Despite extensive laws and regulations designed to prevent work-related illnesses, workers continue to fall ill due to exposure to hazardous substances. One explanation is that there is often insufficient information about a hazardous substance, or about the type of work that can cause illness. As a result, the link between illness and work is often recognised only after someone becomes ill: a reactive approach known as the “disease-first approach”.
A better approach is to identify hazardous substances or types of work before people fall ill: the “risk-first approach”. The Dutch National Institute for Public Health and the Environment (RIVM) has compiled an overview of methods that can help predict whether a hazardous substance or type of work is likely to cause an occupational disease.
Persistent gaps in knowledge
Knowledge about the harmful effects of hazardous substances and worker exposure to them still contains significant gaps. One key reason is that the risk assessment of most chemicals is based on oral toxicity tests, while workers are mainly exposed to chemicals through inhalation or skin contact. In addition, some health effects may not yet have been identified, and exposure data may be missing or underestimated.
Risk-first methods: an overview
New and emerging risks of chemicals (NERCs) can be detected at different stages of a substance’s development, using both risk-first and disease-first approaches. The risk-first approach focuses on chemicals and materials that are still mainly in the innovation or early market phase. Signals about potential hazards, both for chemical safety and occupational health, can be picked up by combining data on hazardous properties with data on potential exposure or use.
Several research institutes and regulatory agencies have developed, or are developing, risk-first methods for early risk detection, including the European Food Safety Authority (EFSA), the European Chemicals Agency (ECHA), the European Agency for Safety and Health at Work (EU-OSHA), and RIVM. Additional methods have emerged from collaborations and partnerships. RIVM also identified other approaches that can serve as risk-first methods, such as the TICHNER process and several in silico methods for early detection of chemical toxicity.
The overview shows that each method serves a different purpose, and that the amount of work involved as well as the information required varies considerably from one method to another.
Towards further development
RIVM assessed the identified risk-first methods against a set of criteria to determine their suitability for strengthening the risk-first approach. The most promising methods are high-throughput approaches that draw on large databases and combine hazard and exposure data. However, no single method meets all the criteria, and every method still requires expert judgement for prioritisation and follow-up. Based on this assessment, two methods were selected for further development: the Lexces in silico prediction tools and the RIVM Endocrine Disruptor toolbox. This work contributes to a more preventive approach to occupational cancers.
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