Global nutritional recommendations: a combination of evidence and food availability?
Bibliographic record
Abstract
Abstract Diet and exercise are vital diabetes management strategies. Health professionals (HPs) use dietary guidelines to advise their clients but the current macronutrient recommendation in the guidelines varies. The aim of this study was to explore the similarities and differences in macronutrient dietary advice in different parts of the world and suggest some reasons for any differences identified. The study was undertaken in two phases: (1) a one‐shot cross‐sectional survey of HPs and global diabetes organisations using self‐completed, anonymous questionnaires (n=40), and (2) a review of dietary guidelines from relevant diabetes associations (the American Diabetes Association [ADA], the Diabetes and Nutrition Study Group [DNSG] of the European Association for the Study of Diabetes [EASD], the Canadian Diabetes Association [CDA], the Joslin Diabetes Center, Diabetes UK, and the Indian Council of Medical Research [ICMR]). Dietary recommendations differed among countries and from the guidelines, and reflected socioeconomic factors and local food availability. With regard to macronutrient recommendations, carbohydrate ranged from 40–70%, protein 12–20% and fat 15–40% of total energy intake. Nations with higher gross domestic product (GDP) based on purchasing‐power‐parity (PPP) per capita tended to recommend a much lower ratio of carbohydrate than those with lower GDP PPP per capita . However, all guidelines stressed the importance of healthy eating. It was concluded that socioeconomic factors and local food availability appear to influence HPs' dietary recommendations. Copyright © 2008 John Wiley & Sons.
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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 | 0.000 | 0.004 |
| 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".