Regression-Based Normative Data for Independent and Cognitively Active Spanish Older Adults: Digit Span, Letters and Numbers, Trail Making Test and Symbol Digit Modalities Test

Abstract

In this work, we developed normative data for the neuropsychological assessment of independent and cognitively active Spanish older adults over 55 years of age.

Method:
Regression-based normative data were calculated from a sample of 103 non-depressed independent community-dwelling adults aged 55 or older (67% women). Raw data for Digit Span (DS), Letters and Numbers (LN), the Trail Making Test (TMT), and the Symbol Digit Modalities Test (SDMT) were regressed on age, sex, and education. The model predicting TMT-B scores also included TMT-A scores. Z-scores for the discrepancy between observed and predicted scores were used to identify low scores. The base rate of low scores for SABIEX normative data was compared to the base rate of low scores using published normative data obtained from the general population.

Results:
The effects of age, sex, and education varied across neuropsychological measures. Although the proportion of low scores was similar between normative datasets, there was no agreement in the identification of cognitively impaired individuals.

Conclusions:
Normative data obtained from the general population might not be sensitive to identify low scores in cognitively active older adults, incorrectly classifying them as cognitively normal compared to the less-active population. We provide a friendly calculator for use in neuropsychological assessment in cognitively active Spanish people aged 55 or older.

Full text

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Int.J.Environ.Res.PublicHealth2021,18,9958.https://doi.org/10.3390/ijerph18199958www.mdpi.com/journal/ijerph
Article
Regression‐BasedNormativeDataforIndependentand
CognitivelyActiveSpanishOlderAdults:DigitSpan,Letters
andNumbers,TrailMakingTestandSymbolDigit
ModalitiesTest
ClaraIñesta
1
,JavierOltra‐Cucarella
1,2,
*,BeatrizBonete‐López
1,2
,EvaCalderón‐Rubio
1
andEstherSitges‐Maciá
1,2

1
SABIEX,UniversidadMiguelHernándezdeElche,Avda.delaUniversidad,03207Elche,Spain;
clara.inesta@goumh.umh.es(C.I.);bbonete@umh.es(B.B.‐L.);eva.calderon@goumh.umh.es(E.C.‐R.);
esther.sitges@umh.es(E.S.‐M.)
2
DepartmentofHealthPsychology,MiguelHernandezUniversityofElche,03202Elche,Spain
*Correspondence:joltra@umh.es
Abstract:Inthiswork,wedevelopednormativedatafortheneuropsychologicalassessmentofin‐
dependentandcognitivelyactiveSpanisholderadultsover55yearsofage.Method:Regression‐
basednormativedatawerecalculatedfromasampleof103non‐depressedindependentcommu‐
nity‐dwellingadultsaged55orolder(67%women).RawdataforDigitSpan(DS),LettersandNum‐
bers(LN),theTrailMakingTest(TMT),andtheSymbolDigitModalitiesTest(SDMT)werere‐
gressedonage,sex,andeducation.ThemodelpredictingTMT‐BscoresalsoincludedTMT‐A
scores.Z‐scoresforthediscrepancybetweenobservedandpredictedscoreswereusedtoidentify
lowscores.ThebaserateoflowscoresforSABIEXnormativedatawascomparedtothebaserate
oflowscoresusingpublishednormativedataobtainedfromthegeneralpopulation.Results:The
effectsofage,sex,andeducationvariedacrossneuropsychologicalmeasures.Althoughthepropor‐
tionoflowscoreswassimilarbetweennormativedatasets,therewasnoagreementintheidentifi‐
cationofcognitivelyimpairedindividuals.Conclusions:Normativedataobtainedfromthegeneral
populationmightnotbesensitivetoidentifylowscoresincognitivelyactiveolderadults,incor‐
rectlyclassifyingthemascognitivelynormalcomparedtotheless‐activepopulation.Weprovidea
friendlycalculatorforuseinneuropsychologicalassessmentincognitivelyactiveSpanishpeople
aged55orolder.
Keywords:cognitivelyactive;cognitiveimpairment;neuropsychologicalassessment;normative
data;olderadults

1.Introduction
Thepopulationaged65yearsorolderisexpectedtoriseworldwideinthecoming
decades.TheUnitedNations[1]predictedanincreasefrom9%in2020toaround16%in
2050.AsreportedbytheEurostatdatabase,20%ofpeopleinEuropeareaged65orolder
andthispercentageisestimatedtoincreaseto30%by2070.AccordingtotheSpanish
NationalStatisticsInstitute[2],Spainisoneofthecountrieswiththehighestrateofolder
peopleinEurope,with18.58%ofpeopleaged65yearsorolder.
Sinceageisthemainriskfactorfordementia[3,4],theincreaseintheproportionof
olderpeopleisassociatedwithanincreaseintheincidenceandprevalenceofcognitive
impairmentanddementia[5,6].Thenumberofpeoplelivingwithdementiaworldwide
iscurrentlyestimatedat50million,withdementiabeingtheleadingcauseofdisability
anddependenceduringaging[7].Arecentmeta‐analysisreporteda12.4%prevalenceof
dementiainEuropeand5–9%inSpaininpeopleolderthan65[8].Previousresearchhas
foundthatpeoplediagnosedwithMildCognitiveImpairment(MCI)areatahigherrisk
Citation:Iñesta,C.;Oltra‐Cucarella,
J
.;Bonete‐López,B.;Calderón‐Rubio,
E.;Sitges‐Maciá,E.Regression‐Based
NormativeDataforIndependent
andCognitivelyActiveSpanish
OlderAdults:DigitSpan,Letters
andNumbers,TrailMakingTest
andSymbolDigitModalitiesTest.
Int.J.Environ.Res.PublicHealth2021,
18,9958.https://doi.org/
10.3390/ijerph18199958
AcademicEditor:PaulB.
Tchounwou
Received:29July2021
Accepted:18September2021
Published:22September2021
Publisher’sNote:MDPIstaysneu‐
tralwithregardtojurisdictional
claimsinpublishedmapsandinstitu‐
tionalaffiliations.

Copyright:©2021bytheauthor.
LicenseeMDPI,Basel,Switzerland.
Thisarticleisanopenaccessarticle
distributedunderthetermsand
conditionsoftheCreativeCommons
Attribution(CCBY)license
(http://creativecommons.org/licenses
/by/4.0/).

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ofdevelopingdementia[9].Thus,intheabsenceofeffectivepharmacologicalandnon‐
pharmacologicaltreatmentsfordementia[10–12],earlydetectionofcognitiveimpairment
duringaginghasbecomeamajorresearchtopic.
Neuropsychologicalassessmentisessentialtoidentifypathologicalcognitive
changesduringaging[13,14].Standardizedtestsareadministeredinordertoassessthe
functioningofdifferentcognitivedomainssuchasattention,memory,language,
visuospatialabilities,andexecutivefunctions.Performanceisinterpretedbycomparing
individuals’scoreswithscoresfromareferencegroup[13].Asrawscoresincognitive
testsareaffectedbydemographicvariablessuchasage,sex,oreducationallevel[15–17],
normativedataareusedtotransformthemintorelativemeasurescorrectedfortheinflu‐
enceofthesevariables[16,18]andtoprovideaframeworkinwhichthesesscorescanbe
locatedandinterpreted.Thus,selectingappropriatenormativedatasetsisnecessaryfor
accuratelyinterpretingtheresultsoftheneuropsychologicalassessment,andforreducing
theprobabilityoffalsediagnosesofcognitiveimpairment[15,19].
Differentapproachestodevelopingnormativedatahavebeenreported.Thesimplest
procedureisbasedonthetests’scoredistributiontogeneratenormsfromthemeansand
standarddeviations.Thisstrategycanbeusedwiththeentiresampleorstratifyingthe
samplebyage[20,21],sex[22],andeducation[20,21,23].Meansandstandarddeviations
withineachsubgroupareusedtotransformrawscoresintoeasilyinterpretablemeasures
suchasZscores,T‐scores,scaledscores,orpercentileranks[22].Thismethodhassome
limitations:First,itisbasedonaseriesofarbitrarystrata[24],assumingwhichperson
variablesarepredictiveofthetestscore;second,theestimatedpopulationmeansandvar‐
iancescanbelessreliablewhendividingthesampleintosubgroupsthanusingthewhole
sample[25].Amoreadvancedproceduretodevelopnormativedataisusingmultiple
linearregressionmodelstoestimateanindividual’spredictedlevelofperformance,based
onsociodemographicvariablessuchasage,sex,andeducation.Thedifferencebetween
thepredictedandtheobservedscore(residualvalues)isthenstandardizedandinter‐
preted[26–28].AdifferentprocedureforclinicalclassificationistheReceiverOperating
Characteristiccurve(ROC)analysis,whichisusedtodeterminethecut‐offscorewiththe
optimalbalancebetweensensitivityandspecificity[29,30].TheareaundertheROCcurve
(AUC)offersanindexofthetest’soveralldiscriminationaccuracy,withvaluescloseto1
suggestingahighdiagnosticaccuracy.
1.1.ActiveAging
Althoughbrainchangesduringnormalagingentailchangesinsomecognitiveabili‐
ties[31],certainactivitiesareconsideredprotectivefactorsagainstcognitivedecline,such
ascontinuedlearningandengagementinsociallyandcognitivelystimulatingactivities
duringaging[32,33].Thisprotectivelinkismostlyattributedtoanincreasedcognitive
reserve,whichcompensatesforbrainchangesinnormalaginganddelaystheclinicalex‐
pressionofcognitiveimpairmentdespiteunderlyingbrainpathologycausedbyneuro‐
degenerativeprocesses[34,35].Supportingthesehypotheses,frequentparticipationin
cognitiveactivitieshasbeenassociatedwithslowerlate‐lifecognitivedecline[36]anda
reducedriskofdevelopingMCIanddementia[37].
Asaresponsetothechallengesofpopulationaging,theconceptandpoliciesof“Ac‐
tiveAging”emerged.TheActiveAgingFrameworkpromotestheoptimizationofoppor‐
tunitiesforhealth,participation,andsecuritywiththeaimofimprovingthequalityoflife
aspeopleage[38,39].Thisnotionemphasizestheimportanceofanactivelifestyleandthe
benefitsoflife‐longlearning[40,41].Fromthisperspective,universityprogramsforsen‐
iors(UPS)havebecomeanimportantresourceforincreasingopportunitiesforactiveag‐
ing,improvingseveralaspectssuchashealth,psychologicalwell‐being,cognitivefunc‐
tioning,autonomymaintenance,andsocialparticipation[41–43].Inrecentdecades,UPS
havespreadworldwide[40,44]andhavepromptedanincreaseinthenumberofolder
adultsthatundertakeuniversitycourses.InSpain,accordingtotheStateAssociationof
UniversityProgramsforOlderAdults(AEPUM),thenumberofadultsaged55orolder

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enrollingintheseprogramsincreasedfrom23,000duringthe2005–2006academicyearto
63,173in2018–2019(https://www.aepumayores.org/)(accessedon20June,2021).
Olderpeoplewhoparticipateinuniversitycoursesliveindependentlyintheireve‐
rydaylifeandseekcontinuedpersonaldevelopmentandsocialinteractionsthroughthese
educationalprograms[45].Ithasbeenreportedthatthemotivationstoattendthesepro‐
gramsaretofeelactive,toinvestinpersonaldevelopment,andtogainnewknowledge
andsocialcontacts[45,46].TheevidencealsosuggeststhatindividualswhoengageinUPS
arecognitivelymoreactivethansame‐agepeopleinthegeneralpopulation.Thetendency
toengageinthesecourseshasbeenrelatedtoalargernumberofindividualandcommu‐
nity‐basedactivepractices.Thus,cognitivelyactivepeoplereadmorefrequently,domore
physicalexercise,attendmoreculturalevents,andparticipatemoreinsocialactivities
[42,47].
Ithasbeenreportedthatcognitivelystimulatingactivitiesinmid‐life[48]andlate
life[49]contributetocognitivereserveindependentlyofeducation.Christensenetal.[50]
foundthatthelevelofactivityineverydaylifeinfluencedcognitiveperformanceandac‐
countedforagreaterproportionofvarianceinolderpeople’scognitivefunctioningthan
thelevelofeducation.Inlinewiththeseresults,inapost‐mortemstudy,Reedetal.[51]
foundthatcognitiveactivitiesduringadulthoodhaveahigherinfluencethanthelevelof
educationindeterminingcognitivereserve.Thus,activeagingisrelatedtoaseriesof
practicesineverydaylifethatdiffersfromsame‐ageadultsfromthegeneralpopulation,
contributingtoahighercognitivereservethatmaypreserveorenhancetheircognitive
function.
1.2.ActiveAgingandNeuropsychologicalAssessment
Thereisevidencesuggestingthatactiveolderadults’lifestyleswillaffectperfor‐
manceonneuropsychologicalassessmentirrespectiveofyearsofformaleducation.Active
olderpeoplearelikelytooutperformnon‐activeindividualsoncognitivetests[50,52].
Eventhoughnormativedataaredemographicallycorrectedbyeducation,theydonot
accountforthecharacteristicsofactiveaging,andtherefore,theymightbelesssensitive
foridentifyingcognitiveimpairmentamongcognitivelyactiveolderadultswithhigher
performancelevels.Totheauthors’knowledge,therearenonormativedataforSpanish
activeolderadults.Thisimpliesthatactiveolderadultsmightpresentadiagnosticchal‐
lengeinconditionssuchascognitiveimpairmentandAD,aspathologicalchangesmight
goundetectedintheneuropsychologicalassessment.Tofillthatgap,thisstudydeveloped
normativedataontheassessmentofattention,processingspeed,andworkingmemory
throughfourcognitivetestswidelyusedaspartoftheneuropsychologicalassessment.
TheDigitspanforward(DSF)andbackward(DSB)[53]aretwofrequentlyused
measuresofattentionandworkingmemory.TheSpanisheditionoftheWAIS‐IIIincludes
normativedataforSpanishindividuals.Therearealsonormativedataofthistestforsub‐
jectsover50inSpainwithintheNEURONORMAProject[54].Somestudieswithhealthy
controlsandMCIandADpatientshavereportedtheeffectivenessofbothsubteststo
identifysubtleimpairmentsandtodetectMCI[55],andtodifferentiatepeoplewithMCI
andAD[56].Lortieetal.[57]foundthatindividualswithMCIdeclinedinperformance
over6months,suggestingthatbothsubtestsareareliablemeasureformonitoringthe
diseaseprogression.Thebackwarddigitspansubtesthasalsobeenreportedtobeakey
variablediscriminatingbetweendementiasubtypessuchasADandDementiawithLewy
Bodies[58].
TheLettersandNumberssubtest[53]isusedasameasureofworkingmemory.Some
studiesprovidednormativedataforthistestinSpain[54]andLatinAmerica[59]with
adultsfromthegeneralpopulation.Kesseletal.[60]foundthatMCIandADpatients
performedworseonthissubtestcomparedwithhealthycontrols.Worseperformancein
ADcomparedwithMCIpatientswasalsorevealed,meaningitissuitabletodifferentiate
peoplewithMCIandAD.

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TheSymbolDigitModalitiesTest(SDMT)[61]isusedasameasureofinformation
processingspeed.Normsobtainedwithhealthyadultsfromthegeneralpopulationhave
beenpublishedinSpain[54]andinLatinAmerica[62].Smithalsoincludednormative
datainSpanishforanagerangeof18to85yearsfortwoschoolinggroups[61].Perfor‐
manceontheSDMTisasignificantpredictorofconversionfromcognitivelynormalto
MCI[63]andofprogressionfromMCItoAD[64].Itisalsooneofthemostcommonly
usedtestsintheassessmentofMultipleSclerosis[65],Huntington’sDisease[66],andPar‐
kinson’sdisease[67].
TheTrailMakingTest(TMT)[68]iswidelyusedasameasureofattentionandpro‐
cessingspeed[15].TMTnormativedatahavebeenreportedforadultsover50inSpain
withintheNEURONORMAProject[54]andforadultsaged18–95inLatinAmerica[69].
TheTMTisusedtoscreenforneurodegenerativediseasesinolderadults,suchasAlz‐
heimer’sDisease[70],Parkinson’sDisease[71],andHuntington’sdisease[72].Bothparts
AandBaresensitivetothedetectionofbothprogressivecognitiveimpairmentandde‐
mentia[19,73].
Becausethelikelihoodofdiagnosticerrorsamongactiveolderadultscouldpoten‐
tiallyincreasebyusingnormsobtainedfromthegeneralpopulation,normativedata
adaptedtothespecificcharacteristicsofthispopulationareneeded.Thus,theaimofthis
studyistoprovidenormativedataforthesefourcommonlyusedneuropsychological
testswithasampleofcognitivelyactiveSpanisholderadultswhoattenduniversity
courses.Sincethecognitivelyactivepopulationhashighercognitiveperformanceinde‐
pendentlyofageandyearsofeducation,thehypothesisisthattheywillobtainalower
rateoflowscoresusingnormativedatafromthegeneralpopulationthanwithnormative
dataobtainedfromthecognitivelyactiveolderpopulation.
2.MaterialsandMethods
2.1.Participants
Thisisacross‐sectionalobservationalstudywithcognitivelyhealthyindividualsliv‐
ingindependentlyinthecommunity.Voluntaryparticipantswererecruitedconsecutively
fromtheUniversityforSeniors(SABIEX)attheUniversidadMiguelHernándezdeElche
(Spain)fromOctober2019toJuly2021.SABIEXisacomprehensiveprogramforthepro‐
motionofactiveandhealthyagingandincludesanacademicuniversityprogramforpeo‐
pleaged55yearsorolder,coveringtopicssuchaseconomics,physiology,sociology,pol‐
itics,arts,amongothers,aswellasthepossibilityofparticipatingindifferentactivities
suchasseminars,voluntarywork,theaterworkshops,andradioprograms.
Inclusioncriteriaforparticipationwere(a)being55yearsoldorolder,(b)beingcog‐
nitivelynormal(CN)withoutsubjectivecognitivecomplaints,and(c)livinginde‐
pendentlyinthecommunity.ParticipantswereclassifiedasCNiftheyhada)Mini‐Mental
StateExamination[74]scoreshigherthan23,(b)ClinicalDementiaRatingscale[75]scores
equalto0,and(c)InstrumentalActivitiesofDailyLiving[76]scores7orhigher.Exclusion
criteriawerea)unwillingnesstoparticipateintheneuropsychologicalassessment,and(b)
thepresenceofvisionand/orhearingimpairmentsthatmighthaveimpededtheadmin‐
istrationofcognitivetests.Participantswerenotexcludedbasedonahistoryofmedical
conditions(e.g.,diabetes,highbloodpressure,cancer,psychiatricdisorders,metabolic
disease)inordertoassurethatthesampleisrepresentativeofthepopulationofpeople
over54yearsinSpain[77,78].AllparticipantswerebornandraisedinSpainandhad
Spanishastheirfirstlanguage.
2.2.Procedure
Participantswereinvitedtoparticipatevoluntarilyintheneuropsychologicalassess‐
mentandwereassessedindividuallybyaboard‐certifiedclinicalneuropsychologist(JO‐
C)andtrainedundergraduateandmaster’sorPhDdegreestudents.Theneuropsycho‐
logicalassessmentwasperformedinonesessionandtookapproximately90min.

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Participantssignedtheinformedconsentpriortoenrollmentandprovidedpersonaland
familyhealthhistory.Personaldatawerecodedanonymously.Thisprojectwasapproved
bytheUMHEthicsCommittee(DPS.ESM.01.19).
Asociodemographicquestionnairewascreatedforthisprojecttocollectdataongen‐
der,age,yearsofformaleducation,residencezone(rural,urban),civilstatus,household
context,andmedicalhistory.Theneuropsychologicaltestsincludedinthisworkwere
administeredaspartofalargerneuropsychologicalassessmentcoveringseveralcognitive
domains.Thetestswereadministeredinapre‐establishedordersothattherewasnoin‐
terferencebetweendifferenttasks(e.g.,interactionbetweenlanguageandverbalmemory
tasks).Thetestsincludedintheneuropsychologicalassessmenthavebeenpreviouslyde‐
scribed[79].Wecalculatednormativedatawithmorethan100participantsbecauseusing
linearregressionmodelswithasamplesizegreaterthan100andz≤−1.28givesanumber
oftruepositiveandtruenegativesaroundthe95%confidenceinterval[80].
2.3.Materials
Subjectivecognitivecomplaintsandgeneralcognitivefunctioningwereassessed
withtheCDRscaleandtheMMSE,respectively.Depressivesymptomswereassessed
withtheYessavageGeriatricDepressionScale[81](GDS).
AttentionandworkingmemorywereassessedwiththeDigitSpanForward(DSF)
andbackward(DSB),andLettersandNumbers(LN)subtestsfromtheWechslerAdult
IntelligenceScale—3rdedition[53],andtheTrailMakingTestPartB[68].Speedofpro‐
cessinginformationwasassessedwiththeTMTPartA(TMT‐A)andthewrittenversion
oftheSymbolDigitModalitiesTest[82].Thesetestswereadministeredintheorderpre‐
viouslydescribed.
2.3.1.DigitSpanForwardandBackward
IntheDSFtest,theexamineeisrequestedtorepeataseriesofnumbersindirector‐
der.IntheDSBtest,theexamineeisrequestedtorepeataseriesofnumbersinreverse
order.Inthisstudy,theoutcomevariableswerethelongestseriesrecalled,i.e.,themaxi‐
mumnumberofdigitscorrectlyrepeated(spanscore)withoutanyerrorinoneofthetwo
trials.FortheDSF,themaximumrawscoreis9,andforDSB,itis8.
2.3.2.LettersandNumbers
TheLNtestrequiresaseriesoflettersandnumbersofincreasinglengthtobere‐
peated.Theindividualisreadthecombinationofnumbersandlettersinrandomorder
andinstructedtorepeatbackthenumbersfirst,inascendingorder,followedbytheletters
inalphabeticorder.Thestudyvariablewasthelongestseriesrecalled,foramaximumof
8items.
2.3.3.TrailMakingTest
TheTMTconsistsoftwoparts(TMT‐AandTMT‐B).TMT‐Acontainscirclesnum‐
beredfrom1to25randomlyarrangedonasheetofpaper.Theparticipantisrequiredto
drawalineconnectingthecirclesinascendingorder.TMT‐Bcontainsnumbersfrom1to
13andlettersfromAtoL.Theparticipantisrequiredtoconnectthecirclesalternating
betweennumbersandlettersinascendingorder.Participantsareinstructedtocomplete
bothpartsasfastaspossiblewhilemaintainingaccuracy.Theerrorswerepointedout
immediatelybytheexaminerandcorrectedbytheparticipant.Theoutcomevariablewas
thetimetakentocompletethetasksinseconds.
2.3.4.SymbolDigitModalitiesTest
Inthistest,akeyboxwith2rowsispresentedatthetopofthepagewith9unique
symbolsassociatedwith9uniquesymbols.Onehundredandtwentysymbolsarethen
shown,eachwithablankspaceunderneath.Theparticipantisrequiredtoconsecutively

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fillineachblankwiththenumberthatmatcheseachsymbolasfastaspossible.After10
practiceitems,theparticipantcontinuesthetaskfor90s.Thissubtestwasadministered
accordingtothestandardproceduresdescribedinthetestmanual[82].Theoutcomevar‐
iablewasthenumberofcorrectresponses,andthemaximumscoreis110.
2.4.StatisticalAnalyses
2.4.1.CalculationofNormativeData
Theregression‐basednormativedatawerecalculatedusingage,sex,andeducation
aspredictorsandrawscoresasoutcomesforeachvariable.Thelinearregressionmodel
canbewrittenas
𝑌 𝛼𝛽
∗𝑋
𝛽
∗𝑋
⋯𝛽
∗𝑋
 ∈𝑁0,1,(1)
whereY’isthepredictedscore,𝛼istheintercept,𝑋isthescoreofvariablei,and𝛽is
thebetacoefficientassociatedwithvariablei.Theintercept(𝛼)indicatesthevalueofthe
responsevariablewhenallthepredictorsareequalto0,whereasthebetacoefficientsin‐
dicatethemeanchangeintheresponsevariablefora1‐unitincreaseinthepredictorwhile
holdingconstanttherestofthepredictors.Becauseageandeducationinoursampledid
nothavevaluesof0,wefirsttransformedboththeageandeducationvariablesforthe
intercepttobeinterpretable.Wetransformeddataonageandeducationforeachpartici‐
pant,takingthelowervalueinthedistributionasreference(seeTable1fordescriptive
statistics).Thus,iftheminimumageinthesampleis55,theageofaparticipantaged60
wasrecodedas5.ThesetransformedvariablesarereferredtoasAgeMinandEducationMin
throughoutthemanuscript.Sex,AgeMin,andEducationMinwereincludedaspredictorsin
thefirststepinaforwardmultiplelinearregressionmodel.Thesecondandthirdsteps
addedthequadraticAgeMinandEducationMinandthecubicAgeMinandEducationMin,re‐
spectively,soastoanalyzepossiblecurvilinearrelationships.Thisprocedurewasused
forpredictingeachofthe6variablesindependently.
Table1.DemographicstatisticsandperformanceonMMSE,IADL,andGDS.
VariableMSDRange
Age65.766.56755–87
Education11.443.4633–22
MMSE28.481.48125–30
IADL7.990.0997–8
GDS4.323.3550–14
M:mean,SD:standarddeviation.
Assomevariablesintheneuropsychologicalbatteryarenotindependentofeach
other,normativedatacalculatedindependentlymightbemisleadingifrelevantinfor‐
mationisnotincludedinthemodel.ThisisthecasefortheTMT‐B,whosescoresarenot
independentofscoresontheTMT‐A.Toillustratethedependencyofscores,iftwoindi‐
vidualsscore120sontheTMT‐B,thisscorecorrespondstoanaverageperformance(e.g.,
z‐score=0).IndividualAobtainsaz‐score=1.5ontheTMT‐A,whereasindividualB
obtainsaz‐score=0ontheTMT‐A.Reasonably,anaveragescoreontheTMT‐Bcannotbe
interpretedthesamewayforanindividualwithhigh‐levelperformanceontheTMT‐A
comparedtoanindividualwithaverageperformanceontheTMT‐A.AlthoughTMT‐B
scoresaresimilarforbothindividuals,TMT‐BscoresforindividualAarelikelyshowing
agreaterdeclinecomparedtoTMT‐BscoresforindividualB.Toimprovetheinterpreta‐
tionofscores,itisnecessarytoknowhowfrequentitwouldbetoshowsuchadeclinein
theTMT‐BaccordingtoscoresontheTMT‐A.Forthisreason,wecalculatednormative
datafortheTMT‐BwitharegressionmodelincludingthesamepredictorsplusTMT‐A
scores,whichwillbereferredtoasTMT‐BSABIEX,inordertodifferentiatethesenormative
datafromtheTMT‐BnormativedatacalculatedindependentlyoftheTMT‐A.SinceTMT‐

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Ascoresdidnothaveavalueof0,thisvariablewasfirsttransformedfortheinterceptto
beinterpretablebytakingthelowervalueinthedistributionasareference.Thetrans‐
formedvariablewillbereferredtoasTMT‐Aminthroughoutthemanuscript.
2.4.2.ComparingNormativeDataSets
Toanalyzewhethernormativedataforcognitivelyactiveolderindividualsprovide
differentdatacomparedtonormativedataobtainedinthegeneralpopulation,wecom‐
paredthenumberoflowscoresshownbyoursamplewhenusingeithertheSABIEXor
theNEURONORMAnormativedata.TheNEURONORMAnormativedataweredevel‐
opedwithindividualsrecruitedinthegeneralpopulation[83],andprovideage‐,sex‐,and
education‐correctedScaledScores(SS).UnlikeSABIEXnormativedata,whichprovide
residualz‐scores,NEURONORMAnormativedataprovideSStointerpretperformance,
whichlimitstheselectionofacut‐offpointtodefinelowscores.Toavoidusingdifferent
scales,lowscoreswereidentifiedasSSequaltoorlowerthan6usingNEURONORMA,
andasz‐scoresequaltoorlowerthan−1.28usingSABIEXnormativedata.Individuals
werelabelledasshowinglowscoreswhenshowingatleastonelowscoreasdefined
above.
Asthesameindividualswerecategorizedasshowinglowscoresbasedonboth
SABIEXandNEURONORMAnormativedata,theMcNemartest(correctedforcontinu‐
ity)forrelatedproportions[84]wasusedtoanalyzewhetherthenumberofindividuals
withoneormorelowscoresdifferedbetweennormativedatasets.Additionally,because
itisimportanttonotonlyknowwhethertheproportionsofindividualslabeledasim‐
paireddiffer,butalsowhetherthesameindividualsshowoneormorelowscoresusing
bothnormativedatasets,theFleiss’kappa[84]interratercorrelationcoefficientforcate‐
goricaldatawasusedtoanalyzethelevelofagreementbetweenSABIEXandNEU‐
RONORMAnormativedata.AccordingtoFleissetal.[84],agreementbeyondchancecan
beinterpretedaspoor,fairtogood,andexcellentforvaluesof0–0.40,0.41–0.75,and>0.75,
respectively.
3.Results
Fromapoolof105consecutiveparticipants,twowerenotincludedbecauseofMMSE
scores<24.Thesamplewascomposedof103participants(69women,67%).Participants’
agerangedfrom55to87andyearsofeducationfrom3to22(notincludingUniversityfor
Seniors).DescriptivestatisticsfordemographicvariablesandMMSE,IADL,andGSD
scoresareprovidedinTable1.Statisticallysignificantdifferenceswerefoundbetween
sexesinage(p=0.003,95%CI=1.43,6.67),withmen(M=68.47;SD=6.50)beingolder
thanwoman(M=64.42;SD=6.22),butnotinyearsofeducation(p=0.583,95%CI=−1.04,
1.85),MMSE(p=0.114,95%CI=−1.10,0.12),IADL(p=0.485,95%CI=−0.03,0.06),orGDS
(p=0.240,95%CI=−2.22,0.56).Mostparticipants(59.2%)weremarriedandwereliving
withanotherperson(72.8%).Atotalof63participants(61.2%)reportedahistoryofmed‐
icalillnesses(Table2)and41(39.8%)werecurrentlytakingmedication.Performanceon
neuropsychologicaltestsisshowninTable3.Therewerenostatisticallysignificantdiffer‐
encesbetweensexesintestsperformance.Nostatisticallysignificantdifferenceswere
foundintestsperformancebetweenparticipantswithorwithoutmedicalhistory(allp’s
>0.05),norbetweenparticipantswhowereorwerenottakingmedication(allp’s>0.05).
Table2.Number(and%)ofparticipantswithmedicalhistory(n=103).
n%
Anxiety1918.4
Depression87.8
Epilepsy21.9
Stroke43.9
CVD1211.7

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Hypo/hipertyroidism76.8
Cancer98.7
DM43.9
HBP1312.6
TBI32.9
COPD11.0
RA21.9
Others1411.7
CVD:Cardiovasculardisease,DM:Diabetesmellitus,HBP:Highbloodpressure,TBI:Traumatic
braininjury,COPD:Chronicobstructivepulmonarydisease,RA:Rheumatoidarthritis,Others:
Opticnervesheathmeningioma,hypercholesterolemia,osteopenia,Chronicvenousinsufficiency,
Dyslipidemia,dyspepsia,Cholecystectomy,Autoimmunehypoglycemia,COVID‐19,Asthma.
Table3.Rawscoresonneuropsychologicaltests.
Neuropsychological
MeasuresMSDRange
DSF(n=103)5.361.1533–9
DSB(n=103)3.940.8732–7
LN(n=102)4.501.1152–8
TMT‐A(n=103)47.7916.24924–140
TMT‐B(n=102)119.0857.80741–345
TMT‐BSABIEX(n=102)119.0857.80741–345
SDMT(n=102)37.199.57116–56
M:Mean,SD:Standarddeviation,DSF:DigitSpanForward,DSB:DigitSpanBackwards,LN:Let‐
tersandNumbers,TMT:TrailMakingTest,SDMT:SymbolDigitModalitiesTest.
3.1.CalculationofNormativeData
Theeffectsofage,sex,andeducationvariedacrossneuropsychologicalmeasures.
ThemultiplelinearregressionmodelsarepresentedinTable4.Regressionanalyses
showedthatagewassignificantlyassociatedwithLN,TMTAandTMT‐BSABIEX,and
SDMT.AgeMin2wassignificantlyrelatedtoTMT‐BandTMT‐BSABIEX.Educationhadsignif‐
icanteffectsonDSF,TMT‐A,TMT‐B,TMT‐BSABIEX,andSDMT.EducationMin2wasassoci‐
atedwithDSB,andsexhadnoeffectontheneuropsychologicaltestsincludedinthispa‐
per.Ofrelevancetothisstudywastheassociationfoundindependenttaskswithinthe
TMT.TheregressionanalysesfortheTMT‐BincludingscoresontheTMT‐A(TMT‐BSABIEX)
showedthatperformanceontheTMT‐Aissignificantlyassociatedwithperformanceon
theTMT‐B.
Table4.Multiplelinearregressionmodels.
ΒSE(β)95%CIpcoeffR2Adjusted
DSFIntercept4.7190.2944.14–5.30<0.001
EducationMin0.0760.0320.01–0.14 0.0210.043
DSBIntercept3.6950.1353.43–3.96<0.001
EducationMin20.0030.0010.00–0.00 0.0220.042
LNIntercept5.0140.2044.61–5.42<0.001
AgeMin−0.0480.16−0.08–−0.02 0.0040.071
TMT‐A Intercept48.6764.5539.66–57.70<0.001
AgeMin0.7410.2320.28–1.200.003
EducationMin−1.0510.440−1.92–−0.18 0.0190.111
TMT‐BIntercept155.35214.001127.57–183.13<0.001
EducationMin−6.0291.523−9.05–−3.00<0.001
AgeMin20.0950.0280.04–0.15 0.0010.177

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TMT‐BSABIEXIntercept122.83617.48788.13–157.54<0.001
TMT‐AMin2.0430.2841.48–2.60<0.001
EducationMin−4.3031.272−6.83–−1.78 0.001
AgeMin20.1910.0670.06–0.32 0.005
AgeMin−4.2111.930−8.04–0.380.0320.456
SDMTIntercept36.5082.43531.68–41.34<0.001
AgeMin−0.6550.124−0.90–−0.41 <0.001
EducationMin0.9130.2350.45–1.38<0.0010.273
DSF:DigitSpanForward,DSB:DigitSpanBackward,LN:LettersandNumbers,TMT:TrailMak‐
ingTest,SDMT:SymbolDigitModalitiesTest, β:Regressioncoefficient,SE(β):Standarderrorofβ,
SEM:Standarderrorofthemeasurement.
Forallmultiplelinearregressionmodels,multicollinearity(varianceinflationfactor
[VIF]≤10)wasevaluated.VIFvaluesinallmodelswerewellbelow10andcollinearity
tolerancevaluesdidnotexceedthevalueof1[85].
3.2.ComparingNormativeDataSets(NEURNORMA‐SABIEX)
UsingNEURONORMAnormativedataandtakingascaledscoreof6orlowerasthe
cutoffforalowscore,30participants(29.70%)hadatleastoneormorelowscoresamong
thefivemeasures.UsingSABIEXnormativedata,withTMT‐AandTMT‐Basindepend‐
entandaz‐score≤−1.28asthecutoffforlowscore,32participants(31.68%)hadatleast
onelowscoreamongthesemeasures(seesupplementarymaterial).Thedifferencewas
notstatisticallysignificant(McNemarχ2(n=101)=0.029,p=0.863).TheFleiss’sKappa
coefficientshowedpooragreementintheindividualslabeledasshowingoneormorelow
scoresusingNEURONORMAandSABIEXdata(k=0.209,p=0.036).
UsingtheSABIEXnormativedatasetwiththeTMT‐BconditionalontheTMT‐A
(TMT‐BSABIEX),30participants(29.70%)showedatleastonelowscore.TheMcNemarTest
showednostatisticallysignificantdifferenceswhencomparedtoNEURONORMA
(McNemarχ2(n=101)=0.031,p=0.859).Again,therewaspooragreementidentifying
lowscoresbetweennormativedatasets(k=0.241,p=0.015).
Thenumberoflowscoresshownbyfewerthan10%ofthesamplewastwoormore
withthethreenormativedatasets:NEURONORMA(7.8%;SS<6),SABIEX(8.7%;z≤
−1.28),andSABIEXtakingtheTMT‐BasconditionalontheTMT‐A(9.9%;z≤−1.28).
MMSEscoreswerecomparedbetweenindividualswithandwithoutlowscores
withineachnormativedataset.UsingSABIEXnormativedata,statisticallysignificantdif‐
ferenceswerefoundontheMMSEscores(p=0.010,95%CI=0.22,1.62)betweenindivid‐
ualsshowingoneormorelowscores(M=28.75;SD=1.40)andthoseshowingnolow
scores(M=27.83;SD=1.64).UsingNEURONORMAnormativedata,therewerenosta‐
tisticallysignificantdifferencesintheMMSEscores(p=0.798,95%CI=−0.62,0.80)be‐
tweenindividualswithoneormorelowscores(M=28.50;SD=1.34)andthosewithno
lowscores(M=28.59;SD=1.50).
3.3.ComparingTrailMakingTest(NEURONORMA‐SABIEX)
Separatedcontrastanalysiswasperformedtocomparetheproportionoflowscores
whenusingtheTMT‐BindependentoftheTMT‐A(TMT‐BNEURONORMA)andtheTMT‐B
conditionalontheTMT‐A(TMT‐BSABIEX)
UsingTMT‐BNEURONORMA,thepercentageoflowscoreswas12.75%,andwithTMT‐
BSABIEX,4.9%.ThecorrectedMcNemartestwasnotstatisticallysignificant(McNemarχ2(n
=102)=2.722,p=0.099),probablybecausenoneoftheindividualsshowedalowscore
withbothnormativedatasets.Interestingly,therewasnoagreementbetweenthetwonor‐
mativedatasets(k=−0.097,p=0.344)whenclassifyingindividualsasshowinglowscores.

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Afriendlycalculatorofz‐scoresforDSF,DSB,LN,SDMT,andTMTisavailablefor
cliniciansandresearchersathttps://drive.google.com/file/d/1p‐RDT6F85EsXPxALV‐
l6R8Sq‐E4qGEr0/view?usp=sharing.
4.Discussion
Thisworkaimedtoprovideregression‐basednormativedatafortheDigits,Letters,
andNumbers,TMT,andSDMTtestsforcognitivelyactiveSpanishadultsaged55or
older.Additionally,andcomparedwithothernormativestudies[69,86],ourstudyintro‐
ducedanovelapproachforthecalculationofnormativedatafortheTMT,thatis,consid‐
eringthedependencyofrelatedtasksbycalculatingnormativedatafortheTMT‐Bcon‐
trollingforscoresontheTMT‐A.
RegardingtheuseoftheSABIEXnormativedatacomparedtonormativedataob‐
tainedfromthegeneralpopulation,ourresultsshowedpooragreementinidentifyinglow
scores.Consideringthisdiscrepancyintheclassificationandthatnormativedatamustbe
adaptedtospecificcharacteristicsofindividualsforadequatescoreinterpretation[15,19],
ourdatasuggestthatusingnormativedataobtainedinthegeneralpopulationforthe
neuropsychologicalassessmentofactiveolderadultsmightbeassociatedwithanincrease
inthenumberofmisdiagnosesbyerroneouslyidentifyinglowscores.
Regardingtheresultsintestscomposedofrelatedmeasures,otherstudieshave
shownthatforanaccurateinterpretationofperformanceintheassessment,itisnecessary
toconsiderthecorrelationamongdifferentmeasures[87,88].Eventhoughamoderate
correlation(r=0.31–0.6)betweenTrailAandBhasbeenreported[15],normativedatafor
theTMTareusuallycalculatedtreatingbothpartsasindependents.Thisworkshowsthat
whenTMT‐BisanalyzedconsideringscoresintrailA(TMT‐BSABIEX),theresultsarediffer‐
entfromthoseobtainedwhentheyareconsideredindependent.Inourstudy,astrong
correlationbetweentrailAandB(r=0.62)wasfound,aswellasasignificantcontribution
ofTMT‐AscoresinthepredictionmodelforTMT‐B.Thisfindingsupportsthatinterpret‐
ingthemasindependentmightincreasethelikelihoodofdiagnosticerrorsintheidentifi‐
cationofcognitiveimpairment.Thisconclusionissupportedbythedataindicatingthat
alltheparticipantsclassifiedasshowingalowscoreontheTMT‐BusingtheNEU‐
RONORMAdatasetareclassifiedasshowingaveragescoresontheTMT‐Bconditional
onTMT‐Ascores(TMT‐BSABIEX).
Thedemographicvariablesincludedinthepredictionmodels(age,sex,andeduca‐
tion)haddifferenteffectsacrosstheneuropsychologicaltestsstudiedinthiswork.Asin
previousworks[27,89],ourstudyincludedquadraticageandeducationintheregression
models,whichallowedustoexplorepossiblenon‐linearassociationsbetweenthesevari‐
ablesandperformanceinthetests.Overall,olderageandlowereducationwereassociated
withworseperformance.Thesefindingsareinlinewithpreviousresearchshowingage‐
relateddecreaseinperformanceandpositiveseffectsofeducationoncognitivefunction
[17,90].ConsistentwiththeresultsreportedbySalthouse[91],thecubictermdidnotpro‐
videadditionalinformationoverthemodelincludingthequadraticterm,whichshowed
thatperformanceworsenedfortheoldestagesandincreasedforthehighestyearsofed‐
ucation.
4.1.DigitSpanForwardandBackwards
Arelationshipbetweenolderageandworseperformance,aswellasapositiveeffect
oflevelofeducation,hasbeenfrequentlyreported[54,92].Intermsofeducation,inline
withpreviousstudies,ourworkconfirmstheexistenceofasignificanteffectofeducation
onbothDSFandDSB[54,93].However,therelationshipbetweeneducationandDSB
showedacurvilinearpattern,andcomparedtootherstudies,theeffectsize[93]wassmall
forbothtests(r2=0.05).Contrarytothepreviousstudies[93,94],wedidnotfindany
effectsofageonthedigitspan.
Thefactthatourresultsdifferfrompreviousstudieswitholderadultsintermsof
ageandtheeffectsizeofeducationisofspecialrelevance.Severalworkshavereporteda

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decreaseinperformanceontheDSbeyond65yearsofageandhavealsofoundthatper‐
formanceontheDSisinfluencedbylevelofeducation[19,93,94].However,ithasbeen
reportedthatfrequentcognitiveactivityisassociatedwithareducedrateofcognitivede‐
clineinolderadults[95].Onepossibleinterpretationisthattheinfluenceofageoncogni‐
tivelyactiveadults’performancemightnotfollowthesamepatternthaninthegeneral
populationand,therefore,specificnormativedataforthesepopulationsareneeded.The
smalleffectsizeforeducationsuggeststhatcognitiveactivitiesduringadulthoodhavea
higherinfluencethanthelevelofeducationindeterminingcognitivereserve[51].
4.2.LettersandNumbers(LN)
Regardingtheeffectsofageonperformance,ourresultsshowanegativelinearrela‐
tionshipbetweenageandLNperformance,withalackofcontributionofquadraticage.
Thesefindingsdisagreewithapreviousstudythatreportedasignificantcurvilinearde‐
creasewithage[96]withasampleofyoungandolderadults.Differencesintheagerange
ofthesample,from55to87inourstudyand18to89inMyersonetal.[96],maybere‐
sponsibleforthevariability.However,consistentwithourresults,inthestudyofMyerson
etal.[96],apronouncedlineardeclinewithageisfoundinindividualsbeyond60com‐
paredtothe20‐to60‐year‐olds.
4.3.TrailMakingTest
Inlinewithpreviousstudies,ourresultsindicatethatbothpartsAandBareassoci‐
atedwithageandeducationallevelbutnotwithsex[54,97,98].Moreover,eveninprevi‐
ousworksreportingstatisticallysignificantassociationsbetweensexandTMT[86]orbe‐
tweensexandTMT‐B[99],theseassociationsweresmall,withsexaccountingforanegli‐
gibleproportionofthevarianceontheTMT(<1%).Somestudiesreportedalinearrela‐
tionshipbetweenageandcompletiontimeinbothparts[86,99].Inourstudy,TMT‐B
scoresareaffectedbythequadratictermofage,suggestingthatperformanceontheTMT‐
Bworsensmoremarkedlyintheoldestpopulation.Besides,ourresultssupportthatparts
AandBshouldnotbetreatedasindependentwheninterpretingperformancesoasto
decreasethelikelihoodoffalsepositivediagnoses.TheTMT‐BSABIEXnormativedatamight
provideclinicallyusefuldataasacomplementtoexistinggeneralpopulation‐based
normsforevaluatingSpanisholderadults.Futureworksshouldbeconductedonclinical
settingstoexaminewhethertheuseofbothnormativedatasetsaddsdifferentandvalua‐
bleinformationintheassessmentofattentionandprocessingspeed.
4.4.SymbolDigitModalitiesTest
Inlinewithpreviousworks,wefoundthatyoungerageandhighereducationwere
significantlyassociatedwithbetterperformanceontheSDMT[54,62,89,100,101].Contrary
toRyan[101]andKiely[100],butinlinewithPeña‐Casanova[54]andArango‐Lasprilla
[62],wedidnotfindasignificanteffectofsex.
Sinceolderpeoplehaveanincreasedriskofcognitiveimpairment[102],theavaila‐
bilityofappropriateandreliablenormativedataisessentialforearlyandaccurateidenti‐
ficationofpathologicalchangesincognition.Althoughseveralstudieshavereportedon
normativedataforolderadults,thesestudiesusedgeneralpopulation‐basedsamples.
Thefindingthatthereisnoagreementintheindividualslabeledasshowinglowscores
whenusingnormativedataobtainedfromthegeneralpopulationandSABIEX‐specific
normativedatahighlightstheneedforspecificnormativedataforhighlycognitivelyac‐
tivepeople.
Animportantaspectthatdistinguishesthesenormativedataisthatwedidnotex‐
cludeparticipantswithahistoryofmedicalconditionsthatcouldaffectneuropsycholog‐
icalfunctioning.Ithasbeensuggestedthatlessrigorousexclusioncriteriamightdecrease
thesensitivityofthenormativedatatoidentifytruecognitiveimpairment[103].However,
sinceboththeincidenceandprevalenceofchronicdiseases[104]andmultimorbidity[105]

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increasewithage,thepresenceofmedicalconditionsisfrequentintheolderpopulation.
Therefore,includingonlyhealthyolderadultsinanormativestudycouldbiastheresults
asthesamplewouldbeunrealisticandnotrepresentativeofthepopulationthatwillbe
assessedwiththesenormativedata.Moreover,usinganextremelyhealthysamplemight
increasetheriskofoverdiagnosingcognitiveimpairmentinclinicalsettings.Asinother
normativestudiesforolderadults[26,83],weensuredthenormalcognitivefunctioning
ofparticipantsincludedinoursamplethroughthescoresintheMMSE,CDR,andinde‐
pendenceintheADLs.
Regardingtheclinicalapplicabilityofthesenorms,theneuropsychologicaltestsde‐
scribedinthispapermightbeusefulintheprocessofdiagnosingcognitiveimpairment
anddementia.Sinceactiveolderadultsmayhaveabettercognitivefunctioningcompared
tosame‐agepeoplefromthegeneralpopulation[50,95],impairedperformancecouldbe
moredifficulttoidentifythroughtestsstandardizedonthegeneralpopulation.Thenor‐
mativedatareportedinthepresentworkmightbeespeciallyhelpfulforcliniciansand
researcherstoaccuratelyinterpretscoresofolderadultswhocontinuetoleadaveryactive
lifeduringaging,identifyinglower‐than‐averageperformancemoreaccuratelyand,thus,
reducingtheriskofdiagnosticerrorsiflowscoresaretobeusedtodiagnosecognitive
impairment.SinceindividualswithMCIareatgreaterriskofAD[9,106],theSABIEXnor‐
mativedatamighthelptoidentifyMCIwithgreatercertaintyinhighlycognitivelyactive
Spanishindividuals.Oneofthestrengthsofthisworkisthatweprovidenormativedata
forfiveneuropsychologicalmeasures,whichallowsthecomparisonofanindividual‘s
performanceacrossthedifferentnormedtests.
4.5.Limitations
Thesenormativedatashouldbeinterpretedwithlimitations.First,thesampleused
tocalculatethemwastakenfromuniversitycoursesforseniors.Thisrestrictsthegeneral‐
izabilitytothepopulationwiththischaracteristic.InSpain,duringthe2019–2020aca‐
demicyear,thenumberofadultsthatparticipatedinthesecoursesamountsto35.199
(https://www.aepum.es/)(accessedon20June,2021),whichrepresents0,22%ofthepop‐
ulationaged55orolder(https://www.ine.es)(accessedon13February,20221).However,
differentstudieshavereportedthatotheractivepracticesduringaging,suchasvolun‐
teering,contributetothemaintenanceofcognitivereserveandpositivelyimpactolder
adults’cognitivefunction[107,108];therefore,itisrecommendedtoanalyzewhetherthese
normativedataarealsoappropriatetoproperlyinterprettheperformanceofolderadults
engagedincognitivelystimulatingactivitiesotherthanuniversitycourses.
Anotherpotentiallimitationofthepresentstudyisthat,duetothecompositionof
thesample,thesenormativedatawillbeusefulonlyforpeoplebetween55and87years
oldandwith3to22yearsofeducation.Additionally,takingintoaccountthewell‐docu‐
mentedeffectsofcultureonthediscrepancyinperformanceinthedifferentcognitivedo‐
mains[109,110],anotherlimitationofthesenormativedataisthattheyareonlyapplicable
totheSpanishpopulation.TheirusewithotherSpanish‐speakingpopulations,withdif‐
ferentculturalbackgrounds,islimited.Somestudieshavefounddifferencesinperfor‐
manceinthetestsincludedinthisworkamongindividualsfromdifferentSpanish‐speak‐
ingcountries[62,69],andusingthesenormativedatamightresultindiagnosticerrors.
Afurtherlimitationofthisstudyisthatthenormativedataareobtainedwithcogni‐
tivelyactiveadults,buttheyhavenotbeenappliedinclinicalpopulations.Itisstillun‐
knowniftheyareadequatetoidentifycognitiveimpairment.Futurestudiesshouldbe
conductedwithclinicalpopulationstohelptoclarifytheclinicalusefulnessofthesenor‐
mativedata.Therefore,wesuggestusingthesenormativedataasasupplementofexisting
general‐population‐basednormsuntiltheirclinicalutilityisanalyzed.Anotherlimitation
isthefactthatz‐scoresequaltoorlowerthan−1.28wereusedtointerpretperformance
anddefinelowscores,whilstthemostcommonlyusedcut‐offpointtointerpretcognitive
impairmentisatleast1.5standarddeviationsbelowthemean.

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Lastly,sinceagingisassociatedwithchangesinthebrainstructureandinthefunc‐
tionalconnectivityrelatedtocognitiveprocesses[111,112],alimitationofthepresent
studyisthelackofneuroimageprofilestoanalyzecorrelatesbetweenbrainstructure,
functionalconnectivity,andparticipants’variabilityincognitivefunctioning(e.g.,
whetherthenumberoflowscoresisassociatedwithdifferentstructuralbrainalterations
ortheconnectivitybetweendifferentbrainareas).Byanalyzingourresultstogetherwith
magneticresonanceimages(MRI),amorecompleteunderstandingoftheeffectsofaging
onnetworkfunction,brainstructure,andcognitivefunctionwouldbeobtained.Future
worksarewarrantedtoidentifytheassociationofacognitivelyactivelifestyleandcogni‐
tivefunction,brainstructure,andbrainconnectivity.
5.Conclusions
Inconclusion,thepresentworkprovidesnormativedataforacognitivelyactive
Spanishpopulationthatmayhelptoidentifycognitiveimpairmentduringaging,improve
diagnosticprecision,andreducediagnosticerrors.Ourfindingshighlighttheimportance
ofusingappropriatenormativedata,relevanttothepopulationbeingassessed.Despite
theavailabilityofSpanishnormativedatafortheolderpopulation,ourresultssuggest
thattheaccuracyintheinterpretationofactiveolderadults’performancemightbemax‐
imizedusingpopulation‐specificnormativedata.
SupplementaryMaterials:Thefollowingareavailableonlineatwww.mdpi.com/arti‐
cle/10.3390/ijerph18199958/s1,TableS1:Comparingnumberoflowscoresbetweennormativedata
sets(NEURONORMA‐SABIEX),TableS2:Comparingnumberoflowscoresbetweennormative
datasets(NEURONORMA‐SABIEX)withTMT‐BconditionalonTMT‐A,TableS3.Comparing
numberoflowscoresonTMT‐Bindependent(TMT‐BNEURONORMA)andTMT‐Bconditionalon
TMT‐A(TMT‐BSABIEX)
AuthorContributions:Conceptualization,J.O.‐C,E.S.‐M.,andB.B.‐L.;methodology,J.O.‐C,C.I.,
andE.C.‐R.;formalanalysis,C.I.andJ.O.‐C.;investigation,C.I.,J.O.‐C.,B.B.‐L.,E.C.‐R.,andE.S.‐M.;
datacuration,C.I.andJ.O.‐C;writing—originaldraftpreparation,C.I.andJ.O.‐C;writing—review
andediting,C.I.,J.O.‐C.,B.B.‐L.,E.C.‐R.,andE.S.‐M.;supervision,J.O.‐C.,E.S.‐M.,andB.B.‐L.All
authorshavereadandagreedtothepublishedversionofthemanuscript.
Funding:Thisresearchreceivednoexternalfunding.
InstitutionalReviewBoardStatement:Thestudywasconductedaccordingtotheguidelinesofthe
DeclarationofHelsinkiandapprovedbytheEthicsCommitteeoftheMiguelHernandezUniversity
(protocolcodeDPS.ESM.01.19).
InformedConsentStatement:Informedconsentwasobtainedfromallsubjectsinvolvedinthe
study.
DataAvailabilityStatement:Dataareavailableatrequestfromthecorrespondingauthor.
Acknowledgments:None.
ConflictsofInterest:Theauthorsdeclarenoconflictofinterest.
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