Which came first? Exploring the reciprocal relations between impulsivity and binge eating

Personality and Individual Differences 151 (2019) 109538

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Which came first? Exploring the reciprocal relations between impulsivity and binge eating

T

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Aislin R. Mushquasha, , Laura McGeowna, Christopher J. Mushquasha, Daniel S. McGrathb a b

Department of Psychology, Lakehead University, 955 Oliver Rd, Thunder Bay P7B 5E1, Ontario, Canada Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary T2N 1N4, Alberta, Canada

A R T I C LE I N FO

A B S T R A C T

Keywords: Binge eating Impulsivity Longitudinal Cross-lagged analysis Reciprocal

Binge eating is exceedingly common in nonclinical samples of young adults, with epidemiological evidence that 49.1% and 30.0% of university-aged women and men, respectively, engage in episodic binge eating. Thus, there is impetus to identify dispositional factors contributing to the emergence and maintenance of binge eating. Impulsivity is well cited as an important vulnerability factor, as longitudinal studies have indicated impulsivity prospectively predicts future binge eating (i.e., a predisposing model). However, no studies to date have examined whether binge eating reciprocally influences future impulsivity (i.e., a complication model). In addition, no prior longitudinal studies have included men, despite evidence that a significant proportion engage in binge eating. To address these gaps in the literature, we conducted a short-term 3-week, 3-wave cross-lagged longitudinal design with 241 undergraduate students (186 women; 53 men). Consistent with our hypotheses, we found both impulsivity and binge eating exhibited strong stability over time, and impulsivity predicted future binge eating across all three waves of the study. Contrary to the complication model, binge eating did not predict future impulsivity. The findings from the current study suggest that personality-targeted prevention and intervention approaches targeting impulsivity may demonstrate clinical utility in attenuating binge eating symptomatology.

1. Introduction

exhibiting associations with particular symptomatology (e.g., Farstad, McGeown, & von Ranson, 2016). Personality is defined as a dynamic organization of psychophysical systems that generate an individual's characteristic patterns of behaviour, thoughts, and emotions (Carver & Scheier, 2016). One personality trait frequently implicated in binge eating symptomatology is impulsivity (K. Smith, Mason, Crosby, Engel, & Wonderlich, 2019), which refers to a predisposition to exhibit hasty reactions to internal or external stimuli without forethought or consideration of consequences (Steinberg, Sharp, Stanford, & Tharp, 2013). In a recent review, Farstad et al. (2016) discussed the association between various facets of impulsivity and eating disorders, and summarized that negative urgency (i.e., a tendency to engage in impulsive behaviours when distressed) is consistently associated with elevated levels of binge eating. However, the specific nature of this association is not clear. Various theoretical models exist to conceptualize the relationship between personality and disordered eating. Most often considered is the predispositional model, which implies a given trait precedes and increases risk for eating pathology (Lilenfeld, Wonderlich, Riso, Crosby, & Mitchell, 2006). The complication model, by contrast, does not presume traits precede

Binge eating is characterized by rapid consumption of an amount of food exceeding what most individuals would eat during a similar time period under comparable circumstances, often coupled with a perceived loss of control (APA, 2013). Though binge eating is a core symptom across eating disorders, a considerable proportion of community samples without diagnosed eating disorders report episodes of binge eating (Burton & Abbott, 2017; Mitchison, Touyz, GonzálezChica, Stocks, & Hay, 2017). Binge eating typically emerges during the early adult years (Kessler et al., 2013), with evidence 49.1% of women and 30.0% men, across 12 American colleges and universities engage in binge eating (Lipson & Sonneville, 2017). This eating behaviour is commonly associated with negative psychological outcomes (e.g., guilt, poor self-esteem; McManus & Waller, 1995) and can contribute to eating-related health problems (e.g., diabetes, obesity; Kessler et al., 2013). Given its prevalence and negative consequences, researchers and clinicians are interested in developing a better understanding as to why binge eating occurs and continues. Considerable attention has focused on links between eating disorders and personality, with specific traits

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Corresponding author. E-mail address: [email protected] (A.R. Mushquash).

https://doi.org/10.1016/j.paid.2019.109538 Received 24 April 2019; Received in revised form 20 June 2019; Accepted 28 July 2019 0191-8869/ © 2019 Elsevier Ltd. All rights reserved.

Personality and Individual Differences 151 (2019) 109538

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exist whereby initial impulsivity may promote binge eating, which may consequently exacerbate the probability of impulsive behaviour in the future.

disordered eating; rather, variation in personality is thought to emerge as a complication of the eating pathology itself, either due to acute symptomatology or due to longer-term scar effects following the resolution of symptoms (Lilenfeld et al., 2006). Thus, the optimal methodology to distinguish such relationships is a prospective longitudinal design (Lilenfeld et al., 2006). A relative dearth of prospective longitudinal research has been conducted exploring the link between impulsivity and binge eating, and existent studies have only examined the impact of impulsivity on binge eating, not vice versa. Indeed, impulsivity is well cited as a vulnerability factor for binge eating (Culbert, Racine, & Klump, 2015; Farstad et al., 2016). In longitudinal analyses, negative urgency prospectively predicts increases in binge eating over one semester among college women (Fischer, Peterson, & McCarthy, 2013) and among girls transitioning from elementary to middle school over a one-year period (Pearson, Zapolski, & Smith, 2015). Among the paucity of longitudinal studies examining this association, it is also interesting to note none have included men, despite a considerable number of men exhibiting binge eating behaviour (Lipson & Sonneville, 2017; Striegel, Bedrosian, Wang, & Schwartz, 2012), and men and women showing comparable levels of impairment associated with binge eating (Striegel et al., 2012). Furthermore, less is known about how binge eating might influence impulsivity, as no longitudinal analyses to date have explored reciprocal or bidirectional associations. It is possible that rather than reflecting an enduring personality trait, impulsivity may be influenced by the erratic dietary patterns and distress associated with binge eating (Cassin & von Ranson, 2005). Supporting this notion, Ames-Frankel et al. (1992) found emotional lability and indices of behavioural disinhibition attenuate following reductions in binge eating (as cited in Cassin & von Ranson, 2005). Theoretical models put forth to explain binge eating may also indirectly corroborate such a hypothesis. Herman and Mack's (1975) dietary restraint theory postulates dieting is a key factor maintaining binge eating. Dieters impose cognitively-mediated diet boundaries that often fall below physiological satiety to promote a negative energy balance for weight loss or suppression and certain “bad” foods are deemed off-limits, creating both physiological and psychological pressures to overeat (Herman & Polivy, 1983). Adoption of such unrealistic, rigid dietary rules inevitably leads to violations (Grilo & Shiffman, 1994). When such lapses occur, an allor-nothing mentality may lead to abandoning all control over eating, and consequently, prodigious ad-libitum consumption (Herman & Polivy, 1983). This phenomenon, denoted the “what-the-hell” effect (Herman & Polivy, 1983), resembles Marlatt and Gordon's (1985) abstinence violation effect in the addiction literature, whereby a lapse in self-control predicts escalation in the addictive behaviour (as cited in Grilo & Shiffman, 1994). Episodes of binge eating may affirm to individuals they lack self-control (Burton & Abbott, 2017). Such attributions of the self could plausibly influence later proclivity towards impulsive actions via a self-fulfilling prophecy. In fact, Grilo and Shiffman (1994) found those who made more intense internal, global, and uncontrollable causal attributions for a binge exhibited a shorter latency before their next binge. Heatherton and Baumeister's (1991) escape theory further proposes individuals binge eat to escape aversive self-awareness and emotional distress. As Cyders and Smith (2008) highlight, some rash actions prompted by individuals' impulsivity may be reinforced due to shortterm benefits procured. Indeed, binge eating appears to be negatively reinforced by producing a short-term improvement in mood (Leehr, Krohmer, Schag, Dresler, & Zipfel, 2015). Such immediate reinforcement associated with impulsive action in the form of binge eating could feasibly increase the likelihood of engaging in further rash behaviour in the future (i.e., enhancing impulsivity). This pattern of relying on impulsive actions to cope when faced with distress might also interfere with establishing more effective responding in the face of impulsive urges, thereby enhancing the link between binge eating and subsequent impulsivity (Cyders & Smith, 2008). Thus, a bidirectional cycle may

1.1. The current study Delineating the direction of the relationship between impulsivity and binge eating has important clinical implications with respect to prevention and treatment. The current study thus sought to empirically test the directionality of this association using a short-term 3-week, 3wave cross-lagged longitudinal design. This test will help ascertain whether impulsivity is a predisposing factor for binge eating, a complication of binge eating, or both. Similar models have been tested with other personality vulnerabilities for binge eating, such as perfectionism (M. Smith et al., 2017). Given anticipated inter-individual stability, it was expected impulsivity and binge eating would remain stable over time (e.g., M. Smith et al., 2017; Pearson et al., 2015). Based on prior literature, we also hypothesized impulsivity would predict binge eating over time (e.g., Fischer et al., 2013; Pearson et al., 2015). Finally, we explored whether binge eating prospectively predicted increased impulsivity; however, as the current study is the first to examine this relationship, no a priori hypothesis was put forth. 3. Method 3.1. Participants We recruited 241 undergraduate students (186 women; 53 men; 1 unidentified) at a medium-sized Canadian university.1 On average, participants were 21.74 years old (SD = 6.62) and had 1.79 years (SD = 1.11) of university education. Participants primarily self-identified as Caucasian (82.5%), and relatively equivalent proportions reported being single (46.47%) or in a dating relationship (42.32%). Average body mass index (BMI) was 23.96 (SD = 5.16) for women and 25.60 (SD = 5.80) for men. This sample resembles other undergraduate samples at Canadian universities (e.g., Mushquash & Sherry, 2012). 3.2. Measures 3.2.1. Impulsivity Impulsivity was measured as a latent variable using the following manifest indicators: Steinberg et al.'s (2013) 8-item Barratt Impulsivity Scale – Brief (BIS-B), the 12-item Dysfunctional Impulsivity subscale of Dickman's (1990) Impulsivity Inventory (DII-DI), and the 5-item Impulsivity subscale from the Substance Use Risk Profile Scale (SURPS-I; Woicik, Stewart, Pihl, & Conrod, 2009). Items on the BIS-B (e.g., “I do things without thinking”) were rated on a 4-point scale from 1 (rarely/ never) to 4 (almost always/always). Participants indicated whether items on the DII-DI (e.g., “I often get in trouble because I don't think before I act”) were true or false. Items on the SURPS-I (e.g., “Generally, I am an impulsive person”) were rated on a 4-point scale from 1 (strongly disagree) to 4 (strongly agree). These measures were selected as the reliability and validity of each is well supported in undergraduate samples (Davis MacNevin, Thompson, Teehan, Stuart, & Stewart, 2017; Dickman, 1990; Steinberg et al., 2013), while ensuring the assessment battery remained brief to minimize participant burden. Alpha reliabilities across all waves in our study were good (see Table 1). 3.2.2. Binge eating Binge eating was measured with the 7-item binge eating subscale of 1 Our sample size was selected based upon recommendations which generally advise at least 200 cases when testing complex structural equation models (Kline, 2011). We recruited > 200 to account for potential attrition throughout the study; however, our attrition rates were quite low.

2

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3.4. Data analysis

Table 1 Means, standard deviations, and alpha reliabilities for study variables. Wave 1

Impulsivity BIS-B DII-DI SURPS-I Binge eating EDDS-B

Wave 2

To determine the amount and pattern of missing data, we conducted missing values analysis in SPSS. Descriptive statistics were produced with SPSS. Gender differences across measures were examined with an independent samples t-test. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were conducted with AMOS 7.0. Unexplained variance for the same measures assessed across waves was correlated (Little T.D, 2013). As BMI has been associated with the variables of interest (e.g., Delgado-Rico, Río-Valle, González-Jiménez, Campoy, & Verdejo-García, 2012; Guss, Kissileff, Devlin, Zimmerli, & Walsh, 2002), we included it as a covariate when testing our model. A well-fitting model was indicated by a comparative fit index (CFI) and incremental fit index (IFI) > 0.95, and a root-mean-squared error of approximation (RMSEA) < 0.08 (Little, 2013). When comparing models, the change in CFI (i.e., ΔCFI) was used, with values < 0.01 suggesting the models do not significantly differ (Cheung & Rensvold, 2002). CFA was used to test for factorial invariance – whether relations between latent variables and their manifest indicators are consistent across time (Widaman, Ferrer, & Conger, 2010). First we evaluated model fit for an unconstrained model (i.e., a configural model). We then constrained corresponding factor loadings across time and assessed whether doing so would result in a significant loss of fit using ΔCFI. SEM was used thereafter to assess associations between impulsivity and binge eating, as well as the stability of these constructs, across time.

Wave 3

M

SD

α

M

SD

α

M

SD

α

16.65 2.81 10.24

3.91 2.92 2.71

0.78 0.82 0.75

16.58 2.68 9.97

3.94 2.99 2.71

0.79 0.84 0.76

16.15 2.92 9.94

4.17 3.00 2.73

0.83 0.85 0.78

17.17

9.63

0.90

15.31

8.87

0.91

13.87

8.36

0.91

Note. BIS-B = Barrett Impulsivity Scale – Brief; DII-DI = Dickman Impulsivity Inventory – Dysfunctional Impulsivity subscale; SURPS-I = Substance Use Risk Profile Scale – Impulsivity subscale; EDDS-B = Stice et al.'s (2000) Eating Disorder Diagnostic Scale – Binge eating subscale.

Stice, Telch, and Rizvi's (2000) Eating Disorder Diagnostic Scale (EDDSB). Participants responded to items (e.g., “There were times when I ate an unusually large amount of food and experienced a loss of control”) on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree). Studies support the reliability and validity of this measure (M. Smith et al., 2017). Alpha reliabilities across all waves in our study were good (see Table 1).

3.3. Procedure Lakehead University's Research Ethics Board reviewed and approved this protocol. Students were recruited through advertisements and announcements in classes, and through the Department of Psychology's online experiment management system. At Wave 1, students visited the laboratory and received information about the study. Upon providing consent, participants completed the aforementioned measures and were scheduled to return to the laboratory exactly one and two weeks from that date for Wave 2 and Wave 3 respectively. Of the 241 participants that began the study at Wave 1, 233 (96.68%) completed Wave 2, and 230 (95.44%) completed Wave 3. Congruent with the research design, Wave 2 took place an average of 7.15 (SD = 0.83) days after Wave 1; and Wave 3 took place an average of 14.42 (SD = 1.81) days after Wave1. After Wave 3, participants were debriefed and compensated with up to three bonus points towards an applicable undergraduate psychology course or were entered into a draw for $100.

4. Results 4.1. Descriptive statistics Missing data were minimal across all measures at each wave (0.4–1.2% Wave 1; 3.3–4.1% Wave 2; 4.1–5.4% Wave 3). (Little, R.J.A. 1988) MCAR test indicated data were missing completely at random (χ2 (107) = 99.21, p > .05). Missing data were handled via full information maximum likelihood estimation. Table 1 reports means, standard deviations, and alpha reliabilities for scales across waves, which are consistent with research involving similar samples (e.g., Davis MacNevin et al., 2017; M. Smith et al., 2017; Steinberg et al., 2013; Vigil-Colet & Codorniu-Raga, 2004). Bivariate correlations are reported in Table 2 and show strong test-retest correlations for measures of impulsivity (ranging from 0.79 to 0.90) and binge eating (ranging from

Table 2 Bivariate correlations. Manifest indicators

Wave 1 1. BIS-B 2. DII-DI 3. SURPS-I 4. EDDS-B Wave 2 5. BIS-B 6. DII-DI 7. SURPS-I 8. EDDS-B

Wave 1

Wave 2

Wave 3

1

2

3

4

5

6

7

8

9

10

11

12

–

0.67 –

0.69 0.66 –

0.24 0.29 0.32 –

0.85 0.71 0.71 0.30

0.66 0.89 0.66 0.31

0.62 0.66 0.79 0.35

0.29 0.23 0.33 0.77

0.84 0.70 0.72 0.33

0.67 0.90 0.68 0.31

0.69 0.64 0.82 0.30

0.25 0.26 0.28 0.70

–

0.75 –

0.72 0.69 –

0.30 0.27 0.38 –

0.91 0.74 0.73 0.36

0.73 0.90 0.65 0.25

0.73 0.67 0.82 0.32

0.28 0.26 0.35 0.79

–

0.74 –

0.76 0.67 –

0.34 0.25 0.29 –

Wave 3 9. BIS-B 10. DII-DI 11. SURPS-I 12. EDDS-B

Note. BIS-B = Barrett Impulsivity Scale – Brief; DII-DI = Dickman Impulsivity Inventory – Dysfunctional Impulsivity subscale; SURPS-I = Substance Use Risk Profile Scale – Impulsivity subscale; EDDS-B = Stice et al.'s (2000) Eating Disorder Diagnostic Scale – Binge eating subscale. Test-retest correlations appear in bold. All values are significant at p < .001. 3

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most strongly implicated in binge eating is negative urgency, reflecting a dispositional tendency to act rashly in response to negative affect (Fischer, Smith, & Cyders, 2008). Such evidence is in accordance with the escape theory of binge eating (Heatherton & Baumeister, 1991), suggesting individuals binge eat to escape aversive mood states or selfawareness. Arguably, once binge eating occurs, negative beliefs about binge eating (e.g., “I will gain weight”) and associated shame or guilt may elicit distress and negative self-awareness (Mitchison et al., 2017). To cope with distress associated with one's last binge episode, some may conceivably engage in further binge eating (Mitchison et al., 2017). Thus, it may be that binge eating indirectly influences impulsivity, and in particular, negative urgency, via enhancing individuals' distress. Perhaps if a measure directly assessing negative urgency was utilized, or if negative affect was measured and examined as a mediator, a prospective association between binge eating and impulsivity may have emerged. In addition, Pearson et al.'s (2015) prospective longitudinal study found impulsivity predicts elevated expectancies that eating will help manage negative affect, which consequently predict binge eating behaviour. Fischer, Anderson, and Smith (2004) also found the effect of trait urgency on binge eating was moderated by individuals' expectancies. As evidence suggests binge eating does, in fact, temporarily attenuate negative affective states (Leehr et al., 2015), binge eating may reinforce such expectancies, as individuals learn eating in response to distress is effective. It is possible that binge eating may therefore influence one's propensity to display and endorse impulsivity through enhancing one's expectations that engaging in rash behaviour leads to positive consequences. Lack of consideration of the viable role of these expectancies in the current study may have thus concealed a potential link between binge eating and future impulsivity. Given that this is the first study to explore the directionality of the impulsivity-binge eating link, it is recommended our null findings be interpreted with caution. Notably, subclinical binge eating is associated with significant distress, and even functional impairment, among individuals from community samples (Mitchison et al., 2017). As such, it is important to determine effective strategies to attenuate such symptomatology, even when it may not meet criteria for a diagnosable disorder. Our finding regarding the association between impulsivity and subsequent binge eating may have important clinical implications for treating, and perhaps even preventing, binge eating symptomatology. Using ecological momentary assessment (EMA), Engel et al. (2007) found impulsivity moderates the relationship between distress and binge eating, such that the association is stronger among women with elevated impulsivity. Targeting impulsivity in treatment and prevention efforts may thus attenuate the likelihood individuals' distress potentiates binge eating. Personality-targeted intervention approaches used to intervene with substance misuse and addiction (e.g., O'Leary-Barrett, CastellanosRyan, Pihl, & Conrod, 2016) may demonstrate utility in reducing binge eating. Among other high-risk personality traits, such approaches target those with elevated impulsivity to address the distinct motivations for problematic substance misuse specific to impulsivity in a preventative manner (O'Leary-Barrett et al., 2016). Parallels have notably been drawn between binge eating and addictive behaviours, with evident clinical and behavioural similarities such as loss of control, cravings, inability to cut down, and continued engagement in the behaviour despite negative consequences (Carter, Van Wijk, & Rowsell, 2019). In fact, negative urgency predicts elevated food addiction among undergraduate students (Pivarunas & Conner, 2015), and scores on the Yale Food Addiction Scale version 2.0 significantly predict binge eating frequency among those with binge eating disorder (Carter et al., 2019). Incorporating an addiction perspective may help by highlighting the role of strong neurobiological drives to overeat that might be heightened within the context of environments that exploit such vulnerabilities (Carter et al., 2019). Enhancing individuals' awareness of their impulsive urges could be integrated with instruction on strategies outlining how to inhibit urges following triggers to binge (Carter et al.,

0.70 to 0.79). As expected, impulsivity measures across all waves were related to binge eating measures across all waves. The majority of the study measures were consistent across gender (i.e., non-significant mean differences).2 4.2. CFA Our unconstrained (i.e., configural) model exhibited good fit: χ2 (33) = 49.24, p < .05, CFI = 0.99, IFI = 0.99, RMSEA = 0.05 (90% CI [0.01, 0.07]). Constraining corresponding factor loadings did not result in significant loss of fit (ΔCFI = 0.0005). Therefore, we used the factorially-invariant model for subsequent analyses. The impulsivity latent variables were measured well by their respective manifest indicates across time as suggested by significant (ps < 0.001) standardized factor loadings (0.85–0.90 [BIS-B]; 0.80–0.83 [DII-DI]; 0.81–0.84 [SURPS-I]). 4.3. SEM The fit of our model (see Fig. 1) with freely estimated autoregressive (e.g., between Wave 1 impulsivity and Wave 2 impulsivity) and crosslagged (e.g., between Wave 1 impulsivity and Wave 2 binge eating) paths was good: χ2 (49) = 82.64, p < .01, CFI = 0.99, IFI = 0.99, and RMSEA = 0.05 (90% CI [0.03, 0.07]). No significant loss of fit was observed after constraining corresponding autoregressive paths and cross-lagged paths to equality (ΔCFI = 0.0008), thereby suggesting equality constraints are justified. Consistent with hypotheses, autoregressive paths assessing stability in impulsivity and binge eating over time were significant (ps < 0.001). Cross-lagged paths from impulsivity to binge eating were also significant (p < .05); however, paths from binge eating to impulsivity were not significant. 5. Discussion To our knowledge, the current study is the first to examine the bidirectional relationship between binge eating and impulsivity using a prospective, longitudinal design, as well as the first longitudinal analysis to test this association with a sample including both men and women. In line with hypotheses and prior research (e.g., M. Smith et al., 2017; Pearson et al., 2015), binge eating and impulsivity displayed strong stability across all waves. This suggests impulsivity reflects a stable individual difference and, without intervention, binge eating is persistent over time among young, university-aged adults. Further corroborating previous findings (e.g., Fischer et al., 2013; Pearson et al., 2015), impulsivity predicted future binge eating. However, contrary to speculation, we found no evidence that binge eating prospectively predicted impulsivity. While our null findings may suggest that impulsivity is a cause rather than a consequence or complication of binge eating, it should be emphasized that the duration between each wave was short, and impulsivity showed strong stability. Consequently, there may have been minimal variance left for binge eating to account for over time. In testing our model, BMI was positively and significantly related to binge eating at Wave 1 and 2, but was unrelated to other model variables. Further longitudinal research spanning a longer time period is needed to more fully understand the role of BMI on the binge eating-impulsivity link. Furthermore, it is conceivable that there may be mediating factors in the proposed relationship between binge eating and future impulsivity that were unaccounted for in the current study. Failure to include such intermediary variables may have consequently obscured this potential association. As previously noted, the facet of impulsivity 2 The one exception was the SURPS Impulsivity subscale, which showed statistically significant differences (p < .05), such that men reported higher levels than women across each time point.

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Fig. 1. Ovals represent latent variables. Rectangles represent manifest indicators. Horizontal arrows represent autoregressive paths; diagonal arrows represent cross-lagged paths. Black paths are significant (p < .05); grey paths are non-significant (p > .05). Though unstandardized path coefficients were constrained to equality, standardized path coefficients (displayed) may still vary slightly. BMI was included as a covariate; however, in the interest of clarity, BMI is not displayed. BMI was significantly and positively related to binge eating at Wave 1 and 2 (p < .05) and unrelated (p > .05) to binge eating at Wave 3 and impulsivity at Waves 1, 2, and 3 (p > .05).

symptomatology, as men have historically been largely excluded within this literature. Such research is needed to reduce inaccurate perceptions that men do not encounter eating difficulties. Additionally, there is a critical need to conduct further longitudinal research to delineate prospective influences of personality on eating disorder symptomatology and to examine potential bidirectional relationships, akin to the current study. Such research can more clearly establish both vulnerability factors and maintaining mechanisms that may guide more effective prevention and intervention approaches. The results of this study suggest targeting impulsivity in prevention and intervention efforts may attenuate the emergence and maintenance of binge eating among young adults.

2019). 5.1. Limitations and future directions The results must be considered in the context of the study's limitations. In particular, a relatively short duration of prospective follow-up was used. It is possible a period longer, or perhaps shorter, than three weeks may be necessary to capture the impact of binge eating on later impulsivity. Longer longitudinal studies spanning multiple months may be beneficial to explore whether such a link is revealed over time. An extended longitudinal design could also enable researchers to discern whether the identified relationship between impulsivity and binge eating endures or eventually wanes over a period longer than three weeks. To explore whether binge eating predicts impulsivity on a shorter timescale, an EMA design could be used to discern whether individuals engage in a greater number of impulsive or risky behaviours in the days or hours closely following a binge, for example. Moreover, future studies could explore whether intermediary variables, such as individuals' expectancies or negative affect mediate the plausible link between binge eating and impulsivity over time, as described above. An additional limitation of the current study is the use of a monomethod and mono-source design. Reliance on self-report measures alone may be vulnerable to self-presentational biases and could be vulnerable to common method variance (Holmbeck, Li, Schurman, Friedman, & Millstein Coakley, 2002). Future studies could consider using behavioural tasks or observer ratings to validate the accuracy of self-reported impulsivity. Moreover, it may be ideal to utilize a clinical interview to assess binge eating symptomatology. Use of a standardized interview may ensure that differences in individuals' perceptions of a binge and recent colloquial use of the word “binge” to refer to indulgence in snack foods not meeting clinically-defined criteria for a binge do not unduly influence levels of reported binge eating. Additionally, as the sample was drawn from a nonclinical university population, it is unknown whether these findings will generalize to clinical populations, older adults, and youth. Further research is needed to establish the validity of these findings among such populations. It should also be highlighted that participants were not screened for the presence of clinically diagnosable eating disorders. Based on the results of the current study, it is unknown whether the relationship between impulsivity and binge eating would be consistent among those with binge eating disorder and bulimia nervosa compared to those presenting with subclinical binge eating. While this study is the first longitudinal study to our knowledge to include men in exploring the link between impulsivity and binge eating, we did not separately test the model in men and women due to our unequal sample sizes. Future studies could strive to recruit a large enough sample of both men and women to allow tests of a similar model across genders. Despite the aforementioned limitations, the current study represents an important contribution to the literature. It is essential to begin including men in research on disordered eating

Credit author statement Aislin R Mushquash: Conceptualization, Methodology, Formal Analysis, Writing – Original Draft, Writing – Review & Editing, Project Administration. Laura McGeown: Formal Analysis, Writing – Original Draft, Writing – Review & Editing. Christopher J Mushquash: Conceptualization, Methodology, Writing – Review & Editing, Project Administration. Daniel S McGrath: Conceptualization, Methodology, Writing – Review & Editing, Project Administration. Declaration of Competing Interest None. References American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.). Arlington, VA: American Psychiatric Publishing. Burton, A. L., & Abbott, M. J. (2017). Conceptualising binge eating: A review of the theoretical and empirical literature. Behaviour Change, 34(3), 168–198. https://doi. org/10.1017/bec.2017.12. Carter, J. C., Van Wijk, M., & Rowsell, M. (2019). Symptoms of ‘food addiction’ in binge eating disorder using the Yale Food Addiction Scale version 2.0. Appetite, 133, 362–369. https://doi.org/10.1016/j.appet.2018.11.032. Carver, C. S., & Scheier, M. F. (2016). Perspectives on personality (8th ed.). New York, NY: Pearson Education, Inc. Cassin, S. E., & von Ranson, K. M. (2005). Personality and eating disorders: A decade in review. Clinical Psychology Review, 25, 895–916. https://doi.org/10.1016/j.cpr.2005. 04.012. Culbert, K. M., Racine, S. E., & Klump, K. L. (2015). Research review: What we have learned about the causes of eating disorders – A synthesis of sociocultural, psychological, and biological research. Journal of Child Psychology and Psychiatry, 56(11), 1141–1164. https://doi.org/10.1111/jcpp.12441. Cyders, M. A., & Smith, G. T. (2008). Emotion-based dispositions to rash action: Positive and negative urgency. Psychological Bulletin, 134(6), 807–828. https://doi.org/10. 1037/a0013341. Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. https://doi. org/10.1207/S15328007SEM0902_5. Davis MacNevin, P., Thompson, K., Teehan, M., Stuart, H., & Stewart, S. (2017). Is personality associated with secondhand harm from drinking? Alcoholism: Clinical and Experimental Research, 41(9), 1612–1621. https://doi.org/10.1111/acer.13440. Delgado-Rico, E., Río-Valle, J. S., González-Jiménez, E., Campoy, C., & Verdejo-García, A.

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