EPA-Expo-Box (A Toolbox for Exposure Assessors)
(Biomonitoring and Reverse Dosimetry)
Selected References: Biomonitoring
Centers for Disease Control and Prevention (CDC) (2009). Fourth National Report on Human Exposure to Environmental Chemicals (529 pp, 6.4MB, About PDF).
Centers for Disease Control and Prevention (CDC) (2012). Fourth National Report on Human Exposure to Environmental Chemicals, Updated Tables (241 pp, 15.4MB, About PDF).
Clark, K; David, RM; Guinn, R; Kramarz, KW; Lampi, M; Staples, CA. 2011. Modeling human exposure to phthalate Esters: A comparison of indirect and biomonitoring estimation methods. Human and Ecological Risk Assessment: An International Journal, 17:4, 923-965.
Clewell, HJ; Tan, YM; Campbell, JL; Andersen, ME. 2008. Quantitative interpretation of human biomonitoring data. Toxicology and Applied Pharmacology 231: 122–133.
Hays, SM; Becker, R; Leung, HW; Aylward, LL; Pyatt, DW. (2007). Biomonitoring equivalents: A screening approach for interpreting biomonitoring results from a public health risk perspective. Regulatory Toxicology and Pharmacology. 47:96-109.
Koch, HM; Calafat, AM. Human body burdens of chemicals used in plastic manufacture. Philosophical Transactions of the Royal Society B-Biological Sciences 2009: 364(1526): 2063-2078.
NRC. (2006). Human biomonitoring for environmental chemicals. Washington, DC: National Academy Press. http://www.nap.edu/catalog.php?record_id=11700.
Ott, WR. (1985). Total human exposure: An emerging science focuses on humans as receptors of environmental pollution. Environmental Science & Technology, 19, 880‐886.
Paustenbach, D; Galbraith, D. (2006). Biomonitoring and biomarkers: Exposure assessment will never be the same. Environmental Health Perspectives, 114, 1143–1149.
Sexton, K; Needham, LL; Pirkle, JL. (2004). Human biomonitoring of environmental chemicals: Measuring chemicals in human tissue is the "gold standard" for assessing the people’s exposure to pollution. American Scientist, 92(1), 39-45.
Selected References: Dose Reconstruction and PK Modeling
Blancato, JN; Power, FW; Brown, RN; Dary, CD. (2006). Exposure related dose estimating model (ERDEM): A physiologically-based pharmacokinetic and pharmacodynamic (PBPK/PD) model for assessing human exposure risk. EPA/600/R-06/061.
Egeghy, P; Lorber, M. (2010). An assessment of the exposure of Americans to perfluorooctane sulfonate: A comparison of estimated intake with values inferred from NHANES data. J. Expo Sci Environ Epidemiol 21: 150–168.
Koch, HM; Becker, K; Wittassek, M; Seiwert, M; Angerer, J; Kolossa-Gehring, M. (2007). Di-n-butylphthalate and butylbenzylphthalate – urinary metabolite levels and estimated daily intakes: pilot study for the German Environmental Survey on children. Journal of Exposure Science and Environmental Epidemiology, 17, 378-387.
Lorber, M. (2002). A pharmacokinetic model for estimating exposure of Americans to dioxin-like compounds in the past, present, and future. Science of the Total Environment 288:81-95.
Lorber, M; Calafat, A. (2012). Dose reconstruction of di(2-ethylhexyl) phthalate using a simple pharmacokinetic model. Environ Health Perspect 120:1705–1710.
Moir, D. (1999). Physiological modeling of benzo(a)pyrene pharmacokinetics in the rat. In H. Salem and S.A. Katz (Ed.), Toxicity assessment alternatives: Methods, issues, opportunities (pp. 79-95). Totawa, NJ: Humana Press.
Selected References: Creatinine Correction Approach
Cockcroft, DW; Gault, MH. (1976). Prediction of creatinine clearance from serum creatinine. Nephron 16: 31-41.
Mage, DT; Allen, RH; Gondy, G; Smith, W; Barr, DB; Needham, LL. (2004). Estimating pesticide dose from urinary pesticide concentration data by creatinine correction in the Third National Health and Nutrition Examination Survey (NHANES-III). J Expo Anal Environ Epidemiol 14: 457-465. http://dx.doi.org/10.1038/sj.jea.7500343
Mage, DT; Allen, RH; Kodali, A. (2008). Creatinine corrections for estimating children's and adult's pesticide intake doses in equilibrium with urinary pesticide and creatinine concentrations. J Expo Sci Environ Epidemiol 18: 360-368. http://dx.doi.org/10.1038/sj.jes.7500614