RETRACTED ARTICLE: Ambient air pollution and adverse birthoutcomes: a systematic review and meta-analysis
Post-publication record
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
Abstract
Several reviews have assessed the relationship between exposure to ambient air pollution and adverse birth outcomes during pregnancy, but the results remain controversial. The objective of this study was to assess this correlation quantitatively and to explore sources of heterogeneity. We included all published case-control or cohort studies that evaluated the correlation between ambient air pollution and low birth weight (LBW), preterm birth (PTB), and small for gestational age (SGA). Analytical methods and inclusion criteria were provided on the PROSPERO website (CRD42018085816). We evaluated pooled effects and heterogeneity. Subgroup analyses (grouped by exposure period, study settings, study design, exposure types, data source, Newcastle-Ottawa quality score (NOS), and adjustment for smoking or meteorological factors) were also conducted and publication bias was examined. The risk of bias in systematic reviews (ROBIS) tool was used to evaluate the overall risk of bias in this review. Forty studies met the inclusion criteria. We observed pooled odds ratios (ORs) of 1.03–1.21 for LBW and 0.97–1.06 for PTB when mothers were exposed to CO, NO 2 , NO x , O 3 , PM 2.5 , PM 10 , or SO 2 throughout their pregnancy. For SGA, the pooled estimate was 1.02 in relation to NO 2 concentrations. Subgroup analysis and sensitivity analysis decreased the heterogeneity to some extent, such as the subgroups of continuous measures (OR=0.98 (0.97–0.99), I 2 =0.0%) and NOS>7 (OR=0.98 (0.97–0.99), I 2 =0.0%) in evaluating the association between PTB and NO 2 . This review was completed with a low risk of bias. High concentrations of air pollution were significantly related to the higher risk of adverse birth outcomes. However, the sources of heterogeneity among studies should be further explored.
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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 | 0.024 | 0.125 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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".