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Description of exposure profiles for seven environmental chemicals in a US population using recursive partition mixture modeling (RPMM)

Journal of Exposure Science & Environmental Epidemiology volume 29, pages 61–70 (2019)Cite this article

Abstract

Biomonitoring studies have shown that humans are exposed to numerous environmental chemicals. Previous work provides limited insights into the dynamic relationship between different chemicals within a population. The objective of this study is to develop an analytical method identifying exposure profiles of seven common environmental chemicals and determine how exposure profiles differ by sociodemographic groups and National Health and Nutrition Examination Survey (NHANES) 2003–2012 cycle year. We used recursive partition mixture modeling (RPMM) to define classes of the population with similar exposure profiles of lead, cadmium, 2,4-dichlorophenol, 2,5-dichlorophenol, bisphenol A (BPA), triclosan, and benzophenone-3 in individuals aged ≥6 years. Additionally, quasibinomial logistic regression was used to examine the association between each class and selected demographic characteristics. Eight exposure profiles were identified. Individuals who clustered together and had the highest chemical exposures were more likely to be older, to be Non-Hispanic Black (NHB) or Other Hispanic (OH), more likely to live below the poverty line, more likely to be male, and more likely to have participated in the earlier NHANES cycle (2003–2004). The developed method described the dynamic relationship between chemicals and shows that this relationship is different for subpopulations based on their sociodemographic characteristics.

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References

  1. Weinhold B. Body of evidence. Environ Health Perspect. 2003;111(7):A394.

    Article  Google Scholar 

  2. Watson G. Generations X. Results of WWF’s European Family Biomonitoring Survey. WWF DetoX Campaign. Gidaknubgm Surrey. UK: World Wildlife Fund (WWF); 2005.

    Google Scholar 

  3. Carrico C, Gennings C, Wheeler DC, Factor-Litvak P. Characterization of weighted quantile sum regression for highly correlated data in a risk analysis setting. J Agric Biol Environ Stat. 2014;20(1):100–210.

    Article  Google Scholar 

  4. USEPA. Supplementary guidance for conducting halth risk assessment of chemical mixtures. Washington, DC: US Environmental Protection Agency Office of Pesticidie Programs; 2000.

    Google Scholar 

  5. Bouchard MF, Oulhote Y, Sagiv SK, Saint-Amour D, Weuve J. Polychlorinated biphenyl exposures and cognition in older U.S. adults: NHANES (1999–2002). Environ Health Perspect. 2014;122(1):73–8.

    Article  Google Scholar 

  6. Van den Berg M, Birnbaum LS, Denison M, De Vito M, Farland W, Feeley M, et al. The 2005 World Health Organization reevaluation of human and mammalian toxic equivalency factors for dioxins and dioxin-like compounds. Toxicol Sci. 2006;93(2):223–41.

    Article  Google Scholar 

  7. Van den Berg M, Birnbaum L, Bosveld A, Brunström B, Cook P, Feeley M, et al. Toxic equivalency factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife. Environ Health Perspect. 1998;106:775

    Article  Google Scholar 

  8. Monosson E. Chemical mixtures: considering the evolution of toxicology and chemical assessment. Environ Health Perspect. 2005;113(4):383–390.

    Article  CAS  Google Scholar 

  9. Christensen KLY, Carrico CK, Sanyal AJ, Gennings C. Multiple classes of environmental chemicals are associated with liver disease: NHANES 2003–2004. Int J Hyg Environ Health. 2013;216(6):703–9.

    Article  Google Scholar 

  10. Gennings C, Ellis R, Ritter JK. Linking empirical estimates of body burden of environmental chemicals and wellness using NHANES data. Environ Int. 2012;39(1):56–65.

    Article  CAS  Google Scholar 

  11. Gennings C, Sabo R, Carney E. Identifying subsets of complex mixtures most associated with complex diseases: polychlorinated biphenyls and endometriosis as a case study. Epidemiology. 2010;21(4):S77–S84.

    Article  Google Scholar 

  12. NCHS. NHANES 2003-2004 Dietary Data 2014. http://wwwn.cdc.gov/nchs/nhanes/search/datapage.aspx?Component=Dietary&CycleBeginYear=2003.

  13. CDC. National Health and Nutrition Examination Survey Questionnaires, Datasets and Related Docmentation 2012. http://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm.

  14. CDC. Laboratory Procedure Manual Analyte: Lead Cadmium Mercury 2004. http://www.cdc.gov/nchs/data/nhanes/nhanes_05_06/pbcd_d_met_lead_cadmium.pdf.

  15. CDC. Laboratory Procedure Manual Analyte: 2,4-dichlorophenol, 2,5-dichlorophenol, orthophenylphenol, 2,4,5-trichlorophenol, and 2,4,6-trichlorophenol 2009. http://www.cdc.gov/nchs/data/nhanes/nhanes_05_06/PP_D_met_pesticides.pdf.

  16. CDC. Laboratory Procedure Manual Analyte: Benzophenone-3, bisphenol A, 2,4-dichlorophenol, 2,5-dichlorophenol, ortho-phenylphenol, methyl-, ethyl-, propyl-, and butyl parabens, 4-tertoctylphenol, 2,4,5-trichlorophenol, 2,4,6-trichlorophenol, triclosan 2009. http://www.cdc.gov/nchs/data/nhanes/nhanes_05_06/eph_d_met_phenols_parabens.pdf.

  17. Johnson C, Paulose-Ram R, Ogden C. National Health and Nutrition Examination Survey: Analytic guidelines, 1999–2010. National Center for Health Statistics. Vital Health Stat. 2013;2(161).

  18. Houseman EA, Christensen BC, Yeh R-F, Marsit CJ, Karagas MR, Wrensch M, et al. Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions. BMC Bioinforma. 2008;9:365

    Article  Google Scholar 

  19. Koestler DC, Marsit CJ, Christensen BC, Karagas MR, Bueno R, Sugarbaker DJ, et al. Semi-supervised recursively partitioned mixture models for identifying cancer subtypes. Bioinformatics. 2010;26:2578–85.

    Article  CAS  Google Scholar 

  20. Safe SH, Polychlorinated Biphenyls (PCBs): environmental impact, biochemical and toxic responses, and implications for risk assessment. Crit Rev Toxicol. 1994;24:87–149.

    Article  CAS  Google Scholar 

  21. Tonacchera M, Pinchera A, Dimida A, Ferrarini E, Agretti P, Vitti P, et al. Relative potencies and additivity of perchlorate, thiocyanate, nitrate, and iodide on the inhibition of radioactive iodide uptake by the human sodium iodide symporter. Thyroid. 2004;14:1012–9.

    Article  CAS  Google Scholar 

  22. Cedergreen N, Quantifying synergy: a systematic review of mixture toxicity studies within environmental toxicology. PLoS ONE. 2014;9:e96580

    Article  Google Scholar 

  23. Tanida T, Warita K, Ishihara K, Fukui S, Mitsuhashi T, Sugawara T, et al. Fetal and neonatal exposure to three typical environmental chemicals with different mechanisms of action: mixed exposure to phenol, phthalate, and dioxin cancels the effects of sole exposure on mouse midbrain dopaminergic nuclei. Toxicol Lett. 2009;189:40–7.

    Article  CAS  Google Scholar 

  24. Payne J, Scholze M, Kortenkamp A, Mixtures of four organochlorines enhance human breast cancer cell proliferation. Environ Health Perspect. 2001;109:391

    Article  CAS  Google Scholar 

  25. Hermens J, Leeuwangh P, Musch A, Joint toxicity of mixtures of groups of organic aquatic pollutants to the guppy (Poecilia reticulata). Ecotoxicol Environ Saf. 1985;9:321–6.

    Article  CAS  Google Scholar 

  26. Seed J, Brown RP, Olin SS, Foran JA, Chemical mixtures: current risk assessment methodologies and future directions. Regul Toxicol Pharmacol. 1995;22:76–94.

    Article  CAS  Google Scholar 

  27. Altman RG, Morello-Frosch R, Brody JG, Rudel R, Brown P, Averick M, Pollution comes home and gets personal: women’s experience of household chemical exposure. J Health Social Behav. 2008;49:417–35.

    Article  Google Scholar 

  28. Vrijheid M. Health Eff Resid Hazard Waste Land sites: a Rev Epidemiol Lit Environ Health Perspect. 2000;108(Suppl 1):101.

    Google Scholar 

  29. Center for Disease Control and Prevention. Biomonitoring Summary: Lead 2013. http://www.cdc.gov/biomonitoring/Lead_BiomonitoringSummary.html.

  30. ATSDR. Public Health Statement: Cadmium 2012. http://www.atsdr.cdc.gov/ToxProfiles/tp5-c1-b.pdf.

  31. Wei Y, Zhu J, Nguyen A, Urinary concentrations of dichlorophenol pesticides and obesity among adult participants in the U.S. National Health and Nutrition Examination Survey (NHANES) 2005–2008. Int J Hyg Environ Health. 2014;217:294–9.

    Article  CAS  Google Scholar 

  32. Calafat AM, Ye X, Wong L-Y, Reidy JA, Needham LL, Urinary concentrations of triclosan in the US population: 2003-2004. Environ Health Perspect. 2008;116:303

    Article  CAS  Google Scholar 

  33. ATSDR. Background Information for Cadmium. http://www.atsdr.cdc.gov/interactionprofiles/IP-metals1/ip04-a.pdf.

  34. Leggett RW. An age-specific kinetic model of lead metabolism in humans. Environ Health Perspect. 1993;101(7):598.

    Article  CAS  Google Scholar 

  35. Hauser R, Calafat AM, Phthalates and human health. Occup Environ Med. 2005;62:806–18.

    Article  CAS  Google Scholar 

  36. Mahalingaiah S, Meeker JD, Pearson KR, Calafat AM, Ye X, Petrozza J, et al. Temporal variability and predictors of urinary bisphenol A concentrations in men and women. Environ Health Perspect. 2008;116:173

    Article  CAS  Google Scholar 

  37. CDC. Fourth National Report on Human Exposure to Environmental Chemicals. Department of Health and Human Services: Center for Disease Control and Prevention; 2009.

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Acknowledgements

The authors would like to thank Dr. Robert Tanguay for his input on study design. Additionally, we would like to that Dr Andy Houseman for his insights into applying this clustering modeling framework to NHANES data.

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  1. School of Biological and Population Health, College of Public Health and Human Sciences, Corvallis, OR, 97330, USA

    Jennifer Przybyla, Molly Kile & Ellen Smit

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  1. Jennifer Przybyla
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  2. Molly Kile
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  3. Ellen Smit
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Correspondence to Jennifer Przybyla.

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Przybyla, J., Kile, M. & Smit, E. Description of exposure profiles for seven environmental chemicals in a US population using recursive partition mixture modeling (RPMM). J Expo Sci Environ Epidemiol 29, 61–70 (2019). https://doi.org/10.1038/s41370-017-0008-7

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