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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
THEBIGGESTHEALTHDISPARITIESYOU’LLFINDANYWHERE.PEOPLEWHOLIVEINCERTAINKINGCOUNTYNEIGHBORHOODSENJOYSOMEOFTHE
LONGESTANDHEALTHIESTLIVESOFPEOPLE
ANYWHERE,WHILEJUSTABIKERIDEAWAYLIFE
EXPECTANCYANDQUALITYOFLIFEISMUCHMORE
SIMILARTODEVELOPINGCOUNTRIES.THEREISPLENTYTHATCANBEDONE,ANDMANYWAYSTO
BEPARTOFTHESOLUTIONBOTHLOCALLYAND
GLOBALLY.DavidFleming,FormerDirectorofPublicHealthSeattle
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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)