Determinants for Bullying Victimization among 11–16-Year-Olds in 15 Low- and Middle-Income Countries: A Multi-Level Study
Abstract
:1. Introduction
2. Methods
2.1. Data
Characteristics | N = 33,502 (weighted data) | % Bullied (n = 6,383) | p-value |
---|---|---|---|
Age (years) | |||
11 | 346 | 24.6 | 0.153 |
12 | 2,945 | 20.2 | - |
13 | 7,426 | 20.2 | - |
14 | 8,415 | 19.7 | - |
15 | 7,976 | 17.0 | - |
16 | 6,394 | 18.6 | - |
Gender | <0.001 | ||
Male | 16,631 | 21.3 | - |
Female | 16,871 | 16.8 | - |
Truancy | <0.001 | ||
0 days | 22,346 | 15.3 | - |
1 or 2 days | 7,578 | 22.7 | - |
3 to 5 days | 2,115 | 34.6 | - |
6 to 9 days | 777 | 34.2 | - |
10 or more days | 686 | 35.2 | - |
Hunger | <0.001 | ||
Never | 16,141 | 13.9 | - |
Rarely | 7,562 | 20.8 | - |
Sometimes | 7,614 | 24.0 | - |
Most of the time | 1,321 | 32.4 | - |
Always | 863 | 36.0 | |
Country | <0.001 | ||
Argentina | 4,237 | 11.6 | - |
Ecuador (Quito) | 166 | 8.1 | - |
Egypt | 5,248 | 34.2 | - |
Ghana | 1,902 | 33.9 | - |
Jordan | 669 | 18.3 | - |
Macedonia | 237 | 3.6 | - |
Morocco | 2,730 | 10.3 | - |
Philippines | 8,659 | 21.2 | - |
St. Lucia | 16 | 14.5 | - |
Tanzania (Dar es Salaam) | 319 | 11.3 | - |
Thailand | 6,120 | 10.3 | - |
Trinidad | 188 | 9.0 | - |
Tunisia | 1,282 | 12.4 | - |
Uruguay | 202 | 8.1 | - |
Yemen | 1,527 | 21.5 | - |
2.2. Participants
2.3. Variable Selection (Dependent Variable)
Response items for bullying by type (weighted percentages) | ||||||||
---|---|---|---|---|---|---|---|---|
Country | Hit, kicked, pushed, shoved or locked indoors | Made fun of because of race or color | Made fun of because of religion | Made fun of with sexual jokes | Left out of activities or ignored | Made fun of because of how my face or body looks | Bullied in some other way | Design-based p-value |
Argentina | 11.6 | 15.1 | 1.0 | 17.2 | 3.8 | 23.0 | 28.4 | <0.0001 |
Ecuador (Quito) | 10.4 | 5.1 | 4.6 | 15.4 | 8.1 | 9.3 | 47.0 | - |
Egypt | 28.8 | 25.2 | 7.4 | 13.5 | 4.2 | 3.4 | 17.5 | - |
Ghana | 24.5 | 21.1 | 18.5 | 9.0 | 5.5 | 11.5 | 9.9 | - |
Jordan | 13.2 | 11.0 | 4.7 | 12.6 | 5.4 | 10.9 | 42.2 | - |
Macedonia | 12.0 | 8.7 | 4.0 | 25.2 | 8.2 | 20.6 | 21.4 | - |
Morocco | 15.9 | 16.3 | 24.5 | 6.1 | 0.5 | 11.3 | 25.4 | - |
Philippines | 10.7 | 9.2 | 4.1 | 21.1 | 7.7 | 13.4 | 33.7 | - |
St. Lucia | 24.0 | 8.6 | 6.6 | 8.8 | 6.4 | 19.5 | 26.1 | - |
Tanzania (Dar es Salaam) | 25.6 | 5.8 | 11.2 | 14.0 | 8.0 | 9.2 | 26.1 | - |
Thailand | 30.2 | 7.3 | 3.3 | 22.0 | 3.3 | 8.8 | 25.2 | - |
Trinidad | 19.7 | 9.9 | 3.5 | 10.2 | 5.0 | 14.9 | 36.8 | - |
Tunisia | 15.4 | 10.5 | 5.8 | 12.5 | 5.1 | 14.0 | 36.7 | - |
Uruguay | 5.7 | 4.0 | 1.0 | 21.4 | 5.6 | 33.0 | 29.3 | - |
Yemen | 16.9 | 25.6 | 14.9 | 21.8 | 3.4 | 1.7 | 15.7 | - |
2.4. Individual-Level Variables
2.5. Country-Level Variables
2.6. Random Effects
2.7. Data Analysis
3. Results
Country | GC (Year†) | * Pupil to teacher ratio (Year ‡) | * Intentional homicide rate per 100,000 (Year ‡) | GDP per capita (USD) |
---|---|---|---|---|
Argentina | 48.77 | 12.6 (2006) | 5.5 (2007) | 14 700 |
Ecuador (Quito) | 53.65 | 14.4 (2006) | 18.5 (2006) | 7 800 |
Egypt | 32.14 | 17.1 (2004) | 0.3 (2006) | 6 200 |
Ghana | 42.76 | 19.7 (2006) | 12.8 (2006) | 2 500 |
Jordan | 37.72 | 17.9 (2003) | 6.8 (2006) | 5 400 |
Macedonia | 44.2 | 14.7 (2005) | 5.2 (2006) | 9 700 |
Morocco | 40.88 | 18.7 (2004) | 1.1 (2006) | 4 800 |
Philippines | 44.04 | 32.3 (2006) | 7.6 (2006) | 3 500 |
St. Lucia | 42.58 | 17.0 (2006) | 19.0 (2006) | 11 200 |
Tanzania (Dar es Salaam) | 37.58 | 17.4 (1995) | 26.0 (2006) | 1 400 |
Thailand | 42.45 | 21.7 (2006) | 6.8 (2006) | 8 700 |
Trinidad | 40.27 | 14.0 (2007) | 13.8 (2006) | 21 200 |
Tunisia | 40.81 | 16.9 (2006) | 1.5 (2006) | 9 400 |
Uruguay | 46.24 | 15.4 (2006) | 6.0 (2006) | 13 700 |
Yemen | 37.69 | 24.6 (2003) | 3.2 (2006) | 2 700 |
Variable | Category | OR (99% CI) | p-value |
---|---|---|---|
Age (continuous) | - | 0.97 (0.94–1.00) | 0.025 |
Gender (ref: male) | Female | 0.73 (0.65–0.82) | <0.001 |
Went hungry (ref: never) | Rarely | 1.61 (1.39–1.86) | <0.001 |
Sometimes | 1.95 (1.71–2.22) | <0.001 | |
Most of the time | 2.40 (1.97–2.92) | <0.001 | |
Always | 2.93 (2.39–3.58) | <0.001 | |
Truancy (ref: never) | 1 or 2 days | 1.31 (1.22–1.41) | <0.001 |
3 to 5 days | 2.46 (2.20–2.75) | <0.001 | |
6 to 9 days | 2.20 (1.84–2.62) | <0.001 | |
10 or more days | 3.14 (2.60–3.79) | <0.001 |
Level | Variable | Category | Variance |
---|---|---|---|
Classroom | Intercept | - | 0.5665 |
Classroom | Gender (ref: male) | Female | 0.4019 |
Classroom | Went hungry (ref: never) | Rarely | 0.8373 |
Classroom | Sometimes | 0.5262 | |
Classroom | Most of the time | 0.7723 | |
Classroom | Always | 0.4419 | |
School | Intercept | - | 0.0693 |
Country | Intercept | - | 0.3419 |
4. Discussion
5. Conclusions
Acknowledgments
Conflicts of Interest
References
- Lila C. Fleming, and Kathryn H. Jacobsen. “Bullying among middle-school students in low and middle income countries.” Health Promotion International 25 (2010): 73–84. [Google Scholar] [CrossRef] [PubMed]
- Holan Liang, Alan J. Flisher, and Carl J. Lombard. “Bullying, violence, and risk behavior in South African school students.” Child Abuse & Neglect 31 (2007): 161–71. [Google Scholar]
- Dan Olweus. “Bullying at school. Basic facts and an effective intervention programme.” Promot & Education 1 (1994): 27–31, 48. [Google Scholar]
- Tonja R. Nansel, Mary Overpeck, Ramani S. Pilla, June W. Ruan, Bruce Simons-Morton, and Peter Scheidt. “Bullying behaviors among US youth: Prevalence and association with psychosocial adjustment.” Journal of the American Medical Association 285 (2001): 2094–2100. [Google Scholar] [CrossRef] [PubMed]
- Yulan Cheng, Ian M. Newman, Ming Qu, Lazarous Mbulo, Yan Chai, Yan Chen, and Duane F. Shell. “Being bullied and psychosocial adjustment among middle school students in China.” Journal of School Health 80 (2010): 193–99. [Google Scholar] [CrossRef] [PubMed]
- Rachel C. Vreeman, and Aaron E. Carroll. “A systematic review of school-based interventions to prevent bullying.” Archives of Pediatrics and Adolescent Medicine 161 (2007): 78–88. [Google Scholar] [CrossRef] [PubMed]
- Kaj Björkqvist, Karin Osterman, and Petra Berg. “Higher rates of victimization to physical abuse by adults found among victims of school bullying.” Psychological Reports 109 (2011): 167–68. [Google Scholar] [CrossRef] [PubMed]
- Howard Meltzer, Panos Vostanis, Tamsin Ford, Paul Bebbington, and Michael S. Dennis. “Victims of bullying in childhood and suicide attempts in adulthood.” European Psychiatry 26 (2011): 498–503. [Google Scholar] [CrossRef] [PubMed]
- Pernille Due, Juan Merlo, Yossi Harel-Fisch, Mogens T. Damsgaard, Bjørn E. Holstein, Jørn Hetland, Candace Currie, Saoirse N. Gabhainn, Margarida G. de Matos, and John Lynch. “Socioeconomic inequality in exposure to bullying during adolescence: A comparative, cross-sectional, multilevel study in 35 countries.” American Journal of Public Health 99 (2009): 907–14. [Google Scholar] [CrossRef] [PubMed]
- Pernille Due, Mogens T. Damsgaard, Rikke Lund, and Bjørn E. Holstein. “Is bullying equally harmful for rich and poor children?: A study of bullying and depression from age 15 to 27.” European Journal of Public Health 19 (2009): 464–69. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Etienne G. Krug, James A. Mercy, Linda L. Dahlberg, and Anthony B. Zwi. “The world report on violence and health.” The Lancet 360 (2002): 1083–88. [Google Scholar] [CrossRef]
- Margie Peden, Kayode Oyegbite, Joan Ozanne-Smith, Adnan A. Hyder, Christine Branche, AKM F. Rahman, Frederick Rivara, and Kidist Bartolomeos. “World report on child injury prevention.” Available online: http://www.who.int/violence_injury_prevention/child/injury/world_report/en/ (accessed on 3 December 2012).
- Rait Ram. “Population increase, economic growth, educational inequality, and income distribution: Some recent evidence.” Journal of Development Economics 14 (1984): 419–28. [Google Scholar] [CrossRef]
- CDC. “CDC Global School-based Student Health Survey (GSHS). ” Available online: http://www.cdc.gov/GSHS/ (accessed on 10 April 2012).
- Young S. Kim, W. T. Boyce, Yun-Joo Koh, and Bennett L. Leventhal. “Time trends, trajectories, and demographic predictors of bullying: A prospective study in Korean adolescents.” Journal of Adolescent Health 45 (2009): 360–67. [Google Scholar] [CrossRef] [PubMed]
- Billie Gastic. “School truancy and the disciplinary problems of bullying victims.” Educational Review 60 (2008): 391–404. [Google Scholar] [CrossRef]
- Kirsti Kumpulainen, Eila Räsänen, and Irmeli Henttonen. “Children involved in bullying: Psychological disturbance and the persistence of the involvement.” Child Abuse & Neglect 23 (1999): 1253–62. [Google Scholar]
- Michael Lynch. “Consequences of children’s exposure to community violence.” Clinical Child and Family Psychology Review 6 (2003): 265–74. [Google Scholar] [CrossRef] [PubMed]
- Corrado Gini. “Variabilità e mutabilità (Variability and Mutability). ” Reprinted in Memorie di Metodologica Statistica. E. Pizetti, and T. Salvemini, eds. Rome: Libreria Eredi Virgilio Veschi, 1955.
- Juliet N. Orem, Joses M. Kirigia, Robert Azairwe, Ibrahim Kasirye, and Oladapo Walker. “Impact of malaria morbidity on gross domestic product in Uganda.” International Archives of Medicine 5 (2012): 12. [Google Scholar] [CrossRef] [PubMed]
- Kristine Lykens, Karan P. Singh, Elewichi Ndukwe, and Sejong Bae. “Social, economic, and political factors in progress towards improving child survival in developing nations.” Journal of Health Care for the Poor and Underserved 20 (2009): 137–48. [Google Scholar] [CrossRef] [PubMed]
- Wendy M. Craig, Debra Pepler, and Rona Atlas. “Observations of bullying in the playground and in the classroom.” School Psychology International 21 (2000): 22–36. [Google Scholar] [CrossRef]
- Luiz A. C. Viana, Maria da Conceição N. Costa, Jairnilson S. Paim, and Ligia M. Vieira-da-Silva. “Social inequalities and the rise in violent deaths in Salvador, Bahia State, Brazil: 2000–2006.” Caderdnos de Saúde Pública 27 (2011): S298–S308. [Google Scholar] [CrossRef]
- Deborah Gorman-Smith, and Patrick Tolan. “The role of exposure to community violence and developmental problems among inner-city youth.” Devlopmental Psychopathology 10 (1998): 101–16. [Google Scholar] [CrossRef]
- World Bank World Development Indicators. “Data.” Available online: http://data.worldbank.org/data-catalog/world-development-indicators (accessed on 24 March 2012).
- André Berchtold. “Key elements in the statistical analysis of surveys.” International Journal of Public Health 52 (2007): 117–19. [Google Scholar] [CrossRef] [PubMed]
- Joop J. Hox. Applied Multilevel Analysis. Amsterdam: TT-Publikaties, 1994. [Google Scholar]
- Adrian Raftery. “Bayesian Model Selection in Social Research (with discussion).” In Sociological Methodology. Edited by Peter V. Marsden. Cambridge: Blackwells, 1995, pp. 111–63. [Google Scholar]
- R Development Core Team. R: A Language Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing, 2011. [Google Scholar]
- Wendy Craig, Yossi Harel-Fisch, Haya Fogel-Grinvald, Suzanne Dostaler, Jorn Hetland, Bruse Simons-Morton, Michal Molcho, Margarida G. de Mato, Mary Overpeck, Pernille Due, and William Pickett. “A cross-national profile of bullying and victimization among adolescents in 40 countries.” International Journal of Public Health 54 (2009): 216–24. [Google Scholar] [CrossRef] [PubMed]
- Konstantina Magklara, Petros Skapinakis, Tatiana Gkatsa, Stefanos Bellos, Ricardo Araya, Stylianos Stylianidis, and Venetsanos Mavreas. “Bullying behaviour in schools, socioeconomic position and psychiatric morbidity: A cross-sectional study in late adolescents in Greece.” Child and Adolescent Psychiatry and Mental Health 6 (2012): 8. [Google Scholar] [CrossRef] [PubMed]
- Jorge del Río-Pérez, Xavier Bringué, Charo Sádaba, and Diana González. “Cyberbullying: Un análisis comparativo en estudiantes de Argentina, Brasil, Chile, Colombia, México, Perú y Venezuela.” Available online: http://dspace.si.unav.es/dspace/handle/10171/17800 (accessed on 19 December 2012).
- Enrique Chaux, Andrés Molano, and Paola Podlesky. “Socio-economic, socio-political and socio-emotional variables explaining school bullying: A country-wide multilevel analysis.” Aggressive Behavior 35 (2009): 520–29. [Google Scholar] [CrossRef] [PubMed]
- Jaana Juvonen, Sandra Graham, and Mark A. Schuster. “Bullying among young adolescents: The strong, the weak, and the troubled.” Pediatrics 112 (2003): 1231–37. [Google Scholar] [CrossRef] [PubMed]
- Jayanta Bhattacharya, Janet Currie, and Steven Haider. “Poverty, food insecurity, and nutritional outcomes in children and adults.” Journal of Health Economics 23 (2004): 839–62. [Google Scholar] [CrossRef] [PubMed]
- Mona Khoury-Kassabri, Rami Benbenishty, Ron A. Astor, and Anat Zeira. “The contributions of community, family, and school variables to student victimization.” American Journal of Community Psychology 34 (2004): 187–204. [Google Scholar] [CrossRef] [PubMed]
- Catherine P. Bradshaw, Anne L. Sawyer, and Lindsey M. O’Brennan. “A social disorganization perspective on bullying-related attitudes and behaviors: The influence of school context.” American Journal of Community Psychology 43 (2009): 204–20. [Google Scholar] [CrossRef] [PubMed]
- Heba Alwan, Bharathi Viswanathan, Fred Paccaud, and Pascal Bovet. “Is accurate perception of body image associated with appropriate weight-control behavior among adolescents of the seychelles.” Journal of Obesity 2011 (2011): 817242. [Google Scholar] [CrossRef] [PubMed]
- Riittakerttu Kaltiala-Heino, and Sari Fröjd. “Correlation between bullying and clinical depression in adolescent patients.” Adolescent Health, Medicine and Therapeutics 2 (2011): 37–44. [Google Scholar] [CrossRef] [PubMed]
© 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Share and Cite
Wilson, M.L.; Dunlavy, A.C.; Berchtold, A. Determinants for Bullying Victimization among 11–16-Year-Olds in 15 Low- and Middle-Income Countries: A Multi-Level Study. Soc. Sci. 2013, 2, 208-220. https://doi.org/10.3390/socsci2040208
Wilson ML, Dunlavy AC, Berchtold A. Determinants for Bullying Victimization among 11–16-Year-Olds in 15 Low- and Middle-Income Countries: A Multi-Level Study. Social Sciences. 2013; 2(4):208-220. https://doi.org/10.3390/socsci2040208
Chicago/Turabian StyleWilson, Michael L., Andrea C. Dunlavy, and André Berchtold. 2013. "Determinants for Bullying Victimization among 11–16-Year-Olds in 15 Low- and Middle-Income Countries: A Multi-Level Study" Social Sciences 2, no. 4: 208-220. https://doi.org/10.3390/socsci2040208
APA StyleWilson, M. L., Dunlavy, A. C., & Berchtold, A. (2013). Determinants for Bullying Victimization among 11–16-Year-Olds in 15 Low- and Middle-Income Countries: A Multi-Level Study. Social Sciences, 2(4), 208-220. https://doi.org/10.3390/socsci2040208