In the United States, 24 million people suffer from eating disorders – the highest mortality rate among mental illness (The Renfrew Center Foundation for Eating Disorders, 2003). In the athletic setting, athletes are pressured to eat specific foods, weigh a set amount, and to acquire a certain body type, creating an environment that is often very unhealthy (Anderson, Petrie, & Neumann, 2012). It is important to address the risk of developing an eating disorder among athletes because clinical appearances of maladaptive eating behaviors continue to increase, and athletics is a high stress environment that could be a contributing factor (Atkinson, 2011). The purpose of this study was to examine the critical factors that affect collegiate athletes’ risk of developing an eating disorder.
Method:
Collegiate athletes (N=277) from Divisions I, II, and III institutions participated in this study. Participants completed an online demographics questionnaire and the Eating Attitudes Test-16. A hierarchical multiple regression (HMR) was used to predict eating disorders from gender and other independent variables. Factorial ANOVAs were used to examine the main effects and interactions of genders and divisions as well as between sexual orientation and type of sport on the risk of developing an eating disorder.
Analysis/Results:
The tolerance (from .288 to .866) and the variance inflation factor (from 1.154 to 3.474) suggested low levels of multicollinearity among the independent variables. In step 1 of the HMR, only one predicting variable (gender) was entered. This model was statistically significant (F(1,243)=9.15; p<.05) and explained 3.6% of the total variance. After three predictors (height, weight, and age) were entered in step 2, the total variance explained by the model was 6.1% (F(3,240)=2.12; p<.10), a 2.5% change of explained variance. In step 3, division 1to3, division 2to3, freshman, sophomore, and junior were entered. This model was statistically insignificant (F(5,235)=.29; p=.92) since it added merely 0.6% to the total variance. Meanwhile, results of the factorial ANOVAs supported the HMR outcomes that female athletes had a significantly (F(1,265)=9.39, p=.002) greater risk of eating disorder than male athletes.
Conclusions:
Gender differences in eating attitudes suggest that eating disorders remain more prominent in female athletes, but are present in male athletes. These results suggest that training and awareness programs must be established within athletic departments to promote early detection and create understanding and comfortable environments for athletes, and athletes should be taught healthy eating habits and exercise regimens that are conducive to their sport.