Abstract
Why have occupational safety regulations in the United States not been more successful in protecting worker health from mesothelioma risks, while apparently succeeding relatively well in reducing silicosis risks? This chapter seeks to apply insights from the simulation models developed in Chaps. 4 and 5 to address this important practical question and to suggest possible directions for revising regulations of occupational exposures to make them more causally effective in protecting worker health. It is less technical than Chaps. 4 and 5, however. The main goal of this chapter is not to develop, but to apply, the pharmacokinetic (PBPK) models from Chaps. 4 and 5 to perform computational experiments illuminating how different time courses of exposure with the same time-weighted average (TWA) concentration affect internal doses in target tissues (lung for RCS and mesothelium for asbestos). Key conclusions are that (1) For RCS, but not asbestos, limiting average (TWA) exposure concentrations also tightly constrains internal doses and ability to trigger chronic inflammation and resulting increases in disease risks; (2) For asbestos, excursions (i.e., spikes in concentrations) and especially the times between them are crucial drivers of internal doses and time until chronic inflammation; and hence (3) These dynamic aspects of exposure, which are not addressed by current occupational safety regulations, should be constrained to better protect worker health. Adjusting permissible average exposure concentration limits (PELs) and daily excursion limits (ELs) is predicted to have little impact on reducing mesothelioma risks, but increasing the number of days between successive excursions is predicted to be relatively effective in reducing worker risks, even if it has little or no impact on TWA average concentrations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bang KM, Mazurek JM, Wood JM, White GE, Hendricks SA, Weston A. Silicosis mortality trends and new exposures to respirable crystalline silica - United States, 2001-2010. MMWR Morb Mortal Wkly Rep. 2015;64(5):117–20.
Baroja-Mazo A, MartÃn-Sánchez F, Gomez AI. The NLRP3 inflammasome is released as a particulate danger signal that amplifies the inflammatory response. Nat Immunol. 2014;15(8):738–48. https://doi.org/10.1038/ni.2919.
Belkebir E, Rousselle C, Duboudin C, Bodin L. Bonvallot N Haber’s rule duration adjustments should not be used systematically for risk assessment in public health decision-making. Toxicol Lett. 2011;204(2-3):148–55. https://doi.org/10.1016/j.toxlet.2011.04.026.
Betti M, Neri M, Ferrante D, Landi S, Biava A, Gemignani F, Bertolotti M, Mirabelli D, Padoan M, Ugolini D, Botta M, Bonassi S, Magnani C, Dianzani I. Pooled analysis of NAT2 genotypes as risk factors for asbestos-related malignant mesothelioma. Int J Hyg Environ Health. 2009;212(3):322–9. https://doi.org/10.1016/j.ijheh.2008.08.001.
Bogen KT. Inflammation as a cancer co-initiator: new mechanistic model predicts low/negligible risk at noninflammatory carcinogen doses. Dose-Response. 2019;17(2):1559325819847834. https://doi.org/10.1177/1559325819847834.
Cardarelli JJ 2nd, Ulsh BA. It Is Time to Move Beyond the Linear No-Threshold Theory for Low-Dose Radiation Protection. Dose Response. 2018 Jul 1;16(3):1559325818779651. https://doi.org/10.1177/1559325818779651. PMID: 30013457; PMCID: PMC6043938.
Cho WC, Kwan CK, Yau S, So PP, Poon PC, Au JS. The role of inflammation in the pathogenesis of lung cancer. Expert Opin Ther Targets. 2011;15(9):1127–37. https://doi.org/10.1517/14728222.2011.599801.
Cowan DM, Cheng TJ, Ground M, Sahmel J, Varughese A, Madl AK. Analysis of workplace compliance measurements of asbestos by the U.S. Occupational Safety and Health Administration (1984-2011). Regul Toxicol Pharmacol. 2015;72(3):615–29. https://doi.org/10.1016/j.yrtph.2015.05.002.
Cox LA. Risk analysis implications of dose-response thresholds for NLRP3 inflammasome-mediated diseases: respirable crystalline silica and lung cancer as an example. Dose-Response. 2019;17(2):155932581983690. https://doi.org/10.1177/1559325819836900.
Cox LA Jr, Bird MG, Griffis L. Isoprene cancer risk and the time pattern of dose administration. Toxicology. 1996;113(1-3):263–72.
DeStefano A, Martin CF, Wallace DI. A dynamical model of the transport of asbestos fibres in the human body. J Biol Dyn. 2017;11(1):365–77. https://doi.org/10.1080/17513758.2017.1355489.
Donaldson K, Murphy FA, Duffin R, Poland CA. Asbestos, carbon nanotubes and the pleural mesothelium: a review of the hypothesis regarding the role of long fibre retention in the parietal pleura, inflammation and mesothelioma. Part Fibre Toxicol. 2010;7:5. https://doi.org/10.1186/1743-8977-7-5.
Doney BC, Blackley D, Hale JM, Halldin C, Kurth L, Syamlal G, Laney AS. Respirable coal mine dust in underground mines, United States, 1982-2017. Am J Ind Med. 2019;62(6):478–85. https://doi.org/10.1002/ajim.22974.
Gomes M, Teixeira AL, Coelho A, Araújo A, Medeiros R. The role of inflammation in lung cancer. Adv Exp Med Biol. 2014;816:1–23. https://doi.org/10.1007/978-3-0348-0837-8_1.
Gottschalk RA, Martins AJ, Angermann BR, Dutta B, Ng CE, Uderhardt S, Tsang JS, Fraser ID, Meier-Schellersheim M, Germain RN. Distinct NF-κB and MAPK activation thresholds uncouple steady-state microbe sensing from anti-pathogen inflammatory responses. Cell Syst. 2016;2(6):378–90. https://doi.org/10.1016/j.cels.2016.04.016.
Groslambert M, Py BF. Spotlight on the NLRP3 inflammasome pathway. J Inflamm Res. 2018;11:359–74. https://doi.org/10.2147/JIR.S141220.
Hall NB, Blackley DJ, Halldin CN, Laney AS. Current review of pneumoconiosis among US coal miners. Curr Environ Health Rep. 2019;6:137–47. https://doi.org/10.1007/s40572-019-00237-5.
Hirvonen A, Saarikoski ST, Linnainmaa K, Koskinen K, Husgafvel-Pursiainen K, Mattson K, Vainio H. Glutathione S-transferase and N-acetyltransferase genotypes and asbestos-associated pulmonary disorders. J Natl Cancer Inst. 1996;88(24):1853–6.
Kadariya Y, Menges CW, Talarchek J, Cai KQ, Klein-Szanto AJ, Pietrofesa RA, Christofidou-Solomidou M, Cheung M, Mossman BT, Shukla A, Testa JR. Inflammation-related IL1β/IL1R signaling promotes the development of asbestos-induced malignant mesothelioma. Cancer Prev Res. 2016;9(5):406–14. https://doi.org/10.1158/1940-6207.CAPR-15-0347.
Karki R, Man SM, Kanneganti TD. Inflammasomes and cancer. Cancer Immunol Res. 2017;5(2):94–9. https://doi.org/10.1158/2326-6066.CIR-16-0269.
Kim AH, Kohn MC, Nyska A, Walker NJ. Area under the curve as a dose metric for promotional responses following 2,3,7,8-tetrachlorodibenzo-p-dioxin exposure. Toxicol Appl Pharmacol. 2003;191(1):12–21.
Kukkonen MK, Hämäläinen S, Kaleva S, Vehmas T, Huuskonen MS, Oksa P, Vainio H, Piirilä P, Hirvonen A. Genetic susceptibility to asbestos-related fibrotic pleuropulmonary changes. Eur Respir J. 2011;38(3):672–8. https://doi.org/10.1183/09031936.00049810.
Kukkonen MK, Vehmas T, Piirilä P, Hirvonen A. Genes involved in innate immunity associated with asbestos-related fibrotic changes. Occup Environ Med. 2014;71(1):48–54. https://doi.org/10.1136/oemed-2013-101555.
Li L, Tian T, Zhang X. Stochastic modelling of multistage carcinogenesis and progression of human lung cancer. J Theor Biol. 2019;479:81–9. https://doi.org/10.1016/j.jtbi.2019.07.006.
Mazurek JM, Syamlal G, Wood JM, Hendricks SA, Weston A. Malignant mesothelioma mortality — United States, 1999–2015. MMWR Morb Mortal Wkly Rep. 2017;66:214–8.
Mazurek JM, Wood J, Blackley DJ, Weissman DN. Coal workers’ pneumoconiosis-attributable years of potential life lost to life expectancy and potential life lost before age 65 years - United States, 1999-2016. MMWR Morb Mortal Wkly Rep. 2018;67(30):819–24. https://doi.org/10.15585/mmwr.mm6730a3.
Nakayama M. Macrophage recognition of crystals and nanoparticles. Front Immunol. 2018;9:103. https://doi.org/10.3389/fimmu.2018.00103.
Sato T, Shimosato T, Klinman DM. Silicosis and lung cancer: current perspectives. Lung Cancer. 2018;9:91–101. https://doi.org/10.2147/LCTT.S156376.
Sayan M, Mossman BT. The NLRP3 inflammasome in pathogenic particle and fibre-associated lung inflammation and diseases. Part Fibre Toxicol. 2016;13(1):51. https://doi.org/10.1186/s12989-016-0162-4.
Simmons JE, Evans MV, Boyes WK. Moving from external exposure concentration to internal dose: duration extrapolation based on physiologically based pharmacokinetic derived estimates of internal dose. J Toxicol Environ Health A. 2005;68(11-12):927–50.
Tan E, Warren N. (2011). Mesothelioma mortality in Great Britain The revised risk and two-stage clonal expansion models Prepared by the Health and Safety Laboratory for the Health and Safety Executive. Harpur Hill Buxton Derbyshire SK179JN. www.hse.gov.uk/research/rrpdf/rr876.pdf
Thompson JK, MacPherson MB, Beuschel SL, Shukla A. Asbestos-induced mesothelial to fibroblastic transition is modulated by the inflammasome. Am J Pathol. 2017;187(3):665–78. https://doi.org/10.1016/j.ajpath.2016.11.008.
Tran CL, Graham M, Buchanan D (2001) A biomathematical model for rodent and human lung describing exposure, dose, and response to inhaled silica. Institute of Occupational Medicine Technical Memorandum. 2001 TM/01/01. http://www.iom-world.org/pubs/IOM_TM0104.pdf
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Cox Jr., L.A. (2021). Nonlinear Dose-Time-Response Risk Models for Protecting Worker Health. In: Quantitative Risk Analysis of Air Pollution Health Effects. International Series in Operations Research & Management Science, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-030-57358-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-57358-4_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57357-7
Online ISBN: 978-3-030-57358-4
eBook Packages: Business and ManagementBusiness and Management (R0)