Folate intake, markers of folate status and oral clefts: An updated set of systematic reviews and meta‐analyses
Bibliographic record
Abstract
BACKGROUND: There has been a longstanding debate about the role of folate in the etiology of orofacial clefts (OFCs). Studies of different measures of nutritional intake or folate status have been done to investigate the possible role of folate in the prevention of OFC. Only one knowledge synthesis has attempted to bring together different types of evidence. The aim of the present work was to update it. METHODS: Evidence for associations between OFC and dietary folate, supplement use, folic acid fortification, biomarkers of folate status, and variants of MTHFR (C677T and A1298C) were included. Potentially eligible articles were systematically identified from PubMed, Medline, Embase, and Web of Science (2007-2020) and combined using random-effects meta-analysis when appropriate. Quality assessments were conducted using the Newcastle-Ottawa scale and Cochrane's risk of bias tool. RESULTS: Sixty-four studies published since the previous knowledge synthesis were identified, with eight of these identified through a supplementary search from October, 2018 to August, 2020. There was an inverse association between folic acid-containing supplement use before or during pregnancy and cleft lip with or without cleft palate (CL/P) (OR 0.60, 95% CI 0.51-0.69), with considerable between-study heterogeneity. The prevalence of CL/P showed a small decline post-folic acid fortification in seven studies (OR 0.94, 95% CI 0.86-1.02). No association was found between OFC and genetic markers of folate status. The coronavirus-19 pandemic has threatened food availability globally and therefore there is a need to maintain and even enhance surveillance concerning maternal intake of folate and related vitamins. CONCLUSIONS: The risk of non-syndromic OFC was reduced among pregnant women with folic acid-containing supplements during the etiologically relevant period. However, high heterogeneity between included studies, incomplete reporting of population characteristics and variation in timing of exposure and supplement types mean that conclusions should be drawn with caution.
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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 | 0.019 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".