Increased Dietary Cholesterol is Associated to Greater Increases in Hip Bone Mineral Density with Resistance Training in Seniors
Bibliographic record
Abstract
We have previously shown that dietary cholesterol was directly associated to lean mass gain in response to resistance training (RET). Presently, we examined the association of dietary cholesterol and other dietary factors with bone mineral variables response to RET. 49 men and women performed 12 weeks of whole body RET and submitted 24 hour dietary logs 3X/week for the 12 weeks. BMD was determined at the beginning and end using DEXA. Nutrition data was analyzed using Nutribase V Clinical software. Hip BMD (percent change) was significantly reduced when mean dietary cholesterol over the 12 weeks was below 3.5 mg/kg lean/day (‐1.4% (0.8)) compared to >3.5 mg/kg/day (3.0% (0.7)). Multivitamin use (yes= 2.0% (1.0), no=0.4% (0.5)) and gender (M=3.0% (1.0), W= −1.5% (0.6) were also significantly associated to these changes. Similar associations were not found with Ward’s triangle or lumbar spine bone mineral changes. Other variables such as statins, estrogen, calcium, vitamin D kcal/kg, age or blood cholesterol were not associated to bone mineral variables. These results suggest that dietary cholesterol, multivitamin use and gender influence the magnitude of hip bone mineral responses to RET.
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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".