Fluoride Exposure during Fetal Development and Childhood IQ: The MIREC Study
Bibliographic record
Abstract
Background: The potential neurotoxicity of early life exposure to fluoride, which has sparked controversy about community water fluoridation, is poorly understood.Objective: To test the association between fluoride exposure during fetal development and childhood IQ in a Canadian sample of 510 mother-child pairs enrolled in the Maternal-Infant Research on Environmental Chemicals (MIREC) birth cohort; 38% received “optimal” levels of community fluoridated water.Methods: We measured three maternal urinary fluoride (MUF) concentrations during pregnancy, averaged them and adjusted them for specific gravity. Children’s cognitive abilities were assessed using the Wechsler Primary and Preschool Scale of Intelligence-III at 3-4 years of age. We used multiple linear regression analyses to examine covariate-adjusted associations between MUF and IQ, and to test for interaction with child’s sex. We retained the following covariates based on theoretical and statistical relevance: city, quality of child’s home environment, maternal education, and race.Results: Average MUF concentrations for all women were 0.51 mg/L (+/-0.36; range=0.06-2.44); MUF concentrations were lower in women supplied with non-fluoridated water (0.40 mg/L +/-0.27) than women supplied with fluoridated water (0.69 mg/L +/-0.41). MUF levels were inversely associated with Full Scale IQ in males (B=-4.51, 95% CI: -8.39, -0.63, p=0.02), but not in females (B=2.43, p=0.33). Among males, higher MUF levels were associated with a significantly larger reduction in Performance IQ (B=-4.63, p=0.04) than Verbal IQ (B=-2.85, p=0.14). Sensitivity analyses using MUF adjusted for creatinine and controlling for other known neurotoxins (i.e., lead, mercury and arsenic) did not substantially change the results.Conclusion: An increase of 1mg/L of MUF during prenatal development was associated with a decrease of Full Scale IQ by 4.5 points in young boys.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".