DemographyDemography

Orphaning

Author/s: Katharine Hall
Date: November 2019

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 – 2019) General Household Survey 2002 – 2018. Pretoria, Cape Town: Statistics South Africa.
Analysis by Katharine Hall & Winnie Sambu, 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.
In 2018, there were 2.7 million orphans in South Africa. This includes children without a living biological mother, father or both parents, and is equivalent to 14% of all children in South Africa. The majority (63%) of all orphans in South Africa are paternal orphans (with 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.
 
 
 

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 2018, 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. This means that 5% of children in South Africa (nearly a million children) did not have a living biological mother and twice that number did not have a living biological father. The numbers of paternal orphans are high because of the higher mortality rates of men in South Africa, as well as the frequent absence of fathers in their children’s lives (1.8% or 353,000 children have fathers whose vital status is reported to be “unknown”, compared with 0.3% or 66,000 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 866,000 after which the rates fell again. In 2018, 471,000 children had lost both their parents. Orphaning rates are particularly high in provinces that contain the former homelands, as these areas bear a large burden of care for orphaned children. In terms of orphan numbers, double orphans are concentrated mostly in three provinces: KwaZulu-Natal (24% of double orphans), Gauteng (24%) and the Eastern Cape (17%). Together these three provinces are home to 60% of all double orphans.

KwaZulu-Natal has the largest child population and the highest orphan numbers, with 17% of children in that province recorded as orphans who have lost a mother, a father or both parents. Orphaning rates in the Eastern Cape (17%) are similarly high. Other provinces with high orphaning rates (above the national average) are the Free State (16%), Mpumalanga (15%) and North West (15%). The lowest orphaning rates are in the Gauteng (11% of children have lost at least one parent, and the Western Cape 7%). However it should be remembered that the orphans of parents who died in these provinces may be living with relatives in other provinces, and so might be counted in the orphaning populations of the Eastern Cape or Mpumalanga, for example.

The poorest households carry the greatest burden of care for orphans. Close to half (48%) of all orphans are resident in the poorest 20% of households. Seventeen percent of children in the poorest 20% of households are orphans, compared with the richest 20% where total orphaning rates are around 4%.

The likelihood of orphaning increases with age. Across all age groups, the main form of orphaning is paternal orphaning, which increases from 4% among children under six years of age, to 15% among children aged 12 – 17 years. While less than 1% of children under six years are maternal orphans, this increases to 5% 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.

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.

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 survey uses a sample of 30,000 households. These are drawn from Census enumeration areas using multi-stage stratified sampling and probability proportional to size principles. The resulting estimates should be representative of all households in South Africa.

The GHS 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 should not have a noticeable impact on the findings in respect of children.

Changes in sample frame and stratification
The sample design for the 2015 GHS was based on a master sample that was designed in 2013 as a general purpose sampling frame to be used for all Stats SA household-based surveys. The same master sample is shared by the GHS, the Quarterly Labour Force Survey, the Living Conditions Survey and the Income and Expenditure Survey. The 2013 master sample is 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 the 14-year 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 estimates at the provincial and national levels. The GHS weights are derived from Stats SA’s mid-year population estimates. 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 larger population surveys (such as the Community Survey) or to census data.

In 2013, Stats SA revised the demographic model to produce a new series of mid-year population estimates. The 2013 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 questioned because it seemed to over-count children in the 0 – 4 age group and under-count children in the 4 – 14-year group.

The 2013 model was used to adjust the benchmarking for all previous GHS data sets, which were re-released with the revised population weights by Stats SA, and was still used to calculate weights for the GHS up to and including 2015, even though it is now known that the mid-year population estimates on which the weights are based are incorrect. 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 the period 2002 to 2015. The revised weights particularly affected estimates for the years 2002 – 2007.

It is now thought that the fertility rates recorded in the 2011 population census may have been an accurate reflection of recent trends, with an unexplained upswing in fertility around 2009 after which fertility rates declined 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.

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