DemographyDemography

Orphaning

Author/s: Katharine Hall
Date: August 2024

Definition

An orphan is defined as a child under the age of 18 years whose mother, father, or both biological parents have died (including those whose vital status is reported as unknown, but excluding those whose vital status is unspecified). For the purpose of this indicator, we define orphans in three mutually exclusive categories:

  • A maternal orphan is a child whose mother has died but whose father is alive;
  • A paternal orphan is a child whose father has died but whose mother is alive;
  • A double orphan is a child whose mother and father have both died.

The total number of orphans is the sum of maternal, paternal and double orphans.This definition differs from that sometimes used by United Nations and other agencies, where the definitions of maternal and paternal orphans each include children who are double orphans.

Data


Data Source Statistics South Africa (2003 – 2023) General Household Survey 2002 – 2022. Pretoria, Cape Town: Statistics South Africa.
Analysis by Katharine Hall, Children’s Institute, University of Cape Town.
Notes
  1. Children are defined as persons aged 0 – 17 years.
  2. Population numbers have been rounded off to the nearest thousand.
  3. Sample surveys are always subject to error, and the proportions simply reflect the mid-point of a possible range. The confidence intervals (CIs) indicate the reliability of the estimate at the 95% level. This means that, if independent samples were repeatedly taken from the same population, we would expect the proportion to lie between upper and lower bounds of the CI 95% of the time. The wider the CI, the more uncertain the proportion. Where CIs overlap for different sub-populations or time periods we cannot be sure that there is a real difference in the proportion, even if the mid-point proportions differ. CIs are represented in the bar graphs by vertical lines at the top of each bar.

What do the numbers tell us?

In 2022, there were 2.8 million orphaned children in South Africa. This includes children without a living biological mother, or father or both parents, and is equivalent to 14% of all children in South Africa. The majority (64%) of all orphans in South Africa are paternal orphans (with deceased fathers and living mothers).

The total number of orphans increased by over a million between 2002 and 2009, after which the trend was reversed. By 2017, orphan numbers had fallen to below 2002 levels. This was largely the result of improved access to antiretrovirals and reduced parental death rates. Contrary to expectations, the number of orphaned children did not increase significantly during the COVID-19 pandemic in 2020 and 2021, and in 2022 the orphaning rates in all categories (maternal, paternal and double orphans) were lower than they were in 2019. This may be because COVID-19 related deaths were most prevalent among older people, while prime-age adults with children were less vulnerable.


  

Orphan status is not necessarily an indicator of the quality of care that children receive. It is important to disaggregate the total orphan figures because the death of one parent may have different implications for children than the death of both parents. In particular, it seems that children who are maternally orphaned are at risk of poorer outcomes than paternal orphans – for example, in relation to education.1 

In 2022, 3% of all children in South Africa were maternal orphans with living fathers, 9% were paternal orphans with living mothers, and a further 2% were recorded as double orphans. In total, 5% of children in South Africa (1 million children) did not have a living biological mother and 11% (2.3 million children) did not have a living biological father. The numbers of paternal orphans are high because of the relatively high mortality rates of men among South Africa, as well as a greater probability that the vital status, and perhaps even the identity, of a child's father is unknown. Around 300,000 children have fathers whose vital status is reported to be “unknown”, compared with fewer than 40,000 children whose mothers’ status is unknown).

The number and share of children who are double orphans more than doubled between 2002 and 2009, from 361,000 to 886,000 after which the rates fell again. In 2018, 471,000 children had lost both their parents, but the numbers rose again to over 580,000 in 2019, with a further slight increase to 620,00 in 2020. Subsequently, the rate of double orphaning dropped back to around 540,000 in 2021 and dipped below 500,000 in 2022.

There is some variation across provinces. The Eastern Cape, for example, has historically reported relatively high rates of orphaning, reflecting a situation where rural households of origin carry a large burden of care for orphaned children. In terms of orphan numbers, double orphans are concentrated mostly in three provinces: KwaZulu-Natal (accounts for 23% of double orphans), Gauteng (20%) and the Eastern Cape (14%). Together these three provinces are home to 56% of all double orphans.

KwaZulu-Natal has the largest child population and the highest orphan numbers, with 634,000 children (15% of children in that province) recorded as orphans who have lost a mother, a father or both parents. Orphaning rates in the Eastern Cape (16%) are even higher, although the number of children orphaned is lower (408,000 because the child population is smaller). In 2020, Gauteng emerged as the province with the second highest and quickest growing orphaning numbers, where 13% of children (566,000) were single or double orphans. Orphaning rates in that province remained stable in 2021 and 2022. The lowest orphaning rates are in the Western Cape (10% of children).

The poorest households carry the greatest burden of care for orphans. Nearly 40% of all orphans are resident in the poorest 20% of households. 

The likelihood of orphaning increases as a child gets older. Across all age groups, the main form of orphaning is paternal orphaning, which increases from 4% among children under six years of age, to 14% among children aged 12 – 17 years. While less than 1% of children under six years are maternal orphans, the maternal orphaning rate increases to 4% in children aged 12 – 17 years.


1 Ardington C & Leibrandt M (2010) Orphanhood and schooling in South Africa: Trends in the vulnerability of orphans between 1993 and 2005. Economic Development and Cultural Change, 58(3): 507-536.

Technical notes

Children are defined as orphaned if their parent is known to be deceased or if the vital status of the parent is unknown. Orphans are identified in three mutually exclusive categories: maternal orphans, paternal orphans and double orphans. The three categories add up to the total number of orphans.

The definition used here differs from that commonly used by the UN agencies where the definitions of maternal and paternal orphan include children who are double orphans: for instance, all children who have lost a mother (whether or not their father is alive) are included in their measure of maternal orphans. Using those definitions, there is double counting and maternal, paternal and double orphan numbers add up to more than the total number of orphans.

Strengths and limitations of the data

The numbers are derived from the General Household Survey, a multi-purpose annual survey conducted by the national statistical agency, Statistics South Africa, to collect information on a range of topics from households in the country’s nine provinces.

The GHS uses a Master Sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys that have design requirements that are reasonably compatible with the GHS. The sample is drawn from Census enumeration areas using a stratified two-stage design with probability proportional to size sampling of PSUs in teh first stage, and sampling of dwelling units with systematic sampling in the second stage. The resulting sample consists of just over 20,000 households with around 70,000 individuals, and should be representative of all households in South Africa. It is also designed to be representative at provincial level and within provinces at metro/non-metro levels and three geography types (urban areas, rural areas under traditional authority, and farms).

The sample consists of households and does not cover other collective institutionalised living-quarters such as boarding schools, orphanages, students’ hostels, old-age homes, hospitals, prisons, military barracks and workers’ hostels. These exclusions probably do not have a noticeable impact on the findings in respect of children.

Changes in sample frame and stratification
Since 2014 the GHS has been based on the 2013 master sample that that is, in turn, based on information collected during the 2011 Population Census. The previous master sample for the GHS was used for the first time in 2008, and the one before that in 2004. These again differed from the master sample used in the first two years of the GHS: 2002 and 2003. Thus there have been four different sampling frames during history of the annual GHS, with the changes occurring in 2004, 2008 and 2013. In addition, there have been changes in the method of stratification over the years. These changes could compromise comparability across iterations of the survey to some extent, although it is common practice to use the GHS for longitudinal monitoring and many of the official trend analyses are drawn from this survey.

Weights
Person and household weights are provided by Stats SA and are applied in Children Count analyses to give population estimates on the indicators. The GHS weights are derived from Stats SA’s mid-year population estimates for the relevant year. The population estimates are based on a model that is revised from time to time when it is possible to calibrate the population model to Census data and larger population surveys such as the Community Survey.

In 2017, Stats SA revised its demographic model to produce a new series of mid-year population estimates and the GHS data were re-released with the revised population weights. All the Children Count indicators were re-analysed retrospectively, using the revised weights provided by Stats SA, based on the 2013 model. The estimates are therefore comparable over all years. The revised weights particularly affected estimates for the years 2002 – 2007.

The 2017 model drew on the 2011 census, along with vital registration, antenatal and other administrative data, but was a “smoothed” model that did not mimic the unusual shape of the age distribution found in the census. The results of the 2011 census were initially distrusted because it seemed to over-count children in the 0 – 4 age group and under-count children in the 4 – 14-year group. It is now thought that the fertility rates recorded in the 2011 population census may have been an accurate reflection of demopraphic trends, with an unexplained upswing in fertility around 2009 after which fertility rates declined again gradually. Similar patterns were found in the vital registration data as more births were reported retrospectively to the Department of Home Affairs, and in administrative data from schools, compiled by the Department of Basic Education. In effect, this means that there may be more children in South Africa than appear from the analyses presented in these analyses, where we have applied weights based on a model that it is now known to be inaccurate.

Stats SA has subsequently developed a new population model - the 2022 series, which provides revised mid-year population estimates back to 2002 and projected to 2032. However, the GHS series has not yet been reweighted.The population estimates in Children Count are therefore based on weights derived from outdated population model (2017). It is not yet clear when and how the population model will be revised again following the 2022 Census, as there are concerns around census under-count and plausibility of its findings.

Disaggregation
Statistics South Africa suggests caution when attempting to interpret data generated at low level disaggregation. The population estimates are benchmarked at the national level in terms of age, sex and population group while at provincial level, benchmarking is by population group only. This could mean that estimates derived from any further disaggregation of the provincial data below the population group may not be robust enough.

Reporting error
Error may be present due to the methodology used, i.e. the questionnaire is administered to only one respondent in the household who is expected to provide information about all other members of the household. Not all respondents will have accurate information about all children in the household. In instances where the respondent did not or could not provide an answer, this was recorded as “unspecified” (no response) or “don’t know” (the respondent stated that they didn’t know the answer).

For more information on the methods of the General Household Survey, see the metadata for the respective survey years, available on Nesstar or DataFirst