SECOND CARNEGIE INQUIRY INTO POVERTY
AND DEVELOPMENT IN SOUTHERN AFRICA
, ;1 , I Spatial variations in the levels of living in the cape JretroJXllitan area by N Riley, C Schtmrul, P JOnanovsky and R Gentle Carnegie Con£erence Paper No. 13
Cape Town 13 - 19 April 1984
, ISBN 0 7992 0823 X CONTENTS l'age
INTRODUCTION
LEVEL OF LIVING INDICATORS : A COMPOSITE INDEX 3
I NCOME DIfFERENCES AND THE lNDEX OF INCOHE INEQUALITY
OTHEH CONS] DERATIONS 9
"EPENDENCY RATES AND ACTIVITY RATIOS 9
OCCUPATION 12
EDliCATION 13
HOUSING 13
HEALTH 15
CRIME 16
CONCLUSION 17 LIST OF TABLES
1. Composite index for rich (low scores) and poor (high scores) suburbs
2. Mean Head of Household'and Personal Income
3. I ndex of Income J 11('4ua 1.1 ty for Bel ec ted suburbs
4. CombIned ind{,x of lncom" Inequality, dependency ratios and ActivIty rBtes for Relected suburbs
5~ PPf('f.'lll<:Jge 01 WId tt' and hluf> coJ Jar workers in selected subtlrbs
6. Housing Densities and room occupancy rates
7. Violent crime rRtes and the composite index by selected suburbs
LIST OF FIGURES
1. Composite Indicator of levels of living
2. Income inequality
APPENDICES
1. Table showing composite index scores
2. Figures of IndivIdual indicators
3. Tables of indivIdual indicators
4. Figures of Mean Head of Household and Personal Income
5. Formula for the index of income inequality
6. Table showing index of income inequality
7. Table shoWing frequency distribution of head of household income by number of persons per household (01 Region)
8. Table showing education levels for selected high and low income suhurbs
9. Spatial distribution of tenure
10. Spatial distri but ion of housing densi ties
11. Spatial distribution of occupancy rates
12. Table showing frequency distribution of number of habitable rooms per dwelling by number of persons per household (01 Region and Kullsriver) ,------
• " ..... oyF.~ "A~~ • ~nANGA
GREATER CAPE TOWN (01 REGION ANO KUILSRIVER) r SELECTED SUBURBS E TOWN METROPOliTAN TRANSPORT AREA
(01 REGION AND KUIlS RIVER' 1980 CENSUS - LOCAL ARtAS \1 • "To d.o better we must have game "'ay of ·distinguIshing
better from worse." Rivlin
INTRODUCTION
1. If it i.s 8("crptf'd th"t the injunction "It is not given to m"n to I,now
I.he truth but 1.0 Beek the truth", Is true, then It is lalso) ;,c,""pt •. d
that knowledge of re"lity is relative. lie have at our disposal
concepts and tools (in the heuristic sense) which we use in order to
describe reality. These concepts and tools, however, are not value
free, and the situation often occurs when the concepts used in social
analysis differ subtly in meaning when apparently addressing the same
phenomena or even, in extreme cases, differ diametrically (e.g. the
concept "democracy").
2. The problems of sodal analysIs are further compounded ",hen, wIthin
the same paradigm, consensus cannot be reached on the validi ty or
acceptability of certain concepts.· One "'ay out of such an impasse is
to consider concepts operationally as they are used in particular
studies. An acceptance of limitations imposed by working definition~
at least allows the researcher the room to develop hls ideas or
analysis coherently, that is, the discourse is internally logical.
3. While the Carnegie Inquiry has as its focus the understanding of the
extent and causes of poverty in Southern Africa, it must be accepted
that the concept poverty does not eaSily lend itself to description,
let alone definition. The problem has two dimensions, on the one
hand, conceptual/theoretical difficulties and, on the other, the
limi tations of available data; the conceptual/theoretical
difficulties relate to the problem of measurement, both 2 I
quantitatively and qualitatively. ]s poverty to he considered in
absolute terms or relative terms? Researchers are generally agreed
that it is highly improbable that poverty will ever be defined
absOlutely in a satisfactory manner, and for the purposes of the
paper thp issu~ of absolute poverty is not considered at all.
He]at tve poverty though itCh greater appeal af-i Ii mf~aSUrf:" since it Is a
much hroader COIlCP!'t and since it inherently has a dynamic
dimension. A definition, which captures the fluidity of relative
poverty admirably, reads "People are 'poor' because they are deprived
of the opportunities, comforts, and self-respect regarded as normal
in the community to which they belong. It is therefore the
continually moving average standards of that community that are the
starting points for an assessment of its poverty, and the poor are
those who fall suffIciently far below these aVE'rage standards."l.
Yet, however appealing such a definition may be, it stUI does not
address itself adequately to the notions of "self-respect" ,
"happiness", "misery" etc.
,. The issue of data availability is a further limitation on the
understanding and description of poverty. This paper draws heavily
on da ta ext racted f rom the 1980' Census and While census data itself
imposes restrictions on social research, the problem becomes
exaggerated when not all the information is available and, at the
same time, is available only in the form of a 5% sample. Given the
]jmi tatIons of the available data, as ",ell as the grey areas of
subjectivity in the concept of relative poverty, this paper will
address itself to an appraisal of levels of living in the Cape
Metropolitan Area. 3
5. It must be quite clear from the outset that thts pap~r is exploratory
and descriptive in nature. It is by no means intended as a
definitIve statement of territorial well-being. The notion of levels
of living therefore Is offered as ~ proxy indIcator for relatIve
d'·rrfv~tfon.
LEVELS or LIVING INDICATORS A COMJ'OSlTE J NIJEX
6. For the purposes of this paper, a level of living is defined
operationally as that which is constituted by the overall composition
of income, housing, education and employment aggregately exhibHed
within a given geographical area, together wIth those aspects of
demographic structure, general physical environment and consumption
of goods and servIces which may determine the extent to whIch the
needs relating to the foregoing constituents of level of lIving can
be, or are, met. Although this def.i.nition addresses 'itself to the
factual circumstances of well-being, it has built-in limitations;
the political dimension (democratic partIcipation, etc), leisure,
social security and social ~tatus are not considere~ for the purpose
of the study.
7. The derived composite Index for inter-suburb comparison is likely
to have greater usefulness than the individual indicators, which can
be unwieldy measures of what is essentially a unitary concept.
Notwi thstanding Townsend's stat emen t, "We should ff rs t understand
individual indicators before comhining them into complex indices"2,
it is tel t tha t the foregoing assertion is necessary as a point of
departure. In this regard there is a greater correspondence with
Smi th, "As long as the defects of existing data are recognised and f.tllprovf~ment:6 are conFltRl1t1y sought a useful atart can bp flJ(-Id~ 011
describing Borne Important dimensions of human existence conspicuously
missing from (ll(' conventional view of the ",,,rld,,.3
FurtlH'rIl10re, 11 is .1rkTH)\ •.df .. dg<:>d that in the confilTuction of thf'
composite index tlte 1i,,"fI,od of ",etghtl.ng is arhitrary and Rubjpct to
r{~searchf'rs, ;11 though not BS a deterrent; they feature, inter alta,
~ Dre",nowski and Scott I.n their "The Level of Living Index" ana
Reilly5 in her "Social Indicators."
8. Given the data constraints in the construction of the level of living
index for the Cape J.letropol1tan Area, seven proxy indicators \,if" ..
used as base Ol.1:terjal, viz. These were chosen in such a "'ay that
weJghting of the var.iables occurred implicitly. Generally the
weighting "'as related to recognised standards, for example, income
limits were imposed by the Bureau of Market Research 19/10
supplemented living levels, occupancy rates per room by the British
natlonal housing spec:fLicat.i.ons, shared accommodation by the measure
of one family per dwelling unit, car ownership by one car per
househol d, workers' educational level s by previous minimum levels
under the Apprenticeship Act, single mothers with more than three
children and finally, unemployment by actual levels per suburb.*
9. These variables were selected to represent, amongst them, the
character and composition of the major components of the Census. In
this case the diagnostic variables "'ere selected in such a way that
each was highly associated with at least One of the other six
* Suburbs have been matched approximately to Census Local Areas. In
some cases there is a total correspondence and in others not. 0= HIGH 100 = lOW
m33.80 - 63.34 .• 16.36 - 33.80 1IllIlII7.27 - 16.36 § 4.27 - 7.27 [[0 0.62 - 4.27 00.00 - 0.62 INDEX PRODUCED BY REATER CAPE TOWN CAL FORM LOCAL AREA BASE seAL
1980 DIREctOR OMPOS IT E IN DI CA TOR 1:836000 CENSUS TECHN'~~~v7~;~GEMEN F LEVELS OF LIVING
Figure 1 components (wlth a correlation of .:!:0,6< or more). TllIlS, if Wt,
consider a pair of variahles the correlatlon implfes that, in tlot·
matlH'matl.cRl RenHe at le"6t, and probably also in the conceptual
senRe, there 1 s nn "l "II'"nt of substitutability between the varl. ahles.
]0. Till' spati;l] (s11hllrh) 1 r(:quPllcJes jn pt'Tcentage scores for (';,t'l:
varjable was transformed onto a linear Reale to generate a new f;et of
scores for each varlable On a range 0 to 100, where ° represents th"
suburb with the lowest (j .e. most desirable) incidence and 100
represents the hIghest (.I.e. the worst). After transformaUon, all
the seven 6cores were summed for each suburb, on the assumption that
they contribute equally to living levels (given the weighting
constraints). The composite indicator was arrived at by divIding the
sum by the n\~ber of varIables. The living level index is not itself
on a scale of 0 to 100 hecause no suburb scores 100 on all variables,
but composite indices arrived at in this way do show that any suburb
with a score of ° must have the equivalent of the lowest (best) value
on all contributing v;,riables, and one with 100 must have the worst
performance of them all. (See Figure 1 for spatial representation).
TABLE I COMPOSITE INDEX FOR RICH (LOW SCORES) AND POOR (HIGH SCORES) SUBURBS
HIGH LOW
SUBURB SCORE SUBURB SCORE
Kalksteenfontein 63,3. Plattekloof 0,00 Lavender Hill 61,13 Neadowridge 0,7 I Valhalla Park 59,17 Kingfisher Estate O,lj~ Newtown 56,93 Bishopscourt 1,05 Bonteheuwel 53,3. Llandudno 1,19 Hangberg 53,20 Dunrobin 1,32 Parkwood 53,16 Thalman 1,50 Manenberg 52,9. Eversdale 1,52 Matroosfontein 52,50 Edenpark 1,60 Kraaifontein RurAl 52,38 Akasia Pa rk 1,65
See Appendix I for a nlore cOlIlprehensive table 11. The above table shows the relatIve positions of selected suhurbs
(some of the best and some of the worst). The composi te indicator is
responsible for smoothing the sharp differences hetw""n indf.v.idual
indicators, due largely to the fact that two varf.rlbJes, namely,
sing)e mothers with mOTe than thrpp c1d1dren and un(!mp]oYlJlent rates,
g~lIe~<111y regi.slered ]ower' frt:'quellctcs tll;]n t.h(~ other variables. Iii
the first case the effect is most prohably due to the way th~
variable was defined; in retrospe<;t it would appear that a better
definition should read as follows: single mothers wlth two or more
chUdren. However, the constraints of time and extent (more than 300
Local Areas in the Metropolitan Area) meant that the original
definition had to be retained. Secondly, while unemployment rates
fluctuate markedly from area to area, they average out at
approximately 10%. WhUe this did not markedly affect the scores of
the more affluent areas which regIstered low scores, it certainly
lowered the scores of the more deprived areas; no score higher than
63,34 was registered.
12. There were three "maverick" suburbs as far as the composite index
scores were concerned, namely, Guguletu, Langa and Nyanga •. Contrary
to expectation, all three registered lower scores than expected in
relation to other areas, in fact they did not appear in the ten worst
off suburbs in the metropolitan area at all. Upon examination of
their scores on individual indicators it appeared that their scores
were a function of influx control and the Singular position of
Africans in the Western Cape. It is generally accepted that the
African areas were underenumerated. On 'shared accommodation',
'single mothers with more than three children' and 'unemployment' all
registered low scores while o!, the other indiv.1.dual indicators they
were amongst the highest scoring suburbs. (See Appendix 2 for a
graphic distribution and Table 3 for a statistical representation of
extremes in living levels between the richest and the poorest suburbs.) INCOME DIFFERENCES AND TilE INDEX OF INCOME INEQUALITY
13. In a free market society such as South Africa ultimately the abJliLy
to pay Is the single most lu~ortant criterion of well-b~jng
c(~rtainly liS far as Ilw COIHiulllpti..on of eoods and b(+rvict:B .iE.
c()nc(·nwd. Thus the dil;paraties in incolllf- tynt;ral1y PYt.;Vt: d(~cj.s.ivl...
in distinguishing One arl:8 from auother. Ideally an analysIs of
income patterns which would inform an understanding of poverty should
have as its basis the family and/or the household income, that is, as
the central unit consuming goods and services. However this was not
possible as only head of household income and personal income figures
were available frow the 1980 Census. What is readily apparent
though, is the facl that 49,23% of all income earners earn less than
R3 000,00 per annum in the metropolitan area - an Income picture that
bodes no good for the living levels of the majority of persons living
in this area. l~e spatial variations in head of household income and
personal income are shown graphically in Appendix 4. These are
complemented by the following table showing median income for both
categories in affluent and poor areas.
TABLE 2 : MEAN HEAD OF HOUSEHOLD AND PERSONAL INCOME FOR SELECTED SUBURBS
HIGH INCOME AREAS LOW INCOME AREAS
Mean Mean Mean Mean Suburb Head of Personal Suburb Head of Personal Household Income Household Income Income Income
Welgemoed 20495,45 11651,53 Newtown 1003,33 1208,57 PIa tt ekl oof 18625,00 11004,54 Himosa Park 1150,00 1115,38 Bishopscourt 25238,63 13812,24 Ka1ksteenfontein 1481,57 1433,67 Penzance Est 13812,50 11071,42 Kraaifontein Rural 1400,00 1300,00 Kenridge 16056,33 12053,81 Valhalla Park 1554,34 1363,49 Constantia 18614,96 10361,64 Steenberg 1704,54 1440,00 Newlands. 15835,90 10552,27 Ilangberg 2000,00 1592,46 Chantecler 15937,50 9900,00 Lavender Hill 1990,65 1709, ':Il Fresnaye 15776,80 9053,19 Kew Town 1988,88 1773,52 Llandudno 15125,00 13353,57 Schotse Kloof 2365,00 1983,51 04893.05 - 16336.60
[[] 2215.00 - 4893.05 ~ 409.05 - 2215.00 g -1095.20 - 409.05 III -3121 .35 - - 1 095.20 E;;I-5337.80 - -3121.35 INDEX PRODUCED CAPE TOWN BY AREA BASE CAL FORM seAL ... . N.W.RIlEY ~~~ ~ MS 1.836000 "#;. w 1980 DIRECTOR INC 0 ME '-l ~ TECHNICAL H~N~GEMEN INEOUALITY <- ~ CE NS US SERVICES
Figure 2 8
]~. In order to approach tll{' issue of poverty or deprivation fJolI! nnoth('r
angle, an index of income divergence/inequality used by Smlll,t'
adapted to 11 lilstrat" Once again the sharp dlvergences In the
metropolHall Rrea. The derived index serves to illustrate the (kgree
to which ~rt'a!:; d1vcq:e frolTJ "f~qualfly" :f.f th~ norm Is C:(Jn~frlprf'd t(1
he the .1oCOHl(' Ct-It"t-f,ory, t:fvf'n thE' dfst.rlbutfon of income, .int() which
every earner should fall If they were deemed to be ··equal··. In thIs
partIcular study, head of household income was used (see Appendix 5
for an explanation of the formula). The table below shows the
divergence in scores of selected suburbs while Figure 2 shows the
total spatIal distribution graphically.
TABLE 3 1 NDEX OF 1 NC()~IE 1 NEQUALl TY FOR SELECTED SUBURB S
HIGH INCOME AREAS LOW INCOME AREAS
SUBURB 1 NDEX OF SUBURB INDEX OF I NEQUALlTY INEQUALl TY
Welgemoed + 11999,7 Newtown - 5181,5 Plattekloof + 11695,1 Mimosa Park - 4937,8 Bishopscourt + 10041,4 Kalksteenfontein - 4816,2 Penzance Estate + 9624,4 Kraaifontein Rural - 4787,8 Kenridge + 9603,5 Valhalla Park - 4747,4 Constantia + 9387,5 Steenberg - 4!JlS,O Newlands + 8184,9 Hangberg - 4409,6 Chantecler + 8143,3 Lavender Hill - 4370,3 Fresnaye + 7376,1 Kew Town - 4255,0 Llandudno + 7309,9 Schotse Kloof - 4249,0
See Appendix 6 for a more comprehensive table
15. The Ruburbs depicted in the above table were deliberately selected on
a non-random basis. Since the areal scores derived correspond
over-all to the same patterns exhibited by the composite index, it
was felt that selected suburbs (subjective bias) would suit the
purpose of the exercise. The greatest departures from equality of
distr.l huUon (L c. high indices) correspond wi th high income areas, 9
as m.lght be expected. The question 01 how far observed scores in
this region were inequi table or unjust is beyond th~ scope of tI,..
present discussion, 'however such questions cannot he asked or
answered unless Inequality can be measured. CertRinly, whatever
thresholds are accepted, the poverty they dpf1.ne could be eliminatpd
by raIsing thl' whole population ahov(·
relationships 'between people. !nequa11.ly, on the other h~nd, can
only be eliminated by changing relatIonships hetwl'en people, between
regions, between classes, and between etholc groups. EquaHty would
eliminate poverty, in this sense, whether the average standards
achieved were higher or lower than the present averages.
OTHER CONSIDERATIONS
16. An index of income inequality, of course, has its own limitations;
fundamentally, it says nothing about total wealth, for example,
property, investments, saving,; and inheritance. It also cannot
incorporate fringe benefits, .ubsld!es etc. However, as a measure of
remuneration for services or work performed, it does allow an
indication of the "gaps" that exist in society. As a tool for
analysis, when coupled with other indicators such as dependency
ratios, activity rates and occupations for instance, reasonable
inferences can be made about general conditions in the metropolitan
area.
Dependency rates and activity ratios
17. A dependency ratio consists of the number of non economically active
to every 100 economically active persons in a given population, while
an acti~ity rate refers to the proportion which employed and 10
ulIl'mploypd perROIlS form of the total population. The following tahle
111llRtrRt"s qutte ,"arply the vastness of the "gaps" which exist in
the u,etropo1ftan area.
TABLE 4 COMHI NED ] Ni)I':>: OF J NCOME J NEQUALJ TY , DEPENDENCY RAT! OS AND ACTIVITY RATES FON SELECTED SUHURHS
I1I.CIl J NeONE AREAS
SUBURB DEPENDENCY RATIO INDEX OF ACTIVITY RATES INEQUALITY
Fresnaye 49,6 + 7376,1 48,2 Newlands 45,6 + 8184,9 49,39 Constantia 55,0 + 93B7,5 45,00 Bishopscourt 22,8 +10041,4 4~,30 L1and'udno 21,1 + 7309,9 54,17 Penza nee Estate 33,3 + 9624,4 58,33 Chl!ntec1er 75,0 + B143,3 37,50 Dunrobin 76 t 4 + 7344,1 41,13 We1gemoed 55,3 +11999,7 40,0 Kenrl.dge 67,3 + 9603,5 37,27 Plattekloof 46,2 +11695,1 47,B3
LOW JNCOME AREAS
Scottsdene 61,0 - 4070,0 43,07 Valhalla Park 104,7 - 4747,4 27,50 Kalksteenfontein 68,0 - 4B16,2 33,60 Mimosa pI! rk 176,9 - 4937,B 25,00 Kraaifontein Rural 166,7 - 47B7,8 33,33 Ne.'town 41,5 - 51Bl,5 58,62 Kewtown 60,0 - 4255,0 37,42 Lavender Hill 76,9 - 4370,3 31,75 Hangberg 78,8 - 4409,6 3B,27 Steenberg Bl,8 - 4415,0 31,67 Ocean View 85,7 - 3786,5 31,21 Bonteheuwel 63,7 - 4088,3 38,12 Epping Forest 83,5 - 4831,5 39,03 Nooitgedacht 75,0 - 4019,2 34,48 Sa repta I 11,5 - 3268,3 29,06
18. The large degree to which the affluent areas deviate from the norm is
remarkable. This difference is further exaggerated by the effect of
the corresponding activity rates and dependency ratios. Thus, for
instance, WelgE'moed, Plattekloof and Bishops Court all have the
activity rates of 40 or more (relatively,high) and dependency ritlos
of acceptable proportions when compared to the more deprived areas 11
such RS, for example, Kraatfontein's rural hinterland, Valhalla Par,
and Sarepta. The poorer areas, convprsely, also have lower Rctivity
rates. ThIs means in real terms that the former areas, While not
only having .. xrel'dlngly higher levels of Income (h"ads of households)
8]60 Ilave fewer deppnrieJlt per~ons ~ndt at the ~alne tj.me, nl()re people
..",rklng. Ilence when income from other "arners 'is added (assuming they
have roughly the same relative Inter-suburb dJstrJbutJon, disposable
income must diverge even more.*
19. Applying the Bureau of Market Research's Minimum LivIng Levels for
households ranging in size from 1 to 8 persons per household, it is
illuminating to see that for coloured households (the largest ethnic
component by far in the region) some &8,8% of households fall below
mt ntmum income levels. The matrix from which this statement is
derIved however does not incorporate the number of workers per
household. Undoubtedly their (workers) presence would supplement
household income and certainly modIfy the gross percentage. An
indication of its modifying Influence is offered by the figure of
3,6& workers per household in the coloured group for the region as a
whole. Notwithstanding their modifying Influence, the general
position still appears to be one of considerable deprivation (see
Appendix 7 for a frequency distribution of head of household income
by number of persons per household - 01 Region).
* An examination of the spatial patterns of Appendix & showing personal income, will confirm this assumption 12
OCCllpat ion
20. An lnt('gral component of deprivation, in so far as it 1s A prime
determinant ·of income, is occupation. This assertj on is made in
support of Rp I HS wilo ilia I nl a j ns t ha t, "wh11 e We may think of income as
hejn~ rf'ceived "'OTf' or Jess s:tmuJtan('o1Js]y with the purfiuJt of ali
occupation, it is l rue that most of the income received from an
occupational pursuit accrues subsequent to the entry Into and
Identification with that occupation. There is a sense, then, in
which occupaUon may he considered logically or temporally prior to 7 income, as well as fllnctionally relRted thereto· • Thus a spatial
Indication of skIlled, semi-skilled and unskilled persons by actual
occupational catego!".ies would go A long way in furnishing the
understanding of .1 Ivi ng levels in the metropolitan area.
Unfortunately, this was not possible given the census constraints On
available information. Instead, whAt is offered is a slightly cruder
distinction between white collar workers and blue collar workers.
Crude as this distinctJ.on may be, it certainly supports the above
mentioned hypothesis that income and occupation are "functionally
related". WIIE'n one considers the table below then it is quite clear
that the high income areas have a larger proportion of white collar
workers than blue collar workers and, conversely, the poorer areas
have a higher proporti.on of blue collar workers than white collar
workers. 13
TABLE -5 PERCENTAGE Of WHITE AND BLUE COLLAR WORKERS IN SELECTED SUIlURBS
LOW INCOME AREAS
Valhalla Park Mimosa Park Kraaifon- Epping Sarepta tein RurAl Forest
WHITE COLLAR 13,6% 0% 0% 13,4% 20,6%
BLUE COLLAR 86,4% 100% 100% 8b,6% 79,47.
TOTAL 100,0% 100,0% 100,0%' 100,0% 100,02:
HIGH INCOME AREAS
Constantia Bishopscourt Penza nee Welgemoed Platte- Es ta te kloof
WHITE COLLAR 54,9% 62,9% 57,1% 71,2% 54,6%
BLOE COLLAR 45,1% 37,1% 42,9% 28,8% 45,4%
TOTAL 100,0% 100,0% 100,0% 100,02: 100,0%
Education
21. On the question of education Reiss continues "We have, therefore, the
following sequence: a man qualifies for occupational life by
obtaining an education; as a consequence of pursuing his occupation
be obtains income. Occupation, therefore, is the intervening
activity linking income to education". 8 Appendix 8 demonstrates
this relati.onship by showing the educational levels for selected high
income and low income suburbs.
Housing
22. The form of tenure under which people are housed is an important
indicator of material well-being. Generally in the metropolitan area
the people who "have", possess their own homes and those who "have 14
not" ] ive in public rented accommodation (economic and 6ub-economl c
units) while those inbetween, rent privately. The qual i ty of
people's physical exlstence tends to be the mirror-image of the samp
grada tions. Appendix 9 shows the same spatial patterns as the
composite lndex of lpvels of lJvlng and the Index of fn~orr.e
Apl,(·"dJx 1(1 showIng housing densftf~!: also hears rhis
out. Furthermore, the tahle below which depicts occupancy rates for
selected suburbs 8S well as their corresponding hOUSing densities
once. again reinforces the view that tenure and well-being are closely
related. See Appendix 11 for spatial variations in persons per
habitable room.
TARLE 6 HOUSING DENSITIES AND ROOM OCCUPANCY RATES
LOW INCOME AREAS
Suburb Average persons Housing units per room per hectare
Factreton 2,19 9,26 Hanover Park 2,12 19,14 Lavender Iii 1 I 2,08 43,93 Manenberg 2,19 23,81 parkwood 2,20 17 ,97 Nyanga 2,62 6,77 Kalksteenfontein 2,57 20,95 Bonteheuwel 2,03 15,56
HIGH INCOME AREAS
Suburb Average persons Housing units per room per hectare
Fresnaye 0,47 9,26 ~Ii lnerton 0,56 0,36 Mead owridge 0,63 6,30 Bishopscourt 0,44 1,96 Llandudno 0,42 1,19 Hout Bay 0,44 0,14 Edgemead 0,66 2,53 Pinelands 0,57 6,00 Welgemoed 0,55 2,64 Durbanville 0,60 2,76 15
23. What is important, with the above table in mind, is to realise that
overcrowding is a multi-dimensional problem, resulting from the
interaction of physical arrangement of space, noise, temperalure and
social (degree of cohesion, personality interactions etc.) factors.
It i6 characterised by adverse manifestst ions of stress. Numerous
examples from research li.terature lndicate that \o,lhen privacy
disappears, the maintenance of harmonious social relationships is
threatened. There is no opportunity to wi t hd raw from rela tionships
that have become sufficiently intense to cause confilict. It is
therefore alarming to discover that 58,9% of all Coloured households
in the region are overcrowded. (This figure was derived from a
mat rix of persons per household by the numher of rooms per house with
a desired ratio of 1,5 persons per room. See Appendix 12).
Health
24. A number of studies have indicated that high density living is
associated with many deprivations and stresses, and that both
infectious and non-infectious diseases tend to cluster together under
such conditions. In a study done in Baltimore, USA among high
density housing areas with high occupancy rates it was stated that
"Various diseases and maladies, including pysychoneurosis were
found" 9 In Cape Town itself this is manifested by the prevalence
of tuberculosis which "affects mainly the underprivileged and, •••••
will remain a problem as long as sections of the Cape Town population
remain exposed to the effects of malnutrition, overcrowding
etc." Furthermore, "overcrowding especially in cold weather" which
"is unavoidable for large sections of the community"lO is also seen
to have a high correlation with cerebrospinal fever. 16
25. Given the low scores on the index of Income. inequality, lilt· !.11'.!.
dependency ratios, overcrowding etc it is nol su~prl.6illg thaI lIIosl of
the local authority health clinics (preventive medicine) are si[uatpd
in the pubJ i c rented "ccon1lnoda tl.on a reas must sure] y be one of the
strongest slate",(,nls "hollt reJativ(> deprivatIon.
Crime
26. Certain types of crimes, particularly crimes of violence, are
generally considered to correlate highly with areas exhibiting marked
depr iva tion. II is therefore interesting to note that the areas
identified by the composite index as being highly deprived also tend
to have the highest vIolent crime ratios in the Cape PenInsula. The
table below ilJuslrates the spatial affinity of violent crimes and
deprivation in se]('cted suburbs. These suburbs were identified as
the most criminogenic in a study conducted in the months of January, 11 June and December 1979.
TABLE 7 VIOLENT CRHlE RATES AND THE COMPOSITE INDEX BY SELECTED SUBURBS
Suburb Crimes per 100 000 Compnsite Index for 3 month period
Guguletu 397 46,90 Retreat 280 45,95 Bonteheuwel 721 53,34 Manenberg 715 52,94 Grassy Park 353 31,24 Bishop Lavis 371 47,97 Langa 039 44,67 Athlone 160 39,39 Hanover Park 387 50,37 Nyanga 513 43,47 Philippi 175 32,00 17
CONCLUSION
27. This study has demonstrated spatially the large "gaps· that exist in
levels of living in the metropolitan ar~a. Undoubtedly there are
large areas, some of which are contigllOUti \,oJhile uthers are almost
islands, that are suffering condl t Ions of extreme deprivation. FroID
a developDl~ntal point of view these structural obstacles need to be
addressed if there is to be stability and growth in the region.
28. There is a need for work and the acquisition of skills for productive
economic performance. It is essential that access to infrastructural
facilities be provided. Research has shown that the constraints imposed by jobs, school, health facilities and recreation facilities
affect productivity, conjugal relationships and amount of leisure
time etc. The growing specialization of our economy has. increased
the significance of education as a prerequisite of employment and as
a determinant of occupational status.
29. Opportunities for social participation, interaction, community cohesion and communication are needed. The provision of adequate and
sufficient housing is of vital importance. Based on the 1980 Census
an estimated minimum backlog of 46 000 houses was determined. Along
with the provision of housing there should be security of tenure.
30. Finalli, it can be said with reasonable certainty, that if a
conscious effort is not made to raise the levels of living of the
people within the study area that conditions will worsen. It is
time to acknowledge that the depriva tIon of one is inextricably bound
up with the affluence of another. APPENDICES 18
APPENDIX I : COMPOSITE INlJEX
HIGH SCORES LOW SCORES
SUBURB SCORE SUBURB SCORE
Factreton 50,94 Akasia Park 1,65 Schotse Kloof 50,61 Bantry Bay 3,36 Sa It Rl ver 46,71 Fr~snaye 2,b2 Hanover Park 50,57 Camps Bay 3,92 Il,' ze ndal 50,43 Frere Estate 4,59 lIeideveld 41,24 Ilat ton £s tal e 3,57 Lavender Hill 61,13 Kingfisher Estate 0,84 Manenberg 52,94 Meadowridge 0,71 Parkwood 53,16 Newlands 2,25 Retreat 45,95 Rondebosch 4,05 Hangberg 53,20 Bi shops Cou rt 1,05 Guguletu 46,90 Llandudno 1,19 Langa 44,67 lIout Bay 3,29 Nyanga 43,47 Richmond Estate 3,23 Ocean View 46, 4~ Bellville Central 3,90 Scottsdene 49,86 Chrismar 2,86 Kalksteenfontein 63,34 Dunrobin 1,32 Valhalla Park 59,17 Thalman 1,50 Eisies River 48,82 lielgelDoed 2,30 Uitsig 47,02 Eversdale 1,52 Matroosfontein 52,50 Kenridge 2,42 Bishop Lavis 47,97 Belmont Park 3,98 Mimosa Park 44,05 Peerless Park North 3,23 Newtown 56,93 Clam lIall 1,79 Kraaifontein Rural 52,38 Panorama 1,79 Bonteheuwel 59,07 Plat:tekloof 0,00 Eden Park 1,60 Durbanville 2,04 '.
I!I 65.86 - 100.00 • 33.33 - 65.86
• 16.37 - 33.33 § 8.51 - 16.37 Illl 0.00 - 8.51 00.00 - 0.00 INDEX PRODUCED BY REATER CAPE TOWN CALFORH LOCAL AREA BASE seAL N.W.RILEY MS 1980 DIRECTOR HOUSEHOLD HEADS 1 1836000 CEN sus ECHH'~:~v7~~~GEt1EH EARNING < R3000 Appendix 2A 18162.02 - 100.00 III 33.52 - 62·02 m18.65 - 33.52 § 7.34 - 18.65 OIl 0.00 - 7~34 00.00 - 0.00 INDEX REATER CAPE TOWN LOCAL AREA BASE seAL ~ ;; .., 0 N.W.RILEY o ~ MS 1980 DIRECTOR HOUSEHOLDS WITH 11836000 ~. ~~ ~ CENS US TECHHI;~~v~~~:CEH£M NO CARS .. -
Appendix 28 '.
£1'48.43 - 100.00
• 19.26 - 48.43 ffiI 3. 66 - I 9. 26 § 0.00 - 3.66 IJ] O. 00 - O. 00 00.00 - 0.00 INDEX PRODUCED BY REATER CAPE TOWN CAL FORM lOCAL AREA BASE seAL N.W.RILEY 1980 DIRECTOR OCCUPANCY RATES 1 1836000 MS CENSUS rEcHNI~:~v~~~~GEMfN GREATER THAN 1.5 Appendix 2C (31 22.78 - 100.00 • 5.95 - 22.78 l1li o. 00 - 5. 95 § 0.00 : 0.00 lID o. 00 - o. 00 o 0.00 - 0.00 INDEX CAPE TOWN AREA BASE seAL MS 1980 .'0EC,.0 1. 8J6000 CENSUS ECHMI~~~y7c::GEt'EN HARED ACCOMMODATION
Appendix 2D g 13.77 - 71.40 .0.00 - 13.77 IIIIIIII 0.00 - 0.00 ~ 0.00 - 0.00 ITO 0.00 - 0.00 00.00 - 0.00 INDEX PRODUCED J.G.BRAND BY ITY ENGINEER REATER CAPE· TOWN CAL FORM LOCAL AREA BASE seAL N.W.RILEY MS 1980 DIRECTOR I NG L. E MOT HER S WIT H" 836000 CENS US TECHNI;;~V~~~:GENEN ORE THAN 3 CHILDREN Appendix 2E ~ 16.68 - 100.00
.2.58 - 16.68
• 0.00 - 2.58 § 0.00 - 0.00 []]] 0.00 - 0.00
00.00 - 0.00
INDEX CAPE TOWN AREA BASE seAL N.W.RILEY MS 11836000 1980 DIRECTOR UNEMPLOYED CENS US ECHM 1~~~¥ ~~GEHE"
Appendix 2F R"zrm
E! 22·S3 - 100.00 • 7.7i - 22.53 ffiI 2.02 - 7. 71 ~ 0.00 - 2.02 IIIl 0.00 - 0.00 00.00 - 0.00 INDEX REATER CAPE TOWN LOCAL AREA BASE seAL ... ~ N.II.RILEY ...o 0• MS 1980 OIRECTOR EDUCATION OF " 8J60tO ~..... w 'i i CENS US ECHN I ~~~v ~~~GEt1EH WORf Appendix 2G 19 APPENDIX 3A HOUSEHOLD HEADS EARNING LESS THAN R3 000 PER ANNUH SUBURB SCORE SUBURB SCORE Zonnebloem 8~,70 Akasia Park 3,84 Bridgetown 73,80 Bantry Bay 6,12 Hanover Park 78,75 fresnaye 8,69 lI"zenda] 73,58 Camps /lay 9,73 Kew Town 83,90 Hi Inert on 9,30 Klipfontein Mission 81,81 Kenilworth 3,~6 Lavender Hill 80,48 Hcadowridge 2,50 Manenberg 82,00 Ne..,lands 6,62 Parkwood 77 ,35 Rondebosch 9,~5 Silvertown 76,36 Constantia 9,43 Hangberg 90,62 Welgemoed 6,25 Guguletu 90,80 Durbanville 5,55 Langa 90,58 Kenridge 2,81 NyangB 86,72 Glen Lily 5,26 Steenberg 90,90 Panorama 1,79 Ocean View 74,39 Parow North 2,09 Kalksteenfontein 97,72 Plat tekl oof 1,60 Valhalla Park 100,00 Matroosfontein 72,22 Bishop Lavis 75,86 Nooitgedacht 77,14 Newtown 93,75 Bonteheuwel 92,85 Kleinvlei 75,43 Scottsdene 83,33 Mfuleni 100,00 , ;1 , I 2U APPENDIX 3B HOUSEHOLD HEADS WITH NO CARS SUBURB SCORE SUBURB SCORE FRcreton 74,71 Bridgetown 76,18 HAnover Park 80,71 Fresnaye 5,78 H('ideveld 71,77 Camps Bay 9,73 Kew Town 1ll,59 Milnerton 5,81 Lavender Hill 84,55 Table View 5,94 Manenberg 86,UO Kingfisher Est~te 5,88 PRrkwood 77 ,35 Newlands 8,60 Si lvertown 85,84 Bishopscourt 0,00 Hangberg 84,37 Kirstenbosch 0,00 Cuguletu 84,68 Constantia 6,91 Langa 85,87 Pinelands 9,64 Nyanga 78,75 Bellville Central 8,12 Steenberg 90,90 Plattekloof 0,00 Ocean View 82,91 Bonteheuwel 79,68 Ka1ksteenfontein 90,90 Valhalla Park 84,61 Elsies River 77 ,16 Uitsig 86,03 The Range 73,33 Matroosfontein 72,21 Mimosa Park 100,00 Newtown 87,50 Kraaifontein Rural 100,00 Scottsdene 85,55 21 APPENDIX 3C OCCUPANCY RATES HIGH LOW SUBURB SCORE SUBURB SCORE Facreton 75,86 Bantry Bay 0,00 Athlone 54,23 Frefinaye 0,00 Hanover Park 76,13 Green Point 2,58 He1develd 58,89 Camps Bay 5,30 Lavender Hill 76,41 Sea Point 1,60 Manenberg 74,28 Tamboerskloof 4,23 Parkwood 74,52 Gardens 1,12 Retreat 66,65 Milnerton 1,16 Silvertown 50,90 Table View 0,98 Hangberg 75,00 Claremont 3,95 Guguletu 76,58 Kenilworth 2,B8 Langa 57,64 Meadowridge 2,50 Nyanga 80,53 RondeboRch 0,00 Ocean View 57,31 Rosebank 0,00 Mfuleni 50,00 Constantia 4,40 Kalksteenfontein 72,71 Bishopscourt 0,00 0,00 El~tes River 65,50 Llandudno Cravenby Estate 64,28 Hout Bay 0,00 Ui tsig 67,69 Simon's Town 1,29 Matroosfontein 68,50 Fish Hoek 1,14 Bi shop Lavi s 63,35 Edgemead 0,00 Bellville .South 60,B2 Pine lands 1,12 Newtown 68,75 Bellville Central 2,32 Kraaifontein Rural 100,00 Bell ville West 0,00 Ravensmead 67,90 Boston 0,00 Bonteheuwel 78,56 Chantecler 0,00 Sc ot tsdene 75,55 Welgemoed 0,00 Durbanville 1,37 BelvedE'.re 0,00 Panorama 0,00 Plattekloof 0,00 Welgelegen 0,00 22 APPENDIX 3D 1 SHARED ACCOMMODATlON HIGH LOW'" SUBURB SCORE SUBURB SCORE Facreton 89,64 Akasia 0,00 KensIngton 75,48 Bantry Bay 0,00 Schoonekloof Ill,81 CI if ton 0,00 Salt River 33,33 Three Anchor Bay 0,00 WaIDler Estate 42,84 Fresnaye 0,00 Woodstock 50,74 Camps Bay 0,00 Athlone 50,82 Mouille Point 0,00 Athlone West 94,71 oranjezicht 0,00 Belgravia Estate 32,28 Bridgetown 35,70 Gleemoor 63,63 Hanover Park 30,39 Lavender Hill 34 t 14 Lincoln EstRte 60,00 Pen1yn Es tate 30,76 Primrose Park 49,98 Retreat 41,22 She ,,",ood Pa rk 46,86 Silvertown 65,43 Strandfontein 72,00 Wynberg 36,18 Ocean View 62,19 Bonteheuwel 44,52 Kalksteenfontein 81,81 Valhalla Park 51,90 Elsies River 30,51 MatroosfoTltein 94,44 Nooitgedacht 51,42 Newtown 93,75 Sarepta 54,04 Scottsdene 33,33 * No shared accommodation in most affluent areas 23 APPENDIX 3E SINGLE MOTHERS WITH MORE THAN 3 CHILDREN HIGH LOW* SCORE SUBURB SCORE SUBURB 12,79 AkaRia 0,00 Schotse Kloof 0,00 Sc hoonekl oof 45.~5 Bantry Bay 42,34 Clifton 0,00 Athlone 0,00 Belgravia Estate 30,75 Th ree Anchor Bay 0,00 Bridgetown 23,79 Fresnaye 0,00 Gleemoor 45,45 Green Point 18;85 Camps Bay 0,00 Grassy park 0,00 Greenhaven 57,65 MouUIe Point 0,00 Hanover Park 31,00 Sea Point Hazendal/Bokmakierie 56,60 Heideveld 18,39 Kew Town 22,95 Lan"downe 39,04 Lavender Hill 60,95 Lotus River 13,30 Manenberg 45,70 Montagu's Gift 23,96 Parkwood 18,85 Retreat 23,35 Sherwood Park 15,60 Silvertown 18,14 Surrey Estate 31,90 Wynberg 12,90 Zeekoevlei 38,45 IIangberg 46,85 Philippi 44,10 Guguletu 5,44 Kalk Bay 20,80 Steenberg 45,45 Bonteheuwel 31,25 45,45 ,I Kalksteenfontein . \ Valhalla Park 38,45 Elsies River 43,40 E}>ping Forest 50,00 Uitsig 41 ,64 Matroosfontein 27,75 Bishop Lavis 28,00 Bellville South 20,94 Mimosa Park 62,50 Sarepta 27,75 Newtown 31,25 Scottsdene 33,29 * Most affluent areas score 0 APPENDIX 3r ALL UNENI'LOYED HIGH LOW SUBURB SCORE SUBURB SCORE F<1ctreton 26,79 Akasia 0,00 N~jtl~lld 21,33 Bt'ooklyn 0,00 Schot"e Kloo! "1 ,2(J Three Anchor Bay 0,00 Salt RIver 00,37 Camps Bay 0,00 Sa It R:lver 35,37 Mouille Po:lnt 0,00 Woodstock 26,66 Sanddrift 0,00 Bridgetown 36,12 Schoonekloof 0,00 Grassy Park 34,79 Sea Point 0,00 Hazendal/Bokmaklerle 42,70 Tamboerskloof 0,00 Heideveld 22 ,54 Vredehoek 0,00 Lavender Hi 11 47,04 Bloubergstrand 0,00 Lotus River 25,74 Blouberg Strand 0,00 Manenberg 26,00 Montagu's Gift 23,79 Mount View 43,08 Parkwood 62,29 Retreat 28,70 Sllvertown 22,24 Surrey Estate 24,50 Wynberg 27,20 lIangberg 22,20 Gugllletu 28,45 Ka Ik Bay 54,79 Bontehellwel 25,54 Epping Forest 67,45 Bishop Lavis 22 ,70 Sa repta 32,33 Scottsdene 35,04 25 APPENDIX 3G EDUCATION OF WORKERS WITH LESS THAN STD & HIGH LOW SCORE SUBURB SCORE SUBURB Park 0,00 Factreton 38,&2 Akasia 2,50 Hazendal 27,35 Bant ry Bay 3,44 Bridgetown 3&,35 Clifton 2,70 Ileideveld 3&,75 Camps Bay 1,72 Kew Town 39,28 Oranjeztcht 0,94 Kllpfontetn Mission 33,32 Sea Point 1,50 Lavender Hill 44,34 Gardens 1,33 Manenberg 43,82 Table View 3&,31 Claremont 1,39 Parkwood 0,00 Retreat 34,07 KirstenboBch 0,00 Welcome Estate 33,32 Meadowridge 2,45 Hangberg 34,&5 Newlands 1,47 Langa 45,23 Rondebosch 0,00 Nyanga 39,75 Rosebank 2,84 Steenberg 47,35 Bishopscourt 0,00 Ocean View 42,25 LI andudno 0,00 Bonteheuwel 42,79 Hout Bay Kalksteenfontein 54,76 Simon's Town 1,14 0,00 Valhalla Park 52,71 Marina da Gama 0,00 Elsies River 37,35 St .James 0,54 Ul.tsig 34,45 Fish Hoek 1,52 Matroosfontein 32,37 Bell ville Central 0,00 Bishop Lavis 38,20 Boston 0,00 Nooitgedacht &0,00 Chantecler 0,00 Sarepta 32,34 Dunrobin 1,79 Kraaifontein Rural &&,65 Durbanville Ravensmead 35,39 Eversdale 0,00 Panorama 1,79 Plattekloof 0,00 iii 12500.00 - 30000.00 611 9999.99 - 12499.90 lID 7500.00 - 9999.90 ~ 5000.00 - 7499.90 [OJ 2500.00 - 4999.90 00.00 - 2499.90 RANDS PER ANNUM PRODUCED REATER CAPE TOWN BY LOCAL AREA BASE CALFORM SCALE <~'I; iT MS 1980 NO',~('C~O~LfY HEAD OF HOUSEHOLD 1:836000 .,. w CENSUS lrcHIH~:~v7~~~r,r.Mr.N 1 N COME '} ~ ______. ___ -"--'--'-=-~:.:::._ ____~_.___L _ ___L Appendix 4A I, i ~=-I '-" 1,,; I:l i 2500.00 - 30000.00 1I!l9999.99 - 12499.90 I~ill 7500. 00 ~ 9999.90 ~ ~OOO.OO - 7499.90 III] 2500. 00 - 4999.90 00.00 - 2499.90 PROD:-U-C-CE:::-:D.----:---c:c:---:--.:::--=-=--=--=-=--C-,---A-P~E,--tA~~i~!-lA~IWM JE CALnRM AREA BASE SCALE . T MS N.II.RILEY ~"O:- ~z: 1980 O!REefOR PER SON AL INC 0 ~1E ,,636000 '''l ~ CEN SUS TECH~I;~~v7~~~CrMi:H .. - LO.::..:c:_::..=.t_-=:.:.::..:--'------. --~.--~- -- Appendix 4B 2& APPENDIX 5 FORMULA FOR TIlE INDEX OF THE INEQUALITY OF INCOME Houaehold Head Income It is proposed lo me~sure the degree of income inequality in the 01 Economic RegIon and Kul Is River. The method of measuring the income distribution by a co-efflcjent is to compare the local observed percentage dIslrlbuUon against the degree of deviation from the median income. The calculation is b~sed on a methodology devised by P M Smith and R J Gray. (Social Indicators for Tampa, Florida, Urban Studies Bureau, University of Florida, 1972). The index is calculated in the following way: 1. Where xy is the percentage in a given income category for local area j .. 2. Where Wi is the difference between the mid-point value of an income category and that of the median income (Median income calculated for household heads for the Metro region is R4 255,18). 3. The cut-off point for the income dIstribution of household heads is +R15 000, however an upper interval has been calculated as RI5 000 to R29 850. The Internal average of the upper income group is R22 424,50. Example: The median income of household heads (4255,18) subtracted from the mid-point of a particular income category (example 500-999) 750, multiplied by the percentage of occurrences in that particular income category. Summed overall categories in each local area. 27 APPENDIX 6 INEQUALITY INDEX Low - Index High + Index Bridgetown - 4054,4 Akasfa Park + 8653,2 Ha nover Pa rk - 3996,7 Fresnaye + 7376,1 Ileldeveld - 3791,7 Camps Bay + 6256,0 Kew Town - 4255,0 MUnerton + 4937,9 Lavender Hill - 4370,3 Groote Schuur Estate + 5H2,l LotlI" River - 2939,6 Kenilworth + 4178,7 Manenberg - 4283,0 Mead owrJ dge + 7535,1 Pa rkwood - 3693,2 Newlands + 8184,9 Retreat - 3709,6 Constantia + 9387,5 Hangberg - 4409,6 Bishopscourt +10041,4 Guguletu - 4907,8 LIandudno + 7309,9 Lango - 4786,0 St James + 6552,9 Nyanga - 4705,9 Pine lands + 5178,4 Ocean View -...3786,5 Belgravia + 5774,6 Bonteheuwel - 4088,3 Chantecler + 8143,3 Kalksteenfontein - 4816,2 Eversdale + 7344,1 Valhalla Park - 4747,4 Welgemoed +11999,7 Elsies River - 3911,5 Kenridge + 9603,5 Uitsig - 4008,6 Belvedere +16336,6 Range - 4517,8 Panorama + 8956,9 Bishop Lavis - 4221,8 Plattekloof +11695,1 Ravensmead - 3412,1 Scottsdene - 4070,0 Mfuleni - 4629,4 APPENDIX 7 HEAD OF HOUSEHOLD INCOME BY NUMBER OF PERSONS PER HOUSEHOLD - COLOURED (5% SAMPLE - 01 REGION) PERSONS PER HOUSEHOLD HEAD OF HOUSEHOLD INCOME None 0- 500- 1000- 1600- 2000- 2500- 3000- 3500- 4000- 4500- 5000- 6000- 7000- 8000- 15000 TOTAL 499 999 1599 1999 2499 2999 3499 3999 4499 4999 5999 6999 7999 14999 + 6 5 58 25 8 6 3 5 8 a ° 135 % 0,09 0,07 0,91 0,39 0,12 0,09 0,04 0,01 0,06 0,07 0,06 0,12 0,01 0,00 0,01 0,00 2,12 2 48 11 136 94 58 39 39 27 21 15 1~ 29 13 553 % 0,75 0,17 2,14 1,48 0,91 0,61 0,61 0,42 ~,33 0,23 0,22 0,45 0,11 0,03 0,20 °0,00 8,72 3 58 12 110 95 67 106 51 64 54 42 36 30 31 21 23 802 % 0,93 0,18 1,73 1,49 1,05 1,67 0,80 1,00 0,85 0,66 0,56 O,~7 O,~8 0,33 0,36 0,01 12,64 71 14 96 86 79 '[109 80 85 82 72 46 63 53 27 40 3 1006 % I,ll 0,22 1,51 1,35 1,24, 1,71 1,26 1,34 1,29 1,13 0,72 0,99 0,83 O,~2 0,63 0,04 15,86 5 75 12 100 119 86 107 85 73 74 61 H 57 53 25 45 1023 % 1,18 0,18 1,57 1,87 1,35 1,68 1,34 1,15 1,16 0,96 0,74 0,89 0,83 0,39 0,70 0,06 16,13 6 58 12 78 108 80 110 74 66 62 40 31 52 34 15 34 3 857 % 0,91 0,18 1,23 1,70 1,26 1,73 1,16 1,04 0,97 0,63 0,48 0,82 0,53 0,23 0,53 0,04 13 ,51 84 14 112 112 77 127 84 59 49 38 29 29 34 14 27 ° 889 % 1,32 0,22 1,76 1,76 1,21 2,00 1,32 0,93 0,77 0,59 0,45 0,45 0,53 0,22 0,42 0,00 14,02 8 35 40 H 29 58 25 18 20 17 3 9 ° 361 % 0,55 0,11 0,63 0,69 0,45 0,91 0,39 0,28 0,31 0,26 0,11 0,04 0,14 0,00 5,69 9 25 3 22 23 18 34 26 15 10 16 8 12 6 2 ° 214 % 0,39 0,04 0,34 0,36 0,28 0,53 0,41 0,23 0,15 0,09 0,12 0,18 0,09 0,03 0,06 0,00 3,37 10 18 17 27 30 31 13 8 10 2 179 % 0,28 0,06 0,26 0,42 0,47 0,48 0,20 0,11 0,12 0,15 0,06 0,11 0,01 °0,00 0,03 °0,00 2,82 11 17 13 12 16 13 14 6 5 3 2 2 109 % 0,26 °0,00 0,20 0,18 0,25 0,20 0,22 0,09 0,06 0,07 0,01 0,04 0,01 0,03 0,03 °0,00 1,71 12+ 23 8 19 44 22 38 12 8 8 6 7 3 2 212 % 0,36 0,12 0,29 0,69 0,34 0,59 0,18 0,12 0,12 0,09 0,11 0,11 0,04 0,03 0,01 0,06 J ,3 ~ TOTAL % 519 102 801 789 570 778 506 439 397 318 247 314 231 113 201 15 6340 8,18 1,60 12,63 12,44 8,99 12,27 7,98 6,92 6,26 5,01 3,89 4,95 3,64 1,78 3,17 0,23 100,00 29 APPENDIX 8 EDUCATION LEVELS FOR SELECTED HIGH AND LOW INCOME SUBURBS (PERCENTAGE) HIGH INCOME AREAS Fres- Camps New- Cons tan- Bishops- Llan- Evers- Welge- Ken- Pano- Platte- naye Bay lands tia court dudno dale moed ridge rams k.1oof Sub A, B, Std 1 4,4 6,7 5,3 9,7 2,7 13,4 5,5 8,7 16,4 Std 2 2,9 1,5 2,0 4,5 8,3 3,7' 6,4 ~,5 9,6 11,0 Std 3 3,9 2,6 2,2 3,1 3,7 4,6 3,1 1,4 Std 2,4 2,1 3,5 5,2 1,4 7,4 3,7 2,6 2,7 Std 5 6,3 5,3 3,3 6,1 6,7 8,3 1,8 3,7 2,6 2,7 11,0 Std 6 5,8 7,0 5,3 5,0 10,8 3,7 4,6 6,1 2,7 1,4 5,6 Std 7 7,8 5,7 3,3 3,8 1,4 4,2 1 t 4 3,7 4,8 Std 8 11,2 13,2 11 ,3 12,1 9,4 16,7 14,3 15,6 7,9 9,6 5,6 Std 9 9,3 3,5 4,7 4,5 2,7 8,3 2,8 2,8 6,1 4,1 5,6 Std 10 26,3 32,0 25,7 24,2 20,3 25,0 23,0 16,5 30,6 17,8 39,0 Bachelors Degree or equilavent 4,9 3,8 ll,8 6,0 17,6 12,5 2,8 5,5 8,7 5,6 5,6 Masters 0,5 0,6 1,1 0,2 0,4 2,7 0,9 Doctorate 0,5 0,6 a,s Std 10 + Diploma 10,8" 13,0 15,8 12,3 18,9 12,5 14,3 17,4 9,6 13,7 Std 8 + Std 9 + Diploma 3,4 1,5 0,3 1,5 0,8 5,4 4,2 2,3 0,9 Std 7· or lower + Di ploma 0,5 1,4 Diploma + Degree ll,O Bachelor 1,5 1,2 1,5 1,6 2,7 4,6 7,3 3,9 4,1 Diploma + Masters Diploma + Doctorate 0,4 Unknown 0,9 0,7 0,2 6,8 5,6 100,0 100,0 TOTAL 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 r 30 APPENDIX 8 (Contd) EDUCATION LEVELS FOR SELECTED RIGH AND LOW INCOME SUBURBS (PERCENTAGE) LOW INCOME AREAS Han- Kew Laven- Manen- Park- Hang- Gugu- Ocean Kalk- Val- Elsies B:lshop over Town der berg wood berg letu View steen- halla River Lav:ls Park Hill fontetn Park Sub A,B, Std 1 15,3 13,4 19,7 17,0 13 ,0 16,4 15,0 18,9 17,6 27,1 18,0 16,0 Std 2 8t~ 6,4 8,7 10,4 12,6 13,7 7,9 8,4 12, I 12,9 6,8 5,8 Std 3 10,5 7,9 10,8 9,8 9,4 8,9 9,5 8,4 8,0 5,3 7,7 7 , ~ Std 13,9 14,6 12,7 14,1 12,6 17 ,I 10,8 12,8 15, I 12,2 12,0 11,2 Std 5 16,5 20,1 17,9 17,2 17, I 17,8 12,4 16,5 17.6 19,1 13,8 17,6 Std 6 18,8 19,8 14,0 17,5 18,1 15,1 17,8 13 ,3 10,1 13,5 17,5 17 , ~ Std 7 6,4 9,5 9,4 5,2 6,8 6,8 9,3 10,2 9,5 3,6 7,0 8,7 Std 8 5,8 4,4 4,4 4,1 5,8 2,1 9,4 5,8 5,0 2,0 4,0 6,7 Std 9 1,1 1,5 0,6 1,2 0,6 3,2 0,3 0,7 1,8 2,6 Std 10 1,5 1,2 1,1 1,1 1,3 3,2 1,2 1,3 2,3 1,9 Bachelors Degree or equilavent 0,2 0,6 0,0 0,0 0,3 0,0 Masters degree Doctorate Std '10 + Diploma 0,3 0,1 0,4 0,6 Std 8 + Std 9 + Diploma 0,5 0,6 0,2 0,3 0,6 0,7 0,4 1,2 0,4 Std 7 or lower + Diploma 0,1 0,6 0,1 Diploma + Degree Bachelor Diploma + Masters Diploma + Doctorate Unknown 0,8 0,6 0,5 2,0 1,7 1,4 0,8 1,8 5,0 2,3 7,7 4,7 TOTAL 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 E;) 75.00 - 100.00 .60.00 - 74.90 1IIIlill45.00 - 59.90 ~ 30.00 - 44.90 ITlJ 15.00 - 29.90 D 0.00 - 14.90 PERCENT PRODUCED BY REATER CAPE TOWN LOCAL AREA BASE seAL CALFDRM <- ~ ... 0 N.II.RILEY I: 836000 o z MS 1980 DIRECTOR TYPE OF TENURE ~. '1-1. ~ CENSUS TECHNT;:~v~~~~GEHEH HOME OWNERSHIP <- ~ Appendix 9A • 1ii175.00 - 100.00 •. 60.00 - 74.90 .45.00 - 59.90 ~ 30.00 - 44.90 OJ] 15.00 - 29.90 o O. 00 - 1 4 . 90 PERCENT PRODUCED BY REATER CAPE TOWN CALFDRM LOCAL AREA BASE seAL N.W.RILEY 1980 DIRECTOR TYPE OF TENURE 1:836000 MS CENS US' ECHH I ~:~v ~~=~GEMEH PUBLIC RENTED Appendix 98 III 75,00 - 100,00 11160,00 - 74,90 IIIIIIII45,00 - 59,90 § 30,00 - 44,90 rrn 15,00 - 29,90 o 0,00 - 1 4 . 90 PERCENT CAPE TOWN LOCAL AREA BASE SCALE ~~ N.W.RILEY I : 836000 \ ~ T MS 1980 DIREcrOR TYPE OF TENURE 'i CEN SUS ECtfNI~~~v~~GO'EH PRIVATE RENTED .. -~ Appendix 9C IDI~ ,=- II IlD 14.82 - 58.62 .9.25 - 14.82 1ID11115.77 - 9.25 §j2.75 - 5.77 [IT] 0.67 - 2.75 00.00 - 0.67 DWELLING UNITS PER HECTARE PRODUCED BY REATER CAPE TOWN CAL FORM LOCAL AREA BASE N.W.RILEY seAL s~~ ~ 1980 DIRECTOR ~ ~ MS '-836000 "'-: ~ CENSUS 'ECHNT~:~v~~:~GEt1[N HOUSING DENSITY 'i ~ . ~ Appendix 10 13 2.49 - 4.99 .2.00 - 2.49 III 1.50 - 1.99 §:l1.00- 1.49 []] 0.50 - 0.99 D 0.00 - 0.49 PERSONS PER HABlTABLE ROOM PRODUCED BY CAPE TOWN CALFORN AREA BASE . N.W.RlLEY MS 1980 DIRECTOR CENS US J ECHN 1 ;:~V ~~;:GEt1EH OCCUPANCY RATES Appendix 11 3J APPENDIX 12 NUMBER OF HAlllTABLE ROOMS PER DWELLING BY NUMBER OF PERSONS PER I!OUSEIWUJ - COUJlf'f.IJS (METROPOLITAN AREA - 5% SAMPLE) PERSONS 2 3 5 6 8 9 J 0+ . T01 AI. PER ROOM ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS ROOMS 1l0USE- HOLD 17 62 I b o l_~,251. 0,92% 0,23% 0,01% °0,00% °0,00% °0,007., °0,00% O,OO:t 2 86 168 206 99 17 6 583 1,27% ° 1 2,50% 3,06% 1,47% 0,25% 0,08% 0,00% 0,01% °0,00% °0,00% 8,67% 3 87 223 319 168 45 8 6 ° o 856 1,29% 3,31% 4,74% 0,66% 0,11% 0,08% 0,00% 0,00% °0,00% 0,00% 12,73% 77 207 311 73 10 3 ° ° 1074 1,14% 3,08% 4,62% 1,08% 0,14% 0,04% 0,01% 0,00% 0,00% 15,98% 5 46 220 307 64 15 6 2 1076 0,68% 3,27% 4,56% 0,95% 0,22% 0,08% 0,02% °0,00% °0,00% 16,01% 6 30 132 429 255 44 16 3 ° ° 910 0,44% 1,96% 6,38% 3,79% 0,65% 0,23% 0,04% 0,00% 0,00% 0,01% 13 ,54% 7 25 108 447 281 48 21 10 3 ° ° 943 0,37% 1,60% 6,65% 4,18% 0,71% 0,31% 0,14% 0,04% 0,00% 0,00% 14,03% 8 9 177 126 13 377 0,13% 0,65% 2,63% 1,87% 0,19% °0,00% °0,00% °0,00% 5,61% 9 9 22 105 72 13 230 0,13% 0,32% 1,56% 1,07% 0,19% °0,00% °0,00% °0,00% 3,42% 10 3 19 88 72 10 2 195 0,04% 0,28% 1,30% 1,07% 0,14% 0,02% °0,00% 0,01% °0,00% °0,00% 2,90% 11 2 53 40 13 118 0,02% 0,10% 0,78% 0,59% 1 2 0 ° ° 0,19% 0,01% 0,02% 0,00% 0,00% 0,00% 1,75% 12+ 2 20 80 88 14 217 7 6 0,02% 0,29% 1,19% 1,30% 0,20% 0,10% 0,08% °0,00% °0,00% °0,00% 3,22% TOTAL 393 1232 2756 1835 355 100 39 8 ° 6719 5,84% 18,33 41,01 27,31 5,28% 1,48% 0,58% 0,11% 0,00% 0,01% 100,00 % % % % 32 REFERENCES 1. Social Science Research Council (1968) "Research on Poverty" p. 5, Heinemann Educational Books Ltd 2. TOImsend, P (1970) "The Concept of Poverty", p.2l, Heinemann Educational Books Ltd 3. Smith, D M (1973) "The Geography of Social Well-Being in the United States", p.136, McGraw-Hill 4. Drewnowski, J EScott, W (1966) "The Level of living Index" United National Research Institute for Socia 1 Development, pp17-22, Report No.4 5. Reilly. EM: Social Indicators An Introduction and Bibliography, unpublished mimeograph 6. Smith, D M (1977) "Patterns in Human Geography" pp.166-l70, Penguin Education 7. Reiss, A J et al. (1961) "Occupations and social status", p.116, The Free Press of Glencoe Inc. 8. Reiss, ibid p.116 9. Mitchell, E R (1971) "Some social implicati~ns of high density housing" pp.18-29. American Sociological Review, Vol 36 10. Medical Officer of Health, City of Cape Town, Annual Report 1981, p.73 11. City Engineer's Department, City of Cape Town (1980) "Crime in the Council's Housing Estates" p.12.