Demography

Children living with parents

Author/s: Katharine Hall
Date: December 2023

Definition

This indicator shows the number and share of children in South Africa who live in the same household as both their biological parents; with their mother only; with their father only; or who do not live with either of their biological parents.

Data

Data Source

Statistics South Africa (2003 – 2023) General Household Survey 2002 – 2022. Pretoria, Cape Town: Stats SA.
Analysis by Katharine Hall, Children’s Institute, University of Cape Town.

Notes

Children are defined as persons aged 0 – 17 years.
Population numbers have been rounded off to the nearest thousand.
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 the vertical lines at the top of each bar.

What do the numbers tell us?

Many children in South Africa do not live consistently in the same household as their biological parents. This is an established feature of childhoods in South Africa, and international studies have shown that the country is unique in the extent that parents are absent from children’s daily lives.¹ Parental absence is related to many factors, including apartheid-era controls on population movement, labour migration, poverty, housing and educational opportunities, low marriage and cohabitation rates, as well as customary care arrangements.² It is common for relatives to play a substantial role in child-rearing. Many children experience a sequence of different caregivers, are raised without fathers, or live in different households to their biological siblings.

Parental absence does not necessarily mean parental abandonment. Many parents continue to support and see their children regularly even if they have to live elsewhere.³ Virtually all children live with at least one adult, and 89% of children live in households where there are two or more co-resident adults. This indicator tracks co-residence between children and their biological parents specifically. Although many children live with just one of their biological parents (usually the mother), this does not mean that the mother is a “single parent” as she is not necessarily the only adult caregiver in the household. In most cases, there are other adult household members such as aunts, uncles and grandparents who may contribute to the care of children.

The share of children living with both parents decreased gradually from 39% in 2002 to 34% in 2010, and remained stable at around 34% for the next 10 years. In 2022, 33% of children had both their biological parents living in the same household. Forty-four percent of all children (9.2 million children) live with their mothers but not with their fathers. Only 4% of children live in households where their fathers are present and their mothers absent. Twenty percent do not have either of their biological parents living with them. This does not necessarily mean that they are orphaned: 80% of children who do not have any co-resident parent do have a living mother, and 88% of children without any co-resident parents have at least one parent who is alive but living elsewhere.

There is substantial provincial variation within these patterns. In the Western Cape and Gauteng, the share of children living with both parents is significantly higher than the national average, with around half of children resident with both parents (50% and 47%, respectively). Similarly, the number of children living with neither parent is relatively low in these two provinces (11% in both cases). In contrast, a third of children (33%) in the Eastern Cape live with neither parent. These patterns have been fairly consistent from 2002 to 2020.

Children in the poorest 20% of households are least likely to live with both parents: only 17% of the poorest children have both parents living with them, compared with 73% of children in the wealthiest 20% of households.

Less than 30% of African children live with both their parents, while over 80% of Indian and White children reside with both biological parents. More than one in five of all African children do not live with either parent and a further 47% live with their mothers but not their fathers. These figures are striking for the way in which they suggest the limited presence of biological fathers in the home lives of large numbers of children.

Younger children are more likely than older children to have co-resident mothers, while older children are more likely to be living with neither parent. While 13% of children aged 0 – 5 years (906,000) live with neither parent, this increases to 25% (1.7 million) of children aged 12 – 17 years.

1 Social Trends Institute (2017) World Family Map 2017: Mapping family change and child well-being outcomes. New York, Barcelona: Social Trends Institute;
Martin F (2016) Who Cares for Children? A descriptive study of care-related data available through global household surveys and how these could be better mined to inform policies and services to strengthen family care. Global Social Welfare, 3(2): 51-74.

2 See, for example: Hall K & Mokomane Z (2018) The shape of children’s families and households: A demographic overview. In: Hall K, Richter L, Mokomane Z & Lake L (2018) Children, Families and the State: Collaboration and Contestation. South African Child Gauge 2018. Cape Town: Children’s Institute, UCT;
Hall K & Posel D (2019) Fragmenting the family? The complexity of household migration strategies in post-apartheid South Africa. IZA Journal of Development and Migration, 10(4), 20190004. Doi: https://doi.org/10.2478/izajodm-2019-0004;
Hall K (2017) Children’s Spatial Mobility and Household Transitions: A study of child mobility and care arrangements in the context of maternal migration. Unpublished PhD thesis. University of the Witwatersrand;
Makiwane M, Nduna M & Khalema E (2016) Children in South African Families: Lives and Times. Newcastle upon Tyne: Cambridge Scholars;
Amoateng A & Heaton T (eds) (2007) Families and Households in Post-Apartheid South Africa: Socio-demographic Perspectives. Cape Town: HSRC Press.

3 Hatch M & Posel D (2018) Who cares for children? A quantitative study of childcare in South Africa. Development Southern Africa, 35(2): 267-282;
Van den Berg W & Makusha T (2018) State of South Africa’s Fathers 2018. Cape Town: Sonke Gender Justice and Human Sciences Research Council;
Madhavan S, Townsend N & Garey A (2008) ‘Absent breadwinners’: Father–child connections and paternal support in rural South Africa. Journal of Southern African Studies 34(3): 647-663.

Technical notes

Statistics South Africa, the agency responsible for the General Household Surveys, defines a household as consisting of people who have stayed in a common dwelling for an average of at least four nights a week in the month preceding the survey.

The General Household Survey asks whether children’s biological mothers and fathers are part of the same household. This indicator is therefore calculated by identifying children who have their mothers living with them but not their fathers, their fathers but not their mothers, neither parent resident, or both parents resident with them, and dividing the resulting figures by the total child population.

For purposes of measuring and monitoring persistent racial inequality, population groups are defined as 'African', 'Coloured', 'Indian', and 'White'.

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 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