Novel high-oleic oil consumption for cardiometabolic health: a narrative review
Bibliographic record
Abstract
Several cardiometabolic disorders are risk factors for cardiovascular diseases (CVDs), and prevention is imperative in reducing the burden of these diseases on the healthcare system. Although novel high-oleic acid oils (HOOs) are now commonly used for high-temperature frying in both foodservice and the manufacture of processed foods, there are still limited data regarding their effects on CVD risk. This narrative review aims to clarify these effects by comparing HOOs with saturated fatty acid (SFA)-rich and polyunsaturated fatty acid (PUFA)-rich oils, first regarding their physicochemical properties and then concerning their effects on CVD risk factors using recent randomized controlled trials (RCTs). Overall, although HOOs are more stable than PUFA-rich oils, they do not have the same high-temperature stability as SFA-rich oils. RCTs demonstrate that HOO consumption improves the plasma lipid profile compared with SFA-rich oils while showing similar effects to those of PUFA-rich oils on CVD risk factors. Finally, the current literature lacks information on the actual consumption of HOOs, their long-term effects on cardiometabolic health, and the impact of prolonged heating of these oils on CVD risk factors. In sum, the short-term intake of HOOs may be beneficial for cardiometabolic health; however, more research is needed.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".