摘要：Objectives. We used a simulation model to analyze whether the Healthy People 2010 goal of reducing smoking prevalence from the current 19.8% rate to 12% by 2010 could be accomplished by increasing quit attempts, increasing the use of treatments, or increasing the effectiveness of treatment. Methods. We expanded on previous versions of the tobacco control simulation model SimSmoke to assess the effects of an increase in quit attempts, treatment use, and treatment effectiveness to reduce smoking prevalence. In the model, we considered increases in each of these parameters individually and in combination. Results. Individually, 100% increases in quit attempts, treatment use, and treatment effectiveness reduced the projected 2020 prevalence to 13.9%, 16.7%, and 15.9%, respectively. With a combined 100% increase in all components, the goal of a 12% adult smoking prevalence could be reached by 2012. Conclusions. If we are to come close to reaching Healthy People 2010 goals in the foreseeable future, we must not only induce quit attempts but also increase treatment use and effectiveness. Simulation models provide a useful tool for evaluating the potential to reach public health targets. Since the 1964 Surgeon General's Report first warned of the hazards of smoking tobacco, 1 enormous strides have been made in reducing adult smoking prevalence. At the peak of US tobacco use in 1965, the adult smoking prevalence was 42.4% 2 ; now, only 19.8% of adults smoke. 3 Nevertheless, an estimated 44.4 million American adults continue to smoke, incurring 443 000 premature deaths, with $97 billion in productivity losses and $96 billion in health care expenditures. 4 In recognition of the problem, Healthy People 2010 set an ambitious goal of reducing smoking prevalence to 12% by 2010. 5 With that goal now almost certainly unattainable, 6 new approaches need to be explored. Smoking prevalence can be reduced in 3 ways: (1) by preventing nonsmokers from initiating smoking, (2) by inducing current smokers to quit, and (3) by preventing those who have already quit from relapsing back to smoking. Because prevention strategies apply largely to persons in the 14- to 20-year-old age group, 7 only a small percentage of the population is affected at any point in time and many years must pass before the strategies lead to large reductions in adult rates. 8 By contrast, quitting strategies can be targeted at smokers of all ages and can lead to a more immediate drop in adult prevalence. Still, encouraging smokers to quit will only go so far in reducing prevalence unless something is done in tandem to help smokers maintain their abstinence. Each year, fewer than 45% of smokers make a serious quit attempt and quit for even 24 hours. 9 More than three fourths of smokers making a quit attempt each year do not use efficacious treatment, 10 and only 3% to 5% of those untreated smokers remain abstinent for 12 months. 11 , 12 Quit success increases 2- to 3-fold when proven treatments are used. 13 Those at the lowest socioeconomic levels are the most vulnerable to smoking but the least successful at quitting when making a quit attempt. 9 , 14 – 18 Thus, much is to be gained by improving treatment effectiveness along with increasing the number of smokers who attempt to quit and who use evidence-based treatment. Simulation models are useful for understanding and predicting how changes in specific inputs (e.g., treatment use) lead to changes in outputs (e.g., quit rates) over time in complex social systems. 19 , 20 Modeling helps to reveal relationships by organizing the channels of influence and by making assumptions about the relevant relationships more explicit. This process generally proves more robust than relying on intuition alone and is thereby useful for evaluating hypothetical future scenarios. Numerous models of smoking behaviors have been developed to show the effect of tobacco control policies on smoking prevalence and health outcomes. 8 , 21 – 28 These models use information from studies of past policies or smoking behaviors to predict future smoking rates. We were motivated by the need to better understand the changes that would be necessary to meet prevalence goals. Because changes in smoking initiation will have minimal impact on smoking prevalence within the next 15 years, we focused on the cessation process. We carried out a series of simulations that focused on the quitting process and were intended to examine hypothetical effects of changes in quitting behaviors on smoking prevalence. Specifically, we generated a model that predicted smoking prevalence by using 3 strategies: (1) by increasing the percentage of current smokers making a quit attempt, (2) by increasing the percentage of current smokers who use an evidence-based treatment, and (3) by improving treatment effectiveness. We explored the magnitude of the various strategies necessary to reach the Healthy People 2010 goal of a 12% smoking prevalence and the time frame in which it could be achieved.
