Hierarchical cluster analysis for exposure assessment of workers in the semiconductor health study

C. J. Hines, S. Selvin, S. J. Samuels, S. K. Hammond, S. R. Woskie, M. F. Hallock, Marc B Schenker

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

The fabrication of integrated circuits in the semiconductor industry involves worker exposures to multiple chemical and physical agents. The potential for a high degree of correlation among exposure variables was of concern in the Semiconductor Health Study. Hierarchical cluster analysis was used to identify groups or 'clusters' of correlated variables. Several variations of hierarchical cluster analysis were performed on 14 chemical and physical agents, using exposure data on 882 subjects from the historical cohort of the epidemiological studies. Similarity between agent pairs was determined by calculating two metrics of dissimilarity, and hierarchical trees were constructed using three clustering methods. Among subjects exposed to ethylene-based glycol ethers (EGE), xylene, or n-butyl acetate (nBA), 83% were exposed to EGE and xylene, 86% to EGE and nBA, and 94% to xylene and nBA, suggesting that exposures to EGE, xylene, and nBA were highly correlated. A high correlation was also found for subjects exposed to boron and phosphorus (80%). The trees also revealed cluster groups containing agents associated with work-group exposure categories developed for the epidemiologic analyses.

Original languageEnglish (US)
Pages (from-to)713-722
Number of pages10
JournalAmerican Journal of Industrial Medicine
Volume28
Issue number6
StatePublished - 1995

Keywords

  • chemicals
  • exposure assessment
  • glycol ethers
  • hierarchical cluster analysis
  • occupational epidemiology
  • semiconductor industry

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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    Hines, C. J., Selvin, S., Samuels, S. J., Hammond, S. K., Woskie, S. R., Hallock, M. F., & Schenker, M. B. (1995). Hierarchical cluster analysis for exposure assessment of workers in the semiconductor health study. American Journal of Industrial Medicine, 28(6), 713-722.