Maternal cannabis use in pregnancy, perinatal outcomes, and cognitive development in offspring: a longitudinal analysis of the ALSPAC cohort using paternal cannabis use as a negative control exposure
Bibliographic record
Abstract
Maternal cannabis use in pregnancy is reported to be associated with perinatal and neurodevelopmental outcomes in offspring. Such associations, however, may be biased by residual confounding by socioeconomic position (SEP). To assess confounding, we use paternal cannabis use in pregnancy as a negative control exposure. We use data from 15,013 mother-father-child trios from the ALSPAC birth cohort, with participants initially recruited between 1990 and 1992. Exposures were maternal and paternal cannabis use during pregnancy. Neonatal anthropometry, perinatal, cognitive, and neurodevelopmental outcomes were modelled as a function of maternal and paternal cannabis use in pregnancy, adjusting for household-level SEP markers and maternal and paternal tobacco, alcohol, and drug use in pregnancy. We compared the strength of the association between maternal and paternal cannabis on outcomes using Wald tests. 5 and 13% of mothers and fathers reported cannabis use, which was inversely related to measures of SEP. Maternal cannabis use during pregnancy was associated with decreased infant birth weight (b = - 110.2 g, 95% CI - 185.1 to - 35.3 for any cannabis use) and length (b = - 0.45 cm, 95% CI - 0.84 to - 0.07). Maternal cannabis during pregnancy was also associated with neonatal special care admission (odds ratio 1.64, 95% CI 1.05 to 2.56) and lower education achievement scores at age 16 (b = - 19.2, 95% CI - 32.0 to - 6.3). Maternal cannabis use in pregnancy was modestly associated with perinatal outcomes and markers of cognitive development. However, most associations were attenuated after controlling for potential confounders, including SEP, and associations were not quantitatively different from paternal cannabis use. The association of maternal cannabis use in pregnancy with perinatal or cognitive outcomes in offspring may be driven by residual confounding, including SEP, rather than causal biological effects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".