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PSYCHOLOGICAL ISSUES (V DRAPEAU AND V IVEZAJ, SECTION EDITORS)
The Impact of Physical Activity on Food Reward: Reviewand Conceptual Synthesis of Evidence from Observational, Acute,and Chronic Exercise Training Studies
Kristine Beaulieu1& Pauline Oustric1 & Graham Finlayson1
# The Author(s) 2020
AbstractPurpose of Review This review brings together current evidence from observational, acute, and chronic exercise training studiesto inform public debate on the impact of physical activity and exercise on food reward.Recent Findings Low levels of physical activity are associated with higher liking and wanting for high-energy food. Acute boutsof exercise tend to reduce behavioral indices of reward for high-energy food in inactive individuals. A dissociation in liking(increase) and wanting (decrease) may occur during chronic exercise training associated with loss of body fat. Habitual moderate-to-vigorous physical activity is associated with lower liking and wanting for high-fat food, and higher liking for low-fat food.Summary Food reward does not counteract the benefit of increasing physical activity levels for obesity management. Exercisetraining appears to be accompanied by positive changes in food preferences in line with an overall improvement in appetitecontrol.
Keywords Physical activity . Exercise . Food reward . Appetite . Liking and wanting . Obesity management
Introduction
Among the reasons that people with obesity cite for avoidingexercise is a lack of enjoyment and perceived failure to loseweight [1, 2]. Moreover, there is a misconception that persistsamong some individuals that exercise is counter-productivefor weight management. This common assertion is reinforcedby occasional reports in the media about exercise and foodreward [3, 4]. Biological explanations, reliant on soft evi-dence, have been put forward suggesting that glycogen deple-tion, reduced blood glucose levels, endorphin release or othersignals generated during exercise can increase appetite orcause specific cravings for foods. Alternatively, psychologicalaccounts propose that high fat or sugary foods are sought outpost-exercise to counteract negative affect or reward virtuousbehavior. Research over the past 10 years has shown that
physical activity and eating behavior are loosely coupled,but the physiological and neurocognitive mechanisms thatcontribute to this relationship are complex [5]. Moreover, theevidence for the impact of physical activity on food reward isdifficult to assess due to the absence of randomized controlledtrials and differences between study designs—encompassingobservational, acute, and chronic interventions. Differencesalso exist in the modality and intensity of physical activityexamined and the variety of methodologies used to measurereward responses to food. In a review of longitudinal weightmanagement interventions that measured food reward out-comes at baseline and follow-up, Oustric and colleagues[6••] identified 17 studies consisting of dietary, pharmacolog-ical, cognitive, and exercise-based intervention types. Overall,a post-intervention reduction in food reward was found acrossall treatment types—except exercise, where no consistentchanges were reported. While it is interesting to speculate thatexercise training may have a moderating influence on therelationship between weight management and food reward,only three exercise studies were eligible for inclusion in thissystematic review. Moreover, interpretation was limited bysmall sample sizes, lack of a control condition in one study,and inconsistent use of food reward measures. Further re-search is needed to update and summarize the available
This article is part of the Topical Collection on Psychological Issues
* Graham [email protected]
1 Appetite Control & Energy Balance Research Group, School ofPsychology, Faculty of Medicine & Health, University of Leeds,Leeds, West Yorkshire, UK
https://doi.org/10.1007/s13679-020-00372-3Current Obesity Reports (2020) 9:63–80
Published online: 15 April 2020
evidence from observational, acute, and chronic study designsto gain an overview of the influence of physical activity andexercise on food reward. With this objective in mind, thespecific aims of this review were to describe the role of phys-ical activity and food reward in appetite control and weightmanagement; to tabulate and synthesize the different types ofevidence that have addressed the impact of physical activityon food reward; and to discuss, and where possible harmo-nize, the findings in the light of relevant moderators and meth-odological issues. To our knowledge, there is currently nocomprehensive review of the literature on physical activityand food reward. A critical examination of the evidence mayhelp to clarify some of the perceived barriers for engaging inphysical activity and exercise for obesity management.
Current Thinking on the Role of PhysicalActivity in Appetite Control
In the last 5 years, evidence has accrued showing that physicalactivity affects both episodic (meal-to-meal) and tonic (basal)homeostatic mechanisms that influence appetite control [7].Acute exercise influences gastric emptying [8], and attenuatesthe release of ghrelin and increases the secretion of satietypeptides, e.g., peptide YY, glucagon-like peptide-1, and pan-creatic polypeptide [9]. Chronic exercise improves body com-position [10–12], and leptin and insulin sensitivity [13–15].
Our research has shown that habitual physical activity has asmall positive association with daily energy intake (account-ing for around ~ 3% of the variance) [16], but this is onlylogical when considering the increase in energy requirementsand the longer-term indirect effects from increased restingmetabolic rate after changes in fat-free mass. It has been pro-posed that chronic exercise influences appetite control throughan increase in hunger but also a strengthening of post-mealsatiety [17]. Indeed, exercise and physical activity appear tointeract with nutritional factors to enhance satiety signaling,with studies showing that people who engaged in more exer-cise and physical activity were better able to compensate fordifferences in the energy content of food (achieved by increas-ing the ratio of fat to carbohydrate) at a subsequent meal thantheir less active counterparts [18]. While more active individ-uals are driven to eat more due to their greater energy require-ments, their stronger satiety response to food appears to allowfor a better matching between energy intake and energy ex-penditure [19••]. This relationship between physical activitylevel and daily energy intake is best represented by a J-shapedcurve, whereby individuals with low levels of physical activ-ity on the left of the curve have dysregulated appetite withgreater intake than expenditure, and individuals with greaterlevels of physical activity towards the right of the curve have aproportional increase in intake with increasing expenditure.These findings suggest that concerns about exercise or
increased levels of physical activity being counter-productive for obesity management should be concerned withnon-homeostatic and food reward-related mechanisms thatmay be driving unhealthy food choices.
Defining Food Reward and Its Importancefor Weight Management
Food reward is important for understanding appetite controland has the logical status of an intervening variable that guideseating behavior. Food reward is encoded by distinct neuralpathways in the brain and can be modulated by metabolicsignaling, sensory stimuli from the food environment and cog-nitive processes such as attention, learning, and memory [20].Food reward is often conceptualized to consist of two distinctsub-components—“liking” and “wanting.” These have beenbroadly studied [21], following extensive work demonstratingtheir dissociation in the brain and behavior of many speciesincluding humans [22]. Liking is the sensory pleasure exertedwhile eating a food and wanting is rather the, often implicit,drive to eat triggered by a food cue [23]. Liking and implicitwanting for energy-dense foods are related to excess energyintake in free-living and laboratory settings [23, 24]. However,liking accounts only for a small proportion of the variance infood intake [25, 26], and unconscious processes such as im-plicit wanting may play a larger role in driving overeating [27,28]. Food reward is an important factor in weight managementthrough its intervening status between the nutritional require-ments of the body and stimulation from the food environment[23], but it is likely that liking and implicit wanting sometimesact separately to influence appetite control [6••].
While several techniques to measure food reward havebeen developed [21] (e.g., reinforcing value tasks, willingnessto pay), the Leeds Food Preference Questionnaire (LFPQ) hasbeen designed to measure both liking and implicit wanting fordistinct dimensions (e.g., fat and sweet taste) of foods com-mon in the diet. Food reward measured by the LFPQ can beinterpreted as both a state- and a trait-dependent measure de-pending on the timing and condition of measurement. Indeed,liking and wanting have been shown to be partially dissocia-ble pre to post food consumption according to sensory-specific satiety [29]. On the contrary, food cravings, definedhere as spontaneous instances of strong explicit wanting for aspecific food, tend to be measured as a trait reflecting thefrequency, intensity or quality of cravings experienced overa specified time period [30–32]. Neural activation to foodsmeasured through functional magnetic resonance imaging(fMRI) are also used as an inference of food reward and thistechnique allows the analysis of different regions of interestand their functional connectivity [33]. However, fMRI mea-sures of reward should be used in conjunction with behavioralmeasures or actual food intake to support their interpretation.
Curr Obes Rep (2020) 9:63–8064
Review of Literature
Methods
The inclusion and exclusion criteria for this non-systematicreview were established prospectively. We included studieswith a general, healthy population of adults (≥ 18 years) orchildren (< 18 years), including those with overweight or obe-sity. Studies that included adults or children with overweightor obesity who were specifically trying to lose weight werealso included. We excluded studies in populations with dis-eases (including substance related and addictive disorders),in vitro and animal studies. The interventions and compari-sons of interest included any type of structured exercise orcomparisons between different physical activity levels. Allchronic training studies had to have a minimum interventionduration of 4 weeks. The outcomes of interest included allpsychometric measures of food reward obtained either directly(e.g., ratings or pleasantness or desire to eat) or indirectly (e.g.,measure of the willingness to work to obtain a food, reactiontime), as well as neuronal response to food cues measured byfMRI. We included unpublished and ongoing studies whererelevant.
The search strategy for this review combined electronicsearches and hand searching. To identify ongoing or complet-ed, but unpublished trials, ClinicalTrials.gov was searched on22 November 2019 and researchers known to be active in thetopic were contacted. Limits were set to include all paperspublished in English or French after 2009, in healthy humansamples. Authors were contacted for additional information ifunclear or not reported in the manuscript.
Observational Studies of Physical Activityand Exercise
As shown in Table 1, only three studies have examined foodreward differences in defined active and inactive groups [34,35, 38]. Horner et al. [38] found that in the fed state, overallliking, and liking for high-fat savory, high-fat sweet, and low-fat sweet food measured by the LFPQ was lower in activecompared with inactive men differing in BMI, and differencesfor foods overall and low-fat sweet foods remained afteradjusting for differences in percentage body fat. In both fedand hungry states, active men had a greater implicit wantingfor low-fat savory foods comparedwith inactivemen, but onlythe differences in the fed state remained after adjusting forpercentage body fat. Faster gastric emptying was found to beassociated with greater liking for savory food and lower im-plicit wanting for high-fat food. Two studies in men and wom-en differing in physical activity levels but matched for BMI (~23 kg/m2) found no differences in liking or wanting for high-fat relative to low-fat food in the hungry or fed states [34, 35].
In terms of correlational studies, objectively measuredMVPAwas found to be inversely associated with liking (r =− 0.25, p < 0.001) and wanting (r = − 0.27, p = 0.001) forhigh-fat relative to low-fat food measured by the LFPQ in156 women across a range of BMI [41]. This is in line witha study showing that self-reported physical activity was asso-ciated with reduced fMRI responses to high-energy relative tolow-energy food [39]. Another fMRI study in participantsranging in BMI found an inverse association between self-reported moderate-to-vigorous physical activity and brain re-sponse to food cues [40•]. This relationship appeared to bemore prominent in the participants with obesity than the leanparticipants. In individuals with overweight/obesity and im-paired fasting glucose and/or glucose tolerance, food com-pared with non-food brain activation was negatively associat-ed with leisure-time physical activity [36•]. Interestingly, therewas a positive association between brain activation and work-related physical activity, which lost statistical significance af-ter adjusting for BMI and age, and there was no associationwith sport-related physical activity.
Overall, these studies suggest a reduction in food reward(both liking and wanting) with increasing levels of habitualphysical activity, particularly at higher levels of adiposity.Those who accumulate more time in moderate-to-vigorousphysical activity tend to prefer low-fat food and those whoengage in more sedentary activity prefer high-fat food.These findings do not seem to be restricted to those whoperform structured exercise. The inter-relationships betweenfood reward, physical activity, and adiposity remain to be fullydisentangled, as well as the mechanisms underlying these ob-served effects. One simple explanation could be that avoid-ance of high-fat food perceived to be unhealthy, preference forlow-fat food and greater physical activity levels are all drivenby a dispositional desire to be healthy and engage in a range ofpositive health behaviors [64, 65]. Alternatively, it has beenproposed that physical activity may act as a reward “buffer”against liking and wanting for high-fat foods, whereas lowlevels of physical activity may render people more susceptibleto hedonic eating [66, 67]. The possibility of stronger inverseassociations between physical activity and food reward in leangroups versus groups with obesity suggests that exercise andleisure-time physical activity may be an effective strategy forcontrolling hedonic eating in people with obesity.
Acute Exercise Studies
At least eight studies have investigated the effect of acuteexercise on food reward measured by the LFPQ which allowsdirect comparison of outcomes (Table 1). All these studies hada no-exercise control group except for Alkahtani et al. [42],but the exercise varied in intensity (low to high), modality(aerobic vs resistance; cycling vs swimming) or in musclecontraction type (eccentric vs concentric). Two studies
Curr Obes Rep (2020) 9:63–80 65
Table1
Descriptio
nof
theobservational,acute,andchronictraining
studiesexam
iningtheim
pactof
physicalactiv
ityon
food
reward
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
Observationalstudies
Beaulieuetal.
2017
[34]
UK
Sex:
females
andmales
BMIstatus:<
29.9
kg/m
2
Active:n=20
(50%
males)
Age:3
0(10)
years
BMI:22.6(1.9)kg/m
2
Inactive:n=19
(42%
males)
Age:3
0(9)years
BMI:23.1(2.7)kg/m
2
PAlevelassessm
ent:IPAQandPA
monito
r(SenseWear)
Active:≥4exercise
sessions/week
(MVPA
=182(67)
min/day)
Inactive:≤1exercise
session/week
(MVPA
=103(37)
min/day)
Exercisesession:
≥40
min
MVPA
-LFP
Q:likingandim
plicitwantin
gbias
forfat
-Setting:laboratory
-State:preandposthigh-fator
high-carbohydratelunch(adlibitu
m)
-Nodifference
infood
reward(likingand
wantin
g)betweengroups.
-Differencebetweenlik
ing/wantin
g:none
-Fo
odintake:energyintake
greaterin
high-fatrelativ
eto
high-carbohydrate
inboth
groups.
-Eatingbehavior
traits:tendencyfor
restrainttobe
higher
inHiPA
comparedwith
LoPA
-Bodycomposition:
HiPAhadlower
body
fatp
ercentagethan
LoPA
Beaulieuetal.
2017
[35]
UK
Sex:
females
andmales
BMIstatus:<
29.9
kg/m
2
HiM
VPA
:n=12
(33%
males)
Age:2
9(10)
years
BMI:22.4(2.1)kg/m
2
ModMVPA
:n=11
(27%
males)
Age:2
6(3)years
BMI:22.7(2.2)kg/m
2
LoM
VPA
:n=11
(27%
males)
Age:3
0(11)
years
BMI:23.1(2.9)kg/m
2
PAlevelassessm
ent:Tertilesof
daily
MVPA
measuredby
PAmonito
r(SenseWear)
HiM
VPA
:174
(39)
min/day
ModMVPA
:121
(15)
min/day
LoM
VPA
:83(16)
min/day
-LFP
Q:likingandim
plicitwantin
gbias
forfat
-Setting:laboratory
-State:preandpostpreloads—HE
(~700kcal)andLE(~
260kcal)
relativ
eto
watercontrol(0kcal)
-Nodifference
infood
reward(likingand
wantin
g)betweengroups
-Differencebetweenlik
ing/wantin
g:none
-Fo
odintake:g
reaterreductionin
liking
andwantingafterHEpreloadrelative
toLEpreloadin
allg
roups.
ModMVPA
andHiM
VPA
reducedad
libitumenergy
intake
atthelunchmeal
follo
wingconsum
ptionof
theHE
comparedwith
theLEpreload,while
theLoM
VPA
groupdidnot.Noeffect
ofMVPA
groupon
energy
intake
atdinner
oreveningsnackbox.
-Eatingbehavior
traits:n
odifferences
betweengroups
-Bodycomposition:
nodifferences
betweengroups
Drummen
etal.2019
[36•]
Netherlands
Sex:
females
andmales
BMIstatus:>
25kg/m
2
n=39
(56%
males)
Age:5
3(11)
years
BMI:32.3(3.7)kg/m
2
Participantshadim
paired
fasting
glucoseand/or
glucose
tolerance
PAlevelassessm
ent:Baecke
questio
nnaire
(work,sport,and
leisure-tim
ephysicalactiv
ity)
[37]
Work=2.6(0.8)range1.3–4.3
Sport=
2.6(0.7)range1.0–4.0
Leisure=2.9(0.7)range1.5–4.4
Scores
rangingfrom
1(low
levelo
fPA
)and5(highlevelo
fPA
)
-fM
RI:BOLDsignalsto
high-energy
food,low
-energyfood
andnon-food
images
-Setting:laboratory
-State:afterovernightfast
-Inverseassociationbetween
leisure-tim
ePA
andfood
compared
with
non-food
brainactiv
ationin
the
rightthalamus,leftm
iddlecingulate
gyrus,rightp
recuneus,leftp
utam
en,
andleftangulargyrus.
-Po
sitiv
eassociationbetween
work-relatedphysicalactiv
ityand
brainactiv
ation(disappeared
after
adjustingforBMIandage)
-Noassociationwith
sport-related
physicalactiv
ity.
-Differencebetweenliking/wanting:
NR
-Fo
odintake:N
R-Eatingbehavior
traits:p
ositive
associationbetweenbrainactivation
anddisinhibition.N
oassociationwith
restrainto
rsusceptibility
tohunger.
-Bodycomposition:
noassociation
Horneretal.
2016
[38]
Australia
Sex:
males
BMIstatus:1
8–40
kg/m
2
Active:n=22
Age:2
9(8)years
BMI:24.5(2.6)kg/m
2
Inactive:n=22
Age:3
1(9)years
BMI:27.4(4.2)kg/m
2
PAlevelassessm
ent:Self-reportand
PAmonitor(A
ctiGraph)
Active:≥4exercise
sessions/week
(PA=709(239)kcal/day)
Inactive:≤1exercise
session/week
(PA=525(185)kcal/day)
Exercisesession:
≥40
min
MVPA
-LFP
Q:likingandim
plicitwantin
gfor
HFS
W,L
FSW,H
FSA,L
FSA
-Setting:laboratory
-State:postfixedbreakfast(400kcal)
andprelunch5hlater
-Fed:
Activehadlower
likingfor
high-fatfoods,low-fatsw
eetfoods
andforfoodsoverallcom
paredwith
inactiv
e.Activehadgreaterwanting
forlow-fatsavory
foods.
-Hungry:
Nodifferencesin
liking
betweenactiv
eandinactiv
e.Active
hadgreaterwantin
gforlow-fatsavory
foods.
-Gastricem
ptying:Inverse
association
with
post-prandialchanges
inlik
ing
low-fatsavory
foods.Po
sitive
associationwith
likingtastebias
inhungry
state(i.e.,fastergastric
emptying
associated
with
greater
likingforsavory
foods).N
oassociationwith
likingfatb
iasnor
implicitwantingtastebias.P
ositive
associationwith
implicitwantin
gfat
Curr Obes Rep (2020) 9:63–8066
Tab
le1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
-Fedto
hungry:A
ctivehadgreater
increase
inlik
ingforallfood
categories
combinedthan
inactive.
-Differencebetweenlik
ing/wantin
g:Fastergastricem
ptying
associated
with
likingforsavory
foodsand
slow
ergastricem
ptying
associated
with
greaterim
plicitwantingfor
high-fatfoods.
bias
infedandhungry
states.E
ffects
independento
fbody
fat.
Killgore
etal.
2013
[39]
USA
Sex:
females
andmales
BMIstatus:1
9.8–34.8
kg/m
2
n=37
(59%
males)
Age:3
0(8)years
BMI:24.5(3.7)kg/m
2
PAlevelassessm
ent:Self-reported
habitualPA
inmin/week(typical
days/week×duration/day)
PA=151(160)min/week(range
0–540)
-fM
RI:response
tohigh-energyfood,
low-energyfood
andnon-food
images
-Su
bjectivefood
preferences:desire
toeatd
epictedfood
item
atthatmom
ent
(VAS)
-Setting:laboratory
-State:1hfasted
(pre
scan
food
intake
323(245)kcal)
-InverseassociationbetweenhabitualPA
andfM
RIresponses(m
edial
orbitofrontalcortexandleftinsula)to
high-energyfoodsrelativeto
low-energyfoods
-InverseassociationbetweenhabitualPA
andpreference
forhigh-energysavory
foods
-Su
bjectiv
efood
preference:fMRI
responsespositiv
elyassociated
with
preference
forhigh-energysavory
foods(not
forhigh-energysw
eet
foods).N
oassociationbetweenfM
RI
responsesto
high-energyrelativ
eto
low-energyfoodsandpreference
for
low-energyfoods.
Luo
etal.
2018
[40•]
USA
Sex:
females
andmales
BMIstatus:N
Rn=40
(48%
males)
Leanindividuals:n=22
(46%
males)
Age:2
1(2)years
BMI:22.6(1.9)kg/m
2
Individualswith
obesity:n
=18
(50%
males)
Age:2
2(2)years
BMI:35.2(4.0)kg/m
2
PAlevelassessm
ent:Self-reported
from
3to
524-h
recalls
over
2months(m
eandaily
minutes
ofMVPA
i.e.,activities
≥3METs)
Leanindividuals:MVPA
=125(84)
min/day
Individualswith
obesity:
MVPA
=134(114)min/day
-fM
RI:responsesto
high-energyfood
andnon-food
images
-Setting:laboratory
-State:9–11
amaftero
vernightfast,task
performed
20–30min
after75
gglucoseingestion
-Inverse
associationbetweenMVPA
and
brainresponse
tofood
cues
inmiddle
insulaandleftpostcentralg
yrus.
-Individualswith
obesity:inverse
associationbetweenMVPA
andbrain
responses.
-Leanindividuals:non-significant
inverseassociationbetweenMVPA
andbrainresponses.
-Associatio
nbetweenMVPA
andbrain
responsesstronger
inmales
than
females.
-Fo
odintake:N
R-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Oustricetal.
2018
[41]
UK
Sex:
females
BMIstatus:1
8.5–45.0
kg/m
2
n=156
Age:5
3(11)
years
BMI:32.3(3.7)kg/m
2
Pooled
datafrom
6studies
PAlevelassessm
ent:Quintilesof
daily
MVPA
measuredby
PAmonito
r(SenseWear)
Q1:
25(8)min/day
Q2:
53(9)min/day
Q3:
83(9)min/day
Q4:
120(12)
min/day
Q5:
197(62)
min/day
-LFP
Q:likingandim
plicitwantin
gbias
forfat/taste
-Setting:laboratory
-State:hungry
(3–10hfast)
-MVPA
inverselyassociated
with
liking
andim
plicitwantingfatb
ias.
-MVPA
positiv
elyassociated
with
liking
tastebias.
-Q5greaterlik
ingandwantin
gfor
low-fatfoods,whileQ1-Q3greater
likingandwantin
gforhigh-fatfoods.
-Differencebetweenlik
ing/wantin
g:none
-Fo
odintake:N
R-Eatingbehavior
traits:N
oassociation
betweenPA
andfood
cravings.
Craving
forsw
eetfood(Control
ofEatingQuestionnaire;C
oEQ)
positivelyassociated
with
explicit
likingandim
plicitwantin
gforsw
eet
foodson
theLFP
Q.C
raving
for
savory
foods(CoE
Q)associated
with
LFP
Qexplicitwantin
gforsavory
foods.Craving
control(CoE
Q)
negativ
elyassociated
with
implicit
wantin
gforhigh-fatfoods.
-Bodycomposition:
Fatm
assindex
(FMI)butn
otwaistcircum
ference
(WC)was
inverselyassociated
with
explicitlikingandim
plicitwantin
gfor
Curr Obes Rep (2020) 9:63–80 67
Tab
le1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
sweetrelativeto
savory
foods.WC
was
positiv
elyassociated
with
all
likingandim
plicitwantin
gforhigh-fat
relativ
etolow-fatfoods.FM
Iwas
also
associated
with
implicitwantin
gfor
high-fatfoods.
Acuteexercise
studies
Alkahtani
etal.2014
[42]
Australia
Sex:
males
BMIstatus:>
25kg/m
2
PAlevel:sedentary(criteriaNR)
n=12
Age:2
9(4)years
BMI:29.1(2.4)kg/m
2
-Intensity:m
oderate-intensity
intervaltraining
(MIIT;
alternatingbetween±20%
FATmax)vs.high-intensity
intervaltraining
(HIIT;
85%
VO2peak)
-Ty
pe:cycleergometer
-Duration:
MIIT5-min
stages
at±2
0%FA
Tmaxfor30
min,H
IIT
15-sintervalsand15-srecovery
(workloadmatched
toMIIT;
~18
min)
-Tim
ing:
morning
-Control
condition:n
o;MIITvs.
HIIT
-LFP
Q:likingandim
plicitwantin
gfor
HFS
W,L
FSW,H
FSA,L
FSA
-Setting:laboratory
-State:beforeandafterexercise
(afteran
overnightfast)
-Decreasein
wantingandincrease
inlik
ingforallthe
food
categories
independento
ftheintensity
-Differencebetweenlik
ing/wantin
g:lik
ingincreasedwhilewantin
gdecreasedbutw
ithouta
controlthis
response
might
bedueto
theeffectof
timerather
than
exercise
-Fo
odintake:N
R-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Alkahtani
etal.2019
[43]
SaudiA
rabia
Sex:
males
BMIstatus:N
RPA
level:moderatelyactive
(2–5
hstructured
aerobic
exercise/week)
n=14
(8forfood
rewarddata)
Age:2
4(6)years
BMI:23.4(3.3)kg/m
2
-Intensity
:moderate(60%
VO2m
ax)
interspersed
with
low(30%
VO2m
ax)
-Ty
pe:contractio
ntype
eccentric
(dow
nhill
runningat−12%
inclination)
vs.concentric(flat
running)
-Duration:
5stages
of8min
at60%VO2max/2
min
at30%VO2max
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-LFP
Q:likingandim
plicitwantin
gbias
forfat/taste
-Setting:laboratory
-State:before,after
exercise
and24
hafterexercise
(beforean
adlibitu
mlunch)
-Nochange
infood
rewardafterexercise
-Differencebetweenlik
ing/wantin
g:greaterlik
ingof
savory
foodsover
sweetfoods
indownhill
runningthan
frontrunning
-Fo
odintake:n
ochange
-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Crabtreeetal.
2014
[44]
UK
Sex:
males
BMIstatus:2
1.8–26.6
kg/m
2
PAlevel:moderatelyactive
(2h/week)
n=16
Age:2
3(3)years
BMI:24.2(2.4)kg/m
2
-Intensity:h
igh(70%
VO2max)
-Ty
pe:treadmill
run
-Duration:
60min
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-fM
RI:BOLDsignalsto
high-and
low-energyfood
cues
comparedwith
non-food
pictures
-Setting:laboratory
-State:fasted
-Decreased
activationinthepallidumfor
high-energyfood
andincrease
for
low-energyfood
afterexercise
-Differencebetweenliking/wanting:
NR
-Fo
odintake:N
R-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Evero
etal.
2012
[45]
USA
Sex:
females
andmales
BMIstatus:<
25kg/m
2
PAlevel:habitually
activ
e(>
3h/week)
n=30
(57%
males)
-Intensity:h
igh(83%
HRmax)
-Ty
pe:cycleergometer
-Duration:
60min
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-fM
RI:BOLDsignalsto
high-and
low-energyfood
cues
comparedwith
neutralcontrol
-Setting:laboratory
-Exercisereducedtheneuronalresponse
tofood
cues
inbrainregionsrelated
with
food
reward(i.e.,insula,
putamen,rolandicoperculum)
-Fo
odintake:N
R-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Curr Obes Rep (2020) 9:63–8068
Tab
le1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
Age:2
2(4)years
BMI:23.6(2.2)kg/m
2-State:fM
RIwas
performed
after
exercise
afteran
8–12
hovernightfast-Differencebetweenlik
ing/wantin
g:decrease
inregionsrelatedto
liking
andwantingbutn
obehavioral
measures
Farahetal.
2012
[46]
UK
Sex:
females
andmales
BMIstatus:n
olim
itsPA
level:NR
n=27
(52%
males)
Female:n=13
Age:2
6(3)years
BMI:BMI:22.8(3.1)kg/m
2
Male:n=14
Age:3
6(10)
years
BMI:26.1(3.3)kg/m
2
-Intensity:m
oderate(6
METs)
-Ty
pe:treadmill
walk
-Duration:
60min
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-VAS:
liking
-Setting:laboratory
-State:im
mediately,60,120,and
180min
afterexercise
(overnight
fasted)
-Nochange
inlik
ing
-Differencebetweenlik
ing/wantin
g:wantin
gnotm
easured
-Fo
odintake:N
R-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Finlayson
etal.2009
[47]
UK
Sex:
females
BMIstatus:<
25kg/m
2
PAlevel:2.4(1.2)
engagements/week
n=24
Age:2
4(6)years
BMI:22.3(2.9)kg/m
2
-Intensity:m
oderate(70%
HRmax)
-Ty
pe:cycleergometer
-Duration:
50min
-Tim
ing:
morning
-Controlcondition:yes,noexercise
-LFP
Q:relativepreference
(food
choice),lik
ingandim
plicitwantin
gforHFS
W,L
FSW,H
FSA,L
FSA
-Setting:laboratory
-State:beforeandafterexercise(2
hafter
afixedbreakfast,kcalNR)and
afteran
adlib
itum
lunch30-m
inpostexercise
-Increase
inim
plicitwantin
gafter
exercise
inthosewho
compensated
oratemoreatthead
libitu
mlunchin
response
toexercise
-Differencebetweenlik
ing/wantin
g:Changes
inim
plicitwantin
gbutn
otlik
ing
-Fo
odintake:A
fter
exercise
some
individualsincreasedtheirenergy
intake
(com
pensators)andhad
enhanced
implicitwantin
g-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Martin
setal.
2015
[48]
Norway
Sex:
females
andmales
BMIstatus:>
25kg/m
2
PAlevel:sedentary(criteriaNR)
n=12
(42%
males)
Age:3
3(10)
years
BMI:32.3(2.7)kg/m
2
-Intensity:H
IITand½HIIT(allout;
average~85%
HRmax),
continuous
(70%
HRmax)
-Ty
pe:H
IITvs.½
HIITvs.
continuous
cycling
-Duration:
HIIT(8-sintervalsand
12-srecovery
for250kcal;
~18
min),½
HIIT(8-sintervals
and12-srecovery
for125kcal;
~9min),continuous
exercise
(250
kcal;~
27min)
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-LFP
Q:relativepreference
(food
choice),lik
ingandim
plicitwantin
gbias
forfat
-Setting:laboratory
-State:before
andafterexercise/b
efore
anad
libitum
lunch
(standardizedbreakfasto
f600kcal
consum
ed1hbefore
exercise/rest)
-Nochange
infood
reward
-Differencebetweenlik
ing/wantin
g:no
differences
-Fo
odintake:n
ochange
-Eatingbehavior
traits:N
R-Bodycomposition:
NR
McN
eiletal.
2015
[49]
Canada
Sex:
females
andmales
BMIstatus:<
25kg/m
2
PAlevel:inactive
(<150min/week)
n=16
(50%
males)
Age:2
2(3)years
BMI:22.8(1.8)kg/m
2
-Intensity:h
igh(aerobic70%
VO2peak,resistance70%
1-repetitionmaxim
um)
-Ty
pe:aerobicvs.resistance
-Duration:
aerobic~24
min,
resistance
~86
min
(matched
for
energy
expenditu
reat4kcal/kg;
~275kcal)
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-LFP
Q:relativepreference
(food
choice),lik
ingandim
plicitwantin
gbias
forfat/taste
-Setting:laboratory
-State:preandpostad
libitum
lunch
30min
afterexercise
(standardized
breakfasto
f534kcalconsum
ed~1.5hbefore
exercise)
-Decreasein
therelativepreference
for
high-fatrelativ
eto
low-fatfoodsafter
both
exercise
-Decreasein
likingforhigh-fatfoods
follo
wingresistance,but
notaerobic
-Differencebetweenlik
ing/wantin
g:change
infood
choice
andliking,but
notimplicitwantin
g
-Fo
odintake:n
ochange
-Eatingbehavior
traits:N
R-Bodycomposition:
nodifference
inbodyweight
Miguetetal.
2018
[50]
Sex:
females
andmales
(adolescents)
-Intensity:h
igh(70%
,75%
,80%
,85%,and
90%
HRmax)
-LFP
Q:relativepreference,likingand
implicitwantingbias
forfat/taste
-Fo
odintake:d
ecreasein
energy
intake
atlunchanddinner
Curr Obes Rep (2020) 9:63–80 69
Tab
le1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
France
BMIstatus:>
29.9
kg/m
2
PAlevel:inactive(<2h/week)
n=33
(36%
males)
Age:1
3(1)years
BMI:35.0(4.3)kg/m
2
-Ty
pe:h
igh-intensity
interval
training
cycling
-Duration:
5×2-min
increasing
intensity
intervalsfollowed
by30-srecovery
(15min)
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-Setting:laboratory
-State:preandpostad
libitum
lunch
30min
afterexercise
(standardized
breakfasto
f500kcalconsum
ed2.5h
before
exercise)
-Decreasein
implicitwantin
gforsw
eet
intheexercisecondition
vs.increasein
thecontrol
-Differencebetweenlik
ing/wantin
g:im
plicitwantingbutn
otlik
ingis
decreasing
-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Thackray
etal.
unpublished
UK
Sex:
females
andmales
BMIstatus:1
8.5–29.9
kg/m
2
PAlevel:habitually
activ
en=32
Age:2
3(2)years
BMI:23.9(2.6)kg/m
2
-Intensity:self-determ
ined
moderate-to-highintensity
(RPE
of15
“hard”)
-Ty
pe:swim
mingvs.cyclin
g-Duration:
6×8-min
intervalswith
2-min
recovery
-Tim
ing:
morning
-Controlcondition:yes,noexercise
-LFP
Q:relativepreference
(food
choice),lik
ingandim
plicitwantin
gbias
forfat/taste
-Setting:laboratory
-State:post-exercise(3
hafterfixed
breakfasto
f650kcalformales,
525kcalforfemales,and
before
adlibitu
mlunchmeal)
-Tendency
foramaineffectof
trialfor
implicitwantingfatb
ias(posth
oc:
cycling<control,cycling<
swim
ming).
-Noim
pactof
swim
mingor
cyclingon
otherfood
rewardparameters.
-Differencebetweenlik
ing/wantin
g:Changes
inim
plicitwantin
gbutn
otlik
ing
-Fo
odintake:increasein
adlib
itum
energy
intake
aftersw
immingbutn
otaftercycling
-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Thiveletal.
2019
[51]
France
Sex:
females
andmales
BMIstatus:<
25kg/m
2
PAlevel:moderatelyactive
(150–240
min/week)
n=19
(52%
males)
Age:2
1(1)years
BMI:22.3(2.9)kg/m
2
-Intensity:low
50%
VO2max,high
75%
VO2max
-Ty
pe:cyclin
g-Duration:
lowintensity
45min,
high
intensity
30min
-Tim
ing:
morning
-Controlcondition:yes;noexercise
-LFP
Q:relativepreference,likingand
implicitwantingbias
forfat/taste
-Setting:laboratory
-State:preandpostfixedlunch30
min
afterexercise
(fem
ales
750kcaland
males
900kcal;standardized
breakfasto
f500kcalconsum
ed3h
before
exercise).
-Nochange
infood
reward
-Differencebetweenlik
ing/wantin
g:no
differences
-Fo
odintake:(self-reported)
nochange
-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Saanijo
kietal.2018
[52]
Finland
Sex:
males
BMIstatus:1
9.9–26.9
kg/m
2
PAlevel:NR
n=24
Age:2
7(5)years
BMI:23.5(1.6)kg/m
2
-Intensity:m
oderate(74%
HRmax)
-Ty
pe:aerobiccycling
-Duration:
60min
-Tim
ing:
NR
-Controlcondition:yes;noexercise
-fM
RI:BOLDsignalsto
palatableand
non-palatablefoodscomparedwith
neutralcontrol
(cars)
-Setting:laboratory
-State:post-exercise
fasted
for3
hbefore
thescans
-Noeffectsof
exercise
vsreston
neuronalresponses.
-Individualvariability
intheBOLD
signalsafterexercise
might
beexplainedby
changesin
thebrain
opioid
system
.Participantswho
show
edmostincreases
inendogenous
opioid
releasealso
hadhighest
anticipatoryfM
RIrewardresponses
follo
wingtheexercise
-Differencebetweenlik
ing/wanting:
not
assessed
-Fo
odintake:N
R-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Chronicexercise
training
studies
Alkahtani
etal.2014
[53]
Australia
Sex:
males
BMIstatus:≥
25kg/m
2
PAlevel:inactive(criteriaNR)
n=10
Age:2
9(4)years
Moderate-intensity
interval
training
(MIIT):
BMIbaselin
e=30.7(3.5)kg/m
2
BMIpost=30.8(3.5)kg/m
2
-Frequency:
3days/weekfor4
week(cross-overwith
6-week
washout)
-Intensity:M
IIT±20%
workloadat
45%
VO2peak,HIIT90%
VO2peak
-Ty
pe:M
IITvs.H
IIT
-Duration:30–45min(M
IIT5-min
stages
alternatingbetween±20%
-LFP
Q:likingandim
plicitwantin
gfor
HFS
W,L
FSW,H
FSA,L
FSA
-Setting:laboratory
-State:preandpost45-m
incyclingat
45%
VO2m
ax
-Measurementtim
epoints:w
eek0and
week4in
each
interventio
n
-Tendency
forexplicitlik
ingforhigh-fat
non-sw
eetfoods
afteracuteexercise
toincrease
with
MIITanddecrease
with
HIIT.
-Nochangesin
wanting.
-Differencebetweenliking/wantin
g:yes;
changesin
likingbutn
otwantin
g
-Fo
odintake:N
oeffectsof
training
onfood
intake
orenergy
intake.
Tendency
forfatintake(g)and%
energy
from
fattoincrease
afterMIIT.
-Eatingbehavior
traits:N
R-Bodycomposition:
NR
Curr Obes Rep (2020) 9:63–8070
Tab
le1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
High-intensity
intervaltraining
(HIIT):
BMIbaselin
e=30.9(3.2)kg/m
2
BMIpost=30.9(3.2)kg/m
2
workload,HIIT30-sintervals
and30-srecovery)
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
no;M
IITvs.H
IIT
Beaulieuetal.
2019
[54]
UK
Sex:
females
andmales
BMIstatus:2
6.0–38.0
kg/m
2
PAlevel:inactive(≤
2h/week)
Exercisers:n=46
(35%
males)
Age:4
3(8)years
BMIbaselin
e=30.5(3.8)kg/m
2
BMIpost=29.9(4.0)kg/m
2
Controls:n=15
(40%
males)
Age:4
1(11)
years
BMIbaselin
e=31.4(3.7)kg/m
2
BMIpost=31.8(3.9)kg/m
2
-Frequency:
5days/weekfor12
weeks
-Intensity:7
0%HRmax
-Ty
pe:aerobic(treadmill,row
er,
cycleergometer,and
ellip
tical)
-Duration:
500kcal(m
ales
~40–45min,fem
ales
~60
min)
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
yes;no
exercise
-LFP
Q:likingandim
plicitwantin
gbias
forfat
-Setting:laboratory
-State:preandpostfixedlunch(high-fat
orhigh-CHO;8
00kcal)
-Measurementtim
epoints:w
eek0and
week12
-Decreasein
wantin
gaftertraining
-Nochange
inlik
ing
-Differencebetweenliking/wantin
g:yes;
changesin
wantin
gbutn
otlik
ing
-Fo
odintake:reductio
nin
high
fatad
libitu
mdinnerintake
butnochange
indaily
high-fatenergy
intake
[55]
-Eatingbehavior
traits:d
ecreasein
disinhibition
andbingeeatingscore
-Bodycomposition:
reductionin
body
weightand
percentage
body
fat,but
notassociatedwith
changesinwantin
g
Cornier
etal.
2012
[56]
USA
Sex:
females
andmales
BMIstatus:>
25kg/m
2
PAlevel:NR
n=12
(42%
males)
Age:3
8(10)
years
BMIbaselin
e=33.3(4.3)kg/m
2
BMIpost=NR
-Frequency:
5days/weekfor24
weeks
-Intensity:u
pto
75%
VO2m
ax
-Ty
pe:treadmill
-Duration:
upto
500kcal/day
(40–60
min/day)
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
no
-fM
RI:responsesto
food
vsnon-food
cues
-Setting:laboratory
-State:fasted
withoutexercisefor24
h(chronicexercise)andfasted
within
30min
ofacuteexercise
(chronic+
acute;500kcal60–75%
VO2m
axfor
40-60min)
-Measurementtim
epoints:w
eek0and
week24
-Chronicexercise:reductio
nin
neuronal
responsesobserved
inthebilateral
parietalcortices,leftinsulaandvisual
cortex.
-Chronic+acuteexercise:intermediate
attenuationof
theresponse
tovisual
food
cues
inbrainregion
importantin
food
regulatio
ncomparedwith
chronicexercise
andbaselin
e-Differencebetweenliking/wanting:
NR
-Foodintake:self-reported
energy
intake
lower
aftertraining
comparedwith
baselin
ebutn
ochange
inmacronutrient
intake.N
oassociation
with
changesin
neuronalresponses.
-Eatingbehavior
traits:n
ochange
indietaryrestrainto
rdisinhibition
-Bodycomposition:
reductionin
body
fatp
ercentage.Changes
inanterior
insularesponsespositivelyassociated
with
changesin
body
massandfat
mass.
Finlayson
etal.2011
[57]
UK
Sex:
females
andmales
BMIstatus:2
6.0–38.0
kg/m
2
PAlevel:inactive(≤2h/week)
Responders(non-com
pensators):
n=20
(43%
males)
Age:4
1(9)years
BMIbaselin
e=32.3(4.3)kg/m
2
BMIpost=30.9(4.3)kg/m
2
Non-Responders(com
pensators):
n=14
(50%
males)
Age:3
7(12)
years
BMIbaselin
e=29.7(2.2)kg/m
2
BMIpost=29.3(2.5)kg/m
2
-Frequency:
5days/weekfor12
weeks
-Intensity:7
0%HRmax
-Ty
pe:aerobic(treadmill,row
er,
cycleergometer,and
ellip
tical)
-Duration:
500kcal(m
ales
~40–45min,fem
ales
~60
min)
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
no
-LFP
Q:relativepreference
(food
choice),liking,explicitwantin
gfor
HFS
W,L
FSW,H
FSA,L
FSA
-Setting:laboratory
-State:preandpostacuteexercise
(scheduled
session)
-Measurementtim
epoints:w
eek0and
week12
-Increase
inlikingafterexercise
innon-responderscomparedwith
respondersatbaselineandweek12.
-Increase
inexplicitwantin
gforhigh-fat
sweetfoods
innon-responders.
-Increase
inrelativ
epreference
for
high-fatsw
eetfoodinnon-responders.
-Differencebetweenlik
ing/wantin
g:im
plicitwantingNR
-Fo
odintake:N
R-Eatingbehavior
traits:N
R-B
odycompositio
n:greaterfatmassloss
inresponders
Finlayson
etal.
unpublished
UK
Sex:
females
andmales
BMIstatus:2
6.0–38.0
kg/m
2
PAlevel:inactive(≤
2h/week)
Non-com
pensators:n=15
(33%
males)
-Frequency:
5days/weekfor12
weeks
-Intensity:7
0%HRmax
-Ty
pe:aerobic(treadmill,row
er,
cycleergometer,and
ellip
tical)
-LFP
Q:likingandim
plicitwantin
gbias
forfat
-Setting:laboratory
-State:preandpostfixedlunch(high-fat
orhigh-CHO;8
00kcal)
-Non-com
pensatorsshow
edasm
aller
likingandim
plicitwantin
gforhigh-fat
food.
-Atb
aseline,compensatorsshow
eda
strong
likingandwantin
gforhigh-fat
-Fo
odintake:tendencyfor
non-compensatorsto
decrease
adlib
itum
dinnermealsizefrom
baseline
topost-interventionthatwas
notseen
incompensators.
Curr Obes Rep (2020) 9:63–80 71
Tab
le1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
Age:4
2(8)years
BMIbaselin
e=30.7(4.9)kg/m
2
BMIpost=29.1(5.0)kg/m
2
Com
pensators:n=15
(33%
males)
Age:4
1(9)years
BMIbaselin
e=31.8(3.7)kg/m
2
BMIpost=32.1(3.9)kg/m
2
Controls:n=15
(33%
males)
Age:4
1(11)
years
BMIbaselin
e=31.4(3.7)kg/m
2
BMIpost=31.8(3.9)kg/m
2
-Duration:
500kcal(m
ales
~40–45min,fem
ales
~60
min)
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
yes,no
exercise
-Measurementtim
epoints:w
eek0and
week12
food
whereas
non-compensators
show
edno
difference
betweenhigh-fat
andlow-fatfood.
-Greater
baselinerewardforhigh-fat
food
incompensatorsreduced
follo
wingtheexercise
interventio
n.-Inthenon-compensators,sm
allincrease
inlik
ingforhigh-fatfood
after
exercise
training,but
asimultaneous
decrease
inwantin
gforhigh-fatfood.
-Differencebetweenliking/wanting:yes,
non-compensatorsincreasedlik
ingbut
decreasedwantingforhigh-fatfood
post-intervention.
-Eatingbehavior
traits:N
R-B
odycompositio
n:significantreductio
nin
BMI,body
mass,fatm
assandWC
innon-compensators,whereas
nochangesincompensators,andincrease
inbody
massandWC.
Martin
etal.
2019
[58]
USA
Sex:
females
andmales
BMIstatus:2
5–45
kg/m
2
PAlevel:inactive(<
20min
<3
days/week)
8kcal/kgbody
weight/w
eek
(KKW):n=59
(27%
males)
Age:4
8(11)
years
BMIbaselin
e=31.4(4.6)kg/m
2
BMIpost=NR(~
31.3
kg/m
2)
20KKW:n
=51
(29%
males)
Age:4
9(12)
years
BMIbaselin
e=30.6(4.4)kg/m
2
BMIpost=NR(~
30.0
kg/m
2)
Control:n
=61
(26%
males)
Age:5
0(1)years
BMIbaselin
e=32.3(4.8)kg/m
2
BMIpost=NR(~
32.2
kg/m
2)
Pooled
exercisers(n=110)
divided(m
ediansplit)into
compensators/non--
compensatorsbasedon
actual
andpredictedweightloss.
-Frequency:
3–5days/week
(self-selected)for24
weeks
-Intensity:6
5–85%
VO2peak
(self-selected)
-Ty
pe:treadmill
-Duration:
8KKW
~35
min/session
(~700kcal/week)
vs.20KKW
~55
min/session
(~1760
kcal/week)
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
yes;no
exercise
-Fo
odPreference
Questionnaire
[59]
preferencesforfood
classified
asalongside2components:fat(2factors:
HighFatand
Low
Fat)and
carbohydrate(3
factors:HighSimple
Sugar,HighCom
plex
CHO,and
Low
CHO/HighProtein)
-Setting:laboratory
-State:NR
-Measurementtim
epoints:w
eek0and
week24
-8KKW
groupincreasedpreference
for
high
fat/highCHOfoodswhereas
20KKW
groupdecreased.
-Com
pensatorsdecreasedpreferences
forhigh
CHO,low
fat,andlow
fat/highCHOfoodswhereas
non-compensatorsincreased.
-Differencebetweenliking/wanting:
NR
-Fo
odintake:adjusteddoubly-labeled
water
energy
intake
increasedin
both
exercise
groups
(relativeto
control
group).N
ochangesintestmealenergy
intake.
-Eatingbehavior
traits:greaterreduction
indisinhibition
innon-compensators
relativ
eto
compensators.
-Bodycomposition:
difference
inbody
massandbody
fatp
ercentageloss
between20
KKW
andcontrol.
Martin
setal.
2017
[60]
Norway
Sex:
females
andmales
BMIstatus:≥
30kg/m
2
PAlevel:inactive(<1day/week
MVPA
,<20
min/day
<3days/weeklight
PA)
HIIT:n
=16
(13completers;40%
males)
Age:3
4(8)years
BMIbaselin
e=33.2(3.5)kg/m
2
BMIpost=NR
-Frequency:
3days/weekfor12
weeks
-Intensity:H
IITand½
HIIT
(85–90%
HRmax),continuous
(70%
HRmax)
-Ty
pe:H
IITvs.½
HIITvs.
continuous
cycling
-Duration:
HIIT(8-sintervalsand
12-srecovery
for250kcal;
~20
min),½
HIIT(8-sintervals
-LFP
Q:relativepreference
(food
choice),lik
ingandim
plicitwantin
gbias
forfat/taste
-Setting:laboratory
-State:preandpostfixedbreakfast
(600
kcal)
-Measurementtim
epoints:w
eek0and
week12
-Noeffectof
exercise
onlikingor
wantin
g-Differencebetweenlik
ing/wantin
g:no
-Fo
odintake:n
ochange
[61]
-Eatingbehavior
traits:N
R-Bodycomposition:
reductionin
body
weightand
trunkandleg%
fatm
ass
[61]
Curr Obes Rep (2020) 9:63–8072
Tab
le1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
½HIIT:n
=16
(9completers;
80%
males)
Age:3
4(7)years
BMIbaselin
e=32.4(2.9)kg/m
2
BMIpost=NR
Contin
uous:n
=14
(13
completers;60%
males)
Age:3
3(10)
years
BMIbaselin
e=33.3(2.4)kg/m
2
BMIpost=NR
and12-srecovery
for125kcal;
~10
min),continuous
exercise
(250
kcal;~
32min).
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
no;H
IITvs.½
HIITvs.contin
uous
Miguetetal.
under
review
France
Sex:
females
andmales
(adolescents)
BMIstatus:≥
95th
percentilefor
sexandage
PAlevel:inactive(<2h/week)
n=30
(23%
males)
Age:1
3(1)years
BMIbaselin
e=35.7(4.5)kg/m
2
BMIpost=30.9(5.0)kg/m
2
-Frequency:
4days/weekfor
10months
-Intensity:N
R-Ty
pe:v
arious
(aerobic,strength,
aquatic
andleisure-tim
eactiv
ities)
-Duration:
60min
-Tim
ing:
NR
-Su
pervision:
yes
-Control
group:
noAspartof
aninpatient
multidisciplinaryweightloss
program
-LFP
Q:likingandim
plicitwantin
gfor
HFS
W,L
FSW,H
FSA,L
FSA
-Setting:laboratory
-State:preandpostlunch(adlib
itum)
-Measurementtim
epoints:b
aseline,
5months,10
months
-Hungry:
Increase
inlik
ingat5months
follo
wed
bydecrease
at10
months
(sim
ilartobaselin
evalues).Nochange
inwanting.
-Fed:
Decreasein
likingat5and
10months.Nochange
inwantin
g.-Hungryto
fed:
Decreasein
likingat5
and10
months,butn
otbaselin
e.No
change
inwantin
g.-D
ifferencebetweenliking/wantin
g:yes;
decrease
inlik
ing,no
change
inwantin
g
-Fo
odintake:d
ecreasein
lunchEIat
10months
-Eatingbehavior
traits:d
ecreasein
uncontrolledeatingandem
otional
eatin
gat5and10
months
-Bodycomposition:
decrease
inpercentage
fatm
assat5and
10months
Riouetal.
2019
[62]
Canada
Sex:
females
(premenopausal)
BMIstatus:>
27kg/m
2
PAlevel:inactive
(<150min/week)
Low
intensity
:n=11
week
Moderateintensity
:n=10
Age:3
1(11)
years
BMIbaselin
e=35.1(6.2)kg/m
2
BMIpost=NR(~
35.5
kg/m
2)
-Frequency:
5days/weekfor
12–14weeks
-Intensity:L
OW
(40%
VO2reserve)
vs.m
oderate(M
OD;6
0%VO2reserve)
-Ty
pe:aerobic(treadmill
orcycle
ergometer)
-Duration:
to300kcal(LOW
~62
min,M
OD~46
min)
-Tim
ing:
NR
-Su
pervision:
3/5days
-Controlgroup:no;L
OW
vs.M
OD
-LFP
Q:likingandim
plicitwantin
gbias
forfat/taste
-Setting:laboratory
-State:postbreakfast/p
reexercise
(ad
libitu
mbreakfasto
nfirstsession
and
quantitiesreplicated
onsubsequent
sessions;L
OW
~648kcal,M
OD
~746kcal)andpostrest(w
eek4)
orexercise
(scheduled
session;
weeks
1and12–14)
-Measurementtim
epoints:w
eek4,week
1,andweek12–14(inlin
ewith
menstrualcycle)
-Decreasein
wantin
gforfatafter
training.
-Increaseinlikingforsavoryfoodspreto
post-exerciseatweek1butdecreaseat
week12–14.
-Differencebetweenliking/wantin
g:yes;
changesin
wantin
gbutn
otlik
ingfor
fatw
ithtraining
-Fo
odintake:n
ochange
-Eatingbehavior
traits:increasein
susceptib
ility
tohunger
-Bodycomposition:
groupby
time
interactionforbody
weightand
fat
massshow
ingincrease
inMODand
decrease
inLOW
Thiveletal.
2019
[63]
France
Sex:
females
andmales
(adolescents)
BMIstatus:>
90th
percentilefor
sexandage
PAlevel:NR
Eccentric:n
=12
(50%
males)
Age:1
4(1)years
BMIbaselin
e=34.8(5.5)kg/m
2
BMIpost=29.0(4.5)kg/m
2
Concentric:n=12
(50%
males)
-Frequency:
3days/weekfor12
weeks
(+2h/weekphysical
education)
-Intensity:5
0%up
to70%
VO2peak
-Ty
pe:eccentricvs.concentric
cycling
-Duration:
30up
to45
min
-Tim
ing:
NR
-Su
pervision:
yes
-LFP
Q:relativepreference
(food
choice),lik
ingandim
plicitwantin
gbias
forfat/sweet
-Setting:laboratory
-State:fasted
-Measurementtim
epoints:b
aseline,
week12
andweek24
-Eccentricgroup:
increase
inpreference
forhigh-fatfoodsandsavory
foods
(decreasein
sweetb
ias).Increasein
implicitwantingforsavory
foods
(decreasein
sweetb
ias).
-Group
bytim
einteractionshow
edconcentricgroupincreasedpreference
andim
plicitwantin
gforsw
eetfoods
whileeccentricdecreased.
-Fo
odintake:totaldaily
energy
intake
increasedinbothgroups
from
baselin
eto
week24,but
only
increasedin
concentricgroupfrom
week12
to24.
-Eatingbehavior
traits:N
R-Bodycomposition:
greaterpercentage
body
fatlossaftereccentricvs.
concentricexercise
from
week12
to24
Curr Obes Rep (2020) 9:63–80 73
showed a decrease in food reward after acute exercise com-pared with the sedentary control. McNeil and colleagues re-vealed a decrease in the preference for high-fat relative to low-fat food independently of the modality of exercise (aerobic orresistance) in inactive adults within the normal range of BMI[49]. Miguet and colleagues showed a decrease in implicitwanting for sweet relative to savory food in response to anad libitum meal after a session of high intensity interval exer-cise in inactive adolescents with obesity [50]. Interestingly, nochange in food intake was observed in the McNeil studywhereas a decrease in total energy intake (both lunch anddinner) was noted in the Miguet study. This might be relatedto the fact that changes in implicit wanting are a greater driverof food intake than changes in liking. Also, the McNeil studymight have been underpowered to detect a change in implicitwanting. Four studies showed no changes in food reward (fator taste bias for liking, relative preference or implicit wanting).One study compared eccentric vs concentric exercise on mod-erately active men (BMI 23.4 ± 3.3 kg/m2) and showed noeffect on either appetite sensations, appetite-related hormones,or food reward [43]. Three studies compared the intensity ofexercise (low versus high [51] or high- or moderate-intensityintermittent cycling [42, 48]). Two reported no effects on foodreward or food intake [48, 51] whereas one found a decreasein wanting and increase in liking after both high- andmoderate-intensity exercise [42]. Of note, these studies wereconducted in moderately active normal-weight adults [51] andinactive adults with overweight/obesity [42, 48]. A recentlycompleted study compared bouts of swimming or cycling to ano-exercise control in a within-subjects design (Thackrayet al. unpublished). While they found that energy intake wasincreased after swimming but not cycling compared with con-trol, no differences in food reward were detected except for atendency for a main effect of trial for implicit wanting fat biaswith wanting being smaller after cycling relative to swimmingand control. Lastly, Finlayson and colleagues demonstratedthat implicit wanting was increased in response to moderate-intensity exercise only in those individuals that increased theirenergy intake relative to no exercise (i.e., compensators) [47].Consequently, even with the samemethodology to assess foodreward, the response to acute exercise seems to be equivocaland subject to individual variability. This could be explainedby methodological issues; even though the same tool is used,the studies were conducted in different countries (UK, SaudiArabia, Canada, France, and Norway) and the food imagesused may not have been cross-culturally validated [68]. Thesample sizes were relatively small for most of the studies(ranging from 12 to 33), including mainly both genders andwith different ranges of BMI. However, it can be noticed thatexercise seems to affect food reward more clearly in inactiveindividuals compared with active ones in both adolescents andadults. One tentative hypothesis could be that inactive indi-viduals (within the non-regulated zone of the J-shape curve)T
able1
(contin
ued)
Reference
Participantcharacteristics
Exercise/physicalactiv
itydetails
Food
rewardmethod
Food
rewardresults
Associatio
nswith
appetiteoutcom
es
Age:1
3(1)years
BMIbaselin
e=31.8(3.8)kg/m
2
BMIpost=27.6(4.0)kg/m
2
-Control
group:
no;eccentricvs.
concentric
Phase2(w
eek12–24)
ofa24-w
eek
inpatient
multidisciplinary
weightlossprogram
-Differencebetweenliking/wantin
g:yes;
changesin
implicitwantingforsw
eet
foods,no
change
inlik
ing.
Dataaremeans
(SD).CoE
Q,C
ontrol
ofEatingQuestionnaire;F
MI,fatm
assindex;
fMRI,functio
nalm
agnetic
resonanceim
aging;
LFPQ,L
eeds
Food
Preference
Questionnaire;L
FSA
,low
-fatsavory;
LFSW
,low
-fatsw
eet;HFSA
,high-fatsavory;H
FSW
,high-fatsw
eet;HIIT,high-intensity
intervaltraining;MET,metabolicequivalent
ofatask;MVPA
,moderate-to-vigorousphysicalactiv
ity;N
R,n
otreported;PA,physicalactivity
;VAS,visualanalogue
scales;W
C,w
aistcircum
ference
Curr Obes Rep (2020) 9:63–8074
would benefit more from acute exercise than active individ-uals for whom the appetite control system is more sensitive.
Farah and colleagues used a computer-based task to mea-sure the effect of acute exercise on liking (visual analoguescale) and other non-homeostatic indicators (ideal portionsize, food utility, hunger) [46]. They found that a 60-minmoderate-intensity exercise bout reduced hunger and idealportion size but not liking. This is in concordance with previ-ous results showing that implicit wanting rather than liking
might be influenced by exercise. However, the physical activ-ity level of the participants was not reported, and implicitwanting was not measured.
Acute exercise has also been shown to have an effect on brainreward measured by BOLD response to food cues with fMRI.Evero and colleagues showed that a 60-min high-intensity exer-cise bout decreased the neuronal response to food cues in brainregions related to food reward, visual attention, and inhibitorycontrol [45]. Interestingly, regions related to both liking (i.e.,
Fig. 2 Conceptual model of the impact of habitual physical activity andexercise on appetite control. The model builds upon the relationshipbetween physical activity level, energy intake, and body fat recentlydemonstrated by Beaulieu et al. [19••]. Higher levels of physicalactivity are associated with enhanced satiety signaling—within a“regulated zone” of appetite control—resulting in a better matchingbetween energy intake and energy expenditure. Lower levels ofphysical activity are associated with higher body fat, weaker satietysignaling, and greater responsiveness to hedonic inputs from the foodenvironment—within a “non-regulated zone” of appetite control—allowing for overconsumption to occur and body fat to increase further.This review adds to this model by proposing effects of physical activity
on liking and wanting as processes of food reward. Specifically, lowerlevels of physical activity are associated with greater liking and wantingfor high-fat/high-energy food, with wanting as the stronger driver ofexcess energy intake. Acute exercise leads to a reduction in liking andwanting, especially in inactive individuals. As habitual levels of physicalactivity increase (including during chronic exercise interventions), thereis a small increase in liking and decrease in wanting that accompanyweight loss and improvement in appetite control. Finally, higher levelsof habitual physical activity (e.g., regular bouts of moderate-to-vigorousphysical activity) are associated with greater liking for low-fat/low-energy food and lower wanting for high-fat food
Fig. 1 The impact of a 12-weekaerobic exercise intervention(70% HRmax, 500 kcal/day,5 days/week) on liking andimplicit wanting for high-fat foodin weight loss non-compensators(n = 15), compensators (n = 15),and non-exercising controls (n =15) (Finlayson et al.unpublished). *p < 0.05,**p < 0.01, #p = 0.08, §p = 0.10
Curr Obes Rep (2020) 9:63–80 75
insula, orbitofrontal cortex) and wanting (i.e., putamen) werereduced after exercise. This is in line with another study thatfound that exercise increases neural responses in reward-relatedregions in response to images of low-calorie foods and sup-presses activation during the viewing of high-calorie foods[44]. These central responses were associated with exercise-induced changes in peripheral signals related to appetite controland hydration status. However, liking and implicit wanting werenot measured directly in these studies (i.e., behavioral measures)nor was food intake. Lastly, Saanikoji et al. found no effect of anacutemoderate-intensity aerobic exercise on brain food reward inlean men [52]. However, they showed that individuals who in-creased the most in endogenous opioid release had the highestbrain reward response after the exercise compared with the con-trol. Consequently, the opioid systemmight contribute to explainsome individual variability in the food reward responses toexercise.
Chronic Exercise Training Studies
As mentioned above, our recent systematic review on weightmanagement interventions found limited evidence on the im-pact of exercise interventions on food reward [6••]. Amongthe included studies, two investigated the impact of high-intensity interval exercise compared with either moderate-intensity interval training [53] or continuous training [60].Using a cross-over design, Alkahtani et al. [53] found that inresponse to acute exercise after a 4-week exercise interven-tion, liking for high-fat savory food seemed to increase afterMIIT and decrease after HIIT in men with overweight or obe-sity (interaction p = 0.09). Another study in individuals withobesity found no changes in food reward in response to abreakfast meal (hungry and fed states) after a 12-week inter-vention of either high-intensity interval exercise (125 or250 kcal, 3 days/week) or moderate-intensity continuous ex-ercise (250 kcal, 3 days/week) [60]. In another study, nochanges in liking or implicit wanting for high-fat relative tolow-fat food in the hungry state were observed after a 12-weekaerobic exercise intervention (500 kcal, 5 days/week), al-though a trend towards a reduction in wanting was noted[69]. However, more recent analyses with a non-exercisingcontrol group revealed that in response to a high-fat andhigh-carbohydrate fixed lunch (hungry and fed states), overallimplicit wanting decreased after the 12-week exercise inter-vention, whereas no changes in explicit liking were found[54]. This is corroborated by another study that found a de-crease in implicit wanting for high-fat relative to low-fat foodin women who underwent a 3-month exercise intervention(300 kcal, 5 days/week) [62]. When food reward was mea-sured in response to an exercise bout post-intervention in thatstudy, there was also a decrease in liking for savory foodswhereas liking for savory foods increase after acute exerciseat baseline. Thus, it appears that chronic exercise training may
modulate the food reward response to acute exercise in inac-tive individuals, also shown in an fMRI study [56].
Interestingly, changes in food reward in the study by Beaulieuet al. [54] were not associated with changes in body weight orcomposition, suggesting a potential independent effect of exer-cise. Indeed, an inverse association was found between changesin leptin (adjusted for percentage body fat) and changes in liking,but not wanting, for high-fat food [69]. Thus, leptin may have arole inmediating changes in food reward during exercise trainingin individuals with overweight/obesity. In contrast, a 6-monthexercise intervention led to a reduction in the fasted neuronalresponse to food compared with non-food, and some of thesechanges were associated with changes in fat mass, body weightand leptin [56]. These findings are interesting in light of theseminal study by Rosenbaum [70], who reported that leptin re-placement after > 10% weight loss using a liquid formula diet,modulated food cue-elicited neuronal activation in reward-related regions (consistent with wanting), but did not affect likingfor the diet. Beyond leptin, it is known that weight loss alsoimpacts fasting levels of ghrelin. For example, the RESOLVEstudy (NCT00917917) showed that long-term physical activitymay reverse the early enhancing effect of body weight loss onplasma ghrelin [71]. Future studies should examine whether fa-vorable effects of exercise-induced weight loss on food rewardcan be partly explained by modulation of ghrelin as well asleptin.
Differences in food preferences have also been found be-tween individuals who compensated (less than expectedweight loss based on median split) compared with non-compensators during a 6-month intervention expending either~ 700 kcal/week or ~ 1760 kcal/week [58]. Compensators hadreduced preference for low-fat and high-carbohydrate foodrelative to non-compensators. Indeed, the hedonic responseto acute exercise also appears to impact weight loss outcomesduring chronic exercise training [57]. We have shown thatafter acute exercise, liking for all foods and wanting forhigh-fat sweet food increased only in compensators to a 12-week exercise intervention (those who achieved less than ex-pected weight loss), compared with no change in non-compensators (those achieving at or above expected weightloss). These differences were independent of the exercise in-tervention and weight loss [57] and add to other evidence ofimproved appetite control in this group [72]. In a further un-published study from our laboratory where sub-groups of 12-week exercise intervention non-compensators and compensa-tors were compared with a non-exercising control group(Fig. 1), we observed that prior to the exercise intervention,compensators showed a strong liking and wanting for high-fatfood whereas non-compensators showed no difference be-tween high-fat and low-fat food. Secondly, we found that thegreater reward for high-fat food in compensators reduced fol-lowing the exercise intervention, compared with no change incontrols. Lastly, there appeared to be a unique pattern of
Curr Obes Rep (2020) 9:63–8076
change in liking and wanting in the non-compensators whoshowed a small increase in liking for high-fat food after exer-cise training, but a simultaneous decrease in wanting for high-fat food.
In adolescents with obesity, eccentric cycling exercise as partof a 12-week inpatient multidisciplinary weight loss interventionincreased the relative preference for high-fat food and increasedboth the relative preference and implicit wanting for savory food,whereas no changes were observed in response to concentricexercise training [63]. Another study in adolescents with obesityshowed that during a 10-month inpatient multidisciplinaryweight loss intervention including physical activity, liking forfood in the hungry state increased from baseline to 5 months,then returned to baseline values at 10 months, whereas liking forfood in the fed state decreased (Miguet et al., under review).There were no changes in wanting observed.
These studies are suggestive that chronic exercise improvesfood reward (reduced response to high-energy foods and in-creased response to low-energy foods). However, the effectsizes were relatively small and inter-individual variabilitytended to be large. Two studies found a reduction in implicitwanting for high-fat relative to low-fat foods after exercisetraining [54, 62]. This may be a result of a direct effect ofexercise on brain regions related to food reward, as shownby the fMRI studies included in the current review, and others[73, 74]. Furthermore, as exercise affects cognition and exec-utive function, it has been proposed that processes such asinhibitory control could have a moderating effect on wantingand modulate eating behavior [66].
Another two studies found an increase in liking after exer-cise training, which might be explained by concomitant im-provements in homeostatic appetite control in these studies (asmall increase in hunger or a reduction in fasting leptin con-centrations). Individual differences in food reward appear toact as pre-existing moderators of the impact of exercise train-ing on weight loss and suggest that those with healthier pref-erences or better satiety signaling at baseline appear to losemore weight with exercise. No clear evidence exists regardingthe optimal mode, frequency, intensity, duration, and time ofday for exercise to have the most impact on food reward.Further systematic research into these factors is warranted.
Conclusions
One of the perceived barriers for engaging in exercise is itspotential to promote hedonic eating. Food reward plays animportant role in weight management through its interveningstatus between the nutrient requirements of the body and he-donic inputs from the food environment that promote foodintake. This review brings together current evidence from ob-servational, acute, and chronic exercise training studies to in-form public debate on the impact of physical activity on food
reward. A conceptual model, building on previous theory[19••] is shown in Fig. 2. Observational studies show thatperformance of moderate-to-vigorous physical activity is as-sociated with lower liking and wanting for high-fat or high-energy food, and higher liking for low-fat/low-energy food.These findings may reflect improved appetite control and aresupported by evidence from chronic exercise training inter-ventions. Where exercise training leads to successful weightloss, it appears to be accompanied by a dissociation betweenliking and wanting evidenced by a reduction in wanting forhigh-energy food but increase in liking for low-energy food.Acute bouts of exercise tend to only impact behavioral indicesof food reward in less active individuals or those with poorappetite control, where it tends to result in reduced food re-ward. These findings are corroborated by observational stud-ies that demonstrate greater liking and especially wanting forhigh-energy foods (and greater susceptibility to food cravings)in inactive individuals. Food reward does not counteract thebenefit of physical activity for obesity management. Rather,exercise appears to accompany positive changes in food pref-erences in line with improvements in appetite control.
Compliance with Ethical Standards
Conflict of Interest The authors declare no conflict of interest.
Human and Animal Rights and Informed Consent This article does notcontain any studies with human or animal subjects performed by any ofthe authors.
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