The factor structure of the metabolic syndrome in obese individuals with binge eating disorder

Volume changes of hippocampal and amygdala subfields in patients with mild cognitive impairment and Alzheimer's disease

BACKGROUND

Automated segmentation of hippocampal and amygdala subfields could improve classification accuracy of Mild Cognitive Impairments (MCI) and Alzheimer's Disease (AD) individuals.

METHODS

We applied T1-weighted magnetic resonance imaging (MRI) for 21 AD, 39 MCI and 32 normal control (NC) participants at 3-Tesla MRI. Twelve hippocampal subfields and 9 amygdala subfields in each hemisphere were analyzed using FreeSurfer 6.0.

RESULTS

Smaller volumes were observed in right/left whole hippocampus, right/left hippocampal tail, right/left subiculum, right Cornu ammonis 1(CA1), right/left molecular layer, right granule cell-molecular layer-dentate gyrus (GC-ML-DG), right CA4, right fimbria, right whole amygdala, right/left accessory basal, right anterior amygdala area, left central, left medial and right/left cortical nucleus of AD group compared to both MCI and NC groups (p < 0.001). The volumes of right presubiculum, right CA3, right hippocampus-amygdala-transition-area (HATA), right lateral, right basal, right central, right medial, right cortico-amygdaloid transition (CAT) and right paralaminar nucleus were significantly larger in NC than AD group (p ≤ 0.001), while the volumes of right subiculum, right CA1, right molecular layer, right whole hippocampus, right whole amygdala, right basal and right accessory basal were significantly larger in NC than MCI group (p ≤ 0.002). Trend analysis showed that most hippocampus and amygdala subfields have a trend of atrophy with the decline of cognitive function. Six core components were identified by the hierarchical clustering. The combined Receiver operating characteristic (ROC) analysis achieved the diagnostic performances (AUC: 0.81) in differentiating AD from MCI; (AUC: 0.79) in differentiating MCI from NC and (AUC: 0.97) in differentiating AD from NC.

CONCLUSIONS

Volumetric differences of hippocampus and amygdala were at a finer subfields scale, and the volumes of right basal nucleus, left parasubiculum, left medial nucleus, left GC-ML-DG, left hippocampal fissure, and right fimbria can be employed as neuroimaging biomarkers to assist the clinical diagnosis of MCI and AD.

Clinical aspects of binge eating disorder: A cross-sectional mixed-methods study of binge eating disorder experts' perspectives

Introduction

Research on binge eating disorder continues to evolve and advance our understanding of recurrent binge eating.

Methods

This mixed-methods, cross-sectional survey aimed to collect information from experts in the field about clinical aspects of adult binge eating disorder pathology. Fourteen experts in binge eating disorder research and clinical care were identified based on receipt of relevant federal funding, PubMed-indexed publications, active practice in the field, leadership in relevant societies, and/or clinical and popular press distinction. Anonymously recorded semi-structured interviews were analyzed by ≥2 investigators using reflexive thematic analysis and quantification.

Results

Identified themes included: (1) obesity (100%); (2) intentional/voluntary or unintentional/involuntary food/eating restriction (100%); (3) negative affect, emotional dysregulation, and negative urgency (100%); (4) diagnostic heterogeneity and validity (71%); (5) paradigm shifts in understanding binge eating disorder (29%); and (6) research gaps/future directives (29%).

Discussion

Overall, experts call for a better understanding of the relationship between binge eating disorder and obesity, including a need for clarification around the extent to which the two health issues are separate vs. related/overlapping. Experts also commonly endorse food/eating restriction and emotion dysregulation as important components of binge eating disorder pathology, which aligns with two common models of binge eating disorder conceptualization (e.g., dietary restraint theory and emotion/affect regulation theory). A few experts spontaneously identified several paradigm shifts in our understanding of who can have an eating disorder (beyond the anorexi-centric "thin, White, affluent, cis-gendered neurotypical female" stereotype), and the various factors that can drive binge eating. Experts also identified several areas where classification issues may warrant future research. Overall, these results highlight the continual advancement of the field to better understand adult binge eating disorder as an autonomous eating disorder diagnosis.

Psychological and metabolic risk factors in older adults with a previous history of eating disorder: A cross-sectional study from the Predimed-Plus study

GOALS

To explore affective and cognitive status, later in life, in individuals with and without previous history of eating disorder (ED), and also its association with higher risk for metabolic syndrome (MetS) symptomatology.

METHODS

A cross-sectional analysis of 6756 adults, aged 55-75 years with overweight/obesity and MetS participating in the Predimed-Plus study was conducted. Participants completed self-reported questionnaires to examine lifetime history of ED, according to DSM-5 criteria, and other psychopathological and neurocognitive factors. Anthropometric and metabolic measurements were also collected.

RESULTS

Of the whole sample, 24 individuals (0.35%) reported a previous history of ED. In this subsample, there were more women and singles compared to their counterparts, but they also presented higher levels of depressive symptoms and higher cognitive impairment, but also higher body mass index (BMI) and severe obesity, than those without lifetime ED.

CONCLUSIONS

This is one of the first studies to analyse the cognitive and metabolic impact of a previous history of ED. The results showed that previous ED was associated with greater affective and cognitive impairment, but also with higher BMI, later in life. No other MetS risk factors were found, after controlling for relevant variables.

Variable reduction for past year alcohol and drug use in unmet need for mental health services among US adults

BACKGROUND

No previous study has focused on the inter-relationship among alcohol and drug use variables in the past year. This study aimed to classify the past year alcohol and drug use variables and investigate the selected variables in past year alcohol and drug use with the unmet need for mental health services among US adults.

METHODS

Data came from the 2015 National Survey on Drug Use and Health (NSDUH). Oblique principal component cluster analysis (OPCCA) was used to classify 37 variables on alcohol and drug use in the past year into disjoint clusters. Weighted multiple logistic regression analysis was used to examine the associations of selected variables with the unmet need.

RESULTS

37 alcohol and drug use variables were divided into 7 clusters. The variable with the lowest 1-R² ratio (R² is the squared correlation) from each cluster was selected as follows: tobacco use, pain reliever use, tranquilizer use, stimulant use, zolpidem products use, illicit drug and alcohol use, and benzodiazepine tranquilizers misuse. Multiple logistic regression analysis showed that pain reliever use (OR = 1.33, 95% CI = 1.17-1.50), tranquilizer use (OR = 2.49, 95% CI = 2.16-2.86), stimulant use (OR = 1.22, 95% CI = 1.01-1.47), and illicit drug and alcohol use (OR = 1.54, 95% CI = 1.34-1.77) revealed positive associations with the unmet need for mental health services.

CONCLUSION

This is the first study using OPCCA to reduce the dominations of alcohol and drug use; several alcohol and drug use variables in the past year were associated with unmet need of mental health services.

Preliminary examination of metabolic syndrome response to motivational interviewing for weight loss as compared to an attentional control and usual care in primary care for individuals with and without binge-eating disorder

Motivational interviewing (MI) treatment for weight loss is being studied in primary care. The effect of such interventions on metabolic syndrome or binge eating disorder (BED), both highly related to excess weight, has not been examined in primary care. This study conducted secondary analyses from a randomized controlled trial to test the impact of MI for weight loss in primary care on metabolic syndrome. 74 adult participants with overweight/obesity recruited through primary care were randomized to 12weeks of either MI, an attentional control, or usual care. Participants completed measurements for metabolic syndrome at pre- and post-treatment. There were no statistically significant differences in metabolic syndrome rates at pre-, X²(2)=0.16, p=0.921, or post-, X²(2)=0.852, p=0.653 treatment. The rates in metabolic syndrome, however, decreased for MI (10.2%) and attentional control (13.8%) participants, but not for usual care. At baseline, metabolic syndrome rates did not differ significantly between participants with BED or without BED across treatments. At post-treatment, participants with BED were significantly more likely to meet criteria for metabolic syndrome than participants without BED, X²(1)=5.145, p=0.023, phi=0.273. Across treatments, metabolic syndrome remitted for almost a quarter of participants without BED (23.1%) but for 0% of those with BED. These preliminary results are based on a small sample and should be interpreted with caution, but they are the first to suggest that relatively low intensity MI weight loss interventions in primary care may decrease metabolic syndrome rates but not for individuals with BED.

Medical comorbidity of binge eating disorder

PURPOSE

To gain further understanding of the general medical comorbidity of binge eating disorder (BED) beyond its association with obesity.

METHOD

We reviewed studies of general medical comorbidity in people with BED or clinically significant binge eating behavior beyond obesity. We also reviewed studies of BED in specific medical conditions.

RESULTS

Three broad study categories of medical comorbidity in BED were found: cross-sectional studies of medical conditions in BED; prospective studies of medical conditions in BED; and studies of BED in specific medical conditions. Cross-sectional epidemiologic data suggest that BED is associated with medical conditions related to obesity, including diabetes, hypertension, dyslipidemias, sleep problems/disorders, and pain conditions, and that BED may be related to these conditions independent of obesity and co-occurring psychiatric disorders. Prospective data suggest that BED may be associated with type 2 diabetes and metabolic syndrome. BED or binge eating behavior is also associated with asthma and gastrointestinal symptoms and disorders, and among women, menstrual dysfunction, pregnancy complications, intracranial hypertension, and polycystic ovary syndrome.

CONCLUSIONS

BED is associated with substantial medical comorbidity beyond obesity. Further study of the general medical comorbidity of BED and its relationship to obesity and co-occurring psychiatric disorders is greatly needed.

Factor structure of the Bern Psychopathology Scale in a sample of patients with schizophrenia spectrum disorders

BACKGROUND

The Bern Psychopathology Scale (BPS) is based on a system-specific approach to classifying the psychopathological symptom pattern of schizophrenia. It consists of subscales for three domains (language, affect and motor behaviour) that are hypothesized to be related to specific brain circuits. The aim of the study was to examine the factor structure of the BPS in patients with schizophrenia spectrum disorders.

METHODS

One hundred and forty-nine inpatients with schizophrenia spectrum disorders were recruited at the Department of Psychiatry II, Ulm University, Germany (n=100) and at the University Hospital of Psychiatry, Bern, Switzerland (n=49). Psychopathology was assessed with the BPS. The VARCLUS procedure of SAS(®) (a type of oblique component analysis) was used for statistical analysis.

RESULTS

Six clusters were identified (inhibited language, inhibited motor behaviour, inhibited affect, disinhibited affect, disinhibited language/motor behaviour, inhibited language/motor behaviour) which explained 40.13% of the total variance of the data. A binary division of attributes into an inhibited and disinhibited cluster was appropriate, although an overlap was found between the language and motor behaviour domains. There was a clear distinction between qualitative and quantitative symptoms.

CONCLUSIONS

The results argue for the validity of the BPS in identifying subsyndromes of schizophrenia spectrum disorders according to a dimensional approach. Future research should address the longitudinal assessment of dimensional psychopathological symptoms and elucidate the underlying neurobiological processes.