healthy childhood diet and high levels of physical activity were associated with improved bone parameters.Conclusions Most, but not all, of the sex differences observed, were explained by height and lean mass differences. The importance of diet and physical activity on obtaining optimal bone mass during adolescence in both sexes was also paramount.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".