Birth, cognitive and behavioral effects of intrauterine cannabis exposure in infants and children: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Δ9-tetrahydrocannabinol (THC), the principal psychoactive component of cannabis, has been implicated in affecting fetal neurodevelopment by readily crossing the placenta. However, little is known regarding the long-term effects of intrauterine cannabis exposure. This systematic review and meta-analysis synthesized prospective and cross-sectional human studies to measure the effects of intrauterine cannabis exposure on birth, behavioral, psychological and cognitive outcomes in infancy until early childhood. METHODS: Reporting according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, cross-sectional and prospective studies published from database inception until June 2023, investigating developmental outcomes of infants, toddlers and young children with intrauterine cannabis exposure were considered. All articles were obtained from PubMed or PsycINFO databases. RESULTS: The literature search resulted in 932 studies, in which 57 articles met eligibility criteria. The meta-analysis revealed that intrauterine cannabis exposure increases the risk of preterm delivery [odds ratio (OR) = 1.68, 95% confidence interval (CI) = 1.05-2.71, P = 0.03], low birth weight (OR = 2.60, CI = 1.71-3.94, P < 0.001) and requirement for neonatal intensive care unit (NICU) admission (OR = 2.51, CI = 1.46-4.31; P < 0.001). Our qualitative synthesis suggests that intrauterine cannabis exposure may be associated with poorer attention and externalizing problems in infancy and early childhood. We found no evidence for impairments in other cognitive domains or internalizing behaviors. CONCLUSIONS: Prenatal cannabis use appears to be associated with lower birth weight, preterm birth and neonatal intensive care unit admission in newborns, but there is little evidence that prenatal cannabis exposure adversely impacts behavioral or cognitive outcomes in early childhood, with the exception of attention and externalizing problems.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".