ArticleFrontiers in public health2022
An interdisciplinary framework for derivation of occupational exposure limits.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Requirements for occupational exposure limits in psychosocial risk assessment: What we know, what we don't know and what we can learn from other disciplines.Scandinavian journal of work, environment & health · 2025Review
- Recommended Occupational Exposure Limits for GMA Using Benchmark Dose and Bayesian Model Averaging.China CDC weekly · 2024Article
- Current frameworks for environmental and health assessment of hydrocarbon streams and products are flexible and ready for alternative non crude oil-based feeds.Toxicology research · 2024Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protecting the health and safety of workers in industrial operations is a top priority. One of the resources used in industry to ensure worker safety is the occupational exposure limit (OEL). OELs are derived from the assessment and interpretation of empirical data from animal and/or human studies. There are various guidelines for the derivation and implementation of OELs globally, with a range of stakeholders (including regulatory bodies, governmental agencies, expert groups and others). The purpose of this manuscript is to supplement existing guidance with learnings from a multidisciplinary team approach within an industry setting. The framework we present is similar in construct to other risk assessment frameworks and includes: (1) problem formulation, (2) literature review, (3) weight of evidence considerations, (4) point of departure selection/derivation, (5) application of assessment factors, and the final step, (6) derivation of the OEL. Within each step are descriptions and examples to consider when incorporating data from various disciplines such as toxicology, epidemiology, and exposure science. This manuscript describes a technical framework by which available data relevant for occupational exposures is compiled, analyzed, and utilized to inform safety threshold derivation applicable to OELs.
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