IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v27y2007i2p467-482.html
   My bibliography  Save this article

Health‐Based Population Forecasting: Effects of Smoking on Mortality and Fertility

Author

Listed:
  • Igor Akushevich
  • Julia S. Kravchenko
  • Kenneth G. Manton

Abstract

A microsimulation model, allowing one to forecast short‐ and long‐term population changes conditional on the prevalence of a risk factor in a population, is presented. In this model, population changes result from the aggregation of changes in individual event histories, which, in turn, result from mortality and infertility rates recalculated in accordance with their known relative risks in population groups exposed to a risk factor. Smoking, being the most widespread and influential preventable public health risk factor, is chosen to demonstrate the abilities of the model to forecast the population effects of different hypothetical smoking prevalences. The demographic and population health effects on 20‐, 50‐, and 100‐year projections with the current, hypothetically doubled, and hypothetically halved the current smoking prevalence are analyzed in detail. The model predicts an increase in life expectancy (0.99 year for males and 0.64 years for females), and an increase in population size (2.2–7.5% dependent on the age group) if smoking prevalence is reduced by half. Sensitivity analyses of all findings are performed. The generalization of the model to account for multiple risk factors (e.g., the simultaneous effects of alcohol consumption, obesity, and smoking) and effects on medical expenditures are discussed.

Suggested Citation

  • Igor Akushevich & Julia S. Kravchenko & Kenneth G. Manton, 2007. "Health‐Based Population Forecasting: Effects of Smoking on Mortality and Fertility," Risk Analysis, John Wiley & Sons, vol. 27(2), pages 467-482, April.
    • Handle: RePEc:wly:riskan:v:27:y:2007:i:2:p:467-482
    DOI: 10.1111/j.1539-6924.2007.00898.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2007.00898.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1539-6924.2007.00898.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Tim Miller, 2001. "Increasing longevity and medicare expenditures," Demography, Springer;Population Association of America (PAA), vol. 38(2), pages 215-226, May.
    2. I. Akushevich & A. Kulminski & K. G. Manton, 2005. "Life Tables with Covariates: Dynamic Model for Nonlinear Analysis of Longitudinal Data," Mathematical Population Studies, Taylor & Francis Journals, vol. 12(2), pages 51-80.
    3. Bhattacharya Jayanta & Cutler David M. & Goldman Dana P. & Hurd Michael D. & Joyce Geoffrey F. & Lakdawalla Darius N. & Panis Constantijn W. A. & Shang Baoping, 2004. "Disability Forecasts and Future Medicare Costs," Forum for Health Economics & Policy, De Gruyter, vol. 7(1), pages 1-22, January.
    4. Anatoli Yashin & Ivan Iachine & Alexander Begun, 2000. "Mortality modeling: A review," Mathematical Population Studies, Taylor & Francis Journals, vol. 8(4), pages 305-332.
    5. Manton, Kenneth G. & Stallard, Eric & Singer, Burt, 1992. "Projecting the future size and health status of the US elderly population," International Journal of Forecasting, Elsevier, vol. 8(3), pages 433-458, November.
    6. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    7. Shi, Leiyu & Macinko, James & Starfield, Barbara & Politzer, Robert & Xu, Jiahong, 2005. "Primary care, race, and mortality in US states," Social Science & Medicine, Elsevier, vol. 61(1), pages 65-75, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hui Zheng, 2014. "Aging in the Context of Cohort Evolution and Mortality Selection," Demography, Springer;Population Association of America (PAA), vol. 51(4), pages 1295-1317, August.
    2. M S Finkelstein, 2008. "Reliability modelling for biological ageing," Journal of Risk and Reliability, , vol. 222(1), pages 1-6, March.
    3. Ting Li & James Anderson, 2013. "Shaping human mortality patterns through intrinsic and extrinsic vitality processes," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(12), pages 341-372.
    4. MARK BEBBINGTON & CHIN-DIEW LAI & RIcARDAS ZITIKIS, 2011. "Modelling Deceleration in Senescent Mortality," Mathematical Population Studies, Taylor & Francis Journals, vol. 18(1), pages 18-37.
    5. Cha, Ji Hwan & Finkelstein, Maxim, 2014. "Some notes on unobserved parameters (frailties) in reliability modeling," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 99-103.
    6. Maxim S. Finkelstein, 2011. "On ordered subpopulations and population mortality at advanced ages," MPIDR Working Papers WP-2011-022, Max Planck Institute for Demographic Research, Rostock, Germany.
    7. Li, Ting & Anderson, James J., 2009. "The vitality model: A way to understand population survival and demographic heterogeneity," Theoretical Population Biology, Elsevier, vol. 76(2), pages 118-131.
    8. Anatoly I. Yashin & Igor Akushevich & Konstantin G. Arbeev & Alexander Kulminski & Svetlana Ukraintseva, 2011. "Joint Analysis of Health Histories, Physiological State, and Survival," Mathematical Population Studies, Taylor & Francis Journals, vol. 18(4), pages 207-233, October.
    9. Finkelstein, Maxim, 2012. "On ordered subpopulations and population mortality at advanced ages," Theoretical Population Biology, Elsevier, vol. 81(4), pages 292-299.
    10. Hartemink, Nienke & Missov, Trifon I. & Caswell, Hal, 2017. "Stochasticity, heterogeneity, and variance in longevity in human populations," Theoretical Population Biology, Elsevier, vol. 114(C), pages 107-116.
    11. Maxim S. Finkelstein, 2005. "Aging: damage accumulation versus increasing mortality rate," MPIDR Working Papers WP-2005-018, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Maxim S. Finkelstein, 2003. "Modeling failure (mortality) rate with a change point," MPIDR Working Papers WP-2003-041, Max Planck Institute for Demographic Research, Rostock, Germany.
    13. Hal Caswell, 2014. "A matrix approach to the statistics of longevity in heterogeneous frailty models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(19), pages 553-592.
    14. Kenneth Manton & Igor Akushevich & Alexander Kulminski, 2008. "Human Mortality at Extreme Ages: Data from the NLTCS and Linked Medicare Records," Mathematical Population Studies, Taylor & Francis Journals, vol. 15(3), pages 137-159.
    15. Maxim Finkelstein & James W. Vaupel, 2006. "The relative tail of longevity and the mean remaining lifetime," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 14(7), pages 111-138.
    16. James W. Vaupel & Trifon Missov, 2014. "Unobserved population heterogeneity," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(22), pages 659-686.
    17. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    18. Bagdonavicius, Vilijandas & Nikulin, Mikhail, 2000. "On goodness-of-fit for the linear transformation and frailty models," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 177-188, April.
    19. Yahia Salhi & Pierre-Emmanuel Thérond, 2016. "Age-Specific Adjustment of Graduated Mortality," Working Papers hal-01391285, HAL.
    20. Feehan, Dennis & Wrigley-Field, Elizabeth, 2020. "How do populations aggregate?," SocArXiv 2fkw3, Center for Open Science.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:27:y:2007:i:2:p:467-482. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.