A comparison of the systematic reviews and meta-analyses conducted to explore the effect of air pollution exposure during pregnancy and the risk of preterm birth
Bibliographic record
Abstract
Background and aims There has been a rapid rise in systematic reviews and meta-analyses (SR/MAs) conducted on the association between air pollution exposure during pregnancy and the risk of preterm birth in recent years. Few studies have examined differences in their quality and if they have provided additional insight into the field. This study analysed previous SR/MAs to explore their practices and identify gaps and opportunities for the research field. This work was done to determine if an upcoming SR/MA was needed. Methods A literature search using major English and Chinese databases was performed to find SR/MAs published from 2010 onwards. Information regarding publication date, methods of quality assessment, consideration of population overlap, and primary studies included in their analysis were extracted and compared. Results Seventeen SR/MAs, which included thirteen MAs were conducted from 2010 onwards. A large variety of quality assessment tools were used, but the Newcastle-Ottawa Scale was the most common (n=6). Seven MAs explicitly mentioned that they took population overlap into account. Four SR/MAs were found in 2021 alone, but three did not examine the whole literature and focused on specific study designs or exposure assessment methods. They were thus unable to build on finding of previous work due to exclusion of studies that were included in other SR/MAs. Conclusions A considerable number of SR/MAs provided limited addition to the field as they were conducted without sufficient rigour. This may hinder coming to a consensus on the effect estimate of interest and overlook field-specific biases. Therefore, a new SR/MA with improvements in transparency in reporting, replicability of findings, and quality assessment of studies is required. The protocol of this SR/MA is now registered on PROSPERO and will begin in due course. Keywords Maternal exposure; preterm birth; meta-analysis; birth outcomes, air pollution; pregnancy
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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 | 0.160 | 0.393 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.023 | 0.056 |
| Bibliometrics | 0.056 | 0.037 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| 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".