Relation between trihalomethane compounds and birth defects
Bibliographic record
Abstract
OBJECTIVES: To evaluate the risk of birth defects relative to exposure to specific trihalomethanes in public water supplies. METHODS: A retrospective cohort study was conducted based on data from a population based perinatal database in Nova Scotia, Canada and from the results of routine water monitoring tests. The cohort consisted of women who had a singleton birth in Nova Scotia between 1988 and 1995 and who lived in an area with a municipal water supply. The birth defects analyzed included neural tube defects, cardiovascular defects, cleft defects, and chromosomal abnormalities. Two of the four trihalomethane compounds occur in large enough concentrations to be analyzed (chloroform and bromodichloromethane (BDCM)). RESULTS: Exposure to BDCM at concentrations of 20 microg/l or over was associated with an increased risk of neural tube defects (adjusted relative risk (RR) 2.5, 95% confidence interval (95% CI) 1.2 to 5.1) whereas exposure to chloroform was not. Exposure to BDCM of 20 microg/l and over was associated with decreased risks of cardiovascular anomalies (RR 0.3, 95% CI 0.2 to 0.7). There was a suggestion of an increased risk of chromosomal abnormalities associated with exposure to chloroform, and no evidence of any association between either trihalomethane compound and cleft defects. CONCLUSIONS: In this cohort, differences were found in the RR associated with exposure to chloroform and BDCM for each of the congenital anomalies under study. These findings point to the importance of examining specific byproduct compounds relative to risk for these birth outcomes and in particular implicate BDCM and other correlated disinfection byproducts in the aetiology of neural tube defects.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".