Pali Lehohla, Statistician-General#StatsSA

Vulnerable Groups Series ii: The Social Profile of Older Persons,

2011-2015

AboutthisReport

3

2

1 Profiles the dynamics of living circumstances of elderly persons in South Africa using secondary data from Stats SA.

Provides insight into socio-economic and demographic trends of older persons over a period of 5 years.

Informs policies for persons aged 60 years and older

DataSources

GHS2011&2015

CommunitySurvey

2007&2016

Census1996,2001,&2011

QLFSQ3:2011&Q3:2016

Mid- yearPopulationEstimates2016

MortalityandCausesofDeath

Victimsofcrime2014/15

IncomeandExpenditure2010/2011

Demographic Profiles of the Elderly

AgedPopulationGrowthOverTime

7,3% 7,8% 8,0% 8,1%

2001 2007 2011 2016Source: Census 2001, CS 2007, Census 2011, CS 2016

Nationally,theelderly populationincreasedovertime.

Withover4,5million in2016,theelderlyaccountedforjustover8%oftheSouthAfricanpopulation.

ProvincialGrowthPatternsAmongstOlderPersons

14,1%

-11,7%

15,9%

7,4%3,4%

2,9%

38,6%

4,0%

-6,1%

9,0%

-20,0

-10,0

0,0

10,0

20,0

30,0

40,0

50,0

WC EC NC FS KZN NW GP MP LP RSA

Source:Census2011,CS2016

Gautengprovincehasthehighestproportionofelderly

EasternCapeandLimpopo observedlargerpercentagedecreases

Theelderlypopulation

increasedby9,0%between2011and2016

40,1%

45,5%

43,7%

42,6%

41,9%

40,2%

39,1%

36,7%

34,4%

32,8%

59,9%

54,5%

56,3%

57,4%

58,1%

59,8%

60,9%

63,3%

65,6%

67,2%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

RSA

GP

WC

NW

NC

MP

FS

KZN

EC

LP

Male Female

Percentagedistributionofolderpersonsbyprovinceandgender,2016

Thefemalepopulationdecreasedslightlyfrom60,3%to59,9%between2011and2016.Theelderlyinallprovinceswerestillproportionatelymorelikelytobefemalethanmale.

Source: CS 2016

Percentagedistributionofolderpersonsbyprovinceandpopulationgroup,2016

ThepredominanceofblackAfricansamongsttheelderly,wasmostlyobservedinprovincessuchasLimpopo(93,9%),Mpumalanga(87,4%)andNorthWest(84,1%).

Source:CS2016

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

WesternCape

NorthernCape

Gauteng

KwaZulu-Natal

FreeState

EasternCape

NorthWest

Mpumalanga

Limpopo

Blackafrican Coloured Indian/asian White

1000000 500000 0 500000 1000000

60-64

65-69

70-74

75-79

80-84

85+

Male Female

Source: Census 2001

Male Female

AgeStructure

Bothincreaseandfeminisationamongtheelderly

CS2016

Census2011

FemaleMale

Theagegroup60–64containedthelargestproportionofolderpersons,

AgeingIndex

Theageingindexiscalculatedasthenumberofpersons60yearsoldoroverperhundredpersonsunderage15

AgeingIndexbyPopulationGroup

84

33

21 19 23

130

57

32

2027

0

20

40

60

80

100

120

140

White IndianorAsian Coloured BlackAfrican RSA

20012016

Between2001and2016,theageingindexamongstthewhitepopulationgroupincreased from84to130

BlackAfricanshadthelowestageingindexrelativetoallotherpopulationgroups(lowerproportionsofolderpersonstochildren)andhighlightstheyouthfulnessofblackAfricanpopulationinthecountry

Source: Census 2011, CS 2016

SexRatiosbyAgeGroup

0

10

20

30

40

50

60

70

80

90

100

60 - 64 65 - 69 70 - 74 75 - 79 80 - 84 85+ 60+

SEXRA

TIOS

2011 2016Source: Census 2011, CS 2016

Themajority ofolderpersonsarewomen,andfemalepredominancetendstoincreasewithage.

Sexratioswerealmostbalanced fortheagegroup60– 64with(79menper100women)in2011and(81menper100women)in2016.

SexRatio:thenumberofmalesper100females.

Total

CharacteristicsOf Households

Male 45,7% 43,8%

Female 54,3% 56,2%

0

10

20

30

40

50

60

2011 2015

ProportionsofElderlyHeadedHouseholds

Between2011and2015therewasanincreaseintheproportionofhouseholdsheadedbyolderfemales(from54,3%to56,2%)andadeclineinproportionofmaleheadedhouseholds.

ProportionsofElderlyHeadedHouseholds

56,6%

77,4%

43,4%

22,6%

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

Male Female

2011Urban 2011Rural

60,0%

74,7%

40,0%

25,3%

Male Female

2015Urban 2015Rural

Mostelderlywhoarelivingalone,liveinurbanareasregardlessofgender.

Between2011and2015,therewasaslightincreaseinthepercentageofmenlivingaloneinurbanareasandanincreaseofwomenlivingaloneinruralareas.

Source:GHS2011&2015

ElderlyLivingAlone

Ahigherproportionoffemaleswerelivingindependently/aloneinatleasteightofthenineprovincesin2011andseven ofthenineprovincesin2015.

WesternCapeprovincerecordedthehighestproportionsoffemaleswhowerelivingalone

in2015at 63,4%,a

dropof17,2percentagepoints,from80,6%in2011

ElderlyLivingWithSpouses

47,4%50,2%

46,6% 46,3%48,7% 48,8%

46,4%

52,9%47,7%

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

WC EC NC FS KZN NW GP MP LP

Male Female

In2015,EC(50,2%)andMP(52,9%)recordedhigherproportionsoffemaleswhowerelivingwiththeirspouseswhencomparedtootherprovinces.

Source:GHS2015

Howdowedefinehouseholdstructure?

Complexhouseholdsareallhouseholdswithmemberswhoarenotrelatedtothehouseholdhead.

UnitedNationsStatisticsDivision– DemographicandSocialStatistics:http://unstats.un.org

Asinglehouseholdisaone-personhousehold.

Nuclearhouseholdsaredefinedas‘householdsconsistingofhouseholdheads,theirspousesandoffspring’

Extendedhouseholdwouldincludeotherrelativesinadditiontothenucleus.

ElderlyHouseholdStructure

1,5%

14,1%

17,5%

67,0%

Complex

Single

Nuclear

Extended

Black/African

4,5%

9,0%

32,5%

54,1%

Complex

Single

Nuclear

Extended

Coloured

0,9%

14,4%

58,0%

26,8%

Complex

Single

Nuclear

Extended

Indian/Asian

3,1…

32,3%

53,0%

11,7%

Complex

Single

Nuclear

Extended

WhiteWhitesweretheleastlikelytolivein

extendedhouseholds.

Only11,7%ofhouseholdsheadedbytheelderlywereclassifiedasextended.

In2011,40,3%livedinextendedhouseholds,butby2015only26,8wereinextendedfamilies.

MostsignificantchangetookplaceamongsttheIndian/Asianelderly.

BlackAfricanselderlywerethemostlikelytoliveinextendedhouseholds.

Colouredelderlywerethemostlikelytoliveinextendedhouseholds.

Source:GHS2015

IntergenerationalHouseholdTypes

7,1%

9,3%

45,5%

32,1%

6,1%

10,3%

17…

21,3%

35,6%

15,2%

8,9%

10,4%

44,1%

30,8%

5,9%

12,5%

19,0%

20,7%

33,3%

14,4%

Other

Singlegeneration

Doublegeneration

Triplegenerationormore

Skipgeneration

2011SAhouseholds 2011Elderlyhouseholds 2015SAhouseholds 2015Elderlyhouseholds

Percentagedistributionofolderpersonsacrossintergenerationalhouseholds

*Skipgenerationhouseholdsweremoreprevalent(above10%)amongsthouseholdsheadedbytheelderlythanamongSouthAfricanhouseholdsingeneral.

*Skippedgeneration:whenagenerationisskippedornotpresentinahouseholdSource:GHS2011&2015

HouseholdGenerationalTypeAmongtheElderly

11,7%

8,4%

17,5%

42,7%

19,7%

7,2%

13,6%

32,4%

37,9%

9,0%

9,2%

28,5%

37,2%

20,4%

4,8%

17,7%

51,1%

22,7%

5,9%

2,6%

Other

Singlegeneration

Doublegeneration

Triplegenerationormore

Skipgeneration

African/Black Coloured Indian/Asian White

TripleormoregenerationhouseholdsweremostlycommonamongstblackAfricanandcoloured populationgroups

ElderlyfromIndian/Asianandwhitepopulationgroupsweremostlikelytolivein*single-generationhouseholds

*Aone-(orsingle)generationhousehold:consistsofpeopleofthesameagegroup:amarriedorcohabitingcouple,asingleperson,siblings,orroommates

Source:GHS2011&2015

Ratioofchildrentoolderpersons,inhouseholdsheadedbytheelderlybysex,2015

0,75

1,37

1,10

0,00

0,20

0,40

0,60

0,80

1,00

1,20

1,40

1,60

Male Female Bothsexes

Nationally,theratioofchildrentoolderpersonswasvisiblyhigheramongstfemales(1,37)thanmales(0,75).Thisindicatesthathouseholdsheadedbyolderwomenweremorelikelytoresideorcareforchildrenthanmen.

Source:GHS2015

Migration Patterns

MigrationRatesGautengprovincehadthehighestinfluxofolderpersonsfromotherprovincesincludingthosewhoarecomingfromoutsideSouthAfrica,withanin-

migrationrateof413,7 per1000population PosesgrowingburdensforeconomicsupportandhealthcaresystemonGauteng

Source: CS 2016

NetMigrationRates

WC EC NC FS KZN NW GP MP LPNet-migrationrate 211,8 -193,5 -274,6 -326,9 -35,3 229,7 315,9 -82,8 -175,2

-400,0

-300,0

-200,0

-100,0

0,0

100,0

200,0

300,0

400,0

Netm

igratio

nratesp

er1000po

pulatio

n

Source : CS 2016

Gauteng, North West and Western Cape experienced thelargest positive net migration rates. These provincesreceived large proportions of older persons from otherprovinces and had less out-migrants.

WC NW

GP

ECNC

FS

KZN MP

LP

Education

LP73,6%

MP70,1%

KZN55,5%

EC52,8%

FS52,7%

NW55,3%

NC51,2%

WC23,8%

GP30,0%

FunctionalIlliteracyintheElderly,byProvince,2016

FunctionalilliteracyamongsttheelderlyinSA

stoodat47,0%Thiswasadeclinefrom62,6%in1996

74%

70%

55%

53%

56%

51%

47%

53%

30%

24%

87%

81%

71%

70%

69%

63%

63%

62%

38%

31%

0 10 20 30 40 50 60 70 80 90

2016 1996

DecreaseinFunctionalIlliteracyintheElderly,byProvince,1996- 2016

20161996

LargestreductionsinilliteracywererecordedinECandNorthWest

HighestratesoffunctionalilliteracywerefoundinLimpopoandMpumalanga

LP

MP

WC

GP

FS

RSA

NC

EC

KZN

NW

PercentagePointChangesinHighestEducationalAttainmentoftheElderly

The biggest decreases between 1996 and 2016 took place in no schooling with a 23,1 percentage point decrease in the country

-23%

8%

1%

3%

6%

4%

-25 -20 -15 -10 -5 0 5 10

NoSchooling

SomePrimary

Primary

SomeSecondary

MatricOnly

Tertiary

NoSchooling

Thebiggestdecreasesbetween1996and2016tookplaceinnoschoolingwitha23,1percentagepointdecreaseinthecountry

0

5

10

15

20

25

30

35

40

45

Noschooling Someprimary Completedprimary

Somesecondary

Grade12/Standard10

Higher

BlackAfrican Coloured Indian/Asian White

HighestLevelofEducationintheElderly,2016

Morethanaquarterofthewhiteelderlypopulationhaveatleastsometertiaryeducation,comparedtootherpopulationgroups

TheBlackAfricanpopulationgroupcontinuestohavethelowestpercentageofelderly(7,6%)withGrade12orhigher.

BlackAfricansaremorelikelytohavenoeducationorsomeprimaryastheirhighesteducationalattainment.

Income generation, employment and poverty levels

Elderly living without an employed household member

Unemployed females were more likely to live with an elderly person

49,8

54,2

52,5

47,8

52,5

50,7

44

46

48

50

52

54

56

Male Female RSA

2011

2015

More than half of elderly persons live with unemployed household members

44,5%

64,8%

43,7%

63,0%

0

10

20

30

40

50

60

70

Urban Rural

2011

2015

Householdswithnoemployedmembers,containingelderly,weremorelikelytobefoundinrural thaninurbanareas

Elderly Living Without an Employed Household Member

SourcesofIncome

42,2%

33,2%

11,1%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Urban Rural

Grants Salaries/wages/commission Other

80,8%ofelderlyinruralareasarehighlydependentongrants

Salaries/wages/commissionswerethesecondmainsourcesofincomeforelderlyheadedhouseholdsinbothruralandurbanareas

In2015therewere3,1millionoldagegrantrecipients

AccesstoGrantsbyProvince,2015

48,9%

54,4%

70,9%

77,3%

77,5%

79,7%

79,9%

82,3%

89,0%

0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0 90,0 100,0

WesternCape

Gauteng

FreeState

NorthernCape

Mpumalanga

NorthWest

Kwazulu-Natal

EasternCape

Limpopo

Nationally,70%oftheelderly,receiveanold-agegrant

The Western Cape had the lowest number of old-age grant recipients

0

10

20

30

40

50

60

70

80

90

100

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 (AVG)RSA

Receivingoldagegrants Notreceivingoldagegrants ReceivingPensions NotreceivingPensions

Distributionofold-agegrantandpensioncoverageovertimeforpersons60yearsandolder,2003and2015

Source:GHS2003-2015

Priorto2008,ahighernumberofelderlypersonswerenotbenefitingfromold-agegrants.

Thedistributionofpensionbeneficiariesincreased slightlybetween2010and2015,with10,7percentofolderpersonsreportingin2015toberecipientsofpensions,comparedto90,3%whoreportedtobenon-recipients.

Labour marketcomponentsforolderpersonsbyprovince,2016

92,2%

90,8%

89,4%

89,4%

88,0%

86,5%

86,2%

85,1%

80,4%

7,4%

9,0%

9,2%

10,4%

11,3%

13,2%

13,2%

14,4%

18,6%

0,0 20,0 40,0 60,0 80,0 100,0

NW

EC

FS

KZN

MP

NC

LP

WC

GP

NEA Employed Unemployed

Thelabourforce,whichcomprisestheemployedandunemployed,accountedforlessthan15%ofthemarketshare

In2016,Gauteng(18,6%)andWesternCape (14,4%),recordedthehighestpercentagesofelderlypersonsinemploymentcomparedtootherprovinces.

TheNEAaccountedfor86,5%ofthelabourinthethirdquarterof2016

Source:QLFS.Q32016

Life Expectancy, Health Status and Mortality

Lifeexpectancyatbirth,ofmalesandfemales,2002to2016

53,6

59,756,6

65,1

45

50

55

60

65

70

75

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Male Female

Lifeexpectancybysex

Years

Source:StatisticsSouthAfrica,P0302,Mid-yearpopulationestimates2016

MembershipofaMedicalAidSchemebyPopulationGroup

6,0% 16,6%

33,9%

73,5%

17,5%

BlackAfrican Coloured Indian/Asian White SA

Persons60yearsandolderwhoarecoveredbyamedicalaidormedicalbenefitschemeorotherprivatehealthinsuranceishighestamongstwhiteelderlyandIndians/Asians

Nationalaverage

Typeofhealthfacilitiesnormallyusedbyhouseholdheadsaged60yearsandolder,byprovince,2015

Themajorityofelderlyinallprovinces,exceptWesternCapeandGauteng,makeuseofpublicclinicsfortheirhealthcareneeds.

84,8

75,371,8 71,3 71,1

67,2

59,1

46,7

22,4

0

10

20

30

40

50

60

70

80

90

LP EC NW KZN MP NC FS GP WC

PublicClinic PrivateHospital PublicHospital

MostCommonMedicalConditionsAmongsttheElderly

37,9%– Highbloodpressure– 50%

4,4%– Diabetes – 16,6%

7,1%– Arthritis – 18%

Allthreeofthesediseasesaremorecommonamongstfemalesthanmales

Top 5 Causes of Death of the Elderly

Naturalcauses

CirculatorySystem

Diseaseoftherespiratorysystem

Neoplasms

Endocrine,nutritionalandmetabolicdiseases

97,0%

29,7%

14,9%

12,3%

11,3%

1

2

3

4

5

60-64 65-69 70-74 75-79 80-124

DiseasesoftheCirculatorySystemMales

DiseasesoftheCirculatorySystemFemales

60-64 65-69 70-74 75-79 80-124

NeoplasmsMales NeoplasmsFemales

Percentage of male and female individuals 60 years and older who died from some of the main underlying causes of death, by five year age groups, 2014

Thefiguresshowthattheprobabilityofdyingfromadiseaseofthecirculatorysystemincreasedwithage,forbothmenandwomen.

Whiletheprobabilityofneoplasmsdeclinedamongstfemaleswithage,theprobabilityofdyingofneoplasmsinmalesincreaseduntilage79andthendeclined.

Neoplasm:Anewandabnormalgrowthoftissueinapartofthebody,especiallyasacharacteristicofcancer.

CirculatorySystem Neoplasms

Source:CausesofDeath2015

Crime and Victimisation

Safety of the Elderly

Black African Coloured Indian/Asian White RSADuring day 2011 70,2 71,2 49,7 60,6 68During day 2015/2016 69,7 55,5 48,9 57,9 66,1At night 2011 37,5 45,7 24,5 44,3 39,1At night 2015/2016 32,2 44,3 27,7 31,8 32,9

Percen

tage

Duringthepast5years,feelingsofsafetyduringthedayandnighthavedeclinedforallfourpopulationgroups.

Percentagedistributionofhouseholdheadsaged60yearsandolderwhofeelsafewalkingduringthedayandatnightintheareawheretheylivebypopulationgroup,2011and2015/16

TheIndian/Asianelderlyfeelmostunsaferegardlessofwhetheritisduringthedayoratnight

Source:VOCS2011,2015/2016

Victimisation

1,0

1,1

0,8

4,6

1,3

1,3

1,9

4,0

0,6

1,0

1,5

3,3

0,9

1,1

1,7

3,6

Theftfromcar

Homerobbery

Theftoflivestock

Housebreaking/burglary

Elderly Elderlyfemales Elderlymales RSA

Householdsheadedbytheelderlyhadasimilarlikelihoodthanhouseholdsingeneraltobethevictimsofhomerobbery

Householdsheadedbyolderpersonsweremorelikelytobevictimsoflivestocktheft,withmaleheadedhouseholdshavingabiggerprobabilityoffallingvictimthanfemaleheadedhouseholds.

Household Basic Services

Dwellingtypeofhouseholdsheadedbypersonsaged60yearsandolder,2011and2016.

82,5%

12,3% 4,6%

84,9%

9,9% 4,7%

Formal Traditional Informal

2011 2016

TherewasaslightincreaseinthepercentageofolderpersonswhowerelivinginformaldwellingsacrossallprovincesexceptLimpopo.

Source:Census2011,CS2016

Percentagedistributionofpersonsaged60yearsandolderbyaccesstobasicserviceandgeographytype,2011and2015

Urban Rural Urban Rural2011 2015

Access to piped water 96,0 34,3 95,6 34,1Improved Sanitation 95,0 41,6 96,4 62,3Refuse/ Waste 91,4 4,2 91,3 5,8Electricity 96,9 78,8 97,2 87,8

0,010,020,030,040,050,060,070,080,090,0

100,0

Perc

enta

ge

Source: GHS 2011, GHS 2015

Thepercentageofolderpersonswhohadaccesstoimprovedsanitationincreasedinruralareasby21,1 percentagepoints.

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