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Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

Author

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  • Teresa Chahine

    (Harvard School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA 02215, USA)

  • Bradley D. Schultz

    (US Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, NC 27711, USA)

  • Valerie G. Zartarian

    (US Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, NC 27711, USA)

  • Jianping Xue

    (US Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, NC 27711, USA)

  • S. V. Subramanian

    (Harvard School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA 02215, USA)

  • Jonathan I. Levy

    (Harvard School of Public Health, Harvard University, 677 Huntington Avenue, Boston, MA 02215, USA
    Boston University School of Public Health, 715 Albany Street, Talbot Building, Boston, MA 02118, USA)

Abstract

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors.

Suggested Citation

  • Teresa Chahine & Bradley D. Schultz & Valerie G. Zartarian & Jianping Xue & S. V. Subramanian & Jonathan I. Levy, 2011. "Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking," IJERPH, MDPI, vol. 8(9), pages 1-24, September.
    • Handle: RePEc:gam:jijerp:v:8:y:2011:i:9:p:3688-3711:d:13935
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    References listed on IDEAS

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    1. Ari S. Lewis & Sonja N. Sax & Susan C. Wason & Sharan L. Campleman, 2011. "Non-Chemical Stressors and Cumulative Risk Assessment: An Overview of Current Initiatives and Potential Air Pollutant Interactions," IJERPH, MDPI, vol. 8(6), pages 1-54, June.
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    Cited by:

    1. Richard Todd Niemeier & Pamela R.D. Williams & Alan Rossner & Jane E. Clougherty & Glenn E. Rice, 2020. "A Cumulative Risk Perspective for Occupational Health and Safety (OHS) Professionals," IJERPH, MDPI, vol. 17(17), pages 1-19, August.

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