GUIDE FOR SUB-COUNTY ASSESSMENT OF LIFE EXPECTANCY (SCALE)Improving the Capacity of States and Local HealthDepartments to Understand LE Disparities

September 2017Version 2.1

Cross CuttingHealth Disparities

TableofContents1.0.ExecutiveSummary....................................................................................................................................................4

2.0.Introduction...............................................................................................................................................................5

2.1.DisparitiesinLifeExpectancyattheCountry,County,andLocalLevels................................................................5

2.2.InterestinandNeedforLifeExpectancyEstimates...............................................................................................8

3.0.ExamplesfromtheField,PriortoSCALE....................................................................................................................9

3.1.PublicHealth,Seattle&KingCounty.....................................................................................................................9

3.2.LosAngelesCounty..............................................................................................................................................10

3.3RobertWoodJohnsonFoundationLEwork..........................................................................................................11

4.0.SCALEProject...........................................................................................................................................................12

4.1.SCALEProjectGoal...............................................................................................................................................12

4.2.SCALEProjectActivities........................................................................................................................................13

5.0.ReviewofApproachesforCalculatingLifeExpectancy............................................................................................15

5.1Overviewofapproachesconsideredtodevelopthelifeexpectancycalculation.................................................15

LifeTables................................................................................................................................................................16

AbridgedLifeTable..................................................................................................................................................16

AdjustedChiangIIMethods....................................................................................................................................16

5.2Addressingsmall-areamethodologicissues..........................................................................................................17

SmallPopulations/MinimumPopulationSize.........................................................................................................17

Standarderrorandconfidenceintervals.................................................................................................................17

ZeroCells.................................................................................................................................................................17

Age85+YearCategory............................................................................................................................................18

Population...............................................................................................................................................................18

5.3MethodsSelectedforSCALE.................................................................................................................................18

6.0.AcquiringandformattingdataforSCALE.................................................................................................................19

6.1.AcquiringData......................................................................................................................................................19

6.1.1.Datasources,necessaryvariables,andformatting.......................................................................................19

6.1.2.Formaldataagreementsandapprovalstoconsider.....................................................................................20

6.2.GeocodingMortalityData....................................................................................................................................21

6.2.1.Geocodingdefined........................................................................................................................................21

6.2.2.Softwareforbatchgeocoding.......................................................................................................................22

6.2.3.Afterbatchgeocoding...................................................................................................................................22

6.3.Preparingthedata................................................................................................................................................23

7.0.SelectingaSoftware:AvailableOptions...................................................................................................................24

7.1UsingtheSEPHOExceltool...................................................................................................................................24

SEPHOtoolDownload.................................................................................................................................................24

7.2SASorStataoption................................................................................................................................................27

7.3Flowchart...............................................................................................................................................................27

8.0InterpretingtheFindings...........................................................................................................................................28

8.1PhaseIresults........................................................................................................................................................28

8.2Specialconsiderations...........................................................................................................................................29

AreaswithunexpectedlyhighorlowLE.................................................................................................................29

Standarderrorsandconfidenceintervals...............................................................................................................29

ImpactofMigrationonLE.......................................................................................................................................30

8.3Limitationsofthetool...........................................................................................................................................30

9.0UsingtheLEestimates..............................................................................................................................................30

10.0MappingandDisplayofLEresults...........................................................................................................................30

11.0Summary.................................................................................................................................................................31

12.0Acknowledgements.................................................................................................................................................32

References.......................................................................................................................................................................33

AppendixASummaryofPeer-ReviewedLiterature(tobeadded).................................................................................35

AppendixBExamplesofMOU/DSA(TBA).......................................................................................................................35

1.0.ExecutiveSummaryAscommunitiesbecomeincreasinglydatasavvy,residentswanttoknowwhathealthislikeintheirareaorneighborhood.Lookingatdataatanational,state,orevencounty-leveldatahidesawiderangeofvalues,includingsomestarkdisparities.However,manylocalhealthjurisdictionshavelackedthecapacitytoexaminesub-countydata.RecentresultsshowexaminingneighborhoodlevelestimatesofLifeExpectancy(LE)atbirthinthecontextofknownbehavioral,social,andenvironmentalriskandprotectivefactorshasbeeneffectiveatreachingthecommunityandgainingresourcestoaddressareasofconcern.ThisSub-CountyAssessmentofLifeExpectancy(SCALE)Guideisintendedtoserveasaresourceforpublichealthpractitionersandtheirpartnerswhoareworkingtoidentify,measure,andunderstandgrowingandpersistentcommunitylevelhealthdisparitiesandtocatalyzecollectiveactionstoaddresstheunderlyingcausesofthesedisparities.TheSCALEprojectgoalistoimprovethecapacityofstatesandlargelocalhealthdepartmentstocalculatesub-countylevelLEestimates.

LEatbirthisdefinedastheestimatednumberofyearsanewborncanexpecttoliveifcurrentage-specificdeathratesinthatpopulationremainedthesameovertime[1].Thismeasureisparticularlyusefulforexaminingcommunity-leveldisparitiesbecauseitreflectstheimpactofmajorillnessesandinjuriesandtheirunderlyingcauses,enablesdirectcomparisonsacrossgeographiesandtime,andissimplerandmoreintuitivetothepublicandpolicymakersthanareothermeasuresofdeath(e.g.,standardizedmortalityratios,age-adjustedmortalityrates,andyearsofpotentiallifelost)[2-7].

ScalingtheseeffortsacrosstheU.S.caninformfutureresearchandfocusattentionofpolicymakers,legislators,andthepubliconunderlyingconditionsthatareimmediatelyactionable.Toadvancethisinitiative,theCouncilofStateandTerritorialEpidemiologists(CSTE),CentersforDiseaseControlandPrevention(CDC),sixstate(Florida,Massachusetts,Maine,NewYork,Washington,andWisconsin)andtwolocal(LosAngelesCountyandPublicHealth,Seattle&KingCounty)healthdepartmentsreviewedexistingliteratureandmethods,identifiedsoftwaretools,anddevelopedthisdraftGuide.

TheGuideisarrangedtoprovidethebackgroundrationaleforsub-countymethodsusedinSCALE;explainhow,whatandwheretofinddataforLEcalculations;shareanexistingtool;andshowhowStateandLocalHealthDepartmentsutilizedtheprocessandwhatoutcomeswereexperienced.

CalculationofLEcanenablethefollowingfuturepublichealthpracticeandresearchapplications:

1. Identifyandmonitorcommunityhotspotsofhealthdisparities.

2. VisuallyexaminethedegreetowhichLEandassociatedcontributingfactorsvaryacrosspopulationsandgeographies.

3. Raisepublicawarenessabouttheimportanceofplace-basedfactorsincreatinghealthandhealthdisparitiesincludingthosenottraditionallyassociatedwithpublichealth(i.e.,education,housing,transportation,communitydevelopment,andemployment).

4. Facilitateresearchontherelativecontributionofspecificbehavioral,social,andenvironmentalfactorsincreatinghealth.

5. Catalyzemultisectorcollaborationsandempowercommunitiestomoreeffectivelyaddressupstreamfactors,reducedisparities,andimprovecommunityhealth.

2.0.IntroductionLEisameasurethatholdsmanypeople’sattention,andisaconceptthatiseasyforcommunitytograsp.LEatbirthisdefinedastheestimatednumberofyearsanewborncanexpecttoliveifcurrentage-specificdeathratesinthatpopulationremainedthesameovertime[1],andisparticularlyusefulforexaminingcommunity-leveldisparitiesbecauseitreflectstheimpactofmajorillnessesandinjuriesandtheirunderlyingcauses,enablesdirectcomparisonsacrossgeographiesandtime,andissimplerandmoreintuitivetothepublicandpolicymakersthanareothermeasuresofdeath(e.g.,standardizedmortalityratios,age-adjustedmortalityrates,andyearsofpotentiallifelost)[2-7].AllstatesintheU.S.arerequiredtoroutinelyandsystematicallyreportdeath,andinformationfromthedeathcertificates(race/ethnicity,age,andageographicidentifiersuchasaddress,city,orZIPcode)canreadilybeusedtocalculatereliableandcomparableLEestimates.Communitiescangalvanizearoundseeingagapof15or20yearsbetweenthelongestlivedandtheshortestlivedareas.Inmanycases,localpublichealthmayalreadyhavecreatedcalculationsofLEatthecountyorstatelevel,asthoseareoftenstraightforwardandmaynotrequireadetailedlookattheunderlyingdatagoingintothecalculation.Whenlookingatsmallergeographies,however,thereareanumberofissuestokeepinmind,particularlyasnumbersgetsmall.

2.1.DisparitiesinLifeExpectancyattheCountry,County,andLocalLevelsDisparitiesinLEestimatesbetweentheU.S.andothercountriesinthecontextofhealthexpenditureshaveattractedincreasingattentionduringthepastfewyears.In2010,theU.S.ranked40thformaleand39thforfemalelifeexpectancyatbirthamong187countries[8][9],eventhoughtheU.S.spendsalmosttwiceasmuchpercapitaonhealthcarethandoesanyothercountry(Figure1)[9][10].AllAmericans,eventhemosteducated,affluent,andwell-insured,livesickerlivesthanthoseinotherdevelopedcountries[11-14].Moredisturbing,thegapappearstobewidening.ComparisonsofhistoricaltrendsoflifeexpectancybetweentheU.S.andothercountriesfoundthat,sincerankingseventhinlifeexpectancyduringthe1950s,theU.S.hasdroppedmorethan25places,withthemostrapidrelativedeclinesoccurringduringthepastthreedecadesamongwomen[12][15].Accordingtoa2012AnnualReviewofPublicHealtharticle,thislaginU.S.healthstatusresultsfrom“structuralfactorsrelatedtoinequalityandconditionsofearlylife”[9].

1ResultsofmultiplestudiessuggesttheprimarydriverofthepoorrelativenationallevelperformanceoftheU.S.onseveralpublichealthindicators,includingthoseseeninFigure1,isprofounddisparitiesinLEatbirthacrossU.S.counties[15-17].Forexample,LEinsometopperformingcounties—femalesinMarinCounty,California(85.0years)andMontgomeryCounty,Maryland(84.9years)andmalesinFairfaxCounty,Virginia(81.7years),andGunnisonCounty,Colorado(81.7years)—iscomparablewithLEincountrieswherepopulationslivethelongestincludingJapanandSwitzerland.Incontrast,LEestimatesformalesinMcDowellCounty,WestVirginia(63.9years),andBolivarCounty,Mississippi(65.0),andforfemalesinPerryCounty,Kentucky(72.7),andTunicaCounty,Mississippi(73.4),werelowerthanestimatesforAlgeria,Bangladesh,andNicaragua[18].TheU.S.LEremainssignificantlylowerthanthelongestlivedcountries.In2009,theU.SLEwas78.2years,comparedto81.8inthelongestlivedcountries.ThecurrentU.S.LEisequivalenttotheLEthatthe10longestlivedcountrieshadin1990.Extrapolatingfromthisfinding,itwouldtake19yearsofimprovementfortheU.S.tocatchuptothecurrentLEinthelongestlivedcountries.Similarcomparisonsdemonstratethatdisparitiesamongcountieswhencomparedtothelongestlivedcountrieswereevengreaterthanbetweennations(Figure3).LErangedfrom16years*ahead*ofthelongestlivedcountriestomorethan50yearsbehind[18].Ifcurrenttrendshold,theworstperformingcountiesdon’thavemuchofachancetocatchuptothebestperformingcountriesORcounties,asthetopperformingcountieshaveseensteadygainsovertime,whereasLEintheworstperformingcountieshavestagnatedoverthepast25years[19].

1http://data.worldbank.org/,accessedJuly2015

Figure1:HealthCareandSocialServicesSpendingversusLifeExpectancy,byCountry

Figure2:HistoricandProjectedLifeExpectancyoftheLongest-livedCountries,byYear,1950to20502

Figure3:LifeExpectancybyU.S.Countyandbythe10CountrieswiththeHighestLifeExpectancy18

Asseeninthecomparisonsabove,thenationalestimatesmaskcounty-leveldisparitiesinLE.Recentevidencesuggeststhatcounty-levelLEmeasuresaremaskingsimilarmagnitudesofdisparitiesatthe

2PresentationtoKingCountyBoardofHealth,Assessment,PolicyDevelopment&Evaluation,5/2013

sub-countylevel,evenincountiesthatperformwelloverallonothermeasuresofprematuredeath.Forexample,researchersreportedthattheincidenceofprematuredeathinBostonwas1.39timeshigher(95%CI1.09–1.78)forpersonslivingincensustractswhere>20%ofthepopulationhadincomesbelowthefederalpovertylevelthanitwasforcensustractswhere<5%ofthepopulationlivedinpoverty.Similarly,theresultsofastudyexamininghealthdisparitiesin77communitieswithinChicagofoundLEestimatesvariedbymorethan15years,rangingfrom68.2to83.3years[20].Asdemonstratedintheseexamples,consideringthegeographiccontextofprematuredeathhasenormouspotentialforidentifyinglocalconcentratedareas(or“hotspots”)ofhealthdisparitiesandfacilitatingresearchontheroleoflocalareafactorsincludinghousing,education,employmentopportunities,environmentalconditions,behavioralfactors,andaccesstohealthcareandmaterialgoodsthatimpactsocialdisparitiesinhealth[21].

2.2.InterestinandNeedforLifeExpectancyEstimatesTheselargemagnitudesofcommunity-leveldisparitieshavecaughttheattentionofU.S.legislators.Forexample,SenatorBernieSanders,whochairedtheSenateSubcommitteeonPrimaryHealthandAging,heldacongressionalhearingin2013titled,“DyingYoung:WhyYourSocialandEconomicStatusMayBeaDeathSentenceinAmerica.”Thehearingincludedtestimonyfromphysicianandresearchexpertsonhealth,economic,andeducationalfactorsthatcontributetodisparitiesinLE.Atthehearing’sconclusion,SenatorSanderscitedpoorerpartsoftheU.S.,includingsomeruralcountiesandinner-cityneighborhoods,noting,“Inmanyways,thestressofpovertyisadeathsentence,whichresultsinsignificantlyshorterlifeexpectancy.PartsofBostonandBaltimorehavealowerlifeexpectancythanEthiopiaandSudan.”

Inadditiontotheincreasedlegislatorandpublicattentiontocommunity-levelhealthdisparities,severalrecentdevelopmentshaveincreasedthedemandforassessingandimprovinglocalpopulationhealth.First,thevoluntarypublichealthaccreditationstandards3,launchedin2011,requireacomprehensivecommunityhealthassessmentandcommunityimprovementplanasprerequisitesforstateandlocalhealthdepartmentsseekingaccreditation.Second,Section9007oftheAffordableCareActrequiresthatthe>3,000nonprofithospitalsacrosstheU.S.completeacommunityhealthneedsassessmentevery3yearsandadoptanimplementationstrategytomeetidentifiedneedsinorderto 3http://www.phaboard.org/

RIGHTHEREINKINGCOUNTYWEHAVESOMEOF

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continuetomeettax-exemptionstatus.OnespecificrequirementoftheaccreditationstandardsandtheInternalRevenueServiceregulationsisidentificationofandengagementwithcommunitymembersortheirrepresentativesfrompopulationsexperiencinghealthdisparitieswithintheirjurisdictions.Finally,PublicHealth3.04challengeslocalhealthtoserveasachiefhealthstrategist,lookingatsocialdeterminantsofhealth,andexaminingdataatalocallevel,withcommunitycontext.

3.0.ExamplesfromtheField,PriortoSCALESeveralhealthdepartmentshavesuccessfullyusedsub-countyestimatesofLEatbirthtoidentifyandexplorelocalhotspotsofhealthdisparities,toraisepublicawareness,andtocatalyzemultisectorpartnershipsandcollectiveactions.InSections3.1and3.2,wepresentcasestudiesfromtwosuchhealthdepartments,PublicHealth—Seattle&KingCountyandtheLosAngelesCountyDepartmentofPublicHealthtoprovideexamplesofthepromiseandutilityofsub-countylifeexpectancyestimatesforinformingpublichealthaction.Inaddition,theRobertWoodJohnsonFoundation(RWJF)hasproducedaseriesofstorymapstocatalyzeconversationsabouttheinequityinLE.WeprovideabriefsummaryoftheRWJFeffortinSection3.3

3.1.PublicHealth,Seattle&KingCountyKingCounty,hometo2.1millionresidentsand39cities,isthemostpopulouscountyinWashingtonState.HometobusinessessuchasMicrosoft,Amazon,Weyhauser,andsportingothertechnologyhubs,KingCountyhealthoutcomesandriskbehaviorstendtocomparefavorablytoothercountiesintheUS;however,healthequityworkhasshownthehighperformingcountyratemaskslargedisparitiesinhealth[27].In2012,PublicHealth,Seattle&KingCounty(PHSKC)calculatedLEatacensustractlevelforthe398tractsinKingCountytobeginexaminingplace-baseddisparities.The5-yearestimatesshowedarangeof25years(aftersuppressionofunreliablerates),withalowof72yearsandahighof96years.TheoverallKingCountyLEwas81.6years.

Thesefindingsgeneratedquestionsfromlocalleadersandcommunitymembershowadditionalhealthbehaviorsandhealthoutcomeswouldlookatasimilargeography,andPHSKCembarkedonasmallareaestimationprojectthatshowedaconsistentpatternofdisparities.[23]Thisworkwaspresentedin2013ataFederalReserveBankmeeting,culminatinginaplace-basedinitiativecalledCommunitiesofOpportunity(COO),5apublic-privatepartnershipwiththeSeattleFoundationandLivingCities,andisacross-divisionalinitiativewithPHSKCandtheDepartmentofCommunityandHumanServicesinKingCounty.COO’sgoalistocreategreaterhealth,social,economicandracialequityinKingCountysothatallpeoplethriveandprosper,regardlessofraceorplace,withafocusoneconomic,health,housing,andcommunitymetrics.Theprojectisrootedinthecommunity,usingacollectiveimpactframeworkthatallowsthecommunitytoshapetheirownsolutions.TheCOOprojectisalsoalignedwithintheKingCountyAccountableCommunityofHealth.6

4DeSalvo,K.PublicHealth3.0:TimeforanUpgrade.,AJPH106(4),pp.621–6225http://www.kingcounty.gov/elected/executive/health-human-services-transformation/coo.aspx,lastchecked2/20176http://www.kingcounty.gov/elected/executive/health-human-services-transformation/ach.aspx

Figure4.LifeExpectancyatBirth,KingCountyCensusTracts,2008-2012

3.2.LosAngelesCountyIn2009,theLosAngelesCountyDepartmentofPublicHealth(LACDPH)calculatedLEatbirthfor103citiesandcommunitieswithintheCounty.[2]Inearlieranalyses,largeandpersistentdisparitiesinLEhadbeenobserved,andtheLACDPHrecognizedthattherewasaneedtobringincreasedattentiontoaddressingtheunderlyingsocialandphysicaldeterminantsofhealthinordertomakeprogressinnarrowingthesedisparities.TheCounty’scitiesandunincorporatedcommunitieswereviewedasimportantpartnersinthiseffort,anditwashopedthatexaminingLEatthecityandcommunitylevelwouldbringincreasedattentionandengagement.

LEacrosscitiesandcommunitiesvariedwidely,rangingfrom72.4yearsto87.6years,andwasstronglycorrelatedwithcommunity-leveleconomichardship.Cities/communitieswererankedbyLEandbyeconomichardship,andthisinformationwaspublishedinareportthatwaspublishedandbroadlydisseminatedtothegeneralpublic,citymayors,councilmembers,cityplanners,andasotherpublichealthstakeholders.Theinformationresultedinincreasedengagementwithcommunities,localgovernments,policymakers,cityplanners,andothersectors;italsoincreasedrecognitionoftheimportantimpactsofthephysicalandsocialenvironmentsonhealth.

Figure5.LifeExpectancyatBirthinLACountyNeighborhoods

3.3RobertWoodJohnsonFoundationLEworkSimilarly,RWJFhasgeneratedpublicattentiononcommunity-levelhealthdisparitiesbyfundingVirginiaCommonwealthUniversitytocreateaseriesofmapsshowingLEin20U.S.cities.ThesemapsdepictdramaticdifferencesinLEinseveraljurisdictions.Forexample,theprojectdemonstrateddisparitiesbyasmuchas25yearswithinNewOrleans(Figure6).

Figure6:MetroMap:NewOrleans,Louisiana.7TheaverageLEforbabiesborntomothersinNewOrleansvariesbyasmuchas25yearsjustafewmilesapart.

4.0.SCALEProjectToaddresstheneedsarticulatedinSection2.0andtoscalethesuccessesdemonstratedby,PHSKC,LosAngelesCounty,andotherjurisdictions,theCentersforDiseaseControlandPrevention(CDC)providedfundstotheCouncilofStateandTerritorialEpidemiologists(CSTE)inOctober2014toengageseveralstateandlocalhealthdepartmentsinamulti-yearproject.Thisproject,nowentitledtheSub-CountyAssessmentofLifeExpectancy(SCALE)Project,hasengagedseveraljurisdictionstodateindevelopingandpilottestingresourcestosupportstateandlocalhealthdepartmentsthroughouttheU.S.incalculatingsub-countyLEestimates.Inthissection,wedescribethegoalsandkeyactivitiesthatcomprisetheSCALEProject.

4.1.SCALEProjectGoalTheSCALEprojectgoalistoimprovethecapacityofstatesandlocalhealthdepartmentstocalculatesub-county–levelLEatbirthestimates.CalculationofLEestimatesinmanyjurisdictionsthroughouttheU.S.canenablethefollowingfuturepublichealthpracticeandresearchapplications:

1. Identifyandmonitorcommunityhotspotsofhealthdisparities.

2. VisuallyexaminethedegreetowhichLEandassociatedcontributingfactorsvaryacrosspopulationsandgeographiclocations.

7http://www.rwjf.org/en/library/articles-and-news/2015/09/city-maps.html

3. Raisepublicawarenessabouttheimportanceofplace-basedfactorsincreatinghealthandhealthdisparitiesincludingthosenottraditionallyassociatedwithpublichealth(i.e.,education,housing,transportation,communitydevelopment,andemployment)

4. Facilitateresearchontherelativecontributionsofspecificbehavioral,social,andenvironmentalfactorstolifeexpectancy.

5. Catalyzemultisectorcollaborationsandempoweredcommunitiestomoreeffectivelyaddressupstreamdeterminantsofhealth,reducedisparities,andimprovecommunityhealth.

4.2.SCALEProjectActivitiesTheSCALEprojectaimstoimprovethecapacityofstateandlocalhealthdepartmentstocalculatesub-countyLEestimatesbyencouragingparticipationintheproject,developinganddisseminatingeasy-to-useresources,andidentifyingandsharinglessonslearnedfromtheprojectthroughevaluationactivities(SeeTable1).SCALEwascreatedasamulti-phaseeffortinwhichtheworkofeachphasebuildsuponthelast.TheprojectcommencedinJanuary2015whenCSTEandCDCinvitedsixstatehealthdepartments(Florida,Massachusetts,Maine,NewYork,Washington,andWisconsin)andtwolocalhealthdepartments(LACDPHandPHSKC)withpreviousexperienceinsmallareaanalysistoparticipateinthefirstphaseoftheproject.

DuringPhaseI,theeightjurisdictionsengagedincollaborativeeffortstoidentifyvialiteraturereview,test,andsuggestmethodsforcalculatingsub-countyLE,andproducedaguidancedocument(this“Guide”)tosharelessonslearnedanddecisionspointguidancewithotherjurisdictions.TheseeightjurisdictionsarethecoreWorkgroup,whichmeetsonaregularbasistodiscusscurrentupdatestoLEwork,additionalmethods,andtoprovideTAtoincomingjurisdictions.

InPhaseII,25additionalstateandlocalhealthdepartmentsofvaryingsizesjoinedtheSCALEproject(Figure7).ThesejurisdictionsweretaskedwithpilottestingthedraftGuideproducedduringPhaseIandassessingtheextenttowhichthemethodsandassociatedtoolidentifiedinPhaseI(i.e.,theSEPHOtool,seeSection5.0)mettheirneedsincalculatingsub-countyLEestimates.

Inaddition,statesandlocalitiesfromPhaseIandasubsetofPhaseIIparticipantsengagedindiscussionsandactivitiestoaddressseveralmethodologicalquestionsraisedduringPhaseI,suchashowtoaddresscellswithzerodeathsandhowtotreatareaswherealargeproportionofthepopulationlivesingroupquarters.Initialeffortstoidentifybestpracticesformappingsub-countyLEestimatesdrawinguponexpertisefromCDC’sGeospatialResearch,Analysis,andServicesProgram(GRASP)werealsoundertakenduringPhaseII.

AdditionalstatesandlocalitieswilljoinPhaseIIIoftheeffortinFall2017tocontinuetestingandrefiningmethodologiesidentifiedordevelopedinPhasesIandII.Inaddition,duringthisfinalphasespecificeffortswillcontinuetodeveloprecommendationsforvisualizingsub-countyLEandforcommunicatingabouttheseestimateswithvarioustargetaudiences.LessonslearnedfromPhaseIIIandrecommendationsfromtheseeffortswillbeincludedinfutureversionsofthisGuide.

Table1.SCALE:ProjectPhases8

PhaseI Conductedaliteraturereviewtounderstandtheapproaches,availableparameters,andlessonslearnedfrompreviouseffortsassociatedwithconstructingsmall-areaLEestimates.

Reviewedcommonapproachesusedintheliteratureforcalculatingdirectsmall-areaLEestimatesandarrivingatinitialdecisionsaboutmethodology.

IdentifiedotherexistingtoolsforcalculatingLEthatmighteasilybeadopted/adapted(SEPHO).

ComparedcalculationsproducedbySEPHOtoolwithothermethodologiesforgeneratingLEestimates(SASandSTATAcodefrompreviousLEefforts),refinedapproach.

DevelopedevaluationplanforPhaseII.

Productsinclude:(1)DraftGuideforstate/localhealthdepartmentswithSEPHOtoolasapproachused,(2)Sub-countyestimatesforPhaseIstates/localities,(3)2015CSTEconferencepresentation,(4)Evaluationplan

PhaseII Recruitandorientnewstates/localitiestomethodologyandgeneralprojectpurpose/approach.

Implementevaluation;Newstate/localitiespilottestdraftmaterialsfromPhaseIandprovidefeedbackthroughtheevaluation.

States/localitiesassesspotentialrefinementsinmethodologytoexpandgeographiccoveragebyperformingseveralsensitivityanalyses.

IncollaborationwiththeGeospatialResearch,Analysis,andServicesProgram(GRASP)theAgencyforToxicSubstancesandDiseaseRegistry(ATSDR),identifymethodsforvisualizingLEusingdirectestimatesofLE.

EngageexpertpaneltodevelopinitialrecommendationsforvisualizingandcommunicatingaboutLEestimates.

Anticipatedproductsinclude:(1)RevisedtoolsforestimatingLE,(2)Revised/updatedGuide,(3)Recommendationsregardingvisualizationandmessaging,(4)2016CSTEconferencepresentations,(5)Evaluationfindings,(6)Manuscript(s)

PhaseIII Recruitandorientnewstates/localitiestomethodologyandgeneralprojectpurpose/approach.

Anticipatedproductsinclude:(1)Revised/updatedGuide,(2)AdditionaltoolsforLEcalculationorconsideration,(3)20167CSTEconferencepresentations,(4)Evaluationfindings

LE:Lifeexpectancy,SEPHO:SouthEastPublicHealthObservatory,CSTE:CouncilofStateandTerritorialEpidemiologists,SCALE:Sub-CountyAssessmentofLifeExpectancy

8Paper,inprogress

Figure7.StatesandLocalHealthDepartmentsparticipatinginSCALE

5.0.ReviewofApproachesforCalculatingLifeExpectancyDefinitionofLifeExpectancy

Lifeexpectancy(LE)isasummarymortalitymeasureoftenusedtodescribetheoverallhealthstatusofapopulation.Foranygivenpopulation,LEcanbecalculatedatanyage(e.g.,birth,age50years,age65years).TheSCALEprojectfocusesonLEatbirth,whichisdefinedastheestimatednumberofyearsanewborncanexpecttoliveifcurrentage-specificdeathratesinthatpopulationremainedthesameovertime[1].

IntheU.S.,LEisacommonlyusedindicatorofpopulationhealthandhealthdisparities.Becauseallstatesrequiredeathstoberoutinelyandsystematicallyreported,informationfromthedeathcertificates(race/ethnicity,age,andageographicidentifiersuchasaddress,city,orZIPcode)canreadilybeusedtocalculatereliableandcomparableLEestimates.

5.1OverviewofapproachesconsideredtodevelopthelifeexpectancycalculationMultiplemethodsexistforestimatingLE.Theseincludemethodsbasedonstablepopulationconcepts,biologicaltheoriesofaging,estimationofpopulationbyage,regressionequationmethodsthatexploittherelationshipbetweenLEandotherdemographicindices,constructionofabridgedlifetablesandmethodsthatcombinetraditionalcompletelifetableconstructiontechniqueswithsmoothingorgraduationmethods[22][24].Afterliteraturereviewandgroupdiscussion,theSCALEWorkgroupdecidedtouseanabridgedlifetablemethod,andtheChiangIIcalculations.Detailsareprovidedbelow.

LifeTablesAlifetableshowstheprobabilitiesofamemberofaparticularagedyingbeforetheirnextbirthday.IntheU.S.,twotypesoflifetablesareused:thecohort(orgeneration)lifetableandtheperiod(orcurrent)lifetable.Thecohortlifetableisbasedonage-specificdeathratesobservedthroughconsecutivecalendaryearsandreflectsthemortalityexperienceofanactualcohortfrombirthuntilnoonefromthegroupisalive[26].Theperiodlifetablerepresentsthemortalityexperienceofahypotheticalbirthcohortifitexperiencedthroughoutitsentirelifethemortalityconditionsoftheperiodofinterest.Theperiodlifetablecanbeconsidered“asnapshotofcurrentmortalityexperienceandshowsthelong-rangeimplicationsofasetofage-specificdeathratesthatprevailedinagivenyear”[26].

CDC’sNationalCenterforHealthStatisticspublishescompleteperiodlifetablesannually.9Giventheroutinenatureandavailabilityofanationallypublishedperiodlifetable,theWorkgroupsettledonusingthisasthebasisforPhaseIoftheSCALEproject.

AbridgedLifeTableAcompletelifetablecontainsdataforeveryyearofage,whereasanabridgedlifetabletypicallycontainsdataby5-or10-yearageintervals.TheSCALEprojectsuggestsusinganabridgedlifetablewith5-yearageintervalsexceptforthefirstinterval,whichissetat0–1year,andthelastinterval,whichisdefinedas85+years.Anabridgedtableisrecommendedforsmallerareasinrecognitionofthefactthatsub-countygeographieswouldhavetoomanyzerosusingsingleagecategories.It’simportanttoseparatetheinfantdeathsfromthe1-4agecategory,asinfantswhodiehaveamuchhigherrateofdeathinthefirst28days,comparedtootherages,whichhaveamorenormaldistributionofdeathsacrosstheyearandage-group.Groupinginfantdeathswiththe1-4categorywillresultinahigherLEestimate.,Theabridgedlifetablemethodcanbeusedforanygeographicarea,includingcensustracts,ZIPcodes,cityboundaries,orothergeopoliticalunits.

AdjustedChiangIIMethodsThelong-establishedChiangmethodforestimatingLEbyusingaperiod(current)lifetablehasbeenwidelyusedinternationally[7][27].TheChiangmethodanditsvariationsassumethatdeathsarespreadevenlythroughouteachageperiod,exceptforpersons<1yearofage,forwhomdeathsarehighlyskewedtowardthefirst28daysoflife.Forallotheragegroups,Chiangassumesa0.5ageinterval;the<1groupisvaluedat0.1.OnemajorconcernabouttheChiangmethodisagegroupsforwhichnodeathsoccur,whichcausesamiscalculationinstandarderror.Therefore,researchershavedevelopedalternativemethodstoaddressthisissue,includingtheChiangIImethodandtheadjustedChiangIImethod[10].Onewaytopreventzerodeathsinasingleyearofageistocollapseagecategories,whichiswhytheabridgedlifetableissuggested.

TheadjustedChiangIImethodwasproposedtomodifytheassumptionintheChiangImethodofazerovarianceforthefinalageband.TheadjustedChiangIImethodusestheformulabySilcockstoadjustforvarianceinthefinalageband[3].

9http://www.cdc.gov/nchs/products/life_tables.htm.

5.2Addressingsmall-areamethodologicissuesCalculationofLEatthecountyorstatelevelistypicallystraightforward,givengenerallylargepopulationnumeratorsanddenominators,andmaynotrequireadetailedlookattheunderlyingdatagoingintothecalculation.Countyandstatesaregeographiesroutinelyassigned,andthereareoftenpopulationestimatesavailableatastateorcountylevel.Whenlookingatsmallergeographies,however,thereareanumberofissuesthatmustbeconsidered,assmallnumbers(deathsorpopulation)orunequallydistributeddata(deathsorpopulation)mayinfluencetheLEcalculations.

SmallPopulations/MinimumPopulationSizeSeveralauthorshaveexaminedtheimpactofsmallpopulationsonlifeexpectancy.Variationsonthesuggestedminimumpopulationsizerangefrom3,750to7,000.AdditionalinformationcanbefoundinAppendixA.SeveralresearchershavesuggestedthatlifetableestimatesoverestimateLEforpopulationslessthan5,000yearsoflifeatrisk[1][28][29].FortheSCALEPhaseIproject,severalWorkgroupmembersassessedtheminimumpopulationsizeforSCALEapplicationsbygeneratingestimatesforalltracts,andexaminedstandarderrorandspecialconditionsofthetracttoassesswhetherauniquefeatureofthetract(e.g.,nursinghomeresidents,incarceratedpopulations,universitystudents)affectedtheLEestimate.OthersusedanR-basedtooltoaggregatetractstotheminimumpopulationsize.OneWorkgroupmemberexcludedtractsthathadahighpercentage(>=50%)livingingroupquarters,tractsthathadnolandarea(wereonlywater),andmilitarybases.InoneWorkgroupcase,tractsremainedtoosmallandtheyusedMinorCivilDivisions(MCDs).

Becausedeathdatararelycomewithassignedgeocodes,jurisdictionsmayneedtouseaddressinformationtogeocodethedeathtotractorothergeography(seeSection6,below).Oncethegeographicassignmentismade,numeratorsanddenominatorscanbeevaluatedtoseewhetheraggregationoftractsoranotherhigherlevelgeographyishelpfultopresentstablerates.

StandarderrorandconfidenceintervalsBecauseLEcanbeatightlygroupeddataset,determiningameaningfuldifferencebetweenLErangesisimportant.Mostofthereviewedpapersdidnotdiscussaspecificstandarderror.TheSCALEPhaseIWorkgrouprecommendsusingastandarderrorof±2,basedonliteraturereviewandafteranalysisofcalculatedLEforlocaljurisdictions.TheWorkgroupsuggestsconsideringsuppressingLEswithalargestandarderror.

ZeroCellsBasedonthepopulation,populationdistribution,anddeathrates,zerocellscanoccur,evenwhengroupingagesandacrossyears,especiallywhensmallgeographicunits,suchascensustract,areused.Azerodeathcountgivesanestimateofzeroforanageinterval,whichcausesunderestimationofthevariation;themorezerosandthemoreunderestimationthatoccur,thelargertheunderestimationofstandarderror[25].Severalcorrectionshavebeensuggestedtoaddresstheconcern,includingsmallsubstitutionsofvaluesforzeroandexpectednumbersofdeaths[1][7][26][28].Thebiggestconcerniswhenthereisazerocountinthe<1ortheoldestageband,asthosehavethelargestimpactonrates.Atthistime,SCALEWorkgroupvieweachoftheoptionsasacceptable,dependingonthejurisdiction’schoices.NewYorkStatechosetouseanR-basedtooltogrouptractstohitathresholdof60deathstoavoidzerocells.

Age85+YearCategoryAdeathcountofzerointhe85+yearagecategorywouldstronglyaffectLEbecausetheChiangcalculationwouldgivethecohortaninfinitesurvival,raisingtheLEestimateandstandarderror.Toaddressthis,someoptionsinclude:replacingthezerocellswithanationaldeathrateforthecountryoranationalage-specificdeathrateforthecountry[7][28],orincreasingthelastagebandto75+.MostWorkgroupparticipantsdidnothaveissueswithzerocellsinthe85+agecategorygiventhe5yearaggregation.

PopulationRoutinelygeneratedpopulationestimatesareprovidedfromsuchentitiesastheNationalCenterforHealthStatistics(NCHS),butonlyonacounty-widelevel.Somejurisdictionsmayhaveaccesstolocalpopulationsmallareaestimates,whichcouldbeusedforthisproject.Workgroupparticipantswhodidnothaveaccesstosub-countypopulationestimatesused2010Censusdataasamid-pointforLE.Thisisstillarecommendationforsmallareaestimates,iftherearenootherlocalorupdatedsourcesforthedata.TheAmericanCommunitySurvey(ACS),theCensusBureau’sannualhouseholdsurvey,doesproducedemographiccharacteristicdistributionatacensustractlevelbutisnotrecommendedforuseasapopulationdenominator.TheprimarypurposeoftheACSistomeasurechangesinacommunity’ssocioeconomiccharacteristicsbasedonasmallsampleofhouseholdssurveyedeverymonth.TheCensusrecommendsACSforgaugingtrendsovertimeandforcomparingcharacteristicsacrossareas,butspecifythatitlackstheprecisionforpopulationestimates.Manyofthetractshaveveryhighcoefficientsofvariation,whichindicatethelackofprecision.Inaddition,ACSprovidessummarydataforaggregatedagegroups,including0-4;theydonotincluderesultsforthe<1population.OnePhaseIWorkgroupmembercomparedtheirLEresultsusingthe2010Censuspopulationvsthe5-yearACSdata,andshowedthattheACSdatamarkedlychangedresults.10

5.3MethodsSelectedforSCALEThePhaseISCALEWorkgroupchosetheadjustedChiangIImethodbecause1)itadjustsforthevarianceinthefinalagebandand2)itaddressesagebandswithzerodeaths.ResearchshowssimulationresultssuggestedthatuseoftheadjustedChiangIImethodprovidestheclosestapproximationstoreferenceLEandstandarderrorsbynotimputinganyvaluesintoagegroupswithzerodeaths[1],withtheexceptionoftheoldestagegroup.

AnenvironmentalscanofexistingLEtoolsbytheWorkgroupledtodiscoveryofanexistingLifeExpectancyTool,createdbytheSouthEastEnglandPublicHealthObservatory(SEPHO)group(http://www.sepho.org.uk/viewResource.aspx?id=6626).ThisLEtool,whichalsousesanadjustedChiangIImethod,iswelldocumented.TheWorkgroupextensivelytestedandvalidatedtheresultsagainstSAS®(SASInstituteInc.Cary,NC,USA.)programmingusedbyLACDPHStata(StataCorp.2013.StataStatisticalSoftware:Release13.CollegeStation,TX,USA:StataCorpLP.)programsusedbyPHSKC,andanin-houseExceltoolforcalculationofLEcreatedbyNYS.Giventheextensive

10Personalcommunication,SCALEWorkgroup.Datatobereleasedafterpaperpublication.

documentationoftheSEPHOtool,similaritiesof,easeofuse,andaccessibility,theWorkgroupunanimouslyrecommendeditasatoolforSCALE.SASandStatatoolsareavailableuponrequest.

6.0.AcquiringandformattingdataforSCALE6.1.AcquiringDataForjurisdictionsthathavenotbeeninvolvedinpreviouseffortstoperformsmall-areaanalyses,itisnotuncommontospendseveralmonths(betweensixtoninemonths)acquiringdataforthepurposeofcalculatingsub-countyLEestimates.OnejurisdictioninPhaseIneededtohaveanInstitutionalReviewBoardreviewtheirrequestfordata.ConnectingwiththedataprovidersandthestakeholderswhocouldusethesmallareaLEisbeneficialinhelpingtogainaccesstothedataaswellaspotentialtechnicalassistancewithvariousaspectsoftheprocess,includingcleaningandformattingdata,geocoding,selectinganappropriatesmall-area,andstatisticalanalysis.

6.1.1.Datasources,necessaryvariables,andformattingTwotypesofdataareneeded:(1)deathcertificatedataand(2)populationestimates.Thedeathcertificatedataandthepopulationdatawillneedtobegeneratedatthesamegeographiclevel(censustract,ZIPcode,city).Mostdeathcertificatedatawillnotcomeassignedtoacensustractorneighborhoodlevel,butmorestateandlocalhealthdepartmentsarestartingtogeocode.SeeSectionXXforconsiderationsaboutwhichgeographicareamightbeoptimalforuse.Oneofthemostessentialdecisionsinvolvesthelevelofgeographytopresentthedata.PhaseIparticipantschosecensustract,aggregationsofcensustracts,ZIPcode,andaMinorCivilDivision.Therearedifferentfactorsdrivingthedecision–forexample,FloridachosetouseZIPcodeastheyhaveanumberofotherhealthindicatorsalsomappedattheZIPcodelevel.Mainetriedavarietyofgeographiesuntiltheyhitonethatworkedfortheirpopulationanddatareliabilityrequirements.NewYorkStateusedaggregationsofcensustracts(andsuppressionoftractsthatwereprimarilygroupquarters).SeveralofthejurisdictionschosetousecensustractforeaseofincorporatingsocialdeterminantsofhealthfromtheAmericanCommunitySurvey.PhaseIandPhaseIIWorkgroupparticipantstypicallyusedbetween5and10yearsofmortalitydatatobeabletogeneratesmallareaestimates.Forthosewhoused5yearsofdata,theyrequested2008-2012data.Populationdatamaycomefrominternallycreatednumbers,orfromtheCensus.ManyPhaseIparticipantsbeganwiththe5yearperiodspanningthe2010Census,multiplyingtheCensalcountstimes5togenerateapopulationestimate.Afewhadtheirownlocallygeneratedpopulationestimates.Bothdatasourcesshouldbebrokendowninto19agegroups(<1,1–4,5–9,10–14,15–19,20–24,25–29,30–34,35–39,40–44,45–49,50–54,55–59,60–64,65–69,70–74,75–79,80–84,85+)forthepurposeofthisanalysis.ThiswillbefedintoanExcelspreadsheettool,sotheagegroupaggregationshouldfollowthisset-up.

6.1.2.FormaldataagreementsandapprovalstoconsiderMortalitydatacanbeobtainedfromastatewidedepartmentofhealth11oravitalregistrationoffice.12Statelimitations,statutes,andpracticesdifferwithrespecttotherequirementsforacquiringmortalitydatahoweverinsomecasesthisincludesarequirementforadatasharingagreement(DSA)oramemorandumofunderstanding(MOU).Inrareinstances,somejurisdictionsmayalsoneedtogaintheapprovalofanInstitutionalReviewBoard(IRB).LocalitiesnewtotheprojectmaywanttofirstdoaquickinternetorintranetsearchtoseeifpreviousworkhasalreadybeencreatedsuchasanMOUorDSAusedbyanothercountythatcanberepurposed.SeeAppendixBforexamplesofMOUsorDSAsusedbySCALEparticipants.Itisimportanttoforgerelationshipstohelpwithdatasharing.Analystswillneedtomakeanumberofdecisionsabouthowtocalculateandpresentthedata,andhavingstakeholderinvolvementinthisprocess.SeetheFigure12foraflowchartsummarywalkthroughofsuggestedsteps.Ataminimum,dateofbirth,gender,dateofdeath,causeofdeath(primaryandunderlying),streetaddress,ZIPcode,city,anddeathcertificatenumbershouldberequested.Datausersmightwanttoconsideraskingforgeocode(tractorlatitude/longitude),ameasureofgeocodequality,andotherdemographicorsocioeconomicpiecesforadditionalanalysis,suchasrace/ethnicity,occupation,etc.Dateofbirthratherthananageoragerangeisuseful,especiallyforthe<1agegroup.PhaseIandPhaseIIparticipantsreportedhavinghad<1“age”berecordedasamonth,whichthetoolsconvertedtoayear,makingcalculationsincorrect.SomeofthesevariablesarenotusedtocalculateLEbutmaybeusefulinpursuinganalysisofLEdisparities.Includingthemintheinitialdatarequestpreventsneedingtogobackforanotherrequest.It’sunlikelythatjurisdictionswillbeabletousethesedirectestimatestoexaminethegranularcauseofdeathinsmallareas,butsomePhaseIIparticipantswereabletoshowimpactsatacountyorstatelevelbycollapsingcategoriesofdeath(e.g.allcancers,allheartdisease)andtolookatpopulationandgeographicalpatterns.Anotherquestiontoaddresswhenrequestingdatafromavitalstatsprovideristoknowwhethertheyhaveareciprocalagreementtogetdataforresidentsoftheirstatethatdieinanotherstate.(SeeSection8.2–borderareasformorediscussion).Iftheydonot,jurisdictionswillneedtodecideiftheywanttoconsiderapproachingtheotherstates,asthisprocessmaybetimeconsumingandwouldbebestinitiatedattheoutsetoftheproject.Onecaveat:Thestandarddeathcertificateformchangedin2004,andjurisdictionsadopteditatdifferenttimes.Todate(2017),notalljurisdictionshaveadoptedthenewcertificate,andsomemayhaveswitchedcertificateformsduringthe5-yearperiodofinterest.It’sworthadiscussionwiththevitalstatisticsregistrarorotherswhoworkwiththedatatounderstandtheimpactofthecertificatechangeonthedatacollected.Oncethedataagreementsareestablished(ifnecessary)andanalystshavebecomemorefacilewiththedata,itallowsforeaseinmultipleiterationsoftheprocess.

11https://www.cdc.gov/stltpublichealth/sitesgovernance/index.html12https://www.cdc.gov/nchs/nvss/deaths.htm

6.2.GeocodingMortalityDataGeocodingistheprocessbywhichdescriptors(e.g.,address,city,ZIPcode,province)areassignedaplaceonamap,alsoknownasageospatiallocation,creatingageoreferenceddataset.Althoughthissectionisnotdesignedtobeacomprehensivetutorial,itwillprovidesomelinksforadditionalinformationandbestpractices.13Recentassessmentsofstatehealthdepartmentepidemiologycapacityindicatethatmorethan50%donotroutinelygeocodetheirdata.[30]Asaresult,itwillbeimportantmanyjurisdictionsthatwishtocalculatesub-countyLEwillneedtogeocodetheirmortalitydataaspartofthisprocess.Inthissectionweoffersometipstomakethisprocesssmootherthanitmaybeotherwise.

6.2.1.GeocodingdefinedTheWorkgroupsuggeststheinitialtaskofgeocodingistoassignaddressinformationfromadeathcertificatetoa2010censustract.Becausethisprojectisexamininggeographicdisparitiesinlifeexpectancy,geocodingdataisessentialtoexaminationofsub-countyLEestimates.

Somejurisdictionsmayalreadyhaveaccesstogeocodeddatawhenthedataarerequested;othersmayneedtoperformthisstep.Evenwhengeocodeddataareavailable,itisimportanttounderstandhowthegeocodingprocesswasaccomplished,andtheattendantlevelsofaccuracyresultingfromthemethodused.Forexample,someautomaticgeocodersmightassignacentroid(acenterpoint)ofacityoraZIPcodetoanaddressthatcannotbematchedtoastreetlocation.Thiscanartificiallyinflatethenumberofdeathsthatareoccurringinthattract,astheindividualsarebeingassignedtothenumeratorbutarenotinthedenominator.Ifdatacomealreadygeocoded,onerecommendation 13http://naaccr.org/LinkClick.aspx?fileticket=ZKekacM8k_IQ0%3d&tabid=239&mid=699

Questionstoconsiderwhenacquiringdataforsub-countylifeexpectancy

Ö WhatelementscanbeincludedwithoutaDSAorMOU?Ö HasanotherjurisdictionororganizationalunitcreatedasuccessfulDSAorMOUthatcanbe

adapted?Ö Arethedatageocoded?Ö Haveotherprogramsorunitsworkedwithgeocodedmortalitydata?Mightyoubeableto

leveragethiswork?Ö Willyouneedtoworkwithotherjurisdictionstogetinformationaboutgeographiesalong

theborderofyourgeography,suchascountiesborderinganotherstateoraZIPcodethatcrossescountyorstateboundaries?

Ö Arethereexistingrequirementsaroundsuppressionorcensorshipofunreliablenumbers?Ö Howmanyyearsofdatamightbeneededforsufficientsamplesize?Ö CouldthisdatabenefitotherprioritiesinyourLHJ?Ö Willyouwantotherdemographicinformationforanalysis(e.g.race/ethnicity,education,

occupation)?

wouldbetorequestamatchscoreandmatchtype,whichwillprovidethedatauserwithappropriateinformationindecidinghowtousethedata.Theusercanmanuallymatchthecentroidormissingvalues,theycanassignbasedonanoverlay,ortheycanrandomlydistributenon-matchingcases.

IfdatadospanaCensalyear,datausersshouldalsoverifythatanygeocodeddataareassignedtothesamecensusgeography.OnePhaseIparticipantreportedneedingtore-geocodethe2008and2009datato2010Censusboundaries.

6.2.2.SoftwareforbatchgeocodingShouldaparticipantneedtogeocodethedeathdata,thereareseveraldifferentsoftwareoptionsavailableforbatchgeocoding.Batchgeocodingoccurswhenthedatasetsareprocessedthroughasoftwarepackageandassignedtoageolocationautomatically.Anygeographicinformationsystem(GIS)willhavebatchgeocodingoptions.Followingareseveralsoftwareoptionsthatmaybevaluabletoexploreinmoredetail:

• ArcGIS(fromESRI)..StatesthatparticipateintheCDCBuildingGISCapacityforChronicDiseaseSurveillance(http://www.cdc.gov/dhdsp/programs/gis_training/index.htm)shouldhaveaccesstothissoftware.AgeocodingtutorialforthissoftwareisaccessibleontheWeb:http://help.arcgis.com/en/arcgisdesktop/10.0/pdf/geocoding-tutorial.pdf.

• GoogleEarth.GoogleEarthhasgeocodingcapability.Tousethefullfunctionalityofthistool,itishelpfulfortheusertoknowHTMLandJavaScript.UsersmustsignupforGoogleEarthandobtainanAPIkey,whichiswhatallowsausertoconnectandgeocodeusingGoogleEarth.Atutorialisavailable.Thereisapaid,unlimitedversionandafreeversion,whichislimitedto2,500geocodesaday.http://www.drew.edu/ess/wp-content/uploads/sites/82/Tutorial-7-Geocoding-with-Batch-Geocode-and-Google-Earth.pdf

• Statisticalanalysispackages.Someanalyticsoftwarepackages,suchasSASandR,alsohavegeocodingtools.Forexample,SAS/GRAPHusesaprocgeocode(http://support.sas.com/documentation/cdl/en/graphref/63022/HTML/default/viewer.htm#a003121448.htm)andRhasapackageonCRANhttp://www.inside-r.org/packages/cran/ggmap/docs/geocode.ThedefaultRpackageusestheGoogleEarthAPI,butotherpackagesalsocanbeused.

6.2.3.AfterbatchgeocodingNosoftwarecanmatchalladdressestoalocation,asthereareerrorsintheaddressfile,thestreetfileformatching,oradditionofnewsroadsthataren’tyetincorporatedintotheGISsoftware.Recordsthatdon’tgeocodearecalledexceptions.Exceptionscanresultfromanincorrectstreetnumber,misspellingofastreet,incorrectpostofficebox,nameofbuildinginsteadofstreet,incorrectdirectionalmismatchbetweenZIPcodeandstreet,oranincorrectunderlyingstreetlayerassomeexamples.Ruralareasmayhaverouteboxesthatalsoaredifficulttoassign.Theseexceptionsshouldbemanuallyreviewedandmatchedwhenpossible,asmostexceptionsdonothappenrandomly.SometimeslocalGISaddresseswillbebetterthananationalone;somemayjustrequirespellingcorrections.IfaZIPcodeispartoftherecord,andthatZIPfallsentirelywithinatract,thattractcanbeassignedtotherecord.Afinalgeocodingmatchof>90%isideal,andthehigheritcanbe,thebetter.MostPhaseIparticipantsachievedagreaterthan95%matchscore.

Addressesthatremainunmatchedafterreviewcanbehandledoneoftwoways.Theycanbetreatedasmissing,ifthereisnon-differentialclassification(i.e.,iftheunmatchedcasesaresimilartothematchedcasesintermsofdemographics),theycanberandomlyassignedbyhavingthemdistributedacrossalltracts,orgeocodescanbeimputed,basedondemographicfactorsimilaritybetweenthecaseandthepopulation.

6.3.PreparingthedataThepopulationanddeathdataneedtobearrangedinthe19agegroupslistedabove.Thisfitstheabridgedlifetableformat.SeeFiguresAandBasexamples.Remember,ifusingthepopulationestimatesfromtheCensus,multipleby5(orthenumberofyearsusedtoaggregate).

FigureA:Exampleofnumerator/deathdata,5yearaggregate14

FigureB.Exampleofdenominator/populationdata;2010populationmultipliedby5

Thereshouldbetwospreadsheets:oneeachforthenumberofdeathsandthenumberofpopulation.Ineachspreadsheet,eachrowrepresentsasmallarea,andeachcolumnrepresentsanagegroup.

14CalculatingLEforSmallAreas,T.Talbot,CSTE2016

Eachrowshouldalsohaveageographicidentifier(city,ZIP,censustract).ThoseusingtheSEPHOtooldescribedinSection7willseethisreferredtoasanareacode.ThisgeographicidentifierisrequiredtocalculateLEforindividualareas.

7.0.SelectingaSoftware:AvailableOptionsWorkgroupparticipantsscannedtheavailabletoolsets,andthisGuidepresentsthe3mostcommonoptions.AllPhaseIandPhaseIImembersusedtheSEPHOtool(SeeSection5formoreinformation),fromtheSouthEastEnglandPublicHealthObservatorygroup,whohavebeendevelopingsmallareaLEformanyyears.Thistoolwasverifiedandtestedforaccuracy.Giventhesimplenatureofneedingnospecialstatisticalsoftware,theeaseofcuttingandpasting,thistoolhasalowbartoentryforeaseofuse.Italsohasmanysub-tabsthatallowtheusertoseeexactlywhatisgoingonineachcalculationandcanbeusefulinhelpingtodiscoverwhysomeresultsmaybedifferentthanexpected.http://webarchive.nationalarchives.gov.uk/20160701122411/http://www.sepho.org.uk/viewresource.aspx?id=8943

7.1UsingtheSEPHOExceltoolThenumeratorandpopulationdatawillbecopiedandpastedintheSEPHOExceltool,whichcontainsmacrosthatwillcalculatetheresult.Thisisasimple,easytousetoolthatwasverifiedforaccuracyagainststatisticalprograms.(Seesection7.2formoredetails).Thiswillinvolveadownloadfromawebsite,andworksbestwithExcelversion10orhigher.PhaseIandPhaseIISCALEparticipantsusedtheSEPHOtoolforsimplicity.Regardlessofthetoolused,thestepsinpreparingdataarethesameforthecalculations.

SEPHOtoolDownload1. DownloadtheSEPHOtoolfrom

http://webarchive.nationalarchives.gov.uk/20160701122411/http://www.sepho.org.uk/viewresource.aspx?id=8943

2. Openthefile(LifeExpectancycalculator_V1.xls)3. Ifthisisthefirsttimeyouareopeningthefile,dependingonthesecuritysettingofyour

MicrosoftOffice,youmightneedtoclick“EnableEditing”(seeFigure8foranexample)

Figure8.SEPHOtool,highlightingthe“EnableEditing”button.

Questionstoconsiderwithrespecttopreparingthedata

Ö Aretheregeographicareaswithpopulationslessthan5000?Usersmaywanttoflagtheseareasforevaluationoftheresult.

Ö Aretherecellswithnodeathsinthe<1agecategoryor85+?Ö Whatdoesthedistributionofdeathslooklikeacrosstracts?Mighttractsneedtobe

groupedtogetherforreliableresults?Ö WillIneedtorequestdatafromanotherjurisdictionthatabutsmyboundaries?Ö Whatisthequalityofthegeocodes?

4. Again,dependingonthesecuritysettingsofyourMicrosoftExcel,youmightneedtoenablethe

Macrobyclicking“EnableContent”(wheretheredarrowpoints).

Figure9.SEPHOtool,showingwheretoclicktoenablethemacro.

5. Suggestsavingtheenabledversiontohaveanuneditedcopy.6. Clickon“Deaths”underLifeTable–SingleArea.7. Adialogboxtitled“SEPHOsmallarealifeexpectancycalculator”willpopoutrequestingthat

theuser“[E]nterthenumberofsmallareas(e.g.,electoralwards)yourequireinyourcalculator.”Putinthenumberofsmallareasintheboxbelow–thisshouldmatchthenumberofgeographicunits(tract,ZIPMCD,etc)beingusedinthecalculation.Makesureyourdataaresortedbygeography.Figure10.SEPHOcalculatorpopup

8. Copythenumbersofdeathbyagegrouptothe“Deaths”spreadsheet(ifthespreadsheetisnot

shown,clicktherightarrowonthebottomleftcornertoshowthe“Deaths”spreadsheet).Copythenumberofpopulationbyagegrouptothe“Pops.”DatashouldbesortedbygeographysothattheordermatchesintheDeathsandPopspage.

Figure11.Spreadsheetexample.

Notethatthecolumn“Areacode”isrequiredforcalculatinglifeexpectancyandstandarderrorsattheindividualarealevel.Thisisjustthegeographicidentifierfromtheinputdataset.Ifthearea code is not provided, the life expectancy and standard error will be calculated for theaggregationbutnotfortheindividualareas.

9. Resultswillbedisplayedonthespreadsheet“Summary.”IntermediateresultsaredisplayedaswellwithLifeExpectancyatStartofAgeintervaldisplayedonspreadsheet“e.”Makesurethetableissetto“Birth”tocomputeLEatbirth.Userscanalsochangethistolookattheimpactofmortalityratesonotheragegroupsaswell,butthatisbeyondthescopeoftheSCALEGuide.

10. Tocalculatelifetableforasinglearea,copyandpasteyourdataontothespreadsheet“LifeTable,”resultswillbedisplayedoncolumns“P,U,V,W”forthepointestimateofthelifeexpectancyatthestartoftheageinterval,samplestandarderror,lowerboundofthe95%confidenceinterval,andupperboundofthe95%confidenceinterval.

11. SavetheExcelWorkbookunderadifferentname.12. Sophisticateduserscanmodifythelifetabletabiftheyprefertouseadifferentlifetable.

Moredetailsareavailableathttp://webarchive.nationalarchives.gov.uk/20160701122411/http://www.sepho.org.uk/viewresource.aspx?id=8943

7.2SASorStataoptionForajurisdictionwishingtouseaSAS-orStata-basedtoolforcalculatinglifeexpectancy,CDChasaSharePointsitehostinglanguageusedfortestingpurposesandforwhichlimitedtechnicalassistanceisavailable.NumeratoranddenominatordataneedtobecreatedasdescribedabovefortheSEPHOtool.

7.3FlowchartOneofthePhaseIWorkgroupmemberscreatedaflowcharttoprovideavisualgivingtheworkflow.MostWorkgroupmembersneededtorunthroughseveraliterationstoreachafinalproductthatwasreadyforanalysis,display,anddistribution.

Figure12.AflowchartofactivitiesforcalculatingLE.

8.0InterpretingtheFindings8.1PhaseIresultsOfthePhaseIparticipants,fouruseddeathdatafrom2008-2012;twousedmorerecentdata(2009-2013),andonejurisdictionwithmoresparsepopulationsused10yearsofdata(2001-2010)togeneratesub-countyLE.FourjurisdictionsusedCensuspopulationestimateswhilethreehadlocalpopulationestimates.AllparticipantsfoundtheSEPHOtooleasytouse,andcustomizableforthespecifictypeofgeographiespertinenttotheirlocality.

Eachjurisdictionexaminedtheoutputofthenumerator,denominator,andthestandarderrors,andmadesomedecisionsaboutwhattopresent.OnePhaseIparticipant(Florida)initiallyusedZIPcodesasitalignedwithothersub-countyhealthandbehavioralindicatorsthatwerealreadyproduced.Maineneededtogroup10yearsofdataandprovidethemattheMinorCivilDivision(MCD),whichisaCensusdesignationforaciviltownship,precinct,ormagisterialdistrict.Theotherjurisdictionsproducedcensustractestimates.

ManyjurisdictionsfoundthatmappingthedataafterthefirstpassthroughtheSEPHOtoolledtoaskmorequestions(seesection8.2).TheWorkgroupdiscussedsensitivityanalyses,whattoconsiderunreliableestimates,howtohandleunreliableestimates,andspecialconsiderationsaroundspecificgeographictypes.

8.2SpecialconsiderationsAreaswithunexpectedlyhighorlowLEBorderareas

Onequestiontoaskisifthevitalstatisticsdepartmenthasareciprocalagreementwithotherstates.ThismeansthataresidentofStateAdiesinanotherstate,StateB,thatStateBwouldsendadeathcertificatetoStateA.NothavingthisagreementmeansthatLEmightbeartificiallyinflatedinareasthatareclosetoborders,especiallyonesthathaveahospitalornursingfacility,asindividualsmightbeseeninthehospitalornursingfacilityinStateB,diethere,andStateAwouldnotknow.Borderissuestypicallyarisebetweencounty,country,andstatelines.

Smallpopulations:

Insomecases,tractsmaynotmeettherecommendedminimumsizeof5,000personyearsatriskduetoasmallnumberofpeopleresidinginthattract.Othersmayhaveonlyafewdeaths.Seesectionuniquetractsbelowfortractsthathaveuniquecharacteristicscausingthesmallpopulation.JurisdictionsparticipatinginPhaseIandPhaseIIdecidedtohandlesmallpopulationsinoneofseveralways.Somesuppressedthedata.SomecalculatedtheLE,andifithadareasonablestandarderror,thedatawerepresented.Othersgroupedadditionalyears,othergeographies,andsomeaggregatedgeographiestogether.NYSaggregatedtractstogetto60deaths,usingtheirR-basedGeographicAggregationTool.15

Uniquetracts:

Sometractsmaycontainahospitalornursingfacility.It’spossiblethatthefacilitycouldbeputonthedeathcertificateastheresidence,causingaspikeinthenumberofdeathsinthattract.

Manytractshavezeroorverysmallpopulation;forexample,manyurbanareashaveassignedatractspecifictoanairportortoaprison.OnejurisdictionidentifiedtheseusingdatafromtheCensusorACS,excludingtractsthathavemorethan50%ofthepopulationlivingingroupquarters.Deathscanstilloccurinthosegeographies,buttheindividualswouldhaveanofficialresidencesomewhereelse.

StandarderrorsandconfidenceintervalsStandarderror(andhenceconfidencelimits)increaseaspopulationdecreases.Literaturesuggeststhatapopulationof5,000lifeyearsatriskproducesan‘acceptable’standarderrorof+/–2years(ora95%confidencelimitof+/–4years).PhaseIandPhaseIIparticipantsfoundthatevenwith5,000personyearsatrisk,therewerestillsmallareaswithastandarderroroutsidetherangeof2.Howtohandletheseareasisstillanitemupfordiscussion.

15http://www.albany.edu/faculty/ttalbot/GAT/

ImpactofMigrationonLEPopulationsthatmaybehighlymobileorareasthathavelargenumbersofinfluxingyounger,healthypeople,mayseechangesinlifeexpectancy.

8.3Limitationsofthetool

9.0UsingtheLEestimatesPolicymakersandcommunitymembersoftenaskwhatisdrivingthegeographicdisparitiesthatareseen.TheNationalEnvironmentalPublicHealthTrackingNetwork(NEPHT)hasproducedlistofusefulrelatedsocial-economicindicatorswhichareimportantwhenlookingathealthoutcomessuchasLE.VirginiaalsocomputedHealthyLifeExpectancy.AsPhaseIandPhaseIIparticipantsreleasedata,thisGuidewillbeupdated.

10.0MappingandDisplayofLEresultsPhaseIandPhaseIIparticipantswhohadsuccessfullygeneratedLEweresurveyedinAugust2016,togetasenseofhowtheywerechoosingtodisplaytheirresults.Mostparticipantswereusingstaticmapsgeneratedinmappingsoftware,althoughafewhadsomeinteractivemapsontheinternet.SomeparticipantsweremappingothersocialdeterminantsofhealthalongsidetheLEestimates,includingeducation,poverty,lackofhealthinsurance,andriskfactororbehavioraldata.

Evenincreatingstaticmaps,nogoldstandardhasyetemergedonthebestwaytopresentthedata.Allparticipantscreatedaclassifiedthematicorchoroplethmapwhereshadesrepresentarangeofvalues.Eachtractfallsintoaspecific“bin”orrange.Therewasawidevarietyofmethodsinhowthemapcutpointswerecreated.Equalinterval:Eachclassconsistsofanequaldataintervalalongthedispersion(fromthehightothelowpoint)ofthedata.Intervalsaredeterminedbydividingtherangeofallyourdatabythenumberofclassesdesired.Equalintervalsarerecommendedifthedataisdistributedinarectangularshapeorifclassificationstepsarenearlyequalinsize.Themajordisadvantageofthismethodisthatclasslimitsfailtorevealthedistributionofthedataalongthenumberline.Theremaybeclassesthatremainblank,whichofcourseisnotparticularlymeaningfulonamap.

NaturalBreaks:

Groups(orclusters)thedataarounddifferentclasses,withthegoalofminimizingthedeviationineachclasswhilemaximizingthedifferencebetweentheothergroups.Inotherwords,itminimizesvaluedifferencesbetweenthedatawithinthesameclassandemphasizethedifferencesbetweentheclasses.

Adisadvantageofthismethodisthatclasslimitsmayvaryfromonemap-makertoanotherduetotheauthor'ssubjectiveclassdefinition(Goodgraphicwayofdeterminingnaturalgroupofsimilarvaluesbysearchingforsignificantdepressionsinfrequencydistribution.Minortroughscanbemisleadingandmayyieldpoorlydefinedclassboundaries.

Quantiles:

Thisisarankorderapproach,usinganequalnumberofobservationsintoeachclass,generatedbytakingthetotalobservationsanddividingbythedesirednumberofclasses.Eachclassisapproximatelyequallyrepresented.However,itmayintroduceanapparentpatternofdissimilarityifthereisnone,overweightthedata,ortheremaybegapsbetweentheobservations.

StandardDeviation:

Thismethodmeasurehowthevalueisdistributedalongadispersiongraph,anditshowthestandarddeviationfromthestatisticalmeanofourdataset.Theresultingclassesrevealthefrequencyofelementsineachclass.Standarddeviationmaybeusefultoshowstatisticalsignificanceortodirectattentiontothehighandlowvalued.It’stypicallybestforastandardnormaldistribution.Onedownsideisitdoesn’tlisttheexactLErate,andmaybedifficultforalaypersontounderstand.

Table2.

*includedmanualclassificationintobinsanddifferencefromstatewideaverage.

Anotherdisplay/mappingissueincludesdetermininghowtorepresentunstablerates.Somechosetogreyoutorcrosshatchunreliabledata.Somesuppressed;othersaggregatedsub-countyunitsuntiltheydidnotneedtosuppressthedata.

Table3.

MethodsemployedtoindicateareaswithhighSE(n=12)*Greyingout 5Crosshatch 3Suppressed 3Aggregated 2

*Participantsindicatedmultiplemethodswereemployed

11.0SummaryTheSCALEprojectsuccessfullypilotedasimplewayforlocaljurisdictionstocalculateLEatsub-countyareas.Therearemanylessonstobelearnedfromtheprocess,includinghowtoobtainthecorrectdata,usinganappropriatetool,andthepowerofcollaboration.ManyofthePhaseIandPhaseIIparticipantshavebeenabletousetheirLEresultslocallyandseveralhavepapersabouttheprocessin

Methodsemployedtogeneratelegends(n=22)NaturalbreaksJenks 6Quantile 4Definedinterval 1Standarddeviation 1Geometricinterval 1Other* 3

theworks.Asthosearereleased,theGuideandSCALEpagewillbeupdated.FeedbackabouttheguideorquestionsabouttheprojectmaybedirectedtoCSTE.http://www.cste.org/?page=SCALE&hhSearchTerms=%22scale%22

12.0Acknowledgements

SCALEPhaseIParticipants

FloridaLosAngelesCounty,CAMaineMassachusettsWashingtonNewYorkSeattle&KingCounty.WAWisconsinSCALEPhaseIIParticipants

AlabamaMaricopaCo.,AZAlamedaCo.,CADistrictofColumbiaCookCo.,IL

AlamanceCo.,NCCaswellCo.,NCChathamCo.,NCDurhamCo.,NCOrangeCo.,NCJohnsonCo.,KSErieCo.,PAShelbyCo.,TNHouston,TXMontanaNewHampshireCleveland,OHMetroAreaPlanningCouncil,MAWashingtonCo.,MNMinnesotaSaltLakeCo.,UTVirginia

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AppendixASummaryofPeer-ReviewedLiterature(tobeadded)

AppendixBExamplesofMOU/DSA(TBA)