As of 2022, South Africa's population increased and counted approximately 60.6 million inhabitants in total, of which the majority (roughly 49.1 million) were Black Africans. Individuals with an Indian or Asian background formed the smallest population group, counting approximately 1.56 million people overall. Looking at the population from a regional perspective, Gauteng (includes Johannesburg) is the smallest province of South Africa, though highly urbanized with a population of nearly 16 million people.

Increase in number of households

The total number of households increased annually between 2002 and 2022. Between this period, the number of households in South Africa grew by approximately 65 percent. Furthermore, households comprising two to three members were more common in urban areas (39.2 percent) than they were in rural areas (30.6 percent). Households with six or more people, on the other hand, amounted to 19.3 percent in rural areas, being roughly twice as common as those in urban areas.

Main sources of income

The majority of the households in South Africa had salaries or grants as a main source of income in 2019. Roughly 10.7 million drew their income from regular wages, whereas 7.9 million households received social grants paid by the government for citizens in need of state support.

South Africa Population: 15 to 64 Years: White data was reported at 2,978.591 Person th in Sep 2018. This records a decrease from the previous number of 2,987.055 Person th for Jun 2018. South Africa Population: 15 to 64 Years: White data is updated quarterly, averaging 3,143.298 Person th from Mar 2008 (Median) to Sep 2018, with 43 observations. The data reached an all-time high of 3,277.317 Person th in Mar 2008 and a record low of 2,978.591 Person th in Sep 2018. South Africa Population: 15 to 64 Years: White data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G001: Population.

Abstract

The 1970 South African Population Census collected data on dwellings and individuals' demographic, migration, family and employment details.

Geographic coverage

National coverage of the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal, and the so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, Kwandebele, Transkei and Bophuthatswana.

Analysis unit

The units of analysis for the South African Census 1970 were households and individuals

Universe

The South African population census of 1970 covered all de jure household members (usual residents) of South Africa and the "national states".

The Census was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night were enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were not enumerated and included in the figures. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census/enumeration data [cen]

Sampling procedure

The 1970 Census was a full count for Whites, Coloureds and Asians, and a 5% sample for Blacks (Africans)

Sampling deviation

The country was divided into 400 census districts for the 1970 Census. In most cases the boundaries of the census districts corresponded with those of the magisterial districts. However, in some cases the boundaries did not correspond, particularly in the areas in and around the "National States". This was to facilitate the administration of the census and to make it easier to exclude figures of the "National states" from provincial totals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1970 Population Census of the Republic of South Africa questionnaires were: Form 01, to be completed by "Whites, Coloured and Asiatics" Form 02, to be completed by "Bantu" Form 03, for families, households and dwellings

Form 01 collected data on relationship to household head, population group, sex, age, marital status, place of birth, and citizenship, as well as usual place of residence, home language, religion, level of education and income. Employment data collected included occupation, employment status and industry type.

Form 02 collected data for African South Africans on relationship to household head, sex, age, marital status, fertility, place of birth, home language and literacy, religion and level of education. Employment data collected included occupation, employment status and industry type.

Form 03 collected household data, including data on dwelling type, building material of dwelling walls, number of rooms and age of the dwelling. Data on home ownership. Data was also collected on the number and sex of household members and their relationship to the household head. Data on household heads included their population group, age and marital status. Income data was also collected, for husbands and wives. Data on home ownership, household size and domestic workers was also collected, but for Urban households only.

As of 2024, South Africa's population increased, counting approximately 63 million inhabitants. Of these, roughly 27.5 million were aged 0-24, while 654,000 people were 80 years or older. Gauteng and Cape Town are the most populated South Africa’s yearly population growth has been fluctuating since 2013, with the growth rate dropping below the world average in 2024. The majority of people lived in the borders of Gauteng, the smallest of the nine provinces in terms of land area. The number of people residing there amounted to 16.6 million in 2023. Although the Western Cape was the third-largest province, the city of Cape Town had the highest number of inhabitants in the country, at 3.4 million. An underemployed younger population South Africa has a large population under 14, who will be looking for job opportunities in the future. However, the country's labor market has had difficulty integrating these youngsters. Specifically, as of the fourth quarter of 2024, the unemployment rate reached close to 60 percent and 384 percent among people aged 15-24 and 25–34 years, respectively. In the same period, some 27 percent of the individuals between 15 and 24 years were economically active, while the labor force participation rate was higher among people aged 25 to 34, at 74.3 percent.

South Africa Population: Mid Year: White: Male: 70 to 74 Years data was reported at 105,238.000 Person in 2018. This records an increase from the previous number of 95,344.570 Person for 2017. South Africa Population: Mid Year: White: Male: 70 to 74 Years data is updated yearly, averaging 78,333.668 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 105,238.000 Person in 2018 and a record low of 55,969.000 Person in 2001. South Africa Population: Mid Year: White: Male: 70 to 74 Years data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G003: Population: Mid Year: by Group, Age and Sex.

In 1800, the population of modern day area of South Africa was approximately 1.44 million. Like most of the continent, the population of South Africa increased gradually through most of the 19th century, reaching 4.71 million by the start of the 20th century. Beginning in the 20th century however, the population would begin to rise exponentially as industrialization, advances in medicine and health, and the spread of vaccinations allowed for lower child mortality rates and increased life expectancy among adults. The population of South Africa would continue to rise exponentially for almost a century, going from just under 5 million at the start of the 1900s to almost 45 million by 2000. However, since the early 2000s, South Africa’s population growth has slowed, the result of a significant decrease in fertility rates in the country in recent years. In 2020, South Africa is estimated to have a population of 59.31 million.

Geographic coverage

The 1985 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

The 1985 Census dataset contains 9 data files. These refer to Development Regions demarcated by the South African Government according to their socio-economic conditions and development needs. These Development Regions are labeled A to J (there is no Region I, presumably because Statistics SA felt an "I" could be confused with the number 1). The 9 data files in the 1985 Census dataset refer to the following areas:

DEV REGION AREA COVERED A Western Cape Province including Walvis Bay B Northern Cape C Orange Free State and Qwaqwa D Eastern Cape/Border E Natal and Kwazulu F Eastern Transvaal, KaNgwane and part of the Simdlangentsha district of Kwazulu G Northern Transvaal, Lebowa and Gazankulu H PWV area, Moutse and KwaNdebele J Western Transvaal

Analysis unit

The units of analysis under observation in the South African census 1985 are households and individuals

Universe

The South African census 1985 census covered the provinces of the Cape, the Orange Free State, Transvaal, and Nata and the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Although the census was meant to cover all residents of the so called white areas of South Africa, in 88 areas door-to-door surveys were not possible and the population in these areas was enumerated by means of a sample survey conducted by the Human Sciences Research Council.

Mode of data collection

Face-to-face [f2f]

Research instrument

The1985 population census questionnaire was administered to each household and collected information on household and area type, and information on household members, including relationship within household, sex, age, marital status, population group, birthplace, country of citizenship, level of education, occupation, identity of employer and the nature of economic activities

Data appraisal

UNDER-ENUMERATION: The following under-enumeration figures have been calculated for the 1985 census. Estimated percentage distribution of undercount by race according to the HSRC: Percent undercount
Whites 7.6%
Blacks in the “RSA” 20.4% Blacks in the “National States” 15.1% Coloureds 1.0% Asians 4.6%

Abstract

The population census conducted in South Africa in 1985 covered the whole of South Africa, but excluded the "Homelands" of Transkei, Bophutatswana, Ciskei, and Venda. This dataset is the full census, as opposed to the 10% sample datasets provided by Statistics South Africa from 1996 onwards.

Geographic coverage

The 1985 census covered the so-called white areas of South Africa - the provinces of the Cape, the Orange Free State, Transvaal, and Natal - and the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

The 1985 Census dataset has 9 data files. These refer to Development Regions demarcated by the South African Government according to their socio-economic conditions and development needs. These Development Regions are labeled A to J (there is no Region I, presumably because Statistics SA felt an "I" could be confused with the number 1). The 9 data files in the 1985 Census dataset refer to the following areas:

DEV REGION AREA COVERED A Western Cape Province including Walvis Bay B Northern Cape C Orange Free State and Qwaqwa D Eastern Cape/Border E Natal and Kwazulu F Eastern Transvaal, KaNgwane and part of the Simdlangentsha district of Kwazulu G Northern Transvaal, Lebowa and Gazankulu H PWV area, Moutse and KwaNdebele J Western Transvaal

Analysis unit

The units of analysis under observation in the South African census 1985 are households and individuals

Universe

All persons who were present on Republic of South African territory during census night were enumerated. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were enumerated but not included in the final data. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The1985 population census questionnaire was administered to each household and collected information on household and area type, and information on household members, including relationship within household, sex, age, marital status, population group, birthplace, country of citizenship, level of education, occupation, identity of employer and the nature of economic activities

Data appraisal

UNDER-ENUMERATION: The following under-enumeration figures have been calculated for the 1985 census. Estimated percentage distribution of undercount by race according to the HSRC: Percent undercount
Whites 7.6%
Blacks in the “RSA” 20.4% Blacks in the “National States” 15.1% Coloureds 1.0% Asians 4.6%

In the second quarter of 2024, the unemployment rate among Black South Africans was 36.9 percent, marking a year-on-year change of 0.8 percent compared to the second quarter of 2023. On the other hand, the unemployment rate among white South Africans was 7.9 percent in the second quarter of 2024, with a 0.5 percent year-on-year change. Unemployment prevalent among youth and women The unemployment rate is the share of the labor force population that is unemployed, while the labor force includes individuals who are employed as well as those who are unemployed but looking for work. South Africa is struggling to absorb its youth into the job market. For instance, the unemployment rate among young South Africans aged 15-24 years reached a staggering 60.7 percent in the second quarter of 2023. Furthermore, women had higher unemployment rates than men. Since the start of 2016, the unemployment rate of women has been consistently more than that of men, reaching close to 36 percent compared to 30 percent, respectively. A new minimum wage and most paying jobs      In South Africa, a new minimum hourly wage went into effect on March 1, 2022. The minimum salary reached 23.19 South African rand per hour (1.44 U.S. dollars per hour), up from 21.69 South African rand per hour (1.35 U.S. dollars per hour) in 2021. In addition, the preponderance of employed South Africans worked between 40 and 45 hours weekly in 2021. Individuals holding Executive Management and Change Management jobs were the highest paid in the country, with salaries averaging 74,000 U.S. dollars per year.

South Africa Population: Mid Year: White: 50 to 54 Years data was reported at 315,881.000 Person in 2018. This records an increase from the previous number of 312,696.200 Person for 2017. South Africa Population: Mid Year: White: 50 to 54 Years data is updated yearly, averaging 315,744.136 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 342,894.000 Person in 2001 and a record low of 312,483.685 Person in 2016. South Africa Population: Mid Year: White: 50 to 54 Years data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G003: Population: Mid Year: by Group, Age and Sex.

Abstract

The 2003-2004 South African Demographic and Health Survey is the second national health survey to be conducted by the Department of Health, following the first in 1998. Compared with the first survey, the new survey has more extensive questions around sexual behaviour and for the first time included such questions to a sample of men. Anthropometric measurements were taken on children under five years, and the adult health module has been enhanced with questions relating to physical activity and micro-nutrient intake, important risk factors associated with chronic diseases. The 2003-2004 SADHS has introduced a chapter reporting on the health, health service utilisation and living conditions of South Africa's older population (60 years or older) and how they have changed since 1998. This has been introduced because this component of the population is growing at a much higher rate than the other age groups. The chapter on adolescent health in 1998 focussed on health risk-taking behaviours of people aged 15-19 years. The chapter has been extended in the 2003-2004 SADHS to include indicators of sexual behaviour of youth aged 15-24 years.

A total of 10 214 households were targeted for inclusion in the survey and 7 756 were interviewed, reflecting an 85 percent response rate. The survey used a household schedule to capture basic information about all the members of the household, comprehensive questionnaires to all women aged 15-49, as well as anthropometric measurements of all children five years and younger. In every second household, interviews of all men 15-59 were conducted and in the alternate households, interviews and measurements of all adults 15 years and older were done including heights, weights, waist circumference, blood pressure and peak pulmonary flow. The overall response rate was 75 percent for women, 67 percent for men, 71 percent for adults, and 84 percent for children. This is slightly lower than the overall response rate for the 1998 SADHS, but varied substantially between provinces with a particularly low response rate in the Western Cape.

OBJECTIVES

In 1995 the National Health Information System of South Africa (NHIS/SA) committee identified the need for improved health information for planning services and monitoring programmes. The first South African Demographic and Health Survey (SADHS) was planned and implemented in 1998. At the time of the survey it was agreed that the survey had to be conducted every five years to enable the Department of Health to monitor trends in health services.

STUDY LIMITATIONS AND RECOMMENDATIONS

Comparison of the socio-demographic characteristics of the sample with the 2001 Population Census shows an over-representation of urban areas and the African population group, and an under-representation of whites and Indian females. It also highlights many anomalies in the ages of the sample respondents, indicating problems in the quality of the data of the 2003 survey. Careful analysis has therefore been required to distinguish the findings that can be considered more robust and can be used for decision making. This has involved considering the internal consistency in the data, and the extent to which the results are consistent with other studies.

Some of the key demographic and adult health indicators show signs of data quality problems. In particular, the prevalence of hypertension, and the related indicators of quality of care are clearly problematic and difficult to interpret. In addition, the fertility levels and the child mortality estimates are not consistent with other data sources. The data problems appear to arise from poor fieldwork, suggesting that there was inadequate training, supervision and quality control during the implementation of the survey. It is imperative that the next SADHS is implemented with stronger quality control mechanisms in place. Moreover, consideration should be given to the frequency of future surveys. It is possible that the SADHS has become overloaded - with a complex implementation required in the field. Thus it may be appropriate to consider a more frequent survey with a rotation of modules as has been suggested by the WHO.

Geographic coverage

The SADHS sample was designed to be a nationally representative sample.

Analysis unit

Households and individuals

Universe

The population covered by the 2003-2004 SADHS is defined as the universe of all women age 15-49, all men 15-59 in South Africa.

Kind of data

Sample survey data

Sampling procedure

The SADHS sample was designed to be a nationally representative probability sample of approximately 10000 households. The country was stratified into the nine provinces and each province was further stratified into urban and non-urban areas.

The sampling frame for the SADHS was provided by Statistics South Africa (Stats SA) based on the enumeration areas (EAs) list of approximately 86000 EAs created during the 2001 census. Since the Indian population constitutes a very small fraction of the South African population, the Census 2001 EAs were stratified into Indian and non-Indian. An EA was classified as Indian if the proportion of persons who classified themselves as Indian during Census 2001 enumeration in that EA was 80 percent or more, otherwise it was classified as Non-Indian. Within the Indian stratum, EAs were sorted descending by the proportion of persons classified as Indian. It should be noted that some provinces and non-urban areas have a very small proportion of the Indian population hence the Indian stratum could not be further stratified by province or urban/non-urban. A sample of 1000 households was allocated to the stratum. Probability proportional to size (PPS) systematic sampling was used to sample EAs and the proportion of Indian persons in an EA was the measure of size. The non-Indian stratum was stratified explicitly by province and within province by the four geo types, i.e. urban formal, urban informal, rural formal and tribal. Each province was allocated a sample of 1000 households and within province the sample was proportionally allocated to the secondary strata, i.e. geo type. For both the Indian and Non-Indian strata the sample take of households within an EA was sixteen households. The number of visited households in an EA as recorded in the Census 2001, 09 Books was used as the measure of size (MOS) in the Non-Indian stratum.

The second stage of selection involved the systematic sampling of households/stands from the selected EAs. Funds were insufficient to allow implementation of a household listing operation in selected EAs. Fortunately, most of the country is covered by aerial photographs, which Statistics SA has used to create EA-specific photos. Using these photos, ASRC identified the global positioning system (GPS) coordinates of all the stands located within the boundaries of the selected EAs and selected 16 in each EA, for a total of 10080 selected. The GPS coordinates provided a means of uniquely identifying the selected stand. As a result of the differing sample proportions, the SADHS sample is not self-weighting at the national level and weighting factors have been applied to the data in this report.

A total of 630 Primary Sampling Units (PSUs) were selected for the 2003-2004 SADHS (368 in urban areas and 262 in non-urban areas). This resulted in a total of 10214 households being selected throughout the country1. Every second household was selected for the adult health survey. In this second household, in addition to interviewing all women aged 15-49, all adults aged 15 and over were eligible to be interviewed with the adult health questionnaire. In every alternate household selected for the survey, not interviewed with the adult health questionnaire, all men aged 15-59 years were also eligible to be interviewed. It was expected that the sample would yield interviews with approximately 10000 households, 12500 women aged 15-49, 5000 adults and 5000 men.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for each DHS can be found as an appendix in the final report for each study.

The survey utilised five questionnaires: a Household Questionnaire, a Women's Questionnaire, a Men's Questionnaire, an Adult Health Questionnaire and an Additional Children Questionnaire. The contents of the first three questionnaires were based on the DHS Model Questionnaires. These model questionnaires were adapted for use in South Africa during a series of meetings with a Project Team that consisted of representatives from the National Department of Health, the Medical Research Council, the Human Sciences Research Council, Statistics South Africa, National Department of Social Development and ORCMacro. Draft questionnaires were circulated to other interested groups, e.g. such as academic institutions. The Additional Children and Men's Questionnaires were developed to address information needs identified by stakeholders, e.g. information on children who were not staying with their biological mothers. All questionnaires were developed in English and then translated in all 11 official languages in South Africa (English, Afrikaans, isiXhosa, isiZulu, Sesotho, Setswana, Sepedi, SiSwati, Tshivenda, Xitsonga and isiNdebele).

a) The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education and relationship to the head of the household. Information was collected about social grants, work status and injuries experienced in the last month. An important purpose of the Household Questionnaire was to

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in South Gorin. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In South Gorin, the median household income for the households where the householder is White decreased by $3,706(9.07%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $40,862 in 2011 and $37,156 in 2021.
• Black or African American: As per the U.S. Census Bureau population data, in South Gorin, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

https://i.neilsberg.com/ch/south-gorin-mo-median-household-income-by-race-trends.jpeg" alt="South Gorin, MO median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in South Gorin.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented in 2022-inflation-adjusted dollars.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for South Gorin median household income by race. You can refer the same here

In the fourth quarter of 2023, the labor force participation rate among Black South Africans reached over 59 percent, marking a year-on-year change of two percent compared to the fourth quarter of 2022. However, the participation rate of the labor force among Indian/Asian South Africans dropped from about 61 percent in the previous year to 58 percent.

Abstract

The purpose of this study was to explore the relationship between truth acceptance and reconciliation among South Africans during and since the political transition from Apartheid to democracy. The study investigated the extent to which South Africans participated in the Truth and Reconciliation Commission and the degree to which they were "reconciled." The Truth and Reconciliation Commission (TRC) was based on the Promotion of National Unity and Reconciliation Act of 1995. The TRC investigated past gross human rights violations and granted amnesty to individuals in exchange for full and public disclosure of information related to these crimes. The hypothesis that truth acceptance leads to reconciliation was tested in this research. Data were collected through a systematic survey of South Africans. Nearly all relevant segments of the South African population were included in the sample, as well as representative subsamples of at least 250 respondents of most major racial/ethnic/linguistic groups.

Questions about the TRC investigated respondent awareness, knowledge, and approval of the activities of the TRC. Respondents were asked for their opinions on the effectiveness of the TRC in its efforts to provide a true and unbiased account of South Africa's history and in awarding compensation to those who suffered abuses under the Apartheid regime. Other questions included those eliciting respondents views on the importance of revealing the truth about the past and achieving racial reconciliation.

Geographic coverage

The Survey of Truth and Reconciliation in South Africa, 2000-2001 had national coverage.

Analysis unit

Individuals

Universe

The universe under investigation included all South Africans aged 18+.

Kind of data

Sample survey data

Sampling procedure

The area probability sample included a primary sample of South Africans of all races and a boost sample of white South Africans. Representative subsamples of at least 250 respondents of most major racial, ethnic, and linguistic groups were also included.

The sampling was divided into two parts – a primary sample, including South Africans of all races, and a boost sample of white South Africans. In the main sample, 3,139 interviews were completed. The Boost Sample was composed only of white South Africans, with a control for language (English versus Afrikaans). A total of 588 additional whites was interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the Survey of Truth and Reconciliation in South Africa, 2000-2001 includes individual characteristics, respondent awareness, knowledge, and approval of the activities of the TRC, how important it was for respondents to find out the truth about the past and achieve racial reconciliation.

Response rate

The overall response rate for the survey was approximately 87 percent (after treating “break-offs” as unsuccessful interviews). The main reason for failing to complete the interview was inability to contact the respondent; refusal to be interviewed accounted for approximately 27 percent of the failed interviews. From the response rate alone, the representativeness of the sample seems assured. Such a high rate of response can be attributed to the general willingness of the South African population to be interviewed, the large number of call-backs we employed, and the use of an incentive for participating in the interview (the incentive was a magnetic torch (flashlight), with which the respondents were quite pleased).

South Africa Population: Mid Year: White: Female: 0 to 4 Years data was reported at 111,757.000 Person in 2018. This records a decrease from the previous number of 115,269.326 Person for 2017. South Africa Population: Mid Year: White: Female: 0 to 4 Years data is updated yearly, averaging 126,548.037 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 148,888.000 Person in 2001 and a record low of 111,757.000 Person in 2018. South Africa Population: Mid Year: White: Female: 0 to 4 Years data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G003: Population: Mid Year: by Group, Age and Sex.

Abstract

The 1980 South African Population Census was a count of all persons present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980). The purpose of the population census was to collect detailed statistics on population size, composition and distribution at small area level. The 1980 South African Population Census contains data collected on HOUSEHOLDS: household goods and dwelling characteristics as well as employment of domestic workers; INDIVIDUALS: population group, citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities

Geographic coverage

The 1980 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered areas in the so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, and Kwandebele. The 1980 South African census excluded the "independent states" of Bophuthatswana, Transkei, and Venda. A census data file for Bophuthatswana was released with the final South African Census 1980 dataset.

Analysis unit

Households and individuals

Universe

The 1980 South African census covered all household members (usual residents).

The 1980 South African Population Census was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980) were enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were not enumerated and included in the figures. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census enumeration data

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1980 Population Census questionnaire was administered to all household members and covered household goods and dwelling characteristics, and employment of domestic workers. Questions concerning individuals included those on citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities.

The following questions appear in the questionnaire but the corresponding data has not been included in the data set: PART C: PARTICULARS OF DWELLING: 2. How many separate families (i) Number of families (ii) Number of non-family persons (iii) total number of occupants [i.e. persons in families shown against (i) plus persons shown against 3. Persons employed by household Full-time, Part-time (a) How many persons employed as domestics (b) Total cash wages paid to above –mentioned persons for April 1980 4. Ownership – Do not answer this question if your dwelling is on a farm. (i) Own dwelling – (Including hire-purchase, sectional title property or property of wife): (a) Is the dwelling Fully paid Partly paid-off (b) If partly paid-off, state monthly repayment (include housing subsidy, but exclude insurance. (ii) Rented or occupied free dwelling : (a) Is the dwelling occupied free, rented furnished, rented unfurnished (b) If rented, state monthly rent (c) Is the dwelling owned by the employer? (d) Does it belong to the state, SA Railways, a provincial administration, a divisional council, or a municipality or other local authority? PART D: PARTICULARS OF THE FAMILY 1. Number of members in the family 2. Occupation. (Nature of work done) (a) Head of family (b) Wife 3. Annual income of head of family and wife. Annual income of: Head, Wife (if applicable)

South Africa Population: Mid Year: White: 40 to 44 Years data was reported at 312,909.000 Person in 2018. This records a decrease from the previous number of 328,421.704 Person for 2017. South Africa Population: Mid Year: White: 40 to 44 Years data is updated yearly, averaging 340,705.303 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 356,735.000 Person in 2001 and a record low of 312,909.000 Person in 2018. South Africa Population: Mid Year: White: 40 to 44 Years data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G003: Population: Mid Year: by Group, Age and Sex.

In 2021, Black South Africans were the largest group in the country accessing the internet via a smartphone. Some 66 percent of Black South Africans used a smartphone to go online, while the white population followed with nearly 20 percent. Indian/Asian individuals, on the other hand, were the population group with the smallest share of internet access via a smartphone. In 2022, Black South Africans were the largest population group in the country, followed by the colored and white populations.

Abstract

An omnibus survey is done quarterly and its purpose is to give clients an opportunity to participate in a national survey at low cost. A number of clients’ questions are combined into one questionnaire. This questionnaire is usually administered to probability sample of 2200 respondents in the whole country (South Africa). The HSRC undertook 2 Omnibus surveys in 1995 - in February and September. The September 1995 omnibus survey was undertaken over the period 04 September to 06 October 1995. The data from this survey was available in December 1995. The fieldwork was done on a countrywide basis including all nine provinces.

Geographic coverage

The survey had national coverage, including coverage of the 'homelands" of Ciskei and Venda.

Analysis unit

Units of analysis in the survey included individuals

Universe

The universe included all household residents 18 years old or older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The South African population of persons 18 years and older was stratified according to: Province (Western Cape, Eastern Cape, Northern Cape, Orange Free State, Natal/KwaZulu, Eastern Transvaal, PWV, North Western Province, Northern Transvaal) Socio-economic classification: Rural areas in former self-governing and TBVC states Squatter areas in former non-white urban (metro and non- metro areas) Hostels and hotels Former urban areas for coloureds Former urban areas for a Asians Former urban areas for blacks Former urban (non- metro) areas for whites Former urban (metro) areas for whites Rural areas, excluding the former self-governing and TBVC states

The sample allocation to these strata was done roughly proportional to the adjusted 1991 populatio n census figures with a few exceptions, among which was to ensure a minimal provincial total of 120. Multistage stratified cluster (probability) sampling was used to draw the respondents with the adjusted 1991 population census figures as measure of size. Census enumerator areas and similar areas were used as the clusters in the pen-ultimate sampling stage, from which an equal number, viz. one or two by four households were drawn. All clusters were drawn with probability proportional to size, whilst households were drawn from the final clusters with equal probability (systematically). Respondents were drawn at random from qualifying household members. In addition, population of live-in domestic workers was sampled in relation to their residence in already drawn households.

Mode of data collection

Face-to-face [f2f]

Abstract

The 1980 South African Population Census was a count of all persons present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980). The purpose of the population census was to collect, process and disseminate detailed statistics on population size, composition and distribution at small area level. The 1980 South African Population Census contains data collected on HOUSEHOLDS: household goods and dwelling characteristics as well as employment of domestic workers; INDIVIDUALS: population group, citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities

Geographic coverage

The 1980 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered areas in the following so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, and Kwandebele. The 1980 South African census excluded the areas of the Transkei and Bophuthatswana. A census data file for Bophuthatswana was released with the final South African Census 1980 dataset.

Analysis unit

The units of analysis of the 1980 census includes households, individuals and institutions

Universe

The 1980 South African census covered all household members (usual residents).

The 1980 South African Population Census was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980) were enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were not enumerated and included in the figures. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1980 Population Census questionnaire was administered to all household members and covered household goods and dwelling characteristics, and employment of domestic workers. Questions concerning individuals included those on citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities.

The following questions appear in the questionnaire but the corresponding data has not been included in the data set: PART C: PARTICULARS OF DWELLING: 2. How many separate families (i) Number of families (ii) Number of non-family persons (iii) total number of occupants [i.e. persons in families shown against (i) plus persons shown against 3. Persons employed by household Full-time, Part-time (a) How many persons are employed as domestics by you? (Include garden workers) (b) Total cash wages paid to above –mentioned persons for April 1980 4. Ownership – Do not answer this question if your dwelling is on a farm. (i) Own dwelling – (Including hire-purchase, sectional title property or property of wife): (a) Is the dwelling Fully paid Partly paid-off (b) If partly paid-off, state monthly repayment (include housing subsidy, but exclude insurance. (ii) Rented or occupied free dwelling : (a) Is the dwelling occupied free, rented furnished, rented unfurnished (b) If rented, state monthly rent (c) Is the dwelling owned by the employer? (d) Does it belong to the state, SA Railways, a provincial administration, a divisional council, or a municipality or other local authority? PART D: PARTICULARS OF THE FAMILY 1. Number of members in the family 2. Occupation. (Nature of work done) (a) Head of family (b) Wife 3. Annual income of head of family and wife. Annual income of: Head, Wife (if applicable)