Hostname: page-component-745bb68f8f-l4dxg Total loading time: 0 Render date: 2025-02-06T04:44:52.816Z Has data issue: false hasContentIssue false
  • English
  • Français

The epidemiology and genetics of binge eating disorder (BED)

Published online by Cambridge University Press:  10 August 2015

Caroline Davis
Caroline Davis*
Affiliation:
Kinesiology & Health Sciences, York University, Toronto, Ontario, Canada
*
*Address for correspondence: Professor Caroline Davis, 343 Bethune College, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada. (Email: cdavis@yorku.ca)
Rights & Permissions [Opens in a new window]

Abstract

This narrative review provides an overview of the epidemiology of binge eating disorder (BED), highlighting the medical history of this disorder and its entry as an independent condition in the Feeding and Eating Disorders section of the recently published Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Estimates of prevalence are provided, as well as recognition that the female to male ratio is lower in BED than in other eating disorders. Evidence is also provided of the most common comorbidities of BED, including mood and anxiety disorders and a range of addiction disorders. In addition, discussion of the viewpoint that BED itself may be an addiction — at least in severe cases — is presented. Although the genetic study of BED is still in its infancy, current research is reviewed with a focus on certain neurotransmitter genes that regulate brain reward mechanisms. To date, a focal point of this research has been on the dopamine and the μ-opioid receptor genes. Preliminary evidence suggests that a predisposing risk factor for BED may be a heightened sensitivity to reward, which could manifest as a strong dopamine signal in the brain’s striatal region. Caution is encouraged, however, in the interpretation of current findings, since samples are relatively small in much of the research. To date, no genome-wide association studies have focused exclusively on BED.

Keywords

BEDbinge eating disorderdopamine geneticsepidemiologyopioids
Type
Review Articles
Information
CNS Spectrums , Volume 20 , Special Issue 6: Binge Eating Disorder Differentiating from General Obesity , December 2015 , pp. 522 - 529
Copyright
© Cambridge University Press 2015 

Introduction

Currently, more than half the adult population, in most developed countries, is overweight or obese — the first time in human evolutionary history that the global number of individuals with excess body weight has exceeded those who are underweight.Reference Flegal, Carroll and Kit 1 , Reference Walls, Magliano and Stevenson 2 While the overall population prevalence of obesity has roughly doubled in the past few decades, there was an astonishing 4-fold increase in its morbid form (ie, a body mass index [BMI: weight(kg)/height(m2)] > 40) between the years 1985 and 2002, compared to a more gradual increase at lower BMI categories.Reference Sturm 3 The chronology of this weight-gain occurrence is particularly pertinent, considering that the first clinical reports of BED were published during the midst of this surge in the early 1990s.† Reference Spitzer, Devlin and Walsh 4 Such an exponential increase in morbid obesity suggests that the more weight one gains, the more likely it is that the trend will escalate over time. In other words, it may be that an “overeating sensitization” develops in some individuals, which contributes to more frequent and more excessive consumption and thereby a more rapid increase in weight.Reference Davis 7

Not surprisingly, the two events described above also coincided temporally with pronounced changes in the food environment. For example, in the decades between 1970 and 1996, per capita consumption of augmented sugars in food and drink increased by a significant 23% in adults, similar to increases in the proportion of carbohydrates to total energy intake.Reference Chun, Chung, Wang, Padgitt and Song 8 Compared to foods grown or raised in nature, the high reward-impact of ultraprocessed foods has been magnified multifold. Indeed, the advanced technology of the food-manufacturing industry is largely responsible for the prodigious addition of sweet, fatty, and salty taste enhancers in much of the food we eat on a daily basis.Reference Davis 9 There is now clear evidence that the chronic consumption of these calorically rich foods has enhanced their ability to sabotage healthy brain function and override well-regulated and adaptive ingestive behaviors.Reference Lustig 10

In light of the relatively recent clinical recognition of BED, and its considerable temporal overlap with the environmental and economic events associated with the rise in obesity, BED has the requisite features of a “culture-bound syndrome” — that is, an illness with its emergence and occurrence in a specific ethnic and/or social context.Reference Griffith 11 This perspective puts BED in rather sharp contrast to its clinical counterpart at the other end of the eating and body weight continuum. Importantly, anorexia nervosa has changed little in its biobehavioral characteristics for centuries, and has been found globally in a myriad of different cultures.Reference Keel and Klump 12

BED can also be suitably conceptualized as an “evolutionary mismatch” condition arising from a maladaptive gene–environment interaction. This viewpoint asserts that certain human behaviors were fostered during the hunter-gatherer era, at a time when our genetic endowment was established, because they bestowed survival and reproductive advantages to the species.Reference Nesse and Williams 13 However, in the face of rapid environmental changes — seen, for instance, in the proliferation of highly palatable, and greatly available, processed foods on the grocery shelves in most Western societies — these same behaviors became maladaptive and greatly over-expressed.Reference Davis 9 Specifically, it is strongly believed by evolutionary biologists that we evolved to desire highly palatable and calorically dense foods, and to eat beyond caloric need, since these strategies were the most adaptive in early environments where energy resources were sometimes of unknown quality, and were often unpredictable and scarce.Reference Saad 14 Simply stated, a strong hedonic response to food was an undeniable survival benefit until relatively recently in our evolutionary history.

In support of both the “culture-bound” and the “mismatch” viewpoints, population estimates suggest a roughly equal impact of biological and environmental factors in the risk for BED, although such evidence is still relatively scant. A U.S.-based case-control study of overweight/obese adults with and without BED calculated the heritability of this disorder as 57%Reference Javaras, Laird, Reichborn-Kjennerud, Bulik, Pope and Hudson 15 — a value that was similar to the 41% found in an earlier Scandinavian twin study of binge eating without compensatory behaviors.Reference Reichborn-Kjennerud, Bulik, Tambs and Harris 16 A later twin study also investigated the heritability of BED, but this time at the symptom level rather than as an overall diagnosis, and found similarly that additive genetic effects accounted for 29–43% of the variance in individual symptom items.Reference Mitchell, Neale, Bulik, Aggen, Kendler and Mazzeo 17

The Epidemiology of BED

Prevalence rates and demographic correlates

Relatively few studies have assessed the population prevalence of BED, and those that exist are based mostly on U.S. data. Not surprisingly, estimates tend to vary depending on the diagnostic assessment method that was used; that is, self-administered questionnaires versus interview-based protocols. Employing the latter methodology, lifetime rates were about 3% of the populationReference Hudson, Hiripi, Pope and Kessler 18 , Reference Stice, Marti and Rohde 19 compared to a 6.6% point-prevalence rate with a self-report inventory.Reference Grucza, Przybeck and Cloninger 20 Among the few exceptions to U.S. prevalence studies are World Health Organization adult data from 14 countries, mostly upper-middle and high income, where lifetime prevalence rates were estimated at 1.4% — considerably lower than equivalent U.S. data.Reference Kessler, Berglund and Chui 21 Even lower rates (0.6% and 0.5%, respectively) were found in 2 studies of high school and college students in Portugal,Reference Machado, Gonçalves and Hoek 22 , Reference Ribeiro, Conceição, Vaz and Machado 23 in accord with U.S. evidence that the prevalence of BED is higher in mature adults than in younger individuals.Reference Brewerton, Rance, Dansky, O’Neil and Kilpatrick 24

There was some initial speculation that prevalence rates would increase with the BED modifications that appeared in the recently published Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). 25 The more liberal diagnostic criteria for BED in DSM-5 specify a 3-month period for symptom duration, compared to 6 months duration in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). 26 Based on predictions derived from existing DSM-IV data, however, Hudson et al Reference Hudson, Coit, Lalonde and Pope 27 estimated only negligible increases of less than 0.2% for either lifetime or point prevalence of BED in future studies employing the newly revised standards.

Overall prevalence rates of BED are also moderated by sex/gender and by the BMI status of the sample. In the former case, as with other eating disorders such as anorexia nervosa and bulimia nervosa, there is a pronounced female bias, although the differences are typically not as large in BEDReference Hudson, Hiripi, Pope and Kessler 18 , Reference Striegel, Bedrosian, Wang and Schwartz 28 and vary from approximately a 2:1 to a 6:1 ratio.Reference Ágh, Kovács, Pawaskar, Supina, Inotai and Vokó 29 While there is little doubt that some of these male–female differences can be attributed to sociocultural factors, there is also good evidence from animal models that some of the variance is accounted for by biologically-based factors. For instance, using numerous behavioral criteria for classifying binge-eating phenotypes in adult rats, occurrence rates were 2 to 6 times higher in the females compared to the males.Reference Klump, Racine, Hildebrandt and Sisk 30 These authors concluded that at least some of the differences were the result of gonadal hormones on sex-differentiated behavior during development — effects such as increased reward responsiveness to food in females that tends to override homeostatic mechanisms. Importantly, however, and despite clear male–female differences in the proneness to binge-eating, few significant sex differences have been found in other aspects of the disorder, such as its developmental history,Reference Udo, McKee, White, Masheb, Barnes and Grilo 31 or in the age of onset, the severity of symptoms, and the response to treatment.Reference Guerdjikova, Blom, Mori, Casuto, Keck and McElroy 32

Given the absence of inappropriate compensatory behaviors in BED, it is not surprising that elevated body weight is strongly correlated with this disorder. For example, the lifetime occurrence of BED is substantially higher in samples comprising overweight and obese adults compared to the general population.Reference Hudson, Hiripi, Pope and Kessler 18 , Reference Marcus and Wildes 33 Similarly, the prevalence of this disorder is elevated in those waiting for bariatric surgery,Reference Dahl, Erikson and Vedul-Kjelsås 34 , Reference Vinai, Da Ros and Speciale 35 and in patients attending other weight-loss treatment facilities.Reference Ricca, Castellini and Lo Sauro 36 Studies suggest that between one-quarter and one-half of patients seeking surgical treatment for obesity meet the diagnostic criteria for BED.Reference Vinai, Da Ros and Speciale 35 , Reference Marek, Ben-Porath, Ashton and Heinberg 37 The evidence is also relatively clear that both pre-surgical and post-operative binge-eating are inverse predictors of weight loss at follow-up.Reference de Zwaan, Hilbert and Swan-Kremeier 38 – Reference Wimmelmann, Dela and Mortensen 40 The mechanisms whereby BED is linked to poor treatment success may be partly explained by psychological factors, as seen in the results of a large study of bariatric surgery candidates with and without BED. The former reported significantly greater dysfunctional negative emotions and fewer positive emotions than their weight- and demographically-matched female counterparts.Reference Marek, Ben-Porath, Ashton and Heinberg 41

Comorbid conditions

In addition to the physical comorbidities associated with BED, such as diabetes and metabolic syndrome — those largely occurring due to its strong links with overweight/obesity — BED is also linked with various co-occurring psychiatric disorders in the majority of patients. Lifetime mood and anxiety disorders are the most frequent conjoint disorders (close to 50%) in those with BED,Reference Grilo, White, Barnes and Masheb 42 as they are with most psychiatric disorders including other eating disorders. The next most common comorbidities include a range of addiction disorders — and their sub-syndromal variantsReference Grilo, White, Barnes and Masheb 42 such as alcoholism,Reference Grilo 43 problem gambling,Reference Yip, White, Grilo and Potenza 44 and compulsive shopping.Reference Muller and Mitchell 45 Based on related risk-factor evidence, it is reasonable to speculate that impairments in impulse control found in BED and in addiction disorders are primary factors in both conditions.Reference Davis 7 , Reference Small, Jones, Williams, Bullmore, Robbins and Ersche 46 Greater comorbidity rates have been found in those with child-adolescent onset of binge eating compared to individuals with onset in adulthood.Reference Brewerton, Rance, Dansky, O’Neil and Kilpatrick 24 They have also been associated with more severe psychopathology and poorer daily functioning — although surprisingly not with more frequent binge eating or higher BMI.Reference Grilo, White, Barnes and Masheb 42

In recent years, it has been proposed that some cases of BED are themselves addiction disorders, based on evidence of their considerable symptom overlap with the so-called food-addiction construct — a proposed clinical entity based on parallels between the psychobiobehavioral responses to hyper-palatable, ultraprocessed foods, and to conventional substances of abuse such as cocaine and alcohol.Reference Davis 7 For research purposes, this putative syndrome is typically diagnosed by the Yale Food Addiction Scale (YFAS),Reference Gearhardt, Corbin and Brownell 47 a self-report scale centered on the DSM-IV diagnostic criteria for substance dependence. 26 Indeed, 2 recent studies found that about 50% of obese adults diagnosed with BED also met criteria for YFAS food addiction.Reference Davis, Curtis, Levitan, Carter, Kaplan and Kennedy 48 , Reference Gearhardt, White, Masheb, Morgan, Crosby and Grilo 49 In addition, in an earlier study of women diagnosed with BED, the investigators found that 92% of their sample met the DSM-IV 26 criteria for substance dependence when the word “food” was substituted for “drug” in the questions used in a structured telephone interview.Reference Cassin and von Ranson 50

Such investigations, and related work, have raised the question of whether — at least in some cases — the YFAS-inspired definition of food addiction simply reflects a more severe sub-type of BED. Some preliminary evidence supports this proposed viewpoint. For instance, a group of overweight men and women with BED was dichotomized according to whether they had co-occurring YFAS-diagnosed food addiction or not. Group differences were assessed on several variables related to demographic characteristics (age and BMI), patterns of overeating, personality risk factors, and comorbid clinical symptoms.Reference Davis 51 Results indicated that the 2 BED groups were equivalent in age and BMI. However, the group with food addiction was significantly much more likely to overeat for emotional and cue-driven reasons, they had more severe binge eating and food cravings, and they were more responsive to the rewarding properties of food. This group also had more addictive personality traits, was more impulsive, and had greatly elevated symptoms of depression compared to their non–food addict BED counterparts.

In summary, and based on an expanding amount of evidence, many scientists and clinicians subscribe to the view that some cases of compulsive overeating — a quintessentially defining feature of BED — share pronounced similarities with conventional addictions like substance abuse.Reference Corwin, Avena and Boggiano 52 , Reference Davis and Carter 53 Not surprisingly, such discussions have inspired cautious conclusions that some forms of excessive overeating may be most appropriately viewed as an addiction to hyper-palatable foods. In other words, as the severity and compulsive nature of overeating increase over time, loss of control begins to resemble the physical dependence seen in those addicted to drugs, with the same concomitant symptoms such as powerful cravings and repeated relapses following efforts to abstain.

In concluding, it should also be noted that some argue that the term “food addiction” is a misnomer because it draws too strong a parallel with substance dependence.Reference Hebebrand, Albayrak and Adan 54 Instead, they propose the term “eating addiction.” Such a distinction in terminology appears more semantic than real. On the one hand, there is clear evidence that certain foods have properties similar to addictive substances in their ability to elicit specific brain and behavioral responses.Reference Davis and Carter 55 On the other hand, it is also well-established that the act of consuming a tasty meal is itself a hedonically rewarding experience.Reference Berthold 56 Attempts to distinguish between food and eating — and which is most important in contributing to excessive and compulsive ingestion of a highly palatable diet — are in the same spirit as trying to separate the effects of nicotine from the act of smoking in those who are addicted to cigarettes. In the opinion of this author, in both cases we are describing 2 sides of the same coin.

The Genetics of BED

There is incontrovertible evidence that the risk for BED has a clear biological basis in forming individual risk. For instance, a large family study including overweight and obese individuals with and without BED, as well as their first-degree relatives, found that BED aggregated strongly in families independent of obesity.Reference Hudson, Lalonde and Berry 57 Such results have prompted a growing interest in “brain and behavior” research, using both clinical and preclinical paradigms, to understand better the development and progression of BED. Much of this work has employed sophisticated neuroimaging techniques.Reference Friederich, Wu, Simon and Herzog 58 , Reference Michaelides, Thanos, Volkow and Wang 59 One must be cautious, however, when interpreting this evidence. Psychiatric case-control designs using this methodology only provide a “snap-shot” of the brain at a finite moment in time. It is therefore not possible to deduce if the observed physiology and/or anatomy are antecedent to the condition we are investigating, or a consequence of the behaviors that characterize individuals with the condition of interest. The limitation of neuroimaging technology is particularly relevant for behavioral conditions such as eating and addiction disorders where evidence of neuro-adaptations during the progression of the disorder are well-established.Reference Zhou and Kreek 60 A genetic approach to investigating the biological basis of, and the risk for, BED has the singular advantage of improving our ability to speculate on causal associations.

It has also become clear that inherent vulnerability factors interact with cultural and environment influences to promote maladaptive behaviors and subsequent pathology. For example, a compelling body of evidence suggests that certain foods — viz. processed foods high in sugar, fat, and salt — have an abuse potential similar to other concentrated and processed substances such as alcohol and cocaine.Reference Davis 9 A heightened preference for a calorically-rich diet can thereby increase the risk for overeating in individuals with this inherent predisposition. At the heart of these relationships is the central role of mesocorticolimbic dopamine in the regulation of rewarding behaviors, whether they are so-called “natural reinforcers” like food or pharmacologic reinforcers like cocaine.Reference Le Foll, Gallo, Le Strat, Lu and Gorwood 61 Both the ANKK1 and the DRD2 dopamine receptor genes, for instance, have been significantly associated with addictions across multiple replicated studies.Reference Ma, Yuan, Jiang, Cui and Li 62 The opioid system is also strongly implicated in the regulation of reward, and is known to foster eating behaviors by amplifying the hedonic properties of palatable food.Reference Baisley and Baldo 63 , Reference Ochoa, Lallès, Malbert and Val-Laillet 64 While the last few decades have seen a wealth of research on the genetics of obesity — and by implicit association the genetics of overeating — only a very few studies have been dedicated specifically to the etiology of BED. The following review will focus on case-control studies of BED and/or genetic studies investigating relevant symptom dimensions of BED, such as binge eating and food cravings.

The most commonly studied functional genetic marker of the brain dopamine system is the Taq1A polymorphism on the ANKK1 gene. There is reasonable evidence to suggest that carrying at least one copy of the minor A1 allele (ie genotypes A1/A1 and A1/A2) is associated with a 30–40% reduction in dopamine D2 receptors in the striatal area contributing to a diminished dopamine signal in the reward pathway.Reference Jönsson, Nöthen and Grünhage 65 A1 can thereby be seen as a “loss-of-function” allele. The A118G polymorphism of the μ-receptor gene (OPRM1) is a functional genetic marker of the brain opioid system.Reference Bart, Kreek and Ott 66 , Reference Peciña, Love, Stohler, Goldman and Zubieta 67 By contrast to A1, the minor G allele has been associated with a “gain-of-function” as reflected by an increased responsiveness to a variety of rewarding stimuli, including palatable food.Reference Davis, Zai and Levitan 68 The G allele has also been associated with stronger negative emotions to social separation and with greater positive emotions to social affiliation.Reference Troisi, Frazzetto and Carola 69 While the exact molecular function of the 118G allele is still unclear, evidence of its modulation of social reward is increasing.Reference Loseth, Ellingsen and Leknes 70 Recent evidence of its positive association with neuroticism (a personality trait associated with anxiousness, worry, and stress-proneness) is also of interest, and suggests that this marker may contribute to more labile and pronounced emotional responses both to anticipated rewards, and to their removal — a phenotype that puts one at risk for various psychiatric disorders, including addictions.Reference Peciña, Love, Stohler, Goldman and Zubieta 67

Because of the association of the 2 markers described above (Taq1A and A118G) with the functioning of brain reward mechanisms, an early study examined their conjoint influence in obese adults with and without BED.Reference Davis, Levitan and Reid 71 A significant gene–gene genotype combination showed that of those with the gain–gain genotype (A1– and G+), 80% were BED participants, whereas only 35% of those with the loss–loss genotype (G– and A1+) were from the BED group. These findings suggest that BED may be a subtype of obesity characterized by a hyper-reactivity to reward and to the hedonic properties of food. A more recent study examined 5 functional markers of the dopamine D2 receptor genes (DrD2/ANKK1) in a group of obese adults with and without BED.Reference Davis, Levitan, Yilmaz, Kaplan, Carter and Kennedy 72 Results indicated that the BED group was significantly related to the Taq1A and the C957T genotypes that reflect enhanced dopamine neurotransmission (viz. A2/A2 and T/T, respectively). Allelic analyses also indicated that the T allele of C957T was significantly overrepresented in the BED group compared to the non-BED obese counterparts. In addition, sub-phenotypes of BED such as binge eating, emotional eating, hedonic eating, and food cravings were also higher in the A2/A2 genotype, while the T/T genotype was only significantly related to the measure of binge frequency and severity.

A recognition that complex human traits and behaviors are under multigenetic control has fostered the current view that common disorders may be better conceptualized in quantitative terms than as discrete qualitative entities.Reference Plomin, Hawthorn and Davis 73 From the perspective of genetic analyses, it has been suggested that relevant genetic variants can be summated into a composite index that reflects a polygenetic liability for the disorder in question — a potentially more powerful approach to uncovering important genetic risk factors, because individual polymorphic loci typically tend only to account for a small proportion of phenotypic variance and therefore may not reach statistical significance in studies with relatively small clinical samples.Reference Nikolova, Ferrell, Manuck and Hariri 74 Using such an approach, and including 6 functional markers on 4 dopamine genes — ANKK1, DRD2, DAT1, and COMT, we found that the BED group showed a significantly higher multilocus genetic profile score than the obese non-BED counterparts, implying greater brain dopamine signaling strength in the striatum and a higher responsiveness to reward among the participants with BED.Reference Davis, Levitan and Carter 75 These findings mesh with other psychobehavioral evidence that BED is a reward-reactive subtype of obesity.Reference Davis, Levitan and Reid 71 , Reference Davis, Levitan, Yilmaz, Kaplan, Carter and Kennedy 72

The role of serotonin (5-HT) involvement in modulating disordered eating has been widely studied for many years, especially in the context of anorexia nervosa. Relatively few studies in this area have focused on BED, and even fewer of these on the possible role of serotonin genes in the development of this disorder. One early study genotyped the 5-HTTLPR polymorphism of the serotonin transporter gene (5HTT) and found that both the Long/Long genotype and the Long allele were significantly more frequent in a sample of women with BED compared to controls,Reference Monteleone, Tortorella, Castaldo and Maj 76 although these findings have not been replicated in subsequent research.Reference Calati, De Ronchi, Bellini and Serretti 77 While a more recent study found no 5-HTTLPR effect on the severity of binge eating in the general population, it was observed that women with the Short/Short genotype had great anxiety and a tendency for higher impulsivity — traits associated with the personality profile of those with BED.Reference Akkermann, Nordquist, Oreland and Harro 78

And finally, because of evidence that melanocortins — peptide hormones that are expressed in the hypothalamus and have an important role in regulating appetite — have strong links with obesity,Reference Muller, Thearle and Piaggi 79 , Reference Wang, Li and Zhang 80 some recent work has investigated whether the melanocortin 4 receptor gene (MC4R) has a role in the etiology of binge eating. While most of the studies have produced null results,Reference Lubrano-Berthelier, Dubern and Lacorte 81 , Reference Valette, Poitou and Kesse-Guyot 82 one such study included more than twice as many patients with bulimia nervosa in the same group as those with BED and only included non-obese participantsReference Gamero-Villarroel, Rodriguez-Lopez and Jimenez 83 — a design that may have compromised the ability to detect effects specific to BED. More promising results have come from a study of adults with European ancestry where the C allele of the rs17782313 MC4R marker was associated with higher scores on a trait measure of food cravings, and suggested that this variable partially mediated the relationship between the genetic variant and BMI.Reference Yilmaz, Davis and Loxton 84

Summary and Conclusions

In the 35 years since the first clinical reports of BED appeared in the literature, we have gained a good understanding of its prevalence and major demographic characteristics — especially its association with obesity and its conceptualization, in severe cases, as a form of addiction. Evidence of its clinical comorbidities and the psychopathology characteristics, such as anxiety, depressed mood, and impulsiveness that link compulsive overeating to other psychiatric conditions, is also well-established. Less clearly delineated is the neuroscience of BED and the innate risk factors that predispose to this condition. To date, the limited genetic research on BED has indicated the involvement of both dopamine and μ-opioid receptor genes in the etiology of this disorder. It has been tentatively concluded that a risk for compulsive overeating may be a strong responsiveness to the hedonic properties of food, and a heightened preference for sweet and fatty cuisine. These particular traits were deemed highly adaptive in an environment characterized by uncertain and often scarce energy resources — one that described most of our evolutionary history. They are, however, mismatched to our current environment with its superfluity of highly palatable, calorically dense, and nutritionally impoverished foods.

An important issue in future BED research — given its strong links with other compulsive behaviors such as substance abuse and gambling addiction — is to include the appropriate control groups, or what have sometimes been called “super-controls.” This is of particular relevance to genetic research in BED given the evidence from population-based transmission studies that common biological factors contribute to the excessive use of a broad range of addictive drugs and activities, and that these influences do not differ between men and women.Reference Agrawal and Lynskey 85 In case-control designs, a control participant should be similar to the cases except that it is absent of the condition under investigation. Since it is known, for example, that polymorphisms of the dopamine receptor genes are associated with a number of impulsive-addictive/compulsive disorders including BED,Reference Chen, Blum and Chen 86 it is important to screen potential control participants for a broader range of conditions than simply for disordered eating.

Disclosures

Caroline Davis has the following disclosure: Shire Pharmaceuticals, consultant advisor, consulting fee.

Footnotes

†

As early as 1955, a related syndrome was reported.5 Found in certain obese individuals, it was referred to as night-eating syndrome and was characterized by “nocturnal hyperphasia, insomnia and morning anorexia” (p. 78).5 This condition appeared to be most prominent during periods of stress and weight gain. The 1950s also saw a few isolated publications about so-called “food addiction” by Randolph,6 but this putative condition also did not gain widespread acceptance for another 30 or 40 years.

References

1. Flegal, KM, Carroll, MD, Kit, BK, et al. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA. 2012; 307(5): 491–497.Google Scholar
2. Walls, HL, Magliano, DJ, Stevenson, CE, et al. Projected prevalence of obesity in Australia. Obesity. 2012; 20(4): 872–878.CrossRefGoogle ScholarPubMed
3. Sturm, R. Increases in clinically severe obesity in the United States, 1986–2000. Arch Intern Med. 2003; 163(18): 2146–2148.CrossRefGoogle ScholarPubMed
4. Spitzer, RL, Devlin, MJ, Walsh, BT, et al. Binge eating disorder – to be or not to be in DSM-IV. Int J Eat Disord. 1991; 10(6): 627–629.Google Scholar
5. Stunkard, AJ, Grace, WJ, Wolff, HG. The night-eating syndrome. Am J Med. 1955; 19(1): 78–86.Google Scholar
6. Randolph, TG. The descriptive features of food addiction — addictive eating and drinking. Q J Stud Alcohol. 1956; 17(2): 198–224.CrossRefGoogle ScholarPubMed
7. Davis, C. From passive overeating to “food addiction”: a spectrum of compulsion and severity. ISRN Obesity. 2013; 2013 Article ID 435027.Google Scholar
8. Chun, OK, Chung, CE, Wang, Y, Padgitt, A, Song, WO. Changes in intake of total and added sugar and their contributions to energy intake in the U.S. Nutrients. 2010; 2(8): 834–854.Google Scholar
9. Davis, C. Evolutionary and neuropsychological perspective on addictive behaviors and addictive substances: relevance to the “food addiction” construct. Subst Abuse Rehabil. 2014; 5: 129–137.CrossRefGoogle Scholar
10. Lustig, RH. Fructose: it’s “alcohol without the buzz.” Adv Nutr. 2013; 4(2): 226–235.Google Scholar
11. Griffith, L. Culture‐bound syndrome. In Cockerham W, Dingwall R, Quah SR, eds. The Wiley Blackwell Encyclopedia of Health, Illness, Behavior, and Society. Wiley-Blackwell;2014.Google Scholar
12. Keel, PK, Klump, KL. Are eating disorders culture-bound syndromes? Implications for conceptualizing their etiology. Psychol Bull. 2003; 129(5): 747–769.Google Scholar
13. Nesse, RM, Williams, GC. Why We Get Sick. New York: Random House; 1994.Google Scholar
14. Saad, G. Evolutionary consumption. J Consum Psychol. 2013; 23(3): 351–371.Google Scholar
15. Javaras, KN, Laird, NM, Reichborn-Kjennerud, T, Bulik, CM, Pope, HG Jr, Hudson, JI. Familiarity and heritability of binge eating disorder: results of a case-control family study and a twin study. Int J Eat Disord. 2008; 41(2): 174–179.Google Scholar
16. Reichborn-Kjennerud, T, Bulik, CM, Tambs, K, Harris, JR. Genetic and environmental influences on binge eating in the absence of compensatory behaviors: a population-based twin study. Int J Eat Disord. 2004; 36(3): 307–314.CrossRefGoogle ScholarPubMed
17. Mitchell, KS, Neale, MC, Bulik, CM, Aggen, SH, Kendler, KS, Mazzeo, SE. Binge eating disorder: a symptom-level investigation of genetic and environmental influences on liability. Psychol Med. 2010; 40(11): 1899–1906.Google Scholar
18. Hudson, JI, Hiripi, E, Pope, HG Jr, Kessler, RC. The prevalence and correlates of eating disorders in the National Comorbidity Survey replication. Biol Psychiatry. 2007; 61(3): 348–358.Google Scholar
19. Stice, E, Marti, N, Rohde, P. Prevalence, incidence, impairment, and course of the proposed DSM-5 eating disorder diagnoses in an 8 year prospective community study of young women. J Abnorm Psychol. 2013; 122(2): 445–457.Google Scholar
20. Grucza, RA, Przybeck, TR, Cloninger, CR. Prevalence and correlates of binge eating disorder in a community sample. Compr Psychiatry. 2007; 48(2): 124–131.Google Scholar
21. Kessler, RC, Berglund, PA, Chui, WT, et al. The prevalence and correlates of binge eating disorder in the World Health Organization World Mental Health Surveys. Biol Psychiatry. 2013; 73(9): 904–914.Google Scholar
22. Machado, PP, Gonçalves, S, Hoek, HW. DSM-5 reduces the proportion of EDNOS cases: evidence from community samples. Int J Eat Disord. 2013; 46(1): 60–65.Google Scholar
23. Ribeiro, M, Conceição, E, Vaz, AR, Machado, PP. The prevalence of binge eating disorder in a sample of college students in the north of Portugal. Eur Eat Disord Rev. 2014; 22(3): 185–190.Google Scholar
24. Brewerton, TD, Rance, SJ, Dansky, BS, O’Neil, PM, Kilpatrick, DG. A comparison of women with child-adolescent versus adult onset binge eating: results from the National Women’s Study. Int J Eat Disord. 2014; 47(7): 836–843.Google Scholar
25. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Washington, DC: American Psychiatric Association; 2013.Google Scholar
26. American Psychiatric Association. Diagnostic and Statistical Manualof Mental Disorders, 4th ed, rev. Washington, DC: American Psychiatric Association; 1994.Google Scholar
27. Hudson, JI, Coit, CE, Lalonde, JK, Pope, HG Jr. By how much will the proposed new DSM-5 criteria increase the prevalence of binge eating disorder? Int J Eat Disord. 2012; 45(1): 139–141.Google Scholar
28. Striegel, RH, Bedrosian, R, Wang, C, Schwartz, S. Why men should be included in research on binge eating: results from a comparison of psychosocial impairments in men and women. Int J Eat Disord. 2012; 45(2): 233–240.CrossRefGoogle ScholarPubMed
29. Ágh, T, Kovács, G, Pawaskar, M, Supina, D, Inotai, A, Vokó, Z. Epidemiology, health-related quality of life and economic burden of binge eating disorder: a systematic literature review. Eat Weight Disord. 2015; 20(1): 1–12.Google Scholar
30. Klump, KL, Racine, S, Hildebrandt, B, Sisk, CL. Sex differences in binge eating patterns in male and female adult rats. Int J Eat Disord. 2013; 46(7): 729–736.CrossRefGoogle ScholarPubMed
31. Udo, T, McKee, SA, White, MA, Masheb, RM, Barnes, RD, Grilo, CM. Sex differences in biopsychosocial correlates of binge eating disorder: a study of treatment-seeking obese adults in primary care setting. Gen Hosp Psychiatry. 2013; 35(6): 587–591.Google Scholar
32. Guerdjikova, AI, Blom, TJ, Mori, N, Casuto, L, Keck, PE Jr, McElroy, SL. Gender differences in binge eating disorder: a pooled analysis of eleven pharmacotherapy trials from one research group. J Mens Health. 2014; 11(4): 183–188.Google Scholar
33. Marcus, MD, Wildes, JE. Disordered eating in obese individuals. Curr Opin Psychiatry. 2014; 27(6): 443–447.Google Scholar
34. Dahl, JK, Erikson, L, Vedul-Kjelsås, E, et al. Prevalence of all relevant eating disorders I patients waiting for bariatric surgery: a comparison between patients with and without eating disorders. Eat Weight Disord. 2010; 15(4): 247–255.Google Scholar
35. Vinai, P, Da Ros, A, Speciale, M, et al. Psychopathological characteristics of patients seeking for bariatric surgery, either affected or not by binge eating disorder following the criteria of the DSM IV TR and of the DSM 5. Eat Behav. 2015; 16: 1–4.Google Scholar
36. Ricca, V, Castellini, G, Lo Sauro, C, et al. Correlations between binge eating and emotional eating in a sample of overweight subjects. Appetite. 2009; 53(3): 418–421.Google Scholar
37. Marek, RJ, Ben-Porath, YS, Ashton, K, Heinberg, LJ. Impact of using DSM-5 criteria for diagnosing binge eating disorder in bariatric surgery candidates: change in prevalence rate, demographic characteristics, and scores on the Minnesota Multiphasic Personality Inventory–2 Restructured Form (MMPI-2-RF). Int J Eat Disord. 2014; 47(5): 553–557.Google Scholar
38. de Zwaan, M, Hilbert, A, Swan-Kremeier, L, et al. Comprehensive interview assessment of eating behavior 18–35 months after gastric bypass surgery for morbid obesity. Surg Obes Relat Dis. 2010; 6(1): 79–85.Google Scholar
39. Sheets, CS, Peat, CM, Berg, KC, et al. Post-operative psychosocial predictors of outcome in bariatric surgery. Obes Surg. 2015; 25(2): 330–345.Google Scholar
40. Wimmelmann, CL, Dela, F, Mortensen, EL. Psychosocial predictors of weight loss after bariatric surgery: a review of the recent research. Obes Res Clin Pract. 2014; 8(4): e299–e313.Google Scholar
41. Marek, RJ, Ben-Porath, YS, Ashton, K, Heinberg, LJ. Minessota Multiphasic Personality Inventory–2 Restructured Form (MMPI-2-RF) scale score differences in bariatric surgery candidates diagnoses with binge eating disorder versus BMI-matched controls. Int J Eat Disord. 2014; 47(3): 315–319.Google Scholar
42. Grilo, CM, White, MA, Barnes, RD, Masheb, RM. Psychiatric disorder co-morbidity and correlates in an ethnically diverse sample of obese patients with binge eating disorder in primary care settings. Compr Psychiatry. 2013; 54(3): 209–216.Google Scholar
43. Grilo, CM. Significance of alcohol use disorders in binge eating disorder: a controlled study of co-morbidity. Alcohol and Alcoholism. 2011; 46(Suppl 1): 35.Google Scholar
44. Yip, SW, White, MA, Grilo, CM, Potenza, MN. An exploratory study of clinical measures associated with subsyndromal pathological gambling in patients with binge eating disorder. J Gambl Stud. 2011; 27(2): 257–279.Google Scholar
45. Muller, A, Mitchell, JE. Internet shopping from a psychiatric perspective. Psychiatric Annals. 2014; 44(8): 384–387.Google Scholar
46. Small, DG, Jones, PS, Williams, GB, Bullmore, ET, Robbins, TW, Ersche, KD. Overlapping decline in orbitofrontal gray matter volume related to cocaine use and body mass index. Addict Biol. 2013; 20(1): 194–196.Google Scholar
47. Gearhardt, AN, Corbin, WR, Brownell, KD. Preliminary validation of the Yale Food Addiction Scale. Appetite. 2009; 52(2): 430–436.Google Scholar
48. Davis, C, Curtis, C, Levitan, RD, Carter, JC, Kaplan, AS, Kennedy, JL. Evidence that ‘food addiction’ is a valid phenotype of obesity. Appetite. 2011; 57(3): 711–717.CrossRefGoogle ScholarPubMed
49. Gearhardt, AN, White, MA, Masheb, RM, Morgan, PT, Crosby, RD, Grilo, CM. An examination of the food addiction construct in obese patients with binge eating disorder. Int J Eat Disord. 2012; 45(5): 657–663.Google Scholar
50. Cassin, SE, von Ranson, KM. Is binge eating experienced as an addiction? Appetite. 2007; 49(3): 687–690.CrossRefGoogle ScholarPubMed
51. Davis, C. Compulsive overeating as an addictive behavior: overlap between food addiction and binge eating disorder. Curr Obes Rep. 2013; 2(2): 171–178.CrossRefGoogle Scholar
52. Corwin, RL, Avena, NM, Boggiano, MM. Feeding and reward: perspectives from three rat models of binge eating. Physiol Behav. 2011; 104(1): 87–97.CrossRefGoogle ScholarPubMed
53. Davis, C, Carter, JC. Compulsive overeating as an addiction disorder: A review of theory and evidence. Appetite. 2009; 53(1): 1–8.Google Scholar
54. Hebebrand, J, Albayrak, Ö, Adan, R, et al. “Eating addiction”, rather than “food addiction”, better captures addictive-like eating behavior. Neurosci Biobehav Rev. 2014; 47: 295–306.CrossRefGoogle Scholar
55. Davis, C, Carter, JC. If certain foods are addictive, how might this change the treatment of compulsive overeating and obesity? Curr Addict Rep. 2014; 1(2): 89–95.Google Scholar
56. Berthold, HR. Metabolic and hedonic drivers in the neural control of appetite: who is the boss? Curr Opin Neurobiol. 2011; 21(6): 888–896.Google Scholar
57. Hudson, JI, Lalonde, JK, Berry, JM, et al. Binge eating disorder as a distinct familial phenotype of in obese individuals. Arch Gen Psychiatry. 2006; 63(3): 313–319.CrossRefGoogle ScholarPubMed
58. Friederich, HC, Wu, M, Simon, JJ, Herzog, W. Neurocircuit function in eating disorders. Int J Eat Disord. 2013; 46(5): 425–432.Google Scholar
59. Michaelides, M, Thanos, PK, Volkow, ND, Wang, GJ. Dopamine-related frontostriatal abnormalities in obesity and binge-eating disorder: emerging evidence for developmental psychopathology. Int Rev Psychiatry. 2012; 24(3): 211–218.Google Scholar
60. Zhou, Y, Kreek, MJ. Alcohol: a stimulant activating brain stress responsive systems with persistent neuroadaptation. Neuropsychopharmacology. 2014; 87: 51–58.Google Scholar
61. Le Foll, B, Gallo, A, Le Strat, Y, Lu, L, Gorwood, P. Genetics of dopamine receptors and drug addiction: a comprehensive review. Behav Pharmacol. 2009; 20(1): 1–17.Google Scholar
62. Ma, Y, Yuan, W, Jiang, X, Cui, WY, Li, MD. Updated findings of the association and functional studies of DRD2/ANKK1 variants with addictions. Mol Neurobiol. 2015; 51(1): 281–299.Google Scholar
63. Baisley, SK, Baldo, BA. Amylin receptor signaling in the nucleus accumbens negatively modulates µ-opioid-driven feeding. Neuropsychopharmacology. 2014; 39(13): 3009–3017.Google Scholar
64. Ochoa, M, Lallès, J-P, Malbert, C-H, Val-Laillet, D. Dietary sugars: their detection by the gut-brain axis and their peripheral and central effects in health and disease. Eur J Nutr. 2015; 54(1): 1–24.Google Scholar
65. Jönsson, EG, Nöthen, MN, Grünhage, F, et al. Polymorphisms in the D2 receptor gene and their relationships to striatal receptor density in healthy volunteers. Mol Psychiatry. 1999; 4(3): 290–296.Google Scholar
66. Bart, G, Kreek, MJ, Ott, J, et al. Increased attributable risk related to a functional mu-receptor gene polymorphism in association with alcohol dependence in central Sweden. Neuropsychopharmacology. 2005; 30(2): 417–422.Google Scholar
67. Peciña, M, Love, T, Stohler, CS, Goldman, D, Zubieta, JK. Effects of the mu opioid receptor polymorphism (OPRM1 A118G) on pain regulation, placebo effects and associated personality trait measures. Neuropsychopharmacology. 2015; 40(4): 957–965.Google Scholar
68. Davis, C, Zai, C, Levitan, RD, et al. Opiates, overeating, and obesity: a psychogenetic analysis. Int J Obes (Lond). 2011; 35(10): 1347–1354.Google Scholar
69. Troisi, A, Frazzetto, G, Carola, V, et al. Social hedonic capacity is associated with the A118G polymorphism of the mu-opioid receptor gene (OPRM1) in adult healthy volunteers and psychiatric patients. Soc Neurosci. 2011; 6(1): 88–97.Google Scholar
70. Loseth, GE, Ellingsen, D-M, Leknes, S. State-dependent µ-opioid modulation of social motivation. Front Behav Neurosci. 2014; 8: 430.Google Scholar
71. Davis, C, Levitan, RD, Reid, C, et al. Dopamine for “wanting” and opioids for “liking”: a comparison of obese adults with and without binge eating. Obesity (Silver Spring). 2009; 17(6): 1220–1225.Google Scholar
72. Davis, C, Levitan, RD, Yilmaz, Z, Kaplan, AS, Carter, JC, Kennedy, JL. Binge eating disorder and the dopamine D2 receptor: genotypes and sub-phenotypes. Prog Neuropsychopharmacol Biol Psychiatry. 2012; 38(2): 328–335.Google Scholar
73. Plomin, R, Hawthorn, CMA, Davis, OSP. Common disorders are quantitative traits. Nat Rev Genet. 2009; 10(12): 872–878.Google Scholar
74. Nikolova, YS, Ferrell, RE, Manuck, SB, Hariri, AR. Multilocus genetic profile for dopamine signaling predicts ventral striatum reactivity. Neuropsychopharmacology. 2011; 36(9): 140–147.Google Scholar
75. Davis, C, Levitan, RD, Carter, JC, et al. Binge eating disorder and ‘food addiction’: a multi-locus genetic profile study. Paper presented at: the annual meeting of the Eating Disorder Research Society; September 2012; Porto, Portugal.Google Scholar
76. Monteleone, P, Tortorella, A, Castaldo, E, Maj, M. Association of a functional serotonin gene polymorphism with binge eating disorder. Am J Med Genet B Neuropsychiatr Genet. 2006; 141B(1): 7–9.Google Scholar
77. Calati, R, De Ronchi, D, Bellini, M, Serretti, A. The 5-HTTLPR polymorphism and eating disorders: a meta-analysis. Int J Eat Disord. 2011; 44(3): 191–199.Google Scholar
78. Akkermann, K, Nordquist, N, Oreland, L, Harro, J. Serotonin transporter gene promotor polymorphism affects the severity of binge eating in general population. Prog Neuropsychopharmacol Biol Psychiatry. 2010; 34(1): 111–114.Google Scholar
79. Muller, YL, Thearle, MS, Piaggi, P, et al. Common genetic variation in and near the melanocortin 4 receptor gene (MC4R) is associated with body mass index in American Indian adults and children. Hum Genet. 2014; 133(11): 1431–1441.CrossRefGoogle ScholarPubMed
80. Wang, K, Li, WD, Zhang, CK, et al. A genome-wide association study on obesity and obesity-related traits. PLoS One. 2011; 6(4): e24303.Google Scholar
81. Lubrano-Berthelier, C, Dubern, B, Lacorte, JM, et al. Melanocortin 4 receptor mutation in a large cohort of severely obese adults: prevalence, functional classification, genotype-phenotype relationship, and lack of association with binge eating. J Clin Endocrinol Metab. 2006; 91(5): 1811–1818.CrossRefGoogle Scholar
82. Valette, M, Poitou, C, Kesse-Guyot, E, et al. Association between melanocortin-4 receptor mutations and eating behaviors in obese patients: a case-control study. Int J Obes (Lond). 2014; 38(6): 883–885.Google Scholar
83. Gamero-Villarroel, C, Rodriguez-Lopez, R, Jimenez, M, et al. Melanocortin-4 receptor variants are not associated with binge-eating behavior in nonobese patients with eating disorders. Psychiatr Genet. 2015; 25(1): 35–38.CrossRefGoogle Scholar
84. Yilmaz, Z, Davis, C, Loxton, NJ, et al. Association between MC4R rs17782313 polymorphism and overeating behaviors. Int J Obes (Lond). 2015; 39(1): 114–120.Google Scholar
85. Agrawal, A, Lynskey, MT. Are there genetic influences on addiction: Evidence from family, adoption and twin studies. Addiction. 2008; 103(7): 1069–1081.Google Scholar
86. Chen, ALC, Blum, K, Chen, TJH, et al. Correlation of the Taq1 dopamine D2 receptor gene and percent body fat in obese and screened control subjects: a preliminary report. Food Funct. 2012; 3(1): 40–48.Google Scholar