A hierarchical Bayesian model for a variability analysis of measurements of occupational n-hexane exposure in Italy

Abstract

This study evaluates changes over time in occupational exposure to n-hexane by longitudinal repeated measurements analysis of data from the Biological Monitoring Registry from 1991 to 1998. The main sources of variability in n-hexane exposure among manufacturing workers in Florence province (Italy) are inspected. The 2,5-hexanedione concentrations in urine of industrial workers are explained by structural, individual and factory information. Here we analyse the effectiveness of a 1994 law on workplace conditions based on variability decomposition of measured 2,5-hexanedione concentrations. We propose a hierarchical Bayesian model which takes into account the different levels of aggregation of data. The results show that for leather and shoe factories, the within-subject and within-factory variance components remain the most important over the time of study, whereas the between-factory components decreased in accordance with the expected effect of the new legislation.