The association of the executive functions with overweight and obesity indicators in children and adolescents: A literature review

Journal Pre-proof The Association of the Executive Functions with Overweight and Obesity Indicators in Children and Adolescents: A Literature Review Paula Mamrot, Tomasz Han´c

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Please cite this article as: Mamrot P, Han´c T, The Association of the Executive Functions with Overweight and Obesity Indicators in Children and Adolescents: A Literature Review, Neuroscience and Biobehavioral Reviews (2019), doi: https://doi.org/10.1016/j.neubiorev.2019.08.021

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The Association of the Executive Functions with Overweight and Obesity Indicators in Children and Adolescents: A Literature Review

Paula Mamrot 1, Tomasz Hanć 1

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Department of Human Biological Development, Institute of Anthropology, Faculty of

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Biology, Adam Mickiewicz University, ul. Uniwersytetu Poznańskiego 6, 61-614 Poznan, Poland

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Address for correspondence: Paula Mamrot, Department of Human Biological

Development, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznań,

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Highlights

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Poland, tel: +48618295729, e-mail: [email protected]

Systematic review supports significant association of the executive functions with

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excess body mass in children and adolescents The strongest evidence supports the relationship between inhibitory control and higher BMI, being overweight or obese There is a need to systematize the way of defining and testing executive functions in

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the context of studying their relationship with body weight

Abstract

The prevalence of obesity in children and adolescents has become an increasing health problem all over the world. Prior studies suggest there is a relationship between excess body mass in adults and executive functions (EF). The paper analyzes recent studies on the

association of obesity indicators and EF performance in children and adolescents. We analyzed four types of studies: comparison studies with obese and healthy children, crosssectional studies describing dependencies between EF and BMI, follow up studies applying EF as a predictor of overweight/obesity and studies describing the effect of weight reduction on improving EF. We interpreted the results based on the categorization of EF into three main processes: inhibitory control, working memory, cognitive flexibility, and higher-level EF such as reasoning, problem-solving and planning. The strongest evidence supports the relationship

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between poor inhibitory control and higher BMI, overweight or obesity. However, the mechanism of the association is still unclear. A better understanding of the EF-obesity link

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may be relevant for the prevention of obesity or help in EF deficits improvement.

Introduction

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Obesity is currently considered one of the most serious growing health problems

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around the world. According to World Health Organization (WHO) reports, in 2016 over 340 million children aged 5-19 years were of excess weight (WHO, 2018). In Europe, the rate of children aged 6-9 with overweight and obesity was 22.7% - 53.05% depending on the country

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(Wijnhoven et al., 2014). Although statistical analysis suggests that in recent years the upward trend in obesity has slowed, the number of obese children is still alarming (Kelsey et al., 2014), especially since childhood obesity increases the likelihood of being obese in adulthood

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(Luppino et al., 2010). Furthermore, being obese affects physical health (Sahoo et al., 2015), as well as causes psycho-social consequences during childhood (Sahoo et al., 2015; Luppino et al., 2010).

Obesity is a disease of multifactorial background, hence it is examined extensively in many aspects: biological (e.g.: genetics) (Locke et al., 2015; Frayling et al., 2007), socioeconomic (Petraviciene et al., 2018; Wagner et al., 2018; Gibbs et al., 2013) or

psychological (Miller et al., 2018; Stoeckel et al., 2017; Beck, 2016; Tanofsky-Kraff et al., 2006). However, recently the attention of many researches has been focused on the relationship between obesity and executive functions. Executive functions (EF), also called executive control (Berthelsen et al., 2017), are neurocognitive mental processes involved in goal-directed behavior, planning and monitoring, such us: inhibitory control, shifting, delaying of gratification, selective attention, sustained attention, working memory (Berhelsen et al., 2017). According to neuroimaging studies, executive functions are processes occurring

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at the prefrontal and parietal regions of the brain (Chung et al., 2014). Across the lifespan, EF develop intensively during childhood into adolescence and decrease during aging (Zelazo et al., 2004). The proper functioning of EF is relevant for physical health, as well as mental

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health, school achievements and job success (Diamond, 2013). It is thought that the following factors have an influence on EF development: socioeconomic status, preterm birth, physical

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activity, sleep deprivation, stress, social network or genetic background (Zysset et al., 2018).

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Understanding the mechanisms of obesity is important for further prevention from early childhood. Therefore, it is important to synthesize the results of previous research on the relationship between EF and obesity, as it could be useful in early psychosocial intervention

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and in the health education area. According to our knowledge, several systematic reviews of the EF-obesity relationship in adults (Rotge et al., 2017; Veronese et al., 2017; Prickett et al., 2015; Fitzpatrick et al., 2013) or across the lifespan (Yang et al., 2018; Gettens et al., 2017;

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Smith et al., 2011) have been published, however, only a limited number of studies address this association exclusively in children and adolescents. The aim of this study was to assess the relation between EF and obesity in children and youths based on a systematic review of the relevant research. In contrast to previous reviews we paid attention to various obesity indicators, not only the most popular BMI, but also body fat, visceral fat and waist circumference. Furthermore, we applied a different division of executive functions than in the

previous works. Since various names of EF and a variety of diagnostic tools are in use the applied division was relevant for explicit interpretation of the research results. Methods A literature review was conducted in 2018 between the 5th and 15th January using Scopus, Medline and Google Scholar databases. The following key words were used in article titles, abstracts and key words’ search: /executive functions and obesity or overweight or body fatness and children or adolescents/. To be included in the analysis, the articles had to meet

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the following criteria: (i) to investigate the relationship between overweight/ obesity indicators and EF in children and adolescents; (ii) to be a quantitative study, (iii) to be written in English. Studies comparing healthy children and children with a serious medical condition

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or mental illness and those focused on adults >18 years were excluded from the review.

The various nomenclature of individual EF is given in the literature (Chung et al.,

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2014). In the works analyzed in this review the authors used different nomenclature for EF as

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well. Although this might indicate the complexity of the EF concept, it brings difficulties in the comparison and consistent interpretation of the results. Therefore, we propose an analysis based on the work of Adele Diamond (2013). To our knowledge, this is one of the most

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comprehensive divisions of EF, based on a wide range literature. She distinguished three main cores of EF which are in the order: inhibitory control, working memory and cognitive flexibility, assigning the other executive functions to those three categories. Higher-level

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executive functions such as reasoning, problem-solving and planning are built from these three main EF. Results

In all, 610 articles were found by a combination of the above mentioned keywords. Four hundred and sixty-eight studies were excluded after screening by title. The remaining 142 articles were reviewed by abstracts. After excluding duplicate articles and those which

did not fit the criteria (language, both EF and obesity indicators, participants’ age, article type), there remained 31 articles. Two of them were not possible to review due to lack of full access (Nelson et al., 2017; Bozkurt et al., 2017), and another two failed to meet the criteria as they made no reference to measurement of body mass or fatness but only unhealthy eating behavior (Tryon et al., 2013; Riggs et al., 2012). Finally, 27 papers from 25 studies met all the criteria and were reviewed by full-text. Both the articles of Wirt et al. (2015; 2014) come from the same study, as do the two articles of Kamijo et al. (2014; 2012). However, we

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decided to include them in the review because of the authors’ use of different diagnostic tools and various kinds of analyses in each article, which led to new conclusions. The process of article selection is shown in Figure 1.

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In all of the studies the number of 13 030 participants aged 3 to 18 years old was examined. From the 27 papers only half include information about the detailed number of

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excess weight participants, although in each study Body Mass Index (BMI) was used as an obesity indicator. In each study, 1 to 7 EF were examined. The most frequently studied

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function was inhibitory control – 85.18%. In above 85% of studies at least one of the EF was associated with excess body mass. Four types of research are distinguished in this review: (i)

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papers describing differences in EF between children with healthy weight and excess weight (40.74%), (ii) cross-sectional studies describing the association of the EF with BMI (37.04%), (iii) follow up studies describing EF as a predictor of excessive weight gain (18.52%) and (iv)

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a study describing the effects of weight reduction on improving EF (3.70%). Detailed results are presented in Table 1. Table 2 presents the EF examined by the researches and applied methods in detail. The

EF strictly defined as inhibitory control was the most frequently tested one (44.04%). Inhibitory control involves the control of impulses, behavior, thoughts and emotions (Diamond, 2013). Based on the division of A. Diamond (2013), other EF that could be

managed with inhibition such as response inhibition, resistance to interference and selfregulation, were examined in the next 11 publications. This means that almost each study (85.18%) was focused on inhibitory control as an important EF in the context of excess weight. To examine inhibitory control the researchers applied the following methods: The Go/NoGo Task (21.74% of inhibitory control studies), Flanker Task (17.39%), The Stroop Color Word Interference Task (13.04%), The Five Digit Test (8.70%) and tasks based on single reaction time – SRT (8.70%). The following methods were applied once: The Conners’

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Continuous Performance Test – II, The Trial Making Test A and B, The Sky Search, The Fruit Stop Task, The Two-Choice Reaction Task, The Tapping Task, The Task Performance, The Ruff2 and 7 Selective Attention Test, The Symbol Search from WISC-III, The Revised-

Task and The Cognitive Assessment System.

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Strategy Application Test, The Sustained Attention Task from KiTAP, The Opposite Words

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Working memory, the next core of EF, refers to holding and working with information

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in mind that is no longer perceptually persistent (Diamond, 2013). For the examination of working memory, the following methods were mostly applied: tests based on counting or remembering backwards (The Digit-span subtest of WISC-III, The Counting Span Task, The

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Digit Span Backwards, the Symbol Digit Modalities Test – 44.44%). Other methods applied in individual studies were The Corsi-Block Tapping Task, The Wide Range Assessment of Learning and Memory, The McCarhy Scales of Children’s Abilities, The Letter-number

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sequencing and working memory functional magnetic resonance imaging (fMRI) task. The third core EF, cognitive flexibility, associated with being mentally flexible in

response to changing stimuli (Diamond, 2013), was examined using The Five Digit Test (28.57%) and the Cognitive Flexibility Task (28.57%). Furthermore, some methods applied only once were as follows: The Flexible Item Selection Task, The Verbal Fluency, The Trial Making Test part B.

Last but not least, the following methods were applied to measure higher-level EF: The Delay of Gratification Task (41.66%), gambling tasks (The Children’s Gambling Task, The Iowa Gambling Task, the Hungry Donkey Task – 25%), The Tower of London Test (16.66%), and methods applied only once - The Choice Delay Task, The Question Based Delay Discounting Test, The McCarthy Scales of Children’s Abilities, The Andre Rey Test, The Cognitive Assessment System, The Zoo map and Similarities. Overweight and obesity measure methods

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In each study BMI was the main indicator of overweight and obesity. The overweight cut off point was set on the 85th percentile. The obesity cut off point was set on the 95th or 97th percentile. Indicators of obesity other than BMI were used in only 7 studies (25.93%). These

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were as follows: waist circumference (1 study), visceral adipose tissue (3 studies), body fat (5 studies).

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Differences in EF between excess body weight and healthy weight children

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The most (40.74%) of the articles focused on a comparison of executive function performance between the group of non-overweight children and children with overweight/obesity. From these, 11 out of 27 publications, 37.03% tested the performance of

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inhibitory control (inhibitory control, response inhibition, impulsive disinhibition, selfregulation, sustained attention and visuospatial attention) and significant differences were found in 70.37% of them, in favor of the group with a healthy body mass (Tsai et al., 2016;

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Wirt et al., 2014; Kamijo et al., 2014; Gentier et al., 2013; Fields et al., 2013; Maayan et al., 2011; Pauli-Pott et al., 2010). Cognitive flexibility (switching, attention shifting, shifting) were examined in 3 studies. In all of them overweight or obese participant response was worse than healthy weight participants (Blanco-Gomez et al., 2015; Maayan et al., 2011; Vardejo-Garcia et al., 2010). The different aspects of working memory, tested by 4 researchers, were found to be related with body weight in one of these studies (Maayan et al.,

2011). Finally, the higher-level executive functions such as the ability to delay gratification, decision making, problem solving, planning and reasoning were tested in 4 studies, of which 75% found significant differences between the groups (Qavam et al., 2015; Fields et al., 2013; Vardejo-Garcia et al., 2010). Based on these results it could be concluded that obese children performed tests more slowly than their healthy-weight peers and made more mistakes. Cross-sectional studies describing the association of the EF with body mass Cross-sectional studies which describe the relationship between EF and body mass

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were the second of the most numerous articles of this review (37.04%). Out of these 10 crosssectional studies, 70% found a significant association of body mass index with at least one

EF: inhibitory control (inhibitory control, Huang et al., 2015; Wirt et al., 2015; Kamijo et al.,

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2012; processing speed, Schwartz et al., 2013), cognitive flexibility (cognitive flexibility, Schwartz et al., 2013; attention shifting, Groppe et al., 2014), working memory (working

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memory, Schwartz et al., 2013; verbal working memory and spatial working memory,

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Alarcón et al., 2015, updating, Groppe et al., 2014) and higher-level executive function (ability to delay gratification, Bruce et al., 2012). What is more, 20% of the studies found an association of visceral fat with executive functions such as working memory, cognitive

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flexibility, inhibitory control (processing speed, Schwartz et al., 2013) and planning (Davis et al., 2011), even though BMI was not associated with EF test results. In the study of Huang (2015) an additional association of greater waist circumference with worse inhibitory control

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was recorded. In conclusion, the better the cognitive performance, the lower BMI or lower visceral fat.

EF as a predictor of excessive weight gain in follow up studies The studies presented in the two above mentioned categories are of an associative nature and do not give any insight as regards an EF-obesity link. Follow up studies are noteworthy due to their ability to assess the long-term relationship between executive

functions and overweight/obesity in children and adolescents. There were only 18.52% longitudinal studies from the total of articles reviewed which tested the values of EF as predictors of excessive weight gain. In all of these studies significant relationships between greater EF performance and a better chance of being a healthy weight at further time point were found. However, the results of a study by Guxens (2009) showed these relationships to be age dependent. At the age of 4 executive functions were not significantly related to BMI, while 2 years later children with worse results at 4y. were more often characterized by

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overweight. These results suggest the influence of EF on excessive body weight gain. In turn, other researchers’ (Stautz et al., 2016) results showed that the working memory but not

inhibitory control at the age 8 and 10 were associated with being overweight at the age of 13.

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The researchers concluded that the better the working memory results, the greater the

likelihood of being a healthy weight child. Likewise, other results of longitudinal research

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concerned the ability to delay gratification (Bruce et al., 2012; Seeyave et al., 2009). Better

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results in the gratification task were important predictors for appropriate body weight several years later. EF training and its impact on weight reduction was examined in one study (Verbeken et al., 2013). The authors tested how an 8-month period of EF training (working

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memory and inhibitory control) could affect weight reduction progress in children and adolescents aged 9-14. For two months after completion of the training the children were more able to lose weight. Overall, the results suggest that low executive functioning in

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childhood is a risk factor for excessive weight gain in the following years of the progressive phase of physical development. It seems, therefore highly likely that interventions focused on EF improvement have the potential for the prevention of obesity and being an effective method of treatment. Effects of weight reduction on improving EF

In one of the studies changes in children’s cognitive functioning were assessed after the reduction of the amount of visceral adipose tissue (Raine et al., 2017). It is worth noticing that, regardless of the amount of total body fat, the reduction of visceral fat tissue was significant predictor of better results in neurocognitive tests, particularly among obese participants. This may suggest the influence of visceral fat on executive functioning. In fact, in the studies of Veit et al. (2014), increasing visceral fat was associated with cortical thinning in adults. According to Isaac et al. (2011), higher visceral adipose tissue in healthy elderly

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people was associated with a lower hippocampus volume and worse cognitive functioning. However, in the scope of this review, the study of Raine et al. (2017) was the only one to test such an intervention. Thus, the conclusions are limited.

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Discussion

The aim of this review was to present analyses of recent studies on the relationship

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between EF and obesity indicators in children and adolescents. Although there are systematic

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reviews of the EF-obesity relationship in adults (Rotge et al., 2017; Veronese et al., 2017; Prickett et al., 2015; Fitzpatrick et al., 2013) or across the lifespan (Yang et al., 2018; Gettens et al., 2017; Smith et al., 2011), fewer address this association only in children and

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adolescents. Yang and co-workers (2018) made a broad meta-analysis concerning the EFobesity link at various stages of ontogenesis, however, they exclude the articles in which children were younger than 6 years and they focused in their analysis on BMI as the only

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obesity indicator. A remarkable review about children and adolescents was made by Martin and co-workers (2017), however, the review concerns the relationship between obesity and school achievements, which are influenced by more factors than EF. In turn, Miller (2016) in her review presented a valuable analysis of conceptual EF-obesity models and suggested pediatric strategies for the prevention of obesity in children, although she focused mainly on a one-way hypothesis direction that EF deficits affect body mass. Thus, we have enriched the

review with additional indicators of obesity, such as body fat, visceral fat and waist circumference. What is more, in order to facilitate the interpretation of research, using different EF nomenclature and different diagnostic tools, we have applied the EF classification to the groups proposed by the work of Diamond (2013). After analysis of the 27 papers it can be concluded that cognitive functioning is significantly related to body weight in children and adolescents. This relationship concerns both children and adolescents. According to main cores of EF, inhibitory control was

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associated with obesity indicators in 70.37% comparisons of healthy and excess weight participant studies and in all of the cross-sectional studies. However, as a weight status predictor, inhibitory control was significant in only one study involving EF training

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(Verbeken et al, 2013). In turn, the working memory component of EF was significantly

worse in obese participants in only 25% studies, however, in cross-sectional studies working

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memory was associated with body mass in each one, as well as in the studies using working

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memory as a predictor of later weight gain. Finally, the third component of EF, cognitive flexibility, was at a higher level in healthy participants in each study and was associated with body mass or weight status in cross-sectional studies, although the value of cognitive

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flexibility as a predictor of future weight gain is unknown. In general, body mass or body status was associated with at least one EF in 81.82% of 11 comparison studies, 70% of 10 cross-sectional studies, while 100% of 5 longitudinal studies tested EF as a weight status

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predictor, and finally, in one study which described the effect of visceral fat reduction on EF. The mechanism that may underlie the relationship between executive functions and

obesity is still not fully explained. It is not clear whether executive functions affect body mass, or body weight affects executive functions. Cognitive deficits lead to obesity

The authors supporting the hypothesis about the influence of cognitive deficits on weight gain suggest mainly a mechanism based on inhibitory control impairment. Children with poorer self-control may be characterized by obesity-related behaviors such us eating greater amounts of food, eating high fat or high sugar products but lower quantities of vegetables (Pieper and Laugero, 2013), and a sedentary life-style (Wirt et al., 2015). Difficulties with self-control also affect the ability to delay gratification and impact eating more unhealthy food (Bruce et al., 2009). As a consequence, such children are more

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vulnerable to putting on weight. An interesting hypothesis on stress as an intermediate variable between EF and obesity was tested by Tryon and co-workers (2013). The researchers conducted a study on chronic stress exposure and its effect on brain activity and obesogenic

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eating habits. According to the authors, chronic stress is related to unhealthy eating habits that may be associated with different brain activity patterns in regions responsible for mediating

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motivation and decision-making. Thus, chronic stress may alter the brain activity in the

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anterior prefrontal cortex (PFC) and dorsolateral PFC, regions associated with executive control and this may lead to obesogenic eating and weight gain (Tryon et al., 2013). Obesity and fatness lead to executive dysregulation

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On the other hand, a large amount of visceral adipose tissue, as the result of a sedentary lifestyle and inappropriate diet, may have an impact on cognitive function through metabolic dysregulation (Raine et al., 2017), changes in brain structure (de Groot et al., 2017)

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such as degeneration of the frontal cortex, associated with EF (Qavam, 2015). According to O’Brien et al. (2017), obesity and a high fat diet have a high impact on the central nervous system (CNS) through increased circulating fat free acids, increased triglyceride level and inflammatory adipokines. It has been demonstrated that a high level of triglycerides and fat free acids lead to increased neurodegeneration (O’Brien et al., 2017). According to the authors, as a consequence, obesity can lead to executive dysregulation and be one of the risk

factors of Alzheimer’s disease or mild cognitive impairment in the elderly. The other possible explanation of an obesity-EF link can be found in the review of Agusti and co-workers (2018). The researchers analyzed the studies on the mutual activity of the gut-brain axis, cognitive function and obesity. They concluded that along with an unhealthy diet and an excessive energy supply that leads to obesity, there are adverse changes in the intestinal microbiota. This, in turn, may affect the neuroendocrine system and contribute to its dysregulation, affecting the executive functions.

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The common background of EF and obesity The third hypothesis regarding the association of EF with obesity is the assumption of common association, but no causation. Of particular interest is an article by Susan Carnell et

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al. (2012). In their comprehensive biobehavioral risk model of child and adult obesity the authors noticed a research gap in the area of common genetic variant of obesity and brain

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response to food, including cognitive traits as inhibitory control. The authors conclude that

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structural and functional characteristics of the brain and obesity may share a common genetic background, although these are hypotheses that require further research. Nevertheless, it seems to be supported by the results of the work of Marioni et al. (2016) who found, using the

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method of genome wide association studies, seven common genetic variants from four genes (AKAP6, TOMM40, THEM161B, TNRC6B) associated with both cognitive function and BMI. Some of the researchers indicate specific genes that may be related to both obesity and

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cognitive dysregulation. For instance, according to Bressler et al. (2013), the FTO gene, associated with adiposity and obesity-related behaviors, might also be related to diminished cognitive functions. Another example is the serotonin transporter gene (SLC6A4). It is thought that SCL6A4 has a significant role in executive functions (Zhao et al., 2013). However, the studies of Zhao et al. (2013b) suggest that promoter methylation of SLC6A4 is also associated with regulating food intake and body mass.

Implications There may be relevant implications in the findings of the reviewed studies. If a low level of executive functioning is associated with a greater risk of excess body mass, some supportive intervention could be implemented for better overweight/obesity prevention and treatment. Better executive functioning might help optimize treatment results through enhancing the maintenance of a healthy and well-balanced diet. Thus, different cognitive training could be used to improve EF skills in children and adolescents. Some of the possible

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interventions previously tested on adults, but also targeted for children, are reviewed in an article of Hayes et al. (2018). She explored different kinds of EF improvement strategies and noticed the need for further studies on their efficiency. These strategies include, for instance,

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computer training programs for enhancing inhibitory control and working memory, or

episodic future thinking (EFT). According to the results of our review the most promising EF

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to implement seems to be inhibitory control, as it is the most widely studied function with the

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highest percentage of significance in the context of obesity indicators. However, our results indicate an insufficient amount of research with other EF. In addition, none of the EF works separately – they are closely related to each other (Diamond, 2013). Thus, comprehensive EF

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training should be considered.

Since some findings on visceral fat and body fat suggest that these may be important parameters in the analysis of the EF-obesity link, it is worth expanding the diagnosis of

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obesity in future research with the parameters of body composition. There may be a relationship between adipose tissue and EF, even if it is not related to BMI.

Conclusions There is a significant association between executive dysfunction and excess body mass in children and adolescents. The strongest evidence supports the relationship between poor

inhibitory control and higher BMI, being overweight or obese. However, more longitudinal studies including EF and body mass assessment at different time points are needed to understand the mechanisms of the link and its direction. A better understanding of the EFobesity link may be relevant for the prevention of obesity through EF enhancement or help in EF deficit improvement through body fat reduction programs. Thus, further studies on the association of executive functions with overweight/obesity in children and adolescents are

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warranted.

Disclosures

This work was supported by the National Science Centre (NCN) in Poland [grant

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number OPUS 2016/21/B/NZ5/00492].

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Table 1. Research testing the relationship between EF and obesity indicators Type First of author analys is

Dat Stud N e y type

Populatio Age n (year s)

Obesity/overwei Executive ght measure function

Results

Obese and healthy weight individuals comparison de Groot et al.

201 C 7

42

Obese (n=23) and matched healthy weight (n=19)

12-16 BMI

Tsai et al.

201 C 6

52 (♀16)

Obese (n=26) and controls (n=26)

9-10

Blanco- 201 C Gomez 5 et al.

515 (♀265)

Obese + 6-10 overweigh t (n=221) and healthy controls

Qavam et al.

♂120

Jo Wirt et al.

201 C 4

(1) Visuospati Obese al children did attention poorer than healthyweight controls in EF tasks (slower reaction time)

-p

BMI; >97th obesity, >95th and <97th overweight; >16th and <95th normal weight

Poorer performanc e of overweight and obese children in switching

Obese 15-18 BMI; >95th (32,5%), obesity; >85th overweigh and < 95th t (30%), overweight normal weight (30%)

(1) Planning and organizing (2) Problem solving

Significant difference between the executive functions in excess and healthy weight students. Obese students have poorer EF than healthy weight peers

Obese 7±0,6 BMI; >97th (n=17), obesity; overweigh >90th and <97th t (n=25), overweight nonoverweigh t (n=454)

(1) Inhibitory control

Obese participants achieved lower level of inhibitory control than non-obese,

re

(1) Inhibitory control (2) Switching (3) Visuomot or ability

lP

498 (♀50,2 %)

No differences between obese and healthy weight adolescents

ro of

BMI; >95th obesity; >5th and <85th healthy weight

ur na

201 C 5

(1) Inhibitory control (2) The ability to delay gratificati on

nonoverweight and overweight children 201 C 4

74

Obese (n=37) and healthy weight (n=37)

7-9

BMI; >87th obesity, BF

(1) Inhibitory control (2) Response accuracy

Obese children performed longer reaction time than healthy weight

Gentier et al.

201 C 3

38 (♀20)

Obese (n=19), healthy weight (n=19)

6-12

BMI BF

(1) Response time

Obese children were slower than healthy weight peers only at Simple Reaction Time Task (EF – response time), not at Choice Reaction Time

Fields et al.

201 C 3

61

Obese 14-16 BMI; >95th (n=21), obesity; >85th overweigh and <95th t (n=20), overweight healthy weight (n=20)

re

-p

ro of

Kamijo et al.

Obese adolescents performed worse at sustained attention task – more omission errors than healthyweight and overweight controls

14-21 BMI; >95th (1) Response obesity or BMI > inhibition 30kg/m2 (2) Attention (3) Cognitive flexibility (4) Verbal fluency (5) Working memory

Obese participants performed worse in all EF measures

ur na

lP

(1) Sustained attention (2) Inhibition control (3) Decision making

91

Obese (n=54) and healthy weight (n=37)

177

Obese 8-15 overweigh t,

Jo

Maayan 201 C et al. 1

PauliPott et al.

201 C 0

BMI; >90th and <95th overweight; >95th obesity;

(1) Inhibitory control

More inattention in obese children and

adolescents , no difference between groups in impulsivity scores 61 (♀24)

Obese, 13-16 BMI; 17-24 overweigh kg/m2 normalt, healthy weight 24-28 weight kg/m2 overweight; 2951 kg/m2 obesity

(1) Response inhibition (2) Shifting (3) Planning (4) Decisionmaking (5) Reasoning (6) Selfregulation (7) Working memory

No difference between excess weight group and healthy weight group at: response inhibition, planning, reasoning and selfregulation. Poorer performanc e of excess weight group at shifting and decisionmaking functions.

152 (♀67)

Obese 12-17 BMI; >95th (n=18), obesity; overweigh >5th and < 85th t (n=46) healthy weight and healthy weight

ur na

Alarcón 201 C et al. 5

lP

EF level with BMI association

re

-p

ro of

Verdejo 201 C -Garcia 0 et al.

201 C 5

Jo

Huang et al.

525 Obese, 12-13 BMI, WC (♀272)s overweigh t and healthy weight

(1) Verbal working (2) memory (3) Spatial working memory

BMI percentile was negatively correlated with verbal and spatial working memory performanc e

(1) Inhibitory control

BMI and WC were negatively associated with inhibitory control, independen tly of aerobic fitness. Positive association

between aerobic fitness and executive function in all children 201 C 5

187 (♀47,6 %)

Obese 15-18 BMI; >95th (26,2%), obesity; >85th overweigh and <95th t (20,9%), overweight normal weight

(1) Delay of gratificati on (2) Response inhibition (3) Cognitive flexibility

No association between EF and excess weight

Wirt et al.

201 C 5

297 (♀52,5 %)

Obese 7±0,6 BMI; >97th (n=4), obesity; >90 and overweigh < 97th t (n=22), overweight; normal <10th weight underweight (n=236), underweig ht (n=35)

(1) Inhibitory control task (2) Cognitive flexibility task (3) Sustained attention task

No association between sustained attention and BMI. Lower inhibitory control and cognitive flexibility were predictors for higher body weight.

Groppe et al.

201 C 4

1657 (♀52,1 %)

Obese, 6-11 overweigh t and normal weight

ur na

lP

re

-p

ro of

Hughes et al.

Jo

Schwart 201 C z et al. 3

983 (♀503)

BMI

Obese, 12-18 VF, BF overweigh t, healthy weight

(1) Attention shifting (2) Updating and monitorin g working memory (3) Inhibitory control (4) Decision making

The negative association between BMI, attention shifting and updating working memory.

(1) Working memory (2) Resistance to interferenc e (3) Cognitive flexibility (4) Processing speed

Female subjects with low VF performed better than female subjects with high VF at working memory tasks, cognitive flexibility

task and processing speed (no difference for men).

201 C 3

29 (♀15)

Obese, 3-6 overweigh t, healthy weight

BMI

Kamijo et al.

201 C 2

126

Obese 7-9 (n=30), overweigh t (n=26), healthy weight (n=70)

Bruce et al.

201 C 2

59 (♀28)

Obese, 8-12 overweigh t, healthy weight

Davis et al.

201 C 1

170 Overweig (♀56%) ht and sedentary healthy weight

No association between EF measures and BMI zscores

BMI; BF; >30,6% and <37,3% overweight; >37,3% obesity

(1) Inhibitory control

Negative association between BMI and inhibitory control

BMI

(4) The ability to delay gratificati on

The higher BMI the poorer the ability to delay gratificatio n

(1) (2) (3) (4)

BMI zscores were not associated with planning and attention, however VF and SAF were positively related with planning.

-p

re

lP

ur na Jo

(1) The ability to delay gratificati on (2) Decision making (3) Inhibitory control (4) Switching

ro of

Pieper and Lauger o

7-11

BMI; >85th overweight; BF, VF, SAF

Planning Attention Sedentary Simultane ous

BMI zscores were negatively associated only with simultaneo us. No association between

EF as a predictor of later weight gain 201 F 3

164 (♀93)

Obese, 4 overweigh t and normal weight

Verbek 201 F en et al. 3

44 (♀22)

Overweig ht

BMI

(1) The ability to delay gratificati on

re

-p

Schlam et al.

ro of

BMI and other executive functions. BF was associated with planning and attention, whereas VF and SAF with planning and simultaneo us.

BMI

(1) Working memory (2) Inhibition

After 8months working memory and inhibition training, children improved their working memory skills and were more capable of maintaining their weight loss at 2 months post training

BMI; >85th overweight

(1) The ability to delay gratificati on

Children who performed worse at age 4 were more likely to be

Jo

ur na

lP

9-14

Seeyav e et al.

200 F 9

805

Obese, 4 overweigh t, healthy weight

Longer time delaying of gratificatio n at age 4 predicted lower BMI 30 years later

overweight at age 11

200 F 9

261

Obese, 4 overweigh t, healthy weight

BMI; >95th obesity; >85th and <95th overweight

Stautz et al.

201 F 6

6069 (♀50,9 %)

Obese, 8-10 overweigh t and healthy weight

BMI (measured at age 13)

(1) Verbal fluency (2) Problem solving (3) Working memory

Executive function scores at age 8 and age 10 predict overweight status at age 13 – the better working memory test results, the greater chance not being overweight

(1) Inhibitory control

The association between reduction in VAT and greater cognitive performanc e, independen t of whole body’s fat changes, particularly among obese participants

-p

(1) Selective attention (2) Attentiona l control (3) Working memory (4) Response Inhibition

re 201 F 7

144

Obese (n=77) and matched healthy weight (n=77)

Jo

ur na

Raine et al.

lP

The effect of fat reduction on EF

8-9

Overweight at 6 years is associated with lower executive functions at age 4 but at age 4 executive functions were not associated with BMI

ro of

Guxens et al.

BMI (BMI-forage-percentiles), VAT, SAT

C – cross-sectional, F – follow-up, BMI – body mass index, BF – body fat, VF – visceral fat, SAF – subcutaneous abdominal fat, VAT – visceral adipose tissue, SAT - subcutaneous abdominal adipose tissue, WC – waist circumference

Table 2. EF methods applied in studies and their association with obesity indicators EF EF tested at the EF measure at the study Authors group* study**

The Stop Signal Task

de Groot et al. (2017)

N

The Flanker Task

Raine et al. (2017)

Y

The Flanker Task

Huang et al. (2015)

Y

The Five Digit Test (FDT)

Blanco-Gomez et al. (2015) Wirt et al. (2015)

N

The Go/NoGo Task (subtest of KiTAP)

Wirt et al. (2014)

Y

Groppe et al. (2014)

N

The Flanker Task

Pieper et al. (2013)

N

The Two-Choice Reaction Task

Verbeken et al (2013)

Y

The Flanker Task

Kamijo et al. (2014)

Y

Kamijo et al. (2012)

Y

The Go/NoGo Task; Interference Task

Pauli-Pott et al. (2011)

Y

The Stop Signal Task

Stautz et al. (2016)

N

The Tapping Task

Hughes et al. (2015)

N

The Stroop Color-Word Interference Test The Five Digit Test (FDT), The Stroop Color-Word Interference Test The Go/NoGo Task

Maayan et al. (2011)

Y

Vardejo-Garcia et al. (2010)

N

Fields et al (2013)

N

The Stroop Color-Word Interference Test The simple and four choice reaction time (SRT/CRT)

Schwartz et al. (2013)

Y(♀)

Gentier et al. (2013)

Y

The Task Performance

Kamijo et al. (2012)

Y

The Ruff 2 and 7 Selective Attention Test; the Symbol Search (from the WISC-III) The Revised-strategy application test (R-SAT) The Sky Search task (from TEACh)

Schwartz et al. (2013)

Y(♀)

Verdejo-Garcia et al. (2010) Stautz et al. (2016)

N

ur na

lP

re

-p

The Go/NoGo Task (subtest of KiTAP) The Fruit Stop Task

The Go/NoGo Task

Response inhibition

Impulsive disinhibition

Jo

Resistance to interference Response time/response accuracy

Processing speed

Self-regulation Selective attention

Y

ro of

Inhibitory Control Inhibitory control

The association with obesity indicators

Y

The sustained attention task (subtest of KiTAP)

Wirt et al. (2015)

N

Fields et al. (2013)

Y

The Opposite Words task (from TEA-Ch) Computerized serial reaction time task (SRT), the Posner paradigm The Cognitive Assessment System The Trial Making Test Part A (TMT-A)

Stautz et al. (2016)

N

Tsai et al. (2016)

Y

Davis et al. (2011)

N

Maayan et al. (2011)

Y

The Five Digit Test (FDT)

Blanco-Gomez et al. (2015)

Y

Attention shifting

The Cognitive Flexibility Task

Groppe et al. (2014)

Y

Shifting

The Five Digit Test (FDT)

Y

Cognitive flexibility

The Flexible Item Selection Task (FITS)

Vardejo-Garcia et al. (2010) Hughes et al. (2015)

Wirt et al. (2015)

Y

Attentional control Visuospatial attention Attention

Cognitive Flexibility Switching

The Cognitive flexibility task (subtest of KiTAP) The Verbal Fluency

Working Memory

The Counting Span Task

Y(♀)

Maayan et al. (2011)

Y

Stautz et al. (2016)

Y

The Corsi Block-Tapping Task

Verbeken et al. (2013)

Y

The Digit-span subtest (WISCIII) The Wide Range Assessment of Learning and Memory (WRAML) The McCarthy Scales of Children’s Abilities (MCSA)

Schwartz et al. (2013)

Y(♀)

Maayan et al. (2011)

Y

Guxens et al. (2009)

The Letter-number sequencing

Vardejo-Garcia et al. (2010)

Y (6-yearold children) N

Updating (working memory)

The Digit Span Backwards Test

Groppe et al. (2014)

Y

Verbal working memory

Working memory functional magnetic resonance imaging (fMRI) task Working memory functional magnetic resonance imaging (fMRI) task The symbol digit modalities test (SDMT)

Alarcón et al. (2015)

Y

Alarcón et al. (2015)

Y

Blanco-Gomez et al. (2015)

N

Jo

ur na

lP

Working memory

N

Schwartz et al. (2013)

re

The Trial Making Test part B (TMT-B)

-p

The Conners’ Continuous Performance Test – II (CPT – II)

ro of

Sustained attention

Spatial working memory Visuomotor ability

Higher-Level Executive Functions

Decision making

Problem solving

The Choice Delay Task

de Groot et al. (2017)

N

The Delay of Gratification Task (DOG) and gift delay task The Delay of Gratification Task (DOG) The Delay of Gratification Task (DOG) The Delay of Gratification Task (DOG) The Delay of Gratification Task (DOG)

Hughes et al. (2015)

N

Schlam et al. (2013)

Y

Pieper and Laugero (2013) Bruce et al. (2012)

N

Seeyave et al. (2009)

Y

The Hungry Donkey Task

Groppe et al. (2014)

N

Question Based Delay Discounting Test (DDQ)

Fields et al. (2013)

Y

The Children’s Gambling Task (CGT) The Iowa Gambling Task (IGT)

Pieper et al. (2013)

N

Vardejo-Garcia et al. (2010) Qavam et al. (2015)

Y

Guxens et al. (2009)

Qavam et al. (2015)

Y (6-yearold children) Y

Davis et al. (2011)

Y

The Tower of London Test

Andre Rey Test, The Tower of London Test The Cognitive Assessment System Zoo map

re

Planning/ planning and organizing

-p

The McCarthy Scales of Children’s Abilities (MCSA)

ur na

lP

Vardejo-Garcia et al. (2010) Reasoning Similarities Vardejo-Garcia et al. (2010) *division based on Diamond (2013); ** the exact EF name from the article; EF - executive function, Y - yes, N - no, KiTAP - the computer-based test battery of attention for children, TEA-Ch - the Test of Everyday Attention for Children, WISC-III - Wechsler Intelligence Scale for Children-III

Jo

Y

ro of

The ability to delay gratification

Y

N N