Modeling the effect of disseminating brief intervention for smoking cessation at medical facilities in Japan: a simulation study

Cancer Causes Control. 2012 Jun;23(6):929-39. doi: 10.1007/s10552-012-9964-3. Epub 2012 Apr 25.

Abstract

Purpose: The Japanese male smoking prevalence is still high. Underlying causes are the low quit attempt rate (QAR) and lack of pharmacotherapy (PT) use. Though health checkups are widely and systematically performed in Japan, this setting has not been utilized for intervention to smokers. We aimed to estimate the population effect of disseminating brief intervention (BI) at health checkup facilities combined with encouraging PT utilization.

Methods: The annual population quit rate (PQR) was modeled as a product of three components: the QAR, utilization of PT, and effectiveness of PT. A policy to disseminate effective BI at health checkup facilities was then incorporated into the PQR model as means to increase the QAR and/or PT utilization. Japanese male smokers aged 40-74 years were the target population, and the baseline year was set at 2005. The PQR and the number of smokers who successfully quit were compared with the baseline to evaluate the BI policy.

Results: The BI policy was estimated to increase the PQR from 4.3 to 5.7 % (rate ratio: 1.34) in a scenario where 75 % of smokers having an annual health checkup received BI and 60 % of BI-induced quit attempts were supported by PT, resulting in 177,000 new successful quitters on an annual basis and 3,000 avoidable cancer deaths in 10 years. Comparisons of different scenarios revealed that increasing QAR and encouraging PT were both essential to maximize the effect of BI policy.

Conclusion: The dissemination of BI at health checkup facilities encouraging PT utilization is an effective tobacco control policy in Japan.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Health Facilities / statistics & numerical data
  • Health Promotion / methods
  • Humans
  • Japan / epidemiology
  • Male
  • Middle Aged
  • Models, Statistical*
  • Prevalence
  • Smoking / adverse effects
  • Smoking / epidemiology*
  • Smoking Cessation / methods*
  • Smoking Cessation / statistics & numerical data