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Descriptive Analytics for Occupational Health: Is Benzene Metabolism in Exposed Workers More Efficient at Very Low Concentrations?

  • Louis Anthony Cox Jr.
  • Douglas A. Popken
  • Richard X. Sun
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 270)

Abstract

The occupational risks to workers from noxious substances inhaled in air depend on the concentrations inhaled and on what happen to the inhaled substances—for example, whether they are swiftly detoxified and eliminated from the body without doing harm, or whether they are metabolized to form toxic concentrations of metabolites in target tissues. Descriptive analytics applied to data on inhaled concentrations and metabolites formed can be used to clarify how efficiently the body produces toxic metabolites at low exposure concentrations. This chapter applies descriptive analytics methods introduced in Chaps.  1 3, including interaction plots, nonparametric regression, CART trees, and Bayesian networks, to data on benzene metabolites in Chinese factory workers in an effort to resolve a recent puzzle in the literature on low dose benzene toxicology. For readers who do not care to pursue this topic further, we recommend quickly examining the figures to see how plots and visualizations of patterns in the data can be displayed and used to gain insight into the dependencies among variables.

References

  1. Aksoy M, Erdem S, DinCol G (1974) Leukemia in shoe-workers exposed chronically to benzene. Blood 44(6):837–841Google Scholar
  2. Cox LA Jr (2006) Universality of J-shaped and U-shaped dose-response relations as emergent properties of stochastic transition systems. Dose Response 3(3):353–368.  https://doi.org/10.2203/dose-response.0003.03.006 CrossRefGoogle Scholar
  3. Cox LA Jr (2009) Hormesis without cell killing. Risk Anal 29(3):393–400.  https://doi.org/10.1111/j.1539-6924.2008.01120.x CrossRefGoogle Scholar
  4. Kim S, Vermeulen R, Waidyanatha S, Johnson BA, Lan Q, Rothman N, Smith MT, Zhang L, Li G, Shen M, Yin S, Rappaport SM (2006a) Using urinary biomarkers to elucidate dose-related patterns of human benzene metabolism. Carcinogenesis 27(4):772–781CrossRefGoogle Scholar
  5. Kim S, Vermeulen R, Waidyanatha S, Johnson BA, Lan Q, Smith MT, Zhang L, Li G, Shen M, Yin S, Rothman N, Rappaport SM (2006b) Modeling human metabolism of benzene following occupational and environmental exposures. Cancer Epidemiol Biomark Prev 15(11):2246–2252CrossRefGoogle Scholar
  6. Kipen HM, Cody RP, Goldstein BD (1989) Use of longitudinal analysis of peripheral blood counts to validate historical reconstructions of benzene exposure. Environ Health Perspect 82:199–206CrossRefGoogle Scholar
  7. Knutsen JS, Kerger BD, Finley B, Paustenbach DJ (2013) A calibrated human PBPK model for benzene inhalation with urinary bladder and bone marrow compartments. Risk Anal 33(7):1237–1251.  https://doi.org/10.1111/j.1539-6924.2012.01927.x CrossRefGoogle Scholar
  8. Lan Q, Zhang L, Li G, Vermeulen R, Weinberg RS, Dosemeci M, Rappaport SM, Shen M, Alter BP, Wu Y, Kopp W, Waidyanatha S, Rabkin C, Guo W, Chanock S, Hayes RB, Linet M, Kim S, Yin S, Rothman N, Smith MT (2004) Hematotoxicity in workers exposed to low levels of benzene. Science 306(5702):1774–1776CrossRefGoogle Scholar
  9. Liermann M, Steel A, Rosing M, Guttorp P (2004) Random denominators and the analysis of ratio data. Environ Ecol Stat 11(1):55–71CrossRefGoogle Scholar
  10. McHale CM, Zhang L, Lan Q, Vermeulen R, Li G, Hubbard AE, Porter KE, Thomas R, Portier CJ, Shen M, Rappaport SM, Yin S, Smith MT, Rothman N (2011) Global gene expression profiling of a population exposed to a range of benzene levels. Environ Health Perspect 119(5):628–634.  https://doi.org/10.1289/ehp.1002546. CrossRefGoogle Scholar
  11. Price PS, Rey TD, Fontaine DD, Arnold SM (2012) A reanalysis of the evidence for increased efficiency in benzene metabolism at airborne exposure levels below 3 p.p.m. Carcinogenesis 33(11):2094–2099.  https://doi.org/10.1093/carcin/bgs257 CrossRefGoogle Scholar
  12. Price PS, Rey TD, Fontaine DD, Arnold SM (2013) Letter to the editor in response to ‘Low-dose metabolism of benzene in humans: science and obfuscation’ Rappaport et al. (2013). Carcinogenesis 34(7):1692–1696.  https://doi.org/10.1093/carcin/bgt101. Epub 2013 Mar 25CrossRefGoogle Scholar
  13. Rappaport SM, Yeowell-O’Connell K, Smith MT, Dosemeci M, Hayes RB, Zhang L, Li G, Yin S, Rothman N (2002) Non-linear production of benzene oxide-albumin adducts with human exposure to benzene. J Chromatogr B Analyt Technol Biomed Life Sci 778(1–2):367–374CrossRefGoogle Scholar
  14. Rappaport SM, Kim S, Lan Q, Vermeulen R, Waidyanatha S, Zhang L, Li G, Yin S, Hayes RB, Rothman N, Smith MT (2009) Evidence that humans metabolize benzene via two pathways. Environ Health Perspect 117(6):946–952.  https://doi.org/10.1289/ehp.0800510 CrossRefGoogle Scholar
  15. Rappaport SM, Kim S, Lan Q, Li G, Vermeulen R, Waidyanatha S, Zhang L, Yin S, Smith MT, Rothman N (2010) Human benzene metabolism following occupational and environmental exposures. Chem Biol Interact 184(1–2):189–195.  https://doi.org/10.1016/j.cbi.2009.12.017 CrossRefGoogle Scholar
  16. Rappaport SM, Kim S, Thomas R, Johnson BA, Bois FY, Kupper LL (2013) Low-dose metabolism of benzene in humans: science and obfuscation. Carcinogenesis 34(1):2–9.  https://doi.org/10.1093/carcin/bgs382 CrossRefGoogle Scholar
  17. Schirrmeister A, Flora B (2008) The coming wave of Benzene litigation. In: Presentation at national association of railroad trial counsel special litigation conference XVIII, Lake Tahoe, CA, 7–8 Feb 2008. http://www.sdablaw.com/html/020708TheComingWaveOfBenzeneLitigation(00051891).pdf
  18. Steinmaus C, Smith AH, Jones RM, Smith MT (2008) Meta-analysis of benzene exposure and non-Hodgkin lymphoma: biases could mask an important association. Occup Environ Med 65(6):371–378.  https://doi.org/10.1136/oem.2007.036913 CrossRefGoogle Scholar
  19. Steinmaus C, Smith AH, Smith MT (2011) Regarding “meta-analysis and causal inference: a case study of benzene and non-Hodgkin lymphoma”: an incomplete analysis. Ann Epidemiol 21(1):67–69CrossRefGoogle Scholar
  20. Thomas R, Hubbard AE, McHale CM, Zhang L, Rappaport SM, Lan Q, Rothman N, Vermeulen R, Guyton KZ, Jinot J, Sonawane BR, Smith MT (2014) Characterization of changes in gene expression and biochemical pathways at low levels of benzene exposure. PLoS One 9(5):e91828.  https://doi.org/10.1371/journal.pone.0091828 CrossRefGoogle Scholar
  21. Vlaanderen J, Lan Q, Kromhout H, Rothman N, Vermeulen R (2012) Occupational benzene exposure and the risk of chronic myeloid leukemia: a meta-analysis of cohort studies incorporating study quality dimensions. Am J Ind Med 55(9):779–785.  https://doi.org/10.1002/ajim.22087 CrossRefGoogle Scholar
  22. Walter RB, Appelbaum FR, Estey EH, Bernstein ID (2012) Acute myeloid leukemia stem cells and CD33-targeted immunotherapy. Blood 119(26):6198–6208.  https://doi.org/10.1182/blood-2011-11-325050 CrossRefGoogle Scholar
  23. Weed DL (2010) Meta-analysis and causal inference: a case study of benzene and non-Hodgkin lymphoma. Ann Epidemiol 20(5):347–355.  https://doi.org/10.1016/j.annepidem.2010.02.001 CrossRefGoogle Scholar
  24. Wong O (1995) Risk of acute myeloid leukaemia and multiple myeloma in workers exposed to benzene. Occup Environ Med 52(6):380–384CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Louis Anthony Cox Jr.
    • 1
  • Douglas A. Popken
    • 2
  • Richard X. Sun
    • 3
  1. 1.Cox AssociatesDenverUSA
  2. 2.Cox AssociatesLittletonUSA
  3. 3.Cox AssociatesEast BrunswickUSA

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