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Optimal Exposure Biomarkers for Nonpersistent Chemicals in Environmental Epidemiology

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      We discuss considerations that are essential when evaluating exposure to nonpersistent, semivolatile environmental chemicals such as phthalates and phenols (e.g., bisphenol A). A biomarker should be chosen to best represent usual personal exposures and not recent, adventitious, or extraneous exposures. Biomarkers should be selected to minimize contamination arising from collection, sampling, or analysis procedures. Pharmacokinetics should be considered; for example, nonpersistent, semivolatile chemicals are metabolized quickly, and urine is the compartment with the highest concentrations of metabolites. Because these chemicals are nonpersistent, knowledge of intraindividual reliability over the biologic window of interest is also required. In recent years researchers have increasingly used blood as a matrix for characterizing exposure to nonpersistent chemicals. However, the biologic and technical factors noted above strongly support urine as the optimal matrix for measuring nonpersistent, semivolatile, hydrophilic environmental agents.

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      Most cited references 48

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      Urinary Creatinine Concentrations in the U.S. Population: Implications for Urinary Biologic Monitoring Measurements

      Biologic monitoring (i.e., biomonitoring) is used to assess human exposures to environmental and workplace chemicals. Urinary biomonitoring data typically are adjusted to a constant creatinine concentration to correct for variable dilutions among spot samples. Traditionally, this approach has been used in population groups without much diversity. The inclusion of multiple demographic groups in studies using biomonitoring for exposure assessment has increased the variability in the urinary creatinine levels in these study populations. Our objectives were to document the normal range of urinary creatinine concentrations among various demographic groups, evaluate the impact that variations in creatinine concentrations can have on classifying exposure status of individuals in epidemiologic studies, and recommend an approach using multiple regression to adjust for variations in creatinine in multivariate analyses. We performed a weighted multivariate analysis of urinary creatinine concentrations in 22,245 participants of the Third National Health and Nutrition Examination Survey (1988–1994) and established reference ranges (10th–90th percentiles) for each demographic and age category. Significant predictors of urinary creatinine concentration included age group, sex, race/ethnicity, body mass index, and fat-free mass. Time of day that urine samples were collected made a small but statistically significant difference in creatinine concentrations. For an individual, the creatinine-adjusted concentration of an analyte should be compared with a “reference” range derived from persons in a similar demographic group (e.g., children with children, adults with adults). For multiple regression analysis of population groups, we recommend that the analyte concentration (unadjusted for creatinine) should be included in the analysis with urinary creatinine added as a separate independent variable. This approach allows the urinary analyte concentration to be appropriately adjusted for urinary creatinine and the statistical significance of other variables in the model to be independent of effects of creatinine concentration.
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        Temporal Variability of Urinary Phthalate Metabolite Levels in Men of Reproductive Age

        Phthalates are a family of multifunctional chemicals widely used in personal care and other consumer products. The ubiquitous use of phthalates results in human exposure through multiple sources and routes, including dietary ingestion, dermal absorption, inhalation, and parenteral exposure from medical devices containing phthalates. We explored the temporal variability over 3 months in urinary phthalate metabolite levels among 11 men who collected up to nine urine samples each during this time period. Eight phthalate metabolites were measured by solid-phase extraction–high-performance liquid chromatography–tandem mass spectrometry. Statistical analyses were performed to determine the between- and within-subject variance apportionment, and the sensitivity and specificity of a single urine sample to classify a subject’s 3-month average exposure. Five of the eight phthalates were frequently detected. Monoethyl phthalate (MEP) was detected in 100% of samples; monobutyl phthalate, monobenzyl phthalate, mono-2-ethylhexyl phthalate (MEHP), and monomethyl phthalate were detected in > 90% of samples. Although we found both substantial day-to-day and month-to-month variability in each individual’s urinary phthalate metabolite levels, a single urine sample was moderately predictive of each subject’s exposure over 3 months. The sensitivities ranged from 0.56 to 0.74. Both the degree of between- and within-subject variance and the predictive ability of a single urine sample differed among phthalate metabolites. In particular, a single urine sample was most predictive for MEP and least predictive for MEHP. These results suggest that the most efficient exposure assessment strategy for a particular study may depend on the phthalates of interest.
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          Temporal variability in urinary concentrations of phthalate metabolites, phytoestrogens and phenols among minority children in the United States.

          Exposure to endocrine disruptors (EDs), including some phthalates, phytoestrogens and phenols can be quantified using biomarkers of exposure. However, reliability in the use of these biomarkers requires an understanding of the timeframe of exposure represented by one measurement. Data on the temporal variability of ED biomarkers are sparse, especially among children. To evaluate intraindividual temporal variability in 19 individual urinary biomarkers (eight phthalate metabolites from six phthalate diesters, six phytoestrogens (two lignans and four isoflavones) and five phenols) among New York City children. Healthy Hispanic and Black children (N=35; 6-10 years old) donated several urine samples over 6 months. To assess temporal variability we used three statistical methods: intraclass correlation coefficient (ICC), Spearman correlation coefficients (SCC) between concentrations measured at different timepoints, and surrogate category analysis to determine how well the tertile categories based on a single measurement represented a 6-month average concentration. Surrogate category analysis indicated that a single sample provides reliable ranking for all analytes; at least three of four surrogate samples predicted the 6-month mean concentration. Of the 19 analytes, the ICC was >0.2 for 18 analytes and >0.3 for 10 analytes. Correlations among sample concentrations throughout the 6-month period were observed for all analytes; 14 analyte concentrations were correlated at 16 weeks. The reasonable degree of temporal reliability and the wide range of concentrations of phthalate metabolites, phytoestrogens and phenols suggest that these biomarkers are appropriate for use in epidemiologic studies of environmental exposures in relation to health outcomes in children.
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            Author and article information

            Affiliations
            [1 ]Centers for Disease Control and Prevention, Atlanta, Georgia, USA
            [2 ]National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
            [3 ]Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Ruhr-Universität Bochum, Bochum, Germany
            [4 ]Icahn School of Medicine at Mount Sinai, New York, New York, USA
            [5 ]Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
            [6 ]Milken Institute School of Public Health, George Washington University, Washington, DC, USA
            [7 ]British Columbia Children’s Hospital, Vancouver, British Columbia, Canada
            [8 ]Silent Spring Institute, Boston, Massachusetts, USA
            [9 ]University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
            [10 ]Mailman School of Public Health, Columbia University, New York, New York, USA
            Author notes
            Address correspondence to M.S. Wolff, Mount Sinai Medical Center, Preventive Medicine, One Gustave L. Levy Place, Box 1057, New York, NY 10029 USA. E-mail: mary.wolff@ 123456mssm.edu
            Journal
            Environ Health Perspect
            Environ. Health Perspect
            EHP
            Environmental Health Perspectives
            NLM-Export
            0091-6765
            1552-9924
            01 July 2015
            July 2015
            : 123
            : 7
            : A166-A168
            26132373
            4492274
            ehp.1510041
            10.1289/ehp.1510041

            Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, “Reproduced with permission from Environmental Health Perspectives”); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.

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            Public health

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