John Yudkin’s hypothesis: sugar is a major dietary culprit in the development of cardiovascular disease
Bibliographic record
Abstract
To date, the risk of developing atherosclerosis has extended beyond Western countries and now affecting individuals from various ethnic backgrounds and age groups. Traditional risk factors of atherosclerosis, such as hypercholesterolemia, has been better controlled than before due to highly effective and inexpensive therapies at lowering plasma cholesterol levels. However, the role of reducing dietary cholesterol intake, as a public healthy strategy, in preventing the occurrence of cardiovascular mortalities has been recently challenged. Indeed, despite our continuous decline of dietary cholesterol intake within the last 50 years, the incidence of cardiovascular mortalities has continued to rise, thus raising the possibility that other dietary factors, such as fructose-containing sugars, are the major culprit. In the 1970s, John Yudkin first proposed that sugar was the predominant dietary factor that underlies the majority of cardiovascular mortalities, yet his hypothesis was dismissed. However, over the last 25 years substantial scientific evidence has been accumulated to support Yudkin's hypothesis. The objectives of this review are to highlight Yudkin's significant contribution to nutritional science by reviewing his hypothesis and summarizing the recent advances in our understanding of fructose metabolism. The metabolic consequences of fructose metabolism, such as fructose-induced uricemia, insulin resistance, lipoprotein hyperproduction and chronic inflammation, and how they are linked to atherosclerosis as risk factors will be discussed. Finally, the review will explore areas that warrant future research and raise important considerations that we need to evaluate when designing future studies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".