Race/Ethnicity, Obesity, and the Risk of Being Verbally Bullied: a National Multilevel Study

J Racial Ethn Health Disparities. 2019 Apr;6(2):245-253. doi: 10.1007/s40615-018-0519-5. Epub 2018 Jul 30.

Abstract

Objective: To examine the effects of obese/overweight status and race/ethnicity on the risk for being verbally bullied among second grade children, and to investigate if the relationship between weight status and verbal bullying varies based on race/ethnicity.

Design: Data on second graders from the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (Children = 18,130; Schools = 2419) were analyzed. Hierarchical generalized logistic modeling was used to address the objectives.

Results: Independent of the child's sex, age, academic performance, family socioeconomic status, and school characteristics, obese/overweight children (relative to non-obese/overweight children) and Black children (relative to White children) were more likely to be verbally bullied. Hispanic and Asian children were less likely to be verbally bullied relative to White children. Hispanic obese/overweight children experienced less verbal bullying than White obese/overweight children.

Conclusions: This study documented disproportionate risks of being verbally bullied for obese/overweight US second graders. The risk of being verbally bullied was significantly greater for obese/overweight White children vs. obese/overweight Hispanic children.

Implications: Findings can inform the development of strategies to reduce verbal bullying of obese/overweight children in US elementary schools.

Keywords: Bullying; Childhood obesity; Race/ethnicity; Verbal bullying.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Asian / statistics & numerical data
  • Black or African American / statistics & numerical data
  • Bullying / statistics & numerical data*
  • Child
  • Crime Victims / statistics & numerical data*
  • Ethnicity / statistics & numerical data*
  • Female
  • Hispanic or Latino / statistics & numerical data
  • Humans
  • Logistic Models
  • Male
  • Multilevel Analysis
  • Pediatric Obesity / epidemiology*
  • Risk Factors
  • Students
  • White People / statistics & numerical data