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

Simona Toti

Department of Statistics ‘G. Parenti’, University of Florence, Florence, Italy, toti{at}ds.unifi.it

Annibale Biggeri

Department of Statistics ‘G. Parenti’, University of Florence, Florence, Italy, Biostatistics Unit, CSPO, Florence, Italy

Alberto Baldasseroni

SA di Epidemiologia, ASF, Florence, Italy

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.

Key Words: hierarchical Bayesian model • measurements variability • occupational exposure

Statistical Modelling, Vol. 6, No. 2, 175-185 (2006)
DOI: 10.1191/1471082X06st110oa
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?