Current Evidence Supporting the Link Between Dietary Fatty Acids and Cardiovascular Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lack of consensus exists pertaining to the scientific evidence regarding effects of various dietary fatty acids on cardiovascular disease (CVD) risk. The objective of this article is to review current evidence concerning cardiovascular health effects of the main dietary fatty acid types; namely, trans (TFA), saturated (SFA), polyunsaturated (PUFA; n-3 PUFA and n-6 PUFA), and monounsaturated fatty acids (MUFA). Accumulating evidence shows negative health impacts of TFA and SFA; both may increase CVD risk. Policies have been proposed to reduce TFA and SFA consumption to less than 1 and 7 % of energy intake, respectively. Cardiovascular health might be promoted by replacing SFA and TFA with n-6 PUFA, n-3 PUFA, or MUFA; however, the optimal amount of PUFA or MUFA that can be used to replace SFA and TFA has not been defined yet. Evidence suggests of the potential importance of restricting n-6 PUFA up to 10 % of energy and obtaining an n-6/n-3 ratio as close as possible to unity, along with a particular emphasis on consuming adequate amounts of essential fatty acids. The latest evidence shows cardioprotective effects of MUFA-rich diets, especially when MUFA are supplemented with essential fatty acids; namely, docosahexaenoic acid. MUFA has been newly suggested to be involved in regulating fat oxidation, energy metabolism, appetite sensations, weight maintenance, and cholesterol metabolism. These favorable effects might implicate MUFA as the preferable choice to substitute for other fatty acids, especially given the declaration of its safety for up to 20 % of total energy.
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.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it