Abstract

Background Road transport workers (RTWs) are at high risk of exposure to several occupational carcinogens. However, there are gaps in knowledge regarding the extent and the circumstances of exposure. As a sub-study of the Australian Work Exposures Study, this study investigated the prevalence of occupational exposure in Australian RTWs. Methods A random sample of Australian working population was invited to a telephone interview regarding their current jobs. An automated expert-assessment procedure was applied to self-reported job-related tasks using a web-based application. 162 RTWs were included in this study. Results RTWs were exposed to diesel exhaust (97%), solar ultraviolet radiation (78%), environmental tobacco smoke (55%), benzene (29%), silica (15%), and asbestos (10%) at work. Besides driving on roads, vehicle maintenance-related tasks were the major source of carcinogen exposures among RTWs. Discussion Most RTWs are exposed to at least one carcinogen at work. We have identified tasks where the use of control measures could potentially reduce exposures. Am. J. Ind. Med. 59:31–41, 2016. © 2015 Wiley Periodicals, Inc.

Abstract

Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients’ symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network. Document type: Article