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Estimating the social cost of respiratory cancer cases attributable to occupational exposures in France

Author

Listed:
  • Hassan Serrier

    (EES - LEG - Laboratoire d'Economie et de Gestion - UB - Université de Bourgogne - CNRS - Centre National de la Recherche Scientifique)

  • Hélène Sultan-Taieb

    (LEG - Laboratoire d'Economie et de Gestion - UB - Université de Bourgogne - CNRS - Centre National de la Recherche Scientifique)

  • Danièle Luce

    (Irset - Institut de recherche, santé, environnement et travail - UA - Université d'Angers - UR1 - Université de Rennes 1 - UNIV-RENNES - Université de Rennes - EHESP - École des Hautes Études en Santé Publique [EHESP] - INSERM - Institut National de la Santé et de la Recherche Médicale - Biosit : Biologie - Santé - Innovation Technologique - Structure Fédérative de Recherche en Biologie et Santé de Rennes - UA - Université des Antilles)

  • Sophie Béjean

    () (Equipe d'Economie de la Santé - LEG - Laboratoire d'Economie et de Gestion - UB - Université de Bourgogne - CNRS - Centre National de la Recherche Scientifique)

Abstract

Purpose The objective of this article was to estimate the social cost of respiratory cancer cases attributable to occupational risk factors in France in 2010. Methods According to the attributable fraction method and based on available epidemiological data from the lit- erature, we estimated the number of respiratory cancer cases due to each identified risk factor. We used the cost- of-illness method with a prevalence-based approach. We took into account the direct and indirect costs. We estimated the cost of production losses due to morbidity (absenteeism and presenteeism) and mortality costs (years of production losses) in the market and nonmarket spheres. Results The social cost of lung, larynx, sinonasal and mesothelioma cancer caused by exposure to asbestos, chromium, diesel engine exhaust, paint, crystalline silica, wood and leather dust in France in 2010 were estimated at between 917 and 2,181 million euros. Between 795 and 2,011 million euros (87-92 %) of total costs were due to lung cancer alone. Asbestos was by far the risk factor representing the greatest cost to French society in 2010 at between 531 and 1,538 million euros (58-71 %), ahead of diesel engine exhaust, representing an estimated social cost of between 233 and 336 million euros, and crystalline silica (119-229 million euros). Indirect costs represented about 66 % of total costs. Conclusion Our assessment shows the magnitude of the economic impact of occupational respiratory cancers. It allows comparisons between countries and provides valu- able information for policy-makers responsible for defining public health priorities.

Suggested Citation

  • Hassan Serrier & Hélène Sultan-Taieb & Danièle Luce & Sophie Béjean, 2013. "Estimating the social cost of respiratory cancer cases attributable to occupational exposures in France," Post-Print halshs-00922838, HAL.
  • Handle: RePEc:hal:journl:halshs-00922838
    DOI: 10.1007/s10198-013-0528-6
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00922838
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    References listed on IDEAS

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    1. Drummond, Michael F. & Sculpher, Mark J. & Torrance, George W. & O'Brien, Bernie J. & Stoddart, Greg L., 2005. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 3, number 9780198529453.
    2. Tarricone, Rosanna, 2006. "Cost-of-illness analysis: What room in health economics?," Health Policy, Elsevier, vol. 77(1), pages 51-63, June.
    3. Sophie Béjean & Hélène Sultan-Taïeb, 2005. "Modeling the economic burden of diseases imputable to stress at work," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 6(1), pages 16-23, March.
    4. Dionne, Georges & Lebeau, Martin, 2010. "Le calcul de la valeur statistique d’une vie humaine," L'Actualité Economique, Société Canadienne de Science Economique, vol. 86(4), pages 487-530, décembre.
    5. Thomas Barnay & Karine Briard, 2009. "Carrière incomplète et départ en retraite. Une estimation de l'incidence de l'état de santé à partir de données individuelles," Revue économique, Presses de Sciences-Po, vol. 60(2), pages 345-363.
    6. Koopmanschap, Marc A. & Rutten, Frans F. H. & van Ineveld, B. Martin & van Roijen, Leona, 1995. "The friction cost method for measuring indirect costs of disease," Journal of Health Economics, Elsevier, vol. 14(2), pages 171-189, June.
    7. Juan Oliva & Félix Lobo & Julio López-Bastida & Néboa Zozaya & Rosa Romay, 2005. "Indirect costs of cervical and breast cancers in Spain," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 6(4), pages 309-313, December.
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    9. repec:dau:papers:123456789/6328 is not listed on IDEAS
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    Cited by:

    1. W. Dominika Wranik & Adam Muir & Min Hu, 2017. "Costs of productivity loss due to occupational cancer in Canada: estimation using claims data from Workers’ Compensation Boards," Health Economics Review, Springer, vol. 7(1), pages 1-11, December.
    2. Erika Wissinger & Ingolf Griebsch & Juliane Lungershausen & Talia Foster & Chris Pashos, 2014. "The Economic Burden of Head and Neck Cancer: A Systematic Literature Review," PharmacoEconomics, Springer, vol. 32(9), pages 865-882, September.

    More about this item

    Keywords

    Cost of illness; Respiratory cancer; Occupational health; Respiratory tract neoplasms; Asbestos;

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H55 - Public Economics - - National Government Expenditures and Related Policies - - - Social Security and Public Pensions
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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