Site and sex specific bone mineral content, and density trajectories from adolescence through to 15 years post peak bone mass
Bibliographic record
Abstract
BACKGROUND: Relatively, little is known about bone parameter trajectories after attainment of peak bone mass (PBM). AIM: To investigate the individual and mean trajectories of bone mineral content (BMC) and areal bone mineral density (aBMD) after the attainment of PBM at four anatomical sites (Total Body (TB), Lumbar Spine (LS), Total Hip (TH), Femoral Neck (FN)). SUBJECTS AND METHODS: SITAR models were fitted to 162 individual's (70 males and 92 females) longitudinally collected bone parameters. RESULTS: It was found from PBM to 15-years post PBM, that males TB, TH and LS increased by 4-7% in BMC and by 10% in TB aBMD, and a 1.3% decrease in FN BMC and a 2-4% decrease in LS, TH and FN aBMD. In comparison, females TB, LS TH and FN increased by 1-7% in BMC and increased in TB and LS aBMD by 3-15% and decreased by 1-3% in TH and FN aBMD, 15 years after the attainment of PBM. CONCLUSION: Comparing the change to the precision of the instrument it was found that males and females showed real change in BMC at the TB, LS and TH but no real change at the FN from PBM to 15 years post PBM. In aBMD a real increase was found in TB and decrease in FN. Future studies should explore the roles of other factors, such as changes in lifestyle, related to bone mineral change after PBM attainment on bone trajectories.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 | 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".