Sleep Quality and Eating Disorder-Related Psychopathologies in Patients with Night Eating Syndrome and Binge Eating Disorders

Hedonic hunger, food addiction, and night eating syndrome triangle in adolescents and ıts relationship with body mass ındex

BACKGROUND

The relationship between adolescent obesity and eating disorders is an issue that needs urgent attention. Screening for eating disorders is as important as dietary interventions to treat obesity. This study aimed to determine the relationship between hedonic hunger, food addiction, and night eating syndrome, which are considered potential risk factors for obesity, and body mass index (BMI) in adolescents.

METHODS

The data were collected through an online questionnaire. The "Power of Food Scale (PFS)" was used to assess hedonic hunger; the "Yale Food Addiction Scale for Children 2.0 (dYFAS-C 2.0)" was used to assess food addiction; and the "Night Eating Questionnaire (NEQ)" was used to assess night eating syndrome (NES)". BMI was calculated using self-reported height and weight values of adolescents. The mediated structural model analysis was performed to evaluate the effect of hedonic hunger on BMI z score via food addiction and NES.

RESULTS

The study was conducted with 614 voluntary adolescents aged between 11 and 18 years. The dYFAS-C 2.0 and NEQ scores were found to be higher in adolescents with overweight and obesity, and the BMI z-score of the adolescents had significant positive correlation with their PFS scores (p < .001). Hedonic hunger has no direct effect on BMI independent of food addiction and NES (β = - 0.051, p = .468), but when the total indirect effect is evaluated with the bootstrap analysis, it was found that one-unit increase in hedonic hunger score increases BMI z-score by approximately 0.22 units (β = 0.223, SE = 0.046, 95% CI 0.131-0.313). Hedonic hunger, food addiction, and NES together explained 5.2% of the total variance in BMI z score.

CONCLUSION

This study showed that hedonic hunger significantly predicted BMI z-score in adolescents through food addiction and NES. This emphasizes the critical importance of evaluating adolescents in terms of hedonic hunger, food addiction, and NES in the prevention, diagnosis, and treatment of obesity.

Examining the relationship between obstructive sleep apnoea and eating behaviours and attitudes: A systematic review

BACKGROUND

Between 60 and 90% of adults with OSA are reported as overweight. The co-existence of obesity and OSA can greatly increase an individual's risk of type 2 diabetes, metabolic syndrome and cardiovascular disease. To better understand this relationship between OSA and weight, this review aimed to investigate if there is evidence of certain eating behaviours or eating attitudes that might be found in adults living with OSA.

METHODS

We searched four databases (MEDLINE, Embase, PsycInfo and Web of Science) on January 17th, 2022, to identify studies assessing the association between eating patterns and OSA in adults. Twenty-one studies met the inclusion criteria. A narrative synthesis was conducted on the included studies, following the vote-counting method.

RESULTS

There is preliminary evidence that the time of day when calories are consumed is associated with lower OSA severity. No other clear patterns of eating behaviours or attitudes were identified however this may be due to disparity within research studies and their reported results.

CONCLUSION

Further research is needed to examine the relationship between eating times and OSA severity. We recommend standardising the approach to examining the eating patterns of those living with OSA and the relationship that this might have on OSA symptoms as well as looking at attitudes towards food in this population. This may prove helpful in providing a better understanding of the relationship between OSA and persons with overweight and help in future intervention development.

Medications as a Trigger of Sleep-Related Eating Disorder: A Disproportionality Analysis

Sleep-related eating disorder (SRED) is a parasomnia with recurrent, involuntary, amnestic eating episodes during sleep. There is growing evidence of the association between SRED and medications. Therefore, we aimed to rank drugs showing the strongest association. VigiBase® (WHO pharmacovigilance database) was queried for all reports of “Sleep-related eating disorder”. Disproportionality analysis relied on the Reporting Odds Ratio, with its 95% Confidence Interval (CI), and the Information Component. Our VigiBase® query yielded 676 cases of drug-associated SRED. Reports mostly involved zolpidem (243, 35.9%), sodium oxybate (185, 27.4%), and quetiapine (97, 14.3%). Significant disproportionality was found for 35 medications, including zolpidem (387.6; 95%CI 331.2−453.7), sodium oxybate (204.2; 95%CI 172.4−241.8), suvorexant (67.3; 95%CI 38.0−119.2), quetiapine (53.3; 95%CI 43.0−66.1), and several psychostimulants and serotonin-norepinephrine reuptake inhibitors (SNRIs). Patients treated with nonbenzodiazepines or SNRIs were significantly older (mean age: 49.0 vs. 37.5; p < 0.001) and their SRED were more likely to be serious (62.6% vs. 51.4%; p = 0.014) than patients treated with sodium oxybate or psychostimulants. Psychotropic drugs are involved in almost all reports. In patients with SRED, an iatrogenic trigger should be searched for.

Sensor technology in eating disorders research: A systematic review

OBJECTIVE

Sensor technologies offer exciting potential to objectively measure psychopathological correlates of eating pathology and eating disorder (ED) research utilizing sensors has rapidly proliferated in the past several years. The aims of the present review are: (1) characterize the types of sensors that have been utilized in ED research, (2) identify the psychopathological factors relevant to EDs that have been assessed using sensors, (3) describe the data supporting the validity and reliability of these sensors, (4) discuss limitations associated with these sensors, and (5) identify gaps that persist within the ED literature with regard to use of sensor technologies.

METHOD

A systematic search was conducted of PubMed, PsycINFO, Web of Science, ProQuest, and "gray" literature sources. Eligible publications were empirical studies that utilized sensors to measure at least one psychological variable among clinical ED populations.

RESULTS

Sensors have been utilized with ED samples to measure eating behaviors, physical activity, sleep, autonomic nervous system activity, eyeblink startle response, visual attention, and visual-haptic object integration. The reliability and validity of these sensors varies widely and there are a number of significant gaps that remain in the literature with regard to the types of sensors utilized, context in which sensors have been used, and populations studied.

DISCUSSION

The existing literature utilizing sensors within ED research largely support the feasibility and acceptability of these tools. Sensors should continue to be utilized within the field, with a specific focus on examining the reliability and validity of these tools within ED samples and increasing the diversity of samples studied.

PUBLIC SIGNIFICANCE STATEMENT

Sensor technologies, such as those included in modern smartwatches, offer new opportunities to measure factors that may maintain or contribute to symptoms of eating disorders. This article describes the types of sensors that have been used in eating disorders research, challenges that may arise in using these sensors, and discusses new applications of these sensors that may be pursued in future research.