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      Socioeconomic Inequality in Exposure to Bullying During Adolescence: A Comparative, Cross-Sectional, Multilevel Study in 35 Countries

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          Abstract

          We examined the socioeconomic distribution of adolescent exposure to bullying internationally and documented the contribution of the macroeconomic environment. 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. 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. 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.

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          Bullying Behaviors Among US Youth

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            Prevalence estimation of school bullying with the Olweus Bully/Victim Questionnaire

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              A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena.

              In social epidemiology, it is easy to compute and interpret measures of variation in multilevel linear regression, but technical difficulties exist in the case of logistic regression. The aim of this study was to present measures of variation appropriate for the logistic case in a didactic rather than a mathematical way. Data were used from the health survey conducted in 2000 in the county of Scania, Sweden, that comprised 10 723 persons aged 18-80 years living in 60 areas. Conducting multilevel logistic regression different techniques were applied to investigate whether the individual propensity to consult private physicians was statistically dependent on the area of residence (that is, intraclass correlation (ICC), median odds ratio (MOR)), the 80% interval odds ratio (IOR-80), and the sorting out index). The MOR provided more interpretable information than the ICC on the relevance of the residential area for understanding the individual propensity of consulting private physicians. The MOR showed that the unexplained heterogeneity between areas was of greater relevance than the individual variables considered in the analysis (age, sex, and education) for understanding the individual propensity of visiting private physicians. Residing in a high education area increased the probability of visiting a private physician. However, the IOR showed that the unexplained variability between areas did not allow to clearly distinguishing low from high propensity areas with the area educational level. The sorting out index was equal to 82%. Measures of variation in logistic regression should be promoted in social epidemiological and public health research as efficient means of quantifying the importance of the context of residence for understanding disparities in health and health related behaviour.
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                Author and article information

                Journal
                American Journal of Public Health
                Am J Public Health
                American Public Health Association
                0090-0036
                1541-0048
                May 2009
                May 2009
                : 99
                : 5
                : 907-914
                Article
                10.2105/AJPH.2008.139303
                2667858
                19299676
                61e9a0e1-c6f9-47a7-bd2d-d1e64657e2b6
                © 2009
                History

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