Dietary animal protein intake: association with muscle mass index in older women.
Bibliographic record
Abstract
BACKGROUND: Aging is associated with reductions in muscle mass and strength, so-called sarcopenia, and is generally characterized using muscle mass index (MMI = FFM (kg)/height (m)2). It is believed that adequate nutrition especially regarding protein intake, can delay this progression and enhance the quality of life of elders. OBJECTIVES: We examined whether the predominant source of protein consumed (animal or vegetal) by older women was associated with MMI. DESIGN: Thirty-eight healthy, normal weight, sedentary women, aged between 57-75 years (mean age: 66 +/- 5 years old), and taking no medication that could influence metabolism were recruited. Body composition was measured by dual-energy X-ray absorptiometry; muscle protein content was measured by the use of creatinine excretion. Physical activity metabolism was obtained by the use of accelerometry, and indirect calorimetry. Finally, protein intake was measured with a 3-day dietary record. RESULTS: Significant correlations were observed between MMI and body mass index, fat-free mass, muscle protein content, total protein intake, animal protein intake, fat mass, visceral fat and daily energy expenditure. However, a stepwise regression analysis showed animal protein intake to be the only independent predictor of MMI (r2=0.19; p=0.008). CONCLUSIONS: Our results suggest that protein intake, especially from animal sources, may be associated with a better preservation of MMI. However, more research is needed to confirm our results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".