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Comprehension and Application of SimSmoke Model to Predict the Future Smoking Prevalence and Evaluate the Tobacco Control Policies
Journal of the Korean Society for Research on Nicotine and Tobacco 2010; 1(2): 73-84
Published online July 15, 2010
© 2010 The Korean Society for Research on Nicotine and Tobacco.

Susan Park, Young-Mee Kim, Sung-il Cho*

Graduate School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, Korea
 Abstract
SimSmoke is an analytic tool to evaluate the effects of tobacco control policies and to predict smoking prevalence and smoking-attributable deaths in the future. SimSmoke can reflect a wider range of tobacco control policies compared with other simulation models for public health research, and has been successfully applied to several Asian countries, including Korea. In this paper, we provide introduction to the Korean SimSmoke model to help understand the feature of this simulation model and show its application process. SimSmoke consists of three parts: population model, smoking model, and policy model. On the basis of population and smoking prevalence of a baseline year, it predicts future prevalence considering the change of smoking initiation rate and cessation rate according to tobacco control policies. SimSmoke was validated through comparison of smoking prevalence from the model with that from the survey data. To evaluate the effects of each tobacco control policy and comprehensive set of policies, the predicted smoking prevalence of status quo was compared with that of various strengthened policy scenarios. Our results showed that tax was the most effective past policy. If full strengthening of 6 non-tax policies accompanied a tax increase of 6,000￦ in 2008, the goal of Health Plan 2010, i.e., 30% male smoking prevalence, would have been attainable and would save lives about 45,000 from 2008 to 2020. If non-tax policies are fully strengthened with a tax increase of 500￦ per year from 2010 to 2020, the male smoking prevalence would decrease by about 25% in 2020. The Korean SimSmoke enbles us to evaluate the past tobacco control policies and provide evidence for the strengthened policies based on the predicted smoking prevalence and smoking-attributable deaths.
Keywords : Tobacco control policy; Simulation model; Framework Convention on Tobacco Control
References
  1. Levy DT, Nikolayev L, Mumford E, Compton C. The Healthy People 2010 smoking prevalence and tobacco control objectives: results from the SimSmoke tobacco control policy simulation model (United States). Cancer Causes Control 2005; 16: 359-71.
    Pubmed CrossRef
  2. Mendez D, Warner KE. Setting a challenging yet realistic smoking prevalence target for Healthy People 2020: learning from the California experience. Am J Public Health 2008; 98: 556-9.
    Pubmed KoreaMed CrossRef
  3. Levy DT, Chaloupka F, Gitchell J, Mendez D, Warner KE. The use of simulation models for the surveillance, justification and understanding of tobacco control policies. Health Care Manag Sci. 2002; 5: 113-20.
    Pubmed CrossRef
  4. Saffer H, Chaloupka F. The effect of tobacco advertising bans on tobacco consumption. J health Econ 2000; 19: 1117-37.
    CrossRef
  5. Mendez D, Warner KE, Courant PN. Has smoking cessation ceased? Expected trends in the prevalence of smoking in the United States. Am J Epidemiol 1998; 148: 249-58.
    Pubmed CrossRef
  6. Levy DT, Hyland A, Higbee C, Remer L, Compton C. The role of public policies in reducing smoking prevalence in California: Results from the California Tobacco Policy Simulation Model. Health Policy 2007; 82: 167-85.
    Pubmed KoreaMed CrossRef
  7. Levy DT, Ross H, Powell L, Bauer JE, Lee HR. The role of public policies in reducing smoking prevalence and deaths caused by smoking in Arizona: results from the Arizona tobacco policy simulation model. J Public Health Manag Pract 2007; 13: 59-67.
    Pubmed CrossRef
  8. Cho SI, Park S, Lee HJ, Kim YM. Prediction for smoking prevalence and smoking attributable death according to tobacco control policy. Seoul: Seoul National University; 2008. [cited 2010 Jun 15]
    Available from: http://library. mohw. go. kr/skyblueopen/users/bogun/PdfViewer. aspx?mastid=58221&pdf_url=MS003649. pdf
  9. Levy DT, Cho SI, Kim YM, Park S, Suh MK, Kam S. SimSmoke model evaluation of the effect of tobacco control policies in Korea: The unknown success story. Am J Public Health 2010; 100: 1267-73.
    Pubmed KoreaMed CrossRef
  10. U. S. Department of Health and Human Service. The health benefits of smoking cessation: A report of the surgeon general. Atlanta Georgia: US. DHHS, 1990. [cited 2010 Jun 14]
    Available from: http://profiles. nlm. nih. gov/NN/B/B/C/T/_/nnbbct. pdf
  11. Shultz JM, Novotny TE, Rice DP. Quantifying the disease impact of cigarette smoking with SAMMEC II software. Public Health Rep 1991; 106: 326-33.
    Pubmed KoreaMed
  12. Khang YH, Lynch JW, Jung-Choi K, Cho HJ. Explaining age-specific inequalities in mortality from all causes, cardiovascular disease and ischaemic heart disease among South Korean male public servants: relative and absolute perspectives. Heart 2008; 94: 75-82.
    Pubmed CrossRef
  13. Jee SH, Lee JK, Kim IS. Smoking-attributable mortality among Korean adults: 1981-2003. Korean J Epidemiol 2006; 28: 92-9.
  14. Wen CP, Tsai SP, Chen CJ, Cheng TY, Tsai MC, Levy DT. Smoking attributable mortality for Taiwan and its projection to 2020 under different smoking scenarios. Tob Control 2005; 14(Suppl 1): S76-80.
    Pubmed KoreaMed CrossRef
  15. Levy DT, Chaloupka F, Gitchell J. The effects of tobacco control policies on smoking rates: a tobacco control scorecard. J Public Health Manag Pract 2004; 10: 338-53.
    Pubmed CrossRef
  16. Levy DT, Friend KB. The effects of clean indoor air laws: what do we know and what do we need to know? Health Educ Res 2003; 18: 592-609.
    Pubmed CrossRef
  17. Levy DT, Friend K. A computer simulation model of mass media interventions directed at tobacco use. Prev Med 2001; 32: 284-94.
    Pubmed CrossRef
  18. Levy DT, Friend K, Holder H, Carmona M. Effect of policies directed at youth access to smoking: results from the SimSmoke computer simulation model. Tob Control 2001; 10: 108-16.
    Pubmed KoreaMed CrossRef
  19. Levy DT, Friend K. Examining the effects of tobacco treatment policies on smoking rates and smoking related deaths using the SimSmoke computer simulation model. Tob Control 2002; 11: 47-54.
    KoreaMed CrossRef
  20. Hughes JR. Reduced smoking: an introduction and review of the evidence. Addiction 2000; 95(Suppl 1): S3-7.
    Pubmed CrossRef
  21. Hymowitz N, Cummings KM, Hyland A, Lynn WR, Pechacek TF, Hartwell TD. Predictors of smoking cessation in a cohort of adult smokers followed for five years. Tob Control 1997; 6(Suppl 2): S57-62.
    Pubmed KoreaMed CrossRef
  22. Meadows D. System dynamics meets the press. System Dynamics Review 1989; 5: 68-80.
    CrossRef
  23. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. Am J Public Health 2006; 96: 452-8.
    Pubmed KoreaMed CrossRef