A review of the effect of omega-3 polyunsaturated fatty acids on blood triacylglycerol levels in normolipidemic and borderline hyperlipidemic individuals
Bibliographic record
Abstract
Circulating levels of triacylglycerol (TG) is a recognized risk factor for developing cardiovascular disease, a leading cause of death worldwide. The Institute of Medicine and the American Heart Association both recommend the consumption of n-3 polyunsaturated fatty acids (PUFA), specifically eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), to reduce serum TG in hyperlipidemic individuals. Additionally, a number of systematic reviews have shown that individuals with any degree of dyslipidemia, elevated serum TG and/or cholesterol, may benefit from a 20-30% reduction in serum TG after consuming n-3 PUFA derived from marine sources. Given that individuals with serum lipid levels ranging from healthy to borderline dyslipidemic constitute a large portion of the population, the focus of this review was to assess the potential for n-3 PUFA consumption to reduce serum TG in such individuals. A total of 1341 studies were retrieved and 38 clinical intervention studies, assessing 2270 individuals, were identified for inclusion in the current review. In summary, a 9-26% reduction in circulating TG was demonstrated in studies where ≥ 4 g/day of n-3 PUFA were consumed from either marine or EPA/DHA-enriched food sources, while a 4-51% reduction was found in studies where 1-5 g/day of EPA and/or DHA was consumed through supplements. Overall, this review summarizes the current evidence with regards to the beneficial effect of n-3 PUFA on circulating TG levels in normolipidemic to borderline hyperlipidemic, otherwise healthy, individuals. Thus demonstrating that n-3 PUFA may play an important role in the maintenance of cardiovascular health and disease prevention.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".