Exposure to lead, mercury, styrene, and toluene and hearing impairment: evaluation of dose-response relationships, regulations, and controls
Bibliographic record
Abstract
The risk of hearing loss from exposure to ototoxic chemicals is not reflected in occupational exposure limits and most jurisdictions. The aims of this research were to investigate dose-response relationships between exposure to lead, mercury, toluene, and styrene and hearing impairment based on current epidemiological evidence, conduct cross-jurisdictional comparisons, and investigate control measures for exposure to ototoxic chemicals. Ovid Medline and Ovid Embase databases were used to find relevant publications. A total of 86 epidemiological studies met the eligibility criteria for final evaluation. When significant associations between exposure and outcome were identified, exposure levels were evaluated to determine whether No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) could be identified. Cross-jurisdictional comparisons included the U.K., U.S., Canada, and Australia occupational health and safety legislations. The majority of lead (75%), styrene (74%), and toluene (77%) studies showed significantly increased risks of hearing loss from exposure to these substances, although numerous studies on toluene (70%) and styrene (16%) compared auditory function between "solvent mixture" or "noise and solvent mixture" exposed groups and controls and not necessarily on groups exposed to a single agent. Based on five studies, blood lead ranges of 1-1.99 μg/dL to 2.148-2.822 μg/dL were identified as NOAELs while blood lead levels of 2 μg/dL up to 2.823-26.507 μg/dL were identified as LOAELs for hearing loss. Except for general duty clauses, the U.S., Canadian, and Australian jurisdictions have set no enforceable regulations specific to ototoxic chemical exposures. A biological exposure index of 2 μg/dL is recommended for prevention of hearing impairment from lead exposure. Based on Safe Work Australia, noise exposure limits may be reduced to 80 dB(A) for 8 hr. Other recommendations include performing audiometric testing and controlling exposure through all routes of entry.
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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 | 0.065 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".