Epidemiology of eating disorders: population, prevalence, disease burden and quality of life informing public policy in Australia—a rapid review
Journal of Eating Disorders volume 11, Article number: 23 (2023)
Understanding of the epidemiology and health burden of eating disorders has progressed significantly in the last 2 decades. It was considered one of seven key areas to inform the Australian Government commissioned National Eating Disorder Research and Translation Strategy 2021–2031, as emerging research had highlighted a rise in eating disorder prevalence and worsening burden-of-illness. The aim of this review was to better understand the global epidemiology and impact of eating disorders to inform policy decision-making.
Using a systematic Rapid Review methodology, ScienceDirect, PubMed and Medline (Ovid) were searched for peer-reviewed studies published between 2009 and 2021. Clear inclusion criteria were developed in consultation with experts in the field. Purposive sampling of literature was conducted, which predominately focused on higher-level evidence (meta-analyses, systematic reviews, and large epidemiological studies), synthesised, and narratively analysed.
135 studies were deemed eligible for inclusion in this review (N = 1324). Prevalence estimates varied. Global Lifetime prevalence of any eating disorder ranged from 0.74 to 2.2% in males, and 2.58–8.4% in females. Australian 3-month point-prevalence of broadly defined disorders was around 16% in females. Eating disorders appeared more prevalent in young people and adolescents, particularly females (in Australia: eating disorders ~ 22.2%; disordered eating ~ 25.7%). Limited evidence was found on sex, sexuality and gender diverse (LGBTQI +) individuals, particularly males, who had a six-fold increase in prevalence compared to the general male population, with increased illness impact. Similarly, limited evidence on First Australian’s (Aboriginal and Torres Strait Islander) suggests prevalence rates similar to non-Indigenous Australians. No prevalence studies were identified specifically assessing culturally and linguistically diverse populations. Global disease burden of any eating disorder was 43.4 age-standardised disability-adjusted-life-years per 100,000; increasing by 9.4% between 2007 and 2017. Australian’s total economic cost was estimated at $84 billion from years-of-life lost due to disability and death, and annual lost earnings ~ $1.646 billion.”
There is no doubt that eating disorder prevalence and impact are on the rise, particularly in at-risk and understudied populations. Much of the evidence came from female-only samples, and Western, high-income countries which more readily have access to specialised services. Future research should examine more representative samples. There is an urgent need for more refined epidemiological methods to better understand these complex illnesses over time, to guide health policy and development-of-care.
Plain English summary
Our understanding of the prevalence and impact of eating disorders has improved significantly over the past 20-years. Research highlights that rates of eating disorders are increasing. To inform the development of the Eating Disorder Research and Translation Strategy 2021–2031 this review aimed to better understand the global change in prevalence and impact of eating disorders to inform policy decision-making.
Three scholarly databases were systematically searched for related research published between 2009 and 2021. Searches identified 135 studies which met our inclusion criteria. Estimates in lifetime eating disorder prevalence varied from 2.58 to 8.4% in women and girls. Findings indicated that eating disorders appeared more prevalent in young people and adolescents, particularly young women, while sexuality diverse (LGBTQI +) individuals were six-times more likely to have an eating disorder compared to the general male population. The little research suggests moderate to high prevalence of eating disorders in First Australian peoples, Australia’s spending on eating disorders was estimated at ~ $84 billion due to disability or death. There is no doubt that eating disorder prevalence and impact are on the rise. Future research should include more diverse populations to increase estimate accuracy and improve care for all.
The epidemiology of eating disorders (EDs) has advanced in recent years to encompass both the ‘core’ well-specified EDs, namely Anorexia Nervosa (AN; ICD-11 Code: 6B80), Bulimia Nervosa (BN; ICD-11 Code: 6B81) and Binge Eating Disorder (BED; ICD-11 Code: 6B82) but also the spectrum of Other Specified (ICD-11 Code: 6B8Y) and Unspecified (ICD-11 Code: 6B8Z) Feeding and Eating Disorders (OSFED and UFED) and Avoidant Restrictive Food Intake Disorder or ARFID (ICD-11 Code: 6B83) . Nevertheless, AN, BN and BED continue to have the largest evidence base and are commonly reported together in prevalence studies. BED and ARFID were only introduced as standalone disorders in the 2013 fifth edition of the Diagnostic and Statistical Manual of Mental Disorders [1, 2]. Prior to the DSM-5, BED (ICD-11 Code: 6B82) was described as a subtype of Eating Disorder Not Otherwise Specified (EDNOS) [1, 3]. Other Specified Feeding and Eating Disorders (OSFED; ICD-11 Code: 6B8Y) as defined in the DSM-5 include Atypical AN (A-AN); Subthreshold BN (S-BN); Subthreshold BED (S-BED); Night Eating Syndrome (NES), and Purging disorder (PD) .
The understanding of the population distribution and community burden of EDs has shifted notably in the last 2 decades. No longer can it be said that EDs are a problem only for young women from the developed world, a perception dating from the times of Bruch, who wrote that anorexia nervosa (AN) “… affects young and healthy girls who have been raised in privileged, even luxurious circumstances” . There is a growing body of evidence that EDs and their related behaviours are prevalent amongst peoples from lower-income groups, non-Western cultures, and of diverse gender [5, 6, 7, 8]. Alongside this is research indicating a rise in prevalence and global burden of EDs . In consideration of this, the prevalence and burden of EDs was considered one of seven key areas to inform the Australian Federal Government’s commissioning of The Australian Eating Disorder Research and Translation Strategy (AEDRTS) that aimed to identify strategic priorities and targets for building research capacity and outputs in Australia .
EDs are often chronic in nature and typically have an early age of onset with periods of recovery and relapse across the lifespan [11, 12]. There is substantial evidence that almost all first-time cases of well-specified EDs occur before the ages of 20 to 30 [11, 13, 14]. Therefore, the measured prevalence rates between age groups vary significantly. The highest prevalence rates are observed in children and adolescents. However, there is emerging evidence that prevalence of well-specified EDs is increasing among older adults .
The present paper is one of a series of Rapid Reviews, with the focus of the current paper on the epidemiology of EDs, specifically their prevalence and incidence, sociodemographic and ethnic distribution, and disease burden and impact on quality of life. The rapid reviews featured in this series, were conducted to guide the AEDRTS, and were completed over 2019–2021, in parallel and synergy with a multi-layered, multi-phased nation-wide co-designed strategy development process. Thus, the current paper aims to better understand the global epidemiology and impact of eating disorders to inform policy decision-making.
The Australian Government funded the InsideOut Institute for Eating Disorders (IOI) to develop the AEDRTS 2021–2031  in partnership with state and national stakeholders including clinicians, service providers, researchers, and experts by lived experience (encompassing consumers and families/carers). Developed through a 2-year national consultation and collaboration process, the strategy provides a roadmap to establishing EDs as national research priority and is the first disorder-specific strategy to be developed in consultation with the National Mental Health Commission. To inform the strategy, IOI commissioned Healthcare Management Advisors (HMA) to conduct a series of Rapid Reviews (RRs) to assess the current research base across the full spectrum of EDs; including knowledge gaps in ED (1) epidemiology; (2) risk factors; (3) comorbidities and medical complications; (4) screening and diagnosis; (5) prevention and early intervention; (6) psychotherapies; (7) models of care; (8) pharmacotherapies and (9) outcomes. The current paper presents the findings related to the epidemiology of EDs specifically on population trends and incidence, prevalence, disease burden and quality of life.
A RR protocol  was utilised to synthesise evidence in order to provide timely guidance to public policy and decision-making . This approach has been adopted by several leading health organisations including the World Health Organisation  and the Canadian Agency for Drugs and Technologies in Health Rapid Response Service , to build a strong evidence base in a timely and accelerated manner, without compromising quality. A RR is not designed to be as comprehensive as a systematic review—it is purposive rather than exhaustive and provides actionable evidence to guide health policy .
The RR is a narrative synthesis and sought to adhere to the PRISMA guidelines . It is divided by topic area and presented as a series of papers. Three research databases were searched: ScienceDirect, PubMed and Ovid/Medline. Included studies were published between 2009 and 2021, in English, and conducted within Western healthcare systems or health systems comparable to Australia in terms of structure and resourcing. Purposive sampling focused on high-level evidence studies such as: meta-analyses; systematic reviews; moderately sized randomised controlled studies (RCTs) (n > 50); moderately sized controlled-cohort studies (n > 50), and population studies (n > 500). Grey literature, such as clinical or practice guidelines, protocol papers (without results) and Masters’ theses or dissertations, was excluded. Instrument validation studies and studies commenting on the current Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for EDs were also excluded as they were not seen to be relevant to the patient-care focus of the review. Other sources included the personal libraries of authors, which yielded four additional studies (Fig. 1). This was conducted in line with the PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews .
Full methodological details including eligibility criteria, search strategy and terms, consort diagram, and data analysis are published in a separate protocol paper, which included a total of 1320 studies . Data from included studies relating to Epidemiology are presented in the current review.
Study characteristics and quality overview of included studies
The search identified 135 papers (Table 1) related to the epidemiology of EDs, of which four were meta-analyses of ED global prevalence, including in non-western populations [9, 24, 25, 26]. One systematic review was identified that provided prevalence ranges from reviewed studies . The search also found 31 primary studies of prevalence which are summarised in Additional file 1: Table S1 (range of population measures for EDs) and Additional file 1: Table S2 (trial features). Findings comprised a wide range of studies conducted in both community-based samples as well as clinical samples. Thus, the estimates derived in this RR show a wide variance in reported prevalence and incidence rates. Other factors contributing to the varied ranges reported include different methods of measurement (e.g., self-report, diagnostic interviews or formal diagnoses obtained through health system registries) and study designs.
Sampled populations were from predominately developed Western countries, with a majority of studies (N = 179) coming from the United States of America (n = 40, 22.3%), Europe (n = 87, 48.6%), and Australia (n = 11, 6.1%). Figure 2 presents a breakdown of included studies by country.
Diversity of study design and quality considerations
Additional file 1: Table S1 highlights that, as may be expected, studies that used self-report to identify cases reported higher prevalence and those that employed interviews demonstrate more consistent prevalence rates. Of the included reviews, Dahlgren et al.  presented prevalence across design types examining studies that used a 2-stage design, interview and self-report data. Galmiche et al.  commented that although the majority (51%) of included studies in their meta-analyses (shown in Table 2) did not present pooled data by study design, the majority had used an interview assessment. Notably, 13% used the Structured Clinical Interview for DSM Disorders (SCID); 12% the Composite International Diagnostic Interview (CIDI); and 11% the Eating Disorder Examination. Furthermore, changes to diagnostic criteria have contributed to shifting prevalence rates even within the same study population.
Notwithstanding the variability in the incidence and prevalence of different EDs in the Australian and global population, it is clear that EDs have a significant effect on the health and quality of life of a wide range of individuals across all demographic categories. Evidence presented in this RR is by life stage (“children and young people” and “adults and older people”) to allow for more direct comparison between study populations. We also present evidence (or lack thereof) for specific population cohorts of interest including well-specified EDs in males, Aboriginal and Torres Strait Islander people, and among the LGBTQI + community. No studies could be identified that reported on the prevalence of well-specified EDs in the culturally and linguistically diverse (CALD) communities of Australia. It is particularly important to consider these populations, as observed longitudinal trends from 1997 to 2010 suggest that patients presenting to ED services are increasingly male and non-Caucasian .
Ages of participants included in studies were generally consistent across studies, including children and adolescents from the age of 11 to 19 or 20. Exceptions were two cohorts, one from Finland (Nagl et al.) where participants were aged 14 to 24, and the other from the US (Rozzell et al.) where participants were significantly younger, aged 9 and 10 [108, 118].
Incidence and prevalence
Most information on incidence is derived from clinical registries and surveillance samples and needs to be interpreted in the context of the age range of the sample. A longitudinal Swedish study (n = 286,232) reported a peak age of onset between 15 and17 years, with an incidence rate for all EDs, of 698/100,000 years in females and 55/100,000 years in males . A longitudinal registry study of older adolescents in Denmark (n = 966,141) reported peak ED incidence between 16 and 20 years with a rate of 7.84/10,000 years for AN; the peak age of onset was younger in men than women for both AN (ICD-11 Code: 6B80) and BN (ICD-11 Code: 6B81) . In younger children and adolescents, the peak mean age of ED onset has been reported to be between the ages of 12 and 13 years old for ARFID (ICD-11 Code: 6B83) and for the other main EDs [52, 81, 110].
In a 14-month national surveillance study of UK children ≤ 13 years old, Nicholls et al.  reported an incidence rate of 3.1 per 100,000 person yearsFootnote 1 (PYs). Further analysis by age group found that incidence peaked between ages 12 and 13 years, with an incidence rate of 9.5 per 100,000 PY; this led the authors to conclude that mean age of ED onset may be getting younger overtime in the UK . Similarly, in Canadian children (n = 2453, aged 5–12 years) the highest incidence rate of restrictive type EDs was in girls aged 10–12 years (9.4/100,000 PYs) . The lowest incidence rate was in boys aged 5–9 years (0.4/100,000 person years) . An Australian national paediatric surveillance sample also reported a younger age of onset as low as 8, and even 5, years old . Additionally, this latter study found that approximately one-quarter of all new cases were male; furthermore, no significant differences were found between boys and girls in terms of age of onset, symptomology, family history or outcome .
Table 2 summarises the prevalence estimates from the four meta-analyses and systematic reviews [9, 24, 25, 26]. It should be noted that the meta-analyses by Kessler et al.  and Erskine and Whiteford  reported on BED (ICD-11 Code: 6B82) prevalence alone and not in the context of other ED. Only one study—by Galmiche et al. —provided a more thorough estimate of global ED prevalence. Studies by Kessler et al.  and Erskine and Whiteford  both used data from World Health Organization (WHO) Mental Health Surveys and analysed these data against national income categories as defined by the World Bank. While findings from Kessler et al.  suggest that prevalence of BN (ICD-11 Code: 6B81) and BED (ICD-11 Code: 6B82) is higher in upper-middle-income countries than in high-income and lower-middle-income countries, it is limited by the inclusion of far fewer samples from lower-middle-income countries (n = 1) and upper-middle-income countries (n = 3) compared with high-income countries (n = 10) .
Consistent with the findings from Kessler et al.  a subsequent meta-analysis conducted by Erskine and Whiteford  found no significant differences in prevalence of BED between high-income countries and lower-middle-income countries [24, 26]. Nonetheless, the authors did note that populations from the lower-middle-income countries included in the sample had higher obesity relative to other lower-middle-income countries, potentially contributing to the increased detection of BED (ICD-11 Code: 6B82) in these populations . Reported 12-month prevalenceFootnote 2 for both genders were consistent between the Kessler et al.  and Erskine and Whiteford  meta-analyses: 0.7% and 0.8%, respectively.
A systematic review of ED prevalence (as defined by the DSM-5 in non-clinical samples) in high-income countries conducted by Dahlgren et al.  reported prevalence ranges for AN (ICD-11 Code: 6B80), BN (ICD-11 Code: 6B81), BED (ICD-11 Code: 6B82), OSFED (ICD-11 Code: 6B8Y) and UFED (ICD-11 Code: 6B8Z) (see Additional file 1: Table S1). Dahlgren et al.  noted that updates to diagnostic criteria contained in the DSM-5 resulted in an increase in individuals meeting criteria for a ‘full-threshold’ disorder. This in turn increased the prevalence of AN, BN, and BED and significantly decreased the prevalence of OSFED (previously EDNOS) . Removal of the amenorrhea criterion increased diagnostic sensitivity for cases of male AN, which is also likely to have contributed to the increase in prevalence of AN following the introduction of the DSM-5 [27, 149]. It was noted that the lower limits of prevalence ranges reported in Table 2 tend to reflect studies of all-male samples while the upper limits of ranges tend to reflect all-female samples.
Prevalence of recently specified or reclassified disorders
EDNOS, OSFED and UFED
There is a much smaller evidence base for less well specified EDs compared with AN (ICD-11 Code: 6B80), BN (ICD-11 Code: 6B81), and BED (ICD-11 Code: 6B82). Table 3 shows prevalence of OSFED (ICD-11 Code: 6B8Y) and UFED (ICED-11 Code: 6B8Z) observed in all community-based studies included in this RR. Findings indicated a considerable variation across OSFED/EDNOS community prevalence studies. General population prevalence studies in adolescents (n = 9244) and adults (n = 879) conducted in the US found the lifetime prevalence of EDNOS to be 4.8% in adults and 4.6% in adolescents . Even with changes to diagnostic criteria, OSFED and UFED are still common EDs.
Little evidence was available on ARFID (ICD-11 Code: 6B83) in the general population, and prevalence is generally considered uncertain . Hay et al.  found a 3-month prevalence of 0.3% for ARFID in the Australian population. In a Swiss study involving 1444 children aged 8 to 13, the prevalence of ARFID features was 3.2% (n = 46) . However, Kurz et al.  noted these children may not meet full DSM-5 criteria . The remaining studies assessing prevalence of ARFID were conducted within North American clinical samples (Canada and the US) and none were conducted in adults. Additional file 1: Table S2 provides a summary of prevalence rates ascertained in clinical settings.
Night Eating Syndrome (NES)
In contrast to other types of OSFED (ICD-11 Code: 6B8Y), the recently defined NES has a limited body of evidence relating to its prevalence. It has been found to range from 0.7% in adult men  and up to 4.9% in adolescent boys  (See Additional file 1: Table S3 for a summary of prevalence rates from the four NES studies reviewed).
In this section we present research with a primary focus on the prevalence of the main EDs.
Aboriginal and Torres Strait Islander individuals
The RR identified limited data pertinent to EDs in Aboriginal and Torres Strait Islander people [39, 71]. Within a sample of 3047 adults randomly selected to participate in a South Australian household survey, there were a total of 159 Aboriginal and Torres Strait Islander respondents. Results indicated that ED symptoms within this group, particularly rates of binge eating, were higher than in non-indigenous people (17% compared with 6.9% for non-Indigenous people) . A smaller prevalence study corroborated findings that EDs were very prevalent in First Australians, and often associated with increased binge-eating frequency, lower Mental Health Related Quality of Life (MHQoL), and higher levels of overvaluation of body shape and weight compared to other Australian’s .
Children and adolescents
Due to their early age of onset, there has been considerable attention to EDs in children and adolescents. As mentioned above, there is also evidence suggesting the age of onset for EDs is getting younger [112, 151]. Data from national surveys has found that ED behaviours, including rarely studied behaviours such as chew and spit (ChSp), are widespread among Australian adolescents [150, 152]. In one study more than one-quarter (n = 628, 25.7%) of participants (aged between 13 and 17 years old) were assessed as having disordered eating, while 11% (n = 267) had a suspected ED and 0.9% had a lifetime ED . The prevalence of fear of weight gain and overvaluation of body weight were also high at 14.3% to 25.7% in 3270 Australians aged 14 and 15 . However, the prevalence of binge eating, and compensatory behaviours has been reported to be low (0.5% and 3.7%) .
Compared with adult and older populations, more comprehensive evidence exists for the prevalence of newly defined DSM-5 disorders in samples of children and adolescents. Lifetime prevalence of any ED has been estimated to be 6.7% in children and adolescents . Table 5 gives a summary of point prevalence estimates from community-based samples across six studies: BN (ICD-11 Code: 6B81) is one of the most prevalent of the well-specified disorders [9, 30, 150]. A prospective longitudinal study of adolescents by Allen et al.  found a significant increase in ED prevalence between ages 14 (8.5%) and 17 (15.2%) and remaining steady to age 20 (15.2%). Age 17 was the peak age for all ED diagnoses (not necessarily onset), except for BED (ICD-11 Code: 6B82), which peaked at age 20 (4.1%) .
The studies by Mitchison et al. and Allen et al. were conducted in Australian populations, with cross-sectional and longitudinal cohort designs, respectively. Mitchison et al.  tracked adolescents aged from 11 to 19, while Allen et al.  measured point prevalence at ages 14, 17 and 20. Notably, rates reported by Mitchison et al.  were classified as ‘probable’ and the need to apply the clinical significance criterionFootnote 3 when assessing population-based ED prevalence was emphasised . Strict application of this criterion reduced prevalence of any ED from 22.2% in the sample population to 13.6%, still considerably higher than rates reported in Canada and the Netherlands [60, 123]. Researchers argued that, without application of this criterion, ED prevalence may be overestimated in population studies for most EDs, aside from AN (ICD-11 Code: 6B80) and atypical AN. Percentages presented in Table 5 are those reported by Mitchison et al.  without clinical significance criteria applied, to allow for comparison with other prevalence studies. Despite the relatively high prevalence in the Australian compared to the Canadian sample (n = 3020)  and the Dutch sample (n = 2230) [60, 123] the Australian’s data were comparable to findings from a German study (n = 1654)  (see Table 5).
Adults and older people
Several studies suggest that EDs are becoming more prevalent across a range of socio-demographic profiles [9, 24, 73, 99]. Studies measuring trends in ED behaviours (as distinct from diagnosis) in the Australian population across 1995 (n = 3001), 1998 (n = 3010), 2005 (n = 3047) and 2008 (n = 3034), indicated that both binge eating and strict dieting had increased significantly in men and women, particularly binge eating in individuals > 45 years old [48, 99]. Significant increases in purging behaviours were also observed among people aged over 45 years and in males of any age . Measurement of objective binge eatingFootnote 4 episodes over a 17-year period (1998 to 2015) in a large sample of Australians (n = 15,126) found 3-month prevalence increased from 2.7% (n = 80) to 13% (n = 390), and twice weekly objectively measured binge eating increased from 1.1% (n = 33) to 5.3% (n = 158) [47, 101].
Increased engagement in ED behaviours within the population could potentially translate to an increase in individuals diagnosed with EDs, especially those characterised by bingeing and purging. This is reflected in 3-month prevalence estimates of well-specified disorders in Australians aged 15 and over in two studies—Hay et al.  (n = 6041) and Hay et al.  (n = 5737) [72, 73]. Both studies used a cross-sectional design, with the earlier sample measuring ED levels in 2008 and 2009 and the later study in 2014 and 2015.
Middle aged and older people
Few community studies have reported EDs in populations over the age of 40 years, and even fewer in older men. This is despite findings by Ackard et al.  that the prevalence in people middle-aged or older has increased over time. Point prevalence studies indicate that, while EDs are less common among older individuals, they continue to be a health concern for this group . Additionally, cross-sectional studies have identified individuals aged 45 to 54 as being at particular risk of experiencing ED symptomology .
Evidence presented in a study of women aged between 40 and 60 in Austria (n = 436) by Mangweth-Matzek et al.  has suggested that menopause, like puberty, may be a period of risk for ED onset . Research also suggests that in older adults with EDs, comorbidities are more frequent, ED symptoms are less severe, and purging and self-harm are less frequent [37, 53, 98]. Older adults with an ED typically experienced early onset and developed a persistent ED with no period of remission [33, 97].
There are inconsistent findings in regard to how the prevalence of ED in older adults compares (i.e., is less than) to the prevalence in younger age groups [37, 53, 98]. A review of community samples by Baker and Runfola  found the lifetime prevalence of EDs in women aged ≥ 45 to be 0.17% for AN (ICD-11 Code: 6B80), 0.21% for BN (ICD-11 Code: 6B81), 0.61% for BED (ICD-11 Code: 6B82), and 4% for any ED. A further systematic review of EDs in people aged over 50 years found AN (ICD-11 Code: 6B80) to be the most common ED among older individuals seeking treatment, with one study reporting that AN accounted for 81% (n = 39), BN (ICD-11 Code: 6B81) in 10% (n = 5) of cases, BED (ICD-11 Code: 6B82) 2% (n = 1) and EDNOS (DSM criteria used), 6% (n = 3) [86, 103, 133, 136].
A distinctive study with a large two-phase retrospective longitudinal cohort study design involving 5658 women living in the UK, indicated that 15.3% (n = 332) had met the diagnostic criteria for an ED by the age of 40. Weighted 12-month prevalence of any ED in the cohort was 3.6% (n = 108) . Prevalence rates by ED diagnosis and subtype are summarised in Table 6. This study also found the median age of onset for AN-restricting type to be 16 years (lowest), while women with BED had the highest median age of onset at 26 . This finding is consistent with existing evidence that AN (ICD-11 Code: 6B80) has the youngest age of onset followed by BN (ICD-11 Code: 6B81) and then BED (ICD-11 Code: 6B82). Rates of AN in this cohort are considerably higher than in other community-based populations, while reported prevalence estimates for BED were lower .
Men and LGBTQI + samples
There is growing recognition of the impact of ED in males. It is estimated that one in four paediatric patients in Australia presenting to an ED service are male, as are one in three in the UK . Few large-scale studies have focused on male prevalence in community-based populations. In their review of several Western countries, Murray et al.  reported community point prevalence of AN (0.1–0.3%), BN (0.1–1.6%), and BED (0.3–2.0%) in men.
LGBTQI + communities
Research indicates that EDs have higher prevalence in LGBTQI + individuals. EDs are more typically associated with individuals identifying as male within the LGBTQI + community, although there is growing evidence that it also has a heightened impact on females in this group , and there is a small volume of emerging evidence on prevalence in other genders. A systematic review suggested that greater overall ED symptomology is displayed by sexual minority males, females, and transgender individuals compared with heterosexual males and females . A small study of transgender youth in Canada (n = 97) also found that risk of ED was higher among transgender males than in females, while both groups were more at risk than the general population .
Adolescence is a particularly risky time for ED development in LGBTQI + people . A study conducted in 46 schools (n = 2429) in the US found that gay males were 12.6 times more likely to engage in fasting, vomiting or taking pills to lose weight than heterosexual males, and 2.4 times more likely to exercise or eat less to lose weight. Bisexual females were two times more likely to report fasting, vomiting or taking pills than heterosexual females, but less likely than heterosexual females to exercise or eat less to lose weight . Similar trends in binge/purge behaviours among homosexual and bisexual males and females was also observed in a much larger US youth sample (n = 55,597) by Watson et al. . Watson et al. , in a separate study (n = 26,002), found that rates of diet pill use, vomiting and fasting among lesbian females was particularly prevalent in those aged 12 to 18 .
In an Australian and New Zealand sample, high rates of body and muscle dysmorphia were detected among gay and bisexual men (n = 2733), who are more likely to participate in anabolic steroid use to build muscle . Results from the UK (n = 5048), indicate that body dissatisfaction and dysfunctional eating behaviours in sexual minority males was up to 12.5 times higher than in heterosexual males by the age of 16 .
Meneguzzo et al.  reported that the prevalence of EDs in LGBTQI + women may be higher compared with rates reported in heterosexual women in the community. However, findings appear to be inconsistent and were not found for any particular ED diagnosis (i.e. AN, BN, or BED) . Only 7 of the 45 (16%) studies included in the synthesis reported on diagnostic status .
Disease burden and impact on quality of life
EDs represent a significant proportion of the global disease burden from psychiatric illnesses, with associated high levels of psychological stress and impairment, as well as a profound impact on physical health . A systematic analysis of data from 195 countries from 1990 to 2017 found that the global disease burden for any ED was 43.4 age-standardised disability adjusted life years (DALYs)Footnote 5 per 100,000. Between 2007 and 2017, global disease burden caused by EDs increased by 9.4%. AN (ICD-11 Code: 6B80) and BN (ICD-11 Code: 6B81) were the only EDs initially specified by the Global Burden of Disease Study 2017, at 9.5 and 33.8 age-standardised-DALYs per 100,000, respectively. Global disease burden attributed to AN (ICD-11 Code: 6B80) increased by 6.1% between 2007 and 2017, and for BN (ICD-11 Code: 6B81) the burden increased by 10.3% . This burden further doubled when BED (ICD-11 Code: 6B82) and OSFED (ICD-11 Code: 6B8Y) were counted as part of measuring burden (disability life adjusted years), in part due to the recognition of BED and OSFED in a large global study of burden of disease .
Erskine et al. , in their review of the 2013 Global Burden of Disease Study, highlight that much of the disease burden associated with EDs is experienced by females, with reported age-standardised-DALYs due to all EDs being over twice as high for females than for males . In AN, the difference was even more pronounced at over four times higher in females .
In Australian populations, investigation of disease burden attributable to more recently specified DSM-5 disorders indicated that individuals with BN (ICD-11 Code: 6B81) and ARFID (ICD-11 Code: 6B83) had more days out-of-roleFootnote 6 than individuals without an ED and for other ED diagnoses . Further, engaging in binge eating behaviours while not necessarily being diagnosed with an ED was also found to have an impact on daily functioning for Australians (n = 15,126). Mitchison et al.  found that participants who reported once or twice weekly objectively measured episodes of binge eating had higher role impairment than individuals who did not report objective binge eating. Observing 18-year trends, Mitchison et al.  also reported marked increases in binge eating within the Australian general population, potentially contributing to increased weight and poor physical health over time.
Two studies assessing the economic burden of EDs were identified. Agh et al. reviewed 22 studies relating to healthcare costs and economic burden associated with AN (ICD-11 Code: 6B80), BN (ICD-11 Code: 6B81) and BED (ICD-11 Code: 6B82) . They found that, while individuals with BED had a higher rate of service utilisation, including inpatient, outpatient and emergency care than healthy controls, levels were comparable to individuals with other psychiatric disorders. It was also noted that very few individuals sought help specifically for their ED, but did so for comorbid psychiatric conditions or for assistance with weight loss . Agh et al. reviewed the cost of services such as therapy, hospital care, diagnostic tests, and medications accessed by ED patients in the US (n = 14), the UK (n = 1), Canada (n = 1) and Germany (n = 5), including studies that measured costs from the perspective of the payer (consumer) (n = 15), hospital/health service (n = 3) or society (n = 3). A diagnosis of AN was associated with highest healthcare costs and longer periods of hospitalisation compared to other well-specified EDs . Estimated annual healthcare costs were reported in Euro (€) and converted to AUD ($) for EDs. Data from the analysis by Agh et al. indicated that the high costs associated with AN were due to longer periods of hospitalisation .
A recent study from the general population of South Australia estimated the total economic cost of all EDs was $AUD84 billion in 2018, from years of life lost due to disability and death, and annual loss of earnings accounted for $AUD1.646 billion. Furthermore, these lost earnings peaked for both males and females in the age group 35–44 years .
Quality of life impact
Individuals with EDs have been found to have lower Health Related Quality of Life (HRQoL) than the general population and individuals with other psychiatric disorders such as major depression . Research on the impact of ED behaviours indicated that HRQoL was equally impacted by a range of ED types, including binge eating, strict dieting, and purging. Distress relating to binge eating was associated with greater functional impairment and lower QoL in trends tracked from 1998 to 2015 in the Australian population . Among school-aged children in Austria (n = 3610), poorer HRQoL was found among females at high risk of ED, potentially indicating more severe symptomology in female adolescents .
A meta-analysis of seven studies conducted by Winkler et al.  comparing HRQoL between AN (ICD-11 Code: 6B80), BN (ICD-11 Code: 6B81), BED (ICD-11 Code: 6B82) and EDNOS found equally low HRQoL scores across all diagnostic groups with no significant differences between groups . However, researchers noted that this finding was from a limited pool of studies that use a range of HRQoL measures both specific to ED (Eating Disorder Quality of Life, EDQoL) and generic measures .
Extremely low BMI experienced by individuals with AN (ICD-11 Code: 6B80) is considered to have a substantial impact on their physical health. However, the egosyntonicity of symptoms may result in lower-than-expected levels of reported mental health impact. In contrast symptoms of BN (ICD-11 Code: 6B81) and BED (ICD-11 Code: 6B82) are experienced with high levels of associated psychological distress, hence individuals with BN and BED have been found to have lower HRQoL than individuals with AN [32, 93, 141].
In studies conducted in the Australian population, BN (ICD-11 Code: 6B81), BED (ICD-11 Code: 6B82), and ARFID (ICD-11 Code: 6B83) were associated with lower HRQoL (particularly lower mental health quality of life, MHQoL) compared with other ED diagnoses and individuals without ED. Australians with BED (ICD-11 Code: 6B82) were found to score lower than individuals with AN (ICD-11 Code: 6B80), BN (ICD-11 Code: 6B81), OSFED (ICD-11 Code: 6B8Y) and UFED (ICD-11 Code: 6B8Z) for mental and physical HRQoL . Compared with healthy Australian women (n = 232), a much higher proportion of women with EDs (n = 159) were assessed to have severe mental health impairment; at 29.8% versus 9.4% . Similar impairments to physical and mental HRQoL were observed among a sample of women in New Zealand (n = 214) with more frequent binge eating associated with lower QoL . Further, longitudinal observation of ED status and HRQoL in Australian women (n = 706) indicated a bi-directional relationship, whereby increasing ED symptomology leads to greater QoL impairment and conversely lower QoL contributes to ED severity over time .
Several studies have also reported poor HRQoL for ARFID (ICD-11 Code: 6B83) in young people (e.g. Krom et al.  and adults ). Krom et al.  found that patients aged 6 to 7 and 8 to 10 years with ARFID (n = 48), had significantly lower physical functioning (appetite, lungs, stomach and motor) and mental health (positive mood and liveliness). Psychosocial health and school functioning measures were also significantly lower in this group indicating that ARFID has a significant negative impact on QoL .
This RR presents a contemporary understanding of the epidemiology of EDs, their sociodemographic distribution, particularly across age and gender, and their comorbidity and burden. It guides the AEDRTS and policy as well as informing the field and Stakeholders more broadly.
Prevalence and incidence
Collectively, epidemiological evidence form this RR suggests that the incidence of EDs is increasing, while age of onset is decreasing. However, as incidence estimates come mainly from studies using registry or clinical data, they are likely underestimates as they only include cases that have been formally diagnosed by a health professional. For example, reported rates in the UK were considerably higher than incidence reported in Australian children aged between 5 and 13 . This variance may be due to differences in methodologies, as some Australian studies, such as that by Madden et al. , were predominantly reported from inpatient services with only a small proportion of outpatient services.
The RR found that EDs are a global and common phenomenon but only one meta-analysis  provided a comprehensive synthesis of epidemiology for all EDs, and there is a paucity of evidence regarding more recently specified disorders such as ARFID (ICD-11 Code: 6B83). Prevalence rates (Table 2) also varied considerably between studies most probably due to differences in study design and measures used to detect EDs. Treasure et al. [132, 157] argue that AN (ICD-11 Code: 6B80) prevalence is impacted by inconsistent use of strictly defined parameters relating to body mass index (BMI) limits, contributing to the variation. This was demonstrated by application of broad and strictly defined parameters for AN (ICD-11 Code: 6B80) to the same community-based samples of female adolescents. Application of strictly defined AN (ICD-11 Code: 6B80) parameters resulted in an observed lifetime prevalence range between 0.6 and 2.2%. However, using broadly defined AN (ICD-11 Code: 6B80) parameters in the same sample, ranges for lifetime prevalence increased to 1.7% to 4.3% .
With regards to prevalence for OSFED (ICD-11 Code: 6B8Y) disorders it is important to note that these appeared to be hierarchical in nature [9, 25, 27, 54]. That is, only one diagnosis assigned at a time, despite potential for overlap. Thus, individuals who were diagnosed with OSFED-PD (purging in the absence of binging) could also have met DSM-5 criteria for atypical AN. It should be noted also that some studies (such as Micali et al. ) did not specify purging for the purpose of weight and shape concerns. However, considering the measures used (EDDS, SCID-I, LIFE) it may be assumed that PD was derived in the context of EDs, where weight and shape concerns are present. The exact diagnostic boundaries between EDNOS/OSFED/UFED are often difficult to delineate, or diagnose, in non-clinical samples as it is dependent on how researchers define these broad categories, particularly as both the DSM and ICD do not outline strict criteria for these diagnostic categories.
Increases in BN (ICD-11 Code: 6B81) and BED (ICD-11 Code: 6B82) prevalence  over time could be attributed to the broader DSM-5 criteria, which reduced the number of required binge eating episodes from twice weekly in the DSM-IV to once weekly. Similarly, changes in the AN (ICD-11 Code: 6B80) diagnostic criteria to remove amenorrhea and vary the weight cut-off likely also play a role in rising prevalence data. Strict diagnostic criteria specified by the DSM-IV decreased BN (ICD-11 Code: 6B81) cases by half and BED (ICD-11 Code: 6B82) cases to less than half, bringing 3-month prevalence down to the same rate detected in the earlier 2005 South Australian study using once weekly criteria [73, 158]. This finding suggests that prevalence rates of BN (ICD-11 Code: 6B81) and BED (ICD-11 Code: 6B82) in the Australian population in 2005 were comparable to rates reported in the 2015 study but not detected using DSM-IV criteria. Further analysis of prevalence rates by participant characteristics found several key differences between studies from 2005 to 2015. In 2015 studies, the median age of participants with an ED was significantly younger than the group without an ED, particularly in AN (ICD-11 Code: 6B80) and BN (ICD-11 Code: 6B81). Further, BED (ICD-11 Code: 6B8) (57% female) and subthreshold BED (S-BED; 55% female) had the lowest sex (female-to-male) ratio of all reported EDs, and BED, S-BED and BN were found to be associated with high BMI .
Prevalence: child and adolescence
Reported lifetime and point prevalence rates varied considerably across studies [76, 108, 129]. However, despite limitations across included studies, literature indicates that less well-specified EDs may be more prevalent in children and adolescents than adult populations [30, 60, 75, 123, 124, 150]. Whilst the prevalence of well-specified EDs (AN, BN and BED) in Australian female adolescents was generally consistent, conflicting prevalence rates were observed in studies of males for BN (1.8%  compared to 0.7% ), and BED (0.2%  compared to 1.2% ).
Prevalence: males and LGBTQI +
The literature notes that males may preference different body types than females, typically presenting with higher BMIs and a drive for muscularity instead of thinness (muscle dysmorphia versus body dysmorphia), as well as reporting less psychological distress relating to binge eating behaviours . These characteristics are more commonly associated with BN (ICD-11 Code: 6B81) and BED (ICD-11 Code: 6B82) and may reflect the relatively low prevalence of AN (ICD-11 Code: 6B80) in males [65, 115]. Males are also more likely to report overeating without loss of control while eating, commonly reported by females, resulting in a higher proportion of males with S-BED [103, 115] and a higher proportion of females diagnosed with full syndrome BED . It may be that binge eating presents differently in males and this warrants further investigation to ensure diagnostic criteria do not contain inherent bias and lead to an inaccurate estimation of prevalence.
Researchers have also observed that changes to diagnostic criteria from DSM-IV to DSM-5 resulted in apparent increases in the prevalence of EDs in females, although male prevalence was largely unchanged for the more common threshold and subthreshold EDs (e.g., AN, S-AN, S-BN). This may indicate that the diagnostic criteria remain largely female-centric even though ED symptomology and behaviours are relatively common among males [7, 43]. For example, Compte et al.  observed no difference in prevalence rates comparing DSM-IV and DSM-5 diagnosed EDs in a group of university-aged men (n = 472). All observed cases in males were subthreshold AN (S-AN) (0.9%, n = 4) and subthreshold BN (S-BN) (1.1%, n = 5) . However, in the same sample group, muscle dysmorphia was determined to occur in 7.0% of men , representing more than a six-fold increase in prevalence of eating pathology compared to other presentations in this illness category. This supports additional academic and clinical focus on ED in males given that clinical data has demonstrated that EDs have a considerable impact on males , accounting for 34% of all patients accessing ED services in one study .
There is a dearth of consistent epidemiological data on EDs in the LGBTQI + community. However, the evidence reviewed here suggests they may be a particularly vulnerable minority group for EDs and further research is needed .
This RR found high fiscal burden from EDs. For example, in a study modelling the cost-effectiveness of an AN prevention, the annual cost of treating an individual with AN (ICD-11 Code: 6B80) was estimated at up to $USD200,000 . This review however found variation in these costs across different countries; in Australia some data suggests a higher cost for BN (ICD-11 Code: 6B81) relative to AN (ICD-11 Code: 6B80) whereas in the US it is reversed, which may be related to the differences in health systems across the two countries. The high costs of care for individuals with AN (ICD-11 Code: 6B80) are associated with lengthy hospital stays, which in Australia are often partially or completed publicly funded, whereas in the US (where a significant proportion of studies have been conducted) hospital costs tend to be paid for by the individual receiving care or under their personal insurance [156, 159].
Quality of life
Disordered eating behaviour in general, and EDs in particular, have been consistently found to impact HRQoL in a variety of ways, in both young people and adults [10, 72, 73, 79, 141, 152, 160]. Variance in findings across diagnostic groups should be addressed in future research by using specific EDQoL measures [32, 141], as generic measures and assessment tools are inefficient at detecting the unique features that impact QoL in EDs . The insensitivity of self-report HRQoL measures to the egosyntonic nature of AN (ICD-11 Code: 6B80) has also been suggested as a possible reason for conflicting findings [79, 141]—people with ED report different sorts of impacts of illness and often do not experience the traditional sort of impacts or fail to find them as distressing. Despite this, a number of studies have found a lower HRQoL in AN (ICD-11 Code: 6B80) as compared to BN (ICD-11 Code: 6B8) and EDNOS (OSFED), noting that individuals with AN (regardless of subtype or age ) experience greater difficulty with social life, relationships and physical mobility  and recognising the close association between AN (ICD-11 Code: 6B80) and suicidality. While outside the date of current review’s eligibility criteria  it should also be mentioned that a very recent study by Appolinario et al.  reported diverse and severe physical health impacts of BN (ICD-11 Code: 6B81) and BED (ICD-11 Code: 6B82), even when controlling for participants’ BMI. This corroborates similar findings of medical comorbidity in individuals with BED as noted by Udo and Grilo , albeit, they did not control for BMI.
Strength and limitations of included studies
A limitation of this RR is that the vast majority of the available epidemiological literature came from Western, educated, industrialized, rich, and democratic (WEIRD) countries, which more readily have access to specialised care and services. Further, much of the evidence base for the ED literature is restricted to younger and female-only samples [9, 24, 26]. Other limitations include wide variability in methods to ascertain ED cases, including application of different diagnostic criteria and use of self-report versus interview instruments. Nonetheless, the breadth of netted literature that met inclusion criteria provided a comprehensive overview of the topic and allowed for trends and themes to be observed, highlighting both trends and gaps in the epidemiological understanding of EDs.
Strengths and limitations of current review
Use of a rapid review methodology allowed for a timely synthesis of the current evidence base as it relates to the epidemiology of EDs. Nonetheless, as the RR was commissioned by the Australian Government to inform the focus of EDs in Australia, it did not address indigenous population in other countries. Similarly, more recently specified disorders (such as ARFID (ICD-11 Code: 6B83) and OSFED (ICD-11 Code: 6B8Y)) were not equally represented when compared to other established ED diagnoses, namely AN (ICD-11 Code: 6B80), BN (ICD-11 Code: 6B81), and BED (ICD-11 Code: 6B82). Representation of countries outside of Australia may have also impacted findings, however this was partially offset by predominantly focusing on WEIRD countries with similar sociodemographic features as Australia—allowing for some findings to be generalised.
Overall clinical implications
EDs are common, and likely increasing in incidence and prevalence in both younger and older populations. They occur across all sociodemographic groups and may be increasing in minority populations. Thus, all services at all levels need to be prepared to identify and offer care for people with EDs. There is a need to develop culturally informed and appropriate assessments and interventions for broader demographic groups, such as men, the LGBTIQ + community and Indigenous peoples.
An Australian nationally representative epidemiologic survey as well as research in economically developing nations, gender and culturally and linguistically populations are needed. There is also a need for greater use of a two-stage design and interview approach in prevalence studies, to increase accurate case identification and inclusion of OSFED (ICD-11 Code: 6B8Y) and UFED (ICD-11 Code: 6B8Z) in study methods. That also includes measurement of burden to improve the Global Burden of Disease (WHO) and other estimates, particularly those used in policy making around health, and the provision of care.
EDs are common, global, present in all age and gender groups and are associated with high fiscal and health burden. There is an urgent need to refine and harmonise epidemiological methods to improve consistency and accuracy in case estimates, for example the development of international agreements on assessment instruments amongst eating disorder organisations and publications. Publication policies can also be implemented to ensure all papers consider and present data regarding demographic diversity of participants to support greater research in minority populations and non-WEIRD populations. Such strategies would enable a better understanding of the distribution of EDs over time, plan services and guide health care policy.
Availability of data and materials
Not applicable—all citations provided.
Person years are a unit of measurement that considers the length of time (e.g., 1 year) and number of individuals enrolled in a study. For example, 10 individuals enrolled in a 10-year study would equate to 100 person years.
Proportion of a population who have had an ED in the past 12 months.
ED symptoms that cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.
Sense of loss of control overeating within a specific timeframe during which the amount of food consumed is larger than what most people would eat under similar circumstances.
Number of potential ‘healthy’ years of life lost to premature death or years lived with disability due a specific disease or disorder.
Days for which a person is completely unable to work or carry out normal activities because of a health problem.
Australian Eating Disorder Research and Translation Strategy
Avoidant Restrictive Food Intake Disorder
Binge Eating Disorder (BED)
Body Mass Index
Bulimia Nervosa (BN)
Culturally and Linguistically Diverse
Disability Adjusted Life Years
Diagnostic and Statistical Manual of Mental Disorders—fifth edition
Eating Disorder not Otherwise Specified
Eating Disorder Quality of Life
Health Management Australia
Health Related Quality of Life
International Classification of Diseases
- LGBTQI +:
Lesbian, Gay, Bisexual, Transgender, Queer, Intersex +
Mental Health Quality of Life
Night Eating Syndrome
Other Specified Feeding and Eating Disorders
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
Quality of Life
Unspecified Feeding and Eating Disorders
Western, Educated, Industrialized, Rich and Democratic (countries)
World Health Organisation
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The authors would like to thank and acknowledge the hard work of Healthcare Management Advisors (HMA) who were commissioned to undertake the Rapid Review. Additionally, the authors would like to thank all members of the consortium and consultation committees for their advice, input, and considerations during the development process. Further, a special thank you to the carers, consumers and lived experience consultants that provided input to the development of the Rapid Review and wider national Eating Disorders Research & Translation Strategy. Finally, thank you to the Australian Government—Department of Health for their support of the current project.
National Eating Disorder Research Consortium Members (alphabetical order of surname) [*indicates named authors]
Phillip Aouad: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Sarah Barakat: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Robert Boakes: School of Psychology, Faculty of Science, University of Sydney, NSW Australia; Leah Brennan: School of Psychology and Public Health, La Trobe University, Victoria, Australia; Emma Bryant*: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Susan Byrne: School of Psychology, Western Australia, Perth, Australia; Belinda Caldwell: Eating Disorders Victoria, Victoria, Australia; Shannon Calvert: Perth, Western Australia, Australia; Bronny Carroll: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; David Castle: Medicine, Dentistry and Health Sciences, University of Melbourne, Victoria, Australia; Ian Caterson: School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia; Belinda Chelius: Eating Disorders Queensland, Brisbane, Queensland, Australia; Lyn Chiem: Sydney Local Health District, New South Wales Health, Sydney, Australia; Simon Clarke: Westmead Hospital, Sydney, New South Wales, Australia; Janet Conti: Translational Health Research Institute, Western Sydney University, Sydney NSW Australia; Lexi Crouch: Brisbane, Queensland, Australia; Genevieve Dammery: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Natasha Dzajkovski: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Jasmine Fardouly: School of Psychology, University of New South Wales, Sydney, New South Wales, Australia; John Feneley: New South Wales Health, New South Wales, Australia; Nasim Foroughi: Translational Health Research Institute, Western Sydney University, Sydney NSW Australia; Mathew Fuller-Tyszkiewicz: School of Psychology, Faculty of Health, Deakin University, Victoria, Australia; Anthea Fursland: School of Population Health, Faculty of Health Sciences, Curtain University, Perth, Australia; Veronica Gonzalez-Arce: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Bethanie Gouldthorp: Hollywood Clinic, Ramsay Health Care, Perth, Australia; Kelly Griffin: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Scott Griffiths: Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia; Ashlea Hambleton: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Amy Hannigan: Queensland Eating Disorder Service, Brisbane, Queensland, Australia; Mel Hart: Hunter New England Local Health District, New South Wales, Australia; Susan Hart: St Vincent’s Hospital Network Local Health District, Sydney, New South Wales, Australia; Phillipa Hay: Translational Health Research Institute, Western Sydney University, Sydney NSW Australia; Ian Hickie: Brain and Mind Centre, University of Sydney, Sydney, Australia; Francis Kay-Lambkin: School of Medicine and Public Health, University of Newcastle, New South Wales, Australia; Ross King: School of Psychology, Faculty of Health, Deakin University, Victoria, Australia; Michael Kohn: Westmead Hospital, University of Sydney, Australia; Eyza Koreshe: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Isabel Krug: Melbourne School of Psychological Sciences, University of Melbourne, Victoria, Australia; Anvi Li*: Healthcare Management Advisors, Victoria, Australia; Jake Linardon: School of Psychology, Faculty of Health, Deakin University, Victoria, Australia; Randall Long: College of Medicine and Public Health, Flinders University, South Australia, Australia; Amanda Long: Exchange Consultancy, Redlynch, New South Wales, Australia; Sloane Madden: Eating Disorders Service, Children’s Hospital at Westmead, Sydney, New South Wales, Australia; Sarah Maguire*: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Danielle Maloney*: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Peta Marks: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Siân McLean: School of Psychology and Public Health, La Trobe University, Victoria, Australia; Thy Meddick: Clinical Excellence Queensland, Mental Health Alcohol and Other Drugs Branch, Brisbane, Queensland, Australia; Jane Miskovic-Wheatley*: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Deborah Mitchison: Translational Health Research Institute, Western Sydney University, Sydney NSW Australia; Richard O’Kearney: College of Health & Medicine, Australian National University, Australian Capital Territory, Australia; Roger Paterson: ADHD and BED Integrated Clinic, Melbourne, Victoria, Australia; Susan Paxton: La Trobe University, Department of Psychology and Counselling, Victoria, Australia; Melissa Pehlivan*: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Genevieve Pepin: School of Health & Social Development, Faculty of Health, Deakin University, Geelong, Victoria, Australia; Andrea Phillipou: Swinburne Anorexia Nervosa (SWAN) Research Group, Centre for Mental Health, School of Health Sciences, Swinburne University, Victoria, Australia; Judith Piccone: Children's Health Queensland Hospital and Health Service, Brisbane, Queensland, Australia; Rebecca Pinkus: School of Psychology, Faculty of Science, University of Sydney, NSW Australia; Bronwyn Raykos: Centre for Clinical Interventions, Western Australia Health, Perth, Western Australia, Australia; Paul Rhodes: School of Psychology, Faculty of Science, University of Sydney, NSW Australia; Elizabeth Rieger: College of Health & Medicine, Australian National University, Australian Capital Territory, Australia; Karen Rockett: New South Wales Health, New South Wales, Australia; Sarah Rodan: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Janice Russell: Central Clinical School Brain & Mind Research Institute, University of Sydney, New South Wales, Sydney; Haley Russell: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Fiona Salter: Ramsay Health Care, Perth, Australia; Susan Sawyer: Department of Paediatrics, The University of Melbourne, Australia; Beth Shelton: National Eating Disorders Collaboration, Victoria, Australia; Urvashnee Singh: The Hollywood Clinic Hollywood Private Hospital, Ramsey Health, Perth, Australia; Sophie Smith: Sydney, New South Wales, Australia; Evelyn Smith: Translational Health Research Institute, Western Sydney University, Sydney NSW Australia; Karen Spielman: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Sarah Squire: The Butterfly Foundation, Sydney, Australia; Juliette Thomson: The Butterfly Foundation, Sydney, Australia; Marika Tiggemann: College of Education, Psychology and Social Work, Flinders University, South Australia, Australia; Stephen Touyz*: InsideOut Institute, Central Clinical School, Faculty of Medicine and Health, University of Sydney, NSW Australia; Ranjani Utpala: The Butterfly Foundation, Sydney, Australia; Lenny Vartanian: School of Psychology, University of New South Wales, Sydney, New South Wales, Australia; Andrew Wallis: Eating Disorder Service, The Sydney Children’s Hospital Network, Westmead Campus, Sydney, Australia; Warren Ward: Department of Psychiatry, University of Queensland, Brisbane, Australia; Sarah Wells: University of Tasmania, Tasmania, Australia; Eleanor Wertheim: School of Psychology and Public Health, La Trobe University, Victoria, Australia; Simon Wilksch: College of Education, Psychology and Social Work, Flinders University, South Australia, Australia; Michelle Williams: Royal Hobart, Tasmanian Health Service, Tasmania, Australia.
The RR was in-part funded by the Australian Government Department of Health in partnership with other national and jurisdictional stakeholders. As the organisation responsible for overseeing the National Eating Disorder Research & Translation Strategy, InsideOut Institute commissioned Healthcare Management Advisors to undertake the RR as part of a larger, ongoing, project. Role of Funder: The funder was not directly involved in informing the development of the current review.
Ethical approval and consent to participate
Consent for publication
ST receives royalties from Hogrefe and Huber, McGraw Hill and Taylor and Francis for published books/book chapters. He has received honoraria from the Takeda Group of Companies for consultative work, public speaking engagements and commissioned reports. He has chaired their Clinical Advisory Committee for Binge Eating Disorder. He is the Editor in Chief of the Journal of Eating Disorders. ST is a committee member of the National Eating Disorders Collaboration as well as the Technical Advisory Group for Eating Disorders. AL undertook work on this RR while employed by HMA. A/Prof Sarah Maguire, Dr. Jane Miskovic-Wheatley and Dr. Phillip Aouad are guest editors of the special issue “Improving the future by understanding the present: evidence reviews for the field of eating disorders.”
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Hay, P., Aouad, P., Le, A. et al. Epidemiology of eating disorders: population, prevalence, disease burden and quality of life informing public policy in Australia—a rapid review. J Eat Disord 11, 23 (2023). https://doi.org/10.1186/s40337-023-00738-7
- Burden of disease
- Eating disorders