Effect of the Arizona tobacco control program on cigarette consumption and healthcare expenditures
Research highlights
► Arizona's tobacco control program reduced cigarette consumption and healthcare expenditures. ► In its first 9 years it prevented about 200 million packs of cigarettes from being smoked. ► In its first 9 years it saved about $2.3 billion in healthcare costs, 10 times what the program cost. ► This return on investment was less than the more aggressive California program.
Introduction
Large scale tobacco control programs reduce cigarette consumption (Institute of Medicine, 2007) and tobacco-induced heart disease (Fichtenberg & Glantz, 2000) and cancer (Barnoya and Glantz, 2004, Centers for Disease Control and Prevention, 2007a, Jemal et al., 2003). Rapidly increasing healthcare expenditures are a major problem in the United States and around the world. The California Tobacco Control Program was created in 1988 by voter initiative and implemented beginning in 1989 (Glantz & Balbach, 2000) and has been associated with significant reductions in smoking and direct healthcare expenditures, which, over the first 15 years of the program, totaled approximately 50 times what the program cost (Lightwood, Dinno, et al., 2008). Arizona voters established its tobacco control program in 1994, with implementation beginning in 1996 (Bialous and Glantz, 1999, Hendlin et al., 2008). There are substantial differences between the two programs. The California program focuses on adults, reinforces the nonsmoking norm, emphasizes policy change, and uses media focused on secondhand smoke and the manipulative behavior of the tobacco industry (Tobacco Control Section, 1998). The Arizona program concentrates on youth uptake of smoking and avoids public policy and commentary on the tobacco industry. This paper applies and extends our earlier California model (Lightwood, Dinno, et al., 2008) to Arizona to estimate the associations between per capita state tobacco control expenditures, cigarette consumption and healthcare expenditures in Arizona and compares the results to California.
Section snippets
Model
Classical time series regression techniques are not be appropriate for analysis of the relationship between aggregate tobacco control expenditures and healthcare costs because these classical techniques require that the parameters describing the underlying processes remain constant over time (ie, the processes are “stationary”). The underlying processes that determine state expenditures on tobacco control programs, smoking behavior, and healthcare costs change with time as does the tobacco
Cointegrating regressions (long run relationships) and ECMs
The data are integrated of order one, except for the proportion of the population that is elderly (A*, t), which may be integrated of order two. Regressions with mixed variables integrated of order one and two may be cointegrating, so Eq. (1) is an acceptable specification (Haldrup, 1997). Eqs. (1), (2) are cointegrating regressions with stationary residuals (Fig. 1). The explanatory value of the regressions is high (using R2 as a measure of fit) and all coefficients are highly significant, as
Discussion
These estimates for Arizona confirm earlier work for California (Lightwood, Dinno, et al. 2008) that large scale tobacco control programs are associated with substantial reductions in smoking and healthcare costs, despite the fact that implementation of the two programs has been quite different. Using a different state, the parameter estimates are very similar in the two analyses. The cointegrating regression coefficients for the effect of per capita cigarette consumption on per capita
Acknowledgments
This research was supported by NCI grant CA-61021. The funding agency played no role in the conduct of the research, preparation of the manuscript or decision to publish.
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