Despite higher n‐6 PUFAs, butter remains a reliable source of saturated fats across the world
Bibliographic record
Abstract
Recent epidemiological data and updated meta‐analyses indicates that the saturated fat from sources like butter is not harmful in appropriate quantities. However, anecdotal evidence suggests that commercial farming, with increased incorporation of linoleic acid [LA, an n‐6 polyunsaturated fatty acid (PUFA)] containing oilseeds in animal feeds enhances LA and depletes saturated fatty acids (SFA) in animal food sources like butter. However, concrete evidence is lacking. We hypothesized that across the world, n‐6 PUFA content in butter would be inversely proportional to SFA content and directly proportional to country‐wide n‐6 PUFA rich oilseed production rates. We analyzed fatty acid compositions of commercial table butter from 7 countries (USA, Canada, Japan, Australia, India, France and the Netherlands) via gas chromatography. A locally sourced butter from a grass‐fed cow was used as a reference. Rates of oilseed production in those countries were collected from the FAOStat 2012 database. Unsurprisingly, all commercial butter contained higher n‐6 and lower beneficial n‐3 PUFA than grass‐fed butter, except in Dutch butter where both were high. However, contrary to our hypothesis, LA content of butter was not reflective of oilseed production rates across countries. Moreover, instead of depleting SFA, LA levels were directly proportional to SFA in butter, with the highest present in Canadian butter. As, the increase of LA in commercial butter compared to our grass fed sample was only 1.17% of total fatty acids, we conclude that the issue of higher n‐6 PUFAs is minor and butter continues to be a reliable source of SFA (72–73% of all fatty acids) across the world. Support or Funding Information Dairy Farmers of Canada
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".