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LaKind JS, O'Mahony C, Armstrong T, et al. ExpoQual: Evaluating measured and modeled human exposure data. Environ Res. 2019;171:302-312doi: 10.1016/j.envres.2019.01.039.
LaKind, J. S., O'Mahony, C., Armstrong, T., Tibaldi, R., Blount, B. C., & Naiman, D. Q. (2019). ExpoQual: Evaluating measured and modeled human exposure data. Environmental research, 171302-312. https://doi.org/10.1016/j.envres.2019.01.039
LaKind, Judy S, et al. "ExpoQual: Evaluating measured and modeled human exposure data." Environmental research vol. 171 (2019): 302-312. doi: https://doi.org/10.1016/j.envres.2019.01.039
LaKind JS, O'Mahony C, Armstrong T, Tibaldi R, Blount BC, Naiman DQ. ExpoQual: Evaluating measured and modeled human exposure data. Environ Res. 2019 Apr;171:302-312. doi: 10.1016/j.envres.2019.01.039. Epub 2019 Jan 25. PMID: 30708234.
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Environ Res. 2019 Apr;171:302-312. doi: 10.1016/j.envres.2019.01.039. Epub 2019 Jan 25.

ExpoQual: Evaluating measured and modeled human exposure data.

Environmental research

Judy S LaKind, Cian O'Mahony, Thomas Armstrong, Rosalie Tibaldi, Benjamin C Blount, Daniel Q Naiman

Affiliations

  1. LaKind Associates, LLC, Department of Epidemiology and Public Health, University of Maryland School of Medicine, 106 Oakdale Ave, Catonsville, MD 21228, USA.
  2. Creme Global, Trinity Technology and Enterprise Campus, Grand Canal Quay, Dublin 2, Ireland, UK. Electronic address: [email protected].
  3. TWA8HR Occupational Hygiene Consulting LLC, Branchburg, NJ 08876, USA.
  4. ExxonMobil Biomedical Sciences, Inc., Annandale, NJ 08801, USA. Electronic address: [email protected].
  5. Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention (CDC), 4770 Buford Highway, NE, Atlanta, GA, USA. Electronic address: [email protected].
  6. Department of Applied Mathematics & Statistics, The Johns Hopkins University, 3400N. Charles Street, Baltimore, MD 21218, USA. Electronic address: [email protected].

PMID: 30708234 DOI: 10.1016/j.envres.2019.01.039

Abstract

Recent rapid technological advances are producing exposure data sets for which there are no available data quality assessment tools. At the same time, regulatory agencies are moving in the direction of data quality assessment for environmental risk assessment and decision-making. A transparent and systematic approach to evaluating exposure data will aid in those efforts. Any approach to assessing data quality must consider the level of quality needed for the ultimate use of the data. While various fields have developed approaches to assess data quality, there is as yet no general, user-friendly approach to assess both measured and modeled data in the context of a fit-for-purpose risk assessment. Here we describe ExpoQual, an instrument developed for this purpose which applies recognized parameters and exposure data quality elements from existing approaches for assessing exposure data quality. Broad data streams such as quantitative measured and modeled human exposure data as well as newer and developing approaches can be evaluated. The key strength of ExpoQual is that it facilitates a structured, reproducible and transparent approach to exposure data quality evaluation and provides for an explicit fit-for-purpose determination. ExpoQual was designed to minimize subjectivity and to include transparency in aspects based on professional judgment. ExpoQual is freely available on-line for testing and user feedback (exposurequality.com).

Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Keywords: BEES-C; Biomonitoring; ExpoQual; Exposure; Fit-for-purpose; Human; Instrument; Model uncertainty; Quality

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