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: 75 to 79 Years data was reported at 23,625.000 Person in 2018. This records an increase from the previous number of 19,387.100 Person for 2017. South Africa Population: Mid Year: Indian and Asian: 75 to 79 Years data is updated yearly, averaging 13,223.851 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 23,625.000 Person in 2018 and a record low of 8,885.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: 75 to 79 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 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: Female: 65 to 69 Years data was reported at 29,522.000 Person in 2018. This records an increase from the previous number of 26,877.369 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Female: 65 to 69 Years data is updated yearly, averaging 19,955.972 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 29,522.000 Person in 2018 and a record low of 12,540.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: Female: 65 to 69 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 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.

In 2018, the population group in South Africa with the highest share in primary education was Black African. This represented 91.2 percent of the share of children between the ages of six and 13 attending primary educational institutions in the country. Moreover, some 90.5 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 85.1 percent.

South Africa Population: Mid Year: Indian and Asian: Male: 45 to 49 Years data was reported at 54,474.000 Person in 2018. This records an increase from the previous number of 52,021.186 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Male: 45 to 49 Years data is updated yearly, averaging 41,858.472 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 54,474.000 Person in 2018 and a record low of 33,522.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: Male: 45 to 49 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: 0 to 4 Years data was reported at 49,001.000 Person in 2018. This records a decrease from the previous number of 49,249.545 Person for 2017. South Africa Population: Mid Year: Indian and Asian: Male: 0 to 4 Years data is updated yearly, averaging 46,593.170 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 49,249.545 Person in 2017 and a record low of 43,012.644 Person in 2005. South Africa Population: Mid Year: Indian and Asian: Male: 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.

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.

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: 55 to 59 Years data was reported at 79,020.000 Person in 2018. This records an increase from the previous number of 75,029.282 Person for 2017. South Africa Population: Mid Year: Indian and Asian: 55 to 59 Years data is updated yearly, averaging 63,554.252 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 79,020.000 Person in 2018 and a record low of 45,963.000 Person in 2001. South Africa Population: Mid Year: Indian and Asian: 55 to 59 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.

As of 2022, 5.5 percent of Black Africans aged 18 to 29 were enrolled at a higher education institution in South Africa, which marks an increase of 2.6 percentage points compared to 2002. And while Black Africans constituted the majority of young adult students in numbers, the participation rate of this population group continued to be lower compared to the Indian/Asians at 19.6 percent and the white population group at 17.7 percent.

Table is ordered alphabetically on the Latin binomial.

Abstract

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.

Geographic coverage

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

Analysis unit

Units of analysis in the Kwazulu Natal Income Dynamics Study 1993-1998 are households and individuals

Universe

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

Kind of data

Sample survey data [ssd]

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. 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.

Mode of data collection

Face-to-face [f2f]

Abstract

The KwaZulu-Natal Income Dynamics Study (KIDS) is a panel study that follows a random sample of households who lived in the South African province of KwaZulu-Natal (KZN) in 1993. These households and those who have split off from them were interviewed again in 1998 and 2004. This document summarizes the main features of the third wave of KIDS conducted in 2004.

Geographic coverage

The Province of Kwazulu-Natal

Analysis unit

individuals, communities

Universe

The sample covered on African and Indian Households.

Kind of data

Sample survey data [ssd]

Sampling procedure

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 - A 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 - Have at least one child living in household - Spouse/partner of person satisfying criterion.

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.

In 2004, due to the aging of the core members and the high prevalence of HIV/AIDS in South Africa, the study was extended in a complementary way to track and interview the households of the children of the core or the next generation. These are sons and daughters of core members older than 18, who have established a "new" household since 1993 (labeled as "K"). By establishing a new household we mean that these children are now living away from their own parents with their own children, or with the children of their partner. Using the next generation to keep track of family "dynasties" provides a way of refreshing the panel and establishing a generational transition. In addition, due to our interest in the impact on children of the HIV/AIDS epidemic, the 2004 wave followed foster children to their new households. This group is defined as children aged less than 18 years old of core and next generation household members who no longer live with their parents i.e. no longer live in core or next generation households (labeled as "N"). As described in Appendix A, different questionnaire modules were administered in the core, next generation, and foster child households.

As the goal of the 2004 wave of KIDS was to find and interview the households of the children of the core and the foster children in addition to those of the regular core members, we had three ways in which we could contact the 1993 dynasties. In 1998, almost 84% of the 1993 dynasties were found as documented by May et al. (2000). From the 1132 dynasties interviewed in 1998, the 2004 wave found 841, yielding a response rate of 74%. Most of these dynasties were still composed of the original core members (760) however some of them were represented by the next generation of household members (K) or foster children (N).

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire containing the following sections:

Household Roster Household Services Food Spending and Consumption Non-Food Spending and Assets Remittances Household Income from Non-Employment Sources Economic Shocks, Agriculture Employment Health Social Capital and Trust Children Tests of Learning and Anthropometry

Response rate

In 1998, almost 84% of the 1993 dynasties were found as documented by May et al. (2000). From the 1132 dynasties interviewed in 1998, the 2004 wave found 841, yielding a response rate of 74%. Most of these dynasties were still composed of the original core members (760) however some of them were represented by the next generation of household members (K) or foster children (N).

At the end of 2022, the Gini coefficient of wealth in India stood at 82.5. This was a slight increase from previous years. The trend since 2000 shows rising inequalities among the Indian population. What is Gini coefficient of wealth? The Gini coefficient is a measure of wealth inequality. The coefficient of the Gini index ranges from 0 to 1 with 0 representing perfect equality and 1 representing perfect inequality. Wealth and income distribution and inequality can however vary greatly. In 2023, South Africa topped the list of the most unequal countries in the world in terms of income inequality.
Why do economic inequalities persist in India? By the end of 2022, the richest citizens in the country owned more than 40 percent of the country’s wealth. Asia’s two richest men Mukesh Ambani and Gautam Adani are Indians. The number of high-net-worth individuals has continuously increased over the last decades. While millions of people escaped poverty in the country in the last few years, the wealth distribution between rich and poor remains skewed. Crony capitalism and the accumulation of wealth through inheritance are some of the factors behind this widening gap.

In 2018, the population group with the highest share of children between the ages of 14 and 17 years in secondary education in South Africa was Asian/Indian, at 87.8 percent. Moreover, 83.3 percent of the Black African children were enrolled in secondary education. The population group with the lowest secondary education enrollment level was the White population, at 73.3 percent.