Fortifying whole wheat flour with folic acid does not change the prevalence of folate inadequacy nor the percentage of Canadians with intakes above the Tolerable Upper Intake Level (UL)
Bibliographic record
Abstract
While folic acid fortification of white wheat flour in Canada has reduced neural tube defects, whole wheat flour does not fall under the current mandate. Our aim was to estimate the impact of adding folic acid to whole wheat flour on the folate intake distribution of Canadians. Twenty‐four hour dietary recalls and supplement intake data collected in the 2004 Canadian Community Health Survey 2.2 (n=35,107) were used for the analysis. The amount of folic acid added to whole wheat flour‐containing foods was set to be equivalent to the amount of folic acid in comparable white wheat flour products. SIDE (Software for Intake Distribution Estimation) was used to model distributions of folate intake and to estimate the prevalence of folate inadequacy (POFI) using the Estimated Average Requirement (EAR) cut‐point method and the proportion of the population with folic acid intakes >; UL. After folic acid addition to whole wheat foods, the POFI and intakes above the UL did not change among non‐supplement users (95% CIs overlap). Likewise, the POFI and percentages of intakes above the UL did not change after whole wheat flour fortification in supplement users (95% CIs overlap). Mean folate intake increased (432±3 to 454±3 μg DFE, p<0.0001) when whole wheat foods were fortified. In conclusion, adding folic acid to whole wheat flour will not likely change the POFI or proportion of folic acid intakes >; UL among Canadians. YC funded by NSERC‐CGS. Grant Funding Source : NSERC
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".