MonicaSerrano-Gonzalez,MDPGY-5,Year2PediatricEndocrinologyFellowChildren’sHospitalLosAngelesCenterforEndocrinology,DiabetesandMetabolismE-mail:mserranogonzalez@chla.usc.edu;Office:323-361-8848

EndocrineFellowsFoundation–FinalProjectUpdateFoodDecision-makinginChildhood

Thisisacross-sectionalstudythataimstocharacterizethedietary-decisionmakingprocessin8-12year-old lean and obese children, particularly as it pertains to the processing speed of health and tasteattributes,byutilizinganovel,computer-basedtask.

InTask1(FoodRatings),subjectswillrate60differentfoodsviewedonacomputerscreen(30high-and30 low-calorie images) in termsof tastiness,healthiness,andoverall liking (ie, “howmuchwouldyouliketoeatthisfoodattheendoftheexperiment?”).Ratingswillbemadeona5-pointfacesscale(“verybad”to“verygood”withaneutraloption)andwillbeenteredonakeyboardwithcorrespondingfaceson5keys.Blockandstimulusorderwillbe randomizedacross subjects.Per rating trial, a single colorimagewill be presented at the center of a black screen in high resolution (1,680 x 1,050 pixels; LCDmonitor).

In Task 2 (Food Choices), subjects will make 100 binary choices among randomly presented pairs offoods. Food pairs will be coded a priori so that different combinations of tastiness and healthinessratingsareequallyrepresentedbasedonthesubject’sownfoodratingsfromTask1.Themousecursor’sx,ypositionwillbetrackedusingPsychophysicsToolbox(temporalresolution67Hz).

Recruitmentstrategiesandlogistics

Overall,wehavemadesignificantstridestowardsconductingandrecruitingforthisstudy.Atthistime,wearefocusedonrecruitment,withelevenchildrenalreadyhavingparticipatedinthestudy.Ourworkto get the study to this point has included twomain areas: recruitment strategies and logistics, andrefinementofoutcomemeasures.Preliminaryanalysisofdatashowspromisingresultsthatsupportourstudyhypotheses.

Wehavepolishedtherecruitmentstrategyholdingmultiplemeetingswith theChildren’sHospitalLosAngeles clinic teams for recruitment (i.e., General Pediatrics clinic, EMPOWER obesity clinic, andPediatric Endocrinology clinic), placing flyers in the clinics, learning clinic flowand logistical details ofrecruitingwithinclinicsandcontacting interestedandeligible individuals.Wehavealso recentlybeenworking on adding twomore recruitment sites: theBodyWorks (weight loss) programat theGeneralPediatricsclinicandtheSIPA(SearchtoInvolvePilipinoAmericans)SummerProgram.Aswell,wehad

submitted several IRB amendments, including a Spanish-translated consent, Spanish-translated flyers,theparentalCEBQ (ChildEatingBehaviorQuestionnaire), and sharingoutputdatawitha collaboratoroutsideourinstitution.

Refinementofoutcomemeasures

Wehadinitiallyfocusedonoptimizinganovel,computer-basedtaskforthestudy.Thisinvolvedlearningthe software for the task (Matlab & Psychtoolbox) and computer coding, in order to adapt the taskcomponents for children. I completed an online course offered by the University of Vanderbilt,‘Introduction to Programming with Matlab’, via Coursera, and earned the course certificate. I alsoestablishedtheset-uptorunthetask,includingacustomizedkeyboard,child-friendlymouse,andtwoMacbooks tailored for the study tasks. As a result, we are successfully running the child-friendly,modifiedversionofbothcomputer-basedtasks(theFoodRatingstask,andtheFoodChoicestask).Wealsohaverefineda24-hourdietaryrecallmeasure(ASA24KIDS;NationalCancerInstitute)forthestudy,withboththeparentandchildnowcompletingthedietaryrecalltogether,forimprovedaccuracy1,2.Wealsoadded twohandoutsonhealthy-eatingas educational incentives for theparents:USDAMyPlate,and‘URWhatUEat’(DHHS/NIH).Wearenowfollowingupwiththeparentsonemonthafterthestudyvisitwithabrief survey toassess their receptiveness to the twohandouts, and tohelp inform futurenutritionalinterventions.

After attending the Obesity Society’s ObesityWeek national conference (Los Angeles) in November,where Ihadtheopportunity todiscussmystudywithotherscientistsandattendrelevantsessions tothiswork, Iwantedtoaddaparentquestionnaire,Children’sEatingBehaviorQuestionnaire(CEBQ)asanoutcomemeasurethatcouldbeanalyzedwiththeFoodChoicesdata.Wearealsoinvestigatingthefeasibilityofaddingameasureofimpulsivity,suchasabehavioralquestionnaire,toourstudyprotocol(e.g.,UPPS-R-C)3.

Wehavealsostandardizedthefoodimage‘cues’thatareused inthecomputertasks,eliminatinganybranding with labels on the images, and standardizing image characteristics between high- and low-calorie groups. Branding has been shown to skew food perception4 and so several images that hadbrandingwordsremoved.Wealsosubstitutedseveralfoodimagesfromapublishedfoodcuesdatabase(Blechertetal.,food-pics imagedatabase)tohelpstandardizeimagecharacteristicsbetweenthehigh-andlow-caloriegroups,implementingMatlab-codedalgorithmsfromtheBlechertgrouptoanalyzefoodcues for characteristics such as: red/green/blue color, object size, contrast andbrightness5.However,when making even small changes to the computer task, as it is typically the case in computerprogramming,weoftenfacetheneedtodebugthecomputercode.

Results

Ihaveperformedapreliminaryanalysisofdatacollected thus far, in conjunctionwitha collaboratingneuroscientistandstatistician.InTask1,FoodRatings,participantsfirstratefooditemsforhealth,taste

and likeability. Subsequently, inTask2, FoodChoices, theychoosebetween foodpairs (Figure1).Werecordthepositionofthemouseasthesubjectmovesthemousetowardthefooditemoftheirchoice.

Paradigmvalidation

Thus far, thedatashowsthatthetaskparadigmworks,as theparticipantsarechoosingfood items inTask2(FoodChoices)accordingtotheirfoodpreferencesfromTask1(FoodRatings),asdepictedinanaveragepsychometricplot(Figure2).

HealthandtasteprocessinganddietarychoiceWenextexamined the influenceof tasteandhealthprocessing speed on the mouse trajectory. Becauseresponse times for choosing a food item in Task 2differwithinandbetweenparticipants,theresponsetime has to be normalized. Thus, response timesweredividedinto101timebins(Figure3,x-axis).Weperformed linear regressions for the relative health(health rating for the right food item–health ratingfor the left food item) and the relative taste (tasteratingfortherightfooditem–tasteratingfortheleftfood item) to predict the angle trajectory of the

mousemovementtowardthefooditemthatthechildchooses.Theresultantβcoefficientsacrosstime(Figure 3, y-axis) show that the attribute of taste becomes significant as a predictor of the mousetrajectoryatnormalizedtimewindowt=76.Ontheotherhand,theattributeofhealththusfarhasnotbecomesignificant.Thisisnotverysurprising,asinadults,‘health’wasnotasignificantpredictorofthemousetrajectoryin32%ofsubjects6.Healthandtasteprocessingandself-controlWenextexaminedtheprocessingspeedoftasteandhealthinrelationtoself-control.Theself-controlsuccess ratio (SCSR) is thepercentageof timesubjectschose thehealthier food.Whenregressing theaveragetimewhentastebecomesasignificantpredictorofthemousetrajectory,againsttheSCSR,theresultsarestriking,withanR2=0.58andp=0.029,showingthattasteprocessingspeedexplains58%ofthevarianceinself-control.Thisresultisstronglysignificant,eveninoursmallsample.Incontrast,theaveragetimewhenhealthpredictsthemousetrajectoryisnotasignificantpredictorofself-control(R2=0.69,p=0.169)(Figure4).For each subject, we then calculated a measure of the ‘computational advantage’ of taste. The‘computationaladvantageoftaste’isgivenbytheearliesttimeatwhichtastesignificantlyaffectedandcontinuedtoaffect thetrajectories,minustheearliest timeatwhichhealthdid.WethenestimatedalinearregressionoftheSCSRagainsttheindividualmeasuresofthe‘computationaladvantage’fortasteversus health. This regression tests the extent to which individual differences in self-control can beattributed to individual differences in the relative speed atwhich the health and taste attributes areprocessed.TheresultofthisregressionhadanR2=0.41andap=0.069(Figure4).Eventhoughthisisnotyetsignificant,it’sapproachingsignificanceandislikelynotsignificantyetgiventhesmallsamplesize.

Goals/TimelineMyfirstgoalistocompleterecruitmentof60childrenbytheendofDecember2016.Next,istoanalyzedata and submit an abstract in March 2017 for the combined Pediatric Endocrine Society/EuropeanSocietyofPediatricEndocrinologyPES/ESPEmeeting(September2017),andtowritethemanuscriptbythefallof2017.Inthefuture,I’minterestedinapplyingthiscomputertaskbeforeandafteranutritionalintervention toassesswhether it candetect changes specifically in tasteandhealthprocessing speedand its influenceonchoice.The idea is that thismodelcansupport thedevelopmentof interventionsthatspecificallyincreasetherelativespeedwithwhichhealthinformationisprocessed.Thankyouforyoursupport,

References

1. LivingstoneMBE,RobsonPJandWallaceJMW.IssuesinDietaryIntakeAssessmentinChildrenandAdolescents.BritishJournalofNutrition2004.92:S213-S222.

2. Sobo EJ, Rock CL, NeuhouserML,Maciel TL, Neumark Sztainer D. Caretaker-child interactionduringchildren’s24hourdietaryrecalls:Whocontributeswhattotherecallrecord?JournaloftheAmericanDieteticAssociation2000.100:428-433.

3. ZapolskiT,StairsA,FriedSettlesR,CombsJLandSmithG.TheMeasurementofDispositionstoRashActioninChildren.Assessment2010.17(1):116-125.

4. RobinsonT,BorzekowskiDLG,MathesonDMandKraemerHC.Effectsoffast-foodbrandingonyoungchildren’stastepreferences.ArchPediatrAdolescMed2007.161(8):792-797.

5. Blechert J, Meule A, Busch NK and Ohla K. Food-pics: an image database for experimentalresearchoneatingandappetite.FrontiersinPsychology2014.5:1-8.

6. SullivanN, Hutcherson C, Harris A and Rangel A. Dietary Self-Control Is Related to the SpeedWith Which Attributes of Healthfulness and Tastiness Are Processed. Psychological Science2014.1:13.