Emotional eating: elusive or evident? Integrating laboratory, psychometric and daily life measures.

PURPOSE: Emotional eating (EE) refers to eating in response to (negative) emotions. Evidence for the validity of EE is mixed: some meta-analyses find EE only in eating disordered patients, others only in restrained eaters, which suggest that only certain subgroups show EE. Furthermore, EE measures from lab-based assessments, ecological momentary assessment (EMA), and psychometric measures often diverge. This paper tested whether the covariance of these three different EE methods can be modeled through a single latent variable (factorial validity), and if so, how this variable would relate to restrained eating (construct validity), Body-Mass-Index (BMI), and subclinical eating disorder symptomatology (concurrent validity). METHODS: 102 non-eating disordered female participants with a wide BMI range completed EE measures from three methods: psychometric questionnaires, a laboratory experiment (craving ratings of food images in induced neutral vs. negative emotion) and EMA questionnaires (within-participant correlations of momentary negative emotions and momentary food cravings across 9 days). Two measures for each method were extracted and submitted to confirmatory factor analysis. RESULTS: A one-factor model provided a good fit. The resulting EElat factor correlated positively with subclinical eating disorder symptoms and BMI but not with restrained eating. CONCLUSIONS: The one-factor solution shows that the EE construct can validly be assessed with three different methods. Individual differences in EE are supported by the data and are related to eating and weight problem symptomatology but not to restrained eating. This supports learning accounts of EE and underscores the relevance of the EE construct to physical and mental health. LEVEL OF EVIDENCE: II (Evidence obtained from well-designed controlled trials without randomization).

Predicting food craving in everyday life through smartphone-derived sensor and usage data.

Background: Food craving relates to unhealthy eating behaviors such as overeating or binge eating and is thus a promising target for digital interventions. Yet, craving varies strongly across the day and is more likely in some contexts (external, internal) than in others. Prediction of food cravings ahead of time would enable preventive interventions. Objective: The objective of this study was to investigate whether upcoming food cravings could be detected and predicted from passive smartphone sensor data (excluding geolocation information) without the need for repeated questionnaires. Methods: Momentary food craving ratings, given six times a day for 14 days by 56 participants, served as the dependent variable. Predictor variables were environmental noise, light, device movement, screen activity, notifications, and time of the day recorded from 150 to 30 min prior to these ratings. Results: Individual high vs. low craving ratings could be predicted on the test set with a mean area under the curve (AUC) of 0.78. This outperformed a baseline model trained on past craving values in 85% of participants by 14%. Yet, this AUC value is likely the upper bound and needs to be independently validated with longer data sets that allow a split into training, validation, and test sets. Conclusions: Craving states can be forecast from external and internal circumstances as these can be measured through smartphone sensors or usage patterns in most participants. This would allow for just-in-time adaptive interventions based on passive data collection and hence with minimal participant burden.

Toward Individualized Prediction of Binge-Eating Episodes Based on Ecological Momentary Assessment Data: Item Development and Pilot Study in Patients With Bulimia Nervosa and Binge-Eating Disorder.

BACKGROUND: Prevention of binge eating through just-in-time mobile interventions requires the prediction of respective high-risk times, for example, through preceding affective states or associated contexts. However, these factors and states are highly idiographic; thus, prediction models based on averages across individuals often fail. OBJECTIVE: We developed an idiographic, within-individual binge-eating prediction approach based on ecological momentary assessment (EMA) data. METHODS: We first derived a novel EMA-item set that covers a broad set of potential idiographic binge-eating antecedents from literature and an eating disorder focus group (n=11). The final EMA-item set (6 prompts per day for 14 days) was assessed in female patients with bulimia nervosa or binge-eating disorder. We used a correlation-based machine learning approach (Best Items Scale that is Cross-validated, Unit-weighted, Informative, and Transparent) to select parsimonious, idiographic item subsets and predict binge-eating occurrence from EMA data (32 items assessing antecedent contextual and affective states and 12 time-derived predictors). RESULTS: On average 67.3 (SD 13.4; range 43-84) EMA observations were analyzed within participants (n=13). The derived item subsets predicted binge-eating episodes with high accuracy on average (mean area under the curve 0.80, SD 0.15; mean 95% CI 0.63-0.95; mean specificity 0.87, SD 0.08; mean sensitivity 0.79, SD 0.19; mean maximum reliability of rD 0.40, SD 0.13; and mean rCV 0.13, SD 0.31). Across patients, highly heterogeneous predictor sets of varying sizes (mean 7.31, SD 1.49; range 5-9 predictors) were chosen for the respective best prediction models. CONCLUSIONS: Predicting binge-eating episodes from psychological and contextual states seems feasible and accurate, but the predictor sets are highly idiographic. This has practical implications for mobile health and just-in-time adaptive interventions. Furthermore, current theories around binge eating need to account for this high between-person variability and broaden the scope of potential antecedent factors. Ultimately, a radical shift from purely nomothetic models to idiographic prediction models and theories is required.

Prone to food in bad mood-Emotion-potentiated food-cue reactivity in patients with binge-eating disorder.

OBJECTIVE: Theories on emotional eating are central to our understanding of etiology, maintenance, and treatment of binge eating. Yet, findings on eating changes under induced negative emotions in binge-eating disorder (BED) are equivocal. Thus, we studied whether food-cue reactivity is potentiated under negative emotions in BED, which would point toward a causal role of emotional eating in this disorder. METHODS: Patients with BED (n = 24) and a control group without eating disorders (CG; n = 69) completed a food picture reactivity task after induction of negative versus neutral emotions. Food-cue reactivity (self-reported food pleasantness, desire to eat [DTE], and corrugator supercilii muscle response, electromyogram [EMG]) was measured for low- and high-caloric food pictures. RESULTS: Patients with BED showed emotion-potentiated food-cue reactivity compared to controls: Pleasantness and DTE ratings and EMG response were increased in BED during negative emotions. This was independent of caloric content of the images. CONCLUSIONS: Food-cue reactivity in BED was consistent with emotional eating theories and points to a heightened response to all foods regardless of calorie content. The discrepancy of appetitive ratings with the aversive corrugator response points to ambivalent food responses under negative emotions in individuals with BED.

(Mouse cursor)-Tracking food decisions in binge eating disorder reveals preference for high-energy foods and a role of BMI.

Binge Eating Disorder (BED) has been associated with deficits in cognitive control and decision-making. Yet, no study has yet investigated the characteristics of food choice and the involved choice conflict in this disorder. In the present study individuals with BED (N = 22) and without BED (N = 61), with a body mass index (BMI) between 21 and 44 completed 153 binary food decisions among foods varying in palatability and energy density. To assess conflict during choice we recorded computer mouse paths and reaction times. Subsequently, participants rated all foods on liking and energy content. Finally, participants completed a bogus taste test with the same foods to measure actual consumption. Predictors were modelled continuously using Bayesian mixed-effects modelling. Individuals with BED liked foods with higher energy content more and chose them more often in the choice task. Yet, actual consumption in the taste test did not differ between groups, neither regarding total consumption, nor of foods with higher energy. Mouse cursor-tracking revealed that control participants with higher BMIs showed more choice conflict than those with lower BMIs. This pattern was reversed in those with BED. The high-energy preference in ratings and food choice represent the first evidence in a controlled laboratory context for disorder-congruent food choice in BED. The fact that this was not reflected in actual consumption might have methodological implications for measuring laboratory eating behaviour. Mouse cursor-tracking gave further insights into choice processes and showed a less conflicted food choice in those with BED with higher BMI compared to those with lower BMI.

Bad mood food? Increased versus decreased food cue reactivity in anorexia nervosa and bulimia nervosa during negative emotions.

OBJECTIVE: Emotion regulation difficulties in anorexia nervosa (AN) and bulimia nervosa (BN) might underlie bingeing and purging in BN, extreme fasting in AN, or combinations of these symptoms in binge-purge type AN. In this study, we tested for decreased food cue reactivity in response to negative emotions in AN, and the opposite pattern for BN. Furthermore, we explored subgroup differences (restrictive vs. binge-purging AN; history of AN in BN). METHOD: Patients with AN (n = 41), BN (n = 39), and matched controls (n = 70) completed an emotional eating questionnaire. In a laboratory experiment, we induced negative emotions and measured food cue reactivity (pleasantness, desire to eat (DTE), and corrugator muscle activity). RESULTS: AN reported emotional undereating, while BN reported emotional overeating. In the laboratory task, BN showed increased DTE and an appetitive corrugator response during negative emotions, selectively towards high-calorie foods. AN showed generalized reduced cue reactivity to high-calorie food regardless of emotional state. This pattern appears to be characteristic of restrictive AN, while cue reactivity of both BN subgroups pointed towards emotional overeating. CONCLUSIONS: The emotional over- versus undereating framework might help to explain bingeing and restricting along the anorectic-bulimic disorder spectrum, which calls for novel transdiagnostic theories and subgroup-specific treatments.

Emotional eating across different eating disorders and the role of body mass, restriction, and binge eating.

OBJECTIVE: Different subtypes of eating disorders (ED) show dysfunctional eating behaviors such as overeating and/or restriction in response to emotions. Yet, systematic comparisons of all major EDs on emotional eating patterns are lacking. Furthermore, emotional eating correlates with body mass index (BMI), which also differs between EDs and thus confounds this comparison. METHOD: Interview-diagnosed female ED patients (n = 204) with restrictive (AN-R) or binge-purge anorexia nervosa (AN-BP), bulimia nervosa (BN), or binge-eating disorder (BED) completed a questionnaire assessing "negative emotional eating" (sadness, anger, anxiety) and "happiness eating." ED groups were compared to BMI-matched healthy controls (HCs; n = 172 ranging from underweight to obesity) to exclude BMI as a confound. RESULTS: Within HCs, higher BMI was associated with higher negative emotional eating and lower happiness eating. AN-R reported the lowest degree of negative emotional eating relative to other EDs and BMI-matched HCs, and the highest degree of happiness eating relative to other EDs. The BN and BED groups showed higher negative emotional eating compared to BMI-matched HCs. Patients with AN-BP occupied an intermediate position between AN-R and BN/BED and reported less happiness eating compared to BMI-matched HCs. DISCUSSION: Negative emotional and happiness eating patterns differ across EDs. BMI-independent emotional eating patterns distinguish ED subgroups and might be related to the occurrence of binge eating versus restriction. Hence, different types of emotional eating can represent fruitful targets for tailored psychotherapeutic interventions. While BN and BED might be treated with similar approaches, AN-BP and AN-R would need specific treatment modules.

Does stress eat away at you or make you eat? EMA measures of stress predict day to day food craving and perceived food intake as a function of trait stress-eating.

Eating behaviour can be driven by non-homeostatic factors like stress. Both increased and decreased food intake in response to stress has been documented, but it has remained difficult to identify a trait that predicts who shows either pattern. Thus, we collected naturalistic data from Ecological Momentary Assessment in combination with the trait-level Salzburg Stress Eating Scale (SSES). In study 1, 97 individuals completed the SSES and 6 daily reports about stress, food craving and perceived food intake across 8 days, whereas in study 2, 83 diet-interested participants completed the same measures at 4 daily prompts across 14 days. Consistent across both studies, multilevel modelling revealed that participants with high SSES-scores showed relatively more positive intra-day stress-craving relationships than those with low SSES-scores. On the day level, stress also predicted perceived food intake as a function of SSES-scores. Controlling for negative affect did not alter results. Results support an individual difference model of stress-eating where decrease vs increase of eating depends on SSES-scores. In affected individuals stress influences simultaneous food craving but might exhibit cumulative or delayed effects on food intake. Furthermore, the SSES provides a valid instrument for identifying at risk individuals and for tailoring interventions.

Fight, Flight, - Or Grab a Bite! Trait Emotional and Restrained Eating Style Predicts Food Cue Responding Under Negative Emotions.

In today's society, obesity rates are rising as food intake is no longer only a response to physiological hunger signals that ensure survival. Eating can represent a reward, a response to boredom, or stress reduction and emotion regulation. While most people decrease food intake in response to stress or negative emotions, some do the opposite. Yet, it is unclear who shows emotional overeating under which circumstances. Emotion regulation theories describe emotional overeating as a learned strategy to down-regulate negative emotions. Cognitive theories, by contrast, attribute emotional overeating to perceived diet breaches in individuals who chronically attempt to diet. After consuming "forbidden foods", they eat more than individuals who do not restrict their food intake. This laboratory study investigated emotional overeating by exposing individuals to a personalized emotion induction while showing images of palatable foods. Outcome variables indexed cue reactivity to food images through picture ratings (valence, desire to eat), facial expressions (electromyography of the corrugator supercilii muscle), and brain reactivity by detecting event-related potentials (ERPs) by means of electroencephalography (EEG). The influence of emotion condition (negative, neutral) and individual differences (self-reported trait emotional and restrained eating) on outcome variables was assessed. Valence ratings and appetitive reactions of the corrugator muscle to food pictures showed a relative increase in the negative condition for individuals with higher emotional eating scores, with the opposite pattern in lower scores. Desire to eat ratings showed a similar pattern in individuals who showed a strong response to the emotion induction manipulation, indicative of a dose-response relationship. Although no differences between conditions were found for ratings or corrugator activity with restrained eating as a predictor, an ERP at P300 showed increased activation when viewing food compared to objects in the negative condition. Findings support emotion regulation theories: Emotional eaters showed an appetitive reaction in rating patterns and corrugator activity. EEG findings (increased P300) suggest a motivated attention toward food in restrained eaters, which supports cognitive theories. However, this did not translate to other variables, which might demonstrate successful restraint. Future studies may follow up on these findings by investigating eating disorders with emotion regulation difficulties.

Emotional eating in healthy individuals and patients with an eating disorder: evidence from psychometric, experimental and naturalistic studies.

Emotional eating has traditionally been defined as (over)eating in response to negative emotions. Such overeating can impact general health because of excess energy intake and mental health, due to the risks of developing binge eating. Yet, there is still significant controversy on the validity of the emotional eating concept and several theories compete in explaining its mechanisms. The present paper examines the emotional eating construct by reviewing and integrating recent evidence from psychometric, experimental and naturalistic research. Several psychometric questionnaires are available and some suggest that emotions differ fundamentally in how they affect eating (i.e. overeating, undereating). However, the general validity of such questionnaires in predicting actual food intake in experimental studies is questioned and other eating styles such as restrained eating seem to be better predictors of increased food intake under negative emotions. Also, naturalistic studies, involving the repeated assessment of momentary emotions and eating behaviour in daily life, are split between studies supporting and studies contradicting emotional eating in healthy individuals. Individuals with clinical forms of overeating (i.e. binge eating) consistently show positive relationships between negative emotions and eating in daily life. We will conclude with a summary of the controversies around the emotional eating construct and provide recommendations for future research and treatment development.

Increased Screen Use on Days With Increased Perceived COVID-19-Related Confinements-A Day Level Ecological Momentary Assessment Study.

Introduction: Coronavirus 2019 (COVID-19) quickly evolved into a global pandemic in early 2020, and most countries enforced social confinements to reduce transmission. This seems to dovetail with increasing, potentially problematic, screen use habits, such as gaming and "binge-watching." Yet, the subjective experience of the common confinements may vary not only between individuals depending on age, sex, and living conditions (i.e., living alone) but also within individuals from day to day: confinements might interfere with habitual activity schedules more strongly on some days than on others. Such dynamic confinement experience has not been studied in relation to screen use yet but might guide targeted intervention. Method: In total, 102 participants (n = 83 female, n = 80 university students) completed 14 days of ecological momentary assessment during a COVID-19-related lockdown in Germany and Austria. Each evening, they indicated the extent to which they felt restricted by confinements in their social and work lives and whether they engaged in unusually high and intense levels of television watching, social media use, news consumption, internet surfing, and gaming. They also reported on how much they experienced their day to be structured. Results: Experienced work confinements were positively associated with social media usage. Further, work confinements were positively associated with gaming in males and with news consumption, especially in individuals living alone. Social confinements were positively associated with watching television especially in younger participants and with social media consumption in younger participants. Higher experienced day structure was related to less television watching, gaming, and internet surfing but more news consumption. Discussion: Screen use behaviors increased with higher confinements within person, dependent on sex, age, and living situation. Such knowledge allows tailoring on the person level (who should be addressed?) and the time level (when should interventions be scheduled?) as the negative consequences of excessive screen use behaviors on mental and physical health are well-documented. One potential low-threshold intervention might be day-structuring.