Finding 'new' occupational diseases and trends in 'old' ones.

Strategies for the reduction of risk to the health of workers, as well as the population in general, rely on the collection, analysis and interpretation of valid data to study work-related ill-health in relation to its determinants. In the developed world, through advances in occupational medicine and changing societal attitude reflected in legislation, the scourges of many occupational diseases such as those caused by asbestos, coal dust and silica have abated significantly. However, the risks of these diseases and many other categories of occupational ill-health ranging from noise-induced hearing loss to musculoskeletal and mental disorders still persist globally. It is clearly essential for all stakeholders including policy makers, occupational health professionals as well as employees, employers and the public to have reliable information on the trends in incidence of these conditions so as to intervene and achieve reductions in risk through legislation, enforcement and education [1]. In order to evaluate policy and its implementation, the results of these interventions can and should also be evaluated using corresponding reliable measurements of frequency of disease [1,2]. However, the challenges that hinder such reliable measurements should not be underestimated especially when potentially flawed, and in any case diverse, methods of data collection exist across national systems. To achieve better comparability of figures between countries, it is necessary to harmonize definitions and methods of recording of occupational diseases. However, the availability of reliable and integrated occupational health indicators to guide policymaking is hampered by societal, economic, financial and cultural differences between countries. Thus, Eurostat (the statistical office of the European Union) has curtailed publication of its previous range of occupational health statistics prompting a search for alternative approaches [2]. Another, arguably even bigger challenge, arises from the need for the early identification, or even the prediction of ‘new’ or emerging diseases arising from novel hazards, changing circumstances of occupational exposure, or evolution in modes of employment. In essence, new or emerging risks may result from completely novel physical, chemical or biological agents, from known risks associated with the introduction of changes in work conditions or from unforeseen methods of uptake of, or exposure to, previously recognized hazardous entities. In occupational health and safety, considerable effort can be invested in risk assessment in order to manage hazards and their risks. The risk assessment process can be viewed as a deductive method starting with established premises. However, for new risks, these premises are not known and consequently an inductive method might be more appropriate to discover and quantify previously unknown risks. Moreover, the existing ‘registries’ for occupational diseases are usually less suitable for the detection of ‘new’ occupational of work-related diseases, since they are aimed primarily at already known and established conditions. There is an urgent need to develop and study consistent methods that can improve the re cognition, validation and sharing of information about new occupational health risks [3]. The European Agency for Safety and Health at Work has used techniques such as literature reviews, interviews and expert consultations to help identify and predict new and emerging occupational health risks [4]. Notwithstanding such laudable initiatives, direct observation through sentinel reporting or surveillance schemes accompanied by expert interpretation is vital to demonstrate early signals of these new hazards and emerging risks [1,5]. Once a suspicion of a new hazard is raised, targeted ‘case-finding’ may be warranted to generate a hypothesis for further research and appropriate and timely protection of workers’ health [6]. The ‘holy grail’ is to aim towards ‘ideal prevention’ by pre-empting hazards to health even before they become manifest as disease. While no system could ever promise zero-risk, it nevertheless behoves all concerned to learn from the past to achieve a better future. Strategies need to be further developed in order to utilize extant data to best advantage by predicting potential new hazards and taking steps to protect workers and consumers before any health damage is manifest. Thus, techniques such as Quantitative Structure Activity Relationships (QSARs) have been applied to a variety of potential toxicants ranging from carcinogens, mutagens and reprotoxic agents to skin sensitizers. QSARs advocated and developed for occupational asthmagens [7] and for nanoparticles [8] aim to effectively forecast unknown hazards from those which are known. For the purposes of investigating trends in the incidence of work-related ill-health as well as to identify new or emerging health risks arising from work, an international consortium entitled MODERNET (Monitoring trends in Occupational Diseases and tracing new and Emerging Risks in a NETwork) was founded in 2008 [9]. MODERNET is a collaboration between academic centres investigating occupational disease and work-related ill-health incidence