Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Am J Clin Nutr. Author manuscript; available in PMC 2010 March 1.
Published in final edited form as:
PMCID: PMC2646816

Laboratory assessment of the food intake of children and adolescents with loss of control eating



The presence of loss of control (LOC) eating in youth predicts excessive weight gain. However, few studies have measured the actual energy intake of children reporting LOC eating.


To characterize energy intake and macronutrient composition of “normal” and “binge” laboratory meals in non-overweight and overweight boys and girls with LOC eating.


177 youth (8–17y) consumed two lunchtime meals ad libitum from a multi-item food array after being instructed either to binge-eat (binge meal) or to eat normally (normal meal). Prior LOC eating was determined by semi-structured clinical interview.


Participants consumed more energy at the binge meal than the normal meal (p=0.001). Compared to youth without LOC episodes (n=127), those reporting LOC (n=50) did not consume more energy at either meal. However, at both meals, youth with LOC consumed a greater percentage of calories from carbohydrate and a smaller percentage from protein than those without LOC (ps<0.05). Children with LOC ate more snack and dessert-type foods and less meats and dairy (ps<0.05). LOC participants also reported greater increases in post-meal negative affect at both meals compared to those without LOC (ps≤0.05). Secondary analyses restricted to overweight and obese girls found that those with LOC consumed more energy at the binge meal (p=0.025).


When presented with an array of foods, youth with LOC consumed more high-calorie snack and dessert-type foods than those without LOC. Further research is required to determine whether habitual consumption of such foods may promote overweight.


Binge eating disorder (BED), presently a form of “eating disorder not otherwise specified” listed in the appendix of the Diagnostic and Statistical Manual of Mental Disorders-IV-Text Revision (DSM-IV-TR)(1), is characterized by recurrent episodes of binge eating without regular compensatory behaviors. Binge episodes are defined as the consumption of a large amount of food during which a sense of loss of control (LOC) over eating is experienced. To meet criteria for BED, individuals must engage in an average of at least two episodes of binge eating per month for at least six months (1). BED is common among obese adults. Few children meet criteria for BED. However, youth commonly report binge eating episodes with less frequency than required to meet criteria for BED (2). One laboratory meal study, by Mirch et al (3) has investigated binge eating behavior in children. Sixty overweight boys and girls (6–12y) who had agreed to participate in a weight loss study, self-reported on a questionnaire whether they had engaged in binge eating at least once in the past 6mo. Children ate ad libitum from a 9,835 kcal buffet meal on two separate occasions; after an overnight fast and after a standardized breakfast. At both meals, binge eating children (n=10) consumed >400 kcal more energy than children without binge eating episodes (n=50). To our knowledge, no studies have examined binge eating behavior in the laboratory among both overweight and non-overweight youth.

LOC eating – defined as the experience of loss of control while eating, regardless of whether the reported amount of food consumed is unambiguously large – is common in youth (2). The term LOC eating includes both binge episodes and eating episodes during which the amount consumed may be less clearly considered large. Most of the literature on pediatric LOC eating describes children who report at least one episode in the month prior to assessment (2). LOC eating is associated with elevated eating-related and psychological distress (46), with overweight, and with high body fat mass (7, 8). Both reported binge (911) and LOC (12) eating in youth predict excessive body weight gain in longitudinal studies of children and adolescents of all weight strata. Thus, it is possible that reported LOC eating is an important construct among all children who report such episodes since, regardless of weight status, the behaviors may have an adverse impact on outcome.

We therefore carried out a laboratory feeding paradigm to extend Mirch et al’s (3) study by including male and female children and adolescents (age 8–18y) of a broad range in a body weight and studying the impact of reported LOC eating, as opposed to binge eating exclusively, on actual food intake. The study protocol was modeled after adult paradigms (13) in which participants completed two separate meals: one where they were told to eat normally and another where they were instructed to binge eat. Based upon the prior literature (3, 13), we hypothesized that after accounting for the contribution of body composition, compared to participants without LOC eating, those reporting LOC would consume more energy during the binge meal. Given that youth frequently report negative affect following meals that involve the experience of LOC (14), we also studied the affect of participants immediately after eating. We expected that those with LOC would report greater increases in negative emotions after the binge meal.



Participants were healthy volunteers recruited for this study through flyers posted on public bulletin boards at the National Institutes of Health (NIH), and at local libraries, supermarkets, and school parent email listservs in the Washington, DC greater metropolitan area. The study was also advertised in a local newspaper and posted on free websites (e.g., Craig’s List and Backfence). The flyer and advertisement explained that the study was investigating eating behaviors in youth and that no treatment would be provided. Children and adolescents were financially compensated for their participation. Boys and girls of any race or ethnicity who had a BMI ≥ 5th percentile for age and sex (15) were eligible for participation. Individuals were excluded if they had a significant medical condition, abnormal hepatic, renal, or thyroid function, were taking medication known to impact body weight, or had a psychiatric disorder that might impede protocol compliance. Pregnant girls were not eligible for the study, nor were children who had lost more than 5 lbs. (2.3 kg) in the past three months or who were undergoing weight loss treatment. Individuals were excluded if they reported disliking more than 50% of the foods to be offered on the test meal buffet or if they were unable to acclimate to laboratory conditions, by virtue of being unable to consume at least half of a high-calorie shake. Youth provided written assent and parents gave written consent for participation in the study. This study was approved by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) institutional review board and registered in (NCT00320177). Data were collected between February, 2004 and June, 2008.


Each subject participated in three visits on three separate days at the Hatfield Clinical Research Center at the NIH.

Visit 1: Screening

At the first visit, children were screened for eligibility following an overnight fast. Participants and their parent/guardian were informed that the study was to better understand eating behaviors in children. Each participant’s weight and height were measured using calibrated electronic instruments as described previously (16). BMI was calculated as weight in kilograms divided by the square of height in meters. BMI standard deviation scores (BMI Z-scores) were calculated according to the Centers for Disease Control and Prevention 2000 growth charts (17). Body composition was measured as previously described (16, 18) using air displacement plethysmography (Life Measurement Inc., Concord, CA) to determine fat-free mass and fat mass. All participants underwent a medical history and a physical examination performed by an endocrinologist or a trained nurse practitioner. Breast and pubertal hair development were assigned according to the stages of Tanner (19, 20), and testicular volumes were measured (in cc) according to Prader (21).

In order to acclimate children to the test meal condition, each participant was placed in a private room in the pediatric clinic, provided with a high calorie shake (Axcan Pharma Inc., Birmingham, AL; 787 kcal, 52% carbohydrates, 11% protein, 37% fat), and given the tape-recorded instruction to “eat as much as you would at a normal meal.” If a child was unable to consume at least 50% of the shake under these conditions, they were considered unable to acclimate and deemed ineligible.

The Eating Disorder Examination version 12OD/C.2 (EDE) (22) or the EDE adapted for children (23) was administered to each participant to determine the presence or absence of LOC eating as described previously (8, 14). The child version differs from the adult EDE only in that its script has been edited to make it more accessible to children ages 8–14 years. Based on their responses to the EDE, participants were categorized as engaging in objective binge episodes (overeating with LOC), subjective binge episodes (LOC without objective overeating as assessed by the interviewer, but viewed as excessive by the interviewee), objective overeating (overeating without LOC) or no episode (a normal meal involving neither LOC nor overeating) over the 28 days prior to assessment. Eating episodes were assessed by asking children to describe the largest amount of food consumed in the past month. A book of photographed food portions in various sizes and types (24) was used during every interview to assist participants in determining the amount and variety of food consumed during the episode. At weekly meetings, team members discussed the amount of food eaten and came to a unanimous consensus regarding whether the amount was unambiguously large (e.g., 8 slices of pizza) or subjectively large (e.g., 2 slices of pizza) given the circumstances for the child’s age. If one or more team members disagreed with the rest of the group, an outside team proficient at administering both the EDE and child version was contacted for further input. If, in the final analysis, an episode size was still questionable, it was coded conservatively as not unambiguously large. For the purposes of the current study, participants reporting at least one instance of an objective or a subjective binge episode in the past month were categorized as those with LOC eating. Children with objective overeating or no episodes over the month prior to assessment were categorized as those without LOC eating.

The EDE has good inter-rater reliability for all episode types (Spearman correlation coefficients: ≥0.70) (25). Tests of the EDE adapted for children have demonstrated good inter-rater reliability (Spearman rank correlations from 0.91–1.00) and discriminant validity in eating disordered samples and matched controls ages 8–14 years (26). Among non-overweight and overweight 6–13 year olds, the child version of the EDE revealed excellent inter-rater reliability with a Cohen’s kappa for presence of the different eating episode categories of 1.00 (p<0.001) (8).

To ensure that participants found the foods offered at the buffet test meals to be acceptable, participants completed a food preference questionnaire on which they rated how much they liked 57 foods that children commonly consume (27) (including the 28 foods offered on our buffet) using 10-point Likert scales (28).

Visits 2 and 3: Buffet Test Meals

Participants were asked to consume their lunch ad libitum from a multiple-item buffet test meal on two separate days, scheduled at least two days apart. Children were randomized to complete either the “normal” meal (at which they were told to “eat as much as you would at a normal meal”) or the “binge” meal (during which they were instructed to “let yourself go and eat as much as you want”) first. Participants were instructed to adhere to an overnight fast initiated at 10:00pm the night before each test meal visit. At each test meal day, participants were instructed to consume an entire standard breakfast consisting of 288 kcal (240 mL apple juice, 1 English muffin, and 6 g butter) at 8:40am. Following the breakfast, each subject remained at the NIH, participating in sedentary activities (e.g., playing computer games, reading, doing arts and crafts, etc.) and was observed to ensure there was no food intake until the afternoon test meal.

At 2:30pm, each child was presented with a 9,835 kcal buffet test meal (3) with individual items that varied in macronutrient composition (12% protein, 51% carbohydrate, 37% fat across all foods) and contained a wide assortment of foods (Table 1). When each child entered the room containing the buffet, the following tape-recorded instruction was played for the normal meal: “Eat as much as you would at a normal meal;” and for the binge meal, “Let yourself go and eat as much as you want.” Participants were then left alone in the room containing the buffet to eat ad libitum. During the test meals, children viewed pre-taped episodes of a television show with commercials removed. Episodes were pre-viewed so that none involved food, eating, shape, or weight-related topics. Participants were instructed to open the room door when they were finished eating. Time spent eating was measured from the time the investigator left the room to the time the participant opened the door after eating. The amount of each food and beverage consumed was measured using the differences in weight of each food item before and after the meal. Energy content and nutrient composition for each food was determined according a metabolic diet study management system that uses the USDA Nutrient Database for Standard Reference, Release 16 (Viocare Technologies, Inc., Princeton, NJ), as well as nutrient information supplied by food manufacturers.

Energy of Meal Items by Food Groups Presented at the Buffet Test Meals

Immediately before, and again, after each test meal, participants completed the psychometrically sound, State Form of the State-Trait Anxiety Inventory for Children (STAIC) (29) which measures anxiety “right now, at this very moment.” They also completed the well-validated Brunel Mood Scale (BRUMS) (30), which measures present mood state and generates six subscales pertaining to Anger, Confusion, Depression, Fatigue, Tension, and Vigor.

Statistical Methods

All analyses were performed with SPSS 14.0 (31). Data were screened for univariate and multivariate normality. There were no influential outliers. Logarithmic transformations were made for total energy intake and fat-free mass, and arcsine transformations were conducted for the percentage of macronutrient content (fat, protein, and carbohydrate) intake. Pre- and post-meal mood states, as assessed by the BRUMS, were mean rank transformed to achieve normality.

Primary hypotheses were examined with a series of linear mixed models with repeated measures. The dependent variables were total energy intake (kcal), percentage of energy intake from protein, carbohydrate, and fat, food groups (dairy, desserts/snacks, meats, vegetables, fruits, bread, condiments, drinks), duration of eating (minutes), post-meal state Anxiety, and post-meal state Anger, Confusion, Depression, Fatigue, Tension, and Vigor. The fixed-factor main effects in the model were LOC (presence or absence of at least one episode in the month preceding assessment) and meal type (normal, binge). We also tested the two-way interaction between LOC and meal type to determine whether any observed effects of LOC significantly varied between the normal meal and the binge meal. Each model included sex, age, race (coded non-Hispanic Caucasian and all other racial/ethnic minorities), fat-free mass, and percent fat mass as covariates. For the models predicting duration of eating and post-meal state anxiety and mood, total energy intake also was included as a covariate. Pre-test meal anxiety or mood state was included in the models predicting post-test meal anxiety and mood states. Randomization order was also considered as a covariate in all analyses, but was removed because it did not significantly contribute to any model. Reported means and standard errors are adjusted for all variables included in each model. Differences were considered significant when p values were ≤0.05. All tests were two-tailed.


One-hundred-ninety-eight children and adolescents attended a screening appointment. A total of 19 children did not complete all study procedures for the following reasons: nine were unable to consume at least 50% of the high-calorie shake and were excluded, four did not schedule their test meal visits within six months of the screening appointment, two scheduled test meal appointments, but did not attend, and four children decided not to continue the study but did not provide a reason. Of the 179 participants who completed both test meals, the data from two children were excluded because one child did not eat at the test meals and the other did not follow study procedures. Compared to children who did not complete the study in its entirety, completers were significantly older (13.9±2.6 vs. 12.1±3.1 years, p=0.005) and of a higher socioeconomic status according to the Hollingshead Index (32) (median 3 vs. 2, p=0.01); the two groups did not differ with regard to sex, race, any measure of body composition, or LOC status. The final sample consisted of 177 participants, 48% of whom were boys (Table 2). Fifty participants reported at least one episode of LOC eating in the month prior to assessment. Participants with LOC had significantly greater BMI and fat mass, and were more likely to be female than those without LOC (Table 2, p’s ≤ 0.01). Thirty of those with LOC eating also met criteria for objective binge episodes in the past month; two participants met proposed DSM-IV-TR research criteria for BED (1). The number of episodes reported in the prior month ranged from 1 to 28 (median: 2 episodes per month).

Participant Demographics

Energy Intake

After controlling for all other variables in the model, there was a main effect for meal type (p=0.001). On average, participants consumed an adjusted 1301.2±103.0 kcal at the normal meal compared to an adjusted 1428.9±105.2 kcal at the binge meal (Figure 1). Race, sex, and fat-free mass (all p’s <0.01), as well as percentage fat mass (p=0.05), each independently contributed to the model. Compared to Caucasian children, non-Caucasian children consumed more energy; boys ate more than girls; and there were positive relationships between energy intake and both fat-free mass and fat mass. However, there was no main effect of age or LOC eating status, and the interaction of LOC by the type of meal instruction was not significant (Table 3). Findings remained non-significant when examining number of LOC episodes as a continuous variable (p=0.63) or when categorizing youth by the presence of classic objective binge eating episodes (p=0.50), as opposed to LOC eating. The association between LOC eating and energy intake was not significant (p=0.64) in a model defining LOC eating episodes according to a self-report questionnaire (33) instead of by the EDE interview. Lastly, findings did not change when examining only those children who reported after the meals that they had experienced a sense of LOC while eating (61% of children who endorsed LOC eating during the EDE interview).

Figure 1
Energy Intake for all participants at the two meals
Linear Mixed Model Predicting Energy Intake (kcal)

Intake Categorized According to Macronutrient Composition and Food Group

There was a main effect of LOC status in predicting percentage of intake from protein. Regardless of meal type, participants with LOC consumed smaller percentage intake from protein than those without LOC (p=0.005; Figure 2). A main effect for LOC status was also found with regard to percentage intake from carbohydrate. Across both meals, participants with LOC ate a greater percentage of energy from carbohydrate than those without LOC (p=0.02, Figure 2). No other model variable significantly predicted consumption of percentage intake from protein or carbohydrate. There were no main or interactional effects of LOC or meal type for percent energy from fat consumed.

Figure 2
Macronutrient content of meals

In an examination of intake classified by food group, compared to children without LOC, those with LOC consumed significantly less dairy (p=0.04) and meats (p=0.02), but more snack and dessert-type foods (p=0.05) across both meals (Figure 3). Comparing intake at the binge meal to that at the normal meal among all participants, youth ate more snack and dessert-type foods and (422.4±23.4 vs. 380.2±23.5 kcal, p=0.02) meats (444.5±16.2 vs. 406.0±16. 2 kcal, p=0.001), fruits (67.6±6.1 vs. 57.7±6.1 kcal, p=0.04), and drinks (120.7±7.7 vs. 108.5±7.7 kcal, p=0.05).

Figure 3
Food types consumed at the two meals

Time Spent Eating

After accounting for total energy intake (p<0.001), there was an effect for meal type (p=0.02), such that participants, overall, took longer to complete their meal when asked to binge eat. Furthermore, there was a main effect of LOC eating status, such that youth with LOC took longer to indicate that they had finished their meals (29.8±1.3 minutes) compared to youth with no LOC eating (26.2±0.8 minutes, p=0.02). Fat-free mass also significantly contributed to the model (p<0.001), such that fat-free mass was positively associated with duration of eating. Girls also ate more slowly than boys across both meals (p=0.02). No other variables in the model predicted time spent eating.

Changes in Affect

After controlling for pre-meal state Anxiety (p<0.001) and all other variables in the model, age (p=0.05), LOC status (p=0.01) and fat mass (p= 0.03) were positively associated with post-meal Anxiety (Figure 4). Similarly, after accounting for respective pre-meal state affect (p’s<0.001), LOC status was positively associated with post-meal state Confusion (p=0.05) and Fatigue (p=0.01) for both the normal and binge meals (Figure 4). There were no significant differences according to LOC status in post-meal state Anger, Depression, Tension, or Vigor based upon LOC status, no significant effects of meal type, and no significant interactions between meal type and LOC status for any post-meal state affect measure.

Figure 4
State affect following the meals

Post Hoc Analyses of Energy Intake by Sex in Overweight and Obese Youth

Because of the significant effect of sex observed in our model predicting energy intake, we conducted post-hoc analyses to determine whether LOC status differentially impacted girls compared to boys with regard to energy consumption. Furthermore, since prior laboratory studies of binge eating have generally included only overweight or obese participants (3, 13), we particularly studied only those youth with a BMI equal to or greater than the 85th percentile for age and sex (15) in these post-hoc analyses. Accounting for all covariates, a main effect for LOC status among girls at the binge meal, but not at the normal meal, was revealed. Compared to overweight or obese girls without LOC (n=23), overweight or obese girls with LOC (n=22) consumed significantly more energy at the binge meal (No LOC: adjusted mean, SE: 1,288.3 ± 105.4 vs. LOC: 1,548.8 ± 105.4 kcal; p=0.025), but not at the normal meal (No LOC: 1,174.9 ± 107.4 vs. LOC: 1,349.0 ± 107.9 kcal; p=0.22). For overweight or obese boys with (n=10) and without LOC (n=35), there were no significant differences at either the binge meal (No LOC: 1,737.8 ± 105.2 vs. LOC: 1,621.8 ± 110.2 kcal, p=0.54) or the normal meal (No LOC: 1,592.2 ± 105.7 vs. LOC: 1,566.7. ± 110.9 kcal, p=0.89).


We found that children and adolescents consumed more energy when instructed to binge eat than when instructed to eat normally. This finding suggests that participants were able to follow meal instructions in our paradigm. We also found that endorsement of loss of control eating was associated with the consumption of less energy from protein and more from carbohydrate, regardless of meal instructions. Post-hoc analyses found among overweight girls, but not boys, reported LOC eating was associated with greater energy intake at the binge meal than the normal meal. At both meals, participants who reported LOC eating consumed more snack and dessert-type foods and less dairy and meats. LOC eating was also predictive of a longer duration of eating, and of greater post-meal anxiety, confusion, and fatigue.

Unexpectedly, there were no differences in energy intake based upon LOC status at the two laboratory meals. LOC was examined as a discrete construct in our analysis; however no relationship was identified with energy intake when LOC was examined using the number of LOC episodes as the independent variable. It is possible that in contradistinction to adult binge episodes, the construct of reported LOC eating during youth is behaviorally manifested as a specific style of eating for which the number of episodes reported is not particularly illuminating. Participants reporting LOC eating were distinguished from those without LOC by the macronutrient composition and types of foods consumed at both meals. If the composition of these test meals reflect typical food intake, youth with LOC may habitually consume meals (normal and binge) comprised of less protein and more snack and dessert-type, high energy density foods. Although the causal relationship between high carbohydrate intake and overweight is unclear, lower protein consumption has been associated with lesser post-meal satiety, which may conceivably increase overall energy intake (3436). Furthermore, high calorie snack and dessert-type foods may serve as “comfort” food that individuals with LOC may consume in large quantities at times outside of the laboratory setting in response to negative affect (37). Indeed, participants with LOC reported greater negative affect both before and after the meals. Interestingly, those with LOC consumed less dairy and meats than youth without LOC. In contrast to children without disordered eating behaviors, those with LOC opted to eat foods that are less representative of a typical lunch meal. Taken together, if the observed style of eating promotes overeating outside of the laboratory setting, our findings may explain why binge (911) and LOC (12) eating predict excess weight gain over time.

Notably, those with LOC did not consume more energy from fat at either meal compared to youth without LOC. This finding is in contrast to adult laboratory data (38), but consistent with another study of self-reported food intakes of children that found no difference in the percentage of energy from fat consumed in episodes with and without LOC (39). Our findings regarding macronutrient consumption may differ from those in adults due, in part, to the inclusion of different foods on our array compared to those used for buffets in the prior adult studies. Our array included several dessert-type foods high in carbohydrate, but low in fat (e.g., jellybeans), rather than solely offering the high fat dessert options (e.g., ice cream) included in adult studies (13).

Compared to youth without LOC, those with LOC eating reported greater increases in state anxiety, confusion and fatigue following both meals. These findings are consistent with the results from a multi-site study of the self-reported emotional experiences among youth who describe experiencing LOC eating (14). These affective patterns are in concert with adult data insofar as binge episodes are reported to be followed by increases in negative mood (40). However, these findings differ from the adult literature in that youth with LOC increased negative affect after both normal and binge meals. Notably, after eating, youth with LOC did not report increases in other types of negative affect; namely, feelings of anger, depression, or tension. Compared to these affective states, it is possible that anxiety, confusion and fatigue are constructs more closely aligned with the experience of “numbing” while eating, which has been reported by children and adolescents with LOC (14) and adults with binge eating (41).

In contrast to some findings from adult laboratory studies that included both a normal and a binge meal (13), our child and adolescent participants with LOC did not distinguish between meal type in terms of macronutrient intake or their affect before and after the meals. Unlike adult studies that included individuals with full-syndrome BED, the children in our sample did not report extensive disordered eating. Only two participants in our study met research criteria for BED (1). Therefore, because our participants were not engaging in chronic and routine binge episodes, they may have not yet established a distinct set of behaviors that differentiated normal meals from binge meals. Further, it is possible that LOC eating during youth represents a somewhat different construct than binge eating in adults. For example, the presence of a large buffet of palatable foods when hungry may cause children with LOC to consume typical adult “binge” foods even if children are instructed to eat normally.

In post-hoc analyses of participants with a BMI ≥ 85th percentile, however, we found that girls, but not boys, with LOC consumed more energy at the binge meal compared to the normal meal. Although this finding should be interpreted with caution since the 3-way interaction of LOC by sex by weight status did not reach significance (p=0.15), this pattern suggests that heavier girls with LOC may behave differently at a binge meal. The excessive energy intake associated with LOC eating may further clarify, at least for overweight girls, a mechanism whereby youth who report LOC eating are heavier (7, 8) and at greater risk for excess weight gain over time (1012). Consistent with the data from the one adult laboratory study that included obese men with BED (42), we found no difference between heavy boys with and without LOC eating in terms of energy intake at either meal. These findings differ from a previous study conducted in our laboratory using a similar feeding paradigm (3). Mirch and colleagues studied a younger sample, all of whom had elevated insulin and were seeking treatment for severe overweight, and the buffet was offered at an earlier time of day. Although our methodology to determine the presence of LOC differed from Mirch et al.’s assessment of binge eating, our findings did not change when we used a self-report measure to determine the presence of LOC eating. It is possible that the differences in sample characteristics or the exact methods used may have contributed to the lack of consistency in findings across these two studies.

Strengths of this study include the large sample size, the use of both a normal meal and a binge meal, and the inclusion of boys and girls who were not seeking weight-loss treatment, and who were of a broad age and weight range. Furthermore, we used a semi-structured clinical interview to assess the presence of LOC eating. Limitations include that all participants were provided the same standardized breakfast prior to each test meal, regardless of body weight. It is possible that heavier youth required substantially more energy than what was provided for breakfast to have equal satiety, thereby potentially masking some differences between groups with regard to LOC or meal type. However, we accounted for body composition in all analyses. A large buffet, although effectively used in prior studies (3, 13), may have impacted participants’ consumption. Preliminary data suggest that when greater amounts of food are presented the amount of food eaten generally increases (43). Examining the energy intake and macronutrient composition of meals that children with and without LOC consume in their natural environment over the course of an extended time period will be an important next research step. Finally, although consistent methods were used throughout data collection, they vary slightly, from some of the directions given in adult studies in that the language for the meal instructions were more child-accessible and the time of the buffet meals were earlier. Further research should focus on the standardization of procedures across studies.

In conclusion, children and adolescents who report a lack of control over eating may be at particular risk for consuming foods that promote overweight when they are offered large quantities of palatable foods. Future studies are needed to examine methods that may help children and adolescents with LOC eating modify their choices and prevent excessive weight gain.


We thank the families who participated in these studies, and the staff of the metabolic kitchen at the NIH Clinical Center. J Yanovski and M Schollnberger are Commissioned Officers in the United States Public Health Service, Department of Health and Human Services. MTK, JRM, SZY, and JAY were primarily responsible for developing the study design and conceived the hypothesis for this article. MTK and JAY supervised the data collection. MTK, LBS, and JAY conducted the data analysis. MS, NAS and CS contributed to data collection and provided critical input on data analyses and on versions of the manuscript. All authors participated in the interpretation of the results and approved the final version of the manuscript.

The funding organization played no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; nor preparation or review of the manuscript.

Research support: Intramural Research Program, NIH, grant Z01-HD-00641 (to JAY) from the NICHD, supplemental funding from NCMHD (to JAY), and USUHS grant R072IC (to MTK). J. Yanovski and M. Kozlosky are commissioned officers in the U.S. Public Health Service


Publisher's Disclaimer: DHHS. Disclaimer: The opinions and assertions expressed herein are those of the authors and are not to be construed as reflecting the views of USUHS or the U.S. Department of Defense.

This is an un-copyedited author manuscript that has been accepted for publication in The American Journal of Clinical Nutrition, copyright American Society for Nutrition (ASN). This manuscript may not be duplicated or reproduced, other than for personal use or within the rule of ‘Fair Use of Copyrighted Materials’ (section 107, Title 17, US Code) without permission of the copyright owner, the ASN. The final copyedited article, which is the version of record, can be found at The ASN disclaims any responsibility or liability for errors or omissions in this version of the manuscript or in any version derived from it by the National Institutes of Health or other parties.”

None of the authors had any conflicts of interest.


1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders DSM-IV-TR. Washington, DC: Authors; 2000.
2. Tanofsky-Kraff M. Binge eating among children and adolescents. In: Jelalian E, Steele R, editors. Handbook of Child and Adolescent Obesity. Springer; 2008. pp. 41–57.
3. Mirch MC, McDuffie JR, Yanovski SZ, et al. Effects of binge eating on satiation, satiety, and energy intake of overweight children. Am J Clin Nutr. 2006;84:732–8. [PMC free article] [PubMed]
4. Decaluwe V, Braet C. Prevalence of binge-eating disorder in obese children and adolescents seeking weight-loss treatment. Int J Obes Relat Metab Disord. 2003;27:404–9. [PubMed]
5. Tanofsky-Kraff M, Faden D, Yanovski SZ, Wilfley DE, Yanovski JA. The perceived onset of dieting and loss of control eating behaviors in overweight children. Int J Eat Disord. 2005;38:112–22. [PMC free article] [PubMed]
6. Glasofer DR, Tanofsky-Kraff M, Eddy KT, et al. Binge eating in overweight treatment-seeking adolescents. J Pediatr Psychol. 2007;32:95–105. [PMC free article] [PubMed]
7. Morgan C, Yanovski S, Nguyen T, et al. Loss of control over eating, adiposity, and psychopathology in overweight children. Int J Eat Disord. 2002;31:430–41. [PubMed]
8. Tanofsky-Kraff M, Yanovski SZ, Wilfley DE, Marmarosh C, Morgan CM, Yanovski JA. Eating disordered behaviors, body fat, and psychopathology in overweight and normal weight children. J Consult Clin Psychol. 2004;72:53–61. [PMC free article] [PubMed]
9. Field AE, Austin SB, Taylor CB, et al. Relation between dieting and weight change among preadolescents and adolescents. Pediatrics. 2003;112:900–6. [PubMed]
10. Stice E, Cameron RP, Killen JD, Hayward C, Taylor CB. Naturalistic weight-reduction efforts prospectively predict growth in relative weight and onset of obesity among female adolescents. J Consult Clin Psychol. 1999;67:967–74. [PubMed]
11. Tanofsky-Kraff M, Cohen ML, Yanovski SZ, et al. A prospective study of psychological predictors of body fat gain among children at high risk for adult obesity. Pediatrics. 2006;117:1203–9. [PMC free article] [PubMed]
12. Tanofsky-Kraff M, Yanovski SZ, Schvey NA, Olsen CH, Gustafson J, Yanovski JA. A prospective study of loss of control (LOC) eating for body weight gain in children at high-risk for adult obesity. Int J Eat Disord. In press. [PMC free article] [PubMed]
13. Walsh BT, Boudreau G. Laboratory studies of binge eating disorder. Int J Eat Disord. 2003;34(Suppl):S30–8. [PubMed]
14. Tanofsky-Kraff M, Goossens L, Eddy KT, et al. A multisite investigation of binge eating behaviors in children and adolescents. J Consult Clin Psychol. 2007;75:901–13. [PMC free article] [PubMed]
15. Kuczmarski RJ, Ogden CL, Guo SS, et al. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat 11. 2002:1–190. [PubMed]
16. Russell DL, Keil MF, Bonat SH, et al. The relation between skeletal maturation and adiposity in African American and Caucasian children. Journal of Pediatrics. 2001;139:844–48. [PubMed]
17. Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, et al. CDC growth charts: United States. Adv Data. 2000:1–27. [PubMed]
18. Dempster P, Aitkens S. A new air displacement method for the determination of human body composition. Med Sci Sports Exerc. 1995;27:1692–7. [PubMed]
19. Marshall WA, Tanner JM. Variations in pattern of pubertal changes in girls. Archives of Disease in Childhood. 1969;44:291–303. [PMC free article] [PubMed]
20. Marshall WA, Tanner JM. Variations in the pattern of pubertal changes in boys. Archives of Disease in Childhood. 1970;45:13–23. [PMC free article] [PubMed]
21. Tanner JM. Growth and maturation during adolescence. Nutritional Review. 1981;39:43–55. [PubMed]
22. Fairburn C, Cooper Z. The Eating Disorder Examination. In: CG F, GT W, editors. Binge eating, nature, assessment and treatment. 12. New York: Guilford; 1993. pp. 317–360.
23. Bryant-Waugh RJ, Cooper PJ, Taylor CL, Lask BD. The use of the eating disorder examination with children: a pilot study. Int J Eat Disord. 1996;19:391–7. [PubMed]
24. Hess MA. Portion photos of popular foods. Madison, WI: Center for Nutrition Education, University of Wisconsin-Stout; 1997.
25. Rizvi SL, Peterson CB, Crow SJ, Agras WS. Test-retest reliability of the eating disorder examination. Int J Eat Disord. 2000;28:311–6. [PubMed]
26. Christie D, Watkins B, Lask B. Assessment. In: Lask B, Bryant-Waugh RJ, editors. Anorexia nervosa and related eating disorders in childhood and adolescence. 2. East Essex, UK: Psychology Press; 2000. pp. 105–125.
27. Block G, Norris JC, Mandel RM, DiSogra C. Sources of energy and six nutrients in diets of low-income Hispanic-American women and their children: quantitative data from HHANES, 1982–1984. J Am Diet Assoc. 1995;95:195–208. [PubMed]
28. Hetherington MRB. Methods of investigating human behavior. In: Toates FRN, editor. Feeding and Drinking. Amsterdam: Elsevier Science Publishers B. V; 1987. pp. 77–109.
29. Spielberger G, Lushene, Vagg, Jacobs . Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologist Press; 1983.
30. Terry PC, Lane AM, Lane HJ, Keohane L. Development and validation of a mood measure for adolescents. J Sports Sci. 1999;17:861–72. [PubMed]
31. SPSS. SPSS 14.0. Chicago, IL: 2006.
32. Hollingshead A. Four factor index of social status. New Haven: Yale University; 1975.
33. Johnson WG, Grieve FG, Adams CD, Sandy J. Measuring binge eating in adolescents: adolescent and parent versions of the questionnaire of eating and weight patterns. Int J Eat Disord. 1999;26:301–14. [PubMed]
34. Paddon-Jones D, Westman E, Mattes RD, Wolfe RR, Astrup A, Westerterp-Plantenga M. Protein, weight management, and satiety. Am J Clin Nutr. 2008;87:1558S–1561S. [PubMed]
35. Schoeller DA, Buchholz AC. Energetics of obesity and weight control: does diet composition matter? J Am Diet Assoc. 2005;105:S24–8. [PubMed]
36. Westerterp-Plantenga MS. The significance of protein in food intake and body weight regulation. Curr Opin Clin Nutr Metab Care. 2003;6:635–8. [PubMed]
37. Gibson EL. Emotional influences on food choice: sensory, physiological and psychological pathways. Physiol Behav. 2006;89:53–61. [PubMed]
38. Yanovski SZ, Leet M, Yanovski JA, Flood M, Gold PW, Kissileff HR, Walsh TB. Food selection and intake of obese women with binge-eating disorder. American Journal of Clinical Nutrition. 1992;56:975–980. [PubMed]
39. Theim KR, Tanofsky-Kraff M, Salaita CG, et al. Children's descriptions of the foods consumed during loss of control eating episodes. Eat Behav. 2007;8:258–65. [PMC free article] [PubMed]
40. 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. Int J Eat Disord. 2007;40:195–203. [PubMed]
41. Pinaquy S, Chabrol H, Simon C, Louvet JP, Barbe P. Emotional eating, alexithymia, and binge-eating disorder in obese women. Obes Res. 2003;11:195–201. [PubMed]
42. Geliebter A, Hassid G, Hashim SA. Test meal intake in obese binge eaters in relation to mood and gender. Int J Eat Disord. 2001;29:488–94. [PubMed]
43. Gosnell BA, Mitchell JE, Lancaster KL, Burgard MA, Wonderlich SA, Crosby RD. Food presentation and energy intake in a feeding laboratory study of subjects with binge eating disorder. Int J Eat Disord. 2001;30:441–6. [PubMed]