Executive functions and depressive symptoms interplay in binge eating disorder: A structural equation model analysis

Empirical validation of a developmental model for binge-eating disorder in adolescents: a structural equation modeling approach

Loss of control (LOC) eating is characterized by a reported sense of being unable to control food intake, regardless of the amount of food consumed. It is the hallmark feature of binge-eating episodes, which involve consuming an unusually large amount of food within a discrete time frame, accompanied by a sense of LOC over eating. Some studies investigating the progression of LOC-eating symptoms in children and adolescents suggest that LOC-eating may be a precursor to binge-eating disorder (BED) in adults. To explain the progression from LOC-eating in childhood and adolescence to BED in adulthood, Tanofsky-Kraff and her colleagues developed a theoretical model highlighting three main constructs: negative affectivity, reward sensitivity, and executive functioning. However, a thorough empirical validation of this model has not yet been performed. The current study aims to empirically test Tanofsky-Kraff and her colleagues' model via structural equation modeling (SEM) and explore potential gender and age differences within this framework. We surveyed 969 adolescents aged 12 to 18 years from the Quebec City area who completed self-report questionnaires. Our findings revealed that both negative affectivity and reward sensitivity are significantly associated with binge-eating symptomatology, whereas self-reported executive functioning is not significantly associated with binge-eating symptomatology. These results support several key components of the proposed model and provide insights into the interactions between the variables when tested simultaneously. Additionally, our study underscores the importance of considering individual factors such as age and gender in understanding binge-eating symptomatology.

Leveraging OGTT derived metabolic features to detect Binge-eating disorder in individuals with high weight: a "seek out" machine learning approach

Binge eating disorder (BED) carries a 6 times higher risk for obesity and accounts for roughly 30% of type 2 diabetes cases. Timely identification of early glycemic disturbances and comprehensive treatment can impact on the likelihood of associated metabolic complications and the overall outcome. In this study, machine learning techniques were applied to static and dynamic glucose-derived measures to detect BED among 281 individuals with high weight. Data from the classic (2 h) and the extended (5 h) glucose load were computed by multiple algorithms and two models with the most relevant features were trained to detect BED within the sample. The models were then tested on an independent cohort (N = 21). The model based on the 5 h-long glucose load exhibited the best performance (sensitivity = 0.75, specificity = 0.67, F score = 0.71) diagnosing BED in 7 out of 10 cases. Sex, HOMA-IR, HbA1c and plasma glucose in different times, and hypoglycemia events were the most sensitive features for BED diagnosis. This study is the first to use metabolic hallmarks to train ML algorithms for detecting BED in individuals at high risk for metabolic complications. ML techniques applied to objective and reliable glycemic features might prompt the identification of BED among individuals at high risk for metabolic complications, enabling timely and tailored multidisciplinary treatment.

Potential pathways to the onset and development of eating disorders in people with overweight and obesity: A scoping review

OBJECTIVE

To describe pathways to eating disorder (ED) development that have been evaluated in people with overweight and obesity.

METHODS

Four databases were searched to identify studies testing ED development models in adolescents (10-19 years) or adults (>19 years) with overweight and obesity. Explanatory variables were thematically grouped into constructs to describe pathways to each ED outcome.

RESULTS

Of 2226 studies screened, 46 (10 adolescent; 36 adult) were included. Study samples were predominantly female, ranging from 22 to 2236 participants and mean age 12.3 to 56.0 years. In total, 207 explanatory variables were grouped into 18 constructs to summarize 107 pathways that were identified. The most common ED outcome was binge eating (n = 24 studies), followed by global ED psychopathology (n = 10 studies). Across pathways to ED development, negative affect was the most proposed construct, followed by preoccupation with weight/shape and weight stigma.

CONCLUSION

Pathways to ED development in people with overweight and obesity are complex and may include more than 18 different explanatory factors of which negative affect, preoccupation with weight/shape, and weight stigma are the most common. More research on adolescents, males, and the spectrum of ED in diverse populations is required for early identification and intervention.

Dysfunctional decision-making in binge-eating disorder: A meta-analysis and systematic review

Binge-Eating Disorder (BED) involves anticipatory craving and urges, subjective loss-of-control during binge-eating episodes, and post-feeding psychological distress and guilt. Evidence indicates neurocognitive dysfunctions contribute to BED onset, maintenance, and treatment response. However, an integrated understanding of how cognitive processes underpin BED symptomology is lacking. We utilised a multi-stage decision-making model defining ten cognitive processes underpinning Preference Formation, Choice Implementation, Feedback Processing, and Flexibility/Shifting, to comprehensively review research published since 2013. We used preregistered PICOS criteria to assess 1966 articles identified from PubMed, PsycInfo, and Scopus database searches. This yielded 50 studies reporting behavioural cognitive tasks outcomes, comparing individuals with BED to controls with normal and higher weight. Meta-analyses revealed a unique profile of cognitive dysfunctions that spanned all decision-making stages. Significant deficits were evident in Uncertainty Evaluation, Attentional Inhibition, Choice Consistency, and Cognitive Flexibility/Set-shifting. We propose a novel model of dysfunctional decision-making processes in BED and describe their role in binge-eating behaviour. We further highlight the potential for cognitive interventions to target these processes and address the significant treatment gap in BED.

Executive Functions of Adults with Binge-Eating Disorder: The Role of Weight Status and Psychopathology

Findings on executive functions (EFs) in binge-eating disorder (BED) are inconsistent and possibly biased by associated comorbidities. This study aimed to identify whether distinct levels of physical and mental comorbidity are related to EFs in BED. General and food-specific EFs in n = 77 adults with BED were compared to population-based norms and associations with weight status, depressive symptoms, and eating disorder psychopathology were analyzed. To detect within-sample patterns of EF performance, k-means clustering was applied. The results indicated that participants' general EFs were within the average range with slight deficits in alertness. While depression and eating disorder psychopathology were unrelated to EFs, weight status was associated with food-specific attentional bias that was significantly higher in obesity class 2 than in overweight/obesity class 1 and obesity class 3. Four meaningful clusters with distinct strengths and impairments in general and food-specific EFs but without differences in clinical variables were identified. Altogether, adults with BED showed few specific deficits compared to normative data. Performance was unrelated to depression and eating disorder psychopathology, while weight status was associated with food-specific EFs only. The results highlight the need for longitudinal studies to evaluate the relevance of EFs in BED development and maintenance in neurologically healthy adults.