Within-subject biospecimens pooling can theoretically reduce bias in dose–response functions from biomarker-based studies when exposure assessment suffers from classical-type error. However, collecting many urine voids each day is cumbersome. We evaluated the empirical validity of a within-subject pooling approach and compared several options to avoid sampling each void.
In 16 pregnant women who collected a spot of each urine void over several nonconsecutive weeks, we compared concentrations of 10 phenols in daily, weekly, and pregnancy within-subject pools. We pooled either three or all daily samples. In a simulation study using these data, we quantified bias in dose–response functions when using one to 20 urine samples per subject to assess methylparaben (a compound with moderate within-subject variability) and bisphenol A (high variability) exposures.
Correlations between exposure estimates from pools of all and of only three voids per day were above 0.80 for all time windows and compounds, except for benzophenone-3 and triclosan in the daily time window (correlations, 0.57–0.68). With one spot sample to assess pregnancy exposure, correlations were all below 0.74. Using only one biospecimen led to attenuation bias in the dose–response functions of 29% (methylparaben) and 69% (bisphenol A); four samples for methylparaben and 18 for bisphenol A decreased bias to 10%.
For nonpersistent chemicals, collecting and pooling three samples per day instead of all daily samples efficiently estimates exposures over a week or more. Collecting around 20 biospecimens can strongly limit attenuation bias for nonpersistent chemicals such as bisphenol A.
From the aInserm, CNRS, Univ. Grenoble Alpes, Institute for Advanced Biosciences (IAB), U1209, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
bOrganic Analytical Toxicology Branch, Division of Laboratory Sciences, Centers for Disease Control and Prevention, Atlanta, GA
cInserm, CNRS, Univ. Grenoble Alpes, Institute for Advanced Biosciences (IAB), U1209, Team of Tumor Molecular Pathology and Biomarkers, Grenoble, France
dEpidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Rockville, MD.
Submitted August 25, 2018; accepted May 30, 2019.
Supported by the European Research Council (ERC consolidator grant N°311765-E-DOHaD, Principal investigator: Rémy Slama); ANR Shalcoh (ANR-14-CE21-0007); Fonds Agir Pour les Maladies Chroniques 2011 (APMC, CDMR R13076CC); AGIRàdom. E.F.S. is supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health. C.V. benefited of a doctoral grant from University Grenoble Alpes.
The authors report no conflicts of interest.
The findings expressed in this article are the opinions of the authors and do not necessarily reflect the official position of the Centers for Disease Control and Prevention (CDC). Use of trade names is for identification only and does not imply endorsement by the CDC, the Public Health Service, or the US Department of Health and Human Services.
† Dr. Xiaoyun Sherry Ye passed away in 2018.
The code of the simulation can be obtained from the last author.
Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).
Correspondence: Rémy Slama, Institute for Advanced Biosciences – Centre de Recherche INSERM-CNRS-Univ. Grenoble-Alpes U1209, UGA Site Santé, Allée des Alpes, 38700 La Tronche, France. E-mail: email@example.com.