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. Author manuscript; available in PMC: 2023 Mar 1.
Published in final edited form as: Eat Disord. 2020 May 13;30(2):154–167. doi: 10.1080/10640266.2020.1746121

Naturalistically assessed associations between physical activity, affective functioning, and binge eating among adults with binge-eating disorder

Kathryn E Smith a, Tyler B Mason b, Lisa M Anderson c, Lauren M Schaefer d, Ross D Crosby d,e, Scott G Engel d,e, Scott J Crow c,f, Stephen A Wonderlich d,e, Carol B Peterson c,f
PMCID: PMC8628298  NIHMSID: NIHMS1758070  PMID: 32397943

Abstract

Binge-eating disorder (BED) is associated with overweight/obesity, physical inactivity, and disturbances in affective functioning. While research suggests that physical activity (PA) may have beneficial effects on BED symptoms, little is known about the daily correlates of PA. As a first step in understanding the processes linking PA and binge eating, this study examined associations between PA (i.e., self-reported time engaged in moderate-to-vigorous PA), affective functioning (i.e., positive and negative affect, body satisfaction, emotion regulation), and eating-related cognitions and behaviors (i.e., craving, overeating, loss of control eating) measured via ecological momentary assessment (EMA). Adults with BED (N = 91) completed a seven-day EMA protocol during which they completed repeated measures of these variables. Results indicated individuals who reported greater time engaged in PA over the EMA protocol evidenced higher positive affect and body satisfaction, and lower overeating (between-subjects effects). No significant within-subjects effects were observed. Findings demonstrate that individual differences in PA levels were related to more adaptive affective functioning and eating regulation in daily life. Results highlight the relevance of PA in BED, and the need for future studies to identify the timescale of these relationships using objective measurements of PA.

Introduction

Binge-eating disorder (BED) is a psychiatric disorder characterized by recurrent binge eating in the absence of regular compensatory behaviors (American Psychiatric Association, 2013) and is accompanied by a range of negative sequalae, including poor quality of life and psychiatric and medical comorbidities (Grilo et al., 2009; Wonderlich et al., 2009). While excess weight is not a diagnostic criterion for BED, this disorder is strongly associated with obesity. For instance, estimates suggest 42–70% of individuals with BED have obesity (Grucza et al., 2007; Hudson et al., 2007); in addition, men and women with obesity are over four times more likely to have a lifetime history of BED compared to individuals of normal weight (Duncan et al., 2017). This is particularly concerning given that obesity is a significant public health concern that contributes to several leading causes of preventable death in the United States (Centers for Disease Control and Prevention, 2018a). Despite the clinical significance of BED and co-occurring overweight/obesity (BED+OW/OB), outcomes of psychological treatments for BED (which do not target weight) remain less than optimal (Grilo, 2017). While behavioral weight loss treatments have been applied to BED and have been shown to reduce weight, effects of behavioral weight loss on binge eating are less than those observed during psychological treatments such as cognitive behavioral therapy (Hilbert et al., 2019). Together these findings indicate a clear need to better understand mechanisms underlying this pathology and identify ways to improve both eating and weight outcomes.

Ecological momentary assessment (EMA), which refers to real-time data collection within individuals’ natural environments, has demonstrated that momentary affective functioning is an important maintenance factor underlying binge eating (Engel et al., 2016). Consistent with affect regulation models, naturalistic studies have shown that negative affect increases and positive affect decreases prior to binge eating episodes, after which affect improves (i.e., negative affect decreases; positive affect increases; Engel et al., 2016). Such evidence is also consistent with the broader literature suggesting that BED is associated with trait-level emotion regulation difficulties (Leehr et al., 2015). Thus, identifying and effectively targeting factors associated with daily affect, emotion regulation, and binge eating are of utmost importance to improve treatment outcomes for individuals with BED.

Notably, outside of EDs, EMA studies have demonstrated that physical activity regulates momentary affect (Liao et al., 2015). This research indicates that positive affect increases and negative affect decreases after physical activity (Dunton et al., 2014; Kanning & Schlicht, 2010), and that exercise may mitigate the degree of persistence in negative affect (Bernstein & McNally., 2018). Furthermore, other data suggest that physical activity has a regulating effect on a range of eating-related domains, including improved appetite control, lower food cue reactivity and hedonic responses to food (e.g., craving), and reduced binge eating (Blanchet et al., 2018; Joseph et al., 2011; Luo et al., 2018; Martins et al., 2008).

In sum, physical activity is a potentially modifiable domain that impacts weight, affect, and eating behavior. The positive impact of physical activity is especially relevant to BED, which is associated with disturbances in eating and emotion regulation as well as overweight/obesity. Further, physical activity levels are generally lower among individuals with overweight/obesity (with and without BED) compared to individuals of lower weight (Hrabosky et al., 2007; Vancampfort et al., 2015). Thus, physical activity may reflect a salient contributing factor to BED+OW/OB, as well as a possible intervention target, which is supported by an emerging literature (Blanchet et al., 2018). However, no EMA studies have examined correlates of physical activity among individuals with BED in naturalistic settings, which would help to better understand how time-varying (i.e., within-subjects) and trait-level (i.e., between-subjects) physical activity levels are related to affect and eating-related variables in BED, and potentially identify moderators and mediators to examine in future research.

Therefore, the present study examined associations between physical activity, affective functioning (i.e., positive and negative affect, body satisfaction, emotion regulation), and eating-related cognitions and behaviors (i.e., craving, overeating, and loss of control [LOC] eating) measured via EMA. Given the health benefits of moderate-to-vigorous physical activity (MVPA; Physical Activity Guidelines Advisory Committee, 2018), physical activity was operationalized as time spent engaged in activities that were consistent with MVPA. It was expected that (1) days when individuals reported higher levels of physical activity, relative to their individual mean, would be related to improved affective functioning (i.e., higher positive affect and body satisfaction; lower negative affect and emotion dysregulation) as well as less craving and binge-eating symptoms (i.e., overeating and LOC eating; within-subjects effect), and that (2) individuals who evidenced higher physical activity levels, compared to the sample mean, would report more adaptive affective functioning (i.e., higher positive affect and body satisfaction; lower negative affect and emotion dysregulation) along with less craving and binge-eating symptoms over the EMA monitoring period (between-subjects effect). In addition, given that weight status may have an independent effect on these dependent variables, BMI was included as a covariate to assess the unique association between physical activity and these domains.

Method

Participants

Participants were drawn from a clinical treatment trial for BED (n = 112; blinded for review). Participants in the trial were eligible if they were within the ages of 18 and 65 and met the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for BED (American Psychiatric Association, 2013). Exclusion criteria included the following: (1) unable to read English, (2) body mass index (BMI, kg/m2) less than 21, (3) lifetime history of psychotic symptoms or bipolar disorder, (4) substance use disorder within six months of enrollment, (5) medically or psychiatrically unstable, (6) purging behavior more than once per month for the previous three months, (7) current diagnosis of bulimia nervosa, (8) medical condition impacting eating or weight, (9) history of gastric bypass surgery, (10) currently pregnant or lactating, (11) currently receiving weight loss or eating disorder treatment, (12) taking medication impacting eating or weight, or (13) psychotropic medication changes in the six weeks prior to enrollment. The Structured Clinical Interview for DSM-IV Axis I Disorders, Patient Version (SCID-I/P; First et al., 1996) assessed current and lifetime history of DSM-IV Axis I psychiatric disorders. At the time of the baseline assessment, 13 individuals (11.6%) met criteria for a DSM-5 mood disorder diagnosis, and 22 (19.6%) met criteria for a DSM-5 anxiety disorder. Lifetime rates of Axis I disorders were 57.1% for mood disorders, 37.5% for anxiety disorders, and 39.3% for substance abuse/dependence. For the current study, only individuals who reported on physical activity during the EMA protocol were included in the analyses, resulting in 91 participants (83.5% women; 93% Caucasian; Mage = 40.99 ± 13.71, range = 18–64; MBMI = 34.46 ± 8.58, range = 21.41–62.03).1

Procedure

Participants were recruited at two study sites in the Midwestern region of the United States from clinical and community settings. Participants first completed a baseline assessment visit that included diagnostic interviews and self-report questionnaires, after which they completed seven days of EMA using the ReTAINE (Real Time Assessment in the Natural Environment; see ReTAINE.org) system administered by smart phone. Participants also completed a day of practice recording prior to the start of EMA, and these data were not used in final analyses. EMA measures were administered at five semi-random signal-contingent recordings each day, which were distributed around five anchor points between 8 am and 10 pm., and one end-of-day signal; no event-contingent recordings were used. Rather, at each semi-random signal participants were asked to report on any eating episodes that had occurred since their last recording. After the EMA protocol, participants were randomized to treatments. Only baseline (pre-treatment) assessments were examined for the present study.

Measures

Baseline assessments

Height and weight were measured to calculate BMI. The Eating Disorder Examination 16.0 (EDE; Fairburn et al., 2008) was used to assess BED diagnostic criteria.

EMA measures

Affect.

Items from the Positive and Negative Affect Scale (PANAS; Watson, et al., 1988) assessed positive affect (alert, inspired, determined, attentive, and active) and negative affect (afraid, nervous, upset, ashamed, and hostile). Participants rated each affect state from 1 (Not at all) to 5 (Very much). Responses to negative and positive affect items were averaged to create composite measures reflecting overall negative and positive affect at each signal (α = .80 and .88, respectively). The validity of the PANAS has been supported by prior EMA work in eating disorders (Wonderlich et al., 2015).

Emotion regulation.

Emotion regulation difficulties were assessed using items from the Modulate subscale of the State Difficulties in Emotion Regulation Scale (S-DERS; Lavender et al., 2017): I am having difficulty controlling behaviors; My emotions feel out of control; I feel out of control; My emotions feel overwhelming; I am having difficulty doing the things I need to do right now. Responses ranged from 1 (Not at all) to 5 (Very much). The S-DERS has demonstrated adequate reliability and validity (Lavender et al., 2017). Items were averaged at each signal to create a composite index, with higher scores indicating greater difficulties modulating emotions and behaviors (α = .90).

Body satisfaction.

State body dissatisfaction was assessed using the item: I am satisfied with my body weight/shape, which has previously been used in EMA research (Mason et al., 2018). Responses ranged from 1 (Not at all) to 5 (Completely), with higher ratings indicating greater body satisfaction.

Craving.

Consistent with previous EMA measurement of food craving (Goldschmidt et al., 2014), at each EMA signal participants rated their degree of craving based on the following item: I am craving food. Responses ranged from 1 (Not at all) to 5 (Completely), with higher ratings indicating greater momentary craving.

Binge eating.

Ratings of LOC eating and overeating were completed if a participant indicated he/she had eaten since the last EMA signal. Participants indicated the extent to which each recorded eating episode was characterized by both overeating and loss of control over eating using a Likert-type scale ranging from 1 (not at all) to 5 (extremely). Items were based on prior EMA research in BED and obesity (Berg et al., 2014). To assess overeating, participants rated the following two items: (a) To what extent to do you feel that you overate?, and (b) To what extent do you feel that you ate an excessive amount of food?. To assess LOC eating, participants rated each of the following four questions: (a) While you were eating, to what extent did you feel a sense of loss of control?, (b) While you were eating, to what extent did you feel that you could not resist eating?, (c) While you were eating, to what extent did you feel that you could not stop eating once you had started?, and (d) While you were eating, to what extent did you feel driven or compelled to eat?. Responses ranged from 1 (Not at all) to 5 (Very much); responses to LOC eating and overeating items were averaged to create composite LOC eating and overeating scores at each signal (α = .83 and .93, respectively), with higher scores reflecting higher binge-eating symptoms at the eating episode. EMA research using similar items (Berg et al., 2014) has demonstrated moderate convergence between interview-based and EMA-measured binge eating (Wonderlich et al., 2015).

Physical activity time.

At the end-of-day recording, participants indicated how much time they spent engaged in categories of physical activity representing MVPA (Centers for Disease Control and Prevention, 2018b): (1) cardio/aerobic activities, (2) strength training, (3) stretching, yoga, pilates, or martial arts, (4) playing a sport, and (5) dancing. Responses for each category ranged from 1 to 9, with each response corresponding to a time interval (i.e., up to 15 minutes, 16–30 minutes, etc.). Responses to each item were first converted to a time estimate (minutes) that corresponded to the middle of the indicated time interval (e.g., “46–60 minutes” was converted to 53 minutes), and then summed to calculate the total daily time spent engaged in physical activity.

Statistical analyses

Within- and between-subjects variance in each variable was calculated using the intraclass correlation coefficient (ICC), which reflects the proportion of variance accounted for by a clustering variable (i.e., person). Associations between physical activity and the variables of interest were examined with generalized estimating equations (GEEs) using a gamma link function and an AR1 serial autocorrelation. The independent variable (i.e., physical activity time) was examined as a predictor of positive and negative affect, body satisfaction, emotion regulation, craving, LOC eating, and overeating in separate GEEs. Each model included between-subjects (i.e., grand-mean centered) and within-subjects effects (i.e., centered within each person) of physical activity time. Given that independent variable assessed only at end-of-day, and the dependent variables were assessed multiple times per day, the dependent variables were aggregated within each day, thereby reflecting average daily levels. Age, BMI (grand-mean centered), and gender were included as covariates in all models.

Results

Each participant completed an average of 29.97 ± 9.18 signals over the course of 6.71 ± 1.26 days. The average daily time spent engaged in physical activity ranged from 0 to 30 minutes (M = 5.54 ± 6.23 minutes).2 The ICC values demonstrated considerable within-subject (i.e., daily) variability in all variables (physical activity: .46; positive affect: .72; negative affect: .73; loss of control eating: .55; overeating: .43; body satisfaction: .58; emotion regulation difficulties: .73; craving: .53).

Results of GEEs (Table 1) indicated significant between-subjects effects for positive affect, overeating, and body satisfaction, such that individuals who reported more time spent engaged in physical activity over the EMA protocol reported higher positive affect and body satisfaction, and lower overeating; however the between-subjects effects were not significant for LOC eating, negative affect, emotion regulation difficulties, or craving. There were no significant within-subjects effects.

Table 1.

Generalized estimating equation models examining physical activity time as a predictor of EMA variables.

Positive affect Negative affect
B SE Lower CI Upper CI Wald χ2 p B SE Lower CI Upper CI Wald χ2 p
Intercept 0.98 0.10 0.79 1.18 96.19 <0.001 0.54 0.12 0.31 0.77 21.49 <0.001
Gender −0.21 0.10 −0.42 −0.01 4.36 0.037 −0.13 0.12 −0.36 0.11 1.14 0.286
BMI <0.01 <0.01 −0.01 0.01 0.13 0.717 0.01 <0.01 <−0.01 0.01 3.07 0.080
Age 0.01 <0.01 <0.01 0.01 16.26 <0.001 −0.01 <0.01 −0.01 <−0.01 4.68 0.031
Physical activity (between) 0.02 0.01 0.01 0.03 8.69 0.003 −0.01 0.01 −0.02 0.01 0.94 0.331
Physical activity (within) <0.01 <0.01 <−0.01 0.01 0.23 0.635 <−0.01 <0.01 −0.01 <0.01 0.44 0.508
Loss of control eating Overeating
Intercept 0.90 0.10 0.71 1.09 85.01 <0.001 0.83 0.09 0.66 1.01 88.45 <0.001
Gender 0.09 0.10 −0.11 0.29 0.75 0.388 0.02 0.09 −0.17 0.21 0.05 0.829
BMI 0.01 <0.01 <−0.01 0.01 1.96 0.162 0.01 <0.01 <−0.01 0.01 3.61 0.058
Age −0.01 <0.01 −0.01 <−0.01 7.44 0.006 −0.01 <0.01 −0.01 <−0.01 6.73 0.009
Physical activity (between) −0.01 0.01 −0.02 0.01 0.86 0.354 −0.02 0.01 −0.03 <−0.01 6.25 0.012
Physical activity (within) <−0.01 <0.01 −0.01 <0.01 0.90 0.342 <−0.01 <0.01 −0.01 <0.01 1.23 0.268
Body satisfaction Emotion regulation difficulties
Intercept 0.27 0.09 0.10 0.44 9.31 0.002 0.62 0.11 0.40 0.85 29.48 <0.001
Gender 0.15 0.10 −0.04 0.34 2.29 0.130 −0.08 0.12 −0.32 0.16 0.46 0.497
BMI −0.01 <0.01 −0.02 <−0.01 7.12 0.008 0.01 <0.01 <0.01 0.02 5.59 0.018
Age <−0.01 <0.01 −0.01 0.01 0.03 0.870 −0.01 <0.01 −0.01 <−0.01 8.42 0.004
Physical activity (between) 0.02 0.01 0.01 0.03 8.25 0.004 <−0.01 0.01 −0.02 0.01 0.13 0.723
Physical activity (within) <−0.01 <0.01 −0.01 0.00 1.10 0.294 <−0.01 <0.01 −0.01 <0.01 0.72 0.396
Craving
Intercept 0.81 0.07 0.67 0.95 130.32 <0.001
Gender 0.02 0.08 −0.13 0.18 0.09 0.766
BMI 0.01 <0.01 <−0.01 0.01 3.07 0.080
Age −0.01 <0.01 −0.01 <−0.01 11.09 0.001
Physical activity (between) <−0.01 0.01 −0.02 0.01 0.16 0.688
Physical activity (within) −0.01 <0.01 −0.01 <0.01 3.56 0.059
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EMA = ecological momentary assessment; CI = 95% confidence interval; between = between-subjects effect (grand-mean centered variable); within = within-subjects effect (person-mean centered variable. Gender was coded such that men were the reference category. Each dependent variable was aggregated within day to represent the daily mean of the variable.

Discussion

The present study investigated correlates of physical activity in naturalistic settings among individuals with BED. Hypotheses were partially supported, and despite low mean physical activity levels, there was meaningful inter-individual variability in physical activity that related to clinically relevant constructs. That is, individuals who reported higher levels of physical activity over the course of the EMA protocol compared to the sample mean evidenced more adaptive affective functioning (i.e., higher positive affect and higher body satisfaction) and eating regulation, as reflected by lower overeating. However, this effect was not significant for LOC eating, craving, or negative emotionality (i.e., negative affect and emotion regulation difficulties), and within-subjects effects were not significant in any model.

The finding that dimensions of positively valenced affective functioning were related to physical activity at the individual level is consistent with the broader literature showing that physical activity improves positive affect and vice versa, while associations have been somewhat less consistent for negative affect (Liao et al., 2015; Reed & Ones, 2006). Although directionality cannot be inferred from between-subjects effects, one possibility is that in addition to the “feel good” effects of physical activity, emotional functioning also influences overall physical activity levels in BED. In line with the Broaden and Build Theory, positive affect may promote expansion of one’s thought-action repertoires by broadening awareness and increasing cognitive and behavioral flexibility; over time, this is thought to lead to improved psychological, social, and physical functioning (Garland et al., 2010). In other words, positive affect may facilitate consideration of a broader range of coping strategies and goal-directed behaviors, including physical activity. Another possibility is that positive affect promotes self-efficacy, which is one of the most consistent correlates of physical activity (Bauman et al., 2012) and is a key factor in social cognitive theories of physical activity (Young et al., 2014). It is also important to consider potential for highly dynamic influences between positive affect and physical activity. That is, emotional experiences related to physical activity may further enhance health and mitigate BED symptoms. For instance, research has found that temporally proximal affective responses, affective judgements about future exercise, and self-efficacy following physical activity bouts predict and maintain future physical activity (Rhodes & Kates, 2015).

The observed relationship between physical activity and body satisfaction was consistent with literature outside of EDs (e.g., Campbell & Hausenblas, 2009), which also converges with a prior review that indicated lower physical activity was related to negative body image in BED (Vancampfort et al., 2014). However, the latter finding was based on two studies, and it is not yet clear if this association is robust in BED. For instance, a recent study showed that the association between self-reported physical activity and body dissatisfaction among those with BED was not significant, and the magnitude of this association did not differ compared to individuals of normal weight or those with OW/OB without BED (Carr et al., 2019). Thus, further work is needed to replicate the present findings as well as examine the direction of this association. Notably, while these results indicate that increasing physical activity could be a viable way to improve body satisfaction, it is also important to consider the degree to which body dissatisfaction is a barrier that impedes subsequent physical activity engagement in BED.

The present study was also the first to demonstrate links between physical activity and naturalistically eating behavior in BED, specifically overeating. Such findings are broadly consistent with literature documenting effects of physical activity on appetite regulation (e.g., Martins et al., 2008). Given that the between-subjects effect for LOC eating and craving did not reach statistical significance, it may be that physical activity levels have a stronger effect on homeostatic hunger and objective eating behaviors predict excess weight gain, more so than cognitive phenomena such as subjective experiences of LOC eating and hedonic hunger. However, temporal associations between these variables have yet to be elucidated, and future research is warranted to investigate the degree to which physical activity may influence these processes in BED.

Contrary to hypotheses, no significant within-subjects emerged when examining associations between daily physical activity time and outcome variables. Given the relatively low levels of daily physical activity, individuals may not have engaged in enough activity throughout the day to elicit beneficial shorter-term effects. This finding may also be due in part to the schedule and nature of physical activity assessments. That is, moment-to-moment relationships could not be elucidated in the present study given that physical activity was only assessed at end-of-day, and it could be that temporal effects can be observed on a shorter (or alternatively, longer) timescale than what was captured in the present study. In addition, physical activity time was based on self-report questions, which are inherently subject to recall biases. Utilizing objective, passive physical activity monitors (i.e., actigraphy) in future EMA studies will provide a more accurate, temporally precise measurements of physical activity duration and intensity over the course of the day. Such measurement is more likely to capture meaningful time-varying relationships with constructs that were assessed in the present study.

Several limitations are worth noting. As mentioned, physical activity was assessed via self-report, and it is imperative for future studies to employ objective physical activity measures. The self-report activity assessment also precluded measurement of overall activity (e.g., step count) and intensity levels. In addition, self-reported overeating may not correspond to objective intake. While this study utilized intensive longitudinal data collection, the design was nevertheless cross-sectional in nature, and directionality cannot be inferred in terms of the temporal relationships between independent and dependent variables. EMA was also limited to seven days; as such, monitoring over more extended time periods would be useful in future studies. The sample consisted of mostly Caucasian women, and thus findings may not generalize to other demographic groups with BED or other diagnoses. In addition, it is possible that comorbidities (e.g., depression) observed among some participants in the sample could influence physical activity levels, and should be further explored in future study (Roshanaei-Moghaddam et al., 2009).

In spite of the limitations, these findings provide a first step in elucidating potential factors linking physical activity and binge-eating symptomatology in daily life. Results also highlight directions for future clinical research. Going forward, it will be important to elucidate the directionality of the observed between-subject associations with longitudinal and intensive longitudinal (i.e., EMA) designs. For instance, while moment-to-moment relationships could not be determined in the present study, it could be that improved positive affect is a proximal antecedent and/or consequence of physical activity in BED, and/or that physical activity mitigates some binge eating symptoms (i.e., overeating) via improvement of momentary positive affect and body satisfaction. These momentary processes will be important to clarify in future research, as well as other individual (e.g., self-efficacy) and contextual factors (e.g., social support, environment) that may promote or impede physical activity in BED.

Such investigations will inform how physical activity may be integrated into theoretical models of etiology and maintenance of BED symptomatology, as well as inform how, when, and for whom to harness physical activity promotion as a potential prevention or intervention component. For instance, a recent review indicated that physical activity interventions for BED were associated with improvements in binge eating, depression, and anxiety, as well as reductions in BMI (Blanchet et al., 2018). Such results suggest that physical activity promotion may be a promising adjunctive intervention to address both eating behavior and weight management in BED, although this body of literature remains small. Although further research is needed, the present study findings lend additional support for the promise of physical activity interventions in BED, particularly with respect to targeting positive affect, body image, and overeating. It is also encouraging that evidence outside of eating disorders indicates that both high and low intensity physical activity are effective in reducing the risk of depression (Mammen & Faulkner, 2013; Teychenne et al., 2008). These findings suggest that even modest levels of physical activity could yield psychological benefits in reducing BED symptomatology, as well as potentially maintaining binge eating abstinence, possibly via influences on affective functioning. Lastly, it will be imperative for researchers and clinicians in this area to draw upon relevant theoretical frameworks (e.g., social cognitive theory, self-determination theory) and utilize novel methodologies being applied in other areas of health psychology (e.g., just-in-time adaptive interventions) to better understand and potentially enhance physical activity in the context of BED.

Clinical implications.

  • Individuals with binge eating disorder and co-occurring overweight/obesity (BED+OW/OB) have been shown to engage in low levels of physical activity.

  • Little is known about how physical activity levels are related to BED symptomatology and emotional functioning in daily life.

  • This study used ecological momentary assessment (EMA) to examine these relationships in the natural environment among 91 adults with BED.

  • Higher levels of physical activity were associated with greater positive affect, body satisfaction, and less overeating.

  • These findings indicate a need for future research to consider physical inactivity as a potential treatment target in this population.

Funding

This research was supported by the National Institute of Mental Health (grant numbers R34 MH099040-01A1 and T32 MH082761).

Footnotes

1.

Participants who completed physical activity assessments did not differ with respect to BMI, age, or any dependent variable compared to those who did not respond to these questions (ps>.255).

2.

This mean reflects the average daily sum of the mid-points of the time intervals endorsed for each activity category.

Disclosure statement

The authors declare no conflicts of interest

References

  1. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). [Google Scholar]
  2. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJ, & Martin BW, & Lancet Physical Activity Series Working Group. (2012). Correlates of physical activity: Why are some people physically active and others not? The Lancet, 380(9838), 258–271. 10.1016/S0140-6736(12)60735-1 [DOI] [PubMed] [Google Scholar]
  3. Berg KC, Peterson CB, Crosby RD, Cao L, Crow SJ, Engel SG, & Wonderlich SA (2014). Relationship between daily affect and overeating-only, loss of control eating-only, and binge eating episodes in obese adults. Psychiatry Research, 215(1), 185–191. 10.1016/j.psychres.2013.08.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bernstein EE, & McNally RJ (2018). Exercise as a buffer against difficulties with emotion regulation: a pathway to emotional wellbeing. Behavior Research and Therapy, 109, 29–36. [DOI] [PubMed] [Google Scholar]
  5. Blanchet C, Mathieu MÈ, St-Laurent A, Fecteau S, St-Amour N, & Drapeau V (2018). A systematic review of physical activity interventions in individuals with binge eating disorders. Current Obesity Reports, 7(1), 76–88. 10.1007/s13679-018-0295-x [DOI] [PubMed] [Google Scholar]
  6. Campbell A, & Hausenblas HA (2009). Effects of exercise interventions on body image: A meta-analysis. Journal of Health Psychology, 14(6), 780–793. 10.1177/1359105309338977 [DOI] [PubMed] [Google Scholar]
  7. Carr MM, Lydecker JA, White MA, & Grilo CM (2019). Examining physical activity and correlates in adults with healthy weight, overweight/obesity, or binge-eating disorder. International Journal of Eating Disorders, 52(2), 159–165. 10.1002/eat.v52.2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Centers for Disease Control and Prevention (2018a). Adult obesity facts. https://www.cdc.gov/obesity/data/adult.html
  9. Centers for Disease Control and Prevention. (2018b). General physical activities defined by level of intensity.
  10. Duncan AE, Ziobrowski HN, & Nicol G (2017). The prevalence of past 12-month and lifetime DSM-IV eating disorders by BMI category in US men and women. European Eating Disorders Review, 25(3), 165–171. 10.1002/erv.v25.3 [DOI] [PubMed] [Google Scholar]
  11. Dunton GF, Huh J, Leventhal AM, Riggs N, Hedeker D, Spruijt-Metz D, & Pentz MA (2014). Momentary assessment of affect, physical feeling states, and physical activity in children. Health Psychology, 33(3), 255. 10.1037/a0032640 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Engel SG, Crosby RD, Thomas G, Bond D, Lavender JM, Mason T, Steffen KJ, Green DD, & Wonderlich SA (2016). Ecological momentary assessment in eating disorder and obesity research: A review of the recent literature. Current Psychiatry Reports, 18(4), 37. 10.1007/s11920-016-0672-7 [DOI] [PubMed] [Google Scholar]
  13. Fairburn CG, Cooper Z, & O’Connor M (2008). Eating Disorder Examination (16.0D). In Fairburn CG (Ed.), Cognitive Behavior Therapy and Eating Disorders. Guilford Press. [Google Scholar]
  14. First MB, Spitzer RL, Gibbon M, & Williams J (1996). Structured clinical interview for DSM-IV Axis I disorders - patient edition (SCID-I/P). Biometrics Research Development, New York State Psychiatric Institute. [Google Scholar]
  15. Garland EL, Fredrickson B, Kring AM, Johnson DP, Meyer PS, & Penn DL (2010). Upward spirals of positive emotions counter downward spirals of negativity: Insights from the broaden-and-build theory and affective neuroscience on the treatment of emotion dysfunctions and deficits in psychopathology. Clinical Psychology Review, 30(7), 849–864. 10.1016/j.cpr.2010.03.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Goldschmidt AB, Crosby RD, Cao L, Engel SG, Durkin N, Beach HM, & Peterson CB (2014). Ecological momentary assessment of eating episodes in obese adults. Psychosomatic Medicine, 76(9), 747–752. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Grilo CM (2017). Psychological and behavioral treatments for Bnge-eating disorder. The Journal of Clinical Psychiatry, 78(Suppl 1), 20–24. 10.4088/JCP.sh16003su1c.04 [DOI] [PubMed] [Google Scholar]
  18. Grilo CM, White MA, & Masheb RM (2009). DSM-IV psychiatric disorder comorbidity and its correlates in binge eating disorder. International Journal of Eating Disorders, 42(3), 228–234. 10.1002/eat.v42:3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Grucza RA, Przybeck TR, & Cloninger CR (2007). Prevalence and correlates of binge eating disorder in a community sample. Comprehensive Psychiatry, 48(2), 124–131. 10.1016/j.comppsych.2006.08.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Hilbert A, Petroff D, Herpertz S, Pietrowsky R, Tuschen-Caffier B, Vocks S, & Schmidt R (2019). Meta-analysis of the efficacy of psychological and medical treatments for binge-eating disorder. Journal of Consulting and Clinical Psychology, 87(1), 91. 10.1037/ccp0000358 [DOI] [PubMed] [Google Scholar]
  21. Hrabosky JI, White MA, Masheb RM, & Grilo CM (2007). Physical activity and its correlates in treatment-seeking obese patients with binge eating disorder. International Journal of Eating Disorders, 40(1), 72–76. 10.1002/()1098-108X [DOI] [PubMed] [Google Scholar]
  22. Hudson JI, Hiripi E, Pope HG Jr., & Kessler RC (2007). The prevalence and correlates of eating disorders in the National comorbidity survey replication. Biological Psychiatry, 61(3), 348–358. 10.1016/j.biopsych.2006.03.040 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Joseph RJ, Alonso-Alonso M, Bond DS, Pascual-Leone A, & Blackburn GL (2011). The neurocognitive connection between physical activity and eating behaviour. Obesity Reviews, 12(10), 800–812. 10.1111/j.1467-789X.2011.00893.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Kanning M, & Schlicht W (2010). Be active and become happy: An ecological momentary assessment of physical activity and mood. Journal of Sport and Exercise Psychology, 32(2), 253–261. 10.1123/jsep.32.2.253 [DOI] [PubMed] [Google Scholar]
  25. Lavender JM, Tull MT, DiLillo D, Messman-Moore T, & Gratz KL (2017). Development and validation of a state-based measure of emotion dysregulation: the state difficulties in emotion regulation scale (s-ders). Assessment, 24(2), 197–209. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Leehr EJ, Krohmer K, Schag K, Dresler T, Zipfel S, & Giel KE (2015). Emotion regulation model in binge eating disorder and obesity-a systematic review. Neuroscience & Biobehavioral Reviews, 49, 125–134. 10.1016/j.neubiorev.2014.12.008 [DOI] [PubMed] [Google Scholar]
  27. Liao Y, Shonkoff ET, & Dunton GF (2015). The acute relationships between affect, physical feeling states, and physical activity in daily life: A review of current evidence. Frontiers in Psychology, 6, 1975. 10.3389/fpsyg.2015.01975 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Luo S, O’Connor SG, Belcher BR, & Page KA (2018). Effects of physical activity and sedentary behavior on brain response to high-calorie food cues in young adults. Obesity, 26 (3), 540–546. 10.1002/oby.v26.3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Mammen G, & Faulkner G (2013). Physical activity and the prevention of depression: A systematic review of prospective studies. American Journal of Preventive Medicine, 45(5), 649–657. 10.1016/j.amepre.2013.08.001 [DOI] [PubMed] [Google Scholar]
  30. Martins C, Morgan L, & Truby H (2008). A review of the effects of exercise on appetite regulation: An obesity perspective. International Journal of Obesity, 32(9), 1337–1347. 10.1038/ijo.2008.98 [DOI] [PubMed] [Google Scholar]
  31. Mason TB, Smith KE, Crosby RD, Wonderlich SA, Crow SJ, Engel SG, & Peterson CB (2018). Does the eating disorder examination questionnaire global subscale adequately predict eating disorder psychopathology in the daily life of obese adults? Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity, 23(4), 521–526. 10.1007/s40519-017-0410-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Physical Activity Guidelines Advisory Committee. (2018). Physical activity guidelines advisory committee scientific report. U.S. Department of Health and Human Services. Retrieved April 22, 2019, from https://health.gov/paguidelines/guidelines/report.aspx [Google Scholar]
  33. Reed J, & Ones DS (2006). The effect of acute aerobic exercise on positive activated affect: A meta-analysis. Psychology of Sport and Exercise, 7(5), 477–514. 10.1016/j.psychsport.2005.11.003 [DOI] [Google Scholar]
  34. Rhodes RE, & Kates A (2015). Can the affective response to exercise predict future motives and physical activity behavior? A systematic review of published evidence. Annals of Behavioral Medicine, 49(5), 715–731. 10.1007/s12160-015-9704-5 [DOI] [PubMed] [Google Scholar]
  35. Roshanaei-Moghaddam B, Katon WJ, & Russo J (2009). The longitudinal effects of depression on physical activity. General Hospital Psychiatry, 31(4), 306–315. 10.1016/j.genhosppsych.2009.04.002 [DOI] [PubMed] [Google Scholar]
  36. Teychenne M, Ball K, & Salmon J (2008). Physical activity and likelihood of depression in adults: A review. Preventive Medicine, 46(5), 397–411. 10.1016/j.ypmed.2008.01.009 [DOI] [PubMed] [Google Scholar]
  37. Vancampfort D, De Herdt A, Vanderlinden J, Lannoo M, Adriaens A, De Hert M, Stubbs B, Soundy A, & Probst M (2015). The functional exercise capacity and its correlates in obese treatment-seeking people with binge eating disorder: An exploratory study. Disability and Rehabilitation, 37(9), 777–782. 10.3109/09638288.2014.942000 [DOI] [PubMed] [Google Scholar]
  38. Vancampfort D, Vanderlinden J, Stubbs B, Soundy A, Pieters G, Hert MD, & Probst M (2014). Physical activity correlates in persons with binge eating disorder: A systematic review. European Eating Disorders Review, 22(1), 1–8. 10.1002/erv.v22.1 [DOI] [PubMed] [Google Scholar]
  39. Watson D, Clark LA, & Tellegen A (1988). Development and validation of brief measures of positive and negative affect: the panas scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. [DOI] [PubMed] [Google Scholar]
  40. Wonderlich JA, Lavender JM, Wonderlich SA, Peterson CB, Crow SJ, Engel SG, … Crosby RD (2015). Examining convergence of retrospective and ecological momentary assessment measures of negative affect and eating disorder behaviors. International Journal of Eating Disorders, 48(3), 305–311. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Wonderlich SA, Gordon KH, Mitchell JE, Crosby RD, & Engel SG (2009). The validity and clinical utility of binge eating disorder. International Journal of Eating Disorders, 42(8), 687–705. 10.1002/eat.20719 [DOI] [PubMed] [Google Scholar]
  42. Young MD, Plotnikoff RC, Collins CE, Callister R, & Morgan PJ (2014). Social cognitive theory and physical activity: A systematic review and meta-analysis. Obesity Reviews, 15(12), 983–995. 10.1111/obr.2014.15.issue-12 [DOI] [PubMed] [Google Scholar]

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