IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0121008.html
   My bibliography  Save this article

Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm

Author

Listed:
  • Eric D Vugrin
  • Brian L Rostron
  • Stephen J Verzi
  • Nancy S Brodsky
  • Theresa J Brown
  • Conrad J Choiniere
  • Blair N Coleman
  • Antonio Paredes
  • Benjamin J Apelberg

Abstract

Background: Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings: We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion: Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.

Suggested Citation

  • Eric D Vugrin & Brian L Rostron & Stephen J Verzi & Nancy S Brodsky & Theresa J Brown & Conrad J Choiniere & Blair N Coleman & Antonio Paredes & Benjamin J Apelberg, 2015. "Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-26, March.
  • Handle: RePEc:plo:pone00:0121008
    DOI: 10.1371/journal.pone.0121008
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0121008
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0121008&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0121008?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. Hendriek Boshuizen & Stefan Lhachimi & Pieter Baal & Rudolf Hoogenveen & Henriette Smit & Johan Mackenbach & Wilma Nusselder, 2012. "The DYNAMO-HIA Model: An Efficient Implementation of a Risk Factor/Chronic Disease Markov Model for Use in Health Impact Assessment (HIA)," Demography, Springer;Population Association of America (PAA), vol. 49(4), pages 1259-1283, November.
    2. King, B.A. & Dube, S.R. & Tynan, M.A., 2012. "Current tobacco use among adults in the United States: Findings from the National Adult Tobacco Survey," American Journal of Public Health, American Public Health Association, vol. 102(11), pages 93-100.
    3. Levy, D.T. & Cho, S.-I. & Kim, Y.-M. & Park, S. & Suh, M.-K. & Kam, S., 2010. "SimSmoke model evaluation of the effect of tobacco control policies in Korea: The unknown success story," American Journal of Public Health, American Public Health Association, vol. 100(7), pages 1267-1273.
    4. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    5. David Levy & Liz Maria de Almeida & Andre Szklo, 2012. "The Brazil SimSmoke Policy Simulation Model: The Effect of Strong Tobacco Control Policies on Smoking Prevalence and Smoking-Attributable Deaths in a Middle Income Nation," PLOS Medicine, Public Library of Science, vol. 9(11), pages 1-12, November.
    6. Pieter H M van Baal & Johan J Polder & G Ardine de Wit & Rudolf T Hoogenveen & Talitha L Feenstra & Hendriek C Boshuizen & Peter M Engelfriet & Werner B F Brouwer, 2008. "Lifetime Medical Costs of Obesity: Prevention No Cure for Increasing Health Expenditure," PLOS Medicine, Public Library of Science, vol. 5(2), pages 1-8, February.
    7. Mendez, D. & Warner, K.E., 2000. "Smoking prevalence in 2010: Why the healthy people goal is unattainable," American Journal of Public Health, American Public Health Association, vol. 90(3), pages 401-403.
    8. Mendez, D. & Warner, K.E., 2004. "Adult Cigarette Smoking Prevalence: Declining as Expected (Not as Desired)," American Journal of Public Health, American Public Health Association, vol. 94(2), pages 251-252.
    9. Levy, David T. & Bales, Sarah & Lam, Nguyen T. & Nikolayev, Leonid, 2006. "The role of public policies in reducing smoking and deaths caused by smoking in Vietnam: Results from the Vietnam tobacco policy simulation model," Social Science & Medicine, Elsevier, vol. 62(7), pages 1819-1830, April.
    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. Rosemary Avery & Donald Kenkel & Dean R. Lillard & Alan Mathios, 2007. "Private Profits and Public Health: Does Advertising of Smoking Cessation Products Encourage Smokers to Quit?," Journal of Political Economy, University of Chicago Press, vol. 115(3), pages 447-481.
    2. David T. Levy & Luz María Sánchez-Romero & Nargiz Travis & Zhe Yuan & Yameng Li & Sarah Skolnick & Jihyoun Jeon & Jamie Tam & Rafael Meza, 2021. "US Nicotine Vaping Product SimSmoke Simulation Model: The Effect of Vaping and Tobacco Control Policies on Smoking Prevalence and Smoking-Attributable Deaths," IJERPH, MDPI, vol. 18(9), pages 1-22, May.
    3. Ahmad, Sajjad & Billimek, John, 2007. "Limiting youth access to tobacco: Comparing the long-term health impacts of increasing cigarette excise taxes and raising the legal smoking age to 21 in the United States," Health Policy, Elsevier, vol. 80(3), pages 378-391, March.
    4. Lanza Queiroz, Bernardo & Lobo Alves Ferreira, Matheus, 2021. "The evolution of labor force participation and the expected length of retirement in Brazil," The Journal of the Economics of Ageing, Elsevier, vol. 18(C).
    5. Tareq Hussein, 2022. "Indoor Exposure and Regional Inhaled Deposited Dose Rate during Smoking and Incense Stick Burning—The Jordanian Case as an Example for Eastern Mediterranean Conditions," IJERPH, MDPI, vol. 20(1), pages 1-20, December.
    6. Rob Hyndman & Heather Booth & Farah Yasmeen, 2013. "Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 261-283, February.
    7. Marko Korhonen & Suvi Kangasrääsiö & Rauli Svento, 2017. "Climate change and mortality: Evidence from 23 developed countries between 1960 and 2010," Proceedings of International Academic Conferences 5107635, International Institute of Social and Economic Sciences.
    8. Hári, Norbert & De Waegenaere, Anja & Melenberg, Bertrand & Nijman, Theo E., 2008. "Estimating the term structure of mortality," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 492-504, April.
    9. Jonas Hirz & Uwe Schmock & Pavel V. Shevchenko, 2017. "Actuarial Applications and Estimation of Extended CreditRisk+," Risks, MDPI, vol. 5(2), pages 1-29, March.
    10. Niels Haldrup & Carsten P. T. Rosenskjold, 2019. "A Parametric Factor Model of the Term Structure of Mortality," Econometrics, MDPI, vol. 7(1), pages 1-22, March.
    11. Hári, Norbert & De Waegenaere, Anja & Melenberg, Bertrand & Nijman, Theo E., 2008. "Longevity risk in portfolios of pension annuities," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 505-519, April.
    12. Jakub Bijak & Viet Dung Cao & Eric Silverman & Jason Hilton, 2013. "Reforging the Wedding Ring," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(27), pages 729-766.
    13. Gong, Guan & Webb, Anthony, 2010. "Evaluating the Advanced Life Deferred Annuity -- An annuity people might actually buy," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 210-221, February.
    14. Fang, Lei & Härdle, Wolfgang Karl, 2015. "Stochastic population analysis: A functional data approach," SFB 649 Discussion Papers 2015-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Carter, Lawrence R., 1998. "Combining probabilistic and subjective assessments of error to provide realistic appraisals of demographic forecast uncertainty: Alho's approach," International Journal of Forecasting, Elsevier, vol. 14(4), pages 523-526, December.
    16. Geert Zittersteyn & Jennifer Alonso-García, 2021. "Common Factor Cause-Specific Mortality Model," Risks, MDPI, vol. 9(12), pages 1-30, December.
    17. Groneck, Max & Ludwig, Alexander & Zimper, Alexander, 2016. "A life-cycle model with ambiguous survival beliefs," Journal of Economic Theory, Elsevier, vol. 162(C), pages 137-180.
    18. Dorota Toczydlowska & Gareth W. Peters & Man Chung Fung & Pavel V. Shevchenko, 2017. "Stochastic Period and Cohort Effect State-Space Mortality Models Incorporating Demographic Factors via Probabilistic Robust Principal Components," Risks, MDPI, vol. 5(3), pages 1-77, July.
    19. Kogure Atsuyuki & Fushimi Takahiro, 2018. "A Bayesian Pricing of Longevity Derivatives with Interest Rate Risks," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 12(1), pages 1-30, January.
    20. Bucciol, Alessandro & Cavalli, Laura & Fedotenkov, Igor & Pertile, Paolo & Polin, Veronica & Sartor, Nicola & Sommacal, Alessandro, 2017. "A large scale OLG model for the analysis of the redistributive effects of policy reforms," European Journal of Political Economy, Elsevier, vol. 48(C), pages 104-127.

    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:plo:pone00:0121008. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.