Socioeconomic inequality in exposure to bullying during adolescence: a comparative, cross-sectional, multilevel study in 35 countries

Pernille Due, Juan Merlo, Yossi Harel-Fisch, Mogens Trab Damsgaard, Bjørn E Holstein, Jørn Hetland, Candace Currie, Saoirse Nic Gabhainn, Margarida Gaspar de Matos, John Lynch

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

OBJECTIVES: We examined the socioeconomic distribution of adolescent exposure to bullying internationally and documented the contribution of the macroeconomic environment. METHODS: We used an international survey of 162,305 students aged 11, 13, and 15 years from nationally representative samples of 5998 schools in 35 countries in Europe and North America for the 2001-2002 school year. The survey used standardized measures of exposure to bullying and socioeconomic affluence. RESULTS: Adolescents from families of low affluence reported higher prevalence of being victims of bullying (odds ratio [OR] = 1.13; 95% confidence interval [CI] = 1.10, 1.16). International differences in prevalence of exposure to bullying were not associated with the economic level of the country (as measured by gross national income) or the school, but wide disparities in affluence at a school and large economic inequality (as measured by the Gini coefficient) at the national level were associated with an increased prevalence of exposure to bullying. CONCLUSIONS: There is socioeconomic inequality in exposure to bullying among adolescents, leaving children of greater socioeconomic disadvantage at higher risk of victimization. Adolescents who attend schools and live in countries where socioeconomic differences are larger are at higher risk of being bullied.
Original languageEnglish
JournalAmerican Journal of Public Health
Volume99
Issue number5
Pages (from-to)907-14
Number of pages7
ISSN0090-0036
DOIs
Publication statusPublished - 1. May 2009

Keywords

  • Adolescent
  • Aggression
  • Child
  • Crime Victims
  • Cross-Sectional Studies
  • Female
  • Health Status Disparities
  • Humans
  • Income
  • Logistic Models
  • Male
  • Odds Ratio
  • Poverty
  • Prejudice
  • Regression Analysis
  • Schools
  • Socioeconomic Factors
  • Students

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