Exposure to drinking water pollutants and non-syndromic birth defects: a systematic review and meta-analysis synthesis
Bibliographic record
Abstract
OBJECTIVES: To evaluate the association between drinking water pollutants and non-syndromic birth defects. DESIGN: Systematic review and meta-analysis synthesis. DATA SOURCES: A search of MEDLINE, EMBASE and Google Scholar was performed to review relevant citations reporting on birth defects in pregnancies exposed to water pollutants between January 1962 and April 2023. ELIGIBILITY CRITERIA: Prospective or retrospective cohort, population studies and case-control studies that provided data on exposure to drinking water pollutants around conception or during pregnancy and non-syndromic birth defects. We included studies published in the English language after the Minamata Bay disaster to reflect on contemporary concerns about the effect of environmental pollution and obstetric outcomes. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently read the retrieved articles for content, data extraction and analysis. The methodological quality of studies was assessed using the Newcastle-Ottawa Scale. Included studies were assessed for comparability when considered for meta-analysis. RESULTS: 32 studies met inclusion criteria including 17 cohorts (6 389 097 participants) and 15 case-control studies (47 914 cases and 685 712 controls). The most common pollutants investigated were trihalomethanes (11 studies), arsenic (5 studies) and nitrates (4 studies). The studies varied in design with different estimates of exposure, different stages of gestation age and different durations of exposure to pollutants. 21 articles reported data on any birth defects in their population or study groups and the others on specific birth defects including congenital heart defects, neural tube defects, orofacial defects and hypospadias. An increased risk or higher incidence of overall birth defects was reported by 9 studies and for specific birth defects by 14 studies. Eight studies compared the risk or incidence of birth defects with exposure to different concentrations of the pollutants. The analysis showed an association between higher levels of trihalomethanes (TTMs) and arsenic increase in major birth defects (lower vs higher exposure (OR 0.76, 95% CI 0.65 to 0.89; p<0.001 and OR 0.56, 95% CI 0.39 to 0.82; p<0.005, respectively). CONCLUSION: The evidence of an association between exposure to average levels of common drinking water chemical pollutants during pregnancy and an increased risk or incidence of birth defects is uncertain. Available evidence indicates that some common chemical pollutants currently found in drinking water may have a direct teratogenic effect at high maternal exposure, however, wide variation in methodology limits the interpretation of the results. Future prospective studies using standardised protocols comparing maternal levels during all three trimesters of pregnancy and cord blood levels at birth are needed to better understand the placental transfer of water pollutants and accurately evaluate individual fetal exposure to drinking water pollutants. PROSPERO REGISTRATION NUMBER: CRD42018112524.
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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 | 0.034 | 0.101 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.042 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".