Hierarchical cluster analysis applied to workers' exposures in fiberglass insulation manufacturing

The objectives of this study were to explore the application of cluster ana lysis to the characterization of multiple exposures in industrial hygiene p ractice and to compare exposure groupings based on the result from cluster analysis with that based on non-measurement-based approaches commonly used in epidemiology. Cluster analysis was performed for 37 workers simultaneous ly exposed to three agents (endotoxin, phenolic compounds and formaldehyde) in fiberglass insulation manufacturing. Different clustering algorithms, in cluding complete-linkage (or farthest-neighbor), single-linkage (or nearest -neighbor), group-average and model-based clustering approaches, were used to construct the tree structures from which clusters can be formed. Differe nces were observed between the exposure clusters constructed by these diffe rent clustering algorithms. When contrasting the exposure classification ba sed on tree structures with that based on non-measurement-based information , the results indicate that the exposure clusters identified from the tree structures had little in common with the classification results from either the traditional exposure zone or the work group classification approach. I n terms of the defining homogeneous exposure groups or from the standpoint of health risk, some toxicological normalization in the components of the e xposure vector appears to be required in order to form meaningful exposure groupings from cluster analysis, Finally, it remains important to see if th e lack of correspondence between exposure groups based on epidemiological c lassification and measurement data is a peculiarity of the data or a more g eneral problem in multivariate exposure analysis, (C) 1999 British Occupati onal Hygiene Society, Published by Elsevier Science Ltd.