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HowPhysicalAmenitiesRelatetotheMentalWell-beingofColumbusResidents

KoriGoldberg

Advisor:JeremyBrooks

SchoolofEnvironmentandNaturalResources

TheOhioStateUniversity

Spring2016

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Introduction

The2014Gallup-HealthwaysWell-BeingIndexanalyzeddataconcerningthewell-beingof

individualsineverymetropolitanstatisticalareaoftheU.S.tolearnmoreaboutthe

nation’swell-being.The“happiest”metropolitanareastendedtobethosewithlow

unemploymentrates,lowpovertyrates,andwarmclimates.Unfortunately,Ohiohadtwo

citiesrankedinthetopten“unhappiest”areas,oneofwhichwasColumbus,whichranked

eighthfromthebottomofthe2014well-beingstudy.Ohiohasconsistentlyhadoneofthe

tenlowestscoresforstatewidewell-beingsince2008whenthestudybegan.Well-beingis

importantbecauseitisanindicationofindividuals’satisfactionwithlifeandhighlife

satisfactionencouragespeopletostayincommunitiesandhelpthemthrive.Inaddition,

policyexpertscareaboutwell-beingbecauseitisoneofmanywaystomeasureand

understandthesuccessandprogressofacommunity.

Well-beingisoftendescribedashavingmanycomponentsandthesecomponentsare

categorizeddifferentlydependingonthefieldofstudyandtheobjectiveoftheresearcher

(Layard,2010).Forinstance,VölkerandKistemann(2011)describewell-beingasa“a

complexmeasurablesubjectivestateofconsciousnesscomprisedofmultipledistinct

components.”Animportantcomponentofwell-beingismentalhealth.Researchthateither

directlyorindirectlyaddresseswell-beingcommonlyreferstothispsychologicalaspectof

well-beingas“positivementalhealth”or,asitisreferredtothroughoutthisthesis,“mental

well-being”(MWB)(Ruthetal.,2007).

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MentalhealthisdefinedbytheWorldHealthOrganizationas“astateofwell-beinginwhich

everyindividualrealizeshisorherownpotential,cancopewiththenormalstressesoflife,

canworkproductivelyandfruitfully,andisabletomakeacontributiontoherorhis

community”(WHO,2014).Healthy,prosperous,andcooperativecommunitiesrelyon

mentallyhealthyresidentsbecausementalhealthdeterminestheextenttowhichresidents

cansuccessfullyovercomechallengesandcontributeeconomicallyandsociallytotheir

community(Galson,2009).Acomplexcombinationoflifestylefactorsandcircumstances

affectemotional,spiritual,andintellectualwell-being,orcollectively,MWB(Corvalanetal.,

2005).Inthisstudy,mentalwell-beingismeasuredusingfiveself-reportedfactors:

spiritualhealth,happiness,enjoymentofleisuretime,positivity,andlifesatisfaction.

Theassessmentofindividualmentalwell-beingiscomplexbecausemanyfactorshavebeen

foundtoaffectit.TheeffectsofdifferentlifefactorsonMWBaredifficulttomeasureand

disentanglefromeachother(DienerandSuh,2000).Someidentifiedfactorsthataffect

well-beingincludeincome,race,gender,andtypeandstateofgovernment(2000).There

aresomespecificfactorsthatconsistentlyshowrelationshipswithmentalwell-being;one

withsignificantpotentialtoaffectMWBisthephysicalsurroundingsofanarea(Jackson,

2003).

Promisingresearchatthenexusofenvironmentalpsychologyandurbanplanninghas

shownthatwell-beingandphysicalsurroundingsareaffectedbyeachother(Leeand

Maheswaran,2010).Threeaspectsspecifically,greenspace,bluespace,andwalkability

mayaffectMWB.Greenspaceisspaceinanurbanareacoveredingrass,trees,orother

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vegetation.Bluespacereferstospacethatiscoveredbyorincloseproximitytorivers,

lakes,ocean,oranyothernaturalormanmadewaterfeatures.Walkabilityisameasureof

howfeasibleandcomfortableitistoaccomplishpedestrianactivitiesinaneighborhood.

Importantly,thereisagrowingamountofliteratureexploringtherelationshipbetween

suchurbanenvironmentalamenitiesandlevelsofmentaldistress(Whiteetal.,2013;

KarmanovandHamel,2008;VolkerandKistemann,2011).

Forinstance,high-quality,accessiblegreenandbluespacemaycontributetohigheroverall

scoresofcommunities’mentalwell-being(KarmanovandHamel,2008).Astudyonthree

communitiesinNewHampshirefoundthaturbanplanningpracticesthatleadtohigher

levelsofwalkabilityhaveimplicationsforhigheroverallqualityoflife(Rogersetal.,2010).

Asmoreresearchisexecutedandpublished,especiallyinareasliketheMidwestwhere

minimalresearchhasbeendone,plannersmaygainstrongerjustificationwhenadvocating

forhigherqualityandquantityoftheseamenitiesinurbanareas.Thisstudyaimstoshed

lightonseveralquestionsrelatedtoenvironmentalamenitiesandlevelsofmentalwell-

being.

1) First,doestheavailabilityofgreenspace(parks,cemeteries,golfcourses)inone’s

neighborhoodcorrelatewithoverallmentalwell-beingoraspecificmeasureof

mentalhealth(happiness)?

2) Doestheavailabilityofbluespaceinaneighborhoodcorrelatewithoverallmental

well-beingofresidentsoraspecificmeasureofmentalhealth(happiness)?

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3) How,ifatall,doesneighborhoodwalkability(measuredassidewalklength)relate

tomentalwell-being?

Background

Boththenaturalandbuiltenvironmenthavedailyandsignificanteffectsonourmental

stateandbehaviors(Jackson,2003).Threeaspectsofneighborhooddesignthatmayaffect

MWBaregreenspace,bluespaceandthewalkabilityofthearea.

Thebiophiliahypothesis,putforthbyE.O.Wilson,suggeststhatinteractionwiththe

environmentanditslivingcomponentsisfundamentaltohumanwell-being(Wilson,

1984).Theauthorhypothesizedthathumansarepredisposedtoaloveoflivingthingsand

heteachesthatphysical,emotional,andphysiologicalbenefitsaccruetoindividualswho

haveanappreciationforandconnectiontonature.Furthermore,arelatedhypothesis

proposesthatgreenspaceinurbanareascanhavesignificanteffectsonthementalwell-

beingofpeoplewholivenearit(Fulleretal.,2007).

Inthefieldofcityandregionalplanning,itiscommonforpolicymakerstoregardgreen

spaceasaluxurygood,underestimatingthehiddenpotentialforgreenspacetopositively

affecturbanresidents(Groenewegenetal.,2006).Ameta-studyconductedin2010

concludedthereisalackofconcreteevidenceassociatingmentalhealthandgreenspace

despiteanumberofpreviouslypublishedstudies(LeeandMaheswaran,2010).The

researchersreviewedstudiespublishedafter1990withaspecificfocusongreenorpublic

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openspacesastheyrelatetohumanhealth.Thiswasdoneinanattempttodevelopa

“narrativesummaryforhealthpolicy-makersandurbanplanners”(LeeandMaheswaran,

2010:212).Thismeta-studyfoundarangeofresultssuchasstrongsupportfortheclaim

thatgreenspaceoffersincreasedopportunityforexercise,whichinturnimproves

residents’physicalhealth.Asfortheconnectionbetweenmentalhealthandgreenspace,

thesestudiestendtorelyonqualitativereportsratherthanquantitativestudies.Positive

correlationsbetweengreenspaceandsocialcapital,senseofsafety,andreducedstress

werepresentedanddiscussed.Thesecorrelationswerefoundtobegenerallyconsistent

acrossthereviewedstudiesdespitedifferentlocationsandmeasurementtoolsusedby

researchers.

Greenspacehasbeenfoundbothtoreducestressandanxietyassociatedwithnegative

mentalhealthandalsotoaddpositivementalbenefitstothosewhointeractwithit(Van

DenBergetal.,2010).Studieshaveshownthatnearnessandinteractionwithgreenspace

canreducesymptomsofanxietyanddepressionandimproverecoveryfrommentalfatigue

(PearsonandCraig,2014).Researcherswholookedatindividualsmovingtogreenerand

lessgreenurbanareasfoundthat“sustainedmentalhealthimprovements”(VanDenBerg

etal.,2010:1247)wereassociatedwithindividualswhomovedtourbanareasthatwere

greenerthantheirpreviousneighborhoods(Alcock,2014).AstudyofDutchresidents

foundthatthepresenceofgreenspaceincommunitiescanmitigateboththephysicaland

mentalnegativeeffectsthatstressfullifeeventshaveonindividuals(VanDenBergetal.,

2010).Exercisedoneingreenspacehasbeenfoundtoresultinhigherratingsofmental

well-beingthansimilaractivityconductedinanindoorenvironment(Coonetal.,2011).

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WhilesomerelationshipsbetweenMWBandgreenspacehavebeenfound,themeta-study

discussedearlierconfirmsthatcurrentevidenceandconclusionsinthisareaofresearch

arestillweakatbest(Whiteetal.,2013;LeeandMaheswaran,2010).

Inrecentyears,another,lesser-knowntypeofspacecalled“bluespace”iscapturingthe

attentionofresearcherswhobelievethatitmayhavebenefitssimilartothatofgreen

space.OnestudylookedathowthehealthofEnglishresidentsrelatedtotheirresidential

proximitytowater.Theresearchersfoundthatasdistancetothecoastdecreased,overall

healthincreased(Smedley,2013).Resultsfromthisstudyindicatedthatotherwater

featuresalsopositivelyaffecthealth.Aplausibleexplanationsforthisrelationshipfocuses

onthefactthathumans“evolvedinintimatecontactwithnature,anditisonlyreallyinthe

last200yearsthatpeoplehavebeenincreasinglyremovedfromnature“(2013).Humans

mayhaveaninnatedesiretobenearwater:“Thereissomethingdeeplyprofoundabout

waterandhumans,anditmayreflectevolutionaryhistory",marinebiologistAlisterHardy

hassaid(2013).Humanattractiontowatermayrelatebacktoandbeanextensionofthe

biophiliahypothesis(Wilson,1984).

Further,KarmanovandHamel(2008)foundthatbluespaceinurbanandnaturalcontexts

isassociatedwithmultiplepositiveeffectsincludingmoodenhancement,stressreduction,

andexpansionofmentalattention.Therangeofrecreational,restorativeandspiritual

benefitsofbluespacehavebeendocumentedonanindividualandpersonallevel(Völker

andKistemann,2011).Inastudypublishedin2010participantswereshownarangeof

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120photoswithamixofgreen,blue,andbuiltspaceandtheirreactionstotheimageswere

recorded.Theresearchersfoundthatbluespaceinnaturalandbuiltenvironments

producedmorepositivesubjectivereactionsfromindividualsthansimilarareaswithout

waterfeatures(Whiteetal.,2010).

VolkerandKistemann(2011)lookedatliteraturerelevanttobluespaceandwell-being,

ultimatelyincluding36studiespublishedafter1981.Acrossthestudies,viewsof

landscapescontainingwaterwereconsistentlyreportedas“positive,attractive,and

fascinating”withtheexistenceofwaterfeaturesbeing“astrongpredictorofpreferencefor

landscapesingeneral”.Thispreferenceexistsduetobluespace’spotentialtooffer

refreshing,calmingandenergizingeffects(VolkerandKistemann,2011;Whiteetal.,2010).

Thereviewalsopointsoutfascinatingspiritualandemotionalreactionsbyindividualsin

responsetothepresenceofwaterintheirlandscapes.Studiesalsoexistthatquantitatively

supportthenotionthathumanspreferenvironmentswithwatersuchasa2000studythat

usedahedonicmodeltoshowthathousepricesnearwatertendtobehigherthanthose

notnearwater(Luttik,2000).Asarelativelynewfieldofinquiry,bluespacemayhave

intuitiveandencouragingbenefitsforallbutthereisanoticeablelackofresearch

addressingtheeffectofwateronurbandwellers(Luttik,2000).

Walkabilityofaneighborhood,inadditiontogreenandbluespace,mayalsoaffectthe

MWBofitsresidents.Walkabilityreferstothewaysinwhichthebuiltenvironmentenables

pedestrianactivities.Inthepastdecade,walkabilityhasreceivedincreasedattentionin

regardstoitsrelationshiptohumanhealth.Andrewsetal.(2012)note“aninitialscanof

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theliteraturepublishedinSocialScience&MedicineanditssisterjournalHealth&Place

foundmorethanfortypapersthatfocusexclusivelyonwalkability”.Anumberofthese

studieslookedattheconnectionbetweenmentalhealthandwalkableareasandfoundthat

pedestrianactivities,facilitatedbyimprovedwalkabilityofneighborhoods,providemeans

forresidentstoexperiencearangeofpositiveemotions,includinghigherself-confidence

andothertherapeutic,spiritualandescapefulfeelings.

Likebluespace,researchintothebenefitsofwalkableneighborhoodsisanemergingfield

thatstillhaslimitedconclusionsbuthasexperiencedimmensegrowthinrecentyears

(Florida,2011).Citiesandneighborhoodswithhighlevelsofwalkabilityhavebeenshown

tofosterhighlevelsofsocialcapitalandcontributetophysicallyhealthyandmore

emotionallyrelaxedresidents(Abrahametal.,2009).

Inonestudy,researchersfoundspecificbenefitsofexerciseforpeople65andolder

includingbetterqualitysleep,delayedonsetofmanydiseases,improvedperceptionoflife

condition,andpositiveeffectsoncognition(SugiyamaandThompson,2007).Inadditionto

encouragingmorephysicalactivity,walkableareashavealsobeenassociatedwithhigher

levelsofcivicengagementandsocialcapital,bettercognitivehealthofresidents,andcrime

reductionincommunities(Florida,2014).

Scalesthatassessandmeasurethewalkabilityofanareamaytakeintoaccountawide

rangeoffactorstogenerateatruemeasurementofthewalkabilityofaspecificaddressor

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generalarea.Commontechniquesusedtoevaluatewalkabilityarepresentedinthe

discussion.

Thoughthereareanumberofstudiesexploringthepositivementalbenefitsassociated

withhighlevelsofaneighborhood’sgreenspace,bluespace,andwalkability,muchofthis

researchhasbeenconductedinEuropeancountries.StudiesfocusedontheurbanMidwest

arefarlesscommon(KarmanovandHamel,2008;LeeandMaheswaran,2010;Abrahamet

al.,2009).Assuch,thisstudylooksatMWBscoresandbuiltenvironmentcharacteristicsto

exploreifandhowthesehypothesizedrelationshipsarepresentinneighborhoodsof

Columbus.

Methods

Theprocessofcollectingdataforthisstudycanbesplitintothreeparts.Collecting

informationregardingthedependentvariable,theindependentvariablesandthecontrol

variableswasdoneinseparateways.

I.Dependentvariable:MentalWell-Being

Dataforthedependentvariableofthisstudy,themulti-dimensionalmeasureofmental

well-being,wascollectedduringFall2015andJanuary2016.Thedatacomesfromasurvey

designedforabroaderstudyexploringtherelationshipbetweenconsumption,

environmentalimpacts,andwell-being.

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Phaseoneofdatacollectioninvolveddevelopingawell-beingmetricforthecityof

Columbus.Ithasbeensuggestedthatacontextspecificmeasurementofwell-beingshould

beusedinthecollectionandcalculationofwell-beingscoresinaparticulararea(Corvalan

etal.,2005).Themetricusedinthisstudywasderivedfromfeedbackgatheredfrom

Columbusresidentsthroughtwointeractiveprocesses.Researchersusedfocusgroupsand

“streetstalls”toengagewithresidentstodeterminetheextenttowhichcertainfactors,

derivedfromtheOxfamHumankindIndex,contributetooverallwell-being(Walkeretal.,

2012).Anexampleoftheactivitydoneatstreetstalls,whereparticipantsrankedthe

importanceof19differentcomponentsofwell-being,canbeseeninAppendixA.

FeedbackfromColumbusresidentsresultedinafinallistof26factors,whichwere

categorizedintoseveralcategories;onecategoryincludedanyfactorsthatmeasuredan

aspectofthementalhealthofindividuals.Theprimarydependentvariableusedforthis

studyisanindexofthesefiveWBfactorsthatrelatespecificallytomentalhealth.In

addition,asecondaryanalysisusedasinglecomponentofthisindex(happiness).

PhaseTwoofdatacollectionwasasurveyconductedintwoneighborhoodsofColumbus.

ClintonvilleandOldeTowneEastwerechosentoexplorevariationintheirgreenspace,

bluespace,andwalkabilityaswellasfortheirsocio-economiccharacteristics(seebelow).

Withineachneighborhood,sixterritorieswereselectedbasedonboundariesofUScensus

blocks.

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The“drop-off,pick-up”(DOPU)methodwasusedtodistributesurveystohouseholdson

threerandomlyselectedstreetsineachofthesixterritoriesofbothneighborhoods.This

methodwasusedbecauseithasbeenfoundtohaveahigherresponseratethanstandard

mailsurveysandbecauseoftheclusteringofhouseholdsintheterritoriestargetedbythe

study.InadditionDOPUhasbeenfoundto“offerpromiseforreducingnon-coverageerror

andpossiblesamplebiaswithoutsacrificingresponserates(Steeletal.,2001).

Researchersaimedtomaximizecontactwiththosesurveyedbyinitiallyonlydropping

surveysoffathouseswhereresidentsansweredthedoor.Respondentswereinformedof

thegeneralnatureofthestudyandtheimportanceofaccuratelyfillingoutthesurveysto

thebestoftheirability.Surveyswereexpectedtotakebetween15and20minutesand

respondentswereinformedthatresearcherswouldreturninseveraldaystopickup

completedsurveysthatcouldbelefthangingonthedoorintheprovidedbag.Onsurvey

visitstheresearchersalsoinformedparticipantsofanonlineoptiontocompletetheir

surveys.Eachofthethreestreetsineachterritorywasultimatelyvisitedfourtimesin

ordertogatheradequateresponsesandgivemultiplechancesforaresponse.Afterthe

fourthvisit,surveyswereleftatallhouseholdsforwhichtherewasatleastoneattemptto

contacttheresident(upto75householdsperterritory).

Thesurveycontainedquestionsrelatedtoenvironmentalbehaviors,well-being,and

demographics.Thewell-beingportionofthesurveyincludedthepreviouslymentioned26

factorsforrespondentstoratethemselveson.Thefactorswerepresentedasstatements

andrespondentswereaskedtoratethemselvesonascaleof1-7(1=stronglydisagree,

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7=stronglyagree).MWBdatawascollectedfromsurveyresultsof271individualsacross

allsurveyedterritories.

AnalgorithmwasdevelopedtocombinethemetricdevelopedfromColumbusresident

feedbackinPhaseOneandtheself-ratingscollectedfromPhaseTwo.Thedatafromphase

onewasusedtoassignaweightingforeachcomponentofwell-beingbasedontheaverage

rankingitreceivedfromparticipants.Assuch,eachfactorwasassignedamultiplier

between.16and1.5toindicatehowimportantthefactorisasacontributortoColumbus

residentwell-being.Inaddition,thisweightingvariedbyagegrouptoreflectthelikelihood

thatthefactorsthatcontributemosttowell-beingchangethroughone’slifecycle(seetable

1).TheadditionalfactorsthatwereaddedafterPhaseOnewereassignedaneutralvalueof

.79(theaverageforthe19componentsincludedinthatstudy).Themultiplierwasthen

appliedtoeachrespondents’self-reportedscoresandsummedtocalculateafinalmental

well-beingvalueforeachterritory(seeAppendixB).Thefivefactorsthatrelatetomental

well-beingandtheirweightsareshowninTable1.

Table1.Mentalwell-beingfactorsandtheirweights

Factor Weightperagegroup

Onanaverageday,Ifeelmentallyhappy(happiness)

Age18-30:1.07Age31-45:1.07Age46-60:0.74Age61-88:1.09

Ienjoymyleisuretime

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(leis.time) Age18-30:1.07Age31-45:1.13Age46-60:0.87Age61-88:0.75

Ihavegoodspiritualhealth*(spir.hlth)

Age18-30:0.79Age31-45:0.79Age46-60:0.79Age61-88:0.79

Iampositiveaboutmyfuture*(pos.future)

Age18-30:0.79Age31-45:0.79Age46-60:0.79Age61-88:0.79

Ifeelgoodaboutmyselfandmylife(feel.good)

Age18-30:1.02Age31-45:0.65Age46-60:0.74Age61-88:0.89

*=oneofsevenfactorsaddedafterfeedbackandresponsesfromPhaseOneofdata

collection

StudySites

BecausethetwoneighborhoodsstudiedinColumbusdonothavedistinctgeographic

boundaries,twozipcodeswereassociatedwitheachoftheneighborhoodsandthelimitsof

thesezipcodeswereusedtodefinetheneighborhoods.Clintonville(43214and43202)is

regardedasaprestigiousneighborhoodofColumbus,whileOldeTowneEast(43202and

43205)hasalessprestigiousreputation.Clintonvillehasbeenexperiencingrisinghousing

pricesinrecentyearswhileOldeTowneEastcontinuestoseehighratesofvacancy.Both

havesimilaraccessibilitytoColumbus’downtownandarewithinthe270outerbelt.In

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termsofdemographics,Clintonvilleislargelywhite(91%“whitealone”)whileOldeTowne

Easthasamuchmoremixeddemographicmakeup(60%“whitealone”)(U.S.Census,

2010).Clintonvillehasahighermedianincome($53,112)andlessvariancethanOlde

TowneEast,whichhasalowermedianincome($35,499)andalargerdiversityofincome

levels.Blockgroupswerechosenwithinthesetwoneighborhoodsbasedoncensusdata

from2010toensurethattherewasdemographicvariation(specificallymedianhousehold

incomeandrace)betweentheblockgroups.Sixblockgroupswerechosenineach

neighborhoodtomakeatotaloftwelveblockgroups.Thesetwelveblockgroupsare

referredtoas“territories”throughoutthestudy.Finally,threestreetsperblockgroupwere

randomlychosen.Theterritories’locationsandsizes,aswellasthespecificstreets

surveyedcanbeseeninFigure1

II.IndependentVariables

Inordertogenerateandorganizethedatarelevanttothetwelveterritoriesandtheirgreen

space,bluespace,andwalkability(theindependentvariables),QGISandExcelwereused

extensively.Ultimatelyfourdistinctindependentvariablesweredefined:greenspace

acreage,percentagegreenspace,sidewalklength,andpercentagebluespace.Thevalues

fortheseamenitieswerecalculatedforeachofthetwelveterritoriesandaresummarized

intable2.

Greenspaceacreagereferstothenumberofacresofgreenspacewithinorintersectinga

territory’sone-milebufferzone.Percentagegreenspaceistheamountofspace(inacres)in

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aterritory’sone-milebufferzonedividedbythetotalacreageofthatzone(zonesdiffered

insizebecauseofsmalldifferencesinterritorysize).Sidewalkwascalculatedbymeasuring

distanceofsidewalkwithinaterritory’sone-milebufferzoneinmiles.Bluespacewas

definedasanypointthatwaswithinaone-miledistanceofamainwaterfeature.

Percentagebluespacewasacreagewithinaterritory’sone-milebufferzonethatwas“blue”

dividedbythetotalacreageofthatzone.

Tobegindatacollection,publiclyaccessiblefilesfromtheMid-OhioRegionalPlanning

Commission(MORPC)wereusedtomapoutgreenspace.Thefileusedcontainsspatial

informationofgolfcourses,cemeteriesandparksinandaroundColumbus.Figure1shows

thebaselayersforworkthatwasdoneinQGIS.Territoriesinthetopleftcornerare

Clintonville1-6andtheterritoriesinthebottomleftareOldeTowneEast1-6.Thismap

alsocontainsMORPC’sopenspacedata(darkgreenareas),asidewalkinventory(with

thoseactuallyusedforsurveyingpurposeshighlightedinwhite),andthemajorrelevant

riversandtributariesthroughoutthearea.

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Figure1.QGISmapofthe12territoriesstudiedandtheirassociatedgreenspace,sidewalk

andwaterfeatureswithsurveyedstreetshighlightedinwhite

ForeachterritoryIcalculatedthepercentageofgreenspacewithinaone-mileradius

aroundtheperimeterofeachterritory.TheanalysiswasperformedinQGIS.Aone-mile

bufferwasdrawnoutwardfromtheperimeterofeachofthetwelveterritoriesbecause,

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althoughthedistancepeoplearewillingtowalkvariesbypersonandbytrip,studieshave

foundthatpedestrianswalkmuchfartherdistanceswhenthedestinationorpurposeisfor

leisureorrecreation(YangandDiez-Roux,2013).Thedistanceofone-milewaschosen

becauseitisestimatedtobeagoodrepresentationofhowfarpeoplearewillingtowalkin

ordertoaccessgreenspace(Iaconoetal.,2008,Donahue,2011).

Oncethebufferswerecreatedthegreenspaces“intersecting”or“contained”bytheone-

milebufferlayerwereselectedindividuallyforeachterritory.Greenspacesthatwere

withinthelayerwereclassifiedas“accessible”,aswellthosethatintersecttheone-mile

buffer,becauseitwasassumedthatifresidentscouldaccessanypartofagreenspace,then

thatentirespacewasaccessible.Figure2showsClintonville6(orange),itsone-milebuffer

zone,andthegreenspacethatiswithinorintersectingtheone-milebuffer(highlighted

darkblueareas).

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Figure2.Clintonville6territory,one-milebufferzone,andassociatedgreenspace

Theacreageofeachbufferedareawascalculatedandthebasicstatisticsanalysistoolwas

utilizedtoconvertunitsandcalculatethetotalgreenspacewithinthebufferzone.Finally,

theacreageofgreenspacewithinorintersectingthezonewasdividedbythetotalacreage

ofthezone,resultinginagreenspacepercentageassociatedwiththatterritory.

Tomeasurebluespace,aone-milezonewasusedagaintodeterminehowmuchofthe

territory’sareaiswithinaone-miledistancetoariverortributary(spatialinformationon

waterfeaturesobtainedfromtheUSGSNationalHydrographyDataset,2011).Then,the

geoprocessingtoolinQGISwasusedtocreateanalgorithmtoselectonlyfeaturesthat

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overlappedbetweentheone-milebufferedindividualterritorylayerandthenewwater

bufferlayer.AnexampleofthebluespaceassociatedwithaterritorycanbeseeninFigure

3.Finally,theacreageofbluespaceintheterritorywasdividedbytheterritory’stotal

acreagetogetpercentagebluespacewithintheterritory’sbufferzone.

Figure3.Clintonville1(darkpurpleterritory)shownwiththebluespacelayerenacted

(lightblue)andtheportionofClintonville1’sone-milebufferzonethatoverlapswithblue

space(teal)

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Tomeasurewalkability,Icalculatedthedistanceofsidewalkwithintheone-milebuffer

area.WithinQGIS,theselectbylocationalgorithmwasusedtoselectandsumthelengthof

sidewalks(inmiles)thatwerecontainedwithintheterritory’sbufferzone(Figure4).

Figure4.Sidewalklength(highlightedinorange)usedtocalculatewalkabilityfor

Clintonville6

OnceamenityvaluesweredrawnfromQGIS,thedatawascompiledinexcelandconverted

intoproperunits.ThedataforeachterritoryissummarizedinTable2.

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Table2.Summaryofphysicalamenitydataperterritory

TerritoryGreenSpace

Acreage

%GreenSpace

within1milebuffer

Sidewalk

Lengthinmiles

%BlueSpace

within1milebuffer

CV1 228.41 7.46% 136.99 56.40%

CV2 230.12 6.41% 164.74 62.71%

CV3 359.95 11.67% 125.59 95.42%

CV4 316.88 9.62% 145.58 91.83%

CV5 285.2 7.13% 169.06 94.95%

CV6 565.48 16.24% 113.33 100.00%

OTE1 119.25 3.81% 163.03 20.36%

OTE2 210.32 6.54% 185.26 36.85%

OTE3 164.25 5.42% 192.81 34.26%

OTE4 129.48 3.96% 223.81 20.37%

OTE5 277.22 9.55% 154.83 77.83%

OTE6 252.68 7.35% 165.67 73.61%

III.ControlVariables

Icontrolledforrace,gender,income,andlevelofeducationbasedonresponsestosurvey

questions.Race,gender,income,andlevelofeducationwereallmeasuredascategorical

variables.Racial/ethniccategoriesweretakendirectlyfromthemostrecentU.S.Census

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survey(2010).Toreducethenumberofcategoriesintheregressionanalysis,theseracial

andethniccategorieswerefurthergroupedintooneoftwocategories:“white”or“non-

white”.ThoseofHispanicethnicitywerealsoconsiderednon-white(though,itis

recognizedthatHispanicsareoftentimesconsideredwhiteintheirracialidentity).This

categorizationwasultimatelyadummyvariableseparatingnon-minorities(non-Hispanic

whites)andminorities(allotherracial/ethnicgroups).Genderwasbrokendowninto

threecategories:male,female,orother.Norespondentsanswered“other”,soanalysiswas

basedontheremainingtwocategories.Householdincomelevelswerebrokendowninto

eightcategories,inrangesof$20,000,spanningfrom“<$20,000”to“>$140,000”.There

wasalsoanoptionof“don’tknow”forthosewhowereuncertain.Educationwasbroken

downintosixcategories:someschoolingbutnodiplomaordegree,highschooldiplomaor

GEDequivalent,somecollege,collegedegree,somegraduateschool,orgraduatedegree.

AnalysisandResults

ThisanalysiswasconductedinthestatisticalprogramR,andtheanalysisproceededintwo

steps.InthefirststeptherelationshipbetweenMWBandeachofthefouramenity

variables(greenspaceacreage,percentagegreenspace,percentagebluespace,and

walkability)wasexplored.Amultilevellinearregressionmodelwasusedtoexplorethis

relationship(seeTable3forresults).Multilevelmodelingallowsonetoavoidstatistical

problemsassociatedwithanestedstudydesign.Forexample,contextualfactors,suchas

localsocialconditions,couldinfluenceindividual-levelofwell-being.Ifthisisthecase,the

assumptionofindependenterrorsisviolated,whichincreasestheriskoftypeIerrors.To

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accountforpotentialnon-independenceofindividualresponses,multilevelmodelsallow

forvariationateachlevel.Forthisanalysis,Iusedtwo-levelmodelshavingsurveyed

individuals(levelone)withintwelveterritories(leveltwo).Theseterritorieswerethen

nestedwithinneighborhoods,butmultilevelmodelsrequiremorethantwogroupingsand

sinceweonlyhavetwoneighborhoods,thislevelwascontrolledforusinganotherdummy

variableintheregression.

Thecontrolvariablesofincome,gender,race,andlevelofeducationwereincludedinthe

model;takingintoaccounttheeffectsofthesevariableshelpedestablishamorerobust

representationoftheinteractionbetweentheprincipalvariables.

Table3:Resultsofmultilevelmodelregressionforthementalhealthindex

Predictor Model1

Estimate(S.E.)

Model2

Estimate(S.E.)

Model3

Estimate(S.E.)

Model4

Estimate(S.E.)

Percentage

greenspace(1

mile)

1.29(2.31) - - -

Greenspace

acreage(1mile)

- 0.00(0.00) - -

Sidewalk(1

mile)

- - 0.00(0.00) -

25

Percentageblue

space(1mile)

- - - 0.01(0.00)**

Income(linear) 0.33(0.10)** .32(0.10)** 0.33(0.10)*** 0.30(0.10)**

Income

(quadratic)

-0.07(0.10) -.07(0.10) 0.07(010) -0.05(0.10)

Gender(male) 0.04(0.10) .03(0.10) 0.04(0.10) 0.04(0.10)

Education

(linear)

0.20(0.15) .20(0.14) 0.20(0.15) 0.20(0.14)

Education

(quadratic)

-0.10(0.11) -.12(0.12) -0.12(0.12) -0.10(0.12)

Race(white) -0.38(0.14)** -.40(0.14)** -0.37(0.14)** -0.37(0.14)**

Neighborhood 0.07(0.16) 0.10(0.16) 0.11(0.19) 0.35(0.17)*

Individual

(residual)

0.59(0.77) 0.59(0.77) 0.59(0.77) 0.58(0.76)

Territory 0.00(0.09) 0.01(0.10) 0.01(0.12) 0.00(0.00)

.=p<.05*=p<0.01**=p<.001***=p<0.00

Thereareseveralimportantresultsfromthesemodels.First,incomeandraceare

significantlyassociatedwithmentalwell-being.Morespecifically,higherincomeis

associatedwithhighermentalwell-beingandwhiterespondentsreported

significantlyhigherwell-beingthannon-whiterespondents.Second,ofthefour

26

amenityvariables,onlypercentagebluespacewassignificantlyassociatedwithhigher

mentalwell-being.Theestimateforthisvariable(0.01)suggeststhataoneunit

increaseinaterritory’spercentagebluespaceisassociatedwitha0.01unitincrease

inmentalwell-being.Percentagebluespaceinthetwelveterritoriesrangedfrom

20.36–100%andMWBrangedfrom2–7.Thisresultindicatesthat,allelsebeing

equal,adifferencefrom20%bluespaceto100%bluespacewouldleadtoa(0.01*80)

=0.80increaseinanindividual’sMWBscore.

Thesecondstepoftheanalysisinvolvedexploringtherelationshipbetweenamenitydata

andthecomponentoftheaveragementalwell-beingscorethatmaybemostimpactedby

localenvironmentalconditions.Thisfactor,“happiness”,wasmeasuredwiththequestion,

“Onanaverageday,Ifeelmentallyhappy”.Iagainfitmultilevelmodelregressiontoeachof

thefouramenityvariablesforthenewdependentvariable“happiness”,theresultsofwhich

canbeseeninTable4.

Table4.Resultsofmultilevelmodelregressionforsinglefactor(happiness)

Predictor Model1

Estimate(S.E.)

Model2

Estimate(S.E.)

Model3

Estimate(S.E.)

Model4

Estimate(S.E.)

Percentage

greenspace(1

3.83(2.42) - - -

27

mile)

Greenspace

acreage(1mile)

- 0.001(0.00). - -

Sidewalk(1

mile)

- - 0.00(0.00) -

Percentageblue

space(1mile)

- - - 0.01(0.003)**

Income(linear) 0.37(0.12)** 0.36(0.12)** 0.39(0.12)** 0.33(0.12)**

Income

(quadratic)

-0.03(0.12) -0.04(0.12) -0.02(0.12) -0.00(0.12)

Gender(male) 0.07(0.13) 0.07(0.13) 0.07(0.13) 0.09(0.13)

Education

(linear)

0.36(0.18)* 0.36(0.18)* 0.36(0.18)* 0.33(0.18).

Education

(quadratic)

-0.11(0.15) -0.11(0.15) -0.12(0.15) -0.07(0.15)

Race(white) -0.54(0.17)** -0.55(0.18)** -.52(0.17)** -0.54(0.17)**

Neighborhood -0.02(0.17) 0.01(0.17) 0.06(0.21) 0.33(0.20)

Individual

(residual)

0.90(0.95) 0.90(0.95) 0.90(0.95) 0.87(0.93)

Territory 0.00(0.00) 0.00(0.00) 0.00(0.06) 0.00(0.00)

.=p<.05*=p<0.01**=p<.001

28

***=p<0.00

ThefirstsignificantresultcamefromModel2,wherethecomparisonbetweengreenspace

acreageandself-ratingsof“happiness”resultedinanestimateof0.001,whichwas

significantatthep<0.05level.Thisfindingsuggeststhatanincreaseof

oneacreofgreenspaceinaterritory’sone-milebufferzonecorrelateswitha0.001

increaseinanindividual’sassessmentoftheirownhappiness.Thegreenspaceacreageof

territoriesrangedfrom119.25to565.48acres.Thisfindingsuggeststhatadifferenceof

446.23acresisassociatedwitha.45increaseinself-reportedhappiness.

Thecomparisontobluespaceresultedina0.01estimatebutatthep<.001level,indicating

thataonepercentincreaseinbluespacecorrelateswitha0.01increaseinself-reported

happinessonthesevenpointscale.Aspercentagebluespaceassociatedwithinthe

territorieshadarangeof80%,thisfindingindicatesthatan80%increaseinbluespaceis

associatedwitha(.01*80=).8increaseinhappinessonthe1-7scale.

Raceandincomewereassociatedwith“happiness”inallfourmodelsandeducationwas

alsosignificantlyandpositivelycorrelatedwithhigherhappinessscoresinallfourmodels.

Discussion

Thekeyresultsfromthisstudysuggestthatthereisapositiverelationshipbetweenblue

spaceandtheMWBofindividuals.When“happiness”wascomparedtocommunityamenity

data,positivecorrelationsbetweengreenspaceacreageandpercentagebluespacewere

alsofound.Theseresultsweresignificantandheldaftercontrollingfordemographic

29

variables.Resultsfromthisstudysupportpriorresearchinthisfieldthatsuggestsa

positivecorrelationbetweengreenspaceorbluespaceandmentalhealth(Leeand

Maheswaran,2010;VolkerandKistemann,2011).

Resultsmaydifferfromthoseofpriorstudies(e.g.thosethatshowasignificantimpactof

walkabilityonMWB)duetodifferencesinthewell-beingmetricusedandthemethods

usedtocollectdataonthemultiplecomponentsofwell-being.Amenitieswerealso

measuredinawaythatdifferedfromcitedstudies.

Forinstance,nosignificantrelationshipbetweensidewalklengthandamenityvalueswas

found,perhapsduetosidewalklengthbeingaweakestimationofanarea’strue

walkability.Walkabilityscalesdifferinthenumberandtypeoffactorsthatareincludedin

anassessment.Astrongerestimationofwalkabilityofeachoftheterritoriesmayhave

beentheNeighborhoodEnvironmentalWalkabilityScale(NEWS),which“includes

dimensionssuchasresidentialdensity,land-usemix,accesstoservices,streetpattern,

availabilityoffacilitiesforwalking,aesthetics,andsafety(SugiyamaandThompson,2007).

TheNEWSscalewasnotusedbecauseitrequiresresponsestoa98questionsurvey,which

werenotincludedintheinitialdatacollectionprocessthattookplacebeforethe

conceptionofthisstudy.Infuturestudies,measurementsofwalkabilityshouldtakeinto

accountnotonlythepresenceofsidewalksbutalsothelength,qualityandsafetyofthose

sidewalksaswelltheirpotentialtofunctionasausefulwaytotraveltodesirable

destinations.

30

FutureResearch

AstudypublishedintheJournalofSocialScience&Medicine,expandsupononeofthe

mainreasonsforslowresearchwithinthefield(Arayaetal.,2006).Howthevariables

underconsiderationaffecteachotherisacombinationofcomplexinteractions.Asan

example,theauthorsoffertheexampleofapoorlycaredforbuiltenvironment,which

negativelyaffectssocialcohesioninthecommunityandleadstopoormentalhealth.Onthe

otherhand,minimalsocialcohesioncouldresultinalackofcareforthecommunity

environment,thusleadingtolowerreportedmentalhealth.Therelationshipanddirection

oftheseeffectsarecomplexanddifficulttodisentanglefromotherneighborhoodaspects

thatalsoaffecttotalwell-being.Thequantityandcomplicationofallthefactorsthatmake

upacommunity’sphysicalamenitiescombinedwiththenumerousfactorsthatcontribute

tomentalwell-beinghasmadeprogressinthisfielddifficult.Controllingforextraneous

andconfoundingvariablesandestablishingathoroughandconsistentmeasurementof

MWBwillbeessentialinfuturestudiestoreachconclusiveresults.

Itshouldbenotedthattheoverallstudyfromwhichthisdatawascollectedwasnot

initiallycreatedwiththeresearchquestionsofthisstudyinmind.Surveyresultsfromthe

largerstudywereusedbecausethewell-beingdatawascurrent,extensive,andrelevantto

thisresearch.Futurestudiesexploringmentalwell-beinganditsrelationshiptoa

community’sphysicalsurroundingsshouldchooseterritoriesmorestrategicallytocontrol

forsocialandeconomicfactorsandtomaximizethediversityofphysicalsurroundings

associatedwiththoseterritories.

31

Implications

Studiesthatfurtherresearchinthisfieldhavewideimplicationsforurbanplanningand

design.Morerobustevidenceisnecessarybecauseurbanplanningprojectscanbea

significantfinancialendeavor,especiallyforsmallcommunities,andsolidevidenceof

mentalbenefitscanprovidejustificationforchangeandinvestment.Asmoresupportis

gatheredrelatingMWBtogreenspace,bluespace,andwalkability,highqualityurban

infrastructuresuchasparks,waterfeatures,and“completestreets”withlandscaping

buffers,trafficcalmingtechniques,sidewalks,crosswalks,andbikelanesmaybecome

morecommon.

Conclusion

Evidencefromcrediblestudieshasshownrepeatedlythatcontactwithnaturedoes

contributetoimprovementsinhumanhealth(Malleretal.,2006).Thisstudyexploredthe

impactofthreephysicalamenities,withthemostsignificantresultscomingfromthe

explorationofarelationshipbetweengreenspaceacreageandMWBandpercentageblue

spaceandMWB.Futurestudieswillcontinuetomakeadvancementsinthefieldby

incorporatingcharacteristics(notmerelythepresenceof)physicalamenitiesintotheir

studies.Ashasbeenrepeatedlyreportedintheliterature,“theeffectsof‘green’

environmentsareincreasinglywellunderstood,[but]littleisknownabouttheimportance

ofvariationinthequalityofgreenspaceforbenefitstohumanwell-being”(Fulleretal.,

32

2007).Thequality,size,andshapeofgreenspaceaswellasthewillingnessofanindividual

toutilizethegreenspaceallchangehowitaffectseachperson.Likewise,thequalityand

accessibilityofthewater,theoptionalrecreationalusesofit,anditsconnectivitytoother

watersourcescanallaffecthowbeneficialawaterfeatureistoacommunity.

TheOxfordJournalofPublicHealthstudypreviouslymentioned(LeeandMaheswaran)

acknowledgestheneedforfurther“robustevidence”withinthisfieldtogenerateastrong

rationaleurbanplannerscanusetoincreaseandimprovegreenandbluespaceandto

makeourcommunitiesmorewalkable.Publicopenoutdoorspacescanandshouldbe

designedconsciouslytoprovidetheoptimalareaforsocialinteractionandsupport,two

communitycharacteristicslinkeddirectlytomentalhealth(Evans,2003).Furthercredible

quantitativeresearchwithinthisareaofenvironmentalpsychologyisessentialformaking

moreinformedandbeneficialpolicydecisions.Ultimately,advancementinthisfieldof

researchwillberelevanttothelocalgovernment,aswellastodesign,architectureand

planningfirms.Developingabetterunderstandofwhatmatterstopeopleandcontributes

totheirhappinesscaninfluencepolicydecisionsandencourageinitiativesand

infrastructurethateffectivelyimproveourcommunities.

33

AppendixA:Well-beingactivityhand-outatstreetstallsusedtodeterminetherelative

significanceoffactorsthatcontributetowell-beinginColumbus,formA.

Pleaseusethese15stickydotstoranktheimportanceofthefollowing19factorsthat

contributetowell-being.

§ Placeeachstickydotinsidethechosenfactor’sbox.

§ Youcanallocateasmanystickydotstoonefactorasyouwouldlike.

§ Beawarethattherearenotenoughstickydotstorankeveryfactor,sochoose

wisely!

Beingabletoeasilyaccesshigh-qualityservices

Gettingenoughskillsandeducationtoliveagoodlife

Havinggoodrelationshipswithfamilyandfriends

Havingasayinwhatmatterstoyouandfeelingthatyourvoiceisheard

Havingasafeandsecurehometolivein

Havingconfidenceinyourself

Havingasecuresourceofmoney

Beingmentallywell,notdepressedorstressed

Beingpartofacommunity

34

Preservingtheenvironmentforthefuture

Livinginaneighborhoodwhereyoucanenjoygoingoutside

Feelingthatyouandthoseyoucareaboutaresafe

Havingenoughmoneytopaythebillsandbuywhatyouneed

Feelinggood–havingfun,beinghappy,etc.

Havinggoodtransporttogettowhereyouneedtogo

Havingsatisfyingworktodo(whetherpaidorunpaid)

Beingphysicallyhealthy

Havingopportunitiesandthefreedomtomakeyourownchoices

Havingacleanandhealthyenvironment

35

A

36

AppendixB:Examplecalculationofmentalwell-beingscores

Eachwell-beingscoreisasumofindividualfactorswhereparticipantsratedtheirown

levelofagreementona7ptLikertscale(i.e.fromstronglydisagreetostronglyagree).Their

scoreforeachfactor,between1-7,wasmultipliedbytheweightassignedtothefactor

basedontheirage.Iftheydidnotprovideanage,anaverageofallweightswasused.

Foran18-30yearold:

SingleFactorscore=Weight(FactorAscore)

MWB=Weight(FactorAscore)+Weight(FactorBscore)…+Weight(Factornscore)

AverageMWBperterritory=SumofindividualMWBscoresofthatterritory/numberof

individualsinthatterritory

Samplecalculation:

MWBofIndividual1(27yearold,CV1):

(1.07*4)+(1.07*2)+(0.79*3)+(0.79*3)+(1.02*2)=13.2

MWBofIndividual2(65yearold,CV1):(1.09*5)+(.75*4)+(.79*4)+(.79*3)+(.89*4)=17.54

AverageforCV1MWB:(Individual1MWB+Individual2MWB)/2

(13.2+17.54)/2=15.37

37

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