Eating Disorders

Summary
In “Risk factors for binge eating and purging eating disorders: Differences Based on Age of Onset,” Allen, Byrne, Oddy, et al (2014) use a logical regression method to determine relationships between various psychological and environmental variables and age of onset of eating disorders. The authors explain the importance of the study in clarifying and detecting risk factors, with clear implications for clinical practice. According to the authors, this study fills a gap in the literature not just in that it is a single cohort design but also one that uses a psychiatric control group. The main variables include parent perceptions of their child’s weight, and also actual body weight in middle childhood. The authors present two hypotheses: first, that among female cohorts, late-onset binge-and-purge eating disorders like bulimia would be positively correlated with parental disapproval of child weight in middle childhood. Second, the authors hypothesize that early adolescents’ concerns about weight, eating, or shape would be more correlated with late onset eating disorders than any other childhood variable.
The authors attempt to address a cluster of intervening variables at the same time, including comorbic psychiatric conditions like anxiety or depression. Using the Raine Study model, the authors assessed childhood variables including early childhood care, parental and family functioning, overall health, and the child’s overall emotional functioning. BMI was also a major predictive variable. The authors also include several other checklists including the Social Problems Scale, the Life Stress Inventory, the Beck Depression Inventory. Both parts of the hypothesis were upheld, except for the fact that BMI was not found to be predictive of risk for developing an eating disorder. The most important finding is that parental pressure to lose weight is a significant risk factor.
Analysis
This article extends the growing body of literature on eating disorders, focusing specifically on bulimia. Although the authors do not discuss the neurological factors of eating disorders, they do address a number of relevant clinical variables including physiological assessments. Self-efficacy and other variables that were included in this study do not cloud the results of the research but do clutter the report and cloud its primary objectives of highlighting the most statistically significant risk factors for early versus late onset bulimia. Intended audiences include both research psychologists and also clinical psychologists intending to implement the results in their practice. Therefore, greater clarification of the relationship between different variables would be helpful.
Multivariate and complex, the study accurately reflects the panoply of variables that do interconnect in eating disorder etiology. The authors intend to differentiate between risk factors for early versus later onset eating disorders, but fail to point out why this differentiation might matter or how it could be applied in clinical practice. Moreover, the authors do not clarify whether the same risk factors predicting early-onset binge-and-purge disorders might also predict later onset eating disorders. In fact, parent perceptions of child weight were the strongest predictor of both early onset and later onset eating disorders. The researchers also measure parent perceptions but cannot accurately measure how the parents expressed their perceptions to the child, and whether those perceptions had been expressly vocalized and if so, how.
Clearly, parenting styles and attitudes towards weight are significant factors in the etiology of some eating disorders. The authors do point out that rather than focusing on age of onset, future researchers would do well to promote public health awareness and family psychology interventions.





References

Allen, K.L., Byrne, S.M., Oddy, W.H., et al (2014). Risk factors for binge eating and purging eating disorders. Int J Eat Disord 2014; 47:802–812