Do Food Group Intake and Physical Activity during Growth Spurt Have Impact on Bone Health during Adulthood
Bibliographic record
Abstract
The amount of bone mass achieved during childhood to early adulthood is one the most important predictors of osteoporosis later in life. Since almost 25% of peak bone mass is attained during the 4‐year period around age at peak height velocity (APHV), we aimed to determine how milk and alternatives intake, fruit and vegetable (F&V) intake and physical activity (PA) during 4‐year period around PHV (growth spurt) impact maximum total‐body bone mineral density (Max‐TBBMD) at least 10 years after age at PHV (adulthood). The Saskatchewan Pediatric Bone Mineral Accrual Study (BMAS 1991‐2011) data from 103 participants (55 female and 48 male) were used for this analysis. Data were collected using serial 24‐h recalls, PA questionnaire and dual‐energy X‐ray absorptiometry machine. Biological age was defined as the number of years after PHV. We analyzed data using stepwise linear regression. Among all modifiable factors, adulthood F&V intake was a significant independent predictor of max‐TBBMD after adjusting for all potential variables (β=0.132 g/cm 2 ; P =0.014). Mean intake of F&V intake during adulthood was 4.82±2.58 serving/d with only 14.6% adequate intake. Other predictors were TBBMD at APHV, adulthood total body lean mass, height, and biological age at Max‐TBBMD. Beneficial effect of adulthood F&V intake might be due to acid‐buffering effect and providing nutrients and natural compounds essential for bone mineral maintenance during adulthood. The source of the research support was Canadian Institutes of Health Research (CIHR).
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".