AREA-BASEDVARIATIONSINCERVICALCANCERPREVENTION:RESULTSOFASPATIALANALYSISIN

COLOMBIA

SilviaBermedo-Carrasco,CherylWaldner,JuanNicolásPeña-Sánchez,MichaelSzafron

2015SaskatchewanEpidemiologyAssociationSymposium

Regina,November5th,2015

Outline

•  Introductiono Colombiaincontexto Primaryandsecondarypreventiono Objectives

• Methodology

• Results

•  Implicationsoftheresults

INTRODUCTION

• OneofthemostinequitablecountriesinLatinAmerica1,2,3o Highlevelsofpovertyo Differencesbyregions

• Barrierstoaccesshealthservicesamong4:o Sociallydisadvantagedpopulationso Individualswithdifferenthealthinsuranceprograms

•  Internalarmedconflicto Higheconomicandsocialimpact5

o Forcedinternaldisplacementofindividualstobigcities6§ Womenandchildren§ Healthstatusofdisplacedpopulations§  Accesstohealthcare

Colombiaincontext

1.  OrtizI,CumminsM.DesigualdadGlobal:Ladistribucióndelingresoen141países.NewYork:UNICEF,2012.2.  CardonaD,etal.[InequitiesinhealthamongLatinAmericanandCaribbeancountries(2005-2010)].GacSanit.2013;27(4):292-7.3.  CortésD,VargasJ.InequidadregionalenColombia.UniversidaddelRosario;2012.4.  VargasI,etal.Barriersofaccesstocareinamanagedcompetitionmodel:lessonsfromColombia.BMCHealthServRes.2010;10:2975.  FrancoS,etal.TheeffectsofthearmedconflictonthelifeandhealthinColombia.Ciência&SaúdeColetiva.2006;11:349-61.6.  MinisteriodeSaludyProtecciónSocial.PlanDecenaldeSaludPública2012-2021:LasaludenColombialaconstruyestú.Bogotá:2013.

Colombiaincontext

• Cervicalcancer(CC)o Secondcauseofcancermortalityamongwomeninthecountry1

o Estimatedburdenofpre-cervicalcancers2:§  8millioninternationaldollars(2005)

o Includedasanationalpriority3

• NostudiesdescribingthespatialvariationsoflimitedaccesstoprimaryandsecondaryCCpreventionprogramshavebeenconducted

1.  Piñeros,M.,etal.PatternsandtrendsincancermortalityinColombia1984-2008.CancerEpidemiology.2013;37,233-239.2.  delaHoz-RestrepoFetal.[EvaluatingtheburdenofdiseasecausedbyhumanpapillomavirusinBogota].RevSaludPublica(Bogota).2009;11(3):454-673.  MinisteriodeSaludyProtecciónSocial.PlanDecenalaraelControldelCáncerenColombia,2012-2021.Bogotá,D.C,2012

Primaryandsecondaryprevention

• Primaryprevention1

o Preventdiseaseoccurrenceamongsusceptibleindividuals§ Diseaseeducation,vaccination,healthpromotion,etc.

• Secondaryprevention1

o Reducetheburdenofdiseasebyidentifyingasymptomaticindividualswiththediseaseinanearlystage§  Screening

• BothstrategiesareimportanttopreventCC2

1.  Oleckno,W.A.,2008.Epidemiology.ConceptsandMethods.LongGrove,IL,WavelandPress,Inc.2.  Grce,M.,2009.Primaryandsecondarypreventionofcervicalcancer.ExpertReviewofMolecularDiagnostics,9,851.

Touseglobalandlocaltestsforclusteringtodescribespa3alpa4ernsinthefrequencyofnothavingheardofHPVvaccina3onandnothavinghadaPaptest

Toexaminewhethertheiden3fiedspa3alpa4ernscouldbeexplainedbysocio-demographicfactorsofwomenatthedepartmentallevel

Objectives

METHODOLOGY

Methodology

• Populationofstudyo Colombiangirlsandwomen(13-49years)whohavenotheardofHPVvaccination

o Colombianwomen(18-49years)whohaveneverhadaPaptesting

• Datao 2010ColombianNationalandDemographicHealthSurveyo 2010estimationsofpopulationbytheColombianNationalDepartmentofStatistics

• Dependentvariables

HavingnotheardofHPVvaccination) HavingnothadaPaptest

FrequencyofwomenwhohavenotheardofHPVvaccinationatthedepartmentlevel

FrequencyofwomenwhohavenothadPaptestingatthedepartmentlevel

Methodology

• Statisticalanalysiso Globalandlocalclusteridentification

§ Moran’sItest(Rsoftware)§  Kulldorff’sspatialscanstatistic(SaTScansoftware)

o BayesianPoissonmodelswithrandomeffects§  Accountforspatiallystructuredandunstructuredvariability(WinBugs)

o Models

o ResultsweremappedinArcGIS

MODEL1DV:havingnotheardofHPVvaccination

MODEL2DV:havingnothadaPaptest

•  Departmentalfrequencyofwomenwithnoformaleducation,subisidsedhealthinsurance,andlivinginruralareas

•  2010populationdensity

RESULTS

• WomenwhohavenotheardofHPVvaccinationo Intotal,39,158(73.2%)

• WomenwhohavenothadPaptestingo Intotal,5,128(12.7%)

• Significantspatialautocorrelationinbothvariablesofstudyo Moran’sIHPVvaccination=0.49,p-value=0.0003o Moran’sIPaptesting=0.34,p-value=0.0004

• Threestatisticallysignificantlocalclustersofcaseswerefoundforeachofthedependentvariables

Results

Results

Results

• Model1

• Model2

• Bothmodelsrecognizedthatthesespatialvariationswereassociatedwiththedepartmentalpercentageofwomenwithsubsidizedhealthinsurance.

• ThesemodelsidentifiedthatHPVvaccineawarenessandPaptestingwerelesscommoninperipheralColombiandepartments.

μisthestructuredvariabilityvistheunstructuredvariability

μisthestructuredvariabilityvistheunstructuredvariability

ResultsHavingnotheardabout

HPVvaccination

HavingnothadPattesting

POPULATIONHEALTHIMPLICATIONS

PopulationHealthImplications

• Thisstudyappliesamethodologyusefulto:o DemonstratespatialvariationsinhealthoutcomestodifferentstakeholdersinColombia

o TargetspecificCCpreventionprogramsinhigh-riskdepartmentso UnderstanddepartmentalsocioeconomicfactorsassociatedwiththeuptakeofprimaryandsecondaryCCpreventionstrategies

• Spatialanalysesareusefultostudypatternsofhealth-relatedoutcomesconsidering:o Behavioroftheoutcomeinneighboringareaso Inclusionofexplanatoryvariables(e.g.area-basedsocio-demographicfactors)

• Thismethodologycouldbesuccessfullyreplicatedinothersettings.

• TherearedepartmentsinColombiawithahigherriskofnothavingheardofHPVvaccinationandnothavinghadPaptestingo Chocóo Vichadao Guaníao Guaviareo Vaupéso Amazonas

• Needtofocusresourcestowardsmoredisadvantagedandhigh-riskareas

PopulationHealthImplications

•  PROFAMILIA,Colombia

•  NationalAdministrativeDepartmentofStatistics,Colombia

•  IntegratedTrainingPrograminInfectiousDiseases,FoodSafety

andPublicPolicy(ITraP)

•  WesternRegionalTrainingCentreforHealthServicesResearch

•  SchoolofPublicHealth,UniversityofSaskatchewan

Acknowledgements

THANKYOU!

ResidualvariationfornothavingheardofHPVvaccination

ResidualvariationfornothavingheardofHPVvaccination

DiagnosticsofBayesiananalysis

•  Informally:o Brook-Gelman-Rubino Autocorrelationplots

• Formallyo GelmanandRubino Gewekeo Raftery-Lewiso Heidelberger-Welch

§  Chainsreachedstationarityforeachofthevariablesinthemodel(p-values>0.05)

Burn-in(M)

Total(N)

Lowerbound(Nmin)

Dependencefactor(I)

%womenwithsubsidisedinsurance

Chain1 4 5059 3746 1.35Chain2 4 5001 3746 1.34Chain3 4 4870 3746 1.30Chain4 4 5123 3746 1.37Populationdensity Chain1 3 4161 3746 1.11Chain2 3 4068 3746 1.09Chain3 3 4095 3746 1.09Chain4 3 4238 3746 1.13Intercept Chain1 4 5038 3746 1.34Chain2 4 4890 3746 1.31Chain3 5 5600 3746 1.49Chain4 6 8782 3746 2.34