Using student and school factors to differentiate adolescent current smokers from experimental smokers in Canada: a multilevel analysis

Prev Med. 2013 Aug;57(2):113-9. doi: 10.1016/j.ypmed.2013.04.022. Epub 2013 May 10.

Abstract

Objective: In order to understand the factors that differentiate adolescents who have tried smoking from those who have become established smokers, this study examined which student- and school-level factors differentiated current smokers from experimental smokers among a nationally representative sample of Canadian secondary school students.

Method: Student-level secondary data from the 2008-2009 Canadian Youth Smoking Survey was linked with school-level data from the 2006 Census and one built environment characteristic, and examined using multilevel logistic regression analyses.

Results: The current smoking rates varied (P<0.001) across schools. The number of tobacco retailers surrounding the schools was associated with current smoking when adjusting for student characteristics. Additionally, students were more likely to be current smokers if they were: male, in higher grades, believed that smoking can help when they are bored, reported low school connectedness, used marijuana, had a sibling or close friend who smoked, and had no smoking bans at home.

Conclusions: These study findings suggest that school anti-smoking strategies need to target males, increase students' attachment to their school, address tobacco-related beliefs, and include interventions targeting smoking siblings and friends. The government should consider zoning restrictions to limit sales of tobacco products near schools.

Keywords: Adolescence; Canada; Current smoking; Factors; Multilevel logistic regression.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adolescent Behavior* / psychology
  • Alcohol Drinking / epidemiology
  • Canada / epidemiology
  • Female
  • Health Knowledge, Attitudes, Practice
  • Humans
  • Interpersonal Relations*
  • Logistic Models
  • Male
  • Risk Factors
  • Schools / statistics & numerical data
  • Sex Distribution
  • Smoking / epidemiology*
  • Social Environment
  • Students / statistics & numerical data*