Prevalence and Characterization of Eating Disorders among Patients with Inborn Errors of Metabolism Managed with Diet

Prevalence and Characterization of Eating Disorders among Patients with Inborn Errors of Metabolism Managed with Diet | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence and Characterization of Eating Disorders among Patients with Inborn Errors of Metabolism Managed with Diet Mary Kate LoPiccolo, Claire Cinnamon, Colleen Donnelly, Ilona Ginevic, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8483533/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Lifelong restrictive diets are a mainstay of management for many inborn errors of metabolism (IEMs). The experience of metabolic care providers suggests a high prevalence of eating disorders among these patients; however, this has not been well characterized. This study applied validated tools to screen patients for eating disorders and to characterize their symptom pathologies. Patients aged 16 years and older on prescription diets at the Program for Inherited Metabolic Diseases at the Icahn School of Medicine at Mount Sinai were recruited, and patient demographics were collected through medical record review. All participants were given 2 assessment tools: the SCOFF questionnaire, a 5-question screen for a possible eating disorder, and a modified Eating Pathology Symptoms Inventory (EPSI), a 45-item Likert-scaled questionnaire characterizing eating disorder pathology. Results Fifty-two subjects were enrolled, and 51 completed both surveys. 27 subjects identified as female (52%), 23 as male (44%), and two as genderqueer (4%). Ages ranged from 16-50 years old. The most common diagnosis was Phenylketonuria (n=34, 65%), followed by glycogen storage disease type 1a (n= 8, 15%). Most patients were on a low-protein diet (n=41, 79%), 17% (n=9) were on a low-carbohydrate diet, and 6% (n=3) were on a low-fat diet. The SCOFF screen positive rate was 35%, indicating that over one third of the participants have a potential eating disorder, which is significantly greater than population norms of 10.1% (p<0.001). EPSI results revealed that our participants were significantly more likely to demonstrate binge eating, restrictive behaviors, excessive exercise, and negative attitudes towards obesity when compared to population norms. Conclusion This study demonstrates a significantly increased prevalence of likely eating disorders among patients with IEM, about three times that of the general population. Metabolic providers should be aware of this risk to their patients, as eating disorders can impact metabolic control and adherence to diet, while also causing significant psychological distress to patients with these rare disorders. Steps must be taken to create a standardized approach to screen patients with IEM in clinic and streamline access to specialized care for eating disorders. Inborn errors of metabolism eating disorder nutrition screening comorbidities Figures Figure 1 I. Introduction Eating disorders (EDs) are life-threatening psychiatric conditions characterized by atypical eating behaviors and an impulse to control bodyweight. The major specified types of EDs described in the Diagnostic and Statistical Manual of Mental Disorders, 5 th Edition (DSM-V) are anorexia nervosa, bulimia nervosa, binge eating disorder, avoidant restrictive food intake disorder, pica, and rumination disorder. 1,2 Presentations are highly variable, and they affect individuals from all genders, races, and socioeconomic backgrounds. 3,4 The lifetime prevalence of eating disorders is 2 to 5%, however the incidence has been rising since the onset of the COVID-19 pandemic, particularly among young adults. 4 EDs can be debilitating—psychologically and physically. Only 50% of patients fully recover from EDs, and timely diagnosis and treatment are critical in optimizing prognosis. 5 Patients with chronic diseases, particularly those managed with dietary therapy, are at high risk of developing EDs. 6–8 Mortality rates are three times higher in individuals with EDs when compared to the general population, so when considered in the context of a comorbid chronic disease, EDs are exceedingly dangerous. 9 While medically necessary, the rigorous dietary restrictions prescribed in chronic disease, such as Type 1 diabetes, cystic fibrosis, inflammatory bowel disease, and inborn errors of metabolism, may encourage destructive relationships with food and dangerous eating behaviors. 6–8 In other words, prescribed diets can be both life-saving and life-threatening long-term. Dietary therapy is one of the cornerstones of management in inborn errors of metabolism (IEMs). 10 To mitigate the impact of enzymatic deficiencies and the resulting accumulation of detrimental metabolites, strict restriction of macronutrients, such as protein, carbohydrates, or fat, is prescribed. Patients must precisely measure their food intake, limit their food choices, and supplement their diets with medical foods and formulas to meet minimum nutritional requirements. Although early and consistent dietary control are a critical part of optimizing outcomes, long-term dietary adherence is very difficult to achieve. A study on patients with PKU revealed that 73% of both adults with PKU and caregivers found maintaining the diet challenging. 11 Participants recognized it as a daily burden, demanding significant discipline and self-control. This study also showed that 55% of PKU patients had difficulty controlling their weight, and 14% had an ED or exhibited disordered eating. Only 4% were receiving therapy for EDs. 11 Research on the prevalence and characterization of eating disorders among patients with IEMs is limited. A retrospective cohort study of 3,714 patients with phenylketonuria (PKU) screened for comorbid neuropsychiatric conditions based on ICD-9 codes noted significantly increased prevalence of eating disorders (3.4%) when compared to the general population (0.9%) and patients with another chronic, diet-managed condition, Type 1 diabetes mellitus (1.9%). 12 Another study examined eating behaviors and attitudes of patients with PKU by administering a survey loosely adapted from the Eating Attitudes Test (EAT-26). 13 This study found that patients with poor metabolic control showed a higher prevalence of disordered eating behaviors, though it acknowledged the limited utility of the data given the small sample size ( n = 15). One study examined eating behaviors and attitudes in 64 patients with hepatic glycogen storage diseases using the Eating Disorders Inventory (EDI-3), EAT-26, and Body Esteem Scale (BES), along with the corresponding pediatric versions. Participants reported increased abnormal attitudes towards food and eating and lower body esteem. 14 They also reported fewer classic symptoms of eating disorders, suggesting that tools assessing for eating disorders among GSD patients may need to be specifically tailored to the patient population. While these few studies are compelling, the broader community of patients living with IEMs managed with diet has yet to be examined and guidance for metabolic providers is lacking. This study screened patients with IEMs treated with dietary management for eating disorders and characterized their symptoms. We accomplished this by offering participants two validated questionnaires, the SCOFF survey and the Eating Pathology Symptoms Inventory (EPSI), and by collecting individual patient perspectives. II. Methods Participants Study participants were recruited from the Mount Sinai Program for Inherited Metabolic Diseases in New York, New York, USA. Eligible patients were actively followed by the clinic, had an IEM managed with diet, and were 16 years of age or older. Patients with intellectual disability impairing their ability to consent and/or comprehend the study questionnaires, pregnant patients, non-English speakers, and patients perceived to be unfit to participate by the study team were excluded. Medical records were reviewed to determine participant eligibility and to collect patient demographics following the consenting process. Demographic information included age, sex assigned at birth, gender identity, height, weight, BMI, race/ethnicity, metabolic disorder, diet prescription, ICD-10 codes, and concomitant medications. Procedure All study procedures were approved by the Mount Sinai Institutional Review Board (IRB 21-01385). Recruitment was conducted by approaching eligible participants in the clinic with a flyer or remotely with telephone calls and emails. Participants or legal guardians were prompted to review and e-sign the consent form. An assent form was required for minors. Participants were prompted to answer questions for 2 validated questionnaires (see “Measures” below). An optional open-ended text box was presented for additional comments in response to the questionnaires. After completion, participants were directed to an optional resources and referrals page, which gave contact information for the Mount Sinai Eating and Weight Disorders Program, and they were emailed a $10 Amazon gift card for their time. ASSESSMENT TOOLS SCOFF Questionnaire The SCOFF questionnaire is a validated self-report screening tool that for eating disorders, consisting of five “yes” or “no” questions. 15,16 “SCOFF” is an acronym for the 5 questions asked, remembered with the mnemonic “Sick, Control, One-Stone, Fat, Food.” For example, “S” represents the word “sick” in the question, “Do you make yourself sick because you feel uncomfortably full?” Other items inquire about loss of control overeating, weight loss, feeling fat, and feelings of a food-dominated life. Two or more “yes” answers qualify as a positive screening. The Eating Pathology Symptoms Inventory (EPSI) The Eating Pathology Symptoms Inventory (EPSI) is a validated self-report questionnaire used to characterize eating disorder pathology. 17,18 The EPSI is composed of 45 statements. Participants rate each using a 5-point Likert scale (0 = Never, 1 = Rarely, 2 = Sometimes, 3 = Often, 4 = Very Often) to report how often the statement applied to them over the preceding 4 weeks. The EPSI contains 8 subscales: Body Dissatisfaction, Binge Eating, Cognitive Restraint, Purging, Restriction, Excessive Exercise, Negative Attitudes towards Obesity, and Muscle Building. Each subscale has a different number of corresponding items, ranging from 3 to 8, resulting in total possible scores ranging from 12 to 32 between subscales. A modified EPSI was utilized for the purpose of the IEM patient population, changing three items: 1. “I used protein supplements” became “I used protein supplements that were not prescribed to me ,” 2. “I made myself vomit in order to lose weight” became “I made myself vomit in order to lose weight or to adhere to my metabolic diet ,” and 3, “I used muscle building supplements” became “I used muscle building supplements that were not prescribed to me .” Data Analysis To explore potential associations among variables such as age, gender, BMI, etc. and a positive screening on the SCOFF survey, we used logistic regression modeling. Variables were first analyzed univariately by the student t-test for continuous variables and the Fisher's exact test for discrete data. For the multivariable analysis, variables with a p value < 0.25 were tested in a logistic regression analysis model. Odds ratios and associated 95% confidence intervals were then generated by exponentiating the beta coefficients (slope estimates) from this equation. For all statistical analysis, data was analyzed using the SAS System software 9.4 (SAS Institute, Inc., Cary, N.C.). III. Results Demographics Fifty-two patients were enrolled in the study. Of the 52 subjects, 51 subjects completed both the SCOFF and the EPSI questionnaires; one participant only completed the SCOFF. Nineteen of the participants filled out responses in the optional open-ended text box. Participant demographics are shown in Table 1. Twenty-seven participants identified as female (52%), twenty-three as male (44%), and two identified as gender queer (4%). There were nine IEMs represented in the study population. Most participants had phenylketonuria, or PKU ( n = 34, 65%). Other represented IEMs included glycogen storage disease type 1a, or GSD1a ( n = 8, 15%), maple syrup urine disease, or MSUD ( n = 3, 6%), ornithine transcarbamylase deficiency, or OTC ( n = 2, 4%), homocystinuria ( n = 1, 2%), multiple acyl-Coa dehydrogenase deficiency ( n = 1, 2%), Citrin deficiency ( n = 1, 2%), carbamoyl phosphate synthetase I deficiency, or CPS I ( n = 1, 2%), and carnitine palmitoyltransferase II deficiency, or CPT 2 ( n = 1, 2%). Of the participants, only 4% ( n = 2) were minors aged 16-17 years, while the majority were adults under the age of 50 years old (n = 49, 94%). One participant was over 50 years old ( n = 1, 2%). The mean age was 29 years. Participant BMI ranged from 16.5 to 40.9 kg/m 2 , with a mean BMI of 27.5 kg/m 2 . Based on CDC BMI classifications, 4% ( n = 2) of the participants were underweight, 38% ( n = 20) were normal weight, 58% were overweight or obese ( n = 30). Most participants were on a protein-restricted diet ( n = 41, 79%), while 17% ( n = 9) were on a low-carbohydrate diet and 6% ( n = 3) were on a fat-restricted diet. Some patients were on a combination of these dietary prescriptions. More than half of participants ( n = 29, 56%) used both medical food and formula, while 31% ( n = 16) only used medical formula. SCOFF Results The SCOFF screen positive rate was 35% ( n = 18). This indicates that over a third of the participants responded ‘yes’ to two or more SCOFF questions and were identified as having a likely eating disorder. Of the male participants, 26% ( n = 6) screened positive, while 37% ( n = 10) of the females and 100% ( n = 2) of those identifying as gender queer screened positive (see Table 2). The average age of those who screened positive was 28.6 years old, and the average BMI was 29.6 kg/m 2 . There was no statistically significant difference in screen positive rates based on sex assigned at birth, gender identity, age, or BMI. Of the five SCOFF items, nearly half ( n = 24, 46%) of participants responded 'yes' to the item, “Would you say food dominates your life?” The question with the next highest response rate was, “Do you worry you have lost control over how much you eat?,” with about 30% ( n = 16) responding 'yes'. The complete SCOFF item breakdown is seen in Table 3 and Figure 1. The SCOFF screen positive rate among our subjects was found to be significantly greater ( p <0.001) than the reported population norm, which is about 10% among a multiethnic UK community sample. 16 EPSI Results The mean score for each of the eight EPSI subscales was calculated for the study population. Study population EPSI characteristics, including number of items per subscale, total possible score, score range, mean, and standard deviation are presented in Table 3. The only subscale where a participant responded “very often” (ie, a score of 4) for each item was Restricting. SCOFF positivity was associated with binge eating (OR = 1.24, p =0.002) and cognitive restraint (OR = 1.24, p =0.002). When compared to population norms, study subjects were significantly more likely to demonstrate binge eating, restrictive behaviors, excessive exercise, and negative attitudes towards obesity. 18 Study subjects were significantly less likely to report purging and muscle building behaviors. (Figure 3; Table 4). Eating disorder symptom pathology, as characterized by the EPSI, was consistent with the open-ended text box responses received. Patterns of restriction were seen by several participants. One noted, “At one point as a teenager I stopped eating food entirely, only surviving on the protein replacement tablets prescribed to me.” Responses explicitly mentioning purging were also seen by several participants. One stated, “I no longer make myself throw up, but I did consistently for about a year” while another participant said, “Recovered from Bulimia, used to (10 years ago) routinely purge after eating. I have related my difficult relationship with food heavily to my childhood growing up with PKU.” IV. Discussion This study screened young adult and adult patients with IEM for EDs and characterized their pathologies using two validated screening tools, the SCOFF and EPSI. The results suggest that there is a significantly higher prevalence of eating disorders among individuals with IEM treated with diet, with our population three times more likely to screen positive for an ED compared to a population norm. Study participants were significantly more likely to demonstrate binge eating, restrictive behaviors, excessive exercise, and negative attitudes towards obesity when compared to a community sample, whereas they were less likely to report purging and muscle building behaviors. Our study is the largest of its kind to-date and included patients from the widest variety of IEMs thus far in the literature. This study had several important limitations. Our cohort size was small, particularly among individual disease groups, limiting the statistical power to detect associations between survey responses and diagnosis. The SCOFF is a screening rather than a diagnostic instrument, thus true prevalence could not be determined. In addition, neither the SCOFF nor the EPSI have been validated in the IEM population. Although the SCOFF was modified to increase its relevance to this population, a more tailored assessment battery may more accurately characterize eating disorder risk in our population. Our findings underscore the need for standardized approaches to diagnosing and treating EDs in this medically complex population. The high screen positive rate on the SCOFF among individuals with IEMs managed with diet raises significant clinical concern about our ability to effectively manage comorbid EDs and IEMs. Metabolic diets are essential to prevent metabolic decompensation and/or chronic accumulation of toxic metabolites. Both restrictive and excessive intake pose risk for injury in this population. Binge eating behaviors may result in excessive intake of offending metabolites, while restriction poses a risk of catabolism and further metabolic instability. Thus, the development of eating disorders may substantially complicate IEM management, highlight the importance of early recognition and intervention. Further work must be done to validate the use of the SCOFF and EPSI in patients with IEMs. Screening of pediatric populations is also a critical next step, as EDs may begin to present earlier in childhood. As we expand our understanding of EDs in IEMs managed with diet, we must also determine targeted modes of therapy for EDs in this population. Earlier identification and treatment is crucial to overall patient outcomes and could reduce morbidity and mortality for our vulnerable patients with IEMs. Declarations Ethics approval and consent to participate: This study was performed in line with the principles of the declaration of Helsinki. Ethics and research governance approval were obtained from the Mount Sinai Institutional Review Board (IRB 21-01385). Consent for publication: Not applicable. Availability of data and materials: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: Not applicable. Authors’ contributions: ML, CC, and MB made significant contributions to the conception and design of the study, analysis, interpretation of data, drafting and revision of the manuscript. CD made significant contributions to the conception and design of the study as well as revision of the manuscript. IG, JW, SD, MM, CS, and LE made contributions to the conception of the study, recruitment of participants, and revision of the manuscript. All authors read and approved the final manuscript. AW worked on analysis and interpretation of data. TH made significant contributions to the conception and design of the study. Acknowledgements: We are grateful for all of the families and patients who agreed to participate in the study. Thank you to the entire Mount Sinai Program for Inherited Metabolic Diseases faculty and staff for supporting this important work. References American Psychiatric Association, American Psychiatric Association, eds. Diagnostic and Statistical Manual of Mental Disorders: DSM-5 . 5th ed. American Psychiatric Association; 2013. Feltner C, Peat C, Reddy S, et al. Screening for Eating Disorders in Adolescents and Adults: Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA . 2022;327(11):1068. doi:10.1001/jama.2022.1807 Attia E, Walsh BT. Eating Disorders: A Review. JAMA . 2025;333(14):1242. doi:10.1001/jama.2025.0132 Silén Y, Keski-Rahkonen A. Worldwide prevalence of DSM-5 eating disorders among young people. Curr Opin Psychiatry . 2022;35(6):362-371. doi:10.1097/yco.0000000000000818 Bryant E, Spielman K, Le A, et al. Screening, assessment and diagnosis in the eating disorders: findings from a rapid review. J Eat Disord . 2022;10(1). doi:10.1186/s40337-022-00597-8 Quick VM, Byrd-Bredbenner C, Neumark-Sztainer D. Chronic Illness and Disordered Eating: A Discussion of the Literature. Adv Nutr . 2013;4(3):277-286. doi:10.3945/an.112.003608 Avila JT, Park K, Golden NH. Eating disorders in adolescents with chronic gastrointestinal and endocrine diseases. Lancet Child Adolesc Health . 2019;3(3):181-189. doi:10.1016/s2352-4642(18)30386-9 Kumar MM. Eating Disorders in Youth with Chronic Health Conditions: Clinical Strategies for Early Recognition and Prevention. Nutrients . 2023;15(17):3672. doi:10.3390/nu15173672 Krug I, Liu S, Portingale J, et al. A meta-analysis of mortality rates in eating disorders: An update of the literature from 2010 to 2024. Clin Psychol Rev . 2025;116:102547. doi:10.1016/j.cpr.2025.102547 Bernstein LE, Rohr F, Helm JR, eds. Nutrition Management of Inherited Metabolic Diseases: Lessons from Metabolic University . Springer; 2015. doi:10.1007/978-3-319-14621-8 Ford S, O’Driscoll M, MacDonald A. Living with Phenylketonuria: Lessons from the PKU community. Mol Genet Metab Rep . 2018;17:57-63. doi:10.1016/j.ymgmr.2018.10.002 Bilder DA, Kobori JA, Cohen-Pfeffer JL, Johnson EM, Jurecki ER, Grant ML. Neuropsychiatric comorbidities in adults with phenylketonuria: A retrospective cohort study. Mol Genet Metab . 2017;121(1):1-8. doi:10.1016/j.ymgme.2017.03.002 Luu S, Breunig T, Drilias N, Kuhl A, Scott Schwoerer J, Cody P. A Survey of Eating Attitudes and Behaviors in Adolescents and Adults With Phenylalanine Hydroxylase Deficiency. WMJ Off Publ State Med Soc Wis . 2020;119(1):37-43. Disordered Eating and Body Esteem Among Individuals with Glycogen Storage Disease. In: JIMD Reports . Springer Berlin Heidelberg; 2014:23-29. doi:10.1007/8904_2014_359 Morgan JF, Reid F, Lacey JH. The SCOFF questionnaire: assessment of a new screening tool for eating disorders. BMJ . 1999;319(7223):1467-1468. doi:10.1136/bmj.319.7223.1467 Solmi F, Hatch SL, Hotopf M, Treasure J, Micali N. Validation of the SCOFF questionnaire for eating disorders in a multiethnic general population sample. 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Eat Behav . 2018;31:1-7. doi:10.1016/j.eatbeh.2018.07.004 Tables Table 1: Participant Demographics Frequency ( n = 52) Percent Age (years): 16-17 2 4 18-29 23 44 30-49 26 50 50+ 1 2 Gender Male 23 44 Female 27 52 Gender Queer 2 4 BMI Underweight (30 kg/m2) 16 31 Metabolic Disorder Glycogen storage disease type 1a 8 15 Maple syrup urine disease 3 6 Ornithine transcarbamylase deficiency 2 4 Phenylketonuria 34 65 Other* 5 10 Diet Prescription Low Protein 41 79 Low Fat 3 6 Low Carbohydrate 9 17 Use of Medical Food and Formula 29 56 Use of Medical Formula Only 16 31 *Carbamoyl phosphate synthetase I deficiency, carnitine palmitoyltransferase II deficiency, citrin deficiency, homocystinuria, multiple acyl-Coa dehydrogenase deficiency Table 2: SCOFF Screening Results Demographics SCOFF Characteristics Positive Negative n (%) n (%) Male 6 (26) 17 (74) Female 10 (37) 17 (63) Gender queer 2 (100) 0 (0.00) Total Population 18 (35) 34 (65) M (SD) M (SD) Age 28.61 (9.71) 29.79 (7.92) BMI (kg/m2) 29.57 (5.79) 26.51 (6.22) Legend: SCOFF screen positive is defined as ≥ 2 yes responses. Table 3: SCOFF Item Breakdown and Total Screen Positive Rate SCOFF Item Breakdown n (%) S- Do you make yourself Sick because you feel uncomfortably full? 7 (14%) C- Do you worry you have lost Control over how much you eat? 16 (31%) O- Have you recently lost more than One stone in a three- month period? 7 (14%) F- Do you believe yourself to be Fat when others say you are too thin? 13 (25%) F- Would you say Food dominates your life? 24 (46%) Total Screen Positive (≥ 2 yes responses) 18 (35%) Table 4: EPSI Characteristics and Comparison to Population Norms EPSI Characteristics Number of Items Total Possible Score Score Range Mean (SD) Study Mean (SD) n=51 Community Mean (SD) n= 341 18 p-value Body dissatisfaction 7 28 0-27 10.8 (6.96) 10.8 (7.0) 10.3 (7.6) 0.65799 Binge eating 8 32 0-30 10.22 (7.17) 10.2 (7.2) 7.8 (6.6) 0.01614 Cognitive restraint 3 12 0-10 5.55 (2.39) 5.6 (2.4) 5.0 (3.1) 0.22542 Purging 6 24 0-12 1.73 (3.02) 1.7 (3.0) 5.2 (4.9) 0.00000 Restricting 6 24 0-24 8.67 (5.87) 8.7 (5.9) 3.3 (4.3) 0.00000 Excessive exercise 5 20 0-17 7.82 (4.62) 7.8 (4.6) 6.3 (5.1) 0.04518 Negative attitudes towards obesity 5 20 0-19 5.73 (4.85) 5.7 (4.9) 2 (4.0) 0.00000 Muscle building 5 20 0-10 2.88 (2.55) 2.9 (2.6) 4.8 (4.8) 0.00542 Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 10 Mar, 2026 Reviewers invited by journal 04 Mar, 2026 Editor assigned by journal 02 Jan, 2026 First submitted to journal 31 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Sinai Department of Psychiatry","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Hildebrandt","suffix":""},{"id":600471720,"identity":"1030aa48-501c-419f-9af1-15ccb0bba961","order_by":11,"name":"Margo Sheck Breilyn","email":"","orcid":"","institution":"Icahn School of Medicine at Mount Sinai Department of Genetics and Genomic Sciences","correspondingAuthor":false,"prefix":"","firstName":"Margo","middleName":"Sheck","lastName":"Breilyn","suffix":""}],"badges":[],"createdAt":"2025-12-30 17:56:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8483533/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8483533/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104320872,"identity":"a4828a1f-2bcb-4da4-b227-d7de58d517b0","added_by":"auto","created_at":"2026-03-10 13:15:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":30299,"visible":true,"origin":"","legend":"\u003cp\u003eEPSI Subscale Scores in Study Population compared to Community Sample\u003csup\u003e18\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLegend: \u003c/strong\u003eEPSI mean subscale scores among study population were compared to a community sample. IEM patients managed with diet were found to have significantly higher mean scores for binge eating, restricting, excessive exercise, and negative attitudes towards obesity. They had significantly lower scores for purging and muscle building behaviors.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8483533/v1/f406f7bb34e00981d7b5cc1a.png"},{"id":104405451,"identity":"f43e6107-137c-4f65-913c-0bff0f8fe4e6","added_by":"auto","created_at":"2026-03-11 12:22:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":724099,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8483533/v1/a6c80cf2-fff5-401d-a803-c3bbdc47c3da.pdf"}],"financialInterests":"","formattedTitle":"Prevalence and Characterization of Eating Disorders among Patients with Inborn Errors of Metabolism Managed with Diet","fulltext":[{"header":"I. Introduction","content":"\u003cp\u003eEating disorders (EDs) are life-threatening psychiatric conditions characterized by atypical eating behaviors and an impulse to control bodyweight. The major specified types of EDs described in the Diagnostic and Statistical Manual of Mental Disorders, 5\u003csup\u003eth\u003c/sup\u003e Edition (DSM-V) are anorexia nervosa, bulimia nervosa, binge eating disorder, avoidant restrictive food intake disorder, pica, and rumination disorder.\u003csup\u003e1,2\u003c/sup\u003e Presentations are highly variable, and they affect individuals from all genders, races, and socioeconomic backgrounds.\u003csup\u003e3,4\u003c/sup\u003e The lifetime prevalence of eating disorders is 2 to 5%, however the incidence has been rising since the onset of the COVID-19 pandemic, particularly among young adults.\u003csup\u003e4\u003c/sup\u003e EDs can be debilitating\u0026mdash;psychologically and physically. Only 50% of patients fully recover from EDs, and timely diagnosis and treatment are critical in optimizing prognosis.\u003csup\u003e5\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatients with chronic diseases, particularly those managed with dietary therapy, are at high risk of developing EDs.\u003csup\u003e6\u0026ndash;8\u003c/sup\u003e Mortality rates are three times higher in individuals with EDs when compared to the general population, so when considered in the context of a comorbid chronic disease, EDs are exceedingly dangerous.\u003csup\u003e9\u003c/sup\u003e While medically necessary, the rigorous dietary restrictions prescribed in chronic disease, such as Type 1 diabetes, cystic fibrosis, inflammatory bowel disease, and inborn errors of metabolism, may encourage destructive relationships with food and dangerous eating behaviors.\u003csup\u003e6\u0026ndash;8\u003c/sup\u003e In other words, prescribed diets can be both life-saving and life-threatening long-term.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDietary therapy is one of the cornerstones of management in inborn errors of metabolism (IEMs).\u003csup\u003e10\u003c/sup\u003e To mitigate the impact of enzymatic deficiencies and the resulting accumulation of detrimental metabolites, strict restriction of macronutrients, such as protein, carbohydrates, or fat, is prescribed. Patients must precisely measure their food intake, limit their food choices, and supplement their diets with medical foods and formulas to meet minimum nutritional requirements. Although early and consistent dietary control are a critical part of optimizing outcomes, long-term dietary adherence is very difficult to achieve. A study on patients with PKU revealed that 73% of both adults with PKU and caregivers found maintaining the diet challenging.\u003csup\u003e11\u003c/sup\u003e Participants recognized it as a daily burden, demanding significant discipline and self-control. This study also showed that 55% of PKU patients had difficulty controlling their weight, and 14% had an ED or exhibited disordered eating. Only 4% were receiving therapy for EDs.\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eResearch on the prevalence and characterization of eating disorders among patients with IEMs is limited. A retrospective cohort study of 3,714 patients with phenylketonuria (PKU) screened for comorbid neuropsychiatric conditions based on ICD-9 codes noted significantly increased prevalence of eating disorders (3.4%) when compared to the general population (0.9%) and patients with another chronic, diet-managed condition, Type 1 diabetes mellitus (1.9%).\u003csup\u003e12\u003c/sup\u003e Another study examined eating behaviors and attitudes of patients with PKU by administering a survey loosely adapted from the Eating Attitudes Test (EAT-26).\u003csup\u003e13\u003c/sup\u003e This study found that patients with poor metabolic control showed a higher prevalence of disordered eating behaviors, though it acknowledged the limited utility of the data given the small sample size (\u003cem\u003en\u003c/em\u003e = 15). \u0026nbsp;One study examined eating behaviors and attitudes in 64 patients with hepatic glycogen storage diseases using the Eating Disorders Inventory (EDI-3), EAT-26, and Body Esteem Scale (BES), along with the corresponding pediatric versions. Participants reported increased abnormal attitudes towards food and eating and lower body esteem.\u003csup\u003e14\u003c/sup\u003e They also reported fewer classic symptoms of eating disorders, suggesting that tools assessing for eating disorders among GSD patients may need to be specifically tailored to the patient population. While these few studies are compelling, the broader community of patients living with IEMs managed with diet has yet to be examined and guidance for metabolic providers is lacking.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study screened patients with IEMs treated with dietary management for eating disorders and characterized their symptoms. We accomplished this by offering participants two validated questionnaires, the SCOFF survey and the Eating Pathology Symptoms Inventory (EPSI), and by collecting individual patient perspectives.\u0026nbsp;\u003c/p\u003e"},{"header":"II.\tMethods ","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy participants were recruited from the Mount Sinai Program for Inherited Metabolic Diseases in New York, New York, USA. Eligible patients were actively followed by the clinic, had an IEM managed with diet, and were 16 years of age or older. Patients with intellectual disability impairing their ability to consent and/or comprehend the study questionnaires, pregnant patients, non-English speakers, and patients perceived to be unfit to participate by the study team were excluded. Medical records were reviewed to determine participant eligibility and to collect patient demographics following the consenting process. Demographic information included age, sex assigned at birth, gender identity, height, weight, BMI, race/ethnicity, metabolic disorder, diet prescription, ICD-10 codes, and concomitant medications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study procedures were approved by the Mount Sinai Institutional Review Board (IRB 21-01385). Recruitment was conducted by approaching eligible participants in the clinic with a flyer or remotely with telephone calls and emails. Participants or legal guardians were prompted to review and e-sign the consent form. An assent form was required for minors. Participants were prompted to answer questions for 2 validated questionnaires (see “Measures” below). An optional open-ended text box was presented for additional comments in response to the questionnaires. After completion, participants were directed to an optional resources and referrals page, which gave contact information for the Mount Sinai Eating and Weight Disorders Program, and they were emailed a $10 Amazon gift card for their time.\u003c/p\u003e\n\u003cp\u003eASSESSMENT TOOLS\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSCOFF Questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SCOFF questionnaire is a validated self-report screening tool that for eating disorders, consisting of five “yes” or “no” questions.\u003csup\u003e15,16\u003c/sup\u003e “SCOFF” is an acronym for the 5 questions asked, remembered with the mnemonic “Sick, Control, One-Stone, Fat, Food.” For example, “S” represents the word “sick” in the question, “Do you make yourself sick because you feel uncomfortably full?” Other items inquire about loss of control overeating, weight loss, feeling fat, and feelings of a food-dominated life. Two or more “yes” answers qualify as a positive screening.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Eating Pathology Symptoms Inventory (EPSI)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Eating Pathology Symptoms Inventory (EPSI) is a validated self-report questionnaire used to characterize eating disorder pathology.\u003csup\u003e17,18\u003c/sup\u003e The EPSI is composed of 45 statements. Participants rate each using a 5-point Likert scale (0 = Never, 1 = Rarely, 2 = Sometimes, 3 = Often, 4 = Very Often) to report how often the statement applied to them over the preceding 4 weeks. The EPSI contains 8 subscales: Body Dissatisfaction, Binge Eating, Cognitive Restraint, Purging, Restriction, Excessive Exercise, Negative Attitudes towards Obesity, and Muscle Building. Each subscale has a different number of corresponding items, ranging from 3 to 8, resulting in total possible scores ranging from 12 to 32 between subscales. A modified EPSI was utilized for the purpose of the IEM patient population, changing three items: 1. “I used protein supplements” became “I used protein supplements \u003cem\u003ethat were not prescribed to me\u003c/em\u003e,” 2. “I made myself vomit in order to lose weight” became “I made myself vomit in order to lose weight \u003cem\u003eor to adhere to my metabolic diet\u003c/em\u003e,” and 3, “I used muscle building supplements” became “I used muscle building supplements \u003cem\u003ethat were not prescribed to me\u003c/em\u003e.”\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore potential associations among variables such as age, gender, BMI, etc. and a positive screening on the SCOFF survey, we used logistic regression modeling. Variables were first analyzed univariately by the student t-test for continuous variables and the Fisher's exact test for discrete data. For the multivariable analysis, variables with a \u003cem\u003ep\u003c/em\u003e value \u0026lt; 0.25 were tested in a logistic regression analysis model. Odds ratios and associated 95% confidence intervals were then generated by exponentiating the beta coefficients (slope estimates) from this equation. For all statistical analysis, data was analyzed using the SAS System software 9.4 (SAS Institute, Inc., Cary, N.C.).\u003c/p\u003e"},{"header":" III. Results ","content":"\u003cp\u003e\u003cstrong\u003eDemographics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFifty-two patients were enrolled in the study. Of the 52 subjects, 51 subjects completed both the SCOFF and the EPSI questionnaires; one participant only completed the SCOFF. Nineteen of the participants filled out responses in the optional open-ended text box. Participant demographics are shown in Table 1. Twenty-seven participants identified as female (52%), twenty-three as male (44%), and two identified as gender queer (4%). There were nine IEMs represented in the study population. Most participants had phenylketonuria, or PKU (\u003cem\u003en\u003c/em\u003e = 34, 65%). Other represented IEMs included glycogen storage disease type 1a, or GSD1a (\u003cem\u003en\u003c/em\u003e = 8, 15%), maple syrup urine disease, or MSUD (\u003cem\u003en\u003c/em\u003e = 3, 6%), ornithine transcarbamylase deficiency, or OTC (\u003cem\u003en\u003c/em\u003e = 2, 4%), homocystinuria (\u003cem\u003en\u003c/em\u003e = 1, 2%), multiple acyl-Coa dehydrogenase deficiency (\u003cem\u003en\u003c/em\u003e = 1, 2%), Citrin deficiency (\u003cem\u003en\u003c/em\u003e = 1, 2%), carbamoyl phosphate synthetase I deficiency, or CPS I (\u003cem\u003en\u003c/em\u003e = 1, 2%), and carnitine palmitoyltransferase II deficiency, or CPT 2 (\u003cem\u003en\u003c/em\u003e = 1, 2%). Of the participants, only 4% (\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 2) were minors aged 16-17 years, while the majority were adults under the age of 50 years old (n = 49, 94%). One participant was over 50 years old (\u003cem\u003en\u003c/em\u003e = 1, 2%). The mean age was 29 years. Participant BMI ranged from 16.5 to 40.9 kg/m\u003csup\u003e2\u003c/sup\u003e, with a mean BMI of 27.5 kg/m\u003csup\u003e2\u003c/sup\u003e. Based on CDC BMI classifications, 4% (\u003cem\u003en\u003c/em\u003e = 2) of the participants were underweight, 38% (\u003cem\u003en\u003c/em\u003e = 20) were normal weight, 58% were overweight or obese (\u003cem\u003en\u003c/em\u003e = 30). Most participants were on a protein-restricted diet (\u003cem\u003en\u003c/em\u003e = 41, 79%), while 17% (\u003cem\u003en\u003c/em\u003e = 9) were on a low-carbohydrate diet and 6% (\u003cem\u003en\u003c/em\u003e = 3) were on a fat-restricted diet. Some patients were on a combination of these dietary prescriptions. More than half of participants (\u003cem\u003en\u003c/em\u003e = 29, 56%) used both medical food and formula, while 31% (\u003cem\u003en\u003c/em\u003e = 16) only used medical formula.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSCOFF Results \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SCOFF screen positive rate was 35% (\u003cem\u003en\u003c/em\u003e = 18). This indicates that over a third of the participants responded ‘yes’ to two or more SCOFF questions and were identified as having a likely eating disorder. Of the male participants, 26% (\u003cem\u003en\u003c/em\u003e = 6) screened positive, while 37% (\u003cem\u003en\u003c/em\u003e = 10) of the females and 100% (\u003cem\u003en\u003c/em\u003e = 2) of those identifying as gender queer screened positive (see Table 2). The average age of those who screened positive was 28.6 years old, and the average BMI was 29.6 kg/m\u003csup\u003e2\u003c/sup\u003e. There was no statistically significant difference in screen positive rates based on sex assigned at birth, gender identity, age, or BMI.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOf the five SCOFF items, nearly half (\u003cem\u003en\u003c/em\u003e = 24, 46%) of participants responded 'yes' to the item, “Would you say food dominates your life?” The question with the next highest response rate was, “Do you worry you have lost control over how much you eat?,” with about 30% (\u003cem\u003en\u003c/em\u003e = 16) responding 'yes'. The complete SCOFF item breakdown is seen in Table 3 and Figure 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe SCOFF screen positive rate among our subjects was found to be significantly greater (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001) than the reported population norm, which is about 10% among a multiethnic UK community sample.\u003csup\u003e16\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEPSI Results\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean score for each of the eight EPSI subscales was calculated for the study population. Study population EPSI characteristics, including number of items per subscale, total possible score, score range, mean, and standard deviation are presented in Table 3. The only subscale where a participant responded “very often” (ie, a score of 4) for each item was Restricting.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSCOFF positivity was associated with binge eating (OR = 1.24, \u003cem\u003ep\u003c/em\u003e=0.002) and cognitive restraint (OR = 1.24, \u003cem\u003ep\u003c/em\u003e=0.002). When compared to population norms, study subjects were significantly more likely to demonstrate binge eating, restrictive behaviors, excessive exercise, and negative attitudes towards obesity.\u003csup\u003e18\u003c/sup\u003e Study subjects were significantly less likely to report purging and muscle building behaviors. (Figure 3; Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEating disorder symptom pathology, as characterized by the EPSI, was consistent with the open-ended text box responses received. Patterns of restriction were seen by several participants. One noted, “At one point as a teenager I stopped eating food entirely, only surviving on the protein replacement tablets prescribed to me.” Responses explicitly mentioning purging were also seen by several participants. One stated, “I no longer make myself throw up, but I did consistently for about a year” while another participant said, “Recovered from Bulimia, used to (10 years ago) routinely purge after eating. I have related my difficult relationship with food heavily to my childhood growing up with PKU.”\u003c/p\u003e"},{"header":"IV.\tDiscussion","content":"\u003cp\u003eThis study screened young adult and adult patients with IEM for EDs and characterized their pathologies using two validated screening tools, the SCOFF and EPSI. The results suggest that there is a significantly higher prevalence of eating disorders among individuals with IEM treated with diet, with our population three times more likely to screen positive for an ED compared to a population norm. Study participants were significantly more likely to demonstrate binge eating, restrictive behaviors, excessive exercise, and negative attitudes towards obesity when compared to a community sample, whereas they were less likely to report purging and muscle building behaviors. Our study is the largest of its kind to-date and included patients from the widest variety of IEMs thus far in the literature.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study had several important limitations. Our cohort size was small, particularly among individual disease groups, limiting the statistical power to detect associations between survey responses and diagnosis. The SCOFF is a screening rather than a diagnostic instrument, thus true prevalence could not be determined. In addition, neither the SCOFF nor the EPSI have been validated in the IEM population. Although the SCOFF was modified to increase its relevance to this population, a more tailored assessment battery may more accurately characterize eating disorder risk in our population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings underscore the need for standardized approaches to diagnosing and treating EDs in this medically complex population. The high screen positive rate on the SCOFF among \u0026nbsp;individuals with IEMs managed with diet raises significant clinical concern about our ability to effectively manage comorbid EDs and IEMs. Metabolic diets are essential to prevent metabolic decompensation and/or chronic accumulation of toxic metabolites. Both restrictive and excessive intake pose risk for injury in this population. Binge eating behaviors may result in excessive intake of offending metabolites, while restriction poses a risk of catabolism and further metabolic instability. Thus, the development of eating disorders may substantially complicate IEM management, highlight the importance of early recognition and intervention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther work must be done to validate the use of the SCOFF and EPSI in patients with IEMs. Screening of pediatric populations is also a critical next step, as EDs may begin to present earlier in childhood. As we expand our understanding of EDs in IEMs managed with diet, we must also determine targeted modes of therapy for EDs in this population. Earlier identification and treatment is crucial to overall patient outcomes and could reduce morbidity and mortality for our vulnerable patients with IEMs.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThis study was performed in line with the principles of the declaration of Helsinki. Ethics and research governance approval were obtained from the Mount Sinai Institutional Review Board (IRB 21-01385).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions:\u003c/strong\u003e ML, CC, and MB made significant contributions to the conception and design of the study, analysis, interpretation of data, drafting and revision of the manuscript. CD made significant contributions to the conception and design of the study as well as revision of the manuscript. IG, JW, SD, MM, CS, and LE made contributions to the conception of the study, recruitment of participants, and revision of the manuscript. All authors read and approved the final manuscript. AW worked on analysis and interpretation of data. TH made significant contributions to the conception and design of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e We are grateful for all of the families and patients who agreed to participate in the study. Thank you to the entire Mount Sinai Program for Inherited Metabolic Diseases faculty and staff for supporting this important work.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmerican Psychiatric Association, American Psychiatric Association, eds. \u003cem\u003eDiagnostic and Statistical Manual of Mental Disorders: DSM-5\u003c/em\u003e. 5th ed. American Psychiatric Association; 2013.\u003c/li\u003e\n\u003cli\u003eFeltner C, Peat C, Reddy S, et al. Screening for Eating Disorders in Adolescents and Adults: Evidence Report and Systematic Review for the US Preventive Services Task Force. \u003cem\u003eJAMA\u003c/em\u003e. 2022;327(11):1068. doi:10.1001/jama.2022.1807\u003c/li\u003e\n\u003cli\u003eAttia E, Walsh BT. Eating Disorders: A Review. \u003cem\u003eJAMA\u003c/em\u003e. 2025;333(14):1242. doi:10.1001/jama.2025.0132\u003c/li\u003e\n\u003cli\u003eSil\u0026eacute;n Y, Keski-Rahkonen A. Worldwide prevalence of DSM-5 eating disorders among young people. \u003cem\u003eCurr Opin Psychiatry\u003c/em\u003e. 2022;35(6):362-371. doi:10.1097/yco.0000000000000818\u003c/li\u003e\n\u003cli\u003eBryant E, Spielman K, Le A, et al. Screening, assessment and diagnosis in the eating disorders: findings from a rapid review. \u003cem\u003eJ Eat Disord\u003c/em\u003e. 2022;10(1). doi:10.1186/s40337-022-00597-8\u003c/li\u003e\n\u003cli\u003eQuick VM, Byrd-Bredbenner C, Neumark-Sztainer D. Chronic Illness and Disordered Eating: A Discussion of the Literature. \u003cem\u003eAdv Nutr\u003c/em\u003e. 2013;4(3):277-286. doi:10.3945/an.112.003608\u003c/li\u003e\n\u003cli\u003eAvila JT, Park K, Golden NH. Eating disorders in adolescents with chronic gastrointestinal and endocrine diseases. \u003cem\u003eLancet Child Adolesc Health\u003c/em\u003e. 2019;3(3):181-189. doi:10.1016/s2352-4642(18)30386-9\u003c/li\u003e\n\u003cli\u003eKumar MM. Eating Disorders in Youth with Chronic Health Conditions: Clinical Strategies for Early Recognition and Prevention. \u003cem\u003eNutrients\u003c/em\u003e. 2023;15(17):3672. doi:10.3390/nu15173672\u003c/li\u003e\n\u003cli\u003eKrug I, Liu S, Portingale J, et al. A meta-analysis of mortality rates in eating disorders: An update of the literature from 2010 to 2024. \u003cem\u003eClin Psychol Rev\u003c/em\u003e. 2025;116:102547. doi:10.1016/j.cpr.2025.102547\u003c/li\u003e\n\u003cli\u003eBernstein LE, Rohr F, Helm JR, eds. \u003cem\u003eNutrition Management of Inherited Metabolic Diseases: Lessons from Metabolic University\u003c/em\u003e. Springer; 2015. doi:10.1007/978-3-319-14621-8\u003c/li\u003e\n\u003cli\u003eFord S, O\u0026rsquo;Driscoll M, MacDonald A. Living with Phenylketonuria: Lessons from the PKU community. \u003cem\u003eMol Genet Metab Rep\u003c/em\u003e. 2018;17:57-63. doi:10.1016/j.ymgmr.2018.10.002\u003c/li\u003e\n\u003cli\u003eBilder DA, Kobori JA, Cohen-Pfeffer JL, Johnson EM, Jurecki ER, Grant ML. Neuropsychiatric comorbidities in adults with phenylketonuria: A retrospective cohort study. \u003cem\u003eMol Genet Metab\u003c/em\u003e. 2017;121(1):1-8. doi:10.1016/j.ymgme.2017.03.002\u003c/li\u003e\n\u003cli\u003eLuu S, Breunig T, Drilias N, Kuhl A, Scott Schwoerer J, Cody P. A Survey of Eating Attitudes and Behaviors in Adolescents and Adults With Phenylalanine Hydroxylase Deficiency. \u003cem\u003eWMJ Off Publ State Med Soc Wis\u003c/em\u003e. 2020;119(1):37-43.\u003c/li\u003e\n\u003cli\u003eDisordered Eating and Body Esteem Among Individuals with Glycogen Storage Disease. In: \u003cem\u003eJIMD Reports\u003c/em\u003e. Springer Berlin Heidelberg; 2014:23-29. doi:10.1007/8904_2014_359\u003c/li\u003e\n\u003cli\u003eMorgan JF, Reid F, Lacey JH. The SCOFF questionnaire: assessment of a new screening tool for eating disorders. \u003cem\u003eBMJ\u003c/em\u003e. 1999;319(7223):1467-1468. doi:10.1136/bmj.319.7223.1467\u003c/li\u003e\n\u003cli\u003eSolmi F, Hatch SL, Hotopf M, Treasure J, Micali N. Validation of the SCOFF questionnaire for eating disorders in a multiethnic general population sample. \u003cem\u003eInt J Eat Disord\u003c/em\u003e. 2015;48(3):312-316. doi:10.1002/eat.22373\u003c/li\u003e\n\u003cli\u003eForbush KT, Hagan KE, Kite BA, Chapa DAN, Bohrer BK, Gould SR. Understanding eating disorders within internalizing psychopathology: A novel transdiagnostic, hierarchical-dimensional model. \u003cem\u003eCompr Psychiatry\u003c/em\u003e. 2017;79:40-52. doi:10.1016/j.comppsych.2017.06.009\u003c/li\u003e\n\u003cli\u003eConiglio KA, Becker KR, Tabri N, et al. Factorial integrity and validation of the Eating Pathology Symptoms Inventory (EPSI). \u003cem\u003eEat Behav\u003c/em\u003e. 2018;31:1-7. doi:10.1016/j.eatbeh.2018.07.004\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Participant Demographics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003eFrequency (\u003cem\u003en\u003c/em\u003e = 52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003ePercent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eAge (years):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003e16-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003e18-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003e30-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003e50+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eGender Queer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eUnderweight (\u0026lt;18.5 kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eNormal Weight (18.5-25 kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eOverweight (25-30 kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eObesity (\u0026gt;30 kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eMetabolic Disorder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eGlycogen storage disease type 1a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eMaple syrup urine disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eOrnithine transcarbamylase deficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003ePhenylketonuria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eOther*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eDiet Prescription\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eLow Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eLow Fat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eLow Carbohydrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eUse of Medical Food and Formula\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 248px;\"\u003e\n \u003cp\u003eUse of Medical Formula Only\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 154px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 202px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 604px;\"\u003e\n \u003cp\u003e*Carbamoyl phosphate synthetase I deficiency, carnitine palmitoyltransferase II deficiency,\u003c/p\u003e\n \u003cp\u003ecitrin deficiency, homocystinuria, multiple acyl-Coa dehydrogenase deficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e SCOFF Screening Results Demographics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"483\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCOFF Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNegative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e6 (26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e17 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e10 (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e17 (63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003eGender queer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003eTotal Population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e18 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e34 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003eM (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003eM (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e28.61 (9.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e29.79 (7.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 260px;\"\u003e\n \u003cp\u003eBMI (kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 123px;\"\u003e\n \u003cp\u003e29.57 (5.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 100px;\"\u003e\n \u003cp\u003e26.51 (6.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eLegend:\u0026nbsp;\u003c/strong\u003eSCOFF screen positive is defined as \u0026ge; 2 yes responses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e SCOFF Item Breakdown and Total Screen Positive Rate\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"521\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 521px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCOFF Item Breakdown\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 252px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 408px;\"\u003e\n \u003cp\u003eS- Do you make yourself Sick because you feel uncomfortably full?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e7 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 408px;\"\u003e\n \u003cp\u003eC- Do you worry you have lost Control over how much you eat?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e16 (31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 408px;\"\u003e\n \u003cp\u003eO- Have you recently lost more than One stone in a three- month period?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e7 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 408px;\"\u003e\n \u003cp\u003eF- Do you believe yourself to be Fat when others say you are too thin?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e13 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 408px;\"\u003e\n \u003cp\u003eF- Would you say Food dominates your life?\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e24 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 408px;\"\u003e\n \u003cp\u003eTotal Screen Positive (\u0026ge; 2 yes responses)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003e18 (35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003eEPSI Characteristics and Comparison to Population Norms\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"714\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEPSI Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eNumber of Items\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003eTotal Possible Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eScore Range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eStudy Mean (SD) n=51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cspan lang=\"EN\"\u003eCommunity Mean (SD)\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003en= 341 \u003csup\u003e18\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eBody dissatisfaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10.8 (6.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10.8 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10.3 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.65799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eBinge eating\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10.22 (7.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10.2 (7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e7.8 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.01614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eCognitive restraint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.55 (2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.6 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.0 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.22542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003ePurging\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.73 (3.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.7 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.2 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eRestricting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e8.67 (5.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e8.7 (5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3.3 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eExcessive exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e7.82 (4.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e7.8 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e6.3 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.04518\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eNegative attitudes towards obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.73 (4.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.7 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 182px;\"\u003e\n \u003cp\u003eMuscle building\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.88 (2.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.9 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4.8 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.00542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv id=\"_com_1\" language=\"JavaScript\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Inborn errors of metabolism, eating disorder, nutrition, screening, comorbidities","lastPublishedDoi":"10.21203/rs.3.rs-8483533/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8483533/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background\n\nLifelong restrictive diets are a mainstay of management for many inborn errors of metabolism (IEMs). The experience of metabolic care providers suggests a high prevalence of eating disorders among these patients; however, this has not been well characterized. This study applied validated tools to screen patients for eating disorders and to characterize their symptom pathologies. Patients aged 16 years and older on prescription diets at the Program for Inherited Metabolic Diseases at the Icahn School of Medicine at Mount Sinai were recruited, and patient demographics were collected through medical record review. All participants were given 2 assessment tools: the SCOFF questionnaire, a 5-question screen for a possible eating disorder, and a modified Eating Pathology Symptoms Inventory (EPSI), a 45-item Likert-scaled questionnaire characterizing eating disorder pathology.\n\nResults\n\nFifty-two subjects were enrolled, and 51 completed both surveys. 27 subjects identified as female (52%), 23 as male (44%), and two as genderqueer (4%). Ages ranged from 16-50 years old. The most common diagnosis was Phenylketonuria (n=34, 65%), followed by glycogen storage disease type 1a (n= 8, 15%). Most patients were on a low-protein diet (n=41, 79%), 17% (n=9) were on a low-carbohydrate diet, and 6% (n=3) were on a low-fat diet. The SCOFF screen positive rate was 35%, indicating that over one third of the participants have a potential eating disorder, which is significantly greater than population norms of 10.1% (p\u0026lt;0.001). EPSI results revealed that our participants were significantly more likely to demonstrate binge eating, restrictive behaviors, excessive exercise, and negative attitudes towards obesity when compared to population norms.\n\nConclusion\n\nThis study demonstrates a significantly increased prevalence of likely eating disorders among patients with IEM, about three times that of the general population. Metabolic providers should be aware of this risk to their patients, as eating disorders can impact metabolic control and adherence to diet, while also causing significant psychological distress to patients with these rare disorders. Steps must be taken to create a standardized approach to screen patients with IEM in clinic and streamline access to specialized care for eating disorders.","manuscriptTitle":"Prevalence and Characterization of Eating Disorders among Patients with Inborn Errors of Metabolism Managed with Diet","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-10 13:14:59","doi":"10.21203/rs.3.rs-8483533/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-03-10T09:12:58+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-04T08:47:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-02T18:11:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2025-12-31T10:57:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fc6fc62d-921b-48db-a433-305d813ba098","owner":[],"postedDate":"March 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T12:39:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-10 13:14:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8483533","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8483533","identity":"rs-8483533","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}