Emma Beard1, Robert West2, Susan Michie3, Jamie Brown4. 1. Research Department of Clinical, Educational and Health Psychology, University College London, London WC1E 7HB, UK Cancer Research UK Health Behaviour Research Centre, Department of Epidemiology and Public Health, University College London, London, UK e.beard@ucl.ac.uk. 2. Cancer Research UK Health Behaviour Research Centre, Department of Epidemiology and Public Health, University College London, London, UK. 3. Research Department of Clinical, Educational and Health Psychology, University College London, London WC1E 7HB, UK. 4. Research Department of Clinical, Educational and Health Psychology, University College London, London WC1E 7HB, UK Cancer Research UK Health Behaviour Research Centre, Department of Epidemiology and Public Health, University College London, London, UK.
Abstract
OBJECTIVES: To estimate how far changes in the prevalence of electronic cigarette (e-cigarette) use in England have been associated with changes in quit success, quit attempts, and use of licensed medication and behavioural support in quit attempts. DESIGN: Time series analysis of population trends. PARTICIPANTS: Participants came from the Smoking Toolkit Study, which involves repeated, cross sectional household surveys of individuals aged 16 years and older in England. Data were aggregated on about 1200 smokers quarterly between 2006 and 2015. Monitoring data were also used from the national behavioural support programme; during the study, 8 029 012 quit dates were set with this programme. SETTING: England. MAIN OUTCOME MEASURES: Prevalence of e-cigarette use in current smokers and during a quit attempt were used to predict quit success. Prevalence of e-cigarette use in current smokers was used to predict rate of quit attempts. Percentage of quit attempts involving e-cigarette use was also used to predict quit attempts involving use of prescription treatments, nicotine replacement therapy (NRT) on prescription and bought over the counter, and use of behavioural support. Analyses involved adjustment for a range of potential confounders. RESULTS: The success rate of quit attempts increased by 0.098% (95% confidence interval 0.064 to 0.132; P<0.001) and 0.058% (0.038 to 0.078; P<0.001) for every 1% increase in the prevalence of e-cigarette use by smokers and e-cigarette use during a recent quit attempt, respectively. There was no clear evidence for an association between e-cigarette use and rate of quit attempts (β 0.025; 95% confidence interval -0.035 to 0.085; P=0.41), use of NRT bought over the counter (β 0.006; -0.088 to 0.077; P=0.89), use of prescription treatment (β -0.070; -0.152 to 0.013; P=0.10), or use of behavioural support (β -0.013; -0.102 to 0.077; P=0.78). A negative association was found between e-cigarette use during a recent quit attempt and use of NRT obtained on prescription (β -0.098; -0.189 to -0.007; P=0.04). CONCLUSION: Changes in prevalence of e-cigarette use in England have been positively associated with the success rates of quit attempts. No clear association has been found between e-cigarette use and the rate of quit attempts or the use of other quitting aids, except for NRT obtained on prescription, where the association has been negative.Study registration The analysis plan was preregistered (https://osf.io/fbgj2/). Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
OBJECTIVES: To estimate how far changes in the prevalence of electronic cigarette (e-cigarette) use in England have been associated with changes in quit success, quit attempts, and use of licensed medication and behavioural support in quit attempts. DESIGN: Time series analysis of population trends. PARTICIPANTS: Participants came from the Smoking Toolkit Study, which involves repeated, cross sectional household surveys of individuals aged 16 years and older in England. Data were aggregated on about 1200 smokers quarterly between 2006 and 2015. Monitoring data were also used from the national behavioural support programme; during the study, 8 029 012 quit dates were set with this programme. SETTING: England. MAIN OUTCOME MEASURES: Prevalence of e-cigarette use in current smokers and during a quit attempt were used to predict quit success. Prevalence of e-cigarette use in current smokers was used to predict rate of quit attempts. Percentage of quit attempts involving e-cigarette use was also used to predict quit attempts involving use of prescription treatments, nicotine replacement therapy (NRT) on prescription and bought over the counter, and use of behavioural support. Analyses involved adjustment for a range of potential confounders. RESULTS: The success rate of quit attempts increased by 0.098% (95% confidence interval 0.064 to 0.132; P<0.001) and 0.058% (0.038 to 0.078; P<0.001) for every 1% increase in the prevalence of e-cigarette use by smokers and e-cigarette use during a recent quit attempt, respectively. There was no clear evidence for an association between e-cigarette use and rate of quit attempts (β 0.025; 95% confidence interval -0.035 to 0.085; P=0.41), use of NRT bought over the counter (β 0.006; -0.088 to 0.077; P=0.89), use of prescription treatment (β -0.070; -0.152 to 0.013; P=0.10), or use of behavioural support (β -0.013; -0.102 to 0.077; P=0.78). A negative association was found between e-cigarette use during a recent quit attempt and use of NRT obtained on prescription (β -0.098; -0.189 to -0.007; P=0.04). CONCLUSION: Changes in prevalence of e-cigarette use in England have been positively associated with the success rates of quit attempts. No clear association has been found between e-cigarette use and the rate of quit attempts or the use of other quitting aids, except for NRT obtained on prescription, where the association has been negative.Study registration The analysis plan was preregistered (https://osf.io/fbgj2/). Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Authors: Ann McNeill; Pete Driezen; Sara C Hitchman; K Michael Cummings; Geoffrey T Fong; Ron Borland Journal: Addiction Date: 2019-08-15 Impact factor: 6.526
Authors: Jenny E Ozga-Hess; Nicholas J Felicione; Stuart G Ferguson; Geri Dino; Daniel Elswick; Catherine Whitworth; Nicholas Turiano; Melissa D Blank Journal: Addict Behav Date: 2019-08-21 Impact factor: 3.913