Literature DB >> 11387530

Effect of policies directed at youth access to smoking: results from the SimSmoke computer simulation model.

D T Levy1, K Friend, H Holder, M Carmona.   

Abstract

OBJECTIVES: To develop a simulation model to predict the effects of youth access policies on retail compliance, smoking rates, and smoking attributable deaths.
METHODS: A model of youth access policies is developed based on empirical research and a theory of perceived risk. The model incorporates substitution into other sources as retail sales are restricted, and is used to project the number of smokers and smoking related deaths. Various policies to limit youth access to cigarettes are evaluated, and we explore how efficient policies may be developed.
RESULTS: The model predicts that a well designed and comprehensive policy that includes sufficient compliance checks, penalties, and community involvement has the potential to reduce the number of young smokers. Because smoking related deaths occur later in life, the effects on health are largely delayed.
CONCLUSIONS: A well designed youth access policy has the ability to affect youth smoking rates in the short term, and will lead to savings in lives in future years. The ability of retail oriented policies to reduce youth smoking, however, is limited. Other tobacco control policies, including those directed at non-retail sources of cigarettes, are also needed.

Entities:  

Mesh:

Year:  2001        PMID: 11387530      PMCID: PMC1747539          DOI: 10.1136/tc.10.2.108

Source DB:  PubMed          Journal:  Tob Control        ISSN: 0964-4563            Impact factor:   7.552


  18 in total

1.  Expert opinions on optimal enforcement of minimum purchase age laws for tobacco.

Authors:  D T Levy; F Chaloupka; S Slater
Journal:  J Public Health Manag Pract       Date:  2000-05

2.  A simulation model of tobacco youth access policies.

Authors:  D T Levy; K B Friend
Journal:  J Health Polit Policy Law       Date:  2000-12       Impact factor: 2.265

3.  A simulation of the effects of youth initiation policies on overall cigarette use.

Authors:  D T Levy; K M Cummings; A Hyland
Journal:  Am J Public Health       Date:  2000-08       Impact factor: 9.308

4.  Increasing taxes as a strategy to reduce cigarette use and deaths: results of a simulation model.

Authors:  D T Levy; K M Cummings; A Hyland
Journal:  Prev Med       Date:  2000-09       Impact factor: 4.018

5.  Predictors of quitting smoking: the NHANES I followup experience.

Authors:  W P McWhorter; G M Boyd; M E Mattson
Journal:  J Clin Epidemiol       Date:  1990       Impact factor: 6.437

6.  Quantifying the disease impact of cigarette smoking with SAMMEC II software.

Authors:  J M Shultz; T E Novotny; D P Rice
Journal:  Public Health Rep       Date:  1991 May-Jun       Impact factor: 2.792

7.  Active enforcement of cigarette control laws in the prevention of cigarette sales to minors.

Authors:  L A Jason; P Y Ji; M D Anes; S H Birkhead
Journal:  JAMA       Date:  1991-12-11       Impact factor: 56.272

8.  How adolescents get their cigarettes: implications for policies on access and price.

Authors:  S Emery; E A Gilpin; M M White; J P Pierce
Journal:  J Natl Cancer Inst       Date:  1999-01-20       Impact factor: 13.506

9.  The relationship between tobacco access and use among adolescents: a four community study.

Authors:  D G Altman; A Y Wheelis; M McFarlane; H Lee; S P Fortmann
Journal:  Soc Sci Med       Date:  1999-03       Impact factor: 4.634

Review 10.  A systematic review of interventions for preventing tobacco sales to minors.

Authors:  L F Stead; T Lancaster
Journal:  Tob Control       Date:  2000-06       Impact factor: 7.552

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  23 in total

1.  The use of simulation models for the surveillance, justification and understanding of tobacco control policies.

Authors:  David T Levy; Frank Chaloupka; Joseph Gitchell; David Mendez; Kenneth E Warner
Journal:  Health Care Manag Sci       Date:  2002-04

2.  The ID effect on youth access to cigarettes.

Authors:  A H Levinson; S Hendershott; T E Byers
Journal:  Tob Control       Date:  2002-12       Impact factor: 7.552

3.  Youth tobacco access: adult attitudes, awareness, and perceived self-efficacy in two Arizona counties.

Authors:  Jason T Siegel; Eusebio M Alvaro
Journal:  J Community Health       Date:  2003-12

4.  SimSmoke model evaluation of the effect of tobacco control policies in Korea: the unknown success story.

Authors:  David T Levy; Sung-il Cho; Young-Mee Kim; Susan Park; Mee-Kyung Suh; Sin Kam
Journal:  Am J Public Health       Date:  2010-05-13       Impact factor: 9.308

5.  Tobacco Policies in Louisiana: Recommendations for Future Tobacco Control Investment from SimSmoke, a Policy Simulation Model.

Authors:  David Levy; Cristin Fergus; Lindsey Rudov; Iben McCormick-Ricket; Thomas Carton
Journal:  Prev Sci       Date:  2016-02

6.  Simulation modeling and tobacco control: creating more robust public health policies.

Authors:  David T Levy; Joseph E Bauer; Hye-Ryeon Lee
Journal:  Am J Public Health       Date:  2006-01-31       Impact factor: 9.308

Review 7.  Environmental and societal influences acting on cardiovascular risk factors and disease at a population level: a review.

Authors:  Clara Kayei Chow; Karen Lock; Koon Teo; S V Subramanian; Martin McKee; Salim Yusuf
Journal:  Int J Epidemiol       Date:  2009-03-04       Impact factor: 7.196

8.  Rating the effectiveness of local tobacco policies for reducing youth smoking.

Authors:  Sharon Lipperman-Kreda; Karen B Friend; Joel W Grube
Journal:  J Prim Prev       Date:  2014-04

9.  Estimating the Potential Impact of Tobacco Control Policies on Adverse Maternal and Child Health Outcomes in the United States Using the SimSmoke Tobacco Control Policy Simulation Model.

Authors:  David Levy; Mary Katherine Mohlman; Yian Zhang
Journal:  Nicotine Tob Res       Date:  2015-09-18       Impact factor: 4.244

10.  The Minnesota SimSmoke Tobacco Control Policy Model of Smokeless Tobacco and Cigarette Use.

Authors:  David T Levy; Zhe Yuan; Yameng Li; Ann W St Claire; Barbara A Schillo
Journal:  Am J Prev Med       Date:  2019-10       Impact factor: 5.043

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