Housing & services

Access to basic sanitation

Author/s: Katharine Hall & Lori Lake
Date: January 2024

Definition

This indicator shows the number and percentage of children living in households with basic sanitation. Adequate toilet facilities are used as proxy for basic sanitation. This includes flush toilets and ventilated pit latrines that dispose of waste safely and that are within or near the house. Inadequate toilet facilities include pit latrines that are not ventilated, chemical toilets, bucket toilets, or no toilet facility at all.

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

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 vertical lines at the top of each bar.

What do the numbers tell us?

A basic sanitation facility was defined in the government’s Strategic Framework for Water Services as the infrastructure necessary to provide a sanitation facility which is “safe, reliable, private, protected from the weather and ventilated, keeps smells to a minimum, is easy to keep clean, minimises the risk of the spread of sanitation-related diseases by facilitating the appropriate control of disease carrying flies and pests, and enables safe and appropriate treatment and/or removal of human waste and wastewater in an environmentally sound manner”.1

Adequate sanitation prevents the spread of disease and promotes health through safe and hygienic waste disposal. To do this, sanitation systems must break the cycle of disease. For example the toilet lid and fly screen in a ventilated pit latrine stop flies reaching human faeces and spreading disease. Good sanitation is not simply about access to a particular type of toilet. It is equally dependent on the safe use and maintenance of that technology; otherwise toilets break down, smell bad, attract insects and spread germs.

Good sanitation is essential for safe and healthy childhoods. It is very difficult to maintain good hygiene without water and toilets. Poor sanitation is associated with diarrhoea, cholera, malaria, bilharzia, worm infestations, eye infections and skin disease. These illnesses compromise children’s health and nutritional status. Using public toilets and the open veld can also put children in physical danger. The use of the open veld and bucket toilets is also likely to compromise water quality in the area and to contribute to the spread of disease. Poor sanitation undermines children’s health, safety and dignity.

The data show a gradual and significant improvement in children’s access to sanitation since 2002, although the share of children without adequate toilet facilities remains worryingly high. In 2002, less than half of all children (46%) had access to adequate sanitation. By 2018, the share of children with adequate toilets had risen to 79%. But 4.2 million children still use unventilated pit latrines, buckets or other inadequate forms of sanitation, despite the state’s reiterated goals to provide adequate sanitation to all and to eradicate the bucket system. Over 340,000 children have no sanitation facilities at all (open defecation). Children (21%) are slightly more likely than adults (18%) to live in households without adequate sanitation facilities. This is because children are more likely than adults to live in poor and rural households.

As with other indicators of living environments, there are great provincial disparities. In provinces with large metropolitan populations, like Gauteng and the Western Cape, around 90% of children have access to adequate sanitation, while provinces with large rural populations have the poorest sanitation, and in Limpopo only 57% of children have adequate sanitation at home. Those with the greatest improvements in sanitation services are the Eastern Cape (where the number of children with access to adequate sanitation more than tripled from 626,000 to nearly 2.2 million, KwaZulu-Natal (an increase of 1.8 million children) and Gauteng (an increase of 1.2 million children with adequate sanitation facilities on site). In the Free State the share of children with sanitation improved from 53% in 2002 to 82% in 2018).

Although there have also been significant improvements in sanitation provision in Limpopo, this province still lags behind, with only 57% of children living in households with adequate sanitation. It is unclear why the vast majority of children in Limpopo are reported to live in formal houses, yet access to basic sanitation is the poorest of all the provinces. Definitions of adequate housing such as those in the UN-HABITAT and South Africa’s National Housing Code include a minimum quality for basic services, including sanitation.

The statistics on basic sanitation provide yet another example of persistent racial inequality: more than 95% of Indian, White and Coloured children had access to adequate toilets in 2018, while only 76% of African children had access to basic sanitation. This is a marked improvement from 37% of African children in 2002.

Children in relatively well-off households have better levels of access to sanitation than poorer children. Among the richest 20% of households, 94% of children have adequate sanitation, while 71% of children in the poorest 20% of households have this level of service.

1 Department of Water Affairs and Forestry (2003) Strategic Framework for Water Services. Pretoria: DWAF.

Technical notes

The former Department of Water Affairs and Forestry² defined the minimum standard for basic sanitation as:

appropriate hygiene (keeping toilets clean and washing hands after handling waste or using a toilet);
a system for disposing of human faeces, waste water and rubbish which is affordable, easy to maintain, safe and environmentally acceptable; and
an adequate toilet for each household.

Sanitation therefore includes infrastructure, service provisioning and behaviour. For the purposes of this indicator we use a narrow definition, based simply on the type of toilet available to each household. The General Household Survey asks about each household’s toilet facilities. The following facilities are included in the category of adequate sanitation: ‘flush on-site’, ‘flush off-site’ and ‘VIP’, standing for ventilated improved pit latrine. Inadequate sanitation includes the following: ‘chemical toilet’, ‘other pit’, ‘bucket’, ‘none’ and a small number of ‘unspecified’.

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

2 Department of Water Affairs and Forestry (2002) The policy on basic household sanitation made easy. Pretoria: DWAF

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