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Constructing a Database of Similar Exposure Groups: The Application of the Exporisq-HAP Database from 1995 to 2015.

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Title: Constructing a Database of Similar Exposure Groups: The Application of the Exporisq-HAP Database from 1995 to 2015.
Authors: Petit, Pascal1, Bicout, Dominique J.1,2, Persoons, Renaud1,3, Bonneterre, Vincent1,4, Barbeau, Damien1,3, Maître, Anne1,3 anne.maitre@univ-grenoble-alpes.fr
Source: Annals of Work Exposures & Health. May2017, Vol. 61 Issue 4, p440-456. 17p.
Subjects: Air pollution, Database design, Industrial hygiene, Polycyclic aromatic hydrocarbons, Information resources, Occupational hazards, Environmental exposure, Descriptive statistics
Abstract: Background: Similar exposure groups (SEGs) are needed to reliably assess occupational exposures and health risks. However, the construction of SEGs can turn out to be rather challenging because of the multifactorial variability of exposures. Objectives: The objective of this study is to put forward a semi-empirical approach developed to construct and implement a SEG database for exposure assessments. An occupational database of airborne levels of polycyclic aromatic hydrocarbons (PAHs) was used as an illustrative and working example. Methods: The approach that was developed consisted of four steps. The first three steps addressed the construction and implementation of the occupational Exporisq-HAP database (E-HAP). E-HAP was structured into three hierarchical levels of exposure groups, each of which was based on exposure determinants, along 16 dimensions that represented the sampled PAHs. A fourth step was implemented to identify and generate SEGs using the geometric standard deviation (GSD) of PAH concentrations. Results: E-HAP was restructured into 16 (for 16 sampled PAHs) 3 x 3 matrices: three hierarchical levels of description versus three degrees of dispersion, which included low (the SEG database: GSD ≤ 3), medium (3 < GSD ≤ 6), and high (GSD > 6). Benzo[a]pyrene (BaP) was the least dispersed particulate PAH with 41.5% of groups that could be considered as SEGs, 48.5% of groups of medium dispersion, and only 8% with high dispersion. These results were comparable for BaP, BaP equivalent toxic, or the sum of all carcinogenic PAHs but were different when individual gaseous PAHs or ∑PAHG were chosen. Conclusion: Within the framework of risk assessment, such an approach, based on groundwork studies, allows for both the construction of an SEG database and the identification of exposure groups that require improvements in either the description level or the homogeneity degree toward SEG. [ABSTRACT FROM AUTHOR]
Copyright of Annals of Work Exposures & Health is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Background: Similar exposure groups (SEGs) are needed to reliably assess occupational exposures and health risks. However, the construction of SEGs can turn out to be rather challenging because of the multifactorial variability of exposures. Objectives: The objective of this study is to put forward a semi-empirical approach developed to construct and implement a SEG database for exposure assessments. An occupational database of airborne levels of polycyclic aromatic hydrocarbons (PAHs) was used as an illustrative and working example. Methods: The approach that was developed consisted of four steps. The first three steps addressed the construction and implementation of the occupational Exporisq-HAP database (E-HAP). E-HAP was structured into three hierarchical levels of exposure groups, each of which was based on exposure determinants, along 16 dimensions that represented the sampled PAHs. A fourth step was implemented to identify and generate SEGs using the geometric standard deviation (GSD) of PAH concentrations. Results: E-HAP was restructured into 16 (for 16 sampled PAHs) 3 x 3 matrices: three hierarchical levels of description versus three degrees of dispersion, which included low (the SEG database: GSD ≤ 3), medium (3 &lt; GSD ≤ 6), and high (GSD &gt; 6). Benzo[a]pyrene (BaP) was the least dispersed particulate PAH with 41.5% of groups that could be considered as SEGs, 48.5% of groups of medium dispersion, and only 8% with high dispersion. These results were comparable for BaP, BaP equivalent toxic, or the sum of all carcinogenic PAHs but were different when individual gaseous PAHs or ∑PAHG were chosen. Conclusion: Within the framework of risk assessment, such an approach, based on groundwork studies, allows for both the construction of an SEG database and the identification of exposure groups that require improvements in either the description level or the homogeneity degree toward SEG. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Annals of Work Exposures &amp; Health is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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        Value: 10.1093/annweh/wxx017
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        Text: English
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      – SubjectFull: Industrial hygiene
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      – SubjectFull: Descriptive statistics
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