BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Authors: Nancy Mervish; Ben Blount; Liza Valentin-Blasini; Barbara Brenner; Maida P Galvez; Mary S Wolff; Susan L Teitelbaum Journal: J Expo Sci Environ Epidemiol Date: 2011-12-14 Impact factor: 5.563
Authors: Candace A Robledo; Jennifer D Peck; Julie Stoner; Antonia M Calafat; Hélène Carabin; Linda Cowan; Jean R Goodman Journal: Int J Hyg Environ Health Date: 2015-01-31 Impact factor: 5.840
Authors: Amir Miodovnik; Stephanie M Engel; Chenbo Zhu; Xiaoyun Ye; Latha V Soorya; Manori J Silva; Antonia M Calafat; Mary S Wolff Journal: Neurotoxicology Date: 2010-12-21 Impact factor: 4.294
Authors: Shaina L Stacy; Melissa Eliot; Taylor Etzel; George Papandonatos; Antonia M Calafat; Aimin Chen; Russ Hauser; Bruce P Lanphear; Sheela Sathyanarayana; Xiaoyun Ye; Kimberly Yolton; Joseph M Braun Journal: Environ Sci Technol Date: 2017-05-25 Impact factor: 9.028
Authors: Mary E Mortensen; Antonia M Calafat; Xiaoyun Ye; Lee-Yang Wong; David J Wright; James L Pirkle; Lori S Merrill; John Moye Journal: Environ Res Date: 2014-01-11 Impact factor: 6.498
Authors: Ryan C Lewis; John D Meeker; Karen E Peterson; Joyce M Lee; Gerry G Pace; Alejandra Cantoral; Martha Maria Téllez-Rojo Journal: Chemosphere Date: 2013-09-14 Impact factor: 7.086