PubMed · 8865596
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R McCully, R Fairfax. 1996. Silica article clarification.. https://pubmed.ncbi.nlm.nih.gov/8865596/
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BACKGROUND: In this study, we describe the methodology used for historical estimation of exposure to fluoride and to PAH in vertical stud Søderberg (VSS) potrooms at two Norwegian aluminum smelters. The assessment was performed in order to develop exposure data for epidemiological studies of cause-specific mortality and cancer incidence. METHODS: The estimation was performed in several steps. In the first step, we estimated the area concentrations of fluoride and PAH in periods with no measurements. Relationships between measured area concentrations and process parameters were investigated by statistical modeling. Process parameters and the models were then used to estimate area concentrations in periods lacking area measurement data. In the second step, the relationships between the area measurements and job specific exposure (personal measurements) were investigated by use of a measurement model. In the last step, the obtained relationships were used to estimate job specific exposure in different periods. RESULTS: The range for the annual exposure estimates in the VSS-potrooms was 0.05-1.7 mg/m3 for fluoride and 3-3,437 micrograms/m3 for PAH. CONCLUSIONS: Despite limitations of available measurements in the early production period, we have concluded that the exposure estimates from this study provide a reasonable tool for the estimation of dose-response relations in subsequent epidemiological analyses.
Chronic inhalation of coal dust can cause several lung disorders, including simple coal workers pneumoconiosis (CWP), progressive massive fibrosis (PMF), chronic bronchitis, lung function loss, and emphysema. This review focuses on the cellular actions and interactions of key inflammatory cells and target cells in coal dust toxicity and related lung disorders, i.e. macrophages and neutrophils, epithelial cells, and fibroblasts. Factors released from or affecting these cells are outlined in separate sections, i.e. (1) reactive oxygen species (ROS) and related antioxidant protection mechanisms, and (2) cytokines, growth factors and related proteins. Furthermore, (3) components of the extracellular matrix (ECM), including the modifying role of ROS, cytokines, proteases and antiproteases are discussed in relation to tissue damage and remodelling in the respiratory tract. It is recognised that inhaled coal dust particles are important non-cellular and cellular sources of ROS in the lung, and may be significantly involved in the damage of lung target cells as well as important macromolecules including alpha-1-antitrypsin and DNA. In vitro and in vivo studies with coal dusts showed the up-regulation of important leukocyte recruiting factors, e.g. Leukotriene-B4 (LTB4), Platelet Derived Growth Factor (PDGF), Monocyte Chemotactic Protein-1 (MCP-1), and Tumor Necrosis Factor-alpha (TNF alpha), as well as the neutrophil adhesion factor Intercellular Adhesion Molecule-1 (ICAM-1). Coal dust particles are also known to stimulate the (macrophage) production of various factors with potential capacity to modulate lung cells and/or extracellular matrix, including O2-., H2O2, and NO, fibroblast chemoattractants (e.g. Transforming Growth Factor-beta (TGF beta), PDGF, and fibronectin) and a number of factors that have been shown to stimulate and/or inhibit fibroblast growth or collagen production such as (TNF alpha, TGF beta, PDGF, Insulin Like Growth Factor, and Prostaglandin-E2). Further studies are needed to clarify the in vivo kinetics and relative impact of these factors.
The objectives of this study were to explore the application of cluster analysis to the characterization of multiple exposures in industrial hygiene practice and to compare exposure groupings based on the result from cluster analysis with that based on non-measurement-based approaches commonly used in epidemiology. Cluster analysis was performed for 37 workers simultaneously exposed to three agents (endotoxin, phenolic compounds and formaldehyde) in fiberglass insulation manufacturing. Different clustering algorithms, including complete-linkage (or farthest-neighbor), single-linkage (or nearest-neighbor), group-average and model-based clustering approaches, were used to construct the tree structures from which clusters can be formed. Differences were observed between the exposure clusters constructed by these different clustering algorithms. When contrasting the exposure classification based on tree structures with that based on non-measurement-based information, the results indicate that the exposure clusters identified from the tree structures had little in common with the classification results from either the traditional exposure zone or the work group classification approach. In terms of the defining homogeneous exposure groups or from the standpoint of health risk, some toxicological normalization in the components of the exposure vector appears to be required in order to form meaningful exposure groupings from cluster analysis. Finally, it remains important to see if the lack of correspondence between exposure groups based on epidemiological classification and measurement data is a peculiarity of the data or a more general problem in multivariate exposure analysis.