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In this introductory article the author argues for an increased use of a multivariate analytical approach to the complex problems encountered in occupational hygiene. Relations between exposure at the work place and reported health effects are mostly so complicated and depend on so many factors that methods other than the traditional statistical techniques should be applied. Chemometrics is a field within chemistry where mathematics, statistics and modern computer technology are used to perform multidimensional data analysis. Graphical plots are extensively used to extract the most relevant information from the measurements. The possibility of performing soft modelling through pattern recognition and multifactorial regression analysis will simplify the management of large data sets. A ‘metric’ philosophy is introduced to describe similarity and dissimilarity among many objects characterized with many variables. This article emphasizes the use of principal component analysis and partial least-squares regression for such purposes. Application of the SIMCA method for classification of objects is also described. These methods are not dependent upon a priori formulated hypotheses, as in the classical modelling techniques. Instead of being restricted to accepting or rejecting previously formulated hypotheses, these methods may lead to new insights and unperceived features of a complex problem. The application of such exploratory methods may produce new hypotheses and further investigations are necessary to confirm or discard any ‘new’ chemometric findings.

CHEMOMETRICS IN OCCUPATIONAL HYGIENE—HOW AND WHY! A PICTURE CAN TELL MORE THAN A THOUSAND WORDS AND FIGURES!