Dietary Protein, Phosphorus and Potassium Are Beneficial to Bone Mineral Density in Adult Men Consuming Adequate Dietary Calcium
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to determine relationships of calcium (Ca), protein (Pr), phosphorus (P) and potassium (K) to measures of bone mineral density in adult men. METHODS: Cross-sectional analysis of 57 men ages 39 to 42 years who were participants in an ongoing study. Dietary assessment was conducted using the Block food frequency questionnaire (FFQ). BMD of total body (TB), hip and lumbar spine (LS) were measured with dual X-ray absorptiometry (DXA). RESULTS: Ca, Pr, P and K, as well as lean body mass (LBM), showed significant correlation with BMD at the total body, hip and lumbar spine. Stepwise forward regression selection method identified LBM, height and fat mass as significant predictors of TB-BMD, LBM and height as significant predictors of hip BMD, and LBM as a significant predictor of LS-BMD. As the nutrients tested correlated significantly with each other, only one nutrient was entered into the regression model at a time to accommodate the potential for multicollinearity. In regression analysis, adjusted for site-specific anthropometric variables and energy intake, K, Pr and P intake accounted for significant (p < 0.05) prediction of TB-BMD and LS-BMD values by 7% to 13%. No bone-related nutrient added significantly to the prediction of hip BMD. Ca intake was not significantly associated with BMD at any site in the adjusted models. CONCLUSIONS: Our analysis provides support that a moderate protein (1.2 g/kg) diet, plentiful in potassium (>100 mmol/day) and phosphorus (1741 +/- 535 mg) is beneficial for maintaining bone mineral density in adult men when Ca intake was adequate (1200 +/- 515 mg).
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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) | 0.001 | 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".