Genetic and environmental contributions to variations on appetitive traits at 10 years of age: a twin study within the Generation XXI birth cohort

Purpose Given the variability in adiposity despite ubiquitous exposure to obesogenic food environments, it has been suggested that individuals respond in divergent ways to the environment they live in. The food environment becomes more ‘permissive’ as children age; therefore, genetic predisposition for a more avid appetite can be better expressed, influencing dietary quality, energy intake and weight gain. Our aim was to explore the genetic and environmental contribution of variations on appetitive traits in a sample of 10-year-old Portuguese children. Methods Participants were twins enrolled in the Generation XXI birth cohort (n = 86 pairs). Parents reported twin’s zygosity and child appetitive traits at 10 years of age through the Children’s Eating Behavior Questionnaire. Intra-class correlations (ICCs) for all appetitive traits were calculated for monozygotic and dizygotic twins separately to examine patterns of resemblance, and structural equation modeling was conducted aiming to estimate the genetic (A), shared (C) and non-shared (E) environmental variances. Results Moderate to strong heritability were found for child appetitive traits, with higher ICCs among monozygotic twin pairs. For all appetitive traits, with the exception of emotional undereating, genetic and non-shared environmental effects contributed to appetite variability. For emotional undereating, environmental effects seem to be more important than genetic effects (C: 0.81; 95% CI 0.71; 0.88 and E: 0.19; 95% CI 0.12; 0.29). Conclusion There was a significant genetic contribution, followed by non-shared environmental contribution, towards variation in appetitive traits in school-age children. Variation in emotional undereating was primarily explained by shared and non-shared environmental factors. Level of evidence Evidence obtained from well-designed cohort or case–control analytic studies.

1334Appetitive behaviors in school-age and their genetic and environmental predisposition

Background Given the great variability in adiposity and the exposure to obesogenic food environments, it has been suggested that individuals respond in divergent ways to the environment they live in. Our aim was to explore the genetic and environmental contribution of variations on appetitive behaviors in 10-year-old Portuguese children. Methods Participants were twins from the Generation XXI cohort (n = 86 pairs). Appetitive behaviors at 10 years was assessed through the Children Eating Behavior Questionnaire. Intra-class correlations for appetitive behaviors were calculated for monozygotic and dizygotic twins, and structural equation modelling was conducted to estimate genetic (A), shared (C) and non-shared (E) environmental variances. Results Twins were mainly dizygotic (65%), and a third was classified as having excess weight (30.2%). For all appetitive behaviors, with exception to Emotional Undereating, moderate to strong heritability were found and non-shared environmental effects contributed to appetite variability. For Emotional Undereating, environmental effects seem to be more important than genetic effects (C: 0.81; 95%CI 0.71;0.88 and E: 0.19; 95%CI 0.12;0.29). Conclusions There is a significant genetic contribution, followed by non-shared environmental effects, on appetitive behaviors in school-age years. Results indicate that Emotional Undereating was not heritable, being explained by shared and non-shared environmental factors. Key messages Appetitive behaviors among 10-year-olds seem to be genetically determined, with exception to Emotional Undereating, which showed to be explained by environmental factors. Understanding which genes are associated with child appetitive behaviors would give an insight in biological and behavioral influences on child eating and obesity risk.

Creating Shared Value to Enhance Customer Loyalty: A Case of a Sporting Goods Company in Korean Athletic Shoe Market

Despite the efforts of academia on exploring the merits of creating shared value, prior relevant literature seems to have a limitation that overlooks the environmental contribution suggested as a crucial component of creating shared value program by Porter and Kramer. More importantly, since most of the existing creating shared value-related studies have focused on firms in the general marketing field, there is a lack of research on the efficacy of creating shared value programs that are implemented by sporting goods companies. Thus, the objective of the present study was to examine the influence of consumers’ perceived creating shared value activities of sporting goods firm on brand image and customer loyalty in the context of the Korean sporting goods market. A total of 187 Korean sport consumers participated in the present study. Results indicated that sporting goods consumers’ perceived economic, social, and environmental values had significant impacts on brand image and, in turn, brand image positively affected customer loyalty. Consequently, the current study’s findings provide sporting goods firms with practical implications for launching creating shared value programs.

Genetic and environment factors of mental disorders: Twin studies about Alzheimer’s disease, Phobia and Autism Spectrum Disorder

With the natural and social environment changing, people’s mental health is facing severe challenges. Many people are suffering from mental disorders in the present day. A large part of mental disorders can be linked with the nerve system. And nerve system disorders tend to be associated with the development of nerve systems. The gene and the environment can play an important role in the development of the body, and abnormal genes and detrimental environmental factors can contribute a lot to nerve system disorders. Previous research has studied the occurrence and gene-and-environmental impact of many nerve system disorders. Among them, this essay chooses three kinds of disorders: Alzheimer’s disease (AD), Phobia, and Autism Spectrum Disorder, which can cause a lot of trouble in people’s daily life. In this essay, we are to study the occurrence of some nerve systems’ disorders and hope to study the genetic and environmental contribution of these disorders. These three disorders gain a lot of attention as they are very common, and they can partly reflect the contribution of genes and the environment.

Genetic and environmental contribution to social dominance orientation and its overlap with HEXACO personality traits

Social dominance orientation (SDO), i.e. the preference toward egalitarian or hierarchically arranged relations within a society may be studied from social/contextual, but also dispositional perspective. The aim of the present study was to explore genetic and environmental contribution to the individual differences in SDO, and its overlap with HEXACO personality traits, both at phenotypic and latent genetic and environmental levels. The sample consisted of 830 Croatian twins aged 19 to 28 years who filled-in the self-report measures. Data analyses indicated the heritability of SDO was over 40%, with no evidence for the common environmental influences. SDO phenotypic variance substantially overlapped with Honesty-Humility, Emotionality, and Openness domains. Numerous significant correlations were found at the facet level, with the highest phenotypic overlap for the “interstitial” altruism facet. However, incremental predictive power of personality (over age and sex) was moderate: 13% and 19% of the phenotypic SDO variance was predicted by HEXACO traits at the domains and facet levels, respectively. Multivariate behavioural genetic analysis indicated that 19% and 3% of the genetic and unique environmental variance of SDO overlapped with the genetic and unique environmental variance of personality, respectively. Substantial genetic correlations of SDO with Honesty-Humility and Openness domains were found, while marginal unique environmental correlation was found for Openness domain only. The etiological overlap between SDO and personality represents an argument in favour of taking dispositional along with social/contextual perspective in explaining social behaviour.

Inferring an animal's environment through biologging: quantifying the environmental contribution to animal movement

Background: Animals respond to environmental variation by changing their movement in a multifaceted way. Recent advancements in biologging increasingly allow for detailed measurements of the multifaceted nature of movement, from descriptors of animal movement trajectories (e.g., using GPS) to descriptors of body part movements (e.g., using tri-axial accelerometers). Because this multivariate richness of movement data complicates inference on the environmental contribution to animal movement, studies generally use simplified movement descriptors in statistical analyses. However, doing so limits the inference on the environmental contribution to movement, as this requires that the multivariate richness of movement data can be fully considered in an analysis. Methods: We propose a data-driven analytic framework to quantify the environmental contribution to animal movement that can accommodate the multifaceted nature of animal movement. Instead of fitting a simplified movement descriptor to a suite of environmental variables, our proposed framework centres on predicting an environmental variable from the full set of multivariate movement data, i.e., the reverse of the route of causal inference. The measure of fit of this prediction is taken to be the metric that quantifies how much of the environmental variation relates to the multivariate variation in animal movement. We demonstrate the usefulness of this framework through a case study about the contribution of grass availability and time since milking to cow movements using machine learning algorithms. Results: We show that on a one-hour timescale 37% of the variation in grass availability and 33% of time since milking contributed to cow movements. Grass availability contributed mostly to the cows’ neck movement during grazing, while time since milking contributed mostly to the movement through the landscape and the shared variation of accelerometer and GPS data (e.g., activity patterns). Furthermore, this framework proved to be insensitive to spurious correlations between environmental variables in quantifying the contribution to animal movement. Conclusions: Not only is our proposed framework well-suited to study the environmental contribution to animal movement; we argue that it can also be applied in any field that uses multivariate biologging data, e.g., animal physiology, to study the relationships between animals and their environment.