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Executive function in weight loss and weight loss maintenance: a conceptual review and novel neuropsychological model of weight control


Abstract and Figures

Weight loss maintenance is a complex, multifaceted process that presents a significant challenge for most individuals who lose weight. A growing body of literature indicates a strong relationship between cognitive dysfunction and excessive body weight, and suggests that a subset of high-order cognitive processes known as executive functions (EF) likely play an important role in weight management. Recent reviews cover neuropsychological correlates of weight status yet fail to address the role of executive function in the central dilemma of successful weight loss maintenance. In this paper, we provide an overview of the existing literature examining executive functions as they relate to weight status and initial weight loss. Further, we propose a novel conceptual model of the relationships between EF, initial weight loss, and weight loss maintenance, mapping specific executive functions onto strategies known to be associated with both phases of the weight control process. Implications for the development of more efficacious weight loss maintenance interventions are discussed.
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Executive function in weight loss and weight loss maintenance:
a conceptual review and novel neuropsychological model of weight
Katelyn M. Gettens
Amy A. Gorin
Received: August 10, 2016 / Accepted: January 18, 2017 / Published online: February 3, 2017
ÓSpringer Science+Business Media New York 2017
Abstract Weight loss maintenance is a complex, multi-
faceted process that presents a significant challenge for
most individuals who lose weight. A growing body of lit-
erature indicates a strong relationship between cognitive
dysfunction and excessive body weight, and suggests that a
subset of high-order cognitive processes known as execu-
tive functions (EF) likely play an important role in weight
management. Recent reviews cover neuropsychological
correlates of weight status yet fail to address the role of
executive function in the central dilemma of successful
weight loss maintenance. In this paper, we provide an
overview of the existing literature examining executive
functions as they relate to weight status and initial weight
loss. Further, we propose a novel conceptual model of the
relationships between EF, initial weight loss, and weight
loss maintenance, mapping specific executive functions
onto strategies known to be associated with both phases of
the weight control process. Implications for the develop-
ment of more efficacious weight loss maintenance inter-
ventions are discussed.
Keywords Obesity Review Weight loss maintenance
Executive function Behavioral intervention Conceptual
maintenance model
Obesity is one of the predominant healthcare concerns in
the United States (Finkelstein et al., 2010; Fryar et al.,
2015; Ogden et al., 2012) with recent reports suggesting
that 38% of adults and 17% of youth are living with obesity
(Ogden et al., 2014,2016; Flegal et al., 2016). Compared to
normal or healthy weight individuals, those with obesity
are at higher risk for many serious health conditions
including all causes of morbidity and mortality, heart dis-
ease, stroke, type 2 diabetes, certain types of cancer, and
dementia (Fryar et al., 2015). The economic, medical, and
social costs of excessive weight are well documented and
predicted to increase by $48–66 billion per year by 2030
(Finkelstein et al., 2012; Wang et al., 2011). Reflecting
these significant health and economic concerns, the United
States’ Surgeon General has identified the obesity crisis
among his top priorities.
Modest weight loss (5–10% of body weight) can be
reliably achieved through several evidence-based methods
and is associated with significant health benefits (MacLean
et al., 2015; Wing & Hill, 2001). Maintaining weight loss,
however, has proven to be a more elusive accomplishment;
most weight is regained within 3–5 years (MacLean et al.,
2015; Wadden & Stunkard, 1986; Wadden et al., 1988). As
noted by a recent workgroup of weight management
experts convened by the National Institutes of Health, the
challenge of weight loss maintenance (WLM) is one of the
field’s most significant dilemmas (MacLean et al., 2015).
Data from several sources suggests that the processes that
drive and support initial weight loss are theoretically and
empirically distinct from those associated with weight loss
maintenance (Williams et al. 1996; Rothman, 2000; Elfhag
¨ssner, 2005). In a large, cross-sectional survey of
1165 U.S. adults, only 8 of 36 weight-control strategies
(22%) were found to be associated with both weight loss
and WLM, while 4 were associated uniquely with main-
tenance. Notably, poor agreement (kappa =0.22) was
reported between practices uniquely associated with weight
&Katelyn M. Gettens
Amy A. Gorin
University of Connecticut, Storrs, CT, USA
J Behav Med (2017) 40:687–701
DOI 10.1007/s10865-017-9831-5
loss and WLM, indicating each process likely requires a
distinct set of skills and behaviors (Sciamanna et al., 2011).
Attempts to understand the process of successful
weight-related behavior change have traditionally focused
on behavioral or social-cognitive predictors of success
(McGuire et al., 1999; Wadden et al., 2009; Wing et al.,
1998; Wing et al., 2006). More recently, advances in
neuroscience and neuropsychology have fueled increased
interest in neurocognitive processes underlying obesity and
weight management. The field is still nascent – relatively
few studies have explored neurocognitive correlates of
weight loss, and even fewer have examined neurocognitive
correlates of long-term maintenance. This is an area ripe
for investigation as work in other health-related domains
(e.g., physical activity, smoking cessation, and stress reg-
ulation) suggest neuropsychological variables are intri-
cately involved in health-behavior change and health-
maintaining behavior (Hall et al., 2006,2008; Loprinzi
et al., 2015; Williams et al., 2009; Williams & Thayer,
2009). Given the complex and multifaceted nature of
weight loss and WLM, a specific subset of processes
known as executive functions, involved in high-order or
top-down functioning, are likely among the most highly
implicated cognitive systems in successful weight man-
agement. The pivotal role that executive function might
play in long-term weight loss success requires attention in
conceptual models of weight management that can guide
future research, and ultimately, integrate executive func-
tion training strategies into our existing framework of
behavioral weight loss intervention.
Executive function, obesity, and weight
Defining and measuring core constructs
Debate exists regarding which functions comprise the core
elements of executive function. However, several key
executive skills are consistently cited in research and
clinical domains of neuropsychology including inhibition,
working memory, planning, organization, and task-
switching (Alvarez & Emory, 2006; Miyake et al., 2000;
Suchy, 2009).
In an influential paper exploring the unity and diversity
of executive function, Miyake et al. (2000) examined the
extent to which functions attributed to executive ability
reflect a single underlying ‘‘executive system’’ or truly
distinct subcomponents. Three central components of
executive function emerged as central to the model: shift-
ing between tasks or mental sets (i.e. ‘‘shifting’’), updating
and monitoring of working memory (i.e. ‘‘updating’’), and
inhibition. Results indicate that these components of
executive function are clearly distinguishable, however
moderate correlations also exist between the three factors,
representing shared underlying cognitive mechanisms
(Miyake et al., 2000). Regardless of how executive func-
tions are defined, the distinction between general cognitive
function and executive function is important to note.
Executive functions are defined as a subset of general
cognitive function, involved specifically in high-order,
self-regulatory, and volitional processes (Baumeister &
Vohs, 2003). Additionally, executive functions are typi-
cally described in terms of ‘‘how’’ behavior is expressed,
while general cognitive function is discussed in terms of
‘what’’ behavior or ‘‘how much’’ a behavior is exhibited
(Lezak et al., 2012).
Weight-related health behavior change and WLM are
sufficiently complex processes to necessitate the recruit-
ment of executive skills. Understanding these complex
processes from an integrated perspective requires mapping
executive functions (rather than general cognitive functions
alone) onto known behavioral correlates of successful
weight management. While executive functions are com-
monly measured using computer and task-based assess-
ment measures (e.g., Stroop color-word task, Go-No-Go,
Trail-Making, Wisconsin Card Sort Task, Tower of Lon-
don, and Iowa Gambling Task) or administered concor-
dantly with scanning methods such as fMRI or EEG,
it is
often difficult to conceptualize how outcome variables
provided by standardized cognitive test batteries might
translate into behavioral outputs. Intervention design and
implementation focused on training and strengthening
executive performance depends, fundamentally, on a
clearer understanding of how task-based assessment mea-
sures of executive performance translate into real world
behaviors. To fully understand the complex relationship
between executive function and weight maintenance, and
how executive functions might contribute to improved
long-term health change, it is crucial to link high-order
cognitive performance to specific weight-related behav-
ioral constructs. Furthermore, elucidating cognitive mod-
erators of successful maintenance will allow clinicians and
researchers to determine who is at highest risk for regain
following initial weight loss, and to develop novel treat-
ment strategies to support these individuals in long-term
maintenance. In developing this model, we will review the
extant literature that has primarily focused on executive
The scope of this paper does not allow for an adequate review of
fMRI and EEG findings regarding executive function and weight loss
maintenance. It should be noted that executive and prefrontal func-
tions do not operate in isolation. Neuroimaging data serve to highlight
the vastly complex and integrated nature of correspondence between
PFC and many other neural networks implicated in eating behavior
and weight management broadly (Jansen et al., 2013, Murdaugh et al.,
2012; Szabo-Reed et al., 2015).
688 J Behav Med (2017) 40:687–701
function ability in adults with obesity, as well as the
potential bidirectional association between weight loss and
executive function. Far fewer studies have explored
potential implications of executive function beyond the
initial weight loss phase.
Executive functioning in overweight and obesity
Evidence suggests that obesity is a risk factor for the
development of neurocognitive deficits, including poor
performance on tests of general cognitive functioning and
executive functioning (Cserjesi et al., 2009; Fitzpatrick
et al., 2013; Gunstad et al., 2007; Prickett et al., 2015).
Cross-sectional designs indicate that executive impair-
ments most consistently found in adults with obesity,
compared to normal weight controls, include inhibition,
decision-making, concept formation, and set shifting.
These deficits are observed independent of age, general
cognitive ability, education, and health factors including
diabetes and hypertension (Boeka & Lokken, 2008; Brogan
et al., 2011; Cserjesi et al., 2009; Davis et al., 2004;
Fagundo et al., 2012; Fergenbaum et al., 2009; Gunstad
et al., 2007; Smith et al., 2011; Roberts et al., 2007),
although there is some evidence to suggest that the obesity-
executive function link may be more pronounced in adults
with more complicated obesity profiles (e.g., metabolic
syndrome, experiences of loss of control eating) (Fergen-
baum et al., 2009). For example, in those who experience
loss of control (LOC) eating, it is hypothesized that deficits
in executive function (including cognitive inflexibility,
poor self-regulation, planning deficits, and difficulty with
inhibition and delayed reward) likely lead to loss of control
or binge eating episodes; significant risk factors for the
development of obesity (Manasse et al., 2014; Manasse
et al., 2015a,b). Cross-sectional analyses indicate adults
with obesity meeting criteria for LOC eating, regardless of
frequency or size of episode, show significantly greater
executive deficits, specifically in self-regulatory control
and planning, than non-LOC participants with obesity
(Manasse et al., 2014). More recently, the same group
reported select deficits in executive function among over-
weight women diagnosed with binge eating disorder
(BED), compared to overweight women without BED.
Differences emerged in the areas of problem solving,
inhibition, and delayed gratification, but not in set shifting,
working memory, or risk taking (Manasse et al., 2015a).
While most studies in this area are cross-sectional in
nature, longitudinal associations (follow-up ranging from 5
to 27 years) between midlife obesity and risk for poor
neurocognitive and executive outcomes have been reported
(Cournot et al., 2006; Fitzpatrick et al., 2009; Gunstad
et al., 2010; Gustafson, 2008; Kivipelto et al., 2005;
Whitmer et al., 2005,2008). Specifically, Cournot et al.
(2006) report higher baseline BMI is associated with cog-
nitive decline over 5 years. Additionally, findings from
Gunstad et al. (2010) suggest that higher body composition
at baseline is associated with more rapid decline in general
cognitive and executive function. Notably, longitudinal
outcomes also indicate that midlife obesity may be a risk
factor for the development of dementia and Alzheimer’s
disease, adjusting for demographics and cardiovascular risk
factors (Gustafson, 2008; Fitzpatrick et al., 2009; Kivipelto
et al., 2005; Whitmer et al., 2005,2008). Together these
results suggest that adults with obesity may not only be
prone to experience a range of executive function impair-
ments, but may also be at increased risk for neurocognitive
deficits later in life. The temporal direction of these rela-
tionships remains controversial however, executive func-
tion deficits appear to map onto several potential
behavioral risk factors for the development of excessive
weight, including difficulty planning regular eating pat-
terns, inability to delay gratification or inhibit prepotent
responses to highly palatable foods, and difficulty updating
goal-relevant information related to weight loss. Additional
research is needed to fully elucidate underlying neuro-
physiological and neurocognitive mechanisms leading to
increased risk for obeseogenic behavior and long-term
neurocognitive consequences. An important next step is to
examine the impact that executive function in adulthood
may have on weight loss outcomes.
Impact of executive functioning on weight loss
Self-regulation, comprised of planning ability, inhibitory
control, initiation, and updating goal-directed behavior, is a
significant predictor of successful health behavior change.
Given the obvious overlap between behaviors defined as
‘self-regulatory’ and those defined as executive functions,
it is reasonable to hypothesize that individual differences in
executive function might also predict individual differ-
ences in health-behavior outcomes, including weight
maintenance success. In fact, compelling evidence from
childhood and adolescent health research suggests that
executive function, measured in early childhood, is corre-
lated with eating behavior in cross-sectional analyses
(Pieper & Laugero, 2013), and predictive of a range of
health outcomes later in life, including body mass index
(BMI) and physical activity (Guxens et al., 2009; Marteau
& Hall, 2013; Moffitt et al., 2011). Preschool children with
higher cognitive function scores had a lower likelihood of
being overweight at 2-year follow-up (Guxens et al., 2009).
Poor cognitive control, measured in children age 3 to 11,
was associated with greater health concerns (including
metabolic and weight-related problems) at 32-year follow-
up (Moffitt et al., 2011). Adjusting for demographics, IQ,
and education level, executive functions have also been
J Behav Med (2017) 40:687–701 689
shown to be associated with non-weight specific health
behaviors including smoking, alcohol use, and sleep
hygiene in adults using cross-sectional (Hall et al., 2006),
and prospective designs (Booker & Mullan, 2013; Moffitt
et al., 2011). Although these studies did not examine the
impact of executive function performance on weight loss or
WLM specifically, the findings are noteworthy as they
suggest a unique contribution of executive function on
general health behavior beyond that of IQ, socioeconomic
status, or educational attainment.
Converging findings suggest that various executive
functions may act as moderators in the relationship
between eating intention and eating behavior (Hall et al.,
2008; Kuijer et al., 2008; Nederkoorn et al., 2010). Hall
et al. (2008) report that executive control moderates the
effect of intention to make healthy dietary choices and
actual eating behavior at 1-week follow-up, such that
individuals with strong intention made significantly fewer
healthy food choices if they had poor executive function,
compared to participants with weak intention and strong
executive skills. Individuals with implicit biases for snack
foods and poor eating restraint were also more likely to
exhibit poor decision-making and weight gain at 1-year
follow-up if they had low executive control (Nederkoorn
et al., 2010). It is also reported that inhibition is a stronger
predictor of healthy dietary choice for those exhibiting
better executive function skills (Hall et al., 2008), sug-
gesting that the intention-behavior relationship is not uni-
form, but likely moderated by specific executive functions
and individual executive ability. Recently, the same group
reported that, in follow-up analyses, executive function
was the only significant predictor of high fat intake, as well
as fruit and vegetable consumption at 1 year, when inclu-
ded in a model with conscientiousness and many other
personality characteristics (Hall & Fong, 2013). These
results demonstrate that executive function may be a more
powerful explanatory variable for weight-related health
behaviors than other characteristics typically studied.
Distinct components of executive function also appear
to be predictive of distinct weight-related behaviors. Lon-
gitudinal designs have demonstrated that engagement in
healthy choices, such as increased physical activity and
consumption of fruits and vegetables, utilizes a unique set
of executive functions, including executive control,
updating, and initiating, while avoidance of health-risk
behaviors (e.g. consumption of high fat foods, snacking,
and disinhibited eating), utilizes a separate set of executive
functions, including task-switching, inhibitory control, and
flexibility (Allan et al., 2011; Allom & Mullan, 2014; Hall
et al., 2006). Similar associations were reported among
young adults in a cross-sectional analysis using self-report
measures of executive function (Limbers & Young, 2015).
Each of these behaviors are crucial to the initial weight loss
phase (Rothman, 2000; Wing & Hill, 2001), however,
successful weight loss maintenance introduces significant
challenges unique from initial weight loss.
These results highlight several important points. First,
specific executive functions may be associated with the ini-
tiation and inhibition of health behaviors known to directly
impact weight outcomes. Second, executive functions that
predict healthy eating patterns appear to be distinct from
those that predict unhealthy eating. Findings suggest that
initiation of healthy behaviors has separate executive func-
tion determinants from unhealthy behaviors that must be
avoided or inhibited to lose or maintain weight loss. These
distinctions will allow researchers to map executive func-
tions onto specific weight-related outcomes, and to generate
more informed hypotheses regarding executive function-
WLM relationships. From a clinical perspective, longitudi-
nal studies implementing standardized executive function
batteries are necessary to more thoroughly examine the
impact of executive function on long-term maintenance
success. Results of such studies will serve to inform the
design and implementation of executive-focused modules
into existing behavioral weight loss programs, with the goal
of targeting maintenance-related health behaviors that
require the greatest executive resources.
Finally, literature indicates that change in executive
function may be an important, and more consistent, pre-
dictor of weight-related behavior and weight change than
executive function measured at a single time point (Best
et al., 2014; Bryant et al., 2012; Dalle Grave et al., 2014;
Murawski et al., 2009). For example, Best et al. (2014)
report that although baseline executive function predicted
physical activity at program completion, improvements in
executive function predicted sustained behavior change,
specifically better adherence to physical activity over the
following year. In several other interventions, increased
restraint and decreased disinhibition were the only vari-
ables associated with weight loss at 12 weeks (Bryant
et al., 2012; Butryn et al., 2009), and change in inhibition is
reported as the strongest predictor of weight loss from 4 to
12 months (Butryn et al., 2009). These results hold
important clinical implications, demonstrating the potential
utility of executive function training in the context of
health-behavior interventions.
While the evidence base is still small, a complex bidi-
rectional relationship between executive function and
weight-related health behaviors appears likely (Allan et al.,
2011; Hall & Fong, 2013). Surprisingly few studies have
implemented prospective designs to draw clear causal
conclusions, therefore the mechanisms and directionality
underlying this relationship remain somewhat unclear.
Certain executive functions predict initiation of healthy
behaviors, other executive functions moderate the rela-
tionship between intention and health behavior, and chan-
690 J Behav Med (2017) 40:687–701
ges or improvements in executive performance, that may
subsequently predict weight loss outcomes, are reported.
Unfortunately, many of these studies were not conducted in
the context of a weight loss intervention, therefore changes
in weight or BMI were not measured as outcome variables.
Given, however, that many of the eating patterns discussed
above are associated with weight change, it is reasonable to
posit that maintaining a healthy weight requires inhibition
of desires to consume high-fat foods, and a consistent
assessment of information relevant to the weight-loss goal
at hand. To further explore the complexities of this rela-
tionship, we turn to an overview of the literature examining
the impact of weight loss on executive function.
Impact of weight loss on executive functioning
Several studies have investigated whether interventions
targeting caloric intake and weight loss might reduce the
risk of cognitive decline typically observed in mid to late
life, and lead to improvements in executive function as a
result of decreased BMI. This line of research also raises
interesting and important questions regarding the extent to
which executive function is a viable target for intervention
and whether brain structure or function might change as
executive function skills are strengthened (Alvarez &
Emory, 2006; Suchy, 2009).
Findings regarding the impact of weight loss on exec-
utive function are mixed. Few studies have implemented
prospective designs to examine the impact of decreased
calorie intake or weight loss on cognitive function,
specifically executive performance, in obese samples.
Several studies report significant negative associations
between baseline BMI and cognitive function at follow-up
(Cournot et al., 2006; Gunstad et al., 2010; Sabia et al.,
2009; Wolf et al., 2007). In an observational prospective
cohort study, Cournot et al. (2006) report that higher
baseline BMI is associated with cognitive decline at 5-year
follow-up, however no significant relationship is reported
between change in BMI and change in cognitive ability,
including measures of executive function.
Significant positive associations between weight loss
and executive function have also been reported (Bryan &
Tiggemann, 2001; Butryn et al., 2009; Green et al., 2005;
Gunstad et al., 2010; Halyburton et al., 2007; Siervo et al.,
2012; Veronese et al., 2017; Wing et al., 1995). Findings
from longitudinal behavioral weight loss interventions
generally suggest significant improvements to overall
executive function as a result of weight loss (ranging from
28-days to 12-week follow-up), however due to the range
of functions measured (e.g., inhibition, set shifting ability),
executive function variables impacted by successful weight
loss are not uniform across studies (Bryan & Tiggemann,
2001; Siervo et al., 2012; Wing et al., 1995).
Finally, evidence of null or negative effects of weight
loss on executive function, in longitudinal behavioral
weight loss and dietary interventions, is reported through-
out the literature (Bryan & Tiggemann, 2001; Cheatham
et al., 2009; Espeland et al., 2014; Green et al., 2005;
Halyburton et al., 2007; Martin et al., 2007). Negative
impacts of weight loss on executive function are often
attributed to the finite availability of cognitive resources,
and the significant amount of cognitive control utilized
during caloric restraint and preoccupation with weight loss
and/or body image (Siervo et al., 2011). For example, as
participants allocate cognitive resources to initiating heal-
thy behaviors like physical activity, and daily self-moni-
toring of food intake, they may have fewer cognitive
resources to allocate towards restraint or avoidance when
presented highly palatable snack options. Some studies
report that working memory and planning ability are neg-
atively impacted by weight loss (Cheatham et al., 2009;
Green et al., 2005), while others report no significant
impact of weight loss on executive function ability
(Espeland et al., 2014; Halyburton et al., 2007; Siervo
et al., 2012).
While the scope of this review does not allow for a
comprehensive summary of findings from the extant bar-
iatric literature, the magnitude and rate of weight loss
outcomes observed post-operatively may serve to eluci-
date, and perhaps augment, potential remediating effects of
weight loss on executive dysfunction that non-surgical
interventions have yet to demonstrate (Handley et al.,
2016; Spitznagel et al., 2015). Findings indicate that bar-
iatric surgery is associated with improved neurocognitive
outcomes, including executive function, at short-term
(12 weeks) and long-term (3 years) follow-up (Alosco
et al., 2014; Handley et al., 2016). Furthermore, executive
function performance has been shown to predict BMI
12 months post-surgery (Spitznagel et al., 2013b) and,
adjusting for baseline cognitive function scores, poorer
cognitive performance at 12 weeks post-surgery predicted
reduced weight loss at 36-month follow-up (Spitznagel
et al., 2014,2013a,2013b). Finally, a recent review of 18
bariatric studies reported change in brain activation fol-
lowing surgical weight loss, specifically associated with
improved cognitive control (Handley et al., 2016).
This body of literature also addresses potential physio-
logical mechanisms underlying the relationship between
weight loss success and executive function. Specifically,
the resolution of comorbidities associated with executive
dysfunction (e.g., sleep apnea, type 2 diabetes, and
hypertension), metabolic regulation (e.g., reduction in
insulin resistance), and changes in neurohormone levels
(e.g., leptin and ghrelin) significantly predict improved
executive function performance 1 year post-surgery
(Spitznagel et al., 2015). Additional research is needed to
J Behav Med (2017) 40:687–701 691
examine whether the executive function benefits exhibited
following initial weight loss, whether surgically- or
behaviorally-induced, are better sustained when weight
regain is avoided.
Overall, findings on the impact of dietary content,
weight loss, and decreased BMI on executive function
among individuals living with overweight or obesity are
somewhat equivocal. Several important limitations to the
aforementioned findings should be noted. First, the length
of interventions varied significantly from approximately
8 weeks to 8 years (Espeland et al., 2014; Halyburton
et al., 2007). A variety of diets are also prescribed for
weight loss purposes including low fat/low calorie diets
(Butryn et al., 2009; Espeland et al., 2014; Siervo et al.,
2011; Siervo et al., 2012; Wing et al., 1995), low carbo-
hydrate diets (Halyburton et al., 2007), and low glycemic
diets (Cheatham et al., 2009) that may differ in their cog-
nitive complexity. It is unclear if and how different types of
dietary restriction may impact executive function. Addi-
tionally, the stability of observed changes in executive
function due to weight loss is unknown and has not been
studied longitudinally. Whether these changes are perma-
nent or transient will be an important point of future
research and particularly crucial to intervention develop-
No studies to date have used prospective or longitudinal
designs to adequately examine executive function as a
predictor of successful long-term weight loss maintenance
in adults. Additionally, few studies have included a full,
comprehensive executive function battery, but instead have
focused on selective executive functions as they relate to
weight-specific behavior. Given the literature reviewed
thus far, and what is known regarding behavioral and
lifestyle characteristics of successful ‘‘maintainers’’ (Peir-
son et al., 2015; Phelan et al., 2009; Teixeira et al., 2010,
2015; Thomas et al., 2014; Wing & Phelan, 2005)itisnot
only reasonable, but necessary, to construct a conceptual
model of the impact executive function might have on
successful weight maintenance.
A new conceptual framework for an executive
function-weight loss maintenance model
Several models hypothesizing the role of executive func-
tioning in obesity or initial weight loss have been published
(Jauch-Chara & Oltmanns, 2014; Raman et al., 2013;
Sellbom & Gunstad, 2012) however, these models do not
map executive functions onto the specific behaviors asso-
ciated with WLM success and/or the known barriers to
WLM. Developing such a model is imperative in guiding
future research, particularly longitudinal designs, that
addresses the nature and directionality of the executive
function-WLM relationship using well-informed hypothe-
ses. Additionally, such a model provides a framework from
which researchers and clinicians might begin to consider
the impact of executive ability beyond neuropsychological
assessment, as it applies to the treatment and challenges of
successful and sustained health behavior change.
The aforementioned findings by Miyake et al. (2000)
outlining distinct core executive functions are crucial in
developing and conceptualizing a novel executive func-
tion-WLM model, as they not only demonstrate that
executive function has the potential to impact WLM in at
least three distinct ways, but that cognitive processes
underlying these relationships are likely interrelated and
may uniquely impact one another. It is clear that behavioral
and psychosocial variables associated with initial weight
loss are distinct from those associated with WLM, and that
the influence of executive function on weight loss differs
based on the specific weight-related behavior in question
(Allan et al., 2011; Allom & Mullan, 2014). It is therefore
conceivable that, in a similar fashion, executive functions
might differentially impact one’s ability to engage in and
sustain behaviors associated with successful weight loss
maintenance versus those associated with initial weight
loss. Furthermore, the impact of specific executive func-
tions may differ between different weight maintenance
Fundamentally, a conceptual executive function-WLM
model might propose that executive function, as a resource
that facilitates self-regulatory processes (Hofmann et al.,
2012), impacts or predicts health outcomes via distinct
health-related behaviors (see Fig. 1). Specific behaviors
associated with successful weight loss or WLM may act as
mediators through which executive function impacts indi-
vidual differences in the ability to maintain weight loss
over time. In order to outline such a model, it is important
to first consider the three core components of executive
function previously mentioned: shifting, updating, and
inhibition (Miyake et al., 2000), and subsequently consider
the specific health behaviors, or mediators, uniquely asso-
ciated with WLM (Byrne, 2002; Elfhag & Ro
¨ssner, 2005;
Svetkey et al., 2008; Teixeira et al., 2010,2015; Thomas
et al., 2014; Williams et al., 1996; Wing & Phelan, 2005).
Updating is defined as the ability to code and monitor
new information as it becomes relevant to the goal at hand.
Updating allows for active manipulation of relevant
information in working memory (Miyake et al., 2000).
Planning is a behavior associated with successful WLM
and likely to be impacted by updating ability. Planning
ability ensures dietary, exercise, and other weight man-
agement goals are more likely to be met in novel situations
when advanced preparation of healthy meals is not feasible
(e.g. restaurant eating or attending social events with novel
food choices). Individuals who set goals in advance, or
692 J Behav Med (2017) 40:687–701
have practice in spontaneous action planning, are likely
better suited to make dietary choices that are concordant
with WLM goals. Meals must also be planned to meet
specific nutritional needs while fitting specific dietary
restraints. Additionally, successful maintenance requires
significant and consistent monitoring of potential dietary
(Miyake et al., 2000) (Mediators)
Initial Weight Loss
Long-Term Weight
Loss Maintenance
Incorporate variety in exercise
Shift to smaller portions
Increased decisional balance
Thinking about progress
Planning meals in
advance/avoid skipping meals
Decreased disinhibited eating
Initiate research on weight loss,
nutrition & exercise
Initiate participation in a weight
loss program
Override impulse for unhealthy
Flexible dietary restraint
Intention-behavior gap for
Hunger vs. Satiety
Setting realistic goals
Delay of gratification
Reminding yourself of weight
Adaptive and Spontaneous
action planning (Restaurant &
Social Eating)
Habituation decreased
effortful inhibition
Physical activity routine
Initial weight loss success
Inhibition of unhealthy behavior
(e.g., TV watching)
Initiation of healthy behaviors
(e.g., exercise)
Fig. 1 A preliminary conceptual model of the impact of executive functions on successful weight control. The model outlines the potential role
of executive functions as moderators of specific behaviors implicated in two distinct phases of the weight management process: (1) initial weight
loss and (2) long-term weight loss maintenance. *Behaviors implicated in both initial weight loss and weight loss maintenance
J Behav Med (2017) 40:687–701 693
slips to detect and compensate for small weight fluctuations
before they become significant regains. Consistent self-
monitoring practices have been documented as one of the
strongest predictors of WLM, including daily self-weigh-
ing, calorie tracking, and physical activity (Anderson et al.,
2001; Barte et al., 2010; Bond et al., 2009; Butryn et al.,
2007; Dombrowski et al., 2014; Peirson et al., 2015; Phelan
et al., 2009; Teixeira et al., 2010). Self-monitoring can
reasonably be considered a process closely related to
updating ability. Goal-relevant information obtained
through the monitoring process is precisely the information
that must be actively manipulated to help individuals assess
which health behaviors promote weight maintenance, and
which behaviors lead to weight fluctuations or gains.
Shifting, also referred to as ‘‘task shifting’’ or attention
shifting, is defined as the ability to disengage from goal-
irrelevant tasks or activities and subsequently engage in a
new, relevant task set. Shifting from one task to the next
also requires overcoming interference from the previous
task, and avoiding perseverations or repeating behaviors
that no longer fit the new goal (Miyake et al., 2000). As it
relates to WLM, task shifting allows individuals to tem-
porarily disengage from self-regulatory behaviors that are
consistently enacted to flexibly accommodate changing
environmental or social influences. In other words, shifting
may allow those attempting maintenance to manage short-
term and long-term weight-related goals by making adap-
tive decisions as their environment and goals fluctuate over
time. Research indicates that individuals engaging in
weight loss or weight loss maintenance, who allow them-
selves to temporarily disengage from strict dietary restraint
without feeling remorse, thereby approaching the WLM
process with ‘‘flexible dietary restraint’’, are more suc-
cessful maintainers than those with ‘‘rigid restraint’’ pat-
terns (Hofmann et al., 2012; Kiernan et al., 2013; Teixeira
et al., 2010). As noted previously, research also suggests
that task switching and flexibility predict intention-behav-
ior gaps in snacking behavior (Allan et al., 2011). It should
be noted that there is a fine line between adaptive methods
of shifting and complete disengagement from the goal at
hand (i.e. regain). Therefore, employing balanced flexibil-
ity likely recruits a host of cognitive resources that
undoubtedly overlap with other executive functions such as
inhibition, control, and planning.
Finally, inhibition, formally defined as the ability to
override a dominant, automatic, or prepotent response, is
highly implicated in initial weight loss, and certainly
contributes significantly to sustained WLM. Despite an
abundance of evidence that inhibition and initiation predict
distinct dietary behaviors, it is crucial to consider how
inhibition and initiation might predict WLM. Inhibition
plays an important role in overriding habits and impulses to
consume high-fat palatable foods (Hofmann et al., 2012).
Elfhag and Ro
¨ssner (2005) report that compared to indi-
viduals who regain, successful maintainers demonstrate
less dietary fat intake, reduced frequency of snacking, and
adaptive management of cravings. Successful maintainers
initiate more health behaviors, including consistent physi-
cal activity, and consumption of fruits and vegetables.
Notably, initiation appears to be one of the most frequently
studied executive functions in the obesity literature, yet
many studies have measured dietary restraint and disinhi-
bition using the self-report Three Factor Eating Question-
naire. When studies have measured executive function with
neuropsychological tests the Stroop or Go-No-Go tasks are
cited most frequently. Several studies report that successful
weight loss maintainers exhibit slowed reaction time and
greater interference on Stroop paradigms using high-fat
food cues compared to participants with obesity and nor-
mal weight controls (Allan et al., 2011; Phelan et al.,
2011). These findings suggest that maintainers may be
employing greater executive resources to resist high fat
foods, leading to increased salience of palatable food cues,
however the directionality and predictive nature of inhi-
bition on maintenance cannot be established from cross-
sectional designs. The interaction between implicit pref-
erence for snack foods and baseline response inhibition
also predicts weight regain over 1 year, such that partici-
pants with lower response inhibition gain more weight
(Daly et al., 2015; Nederkoorn et al., 2010). The impact of
inhibition on successful maintenance over time remains to
be studied.
Mapping core executive functions onto behaviors
known to be associated with, and predictive of WLM, is a
necessary step in further understanding the cognitive
underpinnings of long term weight loss maintenance from a
neuropsychological perspective. Research by Wing and
Phelan (2005) suggests that successful maintainers engage
in the aforementioned behaviors (or mediators) to a greater
extreme than their always normal-weight counterparts,
indicating that these behaviors are a crucial focus for future
executive function research. Evidence of shared variance
between the components of executive function indicates
that future research in this area must also consider the
extent to which executive functions might interact or
impact one another, and the influence such interactions
might have on WLM outcomes.
Treatment implications and future directions
Integration of health and neuropsychological approaches to
weight control holds undeniable implications for clinical
practice. The challenge of understanding successful weight
loss maintenance requires a closer look at the cognitive
underpinnings associated with the weight management
694 J Behav Med (2017) 40:687–701
process. The literature outlined thus far provides sufficient
evidence to suggest that adults with obesity exhibit deficits
in executive function, and that executive performance has
clear connections to skills that are necessary to succeed in
weight management and long-term maintenance.
Weight loss maintenance has become an important focus
for intervention design and implementation. Behavioral
weight loss programs focusing on both diet and physical
activity resulted in a -1.56 kg difference at 12-month
follow-up compared to controls (Dombrowski et al., 2014),
however these interventions clearly lack elements of cog-
nitive or executive function training. In part, this may be
due to difficulty appropriately incorporating individual-
level, biological, or neurocognitive correlates of health
behavior (e.g., executive function), into large-scale treat-
ment studies. If executive function can be trained in adults
with obesity, and training in one realm of executive func-
tion may generalize to other executive functions, there
exists immense clinical potential that will directly impact
the development and design of WLM interventions. In fact,
preliminary evidence suggests that cognitive training, and
some executive function-specific interventions, have suc-
cessfully promoted health behavior change in other clinical
populations, including binge eating disorder (BED), breast
cancer patients, pediatric overweight and obesity, and
ADHD patients (Grilo & Masheb, 2005; Halperin et al.,
2013; Hannesdottir et al., 2014; Juarascio, et al., 2015;
Kesler et al., 2013; Tamm et al., 2014; Verbeken et al.,
Aforementioned findings from the bariatric literature,
and low rates of successful weight loss maintenance
demonstrated in standard behavioral interventions, speak to
the importance of incorporating sensitive standardized
measures of executive function to capture changes in
executive function over time. Neuropsychological batteries
that tap multiple executive functions and allow for both
fixed and flexible testing approaches, include the Neu-
ropsychological Assessment Battery (NAB) (White &
Stern, 2003), the Delis-Kaplan Executive Function System
(DKEFS) (Delis et al., 2004), and the NIH Toolbox Cog-
nition Battery (Weintraub et al., 2013). Careful consider-
ation should also be given to the idea that engagement of
executive function may be context specific, such that high
executive function scores on standardized neuropsycho-
logical measures may not translate directly to successful
implementation of weight management behaviors. A true
understanding of the impact of executive function on suc-
cessful weight loss maintenance should include measures
of executive skills as they apply specifically to the behavior
of interest, and may require the development of novel
measures tapping specific weight loss maintenance skills
(e.g., eating-specific impulsivity) (Liang et al., 2014). Our
model may provide a preliminary foundation on which to
conceptualize and further develop weight management-
specific measures of executive function.
Several studies suggest training cognitive behavioral
(CBT) and cognitive remediation (CRT) strategies assist
in weight management and improve symptoms of BED
(Cooper et al., 2010; Grilo & Masheb, 2005; Raman
et al., 2014). Family members of participants enrolled in a
CBT-based weight loss program have also exhibited
improved food choices and increased motivation for
physical activity (Grilo & Masheb, 2005; Rossini et al.,
2011). Such findings indicate that targeting cognitive
processes more generally, such as cognitive restructuring,
as they relate specifically to weight-control behaviors,
may be an important and viable treatment strategy to
fortify behaviors implicated in successful maintenance
(e.g., increased physical activity). These findings also
indicate that targeting behaviors that engage executive
functions specifically, within the context of a traditional
weight loss program, may be equally promising. In fact,
there is interesting, though preliminary, evidence to sug-
gest that executive functions can be improved if trained
early in children. Particularly among children exhibiting
the greatest difficulties in executive skills, early training
holds the potential to significantly impact a child’s aca-
demic success, mental health, and physical health trajec-
tories later in life (Diamond & Lee, 2011; Diamond et al.,
2016). Perhaps most encouraging are findings from a
recent study conducted with adolescents receiving inpa-
tient treatment for morbid obesity. Results demonstrate
that children with obesity who participate in a computer-
based executive function training game show significantly
greater improvements in WLM and executive function
skills up to 8-weeks post-inpatient treatment compared to
children with obesity in the non-executive function
training group. Notably, WLM benefits were no longer
observed at 12-week follow-up (Verbeken et al., 2013).
Few studies to date have examined the impact of execu-
tive function training over time in a population with
overweight or obesity, however recent longitudinal inter-
ventions and ongoing trials have begun to focus on
training self-regulatory skills specific to the weight loss
process (Forman et al., 2016; Miller et al., 2012;
Warschburger, 2015; Wing et al., 2016).
Paucity of executive function-training interventions for
adults, particularly in the context of weight control inter-
ventions, leaves many questions for future research
regarding the efficacy of such training in the context of
standard behavioral weight loss programs. One crucial
question for future intervention design is whether executive
functions are malleable among adults, and if so, whether
there are critical windows for intervention across the
lifespan. It may also be important to consider whether
variability in mid-life executive performance impacts
J Behav Med (2017) 40:687–701 695
individual efforts towards successful weight loss mainte-
As executive function-training interventions are
designed with the goal of improving weight loss mainte-
nance outcomes, participants might also be encouraged to
practice specific cognitive skills that strengthen aspects of
executive function closely tied to the WLM process. Par-
ticipants should be aware that situations in which executive
resources are in high demand or become depleted might
lead to plateaus or changes in weight loss or WLM pro-
gress. Appelhans et al. (2016) recently proposed a neu-
robehavioral intervention model for targeting and curbing
temptation in the context of weight control programs.
Importantly, the neurobehavioral model outlined by
Appelhans et al. (2016), serves to highlight the crucial role
that executive functions play in temptation prevention and
temptation resistance by organizing intervention strategies
by how taxing or demanding each strategy is on executive
capacity. Such a model is complementary to our own
executive function-WLM model, as it lends strong evi-
dence for the need to map specific WLM behavioral
strategies onto specific executive skills, in order to design
and implement similar interventions, not only for tempta-
tion avoidance, but specifically tailored towards improved
long-term weight loss. As research in the field progresses,
and novel intervention approaches consider incorporating
executive function training, understanding and distin-
guishing executive functions that are most responsive to
training and those executive functions most essential for
successful WLM will be crucial. As noted by Allom and
Mullan (2014), superior executive function does not nec-
essarily lead to expertise and ease across all health-related
behavior change.
Our model attempts to bridge important gaps between
neuropsychological and behavioral approaches to the
weight loss maintenance dilemma, in the hopes of pro-
viding novel perspectives and provide a framework for the
development and implementation of novel treatment
approaches. Given the purpose and extent of this model,
there are several important areas of successful weight
maintenance that fall beyond the scope of this framework.
We acknowledge that there are strategies proven to predict
and assist in successful WLM, including strong social
support networks, psychosocial stressors, and individual
coping strategies that are not addressed or accounted for in
our model. For example, research suggests that adults liv-
ing with obesity are more likely to be depressed than non-
obese adults, 43% of U.S adults with depression are living
with obesity, and in every age group, women with
depression are more likely to have obesity than women
without depression (Pratt & Brody, 2014). This is prob-
lematic given that the majority of weight-related inter-
ventions implement strict exclusion criteria including
history of psychiatric comorbidity, and therefore results
may not generalize to community samples. From a cogni-
tive perspective, assessing depression history in patients
entering a WLM intervention is essential given the well-
documented impact of major depressive disorder (MDD)
on cognitive and executive function (Lam et al., 2014;
Snyder, 2013). Psychiatric comorbidities will likely influ-
ence individuals’ executive function performance, but the
exact nature of such influences, combined with initial
weight loss, on maintenance success, is unclear.
Additionally, the interaction and relationship between
other health behavior changes, like physical activity, that
are known to impact both cognitive function and contribute
to successful long term maintenance should be carefully
considered. In adults, the positive impact of physical
activity on executive function and general cognitive func-
tion is well documented (Chan et al., 2013; Daly et al.,
2015; Hayes, et al., 2014; McAuley et al., 2013). The vast
majority of weight loss and WLM programs implement
physical activity regimens, therefore the influence of
exercise on executive function and WLM should be clearly
distinguished and separately examined from influences of
physical activity and executive function on WLM concor-
True integration of behavioral and neuropsychological
approaches to weight management will first require the
establishment of field-unifying theories in guiding future
research on executive function and WLM. Despite evi-
dence linking executive function to general health out-
comes, cognitive models of health behavior change are
largely dominated by social-cognitive approaches, and few
neuropsychological theories have guided weight manage-
ment research. Weight-related health behavior change,
particularly WLM, is inarguably a complicated process
with many biopsychosocial contributors. As evidenced by
this review, WLM may be uniquely challenging due to the
significant amount of high-order neurocognitive resources
recruited over extended periods of time. Despite increased
awareness of the difficulties associated with WLM, a true
understanding of successful, long-term change continues to
elude the obesity field. The challenge of improving main-
tenance outcomes calls for novel research and clinical
approaches. Acknowledging neuropsychological mediators
and moderators of WLM is crucial in moving the obesity
field toward increased integration and impactful treatment
designs. Cognitive processes defined as executive function
appear to be particularly integral to the weight control
process, and are therefore an excellent target for future
WLM research.
696 J Behav Med (2017) 40:687–701
A focus on neuropsychological factors in weight control
and WLM, using a compilation of self-report, task-based,
and neuroimaging measures will allow for neuropsycho-
logical approaches to be incorporated into traditional gold-
standard behavioral treatment. Increased collaboration will
also allow health psychologist and neuropsychologists to
answer many of the remaining questions regarding the
immense potential of executive function-based training on
sustained health-behavior change.
Currently, research on the executive function-WLM
relationship is sparse. Few attempts have been made to
implement task-based measures of executive function in
prospective, longitudinal obesity studies, and discussion of
executive function-based training in the context of weight
loss and WLM intervention is newly emerging. Current
cross-sectional designs allow for conclusions that are, at
best, suggestive of causal executive function-WLM rela-
tionships. Innovative approaches are necessary to progress
our knowledge of successful weight loss maintenance in
the obesity field, but will require a willingness to integrate
diverse and novel perspectives into current weight control
treatment and research.
Acknowledgements This work was supported by the Grant
NCT02570009 from National Heart, Lung, and Blood Institute. The
authors also thank Deborah Fein, Ph.D., Dean Cruess, Ph.D., Kate
Boudreau, and Arielle Sherman-Golembeski.
Compliance with ethical standards
Conflict of interest Katelyn M. Gettens, and Amy A. Gorin declares
that they have no conflict of interest.
Human and animal rights and Informed consent All procedures
followed were in accordance with ethical standards of the responsible
committee on human experimentation (institutional and national) and
with the Helsinki Declaration of 1975, as revised in 2000. Informed
consent was obtained from all patients for being included in the study.
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... For example, executive function is a term that describes the cognitive processing and coordination involved in behavioral change, such as planning or inhibition of complex behaviors and performance monitoring [4]. Executive functions are intimately involved in goal-setting processes, such as focusing effort towards important weight or eating goals, and inhibiting irrelevant behavior or response to stimuli [5,6]. They are also involved in the coordination and monitoring of weight-related behaviors such as eating behaviors or physical activity [6]. ...
... Executive functions are intimately involved in goal-setting processes, such as focusing effort towards important weight or eating goals, and inhibiting irrelevant behavior or response to stimuli [5,6]. They are also involved in the coordination and monitoring of weight-related behaviors such as eating behaviors or physical activity [6]. Overall, this body of work suggests that executive functioning is relevant to effective weight management. ...
... While standard interventions tend to focus on weight-related behaviors and goals, recent research suggests that improving executive functioning could be beneficial for individuals with obesity. Studies and reviews suggest that impaired executive functioning is associated with difficulties losing or maintaining weight [3,[6][7][8]. Further, studies have shown that improvements in executive function are associated with better future weight loss or adherence to healthy behaviors [9][10][11]. This work raises the possibility that improving or maintaining executive function through weight management interventions could improve weight loss success. ...
Full-text available
Executive functioning is a key component involved in many of the processes necessary for effective weight management behavior change (e.g., setting goals). Cognitive behavioral therapy (CBT) and third-wave CBT (e.g., mindfulness) are considered first-line treatments for obesity, but it is unknown to what extent they can improve or sustain executive functioning in a generalized weight management intervention. This pilot randomized controlled trial examined if a CBT-based generalized weight management intervention would affect executive functioning and executive function-related brain activity in individuals with obesity or overweight. Participants were randomized to an intervention condition (N = 24) that received the Noom Weight program or to a control group (N = 26) receiving weekly educational newsletters. EEG measurements were taken during Flanker, Stroop, and N-back tasks at baseline and months 1 through 4. After 4 months, the intervention condition evidenced greater accuracy over time on the Flanker and Stroop tasks and, to a lesser extent, neural markers of executive function compared to the control group. The intervention condition also lost more weight than controls (−7.1 pounds vs. +1.0 pounds). Given mixed evidence on whether weight management interventions, particularly CBT-based weight management interventions, are associated with changes in markers of executive function, this pilot study contributes preliminary evidence that a multicomponent CBT-based weight management intervention (i.e., that which provides both support for weight management and is based on CBT) can help individuals sustain executive function over 4 months compared to controls.
... Lower EFs were found to be significantly associated with some dysfunctional eating-related behaviors, e.g., weak food inhibition [22][23][24], greater intake of fatty foods [25], reduced control in appetite regulation [26], less physical activity [27], higher emotional eating [28], inability to learn from errors or past experiences [29], delay in weight loss [22], poorer adherence to dietary intentions [30], and poor treatment outcomes during weight loss interventions [31]. In recent decades, some studies have shown that obesity was related to impaired performance on tasks assessing EFs [21,32,33]. It has been argued that obese subjects would be unable to delay gratifications or inhibit prepotent responses to highly palatable foods [33]. ...
... In recent decades, some studies have shown that obesity was related to impaired performance on tasks assessing EFs [21,32,33]. It has been argued that obese subjects would be unable to delay gratifications or inhibit prepotent responses to highly palatable foods [33]. However, other studies were inclined to sustain the opposite point of view, with obese subjects showing equal or better executive performance than normal-weight subjects [34][35][36][37]. ...
... These findings would support the rationale of the so-called "obesity paradox", i.e., excess adiposity as a protective factor for health outcomes including cognitive functioning and mortality, especially in geriatric patients [37][38][39]. Although previous research on the relationship between obesity and EFs has provided conflicting evidence on most of the executive domains explored [21,26,32,33,40,41], many concerns remain about inhibitory control, verbal fluency, and psychomotor speed domains, especially when the potential moderation effect of covariates has not been taken into account. ...
Full-text available
Background: Recent evidence suggests that a higher body weight may be linked to cognitive impairment in different domains involving executive/frontal functioning. However, challenging results are also available. Accordingly, our study was designed to verify whether (i) poor executive functions are related to a higher body weight and (ii) executive functioning could contribute to weight loss in treatment-seeking overweight and obese patients. Methods: We examined general executive functioning, inhibitory control, verbal fluency, and psychomotor speed in a sample including 104 overweight and obese patients. Forty-eight normal-weight subjects participated in the study as controls. Results: Univariate Analysis of Variance showed that obese patients obtained lower scores than overweight and normal-weight subjects in all executive measures, except for errors in the Stroop test. However, when sociodemographic variables entered the model as covariates, no between-group difference was detected. Furthermore, an adjusted multiple linear regression model highlighted no relationship between weight loss and executive scores at baseline. Conclusions: Our results provide further evidence for the lack of association between obesity and the executive domains investigated. Conflicting findings from previous literature may likely be due to the unchecked confounding effects exerted by sociodemographic variables and inclusion/exclusion criteria.
... Executive functions have traditionally been identified as composing 2 broad categories: behavioral regulation and metacognition, both of which interact with each other [15]. Behavioral regulation is referred to as the ability to apply cognitive skills to behavior (inhibitory control, shifting, emotional control, and self-monitoring [29]) and is associated with success in dietary intake modification [30]. Metacognition involves cognitive knowledge (e.g., working memory) and regulation (e.g., planning, task monitoring [31]). ...
... Also, in past research, the task-based assessments were not sensitive enough to detect subtle changes in executive functions [55]. Moreover, it is unclear whether results of these task-based assessments can be translated to daily behavior [30]. The cross-sectional design precludes us from drawing a causal relationship. ...
... Executive functioning is associated with educational quality 30,31 , and educational quality has been shown to be a better predictor of decline in executive function than educational attainment in an ethnically diverse cohort 32 (p.215). Deficits in executive functioning have also been implicated in the onset and progression of multiple diseases, including cardiovascular and metabolic diseases, and have been specifically implicated in weight management (for a review see 33 ). For example, inhibition, a core component of executive function, is germane to weight management because it is associated with lower risk of overeating 33 . ...
... Deficits in executive functioning have also been implicated in the onset and progression of multiple diseases, including cardiovascular and metabolic diseases, and have been specifically implicated in weight management (for a review see 33 ). For example, inhibition, a core component of executive function, is germane to weight management because it is associated with lower risk of overeating 33 . ...
Full-text available
Educational quality may be a closer correlate of physical health than more commonly used measures of educational attainment (e.g., years in school). We examined whether a widely-used performance-based measure of educational quality is more closely associated with cardiometabolic health than educational attainment (highest level of education completed), and whether perceived control (smaller sample only), executive functioning (both samples), and health literacy (smaller sample only) link educational quality to cardiometabolic health. In two samples (N = 98 and N = 586) collected from different regions of the US, educational quality was associated with cardiometabolic health above and beyond educational attainment, other demographic factors (age, ethnoracial category, sex), and fluid intelligence. Counter to expectations, neither perceived control, executive function, nor health literacy significantly mediated the association between educational quality and cardiometabolic health. Findings add to the growing literature suggesting that current operationalizations of the construct of education likely underestimate the association between education and multiple forms of health. To the extent that educational programs may have been overlooked based on the apparent size of associations with outcomes, such actions may have been premature.
... For instance, decreased EFs have been associated with reduced food intake inhibition [12][13][14], high-fat food ingestion [15], lower appetite regulation [16], decreased energy expenditure [17], increased emotional eating [18], inability to learn from past experiences [19], delayed weight loss [12], poor adherence to healthy nutrition [20,21], and poor outcomes to weight loss interventions [22]. In line with these findings, some studies have found poor executive performance in patients with obesity [11,[23][24][25]; furthermore, neuroimaging evidence exists on the relationship between decreased neural activity within the frontal cortex-the main cortical substrate of EFs-and obesity [26][27][28]. This evidence might be supported by studies finding a significant relationship between adipose tissue and systemic inflammation interacting with the physiology of the blood-brain barrier, likely affecting cognitive performance [29][30][31][32][33]. ...
... Still, we found that the motor domain played a non-negligible role in the dynamics of such a relationship. In a scientific context in which the link between EFs and obesity needs to be further investigated [11,16,[23][24][25]103,104], these findings may contribute to extending the debate on the matter. ...
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Background: The association between obesity and executive functions (EFs) is highly controversial. It has been suggested that waist circumference (WC), compared to body mass index (BMI), is a better indicator of fat mass and EFs in obesity. Moreover, according to the viewpoint that the brain's functional architecture meets the need for interactive behavior, we hypothesize that the relationship between EFs and body weight might be mediated by the motor performance. Methods: General executive functioning (frontal assessment battery-15), additional cognitive subdomains (trail making test and digit span backward), and motor performance (finger tapping task) were assessed in a sample that included 330 volunteers (192 females, M age = 45.98 years, SD = 17.70, range = 18-86 years). Results: Hierarchical multiple regression analysis indicated that the FAB15 score and FTT negatively predicted WC but not BMI. A subsequent mediation analysis highlighted that the indirect effect of FAB15 on WC through finger tapping was statistically significant. Conclusions: Our results suggest that WC, as compared to BMI, is a more effective measure for studying the association between EFs and body weight. Still, we found that the motor domain partially mediates the dynamics of such a relationship.
... In a scientific context in which the link between EFs and obesity needs to be further investigated [7,25,[51][52][53][54]81], our findings showed that morbidly obese individuals got poor executive scores regardless of the significant effects of the above-mentioned covariates. Notably, in line with previous studies [50], we found no significant differences between obese, overweight, and normal-weight subjects on the executive domains explored. ...
... The projections from the PFC towards hypothalamic circuits appear to be involved in the modulation of hunger and satiety signals, whereas the striatal and ventral midbrain circuits are relevant for reward processing [83,89,90]. In morbidly obese patients, likely also due to the more complicated clinical profile (e.g., metabolic syndrome) [91][92][93], abnormal activity within these neural circuits might affect EFs and lead to difficulties in planning regular eating patterns, inability to delay gratification, or inhibit prepotent responses to highly palatable foods [53]. ...
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In the last decades, it has been proposed that executive functions may be particularly vulnerable to weight-related issues. However, evidence on the matter is mixed, especially when the effects of sociodemographic variables are weighted. Thus, the current study aimed at further examining the relationship between executive functions and obesity. To this aim, we compared treatment-seeking overweight, obese, and morbidly obese patients with normal-weight control participants. We examined general executive functioning (Frontal Assessment Battery–15) and different executive subdomains (e.g., inhibitory control, verbal fluency, and psychomotor speed) in a clinical sample including 208 outpatients with different degrees of BMI (52 overweight, BMI 25–30, M age = 34.38; 76 obese, BMI 30–40, M age = 38.00; 80 morbidly obese, BMI > 40, M age = 36.20). Ninety-six normal-weight subjects served as controls. No difference on executive scores was detected when obese patients were compared with over- or normal-weight subjects. Morbidly obese patients reported lower performance on executive scores than obese, overweight, and normal-weight subjects. Between-group difference emerged also when relevant covariates were taken into account. Our results support the view that morbid obesity is associated with lower executive performance, also considering the critical role exerted by sociodemographic (i.e., sex, age, and education) variables. Our results support the view that executive functioning should be accounted into the management of the obese patient because of non-negligible clinical relevance in diagnostic, therapeutic, and prognostic terms.
... Adequate executive function is essential for selfmonitoring and problem solving (38), 2 skills necessary for successful weight loss, whereas low levels of executive function predict impulsivity and poor self-control (39). Executive function is also theorized to be associated with long-term weight loss maintenance (41), because reduced executive function can decrease dietary control (42) and lead to lapses in dietary adherence. ...
... CR requires consistent executive function engagement to plan meals, track calories, self-monitor, and inhibit excess caloric intake (43). Given the complexity of many CR diets, adherence can come with associated costs to executive function such as decreased attention and self-control in domains unrelated to diet (e.g., work, relationships, physical exercise regimens) (41). ...
The metabolic syndrome consists of a constellation of clinical factors associated with an increased risk of cardiovascular disease, type 2 diabetes and cancer. Preclinical studies demonstrate that restricting the time during a 24 hour period when an obese animal eats (time restricted feeding) leads to metabolic benefits. These benefits, which may or may not be associated with weight loss, often lead to improvements in glucose tolerance and insulin sensitivity. Studies seeking to determine whether similar benefits result when humans restrict daily eating time (time restricted eating), are less mature and less consistent in their findings. In this commentary we outline some of the exciting preclinical findings, the challenges that preliminary studies in humans present, and efforts of the U.S. National Institutes of Health and specifically the National Cancer Institute to address the role of time restricted eating in cancer.
... They found that employees, friend and coworker support for healthy eating and family support for physical activity predicted improved weight management. In addition to social support, researchers have shown that psychological aspects such as emotion regulation (13), self-regulation (14), mindfulness (15), executive functions (16), personality traits (17) and self-efficacy (18) are associated with loss weight. Some findings across the lifespan is that obesity is associated with cognitive deficits, especially in executive function, in children, adolescents and adults. ...
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The purpose of present study was to clarify the links between Executive function and weight-loss. We firstly investigated definition and functions of executive functions and secondly showed studies done in the links. Studies have shown that executive functions can influence on thinking and behaviors, especially, health behaviors. As a result of the preliminary search, the final keywords utilized for the investigation were weight loss, executive functions, obesity and overweight. After that, we found twelve articles and reviewed methods and results of those. The results consisted of three main methods included correlational, experimental methods and ex-post facto studies. In conclusion, present study indicated that executive control as a central control of behavior plays a key role in weight-loss.
... The first generation of studies investigating the relationship between obesity and cognition found that obese subjects performed worse on tasks assessing global cognitive functioning, particularly impacting attention and memory (13,14). However, more recently, attention has focused on more targeted cognitive abilities, such as executive functions (EFs) (15)(16)(17)(18)(19)(20). Functionally related to the integrity of the prefrontal cortex, EFs are an umbrella term encompassing different higher order cognitive domains (e.g., abstraction, cognitive flexibility, inhibitory control, working memory, and planning) that are crucial for the guidance, direction and management of the general cognition, emotions, and goal-directed behaviors (21,22). ...
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Background The present study examines the relationship between obesity, executive functions, and body image in a nonclinical population from southern Italy. Methods General executive functioning (Frontal Assessment Battery–15), and body image disturbances (Body Uneasiness Test) were assessed in a sample including 255 participants (138 females, M age = 43.51 years, SD = 17.94, range = 18–86 years; M body mass index (BMI) = 26.21, SD = 4.32, range = 18.03–38.79). Findings Multiple Linear Regression Analysis indicated that age, years of education, FAB15 score, body image concerns, and avoidance predicted the variance of BMI. A subsequent mediation analysis highlighted that the indirect effect of FAB15 on BMI through avoidance was statistically significant. Interpretation Our results suggest that more performing executive functioning predicts a decrease in BMI that is partially due to the mitigation of avoidance behaviors.
Weight management can be aided by behavior management therapies, although weight is frequently regained. To avoid this, available interventions are necessary. Researchers did a comprehensive evaluation and integration of qualitative studies on people\'s weight control and sustaining perspectives. They looked for descriptive studies examining the reality of presently or formerly overweight individuals striving to sustain weight loss in bibliographic databases. Researchers developed the model of weight loss maintenance by thematically aggregating study data. There were 16 studies with 610 individuals from 5 nations. Because of the requirement to overcome established behaviors and the incompatibility of the new behaviors with the satisfaction of emotional factors, the model generated via our integration posits that implementing the action modifications essential for weight loss stability generates psychological “stress.” This stress must be managed or resolved for successful maintenance. Self-regulation, motivation renewal, and regulating influences can all help with stress management, while it can take a lot of work. Changes in behavior, nonobesogenic means of fulfilling needs, and maybe a shift in self-concept can all help with recovery.
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Objective: To evaluate the efficacy, as well as potential moderators and mediators, of a revised acceptance-based behavioral treatment (ABT) for obesity, relative to standard behavioral treatment (SBT). Methods: Participants with overweight and obesity (n = 190) were randomized to 25 sessions of ABT or SBT over 1 year. Primary outcome (weight), mediator, and moderator measurements were taken at baseline, 6 months, and/or 12 months, and weight was also measured every session. Results: Participants assigned to ABT attained a significantly greater 12-month weight loss (13.3% ± 0.83%) than did those assigned to SBT (9.8% ± 0.87%; P = 0.005). A condition by quadratic time effect on session-by-session weights (P = 0.01) indicated that SBT had a shallower trajectory of weight loss followed by an upward deflection. ABT participants were also more likely to maintain a 10% weight loss at 12 months (64.0% vs. 48.9%; P = 0.04). No evidence of moderation was found. Results supported the mediating role of autonomous motivation and psychological acceptance of food-related urges. Conclusions: Behavioral weight loss outcomes can be improved by integrating self-regulation skills that are reflected in acceptance-based treatment, i.e., tolerating discomfort and reduction in pleasure, enacting commitment to valued behavior, and being mindfully aware during moments of decision-making.
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Increased body mass is directly associated with reduced cognitive function. The aim of this study was to systematically review the effect of bariatric weight loss surgery on cognitive function. A comprehensive and unrestricted literature search was conducted using the following databases: MEDLINE, EMBASE, PubMed, Scopus, Web of Sciences, and the Cochrane Library. A total of 414 publications were identified, of which 18 were included in the final review. Cognitive function as measured by a number of different assessment tools was shown to improve following surgically induced weight loss in most studies. Significant and rapid weight loss resulting from bariatric surgery is associated with prompt and sustained improvements in cognitive function including memory, executive function, and cognitive control.
There is a general perception that almost no one succeeds in long-term maintenance of weight loss. However, research has shown that ≈20% of overweight individuals are successful at long-term weight loss when defined as losing at least 10% of initial body weight and maintaining the loss for at least 1 y. The National Weight Control Registry provides information about the strategies used by successful weight loss maintainers to achieve and maintain long-term weight loss. National Weight Control Registry members have lost an average of 33 kg and maintained the loss for more than 5 y. To maintain their weight loss, members report engaging in high levels of physical activity (≈1 h/d), eating a low-calorie, low-fat diet, eating breakfast regularly, self-monitoring weight, and maintaining a consistent eating pattern across weekdays and weekends. Moreover, weight loss maintenance may get easier over time; after individuals have successfully maintained their weight loss for 2–5 y, the chance of longer-term success greatly increases. Continued adherence to diet and exercise strategies, low levels of depression and disinhibition, and medical triggers for weight loss are also associated with long-term success. National Weight Control Registry members provide evidence that long-term weight loss maintenance is possible and help identify the specific approaches associated with long-term success.
Reports an error in the original article by M. T. McGuire et al ( Journal of Consulting and Clinical Psychology , 1999[Apr], 67[2], 177–185). On page 181, the Figure 1 caption was incorrect. The correct caption is provided. (The following abstract of this article originally appeared in record 1999-10771-002 .) This study identified predictors of weight gain versus continued maintenance among individuals already successful at long-term weight loss. Weight, behavior, and psychological information was collected on entry into the study and 1 year later. Thirty-five percent gained weight over the year of follow-up, and 59% maintained their weight losses. Risk factors for weight regain included more recent weight losses (less than 2 years vs. 2 years or more), larger weight losses (greater than 30% of maximum weight vs. less than 30%), and higher levels of depression, dietary disinhibition, and binge eating levels at entry into the registry. Over the year of follow-up, gainers reported greater decreases in energy expenditure and greater increases in percentage of calories from fat. Gainers also reported greater decreases in restraint and increases in hunger, dietary disinhibition, and binge eating. … (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Background: Nearly one in five 4-year-old children in the United States are obese, with low-income children almost twice as likely to be obese as their middle/upper-income peers. Few obesity prevention programs for low-income preschoolers and their parents have been rigorously tested, and effects are modest. We are testing a novel obesity prevention program for low-income preschoolers built on the premise that children who are better able to self-regulate in the face of psychosocial stressors may be less likely to eat impulsively in response to stress. Enhancing behavioral self-regulation skills in low-income children may be a unique and important intervention approach to prevent childhood obesity.
Importance Between 1980 and 2000, the prevalence of obesity increased significantly among adult men and women in the United States; further significant increases were observed through 2003-2004 for men but not women. Subsequent comparisons of data from 2003-2004 with data through 2011-2012 showed no significant increases for men or women. Objective To examine obesity prevalence for 2013-2014 and trends over the decade from 2005 through 2014 adjusting for sex, age, race/Hispanic origin, smoking status, and education. Design, Setting, and Participants Analysis of data obtained from the National Health and Nutrition Examination Survey (NHANES), a cross-sectional, nationally representative health examination survey of the US civilian noninstitutionalized population that includes measured weight and height. Exposures Survey period. Main Outcomes and Measures Prevalence of obesity (body mass index ≥30) and class 3 obesity (body mass index ≥40). Results This report is based on data from 2638 adult men (mean age, 46.8 years) and 2817 women (mean age, 48.4 years) from the most recent 2 years (2013-2014) of NHANES and data from 21 013 participants in previous NHANES surveys from 2005 through 2012. For the years 2013-2014, the overall age-adjusted prevalence of obesity was 37.7% (95% CI, 35.8%-39.7%); among men, it was 35.0% (95% CI, 32.8%-37.3%); and among women, it was 40.4% (95% CI, 37.6%-43.3%). The corresponding prevalence of class 3 obesity overall was 7.7% (95% CI, 6.2%-9.3%); among men, it was 5.5% (95% CI, 4.0%-7.2%); and among women, it was 9.9% (95% CI, 7.5%-12.3%). Analyses of changes over the decade from 2005 through 2014, adjusted for age, race/Hispanic origin, smoking status, and education, showed significant increasing linear trends among women for overall obesity (P = .004) and for class 3 obesity (P = .01) but not among men (P = .30 for overall obesity; P = .14 for class 3 obesity). Conclusions and Relevance In this nationally representative survey of adults in the United States, the age-adjusted prevalence of obesity in 2013-2014 was 35.0% among men and 40.4% among women. The corresponding values for class 3 obesity were 5.5% for men and 9.9% for women. For women, the prevalence of overall obesity and of class 3 obesity showed significant linear trends for increase between 2005 and 2014; there were no significant trends for men. Other studies are needed to determine the reasons for these trends.
Importance Previous analyses of obesity trends among children and adolescents showed an increase between 1988-1994 and 1999-2000, but no change between 2003-2004 and 2011-2012, except for a significant decline among children aged 2 to 5 years. Objectives To provide estimates of obesity and extreme obesity prevalence for children and adolescents for 2011-2014 and investigate trends by age between 1988-1994 and 2013-2014. Design, Setting, and Participants Children and adolescents aged 2 to 19 years with measured weight and height in the 1988-1994 through 2013-2014 National Health and Nutrition Examination Surveys. Exposures Survey period. Main Outcomes and Measures Obesity was defined as a body mass index (BMI) at or above the sex-specific 95th percentile on the US Centers for Disease Control and Prevention (CDC) BMI-for-age growth charts. Extreme obesity was defined as a BMI at or above 120% of the sex-specific 95th percentile on the CDC BMI-for-age growth charts. Detailed estimates are presented for 2011-2014. The analyses of linear and quadratic trends in prevalence were conducted using 9 survey periods. Trend analyses between 2005-2006 and 2013-2014 also were conducted. Results Measurements from 40 780 children and adolescents (mean age, 11.0 years; 48.8% female) between 1988-1994 and 2013-2014 were analyzed. Among children and adolescents aged 2 to 19 years, the prevalence of obesity in 2011-2014 was 17.0% (95% CI, 15.5%-18.6%) and extreme obesity was 5.8% (95% CI, 4.9%-6.8%). Among children aged 2 to 5 years, obesity increased from 7.2% (95% CI, 5.8%-8.8%) in 1988-1994 to 13.9% (95% CI, 10.7%-17.7%) (P < .001) in 2003-2004 and then decreased to 9.4% (95% CI, 6.8%-12.6%) (P = .03) in 2013-2014. Among children aged 6 to 11 years, obesity increased from 11.3% (95% CI, 9.4%-13.4%) in 1988-1994 to 19.6% (95% CI, 17.1%-22.4%) (P < .001) in 2007-2008, and then did not change (2013-2014: 17.4% [95% CI, 13.8%-21.4%]; P = .44). Obesity increased among adolescents aged 12 to 19 years between 1988-1994 (10.5% [95% CI, 8.8%-12.5%]) and 2013-2014 (20.6% [95% CI, 16.2%-25.6%]; P < .001) as did extreme obesity among children aged 6 to 11 years (3.6% [95% CI, 2.5%-5.0%] in 1988-1994 to 4.3% [95% CI, 3.0%-6.1%] in 2013-2014; P = .02) and adolescents aged 12 to 19 years (2.6% [95% CI, 1.7%-3.9%] in 1988-1994 to 9.1% [95% CI, 7.0%-11.5%] in 2013-2014; P < .001). No significant trends were observed between 2005-2006 and 2013-2014 (P value range, .09-.87). Conclusions and Relevance In this nationally representative study of US children and adolescents aged 2 to 19 years, the prevalence of obesity in 2011-2014 was 17.0% and extreme obesity was 5.8%. Between 1988-1994 and 2013-2014, the prevalence of obesity increased until 2003-2004 and then decreased in children aged 2 to 5 years, increased until 2007-2008 and then leveled off in children aged 6 to 11 years, and increased among adolescents aged 12 to 19 years.