A Bayesian Approach for Determining the Relationship Between Various Elongate Mineral Particles (EMPs) Definitions. Issue 9 (16th November 2020)

• Record Type: Journal Article
• Authors: Shao, Yuan; MacLehose, Richard F; Lin, Lifeng; Hwang, Jooyeon; Alexander, Bruce H; Mandel, Jeffrey H; Ramachandran, Gurumurthy
• Is Part Of: Annals of work exposures and health. Volume 64:Issue 9(2020)
• Page Start: 993
• Page End: 1006
• Publication Date: 2020-11-16
• Subjects: Bayesian approach -- bivariate lognormal distribution -- elongate mineral particles (EMPs) -- EMP exposure metrics; Medicine, Industrial -- Periodicals; Industrial hygiene -- Periodicals; 613.6205
• DOI: 10.1093/annweh/wxaa074
• Languages: English
• ISSNs: 2398-7316

Abstract

Abstract: A variety of dimensions (lengths and widths) of elongate mineral particles (EMPs) have been proposed as being related to health effects. In this paper, we develop a mathematical approach for deriving numerical conversion factors (CFs) between these EMP exposure metrics and applied it to the Minnesota Taconite Health Worker study which contains 196 different job exposure groups (28 similar exposure groups times 7 taconite mines). This approach comprises four steps: for each group (i) obtain EMP dimension information using ISO-TEM 10312/13794 analysis; (ii) use bivariate lognormal distribution to characterize overall EMP size distribution; (iii) use a Bayesian approach to facilitate the formation of the bivariate lognormal distribution; (iv) derive conversion factors between any pair of EMP definitions. The final CFs allow the creation of job exposure matrices (JEMs) for alternative EMP metrics using existing EMP exposures already characterized according to the National Institute of Occupational Safety and Health (NIOSH)-defined EMP exposure metric (length >5 µm with an aspect ratio ≥3.0). The relationships between the NIOSH EMP and other EMP definitions provide the basis of classification of workers into JEMs based on alternate definitions of EMP for epidemiological studies of mesothelioma, lung cancer, and non-malignant respiratory disease.