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Purpose: In people with obesity, food addiction (FA) tends to be associated with poorer outcomes. Its diagnosis can be challenging in primary care. Based on the SCOFF example, we aim to determine whether a quicker and simpler screening tool for FA in people with obesity could be developed, using artificial intelligence (machine learning)., Methods: The first step was to look for the most discriminating items, among 152 different ones, to differentiate between FA-positive and FA-negative populations of patients with obesity. Items were ranked using the Fast Correlation-Based Filter (FCBF). Retained items were used to test the performance of nine different predictive algorithms. Then, the construction of a graphic tool was proposed., Results: Data were available for 176 patients. Only three items had a FCBF score > 0.1: "I eat to forget my problems"; "I eat more when I'm alone"; and "I eat sweets or comfort foods". Naive Bayes classification obtained best predictive performance. Then, we created a 3-item nomogram to predict a positive scoring on the YFAS., Conclusion: A simple and fast screening tool for detecting high-disordered eating risk is proposed. The next step will be a validation study of the FAST nomogram to ensure its relevance for emotional eating diagnosis., Level of Evidence: Level V, cross-sectional descriptive study., Clinical Trial Registry Number: NCT02857179 at clinicaltrials.gov., (© 2021. Springer Nature Switzerland AG.)

The contribution of an addictive process to anorexia nervosa (AN) is an area of growing interest. Yet, little is known about how the food addiction concept (FA) may be of interest in understanding AN. This study investigates prevalence of FA diagnostic and its association with markers of severity in individuals with AN. We conducted a retrospective study in a sample of 73 patients with AN. We assessed FA with the Yale Food Addiction Scale 2.0, depressive and anxiety disorders, impulsivity (Beck Depression Inventory, STAI, BIS-11) and eating behavior (BITE, EDE-Q). Prevalence of FA in our sample was 47%. FA was significantly associated and positively correlated with the binge-eating/purging subtype of AN, higher levels of depression, anxiety and greater eating psychopathology. FA was not associated with level of impulsivity nor leptin and IGF-1 blood levels. The relationship between FA severity and AN severity was mediated by the severity of binge eating behaviors. Our results suggest that the presence of FA may represent a more severe variant of AN. Longitudinal studies are needed to better understand the etiologic process between FA and AN., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: The current study aimed to test whether food addiction (FA) might mediate the relationship between the presence of a history of childhood maltreatment and eating disorder (ED) symptom severity., Methods: Participants were 231 patients with ED presenting between May 2017 and January 2020 to a daycare treatment facility for assessment and management with mainly the Eating Disorder Inventory-2 (EDI-2), the Child Trauma Questionnaire (CTQ), and the Yale Food Addiction Scale (YFAS 2.0)., Results: Participants had a median age of 24 (interquartile range (IQR) 20-33) years and manifested anorexia nervosa (61.47%), bulimia nervosa (16.88%), binge-eating disorders (9.09%), and other types of ED (12.55%). They were grouped into those likely presenting FA ( N = 154) and those without FA ( N = 77). The group with FA reported higher scores on all five CTQ subscales, as well as the total score of the EDI-2 ( p < 0.001). Using mediation analysis; significant indirect pathways between all CTQ subscales and the EDI-2 total score emerged via FA, with the largest indirect effect emerging for physical neglect (standardized effect = 0.208; 95% confidence interval (CI) 0.127-0.29) followed by emotional abuse (standardized effect = 0.183; 95% CI 0.109-0.262)., Conclusion: These results are compatible with a model in which certain types of childhood maltreatment, especially physical neglect, may induce, maintain, and/or exacerbate ED symptoms via FA which may guide future treatments.

The objective of this study was to identify key elements from the 2007 Canada's Food Guide that should be included in a diet quality score aiming to reflect the risk of metabolic syndrome (MetS). Dietary intakes of 998 adults (mean age: 43.2 years, 50% women) were used to obtain the Canadian Healthy Eating Index 2007 (C-HEI 2007) and Alternative Healthy Eating Index 2010 (AHEI) scores, as well as a dietary pattern (DP) generated by the reduced rank regression (RRR) method. Based on these three scores, a modified version of the C-HEI 2007 (Modified C-HEI) was then proposed. The prevalence ratio (PR) of MetS was examined across diet quality scores using multivariate binomial regression analysis. A higher AHEI, Modified C-HEI, and a lower score for DP were all associated with a significantly lower prevalence of MetS (PR = 0.42; 95% confidence interval (CI) 0.28, 0.64; PR = 0.39; 95% CI 0.23, 0.63; and PR = 0.48; 95% CI 0.31, 0.74, respectively), whereas C-HEI 2007 was not (PR = 0.68; 95% CI 0.47, 1.00). Results suggest that a Modified C-HEI that considers key elements from the C-HEI 2007 and the AHEI, as well the DP, shows that participants with a higher score are less likely to have MetS.

Dietary patterns, representing global food supplies rather than specific nutrients or food intakes, have been associated with cardiovascular disease (CVD) incidence and mortality. The contribution of genetic factors in the determination of food intakes, preferences and dietary patterns has been previously established. The current study aimed to identify novel genetic factors associated with reported dietary pattern scores. Reported dietary patterns scores were derived from reported dietary intakes for the preceding month and were obtained through a food frequency questionnaire and genome-wide association study (GWAS) conducted in a study sample of 141 individuals. Reported Prudent and Western dietary patterns demonstrated nominal associations ( p < 1 × 10 -5 ) with 78 and 27 single nucleotide polymorphisms (SNPs), respectively. Among these, SNPs annotated to genes previously associated with neurological disorders, CVD risk factors and obesity were identified. Further assessment of SNPs demonstrated an impact on gene expression levels in blood for SNPs located within/near BCKDHB ( p = 0.02) and the hypothalamic glucosensor PFKFB3 ( p = 0.0004) genes, potentially mediated through an impact on the binding of transcription factors (TFs). Overrepresentations of glucose/energy homeostasis and hormone response TFs were also observed from SNP-surrounding sequences. Results from the current GWAS study suggest an interplay of genes involved in the metabolic response to dietary patterns on obesity, glucose metabolism and food-induced response in the brain in the adoption of dietary patterns., Competing Interests: The authors declare no conflict of interest.