AnalyzingGeographical

VariationinCause-of-Death

MortalityforChina

Evidencefrom2004to2019

SEPTEMBER|2022

AnalyzingGeographicalVariationinCause-of-DeathMortalityforChina

Evidencefrom2004to2019

AUTHOR

HanLi,PhD,AIAA

CentreforActuarialStudies

TheUniversityofMelbourne

KatjaHanewald,PhD

SchoolofRiskandActuarialStudies

UNSWSydney

SPONSORSAgingandRetirementStrategic

ResearchProgramSteering

Committee

MortalityandLongevityStrategic

ResearchProgramSteering

Committee

CaveatandDisclaimer

TheopinionsexpressedandconclusionsreachedbytheauthorsaretheirownanddonotrepresentanyofficialpositionoropinionoftheSocietyofActuariesResearchInstitute,SocietyofActuaries,oritsmembers.TheSocietyofActuariesResearchInstitutemakesnorepresentationorwarrantytotheaccuracyoftheinformation.

Copyright?2022bytheSocietyofActuariesResearchInstitute.Allrightsreserved.

3

Copyright?2022SocietyofActuariesResearchInstitute

CONTENTS

ExecutiveSummary 4

Section1:Introduction 5

Section2:Literaturereview 7

2.1Cause-of-deathmortalityinChina 7

Allcausesofdeath 7

Cardiovasculardiseasemortality 8

Cancermortality 8

Lungdiseases 9

Roadinjuries 9

Dementia 9

2.2Summary 9

Section3:Data 10

3.1Description 10

3.2Summarystatisticsandvisualization 11

3.3Mortalitybygender 12

3.4Mortalitybyregion 14

3.5Urbanvsruralmortality 18

3.6Mortalitybycauseofdeath 21

Section4:Mortalitymodelingandprojection 22

4.1HyndmanandUllahmodel(2007) 22

4.2Forecastreconciliation 23

4.3Mortalityprojections:2020–2029 25

Malemortalityprojections 25

Femalemortalityprojections 36

Section5:Scenario-basedanalysis 47

5.1Cancerelimination 47

5.2Externaldeathselimination 49

5.3Circulatoryelimination 51

5.4Infectiouselimination 54

5.5Mentalelimination 56

5.6Respiratoryelimination 58

5.7Digestiveelimination 60

5.8Congenitalelimination 62

5.9Diabeteselimination 63

5.10Otherelimination 65

Section6:Conclusion 67

6.1Summaryofkeyresults 67

6.2Limitations 67

Section7:Acknowledgments 68

AboutTheSocietyofActuariesResearchInstitute 71

4

Copyright?2022SocietyofActuariesResearchInstitute

AnalyzingGeographicalVariationinCause-of-DeathMortalityforChina

Evidencefrom2004to2019

ExecutiveSummary

ThisreportmodelsandforecastsfuturemortalityimprovementsinChina,bygeographicalregions,aswellasbycausesofdeath.Wecollectthemostup-to-datedeathsandpopulationexposuresdatafrom“China’sCausesofDeathMonitoringDataset”publishedbytheChineseCenterforDiseaseControlandPreventionovertheperiod2004–2019.Usingthecutting-edgeforecastreconciliationmethod,weconductstochasticmodelingandprojectionofregion-area-cause-specificmortalityratesfor2020–2029.Wealsoconductmortalitypredictionunderseveralcause-eliminationscenariosandquantifytheimpactofthesescenariosonfuturemortalitylevels.

5

Copyright?2022SocietyofActuariesResearchInstitute

Section1:Introduction

Withoneofthefastest-growingeconomies,Chinahasexperiencedrapidimprovementsinlifeexpectancyinrecentdecades.AccordingtotheWorldBank,in2018,thelifeexpectancyinChinawasjusttwoyearslessthanintheUnitedStates(76.3versus78.7years).Despitethisoverallimprovement,thereremainsignificantinequalitiesinmortalityratesbetweendifferentgeographicalregionsandsocioeconomicgroups.Inrecentstudies,substantialregionaldisparitieswerefound,withhealthylifeexpectancyvaryingbyupto10yearsacrossChineseprovincesforbothmenandwomen(see,e.g.,Lietal.,2021).ThismotivatestheneedtobetteridentifyandassessgeographicalvariationsinmortalityratesinChina,andmoreimportantly,toprojecthowthesetrendswilllookinthefuture.

Mortalitybycauseofdeathalsoprovidesimportantinsightsintohowfuturemortalitylevelswillevolve.Thereareanumberofmedicalandepidemiologicalstudiesthatanalyzecross-sectionalandlongitudinaltrendsincause-specificmortalityinChina.Forexample,arecentstudypublishedbyZhouetal.(2019)intheLancetconductedasystematicanalysisofmortality,morbidity,andriskfactorsataChineseprovinciallevelovertheperiod1990–2017.Theirresultsshowsignificantchangesinthecausesofdeathovertime.In1990,thefiveleadingcausesofdeathwere1.Lowerrespiratoryinfection,2.Neonataldisorders,3.Stroke,4.Chronicobstructivepulmonarydisease,and5.Roadinjuries.In2017,thefiveleadingcausesofdeathbecame1.Stroke,2.Ischemicheartdisease,3.Lungcancer,4.Chronicobstructivepulmonarydisease,and5.Livercancer.Theauthorsalsoreportsubstantialregionalvariationsintheprovince-levelmortalityexperiencein2017.Theyconcludethaturban,coastal,andwealthierprovincesandcitiesineasternChinagenerallyhavebetterhealthoutcomesthanthoseinthewest,althoughmortalitybycausevariedsubstantiallybetweenprovinces.Severalotherstudiesfocusonmortalitymodelingbyasinglecauseofdeath.However,tothebestofourknowledge,theliteratureisyettoconductamodelingexercisetoforecasttrendsincause-specificmortalityatthenationalandregionallevelsforChina.

Mortalitybygeographicalregionsandsocioeconomicgroupsandmortalitybycause-of-deatharetwinissuesthatshouldbedealtwithinanintegratedmanner.Theyareofparticularinteresttoactuariesworkinginfieldssuchasproductdesign,underwriting,andvaluingportfoliosoflifeinsurancecontracts.Asmortalityforecastsarekeyinputsintothedecision-makingprocessesofinsurancecompanies,thisprojectfocusesonprovidingforecastsonmortalityimprovementforChina,acrossagegroups,gender,threegeographicalregionsaswellasbyleadingcausesofdeath.Inthisresearch,weaimtoaddressthefollowingquestions:

?WherearethegapsinmortalityexperienceacrossChina?

?Havethesegapsclosedorwidenedovertime?Whichcausesofdeatharedrivingthesegaps?

?Whatcanbesaidaboutthefuture?Howtoforecastregional-area-causespecificmortality?

DrawingonthesuccessfulSOAinitiativesonmortalitymodelingfortheU.S.,weproposeaconsistentframeworktailoreddesignedforthemortalityexperienceinChina.Inthisproject,weconductmortalitypredictionunderseveralcause-eliminationscenariosandevaluatetheimpactontheoverallmortalityimprovementandregional-levelmortalityimprovement.Thesescenario-basedforecastswillbeimplementedviathecutting-edgeforecastreconciliationmethod(Lietal.,2019).

Itshouldbenotedthatourdatasetcoverstheperiod2004–2019,beforetheonsetoftheCOVID-19pandemic.ThereportednumberofdeathscausedbyCOVID-19inChinaisrelativelylow

1

,sowedonotexpectourmodelestimatesandscenario-basedanalysistochangesubstantiallyifmorerecentdatabecomesavailableforChina.

1ThereportednumberofCOVID-19deathsinChinasincethestartofthepandemicwas14,964onSep7,2022(JohnHopkinsUniversity,CoronavirusResourceCenter,

/region/china

,accessedSep7,2022).

6

Copyright?2022SocietyofActuariesResearchInstitute

Theremainderofthisreportisstructuredasfollows.InSection2,weconductaliteraturereviewoncause-of-deathmortalityinChinaandsummarizesomekeyfindings.InSection3,wedescribethedatausedandvisualizemortalityratebygenders,regions,urbanvs.ruralareas,aswellasacrossleadingcausesofdeath.InSection4,weintroducethemortalitymodelandforecastreconciliationmethod.Wealsopresentthereconciledmortalityforecastsduring2020–2029foralllevels.Wepresentresultsonscenario-basedmortalityforecastsinSection5.Section6concludestheprojectanddiscussesitspotentiallimitations.

7

Copyright?2022SocietyofActuariesResearchInstitute

Section2:Literaturereview

2.1CAUSE-OF-DEATHMORTALITYINCHINA

Inthefollowing,wesummarizerecentmedicalandepidemiologicalstudiesthatanalyzecross-sectionalandlongitudinaltrendsincause-specificmortalityinChina.Webeginwithstudiesthatcompareseveralcausesofdeathandthensummarizetheresearchforspecificcausesofdeath.Foreachstudy,wecommentonthedatausedandkeyresultsintermsoftimetrendsandregionalvariations.OurreviewfocusesonstudiesthatcoverallofChinaanddoesnotincludestudiesthatfocusonasingleprovince.WesummarizetheliteraturereviewinSection2.3.

Wenotethatweonlyfoundstudiesthatanalyzelevelsandtrendsincause-specificmortalityinChina.Thereseemstobenopriorresearchthatdevelopsstatisticalmodelsthatcanbeusedtoforecastcause-specificmortalityrates.Existingactuarialmodelstoforecastcause-specificmortalitymodelshaveonlybeenappliedtodevelopedcountries(e.g.,Lietal.,2019;ArnoldandGlushko,2021;Lyuetal.,2021).

ALLCAUSESOFDEATH

AnimportantstudypublishedbyZhouetal.(2019)intheLancetconductedasystematicanalysisofmortality,morbidity,andriskfactorsinChinausingprovincial-leveldatafrom1990–2017fromtheGlobalBurdenofDiseases(GBD)2017study.Theirresultsshowsignificantchangesinthecausesofdeathovertime.In1990,thefiveleadingcausesofdeathwerelowerrespiratoryinfection,neonataldisorders,stroke,chronicobstructivepulmonarydisease,androadinjuries.In2017,thefiveleadingcausesofdeathwerestroke,ischemicheartdisease,lungcancer,chronicobstructivepulmonarydisease,andlivercancer(see

Figure1

below).Theauthorsreportedsubstantialregionalvariationsinprovince-levelmortalityin2017.Theyconcludethaturban,coastal,andwealthierprovincesandcitiesineasternChinagenerallyhavebetterhealthoutcomesthanthoseinthewest,althoughmortalitybycausevariedsubstantiallybetweenprovinces.Anearlier,similarstudybyZhouetal.(2016)usedGBD2013datafortheperiod

1990-2013.

Figure1

DEATHSIN1990AND2017FORTHE25LEADINGCAUSESOFDEATHINCHINA

Othermalignantneoplasms

PancreaticcancerBrainandcentralnervoussystemcancer

Leukaemia

BreastcancerDiabetesmellitusDrowning

Falls

Congenitaldisorders ChronickidneydiseaseColonandrectumcancer

CirrhosisandotherchronicliverdiseasesSelf-harm

Lowerrespiratoryinfection OesophagealcancerHypertensiveheartdiseaseNeonataldisorders

Alzheimer’sdiseaseandotherdementiasStomachcancer

Roadinjuries

Livercancer

Chronicobstructivepulmonarydisease

Tracheal,bronchus,andlungcancerIschaemicheartdisease

Stroke

020406080100120140160

2017

1990

Notes:Deathsper100,000population.Sourceofdata:Zhouetal.(2019).

8

Copyright?2022SocietyofActuariesResearchInstitute

CARDIOVASCULARDISEASEMORTALITY

TwotypesofcardiovasculardiseasemortalityweretheleadingcausesofdeathinChinain2017(strokeandischemicheartdisease,alsocalledcoronaryheartdisease).Athirdtype,hypertensiveheartdisease,wasthe10th

leadingcauseofdeath(see

Figure1

):

Wangetal.(2013)analyzedthelong-termtrendsofstrokemortalityinChinabetween1994and2013usingstrokemortalitydatafromtheGBD2013data.Usinganage-period-cohortframework,theauthorsestimatedtheagepatternofstrokemortalityformalesandfemalesanddocumentedsignificantnegativetrendsinstrokemortalityforbothmalesandfemales.

Lietal.(2017)conductedanage-period-cohortanalysisofstrokemortalitydatafromurbanandruralregionsinChinabetween1988and2013.TheyusedstrokemortalitydatafromtheChineseHealthStatisticsAnnualReport(1987–2001)andChineseHealthStatisticsYearbooks(2003–2014)andpopulationdatafrompopulationcensuses(i.e.,1982,1990,2000,and2010).Theauthorsfoundamodestperiodeffect,accompaniedbysubstantialageandcohorteffectsovertheyears1987to2013.Thedeclineinstrokemortalitywasslowerfortheruralpopulationthantheurbanpopulation(whichhadahigherinitialstrokemortalityratein1987).

CANCERMORTALITY

Threetypesofcancerwereamongthetop10causesofdeathinChinain2017(see

Figure1

):tracheal,bronchus,andlungcancer(#3);livercancer(#5),andstomachcancer(#7).

Jiangetal.(2021)studiedtrendsincancermortalityinChinafrom2004to2018andcomparedruralandurbanresidentsinthreegeographicregions.TheirstudywasbasedonrawdatafromthenationalmortalitysurveillancesystemofChinatoassessthemortalitiesofallcancerandsite-specificcancers.Theauthorsfoundthatcancerwasthesecondleadingcauseofdeathinthewholepopulationandthefirstleadingcauseofdeathinthose<65yearsduring2014-2018.Intermsoftimetrends,Jiangetal.(2021)foundthatcrudemortalityrate(CMR)ofallcancercontinuallyincreasedwhiletheirage-standardizedmortalityrates(ASMR)decreased,whichindicatesthatagingcontributedgreatlytotheincreasedcancerdeath.Furthermore,Jiangetal.(2021)foundthattheCMRofallcancerwashigherinruralresidentsthaninurbanresidentsinthepopulation<65years;however,thesituationwasinversedforthe≥65yearspopulation.Lung/bronchuscancer,colorectalcancer,andpancreascancerincreasedinruralresidents.

AsecondstudybyCaoetal.(2021)summarizedthemostrecentchangingprofilesofcancerburdenworldwideandinChinaandcomparedthecancerdataofChinawiththoseofotherregions.TheauthorsusedGLOBOCAN2018andGLOBOCAN2020data

2

,aswellascancerincidenceandmortalityfromthe2015NationalCancerRegistryReportinChina.TheauthorsfoundthatbothChina’sage-standardizedincidencerate(204.8per100,000)andtheage-standardizedmortalityrate(129.4per100,000)wereabovetheglobalaverage.TheyclassifiedthemortalityrateofcancerinChinaashigh.Furthermore,theauthorsreportedthatworldwide,in2020,lung,liver,stomach,breast,andcoloncancerswerethetopfiveleadingcausesofcancer-relateddeath,whileinChina,thetopfivecauseswerelung,liver,stomach,esophagusandcoloncancer.Chinaisundergoingacancertransitionwithanincreasingburdenoflungcancer,gastrointestinalcancer,andbreastcancers.

2GLOBOCAN2020isanonlinedatabaseprovidingglobalcancerstatisticsandestimatesofincidenceandmortalityin185countriesfor36typesofcancer,andforallcancersitescombined.

9

Copyright?2022SocietyofActuariesResearchInstitute

LUNGDISEASES

Chronicobstructivepulmonarydisease(COPD),atypeoflungdisease,wasthe4thmostprevalentcauseofdeathin

Chinain2017(see

Figure1

).TherearefewrecentstudiesthatanalyzeCOPDmortalityacrossallofChina.

AnolderstudybyYinetal.(2016b)analyzedspatiotemporalvariationsinCOPDinChinabasedondatafromthenationallyrepresentativeChinaMortalitySurveillanceSystemfortheperiod2006–2012.TheauthorsfoundthatCOPDmortalityratedecreasedmarkedlyfrom105.1to73.7per100,000during2006to2012andvariedovertwo-foldacrossChina.Yinetal.foundthatCOPPDmortalityrateswerehigherinwestChinacomparedwitheastChina,andhigherinruralareasthaninurbanareas.Theynotedthatadjustmentforage,gender,urban/rural,region,smokingprevalence,indoorairpollution,meanbodymassindexandsocioeconomiccircumstancesaccountedfor67%ofthegeographicalvariation.Interestingly,Yinetal.reportedthaturban/ruraldifferencesinCOPDmortalitynarrowedovertime,butthemagnitudeoftheeast-westinequalitypersistedwithoutchange.

Fangetal.(2018)estimatedthenationwideprevalenceofCOPDusingdatafromacross-sectionalsurveyofanationallyrepresentativesampleofindividualsfrommainlandChinaaged40+yearsconductedin2014–2015.TheyfoundthatprevalenceofCOPDdifferedbygeographicregion,withthehighestprevalenceinsouthwestChinaandthelowestincentralChina.ThisstudydidnotanalyzeCOPDmortality.

ROADINJURIES

Roadinjurieswerethe6thmostprevalentcauseofdeathinChinain2017(see

Figure1

).

Wangetal.(2019)analyzedmortalityratesfromroadtrafficinjuryinChinafrom2006to2016usingdatafromChina’snationalmortalitysurveillancesystem.Theauthorsfoundthatoverallage-adjustedroadtrafficmortalityincreasedfrom2006to2011andthendecreasedto2016.Theyreportedthatmales,olderadults,andruralareasconsistentlyhadhigherroadtrafficmortalityratesthandidfemales,youngerpeople,andurbanareas.Wangetal.foundthatmortalitychangesvariedacrossurbanandruralareasandbysex,agegroup,andprovincebetween2006and2016.

DEMENTIA

Alzheimer’sdiseaseandotherdementiaswasthe8thmostcommoncauseofdeathinChinain2017(see

Figure1

).

Yinetal.(2016a)analyzedtemporaltrendsandgeographicvariationsindementiamortalityinChina.Theyusedannualdementiamortalitycountsfortheperiod2006to2012fromthenationallyrepresentativeChinaMortalitySurveillanceSystem.Theauthorsfoundsubstantialregionalandspatiotemporalvariationsindementiamortality.Mortalityratesweresignificantlyhigherintheeastcomparedwiththenorth.Theauthorsreportadecliningtrendin2(eastandnorthwest)ofthe7regions.Importantly,theauthorsfoundthatdementiamortalitydecreasedby15%inurbanareasbutincreasedby24%inruralareas.

Boetal.(2019)conductedasimilarstudyasYinetal.(2016a),usingmorerecentdatafromtheMortalitySurveillanceSystemfortheperiod2009–2015.TheyfoundthatthecrudemortalityfromAlzheimer'sdiseaseandotherformsofdementiaincreasedfrom2009to2015,buttheage-standardizedmortalitydecreased.Furthermore,Boetal.(2019)foundthatage-standardizedmortalityintheeastwashigherthanthoseinthewestandmiddleregions,andtheage-standardizedmortalityinruralareaswashigherthanthatinurbanareas.

2.2SUMMARY

Wehavesummarizedrecentmedicalandepidemiologicalstudiesthatanalyzecross-sectionalandlongitudinaltrendsincause-specificmortalityinChina.Theliteraturereviewhasshownthattherearesubstantialregionaldifferencesinthelevelsandtrendsincause-specificmortalityrates.Furthermore,therearealsodifferences

10

Copyright?2022SocietyofActuariesResearchInstitute

betweenruralandurbanpopulationswithinprovinces.Therefore,ontopofthenationalleveltotalmortality,wealsolookintothemortalitydifferencesacrossregions,urbanandruralareas,andcausesofdeath.Inshort,insteadofthe“bigpicture”,wefocusonthedetailedpictureatgranularlevels.

Theexistingliteraturehasfocusedondocumentinglevelsandtrendsincause-specificmortalityinChina.Thereseemstobenopriorresearchthatdevelopsstatisticalmodelsthatcanbeusedtoforecastregion-area-cause-specificmortalityrates.Ourstudyaimstofillthisgap.

Section3:Data

3.1DESCRIPTION

Thisprojectconsiders“China’sCausesofDeathMonitoringDataset”publishedbytheChineseCenterforDiseaseControlandPrevention(hereafterabbreviatedasChinaCDC),andtheinvestigationperiodisfrom2004to2019.ThedataiscollectedviatheNationalDiseaseSurveillanceSystem(NDSS),whichhasbeenresponsibleformonitoringthemortalitylevelanddiseasepatternchangesoftheChinesepopulationsince1978.In2004,NDSSexpandedto161surveillancesitesacrossChinaandbegantoprovideannualcause-of-deathinformation.In2013,therewasafurtherexpansionofthesurveillancesitesto605monitoringpoints.

TheCauseofDeathMonitoringDataset(CDMD)summarizesthepopulationanddeathdatareportedbyeachsurveillancesiteandgroupsthe31provinces,autonomousregions,andmunicipalitiesintothreebroadregions,namelyEast,Central,andWest.

3

Table1

notesregionsinChinashowingthisgroupingmethod.ThecauseofdeathclassificationfollowstheICD-10codification.Wecollectedthemostcompletedandup-to-dateregion-cause-specificmortalitydatafromtheCDMDover2004–2019.Seebelowforsomedetaileddescriptionsofthedatasetandavailablecause-of-deathinformation.

?Annualdeathandpopulationexposuredata:disaggregatedintomales/females,5-yearagegroups(1–4,5–9,...,85+)

4

,East/Central/West,andUrban/Rural.ThedefinitionsofthethreebroadregionsareshowninTable1.

Table1

DEFINITIONOFTHREEBROADREGIONSINCHINA

Region

Province

East

Beijing,Tianjin,Hebei,Liaoning,Shanghai,Jiangsu,Zhejiang,Fujian,Shandong,Guangdong,Hainan

Central

Shanxi,Jilin,Heilongjiang,Anhui,Jiangxi,Henan,Hubei,Hunan

West

InnerMongolia,Guangxi,Chongqing,Sichuan,Guizhou,Yunnan,Shaanxi,Tibet,Gansu,Qinghai,Ningxia,Xinjiang

SpecificcausesofdeathreportedwithcorrespondingICD-10,CDMD,andGBDcodificationsaspresentedin

Table2.

3NotethatthisgroupingmethodfollowstheclassificationofregionsbytheNationalBureauofStatisticsofChina.

4Inthisresearch,wedecidetoexcludedataforage0(i.e.,infantmortality)toavoidpotentialunder-reportingissues,particularlyinruralareas.

11

Table2

CODIFICATIONOF9MAJORCAUSESOFDEATH

Causeofdeath

CDMDcode

ICD-10code

GBDcode

Infectious

C003,C031

A00-B99,G00,G03-G04,H65-H66,J00-J06,J10-J18,J20-J22,N70-N73

U002,U038

Cancer

C054

C00-C97

U060

Diabetes

C074

E10-E14

U079

Mental

C076

F01-F99,G06-G98

U081

Circulatory

C084

I00-I99

U104

Respiratory

C093

J30-J98

U111

Digestive

C098

K20-K92

U115

Congenital

C112

Q00-Q99

U131

External

C115

V01-Y89

U148

3.2SUMMARYSTATISTICSANDVISUALIZATION

Figure2

plotsthetotalmortalityratesfor2004–2019byageonalogscale.Weusedarkercolorstoplotearlieryearsandlightercolorstoshowthemortalityratesinmorerecentyears.Thelogmortalityratesinanygivenyearfollowthetypicalagepatternobservedinmanycountries,withaU-shapeatyoungeragesfollowedbyanalmostlinearincreaseinmortalityratestoages85+.Furthermore,

Figure2

showsthatmortalityratesinChinahavegenerallyimprovedduring2004–2019.

Figure2

TOTALMORTALITY2004-2019(MALESANDFEMALESCOMBINED)

Table3confirmsthatallagesexcepttheagegroup85+experiencedimprovementsinthemortalityratesovertheperiod2004–2019.Theaveragemortalityimprovementratesduring2004–2019areallpositiveexceptforages85+.Theimprovementsweregenerallylargeratyoungeragesandmiddleagesthanathigherages.

AsshowninTable3,theaveragemortalityimprovementrateduring2004–2019isestimatedtobearound3.2%,andthisisacrossallagegroupsexceptforage0.Whenwelookatthegeographicaldifferencesintheimprovementrates,wefindthatEastChinahasthehighestaverageimprovementrate,whichisabout3.4%,whileWestChinahasthelowestaverageimprovementrate,whichisabout2.9%.Ontheotherhand,itisabitsurprisingtoseethaturbanandruralareashadsimilarimprovementratesduringthistime.However,forurbanareas,theimprovementrateisgenerallyhigherforolderagegroups,whereasforruralareas,theimprovementrateishigherforyoungeragegroups.

12

Table3

AVERAGEMORTALITYIMPROVEMENTRATESDURING2004–2019(MALESANDFEMALESCOMBINED)

National

East

Central

West

Urban

Rural

1-4

0.064

0.058

0.048

0.070

0.044

0.070

5-9

0.039

0.039

0.028

0.042

0.037

0.040

10-14

0.022

0.026

0.012

0.027

0.025

0.020

15-19

0.040

0.046

0.031

0.046

0.025

0.046

20-24

0.048

0.055

0.053

0.038

0.043

0.049

25-29

0.040

0.045

0.035

0.034

0.048

0.036

30-34

0.037

0.040

0.033

0.034

0.046

0.032

35-39

0.042

0.038

0.044

0.042

0.042

0.041

40-44

0.037

0.036

0.043

0.036

0.041

0.036

45-49

0.029

0.033

0.032

0.023

0.030

0.029

50-54

0.034

0.039

0.035

0.025

0.037

0.033

55-59

0.031

0.031

0.032

0.029

0.024

0.035

60-64

0.031

0.024

0.034

0.035

0.024

0.035

65-69

0.030

0.029

0.031

0.031

0.028

0.032

70-74

0.029

0.026

0.032

0.030

0.034

0.027

75-79

0.022

0.029

0.024

0.009

0.028

0.019

80-84

0.022

0.028

0.028

0.003

0.028

0.019

85+

-0.016

-0.012

-0.006

-0.033

-0.011

-0.018

Average

0.032

0.034

0.032

0.029

0.032

0.032

3.3MORTALITYBYGENDER

Figure3

showsthelogmortalityratesbyageseparatelyformalesandfemalesforallyears2004–2019.Themortalityratesform