The role of eating behavior traits in mediating genetic susceptibility to obesity

How do lifestyle factors modify the association between genetic predisposition and obesity-related phenotypes? A 4-way decomposition analysis using UK Biobank

BACKGROUND

Obesity and central obesity are multifactorial conditions with genetic and non-genetic (lifestyle and environmental) contributions. There is incomplete understanding of whether lifestyle modifies the translation from respective genetic risks into phenotypic obesity and central obesity, and to what extent genetic predisposition to obesity and central obesity is mediated via lifestyle factors.

METHODS

This is a cross-sectional study of 201,466 (out of approximately 502,000) European participants from UK Biobank and tested for interactions and mediation role of lifestyle factors (diet quality; physical activity levels; total energy intake; sleep duration, and smoking and alcohol intake) between genetic risk for obesity and central obesity. BMI-PRS and WHR-PRS are exposures and obesity and central obesity are outcomes.

RESULTS

Overall, 42.8% of the association between genetic predisposition to obesity and phenotypic obesity was explained by lifestyle: 0.9% by mediation and 41.9% by effect modification. A significant difference between men and women was found in central obesity; the figures were 42.1% (association explained by lifestyle), 1.4% (by mediation), and 40.7% (by modification) in women and 69.6% (association explained by lifestyle), 3.0% (by mediation), and 66.6% (by modification) in men.

CONCLUSIONS

A substantial proportion of the association between genetic predisposition to obesity/central obesity and phenotypic obesity/central obesity was explained by lifestyles. Future studies with repeated measures of obesity and lifestyle would be needed to clarify causation.

Deciphering the Interplay between Genetic Risk Scores and Lifestyle Factors on Individual Obesity Predisposition

Obesity's variability is significantly influenced by the interplay between genetic and environmental factors. We aimed to integrate the combined impact of genetic risk score (GRSBMI) with physical activity (PA), sugar-sweetened beverages (SSB), wine intake, and eating habits score (EHS) on obesity predisposition risk. Adults' (n = 5824) data were analyzed for common obesity-related single nucleotide polymorphisms and lifestyle habits. The weighted GRSBMI was constructed and categorized into quartiles (Qs), and the adjusted multivariate logistic regression models examined the association of GRSBMI with obesity (BMI ≥ 30) and lifestyle factors. GRSBMI was significantly associated with obesity risk. Each GRSBMI unit was associated with an increase of 3.06 BMI units (p ≤ 0.0001). PA markedly reduced obesity risk across GRSBMI Qs. Inactive participants' (≥90 min/week) mean BMI was higher in GRSBMI Q3-Q4 compared to Q1 (p = 0.003 and p < 0.001, respectively). Scoring EHS ≥ median, SSBs (≥1 cup/day), and non-wine drinking were associated with higher BMI within all GRSBMI Qs compared to EHS < median, non-SSBs, and non-wine drinkers. Mean BMI was higher in GRSBMI Q4 compared to other quartiles (p < 0.0001) in non-wine drinkers and compared to Q1 for SSB's consumers (p = 0.07). A higher GRSBMI augmented the impact of lifestyle factors on obesity. The interplay between GRSBMI and modifiable lifestyle factors provides a tailored personalized prevention and treatment for obesity management.

Plant-based dietary patterns and genetic susceptibility to obesity in the CARTaGENE cohort

OBJECTIVE

The study's objective was to examine whether adherence to three plant-based dietary indices (PDIs) mediated or moderated genetic susceptibility to obesity.

METHODS

Baseline participants were 7037 adults (57% women, aged 55.6 ± 7.7 years) from the CARTaGENE cohort of Quebec adults. Two polygenic risk scores for BMI (PRS-BMI), 92 single-nucleotide polymorphisms and 2 million single-nucleotide polymorphisms, and three plant-based scores were calculated (overall, healthy, and unhealthy). Follow-up participants were 2258 adults with data on obesity outcomes, measured 6 years later. General linear models were used to examine the relationships between PRSs and PDI scores on obesity outcomes. Causal mediation analyses were conducted to assess mediation and interaction models.

RESULTS

The overall- and healthy-PDIs and PRSs were significantly associated with obesity outcomes. Adherence to PDIs did not mediate or moderate genetic susceptibility to obesity. Associations between PRSs and obesity outcomes were partly mediated by meat intake cross-sectionally and whole grains intake among males both cross-sectionally and longitudinally. Higher meat intake had a positive association with obesity outcomes, whereas higher whole grains intake had an inverse association.

CONCLUSIONS

These findings suggest that components of a plant-based diet and a shift away from animal products, specifically meat, might be beneficial for nutrition interventions, particularly among individuals with higher genetic risk of obesity.

Mediation and moderation of genetic risk of obesity through eating behaviours in two UK cohorts

BACKGROUND

The mechanisms underlying genetic predisposition to higher body mass index (BMI) remain unclear.

METHODS

We hypothesized that the relationship between BMI-genetic risk score (BMI-GRS) and BMI was mediated via disinhibition, emotional eating and hunger, and moderated by flexible (but not rigid) restraint within two UK cohorts: the Genetics of Appetite Study (GATE) (n = 2101, 2010-16) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 1679, 2014-18). Eating behaviour was measured by the Adult Eating Behaviour Questionnaire and Three-Factor Eating Questionaire-51.

RESULTS

The association between BMI-GRS and BMI were partially mediated by habitual, emotional and situational disinhibition in the GATE/ALSPAC meta-mediation [standardized betaindirect 0.04, 95% confidence interval (CI) 0.02-0.06; 0.03, 0.01-0.04; 0.03, 0.01-0.04, respectively] external hunger and internal hunger in the GATE study (0.02, 0.01-0.03; 0.01, 0.001-0.02, respectively). There was evidence of mediation by emotional over/undereating and hunger in the ALSPAC study (0.02, 0.01-0.03; 0.01, 0.001-0.02; 0.01, 0.002-0.01, respectively). Rigid or flexible restraint did not moderate the direct association between BMI-GRS and BMI, but high flexible restraint moderated the effect of disinhibition subscales on BMI (reduction of the indirect mediation by -5% to -11% in GATE/ALSPAC) and external hunger (-5%) in GATE. High rigid restraint reduced the mediation via disinhibition subscales in GATE/ALSPAC (-4% to -11%) and external hunger (-3%) in GATE.

CONCLUSIONS

Genetic predisposition to a higher BMI was partly explained by disinhibition and hunger in two large cohorts. Flexible/rigid restraint may play an important role in moderating the impact of predisposition to higher BMI.

Biobehavioral susceptibility for obesity in childhood: Behavioral, genetic and neuroimaging studies of appetite

Modern food environments are conducive to overeating and weight gain, but not everyone develops obesity. One reason for this may be that individuals differ in appetitive characteristics, or traits, that manifest early in life and go on to influence their behavioral susceptibility to gain and maintain excess weight. Classic studies showing that eating behavior in children can be measured by behavioral paradigms such as tests of caloric compensation and eating in the absence of hunger inspired the development and validation of psychometric instruments to assess appetitive characteristics in children and infants. A large body of evidence now suggests that food approach traits increase obesity risk, while food avoidant traits, such as satiety responsiveness, decrease obesity risk. Twin studies and genetic association studies have demonstrated that appetitive characteristics are heritable, consistent with a biological etiology. However, family environment factors are also influential, with mounting evidence suggesting that genetic and environmental risk factors interact and correlate with consequences for child eating behavior and weight. Further, neuroimaging studies are revealing that individual differences in responses to visual food cues, as well as to small tastes and larger amounts of food, across a number of brain regions involved in reward/motivation, cognitive control and other functions, may contribute to individual variation in appetitive behavior. Growing evidence also suggests that variation on psychometric measures of appetite is associated with regional differences in brain structure, and differential patterns of resting state functional connectivity. Large prospective studies beginning in infancy promise to enrich our understanding of neural and other biological underpinnings of appetite and obesity development in early life, and how the interplay between genetic and environmental factors affects appetitive systems. The biobehavioral susceptibility model of obesity development and maintenance outlined in this narrative review has implications for prevention and treatment of obesity in childhood.

Associations of timing of food intake with energy intake, eating behaviour traits and psychosocial factors in adults with overweight and obesity

Introduction

Whether a late distribution of food intake impacts obesity through increased energy intake remains uncertain and the behavioural characterization of late eating needs to be further investigated. The first objective of this study was to assess the associations between late eating and body mass index (BMI) and total energy intake (TEI), and whether TEI mediates the association between late eating and BMI. The second objective was to assess the associations between late eating and eating behaviour traits or psychosocial factors and whether eating behaviour traits mediate the association between late eating and TEI.

Methods

Baseline data from 301 individuals (56% women, age = 38.7 ± 8.5 years; BMI = 33.2 ± 3.4 kg/m²), who participated in four weight loss studies were used in this cross-sectional study. Total energy intake was assessed using a three-day food record from which the percentage of TEI after 17:00 and after 20:00 was calculated. Eating behaviour traits and psychosocial factors were assessed with questionnaires. Pearson correlations and mediation analyses adjusted for age, sex, underreporting of energy intake, sleep duration and bedtime were performed.

Results

Percent TEI after 17:00 and after 20:00 were associated with TEI (r = 0.13, p = 0.03 for both), and TEI mediated the association between percent TEI after 17:00 and BMI (β = 0.01 ± 0.01, 95% CI: 0.001, 0.02). Percent TEI after 17:00 was associated with disinhibition (r = 0.13, p = 0.03) and percent TEI after 20:00 was associated with susceptibility to hunger (r = 0.13, p = 0.03), stress (r = 0.24, p = 0.002) and anxiety (r = 0.28, p = 0.0004). In women, disinhibition mediated the association between percent TEI after 17:00 and TEI (β = 3.41 ± 1.43, 95% CI: 0.92, 6.47). Susceptibility to hunger mediated the association between percent TEI after 20:00 and TEI (β = 0.96 ± 0.59, 95% CI: 0.02, 2.34) in men and women.

Conclusion

Late eating is associated with TEI and suboptimal eating behaviours which could contribute to explaining the association between timing of food intake and obesity.

Effects of sodium intake and cardiorespiratory fitness on body composition and genetic susceptibility to obesity: results from the Quebec Family Study

The main aim of this study was to evaluate the effects of Na intake and cardiorespiratory fitness (CRF) on body composition. The study was also intended to assess whether Na intake and/or CRF mediate the genetic susceptibility to obesity. Analyses were performed on a sample of 526 adult participants from the Quebec Family Study for whom a complete data set was available for nutrient and energy intake, CRF and body composition variables. The effects of Na, CRF and their interaction were analysed by comparing sex-specific tertiles using general linear mixed models. In both males and females, we observed a significant effect of Na intake and CRF on all body composition variables. However, in females only, we found that the effect of Na intake on body composition variables varies according to CRF level such that high Na intake was associated with increased body fatness, but only in females with low CRF. This interaction effect remained significant after statistical adjustment for total sugar, fat and energy intake. Using mediation analysis, we also found Na intake and CRF to be significant mediators of the relationship between a polygenic risk score of obesity based on > 500 000 genetic variants and BMI or waist circumference. In conclusion, the current study shows that Na intake influences body composition via mechanisms that interact with aerobic fitness, especially in females. Furthermore, both Na intake and CRF seem to be involved in the expression of the genetic susceptibility to obesity.

Eating behaviour traits mediate the association between satiety responsiveness and energy intake among individuals with overweight and obesity

Whether eating behaviour traits represent factors that could explain the susceptibility to overeating in individuals with low satiety responsiveness remain to be extensively examined. This study aimed to assess if eating behaviours mediate the association between satiety responsiveness and energy intake. Baseline data from individuals with overweight or obesity (n = 303; age = 38.7 ± 8.4 years; BMI = 33.2 ± 3.4 kg/m², 56% women) who participated in four weight-loss studies were included in this cross-sectional study. Satiety responsiveness was determined by the satiety quotient (SQ) based on fullness sensations in response to a standardized breakfast. Energy intake was self-reported in a three-day food record and measured by an ad libitum buffet meal. Eating behaviours were assessed with questionnaires. Mediation analyses adjusted for age and sex, and for underreporting for the food record, were performed using a regression-based and bootstrapping approach. The association between SQ and self-reported total energy intake was mediated by susceptibility to hunger (β = -2.51 ± 1.26, 95% CI, -5.38 to -0.52) and its subscales, internal and external locus of hunger (β = -2.00 ± 1.10, 95% CI, -4.50 to -0.28 and β = -2.42 ± 1.29, 95% CI, -5.30 to -0.30, respectively). Susceptibility to hunger (β = -2.71 ± 1.13, 95% CI, -5.29 to -0.84), internal and external locus of hunger (β = -1.84 ± 0.95, 95% CI -4.00 to -0.30 and β = -3.42 ± 1.31, 95% CI, -6.39 to -1.24, respectively), cues that may trigger food cravings (β = -5.43 ± 2.91, 95% CI, -11.83 to -0.44) and state-craving as a physiological state (β = -4.31 ± 2.51, 95%CI, -10.14 to -0.44) also mediated the association between SQ and measured energy intake. These results suggest that susceptibility to hunger and food cravings partly explained the susceptibility to overeating among individuals with low satiety responsiveness. Interventions targeting susceptibility to hunger and food cravings may thus be helpful to prevent overeating among these individuals.

Validation of the Adult Eating Behaviour Questionnaire adapted for the French-speaking Canadian population

PURPOSE

The Adult Eating Behaviour Questionnaire (AEBQ) is a newly developed questionnaire adapted from the widely used Child Eating Behaviour Questionnaire. This questionnaire assesses four food approach scales, namely hunger, food responsiveness, emotional overeating (EOE) and enjoyment of food, and four food avoidance scales, namely satiety responsiveness (SR), emotional undereating (EUE), food fussiness and slowness in eating (SE). This study aimed to validate a French version of the AEBQ in controlled conditions among French-speaking adults from Quebec, Canada.

METHODS

The AEBQ was pre-tested through structured interviews with 30 individuals. Participants of the validation study (n = 197, aged 19-65 years) had their height and weight measured and completed the AEBQ, Three-Factor Eating Questionnaire (TFEQ) and Intuitive Eating Scale-2 to assess factorial structure, internal consistency and construct validity. Test-retest reliability over 2 weeks was assessed among 144 participants.

RESULTS

Confirmatory factor analysis indicated an excellent model fit (NNFI = 0.98, CFI = 0.98, RMSEA = 0.03, χ²/df = 1.17) and provided support for the use of the original 8-factor questionnaire. Internal consistency was adequate for most scales (Cronbach's alpha = 0.66-0.94) and moderate to excellent test-retest reliability was observed for all scales (ICC = 0.70-90). Women showed higher levels of EOE and SR, and individuals with overweight and obesity showed higher levels of EOE and lower levels of EUE and SE. Construct validity was also supported by expected correlations with disinhibition and susceptibility to hunger from the TFEQ and intuitive eating.

CONCLUSION

This study indicates that the French AEBQ is a valid and reliable tool to measure eating behaviours in the adult population of Quebec.

LEVEL OF EVIDENCE

Level III: Evidence obtained from well-designed cohort or case-control analytic studies. The data are cross-sectional, but all measurement were undertaken in controlled laboratory conditions and the study provided new information.

Understanding gene-lifestyle interaction in obesity: the role of mediation versus moderation

BACKGROUND

Obesity results from complex interactions between genetic susceptibility to weight gain and poor eating and lifestyle behaviors. The approach that has been traditionally used in genetics to investigate gene-environment/lifestyle interaction in obesity is based on the concept of moderation, or effect modification. Another approach called mediation analysis can be used to investigate gene-environment interaction in obesity. The objective of this review article is to explain the differences between the concepts of moderation and mediation and summarize the studies that have used mediation analysis to support the role of eating or lifestyle behaviors as putative mediators of genetic susceptibility to obesity.

SUMMARY

Moderation is used to determine whether the effect of an exposure (genes associated with obesity) on an outcome (obesity phenotype) differs in magnitude and/or direction across the spectrum of environmental exposure. Mediation analysis is used to assess the extent to which the effect of the exposure on the outcome is explained by a given set of hypothesized mediators with the aim of understanding how the exposure could lead to the outcome. In comparison with moderation, relatively few studies used mediation analyses to investigate gene-environment in obesity. Most studies found evidence that traits related to appetite or eating behaviors partly mediated genetic susceptibility to obesity in either children or adults. Key messages: Moderation and mediation represent two complementary approaches to investigate gene-environment interaction in obesity and address different research questions pertaining to the cause-effect relationship between genetic susceptibility to obesity and various obesity outcomes. More studies relying on mediation are needed to better understand the role eating and lifestyle habits in mediating genetic susceptibility to obesity.

Translation and validation of the Child Three-Factor Eating Questionnaire (CTFEQr17) in French-speaking Canadian children and adolescents

OBJECTIVE

To translate and validate the Child Three-Factor Eating Questionnaire (CTFEQr17), assessing cognitive restraint (CR), uncontrolled eating (UE) and emotional eating (EE), among French-speaking Canadian young individuals.

DESIGN

Phase 1 comprised a translation and the evaluation of the comprehension of the questionnaire. Phase 2 comprised a confirmatory factor analysis (CFA), the evaluation of internal consistency (Cronbach's α), test-retest reliability (intra-class correlation coefficients (ICC)) and construct validity, including correlations among the CTFEQr17 and Eating Attitudes Test (EAT-26), anthropometrics, dietary intake and diet quality.

SETTING

Primary and secondary schools, Québec City, Canada.

PARTICIPANTS

Phases 1 and 2 included 20 (40 % boys, mean age 11·5 (sd 2·4) years) and 145 (48 % boys, mean age 11·0 (sd 1·9) years) participants, respectively.

RESULTS

Phase 1 resulted in the questionnaire to be used in Phase 2. In Phase 2, the CFA revealed that the seventeen item, three-factor model (CTFEQr17) provided an excellent fit. Internal consistency was good (Cronbach's α: 0·81-0·90). Test-retest reliability was moderate to good (ICC = 0·59, (95 % CI 0·48, 0·70), ICC = 0·78, (95 % CI 0·70, 0·84), ICC = 0·50, (95 % CI 0·38, 0·62) for CR, UE and EE, respectively). CR correlated with EAT-26 score (r = 0·43, P < 0·0001). UE and EE correlated negatively with BMI Z-scores (r = -0;·26, P = 0·003; r = -0;·19, P = 0·03, respectively). CR correlated with the proportion of energy intake from protein and diet quality (r = 0·18, P = 0·04; r = 0·20, P = 0·02, respectively).

CONCLUSION

The CTFEQr17 is suitable to use among French-speaking Canadian young individuals.

Dietary Mediators of the Genetic Susceptibility to Obesity-Results from the Quebec Family Study

BACKGROUND

Recent studies showed that eating behaviors such as disinhibition, emotional and external eating, and snacking mediate genetic susceptibility to obesity. It remains unknown if diet quality and intake of specific food groups also mediate the genetic susceptibility to obesity.

OBJECTIVE

This study aimed to assess if diet quality and intakes of specific food groups mediate the association between a polygenic risk score (PRS) for BMI and BMI and waist circumference (WC). We hypothesized that poor diet quality, high intakes of energy-dense food groups, and low intakes of nutrient-dense food groups mediate the genetic susceptibility to obesity.

METHODS

This cross-sectional study included 750 participants (56.3% women, aged 41.5 ± 14.9 y, BMI 27.8 ± 7.5 kg/m2) from the Quebec Family Study. A PRSBMI based on >500,000 genetic variants was calculated using LDpred2. Dietary intakes were assessed with a 3-d food record from which a diet quality score (i.e. Nutrient Rich Food Index 6.3) and food groups were derived. Mediation analyses were conducted using a regression-based and bootstrapping approach.

RESULTS

The PRSBMI explained 25.7% and 19.8% of the variance in BMI and WC, respectively. The association between PRSBMI and BMI was partly mediated by poor diet quality (β = 0.33 ± 0.12; 95% CI: 0.13, 0.60), high intakes of fat and high-fat foods (β = 0.46 ± 0.16; 95% CI: 0.19, 0.79) and sugar-sweetened beverages (β = 0.25 ± 0.14; 95% CI: 0.05, 0.60), and low intakes of vegetables (β = 0.15 ± 0.08; 95% CI: 0.03, 0.32), fruits (β = 0.37 ± 0.12; 95% CI: 0.17, 0.64), and dairy products (β = 0.17 ± 0.09; 95% CI: 0.02, 0.37). The same trends were observed for WC.

CONCLUSIONS

The genetic susceptibility to obesity was partly mediated by poor diet quality and intakes of specific food groups. These results suggest that improvement in diet quality may reduce obesity risk among individuals with high genetic susceptibility and emphasize the need to intervene on diet quality among these individuals.

Childhood overeating is associated with adverse cardiometabolic and inflammatory profiles in adolescence

Childhood eating behaviour contributes to the rise of obesity and related noncommunicable disease worldwide. However, we lack a deep understanding of biochemical alterations that can arise from aberrant eating behaviour. In this study, we prospectively associate longitudinal trajectories of childhood overeating, undereating, and fussy eating with metabolic markers at age 16 years to explore adolescent metabolic alterations related to specific eating patterns in the first 10 years of life. Data are from the Avon Longitudinal Study of Parents and Children (n = 3104). We measure 158 metabolic markers with a high-throughput (1H) NMR metabolomics platform. Increasing childhood overeating is prospectively associated with an adverse cardiometabolic profile (i.e., hyperlipidemia, hypercholesterolemia, hyperlipoproteinemia) in adolescence; whereas undereating and fussy eating are associated with lower concentrations of the amino acids glutamine and valine, suggesting a potential lack of micronutrients. Here, we show associations between early behavioural indicators of eating and metabolic markers.

The association between childhood adiposity and appetite assessed using the Child Eating Behavior Questionnaire and Baby Eating Behavior Questionnaire: A systematic review and meta-analysis

This systematic review and meta-analysis aimed to quantify associations between Child Eating Behavior Questionnaire (CEBQ) and Baby Eating Behavior Questionnaire (BEBQ) appetitive traits (food approach: Food Responsiveness [FR], Enjoyment of Food [EF], Emotional Overeating [EOE], and Desire to Drink [DD]; food avoidant: Satiety Responsiveness [SR], Slowness in Eating [SE], Emotional Undereating [EUE], Food Fussiness [FF]) and measures of child adiposity. Searches of six databases up to February 2019 identified 72 studies (CEBQ, n = 67; BEBQ, n = 5), and 27 met the meta-analysis criteria. For cross-sectional studies reporting unadjusted correlations with body mass index z-scores (BMIz) (n = 19), all traits were associated with BMIz in expected directions (positive: FR, EF, EOE, and DD; negative: SR, SE, EUE, and FF). Pooled estimates ranged from r = 0.22 (FR) to r = -0.21 (SR). For cross-sectional studies reporting regression coefficients (n = 10), three traits (FR, EF, and EOE) associated positively, and three traits (SR, SE, and EUE) negatively, with BMIz (β = -0.31 [SR] to β = 0.22 [FR]). Eleven studies reported prospective relationships from appetite to adiposity measures for six scales (positive: FR, EF, EOE, and DD; negative: SR and SE). Five studies reported relationships from adiposity measures to appetite for five traits (positive: FR, EF, and EOE; negative: SR). All BEBQ traits were consistently cross-sectionally associated with adiposity measures. Overall, CEBQ/BEBQ-assessed appetitive traits show consistent cross-sectional relationships with measures of child adiposity.

Independent and combined associations between fast-food outlet exposure and genetic risk for obesity: a population-based, cross-sectional study in the UK

BACKGROUND

Characteristics of the built environment, such as neighbourhood fast-food outlet exposure, are increasingly recognised as risk factors for unhealthy diet and obesity. Obesity also has a genetic component, with common genetic variants explaining a substantial proportion of population-level obesity susceptibility. However, it is not known whether and to what extent associations between fast-food outlet exposure and body weight are modified by genetic predisposition to obesity.

METHODS

We used data from the Fenland Study, a population-based sample of 12,435 UK adults (mean age 48.6 years). We derived a genetic risk score associated with BMI (BMI-GRS) from 96 BMI-associated single nucleotide polymorphisms. Neighbourhood fast-food exposure was defined as quartiles of counts of outlets around the home address. We used multivariable regression models to estimate the associations of each exposure, independently and in combination, with measured BMI, overweight and obesity, and investigated interactions.

RESULTS

We found independent associations between BMI-GRS and risk of overweight (RR = 1.34, 95% CI 1.23-1.47) and obesity (RR = 1.73, 95% CI 1.55-1.93), and between fast-food outlet exposure and risk of obesity (highest vs lowest quartile RR = 1.58, 95% CI 1.21-2.05). There was no evidence of an interaction of fast-food outlet exposure and genetic risk on BMI (P = 0.09), risk of overweight (P = 0.51), or risk of obesity (P = 0.27). The combination of higher BMI-GRS and highest fast-food outlet exposure was associated with 2.70 (95% CI 1.99-3.66) times greater risk of obesity.

CONCLUSIONS

Our study demonstrated independent associations of both genetic obesity risk and neighbourhood fast-food outlet exposure with adiposity. These important drivers of the obesity epidemic have to date been studied in isolation. Neighbourhood fast-food outlet exposure remains a potential target of policy intervention to prevent obesity and promote the public's health.

Social and behavioral science at the forefront of genomics: Discovery, translation, and health equity

This special issue highlights the unique role that social and behavioral science has to play at the forefront of genomics. Through the introduction of papers comprising this special issue, we outline priority research areas at the nexus of genomics and the social and behavioral sciences. These include: Discovery science; clinical and community translation, and equity, including engagement and inclusion of diverse populations in genomic science. We advocate for genomic discovery that considers social context, neural, cognitive, and behavioral endophenotypes, and that is grounded in social and behavioral science research and theory. Further, the social and behavioral sciences should play a leadership role in identifying best practices for effective clinical and community translation of genomic discoveries. Finally, inclusive research that engages diverse populations is necessary for genomic discovery and translation to benefit all. We also highlight ways that genomics can be a fruitful testbed for the development and refinement of social and behavioral science theory. Indeed, an expanded ecological lens that runs from genomes to society will be required to fully understand human behavior.

Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory

Background/objectives

The mediating role of eating behaviors in genetic susceptibility to weight gain during mid-adult life is not fully understood. This longitudinal study aims to help us understand contributions of genetic susceptibility and appetite to weight gain.

Subjects/methods

We followed the body-mass index (BMI) trajectories of 2464 adults from 45 to 65 years of age by measuring weight and height on four occasions at 5-year intervals. Genetic risk of obesity (gene risk score: GRS) was ascertained, comprising 92 BMI-associated single-nucleotide polymorphisms and split at a median (=high and low risk). At the baseline, the Eating Inventory was used to assess appetite-related traits of ‘disinhibition’, indicative of opportunistic eating or overeating and ‘hunger’ which is susceptibility to/ability to cope with the sensation of hunger. Roles of the GRS and two appetite-related scores for BMI trajectories were examined using a mixed model adjusted for the cohort effect and sex.

Results

Disinhibition was associated with higher BMI (β = 2.96; 95% CI: 2.66–3.25 kg/m²), and accounted for 34% of the genetically-linked BMI difference at age 45. Hunger was also associated with higher BMI (β = 1.20; 0.82–1.59 kg/m²) during mid-life and slightly steeper weight gain, but did not attenuate the effect of disinhibition.

Conclusions

Appetite disinhibition is most likely to be a defining characteristic of genetic susceptibility to obesity. High levels of appetite disinhibition, rather than hunger, may underlie genetic vulnerability to obesogenic environments in two-thirds of the population of European ancestry.

The genomics of childhood eating behaviours

Eating behaviors may be expressions of genetic risk for obesity and are potential antecedents of later eating disorders. However, childhood eating behaviors are heterogeneous and transient. Here we show associations between polygenic scores for body mass index (BMI-PGS) and anorexia nervosa (AN-PGS) with eating behavior trajectories during the first ten years of life using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), N=7,825. Results indicated that one standard deviation (SD) increase in the BMI-PGS was associated with a 30-37% increased risk for early- and mid-childhood overeating. In contrast, one SD increase in BMI-PGS was associated with a 20% decrease in risk of persistent high levels of undereating and a 15% decrease in risk of persistent fussy eating. There was no evidence for a significant association between AN-PGS and eating behavior trajectories. Our results support the notion that child eating behavior share common genetic variants associated with BMI.

Obesity and eating behavior from the perspective of twin and genetic research

Obesity has dramatically increased during the last decades and is currently one of the most serious global health problems. We present a hypothesis that obesity is a neuro-behavioral disease having a strong genetic background mediated largely by eating behavior and is sensitive to the macro-environment; we study this hypothesis from the perspective of genetic research. Genetic family and genome-wide-association studies have shown well that body mass index (BMI, kg/m²) is a highly heritable and polygenic trait. New genetic variation of BMI emerges after early childhood. Candidate genes of BMI notably express in brain tissue, supporting that this new variation is related to behavior. Obesogenic environments at both childhood family and societal levels reinforce the genetic susceptibility to obesity. Genetic factors have a clear influence on macro-nutrient intake and appetite-related eating behavior traits. Results on the gene-by-diet interactions in obesity are mixed, but emerging evidence suggests that eating behavior traits partly mediate the effect of genes on BMI. However, more rigorous prospective study designs controlling for measurement bias are still needed.

ImpulsePal: The systematic development of a smartphone app to manage food temptations using intervention mapping

BACKGROUND

Impulsive processes driving eating behaviour can often undermine peoples' attempts to change their behaviour, lose weight and maintain weight loss.

AIM

To develop an impulse management intervention to support weight loss in adults.

METHODS

Intervention Mapping (IM) was used to systematically develop the "ImpulsePal" intervention. The development involved: (1) a needs assessment including a qualitative study, Patient and Public advisory group and expert group consultations, and a systematic review of impulse management techniques; (2) specification of performance objectives, determinants, and change objectives; (3) selection of intervention strategies (mapping of change techniques to the determinants of change); (4) creation of programme materials; (5) specification of adoption and implementation plans; (6) devising an evaluation plan.

RESULTS

Application of the IM Protocol resulted in a smartphone app that could support reductions in unhealthy (energy dense) food consumption, overeating, and alcoholic and sugary drink consumption. ImpulsePal includes inhibition training, mindfulness techniques, implementation intentions (if-then planning), visuospatial loading, use of physical activity for craving management, and context-specific reminders. An "Emergency Button" was also included to provide access to in-the-moment support when temptation is strong.

CONCLUSIONS

ImpulsePal is a novel, theory- and evidence-informed, person-centred app that aims to support impulse management for healthier eating. Intervention Mapping facilitated the incorporation of app components that are practical operationalisations of change techniques targeting our specific change objectives and their associated theoretical determinants. Using IM enabled transparency and provided a clear framework for evaluation, and enhances replicability and the potential of the intervention to accomplish the desired outcome of facilitating weight loss through dietary change.

The Role of Eating Behaviours in Genetic Susceptibility to Obesity

PURPOSE OF REVIEW

Eating behaviours are hypothesised to be the behavioural expression of genetic risk of obesity. In this review, we summarise findings from behavioural genetic research on the association between genetic risk for obesity and validated psychometrics measures of eating behaviours in children and adults (published in the past 10 years).

RECENT FINDINGS

Twin studies have produced some evidence for a shared genetic aetiology underlying body mass index and eating behaviours. Studies using measured genetic susceptibility to obesity have suggested that increased genetic liability for obesity is associated with variation in obesogenic eating behaviours such as emotional and uncontrolled eating. More research on this topic is needed. Especially longitudinal studies using genetically sensitive designs to investigate the direction of genetic pathways between genetic liability of eating behaviours to weight and vice versa, as well as the potential subsequent link to eating disorders.

The genetic architecture of the association between eating behaviors and obesity: combining genetic twin modeling and polygenic risk scores

BACKGROUND

Obesity susceptibility genes are highly expressed in the brain suggesting that they might exert their influence on body weight through eating-related behaviors.

OBJECTIVES

To examine whether the genetic susceptibility to obesity is mediated by eating behavior patterns.

METHODS

Participants were 3977 twins (33% monozygotic, 56% females), aged 31-37 y, from wave 5 of the FinnTwin16 study. They self-reported their height and weight, eating behaviors (15 items), diet quality, and self-measured their waist circumference (WC). For 1055 twins with genome-wide data, we constructed a polygenic risk score for BMI (PRSBMI) using almost 1 million single nucleotide polymorphisms. We used principal component analyses to identify eating behavior patterns, twin modeling to decompose correlations into genetic and environmental components, and structural equation modeling to test mediation models between the PRSBMI, eating behavior patterns, and obesity measures.

RESULTS

We identified 4 moderately heritable (h2 = 36-48%) eating behavior patterns labeled "snacking," "infrequent and unhealthy eating," "avoidant eating," and "emotional and external eating." The highest phenotypic correlation with obesity measures was found for the snacking behavior pattern (r = 0.35 for BMI and r = 0.32 for WC; P < 0.001 for both), largely due to genetic factors in common (bivariate h2 > 70%). The snacking behavior pattern partially mediated the association between the PRSBMI and obesity measures (βindirect = 0.06; 95% CI: 0.02, 0.09; P = 0.002 for BMI; and βindirect = 0.05; 95% CI: 0.02, 0.08; P = 0.003 for WC).

CONCLUSIONS

Eating behavior patterns share a common genetic liability with obesity measures and are moderately heritable. Genetic susceptibility to obesity can be partly mediated by an eating pattern characterized by frequent snacking. Obesity prevention efforts might therefore benefit from focusing on eating behavior change, particularly in genetically susceptible individuals.

What Should I Eat and Why? The Environmental, Genetic, and Behavioral Determinants of Food Choice: Summary from a Pennington Scientific Symposium

This review details the proceedings of a Pennington Biomedical scientific symposium titled, "What Should I Eat and Why? The Environmental, Genetic, and Behavioral Determinants of Food Choice." The symposium was designed to review the literature about energy homeostasis, particularly related to food choice and feeding behaviors, from psychology to physiology. This review discusses the intrinsic determinants of food choice, including biological mechanisms (genetics), peripheral and central signals, brain correlates, and the potential role of the microbiome. This review also address the extrinsic determinants (environment) of food choice within our physical and social environments. Finally, this review reports the current treatment practices for the clinical management of eating-induced overweight and obesity. An improved understanding of these determinants will inform best practices for the clinical treatment and prevention of obesity. Strategies paired with systemic shifts in our public health policies and changes in our "obesogenic" environment will be most effective at attenuating the obesity epidemic.

Eating behavior trajectories in the first 10 years of life and their relationship with BMI

Background

Child eating behaviors are highly heterogeneous and their longitudinal impact on childhood weight is unclear. The objective of this study was to characterize eating behaviors during the first ten years of life and evaluate associations with BMI at age 11 years.

Method

Data were parental reports of eating behaviors from 15 months to age 10 years (n=12,048) and standardized body mass index (zBMI) at age 11 years (n=4884) from the Avon Longitudinal Study of Parents and Children. Latent class growth analysis was used to derive latent classes of over-, under-, and fussy eating. Linear regression models for zBMI at 11 years on each set of classes were fitted to assess associations with eating behavior trajectories.

Results

We identified four classes of overeating; “low stable” (70%), “low transient” (15%), “late increasing” (11%), and “early increasing” (6%). The “early increasing” class was associated with higher zBMI (boys: β=0.83, 95%CI:0.65, 1.02; girls: β=1.1; 0.92, 1.28) compared to “low stable”. Six classes were found for undereating; “low stable” (25%), “low transient” (37%), “low decreasing” (21%), “high transient” (11%), “high decreasing” (4%), and “high stable” (2%). The latter was associated with lower zBMI (boys: β=-0.79; -1.15, -0.42; girls: β=-0.76; -1.06, -0.45). Six classes were found for fussy eating; “low stable” (23%), “low transient” (15%), “low increasing” (28%), “high decreasing” (14%), “low increasing” (13%), “high stable” (8%). The “high stable”class was associated with lower zBMI(boys: β =-0.49; -0.68 -0.30; girls: β =-0.35;-0.52, -0.18).

Conclusions

Early increasing overeating during childhoodis associated with higher zBMI at age 11. High persistent levels of undereating and fussy eating are associated with lower zBMI. Longitudinal trajectories of eating behaviors may help identify children potentially at risk of adverse weight outcomes.

The obesity epidemic - Nature via nurture: A narrative review of high-income countries

Over the last three decades, the prevalence of obesity has increased rapidly in populations around the world. Despite a wealth of research, the relative contributions of the different mechanisms underlying this global epidemic are not fully understood. While there is growing consensus that the rapid rise in obesity prevalence has been driven by changes to the environment, it is evident that biology plays a central role in determining who develops obesity and who remains lean in the current obesogenic environment. This review summarises evidence on the extent to which genes and the environment influence energy intake and energy expenditure, and as a result, contribute to the ongoing global obesity epidemic. The concept of genetic susceptibility to the environment driving human variation in body weight is discussed.

Emotional eating and obesity in adults: the role of depression, sleep and genes

Stress and other negative emotions, such as depression and anxiety, can lead to both decreased and increased food intake. The term 'emotional eating' has been widely used to refer to the latter response: a tendency to eat in response to negative emotions with the chosen foods being primarily energy-dense and palatable ones. Emotional eating can be caused by various mechanisms, such as using eating to cope with negative emotions or confusing internal states of hunger and satiety with physiological changes related to emotions. An increasing number of prospective studies have shown that emotional eating predicts subsequent weight gain in adults. This review discusses particularly three lines of research on emotional eating and obesity in adults. First, studies implying that emotional eating may be one behavioural mechanism linking depression and development of obesity. Secondly, studies highlighting the relevance of night sleep duration by showing that adults with a combination of shorter sleep and higher emotional eating may be especially vulnerable to weight gain. Thirdly, an emerging literature suggesting that genes may influence body weight partly through emotional eating and other eating behaviour dimensions. The review concludes by discussing what kind of implications these three avenues of research offer for obesity prevention and treatment interventions.

Obesity and Eating Disturbance: the Role of TFEQ Restraint and Disinhibition

PURPOSE OF REVIEW

Literature from the past five years exploring roles of Three-Factor Eating Questionnaire (TFEQ) Restraint and Disinhibition in relation to adult obesity and eating disturbance (ED) was reviewed.

RECENT FINDINGS

Restraint has a mixed impact on weight regulation, diet quality, and vulnerability to ED, where it is related detrimentally to weight regulation, diet, and psychopathology, yet can serve as a protective factor. The impact of Disinhibition is potently related to increased obesity, poorer diet, hedonically driven food choices, and a higher susceptibility to ED. Restraint and Disinhibition have distinct influences on obesity and ED and should be targeted differently in interventions. Further work is required to elucidate the mechanisms underlying TFEQ eating behavior traits.

The Challenge of Stratifying Obesity: Attempts in the Quebec Family Study

Background and aims: Obesity is a major health problem worldwide. Given the heterogeneous obesity phenotype, an optimal obesity stratification would improve clinical management. Since obesity has a strong genetic component, we aimed to develop a polygenic risk score (PRS) to stratify obesity according to the genetic background of the individuals. Methods: A total of 231 single nucleotide polymorphisms (SNP) significantly associated to body mass index (BMI) from 21 genome-wide association studies were genotyped or imputed in 881 subjects from the Quebec Family Study (QFS). The population was randomly split into discovery (80%; n = 704) and validation (20%; n = 177) samples with similar obesity (BMI ≥ 30) prevalence (27.8% and 28.2%, respectively). Family-based associations with obesity were tested for every SNP in the discovery sample and a weighed and continuous PRS₂₃₁ was constructed. Generalized linear mixed effects models were used to test the association of PRS₂₃₁ with obesity in the QFS discovery sample and validated in the QFS replication sample. Furthermore, the Fatty Acid Sensor (FAS) Study (n = 141; 27.7% obesity prevalence) was used as an independent sample to replicate the results. Results: The linear trend test demonstrated a significant association of PRS₂₃₁ with obesity in the QFS discovery sample (OR_trend = 1.19 [95% CI, 1.14-1.24]; P = 2.0x10^-16). We also found that the obesity prevalence was significantly greater in the higher PRS₂₃₁ quintiles compared to the lowest quintile. Significant and consistent results were obtained in the QFS validation sample for both the linear trend test (OR_trend = 1.16 [95% CI, 1.07-1.26]; P = 6.7x10^-4), and obesity prevalence across quintiles. These results were partially replicated in the FAS sample (OR_trend = 1.12 [95% CI, 1.02-1.24]; P = 2.2x10^-2). PRS₂₃₁ explained 7.5%, 3.2%, and 1.2% of BMI variance in QFS discovery, QFS validation, and FAS samples, respectively. Conclusions: These results revealed that genetic background in the form of a 231 BMI-associated PRS has a significant impact on obesity, but a limited potential to accurately stratify it. Further studies are encouraged on larger populations.

Association between dietary diversity and obesity in Ardebil adults: a case-control study

Purpose

Obesity is a multi-factorial problem that develops from an interaction between diet, genetics, physical activity, medication, and other factors. This paper aims to examine the association between dietary diversity score (DDS) and obesity among adults of Ardebil.

Design/methodology/approach

This case-control study was conducted on 204 cases (obese and overweight participants) and 204 controls (healthy weight individuals) matched by socioeconomic status (SES), age (older than 30 years) and sex. Dietary intake was assessed using a 24 h food recall questionnaire. Data on physical activity and socio-demographic variables were gathered. DDS was computed based on the scoring of the 14 food groups recommended by the Food and Agriculture organization guideline.

Findings

The DDS of the obese group was higher (5.02 ± 1.02) than that of the healthy weight group (4.23 ± 1.18) (p < 0.001). There was a significant association between DDS and body mass index (BMI) in both groups of study, but this association was more significant in the obese group (β= 0.501,p = 0.021) than that of healthy weight group (β= 0.413,p= 0.042). Vegetable food group score in both groups of the study was associated with obesity inversely (p < 0.05).

Originality/value

This study was conducted for the first time in Ardabil city and the results showed for the first time that there is a relationship between dietary diversity and obesity. People with a higher dietary diversity score are more likely to be obese. In fact, this study for the first time proved that people who are obese have a more varied diet but less vegetables and fruits.

Multi-etiological Perspective on Child Obesity Prevention

PURPOSE OF REVIEW

The simple energy balance model of obesity is inconsistent with the available findings on obesity etiology, prevention, and treatment. Yet, the most commonly stated causes of pediatric obesity are predicated on this model. A more comprehensive biological model is needed upon which to base behavioral interventions aimed at obesity prevention. In this light, alternative etiologies are little investigated and thereby poorly understood.

RECENT FINDINGS

Three candidate alternate etiologies are briefly presented: infectobesity, the gut microbiome, and circadian rhythms. Behavioral child obesity preventive investigators need to collaborate with biological colleagues to more intensively analyze the behavioral aspects of these etiologies and to generate innovative procedures for preventing a multi-etiological problem, e.g., group risk analysis, triaging for likely causes of obesity.