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While personality trait assessments are widely used in candidate selection, coaching, and occupational counseling, little published research has systematically compared occupations in personality traits. Using a comprehensive personality assessment, we mapped 263 occupations in self-reported Big Five domains and various personality nuances in a sample of 68,540 individuals and cross-validated the findings in informant ratings of 19,989 individuals. Controlling for age and gender, occupations accounted for 2%-7% of Big Five variance in both self-reports and informant reports. Most occupations' average Big Five levels were intuitive, replicated across rating methods, and were consistent with those previously obtained with a brief assessment in a different sociocultural context. Often, they also tracked the Occupational Information Network database's work style ratings and clustered along the International Standard Classification of Occupation's hierarchical framework. Finally, occupations with higher average levels of the personality domains typically linked to better job performance tended to be more homogeneous in these domains, suggesting that jobs with higher performing incumbents are often more selective for personality traits. Several personality nuances had intuitive occupational differences that were larger than those of the Big Five domains (explaining up to 12% variance) and replicated well across rating methods, providing more detailed insights into how job incumbents vary in personality. We provide an interactive application for exploring the results (https://apps.psych.ut.ee/JobProfiles/) and discuss the findings' theoretical and practical implications. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Obesity is a significant public health concern. GLP-1 receptor agonists (GLP1-RA), predominantly in use as a type 2 diabetes treatment, are a promising pharmacological approach for weight loss, while bariatric surgery (BS) remains a durable, but invasive, intervention. Despite observed heterogeneity in weight loss effects, the genetic effects on weight loss from GLP1-RA and BS have not been extensively explored in large sample sizes, and most studies have focused on differences in race and ethnicity, rather than genetic ancestry. We studied whether genetic factors, previously shown to affect body weight, impact weight loss due to GLP1-RA therapy or BS in 10,960 individuals from 9 multi-ancestry biobank studies in 6 countries. The average weight change between 6 and 12 months from therapy initiation was -3.93% for GLP1-RA users, with marginal differences across genetic ancestries. For BS patients the weight change between 6 and 48 months from the operation was -21.17%. There were no significant associations between weight loss due to GLP1-RA and polygenic scores for BMI or type 2 diabetes or specific missense variants in the GLP1R, PCSK1 and APOE genes, after multiple-testing correction. However, a higher polygenic score for BMI was significantly linked to lower weight loss after BS (+0.7% for 1 standard deviation change in the polygenic score, P = 1.24×10 -4 ). In contrast, higher weight at baseline was associated with greater weight loss. Our findings suggest that existing polygenic scores related to weight and type 2 diabetes and missense variants in the drug target gene do not have a large impact on GLP1-RA effectiveness. Our results also confirm the effectiveness of these treatments across all major continental ancestry groups considered.

Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood., (© 2024. The Author(s).)

Despite numerous meta-analyses, the true extent to which life satisfaction reflects personality traits has remained unclear due to overreliance on a single method to assess both and insufficient attention to construct overlaps. Using data from three samples tested in different languages (Estonian, N = 20,886; Russian, N = 768; English, N = 600), we combined self- and informant-reports to estimate personality domains' and nuances' true correlations (r true ) with general life satisfaction (LS) and satisfactions with eight life domains (DSs), while controlling for single-method and occasion-specific biases and random error, and avoiding direct construct overlaps. The associations replicated well across samples. The Big Five domains and nuances allowed predicting LS with accuracies up to r true ≈ .80-.90 in independent (sub)samples. Emotional stability, extraversion, and conscientiousness correlated r true ≈ .30-.50 with LS, while its correlations with openness and agreeableness were small. At the nuances level, low LS was most strongly associated with feeling misunderstood, unexcited, indecisive, envious, bored, used, unable, and unrewarded (r true ≈ .40-.70). Supporting LS's construct validity, DSs had similar personality correlates among themselves and with LS, and an aggregated DS correlated r true ≈ .90 with LS. LS's approximately 10-year stability was r true = .70 and its longitudinal associations with personality traits mirrored cross-sectional ones. We conclude that without common measurement limitations, most people's life satisfaction is highly consistent with their personality traits, even across many years. So, satisfaction is usually shaped by these same relatively stable factors that shape personality traits more broadly. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

As COVID-19 vaccines' accessibility has grown, so has the role of personal choice in vaccination, and not everybody is willing to vaccinate. Exploring personality traits' associations with vaccination could highlight some person-level drivers of, and barriers to, vaccination. We used self- and informant-ratings of the Five-Factor Model domains and their subtraits (a) measured approximately at the time of vaccination with the 100 Nuances of Personality (100NP) item pool (N = 56,575) and (b) measured on average ten years before the pandemic with the NEO Personality Inventory-3 (NEO-PI-3; N = 3,168). We tested individual domains' and either items' (in the 100NP sample) or facets' (in the NEO-PI-3 sample) associations with vaccination, as well as their collective ability to predict vaccination using elastic net models trained and tested in independent sample partitions. Although the NEO-PI-3 domains and facets did not predict vaccination ten years later, the domains correlated with vaccination in the 100NP sample, with vaccinated people scoring slightly higher on neuroticism and agreeableness and lower on openness, controlling for age, sex, and education. Collectively, the five domains predicted vaccination with an accuracy of r = .08. Associations were stronger at the item level. Vaccinated people were, on average, more science-minded, politically liberal, respectful of rules and authority, and anxious but less spiritual, religious, and self-assured. The 100NP items collectively predicted vaccination with r = .31 accuracy. We conclude that unvaccinated people may be a psychologically heterogeneous group and highlight some potential areas for action in vaccination campaigns., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Arumäe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Arumäe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Depression has frequently been associated with smaller hippocampal volume. The hippocampus varies in function along its anterior-posterior axis, with the anterior hippocampus more strongly associated with stress and emotion processing. The goals of this study were to examine the associations among parental history of anxiety/depression, polygenic risk scores for depression (PGS-DEP), and anterior and posterior hippocampal volumes in children and adolescents. To examine specificity to PGS-DEP, we examined associations of educational attainment polygenic scores (PGS-EA) with anterior and posterior hippocampal volume., Methods: Participants were 350 3- to 21-year-olds (46 % female). PGS-DEP and PGS-EA were computed based on recent, large-scale genome-wide association studies. High-resolution, T1-weighted magnetic resonance imaging (MRI) data were acquired, and a semi-automated approach was used to segment the hippocampus into anterior and posterior subregions., Results: Children and adolescents with higher polygenic risk for depression were more likely to have a parent with a history of anxiety/depression. Higher polygenic risk for depression was significantly associated with smaller anterior but not posterior hippocampal volume. PGS-EA was not associated with anterior or posterior hippocampal volumes., Limitations: Participants in these analyses were all of European ancestry., Conclusions: Polygenic risk for depression may lead to smaller anterior but not posterior hippocampal volume in children and adolescents, and there may be specificity of these effects to PGS-DEP rather than PGS-EA. These findings may inform the earlier identification of those in need of support and the design of more effective, personalized treatment strategies., Declarations of Interest: none., Declarations of Interest: None., Competing Interests: Declaration of competing interest The authors have no competing interests to declare., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Objective: Various personality traits have longitudinal relations with body mass index (BMI), a measure of body weight and a risk factor for numerous health concerns. We tested these associations' compatibility with causality in either direction., Method: Using three waves of the Wisconsin Longitudinal Study (N = 12,235, M age  = 53.33 at baseline), we tested how accurately the Five-Factor Model personality domains and their items could collectively predict BMI and change in it with elastic net models. With multilevel models, we tested (a) bidirectional and (b) within-person associations between BMI and personality traits., Results: The five domains were able to predict concurrent (r = 0.08), but not future BMI. Twenty-nine personality items predicted concurrent and future BMI at r = 0.21 and r = 0.16 to 0.25, respectively. Neither the domains nor items could collectively predict change in BMI. Similarly, no individual trait predicted change in BMI, but BMI predicted changes in Conscientiousness, Agreeableness, and several items (|b*| = 0.03 to 0.08). BMI had within-person correlations with these same traits; time-invariant third factors like genetics or childhood environments therefore could not (fully) account for their relations., Conclusions: Body weight may contribute to adults' personality development, but the reverse appears less likely., (© 2023 Wiley Periodicals LLC.)

Childhood obesity is a serious health concern that is not yet fully understood. Previous research has linked obesity with neurobehavioral factors such as behavior, cognition, and brain morphology. The causal directions of these relationships remain mostly untested. We filled this gap by using the Adolescent Brain Cognitive Development study cohort comprising 11,875 children aged 9-10. First, correlations between the age- and sex-specific 95th BMI percentile (%BMIp95) and neurobehavioral measures were cross-sectionally analyzed. Effects were then aggregated by neurobehavioral domain for causal analyses. Behavioral genetic Direction of Causation modeling was used to test the direction of each relationship. Findings were validated by longitudinal cross-lagged panel modeling. %BMIp95 correlated with impulsivity, motivation, psychopathology, eating behavior, and cognitive tests (executive functioning, language, memory, perception, working memory). Greater %BMIp95 was also associated with reduced cortical thickness in frontal and temporal brain areas but with increased thickness in parietal and occipital areas. Similar although weaker patterns emerged for cortical surface area and volume. Behavioral genetic modeling suggested causal effects of %BMIp95 on eating behavior (β = 0.26), cognition (β = 0.05), cortical thickness (β = 0.15), and cortical surface area (β = 0.07). Personality/psychopathology (β = 0.09) and eating behavior (β = 0.16) appeared to influence %BMIp95. Longitudinal evidence broadly supported these findings. Results regarding cortical volume were inconsistent. Results supported causal effects of obesity on brain functioning and morphology. The present study highlights the importance of physical health for brain development and may inform interventions aimed at preventing or reducing pediatric obesity. RESEARCH HIGHLIGHTS: A continuous measure related to obesity, %BMIp95, has correlations with various measures of brain functioning and structure Behavioral genetic and longitudinal modeling suggest causal links from personality, psychopathology, and eating behavior to %BMIp95 Results also indicate directional links from %BMIp95 to eating behavior, cognition, cortical thickness, and cortical surface area Obesity may play a role for healthy brain development during childhood., (© 2023 The Authors. Developmental Science published by John Wiley & Sons Ltd.)

Studies have shown cortical alterations in individuals with autism spectrum disorders (ASD) as well as in individuals with high polygenic risk for ASD. An important addition to the study of altered cortical anatomy is the investigation of the underlying brain network architecture that may reveal brain-wide mechanisms in ASD and in polygenic risk for ASD. Such an approach has been proven useful in other psychiatric disorders by revealing that brain network architecture shapes (to an extent) the disorder-related cortical alterations. This study uses data from a clinical dataset-560 male subjects (266 individuals with ASD and 294 healthy individuals, CTL, mean age at 17.2 years) from the Autism Brain Imaging Data Exchange database, and data of 391 healthy individuals (207 males, mean age at 12.1 years) from the Pediatric Imaging, Neurocognition and Genetics database. ASD-related cortical alterations (group difference, ASD-CTL, in cortical thickness) and cortical correlates of polygenic risk for ASD were assessed, and then statistically compared with structural connectome-based network measures (such as hubs) using spin permutation tests. Next, we investigated whether polygenic risk for ASD could be predicted by network architecture by building machine-learning based prediction models, and whether the top predictors of the model were identified as disease epicenters of ASD. We observed that ASD-related cortical alterations as well as cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. We also observed that age progression of ASD-related cortical alterations and cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. Further investigation revealed that structural connectomes predicted polygenic risk for ASD (r = 0.30, p < 0.0001), and two brain regions (the left inferior parietal and left suparmarginal) with top predictive connections were identified as disease epicenters of ASD. Our study highlights a critical role of network architecture in a continuum model of ASD spanning from healthy individuals with genetic risk to individuals with ASD. Our study also highlights the strength of investigating polygenic risk scores in addition to multi-modal neuroimaging measures to better understand the interplay between genetic risk and brain alterations associated with ASD., (© 2022. The Author(s).)

Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity., (© 2023. The Author(s).)

Genome-wide polygenic scores for educational attainment (PGS-EA) and socioeconomic factors, which are correlated with each other, have been consistently associated with academic achievement and general cognitive ability in children and adolescents. Yet, the independent associations of PGS-EA and socioeconomic factors with specific underlying factors at the neural and neurocognitive levels are not well understood. The main goals of this study were to examine the unique contributions of PGS-EA and parental education to cortical structure and neurocognitive skills in children and adolescents, and the associations among PGS-EA, cortical structure, and neurocognitive skills. Participants were typically developing 3- to 21-year-olds (53% male; N = 391). High-resolution, T1-weighted magnetic resonance imaging data were acquired, and cortical thickness (CT) and surface area (SA) were measured. PGS-EA were computed based on the EA3 genome-wide association study of educational attainment. Participants completed executive function, vocabulary, and episodic memory tasks. Higher PGS-EA and parental education were independently and significantly associated with greater total SA and vocabulary. Higher PGS-EA was significantly associated with greater SA in the left medial orbitofrontal gyrus and inferior frontal gyrus, which was associated with higher executive function. Higher parental education was significantly associated with greater SA in the left parahippocampal gyrus after accounting for PGS-EA and total brain volume. These findings suggest that education-linked genetics may influence SA in frontal regions, leading to variability in executive function. Associations of parental education with cortical structure in children and adolescents remained significant after controlling for PGS-EA, a source of genetic confounding., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Background: Schizophrenia is widely recognized as a neurodevelopmental disorder. Abnormal cortical development in otherwise typically developing children and adolescents may be revealed using polygenic risk scores for schizophrenia (PRS-SCZ)., Methods: We assessed PRS-SCZ and cortical morphometry in typically developing children and adolescents (3-21 years, 46.8% female) using whole-genome genotyping and T1-weighted magnetic resonance imaging ( n  = 390) from the PING (Pediatric Imaging, Neurocognition, and Genetics) cohort. We contextualized the findings using 1) age-matched transcriptomics, 2) histologically defined cytoarchitectural types and functionally defined networks, and 3) case-control differences of schizophrenia and other major psychiatric disorders derived from meta-analytic data of 6 ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) working groups, including a total of 12,876 patients and 15,670 control participants., Results: Higher PRS-SCZ was associated with greater cortical thickness, which was most prominent in areas with heightened gene expression of dendrites and synapses. PRS-SCZ-related increases in vertexwise cortical thickness were mainly distributed in association cortical areas, particularly the ventral attention network, while relatively sparing koniocortical type cortex (i.e., primary sensory areas). The large-scale pattern of cortical thickness increases related to PRS-SCZ mirrored the pattern of cortical thinning in schizophrenia and mood-related psychiatric disorders derived from the ENIGMA consortium. Age group models illustrate a possible trajectory from PRS-SCZ-associated cortical thickness increases in early childhood toward thinning in late adolescence, with the latter resembling the adult brain phenotype of schizophrenia., Conclusions: Collectively, combining imaging genetics with multiscale mapping, our work provides novel insight into how genetic risk for schizophrenia affects the cortex early in life., (© 2022 The Authors.)

Various personality traits are known to correlate with body mass index (BMI). However, this index of adiposity conflates fat mass 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. Using previously validated formulas, 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 = 3535), we compared how the five domains and 30 facets of NEO Personality Inventory-3 correlated with RFM, BMI, and BMR. Various traits, notably Openness to Experience and its facets, were associated with RFM above and beyond BMI; these traits may relate to lower adiposity through eating habits. Assertiveness, a facet of Extraversion, correlated more strongly with BMI than with RFM and also correlated with BMR. These correlations mirror associations of metabolic rate with conceptually similar traits in non-human animals and are consistent with Assertiveness being based on biological processes. Finally, BMI-personality trait correlations appeared to conflate personality traits' associations with fat mass and lean mass; the use of BMI as an indicator of adiposity can lead to both attenuated and inflated estimates of personality trait-adiposity associations., (Copyright © 2022. Published by Elsevier Inc.)

Background: Impulsivity increases the risk for obesity and weight gain. However, the precise role of impulsivity in the aetiology of overeating behavior and obesity is currently unknown. Here we examined the relationships between personality-related measures of impulsivity, Uncontrolled Eating, body mass index (BMI), and longitudinal weight changes. In addition, we analyzed the associations between general impulsivity domains and cortical thickness to elucidate brain vulnerability factors related to weight gain., Methods: Students (N = 2318) in their first year of university-a risky period for weight gain-completed questionnaire measures of impulsivity and eating behavior at the beginning of the school year. We also collected their weight at the end of the term (N = 1177). Impulsivity was divided into three factors: stress reactivity, reward sensitivity and lack of self-control. Using structural equation models, we tested a hierarchical relationship, in which impulsivity traits were associated with Uncontrolled Eating, which in turn predicted BMI and weight change. Seventy-one participants underwent T1-weighted MRI to investigate the correlation between impulsivity and cortical thickness., Results: Impulsivity traits showed positive correlations with Uncontrolled Eating. Higher scores in Uncontrolled Eating were in turn associated with higher BMI. None of the impulsivity-related measurements nor Uncontrolled Eating were correlated with longitudinal weight gain. Higher stress sensitivity was associated with increased cortical thickness in the superior temporal gyrus. Lack of self-control was positively associated with increased thickness in the superior medial frontal gyrus. Finally, higher reward sensitivity was associated with lower thickness in the inferior frontal gyrus., Conclusion: The present study provides a comprehensive characterization of the relationships between different facets of impulsivity and obesity. We show that differences in impulsivity domains might be associated with BMI via Uncontrolled Eating. Our results might inform future clinical strategies aimed at fostering self-control abilities to prevent and/or treat unhealthy weight gain., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Introduction: Diurnal preferences have been linked to personality but often with mixed results. The present study examines the relationships between sleep timing (chronotype), diurnal preferences, and the Five-Factor Model of personality traits at the phenotypic and genetic level., Methods: Self- and informant-reports of the NEO Personality Inventory-3, self-reports of the Munich Chronotype Questionnaire, and DNA samples were available for 2,515 Estonian adults (M age  = 45.76 years; 59% females). Genetic correlations were obtained through summary statistics of genome-wide association studies., Results: Results showed that higher Conscientiousness and lower Openness to Experience were significant predictors of earlier chronotype. At the level of facets, we found that more straightforward (A2) and excitement-seeking (E5), yet less self-disciplined (C5) people were more likely to have later chronotypes. The nuance-level Polypersonality score was correlated with chronotype at r = .28 (p < .001). Conscientiousness and Openness were genetically related with diurnal preferences. The polygenic score for morningness-eveningness significantly predicted the Polypersonality score., Conclusion: Phenotypic measures of chronotype and personality showed significant associations at all three of levels of the personality hierarchy. Our findings indicate that the relationship between personality and morningness-eveningness is partly due to genetic factors. Future studies are necessary to further refine the relationship., (© 2021 The Authors. Journal of Personality published by Wiley Periodicals LLC.)

Background/objectives: Many personality traits correlate with BMI, but the existence and direction of causal links between them are unclear. If personality influences BMI, knowing this causal direction could inform weight management strategies. Knowing that BMI instead influences personality would contribute to a better understanding of the mechanisms of personality development and the possible psychological effects of weight change. We tested the existence and direction of causal links between BMI and personality., Subjects/methods: We employed two genetically informed methods. In Mendelian randomization, allele scores were calculated to summarize genetic propensity for the personality traits neuroticism, worry, and depressive affect and used to predict BMI in an independent sample (N = 3 541). Similarly, an allele score for BMI was used to predict eating-specific and domain-general phenotypic personality scores (PPSs; aggregate scores of personality traits weighted by BMI). In a direction of causation (DoC) analysis, twin data from five countries (N = 5424) were used to assess the fit of four alternative models: PPSs influencing BMI, BMI influencing PPSs, reciprocal causation, and no causation., Results: In Mendelian randomization, the allele score for BMI predicted domain-general (β = 0.05; 95% CI: 0.02, 0.08; P = 0.003) and eating-specific PPS (β = 0.06; 95% CI: 0.03, 0.09; P < 0.001). The allele score for worry also predicted BMI (β = -0.05; 95% CI: -0.08, -0.02; P < 0.001), while those for neuroticism and depressive affect did not (P ≥ 0.459). In DoC, BMI similarly predicted domain-general (β = 0.21; 95% CI:, 0.18, 0.24; P < 0.001) and eating-specific personality traits (β = 0.19; 95% CI:, 0.16, 0.22; P < 0.001), suggesting causality from BMI to personality traits. In exploratory analyses, links between BMI and domain-general personality traits appeared reciprocal for higher-weight individuals (BMI > ~25)., Conclusions: Although both genetic analyses suggested an influence of BMI on personality traits, it is not yet known if weight management interventions could influence personality. Personality traits may influence BMI in turn, but effects in this direction appeared weaker., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

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 ( R 2 = 0.206) and trust in COVID-19 information sources ( R 2 = 0.190). COVID-19 threat appraisal contributes significantly and directly to the explanation of the fear of COVID-19 ( R 2 = 0.134). Directly, as well as mediated by COVID-19 conspiracy beliefs, threat appraisal predicts trust in COVID-19 information sources ( R 2 = 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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Šuriņa, Martinsone, Perepjolkina, Kolesnikova, Vainik, Ruža, Vrublevska, Smirnova, Fountoulakis and Rancans.)

Studies of socioeconomic disparities have largely focused on correlating brain measures with either composite measure of socioeconomic status (SES), or its components-family income or parental education, giving little attention to the component of parental occupation. Emerging evidence suggests that parental occupation may be an important and neglected indicator of childhood and adolescent SES compared to absolute measures of material resources or academic attainment because, while related, it may more precisely capture position in social hierarchy and related health outcomes. On the other hand, although cortical thickness and surface area are brain measures with distinct genetic and developmental origins, large-scale neuroimaging studies investigating regional differences in interaction of the composite measure of SES or its components with cortical thickness and surface area are missing. We set out to fill this gap, focusing specifically on the role of parental occupation on cortical thickness and surface area by analyzing magnetic resonance imaging scans from 704 healthy individuals (age = 3-21 years). We observed spatially distributed patterns of (parental occupation × age 2 ) interaction with cortical thickness (localized at the left caudal middle frontal, the left inferior parietal and the right superior parietal) and surface area (localized at the left orbitofrontal cortex), indicating independent sources of variability. Further, with decreased cortical thickness, children from families with lower parental occupation exhibited lower self-esteem. Our findings demonstrate distinct influence of parental occupation on cortical thickness and surface area in children and adolescents, potentially reflecting different neurobiological mechanisms by which parental occupation may impact brain development., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Psychological factors may explain why some people develop obesity and others remain a normal weight during their life course. We use an umbrella review approach to build an evidence-based map of the psychological correlates of heavier body weight. Synthesising findings from 42 meta-analyses that have examined associations between psychological factors and heavier body weight, we assessed level of evidence for a range of cognitive, psychosocial and mental health individual difference factors. There is convincing evidence that impaired mental health is associated with heavier body weight and highly suggestive evidence that numerous cognitive factors are associated with heavier body weight. However, the relatively low methodological quality of meta-analyses resulted in lower evidential certainty for most psychosocial factors. Psychological correlates of heavier body weight tended to be small in statistical size and on average, people with obesity were likely to be more psychologically similar than different to people with normal weight. We consider implications for understanding the development of heavier body weight and identifying effective public health interventions to reduce obesity., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Obesity and diabetes are known to be related to cognitive abilities. The Core Neuropsychological Measures for Obesity and Diabetes Trials Project aimed to identify the key cognitive and perceptual domains in which performance can influence treatment outcomes, including predicting, mediating, and moderating treatment outcome and to generate neuropsychological batteries comprised of well-validated, easy-to-administer tests that best measure these key domains. The ultimate goal is to facilitate inclusion of neuropsychological measures in clinical studies and trials so that we can gather more information on potential mediators of obesity and diabetes treatment outcomes. We will present the rationale for the project and three options for the neuropsychological batteries to satisfy varying time and other administration constraints. Future directions are discussed. Preprint version of the document is available at https://osf.io/preprints/nutrixiv/7jygx/., (Copyright © 2020 D’Ardenne, Savage, Small, Vainik and Stoeckel.)

Autism spectrum disorder is a highly prevalent and highly heritable neurodevelopmental condition, but studies have mostly taken traditional categorical diagnosis approach (yes/no for autism spectrum disorder). In contrast, an emerging notion suggests a continuum model of autism spectrum disorder with a normal distribution of autistic tendencies in the general population, where a full diagnosis is at the severe tail of the distribution. We set out to investigate such a viewpoint by investigating the interaction of polygenic risk scores for autism spectrum disorder and Age 2 on neuroimaging measures (cortical thickness and white matter connectivity) in a general population ( n  =   391, with age ranging from 3 to 21 years from the Pediatric Imaging, Neurocognition and Genetics study). We observed that children with higher polygenic risk for autism spectrum disorder exhibited greater cortical thickness for a large age span starting from 3 years up to ∼14 years in several cortical regions localized in bilateral precentral gyri and the left hemispheric postcentral gyrus and precuneus. In an independent case-control dataset from the Autism Brain Imaging Data Exchange ( n  =   560), we observed a similar pattern: children with autism spectrum disorder exhibited greater cortical thickness starting from 6 years onwards till ∼14 years in wide-spread cortical regions including (the ones identified using the general population). We also observed statistically significant regional overlap between the two maps, suggesting that some of the cortical abnormalities associated with autism spectrum disorder overlapped with brain changes associated with genetic vulnerability for autism spectrum disorder in healthy individuals. Lastly, we observed that white matter connectivity between the frontal and parietal regions showed significant association with polygenic risk for autism spectrum disorder, indicating that not only the brain structure, but the white matter connectivity might also show a predisposition for the risk of autism spectrum disorder. Our findings showed that the fronto-parietal thickness and connectivity are dimensionally related to genetic risk for autism spectrum disorder in general population and are also part of the cortical abnormalities associated with autism spectrum disorder. This highlights the necessity of considering continuum models in studying the aetiology of autism spectrum disorder using polygenic risk scores and multimodal neuroimaging., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Executive functions (EFs) comprise a group of cognitive processes that selectively control and regulate attention. Inverse relations have been reported between EFs and BMI. However, the mechanisms underlying this association are not well understood., Objectives: We aimed to decompose the inverse relation between EFs and BMI into genetic and environmental components., Methods: We employed a cross-sectional analysis of data from 869 twins aged 7-15 y from the Texas Twin Project, who completed a neuropsychological test battery measuring 4 EFs (switching, inhibitory control, working memory, and updating); academic achievement (reading and mathematics); and general cognitive abilities (general intelligence/intelligence quotient; crystallized and fluid intelligence; and processing speed). Participants also had their height and weight measured., Results: After controlling for age, sex, and race/ethnicity, BMI was inversely associated with a general EF factor representing the capacity to control and regulate goal-oriented behaviors (r = -0.125; P = 0.01; Q = 0.04). This inverse BMI-EF association was due to a significant overlap in genetic factors contributing to each phenotype (genetic correlation, rA, = -0.15; P < 0.001). Shared genetic influences accounted for 80% of the phenotypic association., Conclusions: Children with higher general EF have lower BMIs, and this association is primarily attributable to shared genetic influences on both phenotypes. The results emphasize that higher weight associates not only with physical sequelae, but also with important cognitive attributes. This work adds to a growing body of research suggesting there are sets of genetic variants common across physical health and cognitive functioning., (Copyright © American Society for Nutrition 2019.)

Many eating-related psychological constructs have been proposed to explain obesity and overeating. However, these constructs, including food addiction, disinhibition, hedonic hunger, emotional eating, binge eating and the like all have similar definitions, emphasizing loss of control over intake. As questionnaires measuring the constructs correlate strongly (r > 0.5) with each other, we propose that these constructs should be reconsidered to be part of a single broad phenotype: uncontrolled eating. Such an approach enables reviewing and meta-analysing evidence obtained with each individual questionnaire. Here, we describe robust associations between uncontrolled eating, body mass index (BMI), food intake, personality traits and brain systems. Reviewing cross-sectional and longitudinal data, we show that uncontrolled eating is phenotypically and genetically intertwined with BMI and food intake. We also review evidence on how three psychological constructs are linked with uncontrolled eating: lower cognitive control, higher negative affect and a curvilinear association with reward sensitivity. Uncontrolled eating mediates all three constructs' associations with BMI and food intake. Finally, we review and meta-analyse brain systems possibly subserving uncontrolled eating: namely, (i) the dopamine mesolimbic circuit associated with reward sensitivity, (ii) frontal cognitive networks sustaining dietary self-control and (iii) the hypothalamus-pituitary-adrenal axis, amygdala and hippocampus supporting stress reactivity. While there are limits to the explanatory and predictive power of the uncontrolled eating phenotype, we conclude that treating different eating-related constructs as a single concept, uncontrolled eating, enables drawing robust conclusions on the relationship between food intake and BMI, psychological variables and brain structure and function., (© 2019 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Obesity has inconsistent associations with broad personality domains, possibly because the links pertain to only some facets of these domains. Collating published and unpublished studies (N = 14 848), we meta-analysed the associations between body mass index (BMI) and Five-Factor Model personality domains as well as 30 Five-Factor Model personality facets. At the domain level, BMI had a positive association with Neuroticism and a negative association with Conscientiousness domains. At the facet level, we found associations between BMI and 15 facets from all five personality domains, with only some Neuroticism and Conscientiousness facets among them. Certain personality-BMI associations were moderated by sample properties, such as proportions of women or participants with obesity; these moderation effects were replicated in the individual-level analysis. Finally, facet-based personality "risk" scores accounted for 2.3% of variance in BMI in a separate sample of individuals (N = 3569), 409% more than domain-based scores. Taken together, personality-BMI associations are facet specific, and delineating them may help to explain obesity-related behaviours and inform intervention designs. Preprint and data are available at https://psyarxiv.com/z35vn/., (© 2019 World Obesity Federation.)

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/m 2 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.

Automatic detection of important and unexpected stimuli in the visual environment is crucial for survival. We sought to explore whether visual food stimuli are detected already in the pre-attentive stimulus processing phase, and whether hunger enhances such automatic detection. To attain these goals, we adapted an electroencephalography paradigm - visual mismatch negativity (vMMN). vMMN is a useful paradigm to study the processing of salient emotional stimuli which has not yet been applied in the context of eating behaviours. In our study, 18 right-handed women (25.2 ± 7.4 years) underwent two experimental sessions: hunger and fed conditions. Participants had to focus on a 2-back working memory task in the center of the computer screen, while stimuli depicting high fat savoury (HFSA) and high fat sweet (HFSW) foods were presented as deviants in a stream of neutral standard stimuli in the four corners of the screen. Automatic detection of foods was observed within 80-360 ms after stimulus onset, although some foods were better detected than the others. In HFSA, hunger enhanced the processing of all deviant stimuli in the early (100-160 ms) and mid-latency (160-220 ms) time windows. As the modulating effect of hunger was not food-specific, hunger may enhance automatic detection of changes in the visual environment, regardless of the type of input. Nevertheless, hamburger in HFSA was better detected than other stimuli, indicated by larger peak amplitudes, which supports the food-specificity of hunger modulation. In HFSW, the modulating effect of hunger was not observed, possibly due to suboptimally chosen stimuli within this block. In conclusion, we believe that after careful stimulus selection vMMN has a great potential to be a reliable measure of early food-cue processing., (Copyright © 2018. Published by Elsevier Ltd.)

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., (© 2019 The Obesity Society.)

Recent molecular genetic studies have shown that the majority of genes associated with obesity are expressed in the central nervous system. Obesity has also been associated with neurobehavioral factors such as brain morphology, cognitive performance, and personality. Here, we tested whether these neurobehavioral factors were associated with the heritable variance in obesity measured by body mass index (BMI) in the Human Connectome Project ( n = 895 siblings). Phenotypically, cortical thickness findings supported the "right brain hypothesis" for obesity. Namely, increased BMI is associated with decreased cortical thickness in right frontal lobe and increased thickness in the left frontal lobe, notably in lateral prefrontal cortex. In addition, lower thickness and volume in entorhinal-parahippocampal structures and increased thickness in parietal-occipital structures in participants with higher BMI supported the role of visuospatial function in obesity. Brain morphometry results were supported by cognitive tests, which outlined a negative association between BMI and visuospatial function, verbal episodic memory, impulsivity, and cognitive flexibility. Personality-BMI correlations were inconsistent. We then aggregated the effects for each neurobehavioral factor for a behavioral genetics analysis and estimated each factor's genetic overlap with BMI. Cognitive test scores and brain morphometry had 0.25-0.45 genetic correlations with BMI, and the phenotypic correlations with BMI were 77-89% explained by genetic factors. Neurobehavioral factors also had some genetic overlap with each other. In summary, obesity as measured by BMI has considerable genetic overlap with brain and cognitive measures. This supports the theory that obesity is inherited via brain function and may inform intervention strategies., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Heritable variance in psychological traits may reflect genetic and biological processes that are not necessarily specific to these particular traits but pertain to a broader range of phenotypes. We tested the possibility that the personality domains of the five-factor model and their 30 facets, as rated by people themselves and their knowledgeable informants, reflect polygenic influences that have been previously associated with educational attainment. In a sample of more than 3,000 adult Estonians, education polygenic scores (EPSs), which are interpretable as estimates of molecular-genetic propensity for education, were correlated with various personality traits, particularly from the neuroticism and openness domains. The correlations of personality traits with phenotypic educational attainment closely mirrored their correlations with EPS. Moreover, EPS predicted an aggregate personality trait tailored to capture the maximum amount of variance in educational attainment almost as strongly as it predicted the attainment itself. We discuss possible interpretations and implications of these findings.

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.

A diversity of scales capture facets of reward-related eating (RRE). These scales assess food cravings, uncontrolled eating, addictive behavior, restrained eating, binge eating, and other eating behaviors. However, these scales differ in terms of the severity of RRE they capture. We sought to incorporate the items from existing scales to broaden the 9-item Reward-based Eating Drive scale (RED-9; Epel et al., 2014), which assesses three dimensions of RRE (lack of satiety, preoccupation with food, and lack of control over eating), in order to more comprehensively assess the entire spectrum of RRE. In a series of 4 studies, we used Item Response Theory models to consider candidate items to broaden the RED-9. Studies 1 and 2 evaluated the abilities of additional items from existing scales to increase the RED-9's coverage across the spectrum of RRE. Study 3 evaluated candidate items identified in Studies 1 and 2 in a new sample to assess the extent to which they accounted for more variance in areas less well-covered by the RED-9. Study 4 tested the ability of the RED-13 to provide consistent coverage across the range of the RRE spectrum. The resultant RED-13 accounted for greater variability than the RED-9 by reducing gaps in coverage of RRE in middle-to-low ranges. Like the RED-9, the RED-13 was positively correlated with BMI. The RED-13 was also positively related to a diagnosis of type 2 diabetes as well as cravings for sweet and savory foods. In summary, the RED-13 is a brief self-report measure that broadly captures the spectrum of RRE and may be a useful tool for identifying individuals at risk for overweight or obesity.

Self-report measures of physical activity (PA) are easy to use and popular but their reliability is often questioned. Therefore, the general aim of the present study was to investigate the association of PA questionnaires with accelerometer derived PA, in a sample of adolescent boys. In total, 191 pubertal boys (mean age 14.0 years) completed three self-report questionnaires and wore an accelerometer (ActiGraph GT1M) for 7 consecutive days. The PA questionnaires were: International Physical Activity Questionnaire-Short Form (IPAQ-SF), Tartu Physical Activity Questionnaire (TPAQ), and the Inactivity subscale from Domain-Specific Impulsivity (DSI) scale. All three questionnaires were significantly correlated with accelerometer derived MVPA: the correlations were 0.31 for the IPAQ-SF MVPA, 0.34 for the TPAQ MVPA and -0.29 for the DSI Inactivity scale. Nevertheless, none of the questionnaires can be used as a reliable individual-level estimate of MVPA in male adolescents. The boys underreported their MVPA in IPAQ-SF as compared to accelerometer-derived MVPA (respective averages 43 and 56 minutes); underreporting was more marked in active boys with average daily MVPA at least 60 minutes, and was not significant in less active boys. Conversely, MVPA index from TPAQ overestimated the MVPA in less active boys but underestimated it in more active boys. The sedentary time reported in IPAQ-SF was an underestimate as compared to accelerometer-derived sedentary time (averages 519 and 545 minutes, respectively)., Competing Interests: The authors have declared that no competing interests exist.

Subjective energy intake (sEI) is often misreported, providing unreliable estimates of energy consumed. Therefore, relating sEI data to health outcomes is difficult. Recently, Börnhorst et al. compared various methods to correct sEI-based energy intake estimates. They criticised approaches that categorise participants as under-reporters, plausible reporters and over-reporters based on the sEI:total energy expenditure (TEE) ratio, and thereafter use these categories as statistical covariates or exclusion criteria. Instead, they recommended using external predictors of sEI misreporting as statistical covariates. We sought to confirm and extend these findings. Using a sample of 190 adolescent boys (mean age=14), we demonstrated that dual-energy X-ray absorptiometry-measured fat-free mass is strongly associated with objective energy intake data (onsite weighted breakfast), but the association with sEI (previous 3-d dietary interview) is weak. Comparing sEI with TEE revealed that sEI was mostly under-reported (74 %). Interestingly, statistically controlling for dietary reporting groups or restricting samples to plausible reporters created a stronger-than-expected association between fat-free mass and sEI. However, the association was an artifact caused by selection bias - that is, data re-sampling and simulations showed that these methods overestimated the effect size because fat-free mass was related to sEI both directly and indirectly via TEE. A more realistic association between sEI and fat-free mass was obtained when the model included common predictors of misreporting (e.g. BMI, restraint). To conclude, restricting sEI data only to plausible reporters can cause selection bias and inflated associations in later analyses. Therefore, we further support statistically correcting sEI data in nutritional analyses. The script for running simulations is provided.

Introduction: A consistent eating style might be beneficial to avoid overeating in a food-rich environment. Eating consistency entails maintaining a similar dietary pattern across different eating situations. This construct is relatively under-studied, but the available evidence suggests that eating consistency supports successful weight maintenance and decreases risk for metabolic syndrome and cardiovascular disease. Yet, personality and situation predictors of consistency have not been studied., Methods: A community-based sample of 164 women completed various personality tests, and 139 of them also reported their eating behaviour 6 times/day over 10 observational days. We focused on observations with meals (breakfast, lunch, or dinner). The participants indicated if their momentary eating patterns were consistent with their own baseline eating patterns in terms of healthiness or size of the meal. Further, participants described various characteristics of each eating situation., Results: Eating consistency was positively predicted by trait self-control. Eating consistency was undermined by eating in the evening, eating with others, eating away from home, having consumed alcohol and having undertaken physical exercise. Interactions emerged between personality traits and situations, including punishment sensitivity, restraint, physical activity and alcohol consumption., Conclusion: Trait self-control and several eating situation variables were related to eating consistency. These findings provide a starting point for targeting interventions to improve consistency, suggesting that a focus on self-control skills, together with addressing contextual factors such as social situations and time of day, may be most promising. This work is a first step to provide people with the tools they need to maintain a consistently healthy lifestyle in a food-rich environment.

Research on eating behaviour has identified several potentially relevant eating-related traits captured by different questionnaires. Often, these questionnaires predict Body Mass Index (BMI), but the relationship between them has not been explicitly studied. We studied the unity and diversity of questionnaires capturing five common eating-related traits: Power of Food, Eating Impulsivity, emotional eating, Disinhibition, and binge eating in women from Estonia (n = 740) and Canada (n = 456). Using bifactor analysis, we showed that a) these questionnaires are largely explained by a single factor, and b) relative to this shared factor, only some questionnaires offered additional variance in predicting BMI. Hence, these questionnaires seemed to characterise a common factor, which we label Uncontrolled Eating. Item Response Theory techniques were then applied to demonstrate that c) within this common factor, the questionnaires could be placed on a continuum of Uncontrolled Eating. That is, Eating Impulsivity focused on the milder degree, Power of Food Scale, emotional eating scales, and Disinhibition on intermediate degrees, and the Binge Eating Scale on the most severe degrees of Uncontrolled Eating. In sum, evidence from two samples showed that questionnaires capturing five common BMI-related traits largely reflected the same underlying latent trait - Uncontrolled Eating. In Estonia, some questionnaires focused on different severities of this common construct, supporting a continuum model of Uncontrolled Eating. These findings provide a starting point for developing better questionnaires of the neurobehavioural correlates of obesity, and provide a unifying perspective from which to view the existing literature. R scripts and data used for the analysis are provided., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The worldwide increase in obesity has spurred numerous efforts to understand the regulation of eating behaviours and underlying brain mechanisms. These mechanisms can affordably be studied via neurobehavioural measures. Here, we systematically review these efforts, evaluating neurocognitive tests and personality questionnaires based on: (a) consistent relationship with obesity and eating behaviour, and (b) reliability. We also considered the measures' potential to shed light on the brain mechanisms underlying these individual differences. Sixty-six neurocognitive tasks were examined. Less than 11%, mainly measures of executive functions and food motivation, yielded both replicated and reliable effects. Several different personality questionnaires were consistently related to BMI. However, further analysis found that many of these questionnaires relate closely to Conscientiousness, Extraversion and Neuroticism within the Five-Factor Model of personality. Both neurocognitive tests and personality questionnaires suggest that the critical neural systems related to individual differences in obesity are lateral prefrontal structures underpinning self-control and striatal regions implicated in food motivation. This review can guide selection of the highest yield neurobehavioural measures for future studies., (Copyright © 2012 Elsevier Ltd. All rights reserved.)