Association of physical activity and bone: influence of vitamin D receptor genotype
Bibliographic record
Abstract
PURPOSE: The aim of the study was to investigate the interaction between leisure physical activity and a BsmI polymorphism at the vitamin D receptor (VDR) gene on the modulation of bone mineral density (BMD). METHODS: We studied 575 unrelated healthy postmenopausal women. Lumbar spine and femoral neck BMD were measured by dual-energy x-ray absorptiometry (DXA), and results were expressed as age-and-weight-adjusted (Z-score). VDR BsmI genotype was determined by polymerase reaction chain on peripheral blood leukocytes. RESULTS: Overall, no significant association was found between the level of leisure physical activity or VDR genotypes and adjusted BMD at both bone sites. However, in active women, there was a trend for an association between VDR genotypes and adjusted BMD at the lumbar spine. Active women, who exercised three times or more a week, carrying the "bb" genotype had a lower BMD at the lumbar spine than active women carrying "BB" genotype (ANOVA; P = 0.04). No significant difference in crude or adjusted BMD at both bone sites was found between VDR genotypes in sedentary or moderately active women. Furthermore, classification of women according to the median-age of the sample (63.1 yr) revealed a significant interaction between the level of leisure physical activity and VDR genotype on adjusted lumbar spine BMD in the older active postmenopausal women (N = 137). Older active women carrying the "bb" genotype showed a lower adjusted BMD at the lumbar spine compared with active women carrying the "BB" genotype (P = 0.007). CONCLUSION: These results suggested that gene-environment interactions such as leisure physical activity and VDR genotype may play a role in maintaining the BMD at the lumbar spine in active postmenopausal women, especially in older active women.
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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 | 0.000 |
| 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".