Table 3 Cross-sectional studies
From: Avoidant/restrictive food intake disorder (ARFID) in New Zealand and Australia: a scoping review
Author and year (Country) | Study Population focus | Study focus | Setting | Methodology | Key data collected | Sample n | Gender (Age) | Ethnicity | Summary results |
|---|---|---|---|---|---|---|---|---|---|
Acharya (NSW, Australia) [41] J Gastroenterol Hepatol | Adult ED in-patients | Retrospectively characterise and report on adult patients admitted to inpatient refeeding in context of EDs | Multidisciplinary team (gastroenterology psychiatry specialised nursing dietetics social work) | Retrospective clinical data collation | Diagnosis, demographics, length of stay, type of refeeding (oral, nasogastric tube), BMI (admission/discharge), medical complications, Mental Health Act scheduling, and relapse and readmission rates | ARFID n = 2 Other ED n = 8 | 5 F (> 16y) | Not stated | All admissions had episodes of hypoglycaemia. The average change in BMI from admission to discharge was 1.7 kg/m2 but was -1.8 to 3.8 kg/m2 for patients with AN or ARFID |
Burt (Australia) [34] BMC Psychiatry | Aboriginal and Torres Strait Islanders (First Australians) | DSM-5 diagnostic threshold eating disorders prevalence | Epidemiology study | Face to face interviews Logistic regression | Mental HRQoL, BMI, questions adapted from the EDE, ARFID questions. First Australian status. Physical HRQoL, demographics | 92 | 53% F (mean = 36.49y) | First Australian | 27% of First Australian respondents had an eating disorder, significantly higher than for other Australians. 1 respondent endorsed ARFID |
Hay (SA, Australia) [7] J Eat Disord | Representative late adolescent/adult population sample | Assessing burden and HRQoL of EDs in Australian population | Epidemiology | Face-to-face survey interviews | Health Omnibus surveys [55]:(Demographics, DSM-5 ED features, functional impact on role performance, HRQoL, SF12v1 | 2014 = 2732 (9 ARFID) 2015 = 3005 (10 ARFID) | ARFID only: 2014 11% F 2015 50% F (≥ 15y, ARFID median = 46y) | Not stated | ARFID was reported in 1 in 300 people, was associated with poorer mental HRQoL (compared to non-ED participants) and significant functional impairments. Mean BMI was higher than for AN, but lower than no-ED |
Pinhas (Australia; Canada; UK) [29] Int J Eat Disord | Representative child population sample | Can latent class analysis (LCA) classify ED symptoms in children that can be mapped onto DSM-5 diagnoses, and are these consistent between countries | Paediatrics | Latent class analysis of clinician case details from online survey | Clinician-completed questionnaires on cases (socio-demographic information, diagnosis, comorbidity, management, and short-term outcomes) | N = 436 (Australia n = 70) 26/70 who clustered as “more consistent with ARFID” | 49% F (5-12y) | Not stated | LCA performed on eating symptoms clustered into 2-class model across all populations. Cluster 1 (74.6% of Australian sample) exhibited symptoms consistent with AN (DSM-IV TR). Cluster 2 was distinct from the AN group, and was more consistent with the DSM-5 category of ARFID |
Newport (New Zealand) [56] Thesis | Representative child population sample (NZ birth cohort (Growing Up In New Zealand (GUINZ)) | Exploring food intake and temperament of children aged 4.5y. Compared 'fussy eaters' vs. 'non-fussy' eaters | Epidemiology | Mother and Child Proxy Questionnaire completed in a face-to-face computer assisted personal interview | Socio-demographic data, child food intake (food frequency data (FFQ)), anthropometrics, Mother and Child Proxy Questionnaire (including child diet and nutrition, general health, motivation and emotion, and relationships) | 6156 | 48.6% F (49–68 months (mean = 53.95y, SD = 1.55) | European (60%) Māori (13.4%), Pacific (13.2%), Asian (12.1%), and Middle Eastern, Latin American, or African (1.4%) | Prevalence of severe fussy eating was 1.9% (increased to 2.8% when starchy vegetables were classified as grain food group rather than vegetable). Predictors of fussy eating included gender, temperament dimensions (Attention to change, Fear) and socio-economic status. Increased fussy eating was observed in males, children with higher levels of fear, lower levels of attention to change, or who lived in more deprived households |
Claudino (*Oceania; North America; South America, Asia; Africa; Europe) [52] BMC Med | Mental health professionals registered with WHO's Global Clinical Practice Network | Application of ICD-10 and ICD-11 diagnostic guidelines for FED to case vignettes – evaluate clinical utility of diagnostic guidelines | Psychiatry | Experimental vignette-based case-controlled | Diagnosis selection for vignettes, a set of questions related to clinical utility of the diagnostic guidelines (including ease of use, goodness of fit, and clarity) | 2288 total (Western Pacific – Oceania = 66 (2.9%)) | 56% male (mean = 44.52y, SD = 10.91) | Not stated | Respondents rated ICD-11 favourably with use of the “Extremely” category, for ‘ease of use’ (85% or respondents), ‘goodness of fit’ (88%), and ‘clarity and understandability’ (88.6%). Clinicians diagnosed AN correctly using both ICD-10 and ICD-11, however the ARFID vignette (as per ICD-11) resulted in multiple diagnoses using ICD-10 criteria which reduced with ICD-11 criteria |
Jackson (New Zealand) [47] Speech Lang Hear | Health professionals (speech-language therapist, dietitians and medical practitioners) working with children and feeding difficulties in New Zealand | Explored changes in perspective from 2013 to 2018 among health professional, regarding picky eating behaviour and the DSM-5 ARFID diagnosis | Speech-language therapy, Dietetics, General practice, paediatrics | Online survey, case vignette Qualitative content analysis | Respondent demographics, vignette diagnosis, open ended survey questions | 141 total (2013 = 73, 2018 = 68) | Not stated | Not stated | There was a continued lack of consensus for diagnosing children with ARFID in 2018 |
Le (South Australia, Australia) [35] Psychol Med | Representative samples of individuals aged 15 + years living in South Australia | Present Health state utility values (HSUV) for a broad range on DSM-5 EDs | Epidemiology | Face to face interviews Multiple linear regression models | HRQoL was assessed using SF-12, EDE, ARFID-specific questions assessing the presence and reasons for current food avoidance/restriction based on DSM-5 criteria for ARFID | 5609 total (ARFID = 13) | 2232 M 3355 F (15 + y (EDs mean = 40y No-ED mean = 48.8y)) | Not stated | HSUVs are used to determine quality-adjusted life years (or measure disease burden). The average HSUV was lowest in the ED threshold group (0.68, SD = 0.13), followed by the ARFID group (0.74, S.D. = 0.14) indicating high burden |
Selllbom (Dunedin, New Zealand) [57] Assessment | University population sample (non-clinical) | Hierarchical Taxonomy of Psychopathology (HiTOP) measurement subgroup—Results from phase 1: Developing scales for the somatoform spectrum and eating disorders | Psychopathology taxonomy | Exploratory factor analysis In-person study measure completion | Selected scales from the MMPI-2-RF, EDDS-DSM-5 | 550 | 115 M 433 F 1 Transgender 1 unreported (17-51y (mean = 19.76) | NZ European (73%). Other European (17%), New Zealand Māori (10%), Chinese, Pacific Islander, Indian and “other” also represented | 10- item scale for ARFID was developed. No large correlations between the ARFID scale and existing ED symptoms demonstrating discriminant validity of the scale. May help distinguish between non-weight phobic AN, and ARFID |