South Africa is the sixth African country with the largest population, counting approximately 60.5 million individuals as of 2021. In 2023, the largest city in South Africa was Cape Town. The capital of Western Cape counted 3.4 million inhabitants, whereas South Africa's second largest city was Durban (eThekwini Municipality), with 3.1 million inhabitants. Note that when observing the number of inhabitants by municipality, Johannesburg is counted as largest city/municipality of South Africa.

From four provinces to nine provinces

Before Nelson Mandela became president in 1994, the country had four provinces, Cape of Good Hope, Natal, Orange Free State, and Transvaal and 10 “homelands” (also called Bantustans). The four larger regions were for the white population while the homelands for its black population. This system was dismantled following the new constitution of South Africa in 1996 and reorganized into nine provinces. Currently, Gauteng is the most populated province with around 15.9 million people residing there, followed by KwaZulu-Natal with 11.68 million inhabiting the province. As of 2022, Black African individuals were almost 81 percent of the total population in the country, while colored citizens followed amounting to around 5.34 million.

A diverse population

Although the majority of South Africans are identified as Black, the country’s population is far from homogenous, with different ethnic groups usually residing in the different “homelands”. This can be recognizable through the various languages used to communicate between the household members and externally. IsiZulu was the most common language of the nation with around a quarter of the population using it in- and outside of households. IsiXhosa and Afrikaans ranked second and third with roughly 15 percent and 12 percent, respectively.

As of 2023, South Africa's population increased and counted approximately 62.3 million inhabitants in total, of which the majority inhabited Gauteng, KwaZulu-Natal, and the Western-Eastern Cape. Gauteng (includes Johannesburg) is the smallest province in South Africa, though highly urbanized with a population of over 16 million people according to the estimates. Cape Town, on the other hand, is the largest city in South Africa with nearly 3.43 million inhabitants in the same year, whereas Durban counted 3.12 million citizens. However, looking at cities including municipalities, Johannesburg ranks first. High rate of young population South Africa has a substantial population of young people. In 2024, approximately 34.3 percent of the people were aged 19 years or younger. Those aged 60 or older, on the other hand, made-up over 10 percent of the total population. Distributing South African citizens by marital status, approximately half of the males and females were classified as single in 2021. Furthermore, 29.1 percent of the men were registered as married, whereas nearly 27 percent of the women walked down the aisle. Youth unemployment Youth unemployment fluctuated heavily between 2003 and 2022. In 2003, the unemployment rate stood at 36 percent, followed by a significant increase to 45.5 percent in 2010. However, it fluctuated again and as of 2022, over 51 percent of the youth were registered as unemployed. Furthermore, based on a survey conducted on the worries of South Africans, some 64 percent reported being worried about employment and the job market situation.

ObjectiveGlycated haemoglobin (HbA1c) is recommended as an additional tool to glucose-based measures (fasting plasma glucose [FPG] and 2-hour plasma glucose [2PG] during oral glucose tolerance test [OGTT]) for the diagnosis of diabetes; however, its use in sub-Saharan African populations is not established. We assessed prevalence estimates and the diagnosis and detection of diabetes based on OGTT, FPG, and HbA1c in an urban black South African population.Research Design and MethodsWe conducted a population-based cross-sectional survey using multistage cluster sampling of adults aged ≥18 years in Durban (eThekwini municipality), KwaZulu-Natal. All participants had a 75-g OGTT and HbA1c measurements. Receiver operating characteristic (ROC) analysis was used to assess the overall diagnostic accuracy of HbA1c, using OGTT as the reference, and to determine optimal HbA1c cut-offs.ResultsAmong 1190 participants (851 women, 92.6% response rate), the age-standardised prevalence of diabetes was 12.9% based on OGTT, 11.9% based on FPG, and 13.1% based on HbA1c. In participants without a previous history of diabetes (n = 1077), using OGTT as the reference, an HbA1c ≥48 mmol/mol (6.5%) detected diabetes with 70.3% sensitivity (95%CI 52.7–87.8) and 98.7% specificity (95%CI 97.9–99.4) (AUC 0.94 [95%CI 0.89–1.00]). Additional analyses suggested the optimal HbA1c cut-off for detection of diabetes in this population was 42 mmol/mol (6.0%) (sensitivity 89.2% [95%CI 78.6–99.8], specificity 92.0% [95%CI: 90.3–93.7]).ConclusionsIn an urban black South African population, we found a high prevalence of diabetes and provide the first evidence for the utility of HbA1c for the diagnosis and detection of diabetes in black Africans in sub-Saharan Africa.

Abstract

The South Africa Enterprise Survey was conducted between January and December 2007. Data from 1057 establishments in private manufacturing and services sectors were analyzed. The sample included enterprises with more than four employees (937 companies) as well as micro firms, establishments with less than 5 workers, (120 observations). The survey targeted establishments in Johannesburg, Cape Town, Port Elizabeth and Durban.

The objective of the survey is to obtain feedback from enterprises in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The South Africa Enterprise Survey 2007 included enterprises with more than four employees as well as micro establishments, firms with less than five workers. There are 120 micro establishments in the sample.

The sample for enterprises with more than four employees was designed using stratified random sampling with strata defined by region, sector and firm size.

Establishments located in Johannesburg, Cape Town, Port Elizabeth and Durban were interviewed.

Following the ISIC (revision 3.1) classification, the following industries were targeted: all manufacturing sectors (group D), construction (group F), retail and wholesale services (subgroups 52 and 51 of group G), hotels and restaurants (group H), transport, storage, and communications (group I), and computer and related activities (sub-group 72 of group K). For establishments with five or more full-time permanent paid employees, this universe was stratified according to the following categories of industry: 1. Manufacturing: Food and Beverages (Group D, sub-group 15), Machinery and Equipment (Group D, sub-group 29), Electrical Machinery and Equipment (Group D, sub-group 31); 2. Manufacturing: Textiles (Group D, sub-group 17), Garment (Group D, sub-group 18), Leather and Footwear (Group D, sub-group 19), Paper and Paper Products (Group D, sub-group 21), Printing and Publishing (Group D, sub-group 22); 3. Manufacturing: Non-Metallic Mineral Products (Group D, sub-group 26), Basic Metals (Group D, sub-group 27), Fabricated Metal Products (Group D, sub-group 28); 4. Manufacturing: Wood and Wood Products (Group D, sub-group 20), Furniture (Group D, sub-group 36) 5. Manufacturing: Refined Petroleum Products (Group D, sub-group 23), Chemical Products (Group D, sub-group 24), Rubber and Plastics (Group D, sub-group 25) 6. Retail Trade: (Group G, sub-group 52); 7. Rest of the universe, including: • Other Manufacturing (Group D excluding sub-groups in strata 1-5); • Construction (Group F); • Wholesale trade (Group G, sub-group 51); • Hotels, bars and restaurants (Group H); • Transportation, storage and communications (Group I); • Computer related activities (Group K, sub-group 72).

Size stratification was defined following the standardized definition used for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers.

The implementing agency (EEC Canada) was unable to obtain a satisfactory sample frame from South African statistical agency (STASA) or its Department of Revenue. The best alternative solution was a list obtained from the Department of Trade and Industry Companies and Intellectual Property Registration Office (CIPRO), which contained about 800000 establishments when delineating in-scope cities and industries, but which had incomplete firm characteristics necessary for stratification purposes (e.g. contact information, size). In order to determine the sample frame, EEC Canada randomly drew 9550 units and contacted them.

In South Africa, the survey included panel data collected from establishments surveyed in the 2003 Investment Climate Survey (ICS) of South Africa. That survey included establishments in the manufacturing and the rest of universe strata, distributed across Gauteng (Johannesburg), KwaZulu Natal (Durban), Western Cape (Cape Town) and Eastern Cape (Port Elizabeth) provinces.

In order to collect the largest possible set of panel data, an attempt was made to contact and survey valid establishments (579) in the panel list provided which was part of the Enterprise Survey's scope. Of the 716 establishments provided to EEC Canada from those surveyed in 2003, there were 35 doubles, 8 out-of-scope, 89 excluded from this survey by The World Bank to avoid over representing Construction in a single Residual stratum, and 5 with undefined ISIC codes. This left a total potential of 579 panel establishments. EEC Canada surveyed 231 panel establishments or 40% of the total potential panels without eliminating those establishments which had closed. Once eliminated, this percentage coverage exceeded 55%. Given the non-random nature of panel establishment selection, these establishments are not allocated probability weights in the final dataset.

In this survey, the micro establishment stratum covers all establishments of the targeted categories of economic activity with less than 5 employees located in Johannesburg. The implementing agency selected an aerial sampling approach to estimate the population of establishments and select the sample in this stratum for all states of the survey.

First, to randomly select individual micro establishments for surveying, the following procedure was followed: i) select districts and specific zones of each district where there was a high concentration of micro establishments; ii) count all micro establishments in these specific zones; iii) based on this count, create a virtual list and select establishments at random from that virtual list; and iv) based on the ratio between the number selected in each specific zone and the total population in that zone, create and apply a skip rule for selecting establishments in that zone.

The districts and the specific zones were selected at first according to local sources. The EEC team then went in the field to verify the sources and to count micro establishments. Once the count for each zone was completed, the numbers were sent back to EEC head office in Montreal.

At the head office, the count by zone was converted into one list of sequential numbers for the whole survey region, and a computer program performed a random selection of the determined number of establishments from the list. Then, based on the number that the computer selected in each specific zone, a skip rule was defined to select micro establishments to survey in that zone. The skip rule for each zone was sent back to the EEC field team.

In Johannesburg, enumerators were sent to each zone with instructions how to apply the skip rule defined for that zone as well as how to select replacements in the event of a refusal or other cause of non-participation.

For complete information about sampling methodology, refusal rate and weighting please review "South Africa Enterprise Survey 2007 Implementation Report" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Micro

The Population Council is the research partner to DREAMS—a global partnership to reduce HIV infections among adolescent girls and young women (AGYW) in over 10 sub-Saharan African countries and Haiti. DREAMS aims to reduce HIV infections among AGYW. This dataset contains data from two independent cross-sectional surveys with men (aged 20–40 years) interviewed in 2017 and 2018 at community hot spots or HIV service sites in Ethekwini (Durban), South Africa. These data are from a Population Council-led implementation science study to assess HIV risk and service use among male partners of AGYW.

Abstract

The survey was undertaken in 2005 and conducted face-to-face interviews with a sample of 1 000 adults from Cape Town, Durban, Pretoria and Johannesburg, where ninety percent of the country's Jewish population reside.

Geographic coverage

The survey covered selected Jewish households in Cape Town, Durban, Pretoria and Johannesburg

Analysis unit

Households and individuals

Universe

The target population of the survey consists of Jewish South Africans.

Kind of data

Sample survey data

Mode of data collection

Face-to-face [f2f]

Research instrument

A single questionnaire was used for the study