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Abstract
We created an exposure database of respirable crystalline silica levels in the construction industry from the literature. We extracted silica and dust exposure levels in publications reporting silica exposure levels or quantitative evaluations of control effectiveness published in or after 1990. The database contains 6118 records (2858 of respirable crystalline silica) extracted from 115 sources, summarizing 11,845 measurements. Four hundred and eighty-eight records represent summarized exposure levels instead of individual values. For these records, the reported summary parameters were standardized into a geometric mean and a geometric standard deviation. Each record is associated with 80 characteristics, including information on trade, task, materials, tools, sampling strategy, analytical methods, and control measures. Although the database was constructed in French, 38 essential variables were standardized and translated into English. The data span the period 1974–2009, with 92% of the records corresponding to personal measurements. Thirteen standardized trades and 25 different standardized tasks are associated with at least five individual silica measurements. Trade-specific respirable crystalline silica geometric means vary from 0.01 (plumber) to 0.30 mg/m3 (tunnel construction skilled labor), while tasks vary from 0.01 (six categories, including sanding and electrical maintenance) to 1.59 mg/m3 (abrasive blasting). Despite limitations associated with the use of literature data, this database can be analyzed using meta-analytical and multivariate techniques and currently represents the most important source of exposure information about silica exposure in the construction industry. It is available on request to the research community.
[Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplementary resource: appendices containing a list of data sources and detailed descriptions of each parameter.]
ACKNOWLEDGMENTS
This research was funded by the Institut de recherche Robert-Sauvé en santé et en sécurité du travail (grant no. 099–753). Thanks to Alan Echt, Matt Gillen, and Faye Rice of NIOSH, and Laurène Delabre, Corinne Pilorget, and Ellen Imbernon of the InVS for the information they shared with us and for helping us refine our methodology. Special thanks to Mary Ellen Flanagan for gallantly sharing her mass of raw data that make up close to 20% of our inventory.