Addressing Heterogeneity in Binge Eating Disorder
This study investigates clinical heterogeneity in patients with binge eating disorder (BED) and its association with treatment outcomes. A two-step cluster analysis was conducted on a clinical sample of 196 BED patients, using an agglomerative hierarchical procedure based on both categorical and qua...
| Autores: | ; ; ; ; ; ; ; ; ; ; |
|---|---|
| Tipo de documento: | Artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Lenguaje: | Inglés |
| OAI Identifier: | oai:ddd.uab.cat:320614 |
| Acceso en línea: | https://ddd.uab.cat/record/320614 https://dx.doi.org/urn:doi:10.1002/erv.70034 |
| Nivel de acceso: | Acceso abierto |
| Sumario: | This study investigates clinical heterogeneity in patients with binge eating disorder (BED) and its association with treatment outcomes. A two-step cluster analysis was conducted on a clinical sample of 196 BED patients, using an agglomerative hierarchical procedure based on both categorical and quantitative measures-psychopathological symptoms, personality traits, emotional dysregulation, body composition, and food addiction. A subsequent comparison between clusters assessed therapy outcomes. Two distinct clusters emerged: C1 (n = 77) and C2 (n = 119). C2 patients exhibited a more dysfunctional profile, marked by more frequent binge episodes, higher eating psychopathology, greater emotion regulation difficulties, higher impulsivity levels, worse psychopathological state, higher food addiction levels, and personality traits reflecting greater harm avoidance and lower self-directedness and cooperativeness. While clusters did not differ by age, C2 had earlier age of onset and longer duration of the disorder. In contrast, C1 showed a more functional profile, later age of onset, lower total body fat mass, and better treatment outcomes. These findings highlight heterogeneity in BED, particularly regarding age of onset and associated clinical features, which may influence treatment response. The results suggest the need for distinct treatment strategies and more personalised therapeutic approaches tailored to patient subtypes. |
|---|