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Cluster analysis of key diagnostic variables from two independent samples of eating-disorder patients: evidence for a consistent pattern

  • DAVID CLINTON (a1), ERIC BUTTON (a1), CLAES NORRING (a1) and ROBERT PALMER (a1)

Abstract

Introduction. The optimal classification of eating disorders has been a matter of considerable debate. The present paper tackles this issue using cluster analysis with large independent samples of eating-disorder patients.

Method. Two samples of adult female patients from Sweden (n=631) and England (n=472) were classified on the basis of 10 key clinical variables of primary significance for diagnosing eating disorders. A separate series of cluster analyses were conducted on each sample.

Results. Results suggested that a three-cluster solution was optimal in both samples. The first cluster (‘generalized eating disorder’) was characterized by high levels of eating-disorder psychopathology on all variables except weight and menstrual functioning. The second cluster (‘anorexics’) was typified by low weight, amenorrhoea and the absence of binge eating, and seemed to correspond to the clinical picture of anorexia nervosa. The third cluster (‘overeaters’) was characterized by high weight and moderate levels of binge eating and compensatory behaviour.

Conclusions. Results suggest that patients presenting to eating-disorder services in different countries have clinical features that fall into very similar patterns. These patterns resemble, but are not identical to, existing diagnostic categories.

Copyright

Corresponding author

David Clinton, Division of Psychiatry, M57, Neurotec Department, Karolinska Institutet, Huddinge University Hospital, S-141 86, Sweden. (Email: David.Clinton@neurotec.ki.se)

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Cluster analysis of key diagnostic variables from two independent samples of eating-disorder patients: evidence for a consistent pattern

  • DAVID CLINTON (a1), ERIC BUTTON (a1), CLAES NORRING (a1) and ROBERT PALMER (a1)

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