Food addiction and lifetime alcohol and illicit drugs use in specific eating disorders

Breadth of substance use is associated with the selection of a larger food portion size via elevated impulsivity

Substance use is associated with altered or elevated food consumption and disordered eating. In the present study we examined whether breadth (variety) of drug use was associated with elevated portion size in a general population sample as it was in persons in recovery from substance use disorder. Furthermore, measures of emotional eating, impulsivity, food misuse, food craving were taken as possible mediators and reward responsiveness was examined as a potential moderator of this association. 444 adults (48.6 % women, mean age of 47.8 years) completed an online study in which they were asked to make judgements of ideal portion size for 6 different foods using a validated online tool that allowed participants to adjust the portion size of images of foods. Ideal portion size has been identified as a strong predictor of actual consumption. Participants were also asked to report the number of substances used in the past and provide anthropometric information. The results confirmed that breadth of drug use was associated with selection of higher portion size. Reward responsiveness was not a moderator of this relationship. Of the tested mediators, only impulsivity mediated the association between breadth of drug use and portion size. The results show that impulsivity may underlie the association between eating and substance use.

The Role of Food Addiction and Lifetime Substance Use on Eating Disorder Treatment Outcomes

Food addiction (FA) and substance use (SU) in eating disorders (ED) have been associated with a more dysfunctional clinical and psychopathological profile. However, their impact on treatment outcomes has been poorly explored. Therefore, this transdiagnostic study is aimed at examining whether the presence of FA and/or SU is associated with treatment outcomes in patients with different ED types. The results were not able to reveal significant differences in treatment outcomes between patients with and without FA and/or SU; however, the effect sizes suggest higher dropout rates in the group with both FA and SU. The predictive models of treatment outcomes showed different features associated with each group. High persistence (i.e., tendency to perseverance and inflexibility) was the personality trait most associated with poor treatment outcomes in patients without addictions. High harm avoidance and younger age at ED onset were the variables most related to poor outcomes in patients with FA or SU. Finally, in the group with both addictive behaviors (FA and SU), the younger patients presented the poorest outcomes. In conclusion, our results suggest that, regardless of presenting addictive behaviors, patients with ED may similarly benefit from treatment. However, it may be important to consider the differential predictors of each group that might guide certain treatment targets.

Value-based decision-making network functional connectivity correlates with substance use and delay discounting behaviour among young adults

Substance use disorders are characterized by reduced control over the quantity and frequency of psychoactive substance use and impairments in social and occupational functioning. They are associated with poor treatment compliance and high rates of relapse. Identification of neural susceptibility biomarkers that index risk for developing a substance use disorder can facilitate earlier identification and treatment. Here, we aimed to identify the neurobiological correlates of substance use frequency and severity amongst a sample of 1,200 (652 females) participants aged 22-37 years from the Human Connectome Project. Substance use behaviour across eight classes (alcohol, tobacco, marijuana, sedatives, hallucinogens, cocaine, stimulants, opiates) was measured using the Semi-Structured Assessment for the Genetics of Alcoholism. We explored the latent organization of substance use behaviour using a combination of exploratory structural equation modelling, latent class analysis, and factor mixture modelling to reveal a unidimensional continuum of substance use behaviour. Participants could be rank ordered along a unitary severity spectrum encompassing frequency of use of all eight substance classes, with factor score estimates generated to represent each participant's substance use severity. Factor score estimates and delay discounting scores were compared with functional connectivity in 650 participants with imaging data using the Network-based Statistic. This neuroimaging cohort excludes participants aged 31 and over. We identified brain regions and connections correlated with impulsive decision-making and poly-substance use, with the medial orbitofrontal, lateral prefrontal and posterior parietal cortices emerging as key hubs. Functional connectivity of these networks could serve as susceptibility biomarkers for substance use disorders, informing earlier identification and treatment.

Understanding eating behaviours, mental health and weight change in young adults: protocol paper for an international longitudinal study

INTRODUCTION

Understanding the complexities of change in eating behaviours, mental health, well-being and weight is crucial to inform healthcare and service provision, particularly in light of the exacerbating effects of the COVID-19 pandemic. This study aims to address the need for more comprehensive cross-sectional and longitudinal evidence, by tracking eating behaviours, mental health, health related behaviours and weight over a 12-month period, in a sample of young adults (18-35 years) in the UK and Australia.

METHODS AND ANALYSIS

Online surveys administered via the Prolific online research platform will be used for data collection at baseline, 6 months and 12 months. The survey (approximately 45 min) measures demographics, the impact of COVID-19, body mass index (BMI), weight management and health service usage, eating behaviours, personality, mental health, and health-related behaviours. An optional substudy component at each time point aims to validate self-reported weight in the main survey through images. Study inclusion criteria are; aged 18-34 years at baseline, BMI ≥20 kg/m², and residing in the UK or Australia. A target of 500 participants at baseline was set, recruited through Prolific, and with recruitment stratified by BMI, sex and country. The proposed analyses include creating static predictive models using baseline data (eg, using latent class analysis, factor analysis or similar), and mapping changes longitudinally (eg, using multivariate regressions). These analyses will enable changes in the study measures to be identified, as well as predictors and outcomes of change.

ETHICS AND DISSEMINATION

Ethical approval was granted by Leeds Beckett University, UK (reference number 86004) and the University of Newcastle, Australia (reference number H-2022-0110). Study findings will be disseminated through scientific journals, conferences, institute websites and social media, and briefings tailored to policy, practice and the public, with the intention to help inform the future development of health and well-being care and support for young adults across Australia and the UK.

Clinical Considerations of Ultra-processed Food Addiction Across Weight Classes: an Eating Disorder Treatment and Care Perspective

Purpose of Review

To examine the prevalence rates of ultra-processed food addiction across different weight classes and offer guidelines for diagnosis and treatment. Clinicians are provided with practical considerations in the assessment of ultra-processed food addiction beyond the use of validated instruments.

Recent Findings

The weighted mean prevalence of ultra-processed food addiction is approximately 20% worldwide and varies widely based on the sample. At first glance, there appears a linear relationship between ultra-processed food addiction and BMI class. Further investigation indicates a J-shaped curve with heightened prevalence among the underweight. These findings highlight the need to assess for additional factors that may increase objective or subjective food addiction symptoms including eating disorders, dietary restraint, and other mental health diagnoses.

Summary

While clinical considerations across different weight classes vary, overemphasis on weight status may detract from the clinical utility of the ultra-processed food addiction construct. Considering weight status in conjunction with other psychiatric symptoms helps to better understand the various biopsychosocial mechanisms that influence eating behavior and can inform individualized treatment strategies.