Dietary carbohydrates: a review of international recommendations and the methods used to derive them
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Renewed dietary recommendations for carbohydrates have recently been published by various international health authorities. The present work (1) reviews the methods and processes (systematic approach/review, inclusion of public consultation) used to identify, select and grade the evidence underpinning the recommendations, particularly for total carbohydrate (CHO), fibre and sugar consumption, and (2) examines the extent to which variation in the methods and processes applied relates to any differences in the final recommendations. SUBJECTS/METHODS: A search of WHO, US, Canada, Australia and European sources identified 19 documents from 13 authorities with the desired detailed information. Processes and methods applied to derive recommendations were compiled and compared. RESULTS: (1) A relatively high total CHO and fibre intake and limited intake of (added or free) sugars are generally recommended. (2) Even where recommendations are similar, the specific justifications for quantitative/qualitative recommendations differ across authorities. (3) Differences in recommendations mainly arise from differences in the underlying definitions of CHO exposure and classifications, the degree to which specific CHO-providing foods and food components were considered, and the choice and number of health outcomes selected. (4) Differences in the selection of source material, time frames or data aggregation and grading methods appeared to have minor influence. CONCLUSIONS: Despite general consistency, apparent differences among the recommendations of different authorities would likely be minimized by: (1) More explicit quantitative justifications for numerical recommendations and communication of uncertainty, and (2) greater international harmonization, particularly in the underlying definitions of exposures and range of relevant nutrition-related outcomes.
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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 | 0.055 | 0.119 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.026 | 0.022 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".