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.
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South Africa Population: Mid Year: Indian and Asian: Above 80 Years data was reported at 19,993.000 Person in 2018. This records an increase from the previous number of 14,829.578 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Above 80 Years data is updated yearly, averaging 10,196.012 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 19,993.000 Person in 2018 and a record low of 6,006.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: 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.
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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 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.
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.
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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.
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.
The SADHS sample was designed to be a nationally representative sample.
Households and individuals
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.
Sample survey data
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.
Face-to-face [f2f]
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
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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 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.
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Context
The dataset tabulates the population of South Tucson by race. It includes the population of South Tucson across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of South Tucson across relevant racial categories.
Key observations
The percent distribution of South Tucson population by race (across all racial categories recognized by the U.S. Census Bureau): 32.30% are white, 3.11% are Black or African American, 22.89% are American Indian and Alaska Native, 0.37% are Asian, 22.78% are some other race and 18.56% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for South Tucson Population by Race & Ethnicity. You can refer the same here
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South Africa Population: Mid Year: Indian and Asian: 30 to 34 Years data was reported at 136,523.000 Person in 2018. This records a decrease from the previous number of 136,733.801 Person for 2017. South Africa Population: Mid Year: Indian and Asian: 30 to 34 Years data is updated yearly, averaging 109,540.192 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 136,733.801 Person in 2017 and a record low of 86,688.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: 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.
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).
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.
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.
Description: The following topics were covered in this questionnaire: voter education, voter registration and participation, general perceptions on voting, voting behaviour and history, media and information, as well as respondent and household characteristics. Question 32 has been removed from the data. This data set contains 2704 cases and 79 variables. Abstract: In order to assess the electoral landscape prior to the local government elections of December 2000, the Independent Electoral Commission (IEC) approached the Human Sciences Research Council (HSRC). The outcome was a two-phase research process involving both quantitative and qualitative methodologies. The specific purpose of the research was to determine the impact of the IEC's voter education programmes throughout the country and more generally, the extent to which the public was aware of and motivated to participate in the elections. Face-to-face interview National Population: Adults (aged 18 and older). A sample of 2 704 voters was selected across each province of South Africa. Initial stratification was in terms of the lifestyle categorisations of each enumerator area (EA) in the country. EAs were selected randomly to ensure that sufficient numbers of respondents in each of the EA-types were included in the sample. In the cases of small components of the population, namely the Northern Cape and the Indian population in general, over-sampling took place to facilitate generalisability at provincial and population group levels.
The information collected in household surveys, such as this one, is used to describe and understand the living conditions and experiences of South Africans. Often, however, different surveys use different sample areas and interview different households, making it difficult to know whether the living standards or circumstances of particular households have improved. The aim of this survey is to determine whether or not there have been any changes in the socio-economic conditions of those households interviewed in 1993. This information will be used to understand the dynamics of household behaviour over time.
The survey covered households in KwaZulu-Natal Province, on the east coast of South Africa
Units of analysis in the Kwazulu Natal Income Dynamics Study 1993-1998 are households and individuals
The Kwazulu Natal Income Dynamics Study 1993-1998 covered all household members.
Sample survey data [ssd]
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. It was decided not to re-survey the small number of white and coloured households in 1998, however. While there were minor advantages to retaining these groups, the relatively small number of households in each group (112 white households and 53 coloured) would have precluded most comparative ethnic analyses. Moreover, the households in these ethnic groups were entirely located in a small number of clusters (due to the general lack of spatial integration of the population), undermining their representativeness. As a result, the 1998 sample includes only African and Indian households.
Face-to-face [f2f]
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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.
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Context
The dataset tabulates the Non-Hispanic population of South Padre Island by race. It includes the distribution of the Non-Hispanic population of South Padre Island across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of South Padre Island across relevant racial categories.
Key observations
Of the Non-Hispanic population in South Padre Island, the largest racial group is White alone with a population of 2,174 (89.50% of the total Non-Hispanic population).
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for South Padre Island Population by Race & Ethnicity. You can refer the same here
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.