(PS6-B32) Impacts of Disordered Eating Patterns on Health Behaviors and Functioning: Results from a Weight-diverse Community Sample

Introduction:

Patterns of maladaptive eating behaviors such as loss of control over eating (LOC-E) and food addiction (FA) are fixtures in disordered eating literature and associated with health factors such as poor sleep and impaired functioning.  LOC-E and FA do occur in non-clinical samples and it is feasible they may have similar detrimental effects.  The current study sought to investigate the relationship between LOC-E and FA in a non-clinical, weight-diverse population on outcomes including sleep and weight-related disability.

Methods:

With IRB approval, participants (N=631) recruited from Amazon Mechanical Turk provided written informed consent, and completed the following surveys: Eating Loss of Control Scale (ELOCS), modified Yale Food Addiction Scale 2.0 (mYFAS), Patient Health Questionnaire-2 (PHQ-2), Sheehan Disability Scale-Weight (SDS), Pittsburgh Sleep Quality Index (PSQI), and several validity-check questions. Self-reported height and weight were used to calculate BMI (M=27.31,SD=6.94). Participants were on average 37.55 years old (SD=12.25), and primarily female (65.40%) and White, not Hispanic (72.70%). 

Results:

For participants with healthy weight (n=248), overweight (n=198), and obesity (n=185), the YFAS was significantly related to all SDS outcomes (p< .001 for all), most of the 7 PSQI-subscales (p< .001 to p=.032), and PSQI-global (p< .001). The ELOCS was significantly related to SDS outcomes (p< .001 to p=.027), most of the 7 PSQI-subscales (p< .001 to p=.049), and PSQI-global (p< .001). Two hierarchical regression analyses assessed the impact of the YFAS and ELOCS on the SDS and PSQI. Demographics (sex, age, race), BMI, and the PHQ-2 were entered first, followed by the YFAS and ELOCS. The two models were significant when predicting the PSQI (p< .001) and SDS-total (p< .001), with the YFAS (p=.002, p< .001) and ELOCS (p< .001, p< .001) both accounting for unique significant variance in the PSQI and SDS-total, respectively, after accounting for demographics, BMI, and the PHQ-2.

Conclusions:

Although LOC-E and FA are often found in clinical populations, this novel study investigated these concerns across healthy weight, overweight, and obese nonclinical participants. Importantly, our study results showed LOC-E and FA were related to poorer sleep and functioning across domains of work/school, social, and family/home, even among healthy weight adults. Of note, while these data were collected prior to the COVID-19 pandemic, they are likely even more relevant now given the negative impact the pandemic has had on sleep and eating behaviors. These initial findings suggest potentially widespread deleterious impacts of LOC-E and FA in a non-clinical population and may inform future intervention and prevention efforts.