4.6 Article

Reaching Healthy People 2010 by 2013 A SimSmoke Simulation

Journal

AMERICAN JOURNAL OF PREVENTIVE MEDICINE
Volume 38, Issue 3, Pages S373-S381

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amepre.2009.11.018

Keywords

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Funding

  1. Office of Behavioral and Social Sciences Research (OBSSR) at the NIH
  2. Robert Wood Johnson Foundation (RWJF)
  3. Cancer Intervention and Surveillance Modeling Network (CISNET) of the Division of Cancer Control and Population Sciences (DCCPS), National Cancer Institute (NCI) [UO1-CA97450-02]

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Background: Healthy People (HP2010) set as a goal to reduce adult smoking prevalence to 12% by 2010. Purpose: This paper uses simulation modeling to examine the effects of three tobacco control policies and cessation treatment policies-alone and in conjunction-on population smoking prevalence. Methods: Building on previous versions of the SimSmoke model, the effects of a defined set of policies on quit attempts, treatment use, and treatment effectiveness are estimated as potential levers to reduce smoking prevalence. The analysis considers the effects of (1) price increases through cigarette tax increases, (2) smokefree indoor air laws, (3) mass media/educational policies, and (4) evidence-based and promising cessation treatment policies. Results: Evidence-based cessation treatment policies have the strongest effect, boosting the population quit rate by 78.8% in relative terms. Treatment policies are followed by cigarette tax increases (65.9%); smokefree air laws (31.8%); and mass media/educational policies (18.2%). Relative to the status quo in 2020, the model projects that smoking prevalence is reduced by 14.3% through a nationwide tax increase of $2.00, by 7.2% through smokefree laws, by 4.7% through mass media/educational policies, and by 16.5% through cessation treatment policies alone. Implementing all of the above policies at the same time would increase the quit rate by 296%, such that the HP2010 smoking prevalence goal of 12% is reached by 2013. Conclusions: The impact of a combination of policies led to some surprisingly positive possible futures in lowering smoking prevalence to 12% within just several years. Simulation models can be a useful tool for evaluating complex scenarios in which policies are implemented simultaneously, and for which there are limited data. (Am J Prev Med 2010;38(3S):S373-S381) (C) 2010 American Journal of Preventive Medicine

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