2007 Community Survey Analysis for Cape Town
Author: Karen Small
Strategic Development Information and GIS Department
Strategic Information Branch
October 2008
2007 Community Survey Analysis for Cape Town
Table of Contents
1
Introduction.....................................................................................................................................5
2
Methodology ...................................................................................................................................5
3
Demographics .................................................................................................................................6
3.1
3.2
3.3
3.4
4
Population .................................................................................................................................6
Age Distribution.........................................................................................................................7
Migration ................................................................................................................................. 10
Disabilities ............................................................................................................................... 13
Education ...................................................................................................................................... 15
4.1
4.2
5
Educational Institution Attendance .......................................................................................... 15
Adult level of Education........................................................................................................... 17
Employment .................................................................................................................................. 19
5.1
5.2
5.3
5.4
5.5
5.6
Employment Status ................................................................................................................. 19
Work Status ............................................................................................................................ 20
Occupation .............................................................................................................................. 20
Industry ................................................................................................................................... 22
Income of Employed ............................................................................................................... 23
Unemployment Rate ............................................................................................................... 24
6
Social Grants ................................................................................................................................ 26
7
Households ................................................................................................................................... 27
7.1
7.2
8
Household Distribution ............................................................................................................ 27
Household Size ....................................................................................................................... 27
Housing ......................................................................................................................................... 29
8.1
8.2
9
Dwelling Type ......................................................................................................................... 29
Tenure .................................................................................................................................... 31
Services ......................................................................................................................................... 32
9.1
9.2
9.3
9.4
Energy Sources ...................................................................................................................... 32
Access to Water ...................................................................................................................... 34
Access to Sanitation................................................................................................................ 34
Refuse Removal ..................................................................................................................... 36
10
Household Goods ..................................................................................................................... 37
11
Summary ................................................................................................................................... 38
October 2008
Strategic Development Information and GIS Department
Page 2
2007 Community Survey Analysis for Cape Town
Figures
Figure 1: Population by race for 1996, 2001 and 2007 .............................................................................6
Figure 2: Age distributions by functional groups, race and gender for 2007 ..............................................7
Figure 3: Age distributions by functional groups and gender for 1996, 2001 and 2007 .............................7
Figure 4: Population pyramid for 1996 ......................................................................................................9
Figure 5: Population pyramid for 2001 ......................................................................................................9
Figure 6: Population pyramid for 2007 ......................................................................................................9
Figure 7: Place of birth of Cape Town residents for 2007 ....................................................................... 10
Figure 8: Place of birth (excluding Western Cape) of Cape Town residents by race for 2007 ................. 11
Figure 9: Province from which people moved into Cape Town since October 2001 ................................ 11
Figure 10: Number of people moving into Cape Town from other South African Provinces .................... 12
Figure 11: Age of people moving into Cape Town from outside the Western Cape ................................ 13
Figure 12: Disabilities by race for 2007 ................................................................................................... 14
Figure 13: Attendance at an educational institution by age for 1996, 2001 and 2007 ............................. 15
Figure 14: Attendance at an educational institution by race for 1996, 2001 and 2007............................. 16
Figure 15: Type of educational institution attended by race for 2007 ...................................................... 16
Figure 16: Highest level of education obtained by adults for 1996, 2001 and 2007 ................................. 17
Figure 17: Highest level of education amongst adults by race 2007 ....................................................... 18
Figure 18: Employment status by race and gender for 2007 ................................................................... 19
Figure 19: Work status by race for 2007 ................................................................................................. 20
Figure 20: Occupation by gender for 2007.............................................................................................. 20
Figure 21: Occupation by race for 2007 .................................................................................................. 21
Figure 22: Industry by gender for 2007 ................................................................................................... 22
Figure 23: Industry by race for 2007 ....................................................................................................... 22
Figure 24: Monthly income of the employed by gender for 2007 ............................................................. 23
Figure 25: Monthly income of the employed by race for 2007 ................................................................. 23
Figure 26: Unemployment by race and gender for 2007 ......................................................................... 24
Figure 27: Unemployment by race for 1996, 2001 and 2007 .................................................................. 25
Figure 28: Social grants by race for 2007 ............................................................................................... 26
Figure 29: Households by race of household head for 1996, 2001 and 2007 ......................................... 27
Figure 30: Household size by race of household head for 2007 ............................................................. 28
Figure 31: Dwelling type for 1996, 2001 and 2007.................................................................................. 29
Figure 32: Informal dwellings for 1996, 2001 and 2007 .......................................................................... 30
Figure 33: Dwelling type for 2007 ........................................................................................................... 30
Figure 34: Dwellings owned by race for 1996, 2001 and 2007................................................................ 31
Figure 35: Dwelling tenure by race for 2001 and 2007............................................................................ 31
Figure 36: Energy sources for lighting, cooking and heating in 2007 ...................................................... 32
Figure 37: Energy source for lighting in 1996, 2001 and 2007 ................................................................ 33
Figure 38: Main source of water by race for 1996, 2001 and 2007 ......................................................... 34
Figure 39: Access to toilet facilities for 2001 and 2007 ........................................................................... 35
Figure 40: Access to toilet facilities by Black Africans for 2001 and 2007 ............................................... 35
Figure 41: Type of refuse removal for 1996, 2001 and 2007................................................................... 36
Figure 42: Household goods for 2001 and 2007 ..................................................................................... 37
Figure 44: Household goods by race for 2007 ........................................................................................ 37
Tables
Table 1: Population by race and gender for 2007 .....................................................................................6
Table 2: Mean and median age for 1996, 2001 and 2007.........................................................................8
Table 3: Age distribution by gender for 2007 ............................................................................................8
October 2008
Strategic Development Information and GIS Department
Page 3
2007 Community Survey Analysis for Cape Town
Appendices
Appendix 1 – Estimation of Population and Number of Households ....................................................... 39
Appendix 2 – Statement by South African Statistics Council................................................................... 43
Appendix 3 – Western Cape Population by Local Municipality for 1996, 2001 and 2007 ........................ 46
Appendix 4 – Municipalities in the Western Cape ................................................................................... 47
Appendix 5 – Cape Town Population by Race and Gender for 1996, 2001 and 2007 ............................. 48
Appendix 6 – Age Distributions by Race and Gender for 2007 ............................................................... 48
Appendix 7 – Province from which people moved into Cape Town since October 2001 by Race ........... 49
Appendix 8 – Disabilities by Race and Gender for 2007 ......................................................................... 49
Appendix 9 – Highest Level of Education amongst adults by Race for 1996, 2001 and 2007 ................. 50
Appendix 10 – Western Cape Households by Local Municipality for 1996, 2001 and 2007 .................... 51
Appendix 11 – Dwelling Type by Race for 1996, 2001 and 2007 ............................................................ 52
Appendix 12 – Fuel used for Lighting, Cooking and Heating by Race for 2007 ....................................... 53
Appendix 13 – Access to Toilet Facility by Race for 2001 and 2007 ....................................................... 54
Appendix 14 – Refuse Removal by Race for 1996, 2001 and 2007 ........................................................ 55
Citation: City of Cape Town (2008), Strategic Development Information and GIS Department, 2007
Community Survey Analysis for Cape Town, Karen Small, 55 Pages.
2007 Community Survey Data supplied by Statistics South Africa.
October 2008
Strategic Development Information and GIS Department
Page 4
2007 Community Survey Analysis for Cape Town
1
Introduction
The 2007 Community Survey was a large-scale national household survey conducted by Statistics
South Africa in February 2007 as a result of government’s decision to move from a 5-year to a 10year census. The Community Survey was designed to fill the gap in information between the 2001
Census and the next Census in 2011. The survey was based on a random sample which covered
374,348 households across all the provinces resulting in 238,067 completed questionnaires. The
survey provides demographic and socio-economic data down to district municipality level.
This report will analyse both the demographic and socio-economic Community Survey data for
Cape Town and include some trends using the 1996 and 2001 Census information. When looking
at population growth in Cape Town comparison will be made with other municipalities in the
Western Cape.
2
Methodology
As the 2007 Community Survey was a sample survey and not a full census there were
methodologies for selecting the sample and estimating the population and number of households
at municipal level. Details of the estimations can be found in Appendix 1.
There were two stages to the sampling, firstly the selection of enumeration areas (the smallest
geographical unit into which the country is divided for census purposes by Statistics South Africa)
and then the selection of the dwelling units. The selection of the enumerator areas was based on
the Census 2001 enumerator areas and 19% (130) were sampled for Cape Town. To select the
dwelling units a complete list of all dwelling units in the selected enumerator areas was compiled
and using the serpentine selection 10% were selected in each enumerator area. In small
enumerator areas where the number of dwelling units was less than 10 the selection was
increased to 10. All households within the selected dwelling units were included.
The South African Statistical Council was involved in monitoring all the processes in the survey
and issued a statement on the results (see Appendix 2). Resulting from this statement Statistics
South Africa issued a cautionary note on the results as follows:
The Community Survey results were released on 24 October 2007. After the evaluation of the data
by the Stats Council, the Community Survey was found to be comparable in many aspects with
other Stats SA surveys, censuses and other external sources. However, there are some areas of
concern where Statistics South Africa is urging users to be more cautious when using the
Community Survey data.
The main concerns are:
The institutional population is merely an approximation to 2001 numbers and it is not new
data.
The measure of unemployment in the Community Survey is higher and less reliable due to the
differences in questions asked relative to the normal Labour Force Surveys.
The income includes unreasonably high income for children due to presumably
misinterpretation of the question, e.g. listing parent’s income for the child.
The distribution of households by province has very little congruence with the General
Household Survey or Census 2001.
The interpretation of grants or those receiving grants need to be done with caution.
Since the Community Survey is based on random sample and not a Census, any interpretation
should be understood to have some random fluctuation in data, particularly concerning the
small population for some cells. The user should understand that the figures are within a
certain interval of confidence.
Source: Statistical Release: Community Survey, 2007 (Revised version), Statistics South Africa, [Report
No. P0301]
October 2008
Strategic Development Information and GIS Department
Page 5
2007 Community Survey Analysis for Cape Town
3
3.1
Demographics
Population
The Community Survey estimates the population of Cape Town to be 3,497,097. This is an
increase of 20.9% since Census 2001 and 36.4% since Census 1996.
The South African population increased by 8.2% between 2001 and 2007. The Western Cape was
the province with the largest increase (16.7%). 80.2% of the population increase in the Western
Cape occurred in Cape Town. Other municipalities in the Western Cape showing a large
percentage increase between 2001 and 2007 were Stellenbosch (68.9%), Mossel Bay (64.8%),
Overstrand (34.4%), Bitou (33.7%) and Knysna (26.4%).
Details for all Western Cape
municipalities can be found in Appendix 3 and a map showing their location in Appendix 4.
In Cape Town the number of Black Africans has shown the largest increase (89.4%) since 1996
followed by 64.6% for Asians. The number of Whites has increased by 24.3% and Coloureds by
24.1%. See Appendix 5 for more information.
Race
Black African
Coloured
Asian
White
Total
Male
590,546
744,437
31,101
327,175
1,693,259
%
16.9%
21.3%
0.9%
9.4%
48.4%
Female
629,435
793,878
31,253
349,272
1,803,838
%
18.0%
22.7%
0.9%
10.0%
51.6%
Total
1,219,981
1,538,315
62,354
676,447
3,497,097
%
34.9%
44.0%
1.8%
19.3%
100.0%
Table 1: Population by race and gender for 2007
In all race groups the number of females is larger than the number of males (see Table 1).
Coloureds comprise 44.0% of the population, Black Africans 34.9%, Whites 19.3% and Asians
1.8%.
1996
2007
48.4% 48.1%
50%
44.0%
45%
40%
34.9%
35%
30%
2001
31.7%
25.1%
25%
21.2%
20%
18.8% 19.3%
15%
10%
5%
3.8%
1.5% 1.4% 1.8%
0%
Black African
Coloured
Asian
White
Unspecified
Figure 1: Population by race for 1996, 2001 and 2007
As can be seen from Figure 1 the percentage of Coloureds in Cape Town has declined by 4.4%
since 1996 while that for Black Africans has increased by 9.8%. The percentage of Whites
declined by 2.4% between 1996 and 2001 and then increased by 0.5% in 2007.
October 2008
Strategic Development Information and GIS Department
Page 6
2007 Community Survey Analysis for Cape Town
3.2
Age Distribution
80%
70%
60%
50%
40%
30%
20%
10%
0%
Male
Female Total
Male
Black African
0-14
Female Total
Male
Coloured
Female Total
Male
Asian
Female Total
Male
White
Female Total
Total
30.5% 29.3% 29.9% 28.3% 26.6% 27.4% 18.9% 20.6% 19.7% 16.0% 14.3% 15.1% 26.5% 25.1% 25.8%
15-64 67.8% 68.4% 68.1% 67.9% 67.9% 67.9% 77.0% 73.8% 75.4% 70.9% 70.9% 70.9% 68.6% 68.8% 68.7%
65+
1.7%
2.2%
2.0%
3.7%
5.5%
4.6%
4.1%
5.6%
4.9%
13.1% 14.8% 14.0%
4.8%
6.2%
5.5%
Figure 2: Age distributions by functional groups, race and gender for 2007
The percentage of youth (aged 0 to 14 years) in the different race groups decreases from 29.9%
for Black Africans to 15.1% for Whites while the aged (65 years and older) increase from 2.0% for
Black Africans to 14.0% for Whites (see Figure 2). The percentage of those who are in the
potentially economically active group (aged 15 to 64 years) is highest (75.4%) for Asians and
lowest for Coloureds (67.9%).
80%
70%
60%
50%
40%
30%
20%
10%
0%
1996
2001
2007
1996
Male
2001
2007
1996
Female
2001
2007
Total
0-14
29.2%
27.8%
26.5%
27.2%
25.6%
25.1%
28.2%
26.7%
25.8%
15-64
65.5%
68.2%
68.6%
66.0%
68.6%
68.8%
65.7%
68.4%
68.7%
65+
4.1%
4.1%
4.8%
5.9%
5.8%
6.2%
5.0%
5.0%
5.5%
Note: unspecified age in 1996 has been excluded
Figure 3: Age distributions by functional groups and gender for 1996, 2001 and 2007
Figure 3 shows that the percentage of the population in the potentially economically active group
(aged 15 to 64 years) has increased since 1996 while that of the youth (aged 0 to 14 years) has
decreased. The percentage of aged (65 years and older) remained constant from 1996 to 2001
and then increased in 2007. This shows that the age structure of the population is changing
October 2008
Strategic Development Information and GIS Department
Page 7
2007 Community Survey Analysis for Cape Town
putting increasing pressure on the need to create more job opportunities for the economically
active.
Race
Black African
Coloured
Asian
White
Unspecified
Total
1996
24.9
26.3
28.0
36.2
26.8
28.1
Mean Age
2001
25.0
27.7
29.2
37.1
28.6
2007
24.9
29.0
31.5
39.3
29.6
Median Age
1996
2001
2007
24
24
24
24
25
26
25
27
29
34
36
39
24
26
26
27
Note: unspecified age in 1996 has been excluded
Table 2: Mean and median age for 1996, 2001 and 2007
Since 1996 both the mean (average) and median (middle value) age of the population has
increased (See table 2). The mean and median age for all races has increased with the exception
of Black Africans where they have remained constant. With an ageing population additional
provision will have to be made to care for the aged.
Age
Group
0-5
6 - 12
13 - 17
18 - 34
35 - 54
55 - 64
65+
Total
Male
Number
%
192,956
5.5%
202,248
5.8%
148,697
4.3%
537,400
15.4%
425,138
12.2%
104,932
3.0%
81,888
2.3%
1,693,259
48.4%
Female
Number
%
193,910
5.5%
201,332
5.8%
149,498
4.3%
560,912
16.0%
462,065
13.2%
124,930
3.6%
111,191
3.2%
1,803,838
51.6%
Total
Number
%
386,866
11.1%
403,580
11.5%
298,195
8.5%
1,098,312
31.4%
887,203
25.4%
229,862
6.6%
193,079
5.5%
3,497,097 100.0%
Table 3: Age distribution by gender for 2007
There are more females than males in all age groups except those aged 6 to 12 years but the
difference in the number of males and females is small for all those under 17 years (see Table 3).
Of the total population 11.1% are under the age of six years, 11.5% are aged 6 to 12 years and
8.5% are aged 13 to 17 years.
The percentages for the different race groups vary significantly (see Appendix 6). For those aged
under 13 years Black Africans are the highest with 14.4% under six years and 12.6% aged 6 to 12
years and Whites the lowest with 5.9% under six years and 7.0% aged 6 to 12 years. For
Coloureds 10.9% are under six years and 12.8% are aged 6 to 12 years. Those aged 13 to 17
years range from 9.7% for Coloureds to 6.2% for Whites. This high percentage of young people
puts additional pressure on the economically active group to support them particularly for Black
Africans and Coloureds.
The population aged 18 to 54 years is the highest for Asians at 63.6%, followed by Black Africans
at 59.5% and Coloureds at 55.8% with Whites the lowest at 53.6%. The White population has a
relatively low percentage (23.4%) for those aged 18 to 34 years which indicates that this is the
group that has probably experienced the highest levels of emigration. 27.3% of the White
population are over 54 years, followed by 12.7% for Asians, 11.5% for Coloureds and only 5.2% for
Black Africans.
October 2008
Strategic Development Information and GIS Department
Page 8
2007 Community Survey Analysis for Cape Town
2001
1996
Male Female
Male Female
85+
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
85+
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
-6% -5% -4% -3% -2% -1% 0% 1% 2% 3% 4% 5% 6%
-6% -5% -4% -3% -2% -1% 0% 1% 2% 3% 4% 5% 6%
Note: Unspecified age has been excluded
Figure 4: Population pyramid for 1996
Figure 5: Population pyramid for 2001
2007
Male Female
85+
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
-6% -5% -4% -3% -2% -1% 0% 1% 2% 3% 4% 5% 6%
Figure 6: Population pyramid for 2007
The shapes of the population pyramids show trends in fertility, mortality and migration (see figures
4, 5 and 6). For Cape Town migration has a significant impact on the shape of the pyramid with
those in the age groups 20 to 34 moving into Cape Town in search of work. More recently there
has been a trend for secondary school learners from the Eastern Cape to come to the schools in
October 2008
Strategic Development Information and GIS Department
Page 9
2007 Community Survey Analysis for Cape Town
Cape Town with an increase in the 15 to 19 age group in 2001 and an even bigger increase in
2007.
3.3
Migration
68.4%
70%
60%
50%
40%
30%
20%
19.4%
10%
0.7%
3.3%
1.5%
0.2%
0.2%
1.6%
4.0%
0.3%
0%
Eastern
Cape
Free State
Gauteng
Kw aZuluNatal
Limpopo Mpumalanga Northern North West
Cape
Western
Cape
Outside
RSA
Figure 7: Place of birth of Cape Town residents for 2007
In 2007 the place of birth of 68.4% of Cape Town residents was the Western Cape, with 19.4%
having been born in the Eastern Cape, 3.3% in Gauteng and 4.0% outside of South Africa (see
Figure 7). For the different races the percentages that were born in the Western Cape vary from
94.2% for Coloureds to 42.3% for Black Africans with 67.0% for Asians and 57.0% for Whites.
October 2008
Strategic Development Information and GIS Department
Page 10
2007 Community Survey Analysis for Cape Town
Black African
Coloured
Asian
White
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Eastern
Cape
Free State
Gauteng
Kw aZuluNatal
Limpopo
Mpumalanga
Northern
Cape
North West
Outside
RSA
Figure 8: Place of birth (excluding Western Cape) of Cape Town residents by race for 2007
Figure 8 shows the place of birth of Cape Town residents other than the Western Cape. For Black
Africans the highest percentage were born in the Eastern Cape (49.8%), with 2.9% born outside
South Africa and 1.7% in Gauteng. 14.2% of Whites were born outside of South Africa, 12.9% in
Gauteng and 5.0% in the Eastern Cape. For Asians 13.7% were born in KwaZulu-Natal, 11.1%
outside of South Africa, 3.3% in the Eastern Cape and 2.9% in Gauteng. Very small numbers of
Coloureds were born outside of the Western Cape with 2.1% having been born in the Eastern
Cape and 1.9% in the Northern Cape.
50%
44.9%
45%
40%
35%
30%
25%
20%
19.5%
17.3%
15%
10%
6.2%
5%
2.0%
1.7%
1.3%
2.8%
3.5%
0.8%
0%
Eastern
Cape
Free State
Gauteng
Kw aZuluNatal
Limpopo Mpumalanga Northern North West
Cape
Outside
RSA
Unknow n
Figure 9: Province from which people moved into Cape Town since October 2001
October 2008
Strategic Development Information and GIS Department
Page 11
2007 Community Survey Analysis for Cape Town
A total of 190,256 people moved into Cape Town after October 2001 from all provinces other than
the Western Cape as well as from outside of South Africa. This includes 30,964 who were born
after October 2001 and whose place of birth was not the Western Cape. From the data available it
is not possible to determine the number of people who moved into Cape Town from other areas of
the Western Cape. Of those moving from outside the Western Cape 44.9% came from the Eastern
Cape, 19.5% from outside of South Africa and 17.3% from Gauteng (see Figure 9). For the
different race groups the province from which they moved into Cape Town varies significantly with
68.6 % of Black Africans coming from the Eastern Cape and 11.2% from outside of South Africa.
For Coloureds 24.2% came from Gauteng and 23.0% from the Eastern Cape. 37.3% of Asians
came from KwaZulu-Natal and 34.6% from Gauteng. The highest percentage (36.8%) of Whites
came from outside of South Africa and 31.2% from Gauteng. Additional details can be found in
Appendix 7.
Oct 1996 to Sep 2001
Oct 2001 to Feb 2007
120,000
Number of People
100,000
80,000
60,000
40,000
20,000
0
Eastern
Cape
Free State
Gauteng
Kw aZuluNatal
Limpopo
Mpumalanga
Northern
Cape
North West
Figure 10: Number of people moving into Cape Town from other South African Provinces
As can be seen from Figure 10 the number of people moving into Cape Town from other provinces
in South Africa declined from the period October 1996/September 2001 to October 2001/February
2007. With the exception of Limpopo and Mpumalanga the decrease is substantial. During both
periods the largest number came from the Eastern Cape followed by Gauteng. The number of
people in the period October 2001/February 2007 excludes those born after October 2001.
October 2008
Strategic Development Information and GIS Department
Page 12
2007 Community Survey Analysis for Cape Town
16%
14.8%
14.4%
14%
12.8%
12%
10.2%
10%
8.3%
8%
7.0%
6.7%
5.7%
6%
4.4%
4%
3.7%
2.8% 3.0%
2%
1.9% 1.9% 2.3%
0%
0-4
5-9
9-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69
70+
Age in years
Figure 11: Age of people moving into Cape Town from outside the Western Cape
The highest percentage (37.9%) of people moving into Cape Town, from outside the Western,
Cape is aged 20 to 34 years with 14.8% aged 20 to 24 years (see Figure 11). There is also a
relatively large percentage (14.4%) aged 0 to 4 years moving into Cape Town and 62.2% of these
are coming from the Eastern Cape. This indicates that a large proportion of those moving to Cape
Town are coming in search of work particularly from the Eastern Cape and that they are bringing
young children with them but leaving older children in the care of the extended family.
3.4
Disabilities
Statistics South Africa defines a disability as “a physical or mental handicap which has lasted for
six months or more, or is expected to last at least six months, which prevents the person from
carrying out daily activities independently, or from participating fully in educational, economic or
social activities.”
In 2007 there were 114,297 people in Cape Town with disabilities and is 3.5% of the total
population. The number of disabled people has increased from 107,837 in 2001 when the
percentage of the total population was 3.7%. This percentage decrease has occurred for all races,
except Asians, with Whites having the largest decrease falling from 4.7% in 2001 to 3.5% in 2007.
The percentage of disabled Black Africans fell from 3.4% in 2001 to 3.1% in 2007 and Coloureds
from 3.8% in 2001 to 3.5% in 2007. Asian disabled increased from 3.2% in 2001 to 3.5% in 2007.
October 2008
Strategic Development Information and GIS Department
Page 13
2007 Community Survey Analysis for Cape Town
Black African
Coloured
Asian
White
Total
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Sight
Hearing
Communication
Physical
Intellectual
Emotional
Multiple
Disabilities
Figure 12: Disabilities by race for 2007
The type of disability is shown in Figure 12. Physical disability is the highest for all races with
Asians the highest at 44.9% and Black Africans the lowest at 32.1%. The opposite is the case for
multiple disabilities with 22.9% for Black Africans and 3.0% for Asians. Whites have the highest
percentage (10.7%) with a hearing disability while Asians have the highest percentages for sight
disability (11.0%), communication disability (9.5%) and intellectual disability (14.3%). Black
Africans have the highest percentage (18.1%) for emotional disability. Details of disabilities by
race and gender can be found in Appendix 8.
October 2008
Strategic Development Information and GIS Department
Page 14
2007 Community Survey Analysis for Cape Town
4
4.1
Education
Educational Institution Attendance
The analysis focuses on the 5 to 24 year age group as it is this age group that is most likely to be
attending an educational institution. A child may be admitted to Grade 1 should they turn six by 30
June and attendance is compulsory once they are seven. Schooling is also compulsory to the age
of 15. In 2007 64.0% of this age group were attending an educational institution which is lower
than that for 2001 (66.3%). In 1996 64.9% were attending an educational institution.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
1996 16.2 52.0 85.8 91.5 94.5 95.8 96.8 97.2 96.9 95.8 93.4 88.0 79.3 64.2 47.9 38.1 31.2 24.8 19.0 15.8
2001 48.3 73.8 91.7 95.2 96.3 96.6 96.5 96.8 96.2 94.5 90.6 84.5 76.5 60.7 44.3 33.4 26.6 20.0 15.4 12.1
2007 54.0 87.7 93.5 94.7 93.9 94.8 93.9 94.0 93.5 92.8 90.3 84.6 72.3 51.0 43.8 30.0 24.0 19.0 14.2 7.9
Age in Years
Figure 13: Attendance at an educational institution by age for 1996, 2001 and 2007
As can be seen from figure 13 there has been a decrease in the percentage attending an
educational institution for all ages from 11 years since 1996 and for all ages from 8 years since
2001. Those aged 18 years shows the largest decrease. As the figures for 2007 are based on a
sample survey, variations within age groups could be attributed to a relatively low number
surveyed in each of the age groups particularly for ages 8 to 15 years. For those aged 16 to 18
years reasons for not attending an educational institution include having no money for fees,
already working, looking after younger family members following death of parents and pregnancy.
There has been a large increase in the percentage of five and six year olds attending and this can
be attributed to the lowering of the school going age to five years in 2003. For all age categories
from 7 to 15 years attendance was over 90% in 2007.
October 2008
Strategic Development Information and GIS Department
Page 15
2007 Community Survey Analysis for Cape Town
1996
2001
80%
70%
2007
72.5%
62.9% 64.1% 63.6%
63.9% 65.1%
76.1%
75.6%
70.4%
70.6%
72.0%
61.8%
60%
50%
40%
30%
20%
10%
0%
Black African
Coloured
Asian
White
Figure 14: Attendance at an educational institution by race for 1996, 2001 and 2007
The percentage attending an educational institution in the 5 to 24 age group increased from 1996
to 2001 and then decreased in 2007 (see Figure 14). For Black Africans and Whites the
percentage in 2007 was higher than that in 1996 while for Coloureds and Asians the lowest
percentage was in 2007.
60%
50%
40%
30%
20%
10%
0%
Pre-school
Primary school
Secondary
school
College
University/
Technikon
Other
Black African
3.9%
47.9%
41.7%
2.5%
3.3%
0.6%
Coloured
4.3%
51.5%
38.0%
2.5%
3.1%
0.7%
Asian
4.3%
36.0%
29.8%
3.9%
23.3%
2.8%
White
4.0%
37.1%
36.3%
5.3%
16.2%
1.0%
Total
4.1%
47.7%
39.0%
3.0%
5.5%
0.7%
Figure 15: Type of educational institution attended by race for 2007
For those aged 5 to 24 years 4.1% are attending pre-school with almost no variation for the
different races (see Figure 15). Coloureds have the highest percentage (51.5%) attending primary
school and Black Africans the highest (41.7%) attending secondary school. Asians have the
highest percentage (23.3%) attending a university or technikon followed by Whites at 16.2%. 5.3%
of Whites attend a college.
October 2008
Strategic Development Information and GIS Department
Page 16
2007 Community Survey Analysis for Cape Town
4.2
Adult level of Education
Educational attainment is important for those seeking to be employed and thus the level of
education completed for adults (those 20 years and older) is important.
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
No
schooling
Grade 0 - 3 Grade 4 - 7
Grade 8 11
Grade 12
Certificate/
Diploma
Degree
Unspecified
1996
4.2%
1.8%
17.9%
37.5%
19.6%
9.0%
4.6%
5.3%
2001
4.2%
2.4%
16.5%
38.1%
25.4%
7.9%
5.5%
0.0%
2007
2.0%
2.9%
14.3%
40.1%
20.9%
9.6%
8.8%
1.4%
Figure 16: Highest level of education obtained by adults for 1996, 2001 and 2007
Figure 16 shows that the percentage of those 20 years and older with no education has decreased
from 4.2% in 1996 to 2.0% in 2007 and the percentage with a degree has increase from 4.6% to
8.8% in the same period. From 1996 to 2007 those completing Grade 4 to Grade 7 has shown a
steady decrease while those completing Grade 8 to Grade 11 show a steady increase suggesting
that more are now completing at least some secondary school than previously. The percentage
that completed Grade 12 decreased from 2001 to 2007 but there was an increase in the number
who completed a certificate, diploma or degree indicating that more learners who complete Grade
12 are studying at a tertiary institution.
Since 1996 there had been a significant decrease in adults with no schooling across all races with
Coloureds having the largest decrease from 8.2% to 2.3%. Black Africans decreased from 8.2% to
2.7%, Asians from 3.6% to 1.7% and Whites from 0.8% to 0.3%. Over the same period there has
been a steady increase in higher education across all population groups. The percentage with a
certificate, diploma or degree is highest for Whites having increased from 22.2% in 1996 to 45.2%
in 2007. Asians increased from 18.8% to 34.9%, Black Africans from 4.2% to 10.3% and
Coloureds from 4.2% to 9.4%. In particular the number of Black African adults with a degree
increased from 1.3% to 3.3%, Coloureds from 1.3% to 2.8%, Asians from 8.8% to 23.2% and
Whites from 12.9% to 26.4%. Additional information can be found in Appendix 9.
October 2008
Strategic Development Information and GIS Department
Page 17
2007 Community Survey Analysis for Cape Town
Black African
Coloured
Grade 4 - 7
Grade 8 - 11
Asian
White
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
No schooling
Grade 0 - 3
Grade 12
Certificate/
Diploma
Degree
Figure 17: Highest level of education amongst adults by race 2007
The highest level of education attained by adults show significant variation for the different races in
2007 (see Figure 17). Whites have the highest percentage with degrees (26.4%), certificate or
diploma (18.8%) and Grade 12 (32.7%) followed by Asians with 23.2%, 11.7% and 25.4%
respectively. For those with Grade 8 to Grade 11 Black Africans are the highest with 46.9%
followed by Coloureds at 46.5%. 22.8% of Black Africans and 21.7% of Coloureds only have a
primary school education.
October 2008
Strategic Development Information and GIS Department
Page 18
2007 Community Survey Analysis for Cape Town
5
Employment
In their evaluation of the Community Survey the Stats Council raised the concern that the measure
of unemployment is higher and less reliable than that in the Labour Force Surveys as there were
differences in the way the questions were asked. The employment status figures, and particularly
those for unemployment, should thus be used with caution particularly when looking at trends in
Cape Town.
When looking at employment only the potential labour force has been analysed. These are all
persons aged 15 to 65 years and who do not reside in an institution (a communal place of
residence for people with a common characteristic, such as a hospital, school hostel, home for the
disabled, prison, defence force barracks or convent).
In order to be classified as unemployed, a person must satisfy the following three criteria:
- The person did not work during the seven days prior to the survey interview, and does not
have any job attachment;
- The person wants to work and is available to start work within two weeks;
- The person has taken active steps to look for work or to start own business in the four weeks
prior to the interview.
5.1
Employment Status
In Cape Town 52.5% of the labour force was employed in February 2007, 17.0% unemployed and
28.4% not economically active. Gender variations do exist with 59.1% of males and 46.4% of
females employed, 16.3% of males and 17.6% of females unemployed and 22.5% of males and
34.0% of females not economically active. Information on the official unemployment rate is given
in section 5.6.
Employed
Unemployed
Not economically active
Unspecified
80%
70%
60%
50%
40%
30%
20%
10%
0%
Male
Female
Black African
Total
Male
Female
Coloured
Total
Male
Female
Total
Asian
Male
Female
Total
White
Figure 18: Employment status by race and gender for 2007
Whites have the highest percentage (67.7%) employed and the lowest percentage (3.1%)
unemployed while the opposite is true for Black Africans where 43.8% are employed and 28.9%
unemployed. For Coloureds 52.3% are employed and 14.6% are unemployed and for Asians
56.8% are employed and 6.0% unemployed. As can be seen from Figure 18 more males than
females are employed and more females than males are not economically active across all the
race groups. For Black Africans more females (31.3%) than males (26.2%) are unemployed as
well as Asians where 7.8% of females and 4.4% of males are unemployed. The opposite is true
for Coloureds where 15.3% of males and 13.9% of females are unemployed. For Whites the
percentage unemployed for both males and females is 3.1%. Across all races the percentages for
October 2008
Strategic Development Information and GIS Department
Page 19
2007 Community Survey Analysis for Cape Town
those not economically active is always higher for females than for males with Asian females the
highest (39.7%) and White males the lowest (21.0%).
5.2
Work Status
Of all those who are employed 82.9% are paid employees, 10.6% are self-employed, 1.2% are
employers and 1.3% are family workers not all of which are paid.
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Paid employee
Paid family
worker
Self-employed
Employer
Unpaid family
worker
Unspecified
Black African
85.7%
0.8%
7.4%
0.2%
0.5%
5.4%
Coloured
87.6%
0.9%
6.2%
0.9%
0.3%
4.2%
Asian
73.4%
0.7%
15.5%
3.4%
2.4%
4.6%
White
72.3%
0.8%
21.1%
2.6%
0.3%
2.9%
Figure 19: Work status by race for 2007
For all races paid employees have the highest percentage with Coloureds the highest (87.6%) and
Whites the lowest (72.3%) (see Figure 19). Whites have the highest percentage (21.1%) who are
self-employed and Coloureds the lowest (6.2%). Asians have the highest percentage of employers
(3.4%) and also the highest percentage of unpaid family workers (2.4%).
5.3
Occupation
Male
Female
Total
25%
20%
15%
10%
5%
Unspecified
and not
elsewhere
classified
Elementary
occupations
Plant and
machine
operators and
assemblers
Craft and
related trades
workers
Service
workers,
shop and
market sales
Skilled
agricultural
and fishery
workers
Clerks
Technicians
and associate
professionals
Professionals
Legislators,
senior
officials and
managers
0%
Figure 20: Occupation by gender for 2007
October 2008
Strategic Development Information and GIS Department
Page 20
2007 Community Survey Analysis for Cape Town
For those employed the occupations of 22.6% were either unspecified or not classified into one of
the nine categories. The occupation having the largest percentage (13.5%) was elementary
occupations followed by professionals (11.5%), craft and related trade workers (10.5%) and
legislators, senior officials and manages (10.2%) (see Figure 20). Females have the highest
percentages for elementary occupations (18.0%), clerks (13.9%) and professionals (13.4%) while
males are highest for craft and related trade workers (15.6%), legislators, senior officials and
managers (11.2%), elementary occupations (9.8%) and professionals (9.8%).
Black African
Coloured
Asian
White
30%
25%
20%
15%
10%
5%
Unspecified
and not
elsewhere
classified
Elementary
occupations
Plant and
machine
operators and
assemblers
Craft and
related trades
workers
Service
workers,
shop and
market sales
Skilled
agricultural
and fishery
workers
Clerks
Technicians
and associate
professionals
Professionals
Legislators,
senior
officials and
managers
0%
Figure 21: Occupation by race for 2007
As can be seen from Figure 21 there are significant variations in occupation by race. For Whites
the occupation with the highest percentage is legislators, senior officials and managers (20.7%)
followed by professionals (18.8%) and technicians and associated professionals (11.2%). Asians
have the highest percentages in the same three categories with 23.1% for professionals, 17.2% for
legislators, senior officials and managers and 9.3% for technicians and associated professionals.
Craft and related trade workers is the highest (13.5%) for Coloureds followed by elementary
occupations (13.1%) and clerks (10.9%). For Black Africans 25.6% are in elementary occupations,
13.4% are service workers, shop and market sales workers and 11.5% are craft and related trade
workers.
Looking at highest level of education attained and occupations Black Africans and Coloureds tend
to be employed in elementary and less skilled occupations and have attained lower levels of
education where as far more Asians and Whites are employed in more skilled occupations and
have attained higher levels of education. Levels of education attained thus need to be increased in
order to increase those employed in the more skilled occupations which will lead to improved
standards of living.
October 2008
Strategic Development Information and GIS Department
Page 21
2007 Community Survey Analysis for Cape Town
Male
Female
Total
Transport,
storage and
communication
Industry
Wholesale and
retail trade
5.4
30%
25%
20%
15%
10%
Unspecified
Other and not
adequately
defined
Construction
Electricity, gas
and water
supply
Manufacturing
Mining and
quarrying
Agriculture,
hunting,
forestry and
fishing
0%
Financial,
insurance, real
estate and
business
Community,
social and
personal
services
5%
Figure 22: Industry by gender for 2007
The industry having the highest percentage of those employed is manufacturing (14.9%) followed
by wholesale and retail trade (14.6%), financial, insurance real estate and business services
(12.9%) and community, social and personal services (12.8%) (see Figure 22). The highest
percentages of females are employed in the same four industrial categories with community, social
and personal services the highest at 16.9% followed by wholesale and retail trade at 16.4%. For
males the highest percentage (16.9%) are employed in manufacturing with wholesale and retail
trade second at 13.2% and financial, insurance, real estate and business services third at 13.0%.
Black African
Coloured
Asian
White
30%
25%
20%
15%
10%
Unspecified
Other and not
adequately
defined
Wholesale and
retail trade
Construction
Electricity, gas
and water
supply
Manufacturing
Mining and
quarrying
Agriculture,
hunting,
forestry and
fishing
0%
Transport,
storage and
communication
Financial,
insurance, real
estate and
business
Community,
social and
personal
services
5%
Figure 23: Industry by race for 2007
Figure 23 shows the industries for those employed by race. For Black Africans the highest
percentage (15.3%) is in wholesale and retail trade and 11.9% are in manufacturing. Black
Africans also have a high percentage (13.1%) in the “other and not adequately defined” category.
Manufacturing, at 18.1%, is the highest for Coloureds followed by wholesale and retail trade at
October 2008
Strategic Development Information and GIS Department
Page 22
2007 Community Survey Analysis for Cape Town
16.1% and community, social and personal services at 13.3%. For Whites and Asians financial,
insurance, real estate and business services are the highest at 18.8% and 17.2% respectively.
Asians also have a high percentage (17.1%) in wholesale and retail trade. For Whites, 15.0% are
in community, social and personal services and 13.0% in manufacturing.
5.5
Income of Employed
Male
Female
Total
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
Response
not given
R204,801
or more
R102,401 R204,800
R51,201 R102,400
R25,601 R51,200
R12,801 R25,600
R6,401 R12,800
R3,201 R6,400
R1,601 R3,200
R801 R1,600
R401 R800
R1 - R400
No income
0%
Figure 24: Monthly income of the employed by gender for 2007
For those employed 26.8% earn less than R1,601 per month, 18.2% earn between R1,601 and
R3,200 per month, 14.7% earn between R3,201 and R6,400 per month and 23.2% earn more than
R6,400 per month. 17.1% did not give any response to the question on monthly income. This is
the norm in surveys of this nature as some people are reluctant to disclose their income. In all the
categories below R12,800 there are more females than males with the exception of R1,601 to
R3,200 where there are 18.8% males and 17.4% females. This category also has the highest
percentage of any of the categories (see Figure 24). In all categories above R12,000 there are
more males than females.
Black African
Coloured
Asian
White
35%
30%
25%
20%
15%
10%
5%
Response
not given
R204,801
or more
R102,401
R204,800
R51,201 R102,400
R25,601 R51,200
R12,801 R25,600
R6,401 R12,800
R3,201 R6,400
R1,601 R3,200
R801 R1,600
R401 R800
R1 - R400
No
income
0%
Figure 25: Monthly income of the employed by race for 2007
October 2008
Strategic Development Information and GIS Department
Page 23
2007 Community Survey Analysis for Cape Town
Monthly income by race is shown in Figure 25. Only 8.1% of Black Africans did not give a
response to income as compared to over 20% for all the other races. For Black Africans 30.6%
earn between R801 and R1,600, 25.5% earn between R1,601 and R3,200 and 11.2% between
R401 and R800. Coloureds show a small improvement with 20.9% earning between R1,600 and
R3,200, 18.6% earning between 3,201 and R6,400 and 14.4% earning between R801 and R1,600.
The highest percentage for both Asians and Whites is between R6,401 and R12,800 with 20.1%
and 21.3% respectively. For Asians 19.1% earn between R3,201 and R6,400 and 11.7% between
R12,801 and R25,600. 17.9% of Whites earn between R12,801 and R25,600 and 14% between
R3,201 and R6,400. For Whites 13.3% earn more than R25,600 as compared to 10.0% for
Asians, 1.5% for Coloureds and 1.2% for Black Africans.
5.6
Unemployment Rate
When calculating the official unemployment rate only the economically active population, those
aged 15 to 65 who are employed or unemployed, are taken into account.
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Black African
Coloured
Asian
White
Total
Male
34.3%
20.6%
6.4%
4.0%
21.7%
Female
45.3%
23.1%
13.5%
4.8%
27.6%
Total
39.7%
21.8%
9.6%
4.4%
24.5%
Figure 26: Unemployment by race and gender for 2007
In February 2007 the unemployment rate for Cape Town was 24.5%. Across all races the
unemployment rate is higher for females than males with Black Africans showing the largest
difference and Whites the smallest (see Figure 26). The unemployment rate for Black Africans is
the highest (39.7%), followed by Coloureds (21.8%) and then Asians (9.6%) with Whites the lowest
(4.4%).
October 2008
Strategic Development Information and GIS Department
Page 24
2007 Community Survey Analysis for Cape Town
60%
50%
40%
30%
20%
10%
0%
Black African
Coloured
Asian
White
Total
1996
37.9%
17.7%
10.7%
4.1%
19.6%
2001
49.7%
24.5%
12.0%
4.7%
29.2%
2007
39.7%
21.8%
9.6%
4.4%
24.5%
Figure 27: Unemployment by race for 1996, 2001 and 2007
For all races the unemployment rate was highest in 2001 with that for Black Africans reaching
49.7% (see Figure 27). Black Africans, Coloureds and Whites had the lowest unemployment rates
in 1996 of 37.9%, 17.7% and 4.1% respectively. Between 2001 and 2007 the unemployment rate
for Black Africans decreased by 10.0% and that for Coloureds by 2.7%. Asians had their lowest
unemployment rate (9.6%) in 2007. The unemployment rate for Whites showed little variation.
October 2008
Strategic Development Information and GIS Department
Page 25
2007 Community Survey Analysis for Cape Town
6
Social Grants
Of the total population of Cape Town 13.0% are receiving social grants. Black Africans have the
highest percentage (19.3%) receiving these grants followed by Coloureds with 12.0%, Asians with
6.0% and Whites with 4.4%.
Black African
Coloured
Asian
White
Total
80%
70%
60%
50%
40%
30%
20%
10%
0%
Care
Child support
Foster care
dependency
grant
grant
grant
Old age
pension
Disability
grant
Grant in aid
Social relief
Multiple
social grants
Black African
10.1%
9.8%
73.9%
2.0%
0.2%
1.4%
0.4%
2.1%
Coloured
37.4%
20.6%
35.4%
3.2%
0.5%
1.1%
0.6%
1.2%
Asian
57.8%
29.2%
White
69.2%
22.4%
11.5%
1.6%
0.0%
0.0%
0.0%
0.0%
1.3%
1.2%
0.8%
2.5%
0.3%
2.3%
Total
25.5%
15.2%
53.0%
2.5%
0.3%
1.3%
0.5%
1.8%
Figure 28: Social grants by race for 2007
For those who do receive social grants the highest percentage (53.0%) receive child support
grants, followed by old age pensions (25.5%) and disability grants (15.2%) (see Figure 28). The
type of grants received by the different races vary greatly with 73.9% of Black Africans receiving
child support grants compared to 35.4% for Coloureds 11.5% for Asians and only 1.3% for Whites.
The opposite occurs for old age pensions with 69.2% of Whites, 57.8% of Asians, 37.4% of
Coloureds and 10.1% of Black Africans receiving this grant. Asians have the highest (29.2%) and
Black Africans the lowest (9.8%) percentage of disability grants.
October 2008
Strategic Development Information and GIS Department
Page 26
2007 Community Survey Analysis for Cape Town
7
7.1
Households
Household Distribution
The Community Survey estimates the number of households in Cape Town to be 902,279. This is
an increase of 18.8% since Census 2001 and 38.2% since Census 1996.
In South Africa the number of households increased by 11.6% between 2001 and 2007. The
number of households in the Western Cape increased by 16.7% with 72.9% of this increase
occurring in Cape Town. Other Western Cape municipalities showing a large percentage increase
between 2001 and 2007 include Bitou (44.3%), Mossel Bay (41.3%), Stellenbosch (25.5%),
Overstrand (18.2%) and Knysna (18.2%). Details for all Western Cape municipalities can be found
in Appendix 10 and a map showing their location in Appendix 4.
Since 1996 the number of households in Cape Town having an Black African household head
have shown a large increase (92.3%). Households having a White household head increased by
26.4% and those having a Coloured household head by 21.5%.
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
Black African
Coloured
Asian
White
Unspecified
1996
25.7%
39.8%
1.3%
29.9%
3.3%
2001
32.3%
39.9%
1.3%
26.5%
0.0%
2007
35.8%
35.0%
1.9%
27.3%
0.0%
Figure 29: Households by race of household head for 1996, 2001 and 2007
The percentage of households in each of the race groups is shown in Figure 29. Since 1996 Black
African headed households have increased from 25.7% to 35.8% while Coloured headed
households decreased from 39.8% to 35.0%. Households with a White household head
decreased from 1996 to 2001 and then increased in 2007.
7.2
Household Size
The average household size in Cape Town has shown little change being 3.9 in 1996, 3.7 in 2001
and 3.9 in 2007. Households with Coloured household heads have consistently had the largest
average household size and increase from 4.5 in 2001 to 4.9 in 2007. Asian headed households
have shown the largest decrease in average household size from 4.3 in 1996 to 3.7 in 2007. Black
African headed households had an average household size of 3.8 in both 1996 and 2007and 3.6 in
2001. White headed households have the lowest average household size decreasing from 2.8 in
1996 to 2.7 in 2007.
October 2008
Strategic Development Information and GIS Department
Page 27
2007 Community Survey Analysis for Cape Town
Black African
Coloured
Asian
White
Total
40%
35%
30%
25%
20%
15%
10%
5%
0%
01
02
03
04
05
06
07
08
09
10+
Figure 30: Household size by race of household head for 2007
For 2007 83.2% of households have five people or less, with two persons per household the
highest at 20.8% (see Figure 30). Significant variations occur between the races where the race of
the head of the household determines the race group for the household. For White households
91.7% have less than five persons with two persons per household being the highest at 35.2%.
Starting at four persons per household, Coloured households consistently have the largest
percentage with the highest percentage (24.0%) at four persons. Only 4.5% of Coloured
households have one person. Black households also have a relatively large percentage of one
(14.9%) and two (18.1%) person households.
October 2008
Strategic Development Information and GIS Department
Page 28
2007 Community Survey Analysis for Cape Town
8
8.1
Housing
Dwelling Type
Formal
Informal
Other
100%
90%
80%
83.0%
78.9%
77.4%
70%
60%
50%
40%
30%
20%
19.2%
10%
18.8%
3.3%
15.6%
2.2%
1.4%
0%
1996
2001
2007
Figure 31: Dwelling type for 1996, 2001 and 2007
Note: Informal include shacks not in back yards as well as those in back yards.
Other includes traditional dwellings, caravans, tents, private ships and workers’ hostels.
The percentage of households living in formal dwellings has increased from 77.4% in 1996 to
83.0% in 2007 while those living in informal dwellings fell from 19.2% to 15.6% over the same
period (see Figure 31). Although the percentage of households living in informal dwelling
decreased the actual number increased from 125,233 in 1996 to 142,910 in 2001 and then
decreased to 140,605 in 2007.
The percentage of Black African households living in formal dwellings has doubled while those
living in informal dwellings have decreased from 64.8% to 37.6%. There has been almost no
change in the percentage of Coloured and Asian households living in informal dwelling but the
percentage for While households has increased from 0.1% to 0.5%. Details of dwelling type by
race can be found in Appendix 11.
October 2008
Strategic Development Information and GIS Department
Page 29
2007 Community Survey Analysis for Cape Town
120,000
110,109
108,899
103,458
100,000
84,300
Informal dwelling / shack
in back yard (Statistics SA)
80,000
Informal dwelling / shack
NOT in back yard
(Statistics SA)
Informal Settlement Count
(SDI&GIS Department)
56,305
60,000
40,000
32,801
21,775
20,000
0
1996
2001
2007
Figure 32: Informal dwellings for 1996, 2001 and 2007
Informal dwellings in back yards have shown a steady increase from 21,775 in 1996 to 56,305 in
2007 (see Figure 32). However there is a need for caution when interpreting the 2007 figures for
informal dwellings not in back yards as the number for 2007 is significantly lower than that for 2001
and yet the number of dwellings in informal settlements has increased. The 2007 count of
dwellings in informal settlement was done from aerial photographs taken in January 2007 and
108,899 were counted (Strategic Development Information & GIS Department). The number of
informal dwellings not in back yards is thus underestimated in the Community Survey as the
number should be larger than that counted from aerial photographs.
Black African
Coloured
Asian
White
Total
80%
70%
60%
50%
40%
30%
20%
Other
Workers hostel
Room/flatlet not in
back yard but on
a shared property
Informal
dwelling/shack
NOT in back yard
Informal
dwelling/shack in
back yard
House/flat/room in
back yard
Town/cluster/sem
i-detached house
Flat in block of
flats
House or brick
structure on a
separate stand or
yard
0%
Traditional
dwelling
10%
Figure 33: Dwelling type for 2007
For all races the percentage living in a house of brick structure on a separate stand or yard in 2007
was the largest with Asians the highest at 78.5% and Black Africans the lowest at 48.0% (see
Figure 33). Black Africans have the highest percentages living in informal dwellings with 24.0% in
informal settlements and 13.6% in back yards. 13.5% of Whites and 12.9% of Asians live in a flat
in a block of flats while 7.0% of Whites and 4.3% of Asians live in a town/cluster/semi-detached
house. For Coloureds 9.1% live in a town/cluster/semi-detached house.
October 2008
Strategic Development Information and GIS Department
Page 30
2007 Community Survey Analysis for Cape Town
8.2
Tenure
1996
90%
2001
2007
84.2%
80%
68.4% 66.0%
70%
69.3%
67.9% 69.2% 70.4%
69.8%
74.5%
77.6%
72.9%
60.7%
63.9%
60%
50%
47.9%
42.2%
40%
30%
20%
10%
0%
Black African
Coloured
Asian
White
Total
Figure 34: Dwellings owned by race for 1996, 2001 and 2007
As can be seen from Figure 34 the percentage of households who own their dwelling has shown a
steady increase for both Whites and Asians.
Owned and fully paid off
Owned but not yet paid off
Rented
Occupied rent-free
Other
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
2001
2007
Black African
2001
2007
Coloured
2001
2007
Asian
2001
2007
White
2001
2007
Total
Figure 35: Dwelling tenure by race for 2001 and 2007
For all races the percentage of households whose dwellings are owned and fully paid off increased
between 2001 and 2007 while those owned and not yet fully paid off declined (see Figure 35).
Black Africans have the highest percentage of dwellings owned and fully paid off (41.1%) followed
by Whites (40.8%). Black Africans have the highest percentage occupying dwellings rent free
decreasing from 37.4% in 2001 to 28.1% in 2007. Between 2001 and 2007 the percentage of
households living in rented dwellings fell for all races except Black Africans with Coloureds having
the largest decrease (4.8%). Black African households living in rented dwellings increased by
2.3%.
October 2008
Strategic Development Information and GIS Department
Page 31
2007 Community Survey Analysis for Cape Town
9
9.1
Services
Energy Sources
Lighting
Cooking
Heating
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Electricity
Gas
Paraffin
Wood
Coal
Candles
Solar
Other
Figure 36: Energy sources for lighting, cooking and heating in 2007
Electricity is the fuel used by over 80% of all households in Cape Town with 94.4% using it for
lighting, 89.5% for cooking and 80.4% for heating (see Figure 36). Paraffin is the next most
commonly used fuel with 14.7% of households using it for heating, 6.0% for cooking and 4.0% for
lighting. Gas is used by 4.3% of households for cooking and 1.8% for heating. 0.9% of
households use candles for lighting and 1.2% use wood for heating.
When taking into account the race of household heads different patterns of energy sources
emerge. Over 91% of Coloured, Asian and White households use electricity for lighting, cooking
and heating while 87.0% of Black Africans households use it for lighting, 78.1% for cooking and
56.7% for heating. Black African households use a significant amount of paraffin with 39.0% using
it for heating, 15.7% using it for cooking and 10.7% using it for lighting. Further information can be
found in Appendix 12.
October 2008
Strategic Development Information and GIS Department
Page 32
2007 Community Survey Analysis for Cape Town
Electricity
Paraffin
Candles
Other
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1996
2001
2007
1996
Black African
2001
2007
1996
Coloured
2001
2007
1996
Asian
2001
2007
1996
White
2001
2007
Total
Electricity 57.0% 69.4% 87.0% 95.5% 97.1% 97.8% 99.0% 98.9% 98.8% 99.5% 99.4% 99.3% 86.8% 88.8% 94.4%
Paraffin
37.0% 25.9% 10.7% 1.2%
0.6%
0.6%
0.2%
0.1%
0.4%
0.0%
0.0%
0.1% 10.0% 8.6%
4.0%
Candles
5.0%
4.0%
1.8%
2.7%
1.9%
0.7%
0.3%
0.3%
0.0%
0.0%
0.1%
0.0%
2.4%
2.1%
0.9%
Other
0.6%
0.7%
0.5%
0.2%
0.3%
1.0%
0.1%
0.7%
0.8%
0.0%
0.4%
0.6%
0.2%
0.4%
0.7%
Figure 37: Energy source for lighting in 1996, 2001 and 2007
There has been an increase in the percentage of households using electricity for lighting from
86.8% in 1996 to 94.4% in 2007 and a decrease in those using paraffin and candles (see Figure
37). The percentage of Asian and White households using electricity for lighting has remained
almost constant while Coloured households have increased by 2.3%. Black African households
have had a 30.0% increase in the use of electricity for lighting with significant decreases in those
using paraffin (26.3%) and candles (3.2%).
For households living in an informal dwelling not in a backyard 58.9% use electricity for lighting
while 34.4% use paraffin and 6.0% use candles. For cooking 47.6% use electricity 41.2% use
paraffin and 10.2% use gas while 61.2% use paraffin and 32.5% use electricity for heating. Of
those living in an informal dwelling in a back yard 86.7% are using electricity, 8.4% paraffin and
3.5% candles for lighting. The percentage using paraffin of cooking increases to 15.9% and to
31.9% for heating and decreases to 78.4% for cooking and 61.7% for heating.
With the large
percentage of households in informal dwellings, particularly those not in back yards, who do not
use electricity for lighting, cooking and heating the incidence of fires is far greater leading to loss of
possessions and lives for those who are already disadvantaged.
October 2008
Strategic Development Information and GIS Department
Page 33
2007 Community Survey Analysis for Cape Town
9.2
Access to Water
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1996 2001 2007 1996 2001 2007 1996 2001 2007 1996 2001 2007 1996 2001 2007
Black African
Coloured
Asian
White
Total
Piped w ater inside dw elling 34.2% 28.9% 52.6% 91.2% 84.5% 93.7% 98.1% 91.8% 97.8% 99.1% 94.6% 98.8% 79.0% 69.3% 80.5%
Piped w ater inside yard
30.9% 33.3% 25.6% 5.9% 9.3% 3.8% 1.2% 3.3% 1.0% 0.3% 2.2% 0.3% 10.5% 15.1% 10.6%
Piped w ater outside yard
28.9% 34.9% 21.1% 1.9% 5.5% 2.0% 0.3% 4.5% 0.4% 0.1% 3.0% 0.4% 8.3% 14.3% 8.4%
Other
5.6% 2.8% 0.7% 0.7% 0.7% 0.6% 0.1% 0.3% 0.8% 0.3% 0.3% 0.4% 1.8% 1.3% 0.5%
Figure 38: Main source of water by race for 1996, 2001 and 2007
The number of households having access to piped water increased from 97.8% in 1996 to 99.5%
in 2007 with over 99% of households in all race groups having access. By 2007 80.5% of all
households had piped water inside their dwelling, 10.6% had piped water inside their yard and
8.4% had access to piped water outside their yard (see Figure 38). For all races the percentage of
households having piped water inside their dwelling fell in 2001 and rose again in 2007. Over 93%
of all Coloured, Asian and White households had piped water inside their dwellings by 2007. Black
African households had a significant increase in the percentage of having piped water inside their
dwellings from 28.9% in 2001 to 52.6% in 2007. Having access to piped water reduces the risk of
water borne diseases and increases quality of life.
9.3
Access to Sanitation
The number of households having access to flush or chemical toilets decreased from 89.3% in
1996 to 87.5% in 2001 and then increased to 93.0% in 2007. Households using bucket toilets or
having no toilet facilities increased from 8.0% in 1996 to 11.6% in 2001 and then decreased to
6.4% in 2007.
October 2008
Strategic Development Information and GIS Department
Page 34
2007 Community Survey Analysis for Cape Town
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Flush toilet
Flush toilet
(sewerage
(septic tank)
system)
2001
85.3%
2.0%
2007
91.2%
1.6%
Dry toilet
facility
0.5%
Pit toilet
with
ventilation
Pit toilet
without
ventilation
0.3%
0.6%
0.2%
4.4%
7.2%
0.0%
0.0%
0.2%
2.9%
3.5%
Chemical Bucket toilet
toilet
system
None
Figure 39: Access to toilet facilities for 2001 and 2007
The number of households having a flush toilet connected to the sewerage system has increased
from 85.3% in 2001 to 91.2% in 2007 (see Figure 39). From 2001 to 2007 the percentage using
the bucket toilet system has decreased from 4.4% to 2.9% and households having no toilet
facilities have decreased from 7.2% to 3.5%.
Coloured households having access to a flush toilet increased from 95.3% in 2001 to 97.7% in
2007, Asian households increased from 97.8% to 99.2% and White households increased from
99.0% to 99.8%. Coloured households using the bucket system decreased from 1.3% in 2001 to
1.2% in 2007 while no Asian or White households were found to be using this system in 2007.
Coloured, Asian and White households having no access to toilet facilities had all dropped to below
1% by 2007. More details are shown in Appendix 13.
80%
70%
60%
50%
40%
30%
20%
10%
0%
Flush toilet
Flush toilet
(sewerage
(septic tank)
system)
2001
65.0%
2.5%
2007
78.5%
3.7%
Dry toilet
facility
1.0%
Pit toilet with
ventilation
Pit toilet
without
ventilation
Chemical
toilet
Bucket toilet
system
None
0.4%
1.3%
0.4%
11.9%
18.5%
0.0%
0.1%
0.6%
6.9%
9.1%
Figure 40: Access to toilet facilities by Black Africans for 2001 and 2007
October 2008
Strategic Development Information and GIS Department
Page 35
2007 Community Survey Analysis for Cape Town
Figure 40 shows the access to toilet facilities by Black African households. The percentage
connected to the sewerage system has increased to 78.5% in 2007 and 3.7% have toilets with a
septic tank. There has been a decline in those using the bucket system from 11.9% to 6.9% and
those having no access to a toilet facility from 18.5% to 9.1%.
Households who do not have access to adequate toilet facilities are more vulnerable to diseases
and epidemics which in turn increase the need for additional health care facilities. In areas without
adequate toilet facilities the pollution of waterways and wetlands increases and this puts a large
percentage of the population at risk of contracting water born diseases.
9.4
Refuse Removal
1996
100%
90%
2001
2007
94.2%94.2%
88.6%
80%
70%
60%
50%
40%
30%
20%
10%
3.1% 1.2%
1.0%
1.5% 1.3% 2.6%
3.3% 2.0%
1.1%
2.1% 1.4% 1.0%
Own refuse dump
No rubbish
disposal
1.3%
0.2%
0%
Removed by local Removed by local Communal refuse
authority at least authority less often
dump
weekly
Other
Figure 41: Type of refuse removal for 1996, 2001 and 2007
The removal of refuse by local authority at least weekly increased from 88.6% in 1996 to 94.2% in
2001 and was unchanged in 2007 (see Figure 41). Removal of refuse less than once a week
decreased from 3.1% in 1996 to 1.0% in 2007. The percentage of households having no rubbish
disposal and using their own refuse dump also decreased from 2.1% and 3.3% to 1.0% and 1.1%
respectively. The percentage using communal refuse dump has doubled since 2001.
Changes in refuse removal are most significant for Black African households with removal by local
authority at least weekly increasing from 66.7% in 1996 to 90.0% in 2007. Black African
households saw a decrease from 10.0% in 1996 to 1.8% in 2007 where refuse is removed by local
authority less than weekly, from 9.9% in 1996 to 1.7% in 2007 for those using their own refuse
dump and from 6.9% in 1996 to 2.4% in 2007 for those having no refuse removal. More details of
refuse removal by race can be found in Appendix 14.
Once again having adequate refuse removal decreases the incidence of diseases and epidemics
and improves the standard of living.
October 2008
Strategic Development Information and GIS Department
Page 36
2007 Community Survey Analysis for Cape Town
10 Household Goods
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Cell-phone
Landline
Telephone
Refrigerator
Radio
Television
Computer
2001
45.2%
55.0%
76.0%
80.4%
76.5%
21.0%
2007
77.1%
47.0%
83.9%
84.0%
85.9%
34.3%
Internet
Facility
18.9%
Figure 42: Household goods for 2001 and 2007
As can be seen from Figure 42 there has been a significant increase in the percentage of
households who have cell-phones. Households having landline telephones have decreased from
55.0% to 47.0%. By 2007 over 80% of households have refrigerators, radios and televisions.
Households having computers increased from 21.0% to 34.3%. In 2007 18.9% of households had
internet facilities.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Cell-phone
Landline
Telephone
Refrigerator
Radio
Television
Computer
Internet
Facility
Black African
75.2%
12.8%
62.5%
73.9%
69.3%
8.2%
2.9%
Coloured
69.7%
55.5%
93.0%
85.2%
94.0%
30.7%
9.4%
Asian
86.4%
75.4%
98.9%
97.4%
96.4%
65.8%
36.1%
White
88.3%
79.0%
99.3%
94.6%
96.6%
70.8%
51.0%
Figure 44: Household goods by race for 2007
For all races a larger percentage of households had cell-phones than landline telephones in 2007
with the largest difference occurring in Black African households where 75.2% have cell-phones
and 12.8% have landline telephones (see Figure 44). Over 94% of Asian and White households
have refrigerators, radios and televisions. A higher percentage of Coloured households have
televisions than radios with the opposite being true for Black African households. White
October 2008
Strategic Development Information and GIS Department
Page 37
2007 Community Survey Analysis for Cape Town
households have the highest percentage (70.8%) of computers and Black African households the
lowest (8.2%). Only 2.9% of Black African households have internet access as compared to
51.0% of White households.
11 Summary
The Community Survey has shown that the population of Cape Town has increased by 20.9%
since 2001 to just fewer than 3.5 million. All races showed an increase with Black Africans having
the largest increase at 33.1%. Since 2001 almost 111,000 Black Africans have moved into Cape
Town from outside of the Western Cape with 68.6% coming from the Eastern Cape.
The number of adults who have no schooling has declined by 43.5% since 2001 with only 2% of
the adult population having no schooling in 2007. The number of people with a degree, certificate
or diploma has increased by 67.3% since 2001.
The unemployment rate was at 24.5% in 2007, a decrease of 4.7% since 2001 with that of Black
Africans decreasing by 10%.
By 2007 83% of all households in Cape Town were living in formal dwellings. From 2001 to 2007
the number of Black African households in formal dwellings increased from 109 thousand to 194
thousand while the number in informal dwellings remained almost constant.
The percentage of households having access to electricity for lighting increased from 88.8% in
2001 to 94.4% in 2007 with Black African households increasing by 17.6%.
Over 99% of all households had access to piped water by 2007 with 80.5% having piped water in
their dwelling.
The number of households having access to a flush toilet increased from 87.3% in 2001 to 92.8%
in 2007. A relatively large number of households, 2.9%, were still using the bucket system in 2007
with a decline in the number of households from 34,310 in 2001 to 26,220 in 2007. In 2007 3.5%
of households had no access to toilet facilities.
Just over 95% of households have their refuse removed by the local authority in 2007 which shows
no change from 2001.
Households having cell-phones have increased from 45.2% in 2001 to 77.1% in 2007 while those
having landline telephones decreased from 55% to 47% in the same period. In 2007 75.2% of
Black African households had cell-phones while only 12.8% had landline telephones.
The number of households having computers also increased sharply from 21% in 2001 to 34.3% in
2007 with 18.9% of households having internet facilities in 2007.
There has been progress in improving the living conditions of people living in Cape Town. More
people are living in formal housing but more formal housing is needed for the many households still
living in informal dwellings. More households have access to services and in particular electricity
and piped water. Progress has been made with providing adequate toilet facilities but there are
still many households who are using the bucket system or who have no toilet facilities. The advent
of cell-phones has greatly improved communication particularly for Black Africans
Although the number employed has increased the challenge remains in creating more employment
opportunities as well as providing education opportunities to improve the skill levels of the existing
and potential work force.
October 2008
Strategic Development Information and GIS Department
Page 38
2007 Community Survey Analysis for Cape Town
Appendices
Appendix 1 – Estimation of Population and Number of Households
4 Methods used to estimate the population and number of households at municipal level
4.1 Introduction
This section summarises the methods used to estimate the population and households from the
Community Survey (CS) at municipal level. The user should be aware of the results and the Statistics
Council’s recommendations (see Appendix 2) regarding the national, provincial and municipal estimated
released in October 2007 (Report Nos. 03-01-20 and P0301). A cautionary note was included in the
aforementioned reports for the users to be aware of the following limitations:
The population out of the survey scope (i.e. institutions) was considered as an approximation from
2001 Census;
In the Community Survey, unemployment was measured by using a different set of questions than in
the regular Labour Force Survey;
An unreasonable high income for children, probably due to misinterpretation or no differentiation
between parent’s income and children’s income;
New trends from the Community Survey with little congruence in numbers of households by
province, as compared to the General Household Survey;
Caution should be maintained when interpreting the grants or number of those receiving grants;
Readers should be aware that the Community Survey does not replace the Census. Hence any
interpretation should be understood to have some random fluctuations in data, particularly
concerning the small number cells.
The release in October 2007 gave adjusted estimates of the survey at national and provincial levels.
These adjustments were done to ensure that the data remained internally and externally consistent at
national and provincial level, and by age, population group and sex. The random fluctuation was
maintained because the coefficients of variation (CV) were tolerable for national and provincial
estimates. However, the same was not true for the municipal domain of estimation as some
municipalities showed large CVs. Hence it became necessary to review the estimates at municipal level
in order to remove the systematic biases due to poor realisation of the sample at small-area level.
The statistical count of the Community Survey was measured in terms of number of persons and/or
households. The universe of the Community Survey covers the persons and households that were
sampled within all different enumeration areas as demarcated in the 2001 Census, excluding those
classified as institutions and recreational areas.
In order to have new estimates, the past Censuses are considered as the best available source of data
that give information at lower geographical level. Therefore, the CS estimates for lower geographical
levels are an adjustment to the projected information from these data sets.
4.2 The methods of estimation for different municipalities
4.2.1 The estimation of the number of persons
The ratio method (Shryock and Siegel, 1973) of projecting geographical subdivisions was used to
estimate the populations of the district councils and municipalities in the CS, stratified by population
group, sex and single-year-age. The method is agreeable to this purpose and its execution involved the
four stages as follows:
Observing the percentage share of the populations of geographic subdivisions (e.g. district councils)
in the parent population (e.g. province) in one or more reference dates. The current exercise made
use of the percentage distribution of district councils in a province (and percentage distribution of
October 2008
Strategic Development Information and GIS Department
Page 39
2007 Community Survey Analysis for Cape Town
municipalities in a district council) in the 1996 and 2001 censuses, adjusted to the 2006 official
boundaries1;
Projecting these percentage shares into future dates (the reference date for the CS – mid-February
2007 in the current exercise);
Applying the projected proportions/percentage shares into independently derived projections of the
parent population (in this case the provincial population estimates as published in the October 2007
release of the CS); and
Converting back into numbers of persons (by age, sex and population group) in each district
municipality and in each local municipality the estimated proportions.
In view of these projections or estimates, a choice was made for the beat estimates based on the
comparison between direct CS proportion and the closest estimates in absolute numbers. Any
difference greater than 1 000 persons or 10% was subjected to further scrutiny either by checking
estimates from recent aerial photographs or administrative registers, or own local municipality survey or
estimates. Although these further investigations were limited in nature because of the poor reliability of
ancillary sources, the approximation from aerial photographs and independent local estimates results
were closer to the projections than direst estimates from CS. If the projection using the ratio method was
consistent with the CS, no further change was made. If not, a weighted average was used, as the CS
and Census data were not consistent.
Assumptions of the method
Several assumptions could be employed when projecting population percentage distributions of
geographical subdivisions. The procedure used in the CS exercise assumes that the average annual
rate of change in the proportion observed in the 1996 and 2001 census enumerations, for each area will
tend to zero2 over a long period (say 60 years).
Limitations of the method
The method does not explicitly account for other socio-economic and demographic variables that
might be related to the observed proportion by the specific strata.
The method is not a detailed cohort component projection.
4.2.2 Re-calculation of the person weights
The new population estimates by municipalities described above provides additional information about
the population that is believed to be more reliable than direct survey estimates. It is therefore possible to
get improved precision of the survey estimates in term of reducing bias and increasing efficiency by
applying some form of post-stratification adjustment where the weighted estimated total of the population
(age, sex, population group) is constrained to the one coming from the estimated population on national
and provincial level.
The calculation of the municipality new adjusted weight for persons by age, sex and population group in
each municipality is given by:
Dividing the CS design weight by the response rate for each primary sampling unit within each
municipality (stratum);
Multiplying the first adjustment factor based on national and provincial estimates by age, sex,
population group; and
Multiplying the second adjustment factor deduced from the local municipality estimates by age, sex
and population group.
1
To maximise the usage of the data, the percentage distributions were observed for both PES weighted and unweighted versions of the censuses. Additionally, weighted averages of the observed percent distributions were
calculated (data for census 1996 were assigned a weight of 0,5 because they pertain to a period that is further
away from the CS date compared to data from census 2001 which were assigned a weight of 1).
2
Note that it is the annual rate of change (not the proportions themselves) that approach zero over time.
October 2008
Strategic Development Information and GIS Department
Page 40
2007 Community Survey Analysis for Cape Town
4.2.3 The estimation of the number of households
The approach separated individuals from households in order to derive more reliable population
estimates at a municipal level. After the number of people were estimated, revised estimates of the
number of households in each municipality were calculated by assuming that the average household
size (stratified by majority population group in the households) in each municipality remained unchanged
from the data collected in the CS. This ensured that inter-municipality differentials in household
composition were preserved. Dividing the new estimate of the number of people in each municipality
(stratified by population group) by the average household size (stratified by majority population group of
the household) gives a revised estimate (stratified by population group) of the number of households in
each municipality.
4.2.4 The derivation of CS out-of-scope population
Since the 2007 Community Survey has not taken into account some elements considered as out of
scope of the survey. In order to have as complete an estimate of the population of South Africa as
possible, those cases not in scope (such as collective living quarters (institutions) and some households
in EAs classified as recreational areas or institutions), needed to be added to the CS estimates.
However, as there has not been any recent estimate of these out-of-CS-scope cases, the only possibility
was to assume that each individual record falling within the defined categories had remained as counted
in the 2001 Census without any change over time.
The above considerations are applied at municipal level in the same way as they have been at provincial
level. In order to facilitate data management manipulation, the 2001 Census unit records that covered
out-of-CS-scope cases were reduced to easy manageable data points that give the same profile of age,
sex, population group and municipality distribution.
4.3 Consideration for CS interpretation of results
The users should note that the Community Survey is not a replacement of the Census. An attempt was
made to adjust the measurement to a best estimate. Any adjustment done has maintained the profiling
of the community in terms of the people and households while compensating and correcting undercount
bias by different projections on national, provincial and municipalities.
However, the reliability of each of the different estimation methods depends on their internal limitations
that lead to some assumptions based on what information is available. Most of the adjustments that
were made show that the direct measure by the Community Survey could not produce usable estimates
in some municipalities. The exception of better estimates was observed in densely populated
municipalities like metros. The less reliable estimates for some small municipalities that were observed
in the Community Survey would be part of the sampling methodology for future surveys. However, the
measurement in terms of proportion is much less susceptible to random error than counts (numbers). As
a consequence, the Community Survey gives useful information for estimating proportions, averages or
ratios for smaller area domains.
Users should be aware of these statements as part of the cautionary notes:
The household estimates at municipal level differ slightly from the national and provincial estimates
in terms of the household variables profile;
The Community Survey has considered as an add-on an approximation of population in areas not
covered by the survey, such as institutions and recreational areas. This approximation of people
could not provide the number of those households (i.e. institutions). Thus, there is no household
record for those approximated as living out of CS scope;
Any cross-tabulation giving small numbers at municipal level should be interpreted with caution such
as taking small value in given table’s cell as likely over or under estimation of the true population;
October 2008
Strategic Development Information and GIS Department
Page 41
2007 Community Survey Analysis for Cape Town
No reliance should be placed on numbers fro variables broken down at municipal level (i.e. age,
population group etc.). However, the aggregated total number per municipality provides more
reliable estimates;
Usually a zero figure (excluding those in institutions) reflects the fact that no sample was realise,
and in such cases, this is likely to be a significant underestimate of the true population;
As an extension from the above statement, in a number of instances the number realised in the
sample, though not zero, was very small (maybe as low as a single individual) and in some cases
had to be reweighted by a very large factor (maximum nearly 800 for housing weight and over 1 000
for person weight);
As a further consequence, small sub-populations are likely to be heavily over or under-represented
at a household level in the data.
It should be noted that the estimates were done with the use of the de-facto population and not the
de-jure population. These results are presented as de-jure population.
(Source: Community Survey 2007: Municipal data on household services / Statistics South Africa.
Pretoria: Statistics South Africa, 2007, 336p. [Report No. 03-01-22 (2007)])
October 2008
Strategic Development Information and GIS Department
Page 42
2007 Community Survey Analysis for Cape Town
Appendix 2 – Statement by South African Statistics Council
South African Statistics Council: Statement on the results of the Community Survey (CS)
1. Background
Stats SA conducted the Community Survey in February 2007. The Council has been intimately involved
in monitoring all the processes (including the sample design, questionnaire design, listing, fieldwork,
communications campaign, data processing, data analysis and dissemination) in this survey, since the
inception of the new Council in June 2005.
The focus of this statement is on the data analysis conducted by a team of consultants on behalf of the
Council.
2. The objectives of the Community Survey
The main objectives of the Community Survey conducted in February 2007 were to:
provide data at lower levels of geography (at district and municipal levels) in addition to national and
provincial levels;
build human, management and logistical capacity for Census 2011; and
provide the primary data as a base for population projections.
3. Main findings
The main findings of the investigation conducted by the Council are as follows:
Demographic rates
Fertility and mortality rates derived from the Community Survey data are entirely plausible.
Service delivery indicators
Most of the service delivery indicators compare well with other surveys conducted by Stats SA and other
surveys, such as All Media and Products (AMPS).
There are some concerns with certain variables and Council suggests that warnings be issued to caution
users on data relating to:
Institutional population (merely and approximation to 2001 numbers and not new data);
Unemployment in the Community Survey is higher and less reliable because of questions that were
asked differently;
Grants (do not match the (SASSA) data and should be interpreted with great care);
Income (includes unreasonably high income for children – presumably misinterpretation of the
question, listing parents’ income for the child); and
Distribution of households by province has very little congruence with the General Household
Survey or last census.
In the absence of a comprehensive sampling frame, it is difficult to determine whether the differences are
due to sampling error, biases or the reality that has changed beyond our expectations. There may be
other variables that will require similar warnings after further interrogation.
Systematic errors
A number of systematic errors were observed in the data, which include:
An underestimate of men relative to women;
An underestimate of children younger than 10 years;
An excess of those aged 85+, in particular among men;
October 2008
Strategic Development Information and GIS Department
Page 43
2007 Community Survey Analysis for Cape Town
Missing women aged 20–34 from the Coloured population;
Maldistribution of the population by province;
Excess of people aged 10–24 in Western Cape and Gauteng; and
A shortfall of women aged 20–34 in Free State, KwaZulu-Natal and Limpopo.
With reference to the systematic errors in particular, Council advised that Stats SA use a set of revised
weights – even though the weights are aimed at addressing sampling errors, which when applied provide
more credible estimates of the population at national and provincial levels. This will be achieved by using
CS data to determine an estimated population for the country and each province against which the CS
data can then be calibrated.
Data at municipal and district levels
Council found that the confidence intervals at some municipal levels are very wide. It then recommended
that further analysis and investigation be conducted into the data to ensure that reliable data are
released at district and municipal levels.
Other issues
Council made extensive comments and recommendations on the detailed reports received from Stats
SA over the past two years on the following:
Sample design
Listing
Questionnaire design
Fieldwork (including non-response)
Logistics
Data processing
Data analysis
Data dissemination
While the focus of this report is on the data analysis, there are important lessons to be learnt from all the
stages of this survey that will be valuable for Census 2011. Council recommends that Stats SA should
prepare a consolidated report on lessons learnt for 2011.
4. Main recommendations
In view of the findings of the investigation conducted by the Council, we make the following
recommendations to the Minister and Statistician-General for approval, in terms of Section 13 of the
Statistics Act (Act No.6 of 1999):
The Statistician-General releases the data of the Community Survey disaggregated at national and
provincial levels (summary statistics and tabulations, not the dataset) in October 2007, using the
proposed weights as discussed with the Statistician General.
The Statistician-General releases the data of the Community Survey disaggregated to district and
municipal levels on 31 January 2008.
Further investigations into the stability of the data be conducted at district and municipal level prior
to the proposed release on 31 January 2008.
Stats SA includes warnings to users on the following variables:
o Institutional population
o Unemployment
o Grants
o Income
o Distribution of households by province
October 2008
Strategic Development Information and GIS Department
Page 44
2007 Community Survey Analysis for Cape Town
Stats SA maintains key databases on population, housing and school enrolment. This is particularly,
necessary if a large sample survey such as the Community Survey is to be calibrated against a
dwelling frame, a housing register, a population register or school enrolment data.
Stats SA prepares a consolidated report on lessons learnt from the Community Survey to provide a
coherent basis for the planning of Census 2011.
The data gathered in the Community Survey be used to revise the models to determine the mid-year
population estimates.
Stats SA gives urgent attention to the development of key high-level skills required to conduct a
survey of this nature.
5. Conclusion
Council also wishes to record their sincere appreciation to the Statistician-General and the management
team at Stats SA for the professional and transparent manner in which they have engaged with Council.
Howard Gabriels
Chairperson
South African Statistics Council
24 October 2007
(Source: Statistical release: Community Survey, 2007 (Revised version) / Statistics South Africa.
Pretoria: Statistics South Africa, 2007, 95p. [Report No. P0301])
October 2008
Strategic Development Information and GIS Department
Page 45
2007 Community Survey Analysis for Cape Town
Appendix 3 – Western Cape Population by Local Municipality for 1996, 2001 and 2007
District
DC1
DC1
DC1
DC1
DC1
DC1
DC1
DC2
DC2
DC2
DC2
DC2
DC2
DC2
DC3
DC3
DC3
DC3
DC3
DC3
DC4
DC4
DC4
DC4
DC4
DC4
DC4
DC4
DC4
DC5
DC5
DC5
DC5
DC5
CPT
Local Code
Local Name
WC011
Matzikama
WC012
Cederberg
WC013
Bergrivier
WC014
Saldanha Bay
WC015
Swartland
WCDMA01
West Coast
West Coast District Total
WC022
Witzenberg
WC023
Drakenstein
WC024
Stellenbosch
WC025
Breede Valley
WC026
Breede River/Winelands
WCDMA02
Cape Winelands
Cape Winelands District Total
WC031
Theewaterskloof
WC032
Overstrand
WC033
Cape Agulhas
WC034
Swellendam
WCDMA03
Overberg
Overberg District Total
WC041
Kannaland
WC042
Hessequa
WC043
Mossel Bay
WC044
George
WC045
Oudtshoorn
WC047
Bitou
WC048
Knysna
WCDMA04
Eden
Eden District Total
WC051
Laingsburg
WC052
Prince Albert
WC053
Beaufort West
WCDMA05
Central Karoo
Central Karoo District Total
CPT
City of Cape Town
Western Cape
August 2008
1996
39,787
31,707
37,025
57,015
64,951
4,123
234,608
73,084
177,093
112,426
128,820
63,564
8,189
563,176
74,580
37,469
22,103
24,722
132
159,006
21,191
38,550
59,792
108,375
79,176
18,432
42,947
12,417
380,880
5,919
9,511
34,687
5,994
56,111
2,563,095
3,956,876
2001
50,208
39,326
46,325
70,440
72,115
4,258
282,672
83,567
194,417
118,709
146,028
81,271
6,500
630,492
93,276
55,451
26,468
28,076
248
203,519
23,971
44,114
71,494
135,409
84,692
29,182
51,468
14,594
454,924
6,680
10,512
37,106
6,184
60,482
2,892,243
4,524,332
2007
46,361
31,944
44,740
78,982
77,525
7,203
286,755
75,149
217,087
200,522
134,267
80,122
5,259
712,406
86,715
74,543
28,442
22,840
246
212,786
24,714
39,076
117,840
136,540
79,604
39,002
65,043
11,485
513,304
5,154
8,383
37,092
5,609
56,238
3,497,097
5,278,586
Change 1996-2001
Number
%
10,421
26.19%
7,619
24.03%
9,300
25.12%
13,425
23.55%
7,164
11.03%
135
3.27%
48,064
20.49%
10,483
14.34%
17,324
9.78%
6,283
5.59%
17,208
13.36%
17,707
27.86%
-1,689
-20.63%
67,316
11.95%
18,696
25.07%
17,982
47.99%
4,365
19.75%
3,354
13.57%
116
87.88%
44,513
27.99%
2,780
13.12%
5,564
14.43%
11,702
19.57%
27,034
24.94%
5,516
6.97%
10,750
58.32%
8,521
19.84%
2,177
17.53%
74,044
19.44%
761
12.86%
1,001
10.52%
2,419
6.97%
190
3.17%
4,371
7.79%
329,148
12.84%
567,456
14.34%
Strategic Development Information and GIS Department
Change 2001-2007
Number
%
-3,847
-7.66%
-7,382
-18.77%
-1,585
-3.42%
8,542
12.13%
5,410
7.50%
2,945
69.16%
4,083
1.44%
-8,418
-10.07%
22,670
11.66%
81,813
68.92%
-11,761
-8.05%
-1,149
-1.41%
-1,241
-19.09%
81,914
12.99%
-6,561
-7.03%
19,092
34.43%
1,974
7.46%
-5,236
-18.65%
-2
-0.81%
9,267
4.55%
743
3.10%
-5,038
-11.42%
46,346
64.83%
1,131
0.84%
-5,088
-6.01%
9,820
33.65%
13,575
26.38%
-3,109
-21.30%
58,380
12.83%
-1,526
-22.84%
-2,129
-20.25%
-14
-0.04%
-575
-9.30%
-4,244
-7.02%
604,854
20.91%
754,254
16.67%
Change 1996-2007
Number
%
6,574
16.52%
237
0.75%
7,715
20.84%
21,967
38.53%
12,574
19.36%
3,080
74.70%
52,147
22.23%
2,065
2.83%
39,994
22.58%
88,096
78.36%
5,447
4.23%
16,558
26.05%
-2,930
-35.78%
149,230
26.50%
12,135
16.27%
37,074
98.95%
6,339
28.68%
-1,882
-7.61%
114
86.36%
53,780
33.82%
3,523
16.62%
526
1.36%
58,048
97.08%
28,165
25.99%
428
0.54%
20,570 111.60%
22,096
51.45%
-932
-7.51%
132,424
34.77%
-765
-12.92%
-1,128
-11.86%
2,405
6.93%
-385
-6.42%
127
0.23%
934,002
36.44%
1,321,710
33.40%
Page 46
2007 Community Survey Analysis for Cape Town
Appendix 4 – Municipalities in the Western Cape
August 2008
Strategic Development Information and GIS Department
Page 47
2007 Community Survey Analysis for Cape Town
Appendix 5 – Cape Town Population by Race and Gender for 1996, 2001 and 2007
Race
Black African
Coloured
Asian
White
Unspecified
Total
Male
320,779
593,640
18,972
259,818
48,255
1,241,464
1996
Female
323,402
646,303
18,910
283,607
49,409
1,321,631
Total
644,181
1,239,943
37,882
543,425
97,664
2,563,095
Male
447,793
662,279
20,542
258,725
0
1,389,339
2001
Female
468,791
730,315
20,974
283,830
0
1,503,910
Total
916,584
1,392,594
41,516
542,555
0
2,893,249
Male
590,546
744,437
31,101
327,175
0
1,693,259
2007
Female
629,435
793,878
31,253
349,272
0
1,803,838
Total
1,219,981
1,538,315
62,354
676,447
0
3,497,097
Appendix 6 – Age Distributions by Race and Gender for 2007
Age
Group
0-5
6 - 12
13 - 17
18 - 34
35 - 54
55 - 64
65+
Total
Male
87,750
7.2%
75,554
6.2%
47,937
3.9%
226,751
18.6%
123,930
10.2%
18,657
1.5%
9,967
0.8%
590,546
48.4%
August 2008
Black
Coloured
Female
Total
Male Female
Total
87,466
175,216 83,450 83,600
167,050
7.2%
14.4%
5.4%
5.4%
10.9%
77,674
153,228 98,723 98,145
196,868
6.4%
12.6%
6.4%
6.4%
12.8%
54,067
102,004 77,382 72,479
149,861
4.4%
8.4%
5.0%
4.7%
9.7%
246,631
473,382 221,177 223,265
444,442
20.2%
38.8% 14.4% 14.5%
28.9%
128,441
252,371 194,393 219,051
413,444
10.5%
20.7% 12.6% 14.2%
26.9%
21,151
39,808 41,591 53,598
95,189
1.7%
3.3%
2.7%
3.5%
6.2%
14,005
23,972 27,721 43,740
71,461
1.1%
2.0%
1.8%
2.8%
4.6%
629,435 1,219,981 744,437 793,878 1,538,315
51.6%
100.0% 48.4% 51.6%
100.0%
Indian or Asian
Male
Female
Total
Male
2,297
2,214
4,511 19,459
3.7%
3.6%
7.2%
2.9%
2,977
2,909
5,886 24,994
4.8%
4.7%
9.4%
3.7%
1,902
2,551
4,453 21,476
3.1%
4.1%
7.1%
3.2%
11,947
10,547
22,494 77,525
19.2%
16.9%
36.1%
11.5%
8,282
8,871
17,153 98,533
13.3%
14.2%
27.5%
14.6%
2,416
2,414
4,830 42,268
3.9%
3.9%
7.7%
6.2%
1,280
1,747
3,027 42,920
2.1%
2.8%
4.9%
6.3%
31,101
31,253
62,354 327,175
49.9%
50.1% 100.0%
48.4%
White
Grand Total
Female
Total
Male
Female
Total
20,630 40,089 192,956 193,910 386,866
3.0%
5.9%
5.5%
5.5%
11.1%
22,604 47,598 202,248 201,332 403,580
3.3%
7.0%
5.8%
5.8%
11.5%
20,401 41,877 148,697 149,498 298,195
3.0%
6.2%
4.3%
4.3%
8.5%
80,469 157,994 537,400 560,912 1,098,312
11.9%
23.4%
15.4%
16.0%
31.4%
105,702 204,235 425,138 462,065 887,203
15.6%
30.2%
12.2%
13.2%
25.4%
47,767 90,035 104,932 124,930 229,862
7.1%
13.3%
3.0%
3.6%
6.6%
51,699 94,619
81,888 111,191 193,079
7.6%
14.0%
2.3%
3.2%
5.5%
349,272 676,447 1,693,259 1,803,838 3,497,097
51.6% 100.0%
48.4%
51.6% 100.0%
Strategic Development Information and GIS Department
Page 48
2007 Community Survey Analysis for Cape Town
Appendix 7 – Province from which people moved into Cape Town since October 2001 by Race
Race
Black African
Coloured
Asian
White
Total
Eastern
Cape
76,087
68.62%
3,250
23.04%
232
3.81%
5,880
9.94%
85,449
44.91%
Free
State
1,700
1.53%
299
2.12%
0
0.00%
1,877
3.17%
3,876
2.04%
Gauteng
8,892
8.02%
3,414
24.21%
2,107
34.56%
18,435
31.15%
32,848
17.27%
KwaZuluNatal
4,095
3.69%
529
3.75%
2,276
37.33%
4,922
8.32%
11,822
6.21%
Limpopo
Mpumalanga
1,645
1.48%
65
0.46%
0
0.00%
1,485
2.51%
3,195
1.68%
584
0.53%
527
3.74%
0
0.00%
1,439
2.43%
2,550
1.34%
Northern
Cape
1,497
1.35%
1,965
13.93%
0
0.00%
1,863
3.15%
5,325
2.80%
North
West
982
0.89%
189
1.34%
0
0.00%
282
0.48%
1,453
0.76%
Outside
RSA
12,400
11.18%
1,576
11.17%
1,253
20.55%
21,800
36.84%
37,029
19.46%
Unknown
Total
2,997
2.70%
2,289
16.23%
229
3.76%
1,194
2.02%
6,709
3.53%
110,879
100.00%
14,103
100.00%
6,097
100.00%
59,177
100.00%
190,256
100.00%
Appendix 8 – Disabilities by Race and Gender for 2007
Disability
Sight
Hearing
Communication
Physical
Intellectual
Emotional
Multiple
Disabilities
Total
August 2008
Male
Black African
Female
Total
2,438
6.42%
952
2.51%
1,010
2.66%
6,638
17.48%
1,782
4.69%
2,994
7.88%
4,047
10.66%
19,861
52.30%
1,396
3.68%
1,258
3.31%
476
1.25%
5,533
14.57%
943
2.48%
3,874
10.20%
4,634
12.20%
18,114
47.70%
3,834
10.10%
2,210
5.82%
1,486
3.91%
12,171
32.05%
2,725
7.18%
6,868
18.09%
8,681
22.86%
37,975
100.00%
Male
Coloured
Female
Total
Male
Asian
Female
Total
Male
White
Female
Total
Male
Total
Female
Total
2,699
5.04%
1,948
3.64%
1,435
2.68%
12,614
23.55%
2,472
4.62%
4,960
9.26%
1,946
3.63%
28,074
52.41%
2,665
4.98%
2,368
4.42%
1,352
2.52%
9,959
18.59%
2,341
4.37%
4,388
8.19%
2,416
4.51%
25,489
47.59%
5,364
10.01%
4,316
8.06%
2,787
5.20%
22,573
42.14%
4,813
8.99%
9,348
17.45%
4,362
8.14%
53,563
100.00%
140
7.56%
0
0.00%
175
9.45%
306
16.52%
265
14.31%
0
0.00%
0
0.00%
886
47.84%
64
3.46%
0
0.00%
0
0.00%
525
28.35%
0
0.00%
322
17.39%
55
2.97%
966
52.16%
204
11.02%
0
0.00%
175
9.45%
831
44.87%
265
14.31%
322
17.39%
55
2.97%
1,852
100.00%
857
4.10%
1,272
6.08%
385
1.84%
3,784
18.10%
803
3.84%
1,360
6.50%
1,391
6.65%
9,852
47.12%
532
2.54%
973
4.65%
231
1.10%
4,933
23.59%
816
3.90%
1,832
8.76%
1,738
8.31%
11,055
52.88%
1,389
6.64%
2,245
10.74%
616
2.95%
8,717
41.69%
1,619
7.74%
3,192
15.27%
3,129
14.97%
20,907
100.00%
6,134
5.37%
4,172
3.65%
3,005
2.63%
23,342
20.42%
5,322
4.66%
9,314
8.15%
7,384
6.46%
58,673
51.33%
4,657
4.07%
4,599
4.02%
2,059
1.80%
20,950
18.33%
4,100
3.59%
10,416
9.11%
8,843
7.74%
55,624
48.67%
10,791
9.44%
8,771
7.67%
5,064
4.43%
44,292
38.75%
9,422
8.24%
19,730
17.26%
16,227
14.20%
114,297
100.00%
Strategic Development Information and GIS Department
Page 49
2007 Community Survey Analysis for Cape Town
Appendix 9 – Highest Level of Education amongst adults by Race for 1996, 2001 and 2007
Education Level
No schooling
Grade 0 – 3
Grade 4 – 7
Grade 8 – 11
Grade 12
Certificate/ Diploma
Degree
Unspecified
Total
August 2008
1996
Black African
2001
2007
32,404
8.2%
10,907
2.8%
101,927
25.8%
168,429
42.7%
53,355
13.5%
11,473
2.9%
5,288
1.3%
10,939
2.8%
394,722
100.0%
47,461
8.4%
21,604
3.8%
116,454
20.6%
229,718
40.6%
114,193
20.2%
25,249
4.5%
11,309
2.0%
0
0.0%
565,988
100.0%
1996
Coloured
2001
2007
1996
Asian
2001
2007
1996
White
2001
2007
19,855 29,181 26,993 21,545
830
586
742
3,182
2,257
1,503
2.7%
8.2%
3.2%
2.3%
3.6%
2.2%
1.7%
0.8%
0.6%
0.3%
32,472 16,012 22,093 30,897
218
264
566
389
683
1,141
4.5%
2.8%
2.6%
3.2%
0.9%
1.0%
1.3%
0.1%
0.2%
0.2%
132,923 168,926 178,350 176,892
2,605
2,420
3,479
3,046
4,818
6,645
18.3%
25.8%
21.4%
18.5% 11.3%
9.0%
8.0%
0.8%
1.2%
1.3%
340,393 320,788 379,401 444,208
7,463
8,000 12,301 80,373 81,256 99,213
46.9%
42.7%
45.5%
46.5% 32.3% 29.9% 28.2%
20.2%
19.9%
19.4%
114,507 98,129 175,739 174,810
6,357
9,152 11,072 143,604 167,444 167,625
15.8%
13.5%
21.1%
18.3% 27.5% 34.2% 25.4%
36.0%
41.1%
32.7%
50,610 43,659 37,130 63,257
2,308
2,985
5,094 79,374 79,266 96,267
7.0%
2.9%
4.5%
6.6% 10.0% 11.2% 11.7%
19.9%
19.4%
18.8%
24,171 11,187 14,528 26,556
2,046
3,353 10,090 51,540 72,134 135,439
3.3%
1.3%
1.7%
2.8%
8.8% 12.5% 23.2%
12.9%
17.7%
26.4%
10,713 31,181
0 16,799
1,302
0
240 37,085
0
4,423
1.5%
2.8%
0.0%
1.8%
5.6%
0.0%
0.6%
9.3%
0.0%
0.9%
725,644 719,063 834,234 954,964 23,129 26,760 43,584 398,593 407,858 512,256
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Strategic Development Information and GIS Department
Unspecified
1996
1996
Total
2001
2007
1,661
67,258
77,297
43,645
3.0%
4.2%
4.2%
2.0%
747
28,273
44,644
65,076
1.4%
1.8%
2.4%
2.9%
7,582
284,086
302,042
319,939
13.9%
17.9%
16.5%
14.3%
19,927
596,980
698,375
896,115
36.4%
37.5%
38.1%
40.1%
10,685
312,130
466,528
468,014
19.5%
19.6%
25.4%
20.9%
6,590
143,404
144,630
215,228
12.1%
9.0%
7.9%
9.6%
3,014
73,075
101,324
196,256
5.5%
4.6%
5.5%
8.8%
4,480
84,987
0
32,175
8.2%
5.3%
0.0%
1.4%
54,686 1,590,193 1,834,840 2,236,448
100.0%
100.0%
100.0%
100.0%
Page 50
2007 Community Survey Analysis for Cape Town
Appendix 10 – Western Cape Households by Local Municipality for 1996, 2001 and 2007
District
DC1
DC1
DC1
DC1
DC1
DC1
DC1
DC2
DC2
DC2
DC2
DC2
DC2
DC2
DC3
DC3
DC3
DC3
DC3
DC3
DC4
DC4
DC4
DC4
DC4
DC4
DC4
DC4
DC4
DC5
DC5
DC5
DC5
DC5
CPT
Local Code
Local Name
WC011
Matzikama
WC012
Cederberg
WC013
Bergrivier
WC014
Saldanha Bay
WC015
Swartland
WCDMA01
West Coast
Wets Coast District Total
WC022
Witzenberg
WC023
Drakenstein
WC024
Stellenbosch
WC025
Breede Valley
WC026
Breede River/Winelands
WCDMA02
Cape Winelands
Cape Winelands District Total
WC031
Theewaterskloof
WC032
Overstrand
WC033
Cape Agulhas
WC034
Swellendam
WCDMA03
Overberg
Overberg District Total
WC041
Kannaland
WC042
Hessequa
WC043
Mossel Bay
WC044
George
WC045
Oudtshoorn
WC047
Bitou
WC048
Knysna
WCDMA04
Eden
Eden District Total
WC051
Laingsburg
WC052
Prince Albert
WC053
Beaufort West
WCDMA05
Central Karoo
Central Karoo District Total
CPT
City of Cape Town
Western Cape
August 2008
1996
9,958
7,803
8,889
13,002
15,791
1,013
56,456
16,395
40,320
27,699
29,193
15,512
2,062
131,181
18,059
11,654
5,594
6,089
11
41,407
4,857
9,742
15,414
25,774
15,732
5,078
11,433
2,870
90,900
1,462
2,133
7,529
1,335
12,459
653,085
985,488
2001
14,094
10,365
11,706
18,706
17,403
1,175
73,449
19,413
44,410
29,023
34,100
20,926
1,526
149,398
23,044
18,568
7,513
7,494
38
56,657
6,070
12,510
20,060
35,520
18,124
8,763
14,732
3,527
119,306
1,922
2,547
8,994
1,546
15,009
759,485
1,173,304
2007
12,881
9,212
12,197
20,786
19,939
1,200
76,215
24,410
51,614
36,413
36,495
21,856
2,559
173,347
23,464
21,953
7,615
6,958
66
60,056
6,344
12,481
28,349
42,793
17,913
12,645
17,416
3,635
141,576
1,966
2,747
9,149
1,845
15,707
902,278
1,369,179
Change 1996-2001
Number
%
4,136
41.53%
2,562
32.83%
2,817
31.69%
5,704
43.87%
1,612
10.21%
162
15.99%
16,993
30.10%
3,018
18.41%
4,090
10.14%
1,324
4.78%
4,907
16.81%
5,414
34.90%
-536
-25.99%
18,217
13.89%
4,985
27.60%
6,914
59.33%
1,919
34.30%
1,405
23.07%
27
245.45%
15,250
36.83%
1,213
24.97%
2,768
28.41%
4,646
30.14%
9,746
37.81%
2,392
15.20%
3,685
72.57%
3,299
28.86%
657
22.89%
28,406
31.25%
460
31.46%
414
19.41%
1,465
19.46%
211
15.81%
2,550
20.47%
106,400
16.29%
187,816
19.06%
Strategic Development Information and GIS Department
Change 2001-2007
Number
%
-1,213
-8.61%
-1,153
-11.12%
491
4.19%
2,080
11.12%
2,536
14.57%
25
2.13%
2,766
3.77%
4,997
25.74%
7,204
16.22%
7,390
25.46%
2,395
7.02%
930
4.44%
1,033
67.69%
23,949
16.03%
420
1.82%
3,385
18.23%
102
1.36%
-536
-7.15%
28
73.68%
3,399
6.00%
274
4.51%
-29
-0.23%
8,289
41.32%
7,273
20.48%
-211
-1.16%
3,882
44.30%
2,684
18.22%
108
3.06%
22,270
18.67%
44
2.29%
200
7.85%
155
1.72%
299
19.34%
698
4.65%
142,793
18.80%
195,875
16.69%
Change 1996-2007
Number
%
2,923
29.35%
1,409
18.06%
3,308
37.21%
7,784
59.87%
4,148
26.27%
187
18.46%
19,759
35.00%
8,015
48.89%
11,294
28.01%
8,714
31.46%
7,302
25.01%
6,344
40.90%
497
24.10%
42,166
32.14%
5,405
29.93%
10,299
88.37%
2,021
36.13%
869
14.27%
55
500.00%
18,649
45.04%
1,487
30.62%
2,739
28.12%
12,935
83.92%
17,019
66.03%
2,181
13.86%
7,567
149.02%
5,983
52.33%
765
26.66%
50,676
55.75%
504
34.47%
614
28.79%
1,620
21.52%
510
38.20%
3,248
26.07%
249,193
38.16%
383,691
38.93%
Page 51
2007 Community Survey Analysis for Cape Town
Appendix 11 – Dwelling Type by Race for 1996, 2001 and 2007
Housing
Type
Formal
Informal
Other
Total
Black African
Coloured
Asian
White
Unspecified
Total
1996
2001
2007
1996
2001
2007
1996
2001
2007
1996
2001
2007
1996
1996
2001
2007
50,522 109,412 193,772 236,605 283,085 296,036 8,431 9,619 16,714 190,927 197,676 242,109
18,452 504,937 599,792 748,631
30.1% 45.3% 60.0% 91.0% 92.1% 93.7% 96.5% 97.1% 99.0% 97.9% 98.5% 98.2%
91.2% 77.4% 78.9% 83.0%
108,941 124,914 121,550 15,171 17,077 17,709
97
108
161
158
811
1,185
866 125,233 142,910 140,605
64.8% 51.7% 37.6%
5.8%
5.6%
5.6%
1.1%
1.1%
1.0%
0.1%
0.4%
0.5%
4.3% 19.2% 18.8% 15.6%
8,541
7,461
7,695
8,208
7,129
2,088
212
180
0
3,920
2,290
3,256
921 21,802 17,060 13,039
5.1%
3.1%
2.4%
3.2%
2.3%
0.7%
2.4%
1.8%
0.0%
2.0%
1.1%
1.3%
4.6%
3.3%
2.2%
1.4%
168,004 241,787 323,017 259,984 307,291 315,833 8,740 9,907 16,875 195,005 200,777 246,550
20,239 651,972 759,762 902,275
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
100.0% 100.0% 100.0% 100.0%
Note: Informal include shacks not in back yards as well as those in back yards.
Other includes traditional dwellings, caravans, tents, private ships and workers’ hostels.
August 2008
Strategic Development Information and GIS Department
Page 52
2007 Community Survey Analysis for Cape Town
Appendix 12 – Fuel used for Lighting, Cooking and Heating by Race for 2007
Fuel
Electricity
Gas
Paraffin
Wood
Coal
Candles
Animal
dung
Solar
Other
Total
August 2008
Black African
Coloured
Asian
White
Total
Lighting Cooking Heating Lighting Cooking Heating Lighting Cooking Heating Lighting Cooking Heating Lighting Cooking Heating
281,180 252,154 183,244 308,900 305,077 296,431
16,679
15,501 15,887 244,812 234,948 229,898 851,571 807,680 725,460
87.0%
78.1%
56.7%
97.8%
96.6%
93.9%
98.8%
91.9%
94.1%
99.3%
95.3%
93.2%
94.4%
89.5%
80.4%
616
19,508
5,856
522
7,064
2,220
70
1,248
662
69
11,175
7,821
1,277
38,995 16,559
0.2%
6.0%
1.8%
0.2%
2.2%
0.7%
0.4%
7.4%
3.9%
0.0%
4.5%
3.2%
0.1%
4.3%
1.8%
34,440
50,727 126,105
1,813
2,641
5,647
64
64
64
208
291
471
36,525
53,723 132,287
10.7%
15.7%
39.0%
0.6%
0.8%
1.8%
0.4%
0.4%
0.4%
0.1%
0.1%
0.2%
4.0%
6.0%
14.7%
185
2,720
658
3,650
62
64
136
4,359
1,041 10,793
0.1%
0.8%
0.2%
1.2%
0.4%
0.4%
0.1%
1.8%
0.1%
1.2%
106
279
0
116
0
0
0
581
106
976
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.2%
0.0%
0.1%
5,725
2,180
0
0
7,905
1.8%
0.7%
0.0%
0.0%
0.9%
54
0
0
0
0
0
0
0
54
0
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
57
63
178
219
56
67
0
0
58
373
0
587
649
119
890
0.0%
0.0%
0.1%
0.1%
0.0%
0.0%
0.0%
0.0%
0.3%
0.2%
0.0%
0.2%
0.1%
0.0%
0.1%
999
220
4,635
2,199
337
7,702
62
0
140
1,088
0
2,833
4,348
557 15,310
0.3%
0.1%
1.4%
0.7%
0.1%
2.4%
0.4%
0.0%
0.8%
0.4%
0.0%
1.1%
0.5%
0.1%
1.7%
323,017 323,017 323,017 315,833 315,833 315,833
16,875
16,875 16,875 246,550 246,550 246,550 902,275 902,275 902,275
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Strategic Development Information and GIS Department
Page 53
2007 Community Survey Analysis for Cape Town
Appendix 13 – Access to Toilet Facility by Race for 2001 and 2007
Toilet Facility
Flush toilet (connected to sewerage
system)
Flush toilet (with septic tank)
Dry toilet facility
Pit toilet with ventilation (VIP)
Pit toilet without ventilation
Chemical toilet
Bucket toilet system
None
Total
August 2008
Black African
2001
2007
163,308 253,686
65.0%
78.5%
6,275
11,880
2.5%
3.7%
3,158
1.0%
911
111
0.4%
0.0%
3,219
293
1.3%
0.1%
916
1,965
0.4%
0.6%
29,921
22,432
11.9%
6.9%
46,584
29,492
18.5%
9.1%
251,134 323,017
100.0% 100.0%
Coloured
2001
2007
290,718 307,023
93.6%
97.2%
5,152
1,513
1.7%
0.5%
959
0.3%
961
323
0.3%
0.1%
1,140
88
0.4%
0.0%
618
117
0.2%
0.0%
4,114
3,676
1.3%
1.2%
7,802
2,134
2.5%
0.7%
310,505 315,833
100.0% 100.0%
Asian
2001
2007
9,703 16,663
96.4%
98.7%
140
77
1.4%
0.5%
0
0.0%
22
0
0.2%
0.0%
36
0
0.4%
0.0%
9
0
0.1%
0.0%
45
0
0.4%
0.0%
113
135
1.1%
0.8%
10,068 16,875
100.0% 100.0%
White
2001
2007
199,651 245,417
97.1%
99.5%
3,835
755
1.9%
0.3%
84
0.0%
228
0
0.1%
0.0%
263
0
0.1%
0.0%
106
0
0.1%
0.0%
230
112
0.1%
0.0%
1,365
182
0.7%
0.1%
205,678 246,550
100.0% 100.0%
Strategic Development Information and GIS Department
Total
2001
663,380
85.3%
15,402
2.0%
2,122
0.3%
4,658
0.6%
1,649
0.2%
34,310
4.4%
55,864
7.2%
777,385
100.0%
2007
822,789
91.2%
14,225
1.6%
4,201
0.5%
434
0.0%
381
0.0%
2,082
0.2%
26,220
2.9%
31,943
3.5%
902,275
100.0%
Page 54
2007 Community Survey Analysis for Cape Town
Appendix 14 – Refuse Removal by Race for 1996, 2001 and 2007
Refuse Removal
Removed by local
authority at least weekly
Removed by local
authority less often
Communal refuse dump
Own refuse dump
No rubbish disposal
Other
Total
August 2008
Black African
Coloured
1996
2001
2007
1996
2001
2007
1996
111,994 218,707 290,627 246,460 301,826 302,967 8,583
66.7% 87.1% 90.0% 94.8% 97.2% 95.9% 98.2%
16,745
6,145
5,756
3,005
1,659
1,868
29
10.0%
2.4%
1.8%
1.2%
0.5%
0.6%
0.3%
7,003
7,577 12,271
2,356
1,717
7,122
29
4.2%
3.0%
3.8%
0.9%
0.6%
2.3%
0.3%
16,563
9,575
5,449
3,767
4,089
2,646
15
9.9%
3.8%
1.7%
1.4%
1.3%
0.8%
0.2%
11,628
9,130
7,784
1,472
1,215
901
12
6.9%
3.6%
2.4%
0.6%
0.4%
0.3%
0.1%
4,068
1,130
2,928
329
75
2.4%
0.3%
1.1%
0.1%
0.9%
168,001 251,134 323,017 259,988 310,506 315,833 8,743
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Asian
White
Unspecified
2001
2007
1996
2001
2007
1996
9,937 16,506 191,845 201,717 239,841
19,270
98.7% 97.8% 98.4% 98.1% 97.3%
95.2%
54
0
612
1,562
1,033
102
0.5%
0.0%
0.3%
0.8%
0.4%
0.5%
42
195
456
476
3,760
57
0.4%
1.2%
0.2%
0.2%
1.5%
0.3%
24
64
872
1,480
1,583
321
0.2%
0.4%
0.4%
0.7%
0.6%
1.6%
12
56
251
442
333
96
0.1%
0.3%
0.1%
0.2%
0.1%
0.5%
54
978
0
391
0.3%
0.5%
0.0%
1.9%
10,069 16,875 195,014 205,677 246,550
20,237
100.0% 100.0% 100.0% 100.0% 100.0%
100.0%
Strategic Development Information and GIS Department
Total
2001
732,187
94.2%
9,420
1.2%
9,812
1.3%
15,168
2.0%
10,799
1.4%
1996
2007
578,152
849,941
88.6%
94.2%
20,493
8,657
3.1%
1.0%
9,901
23,348
1.5%
2.6%
21,538
9,742
3.3%
1.1%
13,459
9,074
2.1%
1.0%
8,440
1,513
1.3%
0.2%
651,983 777,386 902,275
100.0% 100.0% 100.0%
Page 55