Variability in biological monitoring of solvent exposure. I. Development of a population physiological model

Biological indicators of exposure to solvents are often characterised by a high variability that may be due either to fluctuations in exposure or individual differences in the workers. To describe and understand this variability better a physiological model for differing workers under variable indus...

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Bibliographic Details
Published in:British Journal of Industrial Medicine 1989-07, Vol.46 (7), p.447-460
Main Authors: Droz, P O, Wu, M M, Cumberland, W G, Berode, M
Format: Article
Language:English
Subjects:
Adipose Tissue - metabolism
Adolescent
Adult
Aged
Biological and medical sciences
Blood
Blood flow
Body Constitution
Cardiac Output
Cardiac Volume
Chemical and industrial products toxicology. Toxic occupational diseases
Environmental assessment
Environmental Monitoring
Humans
Liver - metabolism
Liver - physiopathology
Liver Circulation
Male
Medical sciences
Metabolic Clearance Rate
Metabolism
Metabolites
Middle Aged
Modeling
Models, Biological
Physical Exertion
Renal clearance
Solvents
Solvents - metabolism
Toxicology
Workloads
Citations: Items that this one cites
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Summary:Biological indicators of exposure to solvents are often characterised by a high variability that may be due either to fluctuations in exposure or individual differences in the workers. To describe and understand this variability better a physiological model for differing workers under variable industrial environments has been developed. Standard statistical distributions are used to simulate variability in exposure concentration, physical workload, body build, liver function, and renal clearance. For groups of workers exposed daily, the model calculates air monitoring indicators and biological monitoring results (expired air, blood, and urine). The results obtained are discussed and compared with measured data, both physiological (body build, cardiac output, alveolar ventilation) and toxicokinetic for six solvents: 1,1,1-trichloroethane, trichloroethylene, tetrachloroethylene, benzene, toluene, styrene, and their main metabolites. Possible applications of this population physiological model are presented.
ISSN:0007-1072
1351-0711
1470-7926
DOI:10.1136/oem.46.7.447