DemographyDemography

Child-only households

Author/s: Katharine Hall
Date: November 2018

Definition

A child-only household is defined as a household in which all members are younger than 18 years. These households are also commonly referred to as “child-headed households”.

The Children’s Act definition of a child-headed household is different in that it includes households where there are adults who may be too sick or too old to effectively head the household and a child over 16 years bears this responsibility. It is not possible to count this type of child-headed household from the available survey data,

Data


Data Source Statistics South Africa (2003 – 2018) General Household Survey 2002 – 2017. 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.
While orphaning undoubtedly places a large burden on families, there is little evidence to suggest that their capacity to care for orphans has been saturated, as commentators feared in the past. Rather than seeing increasing numbers of orphaned children living on their own, the vast majority of orphans live with adult family members.

There were about 58,000 children living in a total of 32,000 child-only households across South Africa in 2017. This equates to 0.3% of all children. While children living in child-only households are rare relative to those residing in other household forms, the number of children living in this extreme situation is of concern.

Importantly, however, there has been no increase in the share of children living in child-only households in the period 2002 – 2017. If anything, the number has dropped. Predictions of rapidly increasing numbers of child-headed households as a result of HIV are at this point unrealised. An analysis of national household surveys to examine the circumstances of children in child-headed households in South Africa revealed that most children in child-only households are not orphans,1  and 84% have a living mother. These findings suggest that social processes other than HIV-related mortality may play important roles in the formation of these households. For example, leaving teenage boys to look after a rural homestead while parents migrate to work may be a livelihood strategy for the household.

While it is not ideal for any child to live without an adult resident, it is positive that more than half (57%) of all children living in child-only households are aged 15 years and above. Children can work legally from the age of 15, and from 16 they can obtain an identity document and receive grants on behalf of younger children. Only 6% of children in child-headed households are under six years of age.
Research suggests that child-only households are frequently temporary arrangements, and often exist just for a short period, for example while adult migrant workers are away, or for easy access to school during term-time, or after the death of an adult and prior to other arrangements being made to care for the children (such as other adults moving in or the children moving to live with other relatives).2

More than 50% of all children in child-only households live in two provinces: Limpopo and Eastern Cape, each with 26% of children in child-only households. From 2002 to 2017, these provinces have consistently been home to the majority of children living in child-only households. The number of child-only households in KwaZulu-Natal appears to have dropped, but this may not be significant because the numbers are so small and the confidence intervals relatively wide.

Relative to children in mixed-generation households, child-only households are vulnerable in a number of ways. Child-only households are predominantly clustered in the poorest households; 88% of children living in child-only households are in the poorest 20% of households. In addition to the absence of adult members who may provide care and security, they are at risk of living in poorer conditions, with poor access to services, less (and less reliable) income, and low levels of access to social grants.
There has been very little robust data on child-headed households in South Africa to date. The figures should be treated with caution as the number of child-only households forms just a very small sub-sample of the General Household Survey. In particular, we caution against reading too much into the provincial breakdowns. When comparing the overall estimates nationally, the number of children in child-headed households seems to have declined since 2002.



1 Meintjes H, Hall K, Marera D & Boulle A (2010) Orphans of the AIDS epidemic? The extent, nature and circumstances of child-headed households in South Africa. AIDS Care, 22(1): 40-49.

2 Hill C, Hosegood V & Newell M-L (2008) Children's care and living arrangements in a high HIV prevalence area in rural South Africa. Vulnerable Children and Youth Studies, 3(1): 65-77.

See also:

Hosegood V, Floyd S, Marston M, Hill C, McGrath N, Isingo R, Crampin A & Zaba B (2007) The effects of high HIV prevalence on orphanhood and living arrangements of children in Malawi, Tanzania and South Africa. Population Studies 61(3): 327-336;
Meintjes H & Giese S (2006) Spinning the epidemic: The making of mythologies of orphanhood in the context of AIDS. Childhood: A Global Journal of Child Research, 13(3): 407-430.

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 share of children living in child-only households in South Africa is calculated by identifying the number of children living in households where the oldest resident is no older than 17 years, and dividing this figure by the total child population in South Africa.

The share of child-only households is calculated by dividing the number of households where the oldest resident is no older than 17 years, by the total number of households in South Africa.

The figures should be treated with caution as the number of child-only households form just a very small sub-sample of the General Household Survey, which reduces the reliability of the weighted total. In particular, we caution against reading too much into the provincial breakdowns, or into apparent differences between the estimates from different years.

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