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Including the Smoking Epidemic in Internationally Coherent Mortality Projections

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  • Fanny Janssen
  • Leo Wissen
  • Anton Kunst

Abstract

We present a new mortality projection methodology that distinguishes smoking- and non-smoking-related mortality and takes into account mortality trends of the opposite sex and in other countries. We evaluate to what extent future projections of life expectancy at birth (e 0 ) for the Netherlands up to 2040 are affected by the application of these components. All-cause mortality and non-smoking-related mortality for the years 1970–2006 are projected by the Lee-Carter and Li-Lee methodologies. Smoking-related mortality is projected according to assumptions on future smoking-attributable mortality. Projecting all-cause mortality in the Netherlands, using the Lee-Carter model, leads to high gains in e 0 (4.1 for males; 4.4 for females) and divergence between the sexes. Coherent projections, which include the mortality experience of the other 21 sex- and country-specific populations, result in much higher gains for males (6.4) and females (5.7), and convergence. The separate projection of smoking and non-smoking-related mortality produces a steady increase in e 0 for males (4.8) and a nonlinear trend for females, with lower gains in e 0 in the short run, resulting in temporary sex convergence. The latter effect is also found in coherent projections. Our methodology provides more robust projections, especially thanks to the distinction between smoking- and non-smoking-related mortality. Copyright Population Association of America 2013

Suggested Citation

  • Fanny Janssen & Leo Wissen & Anton Kunst, 2013. "Including the Smoking Epidemic in Internationally Coherent Mortality Projections," Demography, Springer;Population Association of America (PAA), vol. 50(4), pages 1341-1362, August.
    • Handle: RePEc:spr:demogr:v:50:y:2013:i:4:p:1341-1362
    DOI: 10.1007/s13524-012-0185-x
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    3. Tobias Vogt & Alyson van Raalte & Pavel Grigoriev & Mikko Myrskylä, 2017. "The German East-West Mortality Difference: Two Crossovers Driven by Smoking," Demography, Springer;Population Association of America (PAA), vol. 54(3), pages 1051-1071, June.
    4. Lenny Stoeldraijer & Coen van Duin & Leo van Wissen & Fanny Janssen, 2013. "Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(13), pages 323-354.
    5. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2022. "Thirty years on: A review of the Lee-Carter method for forecasting mortality," SocArXiv 8u34d, Center for Open Science.
    6. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2023. "Thirty years on: A review of the Lee–Carter method for forecasting mortality," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1033-1049.
    7. F. Peters & J. P. Mackenbach & W. J. Nusselder, 2016. "Does the Impact of the Tobacco Epidemic Explain Structural Changes in the Decline of Mortality?," European Journal of Population, Springer;European Association for Population Studies, vol. 32(5), pages 687-702, December.
    8. Bergeron-Boucher, Marie-Pier & Vázquez-Castillo, Paola & Missov, Trifon, 2022. "A modal age at death approach to forecasting mortality," SocArXiv 5zr2k, Center for Open Science.
    9. Jarner, Søren F. & Jallbjørn, Snorre, 2020. "Pitfalls and merits of cointegration-based mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 80-93.
    10. John Bongaarts, 2014. "Trends in Causes of Death in Low-Mortality Countries: Implications for Mortality Projections," Population and Development Review, The Population Council, Inc., vol. 40(2), pages 189-212, June.
    11. Ziebarth Nicolas R., 2018. "Biased Lung Cancer Risk Perceptions: Smokers are Misinformed," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 238(5), pages 395-421, September.
    12. Tobias C. Vogt & Alyson A. van Raalte & Pavel Grigoriev & Mikko Myrskylä, 2016. "German East-West mortality difference: two cross-overs driven by smoking," MPIDR Working Papers WP-2016-004, Max Planck Institute for Demographic Research, Rostock, Germany.
    13. Pieter van Baal & Frederik Peters & Johan Mackenbach & Wilma Nusselder, 2016. "Forecasting differences in life expectancy by education," Population Studies, Taylor & Francis Journals, vol. 70(2), pages 201-216, May.
    14. Christina Bohk-Ewald & Marcus Ebeling & Roland Rau, 2017. "Lifespan Disparity as an Additional Indicator for Evaluating Mortality Forecasts," Demography, Springer;Population Association of America (PAA), vol. 54(4), pages 1559-1577, August.
    15. Bergeron-Boucher, Marie-Pier & Kjærgaard, Søren, 2022. "Mortality forecasts by age and cause of death: How to forecast both dimensions?," SocArXiv d7hbp, Center for Open Science.
    16. Ricarda Duerst & Jonas Schöley & Christina Bohk-Ewald, 2023. "A validation workflow for mortality forecasting," MPIDR Working Papers WP-2023-020, Max Planck Institute for Demographic Research, Rostock, Germany.
    17. Nikoletta Vidra & Maarten J. Bijlsma & Sergi Trias-Llimós & Fanny Janssen, 2018. "Past trends in obesity-attributable mortality in eight European countries: an application of age–period–cohort analysis," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(6), pages 683-692, July.
    18. de Jong, Piet & Tickle, Leonie & Xu, Jianhui, 2020. "A more meaningful parameterization of the Lee–Carter model," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 1-8.

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