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: Mid Year: Indian and Asian: Female: Above 80 Years data was reported at 14,151.000 Person in 2018. This records an increase from the previous number of 10,427.150 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Female: Above 80 Years data is updated yearly, averaging 7,303.049 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 14,151.000 Person in 2018 and a record low of 3,838.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: Female: Above 80 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.

South Africa Population: Mid Year: Indian and Asian: Male: 30 to 34 Years data was reported at 74,569.000 Person in 2018. This records a decrease from the previous number of 74,583.874 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Male: 30 to 34 Years data is updated yearly, averaging 58,776.088 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 74,583.874 Person in 2017 and a record low of 42,988.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: Male: 30 to 34 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 2022, women in South Africa represented 51.1 percent of the population. The majority of them were White South African, reaching 51.7 percent of the population. On the other hand, Indian/Asian women had a share of 48.9 percent.

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.

South Africa Population: Mid Year: Indian and Asian: 20 to 24 Years data was reported at 103,662.000 Person in 2018. This records a decrease from the previous number of 105,703.736 Person for 2017. South Africa Population: Mid Year: Indian and Asian: 20 to 24 Years data is updated yearly, averaging 111,125.991 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 114,481.589 Person in 2006 and a record low of 103,662.000 Person in 2018. South Africa Population: Mid Year: Indian and Asian: 20 to 24 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 ** percent of Black South Africans used a smartphone to go online, while the white population followed with nearly ** 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

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

South Africa Population: Mid Year: Indian and Asian: 50 to 54 Years data was reported at 91,020.000 Person in 2018. This records an increase from the previous number of 88,080.250 Person for 2017. South Africa Population: Mid Year: Indian and Asian: 50 to 54 Years data is updated yearly, averaging 74,090.445 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 91,020.000 Person in 2018 and a record low of 59,531.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: 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.

As of 2019, 14.6 million Black Africans were attending classes at educational institutions in South Africa, which marks over 34 percent of South Africa's total Black population. Another 1.25 million Coloreds, 294 thousand with an Indian/Asian background, as well as 865 thousand white individuals were attending schools and higher educational institutions.

South Africa Population: Mid Year: Indian and Asian: 25 to 29 Years data was reported at 124,722.000 Person in 2018. This records an increase from the previous number of 124,273.103 Person for 2017. South Africa Population: Mid Year: Indian and Asian: 25 to 29 Years data is updated yearly, averaging 121,309.750 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 124,797.624 Person in 2013 and a record low of 93,363.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: 25 to 29 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.

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Chad, South Sudan, Somalia, and the Central African Republic, the population increase peaks at over 3.4 percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. African cities are also growing at large rates. Indeed, the continent has three megacities and is expected to add four more by 2050. Furthermore, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria, by 2035.

South Africa Population: Mid Year: Indian and Asian: Male: 70 to 74 Years data was reported at 15,389.000 Person in 2018. This records an increase from the previous number of 13,060.203 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Male: 70 to 74 Years data is updated yearly, averaging 9,145.247 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 15,389.000 Person in 2018 and a record low of 6,134.328 Person in 2002. South Africa Population: Mid Year: Indian and Asian: 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.

As of 2018, the share of children in south Africa who stayed with a mother in the household was significantly higher than children staying in households with their biological father across all population groups. However, the gap was largest among the Black African population, where the share of children living with their father was as low as 31.7 percent, compared to the 74 percent for mothers in households. The story was different among Indian/Asian and White population with a higher share of the children living with their biological parents.

South Africa is the southernmost country in Africa. It covers an area of 1,221,037 square kilometres (471,445 square miles). South Africa has three capital cities: executive Pretoria, judicial Bloemfontein and legislative Cape Town. The largest city is Johannesburg. About 80% of South Africans are of Black African ancestry, divided among a variety of ethnic groups speaking different African languages. The remaining population consists of Africa's largest communities of European (White South Africans), Asian (Indian South Africans and Chinese South Africans), and Multiracial (Coloured South Africans) ancestry.

Source: Objaverse 1.0 / Sketchfab

HLA Class II Haplotype Frequency Distributions (for 99% haplotypes per population) and HLA Class II Simulated Populations (Genotype level information for sample sizes of 1000, 5000, 10000 simulated individuals) for 4 broad and 21 detailed US population groups.

Broad population groups: African Americans (AFA), Asian and Pacific Islanders (API), Caucasians (CAU), Hispanics (HIS).

Detailed population groups: African American (AAFA), African (AFB), South Asian Indian (AINDI), American Indian - South or Central American (AISC), Alaska native of Aleut (ALANAM), North American Indian (AMIND), Caribbean Black (CARB), Caribbean Hispanic (CARHIS), Caribbean Indian (CARIBI), European Caucasian (EURCAU), Filipino (FILII), Hawaiian or other Pacific Islander (HAWI), Japanese (JAPI), Korean (KORI), Middle Eastern or North Coast of Africa (MENAFC), Mexican or Chicano (MSWHIS), Chinese (NCHI), Hispanic - South or Central American (SCAHIS), Black - South or Central American (SCAMB), Southeast Asian (SCSEAI), Vietnamese (VIET).

Abstract

The 1993 Project for Statistics on Living Standards and Development was an integrated household survey similar in design to a World Bank Living Standards Measurement Survey. The survey collected data on the socio-economic condition of households. Households in Kwazulu-Natal province were re-surveyed from March to June 1998 for the Kwazulu-Natal Income Dynamics Study. Combining these two survey datasets has yielded a panel (or longitudinal) dataset in which the same individuals and households have been interviewed at two points in time, 1993 and 1998. These are the first two waves of the KIDS panel study.

The institutions collaborating in the KIDS study include the University of KwaZulu-Natal (UKZN), the University of Wisconsin-Madison and the International Food Policy Research Institute (IFPRI).

Geographic coverage

The survey covered households in the KwaZulu-Natal Province, on the east coast of South Africa.

Analysis unit

Households and individuals

Universe

The Kwazulu Natal Income Dynamics Study 1993-1998 covered all household members.

Kind of data

Sample survey data

Sampling procedure

The 1993 sample was selected using a two-stage self-weighting design. In the first stage, clusters were chosen with probability proportional to size from census enumerator subdistricts (ESD) or approximate equivalents where an ESD was not available. In the second stage, all households in each chosen cluster were enumerated and a random sample of them selected. (See PSLSD, 1994, for further details.) In 1993, the KwaZulu-Natal portion of the PSLSD sample was designed to be representative at the provincial level, conditional on the accuracy of the 1991 census and other information used for the sampling frame, and contained households of all races. Due to the geographic concentration of African and Indian households, KIDS-unlike the PSLSD-limits its scope to African and Indian households. In the KwaZulu-Natal province, Africans represent 85 percent of the population and Indians represent 12 percent. Compared with their representation nationally, White and Coloured people are underrepresented in KwaZulu-Natal. Effectively, the numbers of White and Coloureds in the KwaZulu-Natal sample are too small, and too geographically concentrated in a few clusters, to permit meaningful inference. The KIDS study has thus been limited to the first two population groups.

PSLSD was a survey of households. However, households are a complicated object to define, particularly in longitudinal studies. To transform KIDS from a single-round household survey into a longitudinal household panel study required a redefinition of the sampling unit. In 1998, a decision was made to follow the core household members with the intention of capturing the major decision makers within the household. A household member is a core person if he/she satisfied any of the following criteria (the self-declared head of household from the 1993 survey):

• Spouse/partner of the self-declared head of household (from the 1993 survey)
• Lives in a three generation household and all of the following are true:
• Child of the self-declared household head, son/daughter-in-law of the household head, or niece/nephew of self-declared head
• At least 30 years old
• Has at least one child living in household
• Spouse/partner of person satisfying criteria

Thus all heads of households and spouses of heads are automatically classified as core and in some three-generation households, adult children are also included in this cateogry. In this way, we can see the 1993 survey as the baseline information for a random sample of dynasties. The efforts of the 1998 and 2004 surveyors to find the location of the 1993 core members can then be seen as a way to keep track of the 1993 dynasties.

Mode of data collection

Face-to-face [f2f]

Research instrument

KIDS re-interviews the KwaZulu-Natal (KZN) sample of the 1993 nationwide survey known as the Project for Statistics on Living Standards and Development (PSLSD.) The original project was financed by the World Bank and had the characteristics of the Living Standard Measurement Surveys. Reflecting their origin, all three waves of fieldwork for KIDS-1993, 1998, and 2004-collected information on household composition, expenditure on food and on other durable and non-durable goods, education, health, agricultural production, employment, and additional sources of labor and non-labor income. To ensure comparability, the 1998 and 2004 questionnaires largely followed the 1993 version of the questionnaire, however, a few modules have been added and removed. For example, the 1998 survey added sections on assets to marriage, economic shocks, and social capital and trust.

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File. Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:Population by RaceWhite – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American – A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.Some Other Race - this category is chosen by people who do not identify with any of the categories listed above. People can identify with more than one race. These people are included in the Two or More Races Hispanic or Latino PopulationThe Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

ObjectivesThe elderly are particularly prone to complications from a number of vaccine-preventable diseases. However, there are limited data on vaccine uptake for this vulnerable population in South Africa. Consequently, this study investigated influenza, pneumococcal and shingles vaccine uptake among elderly people in South Africa; reasons for their vaccination status; and factors associated with their uptake.MethodsCross-sectional study using an interviewer-administered questionnaire to survey 985 consenting adults aged ≥65 years in 2018. Participants were recruited from across South Africa. Bivariate analysis was used to identify socio-demographic variables associated with vaccine uptake, with multivariate logistic regression analysis used to identify key factors associated with vaccine uptake.ResultsInfluenza vaccine uptake was 32.3% (318/985), with uptake highest in those aged 85–90 years. Pneumococcal and shingles vaccine uptake was 3.8% (37/985) and 0.4% (4/985) respectively, being highest among those aged >90 years. The strongest statistically significant predictors for influenza vaccination were previous influenza vaccination (OR: 8.42 [5.61–12.64]); identifying as ‘Coloured’ (OR: 8.39 [3.98–17.69]); and residing in Gauteng Province (OR: 5.44 [3.30–9.02]). The strongest statistically significant predictors of receiving pneumococcal vaccination included receiving influenza vaccination (OR = 10.67 [3.27–37.83]); residing in the Western Cape Province (OR: 7.34 [1.49–36.22]); identifying as ‘Indian’ (OR: 5.85 [2.53–13.55]); and having a university education (OR: 5.56 [1.25–24.77]). Statistically significant barriers to receiving influenza vaccination included following the Traditional African religion (OR: 0.08 [0.01–0.62]) and residing in Limpopo Province (OR: 0.16 [0.04–0.71]). The main reasons for non-vaccination were considering influenza as a mild illness (36.6%; 242/661), and lack of knowledge about the pneumococcal (93.4%; 886/948) and shingles (95.2%; 934/981) vaccines.ConclusionVaccine uptake for all vaccines was sub-optimal, with multiple non-modifiable factors predicting vaccine uptake. These pre-COVID-19 data provide a baseline for measuring the effectiveness of future interventions to increase vaccine uptake and safeguard the health of the elderly.

South Africa Population: Mid Year: Indian and Asian: Female: 25 to 29 Years data was reported at 57,621.000 Person in 2018. This records a decrease from the previous number of 57,990.239 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Female: 25 to 29 Years data is updated yearly, averaging 56,930.663 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 58,519.343 Person in 2012 and a record low of 47,013.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: Female: 25 to 29 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.