Journal article
Improving the design of epidemiology studies that use biomonitoring for exposure assessment: a SciPinion panel recommendation
BMC medical research methodology, v 26(1), Forthcoming
12 Jan 2026
PMID: 41527048
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
BACKGROUND: Epidemiological studies that rely on biomarkers of exposure typically estimate each subject's exposure from measurements on that individual. If repeated measurements of biomarkers of exposure are obtained on an individual, they are typically averaged. This averaging helps to reduce error from within-person variability if average exposure is a better measure of the biologically effective dose than the instantaneous one. However, these analyses then often ignore the residual within-person variation in the averages of measurements. Not considering this variation can bias effect estimates and lead to inaccurate risk assessment.
METHODS: We developed software ("calculators") that help design studies of continuous and binary outcomes that rely on biomarkers of exposure. An independent panel of experts was employed to peer review the models and answer questions regarding their use and best practices for the design of epidemiology studies that utilize biomonitoring data for the exposure assessment.
RESULTS: Web-based tools were developed to estimate the required sample sizes, number of repeated measurements, and the trade-offs between power and bias in simple linear and logistic regression models under classical (independent, additive, normally distributed, homogeneous variance) measurement error assumptions. Application of the calculators was illustrated in case studies of investigation of the associations between urinary levels of bisphenols during pregnancy and fetal growth, and urinary levels of triclosan and neurodevelopment in children. Best practices are recommended for the design of epidemiology studies that utilize biomonitoring data for the exposure assessment.
CONCLUSIONS: Calculators have been developed and vetted by a panel of experts. They are designed to estimate sample size (number of individuals sampled and number of samples per individual), power and bias in epidemiological studies that use biomonitoring to assess each subject's exposure in the presence of classical measurement errors. These user-friendly tools account for measurement error and allow researchers to design more accurate and appropriately powered studies, ultimately improving quality of public health research.
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Details
- Title
- Improving the design of epidemiology studies that use biomonitoring for exposure assessment
- Creators
- Igor Burstyn - Drexel UniversityLouis Anthony Cox - University of Colorado DenverYang Cao - Örebro UniversityGuy Eslick - University of Newcastle AustraliaShelley Harris - University of TorontoLeeka Kheifets - University of California, Los AngelesMichael Kramer - McGill UniversityPeter Langlois - University of Texas School of Public Health, Dallas, TX, USAPaul Lee - University of SouthamptonBoris Reiss - KU LeuvenTrudy Voortman - Stanford UniversityTyler M. Carneal - SciPinion, Bozeman, MT, USASean M. Hays (Corresponding Author) - Dominion (United States)
- Publication Details
- BMC medical research methodology, v 26(1), Forthcoming
- Publisher
- Springer Nature
- Number of pages
- 14
- Grant note
- Corteva AgriscienceSciPinion
The development of the calculators included in this manuscript, as well as the panel review was funded by Corteva Agriscience. SMH and TMC were the only coauthors aware of the funding source and had complete control over the project. IB and LAC were selected by SMH to develop the calculators and were all compensated for the work. SMH, TMC, IB and LAC had full control over the design and scope of the calculators and panel charge questions. The panel members were selected using SciPinion's merit based expert selection tool and was solely based on area of expertise, experience relevant to the project and an independent audit of the panel by IB to help select the panelists. The panel members were compensated for their work. All panel members were unaware of the funding source throughout the panel review and editing of the manuscript. All panel members, IB and LAC were only made aware of the funding source directly prior to the submission of the manuscript for peer review, at which time they chose whether to be listed as coauthors on the manuscript. Corteva had no knowledge of any participants in this project, was not provided a copy of the manuscript until after submission to the journal, and had no input on the scope of the project, calculators, scope of the panel review, charge questions posed to the panel or selection of the studies chosen for the critique using the calculators.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Environmental and Occupational Health
- Web of Science ID
- WOS:001685753000002
- Scopus ID
- 2-s2.0-105029541356
- Other Identifier
- 991022153459504721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Health Care Sciences & Services