Food addiction in Bulimia Nervosa: Analysis of body composition, psychological and problematic foods profile

IntroductionFood Addiction (FA) has been related with eating disorders (ED), especially Bulimia Nervosa (BN). BN + FA may have different physical characteristics than patients with BN without the comorbidity, such as body mass index (BMI) or body composition, and psychological as emotion regulation. However, the relationship between psychological and physical aspects, connected by problematic food and its influence on body composition, has been barely studied. Therefore, the aims of the present study are: Aims(a) To explore the differences in body composition between FA positive (FA+) and negative (FA-) in women with BN; (b) to identify problematic relationship with certain food types, according with the foods mentioned in the YFAS scale questionnaire, between FA+ and FA- patients; (c) to know the psychological characteristic differences between FA+ and FA- patients, considering emotion regulation, personality traits and general psychopathological state; (d) to identify the relationship between physical and psychological traits, and the identified problematic foods, in patients with BN and FA. MethodologyN = 81 BN women patients, with a mean age of 29.73 years +/- 9.80 SD, who completed the questionnaires: Yale Food Addiction Scale V 1.0 (YFAS 1.0), Eating Disorder Inventory-2 (EDI-2), Symptom Checklist-90 Items-Revised (SCL-90-R), and Difficulties in Emotion Regulation Strategies (DERS). YFAS problematic foods were grouped considering their principal nutrients sources. Body composition and difference in metabolic age was determined using bioimpedance analyzer. ResultsThe 88% of patients with BN presented FA+. Patients with BN who were FA+ self-reported more problematic relationships with sweets and starches. Also presented higher emotion regulation difficulties, general psychopathology and eating symptomatology severity, than those without FA. Finally, emotional regulation difficulties were positively associated with higher eating disorder symptomatology and more types of foods self-reported as problematic, which increased indirectly fat mass. ConclusionThe results suggest that BN + FA presented more eating and psychopathology symptomatology and higher problems with specific food types. As well, the path analysis emphasized that emotion regulation difficulties might be related with problematic food relationship in BN, impacting over the ED severity. ImplicationsThe results may impact the development of precise therapies for patients with BN + FA

Which Foods May Be Addictive? The Roles of Processing, Fat Content, and Glycemic Load

http://deepblue.lib.umich.edu/bitstream/2027.42/109750/1/StudyOne_FoodListMeans.savhttp://deepblue.lib.umich.edu/bitstream/2027.42/109750/2/StudyOne_Demographics.savhttp://deepblue.lib.umich.edu/bitstream/2027.42/109750/3/StudyTwo_LevelOne.savhttp://deepblue.lib.umich.edu/bitstream/2027.42/109750/4/StudyTwo_LevelTwo.savDescription of StudyOne_FoodListMeans.sav : Dataset for calculating the food frequencies in Study One (Table 2)Description of StudyOne_Demographics.sav : Dataset for demographics in Study OneDescription of StudyTwo_LevelOne.sav : Dataset for HLM level one in Study TwoDescription of StudyTwo_LevelTwo.sav : Dataset for HLM level two in Study Tw

Which foods may be addictive? The roles of processing, fat content, and glycemic load.

We propose that highly processed foods share pharmacokinetic properties (e.g. concentrated dose, rapid rate of absorption) with drugs of abuse, due to the addition of fat and/or refined carbohydrates and the rapid rate the refined carbohydrates are absorbed into the system, indicated by glycemic load (GL). The current study provides preliminary evidence for the foods and food attributes implicated in addictive-like eating.Cross-sectional.University (Study One) and community (Study Two).120 undergraduates participated in Study One and 384 participants recruited through Amazon MTurk participated in Study Two.In Study One, participants (n = 120) completed the Yale Food Addiction Scale (YFAS) followed by a forced-choice task to indicate which foods, out of 35 foods varying in nutritional composition, were most associated with addictive-like eating behaviors. Using the same 35 foods, Study Two utilized hierarchical linear modeling to investigate which food attributes (e.g., fat grams) were related to addictive-like eating behavior (at level one) and explored the influence of individual differences for this association (at level two).In Study One, processed foods, higher in fat and GL, were most frequently associated with addictive-like eating behaviors. In Study Two, processing was a large, positive predictor for whether a food was associated with problematic, addictive-like eating behaviors. BMI and YFAS symptom count were small-to-moderate, positive predictors for this association. In a separate model, fat and GL were large, positive predictors of problematic food ratings. YFAS symptom count was a small, positive predictor of the relationship between GL and food ratings.The current study provides preliminary evidence that not all foods are equally implicated in addictive-like eating behavior, and highly processed foods, which may share characteristics with drugs of abuse (e.g. high dose, rapid rate of absorption) appear to be particularly associated with "food addiction.

Study Two: Average food ratings based on 7-point Likert scale (1 = not problematic at all, 7 = extremely problematic).¹

<p>¹ Information in parentheses was explicitly stated to participants. This decision was made because the addition of these ingredients would change the processing categorization and nutrition information of that food item.</p><p>Study Two: Average food ratings based on 7-point Likert scale (1 = not problematic at all, 7 = extremely problematic).<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117959#t003fn001" target="_blank">¹</a></p

Endorsement of YFAS Symptoms in Study One and Two.

<p>Endorsement of YFAS Symptoms in Study One and Two.</p

Study One: Average frequency count of how often a food was selected as problematic.¹

<p>¹ Information in parentheses was explicitly stated to participants. This decision was made because the addition of these ingredients would change the processing categorization and nutrition information of that food item.</p><p>Study One: Average frequency count of how often a food was selected as problematic.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117959#t002fn001" target="_blank">¹</a></p

Which Foods May Be Addictive? The Roles of Processing, Fat Content, and Glycemic Load

http://deepblue.lib.umich.edu/bitstream/2027.42/109750/1/StudyOne_FoodListMeans.savhttp://deepblue.lib.umich.edu/bitstream/2027.42/109750/2/StudyOne_Demographics.savhttp://deepblue.lib.umich.edu/bitstream/2027.42/109750/3/StudyTwo_LevelOne.savhttp://deepblue.lib.umich.edu/bitstream/2027.42/109750/4/StudyTwo_LevelTwo.savDescription of StudyOne_FoodListMeans.sav : Dataset for calculating the food frequencies in Study One (Table 2)Description of StudyOne_Demographics.sav : Dataset for demographics in Study OneDescription of StudyTwo_LevelOne.sav : Dataset for HLM level one in Study TwoDescription of StudyTwo_LevelTwo.sav : Dataset for HLM level two in Study Tw

&quot;Food addiction&quot; in patients with eating disorders is associated with negative urgency and difficulties to focus on long-term goals

Objectives: The present study aimed to investigate if eating disorder patients differ in specific personality traits depending on a positive screening of food addiction and to find a model to predict food addiction in eating disorder patients using measures of personality and impulsivity. Methods: 278 patients having an eating disorder self-reported on food addiction, impulsivity, personality, eating and general psychopathology. Patients were then split into two groups, depending on a positive or negative result on the food addiction screening. Analysis of variance was used to compare means between the two groups. Stepwise binary logistic regression was used to obtain a predictive model for the presence of food addiction. Results: Patients with food addiction had lower self-directedness, and more negative urgency and lack of perseverance than patients not reporting addictive eating. The probability of food addiction can be predicted by high negative urgency, high reward dependence, and low lack of premeditation. Conclusions: Eating disorder patients who have more problems to pursue tasks to the end and to focus on long-term goals seem to be more likely to develop addictive eating patterns