Smoking reduction trajectories and their association with smoking cessation: a secondary analysis of longitudinal...

Tobacco smoking remains the leading cause of preventable death worldwide. Smoking reduction can be recommended to people unmotivated to quit, but evidence on trajectories of reduction and associated outcomes is mixed.

In a secondary analysis of five randomised, placebo-controlled trials of nicotine replacement therapy, we used latent class analysis and elastic net regression to determine latent smoking trajectories using cigarettes-per-day (CPD) across 26 weeks. Participants were adults who smoked daily without intention to quit in the next month. We used predictive modelling and receiver operator characteristic area under-the-curve (AUC) to assess smoking cessation after 1 year.

Participants (n=2066) smoked a mean 27.26±9.74 CPD at baseline. Three distinct smoking patterns emerged: Class 1 (n=186, 10%) achieved the greatest reduction in CPD (2-week mean 57% reduction) with subsequent reduction; Class 2 (n=803, 45%) saw a 2-week mean 50% reduction and remained at that level and Class 3 (n=794, 45%) reduced by a 2-week mean of 22% and returned to near-baseline CPD. Older, male participants with lower anxiety and lower nicotine dependence were more likely to be in Class 1. Abstinence rates at 1 year (~50 weeks after reduction) were 37.6% for Class 1, 4.2% for Class 2 and 2.3% for Class 3.Using latent class assignment as a predictor improved prediction of smoking cessation at 1 year follow-up over prediction using baseline characteristics by 14.4% (AUC=0.776±0.010, p=0.002). Those who reduced their CPD minimally were nearly 90% less likely to achieve cessation than those who reduced by over 50% (ORs: Class 2=0.111±0.013, Class 3=0.070±0.005).

Findings suggest adults who are unmotivated to quit at baseline but reduce their smoking by more than half are most likely to achieve smoking cessation. A lack of early reduction success could indicate that greater support is needed to help people to quit.