Remodeling of data in the 2004 Canadian Community Health Survey 2.2 (CCHS) using actual rather than mandated levels of folic acid fortification suggests a lower prevalence of inadequacy of folate in women of reproductive age
Bibliographic record
Abstract
Folic acid (FA) fortification of grain products has been mandatory in Canada for 10 years. Previously we reported that foods are over‐fortified by approximately 50% of the values in Canada's main food composition database, the Canadian Nutrient File. We used SIDE to calculate usual intakes of folate based on mandated and actual levels (based on 50% overage) of FA fortification from 24‐hour dietary recall data of approximately 35,000 respondents in the CCHS. In women of reproductive age, the prevalence of inadequacy (intakes below the Estimated Average Requirement) based on actual levels decreased by more than half when compared to that based on mandated levels (27.3% to 12.4% in 14‐18y; 24.5% to 10.2% in 19‐30y; 28.1% to 14.2% in 31‐50y). A similar decline was observed in lactating females (27.7% to 12%), while in pregnant females, the decline was more pronounced (50.2% to 18.4%). In sum, given its protective role in the prevention of neural tube defects, women capable of becoming pregnant should consume a FA supplement; however, at actual levels of FA fortification in the Canadian food supply, the prevalence of inadequacy in women of reproductive age is lower than estimated using mandated levels. Grant Funding Source Research Training Award
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".