Occupational exposures to chemicals in dentistry: A scoping review
Bibliographic record
Abstract
The dental workforce comprises a variety of professions, most of which are predominantly occupied by women. Dental workers can be exposed to numerous toxic chemicals such as mercury, methacrylate polymers, and silica. This scoping review aims to synthesize the scientific literature on quantified chemical exposures and to identify research gaps in occupational chemical hazards faced by dental professionals. This review followed the Joanna Briggs Institute approach and PRISMA-ScR guidelines, using three concepts to search PubMed, Embase, and Web of Science: workers, dental care, and chemicals. Studies from high-income countries, published in French or English between 2000 and 2024 and reporting direct quantitative exposure data, were included. A descriptive analysis presents exposures measured in urine, blood, and air samples for the most assessed chemicals. Thirty articles were included in the review, with two-thirds focused on exposures of dentists and none of denturists. Exposure assessments most often focused on mercury (n = 17 studies), followed by nitrous oxide (n = 6), methacrylate compounds (n = 4), and silica (n = 3). Most studies showed exposure levels below occupational exposure standards; however, certain aerosol-releasing tasks could exceed recommended occupational exposure limits of 0.025 mg/m³ for mercury and silica. Dental students in a simulation laboratory were exposed to a 4-hr mercury vapor level up to 3 mg/m3, and dentists’ exposure in clinics reached 0.45 mg/m³. Silica concentrations were below occupational exposure limits in dental clinics but reached twice the standard in a dental laboratory during prosthodontics polishing activities. The review emphasizes the need for comprehensive exposure assessments among dental workers and highlights the lack of focus on denturists, dental technicians, and dental assistants. To adequately assess the overlooked risks posed by multi-exposures to chemicals among dental workers, future studies need to analyze and report on exposures and risks stratified by occupation, task, and sex.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".