Associations of acetaminophen use during pregnancy and the first year of life with neurodevelopment in early childhood
Bibliographic record
Abstract
BACKGROUND: Over-the-counter analgesic use during pregnancy, particularly acetaminophen, may be associated with negative developmental outcomes in children. OBJECTIVE: Estimate associations of prenatal and early-life exposure to acetaminophen in early childhood with cognitive, motor, and language skills in two birth cohorts. METHODS: The American Project Viva cohort (1217 mother-child pairs enrolled 1999-2002) assessed cognition at approximately 3 years using the Peabody Picture Vocabulary Test and the Wide Range Achievement of Visual Motor Abilities (WRAVMA). The Brazilian 2015 Pelotas Birth Cohort (3818 mother-child pairs) assessed cognition at 2 years using the INTERGROWTH-21st Neurodevelopment Assessment. We used linear regression to estimate associations of acetaminophen use during pregnancy (Project Viva and Pelotas) and infancy (Project Viva) with children's cognitive scores adjusted for maternal age, pre-pregnancy body mass index, education, parity, race/ethnicity, smoking and alcohol use during pregnancy, depression during pregnancy, antibiotic and ibuprofen use during pregnancy, household income, and child's sex. RESULTS: In Project Viva, exposure to acetaminophen in both the 1st and 2nd trimester of pregnancy was associated with lower WRAVMA drawing scores (β -1.51, 95% CI -2.92, -0.10). However, in Pelotas, exposure to acetaminophen in both the 1st and 2nd trimester of pregnancy was not associated with INTER-NDA motor scores (β 0.02; 95% CI -0.05, 0.09) and was associated with higher INTER-NDA total scores (β 0.08, 95% CI 0.01, 0.16). Other comparisons did not show evidence for any associations. CONCLUSIONS: Inconsistencies and lack of specificity of the findings did not clarify the research question considering that we still have a large variability and uncertainty to define the risk or safety in the use of acetaminophen related to cognition in early childhood. More studies using better exposure assessment and better confounding variables are needed to clarify these associations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".