ArticleEuropean child & adolescent psychiatry2024
Early-onset restrictive food intake disorders in children: a latent class analysis.
Article in European child & adolescent psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Clinical profiles of ARFID compared with anorexia and bulimia in young people: a systematic review and meta-analysis.Journal of eating disorders · 2026Review
- Empirical Approaches to the Classification of Avoidant/Restrictive Food Intake Disorder.The International journal of eating disorders · 2025Article
- Neuroimaging insights into brain mechanisms of early-onset restrictive eating disorders.Nature. Mental health · 2025Article
- Early-onset anorexia nervosa: a scoping review and management guidelines.Journal of eating disorders · 2024Article
- A living experience proposal for the co-occurring diagnosis of avoidant/restrictive food intake disorder and other eating disorders.Journal of eating disorders · 2024Article
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Authors and funding
11 authors.
Funding
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Abstract
The two most frequent early-onset restrictive food intake disorders are early-onset anorexia nervosa (EOAN) and avoidant/restrictive food intake disorders (ARFID). Although the core symptoms of EOAN (i.e., fear of gaining weight and disturbed body image) are not present in ARFID, these symptoms are difficult to assess during the initial phase of hospitalisation. Our aim was to identify restrictive food intake disorder subtypes in children using latent class analysis (LCA) based on the information available at admission to hospital, and to determine the agreement between the subtypes identified using LCA and the final diagnosis: EOAN or ARFID. We retrospectively included 97 children under 13 years old with severe eating disorders (DSM-5) at their first hospitalisation in a specialised French paediatric unit. LCA was based on clinical information, growth chart analyses and socio-demographic parameters available at admission. We then compared the probabilities of latent class membership with the diagnosis (EOAN or ARFID) made at the end of the hospitalisation. The most parsimonious LCA model was a 2-class solution. Children diagnosed with EOAN at the end of hospitalisation had a 100% probability of belonging to class 1 while children diagnosed with ARFID had an 8% probability of belonging to class 1 based on parameters available at admission. Our results indicate that clinical and socio-demographic characteristics other than the core symptoms of EOAN may be discriminating for a differential diagnosis.
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