Birte Mester

Sharing the knowledge gained from occupational cohort studies: A call for action

Objectives An immense body of knowledge has been created by establishing various job-exposure matrices (JEMs) to assess occupational exposures in community- and industry-based cohort studies. These JEMs could be made available to occupational epidemiologists using knowledge-sharing technologies, thereby saving considerable amounts of time and money for researchers investigating occupation-related research questions. In this paper, the authors give an example of how a detailed JEM can be easily transformed into a job-specific module (JSM) for use in community-based studies. Methods OccIDEAS is operationalised as a web-based software, combining the use of JSMs with an individual expert exposure assessment to assess occupational exposures in various industries according to a set of predefined rules. The authors used a JEM focusing on endocrine-disrupting chemicals from a German study on testicular cancer in the automobile industry to create a JSM in OccIDEAS. Results The JEM was easily translated into OccIDEAS requiring about 50 h of work by an epidemiologist familiar with the German JEM to learn about the OccIDEAS structure, establish the required set of exposure rules and to translate the JEM into OccIDEAS. Language did not represent an obstacle for translation either. To make the data available in an international context, an interpreter had to translate the German tasks and exposures after they were coded into OccIDEAS. Conclusions JEMs which are constructed based on identifying tasks that determine exposure can be easily transformed into a JSM. Occupational epidemiologists are invited to contribute to the international scope of OccIDEAS by providing their previously established JEMs to make existing data on occupational exposures widely available to the epidemiological community.

Exposure to metal-working fluids in the automobile industry and the risk of male germ cell tumours.

Introduction In a previous analysis of a case–control study of testicular cancer nested in a cohort of automobile workers, we observed an increased risk for testicular cancer among workers who had ever been involved in occupational metal-cutting tasks. We investigated whether this risk increase was due to exposure to metal-working fluids (MWF). Methods Occupational exposure to MWF was assessed in detail using a job-specific questionnaire for metal-cutting work. We calculated ORs and associated 95% CIs individually matched for age (±2 years) and adjusted for a history of cryptorchidism by conditional logistic regression. Results The prevalence of exposure to MWF was 39.8% among cases and 40.1% among controls. For total germ cell tumours and seminomas we did not observe risk increases for metal-cutting tasks or occupational exposure to MWF (OR 0.95; 95% CI 0.69 to 1.32 and OR 0.88; 95% CI 0.58 to 1.35, respectively). However, dermal exposure to oil-based MWF was associated with an increased risk for non-seminomatous testicular cancer. Dermal exposure to oil-based MWF for more than 5000 h showed particularly high risk estimates (OR 4.72; 95% CI 1.48 to 15.09). Discussion Long-term dermal exposure to oil-based MWF was a risk factor for the development of non-seminomatous testicular germ cell cancer. Possible measures to reduce exposure include the introduction of engineering control measures such as venting or enclosing of machines, and enforcing the use of personal protective equipment during metal cutting.

Development and evaluation of a tool for retrospective exposure assessment of selected endocrine disrupting chemicals and EMF in the car manufacturing industry.

OBJECTIVES A system for retrospective occupational exposure assessment combining the efficiency of a job exposure matrix (JEM) and the precision of a subsequent individual expert exposure assessment (IEEA) was developed. All steps of the exposure assessment were performed by an interdisciplinary expert panel in the context of a case-control study on male germ cell cancer nested in the car manufacturing industries. METHODS An industry-specific JEM was developed and automatic exposure estimation was performed based on this JEM. A subsample of exposure ratings was done by IEEA to identify determinants of disagreement between the JEM and the individual review. Possible determinants were analyzed by calculating odds ratios (ORs) of disagreement between ratings with regard to different dimensions (e.g. high versus low intensity of exposure). Disagreement in ≥20% of the sampled exposure ratings with a statistically significant OR was chosen as a threshold for inclusion of the exposure ratings into a final IEEA. RESULTS The most important determinants of disagreement between JEM and individual review were working outside of the production line (disagreement 80%), low probability of exposure (disagreement 25%), and exposure depending on specific activities like usage of specific lacquers (disagreement 32%) for jobs within the production line. These determinants were the selection criteria of exposure ratings for the subsequent final IEEA. CONCLUSIONS Combining a JEM and a subsequent final IEEA for a selected subset of exposure ratings is a feasible and labor-saving approach for exposure assessment in large occupational epidemiological studies.

Further potentially carcinogenic effects of chronodisruption.

In addition to the suppression of melatonin production and circadian disruption with deregulation of peripheral growth control functions as discussed in the article, we would like to mention further pathophysiological mechanisms that are fundamental to chronodisruption and may therefore promote the development of cancer (1). Sleep disruption as a consequence of shift work can result in disruption of the hypothalamic-pituitary gland axis, which in turn triggers an increased release of glucocorticoids. A resulting chronic suppression of immune response after years of exposure may increase the susceptibility to developing cancer. In addition to changes to activity periods and dietary habits, night work can cause further lifestyle changes, for example with regard to alcohol and tobacco consumption, and may thus indirectly affect the pathogenesis of cancer. Even though the evidence is inconclusive regarding the cancer-protective effects of vitamin D (2), night work may result in lower exposure to UV light and therefore reduced production of vitamin D, which, for example, may facilitate the development of colorectal cancer. How molecular-biological mechanisms in nocturnal exposure to light and chronodisruption influence the risk of disease is an important research field in occupational epidemiology. In the future it will be importance to study which shift roster triggers relevant chronodisruption. The increasing use of longitudinal study designs with prospective assessment of shift-work systems-as it would be possible for example in the context of the national cohort-can make a valuable contribution to this important research field.

Sharing JEMS in occupational cohort studies: what if measurement data are not available?

We thank Dr Kromhout for his thoughtful comments on our article ‘Sharing the knowledge gained from occupational cohort studies: A call for action’, which were both recently published in OEM .1 ,2 However, we think that his commentary requires some additional explanations as it seems to disregard some of the arguments we expressed in our article. Dr Kromhout states that we are suggesting that by using OccIDEAS, all problems …

Recycling job exposure matrices from occupational cohort studies

Objectives Many industry-based cohort studies have been undertaken in industries around the world. Considerable time and effort goes into identifying the determinants of exposure in the industry and developing Job Exposure Matrices (JEMs) to assign exposure. On the other hand, assessment of exposure in retrospective community-based studies often depends on experts who may not be familiar with all jobs in the study. A solution is to recycle the industry-based JEMs into job specific modules (JSMs) which contain questions on the determinants of exposure and embedded rules for exposure assessment. Methods OccIDEAS is a web-based application which automates the expert assessment method of assessing occupational exposures. As an example of how a JEM can be recycled we used a JEM from a German study on testicular cancer in the automobile industry to create a JSM in OccIDEAS. Results The JEM clearly identified the main determinants of exposure in the automobile industry, which were job title and work area. These determinants were easily transformed into questions. The exposure rules followed logically. Conclusions JEMs which are based on determinants of exposure in cohort studies can be easily transformed into a JSM. Such international collaboration, which can benefit all of the community, is possible now by using knowledge-sharing technologies and we encourage other researchers to share their knowledge to benefit other researchers.

Correspondence (letter to the editor): Epidemiological Benefits

It is generally accepted that industrial biomonitoring is a valuable tool as it helps to control workplace-related threshold limit values. It is also capable to determine a quantitative relationship between external and internal exposure and to support the diagnosis of diseases caused by acute effects of harmful substances. Biomonitoring may also be used in epidemiological studies to determine group differences between subjects with high and low exposure to improve the description of average pollutant concentrations from chronic exposure. However, when assessing health risks of chronic diseases with long induction periods that arise from these exposures, the article is a bit short-spoken. Biomonitoring is less meaningful when studying these diseases, such as most types of cancer (1). Due to the short half-life of most of these agents, past exposures can hardly be estimated by biomonitoring procedures. In some cases risk estimation is only possible when complex mathematical models are applied. Occupational epidemiologists use a variety of methods to evaluate these exposure scenarios, including historical ones, and the associated risks. Data sources, such as registry data, archive materials, expert evaluations and personal assessment by employees, as well as biological parameters or workplace measurements, may be for example combined in job exposure matrices which allow for automatic classification of historical exposures to evaluate health risks in epidemiological studies.