Relationship between animal protein intake and muscle mass index in healthy women
Bibliographic record
Abstract
The amount and the type of dietary protein could play a role in determining the quantity of skeletal muscle mass. The aim was to examine the relationship between the type of protein intake and the level of muscle mass in healthy omnivorous and vegetarian Caucasian women. The design of the present study was an observational and cross-sectional study. Twenty-one omnivores (Om) and nineteen vegetarians (Ve) were recruited. Muscle mass index (urinary creatinine), dietary intake (5 d dietary records) and biochemical analyses (hormone, phyto-oestrogen and lipid profiles) were obtained. We found differences between groups for muscle mass (Ve: 18 kg v. Om: 23 kg; P = 0.010), muscle mass index (Ve: 6.7 kg/m2 v. Om: 8.3 kg/m2; P = 0.002), animal protein intake in g/d (P = 0.001) and in g/kg body weight per d (P = 0.003), plant protein intake in g/d (P = 0.015) and in g/kg body weight per d (P = 0.007), the animal:plant protein intake ratio (P = 0.001) and sex hormone-binding globulin (SHBG) (P = 0.001). Muscle mass index still correlated with animal protein intake in g/d (P = 0.001) and in g/kg body weight per d (P = 0.008), and the animal:plant protein intake ratio (P = 0.007) even after controlling for SHBG and plant protein intake. Finally, animal protein intake (g/d) was the independent predictor of muscle mass index (adjusted r2 0.42). Thus, a vegetarian diet is associated with a lower muscle mass index than is an omnivorous diet at the same protein intake. A good indicator of muscle mass index in women seems to be animal protein intake.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".