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Obesity and Quality of Life Consulting, 1004 Norwood Avenue, Durham, NC 27707. E-mail: rkolotkin@yahoo.com
Abstract
Objectives: To determine whether binge eating disorder (BED) impacts weight-related quality of life in obese individuals seeking weight loss treatment and to investigate the role of psychological symptoms, BMI, and demographic variables in the relationship between BED and weight-related quality of life.
Research Methods and Procedures: Three hundred seventeen women (BMI = 37.6) and 213 men (BMI = 41.3) completed questionnaires on admission into an intensive residential lifestyle modification program. Weight-related quality of life was assessed using the Impact of Weight on Quality of Life-Lite (IWQOL-Lite). The presence of BED was determined using the Questionnaire on Eating and Weight Patterns-Revised. Psychological symptoms were assessed using the Beck Depression Inventory and the global severity index of the Symptom Checklist 90-R.
Results: BED prevalence in this sample was 17.9%. Participants with BED, in comparison with those without BED, were more likely to be women (75.8% vs. 56.3%, p < 0.001), younger (45.0 vs. 49.7 years, p = 0.003), white (98.9% vs. 91.7%), heavier (BMI = 42.0 vs. 38.5, p = 0.002), psychologically distressed, and more impaired on total IWQOL-Lite (51.5 vs. 65.3, p < 0.001) and all IWQOL-Lite subscales. However, after controlling for demographic variables, BMI, and psychological symptoms, BED was not independently associated with weight-related quality of life.
Discussion: The association between BED and impairment in quality of life that has been previously reported in the literature may largely be accounted for by differences between those with and without BED on demographic variables, BMI, and psychological symptoms. BED does not seem to independently impact weight-related quality of life.
There has been strong interest in assessing the health-related quality of life (HRQOL)1 of obese persons in recent years (1,2,3,4). Indeed, “the impairment in an obese individual's capacity to live as fully and actively as he or she desires may be as serious a consequence as are its adverse effects on morbidity and mortality” (5). Impairments in HRQOL have been noted in obese persons on generic measures of HRQOL (6,7) and on measures that are specific to obesity (8,9,10). The physical aspects of quality of life are most impaired on generic measures of HRQOL (11), whereas on measures specific to obesity (i.e., weight-related quality of life), both physical and psychosocial domains are affected (8,12).
It is a simple assumption that most overweight and obese persons have impaired quality of life. However, certain factors are more easily associated with reduced quality of life than others in persons who are overweight or obese (13,14). These factors include gender (15,16,17), degree of overweight (18), race (15,16), age (19), depression (20), pain (14,20,21), comorbid conditions (11,14,22), and treatment-seeking status (15,23). Determining which factors are associated with poorer quality of life in obese persons may help clinicians identify those patients who are most distressed by their obesity and, therefore, most in need of assistance. Little is known about the role of binge eating disorder (BED) in the HRQOL of obese persons.
The prevalence of BED among obese persons seeking weight reduction treatment typically ranges from 16% to 30% (24) but has been found to be as high as 50% (25) and as low as 3% (26). Obese binge eaters who seek treatment report greater psychological distress than obese treatment seekers who are not binge eaters (25,27). To our knowledge, only three studies have assessed the impact of BED on quality of life, with all three finding evidence of quality-of-life impairment associated with BED. In a study of outpatients seeking cognitive behavior therapy for obesity, there was a significant relationship between BED and HRQOL impairments on a generic measure of HRQOL Medical Outcomes Study Short Form-36 (SF-36), particularly with respect to domains assessing mental health (28). In a study of patients seeking bariatric surgery, patients with BED, as compared with those without BED, had poorer quality of life on three subscales of the SF-36, two of which assessed aspects of mental health (29). In another study of patients seeking bariatric surgery (30), patients with BED reported more impaired quality of life than patients without BED on four scales of the SF-36, three of which were related to mental health. These differences, however, diminished somewhat after controlling for depression and self-esteem. In the same study, patients with BED also differed significantly from those without BED on total score and three of five subscales on a measure of weight-related quality of life [Impact of Weight on Quality of Life-Lite (IWQOL-Lite)], even after controlling for depression and self-esteem.
The limited number of studies on the role of binge eating in the quality of life of obese persons suggests that this is a fruitful area in need of further investigation. The present study had two objectives: to determine whether BED impacts weight-related quality of life in obese individuals seeking treatment for their obesity, and to investigate the role of psychological symptoms, BMI, and demographic variables in the relationship between BED and weight-related quality of life.
Research Methods and Procedures
Participants
On admission, consecutive attendees (n = 819) at the Duke Diet and Fitness Center, an intensive residential program for weight loss and lifestyle modification, completed a packet of questionnaires containing the measures described below. For the present study, we analyzed data from 530 subjects (317 women and 213 men) who completed all questionnaires. There were no differences between those who completed all questionnaires and those who did not in terms of age (48.8 vs. 47.6 years, t = 0.86, df = 646, p = 0.388), percent women (60.2% vs. 58.3%, Fisher's Exact Test, p = 0.762), or BMI (39.1 vs. 40.0, t = 0.99, df = 626, p = 0.321).
The treatment program consisted of the following: individual assessments; group and individual counseling; nutritionally balanced and calorie-reduced meals; supervised exercise; the practice of mindfulness; and participation in educational classes on health, nutrition, physical activity, the body-mind connection, and cognitive-behavioral strategies for lifestyle modification and weight loss.
Measures
The clinic nurse obtained heights and weights from participants on their admission to the treatment program. Participants also completed an assessment battery at the beginning of treatment consisting of the following measures.
IWQOL-Lite
The IWQOL-Lite is a 31-item self-report measure of weight-related quality of life that provides scores on five domains (physical function, self-esteem, sexual life, public distress, and work) plus a total score (31). The IWQOL-Lite has been shown to have good internal consistency (ranging from 0.90 to 0.96) (31), good test-retest reliability (0.83 to 0.94) (12), sensitivity to weight loss and weight gain (32,33), and a scale structure supported by confirmatory factor analysis (31).
Participants in this study completed the original long form (74 items) of this measure (IWQOL) (19,34). However, scores were calculated based on the subset of 31 items that comprise the IWQOL-Lite (31). Previous research on the IWQOL-Lite (31,32) has reported results in terms of raw scores, where higher scores indicate greater impairment in quality of life. Scoring for the present paper is based on transformed scores ranging from 0 to 100, with 100 representing the best and 0 the worst quality of life.
Questionnaire on Eating and Weight Patterns-Revised (QEWP-R)
The QEWP-R was used to identify participants with and without BED. The QEWP-R (35) is a self-report instrument designed to assess the presence or absence of binge episodes in accordance with DSM criteria. Specific items of the QEWP-R (items 10 to 13, 15, and 16) correspond to DSM criteria for BED. For example, item 10 on the QEWP-R, which asks about eating “what most people would regard as an unusually large amount of food,” corresponds to DSM criterion A.1. The diagnosis of BED was made by applying the DSM algorithm for BED to the QEWP-R responses to these items. The diagnosis of BED made from the QEWP-R has been shown to be moderately stable over a 3-week interval (36).
Beck Depression Inventory (BDI)
The BDI is a 21-item questionnaire that measures specific symptoms of depression and has well-established psychometric properties (37).
Symptom Checklist 90-R (SCL-90-R)
The SCL-90 is a 90-item multidimensional self-report inventory designed to screen for a broad range of psychological problems and symptoms of psychopathology (38). For the present study, we analyzed scores from only the global severity index (GSI) of the SCL-90. The GSI is a measure of psychological distress that combines information about the number of symptoms endorsed and the intensity of the distress.
Statistical Analyses
Differences between men and women in rates of BED were compared using Fisher's exact test. Participants with and without BED were compared on continuous measures (age, BMI, BDI, SCL-90, and IWQOL-Lite) using independent sample Student's t tests and on dichotomous measures (gender and ethnicity) using Fisher's exact test. A series of general linear models were performed using demographic variables (gender, age, and ethnicity), psychological symptoms (BDI and SCL-90), BED, and gender-by-BED interaction to predict IWQOL-Lite scales and total score. The relative contribution of each predictor was evaluated using partial η2, a measure of the proportion of unique criterion variance accounted for by each predictor variable. All comparisons were evaluated using an α of 0.05. The software used for data analysis was SPSS/PC statistical program (version 12.0 for Windows; SPSS, Inc., Chicago, IL).
Results
Sample Characteristics
Baseline characteristics of the sample are presented in Table 1. The average BMI at entry into the program was 37.6 for women and 41.3 for men. On average, participants were middle aged (46.8 years for women and 52.1 years for men) and predominantly white (93% of the sample). Although we did not specifically assess socioeconomic status, participants in this program tended to be from the uppermost socioeconomic levels.
Table 1. Baseline characteristics of the study sample
Variable
Women
Men
Overall
N
317
213
530
Age (mean, SD)
46.8 (14.2)
52.1 (13.4)
48.9 (14.1)
White (N, %)
295 (93.4%)
197 (92.5%)
492 (93.0%)
BMI (mean, SD)
37.6 (9.6)
41.3 (11.1)
39.1 (10.4)
BED (N, %)
72 (22.7%)
23 (10.8%)
95 (17.9%)
Prevalence of BED
Overall prevalence of BED for the sample was 17.9%. Prevalence of BED for women was significantly higher than for men (22.7% vs. 10.8%, Fisher's exact p < 0.001) (Table 1).
BED vs. nonBED
Comparisons between BED and nonBED participants are presented in Table 2. Those with BED were, on average, more likely to be women (75.8% vs. 56.3%), younger (45.0 vs. 49.7), white (98.9% vs. 91.7%), heavier (42.0 vs. 38.5), psychologically distressed, and more impaired on all IWQOL-Lite scales and total score.
Table 2. Comparison of BED vs. no BED
Variable
BED (n = 95)
No BED (n = 435)
Significance
*
Lower scores indicate greater impairment in HRQOL.
Table 3 presents results of the general linear models for predicting IWQOL-Lite scores from demographic variables, BMI, measures of psychological distress, and BED status. Cell entries in Table 3 (partial η2 values) represent the unique effects of each predictor variable after controlling for all of the other variables. Adjusted R2 values indicate the percentage of variance accounted for by this set of predictor variables.
Table 3. Linear models predicting IWQOL-Lite scores
The total adjusted R2 value was 0.606 for IWQOL-Lite total score, indicating that over 60% of the variance in IWQOL-Lite total score could be accounted for by this set of variables. For individual IWQOL-Lite scales, total adjusted R2 values ranged from 0.223 to 0.588, indicating that these variables were better able to predict some IWQOL-Lite domains than others. Although over 50% of the variance for physical function, self-esteem, and public distress could be accounted for by these predictor variables, the models for sexual life and work were much less robust, accounting for 22% and 33% of the variance, respectively. This suggests that these domains (sexual life and work) are much less influenced by these predictor variables than are other domains.
Demographic Variables
Gender accounted for a significant portion of the variance for all IWQOL-Lite scores, with the exception of work. The contribution of gender to IWQOL-Lite scores, although small, was highest for total score and self-esteem (just over 3%). Women reported poorer quality of life for self-esteem, sexual life, and total score, whereas men reported poorer quality of life for physical function and public distress. Age was significantly associated with all IWQOL-Lite scales, accounting for over 15% of the variance in physical function, over 9% of the variance in self-esteem, and over 4% of the variance in sexual life. Higher age was associated with poorer quality of life with respect to physical function (r = −0.211) and sexual life (r = −0.122) but better quality of life with respect to self-esteem (r = 0.341). Ethnicity was significantly associated only with self-esteem, with nonwhites reporting better quality of life (mean = 67.9 vs. 56.9).
BMI
BMI was significantly and negatively associated with all IWQOL-Lite scores, accounting for 34.1% of the variance in IWQOL-Lite total score, 44.5% of the variance in public distress, and 35.2% of the variance in physical function. However, BMI accounted for much smaller portions of the variance in the other IWQOL-Lite scales. The associations between IWQOL-Lite scores and BMI were much stronger for public distress (r = −0.679), physical function (r = −0.575), and total score (r = −0.561) than for self-esteem (r = −0.295), work (r = −0.238), and sexual life (r = −0.178).
Psychological Symptoms
Psychological symptoms, as measured by the BDI and SCL-90 GSI, were significantly and negatively associated with all IWQOL-Lite scores. The variance in IWQOL-Lite total score accounted for by psychological symptoms was 12.9% for the GSI and 9.5% for the BDI, representing the second largest contribution to IWQOL-Lite total score after BMI. With respect to individual IWQOL-Lite scales, the GSI accounted for 5.0% to 9.4% of the variance, whereas the BDI accounted for 1.8% to 13.0%, with depression contributing more to self-esteem (13.0% of the variance) and work (8.6%) than to the other scales.
BED Status
Surprisingly, after controlling for the influence of these other variables, BED status did not account for a significant portion of the variance for any IWQOL-Lite score. However, the gender-by-BED interaction was significant for total IWQOL-Lite score, physical function, and public distress, accounting for 1.2%, 1.4%, and 1.2% of the variance, respectively. In all cases, women were more adversely affected in terms of quality of life by BED than were men.
Discussion
The major finding of this study was that observed differences in weight-related quality of life between obese persons with and without BED were accounted for largely by differences in demographic variables, BMI, and psychological symptoms. Participants with BED, in comparison with those without BED, were more likely to be women, younger, white, heavier, and more distressed psychologically. This study provided little evidence that BED, in and of itself, adversely impacts weight-related HRQOL. Although there was some evidence to suggest that BED may have deleterious effects on weight-related HRQOL for women, this effect was quite small in the current sample.
Although our findings were consistent with earlier reports indicating an association between BED and HRQOL impairment (28,29,30), the present study expanded the previous findings by identifying factors that seem to explain this association. Results of the present study suggested that factors other than BED (i.e., BMI, psychological symptoms, and demographic variables) explained the association that has been reported between BED and quality of life. Because earlier studies did not control for pertinent variables, the implication that the presence of BED itself accounts for the observed differences in quality of life may not be correct. Although the study by de Zwaan et al. (30) did control for psychological symptoms (depression and self-esteem), they did not control for other relevant variables, and their study sample was limited to women. In the study by Hsu et al. (29), those with BED did not differ from those without BED on age, gender, or BMI, perhaps because participants in the study all had extreme obesity.
Consistent with previous studies on BED (39,40,41,42,43), we also found higher rates of depression and psychological symptoms among obese persons with BED than among those without BED. Although participants with BED reported poorer quality of life than those without BED, it appears that the presence of depression and other psychological symptoms may have contributed to this finding more than the presence of BED itself. In a recent review paper on BED by Stunkard and Allison (44), the authors conclude that the greatest value of the BED diagnosis may be as a marker of psychopathology, proposing that therapy should focus on the psychopathology associated with BED, rather than on the BED itself. The findings of the present study lend support to this notion.
A strength of the present study was the large sample size of 530 individuals, in contrast to the smaller sample sizes of earlier studies (28,29,30). Because of our large sample, we were able to evaluate the role of gender, psychological symptoms, and other important variables in the relationship between BED and weight-related quality of life.
A limitation of this study was that BED diagnoses were derived from a self-report measure without confirmation from a clinical interview. Although the QEWP-R is based on DSM criteria and is a widely used measure of BED in clinical research, self-report instruments may overestimate the presence of BED (44). It has been suggested that self-report measures be followed up with brief interviews to confirm the diagnosis of BED (45,46).
The lack of ethnic diversity in this study (93% of all participants were white) limited the generalization of the present findings to other ethnic groups. Previous studies of ethnic minorities have found differences in quality of life (15,16) and differences in the prevalence of BED (47,48) as compared with whites. In addition, the results may not generalize to obese persons from a broader spectrum of socioeconomic levels or to obese individuals who are not seeking treatment. Studies have shown that obese treatment seekers report poorer quality of life than obese persons not seeking treatment (15,23,49), as well as more binge eating and psychopathology (50).
An additional limitation of this study concerned the cross-sectional study design. Although the influence of the predictor variables could be accounted for statistically, the current design did not allow us to make strong causal inferences. Prospective studies are needed to further explore the relationship among BED, HRQOL, and these and other variables. Additionally, construct overlap may be an issue in the interpretation of our results. The impact of weight on quality of life could not be seen as fully distinct from BED (as measured by the QEWP-R) and from BDI and GSI. Also, there may be slight overlap among BED, BDI, and GSI.
In conclusion, participants with BED who are seeking weight loss treatment reported poorer weight-related quality of life on every domain than those without BED. However, participants with BED were also more likely to be women, younger, heavier, white, and psychologically distressed. After controlling for these variables, BED was not independently associated with weight-related quality of life. Thus, the association between BED and impairment in quality of life that has previously been reported in the literature may be accounted for largely by differences in BMI, demographic variables, and psychological symptoms. This study also lends support to previous research indicating that psychological distress (20), age (19), gender (15,16,17), ethnicity (15,16), and BMI (18) are important variables that influence whether obese persons are likely to experience impaired quality of life. Knowledge of these variables may allow clinicians to predict who among their obese patients are most likely to be distressed by their obesity and, therefore, most in need of intervention.
Acknowledgment
There was no funding/support for this study.
Footnotes
1
Nonstandard abbreviations: HRQOL, health-related quality of life; BED, binge eating disorder; IWQOL-Lite, Impact of Weight on Quality of Life-Lite; QEWP-R, Questionnaire on Eating and Weight Patterns-Revised; SLC-90-R, Symptom Checklist 90-R; GSI, global severity index; BDI, Beck Depression Inventory; SF-36, Medical Outcomes Study Short Form-36.
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