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. Author manuscript; available in PMC: 2020 Feb 1.
Published in final edited form as: Int J Eat Disord. 2019 Jan 28;52(2):159–165. doi: 10.1002/eat.23003

Examining physical activity and correlates in adults with healthy weight, overweight/obesity, or binge-eating disorder

Meagan M Carr 1, Janet A Lydecker 1, Marney A White 1,2, Carlos M Grilo 1,3
PMCID: PMC6396689  NIHMSID: NIHMS1009133  PMID: 30690763

Abstract

Objective:

To examine physical activity and correlates among three subgroups of adults: healthy weight without binge eating (HW), overweight/obesity without binge-eating (OW/OB), and core-features of binge-eating disorder (BED).

Method:

Participants (N=2,384) completed an online survey with established measures of physical activity, eating psychopathology, and health. Most participants were White (82.55%) women (66.65%). Participants were categorized into three study groups: HW (n = 948; 40%), OW/OB (n = 1,308;55%), and BED (n = 120;5%).

Results:

The BED group had the highest proportion of self-reported insufficiently active individuals (63.8%), followed by OW/OB (41.7%), and HW (29.2.%). Associations between self-reported physical activity, eating pathology, and health were generally small in HW and OW/OB groups, while associations were moderate in the BED group. Self-reported weekly bouts of physical activity were more strongly, positively related to self-reported physical health for OW/OB than HW, and this effect was even more pronounced for BED compared with HW or OW/OB.

Discussion:

This is the first study, to our knowledge, to demonstrate a stronger association between self-reported physical activity and physical health for individuals with BED compared with OW/OB alone. The high rate of physical inactivity and the strong association between physical activity and health among participants with BED suggest physical activity as an important treatment target for individuals with BED.

Keywords: Physical Activity, Binge-eating, Obesity

Introduction

Obesity, which has increased steadily among adults, represents a major public health problem (Flegal, Kruszon-Moran, Carroll, Fryar, & Ogden, 2016). Obesity is a complex heterogeneous medical condition with multiple causes and contributory factors (Keith et al., 2006) including insufficient physical expenditure (Church et al., 2011; Church & Martin, 2018; Sallis, Floyd, Rodriguez, & Saelens, 2012). Problematic eating patterns such as binge-eating disorder (BED), defined by recurrent episodes of eating unusually large quantities of food while experiencing a subjective sense of loss of control, are strongly associated with obesity in epidemiological studies in the US (Udo & Grilo, 2018) and world-wide (Kessler et al., 2013). Moreover, in treatment-seeking patients with obesity, BED is associated with increased weight gain trajectories (Ivezaj, Kalebjian, Grilo, & Barnes, 2014).

It is well-documented that patients with obesity have high levels of physical inactivity (Church & Martin, 2018), and the few available studies of patients with BED have suggested that they are also quite sedentary (Crandall, A. Eisenman, Ransdell, & Reel, 2012; Vancampfort et al., 2015; Vancampfort, De Herdt, et al., 2014). One study found that treatment-seeking individuals with obesity and BED exercised 15% less than their BMI-matched controls (Vancampfort, De Herdt, et al., 2014), and another study with a community sample reported reduced rates of physical activity (PA) in individuals with BED than without BED (Crandall et al., 2012). In contrast, other research with BED is mixed. One small study (27 patients with BED) found that primary care patients with BED did not differ from patients with obesity in amount of self-reported PA (Barber, Ivezaj, & Barnes, 2018). A single study, using objective measures of PA within a treatment-seeking sample, found that individuals with BED had higher levels of continuous bouts of moderate to vigorous PA as compared with a national cohort study in Norway (Mathisen et al., 2018).

It is well-established that PA has many benefits (Haskell et al., 2007; Leitzmann et al., 2007), in addition to weight control (Goodpaster et al., 2010) in individuals with obesity. However, little is known regarding the correlates of PA in people with BED (Vancampfort, Vanderlinden, et al., 2014). A systematic review found that more problematic body image attitudes and lower health-related quality of life were inversely associated with PA within individuals with BED (Vancampfort, Vanderlinden, et al., 2014), although the authors characterize the body of available literature as insufficient and lacking high-quality studies. In order to address this gap in the literature as well as to add evidence related to the mixed findings, the current study: 1) collected a large sample of community data with relevant comparison groups, including individuals with the primary psychopathology of BED, and individuals without BED with and without overweight; and 2) utilized a measure of self-reported physical activity that is validated using objective measures of health. We compared the three groups on self-reported PA (SR-PA) and explored their patterns of correlates of SR-PA. We hypothesized that SR-PA would be lower in BED than in both OW/OB and HW.

Methods

Participants

Participants (N = 2,384) were recruited from the Mechanical Turk website, an online recruitment platform that yields convenient and high-quality data. Recent comparisons suggest that the psychometric properties of data from Mechanical Turk participants do not differ in reliability or validity from participants recruited using traditional sources (Behrend, Sharek, Meade, & Wiebe, 2011). Participants responded to ads to complete an online survey about weight and eating. To be eligible to complete the survey, participants had to be at least 21 years old. This study was reviewed and approved by our university’s institutional review board and all participants provided informed consent. Data were collected between August 2015 and January 2017. Participants included 1,583 (66.65%) women and 792 (33.35%) men. Participants reported the following characteristics: 1,968 (82.55%) White, 58 (2.43%) Black, 248 (10.40%) Asian; and 110 (4.61%) “Other”; 190 (7.97%) identified as Hispanic or Latino and 2,194 (92.03%) non-Latino. Mean age and BMI were 35.65 (SD = 11.59) years and 28.11 (SD = 7.06) kg/m2, respectively. The 2,384 participants were categorized into the following three study group following our classification procedures: HW (n = 948; 39.9%), OW/OB (n = 1,308; 55.1%), and BED (n = 120; 5.1%). Study groups differed significantly on some demographic characteristics, although the effect sizes were generally small. BMI differences were large in magnitude, which reflects the use of BMI in classification algorithms.

Measures

Body Mass Index (BMI).

Participants reported their height and weight, which were used to calculate BMI.

Questionnaire on Eating and Weight Patterns 5 (QEWP-5).

The QEWP-5 assesses frequency of binge-eating episodes (i.e., eating an unusually large amount of food while feeling a sense of loss of control) as well as the associated features of BED as defined in the DSM-5, including the presence of two or more behavioral features of loss of control (e.g., eating rapidly or eating until uncomfortably full) and the absence of purging behaviors (Yanovski, Marcus, Wadden, & Walsh, 2014).

Eating Disorder Examination-Questionnaire (EDE-Q).

The EDE-Q retrospectively measures eating-disorder psychopathology over the past 28 days (Fairburn & Beglin, 1994). The current study used a brief version of the full scale, which has three subscales (Dietary Restraint, Overvaluation, and Dissatisfaction) and a Global scale. This brief version has demonstrated superior psychometric properties in nonclinical and clinical studies compared with those from the original measure (Grilo, Henderson, Bell, & Crosby, 2013; Grilo, Reas, Hopwood, & Crosby, 2015; Machado, Grilo, & Crosby, 2018). This brief version reduces items for the existing subscale of Dietary Restraint, while the Dissatisfaction subscale includes two items assessing dissatisfaction with weight and dissatisfaction with shape, and the Overvaluation subscale includes items assessing the importance of one’s shape and one’s weight (Grilo et al., 2013). Items yielded internally consistent subscales in the current study α = .89–91.

Godin Leisure Time Exercise Questionnaire (GLTEQ).

The GLTEQ assesses the frequency of SR-PA across intensities (mild, moderate, strenuous) during a typical week (Godin & Shepard, 1985). Participants report the number of times per week they spend more than 15 minutes engaged in each level of PA. In the current study, we used a sum of bouts of moderate and strenuous SR-PA, as defined by engaging in the activity for 15 minutes or more. We also categorized participants as sufficiently or insufficiently physically active according to the Amireault and Godin (2015) coding scheme: individuals reporting activity levels ≥24 metabolic equivalent units per week were considered sufficiently active. The validation study (Amireault & Godin, 2015) demonstrated convergent validity between their classification and external measures of fitness and activity: sufficiently active individuals had significantly higher VO2Max, lower body fat percentages, and went to the gym more frequently.

Medical Outcomes Study Short Form Health Survey–12 Item Version (SF-12).

The SF-12 is a twelve-item short form of the SF-36 that assesses physical and mental health functioning (Ware, Sherbourne, & Davies, 1992). The SF-12 demonstrates adequate psychometric properties across diverse samples, including individuals with obesity (Wee, Davis, & Hamel, 2008).

Patient Health Questionnaire-2 (PHQ-2).

The PHQ-2 is a two-item questionnaire that assesses depressed mood over the past two weeks (Kroenke, Spitzer, & Williams, 2003). The PHQ-2 is a short form of the PHQ-9 and demonstrates similar psychometric properties (Kroenke, Spitzer, & Williams, 2001). Items demonstrated good internal consistency (Cronbach’s α = .90).

Creation of Study Groups

Classification algorithms used QEWP-5 behavior items and BMI weight categories to classify participants into study groups. Participants in the healthy-weight group (HW; n = 948) had a BMI < 25 kg/m2 and denied weekly binge-eating episodes. Participants in the overweight/obesity group (OW/OB; n = 1308) had a BMI > 25 kg/m2 and denied weekly binge-eating episodes. Participants in the group demonstrating core features of binge-eating disorder (BED; n = 120) reported weekly binge-eating episodes, associated distress with binge eating episodes, and denied weekly purging behaviors.

Statistical Analyses

For mean group difference testing, Welch’s F was used (due to violations of the homogeneity of variance assumption); ω2 were used as a measures of effects size, which can be interpreted proportion of the total variance in the dependent variable that is accounted for by the levels of the independent variable; and Games-Howell post-hoc tests were used for multigroup comparisons. χ2 tests were used to compare groups on categorical variables, with “number needed to treat (NNT) used as the measure of effect size. NNT describes, based on proportions, the number of individuals who would need to be assessed before the specified outcome is observed when comparing two groups. NNT is calculated by calculating the difference in proportion by group, taking the reciprocal, and then rounding up to the next highest integer. An NNT value equal to 1 indicates a perfect effect, larger NNT values over 1 indicate smaller effects (Citrome, 2008). Log transformation corrected for positive skew to improve normality. Non-parametric correlations were used to explore the linear relationship between depressive symptoms, eating-disorder psychopathology, health-related quality of life, SR-PA, and study group. To compare the magnitude of the correlations among groups, Kendall’s τ correlations were first converted to Pearson’s r based on the methods described by Walker (2003), and then compared using Fisher’s r-to-z transformation. Parallel analyses restricted to women were run on key findings to explore whether the pattern of significant findings remained the same.

Results

Table 1 summarizes the demography and SR-PA of participants. Almost 40% of the overall sample was insufficiently active. The BED group had the greatest proportion of individuals who were insufficiently active (n = 74; 63.8%), followed by the OW/OB group (n = 529; 41.7%), and the HW group (n = 265; 29.2%). When comparing OW/OB group with the HW group, an additional 8 cases would need to be assessed in order for one additional sufficiently active case to be identified. The comparison of BED and HW groups indicated that an additional 3 cases would need to be assessed in order to identify one additional sufficiently active case. BED compared with OW/OB would need an additional 5 cases to be assessed to identify one additional sufficiently active case. Study groups also significantly differed in the self-reported number of bouts of moderate to strenuous PA (p < .001). Games-Howell post-hoc analyses showed that the HW group reported significantly more SR-PA than OW/OB and BED groups and the OW/OB group reported significantly more SR-PA as compared with the BED group (all ps < .05). A parallel series of analyses restricted to women only revealed the same pattern of significant and non-significant findings.

Table 1.

Group Differences ins Demographic and Physical Activity Variables

HW OW/OB BED
Variable (n = 948) (n = 1308) (n = 120) Statistic Effect Size Post Hoc
Demographic Characteristics
Women n (%) 645 (68.18) 844 (64.87) 89 (74.17) χ2(2, 2367) = 5.90,
p = .052 		NNTOW - HW = −30
NNTBED - HW = 17
NNTOW - BED = 11		 ─
BMI, M (SD) 22.21 (1.71) 31.91(6.34) 33.25(8.06) Welch’s F (2, 297.63) =
1483.47, p < .001		 ω2 = .466 HW < OW/OB, BED†
Age, M (SD) 33.89 (11.23) 37.01 (11.81) 34.81 (10.27) Welch’s F (2, 337.03) =
20.74, p < .001		 ω2 = .016 HW < OW/OB†
White, n (%) 751 (79.22) 1107 (84.63) 105 (87.50) χ2(2, 2376) = 13.32
p = .001		 NNTOW - HW = 18
NNTBED - HW = 12
NNTOW - BED = 35		 HW < OW/OB, BED
HS Edu,
n (%)		 112 (11.81) 224 (17.13) 14 (11.67) χ2(2, 2376) = 13.29,
p = .001		 NNTOW - HW = −19
NNTBED - HW = 677
NNTOW - BED = 18
HW < OW/OB
Physical Activity
Insufficiently Active, n (%) 265 (29.25) 529 (41.72) 74 (63.79) χ2(2, N = 2290) = 69.71,
p < .001		 NNTOW - HW = 8
NNTBED - HW = 3
NNTOW - BED = 5		 HW < OW/OB < BED
SR-PA‡ M (SD) 4.67 (3.72) 3.67 (3.41) 2.10 (2.63) Welch’s F (2, 312.06) =
35.10, p < .001		 ω2 = .030 HW < OW/OB < BED†
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Note. HW: healthy weight; OB: individuals with overweight or obesity and without BED; BED: individuals with core features of binge-eating disorder; HS: High school SR-PA is a self-report measure of bouts of moderate/strenuous PA, lasting 15 minutes or longer per week.

†

Significant group differences using Games-Howell post-hoc tests at p < .05 level are noted.

‡

mean difference testing used the natural log of bouts of SR-PA per week; mean and standard deviation reported in original units for ease of interpretation.

In the overall sample, self-reported number of bouts of moderate/strenuous PA was significantly related to self-reported physical health, mental health, dietary restraint, body dissatisfaction, and depressive symptoms (all ps < .001). Table 2 includes a summary of these findings, including 1) Pearson’s r (transformed from rτ) for self-reported bouts of PA and biopsychosocial variables in the total sample, 2) Pearson’s r (transformed from rτ) for self-reported bouts of PA and biopsychosocial variables for each specific study group, 3) the z-score for the difference in correlations between study groups, and 4) an explanation of which study groups differed significantly based on the z-score and the direction of the effect. In the HW group, self-reported bouts of moderate to strenuous PA were significantly related to self-reported physical health, mental health, dietary restraint, and was inversely related to overvaluation of shape and weight and depressive symptoms (all ps < .001). In the OW/OB group, self-reported bouts of PA were significantly and positively related to self-reported physical health, mental health, and dietary restraint, and were significantly and inversely correlated with body dissatisfaction and depressive symptoms (all ps < .001). In the BED group, self-reported bouts of PA were significantly positively related to self-reported physical health (p < .001), mental health and dietary restraint (ps < .05), and inversely associated with depressive symptoms (p < .05). Correlations in HW and OW/OB groups were generally small. Correlations within the BED study group were generally moderate. Self-reported bouts of PA were significantly more strongly, positively related to self-reported physical health for the OW/OB group than the HW group (p = .006), and the strength of the effect was even more pronounced for the BED group as compared with either the HW (p < .001) or OW/OB (p = .006) groups. Overvaluation was weakly yet positively associated with self-reported bouts of PA among the HW group (p < . 05), and not significantly associated with bouts of PA in the OW/OB or BED group (ps > .05). The difference in magnitude of the correlation related to overvaluation across all group comparisons was significant (p < .05). Body dissatisfaction was significantly more strongly, negatively related to SR-PA bouts in the OW/OB group than the HW group (p = .003). No other significant differences were observed.

Table 2.

Correlations between Self-reported Physical Activity and Biopsychosocial Variables Among Groups

Total
M (SD)		 Total† HW†
(n = 948)		 OW/OB†
(n = 1308)		 BED†
(n = 120)		 Z-Score for Difference ‡ Sig. Group Differences
Physical Health (SF-12) 49.92 (9.20) 0.27*** 0.16*** 0.27*** 0.50*** z = −2.77, p = .006;
z = −3.94, p < .001;
z = −2.77, p = .006;		 HW < OW/OB;
HW < BED;
OW/OB < BED
Mental Health (SF-12) 44.56 (12.27) 0.20*** 0.17*** 0.16*** 0.23* — no significant differences
Restraint (EDE-Q) 2.53 (2.10) 0.17*** 0.22*** 0.20*** 0.22* — no significant differences
Overvaluation (EDE-Q) 3.06 (1.91) −0.03 0.12*** −0.03 −0.11 z = 2.29, p = .022;
z = 3.50, p < .001		 HW > OW/OB
HW > BED
Dissatisfaction (EDE-Q) 3.25 (1.94) −0.19*** −0.05 −0.18*** −0.10 z = 2.94, p = .003 HW < OW/OB
Depression (PHQ-2) 1.68 (1.78) −0.21*** −0.18*** −0.17*** −0.23* — no significant differences
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Note. Correlations and magnitude differences were calculated using r based on the transformation from Kendall’s tau.

SR-PA is a self-report measure by bouts of moderate/strenuous PA, lasting 15 minutes or longer per week.. HW: healthy weight; OB: individuals with overweight or obesity and without BED; BED: individuals with core features of binge-eating disorder; SF-12: Short Form Health Survey; EDE-Q: Eating Disorder Examination Questionnaire. PHQ-2: Patient Health Questionnaire-Short Depression Screener.

†

Significance flags indicate whether the correlation is significantly different than 0.

‡

Correlations were compared using Fisher’s r-to-z test.

*

p≤ .05

***

p< .001

Discussion

The current study examined SR-PA and associated correlates in an online community sample. Participants generally had a high level of inactivity, and the highest rates of inactivity occurred among individuals with core features of BED. Consistent with prior research, SR-PA was significantly associated with several important biopsychosocial variables, including self-reported physical health, eating-disorder psychopathology, and depressive symptoms. Our study adds to the existing literature by comparing associations of SR-PA and biopsychosocial variables among individuals with BED, individuals with excess weight and no eating disorder, and individuals with healthy weight and no eating disorder.

Approximately 40% of the sample was classified as insufficiently active, and SR-PA differed based on weight status and BED, with about 31% of HW, 42% of OW/OB, and 65% of BED participants reporting insufficient levels of PA. Significantly lower SR-PA in the BED than OW/OB study group aligns with other research in community samples showing that people with BED are particularly at risk for high levels of physical inactivity (Crandall et al., 2012). These differences are also observed when considering self-reported total bouts of moderate to strenuous PA. More research is needed to understand possible contributing factors to the high rates of inactivity, particularly among individuals with BED; some research supports internalization of obesity stereotypes (Pearl, Puhl, & Dovidio, 2015), negative body image (Anton, Perri, & Riley, 2000; Hrabosky, White, Masheb, & Grilo, 2007), and perceived physical competence (Vancampfort, De Herdt, et al., 2014).

Participants’ reports of higher PA were related to reports of greater physical and mental health, lower body dissatisfaction and depressive symptoms, and greater restraint, although correlations generally had small magnitudes in the total sample and HW sample. Across study groups, the strongest association was demonstrated for SR-PA and higher levels of self-reported physical health. The cross-sectional nature of this study precludes any statements about directionality or causality; we note it is possible, for example, that individuals who feel physically healthy are more likely to be physically active and those who are physically active are more likely to experience the benefits of improved physical health (Schuch et al., 2017).

In the OW/OB group, the association between self-reported physical health and self-reported bouts of PA was significantly stronger than the association observed in the HW group. Growing evidence supports the role of PA in predicting morbidity and mortality over and above weight status (Fogelholm, 2010; Haskell, 2007), which supports the importance of interventions that incorporate a focus on increasing PA rather than interventions that focus on weight reduction alone. With respect to eating-disorder psychopathology, a pattern emerged where the association between self-reported bouts of PA and overvaluation of weight/shape had significantly greater, positive magnitude among individuals with HW as compared with the OW/OB group. In contrast, the association between SR-PA and body dissatisfaction had significantly greater, negative magnitude among individuals with overweight or obesity. PA as an effective strategy for reducing body image disturbances has been established prospectively (Campbell & Hausenblas, 2009; Teixeira et al., 2006), and the current work further supports the association.

For the BED group, the association between SR-PA and self-reported physical functioning was significantly more positive than the association within both the HW and OW/OB groups. This is the first study, to our knowledge, to demonstrate a stronger association between SR-PA and physical functioning for individuals with BED as compared with OW/OB alone. No other significant differences in the correlates of SR-PA were observed for the BED group. Examination of the correlation coefficients reveals moderate effect sizes for the relationship between self-reported bouts of PA and higher levels of mental health and lower rates of depressive symptoms. The combined findings related to high rates of physical inactivity among the BED group and the strong association between SR-PA and self-reported physical health among participants with BED suggest PA as an important treatment target for individuals with BED.

Study findings should be considered within the context of several limitations. First, individuals with overweight or obesity were older than the HW group, which could have contributed to some of the observed differences, although the effect size for the difference in age was small. Second, while racial and gender diversity was observed in the current sample, the sample was predominantly White, which may limit generalizations to other racial/ethnic groups. Additionally, the BED group was formed according to self-reported binge-eating episodes (at-least weekly) and associated distress. Such a classification is less rigorous and specific than clinical diagnosis according to the full features of BED using semi-structured interview procedures. Finally, SR-PA has known limitations (Steene-Johannessen et al., 2015; Warren et al., 2010), with large-scale epidemiologic data suggesting poor concordance for self-reported and objective measurements of PA. However, data consistently demonstrate that general populations overestimate levels of PA, and as such, these results may be considered a minimum estimate for the level of inactivity in this sample. Further, the dichotomization of participants into sufficiently or insufficiently active groups with established construct validity (Amireault & Godin, 2015) increases confidence in findings. Nonetheless, future research should include objective measures of PA. The only available study utilizing objective measurements of PA with a small sample of BED patients provided conflicting evidence with higher levels of activity observed (Mathisen et al., 2018). Prospective and experimental studies are needed to expand on these cross-sectional findings.

Overall, these data reveal a high rate of inactivity and highlight the need to increase PA generally. The results also suggest important differences in both the amount and correlates of SR-PA when comparing HW, OW/OB, and BED study groups. Future research should consider how other sociodemographic characteristics, such as gender, may further moderate the relationship between weight, binge-eating status, and correlates of PA. The known sequelae of overweight, obesity, and BED, and the evidence supporting the positive role PA might play for individuals with these conditions, further stresses the importance of creating and testing interventions aimed at increasing PA for these groups. More research is needed to understand how to influence barriers to PA, how to create sustainable change in the rates of PA, as well as how these changes might influence the experience and trajectory of conditions such as obesity and BED.

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