The effect of increasing intakes of plant protein on the protein quality of Canadian diets
Bibliographic record
Abstract
The 2015 Canadian Community Health Survey was used to investigate the protein content and protein quality of the diets consumed by adults (≥19 years) when plant protein is increased. Individuals (n = 6498) were allocated to quartiles of increasing proportions of protein from plant foods (Quartile 1: 0–24.9%; Quartile 2: 25%−49.9%; Quartile 3: 50–74.9%; Quartile 4: 75–100%). The Protein Digestibility Corrected Amino Acid Score (PDCAAS) of diets were estimated using indispensable amino acid concentrations of foods and an assumed digestibility coefficient of 0.8. Corrected protein intakes were determined by aggregating foods consumed over 24 hours and as the sum of corrected protein consumed at eating events within six 4-hour time intervals. Most individuals (51%) consumed 25–49.9% of protein from plant foods. Cereal-based foods represented the majority of plant protein consumed. PDCAAS of diets remained ≥0.87 for quartiles 1−3, but decreased (p < 0.0001) to 0.71 ± 0.018 in quartile 4 vs. quartile 2 (0.96 ± 0.004). Corrected protein intakes in quartile 2 (80.66 ± 1.21 g/day; 1.07 ± 0.03 g protein/kg body weight) decreased to 37.13 ± 1.88 g/day (0.54 ± 0.03 g/kg body weight) in quartile 4 (p < 0.0001). Aggregated daily corrected protein intake strongly correlated (r = 0.99; p < 0.001) with the sum of corrected protein consumed within time intervals. Intra-time interval analysis revealed that the relative proportions of animal and plant proteins changed at eating events over 24 hours and did not reflect the allocation to quartiles based on the daily proportion of plant protein consumption. Various tools should be explored and developed to assist Canadians in effectively incorporating plant protein foods into dietary patterns. Novelty: Corrected protein intakes decreased as plant protein consumption increased. PDCAAS was ≥0.87 for diets with ≤74.9% plant protein.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".