Assessing the Overlap Between Three Measures of Food Reward

Food reward is an important concept for research in eating behaviors. Many food reward tasks have been developed and are in active use. However, little is known how much these tasks overlap. Here, we sought to compare three promising food reward tasks: (1) the Leeds Food Preference Questionnaire (LFPQ; a procedure combining explicit ratings of wanting and liking and an implicit wanting task based on forced choice), (2) a hand grip force task, and (3) an emotional attentional blink (EAB) task. Specifically, we assessed whether the tasks are sensitive to changes in hunger, correlate with each other, and correlate with trait binge eating and snack food calorie intake. Thirty-nine women aged 25.51 ± 5.99 years, with a BMI of 22.51 ± 3.58 kg/m2 completed the three tasks twice: after a 6-h fast and following a breakfast meal. In the fasted condition, participants were also given ad libitum access to snack foods to assess calorie intake. Prior to the two laboratory sessions, participants completed a trait binge eating questionnaire. Results revealed that the LFPQ’s explicit wanting and explicit liking subscales, as well as grip force reflected higher food reward scores in the fasted condition. The three metrics also correlated positively with each other. Explicit wanting and liking correlated with snack food intake, while grip force did not. None of the tasks were related to trait binge eating. Reaction times in the forced choice procedure did not reflect changes in hunger, but the task was nevertheless able to differentiate between foods varying in taste and fat content. The EAB was not sensitive to the hunger manipulation; neither did the task correlate with binge eating or energy intake. Collectively, our findings suggest that the explicit wanting and liking scales and the grip force task measure the same construct, whereas EAB results may be obscured by a variety of potential confounding factors. Future research could include additional food reward tasks in comparisons, measure covariates that may moderate the variables’ associations, and compare hunger-dependent changes in food reward in different subgroups

A bottom-up approach dramatically increases the predictability of body mass from personality traits

Personality traits consistently relate to and allow predicting body mass index (BMI), but these associations may not be adequately captured with existing inventories’ domains or facets. Here, we aimed to test the limits of how accurately BMI can be predicted from and described with personality traits. We used three large datasets (combined N ≈ 100,000) with nearly 700 personality assessment items to (a) empirically identify clusters of personality traits linked to BMI and (b) identify relatively small sets of items that predict BMI as accurately as possible. Factor analysis revealed 14 trait clusters showing well-established personality trait–BMI associations (disorganization, anger) and lesser-known or novel ones (altruism, obedience). Most of items’ predictive accuracy (up to r = .24 here but plausibly much higher) was captured by relatively few items. Brief scales that predict BMI have potential clinical applications—for instance, screening for risk of excessive weight gain or related complications

Beyond BMI:Personality traits’ associations with adiposity and metabolic rate

Objective: Various personality traits are known to correlate with body mass index (BMI). However, this index of adiposity conflates adiposity with lean body mass and may therefore lead to biased estimates of correlations. Yet, rarely have studies looked beyond BMI to understand how adiposity and other physiological characteristics relate to these psychological traits. Methods: We calculated an improved measure of adiposity (relative fat mass, RFM), as well as basal metabolic rate (BMR); explored their associations with various personality traits; and assessed how personality traits’ associations with RFM differ from their associations with BMI. In a subsample of the Estonian Biobank (N = 3,535), we compared the five domains and 30 facets of NEO Personality Inventory-3 in how they correlated with RFM, BMI, and BMR. Results: Various traits, notably Openness to Experience and its facets, associated with RFM above and beyond BMI. An exception was Assertiveness which correlated more strongly with BMI, and also correlated consistently with BMR. BMI–personality trait correlations appeared to conflate personality traits’ associations with fat mass and lean mass. Conclusions: Because Openness correlates with healthier diet, this trait may link with lower adiposity through eating habits. The correlation between Assertiveness and BMR mirrors associations with conceptually similar traits in non-human animals and is consistent with the idea of personality traits being based in biological pocesses. Although the use of BMI can lead to both attenuated and inflated estimates of personality trait–adiposity associations, more correlations seemed to be underestimated than overestimated when using BMI

Body mass predicts personality development across 18 years in middle to older adulthood

Various personality traits have longitudinal relations with body mass index (BMI), a measure of body weight and a risk factor for numerous health concerns, but causality in and direction of these associations is unclear. Using three waves of the Wisconsin Longitudinal Study (N = 12,235, mean age = 53.33 at baseline), we tested bidirectional longitudinal associations between BMI and the Five-Factor Model personality domains and their items and assessed the associations’ compatibility with causal influences using within-person correlations. In elastic net models, the five domains predicted concurrent BMI with an accuracy of r = .08 but were unable to predict future BMI. In contrast, 29 personality items predicted concurrent and future BMI at r = .21 and r = .16 to .25, respectively, supporting the predictive utility of nuanced trait measurements. In multilevel models, BMI had within-person correlations with Conscientiousness, Agreeableness, and several items; time-invariant third factors like genetics or childhood environments therefore could not (fully) account for their relations. BMI predicted future changes in these same personality traits (|b*| = .03 to .08), but no trait predicted subsequent changes in BMI. In sum, body weight may contribute to adults’ personality development, but the reverse appears less likely

Factors Related to COVID-19 Preventive Behaviors : A Structural Equation Model

Funding Information: The work was supported by Grant No. VPP-COVID-2020/1-0011 of the National Research Program of Latvia. Publisher Copyright: © Copyright © 2021 Šuriņa, Martinsone, Perepjolkina, Kolesnikova, Vainik, Ruža, Vrublevska, Smirnova, Fountoulakis and Rancans.Background: While COVID-19 has rapidly spread around the world, and vaccines are not widely available to the general population, the World Health Organization outlines preventive behavior as the most effective way to limit the rapid spread of the virus. Preventive behavior is associated with a number of factors that both encourage and discourage prevention. Aim: The aim of this research was to study COVID-19 threat appraisal, fear of COVID-19, trust in COVID-19 information sources, COVID-19 conspiracy beliefs and the relationship of socio-demographic variables (gender, age, level of education, place of residence, and employment status) to COVID-19 preventive behavior. Methods: The data originate from a national cross-sectional online survey (N = 2,608) undertaken in July 2020. The data were analyzed using structural equation modeling. Results: COVID-19 threat appraisal, trust in COVID-19 information sources, and fear of COVID-19 are all significant predictors of COVID-19 preventive behaviors. Together they explain 26.7% of the variance of this variable. COVID-19 conspiracy beliefs significantly negatively predict COVID-19 threat appraisal (R2 = 0.206) and trust in COVID-19 information sources (R2 = 0.190). COVID-19 threat appraisal contributes significantly and directly to the explanation of the fear of COVID-19 (R2 = 0.134). Directly, as well as mediated by COVID-19 conspiracy beliefs, threat appraisal predicts trust in COVID-19 information sources (R2 = 0.190). The relationship between COVID-19 threat appraisal and COVID-19 preventive behaviors is partially mediated by fear of COVID-19 (indirect effect 28.6%) and trust in information sources (15.8%). Socio-demographic variables add very little in prediction of COVID-19 preventive behavior. Conclusions: The study results demonstrate that COVID-19 threat appraisal is the most important factor associated with COVID-19 preventive behavior. Those Latvian residents with higher COVID-19 threat appraisal, experienced higher levels of fear of COVID-19, had more trust in COVID-19 information sources, and were more actively involved in following COVID-19 preventive behaviors. COVID-19 conspiracy beliefs negatively predict COVID-19 threat appraisal and trust in COVID-19 information sources, but not the COVID-19 preventive behaviors. Socio-demographic factors do not play an important role here.publishersversionPeer reviewe

Overlapping neural endophenotypes in addiction and obesity

Impulsivity refers to a tendency to act rapidly without full consideration of consequences. The trait is thought to result from the interaction between high arousal responses to potential rewards and poor self-control. Studies have suggested that impulsivity confers vulnerability to both addiction and obesity. However, results in this area are unclear, perhaps due to the high phenotypic complexity of addictions and obesity. Focusing on impulsivity, the aim of this review is to tackle the putative overlaps between addiction and obesity in four domains: (1) personality research, (2) neurocognitive tasks, (3) brain imaging, and (4) clinical evidence. We suggest that three impulsivity-related domains are particularly relevant for our understanding of similarities between addiction and obesity: lower self-control (high Disinhibition/low Conscientiousness), reward sensitivity (high Extraversion/Positive Emotionality), and negative affect (high Neuroticism/Negative Emotionality). Neurocognitive studies have shown that obesity and addiction are both associated with increased impulsive decision-making and attention bias in response to drug or food cues, respectively. Mirroring this, obesity and different forms of addiction seem to exhibit similar alterations in functional MRI brain activity in response to reward processing and during self-control tasks. Overall, our review provides an integrative approach to understand those facets of obesity that present similarities to addictive behaviors. In addition, we suggest that therapeutic interventions targeting inhibitory control may represent a promising approach for the prevention and/or treatment of obesity

Rapid Assessment of Reward-Related Eating: The RED-X5.

OBJECTIVE:The prevalence of obesity has created a plethora of questionnaires characterizing psychological aspects of eating behavior, such as reward-related eating (RRE). The Reward-based Eating Drive questionnaires (RED-9, RED-13) broadly and deeply assess the RRE construct. However, large-sample research designs require shorter questionnaires that capture RRE quickly and precisely. This study sought to develop a brief, reliable, and valid version of the RED questionnaire. METHODS:All-subset correlation was used to find a subset that maximally associated with the full RED-13 in two separate samples. Results were validated in a third independent sample. Internal consistency, test-retest reliability, and ability to explain variance in external outcomes were also assessed. RESULTS:A five-item questionnaire (RED-X5) correlated strongly with RED-13 in the independent sample (r = 0.95). RED-X5 demonstrated high internal consistency (omega total ≥ 0.80) and 6-month test-retest reliability (r = 0.72). RED-X5 accurately reproduced known associations between RED-13 and BMI, diabetes status, and craving for sweet and savory foods. As a novel finding, RED questionnaires predicted laboratory intake of chips. CONCLUSIONS:RED-X5 is a short, reliable, and valid measure of the RRE construct and can be readily implemented in large-sample research designs in which questionnaire space is limited