Effects of the FITKids Randomized Controlled Trial onExecutive Control and Brain Function

WHAT’S KNOWN ON THIS SUBJECT: Physical activity programshave been shown to have positive implications for children’scognitive performance and brain structure and function. However,additional randomized controlled trials are needed to determinewhether daily physical activity influences executive control and itsneural underpinnings.

WHAT THIS STUDY ADDS: The randomized controlled trial,designed to meet daily physical activity recommendations, usedbehavioral and electrophysiological measures of brain function todemonstrate enhanced attentional inhibition and cognitiveflexibility among prepubertal children.

abstractOBJECTIVE: To assess the effect of a physical activity (PA) interventionon brain and behavioral indices of executive control in preadolescentchildren.

METHODS: Two hundred twenty-one children (7–9 years) were randomlyassigned to a 9-month afterschool PA program or a wait-list control. Inaddition to changes in fitness (maximal oxygen consumption), electricalactivity in the brain (P3-ERP) and behavioral measures (accuracy, reactiontime) of executive control were collected by using tasks that modulatedattentional inhibition and cognitive flexibility.

RESULTS: Fitness improved more among intervention participants frompretest to posttest compared with the wait-list control (1.3 mL/kg perminute, 95% confidence interval [CI]: 0.3 to 2.4; d = 0.34 for groupdifference in pre-to-post change score). Intervention participantsexhibited greater improvements from pretest to posttest in inhibition(3.2%, 95% CI: 0.0 to 6.5; d = 0.27) and cognitive flexibility (4.8%, 95%CI: 1.1 to 8.4; d = 0.35 for group difference in pre-to-post change score)compared with control. Only the intervention group increased atten-tional resources from pretest to posttest during tasks requiring in-creased inhibition (1.4 mV, 95% CI: 0.3 to 2.6; d = 0.34) and cognitiveflexibility (1.5 mV, 95% CI: 0.6 to 2.5; d = 0.43). Finally, improvements inbrain function on the inhibition task (r = 0.22) and performance on theflexibility task correlated with intervention attendance (r = 0.24).

CONCLUSIONS: The intervention enhanced cognitive performance andbrain function during tasks requiring greater executive control. Thesefindings demonstrate a causal effect of a PA program on executive con-trol, and provide support for PA for improving childhood cognition andbrain health. Pediatrics 2014;134:e1063–e1071

AUTHORS: Charles H. Hillman, PhD,a Matthew B. Pontifex,PhD,b Darla M. Castelli, PhD,c Naiman A. Khan, PhD, RD,a

Lauren B. Raine, BS,a Mark R. Scudder, BS,a Eric S.Drollette, BS,a Robert D. Moore, MS,a Chien-Ting Wu, PhD,d

and Keita Kamijo, PhDe

aDepartment of Kinesiology and Community Health, Universityof Illinois at Urbana-Champaign, Urbana-Champaign, Illinois;bDepartment of Kinesiology, Michigan State University, EastLansing, Michigan; cDepartment of Kinesiology and HealthEducation, University of Texas at Austin, Austin, Texas;dDepartment of Exercise Science, Schreiner College, Kerrville,Texas; and eSchool of Sport Sciences, Waseda University,Tokorozawa, Saitama, Japan

KEY WORDScognition, physical activity, aerobic fitness, randomized controlledtrial

ABBREVIATIONSANOVA—analysis of varianceCI—confidence intervalERP—event-related brain potentialFITKids—Fitness Improves Thinking in KidsHR—heart rateMVPA—moderate to vigorous physical activitySES—socioeconomic statusRT—reaction timeVO2peak—maximal oxygen consumption

Dr Hillman conceptualized and designed the study, drafted theinitial manuscript, and critically reviewed the manuscript;Dr Pontifex coordinated and supervised data collection andreduction. He assisted in revising the initial manuscript andcritically reviewed the manuscript; Dr Castelli conceptualizedand designed the physical activity intervention, assisted inrevising the initial manuscript, and critically reviewed themanuscript; Dr Khan, Ms Raine, Mr Scudder, Mr Drollette,Mr Moore, Dr Wu, and Dr Kamijo coordinated and superviseddata collection and reduction. They also assisted in revising theinitial manuscript and critically reviewed the manuscript; andall authors approved the final manuscript as submitted.

This trial has been registered at www.clinicaltrials.gov(identifier NCT01334359).

www.pediatrics.org/cgi/doi/10.1542/peds.2013-3219

doi:10.1542/peds.2013-3219

Accepted for publication Jul 25, 2014

Address correspondence to Charles H. Hillman, PhD, Departmentof Kinesiology and Community Health, University of Illinois atUrbana-Champaign, 317 Louise Freer Hall, 906 South GoodwinAve, Urbana, IL 61801. E-mail: chhillma@illinois.edu

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2014 by the American Academy of Pediatrics

(Continued on last page)

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The pandemic of physical inactivity isa serious threat to global public health1

accounting for ∼10% of all prematuredeaths from noncommunicable dis-eases.2 Despite evidence that such in-activity detrimentally affects brain healthand aspects of cognition known as ex-ecutive control (also called cognitivecontrol) in older adult populations,3,4 thisarea remains understudied in children.This is concerning because childhood ischaracterized by extensive changes inbrain structure, function, and connec-tivity.5 Thus, an active lifestyle duringchildhoodmay have protective effects onbrain health across the lifespan, as is thecase for physical health. However, thespecific effects of physical activity (PA)on key cognitive processes and theirneural underpinnings remain unknown.

Executive control, which consists of in-hibition (resisting distractions or habitsto maintain focus), working memory(mentally holding and manipulatinginformation), and cognitive flexibility(multitasking), isvital tosuccessinschool,vocation, and life.6 Cross-sectional stud-ies7,8 have demonstrated that aerobicfitness is positively related to executivecontrol, with more fit children exhibitingsuperior attention, decision-making abil-ity, and differential brain function com-pared with their lesser-fit peers. Inparticular, event-related brain potentials(ERPs), derived from an EEG, allow forthe real-time measurement of changesin electrical activity in brain functionwhile children performed cognitive tasks.The most common way that brain ac-tivity is captured in an ERP is throughthe measurement of the various peaksof the waveform. A peak commonlyused to assess brain activity is the P3,which has been robust in demonstrat-ing differences between individuals ofhigher and lower fitness during tasksthat tap executive control. The P3 re-flects neuronal activity thought to beassociated with the processes of at-tention and working memory,9 and can

be assessed relative to its size (measuredin amplitude) and its timing (measured inlatency). That is, larger P3 amplitudereflects greater allocation of attentionalresources,10 and faster P3 latency re-flects faster cognitive processing speed.11

Our laboratory has previously demon-strated fitness-related differences inP3 such that higher-fit children exhib-ited larger P3 amplitude and shorterP3 latency, indicating greater atten-tional resource allocation and fastercognitive processing speed, respec-tively.7,8 Therefore, differences in fitnessaccount for a portion of the variabilityobserved in executive control and un-derlying brain function in preadolescentchildren.

Despite available correlational evidence,few have manipulated PA or aerobicfitness among children to investigatetheir effects on executive control and itsneural underpinnings.12–15 In addition, itremains unknown whether attendancein a PA program correlates with mea-sures of executive control. Consequently,we investigated the effects of a 9-monthrandomized controlled PA trial (FitnessImproves Thinking in Kids [FITKids]) onbrain and behavior during tasks re-quiring attentional inhibition and cogni-tive flexibility. We hypothesized that,relative to the wait-list control group, theFITKids intervention would result in (1)improvements in behavioral perfor-mance, (2) increased attention allocation(measured via P3 amplitude), and (3)faster cognitive processing speed (mea-sured via P3 latency). Finally, we pre-dicted a positive correlation betweenparticipation in the intervention andimprovements in the cognitive outcomes.

METHODS

Study Design

Participants were randomly assignedto either the FITKids afterschool PAprogram (intervention group) orawait-list control group. Randomization wasperformed by a staff member who was

not involved in the data collection. Therandomization procedure was per-formed only after all participants hadbeen recruited and group allocationwas concealed from the research/datacollection team. Due to the inclusion ofsiblings among 10 families, noninde-pendent observations were included. Assuch, analyses were rerun by using arandomly selected sibling from eachfamily. Thefindings remainedunchangedfromthoseincludedintheresultssection.After baseline testing, pairs of partic-ipants were matched for age, gender,race, socioeconomic status (SES), andVO2max, and a coin was flipped by theindependent researcher to determinegroup assignment. All participants com-pleted a 2-day protocol of testing atbaseline (pretest) and postintervention(posttest). The studywas conducted overthe fall and spring semesters of theschool years between 2009 and 2013. Theinstitutional review board at the Univer-sity of Illinois approved the study pro-tocol. Parents provided written informedconsent, and participants provided writ-ten assent.

Participants

Eligible participants were 8- to 9-year-olds residing in East Central Illinois.This age range was chosen based onpreliminary research investigating fit-nessandpreadolescentcognition,whichfound reliable differences in neuro-imaging, behavioral, and academicachievement test performance occur at,or before, this age range. Four hundredseventy-fivechildrenwerescreened,and221 childrenwere randomly assigned toeither study group (Fig 1). The exclusioncriteria included special educationalservices related to cognitive or atten-tional disorders, neurologic diseases,and physical disabilities.

Study Procedures

Outcome assessors were blinded togroupassignment throughoutall testing.

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On the first visit, demographic infor-mation, including age, gender, race/ethnic group, and SES were collected.16

SES was determined by using a tri-chotomous index based on the following:(1) participation in free or reduced-pricemeal program at school, (2) the highestlevel of education obtained by themother and father, and (3) number ofparents who worked full-time.16 Partic-ipants completed the Kaufman Brief In-telligence Test17 to assess IQ, a TannerStaging System questionnaire to assesspubertal status,18 and the PA ReadinessQuestionnaire19 to screen for health is-sues exacerbated by physical exercise.Participants were then fitted with a Po-lar heart rate (HR) monitor (Model A1,Polar Electro, Finland), had their heightand weight measured by using a TanitaWB-300 Plus digital scale and stadiometer(Tanita Corp, Tokyo, Japan), and com-pleted a maximal exercise test to as-sess aerobic fitness. On the secondvisit, participants performed cognitivetasks assessing attentional inhibitionand cognitive flexibility while fitted withan EEG cap (Compumedics, Inc, Charlotte,

NC). Participants were then randomlyassigned to the FITKids intervention orthe wait-list as described earlier. Aftercompletion of the intervention, partic-ipants returned to the laboratory fortheir posttest assessments, which wasidentical to the baseline assessment.

Aerobic Fitness Assessment

Aerobic fitness was assessed by usinga test of maximal oxygen consumption(VO2peak; see Supplemental Information).This test employed a computerized in-direct calorimetry system while partic-ipants ran/walked on a motor-driventreadmill at a constant speed with in-cremental grade increases every 2minutes until volitional exhaustion.20

Aerobic fitness percentiles were de-termined by using normative values forVO2peak.21

Cognitive Tasks

Response accuracy and reaction time(RT) were collected to assess behav-ioral performance on the attentionalinhibition and cognitive flexibility tasks.

Attentional inhibition was assessed byusing a modified flanker task,22,23 andcognitive flexibility was assessed byusing a color-shape switch task.24 Amodified flanker task is a method tomeasure inhibition in which childrenare engaged in a series of trials that, inthis case, have arrays of fish that eithermatch (ie, congruent arrays) or do notmatch (ie, incongruent arrays). The taskis to press either the right or left buttonas quickly and accurately as possiblebased on the direction in which themiddle fish is facing. Task difficulty ismanipulated by whether the flankingfish face the same direction or the op-posite direction to the middle fish. Thecolor-shape switch task is a measure ofcognitive flexibility, in which children areshown characters of different shapes(ie, square, circle) and color (ie, blue,green), and are asked to make a singlejudgment (ie, homogeneous task condi-tion) via a button press about eithershape or color. Next, they are asked toflexibly switch their decisions aroundboth shape and color creating a moredifficult decision process (ie, heteroge-neous task condition). The task con-ditions that require the greatest amountof executive control are the incongruentcondition in the flanker task and theheterogeneous condition in the switchtask (see Supplemental Information). Inaddition to behavioral measures, EEGactivity was collected during the cognitivetasks from64 electrode sites to derive theP3 amplitude and latency measures (seeSupplemental Information).

PA Intervention

The 2-hour PA intervention occurred ata recreational facility on the Universityof Illinois campus after each school day,and focusedon improvement of aerobicfitness through engagement in a varietyof age-appropriate physical activities.Children intermittently participated inat least 70-minutes of moderate-to-vigorous PA (recorded by E600 PolarHRmonitors;PolarElectro).Specifically,

FIGURE 1Flow diagram of the FITKids intervention.

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the intervention included ∼30 to 40minutes at PA stations. Next, a healthysnack and educational component wereprovided as a rest period, and childrenthen engaged in low organizationalgames (45–55 minutes) centered on askill theme (see Supplemental Infor-mation). The activities were aerobicallydemanding, but simultaneously providedopportunities to refine motor skills. Theprogram was offered 150 days of the170-day school year.

Statistical Analysis

Assuming a small effect size (d = 0.3),reliability of the within-subjects factor(r = 0.8), 2-sided a of 0.05, and 80%power, the required sample size was90 to 100 participants per group. Theprimary outcomes assessed were be-havioral and brain function indices ofperformance in response to the flankerand switch tasks. Analyses were con-ducted by using a 2 (group: intervention,wait-list) 3 2 (time: pretest, posttest)multivariate repeated measures analy-sis of variance (ANOVA) with additionalvariables nested within the primaryanalytical procedure based on the out-come variable. Analysis of behavioralmeasures (response accuracy, RT) wasconducted separatelywithin 2 conditions

(congruency: congruent, incongruent)for the flanker task and within 2 con-ditions (switch: homogeneous, hetero-geneous) for the switch task. The P3ERP component was assessed sepa-rately for amplitude and latency withinthe same 2 conditions for each task. Toaccount for missing data, multiple im-putation was performed by using PASWStatistics, 19.0 to impute 20 values foreach missing observation. Analyseswere performed by using the combinedmultivariable modeling estimates. Allstatistical analyses were conductedwitha = 0.05 by using the Greenhouse-Geisser statistic with subsidiary uni-variate ANOVAs and Tukey’s honestsignificant difference tests for posthoccomparisons. Findings reported hereinare restricted to only those related tothe intervention. For a more completestatistical summary, please refer to theSupplemental Information.

RESULTS

Participants

Demographic data are provided inTable 1. Over half of the participants inboth groups were white, and over 40%of the participants were categorizedas low SES. At baseline, there were no

significant differences between interven-tion and wait-list control groups relativeto age (20.08 years, P = .32), pubertaltiming (20.05, P = .48), aerobic fitness(21.73 mL/kg per minute, P = .07), BMI(0.2, P = .73), or IQ (22.5, P = .17).

Intervention Participation

Participants in the FITKids afterschoolprogram attended 80.6% (615.1) of thesessions. Mean HR during these sessionswas ∼137 beats per minute (68.3) withchildren taking ∼4246 steps (61039.9;see Supplemental Information).

Changes in Aerobic Fitness andWeight Status

Although both groups increased inaerobic fitness, the intervention groupdemonstrated a greater improvementfrom pretest to posttest than the wait-list control group (1.5 mL/kg per min-ute, 95% confidence interval [CI]: 0.5 to2.5, d = 0.39 for group difference in pre-to-post change score). Furthermore,pre- to posttest change in aerobic fit-ness percentile was significant onlyamong intervention participants (5.5 per-centile, 95% CI: 1.9 to 9.1, d = 0.42 for inter-vention group pre-to-post change score)and not among wait-list participants

TABLE 1 Mean (95% CI) Values for Participant Demographic Data

Measure Intervention Wait-list

Pretest Posttest Change Pretest Posttest Change

N 109 — — 112 — —

Gender (% girls) 53 (49)a — — 49 (44)a — —

Race, n (%)Asian 17 (15)a — — 12 (11)a — —

African American 25 (23)a — — 28 (25)a — —

White 51 (47)a — — 59 (53)a — —

Other or mixed-race 16 (15)a — — 13 (11)a — —

Hispanic 10 (9.2)a — — 5 (4.5)a — —

Low SES 43 (39.5)a — — 49 (43.8)a — —

Age, y 8.8a (8.7 to 8.9) 9.5b (9.4 to 9.6) 0.7a (0.6 to 0.7) 8.8a (8.7 to 8.9) 9.5b (9.4 to 9.7) 0.7a (0.7 to 0.8)Pubertal timing 1.4a (1.3 to 1.5) 1.5b (1.4 to 1.6) 0.1a (0.0 to 0.2) 1.5a (1.4 to 1.6) 1.6b (1.5 to 1.7) 0.1a (0.0 to 0.2)IQ (K-BIT composite) 109.8a (107.2 to 112.4) 111.8b (109.2 to 114.3) 2.0a (0.3 to 3.6) 112.6a (109.9 to 115.4) 116.5b (113.7 to 119.3) 3.9a (2.0 to 5.8)Attention-deficit/hyperactivitydisorder-IV composite

42.8a (37.0 to 48.5) 42.3a (36.6 to 47.9) 20.5a (25.8 to 4.8) 44.3a (38.7 to 49.8) 46.2a (40.4 to 51.9) 1.9a (22.7 to 6.5)

BMI 19.1a (18.3 to 19.9) 19.3a,b (18.4 to 20.2) 0.2a (0.0 to 0.5) 18.9a (18.1 to 19.7) 19.8b (18.9 to 20.7) 0.9b (0.6 to 1.2)VO2peak (mL/kg/min) 37.5a (36.2 to 38.8) 39.5b (38.2 to 40.8) 2.1a (1.2 to 2.9) 39.2a (37.9 to 40.5) 39.9b (38.6 to 41.3) 0.7b (0.1 to 1.4)VO2peak percentile 17.5a (13.8 to 21.3) 23.2b (18.5 to 27.8) 5.6a (2.0 to 9.3) 21.9a,c (17.7 to 26.2) 22.8b,c (18.5 to 27.0) 0.8b (21.8 to 3.4)

K-BIT, Kaufman Brief Intelligence Test. Data are presented as mean (95% CI) unless noted otherwise. Values sharing a common superscript are not statistically different at a = 0.05.

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(0.5 percentile, 95% CI:22.0 to 3.0, d = 0.06for wait-list group pre-to-post changescore). Both groups also increased inBMI; however, the wait-list group dem-onstrated a greater increase than theintervention group (0.5 kg/m2, 95% CI:0.2 to 0.9, d = 0.37 for group differencein pre-to-post change score).

Changes in Attentional Inhibition

Pre- and posttest performance is sum-marized in Table 2. Although responseaccuracy increased in both groups, theintervention group demonstrated greaterimprovement from pretest to posttestthan the wait-list control group (3.2%,95% CI: 0.0 to 6.5, d = 0.27 for group dif-ference in pre-to-post change score;Fig 2). However, there was no influenceof group assignment on RT (P $ .18).

Only the intervention group demon-strated increased P3 amplitude frompretest to posttest on incongruent trials(1.4 mV, 95% CI: 0.3 to 2.6, d = 0.34 forintervention group pre-to-post changescore; Fig 3; also Supplemental Fig 9in the Supplemental Information), anda greater change in P3 amplitude onincongruent trials from pretest to post-test relative to the wait-list group(1.9 mV, 95% CI: 0.3 to 3.5, d = 0.31 forgroup difference in pre-to-post changescore). The intervention group demon-strated faster P3 latency for incongruenttrials at posttest relative to pretest (20.1milliseconds, 95% CI: 2.6 to 37.6, d = 0.31for intervention group pre-to-post changescore), and a greater change in P3 la-tency frompretest to posttest relative tothe wait-list group (32.0 milliseconds,95% CI: 6.9 to 57.2, d = 0.34 for groupdifference in pre-to-post change score).

Changes in Cognitive Flexibility

Although both groups increased in pre-to posttest performance on homoge-nous and heterogeneous trials, theimprovement in performance on theheterogeneous taskwasgreateramongintervention participants (4.8%, 95% CI: TA

BLE2

Mean(95%

CI)Values

forTask

Performance

Measure

Intervention

Wait-list

Pretest

Posttest

Change

Pretest

Posttest

Change

Flankertask

Response

accuracy

(%)

Congruenttrials

78.6a(76.3to80.9)

85.8b(84.0to87.5)

7.1a

(4.7to9.6)

82.3c(80.2to84.5)

85.6b(83.5to87.6)

3.2b

(1.0to

5.5)

Incongruenttrials

72.1a(69.8to74.5)

78.9b(76.9to81.0)

6.8a

(4.2to9.5)

75.5c(73.5to77.6)

79.9b(77.5to82.2)

4.3a

(2.0to

6.7)

Alltrials

75.4a(73.2to77.6)

82.4b(80.6to84.2)

7.0a

(4.6to9.4)

79.0c(77.0to81.0)

82.7b(80.6to84.8)

3.8b

(1.6to

5.9)

RT(m

s)Congruenttrials

504.0a

(481.8to526.3)

467.1b

(450.9to

483.3)

236.9a(2

54.6to219.3)

522.2a

(501.8to

542.7)

478.1b

(459.5to496.7)

244.2a(2

64.5to223.8)

Incongruenttrials

531.6a

(507.4to555.9)

502.2b

(484.8to

519.5)

229.5a(2

49.7to29.2)

552.3a

(529.9to

574.7)

508.2b

(489.0to527.5)

244.1a(2

66.1to222.0)

Alltrials

517.2a

(494.2to540.1)

483.8b

(467.2to

500.4)

233.3a(2

51.9to214.7)

536.7a

(515.5to

557.8)

492.5b

(473.7to511.2)

244.2a(2

65.0to223.3)

Switchtask

Response

accuracy

(%)

Homogeneous

trials

87.7a(86.3to89.0)

89.9b(88.7to91.0)

2.2a

(0.7to3.8)

87.8a(86.4to89.1)

90.2b(89.1to91.3)

2.4a

(1.1to

3.7)

Heterogeneoustrials

65.9a(63.2to68.6)

76.6b(74.3to78.9)

10.7a(8.2to13.3)

69.0a(66.6to71.4)

75.0b(72.6to77.4)

6.0b

(3.3to

8.6)

RT(m

s)Homogeneous

trials

792.3a

(760.5to824.2)

754.9b

(721.2to

788.7)

237.4a(2

70.1to24.7)

816.8a

(786.0to

847.6)

759.5b

(730.6to788.5)

257.2a(2

90.2to224.3)

Heterogeneoustrials

1385.4a(1328.7to1442.1)

1407.1a(1362.4to1451.9)

21.7a(2

39.2to82.7)

1475.4a(1426.8to1524.1)

1435.1a(1389.2to1481.0)

240.4a(2

98.9to18.1)

Values

sharingacommon

superscriptarenotstatisticallydifferent

ata=0.05.

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1.1 to 8.4, d = 0.35 for group differencein pre-to-post change score; Fig 2). Anincrease in P3 amplitude to the het-erogeneous trials from pretest toposttest was observed only for the in-tervention group (1.5 mV, 95% CI: 0.6 to2.5, d = 0.43 for intervention group pre-to-post change score), with a greaterchange in P3 amplitude relative to thewait-list group (1.4 mV, 95% CI: 0.0 to2.7, d = 0.27 for group difference in pre-to-post change score; Fig 3; also Sup-plemental Fig 10 in the Supplemental

Information). No influence of groupassignment was observed for homo-geneous trials or P3 latency (P $ .06).

Attendance and Cognitive TaskPerformance

Attendance in the FITKids interventionwas positively correlated with changein P3 amplitude (r = 0.22, P = .02) andnegatively correlated with change in P3latency (r =20.22, P = .02) from pre- toposttest, only for incongruent flankertask trials requiring greater amounts

of inhibitory control. No such relation-shipwas observed for congruentflankertask trials requiring lesser amounts ofinhibitory control. A similar relationshipwas observed for behavioral indices ofthe task-switching task, such that at-tendance was positively correlated withchange in task performance on themore demanding heterogeneous condi-tion necessitating increased inhibition,working memory, and cognitive flexibil-ity (r = 0.24, P = .01), with no such effectrealized for the homogeneous conditionrequiring lesser amounts of executivecontrol (Fig 4).

DISCUSSION

The provision of a 9-month randomizedcontrolled PA intervention, directedtoward increasing aerobic fitness, sig-nificantly improved brain and behav-ioral indices of executive control. Moreimportantly, these effects were selec-tive to aspects of cognition that requiredextensive inhibition and cognitive flexi-bility, with no changes observed for taskcomponents requiring lower-order (ie,nonexecutive) aspects of cognition. Fur-ther, the fitness-related benefits appearto follow a dose–response relationship,as higher attendance rate in the FITKidsprogram was associated with largerchanges in neural indices of attention (ie,P3 amplitude), processing speed (P3 la-tency), and improved performance dur-ing the executive control tasks. Given thatno significant differences were observedfor children assigned to the wait-listcontrol, the key implication from thisstudy is that participating in a daily,afterschool PA program enhances ex-ecutive control.

Previous randomized controlled trialsin this area have varied in outcomesstudied, methodologies, and participantcharacteristics.12–15 Among overweightchildren, Davis et al12 demonstrateddose–response benefits of exercise onexecutive function andmath achievement.Further, functional MRI results revealed

FIGURE 2Change in response accuracy (mean6 SE) from pre- to posttest as a function of group and cognitivetask.

FIGURE 3Topographic scalp distribution of the change in P3 amplitude (spectrum scale: blue to red) during theflanker task (top) and switch task (bottom) is illustrated for the intervention group (left) and wait-listgroup (right). As shown, P3 amplitude was greater in the intervention group at posttest only for theconditions that required the greatest amount of executive control across both tasks as denoted by thegreater amount of red depicted in the electrophysiological plots representing brain function.

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increased prefrontal and reduced pos-terior parietal cortex activity during anantisaccade task. In a similar sample,Krafft et al15 found that an exerciseintervention increased activation in re-gions involved in flanker accuracy in-cluding the anterior cingulate cortexand the superior frontal gyrus. Amonga sample that varied in weight status,Chaddock-Heyman et al14 observed thatchildren receiving a PA interventionimproved performance on a flankertask and showed anterior frontal brainpatterns and incongruent task perfor-mance similar to that of college-agedadults after the intervention. This pat-tern of results was not observed in thepreadolescent wait-list control group.In a similar sample, Kamijo et al13 ob-served that daily PA improved workingmemory performance and increasedfrontal electrophysiological indices (ie,initial contingent negative variation)

associated with improvements in theexecutive control of working memoryafter a 9-month PA intervention. Theresults from the current study arebroadly consistent with the aforemen-tioned studies revealing that daily PAnot only improves aerobic fitness butalso enhances brain function and be-havioral sequelae during tasks thatrequire extensive amounts of executivecontrol among prepubertal children. Inaddition, the current study extendsthese findings to electrophysiologicalindices of cognitive flexibility, a novelcontribution to the literature.

Furthermore, the dose–response re-lationship observed between attendancerate, brain function, and executive con-trol demonstrates that brain and be-havioral changes resulted as a functionof the degree of participation in the PAprogram. These results are consistentwith Krafft et al25 who observed that

attendance in an 8-month exercise pro-gram was positively associated withimproved white matter integrity amonga group of sedentary and overweight(BMI $ 85th percentile) 8- to 11-year-olds (94% African American). However,the findings from the current studyprovide further support for the impor-tance of PA program attendance forcognitive benefit among a large hetero-geneous sample of children with varyingweight status. Given that health factors(physical inactivity, excess adiposity)have been related to absenteeism,26 thefindings herein indicate that increasedtime spent engaging in PA improves bothphysical and brain health, which hasbroad public health implications for ef-fective functioning across the lifespan.

Although children in the FITKids inter-vention exhibited greater improvementsin executive control relative to their wait-list control counterparts, there are somelimitations of the current study. The useof a wait-list control renders it difficultto attribute the observed group differ-ences entirely to the PA participationbecause other aspects of the programsuch as the educational component,social interaction with peers and inter-vention staff, and refining motor skillsmay have contributed to the results.However, it is unlikely that the educa-tional componentwas thecauseof groupdifferences, given that it was brief andtook place as part of the instruction forthe PA intervention (see SupplementalInformation). Another limitation of thestudy was that nonintervention PA wasnot measured. Therefore, we are unableto adjust for any influence of habitual PAon the findings. Future research wouldbenefit from study designs that includeactive control groups and account forthe potential influence of lifestyle factorssuch as habitual PA.

CONCLUSIONS

Participation in the FITKids interventionimproved aerobic fitness, as well as

FIGURE 4Scatterplots of the relationship between attendance at the FITKids afterschool PA program and pre- toposttest change in P3 amplitude to the incongruent condition of theflanker task (A), change in P3 latencyto the incongruent condition of the flanker task (B), change in response accuracy for the homogenouscondition of the switch task (C), and change in response accuracy for the heterogeneous condition of theswitch task (D).

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brain and behavioral indices of ex-ecutive control among prepubertalchildren. Importantly, these effectswere selective to aspects of cognitionthat required extensive inhibition andcognitive flexibility. Given the rapiddecline in PA opportunities for chil-dren at school, the dissemination ofour findings is particularly importantfor educators and policy makers.Specifically, policies that reduce orreplace PA opportunities during theschool day (eg, recess), in an attemptto increase academic achievement,

may have unintended effects.27 In-deed, the current data not onlyprovide causal evidence for the ben-eficial effects of PA on cognitive andbrain health, but they warrant mod-ification of contemporary educa-tional policies and practices, andindicate that youth should receivemore daily PA opportunities.28 Fi-nally, given that scholastic success inreading and mathematics is heavilyreliant upon effective executive con-trol,29,30 our findings have broadrelevance for public health, the

educational environment, and the con-text of learning.

ACKNOWLEDGMENTSWe thank the participants, their families,and the Urbana School District 116 forparticipating in the study. We thankBonnieHemrickforherassistanceinpar-ticipant recruitment and randomization.We also thank Dominika Pindus for pro-viding valuable insight on the discussionand analysis of the data, and we thankthe students and staff who aided in theimplementationoftheFITKidsintervention.

REFERENCES

1. Ng SW, Popkin BM. Time use and physicalactivity: a shift away from movement acrossthe globe. Obes Rev. 2012;13(8):659–680

2. Lee IM, Shiroma EJ, Lobelo F, Puska P, BlairSN, Katzmarzyk PT; Lancet Physical ActivitySeries Working Group. Effect of physicalinactivity on major non-communicable dis-eases worldwide: an analysis of burden ofdisease and life expectancy. Lancet. 2012;380(9838):219–229

3. Hillman CH, Erickson KI, Kramer AF. Besmart, exercise your heart: exercise effectson brain and cognition. Nat Rev Neurosci.2008;9(1):58–65

4. Kramer AF, Hahn S, Cohen NJ, et al. Ageing,fitness and neurocognitive function. Nature.1999;400(6743):418–419

5. Luna B. Developmental changes in cogni-tive control through adolescence. Adv ChildDev Behav. 2009;37:233–278

6. Diamond A, Barnett WS, Thomas J, MunroS. Preschool program improves cognitivecontrol. Science. 2007;318(5855):1387–1388

7. Hillman CH, Buck SM, Themanson JR, PontifexMB, Castelli DM. Aerobic fitness and cognitivedevelopment: Event-related brain potentialand task performance indices of executivecontrol in preadolescent children. Dev Psychol.2009;45(1):114–129

8. Pontifex MB, Raine LB, Johnson CR, et al.Cardiorespiratory fitness and the flexiblemodulation of cognitive control in pre-adolescent children. J Cogn Neurosci. 2011;23(6):1332–1345

9. Polich J. Updating P300: an integrativetheory of P3a and P3b. Clin Neurophysiol.2007;118(10):2128–2148

10. Duncan-Johnson CC. Young Psychophysiol-ogist Award address, 1980. P300 latency:

a new metric of information processing.Psychophysiology. 1981;18(3):207–215

11. Verleger R. On the utility of P3 latency as anindex of mental chronometry. Psychophys-iology. 1997;34(2):131–156

12. Davis CL, Tomporowski PD, McDowell JE,et al. Exercise improves executive functionand achievement and alters brain activationin overweight children: a randomized, con-trolled trial. Health Psychol. 2011;30(1):91–98

13. Kamijo K, Pontifex MB, O’Leary KC, et al. Theeffects of an afterschool physical activityprogram on working memory in preado-lescent children. Dev Sci. 2011;14(5):1046–1058

14. Chaddock-Heyman L, Erickson KI, Voss MW,et al. The effects of physical activity onfunctional MRI activation associated withcognitive control in children: a randomizedcontrolled intervention. Front Hum Neurosci.2013;7:72

15. Krafft CE, Schwarz NF, Chi L, et al. An8-month randomized controlled exercisetrial alters brain activation during cogni-tive tasks in overweight children. Obesity(Silver Spring). 2014;22(1):232–242

16. Birnbaum AS, Lytle LA, Murray DM, Story M,Perry CL, Boutelle KN. Survey developmentfor assessing correlates of young adoles-cents’ eating. Am J Health Behav. 2002;26(4):284–295

17. Kaufman AS. Kaufman Brief IntelligenceTest: KBIT. AGS. Circle Pines, MN: AmericanGuidance Service; 1990

18. Taylor SJC, Whincup PH, Hindmarsh PC,Lampe F, Odoki K, Cook DG. Performance ofa new pubertal self-assessment question-naire: a preliminary study. Paediatr PerinatEpidemiol. 2001;15(1):88–94

19. Thomas S, Reading J, Shephard RJ. Re-vision of the physical activity readinessquestionnaire (PAR-Q). Can J Sport Sci.1992;17(4):338–345

20. Armstrong L. ACSM’s Guidelines for ExerciseTesting and Prescription/American Collegeof Sports Medicine, 7th ed. Philadelphia, PA:Lippincott Williams & Wilkins; 2006

21. Shvartz E, Reibold RC. Aerobic fitnessnorms for males and females aged 6 to 75years: a review. Aviat Space Environ Med.1990;61(1):3–11

22. Eriksen CW, Eriksen BA. Effects of noiseletters upon the identification of a targetletter in a non-search task. Percept Psy-chophys. 1974;2(25):249–263

23. Pontifex MB, Saliba BJ, Raine LB, PicchiettiDL, Hillman CH. Exercise improves behav-ioral, neurocognitive, and scholastic per-formance in children with attention-deficit/hyperactivity disorder. J Pediatr. 2013;162(3):543–551

24. Espy KA. The shape school: Assessing ex-ecutive function in preschool children. DevNeuropsychol. 1997;13(4):495–499

25. Krafft CE, Schaeffer DJ, Schwarz NF, et al.Improved frontoparietal white matter in-tegrity in overweight children is associ-ated with attendance at an after-schoolexercise program. Dev Neurosci. 2014;36(1):1–9

26. Datar A, Sturm R. Childhood overweightand elementary school outcomes. Int JObes (Lond). 2006;30(9):1449–1460

27. Sallis JF. We do not have to sacrifice chil-dren’s health to achieve academic goals.J Pediatr. 2010;156(5):696–697

28. IOM (Institute of Medicine). Educating theStudent Body: Taking Physical Activity and

e1070 HILLMAN et al by guest on June 5, 2018www.aappublications.org/newsDownloaded from

Physical Education to School. Washington,DC: The National Academies Press; 2013

29. Bull R, Scerif G. Executive functioning asa predictor of children’s mathematics ability:inhibition, switching, and working memory.Dev Neuropsychol. 2001;19(3):273–293

30. St Clair-Thompson HL, Gathercole SE. Executivefunctions and achievements in school: Shift-ing, updating, inhibition, and working memory.Q J Exp Psychol (Hove). 2006;59(4):745–759

31. McKenzie TL, Strikmiller PK, Stone EJ, et al.CATCH: physical activity process evaluationin a multicenter trial. Health Educ Q. 1994;(suppl 2):S73–S89

32. Luepker RV, Perry CL, McKinlay SM, et al.Outcomes of a field trial to improve chil-dren’s dietary patterns and physical activ-ity. The Child and Adolescent Trial forCardiovascular Health. CATCH collaborativegroup. JAMA. 1996;275(10):768–776

33. Nader PR, Stone EJ, Lytle LA, et al. Three-year maintenance of improved diet and

physical activity: the CATCH cohort. Childand Adolescent Trial for CardiovascularHealth. Arch Pediatr Adolesc Med. 1999;153(7):695–704

34. Coleman KJ, Tiller CL, Sanchez J, et al. Pre-vention of the epidemic increase in child riskof overweight in low-income schools: the ElPaso coordinated approach to child health.Arch Pediatr Adolesc Med. 2005;159(3):217–224

35. Hoelscher DM, Springer AE, Ranjit N, et al.Reductions in child obesity among disad-vantaged school children with communityinvolvement: the Travis County CATCH Trial.Obesity (Silver Spring). 2010;18(suppl 1):S36–S44

36. Chatrian GE, Lettich E, Nelson PE. Ten per-cent electrode system for topographicstudies of spontaneous and evoked EEGactivity. Am J EEG Technol. 1985;25:83–92

37. Compumedics Neuroscan. SCAN 4.3: OfflineAnalysis of Acquired Data, vol. II. El Paso, TX:Compumedics Neuroscan; 2003

38. Gamer M, Berti S. Task relevance and rec-ognition of concealed information havedifferent influences on electrodermal ac-tivity and event-related brain potentials.Psychophysiology. 2010;47(2):355–364

39. Sass SM, Heller W, Stewart JL, et al. Timecourse of attentional bias in anxiety: emo-tion and gender specificity. Psychophysiol-ogy. 2010;47(2):247–259

40. Utter AC, Robertson RJ, Nieman DC, Kang J.Children’s OMNI Scale of Perceived Exertion:walking/running evaluation. Med Sci SportsExerc. 2002;34(1):139–144

41. Freedson PS, Goodman TL. Measurement ofoxygen consumption. In: Rowland TW, ed.Pediatric Laboratory Exercise Testing: Clini-cal Guidelines. Champaign, IL: Human Ki-netics; 1993:91–113

42. Bar-Or O. Pediatric Sports Medicine for thePractitioner: From Physiologic Principles toClinical Applications. New York, NY: Springer-Verlag; 1983

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FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

FUNDING: All phases of this study were supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), NationalInstitutes of Health (NIH) grant RO1 HD055352 (to Dr Hillman). Funded by the National Institutes of Health (NIH).

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

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