Serum trans-fatty acids level are positively associated with lower food security among american adults
Bibliographic record
Abstract
OBJECTIVES: In the current study we aimed to assess whether the food security is associated with serum trans-fatty acids (TFAs) and dietary fat. METHODS: Analyses were restricted to participants (from the US National Health and Nutrition Examination Survey) with data available on serum and diet TFAs and food security status from 2009 to 2010. All statistical analyses (analysis of covariance and linear regression) accounted for the survey design and sample weights. RESULTS: We included 3876 participants, overall (48.6%) participants were men, and (51.4%) were women, generally (69.0%) had high food security. Subjects with higher food security had a higher level of education as well (p < 0.001). Age-adjusted, sex-adjusted, race-adjusted, education-adjusted mean of trans 9-octadecenoic acid and trans-9, trans-12-octadecadienoic acid were higher in plasma of participants with lower food security (all p < 0.001), moreover in same model there was a significant positive association between plasma level of trans-11-octadecenoic acid, trans-9-octadecenoic acid and trans-9, trans-12-octadecadienoic acid and score of food security. Further, age, sex, race, education, and energy intake adjusted mean of dietary fatty acids show that total polyunsaturated fatty acids are higher in subjects with higher food security (p = 0.026) while, cholesterol consumption is higher in subjects with lower food security (p = 0.039). CONCLUSIONS: Our findings provide more evidence on the association between food insecurity and the higher level of TFAs in serum and different type of fat in the diet.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".