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Reliability of concentrations of organophosphate pesticide metabolites in serial urine specimens from pregnancy in the Generation R Study

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Author: Spaan, S. · Pronk, A. · Koch, H.M. · Jusko, T.A. · Jaddoe, V.M.W. · Shaw, P.A. · Tiemeier, H.M. · Hofman, A. · Pierik F.H. · Longnecker M.P.
Source:Journal of Exposure Science and Environmental Epidemiology, May/June, 25, 286-294
Identifier: 525001
doi: DOI:10.1038/jes.2014.81
Keywords: Nutrition · Organophosphate pesticide metabolites · Environmental exposure · Variability; reliability · Cohort study · Epidemiologic studies · Food and Nutrition · Healthy Living · Life · RAPID - Risk Analysis for Products in Development · ELSS - Earth, Life and Social Sciences


The widespread use of organophosphate (OP) pesticides has resulted in ubiquitous exposure in humans, primarily through their diet. Exposure to OP pesticides may have adverse health effects, including neurobehavioral deficits in children. The optimal design of new studies requires data on the reliability of urinary measures of exposure. In the present study, urinary concentrations of six dialkyl phosphate (DAP) metabolites, the main urinary metabolites of OP pesticides, were determined in 120 pregnant women participating in the Generation R Study in Rotterdam. Intra-class correlation coefficients (ICCs) across serial urine specimens taken at o18, 18–25, and 425 weeks of pregnancy were determined to assess reliability. Geometric mean total DAP metabolite concentrations were 229 (GSD 2.2), 240 (GSD 2.1), and 224 (GSD 2.2) nmol/g creatinine across the three periods of gestation. Metabolite concentrations from the serial urine specimens in general correlated moderately. The ICCs for the six DAP metabolites ranged from 0.14 to 0.38 (0.30 for total DAPs), indicating weak to moderate reliability. Although the DAP metabolite levels observed in this study are slightly higher and slightly more correlated than in previous studies, the low to moderate reliability indicates a high degree of within-person variability, which presents challenges for designing well-powered epidemiological studies.