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Wednesday, April 26 • 10:30am - 12:00pm
An Examination of the Predictors of Weight Bias in College Students

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Weight bias is stigmatization and prejudice based on weight and body size and thus perpetuates discrimination against individuals with overweight or obesity. This prejudice can also facilitate the development of an internal stigma within individuals with overweight or obesity creating a stressful internal environment. Specific negative outcomes of experiencing weight bias include increased risk of cardiovascular disease, depression, anxiety, disordered eating, negative body image, weight gain, and overall decreased quality of life. The prevalence of weight bias in the US remains high and presents a systematic problem within society that is causing widening health disparities, disconnection with health providers, misunderstandings of eating disorders and sociocultural discrimination. For examples, research demonstrates that individuals with overweight and obesity face unfair treatment in both healthcare and employment settings. Given the high prevalence of weight bias and the numerous consequences, understanding factors related to the development of weight bias are essential in order to create interventions to combat this trend. The purpose of this study is to examine factors associated with having high levels of weight bias. More than 200 UNC-Asheville students completed a questionnaire on explicit weight bias measured using the Anti-fat Attitudes Test. In addition, these students completed the Implicit Attitudes Test for Weight, a computer game measuring intrinsic weight bias. Data were also gathered on demographic information, health behaviors, history of depression or eating disorders, body image, and personal/family history with weight maintenance. Finally, students were asked to list their beliefs on why individuals get fat. Data coding and analysis is currently underway. Descriptive statistics will be used to determine prevalence of implicit and explicit weight bias in this sample of students. Pearson correlations and multiple linear regression analysis will be conducted to examine correlates and predictors of weight bias.

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Wednesday April 26, 2017 10:30am - 12:00pm
Concourse - Wilma Sherrill Center

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