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. Author manuscript; available in PMC: 2010 May 13.
Published in final edited form as: J Addict Med. 2009 Mar 1;3(1):26–32. doi: 10.1097/ADM.0b013e31819638b0

Exploration of food addiction in pediatric patients: A preliminary investigation

Lisa J Merlo 1, Courtney Klingman 1, Toree H Malasanos 2, Janet H Silverstein 2
PMCID: PMC2869098  NIHMSID: NIHMS194512  PMID: 20473361

Abstract

Objectives

The goals of the present study were to explore the possibility that symptoms of food addiction may exist for some children and to identify factors that may be associated with pediatric food addiction.

Methods

Participants were 50 children (aged 8-19), recruited from the Pediatric Lipid Clinic at a large southeastern teaching hospital, and their parent/guardian. Participants completed questionnaires to assess food- and eating-related attitudes and behaviors, as well as symptoms of food addiction.

Results

Parent- and child-reported behaviors and attitudes demonstrated similar patterns. Child BMI ratings were significantly correlated with overeating (r = .42, p = .02) and emotional eating (r = .33, p = .04). Of note, 15.2% of children indicated that they “Often,” “Usually,” or “Always” think that they are addicted to food, and an additional 17.4% reported that they “Sometimes” feel that way. Food addiction symptoms were significantly correlated with child overeating (r = .64, p < .001), uncontrolled eating (r = .60, p < .001), emotionol eating (r = .62, p < .001), food preoccupation (r = .58, p < .001), overconcern with body size (r = .54, p < .001), and caloric awareness and control (r = −.31, p = .04).

Conclusions

Results of the present study suggest that “food addiction” may be a real problem for a subset of children who suffer from overweight/obesity. Identification of food addiction may improve obesity treatment efforts for this subset of patients.

Keywords: Food addiction, Obesity, Children, Adolescents

The prevalence of pediatric overweight and obesity has risen substantially across recent decades, with some estimating the increase in pediatric obesity to be between 200-400% since the mid-to-late 1990’s1. This rise is especially concerning because obesity is known to be associated with numerous medical, psychological, and social problems, which can be exacerbated in children and adolescents2. Health consequences of overweight include liver disease, sleep apnea, joint pain, impaired mobility, and fractures of the bone3, and two of the most commonly documented hazards of obesity are metabolic syndrome (i.e., insulin resistance, type 2 diabetes, polycystic ovary syndrome, dyslipidemia) and increased risk for cardiovascular disease in adulthood4,5. In fact, one study of American adolescents showed that 89% of overweight teens had at least one irregular metabolic indicator6, and another study of 500 American children and teens revealed the presence of a metabolic syndrome in nearly 50% of children whose BMI was greater than 99% of the population7. In addition to the innumerable physical health problems, several psychological and behavioral problems are also linked to obesity. Children and adolescents who are overweight generally display more behavioral and self-esteem problems than their peers of normal weight, and show higher incidences of depression and impaired social functioning8,9,10. Unfortunately, the consequences of childhood obesity appear to extend to adulthood as well. A 20-year prospective study demonstrated a connection between childhood obesity and depression/aggression in adulthood11. Studies have also demonstrated that those who binge eat as youth have an increased risk for substance-abuse in adulthood and are more likely to have relatives with addiction disorders12.

Identifying the causes of obesity in pediatric patients can be challenging. Routine screening for risk factors of pediatric obesity is infrequent (and generally limited to an annual well-child visit). In addition, treatment for overweight/obesity is only provided to a small number of children, due to low treatment availability and high costs2. Although diet and exercise are generally targeted, addiction to food has recently been identified as an additional potential factor contributing to the rise in obesity13. Though still a theoretical concept, there are several factors which may play a role in the development of food addiction. Indeed, the mechanisms (including genetics, environmental influences, social learning, and neurobiological factors) contributing to food addiction are being compared to those that influence addiction to drugs2.

With regard to hereditary factors, research suggests that children born to parents who are overweight are more likely to become overweight themselves, and are at higher risk for obesity throughout their lives. In fact, some studies show as much as 60% of one’s vulnerability for obesity can be attributed to genetics13. Researchers who examined concordance rates of obesity in identical twins found that similarities in degree of overweight were twice as high for identical twins as they were for fraternal twins14. Stunkard et al.14 also found in their twin studies that weight, height, and Body Mass Index (BMI) were highly correlated across time, suggesting that genetics play a large role in that co-variation. In addition, just as inherited factors (i.e., mechanisms involved in drug absorption and metabolism) may enhance a person’s vulnerability to substance abuse15, similar factors may affect individuals’ response to food. Kampov-Polevy and colleagues16 reported that family history of alcohol dependence is also associated with increased preference for sweetness, suggesting similar genetic mechanisms that could contribute to both alcohol and high-sugar food addictions. In addition,Tsuang et al.15 assert that, since genes have been shown to affect certain areas of personality, personality may also influence an individual’s potential to become addicted due to variations in the degree to which an individual finds a substance (or, in this case, food) pleasant.

Although genetics play a role in addiction, most experts agree that environmental factors also contribute significantly to the development of addiction17. Regardless of whether the substance of abuse is food or a drug, some believe that the probability of developing an addiction disorder is influenced significantly, and possibly equally, by both genetic and environmental factors17,18. For example, the increased availability of high-fat high-calorie foods and the extensive advertising of sugary foods to children can greatly impact their food selection and the development of pediatric obesity19. Public health initiatives designed to limit the marketing of low-nutrition foods may decrease overconsumption of these products, in the same way that public health interventions have targeted tobacco and alcohol marketing to reduce consumption. Like substance use, compulsive eating may also be influenced by social factors, with children learning over-eating habits by observing their parents and peers. Most individuals initially obtain substances of abuse from family or friends, and model behaviors they have witnessed by these individuals20. Finally, studies have shown that children who experience high levels of stress and anxiety are more likely to develop disordered eating, and particularly compulsive overeating, by turning to food to relieve their worries21. Just as an individual who suffers from drug addiction may turn to drug use as a coping mechanism, some individuals who “abuse” food report using it in order to manage difficult situations, relationships, and negative affect. In humans, the literature shows that few people (~30%) experience a decrease in food intake during times of stress; whereas, the majority of individuals increase their food intake when experiencing stress21. As children’s lives become more fast-paced, complicated, and competitive, they may increasingly turn to food in order to help relieve their stress.

From a neurobiological perspective, evidence is accumulating to show that food addiction and drug addiction are closely related conditions22. Prominent scientists have hypothesized that the biological mechanisms of feeding and addiction have overlapped throughout evolutionary history13. Indeed, appetitive drive for food and craving for drugs purportedly share overlapping and interactive pathways in the brain, especially in the hypothalamus, which is involved in food regulation and energy expenditure2. In addition, both food and drugs are associated with activation of the dopamine-based reward system within the brain. When an individual anticipates the ingestion of food, the body experiences an increase in the extracellular level of dopamine in the nucleus accumbens, just as the body would experience in anticipation of other substances of abuse23. Dopamine D2 receptors are responsible for mediating reinforcing responses, so obesity can be seen as a “reward deficiency syndrome”23. When individuals experience decreased levels of dopamine, this triggers feeding behaviors in order to restore levels of dopamine in the brain23. However, as animal research has demonstrated,24 a “tolerance” can develop such that, when the individual ingests excessive amounts of fat- and sugar-rich foods, the body craves more and more to satisfy the hunger, just as with drugs of abuse.

Despite the many consequences of pediatric obesity and the similarities between drug abuse and excessive food consumption, most clinicians do not screen for the presence of food addiction when evaluating patients or developing a treatment plan. This is not unexpected, as currently there is no accepted definition or diagnostic criteria for food addiction. There are limited data regarding the phenomenology of food addiction in adult patients, but virtually no work has been done in this area for pediatric patients. The present study was designed as a preliminary investigation to explore the possibility that symptoms of food addiction may exist for some individuals beginning in childhood. The goal of the study was to identify factors that may be associated with food addiction during childhood, in order that effective interventions might be developed for this subset of patients.

Methods

Participants

Participants were 50 children, recruited from the Pediatric Lipid Clinic at a large southeastern teaching hospital, and their parent/guardian. The children (64% female) ranged in age from 8 years, 4 months to 19 years (M = 13.8 years, SD = 2.7 years), and self-identified as Causcasian (60%), African American (24%), Hispanic (6%), Asian (2%), American Indian/Alaska Native (2%), or Other (6%) . Children were referred to the Lipid Clinic due to problems associated with overweight/obesity or other metabolic conditions (e.g., hyperlipidemia, type II diabetes, etc.). Body Mass Index (BMI) ratings for children were calculated using the Centers for Disease Control (CDC) BMI Calculator for Child and Teen individuals (http://apps.nccd.cdc.gov/dnpabmi/Calculator.aspx). Based on this calculator, BMI ratings for children were capped at a maximum of 51.5. The children in this study had a mean BMI rating of 35.6 (SD = 10.6), ranging from 19.0 to 51.5. The CDC calculator further classifies children based on their BMI percentile, which is adjusted for age and gender (i.e., underweight = less than 5th percentile, healthy weight = 5th to less than 85th percentile, overweight = 85th to less than 95th percentile, and obese = 95th percentile or greater).

The parent/guardians (87% female) ranged in age from 30-65 years (M = 43.2 years, SD = 7.0 years). The BMI ratings for parents were computed using the Centers for Disease Control Adult BMI Calculator (http://www.cdc.gov/nccdphp/dnpa/healthyweight/assessing/bmi/adult_BMI/english_bmi_calculator/bmi_calculator.htm). Ratings of BMI for the parents ranged from 15.5 to 57.3 (M =33.0, SD = 9.4). Approximately 68% of parents reported being currently married, with 21% divorced, 7% never married, and 4% widowed. Families reported average annual income ranging from less than $15,000 to $200,000 (M = $46,700, SD = $41,322).

Measures

Eating Attitudes Test (EAT)25,26

The EAT is a 26-item measure, scored on a 6-point Likert-type scale. It assesses attitudes towards food and personal eating behaviors. Sample items include “I take longer than others to eat my meals” and “I feel extremely guilty after eating.” The eat also contains 4 questions assessing history of eating disorder behavior, including questions about bingeing, purging, using pills to control weight, and history of treatment for an eating disorder. The measure yields a total score, as well as subscale scores for Dieting, Food Preoccupation, and Oral Control. The EAT has demonstrated good psychometric properties27.

Children’s Eating Attitudes Test (ChEAT)28

The ChEAT is a 26-item children’s version of the EAT, which was developed to assess children’s attitudes regarding food and eating. Items such as, “Scared about being overweight” and “Others pressure me to eat” are scored on a 6-point Likert-type scale. The ChEAT yields subscale scores for Overconcern with Body Size, Dieting, Food Preoccupation, Social Pressure to Gain Weight, Vomiting, and Caloric Awareness & Control. The ChEAT has demonstrated good psychometric properties.28,29 For this study, the ChEAT was scored according to guidelines developed by Anton and colleagues30 (who advocated use of the entire 6-point scale, rather than the abridged 3-point scale) in order to retain the greatest possible variability in scores.

Three Factor Eating Questionnaire (TFEQ)31

The TFEQ is an 18-item questionnaire, scored on a 4-point Likert-type scale. It assesses eating patterns in adults and children across three separate factors: cognitive restraint, uncontrolled eating, and emotional eating. Sample items include, “I deliberately take small helpings as a means of controlling my weight,” and “Sometimes when I start eating, I just can’t seem to stop.” The TFEQ has demonstrated good psychometric properties.32

Inventory of Overeating Situations (IOS)

The Inventory of Overeating Situations was adapted, with permission, from the Inventory of Drinking Situations (IDTS)33 in order to assess situations in which unhealthy overeating is more likely to occur. Both assessments contain 50 items and are scored on a 4-point Likert-like scale. The IDTS measures situations that trigger excessive alcohol use. These questions, such as “I drank when I had trouble sleeping” and “I drank when I was lonely” were modified to deal with food and eating, for example, “I overate when I had trouble sleeping” and “I overate when I was lonely.” For the present samples, internal consistency ratings were excellent (α = .99 for the parent sample and α = .98 for the child sample).

Eating Behaviors Questionnaire (EBQ)

The Eating Behaviors Questionnaire was created for this study. It is a 20-item measure (see table 1) of hypothesized symptoms of food addiction, which are based on adaptations of DSM-IV34 criteria for substance abuse and dependence. The measure was developed to have high face validity, and includes questions assessing the “3 Cs” of addiction (i.e., Compulsive use, attempts to Cut down, and continued use despite Consequences). Parallel forms were used for parents and children, with wording of items altered for easier comprehension in the child sample. Items are scored on a 6-point Likert-type scale ranging from 1 = “Never” to 6 = “Always,” with higher scores indicative of greater symptoms. Sample child items include “Do you spend more time eating than you mean to?” as well as, “Do you eat more food than you mean to? “ and “Do you try to cut down on your eating?” and “Have you gotten into trouble because of your eating?”. For the current samples, internal consistencies were high (α = .84 for the parent sample and α = .88 for the child sample).

Table 1. Children’s Eating Behaviors Questionnaire Items.

  1. Do you eat more food now than you used to?

  2. Do you think eating is less fun than it used to be?

  3. Do you wish you could eat if you have not eaten in a while?

  4. Do you eat more food than you mean to?

  5. Do you spend more time eating than you mean to?

  6. Do you want to cut down on your eating?

  7. Do you try to cut down on your eating?

  8. Do you spend a lot of time getting food (asking for food, making snacks)?

  9. Do you spend a lot of time eating during the day?

  10. Do you spend a lot of time “recovering” after you eat (resting, feeling too full to do anything)?

  11. Do you miss out on activities because of your eating?

  12. Do you eat foods that you know are bad for you and you aren’t supposed to eat?

  13. Do you eat too much food even when you know you aren’t supposed to?

  14. Do you feel upset or sad about your eating habits?

  15. Do you eat even when you know you could get into trouble?

  16. Do you try to eat in places where eating is not allowed?

  17. Have you gotten in trouble because of your eating?

  18. Do you ever fight with your family, friends, or others about your eating?

  19. Do you save up or hide food?

  20. Do you think you are addicted to food?

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Procedures

All procedures were approved by the appropriate Institutional Review Board. Families who were being evaluated by physicians at the Pediatric Lipid Clinic were approached in the waiting room and asked if they would like to participate in a study assessing eating attitudes and behaviors among children and their parents. After obtaining written consent from the parent and written assent from the child, a trained research assistant provided the families with a packet of questionnaires to complete. Both parents and children provided demographic information and completed the EAT (or ChEAT), the TFEQ, the IOS, and the EBQ. The research assistant was available to answer questions, but allowed families to complete packets independently.

Data analysis

In order to address isolated cases of missing data, mean substitution was utilized to fill in missing data points when the individual had completed at least 80% of items for a given subscale. Pearson product-moment correlations were computed to assess for significant relationships among variables of interest. Statistical significance was set at α = .05. A priori research questions included: 1) assessment of correlations among parent and child scores for the same variables, 2) evaluation of the association between various eating behaviors and attitudes with BMI ratings for pediatric patients, and 3) exploration of eating behaviors and attitudes associated with self-endorsed symptoms of food addiction among pediatric patients.

Results

Parent-child similarities

Parent- and child-reported behaviors and attitudes demonstrated similar patterns across the study variables of interest. For example, on the Inventory of Overeating Situations (IOS), children’s and parents’ scores were significantly correlated (r = .54, p = .001). Similarly, children’s total scores on the Three Factor Eating Questionnaire (TFEQ) correlated significantly with parent total scores on the same measure (r = .28, p = .05). Subscale scores demonstrated less consistency, with a significant correlation for the Emotional Eating subscale (r = .29, p = .05), but not the Cognitive Restraint (r = .21, p = .15) or Uncontrolled Eating (r = .21, p = .15) subscales. The children’s total scores on the ChEAT were significantly related to the parents’ scores on the EAT (r = .39, p = .009). And, child scores on the ChEAT Dieting subscale correlated significantly with parent scores on the EAT Diet subscale (r = .30, p = .05). However, child and parent scores on the ChEAT and EAT Food Preoccupation scale were not significantly related (r = −.04, p = .77), and children’s ChEAT Caloric Awareness and Control scores were not significantly correlated with parent EAT Oral Control scores (r = .15, p = .31).

Correlates of child BMI

BMI ratings were available for 40 children and 45 parents, so all analyses involving BMI ratings are based on this subsample of participants only. The correlation among parent and child BMI ratings for the present sample was r = .32 (p = .05). Child scores on the IOS were also associated with child BMI ratings (r = .42, p = .02), as were child scores on the TFEQ Emotional Eating subscale (r = .33, p = .04). In addition, the correlations among child BMI ratings and their scores on the Eating Behaviors Questionnaire (EBQ) and the ChEAT Social Pressure to Gain Weight subscale were relatively large, but did not reach statistical significance (r = .31, p = .06 and r = −.30, p = .07, respectively). Child scores on the TFEQ Cognitive Restraint and Uncontrolled Eating subscales were not related to BMI (r = .12, p = .48 and r = .04, p = .83, respectively).

Correlates of food addiction symptoms

The range of possible scores on the children’s EBQ ranges from 20-120. In this sample, children reported a mean score of 51.6 (SD = 15.6), with a range from 27 to 104. Among children, the most commonly-endorsed items were representative of compulsive eating and lack of control (e.g., “Do you wish you could eat if you have not eaten in a while?” “Do you want to cut down on your eating?” and “Do you try to cut down on your eating?”). The least-commonly-endorsed symptoms among children included, “Do you miss out on activities because of your eating?”, “Do you ever fight with your family, friends, or others about your eating?” and “Do you save up or hide food?” Similarly, among parents, the most commonly-endorsed items were, “Do you find that you start to ‘crave’ food if you have not eaten in a while?”, “Do you want to cut down on your eating?” and “Do you try to cut down on your eating?” The least commonly-endorsed items for parents were included, “Do you miss social or work activities because of your eating?”, “Do you try to eat in places where eating is prohibited?” and “Have you had legal problems related to your eating (e.g., stealing food, fighting with others over food)?”.

When examining correlates of children’s self-reported food addiction symptoms (i.e., child EBQ Total scores), several significant relationships emerged. As expected, food addiction symptoms were significantly correlated with child scores on the IOS (r = .64, p < .001), the TFEQ Total Score (r = .57, p < .001), the TFEQ Uncontrolled Eating subscale score (r = .60, p < .001), the TFEQ Emotionol Eating subscale score (r = .62, p < .001), and the ChEAT Food Preoccupation (r = .58, p < .001), Overconcern With Body Size (r = .54, p < .001), and Caloric Awareness & Control (r = −.31, p = .04) subscales. There was a non-significant trend in the inverse relation between children’s EBQ scores and their scores on the TFEQ Cognitive Restraint subscale (r = −.27, p = .07). The children’s EBQ scores were not significantly correlated with ChEAT Dieting (r = −.13, p = .39), Social Pressure to Gain Weight (r = −.24, p = .11), or Vomiting (r = −.16, p = .29) subscale scores. It is also noteworthy that 15.2% of children responded “Often,” “Usually,” or “Always” to the question, “Do you think you are addicted to food?”, and an additional 17.4% reported that they “Sometimes” feel that way.

Discussion

Pediatric obesity is a significant public health concern than has grown rapidly over the past several decades35. Though many factors contributing to pediatric obesity have been identified, including poor diet with sedentary lifestyle36, hereditary factors13, and family influences37, more information is needed to understand this condition, in order to develop more effective prevention and treatment programs. Results of the present study suggest that children’s attitudes and beliefs related to food, dieting, and weight management are associated with their level of overweight/obesity. In addition, symptoms of compulsive eating behaviors or “food addiction” may contribute to these problems in some children.

Consistent with previous research38,39, children’s eating-related attitudes and behaviors generally correlated significantly with their parents’ eating-related attitudes and behaviors. Though these data may provide additional support for the contribution of hereditary factors to the development of obesity, they also provide evidence that overeating may be a learned behavior. Just as most individuals with a substance use disorder first acquire drugs of abuse from friends or family20, children may learn to acquire excessive amounts of food and abuse food through social learning, by observing their parents overeat throughout their lifespan.

In addition, the present study provides a preliminary downward extension of the pioneering work on food addiction that has been conducted in other populations. Animal studies40,41 and adult human studies42,43 have provided support for this concept by demonstrating neurobiological mechanisms that might account for food addiction, and by demonstrating that humans can validly and reliably self-report symptoms of food addiction. However, we were not aware of any studies that investigated the presence of food addiction symptoms, and their correlates, among children. Results of the present study suggest that some children report experiencing a compulsion to eat, which they describe as feeling like an “addiction.” In addition, the measure of food addiction symptoms (i.e., Eating Behaviors Questionnaire [EBQ]) demonstrated good construct validity in this pediatric sample, with significant correlations between the EBQ and measures of uncontrolled eating, emotional eating, food preoccupation, body size concerns, and attempts at calorie control.

In general, the present study provides preliminary support for the concept of food addiction among pediatric patients. However, results should be evaluated within the context of several limitations. First, the sample was relatively small and consisted primarily of children who were obtaining medical treatment due to symptoms of overweight/obesity. As a result, the generalizability of the results to the population as a whole is unknown. In addition, some of the analyses were likely underpowered, in particular the analyses involving BMI ratings (which utilized a lower n). Next, restriction of range in the BMI ratings for these patients (i.e., the BMI ratings were heavily skewed on the obese end of the spectrum) likely attenuated the significance of the correlations between eating attitudes, behaviors, and food addiction symptoms with BMI. The use of self-report measures should be taken into consideration, as individuals may not have good insight into their symptoms (i.e., some may overidentify themselves as “addicts;”whereas, others mayexhbit “denial” of their symptoms). More research is needed to verify the reliability and validity of this assessment approach. In addition, food addiction remains a theoretical construct at this point, with no accepted diagnostic criteria. As a result, no validated measure of food addiction was available in the literature, so food addiction symptoms were assessed using a questionnaire developed specifically for this study. Though preliminary psychometric properties appear promising (e.g., good internal consistency and concurrent validity in this sample), more research is needed to fully evaluate the utility of this measure.

Future research should seek to replicate the current findings and extend the investigation to a more diverse sample of individuals. Once standardized diagnostic criteria are identified, children who demonstrate symptoms of food addiction should be further evaluated in order to identify ways to develop effective prevention and intervention programs for this population. For example, if individuals experience compulsive overeating as a type of addictive behavior, various preventive efforts might be indicated such as limiting access to high-fat, high sugar foods (i.e., vending machines in schools), providing educational programs designed to help children develop a healthy relationship with food, and mental health treatment for stress/anxiety/depression that might trigger compulsive eating. From an intervention perspective, treatment approaches utilized in substance abuse treatment (e.g., motivational interviewing, cognitive-behavioral therapy, contingency management, participation in 12-step programs) might be emphasized more strongly as alternatives to traditional “dieting,” which has demonstrated very limited success with this population.

Conclusions

Results of the present study suggest that “food addiction” may be a real problem for a subset of children who suffer from overweight/obesity. Given that self-reported symptoms of food addiction were associated with overeating, uncontrolled eating, emotional eating, and BMI ratings, identification of food addiction symptoms may lead to the development of improved obesity treatment methods for this subset of patients. More research is needed to clarify the nosology of food addiction, to develop appropriate screening measures, and to better understand the emotional and behavioral correlates of this problem.

Acknowledgments

The first author is supported in part by National Institute of Drug Abuse (NIDA) training grant T32-DA-07313-10 (PI: Linda B. Cottler), on which she is a postdoctoral research scholar. The authors would like to thank Ms. Amanda Stone for her assistance will data entry, as well as the children and parents who participated in this study.

Funding: Lisa J. Merlo, Ph.D. is supported in part by National Institute of Drug Abuse (NIDA) training grant T32-DA-07313-10 (PI: Linda B. Cottler), on which she is a postdoctoral research scholar.

Footnotes

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References

  • 1.Ogden CL. Defining overweight in children using growth charts. Md Med. 2004;5:19–21. [PubMed] [Google Scholar]
  • 2.Acosta M, Manubay J, Levin F. Pediatric obesity: Parallels with addiction and treatment recommendations. Harv Rev Psychiatry. 2008;16:80–96. doi: 10.1080/10673220802069764. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988;37:1595–607. doi: 10.2337/diab.37.12.1595. [DOI] [PubMed] [Google Scholar]
  • 4.Ogden CL, Caroll MD, Flegal KM. Epidemiological trends in overweight and obesity. Endocrinol Metab Clin North Am. 2003;32:741–60. doi: 10.1016/s0889-8529(03)00074-4. [DOI] [PubMed] [Google Scholar]
  • 5.Gidding SS, Leibel RL, Daniels S, Rosenbaum M, Van Horn L, Marx GR, Writing Group Understanding obesity in youth. A statement for healthcare professionals from the Committee on Atherosclerosis and Hypertension in the Young of the Council on Cardiovascular Disease in the Young and the Nutrition Committee, American Heart Association. Circulation. 1996;94:3383–7. doi: 10.1161/01.cir.94.12.3383. [DOI] [PubMed] [Google Scholar]
  • 6.Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: Findings from the third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med. 2003;157:821–7. doi: 10.1001/archpedi.157.8.821. [DOI] [PubMed] [Google Scholar]
  • 7.Weiss R, Dziura J, Burgert TS, et al. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med. 2004;350:2362–74. doi: 10.1056/NEJMoa031049. [DOI] [PubMed] [Google Scholar]
  • 8.Mustillo S, Worthman C, Erkanli A, Keeler G, Angold A, Costello EJ. Obesity and psychiatric disorder: developmental trajectories. Pediatrics. 2003;111:851–9. doi: 10.1542/peds.111.4.851. [DOI] [PubMed] [Google Scholar]
  • 9.Davison KK, Birch LL. Weight status, parent reaction, and self-concept in five-year-old girls. Pediatrics. 2001;107:46–53. doi: 10.1542/peds.107.1.46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Thompson JK, Tantleff-Dunn S. Assessment of body image disturbance in obesity. Obesity Research. 1998;6:375–377. doi: 10.1002/j.1550-8528.1998.tb00366.x. [DOI] [PubMed] [Google Scholar]
  • 11.Hasler G, Buysse DJ, Klaghofer R, et al. The association between short sleep duration and obesity in young adults: a 13-year prospective study. Sleep. 2004;27:661–6. doi: 10.1093/sleep/27.4.661. [DOI] [PubMed] [Google Scholar]
  • 12.Strober M, Freeman R, Bower S, Rigali J. Binge eating in anorexia nervosa predicts later onset of substance use disorder. A ten year prospective, longitudinal follow-up of 95 adolescents. J Youth Adolesc. 1996;25:519–32. [Google Scholar]
  • 13.Volkow ND, Wise RA. How can drug addiction help us understand obesity? Nat Neurosci. 2005;8:555–60. doi: 10.1038/nn1452. [DOI] [PubMed] [Google Scholar]
  • 14.Stunkard AJ, Foch TT, Hrubec Z. A twin study of human obesity. JAMA. 1986;256(1):51–54. [PubMed] [Google Scholar]
  • 15.Tsuang MT, Lyons MJ, Eisen SA, Goldberg J, True W, Nong L, Meyer JM, Toomey R, Faraone SV, Eaves L. Genetic influences on DSM-III-R drug abuse and dependence: A study of 3,372 twin pairs. American Journal of Medical Genetics (Neuropsychiatric Genetics) 1996;67:473–477. doi: 10.1002/(SICI)1096-8628(19960920)67:5<473::AID-AJMG6>3.0.CO;2-L. [DOI] [PubMed] [Google Scholar]
  • 16.Kampov-Polevoy AB, Garbutt JC, Khalitov E. Family history of alcoholism and response to sweets. Alcohol Clin Exp Res. 2003;27:1743–9. doi: 10.1097/01.ALC.0000093739.05809.DD. [DOI] [PubMed] [Google Scholar]
  • 17.Stein RJ, O’Byrne KK, Suminski RR, Haddock CK. Etiology and treatment of obesity in adults and children: implications for the addiction model. Drugs and Society. 1999;15:103–121. [Google Scholar]
  • 18.Kaplan LM. Genetics of obesity and body weight regulation. Curr Opin Endocrinol Diabetes. 2000;7(5):218–224. [Google Scholar]
  • 19.Harris J, Pomeranz J, Lobstein T, Brownell KD. A Crisis in the Marketplace: How Food Marketing Contributes to Childhood Obesity and What Can Be Done. Annu Rev Public Health. 2008 Oct 31; doi: 10.1146/annurev.publhealth.031308.100304. Epub ahead of print. [DOI] [PubMed] [Google Scholar]
  • 20.Substance Abuse and Mental Health Services Administration. Office of Applied Studies . Results from the 2007 National Survey on Drug Use and Health: National Findings. Rockville, MD: 2008. NSDUH Series H-34, DHHS Publication No. SMA 08-4343. [Google Scholar]
  • 21.Adam TC, Epel ES. Stress eating and the reward system. Physiol Behav. 2007;91(4):449–58. doi: 10.1016/j.physbeh.2007.04.011. [DOI] [PubMed] [Google Scholar]
  • 22.Kalra SP, Kalra PS. Overlapping and interactive pathways regulating appetite and craving. J Addict Dis. 2004;23:5–21. doi: 10.1300/J069v23n03_02. [DOI] [PubMed] [Google Scholar]
  • 23.Blum K, Sheridan PJ, Wood RC, Braverman ER, Chen TJ, Comings DE. Dopamine D2 receptor gene variants: association and linkage studies in impulsive-addictive-compulsive behaviour. Pharmacogenetics. 1995;5:121–41. doi: 10.1097/00008571-199506000-00001. [DOI] [PubMed] [Google Scholar]
  • 24.Avena NM, Rada P, Hoebel BG. Underweight rats have enhanced dopamine release and blunted acetylcholine response in the nucleus accumbens while bingeing on sucrose. Neuroscience. 2008;156:865–71. doi: 10.1016/j.neuroscience.2008.08.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Garner DM, Garfinkel PE. The Eating Attitudes Test: an index of the symptoms of anorexia nervosa. Psychol Med. 1979;9(2):273–9. doi: 10.1017/s0033291700030762. [DOI] [PubMed] [Google Scholar]
  • 26.Garner DM, Olmsted MP, Bohr Y, Garfinkel PE. The eating attitudes test: psychometric features and clinical correlates. Psychol Med. 1982;12(4):871–8. doi: 10.1017/s0033291700049163. [DOI] [PubMed] [Google Scholar]
  • 27.Ocker LB, Lam ET, Jensen BE. Psychometric properties of the eating attitudes test. Measurement in Physical Education and Exercise Science. 2007;11:25–48. [Google Scholar]
  • 28.Maloney M, McGuire J, Daniels S. Reliability testing of a children’s version of the Eating Attitudes Test. Journal of the American Academy of Child and Adolescent Psychiatry. 1988;5:541–543. doi: 10.1097/00004583-198809000-00004. [DOI] [PubMed] [Google Scholar]
  • 29.Smolak L, Levine MP. Psychometric properties of the Children’s Eating Attitudes Test. Int J Eat Disord. 1994;16(3):275–82. doi: 10.1002/1098-108x(199411)16:3<275::aid-eat2260160308>3.0.co;2-u. [DOI] [PubMed] [Google Scholar]
  • 30.Anton SD, Han H, Newton RL, Jr, Martin CK, York-Crowe E, Stewart TM, Williamson DA. Reformulation of the Children’s Eating Attitudes Test (ChEAT): factor structure and scoring method in a non-clinical population. Eat Weight Disord. 2006;11(4):201–10. doi: 10.1007/BF03327572. [DOI] [PubMed] [Google Scholar]
  • 31.Stunkard AJ, Messick S. The three-factor eating questionnaire to measure dietary restraint, disinhibition, and hunger. Journal of Psychosomatic Research. 1985;29:71–83. doi: 10.1016/0022-3999(85)90010-8. [DOI] [PubMed] [Google Scholar]
  • 32.Bardone-Cone AM, Boyd CA. Psychometric properties of eating disorder instruments in Black and White young women: internal consistency, temporal stability, and validity. Psychol Assess. 2007;19:356–62. doi: 10.1037/1040-3590.19.3.356. [DOI] [PubMed] [Google Scholar]
  • 33.Turner NE, Annis HM, Sklar SM. Measurement of antecedents to drug and alcohol use: psychometric properties of the Inventory of Drug-Taking Situations (IDTS) Behav Res Ther. 1997;35(5):465–83. doi: 10.1016/s0005-7967(96)00119-2. [DOI] [PubMed] [Google Scholar]
  • 34.American Psychiatric Association . Diagnostic and statistical manual of mental disorders. fourth edition, text revision Author; Washington DC: 2000. [Google Scholar]
  • 35.National Center for Chronic Disease Prevention and Health Promotion Defining Overweight and Obesity. 2004 Available at: www.cdc.gov/nccdphp/dpna/obesity/defining.htm.
  • 36.Liu L, Hironaka K, Pihokerf C. Type 2 diabetes in youth. Current Problems in Pediatric and Adolescent Health Care. 2004;34:254–272. doi: 10.1016/j.cppeds.2004.05.001. [DOI] [PubMed] [Google Scholar]
  • 37.French SA, Story M, Jeffrey RW. Environmental influences on eating and physical activity. Annual Review of Public Health. 2001;22:309–335. doi: 10.1146/annurev.publhealth.22.1.309. [DOI] [PubMed] [Google Scholar]
  • 38.Yanez AM, Peix MA, Atserias N, Arnau A, Brug J. Association of eating attitudes between teenage girls and their parents. Int J Soc Psychiatry. 2007 Nov;53(6):507–13. doi: 10.1177/0020764007078350. [DOI] [PubMed] [Google Scholar]
  • 39.Brown R, Ogden J. Children’s eating attitudes and behaviour: a study of the modelling and control theories of parental influence. Health Educ Res. 2004 Jun;19(3):261–71. doi: 10.1093/her/cyg040. [DOI] [PubMed] [Google Scholar]
  • 40.Rada P, Avena NM, Hoebel BG. Daily bingeing on sugar repeatedly releases dopamine in the accumbens shell. Neuroscience. 2005;134:737–744. doi: 10.1016/j.neuroscience.2005.04.043. [DOI] [PubMed] [Google Scholar]
  • 41.Avena NM, Rada P, Moise N, Hoebel BG. Sucrose sham feeding on a binge schedule releases accumbens dopamine repeatedly and eliminates the acetylcholine satiety response. Neuroscience. 2006;139:813–820. doi: 10.1016/j.neuroscience.2005.12.037. [DOI] [PubMed] [Google Scholar]
  • 42.Gearhardt AG, Corbin WR, Brownell KD. Preliminary validation of the Yale Food Addiction Scale. under review. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Rolls ET, McCabe C. Enhanced affective brain representations of chocolate in cravers vs. non-cravers. Eur J Neurosci. 2007;26(4):1067–76. doi: 10.1111/j.1460-9568.2007.05724.x. [DOI] [PubMed] [Google Scholar]

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