Impact of folic acid food fortification on the birth prevalence of lipomyelomeningocele in Canada
Bibliographic record
Abstract
BACKGROUND: Recent studies reported no reduction in the frequency of lipomeningomyelocele (LMMC) in Hawaii and Nova Scotia after the implementation of a folic acid food fortification policy in 1998, while a marked reduction in the prevalence of other NTDs was observed. This study was performed to assess the prevalence of LMMC in Canada in relation to the timing of food fortification. METHODS: The study population included livebirths, stillbirths, and terminations of pregnancies because of fetal anomaly to women residing in seven Canadian provinces, from 1993 to 2002. In each province, the ascertainment of NTD cases relied on multiple sources, and in addition all medical charts were reviewed. The study period was divided into pre-, partial, and full fortification periods, based on results of red cell folate tests published in the literature. RESULTS: A total of 86 LMMC cases were recorded among approximately 1.9 million live births. The average birth prevalence rate was 0.05/1,000, ranging from a minimum of 0.01/1,000 in 2002 to a maximum of 0.08/1,000 in 1999. There was statistical heterogeneity between years (p = .01), but no pattern compatible with a decrease following fortification. Comparing the full fortification period with the prefortification period, there was a slight but not statistically significant decrease in LMMC birth prevalence. CONCLUSIONS: LMMC seems to be pathogenically distinct from myelomeningocele and more studies are needed to understand the embryologic mechanisms leading to this condition, and the environmental and genetic factors involved in its etiology.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".