Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2013 Jun 11.
Published in final edited form as: Obesity (Silver Spring). 2009 Jan 22;17(4):689–697. doi: 10.1038/oby.2008.600

Dieting Frequency in Obese Patients With Binge Eating Disorder: Behavioral and Metabolic Correlates

Megan Roehrig 1, Robin M Masheb 1, Marney A White 1, Carlos M Grilo 1,2
PMCID: PMC3678720  NIHMSID: NIHMS466545  PMID: 19165172

Abstract

This study examined the clinical significance of self-reported frequency of time spent dieting in obese patients with binge eating disorder (BED). A total of 207 treatment-seeking obese BED patients (57 men and 150 women) were dichotomized by dieting frequency and gender and compared on a number of historical, psychological, and metabolic variables. Frequent dieters reported significantly earlier age of onset for binge eating, dieting, and obesity, more episodes of weight cycling, greater weight suppression, and greater eating disorder pathology than infrequent dieters; no differences, however, emerged on current binge eating frequency or psychological distress. Among women but not among men, frequent dieters had consistently lower chances of abnormalities in total cholesterol, high-density lipoprotein (HDL) cholesterol, and the total/HDL cholesterol ratio while infrequent dieters had greater chances of abnormalities on these variables. Dietary restraint was inversely correlated with abnormalities in triglycerides, HDL cholesterol, and the total/HDL cholesterol ratio but was unrelated to low-density lipoprotein (LDL) cholesterol. In summary, frequent dieters of both genders had greater lifetime and current eating and weight concerns, and in women, decreased chance of metabolic abnormalities than infrequent dieters. Our findings suggest that frequent dieting attempts, particularly in women, are associated with greater eating disorder pathology but may have a beneficial effect on metabolic functioning and cardiovascular disease risk independent of actual weight status. These findings may have implications for clinical advice provided to obese BED patients.

INTRODUCTION

Obesity is a significant health and economic burden, and prevalence rates have soared to epidemic proportions across the world (1, 2). Binge eating disorder (BED), which is characterized by recurrent episodes of binge eating (eating an unusually large amount of food and feeling a loss of control) in the absence of compensatory behaviors, occurs in a subset of overweight and obese individuals and has been identified as a distinct phenotype (3, 4). BED is associated with severe obesity (3) and occurs in males and ethnically diverse groups at greater rates than anorexia nervosa and bulimia nervosa. Research has found that obese individuals with BED have distinctive psychopathology from other disordered eating groups (5) that is significantly elevated relative to obese individuals without BED (6). Studies have found that obese BED patients have higher levels of psychopathology (7) and comorbid psychological disorders (8, 9), poorer quality of life (10), greater eating disorder pathology (11), and are at an increased risk for morbid obesity (4) compared to their non-BED counterparts. Binge eating may also be associated with metabolic abnormalities, and hyperlipidemia has been found in nonobese, eating disorder patients who binge eat (12, 13). Comparisons of obese BED and non-BED patients have found elevated cholesterol levels overall but no differences based on binge eating status (14, 15).

Dieting is frequently reported in obese individuals with BED (16) and has been implicated in the etiology and maintenance of binge eating behaviors (17–20). Although obese BED patients differ from nonbinge eating obese patients in their lifetime dieting histories (16), this has received surprisingly little research attention, and the nature and clinical significance of dieting in BED patients are poorly understood. One line of behavioral research has examined the timing and sequencing of self-reported onset of dieting and binge eating in BED patients. These studies have found differences between the Diet First and Binge First groups on historical variables, including age of onset of overweight and BED diagnosis, but have yielded inconsistent findings in relation to current eating disorder psychopathology, with one study finding greater eating pathology in the Diet First group (19), and two studies reporting no differences between the Diet First and Binge First groups (17, 20). A second line of research has investigated the relationship between binge eating and weight cycling (repeated episodes of intentional weight loss and subsequent weight regain) on psychological and physical well-being. A positive association between frequent weight cycling and binge eating behaviors has been reliably found in obese adults (21–24). Frequent weight cycling has also been associated with higher levels of dietary restraint (22) and disinhibition (25), greater use of unhealthy weight control strategies (21), and more weight gain than infrequent or nonweight cyclers (21) The findings, however, have generally not supported a greater frequency of full syndrome BED in frequent weight cyclers (26, 27), with one notable exception (28). A third line of research has examined the relationship between dieting and binge eating in the context of both naturalistic dieting and during behavioral weight loss and very-low calorie diet programs (29). These studies have convincingly demonstrated no exacerbation of binge eating in obese BED and non-BED patients as a result of restricting caloric intake during highly structured diet programs (30).

Most studies on dieting history have examined dieting episodes that resulted in significant weight loss (typically ≥10 lb), and little is known about dieting behavior that includes both successful and unsuccessful dieting attempts. One study of bariatric surgery candidates found that patients reported a mean of 4.7 previous diets that resulted in a weight loss of ≥10 lb; however, that number rose to almost 15 when short-lived or unsuccessful dieting attempts were included (31). A history of frequent dieting is often reported in obese BED patients with one study finding that, on average, patients reported spending about half of their adult life on a diet (16). Although obese BED patients of both genders report a history of dieting attempts, women may attempt dieting more frequently than men (32). We are unaware of any research to date that has examined the clinical significance of self-reported dieting frequency in BED patients from either a behavioral or a metabolic standpoint, and it is unclear whether the significance of dieting frequency differs by gender. Therefore, the goals of this study are to explore how self-reported frequency of time spent dieting during adulthood relates to behavioral and metabolic functioning in treatment-seeking obese men and women with BED. Specifically, this study aims to compare self-reported frequent vs. infrequent dieters on a number of clinically relevant variables, including (i) eating and weight history, (ii) current eating behaviors and psychological functioning, and (iii) fasting lipid profiles.

METHODS AND PROCEDURES

Participants

Participants were 207 obese, treatment-seeking adults (57 men; 150 women) who met diagnostic research criteria for BED as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; (33)). Participants ranged in age from 18 to 59 (M = 44.58, s.d. = 9.41). The participant group was 77.3% white (N = 160), 14 % African American (N = 29), 4.8% Hispanic (N = 10), and 3.9% of other ethnicity (N = 8). Mean BMI (weight (kg) divided by height (m2)) was 37.97 (s.d. = 6.25). Participants were recruited via advertisements seeking overweight persons with binge eating problems who wanted to “stop binge eating and lose weight.” Participants were recruited solely for clinical treatment studies being conducted at a medical school-based program. Data for this study were obtained from all participants enrolled in three separate grant-funded treatment studies evaluating behavioral weight loss or cognitive–behavioral interventions for binge eating. The recruitment procedures and assessment protocols were constant across the studies.

Assessment and measures

Assessments were administered by experienced doctoral level research-clinicians who were specifically trained and monitored. BED research diagnoses were determined using the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I/P; (34)) and confirmed by findings from the Eating Disorders Examination (EDE; (35)). The EDE, a semi-structured investigator-based interview, was administered to all participants to assess the psychopathology of eating disorders. Height and weight were measured to calculate BMI.

Eating Disorder Examination

The EDE, used to assess eating disorders and their features, focuses on the previous 28 days, except for diagnostic items that are rated for duration stipulations of the DSM-IV. The EDE assesses the frequency of different forms of overeating, including objective bulimic episodes OBE; defined as consuming unusually large quantities of food with a subjective sense of loss of control). The EDE’s definition of OBEs corresponds to the DSM-IV criteria for binge eating in the BED research criteria. The EDE also comprises four subscales: Restraint, Eating Concern (EC), Shape Concern (SC), and Weight Concern (WC). The Restraint subscale reflects attempts to restrict food intake to influence weight or shape; the EC subscale reflects the degree of concern about eating; and the WC and SC subscales measure the degree of concern about weight and shape, respectively. The items assessing eating disorder features for the four scales are rated on a 7-point forced-choice format (0–6), with higher scores reflecting greater severity or frequency. The EDE is considered the best established method for assessing the cognitive features of eating disorders and has received support for its utility in assessing BED (36, 37). Psychometric studies of the EDE have demonstrated its validity and good inter-rater and test–retest reliability in diverse groups including BED (38), although recent studies have found that the restraint scale is not correlated with actual caloric intake (39).

Beck Depression Inventory

The Beck Depression Inventory (BDI) (40) is a widely used 21-item measure of depressive symptoms, and, more generally, of negative affect (41). Elevated scores on the BDI correlate highly with anxiety measures (41) and efficiently predict elevated psychopathology (42) and psychiatric comorbidity (18). Therefore, the BDI is a useful marker for broad psychosocial distress. Studies with clinical samples have reported good internal consistency (α = 0.81–0.86), test–retest reliability (r = 0.48–0.86), and convergent validity with clinician ratings of depression (r = 0.60–0.72) (ref. 43).

Three Factor Eating Questionnaire

The Three Factor Eating Questionnaire (TFEQ) (44) consists of 51 items that assess three factors: disinhibition, hunger, and cognitive restraint. The TFEQ-cognitive restraint scale and EDE-Restraint scale have been found to measure different aspects of dietary restraint (i.e., dieting to avoid weight gain and dieting to lose weight, respectively) (45) and was therefore included to examine both of these dimensions of dietary restraint. The TFEQ has received some psychometric support including good internal consistency (44) and predictive validity (46), although recent studies have found that TFEQ-Restraint scores are not correlated with actual caloric intake (39, 47).

Body Shape Questionnaire

The Body Shape Questionnaire (BSQ) (a measure of body image dissatisfaction) was included to complement the EDE (which measures cognitive-evaluative and affective aspects of body image) and provide a comprehensive assessment of body image factors. As previously demonstrated empirically, body dissatisfaction and overvaluation of shape and weight are related but distinct attitudinal features of body image (48, 49). The BSQ (50) is a 34-item measure of body dissatisfaction, including preoccupation with and distress about body shape. The BSQ has demonstrated good validity and reliability (51).

Questionnaire for Eating and Weight Patterns-Revised

The Questionnaire for Eating and Weight Patterns-Revised (QEWP-R) (52), used in the DSM-IV field trials, assesses each criterion for BED and has been shown to reliably identify BED in clinical and community samples of adults (53) and adolescents (54). The QEWP-R also assesses historical variables relevant to this study, including age of onset for binge eating, dieting, and obesity, percent of time spent on a diet, highest and lowest adult weights, and parental obesity. Weight suppression, defined as sustained weight reduction over time (55), was calculated using the following formula: ((highest weight − current measured weight)/highest weight) × 100). The QEWP-R measures dieting frequency by inquiring “Since you have been an adult—18 years old—how much of the time have you been on a diet, been trying to follow a diet, or in some way been limiting how much you were eating in order to lose weight or keep from regaining weight you had lost?” Responses are defined on a five-point Likert scale, ranging from “1 = None or hardly any of the time” to “5 = Nearly all of the time.” The reliability and validity of the specific QEWP-R items regarding historical dieting variables are uncertain. We examined short-term (1–week) test–retest reliability of the QEWP-R in a separate series of N = 24 patients. The 1-week test–retest reliability coefficient for the dieting frequency variable was 0.87.

Rosenberg Self-Esteem Scale

The Rosenberg Self-Esteem Scale (RSES) (56) is a 10-item measure of global self-esteem. Global self-esteem relates broadly to adaptive functioning in a variety of domains (57). Studies have noted good internal consistency, test–retest reliability coefficients above 0.85, and good validity (56). Higher scores on the RSES reflect higher self-esteem.

Metabolic functioning

Fasting lipid profile (total cholesterol, high-density lipoproteins (HDLs), low-density lipoproteins (LDLs), and triglycerides) was obtained and analyzed by Quest Diagnostics (Madison, NJ).

Design and analyses

Dieting group status was determined using the QEWP-R dieting frequency item by examining the descriptive statistics (M = 3.41, s.d. = 1.3, Median = 3.0) and distribution characteristics. The frequency of responses to the dieting frequency item were “None of the time”: 8.7% (N = 18); “One-quarter of the time”: 18.8% (N = 39); “Half of the time”: 22.7% (N = 47); “Three-quarters of the time”: 22.7% (N = 47); and “Nearly all of the time”: 27.1% (N = 56). Skewness (−0.28) and kurtosis (−1.07) were within acceptable ranges, and visual inspection of the distribution revealed a slight negative skew. Given these characteristics, a median split was used to dichotomize participants into infrequent (N = 104) and frequent (N = 103) dieters. Infrequent dieters were those who dieted less than or equal to half of the time (responses were ≤3) whereas frequent dieters reportedly dieted more than half of the time (responses of 4 or 5).

Analyses of demographic and historical variables were conducted using χ2-analyses for categorical variables and 2 (Dieting Group) × 2 (Gender) Between-Subjects ANOVAs for continuous variables. The psychological dependent variables were grouped according to eating behavior (i.e., restriction, disinhibition), body image disturbance, and global functioning (i.e., BDI, RSES), and separate 2 × 2 multivariate analysis of variances were computed in order to control Type I error rates. Group differences in metabolic variables were examined both continuously and categorically. Categorical analyses were conducted with separate χ2-analyses by gender. Participants were categorized as At-Risk or Low-Risk on each metabolic variable according to the most recent guidelines from the National Cholesterol Education Program’s Adult Treatment Panel III (58, 59). All analyses were conducted using SPSS 15.0 (SPSS, Chicago, IL).

RESULTS

Demographic and historical illness variables

Table 1 shows the means and standard deviations for the demographic and historical variables. Statistical analyses revealed a number of significant differences between dieting groups as summarized below.

Table 1.

Means and standard deviations for historical illness variables by group and gender

Frequent dieters (n = 103)
 Infrequent dieters (n = 104)
Males (n = 17) Females (n = 86) Total Males (n = 40) Females (n = 64) Total
Age 44.1 (6.5) 43.2 (9.8) 44.5 (9.6) 45.2 (10.1) 44.1 (6.5) 44.9 (9.2)
Current BMI 38.8 (6.7) 38.1 (5.7) 38.2 (5.9) 37.6 (5.3) 37.8 (7.4) 37.7 (6.6)
Highest adult BMI 43.70 (8.9) 40.80 (6.4) 41.28 (6.9)a 39.30 (6.8) 39.47 (6.0) 39.41 (6.3)b
Lowest adult BMI 26.2 (3.8)1 24.01 (4.3)2 24.4 (4.3) 25.3 (3.5)1 22.4 (5.3)2 23.5 (4.9)
Mother silhouette 5.8 (1.6) 5.5 (2.1) 5.6 (2.0) 6.2 (1.5) 5.6 (1.3) 5.8 (1.4)
Father silhouette 6.0 (1.4) 5.6 (1.8) 5.7 (1.8) 5.9 (1.9) 5.1 (1.7) 5.4 (1.8)
Age of obesity onset 12.76 (7.65) 12.56 (6.74) 12.60 (6.86)a 18.40 (10.66) 17.78 (10.9) 18.01 (10.8)b
Age of binging onset 18.0 (10.5) 19.41 (9.8) 19.2 (9.8)a 28.5 (12.8) 27.89 (13.8) 28.13 (13.4)b
Age of dieting onset 21.53 (8.64)1 15.42 (6.21)2 16.44 (7.01)a 25.59 (11.2)1 20.51 (10.8)2 22.43 (11.2)b
Weight cycling 3.12 (0.99) 3.34 (0.90) 3.30 (0.92)a 2.8 (0.99) 2.59 (0.94) 2.67 (0.96)b
Weight suppression 7.22 (9.0) 5.50 (8.4) 5.78 (8.5)a 4.0 (6.8) 3.18 (4.5) 3.50 (5.5)b
Open in a new tab

2 × 2 ANOVAs were conducted. Letters in subscript denote significant differences between diet frequency groups. Numbers in subscript reflect significant between gender differences. Analysis of covariances were also conducted to control for the effects of BMI, and the findings were unchanged.

Gender

The χ2-analysis revealed significant gender differences between the dieting groups, χ2 (1) = 12.50, P < 0.001. Examination of expected and actual values suggests that there were more men and fewer women than expected in the infrequent dieting group. 70.2% (N = 40) of men and 42.7% (N = 64) of women were infrequent dieters. In contrast, there were fewer men and more women in the frequent dieting group. 29.8% (N = 17) of men and 57.3% (N = 86) of women were frequent dieters. To examine these differences systematically, gender was used as a between-subjects factor in all subsequent analyses.

Ethnicity

Ethnic/racial differences between the dieting groups were examined by collapsing the groups into white and nonwhite categories to ensure sufficient power due to small numbers in some cells. The χ2-analysis was nonsignificant, χ2 (1) = 0.68, P > 0.05, and remained nonsignificant when men and women were analyzed separately, χ2 (1) = 0.59, P > 0.05 and χ2 (1) = 0.01, P > 0.05, respectively, suggesting similar racial distribution between the dieting groups.

Age

The ANOVA revealed nonsignificant effects for dieting group, F (1,201) = 1.67, P > 0.05, gender, F (1,201) = 0.002, P > 0.05, or the interaction, F (1,201) = 0.32, P > 0.05, suggesting that age was equivalent across the groups.

Current BMI

No significant differences emerged on current BMI for dieting group, F (1,190) = 0.41, P > 0.05, gender, F (1,190) = 0.06, P > 0.05, or their interaction, F (1,190) = 0.17, P > 0.05. As Table 1 illustrates, mean BMI for both genders and dieting groups was ~38.

Parental obesity

Parental silhouettes were assessed via the QEWP-R and examined as a proxy for genetic predisposition to obesity. No significant differences emerged on silhouettes for mothers or fathers at their heaviest weight for dieting group, gender, or the group by gender interaction.

Age of onset

Patients retrospectively reported the ages of onset for obesity, binge eating, and dieting on the QEWP-R. As Table 1 denotes, clear differences emerged between the dieting groups with frequent dieters reporting earlier onsets for obesity, F (1,189) = 12.41, P < 0.01, partial η2 = 0.06, dieting, F (1,196) = 9.01, P < 0.01, partial η2 = 0.04, and binge eating, F (1,198) = 23.07, P < 0.001, partial η2 = 0.10, than infrequent dieters. A main effect for gender was also found for dieting onset, F (1,196) = 13.49, P < 0.001, partial η2 = 0.06, with women (M = 17.55, s.d. = 8.77) initiating dieting earlier than men (M = 24.31, s.d. = 10.57). No other main effects or interactions were significant for the age of onset variables.

Weight history

Clear differences emerged between dieting groups on weight history variables. As Table 1 illustrates, frequent dieters had a greater highest adult BMI, F (1,192) = 6.49, P < 0.05, partial η2 = 0.03, more weight cycling episodes, F (1,200) = 11.51, P < 0.01, partial η2 = 0.05, and were more weight suppressed, F (1,198) = 5.25, P < 0.05, partial η2 = 0.03, than infrequent dieters. In addition, a significant main effect for gender emerged for lowest adult BMI, F (1,197) = 11.14, P < 0.01, partial η2 = 0.05, with men having a heavier lowest adult BMI than women. No other main effects or interactions were significant.

Current behavioral and psychological correlates

Table 2 presents the means and standard deviations for behavioral and psychological variables.

Table 2.

Means and standard deviations for eating behavior, body image dissatisfaction, and global psychological functioning by group and gender

Frequent dieters (n = 103)
 Infrequent dieters (n = 104)
Males (n = 17) Females (n = 86) Total Males (n = 40) Females (n = 64) Total
Eating behavior
  EDE-past month OBE 15.24 (8.2) 16.60 (9.3) 15.46 (8.8) 15.61 (10.2) 13.83 (7.3) 14.51 (8.5)
  EDE-Restraint 2.52 (1.2) 2.15 (1.4) 2.21 (1.4)a 1.19 (1.0) 1.41 (1.1) 1.33 (1.0)b
  EDE-Eating Concerns 2.35 (1.4) 2.68 (1.3) 2.63 (1.3)a 1.33 (1.2) 1.65 (1.2) 1.53 (1.2)b
  TFEQ-Restraint 8.25 (3.7) 8.71 (3.3) 8.63 (3.4)a 6.04 (3.0) 6.84 (3.4) 6.54 (3.3)b
  TFEQ-Disinhibition 14.8 (1.8) 14.8 (2.2) 14.8 (2.1)a 12.9 (2.9) 13.7 (2.6) 13.4 (2.7)b
  TFEQ-Hunger 12.1 (2.5) 10.1 (3.7) 10.4 (3.6) 10.0 (3.2)1 9.9 (3.7)2 9.95 (3.5)
Body image dissatisfaction
  EDE-Weight Concerns 3.22 (0.8)1 3.53 (0.9)2 3.48 (0.9)a 2.67 (0.7)1 3.16 (0.9)2 2.97 (0.9)b
  EDE-Shape Concerns 3.83 (0.9)1 4.06 (0.9)2 4.0 (0.9)a 2.85 (0.9)1 3.68 (1.1)2 3.36 (1.1)b
  BSQ 134.1 (25.7)1 147.8 (24.1)2 145.5 (24.8)a 104.3 (26.5)1 135.6 (29.4)2 123.6 (32.1)b
Global functioning
  BDI 15.88 (6.9)1 17.85 (8.7)2 17.51 (8.4) 12.19 (7.6)1 16.81 (8.2)2 15.06 (8.3)
  RSES 26.68 (6.1) 28.49 (6.1) 28.18 (6.1) 30.33 (5.3) 27.59 (5.4) 28.63 (5.5)
Open in a new tab

Letters in subscript denote significant differences between diet frequency groups as determined by multivariate analysis of variances. Numbers in subscript reflect significant between gender differences. Multivariate analysis of covariances were also conducted to control for the effects of BMI, and the findings were unchanged.

BDI, Beck Depression Inventory; BSQ, Body Shape Questionnaire; EDE, Eating Disorders Examination; OBE, Objective Binge Episode; RSES, Rosenberg Self-Esteem Scale; TFEQ, Three Factor Eating Questionnaire.

Eating behavior

There were no differences on the number of OBEs in the past month for dieting group, gender, or the dieting group by gender interaction; however, a significant multivariate difference between infrequent and frequent dieters emerged for current eating behavior, Wilks’ λ = 0.79, F (5, 189) = 10.07, P < 0.001, partial η2 = 0.21. The omnibus F-tests were nonsignificant for gender and the gender-by-dieting group interaction. Follow-up univariate F-tests revealed significant differences on four of the five variables (see Table 2 for means and standard deviations). Frequent dieters had significantly higher levels of current restraint, eating concerns, and disinhibition than infrequent dieters as measured by the EDE-Restraint, F (1,197) = 24.50, P< 0.001, partial η2 = 0.11, TFEQ-Restraint, F (1,197) = 13.01, P< 0.001, partial η2 = 0.06, EDE-EC, F (1,197) = 22.75, P < 0.001, partial η2 = 0.11, and TFEQ-Disinhibition, F (1,197) = 12.86, P< 0.001, partial η2 = 0.06. The TFEQ-Hunger subscale was nonsignificant.

Body image disturbance

Significant multivariate main effects were found for dieting group, Wilks’ λ = 0.88, F (3,190) = 8.48, P < 0.001, partial η2 = 0.12, and for gender, Wilks’ λ = 0.88, F (3,190) = 8.66, P < 0.001, partial η2 = 0.12, but the gender-by-dieting group interaction was nonsignificant. Follow-up univariate F-tests suggest reliable differences between these groups on body image disturbance. As Table 2 illustrates, frequent dieters had higher body image disturbance than infrequent dieters as measured by the EDE-WC, F (1,192) = 9.57, P < 0.01, partial η2 = 0.05, EDE-SC, F (1,192) = 16.13, P < 0.001, partial η2 = 0.08, and the BSQ, F (1,192) = 22.30, P < 0.001, partial η2 = 0.10. Significant main effects for gender also emerged on all body image measures, EDE-WC, F (1,192) = 7.21, P < 0.01, partial η2 = 0.04, EDE-SC, F (1,192) = 9.67, P < 0.01, partial η2 = 0.05, and the BSQ, F (1,192) = 25.44, P < 0.001, partial η2 = 0.12, with females having higher dissatisfaction than males.

Global functioning

A significant multivariate main effect was found for gender, Wilks’ λ = 0.96, F (2,202) = 4.39, P < 0.05, partial η2 = 0.04. The main effect for dieting group and the dieting group by gender interaction were nonsignificant. Follow-up univariate F-tests suggest that there was a significant gender difference on BDI scores, F (1, 203) = 5.30, P < 0.05, partial η2 = 0.03, with women (M = 17.37) having higher depressive symptoms than men (M = 13.44). No gender differences were found on self-esteem, F (1,203) = 0.04, P > 0.05.

Metabolic risk status

Figure 1 displays the significant findings from the metabolic risk analyses. The data were also examined continuously in separate ANOVAs, and the findings are reported in Table 3.

Figure 1.

Figure 1

Open in a new tab

Metabolic risk status in women infrequent and frequent dieters. Percentage values are based on actual cell counts for each dieting group obtained through χ2-analyses. Chol, cholesterol; HDL, high-density lipoprotein.

Table 3.

Means and standard deviations for metabolic variables by group and gender

Frequent dieters (n = 103)
 Infrequent dieters (n = 104)
Males (n = 17) Females (n = 86) Total Males (n = 40) Females (n = 64) Total
Triglycerides 164.67 (91.4)1 103.66 (54.4)2 113.71 (65.5) 177.94 (106.4)1 128.61 (101.16)2 146.75 (105.25)
HDL cholesterol 42.07 (7.03)1 56.74 (12.38)2 54.32 (12.86) 39.55 (9.33)1 52.15 (11.14)2 47.42 (12.11)
LDL cholesterol 126.20 (27.29) 124.47 (46.81) 124.75 (44.07) 113.27 (30.58) 132.76 (29.43) 125.72 (31.12)
Total cholesterol 201.20 (23.42) 197.29 (32.92) 197.93 (31.47) 188.79 (34.85)a 208.84 (31.63)b 201.32 (34.10)
Total/HDL ratio 4.92 (1.01)1 3.60 (0.84)2 3.82 (0.99) 5.00 (1.38)1 4.16 (0.99)2 4.47 (1.21)
Open in a new tab

2 × 2 ANOVAs were computed. Letters in subscript denote significant differences between diet frequency groups. Numbers in subscript denote significant between gender differences. Analysis of covariances were also conducted to control for the effects of BMI, and the findings were unchanged.

HDL, high-density lipoprotein; LDL, low-density lipoprotein.

Total cholesterol risk

Total cholesterol risk was defined at ≥200 for both men and women. A significant difference emerged for women, χ2 (1) = 6.38, P < 0.05. As Figure 1 indicates, women who were frequent dieters fell into the “Low-Risk” category at a greater frequency than expected whereas infrequent dieters were in the “Low-Risk” category at rates less than expected. Similarly, infrequent dieters were in the “At-Risk” group more than expected and in the “Low-Risk” group less than expected. No significant differences were found for total cholesterol risk and dieting status for men.

HDL risk

HDL risk was defined as <40 for men and <50 for women. The χ2-analyses revealed a significant difference for dieting frequency in women, χ2 (1) = 6.14, P < 0.05, but no differences emerged for men. Findings suggest that women who are frequent dieters fell into the “Low-Risk” category at greater than expected rates and were in the “At-Risk” category at less than expected rates (see Figure 1). In contrast, the infrequent female dieters were overrepresented in the “At-Risk” category and underrepresented in the “Low-Risk” category.

LDL risk

LDL risk was defined as >130 for both genders. For both men and women, the results approached but did not reach significance, χ2 (1) = 3.46, P = 0.06, and χ2 (1) = 3.68, P = 0.06, respectively. Although nonsignificant, mean trends suggest that a greater than expected number of male infrequent dieters were in the “Low-Risk” category. In females, a different trend emerged with a greater than expected number of frequent dieters categorized as “Low-Risk” while fewer than expected infrequent dieters were “Low-Risk.”

Triglyceride risk

Triglyceride risk was defined as ≥150 for both men and women. χ2-Analyses revealed no significant differences on triglyceride risk by dieting group status or dieting status for men or women.

Total cholesterol/HDL ratio risk

Adult Treatment Panel III does not provide specific guidelines for total/HDL ratio; however, recent research suggests that it is a potent predictor of cardiovascular disease. Risk status was defined using prospective data from the Framingham Study with men ≥5.54 and women ≥4.34 falling into the “At-Risk” group (54). χ2-Analyses revealed significant diet group by risk status differences for women, χ2 (1) = 12.45, P < 0.001, whereas no differences emerged for men. As Figure 1 depicts, women who were frequent dieters fell into the “Low-Risk” category at much greater rates than expected while infrequent female dieters fell in the “At-Risk” group more often than expected.

Correlations among eating behavior and metabolic variables

To examine the relationship between eating behavior and metabolic functioning, zero-order Pearson Product-Moment Correlations were examined. As Table 4 illustrates, consistent positive associations were found between dietary restraint and HDL cholesterol whereas restraint was negatively correlated with triglycerides and total/HDL cholesterol. A similar pattern emerged for disinhibition, in which there was a positive association with HDL and negative correlations with triglycerides and total/HDL ratio. No eating behavior variables were correlated with LDL or total cholesterol, and hunger scores were unrelated to any of the metabolic variables.

Table 4.

Correlations among metabolic and eating behavior variables

Triglycerides HDL LDL Total cholesterol Total/HDL ratio
EDE-Restraint −0.17* 0.19* 0.09 0.09 −0.15
EDE-Eating Concerns −0.14 0.19* 0.01 −0.02 −0.19*
TFEQ-Restraint −0.21** 0.15* −0.02 −0.07 −0.21*
TFEQ-Disinhibition −0.17* 0.22** −0.01 0.03 −0.20**
TFEQ-Hunger 0.12 −0.12 −0.04 0.00 0.13
Open in a new tab

EDE, Eating Disorders Examination; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TFEQ, Three Factor Eating Questionnaire.

*

P < 0.05.

**

P < 0.01.

DISCUSSION

This study examined whether obese men and women with BED who report being either frequent or infrequent dieters differ on historical illness and current clinical variables assessing a range of eating behaviors, psychological functioning, and metabolic characteristics. Overall, the findings suggest broad differences between frequent and infrequent self-reported dieters. Frequent dieters had earlier age of onset for binge eating, dieting, and obesity, had more episodes of weight cycling, and were more weight suppressed than infrequent dieters. Although there were no differences in frequency of current binge episodes between the groups, frequent dieters had higher levels of eating concerns, dietary restraint, disinhibition over eating, and body image disturbance than infrequent dieters. Importantly, no differences on measures of global psychological distress were found between the dieting groups, suggesting that these findings cannot be better accounted for differences in general psychological functioning.

Significant gender differences in psychological functioning also emerged. Consistent with previous findings, women BED patients had higher levels of body image dissatisfaction than men (60). Furthermore, our findings indicate that women BED patients had higher levels of depressive symptoms than men. This is consistent with a large body of evidence that has identified robust gender differences in depressive symptoms in both clinical and nonclinical samples (61) but is in contrast to two previous reports that did not find these typical gender differences in treatment-seeking BED patients (32, 60). Future research is needed to clarify these discrepancies.

Overall, metabolic functioning in our sample of obese BED patients is consistent with findings from nationally representative, stratified studies that have convincingly demonstrated the associations between obesity and metabolic abnormalities (62, 63). Mean total cholesterol approached the at-risk cutoff score of 200 for all groups, and percentages for total cholesterol risk in our sample were comparable to those previously found in class II obese adults (38.6% vs. 39.4%, respectively) compared to 23.5% of normal weight adults (63). HDL cholesterol risk in this study was also consistent with data from a large-scale study of US adults (39.6% vs. 37.1%, respectively) (64). Consistent with previous reports of BED patients (15, 32), our findings suggest that metabolic abnormalities occur at similar rates in obese BED and non-BED populations.

Although we did not find any overall differences between frequent and infrequent dieters on metabolic risk status, significant gender differences emerged within the dieting groups. Female infrequent dieters had the highest total cholesterol levels while male infrequent dieters had the lowest levels; however, no differences in total cholesterol were found between male and female frequent dieters. Moreover, in women, frequent dieters had consistently lower risk for total cholesterol, HDL cholesterol, and the total/HDL cholesterol ratio while infrequent dieters appeared to be at greater than expected risk on these variables. This pattern did not emerge in men, and it is unclear whether these findings are actual gender differences or if the smaller sample size for the men resulted in a Type II error. Correlations among the eating and metabolic functioning variables revealed consistent associations between self-reported dietary restraint with triglycerides, HDL cholesterol, and the total/HDL cholesterol ratio, suggesting that self-reported dietary restraint is inversely correlated with abnormalities on these metabolic variables.

Improvements in serum lipid levels and other cardiovascular risk factors in overweight and obese individuals following short-term, modest weight loss have been widely documented (65, 66). Randomized controlled trials suggest that modest weight loss and the associated cardiovascular benefits can be achieved through a variety of dieting modalities, including behavioral weight loss (67), popular commercial diet programs (i.e., Atkins, Weight Watchers) (68), and pharmacotherapy (69). Weight regain following episodes of weight loss, however, is not uncommon, and recent evidence suggests that cardiovascular health may be adversely affected by the magnitude of fat accumulation over time rather than weight cycling per se in obese individuals (70). While Graci et al. (70) found no association between cardiovascular variables and the number of previous dieting episodes (resulting in >5% weight loss), our findings suggest that metabolic functioning is associated with self-reported dietary restraint and dieting frequency in obese patients with BED, regardless of whether the self-reported dieting resulted in successful weight loss. Our findings yielded modest associations between self-reported dietary restraint and HDL cholesterol and the total/HDL cholesterol ratio, particularly in women, whereas no relationship was found between LDL cholesterol and self-reported dietary restraint. This is particularly noteworthy given recent evidence suggesting that the total/HDL cholesterol ratio is a more potent predictor of cardiovascular disease than other lipid measures in men and women (71, 72). Our findings suggest that frequent attempts at dietary restraint, independent of actual weight status, may have a positive impact on cardiovascular health in obese BED patients and are consistent with longitudinal evidence suggesting that merely “trying to diet” is associated with lower mortality rates over a 9-year period, regardless of actual weight loss (73).

Our findings are important to consider in the context of the considerable controversy that surrounds self-report measures of dietary restraint. Research has found that self-reported dietary restraint prospectively predicts bulimic and binge eating behaviors (74, 75), and predicts outcomes such as weight loss in clinical trials (46). In contrast, laboratory and observational studies of eating behaviors and caloric intake have consistently found no relationship between various measures of self-reported dietary restraint and actual caloric intake in single meals, one day eating episodes, or short-term eating behavior, ranging between 2 weeks and 3 months (39, 47, 76). Moreover, some naturalistic longitudinal studies have found that self-reported dietary restraint prospectively predicts weight gain rather than weight loss (77). One hypothesis proposed for these discrepant findings is that dietary restraint scales may be measuring a relative reduction in caloric intake rather than an absolute reduction that would be necessary to achieve a negative energy balance (76). Although the evidence is convincing that dietary restraint measures are not an accurate assessment of negative energy balance, the findings of our study suggest that self-reported dietary restraint does appear to measure something that is clinically meaningful. In fact, it is striking that one item assessing self-reported frequency of time spent dieting in adulthood produced robust differences across historical, psychological, and metabolic variables in our sample of obese BED patients.

Although our study has several strengths, including the use of standardized diagnostic interviews, inclusion of men and women, and the assessment of metabolic functioning, several limitations of our study warrant discussion. Our study group comprised of treatment-seeking, class II obese BED patients, and the generalizability of our findings to other groups (non-treatment seeking, community samples, other classes of obesity, etc.) is uncertain. The reliance on self-report measures, particularly for retrospectively assessing dieting behaviors, is also a limitation. We note, however, that our separate substudy of the 1-week test–retest reliability of the QEWP-R revealed that the dieting frequency variable had a reliability coefficient of 0.87. These findings converge with those from a previous study that obese patients can reliably report the number of previous diets (defined as diets resulting in least a 10 lb weight loss) over a 9-month period (r = 0.77; (78)). We emphasize, however, that the validity of these recall methods is currently unknown. Additional psychometric research is needed to improve the measurement of this construct. It is also possible that patients’ reports of dieting frequency could have been influenced by their current functioning. Finding meaningful differences between the dieting frequency groups on metabolic variables in addition to the historical and psychological variables, however, argues against this reporting bias. Prospective studies are needed to clarify the cross-sectional findings reported here (29).

With these potential limitations in mind, we tentatively offer a number of conclusions. Self-reported dieting frequency in obese BED patients is a clinically relevant variable that delineates robust differences on a wide range of historical, psychological, and metabolic variables in both men and women. Our findings are consistent with a large body of research that has found that frequent dieting is associated with several negative psychological outcomes (i.e., elevated eating concerns and body image dissatisfaction). Importantly, however, we found new evidence to suggest that consistent dieting efforts, particularly in females, may have beneficial effects on metabolic functioning and cardiovascular disease risk independent of current BMI. These findings may have important implications and raise complex issues pertaining to the clinical advice that be given to obese patients with BED. On one hand, frequent dieting is of concern because it has been associated with elevated eating disorder psychopathology. Our findings, however, also suggest that these concerns be tempered with the potential health benefits associated with frequent dieting attempts regardless of the patient’s weight status or weight loss success with the diet. We emphasize that our findings are preliminary, and much more research is needed to better understand the etiological, physiological, and treatment implications of frequent dieting in obese BED and non-BED individuals.

ACKNOWLEDGMENTS

We were supported by grants from the National Institutes of Health (K24 DK070052, K23 DK071646, R01 DK49587, R01 DK073542, and R21 MH077290). No additional funding was received for the completion of this work.

Footnotes

DISCLOSURE

The authors declared no conflict of interest.

REFERENCES

  • 1.Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295:1549–1555. doi: 10.1001/jama.295.13.1549. [DOI] [PubMed] [Google Scholar]
  • 2.James PT, Leach R, Kalamara E, Shayeghi M. The worldwide obesity epidemic. Obes Res. 2001;9(Suppl 4):S228–S233. doi: 10.1038/oby.2001.123. [DOI] [PubMed] [Google Scholar]
  • 3.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;61:348–358. doi: 10.1016/j.biopsych.2006.03.040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Hudson JI, Lalonde JK, Berry JM, et al. Binge-eating disorder as a distinct familial phenotype in obese individuals. Arch Gen Psychiatry. 2006;63:313–319. doi: 10.1001/archpsyc.63.3.313. [DOI] [PubMed] [Google Scholar]
  • 5.Allison KC, Grilo CM, Masheb RM, Stunkard AJ. Binge eating disorder and night eating syndrome: a comparative study of disordered eating. J Consult Clin Psychol. 2005;73:1107–1115. doi: 10.1037/0022-006X.73.6.1107. [DOI] [PubMed] [Google Scholar]
  • 6.Grilo CM, Hrabosky JI, White MA, et al. Overvaluation of shape and weight in binge eating disorder and overweight controls: refinement of a diagnostic construct. J Abnorm Psychol. 2008;117:414–419. doi: 10.1037/0021-843X.117.2.414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Antony MM, Johnson WG, Carr-Nangle RE, Abel JL. Psychopathology correlates of binge eating and binge eating disorder. Compr Psychiatry. 1994;35:386–392. doi: 10.1016/0010-440x(94)90280-1. [DOI] [PubMed] [Google Scholar]
  • 8.Grucza RA, Przybeck TR, Cloninger CR. Prevalence and correlates of binge eating disorder in a community sample. Compr Psychiatry. 2007;48:124–131. doi: 10.1016/j.comppsych.2006.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Telch CF, Stice E. Psychiatric comorbidity in women with binge eating disorder: prevalence rates from a non-treatment-seeking sample. J Consult Clin Psychol. 1998;66:768–776. doi: 10.1037//0022-006x.66.5.768. [DOI] [PubMed] [Google Scholar]
  • 10.Rieger E, Wilfley DE, Stein RI, Marino V, Crow SJ. A comparison of quality of life in obese individuals with and without binge eating disorder. Int J Eat Disord. 2005;37:234–240. doi: 10.1002/eat.20101. [DOI] [PubMed] [Google Scholar]
  • 11.Wilfley DE, Schwartz MB, Spurrell EB, Fairburn C. Using the eating disorder examination to identify the specific psychopathology of binge eating disorder. Int J Eat Disord. 2000;27:259–269. doi: 10.1002/(sici)1098-108x(200004)27:3<259::aid-eat2>3.0.co;2-g. [DOI] [PubMed] [Google Scholar]
  • 12.Case T, Lemieux S, Kennedy SH, Lewis GF. Elevated plasma lipids in patients with binge eating disorders are found only in those who are anorexic. Int J Eat Disord. 1999;25:187–193. doi: 10.1002/(sici)1098-108x(199903)25:2<187::aid-eat8>3.0.co;2-9. [DOI] [PubMed] [Google Scholar]
  • 13.Sullivan PF, Gendall KA, Bulik CM, Carter FA, Joyce PR. Elevated total cholesterol in bulimia nervosa. Int J Eat Disord. 1998;23:425–432. doi: 10.1002/(sici)1098-108x(199805)23:4<425::aid-eat10>3.0.co;2-v. [DOI] [PubMed] [Google Scholar]
  • 14.Adami GF, Gandolfo P, Bauer B, Scopinaro N. Binge-eating in massively obese patients undergoing bariatric surgery. Int J Eat Disord. 1995;17:45–50. doi: 10.1002/1098-108x(199501)17:1<45::aid-eat2260170106>3.0.co;2-s. [DOI] [PubMed] [Google Scholar]
  • 15.Wadden TA, Foster GD, Letizia KA, Wilk JE. Metabolic, anthropometric, and psychological characteristics of obese binge eaters. Int J Eat Disord. 1993;14:17–25. doi: 10.1002/1098-108x(199307)14:1<17::aid-eat2260140103>3.0.co;2-l. [DOI] [PubMed] [Google Scholar]
  • 16.Brody ML, Walsh BT, Devlin MJ. Binge eating disorder: reliability and validity of a new diagnostic category. J Consult Clin Psychol. 1994;62:381–386. doi: 10.1037//0022-006x.62.2.381. [DOI] [PubMed] [Google Scholar]
  • 17.Grilo CM, Masheb RM. Onset of dieting vs binge eating in outpatients with binge eating disorder. Int J Obes Relat Metab Disord. 2000;24:404–409. doi: 10.1038/sj.ijo.0801171. [DOI] [PubMed] [Google Scholar]
  • 18.Grilo CM, Masheb RM, Wilson GT. Subtyping binge eating disorder. J Consult Clin Psychol. 2001;69:1066–1072. doi: 10.1037//0022-006x.69.6.1066. [DOI] [PubMed] [Google Scholar]
  • 19.Manwaring JL, Hilbert A, Wilfley DE, et al. Risk factors and patterns of onset in binge eating disorder. Int J Eat Disord. 2006;39:101–107. doi: 10.1002/eat.20208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Reas DL, Grilo CM. Timing and sequence of the onset of overweight, dieting, and binge eating in overweight patients with binge eating disorder. Int J Eat Disord. 2007;40:165–170. doi: 10.1002/eat.20353. [DOI] [PubMed] [Google Scholar]
  • 21.Field AE, Manson JE, Laird N, et al. Weight cycling and the risk of developing type 2 diabetes among adult women in the United States. Obes Res. 2004;12:267–274. doi: 10.1038/oby.2004.34. [DOI] [PubMed] [Google Scholar]
  • 22.Marchesini G, Cuzzolaro M, Mannucci E, et al. Weight cycling in treatmentseeking obese persons: data from the QUOVADIS study. Int J Obes Relat Metab Disord. 2004;28:1456–1462. doi: 10.1038/sj.ijo.0802741. [DOI] [PubMed] [Google Scholar]
  • 23.Venditti EM, Wing RR, Jakicic JM, Butler BA, Marcus MD. Weight cycling, psychological health, and binge eating in obese women. J Consult Clin Psych. 1996;64:400–405. doi: 10.1037//0022-006x.64.2.400. [DOI] [PubMed] [Google Scholar]
  • 24.Womble LG, Williamson DA, Martin CK, et al. Psychosocial variables associated with binge eating in obese males and females. Int J Eat Disord. 2001;30:217–221. doi: 10.1002/eat.1076. [DOI] [PubMed] [Google Scholar]
  • 25.Dalle Grave R, Todisco P, Oliosi M, Marchi S. Binge eating disorder and weight cycling in obese women. Eat Dis J Treat Prev. 1996;4:67. [Google Scholar]
  • 26.Bartlett SJ, Wadden TA, Vogt RA. Psychosocial consequences of weight cycling. J Consult Clin Psychol. 1996;64:587–592. doi: 10.1037//0022-006x.64.3.587. [DOI] [PubMed] [Google Scholar]
  • 27.Kuehnel RH, Wadden TA. Binge eating disorder, weight cycling, and psychopathology. Int J Eat Disord. 1994;15:321–329. doi: 10.1002/eat.2260150403. [DOI] [PubMed] [Google Scholar]
  • 28.Spitzer RL, Yanovski S, Wadden T, et al. Binge eating disorder: its further validation in a multisite study. Int J Eat Disord. 1993;13:137–153. [PubMed] [Google Scholar]
  • 29.National Task Force on the Prevention and Treatment of Obesity.Dieting and the development of eating disorders in overweight and obese adults. Arch Intern Med. 2000;160:2581–2589. doi: 10.1001/archinte.160.17.2581. [DOI] [PubMed] [Google Scholar]
  • 30.Wadden TA, Foster GD, Sarwer DB, et al. Dieting and the development of eating disorders in obese women: results of a randomized controlled trial. Am J Clin Nutr. 2004;80:560–568. doi: 10.1093/ajcn/80.3.560. [DOI] [PubMed] [Google Scholar]
  • 31.Gibbons LM, Sarwer DB, Crerand CE, et al. Previous weight loss experiences of bariatric surgery candidates: how much have patients dieted prior to surgery? Surg Obes Relat Dis. 2006;2:159–164. doi: 10.1016/j.soard.2006.03.013. [DOI] [PubMed] [Google Scholar]
  • 32.Guerdjikova AI, McElroy SL, Kotwal R, Stanford K, Keck PE Jr. Psychiatric and metabolic characteristics of childhood versus adult-onset obesity in patients seeking weight management. Eat Behav. 2007;8:266–276. doi: 10.1016/j.eatbeh.2006.11.001. [DOI] [PubMed] [Google Scholar]
  • 33.American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 4th edn. Washington, DC: 1994. [Google Scholar]
  • 34.First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders—Patient Version (SCID-I/P) New York, NY: NY State Psychiatric Institute; 1996. [Google Scholar]
  • 35.Fairburn CG, Cooper Z. The Eating Disorder Examination. In: Fairburn CG, Wilson GT, editors. Binge Eating: Nature, Assessment, and Treatment. 12th edn. New York, NY: Guilford Press; 1993. pp. 317–360. [Google Scholar]
  • 36.Grilo CM, Masheb RM, Lozano-Blanco C, Barry DT. Reliability of the Eating Disorder Examination in patients with binge eating disorder. Int J Eat Disord. 2004;35:80–85. doi: 10.1002/eat.10238. [DOI] [PubMed] [Google Scholar]
  • 37.Grilo CM, Masheb RM, Wilson GT. A comparison of different methods for assessing the features of eating disorders in patients with binge eating disorder. J Consult Clin Psychol. 2001;69:317–322. doi: 10.1037//0022-006x.69.2.317. [DOI] [PubMed] [Google Scholar]
  • 38.Grilo CM, Lozano C, Elder KA. Inter-rater and test-retest reliability of the Spanish language version of the eating disorder examination interview: clinical and research implications. J Psychiatr Pract. 2005;11:231–240. doi: 10.1097/00131746-200507000-00003. [DOI] [PubMed] [Google Scholar]
  • 39.Sysko R, Timothy Walsh B, Terence Wilson G. Expectancies, dietary restraint, and test meal intake among undergraduate women. Appetite. 2007;49:30–37. doi: 10.1016/j.appet.2006.11.002. [DOI] [PubMed] [Google Scholar]
  • 40.Beck AT, Steer R. Manual for Revised Beck Depression Inventory. New York, NY: Psychological Corporation; 1987. [Google Scholar]
  • 41.Watson D, Clark LA. Negative affectivity: the disposition to experience aversive emotional states. Psychol Bull. 1984;96:465–490. [PubMed] [Google Scholar]
  • 42.Fechner-Bates S, Coyne JC, Schwenk TL. The relationship of self-reported distress to depressive disorders and other psychopathology. J Consult Clin Psychol. 1994;62:550–559. doi: 10.1037//0022-006x.62.3.550. [DOI] [PubMed] [Google Scholar]
  • 43.Beck AT, Steer R, Garbin MG. Psychometric properties of the Beck Depression Inventory: 25 years of evaluation. Clin Psych Rev. 1988;8:77–100. [Google Scholar]
  • 44.Stunkard AJ, Messick S. The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J Psychosom Res. 1985;29:71–83. doi: 10.1016/0022-3999(85)90010-8. [DOI] [PubMed] [Google Scholar]
  • 45.Safer DL, Agras WS, Lowe MR, Bryson S. Comparing two measures of eating restraint in bulimic women treated with cognitive-behavioral therapy. Int J Eat Disord. 2004;36:83–88. doi: 10.1002/eat.20008. [DOI] [PubMed] [Google Scholar]
  • 46.Foster GD, Wadden TA, Swain RM, et al. The Eating Inventory in obese women: clinical correlates and relationship to weight loss. Int J Obes Relat Metab Disord. 1998;22:778–785. doi: 10.1038/sj.ijo.0800659. [DOI] [PubMed] [Google Scholar]
  • 47.Stice E, Fisher M, Lowe MR. Are dietary restraint scales valid measures of acute dietary restriction? Unobtrusive observational data suggest not. Psychol Assess. 2004;16:51–59. doi: 10.1037/1040-3590.16.1.51. [DOI] [PubMed] [Google Scholar]
  • 48.Hrabosky JI, Masheb RM, White MA, Grilo CM. Overvaluation of shape and weight in binge eating disorder. J Consult Clin Psychol. 2007;75:175–180. doi: 10.1037/0022-006X.75.1.175. [DOI] [PubMed] [Google Scholar]
  • 49.Masheb RM, Grilo CM. The nature of body image disturbance in patients with binge eating disorder. Int J Eat Disord. 2003;33:333–341. doi: 10.1002/eat.10139. [DOI] [PubMed] [Google Scholar]
  • 50.Cooper PJ, Taylor MJ, Cooper Z, Fairburn CG. The development and validation of the Body Shape Questionnaire. Int J Eat Disord. 1987;6:485–494. [Google Scholar]
  • 51.Rosen JC, Jones A, Ramirez E, Waxman S. Body Shape Questionnaire: studies of validity and reliability. Int J Eat Disord. 1996;20:315–319. doi: 10.1002/(SICI)1098-108X(199611)20:3<315::AID-EAT11>3.0.CO;2-Z. [DOI] [PubMed] [Google Scholar]
  • 52.Yanovski S. Binge eating disorder: current knowledge and future directions. Obes Res. 1993;1:306–324. doi: 10.1002/j.1550-8528.1993.tb00626.x. [DOI] [PubMed] [Google Scholar]
  • 53.Nangle DW, Johnson WG, Carr-Nangle RE, Engler LB. Binge eating disorder and the proposed DSM-IV criteria: psychometric analysis of the Questionnaire of Eating and Weight Patterns. Int J Eat Disord. 1994;16:147–157. doi: 10.1002/1098-108x(199409)16:2<147::aid-eat2260160206>3.0.co;2-p. [DOI] [PubMed] [Google Scholar]
  • 54.Johnson WG, Kirk AA, Reed AE. Adolescent version of the questionnaire of eating and weight patterns: reliability and gender differences. Int J Eat Disord. 2001;29:94–96. doi: 10.1002/1098-108x(200101)29:1<94::aid-eat16>3.0.co;2-8. [DOI] [PubMed] [Google Scholar]
  • 55.Lowe MR. The effects of dieting on eating behavior: a three-factor model. Psychol Bull. 1993;114:100–121. doi: 10.1037/0033-2909.114.1.100. [DOI] [PubMed] [Google Scholar]
  • 56.Rosenberg M. Conceiving the self. New York: Basic Books; 1979. [Google Scholar]
  • 57.Griffiths RA, Beumont PJ, Giannakopoulos E, et al. Measuring self-esteem in dieting disordered patients: the validity of the Rosenberg and Coopersmith contrasted. Int J Eat Disord. 1999;25:227–231. doi: 10.1002/(sici)1098-108x(199903)25:2<227::aid-eat13>3.0.co;2-4. [DOI] [PubMed] [Google Scholar]
  • 58.Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III) JAMA. 2001;285:2486–2497. doi: 10.1001/jama.285.19.2486. [DOI] [PubMed] [Google Scholar]
  • 59.Grundy SM, Cleeman JI, Merz CN, et al. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III Guidelines. J Am Coll Cardiol. 2004;44:720–732. doi: 10.1016/j.jacc.2004.07.001. [DOI] [PubMed] [Google Scholar]
  • 60.Barry DT, Grilo CM, Masheb RM. Gender differences in patients with binge eating disorder. Int J Eat Disord. 2002;31:63–70. doi: 10.1002/eat.1112. [DOI] [PubMed] [Google Scholar]
  • 61.Nolen-Hoeksema S. Sex Differences in Depression. Stanford, CA: Stanford University Press; 1990. [Google Scholar]
  • 62.Brown CD, Higgins M, Donato KA, et al. Body mass index and the prevalence of hypertension and dyslipidemia. Obes Res. 2000;8:605–619. doi: 10.1038/oby.2000.79. [DOI] [PubMed] [Google Scholar]
  • 63.Mokdad AH, Ford ES, Bowman BA, et al. Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001. JAMA. 2003;289:76–79. doi: 10.1001/jama.289.1.76. [DOI] [PubMed] [Google Scholar]
  • 64.Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA. 2002;287:356–359. doi: 10.1001/jama.287.3.356. [DOI] [PubMed] [Google Scholar]
  • 65.Noakes M, Clifton PM. Weight loss and plasma lipids. Curr Opin Lipidol. 2000;11:65–70. doi: 10.1097/00041433-200002000-00010. [DOI] [PubMed] [Google Scholar]
  • 66.Van Gaal LF, Wauters MA, De Leeuw IH. The beneficial effects of modest weight loss on cardiovascular risk factors. Int J Obes Relat Metab Disord. 1997;21(Suppl 1):S5–S9. [PubMed] [Google Scholar]
  • 67.Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults—The Evidence Report. National Institutes of Health. Obes Res. 1998;6(Suppl 2):S51–S209. [PubMed] [Google Scholar]
  • 68.Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: a randomized trial. JAMA. 2005;293:43–53. doi: 10.1001/jama.293.1.43. [DOI] [PubMed] [Google Scholar]
  • 69.Padwal R, Li SK, Lau DC. Long-term pharmacotherapy for obesity and overweight. Int J Obes. 2003;27:1437–1446. doi: 10.1038/sj.ijo.0802475. [DOI] [PubMed] [Google Scholar]
  • 70.Graci S, Izzo G, Savino S, et al. Weight cycling and cardiovascular risk factors in obesity. Int J Obes Relat Metab Disord. 2004;28:65–71. doi: 10.1038/sj.ijo.0802537. [DOI] [PubMed] [Google Scholar]
  • 71.Lemieux I, Lamarche B, Couillard C, et al. Total cholesterol/HDL cholesterol ratio vs LDL cholesterol/HDL cholesterol ratio as indices of ischemic heart disease risk in men: the Quebec Cardiovascular Study. Arch Intern Med. 2001;161:2685–2692. doi: 10.1001/archinte.161.22.2685. [DOI] [PubMed] [Google Scholar]
  • 72.Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000;342:836–843. doi: 10.1056/NEJM200003233421202. [DOI] [PubMed] [Google Scholar]
  • 73.Gregg EW, Gerzoff RB, Thompson TJ, Williamson DF. Intentional weight loss and death in overweight and obese U.S. adults 35 years of age and older. Ann Intern Med. 2003;138:383–389. doi: 10.7326/0003-4819-138-5-200303040-00007. [DOI] [PubMed] [Google Scholar]
  • 74.Stice E. A prospective test of the dual-pathway model of bulimic pathology: mediating effects of dieting and negative affect. J Abnorm Psychol. 2001;110:124–135. doi: 10.1037//0021-843x.110.1.124. [DOI] [PubMed] [Google Scholar]
  • 75.Stice E, Presnell K, Spangler D. Risk factors for binge eating onset in adolescent girls: a 2-year prospective investigation. Health Psychol. 2002;21:131–138. [PubMed] [Google Scholar]
  • 76.Stice E, Cooper JA, Schoeller DA, Tappe K, Lowe MR. Are dietary restraint scales valid measures of moderate- to long-term dietary restriction? Objective biological and behavioral data suggest not. Psychol Assess. 2007;19:449–458. doi: 10.1037/1040-3590.19.4.449. [DOI] [PubMed] [Google Scholar]
  • 77.French SA, Jeffery RW, Forster JL, et al. Predictors of weight change over two years among a population of working adults: the Healthy Worker Project. Int J Obes Relat Metab Disord. 1994;18:145–154. [PubMed] [Google Scholar]
  • 78.Wadden TA, Bartlett S, Letizia KA, et al. Relationship of dieting history to resting metabolic rate, body composition, eating behavior, and subsequent weight loss. Am J Clin Nutr. 1992;56(1 Suppl):S203–S208. doi: 10.1093/ajcn/56.1.203S. [DOI] [PubMed] [Google Scholar]

RESOURCES