Projected Long‐Chain n‐3 Fatty Acid Intake Post‐Replacement of Vegetables Oils with Stearidonic Acid‐Modified Varieties: Results from a National Health and Nutrition Examination Survey 2003–2008 Analysis
Bibliographic record
Abstract
Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) intake is well below the amount recommended by the 2015-2020 Dietary Guidelines for Americans (0.25 g/day), supporting the need for alternative dietary sources. Stearidonic acid (SDA)-enriched soybeans were bioengineered to endogenously synthesize SDA, which can be readily metabolized to EPA in humans; thus, incorporating the derived SDA-enriched soybean oil into the food supply is a potential strategy to increase EPA. We performed a dietary modeling exercise using National Health and Nutrition Examination Survey 2003-2008 repeat 24-h dietary recall data (n = 24,621) to estimate the potential contribution of SDA-enriched oils to total long-chain n-3 fatty acid intake (defined as EPA + DHA + EPA-equivalents) following two hypothetical scenarios: (1) replacement of regular soybean oil with SDA soybean oil and (2) replacement of four common vegetable oils (corn, canola, cottonseed, and soybean) with respective SDA-modified varieties. Estimated median daily intakes increased from 0.11 to 0.16 g/day post-replacement of regular soybean oil with SDA-modified soybean oil, and to 0.21 g/day post-replacement of four oils with SDA-modified oil; the corresponding mean intakes were 0.17, 0.27, and 0.44 g/day, respectively. The percent of the population who met the 0.25 g/day recommendation increased from at least 10% to at least 30% and 40% in scenarios 1 and 2, respectively. Additional strategies are needed to ensure the majority of the US population achieve EPA and DHA recommendations, and should be assessed using methods designed to estimate the distribution of usual intake of these episodically consumed nutrients.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".