Review of epidemiological and toxicological studies on health effects from ingestion of asbestos in drinking water
Bibliographic record
Abstract
Asbestos is a group of naturally occurring fibrous minerals that were commonly used in the construction of cement pipes for drinking water distribution systems. These pipes deteriorate and can release asbestos fibers into drinking water, raising concerns about potential risk to human health. The objective of this work was to synthesize human, animal, and in vitro evidence on potential health risks due to ingested asbestos in drinking water and evaluate the weight of evidence (WoE) of human health risk. A systematic review of epidemiological evidence was conducted, along with critical review of animal and in vitro evidence, followed by WoE evaluation that integrated human, animal, and in vitro evidence. The systematic review included 17 human studies with health outcomes mostly related to various cancer sites, with the majority focusing on the gastrointestinal system. The WoE evaluation resulted in very low levels of confidence or insufficient evidence of a health effect for cancers in 15 organ systems and for three non-cancer endpoints. While eight studies reported possible associations with stomach cancer in males, few high-quality studies were available to verify a causal relationship. Based on high-quality animal studies, an increased risk for cancer or non-cancer endpoints was not supported, aligning with findings from human studies. Overall, the currently available body of evidence is insufficient to establish a clear link between asbestos contamination in drinking water and adverse health effects. Due to the lack of both high-quality epidemiological studies and a validated kinetic model for ingested asbestos, additional research on this association is warranted.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".