Swimming benefits outweigh risks of exposure to disinfection byproducts in pools
Bibliographic record
Abstract
Disinfection of swimming pool water is critical to ensure the safety of the recreational activity for swimmers. However, swimming pools have a constant loading of organic matter from input water and anthropogenic contamination, leading to elevated levels of disinfection byproducts (DBPs). Epidemiological studies have associated increased risks of adverse health effects with frequent exposure to DBPs in swimming pools. Zhang et al. (2023b) investigated the occurrence of trihalomethanes (THMs), haloacetic acids (HAAs), haloacetonitriles (HANs), and haloacetaldehydes (HALs) in eight swimming pools and the corresponding input water in a city in Eastern China. The concentrations of THMs, HAAs, HANs, and HALs in swimming pools were 1-2 orders of magnitude higher than those detected in the input water. The total lifetime cancer and non-cancer health risks of swimmers through oral, dermal, inhalation, buccal, and aural exposure pathways were assessed using the United States Environmental Protection Agency's (USEPA) standard model and Swimmer Exposure Assessment Model (SWIMODEL). The results showed that dermal and inhalation pathways were the most significant for the associated cancer and non-cancer risks. This article provides an overview and perspectives of DBPs in swimming pools, the benefits of swimming, the need to improve the monitoring of DBPs, and the importance of swimmers' hygiene practices to keep swimming pools clean. The benefits of swimming outweigh the risks from DBP exposure for the promotion of public health.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".