The effect of maternal prenatal tobacco smoking on offspring academic achievement: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Previous epidemiological studies examining the prospective association between maternal prenatal tobacco smoking and offspring academic achievement have reported conflicting results. Therefore, this systematic review and meta-analysis was conducted to examine the magnitude and consistency of association reported by those studies. METHODS: This systematic review and meta-analysis was guided by the PRISMA protocol. Relevant epidemiological studies on the topic were extracted from four main databases (PubMed/Medline, Embase, PsycINFO, and Scopus). The Newcastle-Ottawa Scale (NOS) was used to appraise the methodological quality of the included studies. We conducted a narrative assessment of the studies that did not report effect estimates. Inverse variance-weighted random effect meta-analysis was used to combine studies reporting effect sizes to estimate pooled adjusted odds ratio with 95% confidence intervals (95% CI). The review was prospectively registered in PROSPERO (CRD42022350901). RESULTS: Nineteen observational studies, published between 1973 and 2021 with a total of 1.25 million study participants were included in the final review. Of these, fifteen studies (79 %) reported reduced academic achievement in offspring exposed to maternal prenatal tobacco smoking. The eight primary studies (sample size = 723,877) included in the meta-analysis together suggested a 49 % higher risk of reduced academic achievement in offspring exposed to maternal prenatal tobacco smoking when compared to non-exposed offspring (Pooled odds ratio = 1.49, 95 % CI:1.17-1.91). CONCLUSION: Our review found a positive association between maternal prenatal tobacco smoking and offspring reduced academic achievement. However, variation in the adjustment of potential confounders and significant heterogeneity across included studies limited more conclusive inference. Mechanistic studies to identify causal pathways and specific academic impacts are needed to inform targeted developmental programs to assist child learning and academic performance.
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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 | 0.019 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".