Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?

PHB-10313; No of Pages 18 Physiology & Behavior xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Physiology & Behavior journal homepage: www.elsevier.com/locate/phb

Review

Characterization of eating patterns among individuals with eating disorders: What is the state of the plate? Kelsie T. Forbush ⁎, Tyler K. Hunt Purdue University, Department of Psychological Sciences, 703 Third Street, West Lafayette, IN 47907, United States

H I G H L I G H T S • • • •

We We We We

review diagnostic definitions for eating disorders. review literature on eating patterns and diet quality in eating disorders. review ecological momentary assessment studies in eating disorders. identify areas for future research on eating patterns in eating disorders.

a r t i c l e

i n f o

Article history: Received 6 December 2013 Received in revised form 15 February 2014 Accepted 17 February 2014 Available online xxxx Keywords: Eating disorders Eating patterns Diet quality Binge size Ecological momentary assessment Meal skipping

a b s t r a c t Eating disorders will affect approximately 18 million individuals in the United States at some point in their lives, and are associated with significant psychological distress, psychosocial and quality-of-life impairment, medical morbidity, and mortality. Although aberrant eating behaviors play a central role in diagnostic definitions for eating disorders, much remains to be learned about eating patterns, diet quality, and energy balance among individuals with eating pathology. The goal of the current paper was to systematically review and integrate findings from published research studies characterizing the eating behaviors of individuals with eating disorders, including findings from both descriptive and laboratory-based research. We also describe results from studies using ecological momentary assessment — a methodology that assesses individuals' behaviors in their natural environment as they occur, which may reduce retrospective recall bias, and provide improved ability to prospectively assess the temporal occur of changes in multiple eating behaviors over time. We conclude with suggestions for future research, including the need for additional studies to test for differences in eating patterns among different demographic groups of individuals with eating disorders, and the need for new, more objective, assessment tools. © 2014 Published by Elsevier Inc.

Contents 1.

2.

3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1. Diagnostic definitions of eating disorders . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2. Why study eating patterns in individuals with eating disorders? . . . . . . . . . . . . . . . . Caloric intake, diet quality, and energy balance in individuals with anorexia nervosa . . . . . . . . . . 2.1. Caloric intake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Macro- and micro-nutrient intake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Energy balance required for weight restoration . . . . . . . . . . . . . . . . . . . . . . . 2.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Calorie intake, diet quality, and meal patterns in individuals with bulimia nervosa or binge eating disorder 3.1. Caloric intake during binge eating episodes . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Macro- and micro-nutrient intake and palatable food consumption during binge eating . . . . . 3.2.1. Binge eating disorder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2. Bulimia nervosa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

⁎ Corresponding author. Tel.: +1 765 494 6982. E-mail address: [email protected] (K.T. Forbush).

http://dx.doi.org/10.1016/j.physbeh.2014.02.045 0031-9384/© 2014 Published by Elsevier Inc.

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

0 0 0 0 0 0 0 0 0 0 0 0 0

2

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

3.2.3. Palatable food consumption . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.4. Comparisons between binge eating disorder and bulimia nervosa . . . . . . . . 3.3. Eating patterns outside of binge episodes . . . . . . . . . . . . . . . . . . . . . . . 3.4. Meal patterns, snacking, and frequency, timing, and duration of binge eating episodes . . . 3.4.1. Meal patterns and snacking . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.2. Frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.3. Duration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.4. Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.5. Timing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Idiosyncratic consummatory behaviors among individuals with anorexia nervosa or bulimia nervosa 4.1. Fluid intake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Caffeine intake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Artificial sweetener use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Ecological momentary assessment (EMA) studies of eating disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Dietary restraint, hunger, and caloric restriction as antecedents to binge eating . . . . . . 5.2. Temporal patterns of binge eating . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3. Role of loss-of-control over eating . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Conclusions and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Eating disorders will affect approximately 18 million individuals in the United States at some point in their lives [54], and are associated with significant psychological distress, quality-of-life impairment [22,88], and medical morbidity (for a review, see [94]). The risk for mortality for individuals suffering from eating disorders is higher than for any other psychiatric disorder [18,51,91], and on par with mortality rates for serious non-psychiatric diseases, such as acute lymphocytic leukemia [55]. Mortality in individuals with eating disorders is often related to the effects of starvation (e.g., renal failure or heart attack) or to suicide [18,145]. Although eating disorders represent significant public health concerns, treatments for certain eating disorders often are inefficacious [10], and much remains to be learned about psychological, biological, and behavioral factors involved in the etiology and maintenance of eating pathology. 1.1. Diagnostic definitions of eating disorders The Fifth Edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; [3]) includes four specific eating disorders: anorexia

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

. . . . . . . . . . . . . . .

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

0 0 0 0 0 0 0 0

nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), and other specified feeding or eating disorder (OSFED) (see Table 1). The cardinal feature of AN is restriction of energy intake relative to requirements that results in a significantly low body weight. Additional symptoms include an intense fear of gaining weight or becoming ‘fat’, or persistent behavior that interferes with weight gain, and disturbance in the way in which one's body weight or shape is perceived. Notably, a portion of individuals with AN may also regularly engage in binge eating and/or purging behaviors (forced expelling of food or calories from the body [e.g., self-induced vomiting, laxative misuse, diuretic misuse]). Individuals with BN experience recurrent episodes of binge eating (episodes in which the person eats a large amount of food and experiences a subjective sense of loss-of-control over their eating), inappropriate compensatory behaviors (e.g., fasting, excessive exercise, or purging), and their self-evaluation is largely based on their body weight or shape. BED, like BN, is also characterized by recurrent binge eating episodes, but without the accompanying compensatory behaviors. BED requires the presence of several behavioral and cognitive indicators reflecting loss-of-control over eating, and requires that the binge eating episodes be accompanied by marked distress. Low weight is a diagnostic criterion for AN, but not for BN or BED (e.g., if an individual endorses all

Table 1 Diagnostic terms and definitions. Term

Definition

Objective binge episodes (OBEs)

Eating within a discrete period of time (e.g., within any two-hour period), an amount of food that is ‘definitely larger’ than what most others would eat during that time under similar circumstances. These episodes must be accompanied by a sense of lack of control during the eating episode (e.g., feeling that one cannot control what or how much one is eating). An eating episode that occurs within a discrete period of time, and that is accompanied by a sense of lack of control during the eating episode. However, the eating episode is not definitely larger than what most others would eat during that time under similar circumstances. Forced expelling of food or calories from one's body. Includes self-induced vomiting, laxative, diuretic, enema, or suppository misuse. Can also include omission of insulin in individuals with Type I diabetes mellitus, and inappropriate use of thyroid medication. Behaviors to counteract the effects of eating or to lose weight. Includes purging behaviors (see above), fasting, and excessive exercise.

Subjective binge episodes (SBEs) Purging Inappropriate compensatory behavior (ICB) Anorexia nervosa (AN) Bulimia nervosa (BN) Binge eating disorder

Other specified feeding or eating disorder (OSFED)

Self-starvation syndrome characterized by fear of weight gain, and perceptual distortion in how one views one's body weight or shape. Some individuals with AN engage in recurrent episodes of binge eating and/or purging. Recurrent objective binge eating episodes and inappropriate compensatory behavior that occurs once per week or more for three months. Individuals also base their self-evaluation largely upon their body shape or weight. Cannot occur exclusively during episodes of AN. Recurrent objective binge eating episodes and marked distress that the binge eating is present. Associated with cognitive symptoms, such as feeling disgusted, depressed, or very guilty after the binge eating episodes. Cannot be associated with regular use of ICBs, and cannot occur exclusively during episodes of AN or BN. Eating disorders that cause clinically significant distress, psychosocial impairment, or increase risk for death or disability, but do not meet full criteria for the other eating disorders.

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

the required symptoms of BN, but his/her weight is less than minimally normal, he/she would be diagnosed with AN). Although not required for a diagnosis, many individuals with BN have a normal body mass index (BMI), but more recent research indicates that there is a trend for more individuals with BN to present for treatment in the overweight or obese weight ranges [11]. BED is strongly associated with obesity in both clinical [83,89,130] and community samples [114,124]. As we will describe in this review, eating patterns figure prominently into the reasons for these diagnostic differences in body weight. Finally, OSFED represents a range of different types of eating disorders that are clinically significant (i.e., cause significant psychosocial impairment, distress, or increase risk for death or disability), but do not meet criteria for AN, BN, or BED. For example, individuals who engage in recurrent purging in the absence of objectively large binge eating episodes, and do not have a low body weight, would not meet criteria for either BN (due to the absence of objective binge eating episodes) or AN (due to the absence of low weight). Research studies have indicated that OSFED is: (a) not simply a less severe or impairing form of eating pathology, with studies indicating that psychosocial impairment in individuals diagnosed with OSFED is similar to that in individuals with traditionally defined eating pathology [132], and (b) highly prevalent [76]. Indeed, OSFED accounts for fully 50–60% of all individuals with eating disorders [65,75]. 1.2. Why study eating patterns in individuals with eating disorders? As described above, disruptions in eating patterns, diet quality, and energy balance play a central role in diagnostic definitions for eating disorders. Yet, there are relatively few well-controlled, empirical studies that have tested for differences in eating patterns between individuals with and without eating disorders, or among individuals with different types of eating pathology. Additional research characterizing real-world eating patterns among individuals with eating disorders would, therefore, provide useful information that could be used to better distinguish those with eating disorders from abnormal (but benign) eating behaviors that occur in the general population of non-eating-disordered adults. Moreover, data characterizing eating patterns among individuals with different forms of eating pathology could be used to develop more empirically based phenotypes for eating disorders that may improve upon certain limitations inherent to rationally derived nosological schemes, such as the DSM-5. In the current paper, we discuss the results of published research on the eating patterns of individuals with eating disorders, as well as highlight several potential directions for future research on this topic. 2. Caloric intake, diet quality, and energy balance in individuals with anorexia nervosa Methods for assessing dietary intake among individuals with AN have included food diaries, 24 hour recalls, and observational studies. Food diaries are typically filled out for three to seven consecutive days, and participants are instructed to record all food and beverages consumed throughout their day. Similarly, 24-hour recalls require participants to report detailed information documenting their dietary intake, but these recalls cover only one day and participants are asked to report on the foods and beverages consumed over the previous day (i.e., retrospectively) [36,112]. Because 24-hour recalls ask only about the preceding day, they may not represent typical dietary intake (although 24-hour recalls administered at repeated intervals can help to reduce this limitation) [5,15,90]. Observational studies occur in inpatient settings, where participants select foods from a menu or laboratory vending machine; laboratory test meals provide participants with a buffet of food and participants are instructed to eat their meal within a specific amount of time (typically 1 h). For both observational and laboratory test meals, foods are weighed before and after consumption

3

to calculate kilocalories (kcal) and nutrient composition for the eating episode(s).

2.1. Caloric intake Findings from published research studies indicate that individuals with AN eat significantly fewer kcal per day than healthy comparison groups (see Table 2). This pattern of results is robust across method, and is supported by findings from laboratory test meals [16,71,101,144], inpatient observational studies [20,63,64], and 24hour dietary recalls or food diaries [1,85,102]. Across the studies we reviewed, mean intake for individuals with AN was 1285 kcal per day (see Table 2), which was a lower value than the average intake of control participants, which was 1532 kcal per day. Given that a cardinal symptom of AN is low body weight, it is unsurprising that calories consumed by those with AN are lower than those of control subjects. However, average daily kilocalories appeared to be larger for 24-hour recalls or food diaries (1679 kcal) compared to inpatient observational studies (1405 kcal) (see Table 2). The amount of calories reportedly consumed by individuals with AN tends to be higher than expected by clinicians [110], which may be due, in part, to substantial heterogeneity with regard to caloric intake between individuals with the binge–purge sub-type of AN (vs.) the restricting sub-type of AN. For example, Burd et al. [12] examined caloric intake for participants with full- or sub-threshold AN who engaged in binge eating only, purging only, binge eating and purging, and no binge eating or purging. Participants completed one, two, or three 24-hour dietary recalls using the Nutrition Data Systems for Research Database for nutrient calculations. Discrete eating episodes ranged from zero kcal (diet soda only) to 15,000 kcal, suggesting that binge eating episodes among individuals with AN can be extremely large (although the majority of eating episodes were below 1000 kcal). Participants consumed significantly more total daily calories on days during which they binged and purged (vs.) binge only days, purge only days, and days in which no binge eating or purging occurred, providing evidence for variability of caloric intake as a function of the type of eating episode and whether purging behaviors were present after the eating episode. Another explanation for the larger-than-expected self-reported dietary intake of individuals with AN may be due to over-reporting caloric intake. Studies that have directly compared food diaries to actual observed dietary intake (i.e., observational studies or laboratory-based test meals) indicate that persons with AN over-report their caloric intake by up to 460 kcal [45,131], and the tendency to over-report caloric intake persists even after participants have restored their body weight to within normal limits [110,131]. Of interest, these results are the opposite of those found among normal or overweight control subjects, who consistently under-report their caloric intake [45,110,131]. On the other hand, it is important to note that studies using observational or laboratory-based test meals to investigate caloric intake of persons with AN may have limited ecological validity. It is possible that dietary intake assessed by hospital staff within a controlled environment may not be an accurate reflection of patients' eating behaviors as they would occur in the ‘real world’, because participants may modify their eating behaviors within a supervised environment. For example, in the study conducted by Mayer et al. [82], food was presented to patients in a buffet style, which may have induced binge eating episodes among some participants (particularly if patients typically avoid buffet-style restaurants or “forbidden foods” in their daily life). Most observational studies have been limited to foods that are available from the hospital kitchen or pre-packaged foods, which may not reflect patients' typical dietary choices. Relative to participants' typical food selections, prepackaged and hospital-prepared foods may provide greater energy density, which potentially could lead to the perception of greater intake in laboratory-based settings compared to participants' self-reports.

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

4

Reference

Sex

Laboratory test-meal Mayer et al. [82] F (92%), M (8%)

Age

Mean BMI (%ABW, or % IBW)

N

Method

Kilocalories consumed during OBE

Kilocalories consumed during nonbinge days or non-binge test meal

Average daily kilocalories

Kilocalories consumed by control group

Macronutrient differences (or food content differences)

27 ± 8

Baseline: 15.5 ± 2.12 kg/m2 After weight restoration: 20.2 ± 0.68 kg/m2

18

2 d. lab study; multiple-item, 1 d. occurred within first two weeks of inpatient hospital admission; 2 d. occurred after patient had restored to at least 19.5 kg/m2.

–

Baseline: 365a ± 208 After weight restoration: 516a ± 273, participants ate significantly more during the second test meal

–

Meal one: 775 ± 228 Meal two: 758 ± 346

19.7 ± 0.9 kg/m2, participants with AN had restored their weight to 90% of their ideal body weight 20.2 ± 0.8 kg/m2, participants with AN had restored their weight to 90% of their ideal body weight

18

Multiple-item, lab meal.

–

440 ± 254

–

OC: 702 ± 309 NC: 718 ± 255

AN N NCa proportion carbohydrate at both test meals AN N NCa proportion protein at meal one, but not after weight restoration (meal two) AN b NCa proportion fat at both test meals –

27

Ten participants completed a 1 d. yogurt shake, 23 participants completed a multiple-item lab meal, and 11 participants completed a single-item lab meal.

–

Yogurt shake: 116.9 ± 80.2 Single item: 181.3 a ± 235.9 Multiple item: 492.1 a ± 304.2

–

–

Schebendach et al. [110]

F

27.1 ± 8.5

Steinglass et al. [117]

F

25.9 ± 7.0

Steinglass et al. [149]

F

28.1 (range: 17–38) standard deviation not provided

16.1 ± 1.9 kg/m2

9

Multiple-item, lab meal.

–

Pre-treatment: 429 ± 169 Post-treatment: 434 ± 242

–

Yogurt shake: 151.3 ± 69.8 Single item: 530.9 ± 178.3 Multiple item: 750.7 ± 318.3 –

23.8 ± 0.7

16.3 ± 0.3 kg/m2

30

–

–

1289 b ± 150

2220 ± 108

–

Restricting subtype: 29.5 kg Binge/purge subtype: 34.5 kg (mean weight reported; no standard deviations reported) %IBW 57.3 ± 0.95

11

1 d. observation inpatient study, food was provided from a research metabolic kitchen. 1 d. observational inpatient study, food was provided from hospital kitchen. Calories were calculated based on weighing food before and after meals.

–

–

Restricting subtype: 874 ± 222 Binge/purge subtype: 1037 ± 101

1725 ± 304

–

3 d. observational inpatient study, patients told to maintain their weight and allowed to choose any food from the hospital menu.

–

–

1016.6 b ± 54

1652 ± 108.8

AN b NCb total daily intake of protein, fat, and carbohydrates.

Inpatient observational Hadigan et al. [45] F

Kaye et al. [62]

F

Averages not provided

Richardson Curtis et al. [20]

F

23.2 ± 0.94

24

–

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

Table 2 Characterization of eating patterns among individuals with anorexia nervosa across method.

18.2 ± 1.9 kg/m2

8

3 d. food record

–

–

1446 b ± 417

1823 ± 478

Burd et al. [12]

F

24.4 ± 7.5

17.2 ± 0.9 kg/m2

84

1606.7 ± 856.1

1612.1 ± 1568

1812.6 ± 1857.2

–

Hadigan et al. [45] Misra et al. [85]

F F

23.8 ± 0.7 15.9 ± 0.3

16.3 ± 0.3 kg/m2 16.5 ± 0.2 kg/m2

30 39

Eight participants completed a 1 d. 24-hour dietary recall, 11 participants completed a 2 d. 24hour dietary recall, and 65 participants completed a 3 d. 24-hour dietary recall. 30 d. Burke diet history 4 d. food diary, included 3 weekdays and 1 weekend day

– –

– –

1602 b ± 200 1649c ± 110

1614 ± 64 1970 ± 91

Schebendach et al. [110]

F

27.1 ± 8.5

18

4 d. food diary

–

491 ± 290

–

OC: 542 ± 269 NC: 738 ± 310

Steinglass et al. [149]

F

9

4 d. food record

–

–

Pre-treatment: 3251 ± 551 Post-treatment: 2568 ± 425

–

–

Van Binsbergen [150]

F

28.1 (range: 17–38) standard deviation not provided 24.7 ± 3.9

19.7 ± 0.9 kg/m2, participants with AN had restored their weight to 90% of their ideal body weight 16.1 ± 1.9 kg/m2

14.4 ± 1.54 kg/m2

20

Burke diet history

–

–

N 1500 calories for 17 participants; no mean caloric intake reported

Information not provided

–

AN b NCb proportion fat intake AN = NC proportion protein intake –

AN b NCc proportion of carbohydrates as glucose AN N NCc proportion of carbohydrates as lactose AN b NCc calories from fats AN N NCc calories from carbohydrates and proteins –

%ABW = percent of average body weights as defined by the 1959 Metropolitan Insurance Table Standards. d. = day. NC = normal weight controls. OC = weight-stable obese controls. Sysko et al. [131] were not included in the table because average meal consumption was measured in grams instead of kilocalories. Jáuregui-Lobera and Bolaños-Ríos [148] were not included in the table because it was unclear whether participants consumed the food, or simply made selections of what they would choose to eat. a Test meal calories were significantly different between eating disorder (ED) group and normal weight, non-ED control group. b Daily calories were significantly different between ED group and normal weight, non-psychiatric control group. c Daily calories were significantly different between ED group and normal weight, non-ED control group.

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

24-hour dietary recall or food diaries Affenito et al. [1] F 14.5 ± 3.3

5

6

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

2.2. Macro- and micro-nutrient intake Few studies have compared micro- and macro-nutrient intake between individuals with AN compared to healthy controls. Misra et al. [85] compared the nutrient intake of adolescent girls with full- or subthreshold AN to healthy adolescent girls who were recruited from the community. Participants completed food diaries for three weekdays and one weekend day. Results indicated that girls with AN consumed a significantly lower percentage of calories from fats, and a significantly greater percentage of calories from carbohydrates and proteins. There were no significant differences between groups for intake of calcium, zinc, and iron; however, total intake of calcium, zinc, and iron was higher for participants with AN due to greater dietary supplement use. Girls with AN had significantly greater intakes of vitamins A, D, and K, and a significantly greater portion of girls with AN met the reference intake for calcium and vitamin D from dietary supplement use. Similar results were reported by Affenito et al. [1], who used prospective longitudinal data from the National Heart, Lung, and Blood Institute Growth and Health Study to investigate changes in macronutrient intake before and after the acute onset of AN compared to healthy controls (who were matched on ethnicity and age). Information was collected from participants two- and one-year(s) prior to the onset of AN, as well as during the acute illness phase. Results showed no significant between-group differences for macronutrients consumed from total energy prior to the acute onset of illness. During the acute illness phase, individuals with AN consumed a significantly lower proportion of total energy from fat, and a marginally higher proportion of total energy from protein compared to healthy controls. Taken together, these two studies indicate that adolescent girls with AN consume significantly fewer percent total calories from fat and greater calories from protein than healthy comparison participants. 2.3. Energy balance required for weight restoration An important aspect of treatment for AN involves the normalization of eating behaviors to restore patients' body weights to within normal limits. Research has indicated that patients with AN require approximately 8000 ± 2000 kcal to gain 1 kg of body weight [24,32,61,108,123,133]. The large range is due, in part, to the effects of physical over-activity among some individuals with AN [61]. Other possible explanations for the large variance in calories needed to promote weight gain include: prior history of obesity [7,123], individual differences in body composition [56], adjustment to higher kcal intake [4,84], and increased metabolic rate [92,133]. Notably, basal metabolic rate during weight restoration for patients with AN has shown to be double of that observed in studies of normal-weight subjects who are experimentally overfed, or underfed and re-fed [92]. Kaye et al. [62] investigated differences in energy balance requirements needed for weight restoration between individuals with the restricting subtype of AN (AN-R), compared to the binge–purge subtype (AN–BP). Participants were administered nutritionally stabilized meals to ensure weight maintenance for four to six weeks. After the initial weight maintenance period, these same participants were provided with a diet designed to restore body weight for an additional four to six weeks. An independent sample of participants who had recovered from AN for at least one year was admitted to the inpatient unit for a similar period of time. Foods were provided by hospital kitchen staff, and meals were weighed before and after consumption. After controlling for body mass index, results indicated that participants with AN-R needed to eat significantly more than participants with AN-BP to maintain their body weight. All participants were monitored for the presence of binge eating, physical activity, and vomiting; thus, differences in energy balance required to restore weight could not be explained by between-group differences in binge eating, purging, or physical activity. These results were replicated after short- and long-term weight restoration. In other words, individuals with AN-R needed to consume more

kcal per day to maintain (or restore) their weight compared to individuals with AN-BP. Findings reported by Kaye et al. are suggestive of potential alterations in metabolic efficiency that may result from chronic binge–purge behaviors and starvation. 2.4. Summary Individuals with AN consume fewer total calories and calories from fat, but higher protein, compared to controls. Caloric intake appeared to be lower for laboratory or inpatient observational studies compared to self-report-based studies, which may indicate the presence of overreporting dietary intake or a lack of real-world validity in laboratory settings. Notably, over-reporting of caloric intake persists after weight-restoration. Results from other studies indicated substantial between-subject heterogeneity. For example, eating episodes in individuals with AN ranged from 0 to 15,000 kcal, indicating the presence of large binge eating episodes among a portion of those with AN. Overall, results supported diagnostic definitions for AN, although retrospective self-reports of caloric intake among individuals with AN may not accurately reflect actual dietary intake. Additional research using more objective methods in naturalistic settings or statistical adjustments to correct for over-reporting of dietary intake may be warranted. 3. Calorie intake, diet quality, and meal patterns in individuals with bulimia nervosa or binge eating disorder Various methods have been used to characterize dietary intake during binge episodes among individuals with BN or BED. Laboratory studies of binge eating generally present participants with large amounts of a single-food item (e.g., cookies) or a multiple-food item buffet. During “binge” conditions, participants are instructed to “let yourself go…,” and are encouraged to eat as much as they wish. Other laboratory-based methods for studying eating behaviors among individuals with bingeeating syndromes include inpatient observational studies that provide participants with ad libitum access to foods (either from a vending machine or laboratory kitchen). Non-laboratory methods include food diaries or 24-hour dietary recall studies (for additional details, see Section 2). 3.1. Caloric intake during binge eating episodes Findings from the research studies we reviewed indicated that caloric intake during binge eating episodes for individuals with BN or BED is higher than the eating episodes of normal weight or obese control subjects (see Table 3). Control participants consumed 1244 kcal during eating episodes for studies of BN and 1493 kcal for studies of BED. Across the studies we reviewed, the average size of binge eating episodes was 2482 kcal for individuals with BN and 2048 kcal for individuals with BED. For individuals with BN, binge eating episodes were generally larger for laboratory-based studies (2803 kcal) compared to 24-hour dietary recalls or food diaries (1371 kcal) (see Table 3), whereas few between-method differences were found for the size of binge eating episodes in individuals with BED (average size of binge eating episodes was 1956 in laboratory studies and 2753 in 24-hour dietary recalls or food diaries). (It is important to note, however, that these differences were not directly compared using a statistical test. Future studies are needed to determine whether apparent between-method differences in binge eating episode size are statistically significant.) 3.2. Macro- and micro-nutrient intake and palatable food consumption during binge eating 3.2.1. Binge eating disorder Two studies indicated that the proportion of calories consumed from protein or meat during binge eating episodes was significantly greater for individuals with BED (vs.) obese controls [16,103]; however,

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

another study found that the percent of protein intake was lower during binge eating episodes for individuals with BED (vs.) obese controls [144]. Findings from other research suggest that the proportion of calories consumed from dairy or fat during binge eating episodes was greater for persons with BED (vs.) obese controls [101,144]. However, several other studies have failed to find differences in macronutrient composition of binge eating episodes among persons with BED [37,101], and one study found that the percent of calories from carbohydrates was greater for those with BED, compared to obese controls, on non-binge days [102]. Taken together, these results support the theory that individuals prone to engage in binge eating increase their intake of food regardless of taste properties [96]. 3.2.2. Bulimia nervosa Results from two studies indicate that the macronutrient content of binge eating episodes among those with BN does not significantly differ from the eating episodes of normal control subjects [64,136]. However, Kaye et al. [64] found that individuals with BN consumed a greater proportion of calories from carbohydrates, and fewer calories from fat, when meals were matched in size to control participants. Finally, Gendall et al. [35] compared women with BN, who were recruited to take part in an outpatient treatment trial, to population norms for macronutrient content from women aged 19–44 who participated in the Life in New Zealand Study [107]. Results indicated that women with BN ate a lower percentage of calories from protein, and a greater percentage of calories from carbohydrates, sucrose, and fat compared to population norms. Nevertheless, findings from Gendall et al. [35] should be interpreted with caution because individuals with BN completed a 14 day food diary, whereas population norms were obtained using a 24hour recall conducted via telephone interview. Within-group comparisons among persons with BN have found either no differences for macronutrient content between binge and nonbinge days [106], or indicated that individuals with BN eat significantly more vegetables on non-binge days, and significantly more snacks and desserts on binge days [104]. Findings suggest that binge episodes among individuals with BN are characterized by the consumption of a greater portion of calories from carbohydrates, whereas few other consistent results emerged. Inconsistent findings for macro- and micro-nutrient content of eating episodes among individuals with BED and BN may reflect the fact that the majority of studies on this topic had small sample sizes (N's ranged from 5 to 54; see Table 3), that may have been under-powered for testing between-group differences. 3.2.3. Palatable food consumption Findings from laboratory test meal studies indicate that participants with BN or BED select dessert and snack foods first during binge conditions [46,144]. These results were corroborated by Weltzin et al. [136], who found that individuals with BN who overate during a 24 hour observational study tended to eat more dessert and snack foods than individuals with BN who under-ate or normal controls. However, a study by Cooke et al. [16] found that persons with BED did not differ from controls with regard to the number of snack or dessert foods consumed during a multi-item laboratory meal. 3.2.4. Comparisons between binge eating disorder and bulimia nervosa Fitzgibbon and Blackman [31] tested whether energy consumption and diet quality during binge eating episodes differed between individuals with BN (vs.) BED using retrospective self-reported dietary intake. These authors found that individuals with BN reported consuming a greater portion of calories from carbohydrates compared to persons with BED. However, total caloric intake and the portion of calories from fat and protein did not differ significantly between diagnostic groups during binge episodes in Fitzgibbon and Blackman's study (see Table 3).

7

3.3. Eating patterns outside of binge episodes Several studies suggested that individuals with BN consume fewer calories and restrict their eating outside of binge episodes or on nonbinge days [59,71,104,106]. However, Kaye et al. [64] found that nonbinge eating episodes among individuals with BN were relatively large, with amounts of up to 600 calories for single-item test meals and 3000 calories for multi-item test meals — although these results could potentially reflect “failed” attempts to refrain from binge eating episodes among some study participants. Other studies indicated that calories consumed on non-binge days, or during non-binge laboratory meals were greater than the calories consumed during binge days [35,103] (see Table 3). Inconsistent findings for calories consumed outside of binge episodes may be due to within- and between-subject heterogeneity in eating patterns that occur over study observation periods. For example, Weltzin et al. [136] carried out a relatively large study of individuals with BN who were observed for 24 h on an inpatient unit. During the study period, approximately 44% of individuals with BN over- or binge-ate, 37% ate normally, and 19% of the sample underate. These findings suggest that studies following subjects over relatively short time intervals may not accurately reflect overall eating behaviors, given that substantial within-person fluctuations in eating behavior may occur over more extended time periods. Studies of individuals with BED indicate that fewer calories are consumed during non-binge days (vs.) days when binge eating is present [102,144], although one study found that persons with BED ate more during non-binge days [103]. Despite the diagnostic requirement that individuals with BED cannot engage in fasting or dietary restriction, it is unclear whether the size of non-binge eating episodes in those with BED is larger than in persons with BN. For example, Yanovski et al. [144] found that the size of eating episode during a non-binge laboratory test meal was within the range reported for individuals with BN (see Table 3). 3.4. Meal patterns, snacking, and frequency, timing, and duration of binge eating episodes 3.4.1. Meal patterns and snacking Masheb et al. [81] have shown that individuals with BN are significantly more likely to skip meals, compared to normal controls, and are significantly more likely to skip breakfast and lunch when compared to individuals with BED. Somewhat surprisingly, however, these same authors found that the frequency of meal skipping among participants with BN was not significantly correlated with binge eating or purging episodes. With regard to individuals with BED, studies have found that average dinner frequency and average meals per day were significantly negatively correlated with binge eating episodes [80,81], suggesting that greater frequency of eating meals is associated with fewer binge eating episodes in persons with BED. Increased breakfast consumption was significantly negatively correlated with BMI among individuals with BED (but not for persons with BN) [80,81]. Of interest, individuals with BED or BN reported more frequent “nibbling” between meals, eating double-meals, and nocturnal eating episodes (eating episodes that occurred after the person had gone to bed [note that participants were fully conscious for nocturnal eating episodes]) [81], and evening snacking episodes were significantly positive correlated with binge episodes in persons with BED [80]. 3.4.2. Frequency Rossiter and Agras [105] found that the mean number of binge episodes per week was 10 in women with BN who completed a seven day food diary. In a seven day observational inpatient study at the National Institute of Health, individuals with BN experienced an average of 1.6 episodes per day, and purged approximately three times per day [53]. These results are supported by an early descriptive study of over 300 community-recruited women who engaged in binge eating

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

8

Reference

Diagnostic group(s)

Laboratory test-meal Cooke et al. BED [16]

Sex

Age

Mean BMI (%ABW, or % IBW)

N

Method

Kilocalories consumed during OBE

Kilocalories consumed during non-binge days or non-binge test meal

Average daily kilocalories eating disorder group

Kilocalories consumed by control group

Macronutrient differences (or food content differences)

F

37 ± 12.8

33.4 ± 5.1 kg/m2

10

1 d. lab study, multiple-item meal

1515a ± 392.9

–

–

1115 ± 317.6

3 d. lab study; 1 d. yogurt shake, 2–3 d. single-item or multiple-item meal (counterbalanced) 4 d. lab study with 1 week between each laboratory session; conditions included presentation of a single or two preferred binge foods at two or four times the amount consumed during participants' self-reported typical binge episodes

Single item: 742.5 ± 245.4 Multiple item: 1514.7a ± 392.9

–

–

Single item: 781 ± 423 Multiple item: 1115.2 ± 317.6

BED N OC for meat BED = OC for total amount of foods eaten from dessert, vegetable, and carbohydrates categories No significant differences between BED and OC in the single item meal

One food, 2 times quantity: 1769 ± 1399 One food, 4 times quantity: 1825 ± 1238 Two foods, 2 times quantity: 2005 ± 1601 Two foods, 4 times quantity: 2501 ± 1625 3469c ± 1347

–

–

One food, 2 times quantity: 944 ± 841 One food, 4 times quantity: 1020 ± 883 Two foods, 2 times quantity: 1205 ± 945 Two foods, 4 times quantity: 1609 ± 1662

–

1198c ± 11,689

–

Binge: 1412 ± 277 Non-binge: 856 ± 265 –

–

Goldfein et al. [37]

BED

F

37.0 ± 12.8

33.4 ± 5.1 kg/m2

10

Gosnell et al. [150]

BED

F (60%), M (40%)

38 (standard deviation and range not provided)

All participants required to have ≤ 130% IBW

5

Hadigan et al. BN [46]b

F

24.2 ± 2.2

−1.5 ± 12.4% 11 below normal weight for age and height

2 d. lab study; multi-item test meals separated by 2–3 d.

Kissileff et al. [68]

BN

F

23 ± 3.51

%IBW 95.12 ± 12.05

8

Single item: 1335.8 ± 1018.7 Multiple item: 4476.8 ± 2154

Single item normal – meal: 636.9 ± 514.2 Multiple item normal meal: 3076.8 ± 2485.4

LaChaussée et al. [71]

BN

F

24.6 ± 5

19.52 ± 1.82 kg/m2

8

4 d. lab study; 1 d. yogurt shake, 2–3 d. multi-item test meal; 4 d. participants instructed to eat normally. Lab visits were spaced two-three days apart 4 d. lab study; half of sessions were single-item, the other half were multiple-item; meals were between 4–6 PM

Single item: 1389.9 c,d ± 612 Multiple item: 2679.7 c,d ± 2137.2

Single item: 469.8 ± 669 Multiple item: 729.2 ± 658

–

Raymond BED et al. [101]e

F

38 ± 8

40 ± 6 kg/m2

12

2151.31a ± 430.61

–

–

Yanovski et al. [144]

F

36.2 ± 2.6

40.1 ± 3.4 kg/m2

19

2 d. lab study, multiple-item; participants had a pre-visit in which they listed preferred binge foods, and select foods were available for the lab study 3 d. lab study; 1 d. yogurt shake, 2 d.–3 d. multiple-item (separated by two days); 2 d.–3 d. test meals began at 5 PM

2963 a,d ± 127

2343 a ± 240

–

BED

Single item binge: 307.8 ± 44.4 Single item non-binge: 243.5 ± 145.5 Multiple item binge: 1039.6 ± 418.9 Multiple item non-binge: 958.2 ± 311.9 1608.89 ± 700.13

Binge: 2017.2 ± 267.7 Non-binge: 1641.9 ± 64.5

–

–

BED N OC in number of dairy items consumed in lab test meal

BED = OC for non-binge meal BED N OC for percent calories from fat BED b OC for percent calories from protein

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

Table 3 Characterization of eating patterns among individuals with bulimia nervosa or binge eating disorder across diagnosis and method.

Reference Diagnostic group(s)

Sex

Age

Mean BMI (%ABW, or % IBW)

N

Method

Kilocalories consumed during OBE Kilocalories consumed during non-binge days or non-binge test meal

Average daily kilocalories eating disorder group

Kilocalories consumed by control group

Macronutrient differences (or food content differences)

Inpatient observational Hetherington BN et al. [52]

F

24.2 ± 1.3

%ABW 92.8 ± 2.7

10

7 d. observation study on an inpatient unit

–

–

9378f ± 1143

1924 ± 102

BN b NC for percent calories from protein BN N NC for percent calories from fat BN = NC for the percent calories from carbohydrates N for all meals Y for meals matched on size (BN N NC for carbohydrates, BN b NC for fat) –

Kaye et al. [64]

BN

F

23 ± 4

%ABW 103 ± 9

21

3 d. observational inpatient study; foods available from vending machine

7100.9c ± 9546.4 (binge day)

2335.2 ± 2571

–

Kaye et al. [63]

BN

F

21 ± 4

%ABW 106 ± 12

17

2131 ± 1154

–

–

Weltzin et al. [136]

BN

F

24.8 ± 6.3

22.3 ± 3.1 kg/m2

54

1 d. observational inpatient study; foods available from vending machine 1 d. observational study (access to vending machine)

Binge day: 1844.4 ± 618.7 Non-binge day: 1831.1 ± 436.5 –

–

–

4446f ± 584

1845 ± 649

No macronutrient differences between BN and NC Participants with BN who underate, consumed b fat than NC Under-eating BN N NC for carbohydrates

Recovered: 58 kg (range: 47–77 kg) Untreated: 58 kg (range: 47–71 kg)

31 (19 7 d. food diary untreated and 12 recovered)

–

–

1494 (range: 740–2263)

No significant differences between BN groups and NC

23 ± 2.6 kg/m2

50

14 d. food diary; participants contacted on 2 d., 7 d., and 14 d. to encourage adherence

1596.5c ± 1788.7

1362.6 c ± 719.4

Untreated: 1669f (range: 746–2836) Recovered: 1734f (range: 1122–2319) –

Binge: 1020.3 Non-binge: 1301.6 (SD not provided)

2709.5±713.1

BN b Population norms for intake of protein BN N Population norms for intake of carbohydrates, sucrose, saturated fatty acids, and monounsaturated fatty acids N for OBE days Y for non-OBE days (BED NOC for carbohydrates) Participants consumed a greater percentage of calories from protein on binge vs. non-binge days at baseline. Participants consumed a greater percentage of calories from protein and fat on binge vs. non-binge days at six months.

24-hour dietary recall or food diaries Elmore and BN F deCastro et al. [151]

Gendall et al. [35]

BN

F

Recovered: 26 (range: 18–36) Untreated: 22 (range: 18–35) 27.6 ± 6

Raymond et al. [102]

BED

F

37.9 ± 7.8

39.6 ± 6.2 kg/m2

12

Six random 24-hour dietary recall interviews

3395.2a ± 568.2

2458.4 ± 630.4

Reeves et al. [103]g

BED

F

Averages not provided

Averages not provided

36

7 d. food diary completed at baseline and six-month follow-up

Baseline: 2112 ± 532 Six months:1963 ± 621

– Baseline: 2394 ± 633 Six months:1633 ± 626

–

Rosen et al. [104]

BN

F

22 (standard deviation and range not provided)

−0.8% standard deviation from average weights as calculated by Metropolitan Life Insurance Data

20

14 d. food diary

1459 d ± 1172

321 ± 260

–

–

Rossiter and BN Agras [105]

F

21.5 kg/m2 (standard deviation and range not provided)

32

7 d. food diary

1255.89 ± 722.34

–

–

–

Rossiter et al. [106]

F

30.4 (standard deviation and range not provided) 44.4 ± 8.4

33 ± 5.7 kg/m2

22

7 d. food diary

602 ± 634

1500 ± 456.6 d (non-binge days)

–

–

BN (nonpurging)

2423.7 ± 546.3

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

BED N OC for number of dessert and snack foods consumed during normal and binge meals

Within-group differences indicated participants ate more vegetables on non-binge days, and more snacks and desserts on binge days –

No within-group differences for macronutrient percentages eaten on binge vs. non-binge days

9

(continued on next page)

10

Reference

Diagnostic group(s)

Sex

Age

Mean BMI (%ABW, or % IBW)

N

Method

Kilocalories consumed during OBE

Kilocalories consumed during non-binge days or non-binge test meal

Average daily kilocalories eating disorder group

Kilocalories consumed by control group

Macronutrient differences (or food content differences)

Woell et al. [141]

BN

F

27 (range: 20–41 years)

20.5 kg/m2 (range: 17.3–23.9)

30

21 d. food diary

1945 (standard deviation not provided)

–

3117 (standard deviation not provided)

–

–

77 (35 BED and 42 BN)

Retrospective self-report of intake during a binge episode

BED: 2306.5 ± 1205.2 BN: 2799 ± 1536.9

–

–

–

BN N BED for total carbohydrates. BN N BED for sugar intake. BN = BED for fat, protein, and overall kcal consumed.

9

7 d. ecological momentary assessment

BED: 837.6c ± 53.3 SE OC: 739.4 ± 42.0 SE NC: 414.6 ± 40.4 SE

–

BED: 2536f ± 136.1 SE OC: 2005 ± 107.3 SE NC: 1606 ± 103.3 SE

OC binge: 739.4 ± 42 SE NC binge: 414.6 ± 40.4 SE OC daily intake: 2005 ± 107.3 SE NC daily intake: 1606.0 ± 103.3 SE

–

Retrospective self-report (non-food diary or 24-hour recall) BED or BN F (91%), M BED: BED: 41.1 ± Fitzgibbon (9%) 40.3 ± 10.1 9.6 kg/m2 and BN: 28 ± 7.2 BN: 23.5 ± 7.2 kg/m2 Blackman [31]h Ecological momentary assessment Engel BED F, M (genet al.[27] der proportions not provided)

37.3 ± 4.9

42.3 ± 3.4 kg/m2

%ABW = percent of average body weights as defined by the 1959 Metropolitan Insurance Table Standards. d. = day. OC = obese controls. Differences listed in the 'Macronutrient differences' column were significantly different between groups, unless otherwise indicated (above). a Significant difference in eating episode between eating disorder (ED) group and obese, non-ED control group. b Seven participants had to be dropped from data analyses because they did not follow study instructions. c Significant difference in eating episode between ED group and normal weight, non-ED control group. d Calories consumed were significantly different between binge and non-binge meals. e The first three participants with BED expressed a preference for evening binge eating episodes, so the protocol was changed from beginning at 9:30 AM to beginning at 5 PM for all subsequent participants. No analyses were undertaken to determine the potential impact of changing the protocol. f Daily calories were significantly different between ED group and non-ED control group. g Reported race/ethnicity. h Two participants with BED did not have a binge episode during the study period, and are not included in the column describing calories consumed during an OBE.

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

Table 3 (continued)

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

and purging behaviors, which found that approximately 50% of the sample engaged in binge eating at least once per day, and approximately 42% engaged in purging at least once per week [58]. 3.4.3. Duration Binge episodes among individuals with BN during laboratory test meals have been demonstrated to range from approximately 23–25 min for single-item test meals [68,71] to 53 min for multipleitem meals, despite participants being given 2 h to complete the meal [46,68,71]. These data are supported by the results of a food diary study of females with BN-NP, who reported an average binge duration of 38 min [107]. Other self-report studies indicated that binge eating episodes last between 37 min to slightly over 1 h [57,86,87,99], and that 78% to 98% of binge eating episodes last for 2 h or less [53,58]. LaChaussée et al. [71] found that the overall length of meals did not differ significantly between individuals with BN and controls, yet the rate of eating during a multiple-item test meal was significantly different from the speed of eating during a non-binge laboratory meal. Goldfein et al. [37] found that the duration of eating in those with BED was generally longer than that of obese control participants without BED, and ranged from 19 min (single-item test meal) to 34 min (multiple-item meal). Although these data support current diagnostic definitions for binge eating episodes, which require episodes to occur within discrete periods of time (e.g., within 2 h), Wolfe et al. [142] noted that some individuals with BN or BED reported experiencing binge eating episodes that lasted for much longer than two hours, which she referred to as “binge days” (although others have termed this phenomenon “grazing”). In support of the concept of “binge days” or “grazing,” women with the nonpurging sub-type of BN (BN-NP; n = 22) reported eating more frequently (more times throughout the day) on binge days vs. non-binge days in a food diary study [106]. Close to a third of Rossiter et al.'s sample reported “grazing” patterns on at least one of the seven food diary days. However, in a larger 24-hour laboratory observation study of women with BN (n = 54) who had ad libitum access to food, there were no significant differences between those with BN and normal controls on the number of meals eaten per day [136] (note: in the study by Weltzin et al. [136], all participants has self-induced vomiting as their only purging method). As mentioned previously, Rossiter et al. [106] noted that some participants with BN under-ate during the study observation period. Under-eaters ate fewer total meals per day compared to individuals with BN who ate normal daily calorie amounts, or those who over-ate. Moreover, there was a trend for individuals with BN who over-ate during the observation period to eat more total meals than controls. Finally, several studies indicate that individuals with BED eat more on binge days than on non-binge days, which is suggestive of “grazing” patterns within this population [50,72,102,103,109,144]. Together, these studies suggest that for some individuals with BN or BED, it may be difficult to define discrete “binge eating episodes,” given that persons may have difficulty discerning among multiple large eating episodes that occur on the same day. This issue potentially could be even more pronounced for those with BED who do not have clear markers for the end of binge eating episodes (given that individuals with BED do not engage in self-induced vomiting). 3.4.4. Size As noted earlier, the findings we reviewed from laboratory, food diary, and 24-hour dietary recall studies indicated that the average number of calories consumed during binge eating episodes was over 2000 kcal for individuals with BED or BN. For individuals with BN, the results of published studies indicated that binge eating episodes were larger for laboratory-based studies (vs. studies that relied on selfreports). Although these results indicate that binge eating episodes are quite large (on average), other research calls into question the clinical utility and validity of the amount of food eaten for defining binge eating

11

episodes. Studies that have used self-identified binge eating episodes among persons with eating disorders indicate that there is large variability in terms of what is thought to constitute “binge eating.” As noted by Rosen et al. [104], the large range of self-reported kilocalories consumed during self-defined binge eating episodes may reflect the salience of individuals' subjective feelings of anxiety and control when determining what is perceived to be binge eating. In a two-week prospective food diary study, Crowther et al. [19] noted that the lower range of what was considered a “binge eating episode” was 30 kcal, whereas the upper-limit was slightly over 2000 kcal among undergraduate women. Evidence related to this issue is strengthened by results from other studies which show that 30% of participants with bulimic syndromes characterized their eating episodes as “binge episodes,” despite consuming less than 500 kcal, whereas approximately 7% of patients did not consider an eating episode a “binge” unless it was greater than 2000 kcal [141]. The issue of participants' lay definitions of “binge episodes” differing from diagnostic and research definitions is a critical issue, which may potentially impact the results of participant self-reported binge eating. Several studies utilize investigator-defined cut-offs of 500 or 1000 kcal as the minimum size required for an eating episode to be classified as a “binge” [2,44,102]. However, in a study by Rossiter and Agras [105], 55.6% of self-identified binge eating episodes were below 1000 kcal and 27.7% of self-identified binge eating episodes were below 500 kcal in a sample of 32 women with BN. The number of calories for an eating episode to be self-identified as a binge episode among women with BED ranged from 500 to 800 calories [41]. Clarification of the validity and clinical utility of various definitions of binge eating size will be an important area for future assessment and classification research in the field of eating disorders. 3.4.5. Timing A small literature has sought to identify peak times of the day during which binge episodes are most likely to occur. Retrospective data consistently indicate that the peak time for binge eating episodes is in the afternoon or evening [52,58,87,111]. This early finding has been replicated in both naturalistic [111] and laboratory studies [52]. For example, Hetherington et al. [52] reported that for individuals with BN, a significantly greater percentage of binges were reported in the evening (53.2%) and afternoon (32.6%) compared with the morning (14.2%). We will return to the issue of peak times of day for binge episodes in the section on ecological momentary assessment (see Section 5). 3.5. Summary Individuals with BN or BED experience binge eating episodes that are approximately 2000 kcal, although some studies indicate that the threshold for an eating episode to be self-identified as a “binge” may be substantially lower for a sizeable portion of individuals. Meal skipping and evening snacking were associated with increased frequency of binge episodes in individuals with BED, yet were not associated with binge eating or purging frequency among persons with BN. Results generally supported DSM-definitions for the frequency and duration of binge eating episodes. Nevertheless, additional research is needed to: (a) clarify the validity and clinical utility of various definitions of binge eating duration (e.g., whether binge eating that occurs over longer durations, such as “binge days” and “grazing” episodes, should be considered binge eating episodes); (b) identify important sources of within- and between-subject heterogeneity in calories consumed outside of binge eating episodes; and (c) better characterize the quality of binge eating episodes in terms of macro- and micro-nutrient composition. The incorporation of larger, well-powered samples will be critically important for addressing these issues, as the majority of studies we reviewed were based on small samples.

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

12

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

4. Idiosyncratic consummatory behaviors among individuals with anorexia nervosa or bulimia nervosa Clinicians treating individuals with AN and BN have frequently observed that patients engage in a range of “idiosyncratic” consummatory behaviors, including restriction or over-consumption of fluids, aberrant preference for sweet tasting foods, and excessive consumption of caffeine, sugar-free soft drinks, and non-nutritive sweeteners. These clinical observations have recently been supported empirically using retrospective and prospective self-report surveys and interviews, which we describe below: 4.1. Fluid intake Hart et al. [49] carried out the first empirical investigation of fluid intake among 81 patients admitted to an eating disorder treatment program (n = 48 AN, n = 16 BN, n = 17 OSFED). Participants were interviewed by a hospital dietician about their intake of all fluids consumed during the seven days prior to hospital admission. Patients described their fluid intake in terms of cans, glasses, bottles, and cups, which was converted into average daily intake in milliliters and milliliters per kilogram (alcohol use was converted into standard units [i.e., one unit of alcohol equaled 10 g of alcohol]). Results indicated that mean fluid intake among patients was 2731 ± 1580 mL per day (range was 250 mL to 6925 mL per day). Alcohol use was relatively rare among patients (78% reported no alcohol consumption), and only one participant reported excessive alcohol intake in the seven days prior to hospitalization. Based on dietary standards outlined by Curtain University [25], fluid intake was below daily recommendations in 28.4% of the sample, and above recommendations in 54.3% of patients. There was a significant negative correlation between body mass index and fluid intake, and a significant positive correlation among age and fluid intake among patients with eating disorders. Although Hart et al.[49] did not test differences in fluid consumption between sub-types of AN, recent work by Marino et al. [78] indicated that fluid intake does not differ significantly between individuals with AN-R (vs.) AN-BP, although purging behaviors were significantly positively correlated with water intake. The substantial variability in reported fluid intake may be due to different motivations for fluid ingestion among patients with eating disorders. Specifically, some participants may have engaged in “waterloading” in an effort to increase body weight to prevent hospitalization, stave off hunger, or increase feelings of ‘fullness’, whereas other participants may have restricted fluid intake in an effort to lose weight or to gain a greater subjective sense-of-control over their ingestive behavior. 4.2. Caffeine intake Caffeine is a widely used stimulant with properties that include increased metabolism, appetite suppression, diuretic action, and delayed onset of fatigue [17,74]. Several studies have examined caffeine consumption among individuals with eating disorders, and have found evidence that individuals with binge–purge syndromes (such as BN and AN-BP) consume significantly more caffeine than individuals with AN-R or control subjects [9,13,49,70] — however, one study failed to find significant differences in caffeine intake between participants with AN-R (vs.) AN-BP [78]. Hart et al. [49] reported that participants who engaged in purging had greater intake of caffeinated beverages (18 mL/kg body weight ± 23) compared to subjects who did not engage in purging (10 mL/kg body weight ± 16), and similar results were found for participants who engaged in binge eating compared to participants who did not binge eat. Krahn et al. [70] found that the number of binge eating and purging episodes per week was significantly positively correlated with caffeine intake, and other research suggests that the lifetime shift from a non-purging to purging eating disorder is associated with increased caffeine use [13].

Recent studies have attempted to identify potential reasons for excessive caffeine consumption among individuals with binge–purge syndromes. Burgalassi et al. [13] found that caffeine intake had significant positive correlations with other forms of substance abuse, and suggested that individuals with binge–purge syndromes have greater substance and caffeine use due to high levels of disinhibition (i.e., problems with behavioral restraint, which may lead an individual to make impulsive choices). Krahn et al. [70] hypothesized that starvation increases the reinforcing properties of caffeine, given that findings from animal studies show that the reinforcing effects of drugs are potentiated during periods of food deprivation [6,23]. In support of this hypothesis, Krahn et al. note that participants in the Minnesota Starvation Study [67] demonstrated evidence for both increased binge eating and caffeine intake during a period of starvation. We suggest that in addition to the abovementioned reasons for increased caffeine intake among individuals with binge–purge syndromes, individuals who engage in purging may be using caffeine as an additional external method to influence their weight, shape, and appetite (given the presence of diuretic use, laxative use, and diet pill use among these individuals). Although additional studies are needed to test this hypothesis, it is noteworthy that individuals with BED, who engage in binge eating without engaging in inappropriate methods of compensating for eating episodes, do not demonstrate elevated levels of caffeine use compared to control subjects [13], whereas those who engage in only purging or purging and binge eating have been shown to consume significantly higher amounts of caffeine (as described above). 4.3. Artificial sweetener use In a series of case studies, Ohlrich et al. [93] evaluated 21 consecutive patients with eating disorders who were admitted to an adolescent inpatient treatment unit. Ohlrich et al. found that 18 patients reported using sorbitol (a polyalcohol sweetener often used in “sugar free” items) on a daily basis. Patients self-reported the following reasons for sorbitol use: obtaining a laxative effect for the purpose of weight loss, appetite suppression, and avoidance of binge eating and self-induced vomiting (i.e., to refrain from eating-disorder-related behaviors). Klein et al. [69] carried out an empirical investigation of chewing gum, artificially sweetened low-calorie beverage, and artificial sweetener packet use among females with AN (n = 30; 60% restricting subtype), BN (n = 48), and healthy control subjects (n = 32). Participants completed surveys (either written or via interview) to assess their use of artificial sweeteners retrospectively, over the previous month (or in the month prior to hospitalization for inpatients). Their results indicated that participants with AN-BP or BN had significantly higher use of artificially sweetened gum and diet soda than controls. Individuals with AN-BP chewed 26.7 ± 22.8 pieces of gum per week, persons with BN chewed 31.2 ± 56.2 pieces, and controls chewed 7.2 ± 10.1 pieces. Similarly, individuals with AN-BP drank 39.5 ± 23.7 (12 ounce) servings of diet soda per week, individuals with BN drank 25.4 ± 46.1 servings, and controls drank 7.4 ± servings. Klein et al. found that individuals with AN consumed a striking number of packets of artificial sweetener (Splenda ®, Equal ®, Sweet n' Low ®) per week. The mean number of packets of artificial sweetener was 350.3 ± 423.3 among participants with AN-R, 100.7 ± 104.2 among participants with AN-BP, 38.6 ± 97.0 among participants with BN, and 8.7 ± 11.5 among control subjects. Due to the extremely high use of artificial sweeteners per week among participants with AN, study investigators followed-up with select participants to inquire about their patterns of use. An anecdotal response from one of Klein et al.'s participants indicated that she was eating “Equal ® sandwiches,” and a response from another participant indicated she was eating sweeteners directly from the packets — consuming more than 100 packets per day. Although standard deviations for the mean number of artificial sweetener packets consumed per week suggested high variability among participants, it is noteworthy that 33.3% of participants

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

with AN-R, and 91.7% of participants with AN-BP reported consuming artificial sweeteners in the previous month. Brown and Keel [9] carried out a study to identify factors that contribute to excessive intake of diet soda among individuals with eating disorders, including biological (increased appetitive drive) and psychological (increased weight concerns) factors. Community-recruited individuals with an eating disorder (who had current or lifetime diagnoses) were compared to healthy controls matched on gender, age, and race/ ethnicity. Results indicated that individuals with BN drank more diet soda per week compared to control subjects [9]. Results further indicated that endorsement of the following DSM symptoms was associated with greater diet soda intake: heightened fear of weight gain, drive for thinness, consumption of objectively large amounts of food, loss-ofcontrol over eating, and objective binge episodes. Brown and Keel posited that because semi-starvation and weight suppression stimulate appetite, this may drive individuals to choose foods and beverages with high orosensory stimulation and minimal calories (to avoid the potential effects of consumption of energy-dense foods on body weight). Notably, artificial sweetener and diet soda intake stimulates the taste reward circuitry, but at lower magnitudes than sucrose [33], such that individuals with eating disorders may need to consume higher amounts of artificial sweeteners to satisfy their desire for sweet tastes. Findings from research studies have shown a variety of negative health outcomes that may result from the consumption of non-caloric sweetened beverages. For example, evidence suggests that the consumption of artificially sweetened beverages may lead to increased body weight, Type II diabetes, hypertension, and cardiovascular disease [26,34,77]. Swithers et al. [129] have proposed a model for these adverse health outcomes. Specifically, individuals who ingest artificial or non-nutritive sweeteners may be “training” their bodies to associate sweet tastes with the absence of calories, which may lead to dysregulation of the body's ability to accurately signal the caloric consequences of foods and drinks ingested. This hypothesis has been supported by findings from animal studies, which have found that intake of non-nutritive sweeteners is associated with increased food intake, weight gain, accumulation of body fat, and decreased caloric compensation (when compared to the consumption of glucose) in rats [21,127,128]. Thus, artificial sweetener use among individuals with eating disorders may be clinically important itself, given that these ingestive behaviors may lead to adverse physiological effects, or exacerbate already existing medical problems. Additional research in this area would be useful to better understand how excessive use of artificial sweeteners may affect physical health and treatment outcomes in persons with eating pathology.

13

5. Ecological momentary assessment (EMA) studies of eating disorders Past research often has utilized retrospective methods to assess disordered eating behaviors (see Tables 2 and 3). Retrospective reports ask individuals to think back over several hours, weeks, months, or years to make reports about their eating behaviors, which may increase the likelihood that participants will make inferences about partial memories, if they are unable to remember their past eating behaviors [8]. Laboratory studies attempt to mitigate these problems by collecting “real-time” data of participants' eating behaviors. These studies are favored because the experimental design enables researchers to make claims about causal relations among variables. However, the ecological validity of laboratory studies is often questioned because laboratory settings may differ from participants' natural environments. Due to these concerns, researchers in the field of EDs have increasingly been utilizing ecological momentary assessment, which we describe below. Ecological momentary assessment (EMA) is a method for collecting “real-time” data about subjects' current behaviors and experiences, as they are occurring in individuals' natural environments. Current EMA methodology generally uses hand-held computers (e.g., palm pilots) or mobile phone applications to signal participants to complete selfreports at semi-random intervals throughout the day (signal-contingent). The majority of EMA studies in the field of EDs also request that participants report on their behaviors after they have occurred (eventcontingent), and at regular time intervals, such as the end of the day (time-contingent). The utility of EMA is that it reduces error associated with retrospective self-reports, is conducted in participants' natural environment – improving ecological validity – and allows for testing of cause–effect relationships in real time ([i.e., EMA enables examination of short-term prospective associations among eating disorder behaviors and other psychological variables [122]). In the following section we review findings from EMA studies that describe circadian (daily) patterns of ingestive behavior among individuals with AN, BN, and BED. Although mood and emotion play important roles in predicting eating behaviors, we chose to focus our review of EMA studies to those that describe circadian (daily) patterns of ingestive behavior among individuals with AN, BN, and BED. We refer interested readers to Haedt-Matt and Keel [47], Engel et al. [27], and Goldschmidt et al. [39] for information on the role of affect in EMA studies of eating disorders.

5.1. Dietary restraint, hunger, and caloric restriction as antecedents to binge eating

4.4. Summary Our review of the literature on idiosyncratic eating behaviors among individuals with AN or BN indicates variable patterns of fluid intake (viz., over- or under-consumption), which may be due to “water loading” to gain weight or fluid restriction to gain a sense of control over one's ingestive behavior. Studies provided evidence for increased caffeine and artificial sweetener use among individuals with AN or BN (particularly for individuals who engaged in binge eating or purging behaviors). Studies are needed to determine whether increased caffeine use is due to greater disinhibition (given that disinhibition is associated with other forms of substance use) or to influence body weight via the metabolic and diuretic properties of caffeine. Finally, studies show that approximately one-third of individuals with AN-BP and most individuals with AN-R consume non-nutritive sweeteners, and use of these artificial sweeteners was exceptionally high among some of these individuals. Current hypotheses point to prominent roles for reward neural circuitry and weight/shape concerns in promoting these behaviors, yet additional research is needed to elucidate reasons for excessive artificial sweetener use and to identify potential negative health risks associated with these behaviors.

A number of theoretical models suggest that dietary restraint and associated caloric restriction prospectively predict binge eating episodes among individuals with AN-BP and BN [95,97,119]. Indeed, current empirically supported treatments for eating disorders focus on reducing dietary restraint as a primary means for reducing binge episodes in the early stages of therapy [29]. Other research studies, however, have questioned the validity of this theory, and indicate that dietary restriction or restraint may actually decrease binge eating among some individuals [40,118]. With regard to EMA studies, le Grange et al. [73] found that women with BED had higher self-reported dietary restraint (as measured by the Three Factor Eating Questionnaire) immediately prior to binge eating episodes. However, one study found that self-reported dietary restraint was not elevated prior to binge eating episodes among women with bulimic-spectrum disorders [28], although this same study supported indirect relations among variables suggesting that: (a) dietary restraint predicted cravings to binge eat, and (b) cravings to binge eat directly predicted the onset of binge eating episodes. Engelberg et al. explained their findings by suggesting that because individuals with BN spend much of their day trying not to act on urges to binge eat, their cognitive

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

14

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

efforts become depleted as the day continues, and that their urges eventually lead to disinhibited eating behavior. Although findings from other studies indicate that hunger, cravings for sweet foods, and mounting feelings of loss-of-control over eating play an important role in predicting binge episodes among persons with BED [42,115], a recent meta-analysis of EMA studies suggested that self-reported hunger is not a precipitant for binge eating episodes among women with BN, because increased hunger is also reported prior to non-binge eating episodes [48]. Finally, Zunker et al. [147] carried out a study of women with BN who completed daily self-reports for two weeks. In contrast to previous EMA studies of dietary restraint, Zunker et al. [146] quantified caloric restriction more explicitly for participants, who were asked “Outside of the times when you have binged, how much did you restrict the amount of food you ate today?” Participants were given five choices that included no restriction, mild restriction (attempt to generally cut back), moderate restriction (1200–1600 kcal), extreme restriction (b1200 kcal), and very extreme restriction (fasting or no eating except binge). Using this definition, the authors found that the odds of experiencing a binge episode were predicted by restricting that occurred the day before and on the day that the binge eating episode occurred. Taken together, findings from EMA studies indicate that dietary restraint is at least a precursor to cognitive urges to binge eat, and also suggest that more specific definitions for caloric restriction (or more objective methods for assessing dietary intake) may be useful to include in future studies seeking to address the debate regarding the role of dietary restraint and restriction in predicting binge eating episodes. 5.2. Temporal patterns of binge eating Smyth et al. [113] carried out an interesting study investigating time-of-day effects for binge eating among a sample of 133 women with BN. These authors used multilevel logistic models for binary responses to test the probability of an eating behavior occurring during the day, and found that the frequency of binge eating was lowest in the early morning hours, and exhibited peaks at 1 PM and from 7 to 9 PM. The probability of binge eating was low in the morning and then increased substantially until midday, then decreased slightly, peaked again in the evening hours, and decreased after 9 PM. Smyth et al. [113] also tested day-of-week effects and found that binge eating was most frequent on Sunday. These data are important by indicating high risk periods for binge eating among persons with BN, which may be useful information for both therapists (to implement supportive strategies, such as phone calls) and for clients with BN (to develop advance strategies for coping with high-risk periods). 5.3. Role of loss-of-control over eating The DSM-definition of binge eating requires the consumption of a large amount of food, in a discrete time period (e.g., within a 2-hour period), and the subjective sense of loss-of-control. The subjective experience of loss-of-control refers to the feeling that one cannot control what or how much one is eating (e.g., feeling that one's eating is unrestrained or that one cannot stop eating once started). Loss-of-control over eating represents a salient part of the diagnostic definition for binge eating in BN and BED (note that there is no explicit definition for binge eating for the AN-BP subtype). Without a subjective sense of loss-of-control, discrete eating episodes characterized by the ingestion of large amounts of food are not considered binges (and would be classified as overeating episodes). Fairburn and Cooper [30] proposed a model of binge eating in which eating episodes are characterized as either objective or subjective, based on the amount of food that was eaten during the episode. Objective binge episodes involve the ingestion of large amounts of food and the subjective sense of loss-of-control, whereas subjective binge episodes involve loss-of-control over eating small or moderate amounts of food.

Although subjective binge episodes are not part of current diagnostic definitions for DSM-defined eating disorders, Fairburn and Cooper's model appears to have substantial clinical utility. For example, studies have shown that both subjective and objective binge eating episodes are associated with eating disorder and non-eating disorder psychopathology, emotional distress, and poor mental health quality-of-life [14,66,100,125]. Importantly, several recent EMA studies support the inclusion of loss-of-control as a key aspect of binge eating. Goldschmidt et al. [38] found that among persons with BED, greater pre-meal loss-of-control was associated with greater post-meal negative affect — regardless of the amount of food eaten. However, for obese control subjects, loss-of-control and the ingestion of large amounts of food were associated with lower post-meal negative affect. The authors interpreted their findings as suggesting that loss-of-control over eating is more important than the actual amount of food consumed during binge episodes (in terms of causing emotional distress for individuals with BED). Recently, Pollert et al. [98] assessed binge eating episodes (both size and loss-of-control feelings) in individuals with BED and non-BED obese controls. Their results showed that the odds of experiencing a sense of loss-of-control were three times higher among participants with BED vs. obese controls, and this effect remained significant after controlling for negative affect and caloric intake during the eating episode. Notably, caloric intake during the episode and negative affect were significantly associated with loss-of-control episodes, supporting the inclusion of loss-of-control as a defining characteristic of binge eating behavior. Additional studies are needed to better clarify the importance of loss-of-control and eating episode size for diagnostic definitions of eating disorders. As noted in a review by Wolfe et al. [142], few studies have tested the functional role of loss-of-control in binge eating episodes among individuals with BN and AN-BP, and additional research is needed to improve the objective assessment of loss-of-control. For example, in two large-scale assessment studies of eating disorder symptoms [152,153], DSM-defined loss-of-control over eating did not load on a binge eating factor, whereas certain non-traditional items (e.g., “I stuffed myself with food to the point of feeling sick”) showed initial promise for improving the assessment loss-of-control eating episodes. Such items may be particularly useful for inclusion in future EMA studies to identify aspects of loss-of-control eating that are most predictive of eating disorder course and outcome. 5.4. Summary The number of EMA studies in the field of eating disorders research has been steadily growing, and we believe this methodology holds promise for improving the assessment of eating disorder behaviors among individuals with eating pathology. Contrary to popular theoretical models of eating disorders that posit dietary restraint directly predicts binge eating episodes, some studies find that restraint does not predict binge eating, whereas other research has supported indirect paths in which restraint directly leads to cravings to binge eat, and cravings to binge eat directly lead to binge eating. A potential explanation for these mixed findings is that because some measures of dietary restraint have questionable validity for assessing dietary intake, they may not be appropriate for testing these hypotheses [120,121]. Studies that have used more stringent definitions of dietary restriction show that reduced caloric intake does predict binge eating episodes. As we suggest in the Conclusions and future directions section (below), use of more objective measures of dietary intake would be particularly helpful for testing hypotheses regarding eating patterns within an EMA framework. 6. Conclusions and future directions Numerous well-conducted studies have provided useful insights into the eating patterns, diet quality, and energy balance of individuals

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

with eating pathology. Not only are these studies useful for validating (or in some cases challenging) current diagnostic definitions for eating disorders, many of the studies we reviewed have important implications for treatment. For example, knowing the conditions under which clients may be more likely to binge eat (e.g., in the afternoon or evening) can provide clinicians with potentially useful strategies for mitigating disordered eating behaviors. Indeed, recent advances in EMA studies have led to the development of Integrative Cognitive Affective Therapy (I-CAT) [143]. Perhaps because I-CAT was developed based on the results of real-world studies that tested relations among eating behaviors and other relevant psychological and interpersonal variables, initial studies show that it is an efficacious treatment for individuals suffering from BN [143]. We believe that the field of eating disorders is poised to identify additional important insights into the eating patterns of those with eating pathology, and we provide several suggestions for future studies in this area. First, the majority of studies we reviewed were based on extremely small sample sizes (particularly for studies testing between-group differences in caloric intake and nutrient content among individuals with BED or BN), and samples were primarily comprised of Caucasian females. In light of studies indicating that men [54] and individuals in ethnic and racial minorities do suffer from eating disorders (e.g., nationally representative data indicate African American and Hispanic individuals have higher rates of BN than Caucasian individuals [79]), the omission of these populations seriously hampers scientific and clinical knowledge about eating behaviors in the full range of people who suffer from eating disorders. Moreover, larger, well-powered studies would likely resolve some of the inconsistent (or null findings) reported for studies of eating patterns that occur outside of binge episodes, and for studies of the diet quality of binge episodes among persons with BN or BED. Second, more research is needed to understand how to treat aberrant eating behavior patterns in persons with eating disorders. For example, a substantial portion of individuals with AN continue to engage in disordered eating behaviors following treatment discharge, despite substantial weight gain and improvement in psychological functioning and food intake during intensive, structured behavioral treatments. Among the few factors associated with relapse following successful treatment for AN are lower BMI at time of discharge and more rapid rate of weight loss in the first month following discharge [60]. The remarkable persistence of abnormal eating behaviors among individuals with AN is a critical issue for the field (for a recent review of this issue, see [135]), and efforts to improve treatment outcomes for adults with AN have largely been unsuccessful. Based on the high rates of mood and anxiety disorders (such as obsessive compulsive disorder) among individuals with AN, as well as evidence indicating shared genetic transmission of mood, anxiety, and eating disorders, scholars have hypothesized critical roles for fear acquisition, anxiety, and emotion dysregulation in the persistence of AN-behaviors following treatment [126,138]. Other theoretical models point to the role of ‘neurocognitive inflexibility’ (i.e., the inability to shift attention toward novel stimuli or override previously acquired stimulus-reinforcement associations) as contributing to the chronicity of AN symptoms [135,137]. Although additional work in this area is clearly warranted, it is noteworthy that recent pilot studies that have incorporated techniques to reduce fearof-eating or improve emotion regulation have shown promising results [116,117,138,139]. Finally, even when certain treatments are successful at treating eating disorder behaviors, some are not effective in changing body weight. For example, although current psychological and behavioral weightloss treatments for individuals with BED are efficacious for reducing binge eating episodes, these treatments generally do not promote weight loss (for a review, see [140]). As noted by Walsh [134], the lack of association between the reduction in binge eating and the reduction of BMI may be due to: (a) increased number of calories eaten during meals as the frequency of binge eating declines or (b) reductions

15

in the level of distress an individual experiences about their eating behavior — rather than actual changes in the amount of food consumed during eating episodes. Grilo et al. [43] found that post-treatment binge eating and weight loss outcomes were predicted by distinct baseline variables. Reductions in psychological symptoms that accompany binge eating episodes were predicted by higher frequency of binge eating at baseline, whereas weight loss was predicted by low self-esteem and high levels of depression and other negative emotions. The question of whether binge eating represents an objective problem with eating behavior (vs.) an altered perception of eating behavior is difficult to ascertain using current methods. Much of the BED treatment literature utilized self-report measures of binge eating that have questionable psychometric properties and validity for identifying true binge eating episodes [140]. With the proliferation of new, more objective methods for assessing dietary intake and physical activity, future studies could combine EMA methodology with accelerometers, heart rate monitors, and tools designed to assess chewing and hand-to-mouth movements in ‘real-time’ to address unresolved issues about eating behaviors among persons with eating disorders. In summary, our review of the literature indicated that individuals with AN eat fewer calories than healthy normal controls, whereas those with BN or BED eat substantially more calories than healthy normal weight and obese controls — providing credence to current diagnostic definitions for eating disorders. No clear pattern of results regarding macro- and micro-nutrient intake among individuals with eating disorders emerged, which is likely due to small sample sizes for the few studies that have examined this issue. Beyond the amount and type of foods ingested, our review suggested that individuals with AN and BN exhibit myriad dysfunctional eating patterns, including frequent meal skipping, restriction or over-ingestion of fluids, and over-use of caffeine and artificial sweeteners. Additional studies are needed to answer lingering questions about eating patterns among those with eating disorders. Based on our review, some questions include: What is the most valid definition with regard to the duration of binge eating episodes, and should episodes of “grazing” (i.e., “binge days”) be considered binge eating? What is the minimum number of calories for a binge eating episode to be considered objectively large, and does this vary based on race, ethnicity, and sex? What are the typical ingestive patterns for individuals with various forms of OSFED? Are binge eating episodes among individuals with AN similar to those observed in persons with BN or BED? In addition to incorporating novel, improved methodology to assess eating behaviors among persons with eating disorders, it will be important for the field to refine our understanding of the psychological and biological factors that contribute to abnormal ingestive behaviors across the full range of eating disorder phenotypes. Such information has the potential to yield informative insights into disorders that affect millions of individuals world-wide. Acknowledgments We thank Ms. Kayla Donaldson for her assistance with article formatting, and research fellowship funding from the Ingestive Behaviors Research Center (IBRC) to Ms. Tyler Hunt. References [1] Affenito SG, Dohm F-A, Crawford PB, Daniels SR, Striegel-Moore RH. Macronutrient intake in anorexia nervosa: the National Heart, Lung, and Blood Institute Growth and Health study. J Pediatr 2002;141:701–5. http://dx.doi.org/ 10.1067/mpd.2002.129840. [2] Allison S, Timmerman GM. Anatomy of a binge: food environment and characteristics of nonpurge binge episodes. Eat Behav 2007;8:31–8. [3] APA. Diagnostic and statistical manual of mental disorders. 5th Edition. Washington, DC: American Psychiatric Association; 2013. [4] Apfelbaum M, Bostsarron J, Lacatis D. Effect of caloric restriction and excessive caloric intake on energy expenditure. Am J Clin Nutr 1971;24:1405–9. [5] Beaton GH, Milner J, McGuire V, Feather T, Little JA. Source of variance in 24-hour dietary recall data: implications for nutrition study design and

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

16

[6]

[7] [8]

[9]

[10]

[11] [12]

[13]

[14]

[15]

[16]

[17] [18]

[19] [20]

[21]

[22] [23] [24] [25] [26]

[27]

[28]

[29] [30]

[31]

[32]

[33]

[34]

[35]

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx interpretation. Carbohydrate sources, vitamins, and minerals. Am J Clin Nutr 1983;37:986–95. Bell SM, Stewart RB, Thompson SC, Meisch RA. Food-deprivation increases cocaineinduced conditioned place preference and locomotor activity in rats. Psychopharmacology (Berl) 1997;131:1–8. Beumont P, George G, Smart D. “ Dieters” and“ vomiters and purgers” in anorexia nervosa. Psychol Med 1976;6:617–22. Bradburn NM, Rips LJ, Shevell SK. Answering autobiographical questions: the impact of memory and inference on surveys. Science 1987;236:157–61. http:// dx.doi.org/10.2307/1698381. Brown TA, Keel PK. What contributes to excessive diet soda intake in eating disorders: appetitive drive, weight concerns, or both? Eat Disord J Treat Prev 2013;21:265–74. http://dx.doi.org/10.1080/10640266.2013.779190. Bulik CM, Berkman ND, Brownley KA, Sedway JA, Lohr KN. Anorexia nervosa treatment: a systematic review of randomized controlled trials. Int J Eat Disord 2007;40:310–20. Bulik CM, Marcus MD, Zerwas S, Levine MD, La Via M. The changing “weightscape” of bulimia nervosa. Am J Psychiatry 2012;169:1031–6. Burd C, Mitchell JE, Crosby RD, Engel SG, Wonderlich SA, Lystad C, et al. An assessment of daily food intake in participants with anorexia nervosa in the natural environment. [Article] Int J Eat Disord 2009;42:371–4. Burgalassi A, Ramacciotti CE, Bianchi M, Coli E, Polese L, Bondi E, et al. Caffeine consumption among eating disorder patients: epidemiology, motivations, and potential of abuse. Eat Weight Disord 2009;14:e212–8. Colles SL, Dixon JB, O'Brien PE. Loss of control is central to psychological disturbance associated with binge eating disorder. Obesity 2008;16: 608–14. Conway JM, Ingwersen LA, Vinyard BT, Moshfegh AJ. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am J Clin Nutr 2003;77:1171–8. Cooke AA, Guss JL, Kissileff HR, Devlin MJ, Walsh BT. Patterns of food selection during binges in women with binges eating disorder. [Article] Int J Eat Disord 1997;22:187–93. Costill D, Dalsky GP, Fink W. Effects of caffeine ingestion on metabolism and exercise performance. Med Sci Sports 1977;10:155–8. Crow S, Peterson C, Swanson S, Raymond N, Specker S, Eckert E, et al. Increased mortality in bulimia nervosa and other eating disorders. Am J Psychiatry 2009;166:1342–6. Crowther JH, Lingswiler VM, Stephens MAP. The topography of binge eating. Addict Behav 1984;9:299–303. http://dx.doi.org/10.1016/0306-4603(84)90024-8. Curtis SR, Gwirtsman HE, Kaye WH, Lyter LM. Energy intake and dietary macronutrient content in women with anorexia nervosa and volunteers. [Article] J Am Diet Assoc 1989;89(1) [54+]. Davidson TL, Martin AA, Clark K, Swithers SE. Intake of high-intensity sweeteners alters the ability of sweet taste to signal caloric consequences: Implications for the learned control of energy and body weight regulation. Q J Exp Psychol 2011;64:1430–41. http://dx.doi.org/10.1080/17470218.2011.552729. De la Rie S, Noordenbos G, Van Furth E. Quality of life and eating disorders. Qual Life Res 2005;14:1511–21. de Vaca SC, Carr KD. Food restriction enhances the central rewarding effect of abused drugs. J Neurosci 1998;18:7502–10. Dempsey D, Crosby L, Pertschuk M, Feurer I, Buzby G, Mullen J. Weight gain and nutritional efficacy in anorexia nervosa. Am J Clin Nutr 1984;39:236–42. Department of Nutrition Dietetics and Food Science. Dietician's pocket book. Perth, Australia: Curtin University of Technology; 1998. Dhingra R, Sullivan L, Jacques PF, Wang TJ, Fox CS, Meigs JB, et al. Soft drink consumption and risk of developing cardiometabolic risk factors and the metabolic syndrome in middle-aged adults in the community. Circulation 2007;116:480–8. http://dx.doi.org/10.1161/circulationaha.107.689935. Engel SG, Kahler KA, Lystad CM, Crosby RD, Simonich HK, Wonderlich SA, Peterson CB, Mitchell JE. Eating behavior in obese BED, obese non-BED, and non-obese control participants: A naturalistic study. Behavior Research and Therapy 2009;47:897–900. Engelberg MJ, Gauvin L, Steiger H. A naturalistic evaluation of the relation between dietary restraint, the urge to binge, and actual binge eating: a clarification. Int J Eat Disord 2005;38:355–60. http://dx.doi.org/10.1002/eat.20186. Fairburn CG. Cognitive behavior therapy and eating disorders. Guilford Press; 2008. Fairburn CG, Cooper Z. The eating disorder examination. In: Fairburn CG, Wilson GT, editors. Binge eating: nature, assessment, and treatment. New York, NY: Guilford Press; 1993. p. 317–32. Fitzgibbon ML, Blackman LR. Binge eating disorder and bulimia nervosa: differences in the quality and quantity of binge eating episodes. Int J Eat Disord 2000;27:238–43. http://dx.doi.org/10.1002/(sici)1098-108x(200003)27:2b238:: aid-eat12N3.0.co;2-q. Forbes G, Kreipe R, Lipinski B, Hodgman C. Body composition changes during recovery from anorexia nervosa: comparison of two dietary regimes. Am J Clin Nutr 1984;40:1137–45. Frank GK, Oberndorfer TA, Simmons AN, Paulus MP, Fudge JL, Yang TT, et al. Sucrose activates human taste pathways differently from artificial sweetener. Neuroimage 2008;39:1559–69. Fung TT, Malik V, Rexrode KM, Manson JE, Willett WC, Hu FB. Sweetened beverage consumption and risk of coronary heart disease in women. Am J Clin Nutr 2009;89:1037–42. http://dx.doi.org/10.3945/ajcn.2008.27140. Gendall KA, Sullivan PE, Joyce PR, Carter FA, Bulik CM. The nutrient intake of women with bulimia nervosa. Int J Eat Disord 1997;21:115–27. http://dx.doi.org/ 10.1002/(sici)1098-108x(199703)21:2b115::aid-eat2N3.0.co;2-o.

[36] Gibson RS. Principles of nutritional assessment. New York, NY: Oxford University Press; 1990. [37] Goldfein JA, Walsh BT, LaChaussée JL, Kissileff HR, Devlin MJ. Eating behavior in binge eating disorder. [Article] Int J Eat Disord 1993;14:427–31. [38] Goldschmidt AB, Engel SG, Wonderlich SA, Crosby RD, Peterson CB, Le Grange D, et al. Momentary affect surrounding loss of control and overeating in obese adults with and without binge eating disorder. Obesity 2012;20:1206–11. [39] Goldschmidt AB, Wonderlich SA, Crosby RD, Engel SG, Lavender JM, Peterson CB, et al. Ecological momentary assessment of stressful events and negative affect in bulimia nervosa. J Consult Clin Psychol 2014;82:30. [40] Goodrick GK, Poston II WSC, Kimball KT, Reeves RS, Foreyt JP. Nondieting versus dieting treatment for overweight binge-eating women. J Consult Clin Psychol 1998;66(2):363–8. http://dx.doi.org/10.1037/0022-006x.66.2.363. [41] Greeno CG, Wing RR, Marcus MD. How many donuts is a “binge”?: women with bed eat more but do not have more restrictive standards than weight-matched non-bed women. Addict Behav 1999;24:299–303 http://dx.doi.org/10.1016/ S0306-4603(98)00052-5. [42] Greeno CG, Wing RR, Shiffman S. Binge antecedents in obese women with and without binge eating disorder. J Consult Clin Psychol 2000;68:95–102. http:// dx.doi.org/10.1037/0022-006x.68.1.95. [43] Grilo CM, Masheb RM, Crosby RD. Predictors and moderators of response to cognitive behavioral therapy and medication for the treatment of binge eating disorder. J Consult Clin Psychol 2012;80:897. [44] Grilo CM, Shiffman S, Carter‐Campbell JT. Binge eating antecedents in normal‐ weight nonpurging females: is there consistency? Int J Eat Disord 1994;16: 239–49. [45] Hadigan CM, Anderson EJ, Miller KK, Hubbard JL, Herzog DB, Klibanski A, et al. Assessment of macronutrient and micronutrient intake in women with anorexia nervosa. Int J Eat Disord 2000;28:284–92. http://dx.doi.org/10.1002/1098108x(200011)28:3b284::aid-eat5N3.0.co;2-g. [46] Hadigan CM, Kissileff HR, Walsh BT. Patterns of food selection during meals in women with bulimia. Am J Clin Nutr 1989;50:759–66. [47] Haedt-Matt AA, Keel PK. Revisiting the affect regulation model of binge eating: a meta-analysis of studies using ecological momentary assessment. Psychol Bull 2011;137:660–81. http://dx.doi.org/10.1037/a0023660. [48] Haedt‐Matt AA, Keel PK. Hunger and binge eating: a meta‐analysis of studies using ecological momentary assessment. Int J Eat Disord 2011;44:573–8. http:// dx.doi.org/10.1002/eat.20868. [49] Hart S, Abraham S, Luscombe G, Russell J. Fluid intake in patients with eating disorders. Int J Eat Disord 2005;38:55–9. http://dx.doi.org/10.1002/eat.20155. [50] Harvey EMR, Richard A, Alexander E, Bachar KJ. Binge eating in males: a sample description and treatment outcome study. Eat Disord J Treat Prev 2007;2: 215–30. [51] Herzog DB, Greenwood DN, Dorer DJ, Flores AT, Ekeblad ER, Richards A, et al. Mortality in eating disorders: a descriptive study. Int J Eat Disord 2000;28:20–6. [52] Hetherington MM, Altemus M, Nelson ML, Bernat AS, Gold PW. Eating behavior in bulimia nervosa: multiple meal analyses. Am J Clin Nutr 1994;60:864. [53] Hsu LG. Experiential aspects of bulimia nervosa implications for cognitive behavioral therapy. Behav Modif 1990;14:50–65. [54] Hudson JI, Hiripi E, Pope Jr HG, Kessler RC. The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biol Psychiatry 2007;61:348–58. [55] Hunger SP, Lu X, Devidas M, Camitta BM, Gaynon PS, Winick NJ, et al. Improved survival for children and adolescents with acute lymphoblastic leukemia between 1990 and 2005: a report from the children's oncology group. J Clin Oncol 2012;30:1663–9. [56] Jackson AA, Picou D, Reeds P. The energy cost of repleting tissue deficits during recovery from protein-energy malnutrition. Am J Clin Nutr 1977;30:1514–7. [57] Jansen A, den Hout Mv, Griez E. Clinical and non-clinical binges. Behav Res Ther 1990;28:439–44. [58] Johnson CL, Stuckey MK, Lewis LD, Schwartz DM. Bulimia: a descriptive survey of 316 cases. [Article] Int J Eat Disord 1982;2:3–16. [59] Kales EF. Macronutrient analysis of binge eating in bulimia. Physiol Behav 1990;48:837–40 http://dx.doi.org/10.1016/0031-9384(90)90236-W. [60] Kaplan A, Walsh B, Olmsted M, Attia E, Carter J, Devlin M, et al. The slippery slope: prediction of successful weight maintenance in anorexia nervosa. Psychol Med 2009;39:1037. [61] Kaye WH, Gwirtsman HE, Obarzanek E, George DT. Relative importance of calorie intake needed to gain weight and level of physical activity in anorexia nervosa. Am J Clin Nutr 1988;47:989–94. [62] Kaye WH, Gwirtsman HE, Obarzanek E, George T, Jimerson DC, Ebert MH. Caloric intake necessary for weight maintenance in anorexia nervosa: nonbulimics require greater caloric intake than bulimics. Am J Clin Nutr 1986;44:435–43. [63] Kaye WH, Weltzin TE, Hsu L, McConaha C, Bolton B. Amount of calories retained after binge eating and vomiting. Am J Psychiatry 1993;150:969–71. [64] Kaye WH, Weltzin TE, McKee M, McConaha C, Hansen D, Hsu L. Laboratory assessment of feeding behavior in bulimia nervosa and healthy women: methods for developing a human-feeding laboratory. Am J Clin Nutr 1992;55:372–80. [65] Keel PK, Brown TA, Holm‐Denoma J, Bodell LP. Comparison of DSM‐IV versus proposed DSM‐5 diagnostic criteria for eating disorders: reduction of eating disorder not otherwise specified and validity. Int J Eat Disord 2011;44:553–60. [66] Keel PK, Mayer SA, Harnden-Fischer JH. Importance of size in defining binge eating episodes in bulimia nervosa. Int J Eat Disord 2001;29:294–301. [67] Keys A, Brožek J, Henschel A, Mickelsen O, Taylor HL. The biology of human starvation. Oxford, England: University of Minnesota Press; 1950.

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx [68] Kissileff HR, Walsh BT, Kral JG, Cassidy SM. Laboratory studies of eating behavior in women with bulimia. Physiol Behav 1986;38:563–70 http://dx.doi.org/10.1016/ 0031-9384(86)90426-9. [69] Klein DA, Boudreau GS, Devlin MJ, Walsh BT. Artificial sweetener use among individuals with eating disorders. Int J Eat Disord 2006;39:341–5. http://dx.doi.org/ 10.1002/eat.20260. [70] Krahn DD, Hasse S, Ray A, Gosnell BA. Caffeine consumption in patients with eating disorders. Hosp Community Psychiatry 1991;42:313–5. [71] LaChaussée JL, Kissileff HR, Walsh BT, Hadigan CM. The single-item meal as a measure of binge-eating behavior in patients with bulimia nervosa. Physiol Behav 1992;51:593–600 http://dx.doi.org/10.1016/0031-9384(92)901855. [72] Lane B, Szabó M. Uncontrolled, repetitive eating of small amounts of food or ‘grazing’: development and evaluation of a new measure of atypical eating. Behav Chang 2013;30:57–73. http://dx.doi.org/10.1017/bec.2013.6. [73] le Grange D, Gorin A, Catley D, Stone AA. Does momentary assessment detect binge eating in overweight women that is denied at interview? Eur Eat Disord Rev 2001;9:309–24. http://dx.doi.org/10.1002/erv.409. [74] Lieberman H, Wurtman R, Emde G, Roberts C, Coviella I. The effects of low doses of caffeine on human performance and mood. Psychopharmacology (Berl) 1987;92:308–12. [75] Machado PP, Gonçalves S, Hoek HW. DSM-5 reduces the proportion of EDNOS cases: evidence from community samples. Int J Eat Disord 2013;46:60–5. [76] Machado PP, Machado BC, Gonçalves S, Hoek HW. The prevalence of eating disorders not otherwise specified. Int J Eat Disord 2007;40:212–7. [77] Malik VS, Schulze MB, Hu FB. Intake of sugar-sweetened beverages and weight gain: a systematic review. Am J Clin Nutr 2006;84:274–88. [78] Marino JM, Ertelt TE, Wonderlich SA, Crosby RD, Lancaster K, Mitchell JE, et al. Caffeine, artificial sweetener, and fluid intake in anorexia nervosa. Int J Eat Disord 2009;42:540–5. http://dx.doi.org/10.1002/eat.20633. [79] Marques L, Alegria M, Becker AE, Chen Cn, Fang A, Chosak A, et al. Comparative prevalence, correlates of impairment, and service utilization for eating disorders across US ethnic groups: implications for reducing ethnic disparities in health care access for eating disorders. Int J Eat Disord 2011;44:412–20. [80] Masheb RM, Grilo CM. Eating patterns and breakfast consumption in obese patients with binge eating disorder. Behav Res Ther 2006;44(11):1545–53 http://dx.doi. org/10.1016/j.brat.2005.10.013. [81] Masheb RM, Grilo CM, White MA. An examination of eating patterns in community women with bulimia nervosa and binge eating disorder. Int J Eat Disord 2011;44:618–24. http://dx.doi.org/10.1002/eat.20853. [82] Mayer LES, Schebendach J, Bodell LP, Shingleton RM, Walsh BT. Eating behavior in anorexia nervosa: before and after treatment. Int J Eat Disord 2012;45:290–3. http://dx.doi.org/10.1002/eat.20924. [83] McElroy SL, Guerdjikova AI, Winstanley EL, O'Melia AM, Mori N, McCoy J, et al. Acamprosate in the treatment of binge eating disorder: a placebo‐controlled trial. Int J Eat Disord 2011;44:81–90. [84] Miller D, Mumford P. Gluttony 1. An experimental study of overeating low-or highprotein diets. Am J Clin Nutr 1967;20:1212–22. [85] Misra M, Tsai P, Anderson EJ, Hubbard JL, Gallagher K, Soyka LA, et al. Nutrient intake in community-dwelling adolescent girls with anorexia nervosa and in healthy adolescents. Am J Clin Nutr 2006;84:698–706. [86] Mitchell J, Laine D. Monitored binge-eating behavior in patients with bulimia. Int J Eat Disord 1984;4:177–83. [87] Mitchell JE, Pyle RL, Eckert ED. Frequency and duration of binge-eating episodes in patients with bulimia. Am J Psychiatry 1981;138:835–6. [88] Mond JM, Owen C, Hay P, Rodgers B, Beumont P. Assessing quality of life in eating disorder patients. Qual Life Res 2005;14:171–8. [89] Mussell MP, Mitchell JE, Weller CL, Raymond NC, Crow SJ, Crosby RD. Onset of binge eating, dieting, obesity, and mood disorders among subjects seeking treatment for binge eating disorder. Int J Eat Disord 1995;17:395–401. [90] Nelson M, Black AE, Morris JA, Cole TJ. Between-and within-subject variation in nutrient intake from infancy to old age: estimating the number of days required to rank dietary intakes with desired precision. Am J Clin Nutr 1989;50:155–67. [91] Nielsen S, Møller-Madsen S, Isager T, Jørgensen J, Pagsberg K, Theander S. Standardized mortality in eating disorders—a quantitative summary of previously published and new evidence. J Psychosom Res 1998;44:413–34. [92] Obarzanek E, Lesem MD, Jimerson DC. Resting metabolic rate of anorexia nervosa patients during weight gain. Am J Clin Nutr 1994;60:666–75. [93] Ohlrich ES, Aughey DR, Dixon RM. Sorbitol abuse among eating-disordered patients. Psychosomatics 1989;30:451–3. http://dx.doi.org/10.1016/s0033-3182(89)72255-6. [94] Patrick L. Eating disorders: a review of the literature with emphasis on medical complications and clinical nutrition. Alternat Med Rev 2002;7:184–202. [95] Polivy J. Psychological consequences of food restriction. J Am Diet Assoc 1996;96(6):589–92 http://dx.doi.org/10.1016/S0002-8223(96)00161-7. [96] Polivy J, Herman CP, McFarlane T. Effects of anxiety on eating: does palatability moderate distress-induced overeating in dieters? J Abnorm Psychol 1994; 103:505. [97] Polivy J, Zeitlin SB, Herman CP, Beal AL. Food restriction and binge eating: a study of former prisoners of war. J Abnorm Psychol 1994;103(2):409–11. http://dx.doi.org/ 10.1037/0021-843x.103.2.409. [98] Pollert GA, Engel SG, Schreiber-Gregory DN, Crosby RD, Cao L, Wonderlich SA, et al. The role of eating and emotion in binge eating disorder and loss of control eating. Int J Eat Disord 2013;46:233–8. http://dx.doi.org/10.1002/eat.22061. [99] Powell AL, Thelen MH. Emotions and cognitions associated with bingeing and weight control behavior in bulimia. J Psychosom Res 1996;40:317–28.

17

[100] Pratt EM, Niego SH, Agras WS. Does the size of a binge matter? Int J Eat Disord 1998;24:307–12. [101] Raymond NC, Bartholome LT, Lee SS, Peterson RE, Raatz SK. A comparison of energy intake and food selection during laboratory binge eating episodes in obese women with and without a binge eating disorder diagnosis. [Article] Int J Eat Disord 2007;40:67–71. http://dx.doi.org/10.1002/eat.20312. [102] Raymond NC, Neumeyer B, Warren CS, Lee SS, Peterson CB. Energy intake patterns in obese women with binge eating disorder. Obes Res 2003;11:869–79. http:// dx.doi.org/10.1038/oby.2003.120. [103] Reeves RS, McPherson RS, Nichaman MZ, Harrist RB, Foreyt JP, Goodrick GK. Nutrient intake of obese female binge eaters. J Am Diet Assoc 2001;101:209–15 http://dx.doi.org/10.1016/S0002-8223(01)00055-4. [104] Rosen JC, Leitenberg H, Fisher C, Khazam C. Binge-eating episodes in bulimia nervosa: the amount and type of food consumed. [Article] Int J Eat Disord 1986;5:255–67. [105] Rossiter EM, Agras WS. An empirical test of the DSM-III-R definition of binge. Int J Eat Disord 1990;9:513–8. http://dx.doi.org/10.1002/1098-108x(199009)9:5b513:: aid-eat2260090506N3.0.co;2-t. [106] Rossiter EM, Stewart Agras W, Telch CF, Bruce B. The eating patterns of nonpurging bulimic subjects. [Article] Int J Eat Disord 1992;11:111–20. [107] Russell DG, Wilson NC. Life in New Zealand commission report vol. I: executive overview. Dunedin New Zealand: University of Otago; 1991. [108] Russell GFM, Mezey AG. An analysis of weight gain in patients with anorexia nervosa treated with high caloric diets. Clin Sci 1962;23:449–61. [109] Saunders R. “Grazing”: a high-risk behavior. Obes Surg 2004;14:98–102. http:// dx.doi.org/10.1381/096089204772787374. [110] Schebendach JE, Porter KJ, Wolper C, Walsh BT, Mayer LES. Accuracy of selfreported energy intake in weight-restored patients with anorexia nervosa compared with obese and normal weight individuals. [Article] Int J Eat Disord 2012;45:570–4. http://dx.doi.org/10.1002/eat.20973. [111] Schlundt DG, Johnson WG, Jarrell MP. A naturalistic functional analysis of eating behavior in bulimia and obesity. Adv Behav Res Ther 1985;7:149–62. [112] Smiciklas-Wright H, Guthrie H. Dietary intake methods. In: Smiko MD, Cowell C, Gilbride JA, editors. Nutrition assessment: a comprehensive guide for planning intervention. Second ed. Gaithersburg, MD: Aspen Publishers; 1995. [113] Smyth JM, Wonderlich SA, Sliwinski MJ, Crosby RD, Engel SG, Mitchell JE, et al. Ecological momentary assessment of affect, stress, and binge–purge behaviors: day of week and time of day effects in the natural environment. [Article] Int J Eat Disord 2009;42:429–36. http://dx.doi.org/10.1002/eat.20623. [114] Spitzer RL, Devlin M, Walsh BT, Hasin D, Wing R, Marcus M, et al. Binge eating disorder: a multisite field trial of the diagnostic criteria. Int J Eat Disord 1992;11:191–203. [115] Stein RI, Kenardy J, Wiseman CV, Dounchis JZ, Arnow BA, Wilfley DE. What's driving the binge in binge eating disorder?: a prospective examination of precursors and consequences. [Article] Int J Eat Disord 2007;40:195–203. http://dx.doi.org/ 10.1002/eat.20352. [116] Steinglass JE, Sysko R, Glasofer D, Albano AM, Simpson HB, Walsh BT. Rationale for the application of exposure and response prevention to the treatment of anorexia nervosa. Int J Eat Disord 2011;44:134–41. [117] Steinglass JE, Sysko R, Mayer L, Berner LA, Schebendach J, Wang Y, et al. Pre-meal anxiety and food intake in anorexia nervosa. Appetite 2010;55:214–8. [118] Stice E. Dissonance and healthy weight eating disorder prevention programs: a randomized efficacy trial. J Couns Clin Psychol 2006;74:263–75. [119] Stice E, Agras WS. Predicting onset and cessation of bulimic behaviors during adolescence: a longitudinal grouping analysis. Behav Ther 1998;29:257–76 http://dx.doi.org/10.1016/S0005-7894(98)80006-3. [120] Stice E, Cooper JA, Schoeller DA, Tappe K, Lowe MR. Are dietary restraint scales valid measures of moderate-to long-term dietary restriction? Objective biological and behavioral data suggest not. Psychol Assess 2007;19:449. [121] Stice E, Fisher M, Lowe MR. Are dietary restraint scales valid measures of acute dietary restriction? Unobtrusive observational data suggest not. Psychol Assess 2004;16:51. [122] Stone AA, Shiffman S. Ecological momentary assessment (EMA) in behavioral medicine. Ann Behav Med 1994;16:199–202. [123] Stordy BJ, Marks V, Kalucy RS, Crisp AH. Weight gain, thermic effect of glucose and resting metabolic rate during recovery from anorexia nervosa. Am J Clin Nutr 1977;30:138–46. [124] Striegel-Moore RH, Wilfley DE, Pike KM, Dohm F-A, Fairburn CG. Recurrent binge eating in black American women. Arch Fam Med 2000;9:83. [125] Striegel‐Moore RH, Wilson GT, Wilfley DE, Elder KA, Brownell KD. Binge eating in an obese community sample. Int J Eat Disord 1998;23:27–37. [126] Strober M. Pathologic fear conditioning and anorexia nervosa: on the search for novel paradigms. Int J Eat Disord 2004;35:504–8. [127] Swithers SE, Davidson TL. A role for sweet taste: calorie predictive relations in energy regulation by rats. Behav Neurosci 2008;122:161–73. http://dx.doi.org/ 10.1037/0735-7044.122.1.161. [128] Swithers SE, Laboy AF, Clark K, Cooper S, Davidson TL. Experience with the high-intensity sweetener saccharin impairs glucose homeostasis and GLP-1 release in rats. Behav Brain Res 2012;233:1–14. http://dx.doi.org/10.1016/ j.bbr.2012.04.024. [129] Swithers SE, Martin AA, Davidson TL. High-intensity sweeteners and energy balance. Physiol Behav 2010;100:55–62. http://dx.doi.org/10.1016/j.physbeh.2009.12.021. [130] Sysko R, Hildebrandt T, Wilson GT, Wilfley DE, Agras WS. Heterogeneity moderates treatment response among patients with binge eating disorder. J Consult Clin Psychol 2010;78:681.

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045

18

K.T. Forbush, T.K. Hunt / Physiology & Behavior xxx (2014) xxx–xxx

[131] Sysko R, Walsh BT, Schebendach J, Wilson GT. Eating behavior among women with anorexia nervosa. Am J Clin Nutr 2005;82:296–301. [132] Thomas JJ, Vartanian LR, Brownell KD. The relationship between eating disorder not otherwise specified (EDNOS) and officially recognized eating disorders: meta-analysis and implications for DSM. Psychol Bull 2009;135:407. [133] Walker J, Roberts SL, Halmi KA, Goldberg SC. Caloric requirements for weight gain in anorexia nervosa. Am J Clin Nutr 1979;32:1396–400. [134] Walsh BT. The importance of eating behavior in eating disorders. Physiol Behav 2011;104:525–9. [135] Walsh BT. The enigmatic persistence of anorexia nervosa. Am J Psychiatry 2013;170:477–84. [136] Weltzin TE, Hsu LG, Pollice C, Kaye WH. Feeding patterns in bulimia nervosa. Biol Psychiatry 1991;30:1093–110. http://dx.doi.org/10.1016/0006-3223(91)90180-t. [137] Wildes JE, Forbes EE, Marcus MD. Advancing research on cognitive flexibility in eating disorders: the importance of distinguishing attentional set‐shifting and reversal learning. Int J Eat Disord 2014;47:227–30. [138] Wildes JE, Marcus MD. Development of emotion acceptance behavior therapy for anorexia nervosa: a case series. Int J Eat Disord 2011;44:421–7. [139] Wildes JE, Marcus MD, Cheng Y, McCabe EB, Gaskill JA. Emotion acceptance behavior therapy for anorexia nervosa: a pilot study. Int J Eat Disord 2014 [in press]. [140] Wilson GT, Grilo CM, Vitousek KM. Psychological treatment of eating disorders. Am Psychol 2007;62:199. [141] Woell C, Fichter MM, Pirke K-M, Wolfram G. Eating behavior of patients with bulimia nervosa. [Article] Int J Eat Disord 1989;8:557–68. [142] Wolfe BE, Baker CW, Smith AT, Kelly-Weeder S. Validity and utility of the current definition of binge eating. Int J Eat Disord 2009;42:674–86. http://dx.doi.org/ 10.1002/eat.20728. [143] Wonderlich S, Peterson C, Crosby R, Smith T, Klein M, Mitchell J, et al. A randomized controlled comparison of integrative cognitive-affective therapy (ICAT) and

[144]

[145] [146]

[147] [148]

[149]

[150]

[151] [152]

[153]

enhanced cognitive-behavioral therapy (CBT-E) for bulimia nervosa. Psychol Med 2014;44:543–53. Yanovski SZ, Leet M, Yanovski JA, Flood M, Gold PW, Kissileff HR, et al. Food selection and intake of obese women with binge-eating disorder. Am J Clin Nutr 1992;56:975–80. Zipfel S, Löwe B, Reas DL, Deter H-C, Herzog W. Long-term prognosis in anorexia nervosa: lessons from a 21-year follow-up study. Lancet 2000;355:721–2. Zunker C, Peterson CB, Crosby RD, Cao L, Engel SG, Mitchell JE, et al. Ecological momentary assessment of bulimia nervosa: Does dietary restriction predict binge eating? Behav Res Ther 2011;49:714–7. http://dx.doi.org/10.1016/j.brat.2011.06.006. Jáuregui-Lobera I, Bolaños-Ríos P. Choice of diet in patients with anorexia nervosa. Nutricion Hospitalaria 2009;24:682–7. Steinglass J, Albano AM, Simpson HB, Carpenter K, Schebendach J, Attia E. Fear of food as a treatment target: exposure and response prevention for anorexia nervosa in an open series. Int J Eat Disord 2012;45:615–21. Van Binsbergen CJM, Hulshof KFAM, Wedel M, Odink J, Coelingh Bennink HJT. Food properties and aversions and dietary pattern in anorexia nervosa patients. European Journal of Clinical Nutrition 1888;42:671–8. Gosnell BA, Mitchell JE, Lancaster KL, Burgard MA, Wonderlich SA, Crosby RD. Fear of food as a treatment target: exposure and response prevention for anorexia nervosa in an open series. Int J Eat Disord 2011;45:441–6. Elmore DK, deCastro JM. Meal patterns of normal, untreated bulimia nervosa and recovered bulimic women. Physiology & Behavior 1991;49:99–105. Forbush KT, Wildes JE, Pollack LO, Dunbar D, Luo J, Patterson K, Petruzzi L, Pollpeter M, Miller H, Stone A, Bright A, Watson D. Development and validation of the Eating Pathology Symptoms Inventory (EPSI). Psychological Assessment 2013;25:859–78. Forbush KT, Wildes JE, Hunt TK. Gender norms and validity for the Eating Pathology Symptoms Inventory (EPSI). Int J Eat Disord 2014;47:85–91.

Please cite this article as: Forbush KT, Hunt TK, Characterization of eating patterns among individuals with eating disorders: What is the state of the plate?, Physiol Behav (2014), http://dx.doi.org/10.1016/j.physbeh.2014.02.045