Emily Grundy and Michael Murphy Demography and public healtheprints.lse.ac.uk/63076/1/__lse.ac.uk_storage_LIBRARY_Secondary_libfile... · Demography and public health Book section

Emily Grundy and Michael Murphy

Demography and public health Book section

Original citation: Originally published in Grundy, Emily and Murphy, Michael J. (2015) Demography and public health. In: Detels, Roger, Gulliford, Martin , Karim, Quarraisha Abdool and Tan, Chorh Chuan, (eds.) Oxford Textbook of Global Public Health. Oxford textbooks, 2. 6th ed., Oxford University Press, Oxford, UK, pp. 718-735. ISBN 978019966176 © 2015 Oxford University Press

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Demography and public health

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PRINTED FROM OXFORD MEDICINE ONLINE (www.oxfordmedicine.com). (c) Oxford University Press, 2015. All RightsReserved. Under the terms of the l icence agreement, an individual user may print out a PDF of a single chapter of a title in OxfordMedicine Online for personal use (for details see Privacy Policy). Subscriber: Emily Grundy; date: 16 March 2015

Publisher: OxfordUniversityPress PrintPublicationDate: Feb2015PrintISBN-13: 9780199661756 Publishedonline: Feb2015DOI: 10.1093/med/9780199661756.001.0001

Chapter: DemographyandpublichealthAuthor(s): EmilyGrundyandMichaelMurphyDOI: 10.1093/med/9780199661756.003.0126

OxfordMedicine

OxfordTextbookofGlobalPublicHealth(6ed.)EditedbyRogerDetels,MartinGulliford,QuarraishaAbdoolKarim,andChorhChuanTan

Demographyandpublichealth

Introductiontodemographyandpublichealth

Thehealthandhealthcareneedsofapopulationcannotbemeasuredormetwithoutknowledgeofitssizeandcharacteristics.Demographyisconcernedwiththisandwithunderstandingpopulationdynamics—howpopulationschangeinresponsetotheinterplaybetweenfertility,mortality,andmigration.Thisunderstandingisaprerequisiteformakingtheforecastsaboutfuturepopulationsizeandstructurewhichshouldunderpinhealthcareplanning.Suchanalysesnecessitateareviewofthepast.Thenumberofveryoldpeopleinapopulation,forexample,dependsonthenumberofbirthseightorninedecadesearlierandrisksofdeathatsuccessiveagesthroughouttheinterveningperiod.Theproportionofveryoldpeopledependspartlyonthisnumeratorbutmoreimportantlyonthedenominator,thesizeofthepopulationasawhole.Thenumberofbirthsinapopulationdependsoncurrentpatternsoffamilybuilding,andalsoonthenumberofwomen‘atrisk’ofreproduction—itselfafunctionofpasttrendsinfertilityandmortality.Similarly,thenumberandcausesofdeathsarestronglyinfluencedbyagestructure.


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Demographyislargelyconcernedwithansweringquestionsabouthowpopulationschangeandtheirmeasurement.Thebroaderfieldofpopulationstudiesembracesquestionsofwhythesechangesoccur,andwithwhatconsequences.

Thischapterpresentsinformationondemographicmethodsanddatasourcesandtheirapplicationtohealthandpopulationissues,togetherwithinformationondemographictrendsandtheirimplicationsandthemajortheoriesaboutdemographicchange,inordertoelucidatethecomplexinterrelationshipbetweenpopulationchangeandhumanhealth.

Globalissues

Fig.6.3.1showsthattheworld’spopulationhasrecentlybeengrowingatanunprecedentedrateandwasestimatedtobe7.05billionatmid2012(UN2011).Whileittookanestimated123years(from1804to1927)fortheworldtoincreaseitspopulationfrom1to2billion,theincreasefrom6to7billionwasachievedinatenthofthetime(1999–2011).TheUnitedNation’s(UN’s)mediumprojectionsuggestsafurtherincreaseofsome2.3billionby2050(UN2011).Beyondthis,thereisagoodchancethatglobalpopulationgrowthwillceasebytheendofthetwenty-firstcentury(LutzandSamir2010).

Fig.6.3.1Populationandprojectedpopulationoftheworldandmore,less,andleastdevelopedregions,1950–2050.

Source:datafromUnitedNations,WorldPopulationProspects:The2010Revision,UnitedNations,NewYork,USA,Copyright©2011,availablefromhttp://esa.un.org/unpd/wpp/Excel-Data/population.htm.

Thisprospectofglobalpopulationstabilitymaskshugedifferencesbetweenregionsandbetweenricherandpoorercountries.Between1950and2000,77percentofworldpopulationgrowthoccurredincountriescurrentlydesignatedbytheUNaslessdeveloped(excludingthe


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leastdeveloped,seeBox6.3.1fordefinitions);13percentinleastdevelopedcountriesand11percentinmoredevelopedregions.Between2000and2050,medium-termprojectionssuggestthatpopulationgrowthinmoredevelopedregionswillaccountforonly4percentofthetotalwith63percentoccurringinlessdevelopedcountriesand33percentintheleastdevelopedcountries.Theseprojectionsimplythatby2050theshareoftheworld’spopulationlivingincurrentlymoredevelopedregionswillaccountforonly14percentofthetotalworldpopulation—comparedwith32percentacenturyearlier—whiletherepresentationofthoseinthepoorestcountrieswillhaveincreasedfrom8percentofthetotalin1950to19percentin2050.

Box6.3.1Countryandregionalclassificationsbylevelofdevelopment

TheUNclassifiescountriesinto‘more’and‘less’developedandalsoidentifiesagroupof50‘leastdeveloped’countries.ThemoredevelopedcategoryincludesallofEurope,NorthAmerica,Australia,NewZealand,andJapan.Theleastdevelopedcountriesaremostlyinsub-SaharanAfricabutalsoincludeAfghanistan,Bangladesh,Cambodia,andMyanmar.TheclassificationhassomeanomaliesinthatsomewealthyAsianandNearEasterncountriesarecountedaslessdeveloped(e.g.SouthKorea,Singapore,Cyprus,Israel)whereassomepoorerformerEasternbloccountriesaretreatedasmoredeveloped(e.g.Albania,Belarus,Bulgaria).

TheWorldBankemploysaclassificationbasedongrossnationalincomepercapitawhichdividescountriesintohigh-,middle-,andlow-incomegroups,withasubdivisionofthemiddleintoupperandlower.Someofthecountries(principallyfromEasternEurope)classifiedbytheUNasdevelopedfallintomiddle-incomecategories,whilesomeoftheUNlessdevelopedgroupareclassifiedbytheWorldBankasmiddleincome(principallyLatinAmerican)orhighincome(someSouthEastAsian).

MembershipoftheOrganisationforEconomicCooperationandDevelopment(OECD)isalsosometimesusedasanindicatorofdevelopedcountrystatus;membersincludeRussiaandMexico,bothofwhichareclassifiedbytheWorldBankasmiddle-ratherthanhigh-incomecountries.

TheHumanDevelopmentIndexcompiledbytheUNDevelopmentProgrammetakesintoaccountfactorsotherthanincome,suchasschoolenrolment,literacy,andlevelsofmortality.

Regionalgroupingsemployedbydifferentinternationalagenciesalsovaryslightly.Furtherdetailsofalltheseclassificationsareavailableontherelevantorganizations’websites.

Whilesomeregionsgrapplewiththeneedsofrapidlygrowingpopulations,suchaslargeincreasesinrequirementsforchildhealthservicesandschools,othersfacechallengesofpopulationageingand,insomecases,populationdecline.By2025,nearlyaquarteroftheWesternEuropeanpopulationisexpectedtobeaged65ormoreandinsomecountries,suchasJapan,SouthKorea,Spain,andItaly,projectionssuggestthatathirdormoreofthepopulationwillbeaged65andoverby2050(UN2011).


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Thesehugelydifferingratesofgrowtharisefromdifferencesinvitalrates,andassociatedlargevariationsinagestructures,whichareillustratedforregionsandselectedcountrieswithintheminTable6.3.1.InanumberofEuropeancountriesandsomeAsiancountries,suchasJapan,womenonaveragehaveonly1.4childrenorfewer(seeBox6.3.2forderivationoftotalfertilityrate),andpeopleaged65andoveroutnumberchildrenunder15.Insub-SaharanAfrica,womenonaveragehavefivechildreneach,40percentormoreofthepopulationisaged15orunder,andonly3percentaged65ormore.

Table6.3.1Indicatorsofagestructure,fertility,andmortality:worldregionsandselectedcountries,2011

Region/country Proportion(%)ofpopulationaged:

Totalfertilityrate

Lifeexpectancyatbirth(years)

<15 65andover

Africa 41 3 4.6 58

Sub-Saharan

43 3 5.0 56

Northern 33 5 3.1 70

Asia 25 7 2.2 70

India 30 5 2.6 67

China 18 9 1.5 75

Japan 14 23 1.4 84

Indonesia 27 6 2.3 71

SouthKorea

16 11 1.2 79

Australia 18 14 1.8 82

Europe 15 16 1.6 76

Italy 14 20 1.4 82

Poland 15 14 1.3 76

Germany 13 21 1.4 80


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Germany 13 21 1.4 80

Sweden 15 20 1.7 81

Ukraine 14 15 1.3 69

UK 17 16 1.9 80

LatinAmericaandCaribbean

27 7 2.2 74

Brazil 25 7 1.8 73

Chile 22 9 1.9 78

Guatemala 38 4 3.3 71

NorthAmerica 19 14 2.0 79

UnitedStates

20 13 2.1 78

World 26 8 2.4 68

Source:datafromUnitedStatesCensusBureau,PopulationDivision,InternationalProgramsCenter,InternationalDataBase,availablefromhttp://www.census.gov/population/international/data/idb/informationGateway.php.

Levelsofmortality,andassociateddifferencesinageandcausedistributionofdeath,alsovarymarkedly.Insomehigh-incomecountries,averagelifeexpectancyatbirthisabove80,whileinsomesub-Saharancountriesitisbelow50,substantiallybecauseofHIV/AIDS.AsshowninFig.6.3.2,inSierraLeone,40percentofalldeathsinayearareofinfantsandchildrenagedunder5,comparedwith0.3percentinJapan.Conversely,ofalldeaths,70percentinJapanand50percentinChile,amiddle-incomecountry,areofpeopleaged75andover;equivalentproportionsforEgyptandSierraLeoneare20percentand8percentrespectively.Thesevariationshaveenormousimplicationsforhealthandhealthcareprioritiesin,andbeyond,thepopulationsconcerned.Divergenceinpopulationgrowthbetweenregionsoftheworldisalsofuellingmassmigration,whichitselfhasimplicationsforglobalpopulationhealth(Fernandesetal.2007).


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Fig.6.3.2Cumulativedistributionofdeathsbyage;SierraLeone2009,Egypt2009,Chile2008,Japan2009.

Source:datafromUnitedNationsDepartmentofEconomicandSocialAffairs,DemographicYearbook2011,ST/ESA/STAT/SER.R/41,UnitedNations,NewYork,USA,Copyright©UnitedNations2012,availablefromhttp://unstats.un.org/unsd/demographic/products/dyb/dybsets/2011.pdf

Closelyrelatedtovariationsinthedistributionofdeathsbyagearedifferencesinthecausestructureofdeath.AsshowninTable6.3.2,communicablediseases,maternalandperinatalconditions,andnutritionaldeficienciesaccountfor67percentofalldeathsinsub-SaharanAfricabutonly5percentinEurope.Conversely,non-communicablediseasesareresponsiblefor25percentofdeathsinsub-SaharanAfrica,66percentinAsia,but88percentinEurope.Whileinpartsoftheworld,communicablediseasesandreproductiveandchildhealthpresentthemostpressingpublichealthproblems,concernsabouttheprevalenceofage-relatedchronicdegenerativediseasespredominateinothers.Insub-SaharanAfrica,1.2milliondeathsareduetoHIV/AIDS.Althoughthenumbersofsuchdeathsareestimatedtohavepeakedgloballyaround2005(UNAIDS2012),theystillrepresentasubstantialandlong-termburden(UN2011).


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Table6.3.2Distributionofdeaths(%)bycausegroupandworldregion,2010

Communicable Non-communicable

Injuries

Global 24.9 65.5 9.6

Europe 5.1 88.3 6.6

NorthAmerica 5.3 88.0 6.8

High-incomeAsiaandPacific 11.4 81.1 7.5

Oceania 15.1 78.1 6.9

LatinAmericaandCaribbean 14.2 69.0 16.8

NorthAfricaandMiddleEast 16.2 75.2 8.6

Asia(excl.high-incomeandMiddleEast)

23.3 66.2 10.4

sub-SaharanAfrica 66.5 24.9 8.6

Source:datafromGlobalBurdenofDiseaseStudy2010,MortalityResults1970–2010,InstituteforHealthMetricsandEvaluation(IHME),Seattle,Washington,USA,Copyright©2012,availablefromhttp://ghdx.healthdata.org/record/global-burden-disease-study-2010-gbd-2010-mortality-results-1970-2010.

Theprocessthatseparatespopulationswithhighfertility,relativelyhighmortality,youngagestructures,andrapidgrowthfromthosewithlowvitalrates,olderagestructures,andslowornogrowth,isconceptualizedasthedemographictransition.Identifying,andexplaining,thisandassociatedprofoundchangesinhealthhasbeenacentralpreoccupationofmoderndemography(Lee2003).Beforeturningtotheseissues,thebasicmethodsandmaterialsofdemographicanalysismustbeconsideredandtheissueofpopulationdynamics—howpopulationschange—addressed.

Demographicdataandmethodsofanalysis

Intheseventeenthcentury,JohnGraunt,aLondonmerchant,useddatafromtheLondonBillsofMortalitytodeviseanearlylifetable,leadingtohimbeingdubbedthe‘fatherofmoderndemography’.However,whileGraunthadinformationonnumbersofdeaths,helackeddataonthepopulationatriskandcouldnotcomputedeathrates.Essentiallyalldemographicanalysisrequiresdatabothonthepopulation‘stock’andon‘flows’inandout—births,deaths,andmigration.Thetraditionalsourcesofinformationontheformerarepopulationcensusesand,for


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thelatter,vitalregistrationsystems.

Populationcensuses

Thefirst‘modern’censuseswereundertakeninScandinaviaintheeighteenthcentury.CensusesspreadthroughoutEuropeduringthenineteenthcenturyandmostoftherestoftheworldinthetwentieth.Aswellasbasicquestionsaboutage,sex,maritalstatus,andplaceofresidence,dataonothercharacteristicssuchasemployment,educationandhousingareoftencollected.TheUNrecommendsthatcensusesbeconductedatleastdecenniallyinyearsendingin0or1.

Censuseshavemanystrengthsandareoftentheonlysourceofdataforsmallareasorpopulationsubgroups.Althoughprimarilyatoolforcollectingdataonpopulation‘stock’,censuseshavealsobeenusedtofindoutaboutvitalevents.Manycountriesusecensusestoprovidedataonrecentinternalmigration(throughquestionsonplaceofresidence1ormoreyearsearlier)andimmigration(throughquestionsoncountryofbirthand/ordateofentryforthosebornelsewhere).IndirectestimationtechniquesdevelopedbyBrassandothersmeanthatquestionsonnumberofchildrenbornandnumberwhohavedied,onwidowhood,andorphanhoodarewidelyusedtoassessmortalitylevelsandtrendsusingbothcensusesandsurveysincountrieswithdeficientvitalregistrationsystems(Prestonetal.2001).

However,censusesinvolvehugecostsandthechallengeofensuringacceptabledataquality.Approachestoreducingcost(andimprovingquality)includeuseofsamplecensuses,eitherforthecensusasawhole,asinChina,orformoredetailedquestions,asintheUnitedStates.Censustakingrequiresnotonlyareasonableadministrativeinfrastructure,butalsothecooperationofthepopulationtobeenumerated.Somecountrieshavegivenuptakingcensusesbecausethelatterislackingandnowrelyonlarge-scalesurveysor‘virtualcensuses’basedonpopulationregistrationdata.Thetwenty-firstcenturyisseeingmorecountriesadoptingalternativesastheinformationrequiredbygovernmentsbecomesmorecomplexandthedifficultiesofmassdatacollectionescalate.In2010,only11ofthe27currentEuropeanUnionmembersconductedtraditionalcensuses(Valente2010).

Whencensusesaretaken,difficultiesarisingfromerrorsandomissionsarecommon,evenincountrieswithalonghistoryofcensustaking.Young,geographicallymobileadults,recent(especiallyunauthorized)immigrants,membersofminorityethnicgroups,infants,andtheveryoldarethosemostlikelytobeunder-enumerated—someoftheverygroupsthatpolicymakersandhealthprofessionalsmaybemostkeentoknowabout.

Groupssuchasseasonalmigrants,militarypersonnel,peopletemporarilyawayfromhome,andthosewithmorethanoneresidencealsopresentproblems.Notonlyaretheymorelikelytobemissed,butadecisionhastobemadeaboutwhethertheyshouldbeassignedtotheirplaceofusualorlegalresidence(assumingitcanbedetermined),orcountedasbelongingtotheplaceofenumeration.Theformersystemistermeddejure,thelatterdefacto.Theissueofassigningpeopletosomeplaceofusualresidenceisimportantasoftenresourcesareallocatedbasedonpopulationsizeandcharacteristics.Moreover,itisessentialtotryandensurethatdemographiceventsrecordedinonesystem(vitalregistration)areattributedtothepopulationactually‘atrisk’ofexperiencingthem.Inrichercountries,forexample,mostdeathsoccurinhospitalswhichmaydrawpatientsfromawidearea.Ifthesedecedentsarenotassignedtothelocalitywheretheylivedpriortohospitaladmission,areasincludinglarge


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hospitalswillappeartohaveveryhighmortalityrateswhileinothers,recordedmortalitywillbeartificiallylow.

Under-enumerationisusuallyassessedthroughcensusvalidationsurveys(surveysofasampleofcensusaddressesinwhichintensiveeffortsaremadetocontactnon-respondentsandcheckinformationsuppliedbyrespondents)andcomparisonswithpopulationestimatesfromothersources.Beyondensuringnear-completeenumeration,thequalityofthedatacollectedisalsoamajorconcern.

Inmanypopulations,peoplemaynotalwaysknowtheirexactageandsomeapproximationisreportedormadebyanenumerator.‘Heaping’onagesendingin0or5isacommonresult.Heapingcanbedetectedbylookingattheagedistributionandapplyingvarioustestsofconsistencyandsuchdataarenormallyadjustedbeforepublication.Moreseriousproblemsarisewhenreportedageisbasedonothercharacteristics,suchasmaritalstatus,numberofchildrenorgrandparentstatus,asclearlyanyanalysisof,forexample,ageatfirstmarriage,willbebiasedifpeople’sreportoftheirageisinfluencedbytheirmaritalstatus.

Vitalregistration

Dataondemographicevents,aswellasonpopulationcharacteristics,areneeded.Inrichercountriesthesearedrawnfromvitalregistration.CompulsoryregistrationofbirthsanddeathswasestablishedinmostEuropeancountriesduringthenineteenthcentury.InEnglandandWales,forexample,civilregistrationwasintroducedin1837.Subsequentimprovementstothesystemincludedthosefollowingthe1874BirthsandDeathsRegistrationActwhichmadeparentslegallyresponsibleforregisteringbirthsandrequiredattendingphysicianstosupplyinformationoncauseofdeath.Otherrevisionshavesincebeenmade,forexample,theinclusionoffirstmother’sandlaterfather’sageandin2012,recordingofallchildrenpreviouslyborn,ratherthanjustlegitimateones,ontheconfidentialsectionofbirthcertificates.Mosthigh-incomecountrieshavewell-establishedregistrationsystemswithcomplete,orverynearcomplete,coverage.Inpoorerpartsoftheworld,however,vitalregistrationsystemsarefrequentlyseriouslyincompleteornon-existent,althoughthereareexceptionsandsomecountries,includingIndiaandChina,havesampleregistrationsystemsforselectedareas.CurrentlyonlyaboutathirdofdeathsestimatedtooccurgloballyareregisteredandreportedtotheWorldHealthOrganization,althoughifthesampleregistrationsystemsinIndiaandChinaareconsideredassufficientlyrepresentativeoftheirnationalpopulations,thisproportionrisesto72percent(Mathersetal.2005).

Thequalityoftheinformationsuppliedandcodedisofcourseveryimportant.Nooneregisterstheirowndeathandtheinformationobtainedfromproxyinformantsmaybeinaccurate.Differentialreportingofage,occupation,maritalstatus,orothercharacteristicsinthecensusandinothersources,suchasdeathcertificates,presentsafurtherdifficulty.Numerator–denominatordiscrepanciesmayintroduceseriousbiasintotheanalysisofmortalityatadvancedages,orbycharacteristicssuchasoccupationallydefinedsocialclass,maritalstatus,orethnicity(Williamsetal.2006).TheNordicandsomeotherEuropeancountriesavoidtheseproblemsbymaintainingwell-developedregister-basedsystemsthatlinkvitalregistrationdatatopopulation,occupational,andeducationalregisters.Onestudyofmaritalstatusdifferencesinmortalityatolderagesfoundmarkeddifferencesinresultsforcountriesusingtraditionalandregister-basedsystems(Murphyetal.2007).


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Causeofdeath

Deathcertificatesarethemajorsourceofinformationoncauseofdeath.Inrichercountries,causeofdeathisgenerallycertifiedbyaphysicianandcodedaccordingtotheInternationalClassificationofDiseases(ICD)whichoriginatedfromworkundertakenbythenineteenth-centuryBritishmedicalstatistician,WilliamFarr.ThetenthrevisionoftheICDcameintousefrom1994andincludednearlytwiceasmanycodesasICD-9.ICD-11isinpreparationandisexpectedtocomeintousein2015.Nationalpreferences,aswellasICDrevisions,mayinfluenceassignmentofcauseofdeath,asillustratedinanumberofclassicpapersinwhichcasestudiesofdeathsweredistributedtophysiciansindifferentcountries.Growingawarenessofparticularconditionsmayalsoinfluencecodingpractices.IntheUnitedStates,Australia,andelsewhere,forexample,therehavebeenlargeincreasesinmentionsofAlzheimer’sdiseaseandotherdementiasondeathcertificatessince2000.ThesepartlyreflectsomechangesassociatedwiththeintroductionofICD-10butalsoeffectsofincreasedawarenessandsomespecificcampaignstoincreaserecognitionoftheseconditions(Moschettietal.2012).

Olderpeople,nowthevastmajorityofdecedentsinlow-mortalitypopulations,aremorelikelytosuffermultiplepathologiesandthenumberofconditionsrecordedondeathcertificateshasbeenincreasing.Choiceofoneoveranotherasthe‘true’underlyingcauseofdeathisboundtobepartiallyarbitrary.IntheUnitedKingdom,forexample,between1984and1992some25percentfewerdeathswereallocatedtorespiratorydiseasespurelyasaresultofchangesintherulesusedtoselectunderlyingcauseofdeath(GriffithsandBrock2003).Multiplecodingofdeathcertificatesandanalysesbyallmentionsofaconditionmaybemoreinformativebutsuchdataareavailableinonlyafewcountries(Anderson2011).Variationsindeathcertificatecodingreflectingdifferencesinmedicalknowledgeanddiagnosis,intheextenttowhichautopsiesareused,inclassificationsystems,andthequalityofregistrationsystemsareamajorfactorcomplicatinganalysesoftrendsovertimeorbetweencountries.

Deathsassignedtosymptoms,signsandill-definedconditionssuchas‘oldage’or‘senility’orothercauseslackingdiagnosticmeaning,sometimesreferredtoas‘garbagecodes’,presentaparticularproblem.Mathersetal.(2005)inaninvestigationofcoverageandqualityofcauseofdeathcodingin2003,foundthatinsomecountriesover40percentofdeathswereassignedtothese‘causes’.Only23countriesmettheirdefinitionofhighqualityofdatawithcoverageofatleast90percentandfewerthan10percentofdeathsassignedtoill-definedcodes.

Variationsincodingpracticesanduseofill-definedcodescomplicatecomparisonsovertime,aswellasbetweencountries.Preston(1976)arguedthattherewasaninverseassociationbetweentheproportionsofdeathsassignedtocirculatorydiseasesandtoill-definedcauses,andthatpartoftheapparenttwentieth-centuryepidemicinheartdiseasemortalityinrichercountriesmayhavebeenanartefactualconsequenceofimprovementsindeathcertification.AreviewoftheproportionofalldeathsinEnglandandWalesassignedtocirculatorydiseasesandtoill-definedcausesinagegroupsover65from1911–1915to2001–2010isinstructive.Earlyinthetwentiethcentury,largeproportionsofdeathsamongtheveryoldwereassignedtoill-definedcategoriesanddeclinesinthisproportionwereassociatedwithincreasesintheproportionattributedtocirculatorydiseases.Theproportionofill-defineddeathsintheoldestgroupaged80andoverwas,however,slightlyhigherin2001–2010thanintheprecedingperiod,reflectingincreasedassignmentto‘oldage’asacause.Reasonsforthisareunclear,althoughthecessationin1993offurtherenquiryintovaguecausesofdeathmayhavebeenasmallcontributoryfactor.Useofthis‘causeofdeath’islikelytobereversedagaininresponse


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tothe2000–2005publicenquiryintothecaseofHaroldShipman,aBritishfamilydoctorwhoseserialmurderofover250elderlypatientswasnotdetectedformanyyears;anillustrationoftheimportanceofsurveillanceofdeathsforreasonsotherthanepidemiologicalordemographicinvestigation.

Incountrieswhichlackadequatecertificationandregistrationsystems,dataondeathsbycauseareseriouslylimited.Attemptshavebeenmadetodevelopverbalautopsies,protocolsforcollectinginformationfromlayinformantswhichcanbereviewedbyphysiciansandusedtoassigncauseofdeath(Wangetal.2007).Thisapproachhasbeenusefulinanumberofsmallinvestigationsandisbeingemployedonalargerscale,forexample,inIndia(GajalakshmiandPeto2011).However,arecentstudytestedphysician-certifiedverbalautopsiesinsixsitesinfourpoorercountriesagainstgoldstandardassessmentandfoundaconcordanceoflessthan50percent,withsubstantialvariabilitybycauseandphysician(Lozanoetal.2011).Intheabsenceofroutinelyrecordeddata,estimatesmaybeobtainedbymodelling.ThishasbeenusedfortheimportantissueofestablishingthenumberofdeathsfromHIV/AIDS.ThemostambitiousexerciseistheGlobalBurdenofDiseaseprogrammewhichhasusedalargearrayofsourcesandmethods,includingexpertknowledge,vitalregistration,fieldsurveys,surveillance,andpoliceandmortuarydatatoderiveestimatesofcause-specificmortalitybyageandsexfor235separatecausesforeverycountryintheWorld(Wangetal.2012).

Otherdatasources

Manycountrieshavearangeofsurveyswhichprovidemoredetailedinformationon,forexample,health-relatedbehaviour,familybuildingstrategies,reasonsformigration,orinformationonbiomarkersthatwouldbeimpossibletocollectinacensus.Inpoorercountries,whereotherdatasourcesarescarcer,surveysoftenpresentthebestsourceofdataonbasicdemographicparameters.Dataqualityispotentiallybetterinasurveythanacensus,asitismorelikelythatwell-trainedinterviewerscanbeused.TheWorldFertilitySurvey(WFS),aninternationalpopulationresearchprogrammelaunchedin1972todeterminefertilitylevelsthroughouttheworld,anditssuccessor,theDemographicandHealthSurveyProgramme(DHS),havebeenparticularlyvaluableinprovidingdemographicandhealthdataforarangeofpoorercountries.Otherapproachesincludemulti-roundsurveys,inwhichrespondentsareaskedabouteventssincelastcontact,anddual-recordsystemswhichinvolvetwoindependentdatacollectionsystems(oneoftenamulti-roundsurvey),theresultsofwhicharethencombined.Thismethodallowssomeestimationofmissedevents,butisexpensive.Theseapproachesaredescribedinmoredetailinmostdemographictextbooks(Prestonetal.2001;Rowland2003;SiegelandSwanson2004).

Therawmaterialsofdemographyrelatetoindividuals’mostpersonalexperiences—sexualactivity,familyformation,birthcontrol,reproduction,maritalbreakdown,illness,anddeath.Alloftheseoccurinasocialframeworkwhichattachesvaluetosomeofthesebehavioursandstigmatizesothers.Notsurprisingly,respondentsincensusesandsurveysmaybereluctanttodisclosenon-maritalpregnancies,illegalabortions,undocumentedmigration,ordeathsofrelativesfromAIDS.Concealmenthasalsobeenthepolicyofsomenationalgovernmentswhichhavetreateddemographicdataasofficialsecrets.Additionally,theenormouspotentialcomplicationsarisingfrompeople’suncertaintiesaboutageorother‘basic’characteristicsincludingchildrenever-born;uncertainrecollectionsofprioreventsandthevastscopeforadministrativeerrorshavetobeconsidered.Thedemographer’straditionalobsessionwithdata


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qualityishenceunderstandable.Differencesinperceptionsandreportingofhealthstatusarealsoproblematicandhavebedevilledattemptstomakeinternationalcomparisonsofhealthstatusas,evenifquestionsareharmonized,thewayspeoplerespondtothemarenot(Rituetal.2002).

ThestatisticsproducedinseriesliketheUnitedNationsDemographicYearbookshavetheiroriginsinwhatisorhasbeendonebymillionsofpeople,mediatedbywhatissaidabouttheseeventsandexperiences,furtherfilteredbyhowthisisrecorded,processedandanalysed.SomeassessmentofdataqualityisgivenintheUnitedNationsDemographicYearbooks,butsometimesusersmaypayinsufficientattentiontothis.AnumberofotherorganizationsalsoproduceinternationalreferenceworksanddatabasesincludingtheWorldHealthOrganization(WHO),theWorldBank,theOrganisationforEconomicCooperationandDevelopment(OECD),Eurostat,TheUnitedStatesCensusBureauInternationalDataBase(UnitedStatesCensusBureaun.d.),andtheHumanMortalityDatabase.Inmostcases,theseareavailablefreeofchargeonline.

Theanalysisofdemographicdata

Astandardarrayoftechniquesandmeasuresformsthebasisofmuchdemographicanalysis;themostcommonofthesearedescribedbrieflyhere.Furtherdetailissuppliedinanumberoftextbooks(Prestonetal.2001;Rowland2003;SiegelandSwanson2004).Analysisinvolvesnotjusttheapplicationofaparticulartechnique,butalsodecisionsaboutwhatunitsofanalysistouseandhowtogroupthem.Amajordistinctionisbetweenperiodandcohortanalysis.Periodanalysisdealswitheventsofaparticulartimeperiod(e.g.mortalityratesfrom2005to2010)whilecohortanalysesfollowtheexperienceofindividualsthroughtime.Cohortsinthissensearedefinedasgroupsofpeoplewhohaveexperiencedthesamesignificanteventatthesametime.Thusbirthcohortscomprisepeopleborninaparticularyearorgroupofyearsandmarriagecohortsthosemarryingataparticulartime.Cohortandlife-courseapproachestoanalysingmortalityandotherindicatorsofpopulationhealthhaveanintuitiveappealandareincreasinglyused,bothfuellingandfuelledbyagrowingnumberoflongitudinalstudies.Cohortanalysisoftimeseriesdatamaybeusedintheabsenceofspeciallycollectedlongitudinaldata.

Cohortandperiodaretwoofthedimensionswhich‘place’personsintime;thethirdisage.Durationeffects(suchasdurationofmarriage,proximitytodeath,orlengthofexposuretoaparticularpathogen)mayalsobeimportant.Cohorteffectsmaybesubstantialand,unlessallowedfor,maymaskrelationshipsbetweenageandvariousrisks.Differencesinthesmokingbehaviourofcohorts,forexample,haveamajoreffectontherelationshipsbetweenageandsmoking-relateddiseaseobservedatdifferentperiods(Grundy1997).

Decisionsaboutwhethertouseindividuals,families,households,orgeographicareasasunitsofanalysisareoftenconstrainedbydataavailability.Untilrelativelyrecently,mostcensusdatawereonlyavailableasaggregatetabulations,butindividual-levelinformationisincreasinglyavailable.Otherinnovationsincludethedevelopmentofsamplesincludinglinkedcensus,vitalregistration,andinsomecaseshealthservicedatasuchastheLongitudinalStudiesavailableforcountriesoftheUnitedKingdomandanumberofothers(Youngetal.2010).Inthesedatasets,individuals’censusrecordsarelinkedwiththeirvitalregistrationrecordssonumerator–denominatorbiasesin,forexample,theanalysisofmortalityareavoided.InNordiccountries,


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thewholepopulationhasbeenassignedpersonalidentificationnumbersfacilitatinglinkageofinformationfromarangeofregisters.Linkagetouseofhealthandcareservicesisalsoavailableinsomecountries,suchasFinland.

Theseadvanceshavegreatlyextendedthematerialavailableforanalysesofvariationsindemographicbehaviour,andtheirconsequences.Theyhavealsoraisedcomplexsecurityandconfidentialityissuesfuellingdebateoverappropriaterestrictionsonaccesstodata.

Themeasurementoffertility

Fertilitymeansthechildbearingperformanceofawoman,couple,orpopulation.Generallyonlylivebirthsareincluded.Thetermfecundity,bycontrast,isusedtorefertothephysiologicalcapabilityofproducingalive-bornchild.Aroughideaoffertilitymaybegainedfromusingcensusorsurveydatatocalculatechild–womanratios:theratioof0–4-year-oldstowomenaged15–49.However,thesurvivalofinfants(andtheirmothers)andtheagestructureofthefemalepopulationaffectstheseratios,sotheyaregenerallyonlyusedifnootherdataareavailable.

Thesimplestmeasureoffertilitycommonlyusedisthecrudebirthrate—thenumberofbirthsinaparticularyearper1000population.Asthedenominatorofthisincludesthosenot‘atrisk’ofgivingbirth(womenoutsidereproductiveagegroupsandmen),itisreallyaratioratherthanarate.Crudebirthratesareinfluencedbytheagestructureofthepopulation,butlessseriouslysothancrudedeathrates.In2005–2010crudebirthratesrangedfromlessthan10per1000inpartsofEuropetonearly50per1000inthehighestfertilitycountriesofsub-SaharanAfrica.

Slightlymoresophisticatedisthegeneralfertilityratio—birthsper1000womenofreproductiveage(generallydefinedasaged15–49or15–44).Wheredataallow,age-specificfertilityrates(birthsper1000womenofaparticularageoragegroup)arepreferred.Thesearefrequentlysummarizedusingthetotalfertilityrate(TFR).Where,asisusuallythecase,perioddataareusedtocalculatethis,itindicateshowmanychildrenwomeninahypotheticalcohortwouldhaveiftheyexperiencedcurrentage-specificfertilityratesthroughouttheirreproductivelife.ThismeasureissometimesexplicitlydenotedTPFR(totalperiodfertilityrate).Inlow-mortalitypopulations,aTFRof2.1istakentoindicatereplacementlevelfertilityas,underthisregime,acohortofwomenwouldbesucceededbyacohortofdaughtersofthesamesize(aftersomeallowanceformortalityandthefactthat105–106boysarebornforevery100girls).

OnedifficultywiththeTFRisthatitisaffectedbychangesinthe‘tempo’aswellasthe‘quantum’ofchildbearing.Ifwomenstartdelayingtheirfertilitybut‘catchup’later,therewillbeadivergencebetweencohortandperiodmeasures,asthelatterwillbebasedpartlyonthebehaviourofearliercohortswhosetimingofbirthswasdifferent.Similarly,ifwomenhavechildrenearlier,TFRswillrise,evenifeventualfamilysizesremainunchanged.Thismeansthatperiodmeasuresaremuchmorevolatilethancohortones.Forexample,theUSTFR,havingrisenintheearlypartsofthiscentury,fellbymorethan10percent,from2.12to1.89,between2007and2011(Hamiltonetal.2012).Forthesereasons,manystatisticalofficesusecohort,ratherthanperiod,measuresoffertilityasthebasisforprojections.

Moresophisticatedmeasuresoffertilityincludeparityprogressionratios.Theseindicatetheprobabilityofproceedingfromonebirthtoanother(e.g.whatproportionofmotherswithtwo


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childrenprogresstohavingathird).Parityprogressionratiosarenormallycalculatedforcohortswhohavecompleted,ornearlycompleted,theirchildbearingbutitisalsopossibletousedataonbirthsbybirthordertoderiveperiodprogressionratios(BongaartsandFeeney1998).

Inthepast,demographersoftenpreferredtocalculateage-specificmaritalfertilityrates(andTFRsandothermeasures)onthegroundsthattheunmarriedpopulationisnot‘atrisk’(oratreducedrisk)ofchildbearing.Changesinmaritalfertilityindicativeofdeliberateattemptstolimitfamilysizeareregardedasoneofthedefiningfeaturesofthefertility‘transition’(seelater)andsodistinguishingthesefromchangesduetovariationsinthe‘atrisk’(marriedpopulation)hasbeenparticularlyemphasized.However,risesinnon-maritalchildbearing,whichnowaccountforover40percentofbirthsincountriessuchasFrance,theUnitedStates,andUnitedKingdom,meanthatrestrictinganalysestomaritalfertilityisgenerallynolongerappropriate.

Reproductionrates

Intheabsenceofmigrationandwithfixedmortality,populationswillgrowifmothersreplacethemselveswithmorethanone(surviving)daughteranddeclineiftheyhavefewerthanone.Theoretically,itwouldalsobepossibletomeasurethereplacementoffathersbysons,butinpracticethedifficultiesinvolvedinobtainingpaternitydatamakethisinfeasible.Reproductionratesthusrelateonlytofemalefertility—birthsofdaughters.Thegrossreproductionrate(GRR)isderivedinthesamewayastheTFRexceptthatage-specificbirthratesbasedonlyonbirthsofdaughtersareusedinthecalculation.Thenetreproductionrate(NRR)makesanallowanceformortality;specificallythechancethatadaughterwillherselfsurvivetochildbearingage.TheNRRcannotbecalculatedunlessbothage-specificfertilityandmortalitydataareavailable(althoughitcanbeapproximatedusingtheGRRandappropriatelifetablesurvivaldata).Changesineitherfertilityormortality(orboth)willmeanadivergencebetweenperiodmeasures(basedontheexperienceofahypotheticalcohort)andtheexperiencesofrealcohorts.

SummaryinformationonmeasuresoffertilityandreproductionisshowninBoxes6.3.2and6.3.3.

Box6.3.2Fertilitymeasures

DefinitionsFertility:thechildbearingperformanceofindividuals,couples,orpopulations.Fecundity:thephysiologicalcapabilityofproducingalivebirth.Parity:thenumberofchildrenpreviouslybornalive(orsometimesnumberofpreviousconfinements)toawomanorcouple.Nulliparouswomenarethosewhohavebornenochildren.

Measure


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Crudebirthrate:theratioofbirthsinayear(otherspecifiedperiod)totheaveragepopulationinthesameyear/period(mid-yearpopulation),expressedper1000:

Generalfertilityrate:birthstowomenaged15–44/49inayear/periodper1000womenaged15–44/49inthesameperiod:

Age-specificfertilityrate(ASFR):numberofbirthstowomenagedx(orxtox+n)per1000womenagedx(orxtox+n).‘n’referstothelengthofanageinterval.

ASFRsarefrequentlycalculatedfor5-yearagegroupsfrom15–19to40–44or45–49.

Total(period)fertilityrate(TFR/TPFR):thesumoftheage-specificfertilityratesforallreproductiveagegroupsforaparticularperiod(usuallyayear),conventionallyexpressedperwoman.TheTFRindicateshowmanychildrenawomanwouldhaveifthroughoutherreproductivelife,shehadchildrenattheage-specificratesprevalentinthespecifiedyearorperiod.

x=49:

where‘f ’istheage-specificfertilityrateatagex.Ifratesforagegroups,ratherthansingleyears,areusedthenthesumoftheage-specificratesmustbemultipliedbythenumberofsingleagesincludedinthegroup(usuallyfive).

x=45–49:

Parityprogressionratio:theprobabilityofawomenofparityxprogressingtoparityx+1.

Box6.3.3Reproductionrates

Measures

CBR = ×1000.numberofbirths

mid-yearpopulation

GFR = ×1000.numberofbirthstowomenaged15 −44/49

mid-yearpopulationofwomenaged15 −44/49

ASFR = ×1000.birthstowomenagedx

mid-yearpopulationofwomenagedx

TFR = ∑x=15

x=49

fx

x

TFR = 5 ∗ .∑x=15−19

x=45−49

fx


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Grossreproductionrate(GRR):thesumoftheage-specificfemalefertilityrates(birthsofdaughters),forallreproductiveagegroupsforaparticularperiod(usuallyayear)conventionallyexpressedperwoman.TheGRRindicateshowmanydaughtersawomanwouldhaveif,throughoutherreproductivelife,shehadchildrenattheage-specificratesprevalentinthespecifiedyearofperiod.TheGRRcanbecalculatedeitherbysummingfemaleage-specificfertilityrates(relatingtobirthsofdaughtersratherthanallbirths)orusingtheformula:

Theproportionoffemalebirthscanbetakenas0.488(100/205)intheabsenceofmoredetailedinformation.

Netreproductionrate(NRR):theaveragenumberofdaughtersthatwouldbeborne,accordingtospecifiedratesofmortalityandofbearingdaughters,byafemalesubjectthroughlifetotheserates.TheNRRemploysthesamefertilitydataastheGRR,butalsotakesintoaccounttheeffectsofmortality.AnNRRof1.0indicatesthatapopulation’sfertilityandmortalitylevelswouldresultinexactreplacementofmothersbydaughters.

Themeasurementofmortality

Asforfertility,thesimplestmeasureofmortalityisthecrudemortalityrate,deathsper1000population.Thisisstronglyinfluencedbyagestructure.Althoughlifeexpectancyatbirthinthemoredevelopedregionsoftheworldin2005–2010wassome10yearslongerthaninlessdevelopedregions(76yearsand66yearsrespectively),crudedeathrates—deathsper1000populationofallages—werehigherinthemoredevelopedregions(10.0comparedwith8.0inlessdevelopedregions)(UN2011).Age(andsex)specificrates,ormeasuresbasedonthem,arethereforemuchtobepreferredifdataareavailabletocalculatethem.Bothdirectandindirectstandardizationaresometimesusedtomakecomparisonsbetweenpopulationswithdifferentageandsexstructures.Standardizedmortalityratios(SMRs)arecalculatedusingindirectstandardization.Thisinvolvesselectingasetof‘standard’age-specificmortalityrates,forexample,thoseforanationalpopulation,andapplyingthesetothenumbersofpeopleintherelevantagegroupsinthesubpopulationofinterest—forexample,thepopulationofaparticularregion.Thisyieldsan‘expected’numberofdeaths—thenumberofdeathstherewouldbeinthesubpopulationifage-specificdeathrateswerethesameasthoseinthestandardpopulation.TheratioofobservedtoexpecteddeathsgivestheSMR.ThusanSMRof1.24indicatesthatmortalityinthesubpopulationis24percenthigherthaninthestandardpopulation,afterallowingforagedifferences.SMRsareusefulsummarymeasuresofdifferencesinmortality,butgivenoindicationofthelevelofmortality.Indirectstandardization,widelyusedbyWHOandnationalstatisticaloffices,ageandsexspecificratesareappliedtoanexternal‘standard’population,suchastheEuropeanStandardPopulation,toproduceanoverallstandardized(weighted)deathrate.

Age-specificdeathratesarecalculatedusingthenumbersofdeathsatagex(orbetweenagesxandx+n)inaparticularyearasthenumeratorandthemid-yearpopulationofthesameageasthedenominator.Therateisconventionallyexpressedper1000orper100,000population.Themid-yearpopulationisusedasameasureoftheaveragepopulationatriskontheassumptionthatdeathsareevenlydistributedthroughouttheyear.Forsomeagegroups,

GRR = TFR×proportionoffemalebirths.


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notablyinfants,thisassumptionisinvalid.Inlow-mortalitypopulations,deathsinthefirst3daysoflifemayaccountforhalformoreofalldeathsinthefirstyearoflife.Moreover,informationonthesizeofpopulationagedlessthan1normallycomesfrombirthdata(asin9outof10yearsrelevantcensusdatawillnotbeavailable).Forthesereasonslivebirthsinaparticularyearareconventionallyusedasthedenominatoroftheinfantmortalityratewhiledeathstoinfantsagedlessthan1constitutethenumerator.Someinfantsdyinginagivenyearwillhavebeenborninthepreviousyearandsomebornintheyearinquestionwilldiethefollowingyear.Thiscancausedistortionsiftherearelargeannualfluctuationsinnumbersofbirths(orinfantdeaths)andoften3-yearaveragesarepreferred.Deathsatveryoldagesarealsonotevenlydistributedthroughouttheyearandanadjustmentisoftenmadetoallowforthis.

Infantmortalityrates(IMRs)wereveryhighinsomepartsofhistoricalEurope—with300oreven400deathsper1000livebirthsinregionsofRussiaandGermanyattheendofthenineteenthcentury(vandeWalle1986).InEnglandandWalesatthestartofthetwentiethcentury,thereweresome140infantdeathsper1000livebirths.Infantmortalityinhigh-incomecountriesisnowextremelylow—fewerthanfiveinfantdeathsper1000livebirthsinmanyEuropeancountries,Australia,Japan,SouthKorea,HongKong,andSingapore.Therehavealsobeenhugefallsininfantmortalityinmanypoorercountries;in2011ChinaandIndiahadreportedIMRsof13and47respectively(WHO2013).Ratesremainhighinsomeoftheverypoorestcountries—over100deathsper1000livebirths.

Variationsonthisscalehavesubstantialdemographicimpacts.Infantmortalityhasalsoattractedparticularinterestbecauseoflinkswithfertilitybehaviourandasanindicatorofpublichealthconditions.Particularlyinthislattercontext,perinatal,earlyandlateneonatalandpostneonatalmortalityratesareoftendistinguishedwheredataallow(seeBox6.3.4).

Box6.3.4Mortalitymeasures

MeasuresCrudedeathrate:theratioofdeathsinayear(otherspecifiedperiod)toaveragepopulationinthesameyear/period(mid-yearpopulation),expressedper1000:

Age-specificmortalityrate(ASMR):numberofdeathstopersonsagedx(orxtox+n)per1000personsagedx(ortox+n):

Standardizedmortalityratio(SMR):theratioofobservedtoexpecteddeathsinastudypopulation.Expecteddeathsarecalculatedbyapplyingasetofstandardage-specificmortalityratestotheagedistributionofthestudypopulation.Standardizedratiosareonlyusefulforcomparisons.Theyhavenointrinsicmeaning.

CBR = ×1000.numberofdeaths

mid-yearpopulation

ASMR = ×1000.deathstopersonsagedx

mid-yearpopulationofpersonsagedx


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Infantmortalityrate(IMR):

Sometimesdecomposedintoneonatalmortalityrates(deathsofliveborninfantsduringthefirst4weeks)andpost-neonatalmortality(from4to52weeks).

Theperinatalmortalityratemeasureslatefetaldeaths(stillbirths)andearlyneonataldeathsrelativetolivebirths.

Stillbirthsusedtorefertodeathsoffetusesof28ormoreweeks’gestation;however,anearlierthresholdof24weeksisnowmoregenerallyused.

Lifetables

Lifetableanalysisisacoredemographictechniqueandlifetablesprovideoneofthemostpowerfultoolsforanalysingmortalityandotherdemographicprocesses.Lifetablesshowtheprobabilityofdying(andsurviving)betweenspecifiedages.Theyalsoallowthecalculationofvariousotherindicators,includingexpectationoflife.Ifcompletedataonthemortalityofabirthcohortareavailable,thenacohortlifetablemaybeconstructed.However,theuseofcohortlifetablesisobviouslyonlypossibleretrospectively.Morecommonly,periodlifetables,basedonmortalityratesataparticulartime,arecalculated.Theselifetablesshowdeath(andsurvival)probabilitiesforahypotheticalcohortwithanarbitraryradix(numberofbabiesatthebeginning)usuallysetto10,000,100,000orsomeothermultipleof100.

Specificnotation,summarizedinBox6.3.5,isusedinlifetableanalysis.Thebasisofthetableisasetofprobabilitiesofdying— q —whicharecalculatedfromage-specificdeathrates;xherereferstoageatthestartofanintervalwhoselengthisspecifiedbyn.Thus q referstotheprobabilityofsomeonealiveat50dyingbetweenage50andage55.Thecomplementofq —theprobabilityofsurviving—isdenoted p .The(hypothetical)numberofsurvivorsateachageisgivenbyl ;thusl equalstheradix(of100,000)andl thenumberofsurvivorsatage75.Thenumberofpersonyearslivedinaninterval( L )andthetotalnumberofpersonyearslivedafteraparticularage(T )areoftennotshowninpublishedtablesbutarestepsonthewaytothecalculationofe —lifeexpectancyatagex.

Box6.3.5Lifetablemeasuresandnotation

x=ageattainedlastbirthday.

l =theradixofthelifetable(hypotheticalnumberofbabies),usually100,000.

l =numberofsurvivorsatagex,sol isthenumberofpersonsaliveatage65inthehypotheticallifetablepopulation.

×1000.numberofdeathstoinfantsages < 1year

numberoflivebirths

Perinatalmortalityrate

= ×1000.stillbirths+deathsunder1weekstill+livebirths

n x

5 50

n x n x

x o 75

n x

x

x

0

x 65


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q =probabilityofdyingbetweenagexandx+n,so q istheprobabilityofdyingbetweenage1and5forapersonaged1.

p =probabilityofsurvivingbetweenagesxandx+n,so p istheprobabilityofsurvivingfromage65toage85forapersonaged65.

d =numberofdeathsbetweenagexandx+n.

L =numberofpersonyearslivedbetweenxandx+n.

T =totalnumberofpersonyearslivedafteragex.

e =expectationoflifeatagex,soe isexpectationoflifeatbirth.

Thismeasureprovidesanindicatorofmortalitywhichisverylargelyindependentoftheagestructureofthepopulationsinceitdependsonlyonage-specificmortalityrates.Thismakesitmoreusefulthaneitherastandardizedmortalityratio(whichgivesnoindicationoflevel)oracrudedeathrate(whichisstronglyinfluencedbyagestructure).Lifeexpectancyeitheratbirth(e )orfurtherlifeexpectancyataparticularage,say65(e ),iscalculatedbydividingthetotalpersonyearslivedafterage0or65(T orT )bythenumberofsurvivorsaged0(l )or65(l ).

Valuesoflifeexpectancyatbirtharesometimes(mis)interpretedasindicatorsofusualageatdeathinaparticularpopulation.Inverylow-mortalitypopulationswheremostdeathsoccurwithinarelativelysmallrangeofages(seetheexampleofJapaninFig.6.3.2);therewillbeaclosecorrespondencebetweenmedianandmodalagesofdeathandlifeexpectancyatbirth(whichisameanvalue).However,inpopulationssuchasSierraLeonewheresomanydeathsoccurininfancy,therewillbeawidedivergence.Thereisalsosometimesconfusionabouttheinterpretationofvaluesoffurtherlifeexpectancyataparticularage.Thisisderivedfrominformationabouttheprobabilitiesofdeathandsurvivalatsubsequentages,andsoisnotinfluencedbydeathsatearlieragesanditiserroneoustothinkthat,forexample,thefurtherlifeexpectancyofsomeoneaged65willequallifeexpectancyatbirthminus65.Thehigherthemortalityratesatyoungagesthegreaterwillbethisdivergence.In2008,forlifeexample,femalelifeexpectancyatbirthintheUnitedStateswas80.6yearsbutthefurtherlifeexpectancyofwomenaged65was20.0years.Theequivalentfiguresin1900–1901were49yearsand12.0years.

Modellifetables

Patternsofage-specificdeathratesshowsimilaritieswhateverthelevelofmortality.Deathratestendtobehigherininfancythanlaterchildhoodandrisewithagefromaroundtheageofpuberty,althoughintheoldestagegroupsratesofincreasetendtoflattenout.Becauseofthetendencyfordeathratesatoneagetobeassociatedwithdeathratesatotheragesinagivenpopulation,itispossibletoderivehypotheticalschedules,calledmodellifetables,describingvariationsinmortalitybyageandsex,normallyintermsofalimitednumberofparameterswhichallowforparticularfeaturesofthemortalitypatternofthepopulationconsidered.Modellifetablesarederivedfromempiricaldatafromcountrieswheretheseareavailable.Theyareextremelyusefulaidsfortheestimationofmortalitybyageinpopulationswithdefectivedata.

n x 4 1

n x 20 65

n x

n x

x

x 0

0 65

0 65 0

65


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Theyarealsoused(inconjunctionwithfertilitydata)toshowtheoutcomesofparticularfertilityandmortalityregimeson,forexample,populationagestructureandformakingpopulationprojections.Alldemographictextsgivefurtherdetailsoftheirderivationandapplication.

Otherapplicationsoflifetableanalysis

Lifetablesarewidelyusedtoanalyseprobabilitiesassociatedwitheventsotherthandeath,suchasrisksofdivorceorcontraceptiveusefailureanddiscontinuationrates,andinestimatesofdisability-freeorhealthylifeexpectancy.Manychronicconditionsassociatedwithageing,suchasmusculoskeletalandsensoryimpairments,mayhaveseriousimplicationsforhealthstatusbutarenotdirectlylife-threatening.Lifetablemethodsareusedtodecomposetotallifeexpectancyinto‘healthy’and‘unhealthy’or‘disabled’components.Thiscanbedoneusingcross-sectionaldataonmorbidityprevalenceinconjunctionwithmortalitydata,althoughthishassomelimitations.Moresophisticated(anddatademanding)multistateapproacheswhichallowtransitionsbothtoandfromdisabledstateshavealsobeendeveloped(Mantonetal.2006).Despitethesetechnicaladvances,thereisstillcontroversyabouttrendsinindicatorsofthehealthstatusofpopulations,includingdisability.Toalargeextentthisdebatearisesfrommeasurementproblemsandthedifficultiesinvolvedinmakingcomparisonsbetweenhealthindicatorsderivedindifferentways,afurtherreminderoftheimportanceofdataqualityandmeasurement.

Multipledecrementlifetablesallow‘decrements’frommorethanoneevent—forexample,differentcausesofdeath.Causeeliminationlifetablesarealsousedtoidentifythe‘pure’severityofaparticularcauseofdeath.Multistatemodelsallowanalysisofarangeoftransitions,particularlythosewherere-entriesintoaparticularstate,suchasbeingmarriedorlivinginacertainregion,arepossible.Thesemoresophisticatedapplicationsofcourserequiremoredetaileddata.

Themeasurementofmigration

Inmanycountriesmigrationisthepredominantinfluenceonthespatialdistributionofthepopulation.InAsiaandLatinAmericarecentrural-to-urbanmigrationhasresultedinthephenomenalgrowthofcities,oftenlackingtheinfrastructuretomeettheneedsoftheexpandingpopulationforbasicservicessuchassanitationandpower.In2010,52percentoftheworld’spopulationlivedinurbanareascomparedwith29percentin1950(UN2012).

Measuringmigrationrepresentsparticulardifficulties.Theclassicaldefinitionofinternalmigrationisapermanentorsemi-permanentmoveacrossanadministrativeboundary,whichmeansthattheextentofmigrationrecordeddependspartlyonthesizeofadministrativeareas.Forexample,inacountrydividedintomanysmallareas,amoveover5kilometreswillcountasmigration,whichwouldnotbethecaseforcountriesdividedintolargerones.Hence,internationalcomparisonofinternalmigrationratesispotentiallymisleading.Eventhedistinctionbetweeninternationalandinternalmigrationmaybeproblematicifboundariesarecontestedorchanging.Thetemporaldimensiontomigrationpresentsfurtherdifficulties;whatconstitutespermanentorsemi-permanentandhowshouldgroupssuchasseasonalmigrantsbetreated?

Thereasonfordefiningmigrationasamoveoveraboundaryislargelypragmatic.Oftenonly


Page 21 of 37


movesofthiskindarerecorded;moreoverthisistheinformationrequiredbylocaladministrations.Forresearchpurposes,analysesofallmoves(preferablywithanindicationofdistancemoved)mayoftenbepreferred.Somecountrieshaveregistrationsystemsinwhichchangesofaddressarerecorded.Morecommonly,censusesareusedtofindoutaboutmigration.Questionsonusualaddress1or5yearsagoallowtheproportionofmoversinthepopulationtobemeasured(exceptforthoseagedlessthan1or5).Thesedataalsoallowinflowsandoutflowsbetweenpairsofareastobemeasured.Moves,asopposedtomovers,arenotdirectlymeasuredassomeonemovingseveraltimesinthereferenceperiodcannotbedistinguishedfromsomeonemovingonlyonce.Thoseleavinganaddressandlaterreturningtoitcannotbeidentifiedeither.Thismeansthatthelengthofthereferenceperiodusedisimportant;theproportionofmoversinthe5yearsprecedingacensuswillnotequalfivetimestheproportionmovingin1yearbeforethesamecensus.

Intheabsenceofdirectcensusdata,estimatesofmigrationcanbemadeindirectlyusingthe‘balancingequation’referredtointhefollowingsubsection.Differencesinthesizeofapopulationattwopointsintimenotaccountedforbynaturalchange(i.e.birthsminusdeaths)mustbeduetomigration(ordataerrors).Ifvitalregistrationdataareavailable,thenbothbirthsanddeathscanbetakenintoaccount.Iftheyarelacking,thenthesurvivalofgroupsenumeratedinthefirstofapairofcensusesmustbeestimatedfromalifetableandthenumberofexpectedsurvivorscomparedwiththenumberenumeratedinthesecondcensus(obviouslyageingmustbeallowedfor,sothenumberof20–29-year-oldsinthefirstcensuswillbecomparedwith30–39-year-olds10yearslater).Thesemethodsonlyallowestimationofnetmigration(balancebetweenin-migrationandout-migration).Theirmajorweaknessliesinthefactthattheresidualpopulationbalanceassumedtobeduetomigrationmayinfactreflectdifferencesinthequalityofthetwocensusesconsideredorerrorsintheestimatesofsurvivalused.

Surveydataarealsousedtomeasuremigrationandpotentiallyprovideilluminatinginformationonthereasonsfor,andconsequencesof,migration.However,asmigrationoverlongdistancesisarelativelyrareevent,evenlargegeneralpopulationsamplesmayyieldrelativelyfewmigrants.Asimilarproblembesetssamplesofinternationaltravellers,suchastheUKInternationalPassengerSurvey,designedtoestimateflowsofinternationalmigrantsthroughportorbordersurveys.Touristsandbusinesstravellerscomprisethevastbulkofpeopleenteringorleavingsosurveysareaninefficientwayofidentifyingimmigrantsandemigrants.Unfortunately,otherdataareoftenlackingaslegalandadministrativerecordsystemsarefrequentlyconcernedwithcitizenshipandrightofaboderatherthaninternationalmigrationperse(andvirtuallyneverwithemigration).Estimatesofthesizeofimmigrantpopulationsdependonwhetherthemeasureusedisbasedonplaceofbirthoronnationality—thesizeofthelatterisinfluencedbypoliciesonacquisitionofcitizenship.

Populationdynamics

Anypopulationcomprisesthosewhohavemadeanentryandnotyetexited.Whenwholepopulationsofdefinedgeographicareasareconsidered,theonlymeansofentryarebirthorimmigrationandtheonlymeansofexitdeathoremigration.

Themostbasicmethodofdemographicanalysisisthedecompositionofoverallpopulationchange(P −P )intoitscomponents(B,D,I,E):t 0

− = B−D+I −EPt P0


Page 22 of 37


whereP =populationatanendofperiod;P =populationatthebeginningofaperiod;andB,D,I,Erepresentrespectivelybirths,deaths,immigrations,andemigrationsduringthesameperiod(B–DisreferredtoasnaturalincreaseandI−Easnetmigration).Populationsubgroupsmaybesimilarlydefinedintermsofentriesandexits.Intheabsenceofmigration,entrytothepopulationaged75–84isthroughageing(passagefrom74to75)exitisthroughfurtherageing(84to85)ordeath.Thissimpleaccountingequationisanimportantone,bothmethodologicallyandasaformalreminderoftheneedtoconsiderpastaswellascurrentevents.

Ofthethreedemographicdeterminantsofpopulationsize,structure,andgrowth,fertilityhashistoricallybeenofmuchgreaterimportancethaneithermortalityormigration.Everybirthrepresentsnotjustanadditiontothecurrentgenerationofchildren,butalsopotentiallyanexponentiallyincreasingaugmentationinthesizeoffuturegenerations.Deathcarriesnosuchpromiseoffuturereturn.Birthsincreasethepopulationonlyatagezero,somakingityounger,whereasdeathsarespreadacrossthewholeagerangeandsohavemuchlessimpactonagestructure.Thethirddeterminant—migration—isgenerallynotofsignificantmagnitudetohaveamajorimpactonmostnationalpopulations,althoughthereareexceptionsespeciallywhennaturalincreaseisclosetozero.IncreasedlevelsofimmigrationtomanyEuropeancountriessincethe1990shavehadquiteaneffectonpopulationsizeandagestructure;thepopulationofSpainforexample,increasedby10.2percentbetween1999and2006andover90percentofthisincreasewasduetomigration(Sobotka2008).

Forsocialandbiologicalreasonsfertility,mortality,andmigrationhaveinteractiveeffects.Decreasesinmortalityamongthosewithreproductivepotential,forexample,influencenotjustthesizeoftheagegroupaffectedatthetime,butalsothesizeofsucceedinggenerations.Declinesinmalemortality,particularlyinpopulationswherelargeagedifferencesbetweenspousesarecommonandremarriageofwidowsisrare,willsimilarlytendtoincreasefertilitybyeffectivelyincreasingtheproportionofwomenofreproductiveagewhoarestillmarried.Conversely,reductionsinfertilityclearlyreducetheriskofmaternalmortalityandmayhavefurtherpositiveeffectsonthesurvivalofmothers,infantsorboth.Ageatmotherhoodalsoinfluencesratesofpopulationgrowth.Theaverageageofmothersatthebirthoftheirdaughtersistermedthemeanlengthofagenerationandisgenerallyaround29years.Ashorterintervalwillmeanmorerapidgenerationalsuccession(andfasterpopulationgrowth).

Migrationaffectsotherdemographicparametersbecausemigrantsdifferfromthegeneralpopulation.Internationalmigrantsaregenerallyyoungandingoodhealthandoftenmovefromrelativelyhigh-tolow-fertilitypopulations.Consequently,immigrantsmayserveto(temporarily)‘rejuvenate’thehostpopulationand,atleastinitially,havehigherfertilityandlowermortality.InEnglandandWales,forexample,24percentofbirthsin2011weretomothersthemselvesbornoutsidetheUnitedKingdom.Despitethedisadvantagestheyoftenface,mortalityofimmigrantgroupsisoftenlowerthanthatofhostpopulationsbecauseofthedifferentialselectionofimmigrants.Thedegreeofselectiontendstovaryaccordingtodifficultiesanddistancetobeovercomeinmakinganinternationalmove.Forallthesereasons,thedemographiccharacteristicsofpopulationsubgroupslargelycomprisingimmigrantsandtheirimmediatedescendantsmayvarysubstantiallyfromthoseofthepopulationasawhole.

Populationprojections

− = B−D+I −EPt P0

t 0


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Populationprojectionsrepresentoneofthemostwidelyusedoutputsofdemographicanalysis.Strictlyspeaking,aprojectionsimplyrepresentstheoutcomeofapplyingvariousassumptionsaboutfuturefertility,mortality,andmigrationandsodiffersfromaforecast,whichimpliesprediction.However,projectionsareoftentreatedasforecastsandthedegreeofuncertaintyinherentinthemisnotalwayssufficientlyrecognized,althoughtheproductionofprobabilisticforecasts,asinthelatestUNprojections,makesthismoreexplicit.Themostcommonmethodofprojectionisthecomponentmethod,basedonthebalancingequation(P =P +B−D+I−E).Assumptionsaremadeaboutthethreecomponentsofchange—births,deaths,andmigration—andappliedtoageandsexgroupswithintheinitialpopulationtogiveaprojectionoffuturesizeandstructure.Toalargeextentassumptionsarebasedonrecenttrendstogetherwithotherinformation,forexample,surveydataonfertilityintentionsor(sometimes)modelsofchangeinparticularcausesofdeath.Forecastingfertilityhasgenerallybeenregardedasthemostproblematicareaofprojectionbutrecentlygreaterattentionhasbeenpaidtotheerrorsthathavebeenmadeinforecastingmortalityindevelopedcountries.Thishaslittleeffectonagegroupsinwhichsurvivalishigh,butcanhavequitesubstantialimpactsonforecastsofthenumberofolderpeople.Migrationmaybeanimportantelementandmaybeunderestimated,ifprojectionsdonottakeintoaccountfeedbackloopswherebymigrantpopulationstendtogeneratefurthermigration(BongaartsandBulatao2000).Internationalmigrationisalsodifficulttoforecastasitisaffectedbyeventsoutsidethecountry,isoftenasensitivepoliticalissueandmaybevolatile.Partlyforthesereasons,immigrationlevelshavebeenconsistentlyunder-projectedinforecastsinmanyEuropeancountries(Aldersetal.2007).

Populationgrowth

Changesinthesizeofapopulationproducedbythesurplus(ordeficit)ofbirthsoverdeathsaretermednaturalincrease(ordecrease).Acommonindicatorofgrowthisthecruderateofnaturalincrease—thedifferencebetweenthecrudebirthrate(annualbirthsper1000population)andthecrudedeathrate(annualdeathsper1000population).Ifnetmigrationiszero,thiswillbethesameasthegrowthrateofthepopulation—theoverallannualchangeinthepopulationdividedbythepopulationsize—(conventionallyexpressedasapercentage).InseveralEuropeancountriesdeathsoutnumberedbirthsintheperiod2005–2010,withthelargestdeficitsinUkraine,Bulgaria,Latvia,Belarus,Hungary,Lithuania,andtheRussianFederation.Insomeothersbirthsstilloutnumberdeathseventhoughfertilityrateshavebeenbelowthelevelrequiredforlong-termreplacementfor40yearsorso.Thisapparentparadoxlargelyreflectsthefactthatthenumberofbirthsisafunctionofthenumberofpotentialmothers,towhichimmigrationmayalsocontribute,aswellasoftheirfertilitypatterns.Iftheformerisincreasingsotoomaythenumbersofbirths,evenifwomenhavefewerchildreneach.

Theyoungagestructuresofmanypopulationsinthedevelopingworldmeanthatthesepopulationshaveahugebuilt-inpotentialforgrowth.Populationmomentumisthemeasurewhichgivestheratiooftheultimatesizeagivenpopulationwouldachievetocurrentpopulationsizeiffertilityweretoimmediatelyfalltoreplacementlevel.EvenallowingfortheeffectofHIV/AIDS-relatedmortality,thepopulationofsub-SaharanAfricaisexpectedtoincreasefrom0.86billionto1.96billionbetween2010and2050(UN2011),aconsequenceofbothpopulationmomentumandhighlevelsoffertility.Insomelow-fertilitycountriestherearenowconcernsabout‘negativemomentum’—theprospectofdeclineinpopulationeveniffertilityratesincreasesomewhatbecauseofsuccessivelysmallercohortsofwomenin

t 0


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childbearingagegroups.

Intrinsicrateofnaturalincrease:stablepopulationtheory

Earlyinthetwentiethcentury,Lotka(1907)demonstratedmathematicallythatapopulationclosedtomigrationandsubjecttounchangingage-specificfertilityandmortalityratesforalongperiodwouldeventuallyhaveafixedagestructure(inwhichtheproportionineachagegroupremainedunchanged)andwouldgrowataconstantrate.Thistypeofpopulationiscalledastablepopulation.Thefixedagestructureofastablepopulationisindependentoftheinitialagestructure—twoverydifferentpopulationssubjecttothesameunchangingratesforalongperiodwouldeventuallyassumethesamestructure.Aparticularcaseofastablepopulationisastationarypopulation—oneinwhichbirthanddeathratesareconstantandinbalanceandsopopulationgrowthiszero.TheL columnofthelifetableisanexampleofastationarypopulation.Thenumberofbirthsisfixed(theradix)andtheagedistributionisalsofixed.Innon-stationarystablepopulations,theagestructureisalsofixedbutthesizeofeveryagegroupisgrowingatthesameconstantrateastheoverallpopulationandthenumberofbirths.Thisiscalledtheintrinsicrateofnaturalincreaseandisafunctionofthenetreproductionrateandthemeanlengthofageneration(approximatedbythemeanageofchildbearing).Non-stationarystablepopulationscanbecalculatedbyadjustingtheL valuesofaparticularlifetabletoallowfortheintrinsicrateofgrowth.Theseareoftenpublishedinconjunctionwithmodellifetablestoshowtheeffectsofparticular(unchanging)fertilityandmortalityregimes.

Althoughstableandstationarypopulationsaretheoreticalconstructs,realpopulationsatvarioustimeshavemetthemodelrequirementscloselyenoughtoallowstablepopulationtheorytobeusedtodevelopmethodsforindirectlyestimatingfertilityandmortalityinpopulationslackingadequatedirectlyderiveddata.Stablepopulationmodelsarealsowidelyusedforinsurance,pension,andpersonnelplanning.OneoftheimportantresultsoftheworkofLotkaandhissuccessorswastoshowtheoreticallytheimportantinfluenceoffertilityonagestructure.

Agestructure

Populationpyramidsgraphicallyillustratethecurrentstructureofpopulationsandinsodoing,alsoprovideinsightsintoboththefutureandthepastofthepopulation.Highfertilitypopulationshaveapyramidshapewitheachsuccessivecohortbeinglargerthanitspredecessor.ThepopulationpyramidforBangladesh(Fig.6.3.3A)showsatypicalpatternforapopulationwithahistoryofhighfertilitybutarecentdownturn.Eachsuccessivecohortislargerthantheprecedingone,withtheexceptionoftheyoungest.‘Old’populations,suchasthatofEnglandandWales(Fig.6.3.3B),aremorerectangularwithagradualtaperingatthetop.Bulgesinpopulationpyramidsduetohighnumbersofbirthshave‘echo’effectswhenmembersoflargecohortsthemselveshavechildren.Thusthebabyboomexperiencedinmanypopulationsinthepost-SecondWorldWarperiod(precisetimingvariedbetweencountries)hadanechoeffectinthe1980s.

x

x


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Fig.6.3.3Distributionofthepopulationof(A)Bangladeshand(B)theUKbyageandsex,2010.

Source:datafromUnitedNations,WorldPopulationProspects:The2010Revision,UnitedNations,NewYork,USA,Copyright©2012,availablefromhttp://esa.un.org/wpp/documentation/pdf/WPP2010_Volume-I_Comprehensive-Tables.pdf

Historically,andapparentlyparadoxically,improvementsinmortalityinthoseEuropeanpopulationswhichnowhavehighproportionsofoldpeopleinfactservedtooffsetthetrendtowardspopulationageing,astheychieflybenefitedtheyoung—andledtoincreasesintheproportionssurvivingtohavechildrenthemselves.However,althoughfertilityhasthegreatestpotentialimpactonagestructureandpopulationgrowth,insomecircumstancesmortality(ormigration)maybecomeamoreimportantinfluence.Manypopulationsinrichercountriesnowhavefertilityatorbelowreplacementlevel,lifeexpectanciesatbirthcloseto80andnearuniversalsurvivaltotheendofthe(female)reproductivespan.Intheseconditions,furtherimprovementsinmortalityhavethegreatestimpactatoldagesandfurtherpopulationageingoccursfromtheapex,ratherthan,orinadditionto,thebaseofthepopulationpyramid.Mortalitychangesarenowthemainmotorofthefurtherageingofanumberofpopulationswithalreadyoldagestructures(PrestonandStokes2012).Populationagestructuresandassociatedratesofgrowthordecline,changesinagestructuressuchaspopulationageing,andthespeedandstageofagestructuralchangeallhaveimportanteconomicandhealthimplicationswhichhaveattractedconsiderabledebateandcontroversy.

Manyeconomistshavepointedoutthatpopulationgrowthhasoftenprovidedaspurtohumaningenuityandeconomicgrowth.Lesspositively,thecountrieswhichnowhavetheyoungestagestructuresandmostrapidratesofpopulationgrowtharealreadysufferingfromlanddegradationandinmanycases,constrainedagriculturalpotential(Alexandratos2005).Largeandgrowingchildpopulationsalsohampereffortsatimprovinghumancapitalthrougheducationorimprovedhealth(Casterline2010).

Reducedfertilityinitiallyproducesa‘demographicdividend’or‘window’whentheratioofchildrentoadultsfallsandthoseinprimeproductiveages,thesurvivorsoflargerbirthcohorts,accountforahigherproportionofthepopulation.Ithasbeenarguedthatthisdividendoflowerchilddependencyandhigherrepresentationofadultsintheprimeworkingagegroupsplayedanimportantpartintherapideconomicdevelopmentofthe‘EastAsianTigers’,likeSouthKoreaandalsoChina(Bloometal.2000).Thenextphase,involvinghighandincreasingrepresentationofolderpeoplemay,ithasbeensuggested,alsobringsomeeconomicbenefitintheformofincreasedsavings(bythelargenumberofolderpeople)andsogreatercapital


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availableforinvestment(MasonandLee2006).However,populationageingismoreoftenperceivedasachallengewithpotentiallynegativeimplicationsforboththeeconomyandforpopulationhealth(OECD1999).

Themajorconcernsarisingfromincreasesintheproportionsofolderpeoplerelatetoeffectsonproductivityandneedforsupportsystemsofvariouskinds,includingpensions,healthcareandlong-termcare.InOECDcountries,healthcareexpenditureistypicallythreetofivetimesashighforthoseaged65andoverasforthoseagedunder65.HoweverthereisconsiderableinternationalvariationintheproportionofGDPdevotedtohealthcarespendingforolderpeoplewhichbearslittleobviousrelationshiptotheproportionofolderpeopleinthepopulationconcerned.

Inpopulationswhichhavemorerecentlymovedtolowfertilityandlowmortalityregimes,thepaceofdemographicchangehasbeenmuchfasterthanoccurredhistoricallyinEurope.TheproportionoftheJapanesepopulationaged65andoverdoubled,from7percenttoover14percent,between1970and1996.InFranceasimilarincreasetook130yearstoachieveandinSweden85years(KinsellaandPhillips2005).Morerecentlyageingpopulationshavethushadamuchshorterperiodinwhichtoadapttonewpublichealthpriorities.Theoriginsoftheseagestructurechangeslieinthedemographictransition.

Thedemographictransition

Towardstheendofthenineteenthcentury(earlierinFrance)birthanddeathratesstartedfallinginanumberofEuropeancountries.Between1871–1875and1911–1915theTFRforEnglandandWales,forexample,droppedfrom4.8to2.8;bytheearly1930sitwasbelowreplacementlevel,adevelopmentwhichwasviewedwithalarmandledtothefirstRoyalCommissiononPopulation.Althoughmodernmethodsofcontraceptionwerelacking,itwasclearthatthishugedropinfertilitywastheresultofthedeliberatelimitationoffamilysize.Halfofcouplesmarriedinthe1870shadsixormorechildrencomparedwith12percentofcouplesmarriedin1911–1915(ColemanandSalt1992).Expectationoflifeatbirth,meanwhile,increasedbysome15yearsbetweentheendofthenineteenthcenturyandtheearly1930s.

Researchersattemptingtorelatesuchshiftsindemographicregimestoeconomicandsocialchanges,originatedthetheoryofthedemographictransition.The‘classical’viewpropoundedbyNotestein(1945)andotherswasthatin‘traditional’societiesfertilityandmortalityarebothhighandroughlyinbalance.Changeisdrivenbyeconomicadvancewhichresultsinlowermortality.Fertilityinitiallyremainshigh,resultinginarapidperiodofpopulationgrowth.Afterthislag,however,fertilityalsofallsinresponsetofallingmortalityandtheerosionof‘traditional’pro-natalistvalues.

Thisclassicalviewhassincebeenconsiderablymodified(Lee2003).CoaleandhiscollaboratorsinanambitiousprojecttotrackthetransitioninhistoricalEuropesuggestedthatnoeconomic‘threshold’forfertilitydeclinecouldbeidentifiedandthatthepatternofdeclineseemedtofollowregionalgroupings,suggestingaculturalratherthanasocioeconomicdimension(CoaleandWatkins1986).Fallsininfantmortality,assumedtobeaparticularlyimportantstimulustofertilitydecline,sometimesfollowedratherthanprecededchangesinfertility.Forexample,Woodsetal.(1989)arguedthatdeclinesinfertilityledtoreductionsininfantmortality,ratherthanviceversainEnglandandWales.Inshort,theroleofmortality


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declineasatriggerandthedominanceofeconomicchangehavebothbeenquestioned.Caldwell(1982)additionallyarguedthatinnon-Europeancountries,itwasnotsomuchsocioeconomicmodernizationbut‘Westernization’involvingincreasedemphasisonthenuclearfamilyandachangeinintergenerationalwealthflows(resultinginthecostsofchildrenoutweighingtheirpotentialbenefits)thatwastheimportanttriggeroffertilitytransition.

ResearchonthehistoricaldemographictransitioninEuropemayseemoflimitedrelevancetocontemporaryproblems.However,thisresearchwasfuelledbypost-warfearsaboutpopulationgrowth.By1950,significantmortalitydeclineshadbeenachievedorinitiatedthroughouttheworld.InChina,forexample,expectationoflifeatbirthincreasedfrom43in1960toover75by2010.Eveninsub-SaharanAfrica,againofnearly10years—from43to52—wasachievedbetween1950and1990,sadlysincereversedalthoughnowstartingtoincreaseagain(WorldBank1993;UN2011).Inthiscontextitseemedimperativetodiscoverthecausesoffertilitydeclineandusethisknowledgetoacceleratefertility‘adjustment’tofallingmortality.Was‘developmentthebestcontraceptive’asconcludedatthestormy1974WorldPopulationConference;couldchangebeachievedthroughintensivefamilyplanningprogrammes,astheexperienceinTaiwanandSouthKoreaseemedtosuggest;orwassomecombinationoftheseandotherfactorsthekeytofertilitytransition?Studiesofsocietiesinwhichthefertilitytransitionhadoccurredseemedtoofferthebestprospectofananswertothesequestions.Whilesimpleanswerstocomplexquestionsarerarelyforthcoming,Coale(1973)identifiedthreefactorswhichheconsideredprerequisitesforfertilitydeclineincontemporarypopulations.Thesewere:thatpotentialparentsmustthinkitacceptabletobalancetheadvantagesanddisadvantagesofanotherchild,thatsomeadvantagemustbegainedfromreducedfertility,andthateffectivetechniquesoffertilitycontrolmustbeavailable.

Trendsinfertilityinthesecondhalfofthelastcenturyandearlypartofthiscenturyhaveshownconsiderabledivergenceandshedsomelightonthesedebates.TFRsarehighestinsub-SaharanAfrica,withUganda,Somalia,Mali,Timor-Leste,andNigerhavingTFRsabove6.3in2005–2010.Inallotherworldregionstherewasclearevidenceofonsetofatransitiontolowerfertilitybythe1970sor1980s;Japanwasthefirstnon-WesterncountrytoexperienceafertilitytransitionstartingaftertheSecondWorldWar.Globally,theestimatedTFRin2005–2010was2.52,with48percentoftheworldpopulationlivingincountrieswithbelow-replacementfertilitylevels(UN2011).Substantialfertilitydeclineshaveoccurredinanumberofcountrieswhichatthattimehadonlyalimitedamountofdevelopment,suchasSriLanka,Thailand,China,andmorerecentlyBangladesh.OneofthelargestandfastestfertilitydeclinestookplaceintheIslamicRepublicofIranwherefertilityfellfrom7.0in1980to1.9in2006(Abbasi-Shavazietal.2009)defyingassumptionsthatsociallyandreligiouslyconservativeMuslimsocietieswithlowratesoffemaleemploymentwouldberesistanttofertilitychange.

Recentinterpretationsoffertilitychangehaverevertedtoconsideringdevelopment—initsbroadestsenseratherthanrestrictedtoconsiderationofaverageincomes—astrongerinfluenceincontemporarypopulationsthanideationalchanges,althoughtherelevanceandroleofculturalandpolicyrelatedfactorsisrecognized(Bryant2007).Commonfactorsidentifiedinpoorruralpopulationswherefertilityhasfallensignificantlyarewell-establishededucationsystems,improvementsinhealthcareandinchildsurvival,someformofextra-familialwelfare,well-organizedlocalgovernment,andanorganizedfamilyplanningprogramme.Potentialbenefitsofinvestingmoreresourcesinfewerchildren,asaconsequenceofincreasingopportunitiesinurbanorindustriallivelihoods,alsoseemtobeimportant


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(McNicoll2006;Bryant2007).Theeducationofwomenhasbeenidentifiedasaparticularlysignificantinfluenceonbothfallingfertilityandimprovedinfantsurvival(Cleland1990;Hobcraft1993)andfemaleeducationandempowermentwererecognizedaskeypolicyobjectivesatthe1994InternationalConferenceonPopulationandDevelopment(UNFPA1995).

Asnotedearlier,fertilityratesremainhighinmuchofsub-SaharanAfrica.ContinuingexpressedpreferencesforlargefamiliesandotherfamilyandsocialcharacteristicsofAfricanpopulationshaveledsometoconcludethatthemodelofchangeseeninAsiaandLatinAmericamaynotbeapplicabletoAfrica,oratleastnottoallregionsofAfrica(Caldwelletal.1992).Thereisneverthelessevidenceofunmetdemandforfamilyplanningandastrongcasecanbemade,onthegroundsofimprovingmaternalandchildhealth,forrenewedinvestmentinfamilyprogrammeswhichinsomeplacesfalteredasthepolicyfocusandfundingshiftedtotheHIV/AIDscrisis(Clelandetal.2006).

Recenttrendshavealsomadeitclearthattheendpointoffertilitytransitionisnotnecessarilyafertilitylevelaroundthe‘replacementrate’.Insomecountries,suchasGuatemala,Peru,Egypt,TurkeyandGhana,fertilitydeclines‘stalled’(sometimestemporarily)atalevelhigherthantwochildrenperwoman(Bongaarts2005).Inotherstheyhavecontinueddownwardspiralling,givingrisetoanewsetofconcernsabout‘lowestlow’fertility.

Lowestlowfertilityandtheseconddemographictransition

Incontrasttothescenarioofhighfertilityandrapidpopulationgrowthinsomeofthepoorestcountries,agrowingnumberofhigh-incomecountriesnowhaveconcernsabouttheimplicationsoflowfertility.Manyofthesecountriesexperiencedapost-SecondWorldWar‘babyboom’duringthe1950sandearly1960sfollowedbya1970s‘babybust’whenfertilitydeclinedtoverylowlevels.InScandinavia,France,theUnitedKingdom,theUnitedStates,andotherEnglish-speakingcountriesfertilityrateshavesincefluctuatedatlevelsbetween1.6andreplacementlevelwithsomethingofanincreaseinthefirstdecadeofthiscentury—apatternalsoseeninmanyotherindustrializedcountries—however,thismayturnouttobeatemporaryphenomenonparticularlygivencurrenteconomicconditions.Thesepopulationshavealsoexperiencedarangeoffamily-relatedbehaviouralchanges,includedmarkedincreasesincohabitation,non-maritalchildbearing,divorce,postponedchildbearing,andincreasedlevelsofchildlessness,describedbysomeasa‘SecondDemographicTransition’(LesthaegheandNeidert2006).Suchbehaviours,whichhavebecomemoreusualamongNorthernEuropeancohortsbornfromaroundthe1950sonwards,aremuchlessprominentinSouthernandEasternEuropeandtherichercountriesofSouthandEastAsia.However,itismainlyintheselattercountriesthat‘lowestlow’fertility—ratesbelow1.3—hasbeenprevalentwith21countriesfromtheseregionshavingTFRsbelow1.3in2003(Goldsteinetal.2009).Therecentincreaseinfertilityindevelopedsocietiesmeantthatonlythreeofthesecountries,SouthKorea,Slovakia,andSingapore,hadaveragevaluesbelow1.3intheperiod2005–2010(UN2011).However,theTFRremainedbelow1.5inalargenumberofothercountriesincludingPoland,Japan,Germany,Italy,Ukraine,Spain,andtheRussianFederationin2005–2010.Animportantdeterminantofverylowfertilityinmanyofthesesocietieshasbeenaprecipitousfallinmarriagerates(BillariandKohler2004).Japan,forexample,hasbeentransformedfromasocietywithnearuniversalmarriageintheearlyandmidtwentiethcenturytooneinwhichafifthofthepopulationwillremainnever-marriedatage45(Retherfordetal.2001).Inthiscase


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theerosionofarrangedmarriagesaftertheSecondWorldWarhasplayedapart;changinggenderrolesmayalsobeimportant.Insomecountrieswithverylowfertility,explicitpro-natalistpolicesareunderdiscussionorhavebeenintroduced,howevertheseremaincontroversialandofuncleareffectiveness.

Theproximatedeterminantsoffertility

Oneofthecontributionsofresearchintothefertilitytransitionhasbeenimprovedunderstandingofbiosocialinfluencesonreproduction.Ahugerangeofsocial,economic,cultural,andpsychologicalfactorsmayinfluencedecisionsaboutfamilybuildingstrategiesandfamilysize.However,thesecanonlyhaveeffectiftheyaretranslatedintopatternsofbehaviourorphysiologicalcharacteristicsthatinfluencetherisksofconceptionordelivery.

Conversely,otherpatternsofbehaviourwithpotentiallyimportantinfluencesonfertilitymaybeadoptedwithlittleornothoughttotheseconsequences.DavisandBlake(1956)distinguishedaseriesof‘intermediatefertilityvariables’:factorsinfluencingexposuretoriskofpregnancy(marriageandcoitalfrequency),riskofpregnancy(suchascontraception),andpregnancyoutcome(spontaneousandinducedabortion).ThemostinfluentialrefinementofthisworkistheBongaartsdecompositionmodel(Bongaarts1978),whichidentifiedfourelementschieflyresponsibleforobservedfertilityvariations:

◆Theproportionofwomenmarried(exposedtorisk).◆Contraceptiveuse.◆Inducedabortion.◆Post-partumnon-susceptibilitytoconception(largelydeterminedbybreastfeedingpractice).

TheTFRisdependentontheinteractiveeffectofthesevariablesandhypotheticalmaximumfertility.Inmodern‘post-transition’populations,fertilitydecisionsarenormallycouple-(orwoman-)basedandareimplementedthroughcontraceptionandabortion.Innon-contraceptingpopulations,biosocialfactors,notablymarriagepatterns,breastfeedingpractices,sexualfrequencyand,insomepopulations,theprevalenceofinfertility,areofmajorimportance.

Thesocialreproductivespan,fromentrytoendofmarriageoranysexualunion,nearlyalwaysstartslater,oftenmuchlater,thanmenarche.Fecundity—thepotentialforbearingchildren—decreasesafterthethirddecade,moresharplyaftertheageof35andinmostnon-contraceptingpopulationstheaverageageatlastbirthisaround40.Socialfactors,aswellasbiologicalones,areimportantinfluences.Sexualactivitymayceasebeforemenopausebecauseofwidowhoodorseparation.InsomeAfricanpopulations,childbearingafterbecomingagrandmotherisdisapprovedof.

Forthosewithintheeffectivereproductivespan—biologicallycapableofchildbearingandinasexualunion—overallfertilityislargelyafunctionoflengthofintervalsbetweenbirths,itselflargelydeterminedbybreastfeedingpatterns.Amongnon-breastfeedingwomen,averagedurationofpost-partumamenorrheaisonly1.5–2months,comparedwith18monthsormorewithprotractedbreastfeeding,particularlyinsomepopulationswheresexualactivityisproscribedforbreastfeedingmothers.


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Longerbirthintervalsandincreasedbreastfeedingalsohavepositiveeffectsoninfantandchildhealth.Overalldeathsbeforetheageof5mightbereducedbyasmuchas30percentinsomecountriesifcloselyspacedbirthsweredelayed(WorldBank1993;Clelandetal.2006).

Theepidemiologicaltransition

Transitionsfromrelativelyhigh-tolow-mortalityregimeshaveinallpopulationsbeenassociatedwithtransformationsintheage,cause,andsexstructureofdeath.Omran(1971)coinedthephrase‘epidemiologicaltransition’todescribethisprocess.Changesintheresponseofsocietiestohealthanddiseaseprocessesalsoneedconsideration.Theterm‘healthtransition’hasbeenproposedasonewhichembracesboththesephenomena.

Substantialfallsindeathratesfrominfectiousandparasiticdiseasesandmaternalmortalityarehallmarksoftheepidemiologicaltransition.InEnglandandWales,overhalfthegaininlifeexpectancyatbirthbetween1871and1911wasduetoreducedinfectiousdiseasemortality.Some20percentofthetotalgainwasduetoreduceddeathratesfromtuberculosis(Caselli1991).Declinesinthesecausesofdeathweregreateramongtheyoung,hencedeathsatolderagesaccountedforalargershareofalldeaths;theepidemiologicaltransitionhasalsobeenconsistentlyassociatedwithlargerfallsinmortalityamongwomenthanmen.Changesintheintra-householdallocationofresources,declinesincausesofdeathprimarilyaffectingwomen(suchasmaternalmortalityandrespiratorytuberculosis),genderdifferencesinhealth-relatedbehaviourandinexposuretooccupationalhazards,andthepossiblygreatersusceptibilityofmentostressesassociatedwithsocioeconomicchanges,mayallbeunderlyingfactors.

Therelativecontributionofvariouseighteenth-andnineteenth-centurydevelopmentsinpromotingthehistoricalepidemiologicaltransitionintheWestremainsamatterofdebate.Improvednutrition,betterhousingandlivingconditions,publicsanitationschemes,andspecificpublichealthinitiatives,suchassmallpoxinoculation,allhavetheiradherents.Intheearlytwentiethcentury,improvedpersonalhygienepracticesandbetterinfantcarewerealsoimportant.Acommonthreadlinkingmostofthesefactorsistheirrelationshiptooverallsocialandeconomicdevelopmentandimprovementsinstandardsofliving.Duringthetwentiethcentury,however,developmentsinmedicaltechnologyandvectorcontrolofferedthepotentialfor‘exogenous’mortalitydeclinelessdependentonaparticularcountry’slevelofincomeanddevelopment.Oneconsequencewasthattherelationshipbetweenpercapitaincomeandlifeexpectancyhasshiftedtotheright(Preston1975,2007).In1901,forexample,lifeexpectancyintheUnitedStateswas49andincomepercapitawasaboutUS$7300(2005purchasingpowerparity).In2009,incomepercapitainChinawasalmostidentical($7400)butlifeexpectancywas73years(http://www.gapminder.org/).

Manypoorcountrieshavebeenabletoachieveremarkablefallsinmortality,especiallychildmortality,throughbehaviouralchange,improvededucationofwomen,andintroductionofrelativelycheaptreatmentsandinterventions,suchasvaccinationandantibiotics(Cutleretal.2006).Between1975–1980and2005–2010lifeexpectancyatbirthincreasedfrom53to68inBangladeshandfrom56to68inIndonesia(UN2011)andtherearenowanumberofpoorormiddle-incomecountrieswithlifeexpectanciesatbirthashighasintheUnitedStates.

Theprocessoftheepidemiologicaltransition(oratleasttheinitialphases)isnowcompleteor


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underwayinmuchoftheworldandnon-communicablecausesofdeathpredominateinallregionsexceptsub-SaharanAfrica(seeTable6.3.2).However,somerecentchangeshavebeenlessbenignandnewchallengesorreversalshaveemerged,notablytheHIV/AIDSepidemicandthehealthconsequencesofthecollapseoftheformerSovietUnion(Olshanskyetal.1997;Murphy2011).Partlybecauseofthesechallenges,therearesignsthatafteraperiodinwhichrisksofmortalityindifferentpartsoftheworldshowedatendencytoconverge(i.e.poorercountriescaughtupwithricherones),morerecentlytherehasbeenatrendtowardsdivergence.Anotherfactorinthismaybethatrecentsuccessesinrichercountriesin,forexample,loweringmortalityfromheartdisease,havepartlybeenachievedthroughtreatmentswhichareharderto‘transfer’topoorcountriesbecauseofinfrastructureandcostlimitations(VallinandMesle2004;Fordetal.2007).

Recentdemographictrendsandpublichealth

Populationsize,growth,andagestructurearealloutcomesofvariationsindemographicbehavioursandallhaveimplicationsforpopulationhealthandwell-being.Populationageingwillalmostcertainlybethepredominantdemographicissueofthetwenty-firstcenturyinnearlyallricherandagrowingnumberofpoorercountries.Thestrongassociationbetweenageandrisksofhealthimpairmentanddisabilityimplygrowingneedsforsupportservices,eveniflevelsofdisabilityfall.Inthosecountrieswhicharegrowingoldbeforetheygrowrich,changesinfamilysupportsystemsforolderpeoplemayposeadditionalchallenges.Arangeofstrategiesforrespondingtothesechallengeshasbeenproposed,includingencouraginglongerworkinglivesthroughreviewofretirementandpensionspolicies,betterorganizationofacuteandlong-termcareservices,andinitiativestopromotehealthyageing(Recheletal.2013).

Changesinmarriageandfamilypatternsalsohaveotherpublichealthimplications.InNorthAmericaandNorthWestEurope(andalsoLatinAmericaandtheCaribbean)highratesofdivorceandnon-maritalchildbearingmeanthatincreasingproportionsofchildrenarespendingatleastpartoftheirchildhoodinlone-parentfamilies.Althoughcausalpathwaysaredifficulttoelucidatebecauseofvariousselectioneffects,thereisevidenceindicatingpoorerhealthamonglonemothersandtheirchildren,andamongunmarried(especiallydivorced)peoplemoregenerally,sothesetrendshavesomenegativeimplications.

Continuingimprovementinchildandadultmortalityisprojectedforthepoorerworld,basedonoptimisticassumptionsaboutthecourseoftheHIV/AIDSepidemic.Inthepoorestcountriestheinteractionofrapidpopulationgrowth,environmentaldegradationandconflictposecontinuinghealthproblemsandthe‘unfinishedagenda’intermsofhealthincludesprovidingaccesstocontraceptionforwomenwhowishtospaceorlimittheirchildren(Clelandetal.2006).Inothermiddle-andlow-incomecountries,patternsoftobaccousearelikelytohaveasubstantialeffectonhealthtrendsincomingdecades(West2006).

Issuessuchasinternationalmigration,economicandcultural‘globalization’,andclimatechangeallhavesubstantialhealthimplicationsfortherestofthetwenty-firstcentury;allinteractwithdemographicpatternsandprocesses.Measuringthesetrendsandassessingtheireffectonhealthanddemandforhealthcarerequiresanunderstandingofpopulationdynamicsandpopulation-basedmeasures,andsuitabledemographicdata.Demographyisthusanessentialcomponentofpublichealth.


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