ADOLESCENT PHYSICAL ACTIVITY AND ADULT BONE MINERAL STATUS
Bibliographic record
Abstract
Previous studies have shown a positive effect of physical activity on bone mineral density; however, most of these studies have used retrospective approaches and most did not differentiate physical activities based on impact loading on bone. PURPOSE The purpose of this study was to examine the relationship between self-reported physical activity during adolescence and adult bone mineral density (BMD) in 58 males from the Saskatchewan Growth and Development Study (SGDS). METHODS As part of the SGDS, detailed physical activity patterns were assessed annually from 1971 to 1973 (subjects were 14–16 years of age). An impact loading score was calculated based on the estimated loads of the various self-reported activities. An average score was then computed for these 3 years and subjects were placed into tertiles of physical activity impact categories: low; moderate; high. The original SGDS subjects were followed-up in 1997–98, when they were 38–40 years of age. At this time, BMD of the lumbar spine (LS) and femoral neck (FN) were measured using dual energy x-ray absorptiometry (Hologic 2000, array mode). RESULTS At follow-up, there were no differences among groups in adult height, weight, physical fitness, or physical activity scores (p < .05). BMD data were analyzed using a MANOVA procedure, and post-hoc comparisons done with a LSD test. Results showed a positive and significant difference (p < .05) between the low and the high impact group, and the moderate and high impact group at the FN. There were no differences at the LS. CONCLUSION The results of this study are consistent with others that have shown a significant relationship between adolescent physical activity and adult femoral BMD. These data support the theory that physical activity during adolescence is related to adult skeletal health. Supported by CIHR Grant MOP-57671
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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 | 0.001 |
| 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".