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Inside South Africa - Demographics

Market Decisions GIS, Statssa (www.statssa.gov.za)

CALCULATION OF THE POPULATION UPDATE 2014

South Africa’s Population Census 2011 was released in 2012 by Statistics SA. Market Decisions updates the information with data from the municipalities. Between 1996, 2001 and 2011, there have been changes in boundaries and sub-places. The only data that can be adequately compared is at Ward level. The level of information on illegal residents will always be problematical. The population data as extracted from Census 2011 by province, is outlined in the Table below:



Province

Black_African

Coloured

Indian_Asian

White

Other_Race

Group

Eastern Cape

5,660,230

541,850

27,929

310,450

21,595

6,562,054

Free State

2,405,533

83,844

10,398

239,026

6,790

2,745,591

Gauteng

9,493,684

423,594

356,574

1,913,884

84,527

12,272,263

KwaZulu-Natal

8,912,921

141,376

756,991

428,842

27,170

10,267,300

Limpopo

5,224,754

14,415

17,881

139,359

8,459

5,404,868

Mpumalanga

3,662,219

36,611

27,917

303,595

9,597

4,039,939

North West

3,152,063

71,409

20,652

255,385

10,444

3,509,953

Northern Cape

576,986

461,899

7,827

81,246

17,903

1,145,861

Western Cape

1,912,547

2,840,404

60,761

915,053

93,969

5,822,734

Total Population

41,000,937

4,615,402

1,286,930

4,586,840

280,454

51,770,563




% Distribution by Group

Black_African

Coloured

Indian_Asian

White

Other_Race

Group

Eastern Cape

86.3%

8.3%

0.4%

4.7%

0.3%

100.0%

Free State

87.6%

3.1%

0.4%

8.7%

0.2%

100.0%

Gauteng

77.4%

3.5%

2.9%

15.6%

0.7%

100.0%

KwaZulu-Natal

86.8%

1.4%

7.4%

4.2%

0.3%

100.0%

Limpopo

96.7%

0.3%

0.3%

2.6%

0.2%

100.0%

Mpumalanga

90.7%

0.9%

0.7%

7.5%

0.2%

100.0%

North West

89.8%

2.0%

0.6%

7.3%

0.3%

100.0%

Northern Cape

50.4%

40.3%

0.7%

7.1%

1.6%

100.0%

Western Cape

32.8%

48.8%

1.0%

15.7%

1.6%

100.0%




% Distribution by Province

Black_African

Coloured

Indian_Asian

White

Other_Race

Group

Eastern Cape

13.8%

11.7%

2.2%

6.8%

7.7%

12.7%

Free State

5.9%

1.8%

0.8%

5.2%

2.4%

5.3%

Gauteng

23.2%

9.2%

27.7%

41.7%

30.1%

23.7%

KwaZulu-Natal

21.7%

3.1%

58.8%

9.3%

9.7%

19.8%

Limpopo

12.7%

0.3%

1.4%

3.0%

3.0%

10.4%

Mpumalanga

8.9%

0.8%

2.2%

6.6%

3.4%

7.8%

North West

7.7%

1.5%

1.6%

5.6%

3.7%

6.8%

Northern Cape

1.4%

10.0%

0.6%

1.8%

6.4%

2.2%

Western Cape

4.7%

61.5%

4.7%

19.9%

33.5%

11.2%

Total Population

100.0%

100.0%

100.0%

100.0%

100.0%

100.0%



The comparison between StatsSA Population update for 2015 is compared below with Market Decisions figures. There is a marked difference between the data sets for Eastern Cape and KwaZulu-Natal.

Stats SA 2015

Market Decisions 2015

Eastern Cape

6,916,185

6,807,414

Free State

2,617,941

2,831,092

Gauteng

13,200,349

13,208,423

KwaZulu-Natal

10,919,077

10,752,715

Limpopo

5,726,792

5,716,046

Mpumalanga

4,283,888

4,240,588

North West

3,706,962

3,671,417

Northern Cape

1,185,628

1,184,671

Western Cape

6,200,098

6,263,954

Grand Total

54,756,920

54,676,318



The variances can be explained as follows:

  • The Eastern Cape residents move between the Western Cape and the border towns between KwaZulu-Natal and the Eastern Cape.
  • The KwaZulu-Natal variance is best explained by the dual homes of residents who for example have a home in Umlazi Township in Durban and perhaps another in the rural area of Umvoti.
  • The Free State has major unemployment problems but the main cities are experiencing an influx from Northern Cape and North West.
  • The other major problem with population data is the presence of illegal or legal residents from the African continent. Undocumented illegal residents are excluded. They do represent a hefty 7 to 10% of our population.

The population density is outlined below:


Inequality in South Africa

The two images below depict the difference between the socio-economic states of the South African population. There is vast discrepancy between the upper and lower income classes. While the majority of the South African population is disadvantaged, there remains a small percentage of wealthy people located in the major cities.

Deprived population



Wealthy Population



Births

The post-2015 Sustainable Development Goals (SDGs) set for the period 2016 to 2030’s goal 16 calls for free and universal birth registration by 2030 as a way of promoting inclusive and sustainable access to essential services (UNICEF, 2014).

According to the Amendment Act all children born in South Africa must be registered within 30 days of their birth. However, it is still possible to register births after 30 days provided reasons for non-compliance are provided (DHA, 2014). Between 1994 and 2003 total birth registrations increased consistently from 667 107 to 1 677 415. The results further show that during the period 2004 to 2007 total birth registrations took a downward trend from 1 475 809 to 1 119 712 and thereafter there was no noticeable pattern from 2008 up to 2010. Between 2011 and 2014, a consistent decline in total birth registrations was noted again from 1 202 377 in 2011 to 1 161 159 in 2014.

13% of all births are attributed to young mothers (aged 15-19). By region, the highest number of births were registered in Gauteng (303 660), followed by KwaZulu-Natal (235 692) and Limpopo (137 162). Northern Cape had the lowest number, accounting for 31 210 of all birth registrations.



Deaths

The level of mortality is one of the indicators of the well-being and health status of a country, hence its inclusion, among others, in the construction of human development indices, the Millennium Development Goals (MDGs), and in the multi-dimensional approach to the measurement of poverty.

The quality of death registration data can be affected by the extent of late registrations, timeliness of death registration; completeness of information recorded; ill-defined causes of death, and underreporting of causes – especially in the case of HIV/AIDS. Public health programmes and researchers who rely on this data need to be aware of the level of data quality for statistical reliability.

Less than 2% of 2014 registered deaths had missing or unknown information on age of deceased, sex of deceased and province of death occurrence

The number of registered deaths processed by Stats SA for the period 1997−2014 shows that they increased yearly from a low of 317 727 deaths in 1997 and reached a peak of 614 014 deaths in 2006. The results further show that from 2007, a consistent downward trend was observed from 605 949 deaths to 453 360 deaths in 2014. The number of deaths processed for 2014 indicates a decrease of 4,2% from a total of 473 384 deaths that occurred in 2013. These results indicate that the level of mortality is declining in the country. However, the overall number of deaths per year is expected to increase as figures are updated with late registrations or delayed death notification forms.

The distribution of deaths by province of death occurrence, shows that the highest proportion of deaths (21,3%) occurred in Gauteng, followed by KwaZulu-Natal (17,5%) and then Eastern Cape at 14,7%. The lowest proportion of deaths occurred in Northern Cape (3,1%). The order of province of usual residence of the deceased was the same as that of death occurrence, with Gauteng accounting for the highest proportion of deaths (20,4%), followed by KwaZulu-Natal (16,9%) and Eastern Cape (14,7%). Similarly, Northern Cape (3,1%) accounted for the lowest proportion with regard to deceased registered as usual residents of the province. These percentages are reflective of the population sizes of the provinces of death occurrence or usual residence. Deaths can occur outside the usual residence of the deceased:

The figure below shows deaths by age and year.

Non-natural causes of death comprise all deaths that were not attributable, or may not have been attributable to natural causes comprise 10% of all deaths.


Migration

People have moved from their home countries for centuries, for a variety of reasons. The Irish famine resulted in people moving to the United States and slavery was the cause of massive migration from Africa to the colonies. The Huguenots came to South Africa after being persecuted by Catholics.

In South Africa, the country has a sad past in that the homelands were created as separate entities outside of a rigid segregation system which was advantageous to a small minority. There was an increase in migration in 1994 when the country became a free and democratic society. More people moved from the rural homelands to the urban cities. There will always be a perpetual migration between rural and urban. This is because of:

  • Economic opportunities, lack of prospects in their home province
  • Education where students who study at a specific university may choose to stay in the city in which the university is located
  • Young people are lured by to the big cities by the promise of money and jobs
  • Intolerance or human rights abuses
  • Falling birth rates may result in countries likely to experience labour shortage
  • Natural disasters, such as droughts, floods, etc.
  • Retirement, older people moving to the coast or quiet places

In South Africa, the provinces where the migration levels are high remain Gauteng and Western Cape. However, in recent years, the lack of employment has meant that many of the new entrants to these provinces remain unemployed and try to eke out a living on an ad-hoc basis. The graphs below show the net migration to and from each province. North West Province attracted many people because of the mines in the area. Mpumalanga attracts residents from KwaZulu-Natal. The close proximity of Mpumalanga and KwaZulu-Natal to Southern African countries make them an ideal place for trade and more accessible job opportunities.


The graph below shows the incoming and outgoing migration by Province.


Demographics summary

Market Decisions has analysed the data for population inequality, births, deaths, migration per province. There was a marked difference between the provincial population data sets for Eastern Cape and KwaZulu-Natal between StatsSA and Market Decisions. Keeping track of births, deaths as well as causes, ages and locations of deaths, all assists in the creation of data for a well-functioning health system. The key is to keep the information consistent so as to make it comparable across boundaries, regions, and timeframes.