Exploring the Causes and Consequences of Engaging in Fat Talk

Abstract

Fat talk refers to the ritualistic conversations about one's own and others' bodies (e.g., “I'm so fat!” “No you're not, I'm the one who is fat!”). What we say about ourselves has implications for how we make sense of and evaluate ourselves and those around us; thus, the current research presents the results of two studies that sought to identify potential causes and consequences of fat talk. Mutually reinforcing effects were predicted between fat talk and both body image and mental health issues. In two studies, participants completed closed-ended scales reporting their use of fat talk, body satisfaction, perceived pressure to be thin, self-esteem, and depression. Across a three-week span, Study 1 found fat talk to predict lower body satisfaction and higher depression; fat talk also mediated the association between body weight concerns and mental health problems. Study 2 found, across a two-week span, fat talk to predict higher levels of depression and perceived sociocultural pressure to be thin. In addition, low body satisfaction predicted more fat talk. Results suggest that reducing the amount of fat talk weakens its connection to negative aspects of self-concept. Health campaigns, interpersonal strategies, and more positive forms of weight-related communication are discussed as possible ways to potentially reduce the negative effects of fat talk on both body image and mental health issues.

Keywords:

• Body Image
• Health Communication
• Objectification Theory
• Self-esteem
• Depression

Notes

1. Separate standard multiple regressions were run for each of the predictor variables. When all four of the variables were entered into one regression analysis, they were all nonsignificant predictors. With such a small sample size, having seven predictor variables (the four independent variables, the variable controlling for the dependent variable at Time 1, sex, and BMI) both reduces our ability to detect effects and comes close to violating typical requirements for subjects–variables ratios in multiple regression (Cohen, 2008). Therefore, we run these as separate models.

Additional information

Notes on contributors

Analisa Arroyo

Analisa Arroyo is at University of Arizona

Jake Harwood

Jake Harwood is at University of Arizona