Skip to main content
Brazilian Journal of Psychiatry logoLink to Brazilian Journal of Psychiatry
. 2020 Sep 28;43(3):314–323. doi: 10.1590/1516-4446-2020-1099

Risk factors for eating disorders: an umbrella review of published meta-analyses

Marco Solmi 1,2,3,, Joaquim Radua 3,4,5, Brendon Stubbs 6,7,8, Valdo Ricca 9, Davide Moretti 9, Daniele Busatta 9, Andre F Carvalho 10,11, Elena Dragioti 12, Angela Favaro 1,2, Alessio Maria Monteleone 13, Jae Il Shin 14, Paolo Fusar-Poli 3,15,16, Giovanni Castellini 9
PMCID: PMC8136381  PMID: 32997075

Abstract

Objective:

To grade the evidence about risk factors for eating disorders (anorexia nervosa, bulimia nervosa, and binge eating disorder) with an umbrella review approach.

Methods:

This was a systematic review of observational studies on risk factors for eating disorders published in PubMed/PsycInfo/Embase until December 11th, 2019. We recalculated random-effect meta-analyses, heterogeneity, small-study effect, excess significance bias and 95% prediction intervals, grading significant evidence (p < 0.05) from convincing to weak according to established criteria. Quality was assessed with the Assessment of Multiple Systematic Reviews 2 (AMSTAR-2) tool.

Results:

Of 2,197 meta-analyses, nine were included, providing evidence on 50 risk factors, 29,272 subjects with eating disorders, and 1,679,385 controls. Although no association was supported by convincing evidence, highly suggestive evidence supported the association between childhood sexual abuse and bulimia nervosa (k = 29, 1,103 cases with eating disorders, 8,496 controls, OR, 2.73, 95%CI 1.96-3.79, p = 2.1 x 10-9, AMSTAR-2 moderate quality) and between appearance-related teasing victimization and any eating disorder (k = 10, 1,341 cases with eating disorders, 3,295 controls, OR 2.91, 95%CI 2.05-4.12, p = 1.8x10-9, AMSTAR-2 moderate quality). Suggestive, weak, or no evidence supported 11, 29, and 8 associations, respectively.

Conclusions:

The most credible evidence indicates that early traumatic and stressful events are risk factors for eating disorders. Larger collaborative prospective cohort studies are needed to identify risk factors for eating disorders, particularly anorexia nervosa.

Keywords: Eating disorders, anorexia nervosa, bulimia nervosa, binge eating disorder: umbrella review, systematic review, meta-analysis, risk factor, prevention

Introduction

Eating disorders (ED) are a complex group of psychiatric disorders characterized by psychopathology which results in pathological eating behaviors that can lead to medical complications.1 For example, people with anorexia nervosa (AN) are approximately five times more likely to die from any cause and eighteen times more likely to die from suicide than the general population.2,3 In addition, bulimia nervosa (BN) and binge eating disorders (BED) are associated with complications of vomiting, laxative abuse, and obesity, respectively.

ED outcomes have remained poor in recent decades, with high rates of chronicity,4-6 which could suggest a lack of understanding about the underlying pathophysiological mechanisms that lead to ED onset and persistence. For example, the lack of efficacious pharmacological interventions specifically for AN might be due to a relative lack of insight about the biological mechanisms underlying it.7-9 The fact that there is no clearly superior psychosocial intervention among a wide range of interventions for adults and adolescents with AN is also particularly concerning.10

Despite the poor mechanistic knowledge of ED, an extensive body of literature has investigated putative risk factors for ED, testing a wide range of environmental11-15 and genetic16-20 risk factors. However, the contrasting results of individual studies are frequently not confirmed in meta-analysis. A recent large collaborative genome-wide association study has shown that metabo-psychiatric genetic predisposition, specifically eight previously unidentified loci, might increase the risk of AN.21

Poor knowledge of the mechanistic processes that lead to ED and risk factors for ED might be one of the reasons why early ED intervention and prevention has been studied less than psychotic and other non-psychotic disorders.22,23 Despite preliminary evidence suggesting the potential efficacy of ED prevention, more evidence synthesis is needed,24,25 since the state of the art for evidence on interventions to prevent or delay ED onset seems to be relatively less explored than in other fields of psychiatry.26,27 Although the prevention of mental disorders, particularly psychosis, is being explored, it has only been partially implemented worldwide. The results so far have shown that the pre-assessment of risk should be improved to find subjects actually at risk of developing mental disorders.28-32 Since preventive interventions are not free from potential side effects, they must be performed only for individuals with an epidemiologically and clinically significant risk of any mental illness.33 Putative risk factors, whose associations have been inflated by biased results, must be replaced with convincing ones, as is being done for several other mental disorders, including schizophrenia,34,35 autism,36,37 depression,38 bipolar disorder,39 post-traumatic stress disorder,40 anxiety spectrum disorder and obsessive compulsive disorder.41 This a necessary step for finding individuals who might be at risk of ED and could thus benefit from preventive interventions.

Therefore, the aim of the present umbrella review, which graded evidence through a systematic review of meta-analyses, identified quantitative criteria based on additional statistical tests, and re-calculated each meta-analytic association, was to grade the available evidence on risk factors for ED, identifying those that should be targeted in ED prevention and considered when assessing a person with subthreshold symptoms.

Methods

A protocol for this study is publicly available on the Center for Open Science platform (https://osf.io/hu8yd/?view_only=269352b4b1e040bcb825f48b567032a4). We performed a systematic review, considering the Preferred Reporting Items for Systematic Reviews and Meta-analyses42 and the Meta-analysis of Observational Studies in Epidemiology guidelines.43

Search strategy and selection criteria

We searched the PubMed, PsycInfo and Embase databases (final search on December 11th, 2019) to identify systematic reviews with meta-analyses pooling longitudinal observational studies that examined any association between putative risk factors for ED, defined according to clinical records, any version of the DSM or ICD, or validated scales with cut-off points. The following keywords were used in PubMed (meta-analysis OR meta-analysis OR systematic review) AND (anorexia nervosa OR binge* OR bulimi* OR eating disorder*), and equivalent ones were used in PsycInfo and Embase. Two reviewers (DM, DB) independently searched the titles/abstracts for eligibility and assessed the full text of articles that passed this phase. A third reviewer (MS) resolved any conflicts. When more than one meta-analysis assessed the same risk factor, we only included the one with the most studies, as previously described.34,38,39,44,45 The exclusion criteria were: 1) meta-analyses of randomized controlled trials; 2) those published in languages other than English; 3) those that included cross-sectional studies from which no causal inference could be made; 4) systematic reviews without meta-analyses.

The same two investigators who independently performed the screening extracted the data in a predefined Excel spreadsheet. For each meta-analysis, we extracted the PMID/DOI, first author, publication year, population, risk factor, study design, ED type (AN, BN, BED, or mixed), number of included studies and total sample size to identify the largest meta-analysis. For each primary study in the largest meta-analyses, we recorded data on the first author, year of publication, study design, number of cases (subjects who developed ED), subjects who did not develop ED, effect size with 95% confidence intervals (95%CI), ED definition criteria, and study location. The methodological quality of each included meta-analysis was assessed with the Assessment of Multiple Systematic Reviews (AMSTAR) 2 tool (a recent update of AMSTAR,46 available at https://amstar.ca/Amstar-2.php) by the same two investigators.

Data analysis

For each association in each meta-analysis, we re-performed a random-effect meta-analysis that calculated the pooled effect size and the 95% confidence intervals.47 Heterogeneity was assessed with the I2 statistic.48 We calculated the 95% prediction intervals for the summary random effect sizes, which provide the possible range in which the effect sizes of future studies are expected to fall.49 We also tested for the presence of small-study effect bias,38,39,44,50 which was deemed to be present in cases of pooled estimates larger than the largest individual study, as well as publication bias (Egger’s regression asymmetry test [p ≤ 0.10]). Finally, we assessed excess significance bias by evaluating whether the observed number of studies with nominally statistically significant results (p ≤ 0.05) were different from the expected number of studies with statistically significant results (significance threshold set at p ≤ 0.10).51,52

Grading the evidence

The credibility of the meta-analyses was assessed according to stringent criteria based on previously published umbrella reviews.38,39,44,50,53 In brief, associations that presented nominally significant random-effects summary effect sizes (i.e., p < 0.05) were ranked as convincing, highly suggestive, suggestive, or weak evidence based on the number of events, the strength of the association, and the presence of several biases (criteria presented in Box 1). The quality of included meta-analyses was assessed with the AMSTAR-2 tool.

Box 1. Credibility assessment criteria for meta-analyses of observational studies.

Classification Criteria
Convincing evidence (Class I) 1. More than 1,000 cases
2. Significant summary associations (p < 10-6) per random-effects calculations
3. No evidence of small-study effects
4. No evidence of excess of significance bias
5. Prediction intervals not including the null value
6. Largest study nominally significant (p < 0.05)
7. Not large heterogeneity (i.e., I2 < 50%)
Highly suggestive evidence (Class II) 1. More than 1,000 cases
2. Significant summary associations (p < 10-6) per random-effects calculation
3. Largest nominally significant study (p < 0.05)
Suggestive evidence (Class III) 1. More than 1,000 cases
2. Significant summary associations (p < 10-3) according to random effect calculations
Weak evidence 1. All other associations with p < 0.05
Non-significant associations 1. All associations with p < 0.05

Results

Search

A flowchart of the search, selection and inclusion process is presented in Figure 1. Out of 2,197 articles screened at the title/abstract level, we assessed the full text of 45 publications. Of these, 36 were excluded for including only cross-sectional studies (n=26), not conducting a meta-analysis of risk factors for ED (n=4), not being the largest meta-analysis (n=3), not focusing on ED as defined according to the inclusion criteria of the present umbrella review (n=2), or performing a pooled, rather than a meta-analysis (n=1). A reference list of the 36 excluded articles is provided in Table S1 (105.8KB, pdf) , available as online-only supplementary material. Nine meta-analyses were ultimately included, providing evidence on 49 risk factors from a total of 29,272 individuals with ED and 1,679,385 controls.

Figure 1. Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flowchart.

Figure 1

Grading the evidence

The evidence grade for ED risk factors is reported in Table 1. Nine meta-analyses11,12,54-60 investigated a wide range of risk factors for ED. Early menarche was investigated in one meta-analysis, peripartum events were investigated in four (APGAR score, C-section, vaginal instrumental delivery, and gestational age lower than 37 weeks), pre-existing medical or psychiatric conditions were investigated in seven (attention deficit and hyperactivity disorder, substance use, type I diabetes), initial psychological features and BMI at baseline assessment in longitudinal studies were investigated in nine, and the remaining investigated risk factors were lifetime or childhood traumatic events or physical, emotional, sexual abuse.

Table 1. Evidence grading for meta-analyses of observational studies on risk factors for ED.

Study Study design Risk factor ED type ED definition k Grading of evidence AMSTAR-2 eOR
Caslini 201654 Case-control Childhood sexual abuse BN DSM-III 32 Highly suggestive Moderate 2.73
Lie 201957 Case-control Appearance-related teasing victimization ED DSM-III, DSM-IV, ICD-10 10 Highly suggestive Moderate 2.91
Caslini 201654 Case-control Childhood sexual abuse BED DSM-IV 32 Suggestive Moderate 2.31
Caslini 201654 Case-control Childhood physical abuse BED DSM-IV 32 Suggestive Moderate 3.10
Krug 201355 Case-control APGAR score at 5 minutes < 7 AN ICD-9 6 Suggestive Moderate 1.32
Nazar 201656 Cohort ADHD ED DSM-IV 17 Suggestive Moderate 4.24
Nazar 201656 Cohort ADHD ED DSM-IV 17 Suggestive Moderate 4.21
Nazar 201656 Cohort ADHD BED Clinical interview 17 Suggestive Moderate 3.93
Stice 200211 Cohort Initial body dissatisfaction ED EDI NA Suggestive Moderate 1.67
Stice 200211 Cohort Initial self-reported dieting BN EDI NA Suggestive Moderate 2.26
Stice 200211 Cohort Initial negative affect ED EDI NA Suggestive Moderate 1.38
Stice 200211 Cohort Initial perceived pressure to be thin ED EDI NA Suggestive Moderate 1.51
Caslini 201654 Case-control Childhood sexual abuse AN DSM-IV 32 Weak Moderate 1.92
Caslini 201654 Case-control Physical abuse AN DSM-IV 32 Weak Moderate 3.35
Caslini 201654 Case-control Physical abuse BN DSM-IV 32 Weak Moderate 3.44
Chen 201012 Case-control Sexual abuse ED Clinical interview 37 Weak Moderate 2.72
Lie 201957 Case-control Bullying victimization ED DSM-III, DSM-IV, ICD-10 6 Weak Moderate 2.22
Molendijk 201758 Case-control Sexual abuse AN DSM-III-R 82 Weak Moderate 1.74
Molendijk 201758 Case-control Sexual abuse AN BP DSM-III-R 82 Weak Moderate 2.80
Molendijk 201758 Case-control Sexual abuse BED DSM-IV 82 Weak Moderate 1.88
Molendijk 201758 Case-control Sexual abuse BN DSM-III-R 82 Weak Moderate 2.48
Molendijk 201758 Case-control Sexual abuse ED DSM-IV 82 Weak Moderate 2.29
Molendijk 201758 Case-control Physical abuse AN BP DSM-IV 82 Weak Moderate 2.76
Molendijk 201758 Case-control Physical abuse AN R DSM-IV 82 Weak Moderate 2.65
Molendijk 201758 Case-control Physical abuse BED DSM-IV 82 Weak Moderate 2.57
Molendijk 201758 Case-control Physical abuse BN DSM-IV 82 Weak Moderate 3.43
Molendijk 201758 Case-control Physical abuse ED DSM-IV 82 Weak Moderate 2.96
Molendijk 201758 Case-control Emotional abuse AN R DSM-IV 82 Weak Moderate 3.52
Molendijk 201758 Case-control Emotional abuse BED DSM IV 82 Weak Moderate 2.44
Molendijk 201758 Case-control Emotional abuse BN DSM-III-R 82 Weak Moderate 5.13
Molendijk 201758 Case-control Double abuse ED DSM-III-R 82 Weak Moderate 2.09
Nazar 201656 Cohort ADHD ED DSM-IV 17 Weak Moderate 3.33
Stice 200211 Cohort Initial modeling of body image BED EDE Q NA Weak Moderate 1.81
Stice 200211 Cohort Initial thin ideal internalization BED BULIT R, EAT 26 NA Weak Moderate 1.51
Stice 200211 Cohort Initial perfectionism BN EDI NA Weak Moderate 1.24
Stice 200211 Cohort Impulsivity BED BULIT R, EAT 26 NA Weak Moderate 1.28
Stice 200211 Cohort Substance use BN DSM-III-R NA Weak Moderate 1.44
Stice 200211 Cohort Initial BMI BN EDI NA Weak Moderate 1.67
Young 201359 Cohort Diabetes type I BN EAT-26 NA Weak Critically low 1.94
Young 201359 Cohort Diabetes type I ED DSM-IV NA Weak Critically low 2.30
Krug 201355 Case-control Vaginal instrumental delivery AN ICD-9 6 No evidence Moderate 1.07
Krug 201355 Case-control Gestational age < 37 weeks AN ICD-9 6 No evidence Moderate 0.80
Lie 201957 Case-control Appearance-unrelated teasing victimization ED DSM-III, DSM-IV, ICD-10 6 No evidence Moderate 1.5
Molendijk 201758 Case-control Sexual abuse AN R DSM-III-R 82 No evidence Moderate 1.65
Molendijk 201758 Case-control Physical abuse AN DSM-III-R 82 No evidence Moderate 1.23
Molendijk 201758 Case-control Sexual abuse ED DSM-III-R 82 No evidence Moderate 1.29
Stice 200211 Cohort Early menarche ED EAT 26 NA No evidence Moderate 1.19
Zhang 201960 Case-control Caesarean delivery ED ICD-9, ICD-10 4 No evidence High 1.18

ADHD = attention deficit hyperactivity disorder; AMSTAR = Assessment of Multiple Systematic Reviews; AN = anorexia nervosa; BED = binge eating disorder; BMI = body mass index; BN = bulimia nervosa; BULIT R = Bulimia Test; EAT = Eating Attitude Test; ED = eating disorders; EDE Q = Eating Disorder Examination Questionnaire; EDI = Eating Disorders Inventory; eOR = equivalent odds ratio; NA = not available; OR = odds ratio; PI = prediction interval.

Overall, no association was supported by convincing evidence. Highly suggestive evidence supported the association between childhood sexual abuse and BN (k = 29, 1,103 ED cases, 8,496 controls, OR, 2.73, 95%CI 1.96-3.79, p = 2.1 x 10-9, AMSTAR-2 moderate quality)54 and between appearance-related teasing victimization and any ED (k = 10, 1,341 ED cases, 3,295 controls, OR 2.91, 95%CI 2.05-4.12, p = 1.8 x 10-9, AMSTAR-2 moderate quality).57 Suggestive, weak, or no evidence was provided for 10, 29, and 8 risk factor, respectively. More specifically, the 12 meta-analyses that investigated risk factors for AN had the lowest evidence among all ED (one provided suggestive evidence, seven provided weak evidence, and four provided no evidence). Ten meta-analyses investigated risk factors for BED (three provided suggestive evidence and seven provided weak evidence). Ten meta-analyses investigated BN (one provided highly suggestive evidence, one provided suggestive evidence, and eight provided weak evidence). The remaining 17 meta-analyses investigated risk factors for any ED (one provided highly suggestive evidence, five provided suggestive evidence, seven provided weak evidence, and four provided no evidence). The median number of studies per meta-analysis was 32 (interquartile range [IQR] 17-82). The median number of ED cases per risk factor was 514 (IQR 196-1,103), and the median total population was 3,147 (IQR 993-8,478).

Detailed sources of bias are reported in Table 2 for all significant associations. Overall, the following bias pattern emerged: associations based on evidence from at least 1,000 subjects with ED (18%), 95% prediction intervals excluding the null value (18%), small study effect absent (72%), excess significance bias absent (60%), low overall heterogeneity of associations (8% with significant heterogeneity), significance of the largest study (68%), and publication bias (70%). The quality of included meta-analyses was high for one,60 critically low for one,59 and moderate for the reaming seven.

Table 2. Grading criteria for highly suggestive, suggestive, and weak evidence of risk factors for eating disorders.

Study Risk factor k Cases Non cases Total Above1,000 cases Heterogeneity PI includes null p-value ES* Egger’s test Largest study significant Small study effect Excess of significance bias Class of evidence ES type ES 95% low CI 95% upper CI
Caslini 201654 Childhood sexual abuse 26 1,103 7,393 8,496 1 1 1 1 0 1 0 0 2 OR 2.73 1.96 3.79
Lie 201957 appearance-related teasing victimization 10 1,341 1,954 3,295 1 1 1 1 0 1 0 0 2 OR 2.91 2.05 4.12
Caslini 201654 Childhood physical abuse 4 NA NA NA NA 0 0 1 0 1 0 NA 3 OR 3.10 2.48 3.88
Caslini 201654 Childhood sexual abuse 7 NA NA NA NA 0 0 1 0 1 0 NA 3 OR 2.31 1.66 3.20
Krug 201355 APGAR score at 5 minutes < 7 33 2,701 65,443 68,144 1 0 0 2 0 0 0 1 3 OR 1.32 1.17 1.49
Nazar 201656 ADHD 12 3,618 23,398 27,016 1 1 1 1 1 0 1 1 3 OR 4.24 2.62 6.87
Nazar 201656 ADHD 6 1,814 7,709 9,523 1 1 1 2 0 1 0 0 3 OR 4.21 2.22 7.97
Nazar 201656 ADHD 4 1,263 7,163 8,426 1 1 1 2 0 1 0 0 3 OR 3.93 2.09 7.38
Stice 200211 Initial body dissatisfaction 11 NA NA 17,332 NA 1 1 1 0 1 0 NA 3 r 0.14 0.11 0.17
Stice 200211 Initial negative affect 11 NA NA 17,411 NA 1 1 1 0 1 0 1 3 r 0.09 0.06 0.12
Stice 200211 Initial perceived pressure to be thin 4 NA NA 7,517 NA 0 1 1 0 1 0 NA 3 r 0.11 0.08 0.14
Stice 200211 Initial self-reported dieting 7 NA NA 9,436 NA 1 1 1 1 1 1 1 3 r 0.22 0.14 0.30
Caslini 201654 Childhood sexual abuse 13 196 2,264 2,460 0 1 1 3 1 0 1 0 4 OR 1.92 1.13 3.27
Caslini 201654 Emotional abuse 2 NA NA NA NA 0 NA 2 NA 1 NA NA 4 OR 3.69 2.07 6.59
Caslini 201654 Physical abuse 4 30 1,024 1,054 0 0 1 3 0 0 0 0 4 OR 3.35 1.43 7.85
Caslini 201654 Physical abuse 9 222 1,906 2,128 0 0 0 1 1 1 1 1 4 OR 3.44 2.56 4.60
Chen 201012 Sexual abuse 11 292 13,035 13,327 0 0 0 1 0 1 0 0 4 OR 2.72 2.04 3.63
Lie 201957 Bullying victimization 6 554 911 1,465 0 0 0 2 0 1 0 0 4 OR 2.22 1.50 3.28
Molendijk 201758 Double abuse 3 125 4,393 4,518 0 0 1 3 0 0 0 0 4 OR 2.09 1.32 3.30
Molendijk 201758 Emotional abuse 3 129 159 288 0 0 1 3 0 0 0 0 4 OR 3.52 1.68 7.38
Molendijk 201758 Emotional abuse 3 437 2,288 2,725 0 0 1 1 0 1 0 0 4 OR 2.44 1.73 3.48
Molendijk 201758 Emotional abuse 2 61 1,379 1,440 0 0 NA 1 NA 1 0 0 4 OR 5.13 2.80 9.39
Molendijk 201758 Physical abuse 4 83 218 301 0 0 1 3 0 0 0 0 4 OR 2.76 1.44 5.29
Molendijk 201758 Physical abuse 6 176 333 509 0 0 1 3 0 1 0 0 4 OR 2.65 1.33 5.28
Molendijk 201758 Physical abuse 5 591 2,556 3,147 0 0 0 1 0 1 0 0 4 OR 2.57 1.99 3.30
Molendijk 201758 Physical abuse 9 514 1,853 2,367 0 1 0 1 1 0 1 1 4 OR 3.43 2.19 5.39
Molendijk 201758 Physical abuse 7 521 172 693 0 0 0 1 0 1 0 0 4 OR 2.96 1.89 4.62
Molendijk 201758 Sexual abuse 7 314 1,770 2,084 0 1 1 3 0 0 0 0 4 OR 1.74 1.09 2.79
Molendijk 201758 Sexual abuse 6 175 341 516 0 1 1 3 0 0 0 1 4 OR 2.80 1.23 6.36
Molendijk 201758 Sexual abuse 5 591 2,556 3,147 0 0 1 2 0 1 0 0 4 OR 1.88 1.38 2.55
Molendijk 201758 Sexual abuse 18 997 3,969 4,966 0 1 1 2 1 1 1 0 4 OR 2.48 1.70 3.60
Molendijk 201758 Sexual abuse 7 521 172 693 0 0 1 3 0 1 0 0 4 OR 2.29 1.36 3.87
Nazar 201656 ADHD 3 1,174 6,954 8,128 1 1 1 3 0 1 0 0 4 OR 3.33 1.39 7.97
Stice 200211 Initial BMI 10 NA NA 11,063 NA 1 1 2 1 0 1 NA 4 r 0.14 0.06 0.22
Stice 200211 Impulsivity 3 NA NA 933 NA 0 1 3 0 0 0 1 4 r 0.07 0.00 0.13
Stice 200211 Initial modeling of body image 2 NA NA 449 NA 0 NA 3 NA 1 NA NA 4 r 0.16 0.07 0.25
Stice 200211 Initial perfectionism 4 NA NA 2,124 NA 0 1 3 0 1 0 0 4 r 0.06 0.02 0.10
Stice 200211 Initial thin ideal internalization 4 NA NA 15,182 NA 1 1 3 0 1 0 NA 4 r 0.11 0.04 0.20
Stice 200211 Substance use 4 NA NA 2,236 NA 0 1 2 0 1 0 0 4 r 0.10 0.06 0.14
Young 201359 Diabetes 9 NA NA 927 NA 1 1 3 0 1 0 1 4 d 0.36 0.13 0.60
Young 201359 Diabetes 7 NA NA 4,515 NA 1 1 3 1 0 1 0 4 d 0.46 0.10 0.82

ADHD = attention deficit hyperactivity disorder; CI = confidence interval; NA = not available; OR = odds ratio; PI = prediction interval.

*

1 ≤ 10-6, 2 ≤ 10-3, 3 ≤ 0.05, 4 ≤ 0.05.

Discussion

This is the first comprehensive umbrella review of meta-analyses on risk factors for ED, which goes beyond mere pooling of available meta-analyses by including additional stringent statistical tests and evidence grading based on quantitative criteria. This review included 50 associations from nine meta-analyses, showing a lack of convincing evidence supporting all ED risk factors. Highly suggestive evidence was found for childhood sexual abuse as risk factor for BN and appearance-related teasing victimization for any ED.

These results can advance clinical knowledge in the field of ED on various points. First, none of the putative risk factors for ED are supported by convincing evidence, and several types of bias may have inflated the estimates reported in meta-analyses. This is particularly concerning when we compare the evidence of risk factors for ED with the evidence of risk factors for schizophrenia34,35 (seven factors overall supported by convincing evidence), autism36,37 (seven factors), depression38 (eight factors), bipolar disorder39 (one factor), post-traumatic stress disorder40 (three factors), and anxiety spectrum disorder and obsessive compulsive disorder41 (one). Environmental factors play an important role in the pathogenesis of mental disorders, while genetic predisposition still explains only a very small portion of the risk of schizophrenia, depressive disorders, bipolar disorders.61 The lack of established risk factors for ED may be due to limited research in this field or to the heterogeneity of the clinical pictures, which have common characteristics and frequent overlap with other mental disorders. There are common general psychopathologic features in ED (e.g., depressive, anxious, obsessive-compulsive), as well as feelings of ineffectiveness and interpersonal sensitivity, which appear to be even more central than behavioral and specific psychopathologies.62 This could reduce the specificity of risk factors.

Second, while a number of mental disorders have specific risk factors, such as high clinical risk for psychosis,34 or irritable bowel syndrome for bipolar disorder,39 the risk factors for ED found in the present review appear to be relatively unspecific. For example, childhood sexual abuse has been connected with a number of adverse health outcomes, including borderline personality disorder, anxiety, depression, post-traumatic stress disorder, psychosis, and non-suicidal self-injury, in addition to pain, risky sexual behavior, obesity, and HIV infection.63 This is not surprising, given that child abuse is a risk factor for general psychopathology64 and that the effect of sexual abuse on ED psychopathology is probably mediated by ineffectiveness, which is present beyond ED.65 The transdiagnostic nature of these risk factors is relatively underexplored but could, at least theoretically, allow transdiagnostic early detection and intervention for these disorders.66,67 To the best of our knowledge, only one pooled analysis of follow-up data from three randomized controlled trials on ED prevention has focused on a high-risk population with body dissatisfaction, finding that negative affect and low BMI predicted AN, elevated body dissatisfaction, overeating, and fasting predicted BN, and elevated body dissatisfaction, overeating, and functional impairment predicted BED.68 However, such findings have not yet been replicated in larger cohort studies and have not been pooled in meta-analyses accounting for random error and heterogeneity across studies. Moreover, one more reason for the lack of evidence about risk factors for ED might be explained by a recent large GWAS study, which included 16,992 cases of anorexia nervosa and 55,525 controls, finding that eight loci linked to other psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits (independent of the effects of common variants associated with body-mass index) were associated with a higher risk of AN.21 Such results might suggest that some genetic risk is shared with other psychiatric conditions, but that there are also specific metabolic pathways for AN that should be investigated in greater detail. However, an overlap between mental and physical disorders is also present in other mental disorders.69

Third, we found that the least evidence is available for AN, which is, on the other hand, the most severe ED in terms of clinical outcome, medical complications, and survival. Fourth, the lack of clear evidence supporting the identification of ED risk factors, especially for AN, is highly relevant in the light of the need for early ED detection as a crucial component in improving ED treatment efficacy. Some authors70 have proposed a staging model for AN that shows poorer outcomes with illness progression. In line with this framework, the NICE (2010) ED guidelines recommend that treatment should begin at the earliest opportunity to avoid the additional effects of chronicity, psychiatric comorbidity, and complications from malnutrition.71 Promoting mental health, a complementary strategy for preventing mental disorders, is particularly needed in young populations, such as those at risk of developing ED.72

Appearance-related teasing victimization was identified as a risk factor for any ED, with highly suggestive, but not convincing, evidence. This confirms that interpersonal and social functioning might be a risk factor for ED, which was suggested in a systematic review73 that highlighted the role of interpersonal issues as a factor in ED onset. In addition, this finding confirms that emotional abuse in childhood and adolescence, which consists of humiliating and demeaning experiences, is the form of abuse most directly associated with ED psychopathology, independent of other psychiatric comorbidities.74

The strength of the present study is that it is the first umbrella review to demonstrate that no convincing evidence supports any ED risk factor. Moreover, it provides methodological direction for future studies, i.e., a focus on high quality evidence about ED risk factors, such as large-scale collaborative studies, harmonizing measurements, and data sharing to bridge the gap with prevention strategies implemented in other areas of psychiatry. Finally, the focus of collaborative studies should be on metabolic pathways, which were associated with AN in a large recent GWAS study. Thus, leading centers involved clinical research on ED should plan large multicenter longitudinal cohort studies investigating the role of putative risk factors for ED, focusing on metabolic pathways, which have been completely neglected to date.

The main limitation of the present study is that only one of the included meta-analyses met high quality criteria according to the AMSTAR-2 checklist. Furthermore, the lack of evidence for specific risk factors could be related to the paucity of large-scale collaborative longitudinal studies assessing the role of moderating mechanisms in the relationship between conditions preceding the onset of the disorder and the development of ED psychopathology.75 Finally, factors not included in meta-analyses are not considered in umbrella reviews.

In conclusion, no ED risk factor is supported by convincing evidence. The field of ED is being left behind with respect to the preliminary evidence necessary to begin implementing targeted preventive interventions for individuals with subthreshold symptoms. More multi-center longitudinal cohort studies are needed to identify modifiable risk factors for ED, including the metabolic factors suggested by a recent large-scale GWAS study.21

Disclosure

The authors report no conflicts of interest.

Footnotes

How to cite this article: Solmi M, Radua J, Stubbs B, Ricca V, Moretti D, Busatta D, et al. Risk factors for eating disorders: an umbrella review of published meta-analyses. Braz J Psychiatry. 2021;43:314-323. http://dx.doi.org/10.1590/1516-4446-2020-1099

References

  • 1.Treasure J, Duarte TA, Schmidt U. Eating disorders. Lancet. 2020;395:899–911. doi: 10.1016/S0140-6736(20)30059-3. [DOI] [PubMed] [Google Scholar]
  • 2.Keshaviah A, Edkins K, Hastings ER, Krishna M, Franko DL, Herzog DB, et al. Re-examining premature mortality in anorexia nervosa: a meta-analysis redux. Compr Psychiatry. 2014;55:1773–84. doi: 10.1016/j.comppsych.2014.07.017. [DOI] [PubMed] [Google Scholar]
  • 3.Winkler LA. Funen anorexia nervosa study ‐ a follow-up study on outcome, mortality, quality of life and body composition. Dan Med J. 2017;64:B5380. [PubMed] [Google Scholar]
  • 4.Steinhausen HC. The outcome of anorexia nervosa in the 20th century. Am J Psychiatry. 2002;159:1284–93. doi: 10.1176/appi.ajp.159.8.1284. [DOI] [PubMed] [Google Scholar]
  • 5.Steinhausen HC, Weber S. The outcome of bulimia nervosa: findings from one-quarter century of research. Am J Psychiatry. 2009;166:1331–41. doi: 10.1176/appi.ajp.2009.09040582. [DOI] [PubMed] [Google Scholar]
  • 6.Steinhausen HC. Outcome of eating disorders. Child Adolesc Psychiatr Clin N Am. 2009;18:225–42. doi: 10.1016/j.chc.2008.07.013. [DOI] [PubMed] [Google Scholar]
  • 7.Kishi T, Kafantaris V, Sunday S, Sheridan EM, Correll CU. Are antipsychotics effective for the treatment of anorexia nervosa? Results from a systematic review and meta-analysis. J Clin Psychiatry. 2012;73:e757–66. doi: 10.4088/JCP.12r07691. [DOI] [PubMed] [Google Scholar]
  • 8.Frank GK, Shott ME. The role of psychotropic medications in the management of anorexia nervosa: rationale, evidence and future prospects. CNS Drugs. 2016;30:419–42. doi: 10.1007/s40263-016-0335-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Balestrieri M, Oriani MG, Simoncini A, Bellantuono C. Psychotropic drug treatment in anorexia nervosa. search for differences in efficacy/tolerability between adolescent and mixed-age population. Eur Eat Disord Rev. 2013;21:361–73. doi: 10.1002/erv.2240. [DOI] [PubMed] [Google Scholar]
  • 10.Zeeck A, Herpertz-Dahlmann B, Friederich HC, Brockmeyer T, Resmark G, Hagenah U, et al. Psychotherapeutic treatment for anorexia nervosa: a systematic review and network meta-analysis. Front Psychiatry. 2018;9:158. doi: 10.3389/fpsyt.2018.00158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Stice E. Risk and maintenance factors for eating pathology: a meta-analytic review. Psychol Bull. 2002;128:825–48. doi: 10.1037/0033-2909.128.5.825. [DOI] [PubMed] [Google Scholar]
  • 12.Chen LP, Murad MH, Paras ML, Colbenson KM, Sattler AL, Goranson EN, et al. Sexual abuse and lifetime diagnosis of psychiatric disorders: systematic review and meta-analysis. Mayo Clin Proc. 2010;85:618–29. doi: 10.4065/mcp.2009.0583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Stice E, Davis K, Miller NP, Marti CN. Fasting increases risk for onset of binge eating and bulimic pathology: a 5-year prospective study. J Abnorm Psychol. 2008;117:941–6. doi: 10.1037/a0013644. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Wildes JE, Emery RE, Simons AD. The roles of ethnicity and culture in the development of eating disturbance and body dissatisfaction: a meta-analytic review. Clin Psychol Rev. 2001;21:521–51. doi: 10.1016/s0272-7358(99)00071-9. [DOI] [PubMed] [Google Scholar]
  • 15.Stice E, Ng J, Shaw H. Risk factors and prodromal eating pathology. J Child Psychol Psychiatry. 2010;51:518–25. doi: 10.1111/j.1469-7610.2010.02212.x. [DOI] [PubMed] [Google Scholar]
  • 16.Collantoni E, Solmi M, Gallicchio D, Santonastaso P, Meneguzzo P, Carvalho AF, et al. Catechol-o-methyltransferase (COMT) Val158Met polymorphism and eating disorders: data from a new biobank and meta-analysis of previously published studies. Eur Eat Disord Rev. 2017;25:524–32. doi: 10.1002/erv.2555. [DOI] [PubMed] [Google Scholar]
  • 17.Solmi M, Gallicchio D, Collantoni E, Correll CU, Clementi M, Pinato C, et al. Serotonin transporter gene polymorphism in eating disorders: data from a new biobank and META-analysis of previous studies. World J Biol Psychiatry. 2016;17:244–57. doi: 10.3109/15622975.2015.1126675. [DOI] [PubMed] [Google Scholar]
  • 18.Brewerton TD, Lesem MD, Kennedy A, Garvey WT. Reduced plasma leptin concentrations in bulimia nervosa. Psychoneuroendocrinology. 2000;25:649–58. doi: 10.1016/s0306-4530(00)00016-0. [DOI] [PubMed] [Google Scholar]
  • 19.Boraska V, Franklin CS, Floyd JA, Thornton LM, Huckins LM, Southam L, et al. A genome-wide association study of anorexia nervosa. Mol Psychiatry. 2014;19:1085–94. doi: 10.1038/mp.2013.187. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Hinney A, Kesselmeier M, Jall S, Volckmar AL, Föcker M, Antel J, et al. Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index. Mol Psychiatry. 2017;22:192–201. doi: 10.1038/mp.2016.71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Watson HJ, Yilmaz Z, Thornton LM, Hübel C, Coleman JR, Gaspar HA, et al. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nat Genet. 2019;51:1207–14. doi: 10.1038/s41588-019-0439-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Richards K, Austin A, Allen K, Schmidt U. Early intervention services for non-psychotic mental health disorders: a scoping review protocol. BMJ Open. 2019;9:e033656. doi: 10.1136/bmjopen-2019-033656. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Kotlicka-Antczak M, Podgórski M, Oliver D, Maric NP, Valmaggia L, Fusar-Poli P. Worldwide implementation of clinical services for the prevention of psychosis: the IEPA early intervention in mental health survey. Early Interv Psychiatry. 2020 Feb 17; doi: 10.1111/eip.12950. . Online ahead of print. [DOI] [PubMed] [Google Scholar]
  • 24.Stice E, Becker CB, Yokum S. Eating disorder prevention: current evidence-base and future directions. Int J Eat Disord. 2013;46:478–85. doi: 10.1002/eat.22105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Le LK, Barendregt JJ, Hay P, Mihalopoulos C. Prevention of eating disorders: a systematic review and meta-analysis. Clin Psychol Rev. 2017;53:46–58. doi: 10.1016/j.cpr.2017.02.001. [DOI] [PubMed] [Google Scholar]
  • 26.Bulik CM. Are we really paddling as fast as we can? Reflections on why eating disorders treatment and research always seem to be one step behind: commentary on Hay, Mitchell, and Stice & Becker: prevention and treatment. Int J Eat Disord. 2013;46:489–91. doi: 10.1002/eat.22119. [DOI] [PubMed] [Google Scholar]
  • 27.Deady M, Choi I, Calvo RA, Glozier N, Christensen H, Harvey SB. eHealth interventions for the prevention of depression and anxiety in the general population: a systematic review and meta-analysis. BMC Psychiatry. 2017;17:310. doi: 10.1186/s12888-017-1473-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Fusar-Poli P, Schultze-Lutter F, Cappucciati M, Rutigliano G, Bonoldi I, Stahl D, et al. The dark side of the moon: meta-analytical impact of recruitment strategies on risk enrichment in the clinical high risk state for psychosis. Schizophr Bull. 2016;42:732–43. doi: 10.1093/schbul/sbv162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Fusar-Poli P, Rutigliano G, Stahl D, Schmidt A, Ramella-Cravaro V, Hitesh S, et al. Deconstructing pretest risk enrichment to optimize prediction of psychosis in individuals at clinical high risk. JAMA Psychiatry. 2016;73:1260–7. doi: 10.1001/jamapsychiatry.2016.2707. [DOI] [PubMed] [Google Scholar]
  • 30.Fusar-Poli P, Sullivan SA, Shah JL, Uhlhaas PJ. Improving the detection of individuals at clinical risk for psychosis in the community, primary and secondary care: an integrated evidence-based approach. Front Psychiatry. 2019;10:774. doi: 10.3389/fpsyt.2019.00774. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Fusar-Poli P, Palombini E, Davies C, Oliver D, Bonoldi I, Ramella-Cravaro V, et al. Why transition risk to psychosis is not declining at the OASIS ultra high risk service: the hidden role of stable pretest risk enrichment. Schizophr Res. 2018;192:385–90. doi: 10.1016/j.schres.2017.06.015. [DOI] [PubMed] [Google Scholar]
  • 32.Solmi M, Durbaba S, Ashworth M, Fusar-Poli P. Proportion of young people in the general population consulting general practitioners: potential for mental health screening and prevention. Early Interv Psychiatry. 2019 Dec 26; doi: 10.1111/eip.12908. . Online ahead of print. [DOI] [PubMed] [Google Scholar]
  • 33.Fusar-Poli P, de Pablo GS, De Micheli A, Nieman DH, Correll CU, Kessing LV, et al. What is good mental health? A scoping review. Eur Neuropsychopharmacol. 2019;31:33–46. doi: 10.1016/j.euroneuro.2019.12.105. [DOI] [PubMed] [Google Scholar]
  • 34.Radua J, Ramella-Cravaro V, Ioannidis JP, Reichenberg A, Phiphopthatsanee N, Amir T, et al. What causes psychosis? An umbrella review of risk and protective factors. World Psychiatry. 2018;17:49–66. doi: 10.1002/wps.20490. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Belbasis L, Köhler CA, Stefanis N, Stubbs B, van Os J, Vieta E, et al. Risk factors and peripheral biomarkers for schizophrenia spectrum disorders: an umbrella review of meta-analyses. Acta Psychiatr Scand. 2018;137:88–97. doi: 10.1111/acps.12847. [DOI] [PubMed] [Google Scholar]
  • 36.Kim JY, Son MJ, Son CY, Radua J, Eisenhut M, Gressier F, et al. Environmental risk factors and biomarkers for autism spectrum disorder: an umbrella review of the evidence. Lancet Psychiatry. 2019;6:590–600. doi: 10.1016/S2215-0366(19)30181-6. [DOI] [PubMed] [Google Scholar]
  • 37.Dragioti E, Solmi M, Favaro A, Fusar-Poli P, Dazzan P, Thompson T, et al. Association of antidepressant use with adverse health outcomes: a systematic umbrella review. JAMA Psychiatry. 2019;76:1241–55. doi: 10.1001/jamapsychiatry.2019.2859. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Köhler CA, Evangelou E, Stubbs B, Solmi M, Veronese N, Belbasis L, et al. Mapping risk factors for depression across the lifespan: an umbrella review of evidence from meta-analyses and Mendelian randomization studies. J Psychiatr Res. 2018;103:189–207. doi: 10.1016/j.jpsychires.2018.05.020. [DOI] [PubMed] [Google Scholar]
  • 39.Bortolato B, Köhler CA, Evangelou E, León-Caballero J, Solmi M, Stubbs B, et al. Systematic assessment of environmental risk factors for bipolar disorder: an umbrella review of systematic reviews and meta-analyses. Bipolar Disord. 2017;19:84–96. doi: 10.1111/bdi.12490. [DOI] [PubMed] [Google Scholar]
  • 40.Tortella-Feliu M, Fullana MA, Pérez-Vigil A, Torres X, Chamorro J, Littarelli SA, et al. Risk factors for posttraumatic stress disorder: an umbrella review of systematic reviews and meta-analyses. Neurosci Biobehav Rev. 2019;107:154–65. doi: 10.1016/j.neubiorev.2019.09.013. [DOI] [PubMed] [Google Scholar]
  • 41.Fullana MA, Tortella-Feliu M, de la Cruz LF, Chamorro J, Pérez-Vigil A, Ioannidis JP, et al. Risk and protective factors for anxiety and obsessive-compulsive disorders: an umbrella review of systematic reviews and meta-analyses. Psychol Med. 2020;50:1300–15. doi: 10.1017/S0033291719001247. [DOI] [PubMed] [Google Scholar]
  • 42.Moher D, Liberati A, Tetzlaff J, Douglas G Altman; PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. doi: 10.1371/journal.pmed.1000097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group. JAMA. 2000;283:2008–12. doi: 10.1001/jama.283.15.2008. [DOI] [PubMed] [Google Scholar]
  • 44.Solmi M, Köhler CA, Stubbs B, Koyanagi A, Bortolato B, Monaco F, et al. Environmental risk factors and nonpharmacological and nonsurgical interventions for obesity: an umbrella review of meta-analyses of cohort studies and randomized controlled trials. Eur J Clin Invest. 2018;48:e12982. doi: 10.1111/eci.12982. [DOI] [PubMed] [Google Scholar]
  • 45.Fusar-Poli P, Radua J. Ten simple rules for conducting umbrella reviews. Evid Based Ment Health. 2018;21:95–100. doi: 10.1136/ebmental-2018-300014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008. doi: 10.1136/bmj.j4008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7:177–88. doi: 10.1016/0197-2456(86)90046-2. [DOI] [PubMed] [Google Scholar]
  • 48.Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–60. doi: 10.1136/bmj.327.7414.557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Riley RD, Higgins JP, Deeks JJ. Interpretation of random effects meta-analyses. BMJ. 2011;342:d549. doi: 10.1136/bmj.d549. [DOI] [PubMed] [Google Scholar]
  • 50.Veronese N, Solmi M, Caruso MG, Giannelli G, Osella AR, Evangelou E, et al. Dietary fiber and health outcomes: an umbrella review of systematic reviews and meta-analyses. Am J Clin Nutr. 2018;107:436–44. doi: 10.1093/ajcn/nqx082. [DOI] [PubMed] [Google Scholar]
  • 51.Ioannidis JP, Trikalinos TA. An exploratory test for an excess of significant findings. Clin Trials. 2007;4:245–53. doi: 10.1177/1740774507079441. [DOI] [PubMed] [Google Scholar]
  • 52.Ioannidis JPA. Clarifications on the application and interpretation of the test for excess significance and its extensions. J Math Psychol. 2013;57:184–7. [Google Scholar]
  • 53.Li X, Meng X, Timofeeva M, Tzoulaki I, Tsilidis KK, Ioannidis JP, et al. Serum uric acid levels and multiple health outcomes: umbrella review of evidence from observational studies, randomised controlled trials, and Mendelian randomisation studies. BMJ. 2017;357:j2376. doi: 10.1136/bmj.j2376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Caslini M, Bartoli F, Crocamo C, Dakanalis A, Clerici M, Carrà G. Disentangling the association between child abuse and eating disorders: a systematic review and meta-analysis. Psychosom Med. 2016;78:79–90. doi: 10.1097/PSY.0000000000000233. [DOI] [PubMed] [Google Scholar]
  • 55.Krug I, Taborelli E, Sallis H, Treasure J, Micali N. A systematic review of obstetric complications as risk factors for eating disorder and a meta-analysis of delivery method and prematurity. Physiol Behav. 2013;109:51–62. doi: 10.1016/j.physbeh.2012.11.003. [DOI] [PubMed] [Google Scholar]
  • 56.Nazar BP, Bernardes C, Peachey G, Sergeant J, Mattos P, Treasure J. The risk of eating disorders comorbid with attention-deficit/hyperactivity disorder: a systematic review and meta-analysis. Int J Eat Disord. 2016;49:1045–57. doi: 10.1002/eat.22643. [DOI] [PubMed] [Google Scholar]
  • 57.Lie SØ, Rø Ø, Bang L. Is bullying and teasing associated with eating disorders? A systematic review and meta‐analysis. Int J Eat Disord. 2019;52:497–514. doi: 10.1002/eat.23035. [DOI] [PubMed] [Google Scholar]
  • 58.Molendijk ML, Hoek HW, Brewerton TD, Elzinga BM. Childhood maltreatment and eating disorder pathology: a systematic review and dose-response meta-analysis. Psychol Med. 2017;47:1402–16. doi: 10.1017/S0033291716003561. [DOI] [PubMed] [Google Scholar]
  • 59.Young V, Eiser C, Johnson B, Brierley S, Epton T, Elliott J, et al. Eating problems in adolescents with type 1 diabetes: a systematic review with meta-analysis. Diabet Med. 2013;30:189–98. doi: 10.1111/j.1464-5491.2012.03771.x. [DOI] [PubMed] [Google Scholar]
  • 60.Zhang T, Sidorchuk A, Sevilla-Cermeño L, Vilaplana-Pérez A, Chang Z, Larsson H, et al. Association of cesarean delivery with risk of neurodevelopmental and psychiatric disorders in the offspring: a systematic review and meta-analysis. JAMA Netw Open. 2019;2:e1910236. doi: 10.1001/jamanetworkopen.2019.10236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Mistry S, Harrison JR, Smith DJ, Escott-Price V, Zammit S. The use of polygenic risk scores to identify phenotypes associated with genetic risk of bipolar disorder and depression: a systematic review. J Affect Disord. 2018;234:148–55. doi: 10.1016/j.jad.2018.02.005. [DOI] [PubMed] [Google Scholar]
  • 62.Solmi M, Collantoni E, Meneguzzo P, Degortes D, Tenconi E, Favaro A. Network analysis of specific psychopathology and psychiatric symptoms in patients with eating disorders. Int J Eat Disord. 2018;51:680–92. doi: 10.1002/eat.22884. [DOI] [PubMed] [Google Scholar]
  • 63.Hailes HP, Yu R, Danese A, Fazel S. Long-term outcomes of childhood sexual abuse: an umbrella review. Lancet Psychiatry. 2019;6:830–9. doi: 10.1016/S2215-0366(19)30286-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Teicher MH, Samson JA. Childhood maltreatment and psychopathology: a case for ecophenotypic variants as clinically and neurobiologically distinct subtypes. Am J Psychiatry. 2013;170:1114–33. doi: 10.1176/appi.ajp.2013.12070957. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Monteleone AM, Cascino G, Pellegrino F, Ruzzi V, Patriciello G, Marone L, et al. The association between childhood maltreatment and eating disorder psychopathology: a mixed-model investigation. Eur Psychiatry. 2019;61:111–8. doi: 10.1016/j.eurpsy.2019.08.002. [DOI] [PubMed] [Google Scholar]
  • 66.Fusar-Poli P, Solmi M, Brondino N, Davies C, Chae C, Politi P, et al. Transdiagnostic psychiatry: a systematic review. World Psychiatry. 2019;18:192–207. doi: 10.1002/wps.20631. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Fusar-Poli P. TRANSD recommendations: improving transdiagnostic research in psychiatry. World Psychiatry. 2019;18:361–2. doi: 10.1002/wps.20681. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Stice E, Gau JM, Rohde P, Shaw H. Risk factors that predict future onset of each DSM-5 eating disorder: predictive specificity in high-risk adolescent females. J Abnorm Psychol. 2017;126:38–51. doi: 10.1037/abn0000219. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Amare AT, Schubert KO, Klingler-Hoffmann M, Cohen-Woods S, Baune BT. The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies. Transl Psychiatry. 2017;7:e1007. doi: 10.1038/tp.2016.261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Treasure J, Stein D, Maguire S. Has the time come for a staging model to map the course of eating disorders from high risk to severe enduring illness? An examination of the evidence. Early Interv Psychiatry. 2015;9:173–84. doi: 10.1111/eip.12170. [DOI] [PubMed] [Google Scholar]
  • 71.National Institute for Health and Care Excellence (NICE) Eating disorders: recognition and treatment [Intetnet] www.nice.org.uk/guidance/ng69.
  • 72.Fusar-Poli P, Bauer M, Borgwardt S, Bechdolf A, Correll CU, Do KQ, et al. European college of neuropsychopharmacology network on the prevention of mental disorders and mental health promotion (ECNP PMD-MHP) Eur Neuropsychopharmacol. 2019;29:1301–11. doi: 10.1016/j.euroneuro.2019.09.006. [DOI] [PubMed] [Google Scholar]
  • 73.Monteleone AM, Treasure J, Kan C, Cardi V. Reactivity to interpersonal stress in patients with eating disorders: a systematic review and meta-analysis of studies using an experimental paradigm. Neurosci Biobehav Rev. 2018;87:133–50. doi: 10.1016/j.neubiorev.2018.02.002. [DOI] [PubMed] [Google Scholar]
  • 74.Guillaume S, Jaussent I, Maimoun L, Ryst A, Seneque M, Villain L, et al. Associations between adverse childhood experiences and clinical characteristics of eating disorders. Sci Rep. 2016;6:35761. doi: 10.1038/srep35761. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75.Jansen A. Eating disorders need more experimental psychopathology. Behav Res Ther. 2016;86:2–10. doi: 10.1016/j.brat.2016.08.004. [DOI] [PubMed] [Google Scholar]

Articles from Brazilian Journal of Psychiatry are provided here courtesy of Brazilian Psychiatric Association

RESOURCES