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Record W4407246565 · doi:10.1371/journal.pone.0317112

The association between maternal tobacco smoking during pregnancy and the risk of attention-deficit/hyperactivity disorder (ADHD) in offspring: A systematic review and meta-analysis

2025· review· en· W4407246565 on OpenAlexaboutno aff
Mahdi Mohammadian, Lusine Khachatryan, Filipp V. Vadiyan, Mostafa Maleki, Fatemeh Fatahian, Abdollah Mohammadian-Hafshejani

Post-publication record

NatureRetraction
ReasonConcerns/Issues about Article;Investigation by Journal/Publisher;Objections by Author(s);Unreliable Results and/or Conclusions;
Date12/17/2025 0:00
Flagged by OpenAlex?Yes

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenuePLoS ONE · 2025
Typereview
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsOffspringAttention deficit hyperactivity disorderMeta-analysisPregnancyMedicineTobacco usePsychiatryEnvironmental healthBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

INTRODUCTION: Maternal tobacco smoking during pregnancy is a significant public health concern with potential long-lasting effects on child development. ADHD, a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity, may be influenced by prenatal nicotine exposure. This systematic review and meta-analysis examine the association between maternal tobacco smoking during pregnancy and the risk of ADHD in offspring. METHODS: Following PRISMA guidelines, we searched databases including PubMed, Web of Science, Cochrane Central, Embase, Scopus, CINAHL, LILACS, SciELO, Allied and Complementary Medicine Database (AMED), ERIC, CNKI, HTA Database, Dialnet, EBSCO, LENS, and Google Scholar for studies up to November 1, 2024. We included peer-reviewed studies reporting quantitative effect size estimates for the association between maternal tobacco smoking and ADHD. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). RESULTS: We identified 2,981 articles and included 55 studies (4,016,522 participants) in the analysis. The meta-analysis showed a significant association between maternal tobacco smoking during pregnancy and increased risk of ADHD in offspring (pooled Odds Ratio (OR) = 1.71, 95% CI: 1.55-1.88; P < 0.001). Egger's test indicated no publication bias (p = 0.204), but Begg's test did (p = 0.042). By employing the trim and fill method, the revised OR was estimated to be 1.54 (95% CI: 1.40-1.70; P < 0.001). The OR were 2.37 (95% CI: 1.72-3.28; P < 0.001) in cross-sectional studies, 1.72 (95% CI: 1.49-2.00; P < 0.001) in case-control studies, and 1.53 (95% CI: 1.34-1.74; P < 0.001) in cohort studies. Meta-regression showed study design and study region significantly influenced heterogeneity (P < 0.10). Sensitivity and subgroup analyses confirmed the robustness of these findings. CONCLUSION: This systematic review and meta-analysis demonstrate a significant association between maternal tobacco smoking during pregnancy and increased odds of ADHD in offspring. These findings highlight the need for prenatal care guidelines and tobacco smoking cessation programs for pregnant women to reduce ADHD risk and promote optimal neurodevelopmental outcomes. Future research should explore underlying mechanisms and potential confounders further.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.035
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0170.032
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.087
GPT teacher head0.321
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

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