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Avoidant/Restrictive Food Intake Disorder (ARFID)– What’s New?

August 11, 2022

Dr. Debra Katzman and colleagues have examined presenting phenotypes of children and adolescents with “Avoidant/Restrictive Food Intake Disorder (ARFID)”, a study being released this month in Pediatrics (10.1542/peds.2022-057494). Their analysis revealed several clinical subtypes within this heterogeneous and relatively new disorder. For those unfamiliar with this condition, ARFID was added to the Diagnostic and Statistical Manual of Mental Disorders 5th Edition (DSM-5) in 2013. It is defined by an apparent lack of interest in eating, avoidance of food, and concern about adverse consequences of eating, yet it differs from anorexia nervosa and bulimia in that body image is not distorted.1 Criteria for an ARFID diagnosis include one or more of the following: significant weight loss or growth faltering, significant nutritional deficiency, dependence on supplement or on enteral feeding, or marked interference with psychosocial functioning, each not attributable to another medical diagnosis or ‘better explained’ by another mental health condition.1 The cause of ARFID is not known.

ARFID can occur at any age, and typically presents to pediatricians rather than to mental health professionals, so pediatricians will benefit from awareness of this condition.2 Both medical and psychological assessment and management are often needed; however, recognizing ARFID as a possible diagnosis is the initial challenge due to its broad array of possible symptoms. In this article, Dr. Katzman and colleagues tackled this very issue, asking if a statistical technique called ‘latent class analysis’ could be used to identify clinical subtypes with recognizable presentations. Latent class analysis is an analytic process by which individuals who seem quite different are classified into groups (latent classes) based on responses to categorical (think mutually exclusive multiple choice) survey questions or measures.3 In this way underlying common traits can be identified and biologically plausible subtypes can be identified. Study cases for the research were ascertained prospectively through surveillance via the Canadian Paediatric Surveillance Program January 1st, 2016 through December 31st, 2017, and included 207 youth ages 5-18 years. This prospective design avoided many study pitfalls, including provider recall bias.

In summary, the authors succeeded with their approach, and did identify 3 clear subtypes. These 3 classes were named Acute Medical (AM- with increased likelihood of weight loss and acute illness), Lack of Appetite (LOA - with increased likelihood of growth faltering and failure to gain weight) and Sensory (S – with food avoidance and aversion to certain types or textures of food).  There was a 4th group that emerged with a mixture of AM and LOA characteristics – please read the article to understand more! There is lots to learn and understand about ARFID, a relatively new and less well-known eating disorder. This study gives pediatricians a helpful window into potential ARFID presentations, and a clear way to think about an otherwise confusing condition. Let us know if you have had a chance to make this diagnosis, and how you think this article might aid your diagnostic thinking in the future!

References:

  1. Substance Abuse and Mental Health Services Administration. DSM-5 Changes: Implications for Child Serious Emotional Disturbance (Internet). Rockville (MD): Substance Abuse and Mental Health Services Administration (US); 2016 Jun. Table 22, DSM-IV to DSM-5 Avoidant/Restrictive Food Intake Disorder Comparison. Available from: https://www.ncbi.nlm.nih.gov/books/NBK519712/table/ch3.t18
  2. Brigham KS, Manzo LD, Eddy KT, Thomas JJ. Evaluation and Treatment of Avoidant/Restrictive Food Intake Disorder (ARFID) in Adolescents. Curr Pediatr Rep. 2018 Jun;6(2):107-113. DOI: 10.1007/s40124-018-0162-y. PMID: 31134139; PMCID: PMC6534269
  3. Grace-Martin, K. What is Latent Class Analysis? The Analysis Factor, LLC. 2022 https://www.theanalysisfactor.com/what-is-latent-class-analysis/ Accessed 8/10/22
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