Gradients in risk for youth injury associated with multiple-risk behaviours: a study of 11,329 Canadian adolescents

Soc Sci Med. 2002 Sep;55(6):1055-68. doi: 10.1016/s0277-9536(01)00224-6.

Abstract

This study used the Canadian version of the World Health Organization-Health Behaviour in School-Aged Children (WHO-HBSC) Survey to examine the role of multiple risk behaviours and other social factors in the etiology of medically attended youth injury. 11,329 Canadians aged 11-15 years completed the 1997-1998 WHO-HBSC, of which 4152 (36.7%) reported at least one medically attended injury. Multiple logistic regression analyses failed to identify an expected association between lower socio-economic status and risk for injury. Strong gradients in risk for injury were observed according to the numbers of multiple risk behaviours reported. Youth reporting the largest number (7) of risk behaviours experienced injury rates that were 4.11 times (95% CI: 3.04-5.55) higher than those reporting no high risk behaviours (adjusted odds ratios for 0-7 reported behaviours: 1.00, 1.13, 1.49, 1.79, 2.28, 2.54, 2.62, 4.11; p(trend) < 0.001). Similar gradients in risk were observed within subgroups of young people defined by grade, sex, and socio-economic level, and within restricted analyses of various injury types (recreational, sports, home, school injuries). The gradients were especially pronounced for severe injury types and among those reporting multiple injuries. The analyses suggest that multiple risk behaviours may play an important role in the social etiology of youth injury, but these same analyses provide little evidence for a socio-economic risk gradient. The findings in turn have implications for preventive interventions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adolescent Behavior / classification
  • Canada / epidemiology
  • Child
  • Child Behavior / classification
  • Cluster Analysis
  • Female
  • Health Behavior*
  • Health Status Indicators*
  • Humans
  • Life Style
  • Logistic Models
  • Male
  • Odds Ratio
  • Risk Assessment / statistics & numerical data*
  • Risk-Taking*
  • Socioeconomic Factors
  • Wounds and Injuries / epidemiology*
  • Wounds and Injuries / etiology