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. Author manuscript; available in PMC: 2026 May 1.
Published in final edited form as: Appetite. 2025 Aug 7;216:108261. doi: 10.1016/j.appet.2025.108261

Negative Affect Mediates the Association between Nightly Sleep Disturbance and Next-day Binge Eating

Elizabeth W Lampe 1,2, Rebecca J Crochiere 3, Jannah R Moussaoui 2, Caroline Martin 1,2, Destiny Crisp 3, Ashley Kim 3, Adrienne S Juarascio 1,2, Stephanie M Manasse 1,2
PMCID: PMC13129479  NIHMSID: NIHMS2165937  PMID: 40782833

Abstract

Sleep disturbance has been linked with both increased negative affect and engagement in binge-eating (BE; i.e., eating episodes accompanied by a subjective sense of loss-of-control over eating). Negative affect itself is also predictive of BE. As such, it is possible that the effect of sleep disturbance on BE can be explained by increases in negative affect. We recruited adults with clinically significant BE (N = 96, Mage = 41.9 ± 14.1, 80.4% female) to complete seven ecological momentary assessment surveys per day assessing sleep disturbance (morning surveys only), negative affect, and BE over 7-14 days. Mediation models evaluated whether there was an indirect effect of within-person increases in negative affect prior to binge eating on the association between within-person sleep disturbance (i.e., poor sleep quality, heightened morning fatigue, and short sleep duration relative to one’s average) and binge eating. Pre-binge levels of negative affect mediated the association between both sleep quality (Est = −0.019, S.E. = 0.009, p = 0.028) and morning fatigue (Est = 0.020, S.E. = 0.009, p = 0.024) and BE. Negative affect did not significantly mediate the association between sleep duration and BE. Negative affect may be one mechanism linking sleep disturbance and BE. These findings suggest that treatments targeting sleep disturbance merit evaluation in eating disorder populations as they could eliminate sleep-related NA as a driver of BE. Future research should include objective assessment of sleep and test the additive benefit of interventions targeting sleep for BE.

Keywords: Bulimia nervosa, Eating Disorder, Binge eating, Negative affect, Sleep

1. Introduction

Binge-spectrum eating disorders (BSEDs), such as bulimia nervosa and binge eating disorder, are characterized by the experience of binge-eating (BE; i.e., a subjective sense of loss-of-control over one’s eating) and are associated with numerous adverse physical and psychological sequelae (Kessler et al., 2013; Udo et al., 2019; Udo & Grilo, 2018, 2019). Current front-line treatments for BSEDs obtain only modest outcomes, with up to 60% of individuals still engaging in BE at post-treatment (Linardon et al., 2018). Thus, it is critical to better understand both daily and momentary factors driving continued engagement in BE, and their mechanisms of action (i.e., mediators of these relationships).

One factor with growing support for its role in BE engagement is sleep disturbance. Sleep disturbance is highly comorbid with BE behavior (Allison et al., 2016), and increased sleep disturbance is associated with increased BE frequency (Kim et al., 2010). However, minimal research has investigated sleep disturbance as a direct predictor of BE, which is needed for inferences of causality and appropriate treatment targets. Furthermore, research investigating the relations between sleep disturbance and BE has primarily focused on between-subject effects (Cerolini et al., 2018; Kim et al., 2010), which limits understanding of individual-level relationships between sleep disturbance and BE which could better inform intervention approaches. To date, only one study (Manasse et al., 2022) has examined the within-subject, day-to-day directional relationships between sleep disturbance and eating disordered behaviors, including BE, among adults with eating disorders. However, this study did not evaluate any mechanisms driving observed relationships (i.e., mediators). As such, evaluating mediators of these relationships merits attention as this knowledge could inform more targeted interventions for BE.

For several reasons, negative affect (NA; i.e., the momentary experience of unpleasant emotions like sadness, guilt, and anxiety) has high potential to mediate the relationship between sleep disturbance and BE (Russell et al., 2017; Schaefer et al., 2020). First, empirical evidence supports that sleep disturbance leads to increased NA. For example, research has found that shorter sleep duration (Barber et al., 2023) and worse self-reported sleep quality (Difrancesco et al., 2021) both predict higher NA the following day. Second, there is both theoretical and empirical evidence to support that NA leads to BE. Theoretically, the affect regulation model of BE posits that individuals engage in BE as a maladaptive coping strategy to down-regulate negative emotions (Hawkins & Clement, 1984). Empirically, a meta-analysis of 36 studies using within-subject designs and ecological momentary assessment (EMA; brief, repeated surveys typically delivered to participants via smartphone devices) found that NA increased prior to BE episodes, relative to an individual’s average (Haedt-Matt & Keel, 2011). Other studies using EMA also found that the trajectory of NA accelerated in the hours closest to a BE episode and significantly decreased in a linear fashion following BE (Berg et al., 2015; Schaefer et al., 2020), as consistent with the affect regulation model (Hawkins & Clement, 1984). Given this evidence, it is plausible that sleep disturbance leads to increased NA, which in turn increases risk for BE.

Nevertheless, no research has examined whether average NA over the course of the day prior to BE episodes mediates the relation between sleep disturbance and BE at the within-subject level. The evidence above would suggest that greater sleep disturbance on any given night relative to one’s average level predicts increased NA relative to one’s average level the following day, which in turn may contribute to engagement in BE that same day. Further, it is possible that the association between within-person sleep disturbance and next-day BE may only be present when sleep disturbance leads to elevated NA, which could explain robust links between sleep disturbance and BE at the between-person level but a lack of such findings at the within-person level. If such a relationship exists, treatments for BE could target sleep disturbance, which in turn may alleviate subsequent NA and consequently reduce the risk of BE. Additionally, momentary interventions could also cue the use of targeted skills for managing elevated NA when individuals report worse sleep than usual.

Thus, the present analysis builds on that of Manasse et al. (2022) by isolating the potential mediating effect of daily average pre-binge NA on the relation between nightly sleep disturbance and next-day BE at the within-person level among a sample of 96 adults with BE. Participants completed seven daily EMA surveys assessing sleep disturbance (i.e., sleep quality, duration, and morning fatigue), NA, and BE. We hypothesized that increases in average NA prior to BE relative to one’s own daily average would mediate the association between nightly decreases in sleep quality, decreases in sleep duration, and increases in fatigue relative to one’s average levels, and odds of BE that day.

2. Method

2.1. Participants

Participants (N = 96) were treatment-seeking adults with BSEDs, as determined via the Eating Disorder Examination interview (EDE; Fairburn et al., 2014) who received EMA items assessing sleep disturbance. While the parent study included 107 individuals with BE, only 96 received daily EMA surveys assessing sleep disturbance. To be included in the present study, participants had to be living in the United States, experience an average of at least one objective or subjective binge-eating episode per week over the previous 12 weeks, be willing to complete surveys on their smartphone for the course of the study, and had at least 7 days before their first treatment session. Participants were excluded from the present study if they were unable to fluently speak, write, and read English, had a body mass index (BMI) lower than 18.5, were planning to begin or currently in treatment for BE, or had a mental or psychological condition that would limit their ability to participate.

2.2. Procedures

Interested participants completed an informed consent, subsequently set up the EMA application on their smartphone, and were trained on how to report BE episodes. Each day, participants were asked to complete seven signal-contingent EMA surveys (1 morning survey assessing past-night sleep characteristics at 9:00 AM, and 6 surveys semi-randomly distributed throughout the day) for 7–14 days prior to treatment initiation (see Manasse et al, 2022 for more information). Participants were also instructed to complete an event-contingent survey after engaging in BE. All study procedures were approved by the Institutional Review Board at Drexel University.

2.3. Measures

2.3.1. Negative Affect.

NA was measured at each signal-contingent EMA survey using three PANAS items to minimize participant burden: guilt, sadness, and anxiety (Watson et al., 1988). Participants responded to each prompt using 5-point Likert scales ranging from 1 (not at all) to 5 (extremely). NA at each survey was scored by summing these three affective states. The daily average level of NA prior to a BE episode (i.e., pre-binge NA) was calculated by: a) averaging the NA scores up to the survey where a BE episode was reported on binge days; b) averaging all NA scores from the day on non-binge days.

2.3.2. Sleep characteristics.

Sleep quality was measured by asking participants, “How well did you sleep last night?” Morning fatigue was assessed by asking, “How tired do you currently feel?” Participants responded to both these items on a 0-4 Likert scale, where a lower score indicated lower sleep quality and fatigue. Sleep duration was measured by asking participants “What time did you go to bed last night?” and “What time did you wake up this morning?” Participants selected a 30-minute interval for each, ranging from “before 7:00 PM” to “after 5:00 AM” for bedtime and “before 4:00 AM” to “after 1:00 PM” for wake time. Duration was calculated as the difference between bed and wake times.

2.3.3. Binge Eating.

BE was measured through dichotomous endorsement of loss of control over eating (yes/no) at each EMA survey. BE was described to participants as, “a sense that you can’t stop eating once you start eating and/or that you can’t control your eating.” BE episodes were aggregated at the day-level using a binary function (1 = binge day; 0 = non-binge day). We chose not to assess binge size via EMA to reduce participant burden given evidence that the experience of loss-of-control over eating is the feature of BE most associated with impaired quality of life and elevated psychopathology (Latner et al., 2007; Mond et al., 2010). Thus, the current analyses include both objectively and subjectively large binge episodes.

2.4. Statistical Analysis

The ‘lavaan’ package in R (R Core Team, 2023; Rosseel, 2012) was used to test the mediating effect of within-person centered average daily NA prior to BE on the association between within-person centered sleep characteristics (i.e., sleep quality, sleep duration, and morning fatigue; entered in separate models) and next-day BE. The models examined four pathways: a) the effect of within-person nightly sleep disturbance on within-person pre-binge NA the next day; b) the effect of within-person pre-binge NA on same-day BE; c) the effect of within-person sleep disturbance on next-day BE, and c’) the mediating effect of within-person NA on the relation between within-person sleep disturbance and next-day BE. All pathways controlled for age, sex, BMI, ED diagnosis (BN- vs. BED-spectrum), and grand-mean centered sleep characteristics and NA. Data and code are publicly available at https://osf.io/gwfh2.

3. Results

Participant descriptives can be found in Table 1. There were a total of 301 BE episodes and 617 pre-binge NA ratings within the data. Results of models evaluating the mediating effect of average levels of NA prior to BE on the association between nightly sleep disturbance and next-day BE are presented in Figure 1. Elevations in daily average NA prior to BE relative to one’s own average significantly mediated the association between poorer sleep quality relative to one’s average level and next-day BE (Est = -0.019, S.E. = 0.009, p = 0.028; Table 2). Elevations in daily average NA prior to BE relative to one’s own average also significantly mediated the association between higher morning fatigue relative to one’s average level and next-day BE (Est = 0.020, S.E. = 0.009, p = 0.024; Table 2). The mediating effect of average pre-binge NA on the association between within-person centered sleep duration and next-day BE was not statistically significant (see Table 2).

Table 1.

Participant and EMA descriptives.

M (SD)
Age 41.88 (14.1)
Body Mass Index 35.02 (8.8)
Sex N (%)
  Male 19 (19.6)
  Female 77 (80.4)
Race/Ethnicity N (%)
  White (75.2)
  Black (10.5)
  Asian (2.9)
  American Indian/Alaska Native (1.0)
  Multiracial (6.7)
  Unknown/prefer not to say (3.8)
  Hispanic/Latinx (10.4)
Eating Disorder Diagnostic Groups N (%)
  Sub-threshold bulimia nervosa 19 (19.6)
  Full-threshold bulimia nervosa 26 (26.8)
  Sub-threshold binge eating disorder 13 (13.4)
  Full-threshold binge eating disorder 38 (39.2)
EMA Descriptives M (SD) Observed Range
  BE episodes during recording period 4.10 (2.57) 1-12
  Sleep quality 2.21 (0.82) 0-4
  Morning fatigue 1.87 (0.87) 0-4
  Sleep duration (hours) 7.84 (0.97) 3-14.5
  Pre-binge NA 4.43 (2.94) 3-15
  Days of EMA completed 12 (2.48) 7-16
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Note. Participants received sub-threshold binge eating disorder diagnoses if they experienced < 12 objectively large BE episodes and sub-threshold bulimia nervosa diagnoses if they reported < 12 compensatory behaviors in the past three months at baseline.

Figure 1.

Figure 1.

Open in a new tab

Models evaluating (A) the mediating effect of within-person negative affect on the association between within-person sleep quality and next-day binge eating, (B) the mediating effect of within-person negative affect on within-person morning fatigue and next-day binge eating, and (C) the mediating effect of within-person negative affect on within-person sleep duration and next-day binge eating.

Table 2.

Models evaluating the mediating effect of within-person negative affect on the associations between within-person sleep quality and next-day binge eating, within-person morning fatigue and next-day binge eating, and within-person sleep duration and next-day binge eating.

Pathway Est. S.E. z p
a SQ - NA −0.352 0.114 −3.084 0.002*
b NA - BE 0.055 0.017 3.150 0.002*
c SQ - BE 0.011 0.042 0.261 0.794
c’ SQ - NA - BE −0.019 0.009 −2.204 0.028*
a MF - NA 0.392 0.105 3.726 < 0.001*
b NA - BE 0.050 0.018 2.847 0.004*
c MF – BE 0.040 0.039 1.023 0.306
c’ MF - NA - BE 0.020 0.009 2.262 0.024*
a SD - NA 0.011 0.087 0.130 0.897
b NA - BE 0.050 0.017 2.895 0.004*
c SD – BE −0.014 0.031 −0.436 0.050
c’ SD - NA - BE 0.001 0.004 0.130 0.897
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Note. SQ = within-person sleep quality; NA = within-person negative affect; BE = next-day binge eating; MF = within-person morning fatigue; SD = within-person sleep duration

4. Discussion

Results of the current study provide preliminary support for the hypothesis that within-person increases in NA mediate the association between decreased sleep quality and increased morning fatigue, relative to one’s average, and next-day BE. However, this mediation was not detected between sleep duration and BE. It is worth noting that while the a (direct effect of sleep disturbance on NA), b (direct effect of NA on BE), and c’ (indirect effect of sleep disturbance on BE via NA) pathways were statistically significant for both sleep quality and morning fatigue, we did not observe a significant direct effect of sleep quality or morning fatigue on next-day BE (c pathway) in this sample. While initially required by Baron & Kenney (1986), more modern approaches to mediation do not require a significant c pathway for mediation to be present (Fritz et al., 2015; Fritz & MacKinnon, 2007; Kenny & Judd, 2014; MacKinnon, 2012; MacKinnon et al., 2002; O’Rourke & MacKinnon, 2015, 2018). Most relevant to the current study, it is not uncommon to observe a significant indirect effect without a significant direct effect in small samples when the mediated effect and the total effect are equal (ab = c; O’Rourke & MacKinnon, 2018). In such cases, the test of the mediated effect has more statistical power than the test of the total effect (Kenny & Judd, 2014; O’Rourke & MacKinnon, 2015). Further, the difference in power between the indirect and direct pathways is greater when the mediator (NA) is measured closer in time to the outcome (BE) than to the predictor (sleep disturbance) as in the current study (O’Rourke & MacKinnon, 2018). As such, these findings suggest that elevations in NA relative to one’s average level can explain the effect of decreased sleep quality and increased morning fatigue, relative to one’s average, on next-day engagement in BE.

While a preponderance of literature has established the connection between elevated NA and BE (Haedt-Matt & Keel, 2011), and still more has evaluated interventions to decrease NA and prevent BE (e.g., Godfrey et al., 2015; Lammers et al., 2022), our findings suggest that we may be able to prevent some elevations in NA from ever occurring (and thus reduce engagement in BE) by targeting sleep disturbance. Specifically, these findings add to a growing body of literature (Kalmbach et al., 2014) demonstrating that individuals with BSEDs report higher NA following nights where they rated sleep quality lower and fatigue higher, relative to their average levels. Given this new understanding of NA as a mechanism prospectively linking sleep disturbance and BE, it is possible that interventions targeting sleep disturbance, such as Cognitive Behavioral Therapy for Insomnia (CBT-I), could reduce risk for BE by eliminating sleep-related elevations in NA (Cunningham & Shapiro, 2018; Muench et al., 2022).

Although somewhat surprising, the lack of a significant association between sleep duration and NA is not entirely inconsistent with past work. For example, mood has been found to progressively decline as sleep deprivation accumulates throughout the week (Dinges et al., 1997), and because we examined these relationships on the day-level, it is possible that sleep deprivation was too modest to detect an effect. Alternatively, it is possible that sleep duration could be harmful at both low and high levels (e.g., too much sleep could negatively impact NA and/or BE the subsequent day). Indeed past research has also observed this type of “u-shaped curve” in the association between sleep duration and affective outcomes (Konjarski et al., 2018), which could be translated into decreased risk for BE based on our findings above. Overall, these findings may suggest that the subjective quality of one’s sleep is more predictive of BE compared to discretely measured amount of sleep.

The strengths of this study lie in our use of EMA to obtain daily reports of sleep characteristics, which is likely more accurate than retrospective recall and allowed us to infer temporal relationships between within-person sleep disturbance, NA, and BE. Furthermore, this study recruited a transdiagnostic sample of adults with BSEDs, increasing the generalizability of our findings. Of course, this study is not without limitations. First, as we did not collect data on the presence of sleep disorders, we do not know their prevalence in this sample and could not control for them within statistical models. Second, while EMA provides significant advantages over long-term recall, it still relies on self-report, therefore making it prone to several forms of bias. Third, our measure of sleep duration asked about time spent in bed which could be different from the actual time spent asleep. Future work should aim to use sensor-based measures of sleep duration as well as sleep staging, via sleep studies and/or wearable devices, to complement subjective measures of sleep quality and morning fatigue. Using sensor-based approaches, future work should also rigorously examine other metrics relevant to sleep disturbance including sleep regularity, nighttime and early morning awakenings, and sleep latency. Investigation of these factors will better contribute to understanding the role of both sleep and circadian misalignment (e.g., misalignment of sleep/wake with feeding rhythms) and BE. Additionally, there is an opportunity for future work to employ passive sensing of related phenomena (e.g., phone/social media use before bed), which could contribute to sleep disturbance and negative affect, thus increasing risk for BE. Fourth, while work investigating the affect regulation model of BE typically centers NA, associations of BE with lower positive affect have also been observed. Further, sleep dysregulation has also been robustly associated with positive affect. While the current study was unable to evaluate positive affect as a mediator of within-day sleep-BE relationships, future work should seek to understand not the role of just NA, but also positive affect within these relationships. Fifth, while the current analysis was unable to differentiate between objectively- and subjectively-large BE episodes, it is possible that different relationships may be observed between sleep dysregulation and subjectively- or objectively-large binge eating episodes. Future research should aim to clarify these potential differences. Sixth, the current study was not able to evaluate the impact of emotion regulation capacity on the relationship between sleep dysregulation, elevated NA, and risk for BE. For example, it is possible that higher emotion regulation capacity could be a protective factor in the relationship between sleep dysregulation and BE by allowing individuals to down-regulate elevations in NA resulting from poor sleep before they experience a BE episode. Alternatively, prior literature has also identified sleep dysregulation as a risk factor for reduced emotion regulation capacity, and as such already low emotion regulation skills, as often observed in BE samples, could intensify the relationship between sleep dysregulation and BE via elevations in NA. As such, it will be critical to understand the role of emotion regulation capacity in these relationships within future research.

In conclusion, the present study provides preliminary evidence for the role of heightened NA in response to sleep disturbance in elevating risk for BE among adults with BSEDs. Continued research in this area will further clarify the underlying mechanisms and inform the development of effective, adjunctive interventions for BE. Future work should examine the impact of sleep-targeted interventions, particularly among those with comorbid BE and sleep disorders.

Funding:

Dr. Manasse was funded by the National Institutes of Health (K23DK124514).

Footnotes

Ethical Statement: All participants provided informed consent for their participation and all study procedures were approved by the Institutional Review Board at Drexel University.

Analytic plan pre-registration: The analysis plan was not pre-registered but was determined prior to data analysis.

Materials availability: Materials used to conduct the study are available upon reasonable request to the corresponding author.

Conflict of interest: No authors have any conflicts of interest to declare.

Data availability:

De-identified data from this study are available at https://osf.io/gwfh2.

Analytic code availability:

Analytic code used to conduct the analyses presented in this study are available at https://osf.io/gwfh2.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

De-identified data from this study are available at https://osf.io/gwfh2.

Analytic code used to conduct the analyses presented in this study are available at https://osf.io/gwfh2.

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