Measuring 'risk' in occupational health studies: standard methods and some alternatives for epidemiological research.

Understanding the potential relationship between a workplace exposure and whether an employee subsequently contracts a disease represents one of the time-honoured cornerstones of occupational health research. Establishing whether a statistically significant relationship actually exists between these variables, and then quantifying it in terms of 'risk', has long been the domain of occupational epidemiology 1). As human understanding of biological processes progressed throughout the 19th and 20th Centuries, clinicians and practitioners were increasingly able to draw intuitive links from anecdotal reports and individual case studies, thereby leading to disease causation hypotheses and research studies to investigate them 2). For many years the accepted scientific paradigm has demanded that any proposed links between variables under study be mathematically validated via the use of appropriate statistical techniques. To reduce the chance element in scientific research it became necessary to calculate the probability of an outcome occurring due to the experiment, versus the likelihood of it occurring due to chance alone. As a result, most contemporary statistical techniques are based on early studies of games of chance 3) , including two of the most well-known examples: Pearson's chi-squared test and Fisher's exact-test. By the mid 20th Century, the general understanding of statistics, medicine and clinical experimental design had all progressed to a point where simple chi-squared tests were no longer being seen as adequate for determining 'risk' in scientific research. A more reliable method was also being sought in the discipline of occupational health, or industrial hygiene as it was often called at the time, so that the 'risk' to an individual worker exposed to various substances could be calculated and appropriate protective measures determined 4). Although it did not originate in the field of occupational health, the development of an Odds Ratio (OR) calculation as we know it today began to appear in clinical medicine during the mid 20 th Century. Indeed, the original method is now so widely used that most published studies no longer reference the original source 5). Credit for its discovery is generally given to Jerome Cornfield (1912–1979) − a pioneering American biostatistician, who in 1951 demonstrated that an OR calculated from data in case-control studies could be used to estimate the 'relative risk' of developing a disease 5). His exposition of the now-famous Cornfield's Odds Ratio was part of a study that investigated links between smoking and lung cancer and reported the categories as 'relative risk' 6). In …