Prenatal smoking, alcohol and caffeine exposure and offspring externalizing disorders: a systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background and aims Several studies have indicated an association between maternal prenatal substance use and offspring externalizing disorders; however, it is uncertain whether this relationship is causal. We conducted a systematic review to determine: (1) if the literature supports a causal role of maternal prenatal substance use on offspring externalizing disorders diagnosis and (2) whether these associations differ across externalizing disorders. Methods We searched Web of Science, Embase, PsycINFO and Medline databases. Risk of bias assessment was conducted using the Newcastle–Ottawa Scale (NOS), and where possible meta‐analysis was conducted for studies classed as low risk of bias. We included studies of any design that examined prenatal smoking, alcohol or caffeine use. Studies in non‐English language, fetal alcohol syndrome and comorbid autism spectrum disorders were excluded. Participants in the included studies were mothers and their offspring. Measurements included prenatal smoking, alcohol or caffeine use as an exposure, and diagnosis of attention‐deficit hyperactivity disorder (ADHD), conduct disorder (CD) and oppositional defiant disorder (ODD) in offspring as an outcome. Results We included 63 studies, 46 of which investigated smoking and ADHD. All studies were narratively synthesized, and seven studies on smoking and ADHD were meta‐analysed. The largest meta‐analysis based on genetically sensitive design included 1 011 546 participants and did not find evidence for an association [odds ratio (OR) 1–9 cigarettes = 0.90, 95% confidence interval (CI) = 0.83–1.11; OR > 10 cigarettes = 1.04, 95% CI = 0.79–1.36). Studies on alcohol exposure in all the outcomes reported inconsistent findings and no strong conclusions on causality can be made. Studies on caffeine exposure were mainly limited to ADHD and these studies do not support a causal effect. Conclusions There appears to be no clear evidence to support a causal relationship between maternal prenatal smoking and offspring attention‐deficit hyperactivity disorder. Findings with alcohol and caffeine exposures and conduct disorder and oppositional–defiant disorder need more research, using more genetically sensitive designs.
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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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.008 | 0.008 |
| 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".