Effect of Folic Acid Food Fortification in Canada on Congenital Heart Disease Subtypes
Bibliographic record
Abstract
BACKGROUND: Previous studies have yielded inconsistent results for the effects of periconceptional multivitamins containing folic acid and of folic acid food fortification on congenital heart defects (CHDs). METHODS: We carried out a population-based cohort study (N=5 901 701) of all live births and stillbirths (including late-pregnancy terminations) delivered at ≥20 weeks' gestation in Canada (except Québec and Manitoba) from 1990 to 2011. CHD cases were diagnosed at birth and in infancy (n=72 591). We compared prevalence rates and temporal trends in CHD subtypes before and after 1998 (the year that fortification was mandated). An ecological study based on 22 calendar years, 14 geographic areas, and Poisson regression analysis was used to quantify the effect of folic acid food fortification on nonchromosomal CHD subtypes (n=66 980) after controlling for changes in maternal age, prepregnancy diabetes mellitus, preterm preeclampsia, multiple birth, and termination of pregnancy. RESULTS: The overall birth prevalence rate of CHDs was 12.3 per 1000 total births. Rates of most CHD subtypes decreased between 1990 and 2011 except for atrial septal defects, which increased significantly. Folic acid food fortification was associated with lower rates of conotruncal defects (adjusted rate ratio [aRR], 0.73, 95% confidence interval [CI], 0.62-0.85), coarctation of the aorta (aRR, 0.77; 95% CI, 0.61-0.96), ventricular septal defects (aRR, 0.85; 95% CI, 0.75-0.96), and atrial septal defects (aRR, 0.82; 95% CI, 0.69-0.95) but not severe nonconotruncal heart defects (aRR, 0.81; 95% CI, 0.65-1.03) and other heart or circulatory system abnormalities (aRR, 0.98; 95% CI, 0.89-1.11). CONCLUSIONS: The association between food fortification with folic acid and a reduction in the birth prevalence of specific CHDs provides modest evidence for additional benefit from this intervention.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".