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: 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.

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.

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.

About this dataset

Context

This list ranks the 5 cities in the Indian River County, FL by South African population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by South African Population: This column displays the rank of city in the Indian River County, FL by their South African population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• South African Population: The South African population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as South African. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Indian River County South African Population: This tells us how much of the entire Indian River County, FL South African population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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/.

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.

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.

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 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.

Abstract

The 2003 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 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 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 comprised 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 anthropometry 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.

Information on a variety of demographic and health indicators were collected. The results of these surveys are intended to assist policy makers and programme managers in evaluating and designing programmes and strategies for improving health services in the country. In addition to the aspects covered in the 1998 SADHS, information on the following additional aspects was included in the 2003 SADHS: - Information on children living in households where the biological mother is not staying in the household i.e. mother is dead, etc.
- Child anthropometric data
- Information on reproductive health and sexual behaviour of men
- Information on malaria
- Information on pensions/grants received by members of the household.

The primary objective of the 2003 SADHS was to provide up-to-date information on: - Characteristics of households and respondents - Fertility - Contraception and fertility preferences - Sexual behaviour, HIV and AIDS - Infant and child mortality - Maternal and child health - Infant and child feeding - Adolescent health - Mortality and morbidity in adults - Utilisation of health services - Adult health: hypertension, chronic pulmonary disease and Asthma - Risk factors for chronic diseases - Oral health - Health of older persons

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 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.

Analysis unit

• Household
• Women age 15-49
• Men age 15-59
• Children under six years

Universe

The population covered by the 2003 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 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

Research instrument

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

Native-alien population is defined as a population that is within a country to which the species is native and founded by individuals moved by direct human agency (or substantial indirect human agency) over a biogeographical barrier to an area beyond the species’ native range (Nelufule et al. 2022). This dataset followed the data structure used for the species list of South Africa’s second national status report on biological invasions ‘The status of biological invasions and their management in South Africa in 2019' (Zengeya and Wilson 2020). This represents the first inventory of native-alien populations in South Africa, and is a step towards a greater understanding of native-alien populations and the biosecurity threat they pose. Reference Nelufule T, Robertson MP, Wilson JRU, Faulkner KT (2022) Native-alien populations—an apparent oxymoron that requires specific conservation attention. NeoBiota 74: 57–74, https://doi.org/10.3897/neobiota.74.81671 Zengeya, T. A. & Wilson, J. R. U. (eds.). The status of biological invasions and their management in South Africa in 2019. pp.71. South African National Biodiversity Institute, Kirstenbosch and DSI-NRFCentre of Excellence for Invasion Biology, Stellenbosch. (2020).

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.

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.

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).

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.

In 2018, the population group in South Africa with the highest share in primary education was Black African. This represented **** percent of the share of children between the ages of *** and ** attending primary educational institutions in the country. Moreover, some **** percent of the Colored children were enrolled in primary education. The population group with the lowest level of enrollment in primary education was the Asian/Indian population, at **** percent.

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.

In 2022, a survey was conducted in South Africa about the distribution of instant messaging applications among different population groups. It found that Snapchat users are predominantly Indian/Asian, with a share of approximately ** percent of users. Furthermore, population group refers to the ethnicity of different groups which make up a country's population. In 2022, Black South Africans were the largest population group in the country, followed by the colored and white populations.

About this dataset

Context

The dataset tabulates the population of South Gate by race. It includes the population of South Gate across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of South Gate across relevant racial categories.

Key observations

The percent distribution of South Gate population by race (across all racial categories recognized by the U.S. Census Bureau): 23.87% are white, 1.02% are Black or African American, 1.75% are American Indian and Alaska Native, 0.79% are Asian, 0.08% are Native Hawaiian and other Pacific Islander, 44.97% are some other race and 27.51% are multiracial.

Content

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:

• 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: This column displays the racial categories (excluding ethnicity) for the South Gate
• Population: The population of the racial category (excluding ethnicity) in the South Gate is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of South Gate total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Gate Population by Race & Ethnicity. You can refer the same here

AimsTo describe the distribution and examine the associations of diabetes, hypertension and hypercholesterolaemia across and within population groups, gender and body mass index (BMI) categories.MethodsThis national cross-sectional study was conducted in 2013 among ≥18-year-old black African, coloured, white and Indian adults self-selected for screening. Data collection included self-reported behavioural risk factors and clinical measurements comprising blood pressure, anthropometry and point-of-care random blood glucose and cholesterol assessments.ResultsAmong the 7711 participants, 2488 men and 5223 women, the prevalence of diabetes and hypertension increased by BMI category across population groups. Compared with white men and women, black African men (odds ratio: 2.66, 95% confidence interval: 1.70–4.16) and women (2.10, 1.49–2.96), coloured men (2.28, 1.44–3.60) and women (2.15, 1.52–3.05) and Indian men (4.38, 2.65–7.26) and women (3.64, 2.50–5.32) were significantly more likely to have diabetes. The odds for hypertension were significantly higher only in coloured men compared with white men (1.37, 1.02–1.83), while it was significantly higher in black African, coloured and Indian women compared with white women. The odds for hypercholesterolaemia were significantly lower in black African men (0.64, 0.49–0.84) and women (0.52, 0.43–0.62) compared with white men and women, and significantly higher in Indian men (1.47, 1.05–2.08) compared with white men. Black African women compared with their male counterparts were less likely to have diabetes (0.64, 0.46–0.89). Black African (0.66, 0.54-.082), coloured (0.65, 0.50–0.84) and white (0.69, 0.53–0.88) women were significantly less likely to have hypertension compared with their male counterparts. The odds for hypercholesterolaemia were higher in coloured (1.44, 1.16–1.80) and white (1.47, 1.18–1.84) women compared with their counterparts.ConclusionsThe cardio-metabolic diseases of diabetes, hypertension and hypercholesterolaemia were differentially associated with population groups and gender in South Africa. The insights obtained highlight the need for multi-disciplinary targeted management approaches in high-risk populations.