Food Addiction in Eating Disorders: A Cluster Analysis Approach and Treatment Outcome

Lucero Munguía, Anahí Gaspar-Pérez, Susana Jiménez-Murcia, Roser Granero, Isabel Sánchez, Cristina Vintró-Alcaraz, Carlos Diéguez, Ashley N. Gearhardt, Fernando Fernández-Aranda*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review


Background: A first approach of a phenotypic characterization of food addiction (FA) found three clusters (dysfunctional, moderate and functional). Based on this previous classification, the aim of the present study is to explore treatment responses in the sample diagnosed with Eating Disorder(ED) of different FA profiles. Methods: The sample was composed of 157 ED patients with FA positive, 90 with bulimia nervosa (BN), 36 with binge eating disorder (BED), and 31 with other specified feeding or eating disorders (OSFED). Different clinical variables and outcome indicators were evaluated. Results: The clinical profile of the clusters present similar characteristics with the prior study, having the dysfunctional cluster the highest ED symptom levels, the worse psychopathology global state, and dysfunctional personality traits, while the functional one the lowest ED severity level, best psychological state, and more functional personality traits. The dysfunctional cluster was the one with lowest rates of full remission, the moderate one the higher rates of dropouts, and the functional one the highest of full remission. Conclusions: The results concerning treatment outcome were concordant with the severity of the FA clusters, being that the dysfunctional and moderate ones had worst treatment responses than the functional one.

Original languageEnglish
Article number1084
Number of pages11
Issue number5
Publication statusPublished - 4 Mar 2022


  • Cluster analysis approach
  • Eating disorders
  • Food addiction
  • Treatment outcome


Dive into the research topics of 'Food Addiction in Eating Disorders: A Cluster Analysis Approach and Treatment Outcome'. Together they form a unique fingerprint.

Cite this