Modelling how to achieve 5% adult smoking prevalence by 2025: a regional approach
Ailsa Rutter 1  
,  
 
 
More details
Hide details
1
Fresh, Smokefree North East, United Kingdom
2
University College London, United Kingdom
Publish date: 2018-03-01
 
Tob. Induc. Dis. 2018;16(Suppl 1):A28
KEYWORDS
WCTOH
 
TOPICS
Download abstract book (PDF)

ABSTRACT
Background:
The North East of England (population 2.6 million) has a notable track record in tobacco control, and local government organisations have a vision to "Make Smoking History", with all 12 localities agreeing in 2014 to work towards 5% adult smoking by 2025. The target seems ambitious but a comprehensive sub-national programme is in place to achieve it. With a baseline smoking prevalence of 18.7% in 2015, work was undertaken in 2017 to model current trends in smoking prevalence, uptake and quitting in the North East, and identify key targets and policies for further improvements and to assess how realistic the goal is.

Methods:
Data from the Smoking Toolkit Study (www.smokinginengland.info - annual sample size national of >20,000) and the UK's Annual Population Survey (annual national samnple size 300,000) were used to model trends in key parameters (cigarette smoking prevalence; ever-smoking prevalence in young people; quit attempt prevalence; quit success rate; overall quit rate) and make forecasts under a range of different assumptions.

Results:
Smoking prevalence has declined in the North East slightly faster than the national average and this appears to be because of higher quit success rates. Increasing quit attempt rate to 45% per year, maintaining a quit success rate at 20%, and reducing uptake to 0.3% per year could put the North East on a path to 5% adult smoking prevalence within 10 years. These are all realistic targets but will require the implementation of a package of policies and a sustained commitment to investment.

Conclusions:
Modelling has shown that a bold ambition of all but eliminating smoking by 2025 can be achieved in an English region without unrealistic assumptions about the changes that need to be made in uptake, quit attempts and quit success rates. This modelling work has galvanised further action especially within the health system.

eISSN:1617-9625