Bibliographic record
Abstract
Abstract The effect of dietary fat intake on human health has been a hot topic in public for the past four decades. You are what you eat. Dietary fat, as one of the three macronutrients, plays a critical role in health, both bad and good. Metabolic syndrome (MetS) is one of the common clinical disorder. The prevalence of MetS has steadily increased and is linked to a number of major chronic diseases. Intense research has produced massive findings with some pointing out to dramatic changes that may cause significant modification of what we eat, the type of food with various contents of fats and the percentage of all sorts of fats. This article reviews the research findings from animal models, mainly from cross‐sectional, longitudinal and ultimately from clinical trials regarding the prevalence of MetS, the relationship between dietary fat intake and MetS, as well as physiological and clinical effects of dietary fat on MetS. The negative and positive effects of fat on waist circumference, serum levels of triacylglycerol and high‐density lipoprotein cholesterol (HDL‐c), blood pressure, and fasting blood sugar, were individually reviewed as well. Moreover, the effects of mono‐ and polyunsaturated fatty acids substitution of saturated fats (MUFA and PUFA) and trans unsaturated fatty acids on MetS are separately discussed. Finally, contradictory findings and challenges regarding the relationship between dietary fat intake and prevalence of MetS have been explained.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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 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".