Abstract

Background

Characterizing smoking patterns over time is essential for evaluating the impact of tobacco control interventions and predicting smoking-related mortality. Beginning with a 1920s birth cohort, smoking histories (i.e., estimates of smoking initiation and cessation, and prevalence of current and former smokers) were generated.

Data

The Ontario sample (n = 238,411) of the 2003 to 2013 cycles of the Canadian Community Health Survey, which is conducted biennially, was used to obtain cross-sectional information on current smoking behaviour.

Methods

Age at smoking initiation and age at smoking cessation were used to construct smoking histories for each respondent, up to the survey date. An age-period-cohort model was generated and used to examine survival differences by smoking status. Using the model, and adjusting for survival differences in smoking status, the prevalence of current, former and never smokers was estimated in cohorts from 1920 to 1985. Smoking initiation, cessation and intensity were then estimated for age-specific distributions of each birth cohort. These rates were projected forward through to 2041. Smoking patterns by highest level of education were generated using education-stratified models.

Results

Smoking histories show clear trends over time by sex, cohort and age. If current patterns persist, smoking prevalence is projected to decline to single digits (below 10%) by 2023 for women and 2040 for men.

Interpretation

Birth-cohort-specific smoking histories can be generated using cross-sectional health surveys. These cohort histories can describe smoking patterns over time and into the future. In turn, these histories can be used in micro-simulation models to evaluate historic or planned tobacco control interventions, and to project smoking prevalence.

Keywords

models; statistical prevalence; smoking, epidemiology and trends; smoking cessation; statistics and numerical data; education

DOI: https://www.doi.org/10.25318/82-003-x202001100002-eng

Findings

In most countries, including Canada, smoking remains the leading cause of mortality that is attributable to health behaviour. To monitor progress in reducing smoking prevalence, studies have relied on observing smoking prevalence trends using either general population health surveys, such as the Canadian Community Health Survey (CCHS), or tobacco-focused surveys, such as the Canadian Tobacco, Alcohol and Drugs Survey. Two properties of smoking history are important in assessing the effect of anti-smoking strategies: life-course smoking exposure and smoking initiation and cessation information. Life-course smoking exposure is important because smoking-attributable chronic diseases have a long latency. Initiation and cessation information are essential to assess the two main strategies for reducing smoking prevalence (i.e., strategies to reduce smoking initiation or increase smoking cessation). [Full article]

Authors

Douglas G. Manuel (dmanuel@ohri.ca), and Carol Bennett are with the Ottawa Hospital Research Institute and ICES in Ottawa, Ontario. Andrew S. Wilton is also with ICES. Douglas G. Manuel is also with Statistics Canada, and the Department of Family Medicine and the School of Epidemiology, Public Health and Preventative Medicine at the University of Ottawa. Adrian Rohit Dass, and Audrey Laporte are with Institute of Health Policy, Management and Evaluation, at the Dalla Lana School of Public Health, University of Toronto, and the Canadian Centre for Health Economics. Theodore R. Holford is with the Department of Biostatistics at the Yale School of Public Health in New Haven, Connecticut.

 

What is already known on this subject?

  • Holford et al. (2014) developed a smoking history generator model that uses birth-cohort-specific smoking histories to model smoking patters. Using United States survey data, the age-period-cohort model predicted historic smoking prevalence that closely approximated observed smoking prevalence.
  • The smoking history generator model has been used to project future smoking prevalence, incidence and cessation. Using microsimulation models, the model has also been used to assess the effectiveness of smoking prevention strategies.

What does this study add?

  • Smoking patterns based on birth-cohort-specific histories can be generated using the Canadian Community Health Survey and other surveys that contain questions on timing of smoking initiation and cessation.
  • This study found a close approximation between modelled and observed smoking prevalence in Canada. The replication of the same modelling approach in two countries (Canada and the United States) suggests that the approach is robust.
  • To the authors’ knowledge, this the first study to estimate historic smoking initiation and cessation by sociodemographic groups and to project future smoking prevalence. The projections suggest that, in Canada, a large, persistent difference in smoking prevalence will remain through to 2041 between people with a postsecondary education and those with less than a high school diploma.
  • There is merit to replicating this study in other countries with similar population health surveys, given the robustness of the approach and the importance of projecting smoking prevention.

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