Housing & servicesHousing & services

Access to adequate water

Author/s: Katharine Hall
Date: November 2018

Definition

This indicator shows the number and percentage of children who have access to a safe and reliable supply of drinking water at home – either inside the dwelling or on site. A piped water connection is used as a proxy for access to adequate water. All other water sources, including public taps, water tankers, dams and rivers, are considered inadequate because of their distance from the dwelling or the possibility that water is of poor quality or erratic in its supply. The indicator does not show whether the water supply is reliable or if households have broken facilities or are unable to pay for services.

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 lines at the top of each bar.
Clean water is essential for human survival. The World Health Organisation has defined “reasonable access” to water as being a minimum of 20 litres per person per day.1 The 20-litre minimum is linked to the estimated average consumption when people rely on communal facilities and need to carry their own water for drinking, cooking and the most basic personal hygiene. It does not allow for bathing, showering, washing clothes or any domestic cleaning.2 The water needs to be supplied close to the home, as households that travel long distances to collect water often struggle to meet their basic daily quota. This can compromise children’s health and hygiene.

Young children are particularly vulnerable to diseases associated with poor water quality. Gastro-intestinal infections with associated diarrhoea and dehydration are a significant contributor to the high child mortality rate in South Africa,
3 and intermittent outbreaks of cholera in some provinces pose a serious threat to children in those areas. Lack of access to adequate water is closely related to poor sanitation and hygiene. In addition, children may be responsible for fetching and carrying water to their homes from communal taps, or rivers and streams. Carrying water is a physical burden which can lead to back problems or injury from falls. It can also reduce time spent on education and other activities, and can place children at personal risk.4 For purposes of the child-centred indicator, therefore, adequacy is limited to a safe water source on site.

There has been little improvement in children’s access to water over the past 15 years. Close to six million children live in households that do not have access to clean drinking water on site. In 2017, more than three-quarters (78%) of adults lived in households with drinking water on site – compared with only 70% of children.

Provincial differences are striking. More than 90% of children in the Gauteng and the Western Cape provinces have an adequate water connection. However, access to water remains poor in KwaZulu-Natal (58%), Limpopo (52%) and the Eastern Cape (46%). The Eastern Cape appears to have experienced a striking improvement in water provisioning since 2002 (when only 24% of children had water on site). KwaZulu-Natal has also recorded significant improvements: the proportion of children who had water on site increased from 46% (2002) to 58% (2017). Other provinces that have also recorded improvements include Limpopo (from 45% (2002) to 52% (2017), the Free State from 82% to 89% over the same period, and the North-West (from 56% to 64%).The significant decline in access to water in the Northern Cape may represent a deterioration in water access, or may be the result of weighting a very small child population.

Children living in formal areas are more likely to have services on site than those living in informal settlements or in the rural former homelands. While the majority (77%) of children in formal dwellings have access, it decreases to 64% for children living in informal dwellings. Only 23% of children living in traditional housing have water available on the property.

The vast majority of children living in traditional dwellings are African, so there is also a pronounced racial inequality in access to water. In 2017, 66% of African children had water on site in 2017, while more than 96% of all other population groups had drinking water at home.There are no significant differences in access to water across age groups.

Inequality in access to safe water is also pronounced when the data are disaggregated by income category. Only 54% of children in the poorest 20% of households have access to water on site, while 97% of those in the richest 20% of households have this level of service. In this way, inequalities are reinforced: the poorest children are most at risk of diseases associated with poor water quality and the associated setbacks in their development.



1 Ki-moon B (2007) Children and the Millennium Development Goals: Progress towards a World Fit for Children. UNICEF: New York.
2 Howard G & Bartram J (2003) Domestic Water Quantity, Service Level and Health. Geneva: World Health Organisation.
3 Westwood A (2011) Diarrhoeal disease. In: Stephen C, Bamford L, Patrick W & the MRC Unit for Maternal and Infant Health Care Strategies (eds) Saving Children 2009: Five Years of Data. A Sixth Survey of Child Healthcare in South Africa. Pretoria: Tshepesa Press, Medical Research Council & Centre for Disease Control and Prevention.
4 COHRE, AAAS, SDC & UN-Habitat (2007) Manual on the Right to Water and Sanitation. Geneva: Centre on Housing Rights and Evictions.
The General Household Survey asks questions about the household’s main source of water. From 2002 to 2004 there was a single question that asked about the household’s main water source (for all purposes). Since 2005, the question was split into two parts so that respondents report the main water source for drinking water and for water that is used for other purposes. Since then, Children Count presents the main source of drinking water because of the importance of having clean water for children and babies. The slight change in question formulation means that the data before and after 2005 are not directly comparable.
 
This indicator only tells us how many children have access to the infrastructure to deliver clean drinking water to children’s homes. It does not give any indication of how many households have broken facilities, are unable to pay for water, have experienced interruptions in their water, or have been cut off for non-payment.
 
Policy guidelines on basic water supply indicate that water may be off-site, but must be within 200 metres of the house. This child-centred indicator has therefore used a slightly narrower definition and defines ‘adequate’ as being on site. Collecting water from a public source is physically burdensome and can be dangerous, especially for children.
 
For purposes of measuring and monitoring persistent racial inequality, population groups are defined as 'African', 'Coloured', 'Indian', and 'White'.
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