OBJECTIVES: This paper examined the stability over time of daily cigarette consumption of continuing smokers and explored factors that might account for the patterns of change in consumption using a latent growth curve (LGC) analytic approach. METHODS: Data come from the first 5 waves of the International Tobacco Control Four-Country Survey, conducted in Canada, the United States, the United Kingdom, and Australia where a cohort of over 2,000 smokers from each country were recruited and followed up annually with replenishment. RESULTS: Raw data revealed that continuing smokers showed a marked steep decline in cigarettes per day during the first 2 waves followed by a gentler linear decline in consumption over the remaining waves of the study period. This pattern of change in cigarette consumption was best modelled using a piecewise linear LGC model. Baseline consumption level was highest in Australia and lowest in the United Kingdom, although the rate of decline was similar across the 4 countries. Being older than 55 years and having made at least 1 quit attempt were related to greater rate of decline in consumption. CONCLUSIONS: Continuing smokers who are unwilling or unable to quit smoking can and do attempt to reduce their daily cigarette consumption over time. Factors such as making a quit attempt even if unsuccessful and experiencing smoking bans at work and at homes can contribute to reduced smoking among this group, which suggests that interventions focusing in on these factors, along with providing cessation help, may greatly improve their chances of quitting smoking altogether.
OBJECTIVES: This paper examined the stability over time of daily cigarette consumption of continuing smokers and explored factors that might account for the patterns of change in consumption using a latent growth curve (LGC) analytic approach. METHODS: Data come from the first 5 waves of the International Tobacco Control Four-Country Survey, conducted in Canada, the United States, the United Kingdom, and Australia where a cohort of over 2,000 smokers from each country were recruited and followed up annually with replenishment. RESULTS: Raw data revealed that continuing smokers showed a marked steep decline in cigarettes per day during the first 2 waves followed by a gentler linear decline in consumption over the remaining waves of the study period. This pattern of change in cigarette consumption was best modelled using a piecewise linear LGC model. Baseline consumption level was highest in Australia and lowest in the United Kingdom, although the rate of decline was similar across the 4 countries. Being older than 55 years and having made at least 1 quit attempt were related to greater rate of decline in consumption. CONCLUSIONS: Continuing smokers who are unwilling or unable to quit smoking can and do attempt to reduce their daily cigarette consumption over time. Factors such as making a quit attempt even if unsuccessful and experiencing smoking bans at work and at homes can contribute to reduced smoking among this group, which suggests that interventions focusing in on these factors, along with providing cessation help, may greatly improve their chances of quitting smoking altogether.
Authors: David P Hopkins; Sima Razi; Kimberly D Leeks; Geetika Priya Kalra; Sajal K Chattopadhyay; Robin E Soler Journal: Am J Prev Med Date: 2010-02 Impact factor: 5.043
Authors: M E Thompson; G T Fong; D Hammond; C Boudreau; P Driezen; A Hyland; R Borland; K M Cummings; G B Hastings; M Siahpush; A M Mackintosh; F L Laux Journal: Tob Control Date: 2006-06 Impact factor: 7.552
Authors: G T Fong; K M Cummings; R Borland; G Hastings; A Hyland; G A Giovino; D Hammond; M E Thompson Journal: Tob Control Date: 2006-06 Impact factor: 7.552
Authors: Natalie Sachs-Ericsson; Norman B Schmidt; Michael J Zvolensky; Melissa Mitchell; Nicole Collins; Dan G Blazer Journal: Nicotine Tob Res Date: 2009-03-18 Impact factor: 4.244
Authors: Saul Shiffman; Joe G Gitchell; Kenneth E Warner; John Slade; Jack E Henningfield; John M Pinney Journal: Nicotine Tob Res Date: 2002 Impact factor: 4.244
Authors: Judith S Brook; Elizabeth Rubenstone; Chenshu Zhang; Stephen J Finch; David W Brook Journal: Addict Behav Date: 2013-03-21 Impact factor: 3.913
Authors: Amanda R Mathew; Elizabeth Garrett-Mayer; Bryan W Heckman; Amy E Wahlquist; Matthew J Carpenter Journal: Nicotine Tob Res Date: 2017-12-13 Impact factor: 4.244
Authors: Anthony Cunningham; Johan Sommarström; Ajit S Sisodiya; Graham Errington; Krishna Prasad Journal: BMC Public Health Date: 2014-04-12 Impact factor: 3.295
Authors: Anna K M Blackwell; Ilse Lee; Michelle Scollo; Melanie Wakefield; Marcus R Munafò; Theresa M Marteau Journal: Addiction Date: 2019-08-30 Impact factor: 6.526