OBJECTIVES: To compare tobacco control policies independently and as a package through a simulation model to project smoking prevalence and associated future premature mortality in Argentina beginning in 2001. METHODS: A simulation model of tobacco control policies known as SimSmoke was modified using data for Argentina on population, fertility and mortality, smoking prevalence, and tobacco control policies in effect between 2001 and 2004. We used the Argentina Tobacco Policy Simulation model (ATPSM) to consider the effect on smoking prevalence of changes in taxes and prices, clean air laws, media campaigns, cessation programs, and youth access policies on smoking initiation and cessation rates. Smoking prevalence and relative risks of smoking were used to estimate smoking-attributable mortality. The ATPSM was used to project smoking prevalence and smoking-attributable deaths during the period 2001-2034. RESULTS: The largest reductions in smoking prevalence and premature mortality were predicted for a comprehensive tobacco control policy package, but relative reductions of as much as 30% were also predicted for large tax increases. Adding a media campaign along with programs to publicize and enforce clean air laws, advertising bans, and youth access laws would further reduce smoking rates by up to 45% by the year 2034, and would save almost 16 000 lives per year. CONCLUSIONS: Tobacco control policies can substantially reduce smoking rates, which can save many lives. Without such policies, deaths from smoking, and associated medical costs, will increase. The ATPSM is expected to provide guidance in filling the most important information gaps pertinent to both modeling and policy-making in Argentina, e.g., the lack of data on initiation and cessation rates, and the need for studies on the impact of policies. Similar models might be developed for other Latin American countries.
OBJECTIVES: To compare tobacco control policies independently and as a package through a simulation model to project smoking prevalence and associated future premature mortality in Argentina beginning in 2001. METHODS: A simulation model of tobacco control policies known as SimSmoke was modified using data for Argentina on population, fertility and mortality, smoking prevalence, and tobacco control policies in effect between 2001 and 2004. We used the Argentina Tobacco Policy Simulation model (ATPSM) to consider the effect on smoking prevalence of changes in taxes and prices, clean air laws, media campaigns, cessation programs, and youth access policies on smoking initiation and cessation rates. Smoking prevalence and relative risks of smoking were used to estimate smoking-attributable mortality. The ATPSM was used to project smoking prevalence and smoking-attributable deaths during the period 2001-2034. RESULTS: The largest reductions in smoking prevalence and premature mortality were predicted for a comprehensive tobacco control policy package, but relative reductions of as much as 30% were also predicted for large tax increases. Adding a media campaign along with programs to publicize and enforce clean air laws, advertising bans, and youth access laws would further reduce smoking rates by up to 45% by the year 2034, and would save almost 16 000 lives per year. CONCLUSIONS:Tobacco control policies can substantially reduce smoking rates, which can save many lives. Without such policies, deaths from smoking, and associated medical costs, will increase. The ATPSM is expected to provide guidance in filling the most important information gaps pertinent to both modeling and policy-making in Argentina, e.g., the lack of data on initiation and cessation rates, and the need for studies on the impact of policies. Similar models might be developed for other Latin American countries.
Authors: Nancy L Fleischer; Ana V Diez Roux; Marcio Alazraqui; Hugo Spinelli; Paula M Lantz Journal: Nicotine Tob Res Date: 2011-05-26 Impact factor: 4.244
Authors: 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 Journal: PLoS One Date: 2015-03-27 Impact factor: 3.240