EMPIRICAL ARTICLE
DSM-5 Eating Disorders and Other Specified Eating and Feeding Disorders: Is There a Meaningful Differentiation? A. Kate Fairweather-Schmidt, PhD* Tracey D. Wade, PhD
ABSTRACT Objective: In the DSM-5 diagnostic criteria for eating disorders, two main groups appear, threshold eating disorders (TED; anorexia nervosa, bulimia nervosa, and binge eating disorder), and other specified feeding and eating disorders (OSFED). In addition to calculating prevalence of these two groups, we examined the degree to which they could be differentiated in terms of impairment and risk factors. Method: Adolescent female twins (N 5 699) were interviewed with the Eating Disorder Examination on three occasions spanning 12.70–19.84 years of age. Assessments also included self-report measures related to impairment and risk. Results: Prevalence of DSM-5 ED in this adolescent population was 10.4%; 5.4% for TED and 5% for OSFED. Impairment levels did not distinguish TED and OSFED groups at any wave. Examination of latent risk factors showed TED and OSFED groups to share a common genetic basis; however, largely nonoverlapping unique
Introduction Broadly speaking, there have been two major changes introduced with respect to eating disorders in the Diagnostic and Statistical Manual of Mental Disorders—5th Edition.1 First, feeding disThis article was published online on February 25, 2014. Some additional information was added to the already existing acknowledgement section. This notice is included in the online version to indicate it has been corrected on March 13, 2014. Accepted 18 January 2014 Conflict of interest:The authors report no declarations of financial interest. Supported by 324715 and 480420 from the National Health and Medical Research Council (NHMRC) and by the Australian Twin Registry, which is supported by an Enabling Grant (ID 310667), from the NHMRC administered by the University of Melbourne. *Correspondence to: Dr. A. Kate Fairweather-Schmidt, School of Psychology, Flinders University, GPO Box 2100, Adelaide, South Australia 5001, Australia. E-mail: [email protected] School of Psychology, Flinders University, Adelaide, South Australia, Australia Published online 25 February 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/eat.22257 C 2014 Wiley Periodicals, Inc. V
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environmental influences contributed to the two groups. Specific risk factors commonly differentiated the no ED and TED groups, but not OSFED. Discussion: The findings suggest that TED and OSFED groups cannot be discriminated by prevalence or impairment or genetic risk factors. It is anticipated that OSFED will possess limited clinical utility for adolescents. Future research should examine clinical cases of these two groups in terms of meaningful differences, and a research focus should be maintained on both groups. Further examination of specific environmental risk factors that may attenuate the level of symptoms between the two groups may provide useful information for preC 2014 Wiley Periodicals, vention efforts. V Inc. Keywords: eating disorders; DSM-5; impairment; adolescents; OSFED (Int J Eat Disord 2014; 47:524–533)
orders emerging in childhood have been relocated to this section which is now called “Feeding and Eating Disorders.” Second, the criteria for eating disorders have been relaxed. It is this latter change that is the focus of the current investigation. The criteria related to previous threshold eating disorders (TEDs; anorexia nervosa [AN], and bulimia nervosa [BN]) have been broadened while also incorporating dimensionality. BED has now been included as a threshold disorder with specification of binging severity analogous to BN. Atypical anorexia nervosa (A-AN), bulimia nervosa of low frequency and/or limited duration (BN-L), and binge eating disorder of low frequency and/or limited duration (BED-L) joining purging disorder (PD) in the newly termed “Other Specified Feeding and Eating Disorders” (OSFED) category, replacing eating disorder not otherwise specified (EDNOS) in DSM-IV.2 These modifications were anticipated to promote more effective clinical description, in addition to informing/clarifying the expected course, and treatment options over time becoming International Journal of Eating Disorders 47:5 524–533 2014
DSM-5 EATING DISORDERS AND OSFED
achievable when patterns of symptomatology change are recognized and definable.3,4 The DSM-5 criteria modifications were made partially in response to issues with the EDNOS category. According to Keel, Brown, Holland and Bodell,3 “. . .EDNOS [was] a heterogeneous category . . .defined by what it [was] not. . .” (p. 384), that is, neither AN nor BN. This resulted in approximately half of all presenting cases including adolescents and children meeting criteria for EDNOS, which share a significant decrement in functioning and quality of life with threshold disorders, leading to the EDNOS diagnosis being considered deficient of clinical utility.3,5–7 Although criteria dictating DSM-5 diagnoses have been modified with the aim of reducing the number of EDNOS cases, two studies of DSM-5 eating disorders in young people (aged up to 20 years) suggest that OSFED represents 15–40% of DSM-5 cases,8,9 a proportion that is still seen as a cause for concern.10 Whether or not DSM-5 differentiates between TEDs and OSFED in a meaningful way, and thus represents improved clinical utility, can be judged by two main criteria: first, and consistent with the new emphasis in DSM-5, in relation to any differences in levels of reported impairment; and second, in relation to differences in identified risk factors. With respect to the first criterion, impairment can be assessed using a number of dimensional measures, including global eating disorder psychopathology assessed using the Eating Disorder Examination11 (EDE), which is typically used as a measure of treatment outcome in eating disorders across children and adults,11–13 in addition to body mass index (BMI). There is also a suggestion that impairment is indicated by several dimensional cognitive and neurobiological characteristics, including drive for thinness and body dissatisfaction,14 and executive functioning deficits and weak central coherence. Executive functioning deficits are represented by inefficient set shifting, or rigid cognitive styles or response inflexibility when problem solving, and are known to occur more frequently in disordered eating populations.15 Weak central coherence refers to an executive function deficit also occurring more commonly among individuals with eating disorders, demonstrated by an imbalance on dimensions of attention to detail versus global integration of information. Currently, there is stronger evidence linking eating disorders with poor global integrative capacity.16,17 While this deficit has been observed within people with a current eating disorder, individuals recovered from an eating disorder, and also among healthy family members of proInternational Journal of Eating Disorders 47:5 524–533 2014
bands with eating disorders, the deficit is more severe amongst the first group.15 If meaningful differentiation exists between TEDs and OFSED, we hypothesize that markers of impairment differ significantly between the two. The second criterion for judging whether there is meaningful differentiation between TEDs and OFSED is by examination of risk factors. In the broadest terms, latent risk factors can be identified as additive genetic, shared and/or unique environment, the presence of proportions of which is typically identified using twin analyses. Such analyses can also be used to identify overlap between these latent risk factors between different disorders. Specific risk factors for eating disorders are multiple,18 but in particular, this article will focus on environmental/social influences (weight-related peer teasing, thin ideal internalization, perceived pressure to be thin, body dissatisfaction), in addition to perfectionism and efficacy-related factors (need to get things “just right,” concern over mistakes, ineffectiveness). These are shown to consistently relate to eating psychopathological outcomes.18–20 This article utilizes the DSM-5 criteria to identify AN, BN, BED, A-AN, BN-L, and PD diagnoses, which are subsequently used to populate three groups: no eating disorder, TED (AN, BN, and BED), and OSFED (A-AN, BN-L, and PD). These groups are compared across a number of indicators to address our three main objectives. First, given only two previous studies exist that examine the prevalence of DSM-5 disorders in adolescents aged up to 20 years and only one of these examined the prevalence of specific categories within OFSED,8,9 to determine the prevalence of specific DSM-5 eating disorders, and the proportion of OFSED relative to threshold ED diagnoses. Second, to examine whether key variables related to impairment distinguish people with TEDs from OSFED, compared with those without an eating disorder. Third, to investigate whether risk factors for the two eating disorder groups overlap with respect to both latent risk factors (additive genetic and environmental variance in relation to the threshold and OSFED phenotypes) and specific risk factors.
Method Participants The current study uses three waves of data from adolescent female–female twin pairs. Participant characteristics and methodology used to derive this sample have been described previously.11,21–23 At Waves 2 and 3, all twins, responders and non-responders, were
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FAIRWEATHER-SCHMIDT AND WADE TABLE 1.
Diagnostic criteria for threshold and other specified or feeding eating disorders
Diagnosis Threshold eating disorders
Criteria (and Relation to DSM-5 Criteria) Anorexia nervosa
Bulimia nervosa
Binge eating disorder
Other Specified feeding or eating disorders
Atypical anorexia nervosa
Bulimia nervosa low frequency/limited duration Purging disorder
approached. The mean duration of time between Waves 1–2, and Waves 1–3 was 1.15 years (SD 5 0.17) and 2.96 years (SD 5 0.27), respectively, ranging from 1.91 to 4.65 years. Across the three waves, the ages ranged from 12.70 to 19.84 years. Procedure The twins were interviewed via telephone at each of the three waves. The interview consisted of two parts for Wave 1 and 2, where the first used the EDE,24 and the second constituted questions from self-report questionnaires assessing a range of variables including life events, temperament, and family functioning.21,22 Wave 3, however, involved only the EDE interview, whereas the other measures were undertaken online. Postgraduate Clinical Psychology trainees (n 5 16) who had been trained in use of the EDE conducted the interviews. To account for the slightly younger age of the sample relative to the original EDE population, it was modified slightly11,21 and was conducted at separate times and with a different interviewer for each child in the family.
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Intense fear of gaining weight was present on more than half the days over at least a 3-month period (criterion B) Over that period BMI for age percentile was < 5th percentile (pediatric criterion A) Over that time either (i) tried to lose weight or avoid weight gain, (ii) at least moderate importance of weight and/or shape, i.e., definitely one of the main aspects of self-evaluation, or (iii) felt fat for more than half the days (criterion C) Objective binge episodes occurring at least once a week for a 3-month period (criterion A and C) Over that time compensatory behaviors were used at least once a week to prevent weight gain over a 3-month period, either (criterion B and C): Purging: self-induced vomiting, laxative, or diuretic abuse Fasting: going for periods of 8 or more waking hours without eating anything to influence shape or weight Excessive exercise: not including competitive sport, driven, exercised hard, felt guilty if prevented Over that time at least moderate importance of weight and/or shape (criterion D) Did not occur during an episode of AN (criterion E) Objective binge episodes occurring at least once a week for at least a 3month period unaccompanied by compensatory behaviors (criterion A and D) Did not occur during an episode of AN, BN or PD (criterion E) Criteria B and C not assessed Meets all the criteria for anorexia nervosa as defined above but BMI < 18.5 or individuals, who despite significant weight loss, have weight within or above the normal range. Among adolescents, significant weight loss was defined as a reduction of 1.3 kg/m2 in BMI Did not occur during an episode of BN or BED All of the criteria for bulimia nervosa are met, except that the binge eating and inappropriate compensatory behaviors occur, on average, less than once a week and/or for less than 3 months Did not occur during an episode of AN or BED Use of compensatory purging behaviors (as defined above) unaccompanied by objective binge episodes over a 3-month period Over that time at least moderate importance of weight and/or shape Did not occur during an episode of AN, BN, or BED
Diagnostic Assessment The EDE provides diagnostic information relating to the prior 3-month period and was supplemented with lifetime questions for the purpose of this study, including the age range during which each diagnostic criterion was met (to assess the co-occurrence of features). Previous work with the current population identifies the EDE as possessing high inter-rater reliability, good internal reliability, equivalency and stability of the combined weight, and shape concern subscale over increasing age.23 Table 1 provides information as to how the two groups (TED and OSFED) were derived. With respect to AN, the weight criterion is now referred to as “a significantly low body weight in the context of age, sex, developmental trajectory, and physical health.” For adults, the DSM-51 (p.23) details “a BMI of 18.5 kg/m2 has been employed by the Centers for Disease Control (CDC) and Prevention and the World Health Organization as the lower limit of normal body weight.” For children and adolescents, “determining the BMI-forage percentile is useful,” and suggests further that the International Journal of Eating Disorders 47:5 524–533 2014
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CDC uses a BMI-for-age below the 5th percentile as indicative of underweight status. As this sample consists of adolescents, this study adopts the aforementioned CDC recommendation as the criterion for assessing BMI status for children and adolescents. Additional issues regarding the specification of BMI related to the process of delineating A-AN. In translating the criterion for A-AN: “. . .significant weight loss. . .” (p. 353, DSM-5), we considered that many adolescents continue to increase in height and stature well into their teenage years,25,26 thus in relation to A-AN, we considered twins reporting significant weight loss constituting a decrease in BMI of 1.30 from baseline relative to BMI at each subsequent wave, in addition to those twins recording BMI less than 18.5. Both of these BMI thresholds had to be accompanied by the cognitive criteria specified for AN. Further, co-occurrence of the importance of weight and shape with behaviors could not be assessed for the BN, BN-L, and PD when examining occurrences of these diagnoses outside of the previous 3-month period, as this was only assessed where objective binge episodes and weight control behaviors occurred at least twice a week for 3 months (DSM-IV criteria). BED-L was not included in OSFED as a number of adolescents endorsed having an objective binge episode once a week over a 3month period, in excess of what would be clinically anticipated. Given the absence of the assessment of other criteria to assess BED, we determined that inclusion of such cases may increase Type 1 errors, and bias study results. Assessing Impairment In addition to diagnostic information, the EDE yields a global measure of eating psychopathology, which consists of the total of four subscales assessed over the previous 28 days, namely weight concern, shape concern, eating concern, and dietary restraint. This measure and current BMI centile measured at each wave were used to indicate impairment, as were four Wave 3 measures. These constitute two self-report measures, drive for thinness (7 items; a 5 0.83) and interoceptive awareness (10 items; a 5 0.93), sub-scales derived from the Eating Disorder Inventory.27 The two other scores were computerized neuropsychological assessments. The Trail Making Test was used to assess set shifting, where the condition, letters, and numbers are jumbled on the computer screen. Participants are required to click in alphabetical or numerical sequence, alternating between the two. A set shifting outcome previously examined by Tchanturia, Morris, Anderluh, Collier, Nikolaou, and Treasure28 was used in the current study, namely set shifting time that was adjusted by subtracting the practice condition time to control for potential differences in motor speed. A larger score indicates more time is required to respond International Journal of Eating Disorders 47:5 524–533 2014
to changing conditions. Central coherence was assessed using the Navon task.29 Here, participants are directed to search for a particular letter, which may be presented as a large letter formed by a collection of smaller different letters (global), or alternatively, smaller letters constitute the larger different letter (local). Two stimuli were presented simultaneously, a total of 36 items where the global target was produced on the left on 18 occasions and on the right on 18 occasions. Generally, the perceptual system processes every scene beginning with global features and progressing to the local features comprising them. Contrastingly, research identifies those with eating disorders often start locally, then progress to the global (i.e., “not seeing the wood for the trees”).16 This study used differences in local and global reaction times to identify weaknesses in central coherence, where more negative scores indicate faster local than global processing. Specific Risk Factors: Wave 1 Predictors of Wave 2 and 3 Eating Disorder Status Previously described self-report questionnaires21,27 included the following eight measures: concern over mistakes (Frost Multidimensional Perfectionism Scale)30; the internalization sub-scale (Multi-dimensional Media Influence Scale)31; weight-related peer teasing19; the perceived sociocultural pressure scale assessing perceived pressure to be thin from friends, family, media, and dating partners32; ineffectiveness and body dissatisfaction (Eating Disorder Inventory)27; and the “just right” subscale from the Vancouver Obsessional Compulsive Inventory.33 In this study, Cronbach’s alphas ranged from 0.64 to 0.91. Statistical Analysis Prevalence. Prevalence of the six disorders (AN, BN, BED, A-AN, BN-L, and PD) was calculated for each wave, and then across all waves. In the event that an adolescent met criteria for more than one disorder over the three waves, diagnosis was applied hierarchically (AN, BN, BED, A-AN, BN-L, and PD) as is common practice in research in this area.10 To calculate reliability, two raters (T.D.W. and A.K.F.S.) reviewed data for cases meeting eating disorder criteria using different methods of identification. Similarities between the assigned diagnoses were analyzed with the kappa statistic. Comparing Threshold and OSFED Groups. For the remaining analyses, three groups were formed, those people without an eating disorders, those with a threshold ED, and those with OFSED. While the different specific eating disorders with the threshold ED and OSFED cases are more typically compared with no eating disorder status, we considered that it was appropriate to group together the specific disorders within each broad category for the purpose of our aims, and also because:
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(i) the low prevalence rate of some of the specific disorders makes such comparisons unsuitable, (ii) precedence for such an approach when examining low prevalence disorders,32 and (iii) the likelihood that specific diagnostic status was likely to continue to change as the twins entered early adulthood. Indicators of impairment were compared across the three groups using linear mixed effects modeling. This procedure adjusts for correlated observations (such as twin data and repeated measures) and is asymptotically efficient with unbalanced data. Eating disorder status within each wave was used to assign group status, and dependent variables examined gave an indication of impairment from various perspectives. Bonferronicorrected a level adjusted significance for the multiple and post hoc testing required when undertaking a number of group comparisons. In order to examine latent risk factors, twin analyses were conducted of the diagnostic group membership. For the purpose of the twin analyses, a full information maximum likelihood approach was used with the statistical package Mx34 designed to apply structural equation modeling approaches to twin data. In the current study, raw data were analyzed in Mx which incorporates complete and incomplete pairs of twins and those with missing data across the waves of data collection by automatically creating the appropriate mean vector and covariance matrix for each observation.34 The twin pair correlations for monozygotic (MZ) and dizygotic (DZ) twins for each phenotype were computed. Given that MZ twins share 100% of their genes while DZ twins share, on average, only 50%, additive genetic effects on a phenotype are inferred when MZ twin correlations are roughly double DZ twin correlations.35 Shared environmental influences include environmental influences common to co-twins growing up in the same family and therefore contribute to their behavioral similarity to an equal degree in both MZ and DZ pairs. Nonshared environmental influences (which include measurement error) are those unique to each co-twin and are inferred when MZ twin correlations are less than 1.00. Nonadditive genetic influences (known as dominance) are implied if MZ correlations are more than twice that of the DZ correlations. We used a bivariate Cholesky decomposition model that included the two diagnostic groups (ever present across the 3 waves). The structure of this model can be seen in Figure 1. Bivariate models are more powerful than univariate models as they use both variances of individual variables and covariances between the different variables to estimate parameters.36 Our use of repeated measures can correct for any ascertainment bias resulting from differential attrition37 and also reduces the contribution of measurement error to the nonshared environment.38
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We first examined the models where the magnitude of the parameter estimates was allowed to differ across the three age cohorts, starting with a full model (i.e., containing the additive genetic variance [A], shared environment [C], and nonshared environment [E] sources of variance). We then fit a series of nested models in order to examine whether all sources of variance were required, reporting 95% confidence intervals (CI) for all estimates which helps us in examining the significance of models. Twice the difference in the log likelihood (22lnL) between a higher order and sub-model yields a statistic that is asymptotically distributed as chi square, with the degrees of freedom (df) equal to the difference in their number of parameters, and can be used to determine if the submodel is significantly worse fitting than the full model. Typically, where models do not differ significantly, the Akaike’s Information Criterion (AIC) is used to support the choice of a sub-model as the best fitting model, where the lower the value the better the balance between explanatory power and parsimony. In the current analyses, given our small sample size and limited power, the best fitting model will retain all parameters. This follows previous protocol39 and evidence40 suggesting that, in analyses based on discreet traits, estimates from the full ACE model will be more accurate and that attempts at parsimony result in oversimplification of the models rather than a simpler and more accurate representation of the data. Using linear mixed effects modeling, eight Wave 1 variables postulated to be specific risk factors were used to predict the development of TEDs, OSFED, or no disorder at Waves 2 or 3 in participants who had not reported an eating disorder at Wave 1 (i.e., people identified with an eating disorder at Wave 1 were omitted).
Results Prevalence
Across the three waves of female adolescent twin data, 73 girls (10.4%) met DSM-5 criteria for threshold or OSFED criteria (Table 2). The most prevalent diagnoses were BN-L (2.6%) and BED (2.4%), followed by AN, A-AN, BN, and, with very few cases, PD. Prevalence by diagnostic group indicates 5.4% of the sample had TEDs (AN, BN, or BED), and a further 5% had eating disorder symptomatology consistent with OSFED criteria. Therefore, of those cases meeting eating disorder criteria, 48% met OSFED diagnosis. Greater prevalence of binge/purge disorders was evident with increasing age. There were no significant differences between age of first diagnosis (p 5 .74; ES 5 0.08) between threshold (16.11 years) and OFSED (16.01 years) groups. Where data permitted, International Journal of Eating Disorders 47:5 524–533 2014
DSM-5 EATING DISORDERS AND OSFED
FIGURE 1 Path diagram showing the unstandardized parameter estimates (and 95% confidence intervals) for the Cholesky decomposition model for the two diagnostic groups (A, additive genetic influences; C, shared environmental influences; E, nonshared environmental influences).
comparisons of duration (months) across diagnoses were made. At Wave 1, there were no significant differences in duration of key symptoms between AN (fear of weight gain during low weight), BN/
BED (objective binge episodes), or A-AN (fear of weight gain) with respective means (SD) of 18.50 (20.50), 29.33 (18.01), 8.29 (11.84). Similarly, no differences were found at Wave 2, with respective
TABLE 2. Cases with prevalence and inter-rater reliability of lifetime disordered eating reported within and across each of the three waves of data collection Wave 1 12.7–16.28 Years N 5 699
Wave 2 13.76–17.56 Years N 5 669
Wave 3 15.49–19.84 Years N 5 499
Eating Disorder
N (%)
Kappa
N (%)
Kappa
N (%)
Kappa
Waves 1, 2, and 3aN 5 699 N (%)
Anorexia nervosa Bulimia nervosa Binge eating disorder Atypical anorexia nervosa Bulimia nervosa (low frequency/ limited duration) Purging Disorder TOTAL (%: 95% CI)
2 (0.3) 1 (0.1) 2 (0.3) 8 (1.1) 3 (0.4)
1 1 1 1 1
7 (1.0) 3 (0.4) 7 (1.0) 7 (1.0) 2 (0.3)
0.86 1 1 0.86 1
9 (1.8) 3 (0.6) 10 (2.0) 5 (1.0) 15 (3.0)
0.95 0.67 1 0.95 0.94
14(2.0) 7 (1.0) 17 (2.4) 13 (1.9) 18 (2.6)
a
0 (0) — 16 (2.3%: 1.4–3.6%)
3 (0.4) 1 29 (4.3%: 3.0–6.1%)
5 (1.0) 0.89 47 (9.4%: 7.1–12.2%)
4 (0.6) 73 (10.4%: 8.3–12.9%)
Diagnostic “trumping” AN > BN > BED > A-AN > PD > SubBN.
International Journal of Eating Disorders 47:5 524–533 2014
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FAIRWEATHER-SCHMIDT AND WADE TABLE 3. Comparison of impairment and risk factors across no disorder, threshold eating disorder, and other specified feeding or eating disorder groups among adolescent twin girls
Wave 1 Impairment EDE global Current BMI centile Wave 2 impairment EDE global Current BMI centile Wave 3 impairment EDE global Current BMI centile Drive for thinnessa Interoceptive awarenessa Central coherencea Set shifting timea Wave 1, 2, and 3 impairment EDE global Current BMI centile Drive for thinnessa Interoceptive awarenessa Central coherencea Set shifting timea
Wave 1 risk factors EDE global Peer teasing: weight related Thin ideal internalization Ineffectiveness Body dissatisfaction Concern over mistakes Need to get things “just right” Perceived pressure to be thin
No disorder Mean (SE) N 5 683 1
0.40 (0.03) 51.97 (1.53) N 5 670 0.34 (0.03)1 54.23 (1.51) N 5 452 0.31 (0.03)1 52.74 (1.94) 2.65 (0.06)1 2.45 (0.04)1 2192.00 (35.92) 742.87 (23.46)1 N 5 626 0.28 (0.03)1 52.73 (1.96) 2.63 (0.06)1 2.44 (0.04)1 2198.69 (37.18) 739.14 (23.54)
DSM-5 Threshold Mean (SE) N55
DSM-5 OSFED Mean (SE) N 5 11
2
2
1.33 (0.26) 50.42 (9.06) N 5 17 1.58 (0.14)2 52.05 (5.29) N 5 22 1.54 (0.13)2 39.60 (6.47) 4.07 (0.23)2 3.51 (0.15)2 2230.25 (175.62) 981.05 (91.03)2 N 5 38 1.47 (0.10)2 41.38 (5.41) 3.77 (0.19)2 3.24 (0.13)2 222.94 (132.22) 852.96 (77.10)
1.91 (0.18) 51.11 (6.61) N 5 12 1.96 (0.16)2 57.89 (6.27) N 5 25 1.34 (0.12)2 50.14 (5.53) 3.70 (0.21)2 3.05 (0.15)2 246.12 (135.41) 695.12 (83.87) N 5 35 1.27 (0.10)2 54.17 (5.20) 3.68 (0.19)2 2.96 (0.13)2 255.78 (121.40) 793.90 (76.75)
F (df) p [ES] 40.19 (646.88)
DSM-5 Eating Disorders and Other Specified Eating and Feeding Disorders: Is There a Meaningful Differentiation? A. Kate Fairweather-Schmidt, PhD* Tracey D. Wade, PhD
ABSTRACT Objective: In the DSM-5 diagnostic criteria for eating disorders, two main groups appear, threshold eating disorders (TED; anorexia nervosa, bulimia nervosa, and binge eating disorder), and other specified feeding and eating disorders (OSFED). In addition to calculating prevalence of these two groups, we examined the degree to which they could be differentiated in terms of impairment and risk factors. Method: Adolescent female twins (N 5 699) were interviewed with the Eating Disorder Examination on three occasions spanning 12.70–19.84 years of age. Assessments also included self-report measures related to impairment and risk. Results: Prevalence of DSM-5 ED in this adolescent population was 10.4%; 5.4% for TED and 5% for OSFED. Impairment levels did not distinguish TED and OSFED groups at any wave. Examination of latent risk factors showed TED and OSFED groups to share a common genetic basis; however, largely nonoverlapping unique
Introduction Broadly speaking, there have been two major changes introduced with respect to eating disorders in the Diagnostic and Statistical Manual of Mental Disorders—5th Edition.1 First, feeding disThis article was published online on February 25, 2014. Some additional information was added to the already existing acknowledgement section. This notice is included in the online version to indicate it has been corrected on March 13, 2014. Accepted 18 January 2014 Conflict of interest:The authors report no declarations of financial interest. Supported by 324715 and 480420 from the National Health and Medical Research Council (NHMRC) and by the Australian Twin Registry, which is supported by an Enabling Grant (ID 310667), from the NHMRC administered by the University of Melbourne. *Correspondence to: Dr. A. Kate Fairweather-Schmidt, School of Psychology, Flinders University, GPO Box 2100, Adelaide, South Australia 5001, Australia. E-mail: [email protected] School of Psychology, Flinders University, Adelaide, South Australia, Australia Published online 25 February 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/eat.22257 C 2014 Wiley Periodicals, Inc. V
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environmental influences contributed to the two groups. Specific risk factors commonly differentiated the no ED and TED groups, but not OSFED. Discussion: The findings suggest that TED and OSFED groups cannot be discriminated by prevalence or impairment or genetic risk factors. It is anticipated that OSFED will possess limited clinical utility for adolescents. Future research should examine clinical cases of these two groups in terms of meaningful differences, and a research focus should be maintained on both groups. Further examination of specific environmental risk factors that may attenuate the level of symptoms between the two groups may provide useful information for preC 2014 Wiley Periodicals, vention efforts. V Inc. Keywords: eating disorders; DSM-5; impairment; adolescents; OSFED (Int J Eat Disord 2014; 47:524–533)
orders emerging in childhood have been relocated to this section which is now called “Feeding and Eating Disorders.” Second, the criteria for eating disorders have been relaxed. It is this latter change that is the focus of the current investigation. The criteria related to previous threshold eating disorders (TEDs; anorexia nervosa [AN], and bulimia nervosa [BN]) have been broadened while also incorporating dimensionality. BED has now been included as a threshold disorder with specification of binging severity analogous to BN. Atypical anorexia nervosa (A-AN), bulimia nervosa of low frequency and/or limited duration (BN-L), and binge eating disorder of low frequency and/or limited duration (BED-L) joining purging disorder (PD) in the newly termed “Other Specified Feeding and Eating Disorders” (OSFED) category, replacing eating disorder not otherwise specified (EDNOS) in DSM-IV.2 These modifications were anticipated to promote more effective clinical description, in addition to informing/clarifying the expected course, and treatment options over time becoming International Journal of Eating Disorders 47:5 524–533 2014
DSM-5 EATING DISORDERS AND OSFED
achievable when patterns of symptomatology change are recognized and definable.3,4 The DSM-5 criteria modifications were made partially in response to issues with the EDNOS category. According to Keel, Brown, Holland and Bodell,3 “. . .EDNOS [was] a heterogeneous category . . .defined by what it [was] not. . .” (p. 384), that is, neither AN nor BN. This resulted in approximately half of all presenting cases including adolescents and children meeting criteria for EDNOS, which share a significant decrement in functioning and quality of life with threshold disorders, leading to the EDNOS diagnosis being considered deficient of clinical utility.3,5–7 Although criteria dictating DSM-5 diagnoses have been modified with the aim of reducing the number of EDNOS cases, two studies of DSM-5 eating disorders in young people (aged up to 20 years) suggest that OSFED represents 15–40% of DSM-5 cases,8,9 a proportion that is still seen as a cause for concern.10 Whether or not DSM-5 differentiates between TEDs and OSFED in a meaningful way, and thus represents improved clinical utility, can be judged by two main criteria: first, and consistent with the new emphasis in DSM-5, in relation to any differences in levels of reported impairment; and second, in relation to differences in identified risk factors. With respect to the first criterion, impairment can be assessed using a number of dimensional measures, including global eating disorder psychopathology assessed using the Eating Disorder Examination11 (EDE), which is typically used as a measure of treatment outcome in eating disorders across children and adults,11–13 in addition to body mass index (BMI). There is also a suggestion that impairment is indicated by several dimensional cognitive and neurobiological characteristics, including drive for thinness and body dissatisfaction,14 and executive functioning deficits and weak central coherence. Executive functioning deficits are represented by inefficient set shifting, or rigid cognitive styles or response inflexibility when problem solving, and are known to occur more frequently in disordered eating populations.15 Weak central coherence refers to an executive function deficit also occurring more commonly among individuals with eating disorders, demonstrated by an imbalance on dimensions of attention to detail versus global integration of information. Currently, there is stronger evidence linking eating disorders with poor global integrative capacity.16,17 While this deficit has been observed within people with a current eating disorder, individuals recovered from an eating disorder, and also among healthy family members of proInternational Journal of Eating Disorders 47:5 524–533 2014
bands with eating disorders, the deficit is more severe amongst the first group.15 If meaningful differentiation exists between TEDs and OFSED, we hypothesize that markers of impairment differ significantly between the two. The second criterion for judging whether there is meaningful differentiation between TEDs and OFSED is by examination of risk factors. In the broadest terms, latent risk factors can be identified as additive genetic, shared and/or unique environment, the presence of proportions of which is typically identified using twin analyses. Such analyses can also be used to identify overlap between these latent risk factors between different disorders. Specific risk factors for eating disorders are multiple,18 but in particular, this article will focus on environmental/social influences (weight-related peer teasing, thin ideal internalization, perceived pressure to be thin, body dissatisfaction), in addition to perfectionism and efficacy-related factors (need to get things “just right,” concern over mistakes, ineffectiveness). These are shown to consistently relate to eating psychopathological outcomes.18–20 This article utilizes the DSM-5 criteria to identify AN, BN, BED, A-AN, BN-L, and PD diagnoses, which are subsequently used to populate three groups: no eating disorder, TED (AN, BN, and BED), and OSFED (A-AN, BN-L, and PD). These groups are compared across a number of indicators to address our three main objectives. First, given only two previous studies exist that examine the prevalence of DSM-5 disorders in adolescents aged up to 20 years and only one of these examined the prevalence of specific categories within OFSED,8,9 to determine the prevalence of specific DSM-5 eating disorders, and the proportion of OFSED relative to threshold ED diagnoses. Second, to examine whether key variables related to impairment distinguish people with TEDs from OSFED, compared with those without an eating disorder. Third, to investigate whether risk factors for the two eating disorder groups overlap with respect to both latent risk factors (additive genetic and environmental variance in relation to the threshold and OSFED phenotypes) and specific risk factors.
Method Participants The current study uses three waves of data from adolescent female–female twin pairs. Participant characteristics and methodology used to derive this sample have been described previously.11,21–23 At Waves 2 and 3, all twins, responders and non-responders, were
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FAIRWEATHER-SCHMIDT AND WADE TABLE 1.
Diagnostic criteria for threshold and other specified or feeding eating disorders
Diagnosis Threshold eating disorders
Criteria (and Relation to DSM-5 Criteria) Anorexia nervosa
Bulimia nervosa
Binge eating disorder
Other Specified feeding or eating disorders
Atypical anorexia nervosa
Bulimia nervosa low frequency/limited duration Purging disorder
approached. The mean duration of time between Waves 1–2, and Waves 1–3 was 1.15 years (SD 5 0.17) and 2.96 years (SD 5 0.27), respectively, ranging from 1.91 to 4.65 years. Across the three waves, the ages ranged from 12.70 to 19.84 years. Procedure The twins were interviewed via telephone at each of the three waves. The interview consisted of two parts for Wave 1 and 2, where the first used the EDE,24 and the second constituted questions from self-report questionnaires assessing a range of variables including life events, temperament, and family functioning.21,22 Wave 3, however, involved only the EDE interview, whereas the other measures were undertaken online. Postgraduate Clinical Psychology trainees (n 5 16) who had been trained in use of the EDE conducted the interviews. To account for the slightly younger age of the sample relative to the original EDE population, it was modified slightly11,21 and was conducted at separate times and with a different interviewer for each child in the family.
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Intense fear of gaining weight was present on more than half the days over at least a 3-month period (criterion B) Over that period BMI for age percentile was < 5th percentile (pediatric criterion A) Over that time either (i) tried to lose weight or avoid weight gain, (ii) at least moderate importance of weight and/or shape, i.e., definitely one of the main aspects of self-evaluation, or (iii) felt fat for more than half the days (criterion C) Objective binge episodes occurring at least once a week for a 3-month period (criterion A and C) Over that time compensatory behaviors were used at least once a week to prevent weight gain over a 3-month period, either (criterion B and C): Purging: self-induced vomiting, laxative, or diuretic abuse Fasting: going for periods of 8 or more waking hours without eating anything to influence shape or weight Excessive exercise: not including competitive sport, driven, exercised hard, felt guilty if prevented Over that time at least moderate importance of weight and/or shape (criterion D) Did not occur during an episode of AN (criterion E) Objective binge episodes occurring at least once a week for at least a 3month period unaccompanied by compensatory behaviors (criterion A and D) Did not occur during an episode of AN, BN or PD (criterion E) Criteria B and C not assessed Meets all the criteria for anorexia nervosa as defined above but BMI < 18.5 or individuals, who despite significant weight loss, have weight within or above the normal range. Among adolescents, significant weight loss was defined as a reduction of 1.3 kg/m2 in BMI Did not occur during an episode of BN or BED All of the criteria for bulimia nervosa are met, except that the binge eating and inappropriate compensatory behaviors occur, on average, less than once a week and/or for less than 3 months Did not occur during an episode of AN or BED Use of compensatory purging behaviors (as defined above) unaccompanied by objective binge episodes over a 3-month period Over that time at least moderate importance of weight and/or shape Did not occur during an episode of AN, BN, or BED
Diagnostic Assessment The EDE provides diagnostic information relating to the prior 3-month period and was supplemented with lifetime questions for the purpose of this study, including the age range during which each diagnostic criterion was met (to assess the co-occurrence of features). Previous work with the current population identifies the EDE as possessing high inter-rater reliability, good internal reliability, equivalency and stability of the combined weight, and shape concern subscale over increasing age.23 Table 1 provides information as to how the two groups (TED and OSFED) were derived. With respect to AN, the weight criterion is now referred to as “a significantly low body weight in the context of age, sex, developmental trajectory, and physical health.” For adults, the DSM-51 (p.23) details “a BMI of 18.5 kg/m2 has been employed by the Centers for Disease Control (CDC) and Prevention and the World Health Organization as the lower limit of normal body weight.” For children and adolescents, “determining the BMI-forage percentile is useful,” and suggests further that the International Journal of Eating Disorders 47:5 524–533 2014
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CDC uses a BMI-for-age below the 5th percentile as indicative of underweight status. As this sample consists of adolescents, this study adopts the aforementioned CDC recommendation as the criterion for assessing BMI status for children and adolescents. Additional issues regarding the specification of BMI related to the process of delineating A-AN. In translating the criterion for A-AN: “. . .significant weight loss. . .” (p. 353, DSM-5), we considered that many adolescents continue to increase in height and stature well into their teenage years,25,26 thus in relation to A-AN, we considered twins reporting significant weight loss constituting a decrease in BMI of 1.30 from baseline relative to BMI at each subsequent wave, in addition to those twins recording BMI less than 18.5. Both of these BMI thresholds had to be accompanied by the cognitive criteria specified for AN. Further, co-occurrence of the importance of weight and shape with behaviors could not be assessed for the BN, BN-L, and PD when examining occurrences of these diagnoses outside of the previous 3-month period, as this was only assessed where objective binge episodes and weight control behaviors occurred at least twice a week for 3 months (DSM-IV criteria). BED-L was not included in OSFED as a number of adolescents endorsed having an objective binge episode once a week over a 3month period, in excess of what would be clinically anticipated. Given the absence of the assessment of other criteria to assess BED, we determined that inclusion of such cases may increase Type 1 errors, and bias study results. Assessing Impairment In addition to diagnostic information, the EDE yields a global measure of eating psychopathology, which consists of the total of four subscales assessed over the previous 28 days, namely weight concern, shape concern, eating concern, and dietary restraint. This measure and current BMI centile measured at each wave were used to indicate impairment, as were four Wave 3 measures. These constitute two self-report measures, drive for thinness (7 items; a 5 0.83) and interoceptive awareness (10 items; a 5 0.93), sub-scales derived from the Eating Disorder Inventory.27 The two other scores were computerized neuropsychological assessments. The Trail Making Test was used to assess set shifting, where the condition, letters, and numbers are jumbled on the computer screen. Participants are required to click in alphabetical or numerical sequence, alternating between the two. A set shifting outcome previously examined by Tchanturia, Morris, Anderluh, Collier, Nikolaou, and Treasure28 was used in the current study, namely set shifting time that was adjusted by subtracting the practice condition time to control for potential differences in motor speed. A larger score indicates more time is required to respond International Journal of Eating Disorders 47:5 524–533 2014
to changing conditions. Central coherence was assessed using the Navon task.29 Here, participants are directed to search for a particular letter, which may be presented as a large letter formed by a collection of smaller different letters (global), or alternatively, smaller letters constitute the larger different letter (local). Two stimuli were presented simultaneously, a total of 36 items where the global target was produced on the left on 18 occasions and on the right on 18 occasions. Generally, the perceptual system processes every scene beginning with global features and progressing to the local features comprising them. Contrastingly, research identifies those with eating disorders often start locally, then progress to the global (i.e., “not seeing the wood for the trees”).16 This study used differences in local and global reaction times to identify weaknesses in central coherence, where more negative scores indicate faster local than global processing. Specific Risk Factors: Wave 1 Predictors of Wave 2 and 3 Eating Disorder Status Previously described self-report questionnaires21,27 included the following eight measures: concern over mistakes (Frost Multidimensional Perfectionism Scale)30; the internalization sub-scale (Multi-dimensional Media Influence Scale)31; weight-related peer teasing19; the perceived sociocultural pressure scale assessing perceived pressure to be thin from friends, family, media, and dating partners32; ineffectiveness and body dissatisfaction (Eating Disorder Inventory)27; and the “just right” subscale from the Vancouver Obsessional Compulsive Inventory.33 In this study, Cronbach’s alphas ranged from 0.64 to 0.91. Statistical Analysis Prevalence. Prevalence of the six disorders (AN, BN, BED, A-AN, BN-L, and PD) was calculated for each wave, and then across all waves. In the event that an adolescent met criteria for more than one disorder over the three waves, diagnosis was applied hierarchically (AN, BN, BED, A-AN, BN-L, and PD) as is common practice in research in this area.10 To calculate reliability, two raters (T.D.W. and A.K.F.S.) reviewed data for cases meeting eating disorder criteria using different methods of identification. Similarities between the assigned diagnoses were analyzed with the kappa statistic. Comparing Threshold and OSFED Groups. For the remaining analyses, three groups were formed, those people without an eating disorders, those with a threshold ED, and those with OFSED. While the different specific eating disorders with the threshold ED and OSFED cases are more typically compared with no eating disorder status, we considered that it was appropriate to group together the specific disorders within each broad category for the purpose of our aims, and also because:
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(i) the low prevalence rate of some of the specific disorders makes such comparisons unsuitable, (ii) precedence for such an approach when examining low prevalence disorders,32 and (iii) the likelihood that specific diagnostic status was likely to continue to change as the twins entered early adulthood. Indicators of impairment were compared across the three groups using linear mixed effects modeling. This procedure adjusts for correlated observations (such as twin data and repeated measures) and is asymptotically efficient with unbalanced data. Eating disorder status within each wave was used to assign group status, and dependent variables examined gave an indication of impairment from various perspectives. Bonferronicorrected a level adjusted significance for the multiple and post hoc testing required when undertaking a number of group comparisons. In order to examine latent risk factors, twin analyses were conducted of the diagnostic group membership. For the purpose of the twin analyses, a full information maximum likelihood approach was used with the statistical package Mx34 designed to apply structural equation modeling approaches to twin data. In the current study, raw data were analyzed in Mx which incorporates complete and incomplete pairs of twins and those with missing data across the waves of data collection by automatically creating the appropriate mean vector and covariance matrix for each observation.34 The twin pair correlations for monozygotic (MZ) and dizygotic (DZ) twins for each phenotype were computed. Given that MZ twins share 100% of their genes while DZ twins share, on average, only 50%, additive genetic effects on a phenotype are inferred when MZ twin correlations are roughly double DZ twin correlations.35 Shared environmental influences include environmental influences common to co-twins growing up in the same family and therefore contribute to their behavioral similarity to an equal degree in both MZ and DZ pairs. Nonshared environmental influences (which include measurement error) are those unique to each co-twin and are inferred when MZ twin correlations are less than 1.00. Nonadditive genetic influences (known as dominance) are implied if MZ correlations are more than twice that of the DZ correlations. We used a bivariate Cholesky decomposition model that included the two diagnostic groups (ever present across the 3 waves). The structure of this model can be seen in Figure 1. Bivariate models are more powerful than univariate models as they use both variances of individual variables and covariances between the different variables to estimate parameters.36 Our use of repeated measures can correct for any ascertainment bias resulting from differential attrition37 and also reduces the contribution of measurement error to the nonshared environment.38
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We first examined the models where the magnitude of the parameter estimates was allowed to differ across the three age cohorts, starting with a full model (i.e., containing the additive genetic variance [A], shared environment [C], and nonshared environment [E] sources of variance). We then fit a series of nested models in order to examine whether all sources of variance were required, reporting 95% confidence intervals (CI) for all estimates which helps us in examining the significance of models. Twice the difference in the log likelihood (22lnL) between a higher order and sub-model yields a statistic that is asymptotically distributed as chi square, with the degrees of freedom (df) equal to the difference in their number of parameters, and can be used to determine if the submodel is significantly worse fitting than the full model. Typically, where models do not differ significantly, the Akaike’s Information Criterion (AIC) is used to support the choice of a sub-model as the best fitting model, where the lower the value the better the balance between explanatory power and parsimony. In the current analyses, given our small sample size and limited power, the best fitting model will retain all parameters. This follows previous protocol39 and evidence40 suggesting that, in analyses based on discreet traits, estimates from the full ACE model will be more accurate and that attempts at parsimony result in oversimplification of the models rather than a simpler and more accurate representation of the data. Using linear mixed effects modeling, eight Wave 1 variables postulated to be specific risk factors were used to predict the development of TEDs, OSFED, or no disorder at Waves 2 or 3 in participants who had not reported an eating disorder at Wave 1 (i.e., people identified with an eating disorder at Wave 1 were omitted).
Results Prevalence
Across the three waves of female adolescent twin data, 73 girls (10.4%) met DSM-5 criteria for threshold or OSFED criteria (Table 2). The most prevalent diagnoses were BN-L (2.6%) and BED (2.4%), followed by AN, A-AN, BN, and, with very few cases, PD. Prevalence by diagnostic group indicates 5.4% of the sample had TEDs (AN, BN, or BED), and a further 5% had eating disorder symptomatology consistent with OSFED criteria. Therefore, of those cases meeting eating disorder criteria, 48% met OSFED diagnosis. Greater prevalence of binge/purge disorders was evident with increasing age. There were no significant differences between age of first diagnosis (p 5 .74; ES 5 0.08) between threshold (16.11 years) and OFSED (16.01 years) groups. Where data permitted, International Journal of Eating Disorders 47:5 524–533 2014
DSM-5 EATING DISORDERS AND OSFED
FIGURE 1 Path diagram showing the unstandardized parameter estimates (and 95% confidence intervals) for the Cholesky decomposition model for the two diagnostic groups (A, additive genetic influences; C, shared environmental influences; E, nonshared environmental influences).
comparisons of duration (months) across diagnoses were made. At Wave 1, there were no significant differences in duration of key symptoms between AN (fear of weight gain during low weight), BN/
BED (objective binge episodes), or A-AN (fear of weight gain) with respective means (SD) of 18.50 (20.50), 29.33 (18.01), 8.29 (11.84). Similarly, no differences were found at Wave 2, with respective
TABLE 2. Cases with prevalence and inter-rater reliability of lifetime disordered eating reported within and across each of the three waves of data collection Wave 1 12.7–16.28 Years N 5 699
Wave 2 13.76–17.56 Years N 5 669
Wave 3 15.49–19.84 Years N 5 499
Eating Disorder
N (%)
Kappa
N (%)
Kappa
N (%)
Kappa
Waves 1, 2, and 3aN 5 699 N (%)
Anorexia nervosa Bulimia nervosa Binge eating disorder Atypical anorexia nervosa Bulimia nervosa (low frequency/ limited duration) Purging Disorder TOTAL (%: 95% CI)
2 (0.3) 1 (0.1) 2 (0.3) 8 (1.1) 3 (0.4)
1 1 1 1 1
7 (1.0) 3 (0.4) 7 (1.0) 7 (1.0) 2 (0.3)
0.86 1 1 0.86 1
9 (1.8) 3 (0.6) 10 (2.0) 5 (1.0) 15 (3.0)
0.95 0.67 1 0.95 0.94
14(2.0) 7 (1.0) 17 (2.4) 13 (1.9) 18 (2.6)
a
0 (0) — 16 (2.3%: 1.4–3.6%)
3 (0.4) 1 29 (4.3%: 3.0–6.1%)
5 (1.0) 0.89 47 (9.4%: 7.1–12.2%)
4 (0.6) 73 (10.4%: 8.3–12.9%)
Diagnostic “trumping” AN > BN > BED > A-AN > PD > SubBN.
International Journal of Eating Disorders 47:5 524–533 2014
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FAIRWEATHER-SCHMIDT AND WADE TABLE 3. Comparison of impairment and risk factors across no disorder, threshold eating disorder, and other specified feeding or eating disorder groups among adolescent twin girls
Wave 1 Impairment EDE global Current BMI centile Wave 2 impairment EDE global Current BMI centile Wave 3 impairment EDE global Current BMI centile Drive for thinnessa Interoceptive awarenessa Central coherencea Set shifting timea Wave 1, 2, and 3 impairment EDE global Current BMI centile Drive for thinnessa Interoceptive awarenessa Central coherencea Set shifting timea
Wave 1 risk factors EDE global Peer teasing: weight related Thin ideal internalization Ineffectiveness Body dissatisfaction Concern over mistakes Need to get things “just right” Perceived pressure to be thin
No disorder Mean (SE) N 5 683 1
0.40 (0.03) 51.97 (1.53) N 5 670 0.34 (0.03)1 54.23 (1.51) N 5 452 0.31 (0.03)1 52.74 (1.94) 2.65 (0.06)1 2.45 (0.04)1 2192.00 (35.92) 742.87 (23.46)1 N 5 626 0.28 (0.03)1 52.73 (1.96) 2.63 (0.06)1 2.44 (0.04)1 2198.69 (37.18) 739.14 (23.54)
DSM-5 Threshold Mean (SE) N55
DSM-5 OSFED Mean (SE) N 5 11
2
2
1.33 (0.26) 50.42 (9.06) N 5 17 1.58 (0.14)2 52.05 (5.29) N 5 22 1.54 (0.13)2 39.60 (6.47) 4.07 (0.23)2 3.51 (0.15)2 2230.25 (175.62) 981.05 (91.03)2 N 5 38 1.47 (0.10)2 41.38 (5.41) 3.77 (0.19)2 3.24 (0.13)2 222.94 (132.22) 852.96 (77.10)
1.91 (0.18) 51.11 (6.61) N 5 12 1.96 (0.16)2 57.89 (6.27) N 5 25 1.34 (0.12)2 50.14 (5.53) 3.70 (0.21)2 3.05 (0.15)2 246.12 (135.41) 695.12 (83.87) N 5 35 1.27 (0.10)2 54.17 (5.20) 3.68 (0.19)2 2.96 (0.13)2 255.78 (121.40) 793.90 (76.75)
F (df) p [ES] 40.19 (646.88)
