BACKGROUND: Following the landmark lawsuit and settlement with the tobacco industry, Minnesota pursued the implementation of stricter tobacco control policies, including tax increases, mass media campaigns, smokefree air laws, and cessation treatment policies. Modeling is used to examine policy effects on smoking prevalence and smoking-attributable deaths. PURPOSE: To estimate the effect of tobacco control policies in Minnesota on smoking prevalence and smoking-attributable deaths using the SimSmoke simulation model. METHODS: Minnesota data starting in 1993 are applied to SimSmoke, a simulation model used to examine the effect of tobacco control policies over time on smoking initiation and cessation. Upon validating the model against smoking prevalence, SimSmoke is used to distinguish the effect of policies implemented since 1993 on smoking prevalence. Using standard attribution methods, SimSmoke also estimates deaths averted as a result of the policies. RESULTS: SimSmoke predicts smoking prevalence accurately between 1993 and 2011. Since 1993, a relative reduction in smoking rates of 29% by 2011 and of 41% by 2041 can be attributed to tobacco control policies, mainly tax increases, smokefree air laws, media campaigns, and cessation treatment programs. Moreover, 48,000 smoking-attributable deaths will be averted by 2041. CONCLUSIONS: Minnesota SimSmoke demonstrates that tobacco control policies, especially taxes, have substantially reduced smoking prevalence and smoking-attributable deaths. Taxes, smokefree air laws, mass media, cessation treatment policies, and youth-access enforcement contributed to the decline in prevalence and deaths averted, with the strongest component being taxes. With stronger policies, for example, increasing cigarette taxes to $4.00 per pack, Minnesota's smoking rate could be reduced by another 13%, and 7200 deaths could be averted by 2041.
BACKGROUND: Following the landmark lawsuit and settlement with the tobacco industry, Minnesota pursued the implementation of stricter tobacco control policies, including tax increases, mass media campaigns, smokefree air laws, and cessation treatment policies. Modeling is used to examine policy effects on smoking prevalence and smoking-attributable deaths. PURPOSE: To estimate the effect of tobacco control policies in Minnesota on smoking prevalence and smoking-attributable deaths using the SimSmoke simulation model. METHODS: Minnesota data starting in 1993 are applied to SimSmoke, a simulation model used to examine the effect of tobacco control policies over time on smoking initiation and cessation. Upon validating the model against smoking prevalence, SimSmoke is used to distinguish the effect of policies implemented since 1993 on smoking prevalence. Using standard attribution methods, SimSmoke also estimates deaths averted as a result of the policies. RESULTS: SimSmoke predicts smoking prevalence accurately between 1993 and 2011. Since 1993, a relative reduction in smoking rates of 29% by 2011 and of 41% by 2041 can be attributed to tobacco control policies, mainly tax increases, smokefree air laws, media campaigns, and cessation treatment programs. Moreover, 48,000 smoking-attributable deaths will be averted by 2041. CONCLUSIONS: Minnesota SimSmoke demonstrates that tobacco control policies, especially taxes, have substantially reduced smoking prevalence and smoking-attributable deaths. Taxes, smokefree air laws, mass media, cessation treatment policies, and youth-access enforcement contributed to the decline in prevalence and deaths averted, with the strongest component being taxes. With stronger policies, for example, increasing cigarette taxes to $4.00 per pack, Minnesota's smoking rate could be reduced by another 13%, and 7200 deaths could be averted by 2041.
Authors: D P Hopkins; P A Briss; C J Ricard; C G Husten; V G Carande-Kulis; J E Fielding; M O Alao; J W McKenna; D J Sharp; J R Harris; T A Woollery; K W Harris Journal: Am J Prev Med Date: 2001-02 Impact factor: 5.043
Authors: Lawrence C An; Barbara A Schillo; Annette M Kavanaugh; Randi B Lachter; Michael G Luxenberg; Ann H Wendling; Anne M Joseph Journal: Tob Control Date: 2006-08 Impact factor: 7.552
Authors: Galina Ya Maslennikova; Rafael G Oganov; Sergey A Boytsov; Hana Ross; An-Tsun Huang; Aimee Near; Alexey Kotov; Irina Berezhnova; David T Levy Journal: Tob Control Date: 2013-07-12 Impact factor: 7.552
Authors: David T Levy; Eric N Lindblom; Nancy L Fleischer; James Thrasher; Mary Kate Mohlman; Yian Zhang; Karin Monshouwer; Gera E Nagelhout Journal: Tob Regul Sci Date: 2015-04
Authors: Steve Sussman; David Levy; Kristen Hassmiller Lich; Crystal W Cené; Mimi M Kim; Louise A Rohrbach; Frank J Chaloupka Journal: Tob Induc Dis Date: 2013-01-22 Impact factor: 2.600