Atypical anorexia nervosa: Implications of clinical features and BMI cutoffs

ObjectivesRestrictive eating disorders (EDs) occur across the weight spectrum, but historically more focus has been given to anorexia nervosa (AN) than atypical anorexia nervosa (atypAN). AtypAN's relegation to a diagnosis in the “other specified feeding and eating disorder” (OSFED) category and paucity of research surrounding atypAN invariably implies a less clinically severe ED. However, a growing body of research has begun to question the assumption that atypAN is less severe than AN. The current review and meta‐analysis aimed to provide a comprehensive review to compare atypAN and AN on measures of eating disorder psychopathology, impairment, and symptom frequency to test whether atypAN is truly less clinically severe than AN.MethodsTwenty articles that reported on atypAN and AN for at least one of the variables of interest were retrieved from PsycInfo, PubMed, and ProQuest.ResultsFor eating‐disorder psychopathology, results indicated that differences were nonsignificant for most indicators; however, atypAN was associated with significantly higher shape concern, weight concern, drive for thinness, body dissatisfaction, and overall eating‐disorder psychopathology than AN. Results indicated that atypAN and AN did not significantly differ on clinical impairment or the frequency of inappropriate compensatory behaviors, whereas there was a significantly higher frequency of objective binge episodes in AN (vs. atypAN).DiscussionOverall, findings indicated that, in contrast to the current classification system, atypAN and AN were not clinically distinct. Results underscore the need for equal access to treatment and equal insurance coverage for restrictive EDs across the weight spectrum.Public SignificanceThe current meta‐analysis found that atypAN was associated with higher drive for thinness, body dissatisfaction, shape concern, weight concern, and overall eating‐disorder psychopathology than AN; whereas AN was associated with higher frequency of objective binge eating. Individuals with AN and atypAN did not differ on psychiatric impairment, quality‐of‐life, or frequency of compensatory behaviors, highlighting the need for equal access to care for restrictive EDs across the weight spectrum.

Section: Eating Disorder Examination and Eating Disorder Examination-...mentioning

confidence: 74%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Eating Disorder Examination and Eating Disorder Examination-...mentioning

confidence: 88%

See 2 more Smart Citations

Eating disorder psychopathology, psychiatric impairment, and symptom frequency of atypical anorexia nervosa versus anorexia nervosa: A systematic review and meta‐analysis

Johnson

Negi

Chen

et al. 2023

“…Given the ongoing debate surrounding the classification of atypical AN (Golden, 2023), the limitations of using BMI as a diagnostic criterion (Kim et al, 2023;Nuttall, 2015), and prior literature suggesting a large overlap in the presentation of AN and atypical AN (Walsh et al, 2022), this study aims to assess the classification…”

Section: Improving Ed Diagnostic Classification Via Machine Learningmentioning

confidence: 99%

Differentiation between atypical anorexia nervosa and anorexia nervosa using machine learning

Sandoval‐Araujo,

Cusack,

Ralph‐Nearman

et al. 2024

ObjectiveBody mass index (BMI) is the primary criterion differentiating anorexia nervosa (AN) and atypical anorexia nervosa despite prior literature indicating few differences between disorders. Machine learning (ML) classification provides us an efficient means of accurately distinguishing between two meaningful classes given any number of features. The aim of the present study was to determine if ML algorithms can accurately distinguish AN and atypical AN given an ensemble of features excluding BMI, and if not, if the inclusion of BMI enables ML to accurately classify between the two.MethodsUsing an aggregate sample from seven studies consisting of individuals with AN and atypical AN who completed baseline questionnaires (N = 448), we used logistic regression, decision tree, and random forest ML classification models each trained on two datasets, one containing demographic, eating disorder, and comorbid features without BMI, and one retaining all features and BMI.ResultsModel performance for all algorithms trained with BMI as a feature was deemed acceptable (mean accuracy = 74.98%, mean area under the receiving operating characteristics curve [AUC] = 74.75%), whereas model performance diminished without BMI (mean accuracy = 59.37%, mean AUC = 59.98%).DiscussionModel performance was acceptable, but not strong, if BMI was included as a feature; no other features meaningfully improved classification. When BMI was excluded, ML algorithms performed poorly at classifying cases of AN and atypical AN when considering other demographic and clinical characteristics. Results suggest a reconceptualization of atypical AN should be considered.Public SignificanceThere is a growing debate about the differences between anorexia nervosa and atypical anorexia nervosa as their diagnostic differentiation relies on BMI despite being similar otherwise. We aimed to see if machine learning could distinguish between the two disorders and found accurate classification only if BMI was used as a feature. This finding calls into question the need to differentiate between the two disorders.

An examination of adults with atypical anorexia nervosa at admission to treatment at higher levels of care: An attempt to increase diagnostic clarity

Manwaring,

Blalock,

Duffy

et al. 2024

ObjectiveAnorexia nervosa (AN) is a serious illness with a high mortality rate and multiple physiological complications. The vague definition of atypical AN allows for subjective interpretation. This retrospective study aimed to focus future research on the operational definition of atypical AN by examining four factors associated with atypical AN at admission to higher level of care treatment.MethodsAdults with atypical AN (n = 69) were examined within sample analyses among four groups: (1) >10% versus ≤10% weight loss; (2) weight loss within the previous 3 months versus >3 months; (3) engaging in purging behaviors versus absence of purging behaviors; and (4) endorsing versus not endorsing significant cognitive aspects of AN.ResultsPatients with atypical AN endorsed elevated ED cognitions on the Eating Disorder Examination‐Questionnaire and depressive symptoms; a lack of association was found between weight loss severity and weight loss time frame with depressive symptoms, eating concern, and restraint. Purging behavior was associated with a higher expected body weight percentage (%EBW) and dietary restraint, while greater AN cognitions were associated with a higher EBW and weight loss percentage. Few patients demonstrated bradycardia, hypophosphatemia, or amenorrhea.DiscussionThis study demonstrated the severity of ED cognitions and depressive symptoms in this atypical AN sample and provided directions for future studies in the nosology of atypical AN. It may be important to distinguish between individuals with atypical AN who are purging and those who are not. Atypical AN was associated with a low frequency of physiological disturbances.Public SignificanceThis study provides further clarification regarding the operational definition of atypical AN; currently, a constellation of symptoms under Other Specified Feeding or Eating Disorders. This study was consistent with previous research in reporting severe eating disorder cognitions in adults with atypical AN, and noted the potential importance of distinguishing a purging distinction. A minority of patients in this study had physiological impairments.