It is publically acknowledged that South Africa has recently met its millennium development goal of halving water and sanitation services (WSS) backlogs. However, significant deficits remain, especially in the case of sanitation. These shortfalls are unevenly distributed across provinces and can be tracked by socio-economic status. This article seeks to examine and identify the socio-economic factors that may affect poor WSS provision in South Africa. Using the 2014 South African General Household Survey, socio-economic indicators and access to WSS were analysed. Descriptive statistics and multivariate analysis indicate that access to WSS is largely determined by province, race and geographical location. It appears that higher quality levels of sanitation are less accessible relative to piped water access. Identifying these socio-economic factors affecting WSS provides obvious policy direction and better-targeted water infrastructural development.
In 1994, the new democratic government faced massive regional and racial differences with regard to adequate water and sanitation services (WSS) (Department of Environmental Affairs
From a general perspective, providing safe and reliable WSS is a huge and costly undertaking, especially in a developing country context. The World Health Organization estimates the economic costs of poor sanitation to be around $23.5 billion for sub-Saharan Africa or 5% of GDP (Choge & McCornick
MDG aside, the South African government has itself spent billions in the WSS development process. Going beyond the goals, to provide full universal access by 2015, it was estimated that the government would need to spend the equivalent of US $857 million per annum and $1.21 billion per annum as the required investment to meet the total backlog of upgrading water supply services and sanitation facilities, respectively, including all the informal settlements in association with the housing programme (World Bank
Given this high cost, a greater understanding of how and where to target development is required. To improve social returns on public investments, the socio-economic characteristics of the households most in need of better WSS is required to help sharpen the focus of water policy in terms of allocating water-based resources, infrastructure provision and, ultimately, water pricing. The need for higher social returns will continue to grow as water resources in general become more strained. Despite the drive for universal access, policies have to be sensitive to ecological constraints, especially so in South Africa, given its uneven rainfall patterns and climatic variability (Department of Environmental Affairs
In South Africa, there is little recent work on identifying the socio-economic characteristics of households that access piped water and even less on the equivalent analysis for sanitation over the same sample. As such this research is focused on identifying those households that (1) access piped water and (2) access a flush toilet. Comparing access to piped water and flush toilets enables a relative comparison of useful progress indicators.
The section ‘Background’ gives a brief background of South African WSS targets, the challenges faced by the government and progress made since 1994. This section is concluded by a review of the specific relevant economics literature on socio-economic predictors of water access and sanitation. The section ‘Data and methods’ details the chosen methodology of investigation and econometric specification followed by results in the section ‘Results’ and a concluding discussion in the section ‘Discussion’.
Historically, in South Africa, clean piped water and a flush toilet were associated with white privilege, with the majority of black South Africans only having access to dry toilets (Eales
In 1997, South Africa declared basic water and sanitation a human right under the auspices of the
After publishing the National Sanitation Policy in 1996 (much like the 1994 Water Supply and Sanitation Policy), the 2001 White Paper on the Basic Household Sanitation was followed by a series of initiatives, including inter alia the 2003 Water Services Framework and the National Sanitation Strategy tasked with recovering the backlog of sanitation provision by 2010. In 2009, the Department of Water Affairs (DWA) passed the Free Basic Implementation Strategy that was given the mandate to guide the 169 water service authorities across the country in fulfilling national policy as laid down by the 2001 White Paper (Tissington
Much progress has been made concerning WSS access in South Africa. Households with general access to water infrastructure has risen from 61.7% in 1994 to 95.5% by 2012 and just over 8000 households are still using a bucket system for human waste (Department of Environmental Affairs
The statistics are crucial but the human dimension of poor WSS is staggering considering the social loss of personal hygiene, disease protection and dignity (City of Cape Town
Whilst interesting, relevant and necessary, achieving MDGs is no panacea. This article is not intended to test the feasibility of WSS based on any MDG but rather to better understand the socio-economic characteristics of households that do not have access to piped water and a flush toilet. For a given population, piped water and flush toilets for all would arguably be the end point in terms of infrastructural improvement and reversing apartheid-era neglect with maintenance the only concern. Given this development gap, examining water supply and sanitation under these criteria would continue to inform policy and also reveal the dual progress of WSS.
There is a growing body of literature that is making stronger links to the lack of access to safe WSS having devastating effects on labour force participation, education, cooking and food provision and equity of women, especially in rural areas (Choffnes & Mack
Much of recent theoretical and empirical water poverty research over the last decade has focused on developing a water poverty index comprising of variables representing access, use, capacity, resources and environment distilled into one neat number. Unfortunately, this has not resulted in an index definition that all can agree upon (Komnenic, Ahlers & Zaag
There is a broad agreement that household income is a powerful predictor of domestic water quality (Sullivan
Previous research examining associated socio-economic variables on WSS in the South African context is thin. Dungumaro (
StatsSA (
Whilst the few aforementioned studies identified the socio-economic variables associated with safe/unsafe water, there is even less independent research in the South African sanitation context. Kirigia and Kainyu (
The analysis presented later in the article builds on previous work, extends and updates it. There is little literature that focuses on the socio-economic background of water-poor households and even less over the last 10 years where it is hoped that much improvement in water facilities has occurred. The said analysis compares piped and non-piped drinking water rather than the more typical safe and unsafe distinction. According to StatsSA, safe water includes piped water in the dwelling, on-site or off-site and also from a borehole source (Statistics South Africa
For sanitation, the basic provision for adequate sanitation refers to a ventilated pit latrine (VIP) if it is constructed and maintained properly (Statistics South Africa
The data were drawn from the 2014 GHS. The GHS is a nationally representative cross-sectional survey that has been conducted by Statistics South Africa (Stats SA) annually since 2002. The aim of the GHS is to determine the level of development in South Africa. The survey questions are designed to collect information on service delivery and living conditions and cover a range of broad areas such as education, health, labour market participation and household access to services and facilities (Statistics South Africa
There are also a number of questions pertaining to water access, quality and municipal service provision as well as sanitation. This study selected access to piped water as the variable describing the highest provision standard asked in the GHS. If South Africa’s goal is to go beyond the MDGs and provide universal coverage, examining piped water access to households is arguably a key objective consistent with that goal. With regard to sanitation, the highest level of access is arguably access to a flush toilet. The GHS enquires about the type of toilet facility used by each household and the location of the toilet. Detailed responses regarding access to both piped water and a flush toilet then allows an investigation into how different socio-economic variables may affect such access. It is worth noting that this study, whilst examining how socio-economic variables relate to WSS access per se, also uniquely investigates water supply and sanitation separately using the same sample. This allows us to see if both are equally related to socio-economic status.
There are a range of survey questions regarding the socio-economic status of the household. These included questions regarding a household’s geographical location (urban/rural and province), dwelling type (informal or formal), household size (number of people living in the dwelling) and access to electricity as well as information on the household head which includes educational attainment, gender and race. The choice of these variables is based on previous findings from the literature and
The type of dwelling structure captured by the GHS and the number of people living there may significantly be related to WSS provision. Along with electrical supply or lack thereof, these are all typical variables that indicate higher levels of poverty which may also be consistent with a lack of WSS. Lower levels of education are often associated with lower income earning ability and chances of employment and could be strongly linked with lower WSS. The literature has also found that female-headed households are more vulnerable to a lack of WSS and was therefore included in the study as was race given South Africa’s history of underdevelopment for certain groups and communities.
In addition to these, there is information pertaining to household income and asset ownership; however, these were not used in the analysis given that the variables for race, gender and geographical location of the household serve as a sufficient proxy for socio-economic status. All socio-economic variables described above were explored using descriptive statistics. Those found to be significant were used to specify the regression. These results are presented in the next section.
The theoretical framework for the study stems from the notion that the provision of piped water and flush toilet access represent a much higher form of WSS development, reversing years of underdevelopment for certain groups and communities. Whilst costly in terms of public investment expenditure, requiring ongoing maintenance, this is ultimately a long run policy target. This was felt to be the most interesting research question, especially as both sanitation and water supply are examined separately in the same sample. As such, this framework requires that the dependent variables are built on a strict ‘provision or no provision’ principle of piped water and flush toilet access.
The question in the GHS pertaining to piped water asks for households to identify their main source of drinking water. Responses include piped water inside the dwelling, in the yard, in a neighbour’s tap, in a communal or public tap, in boreholes, in rain water tank, in flowing or stagnant water amongst others. For the purpose of this analysis, a variable representing access to piped water was created. The variable is binary and equal to one if a household was identified as having access to piped water inside their dwelling, in their yard, their neighbour’s tap or a communal/public tap and is equal to zero for all other water sources.
In addition, a variable representing household access to a flushing toilet was created such that it equals one if a household has a flush toilet connected to a public sewerage system or septic tank and zero if a household uses a chemical toilet, pit latrine, bucket toilet or no toilet. In South Africa, 90% of households have access to piped water whilst two-thirds have access to flush toilets.
Main source of drinking water for households in South Africa.
Of all the households with access to piped water, just over two-thirds have access to a flush toilet (
Cross tabulation showing access to both piped water and flush toilet.
Toilet type | Piped water |
No piped water |
||
---|---|---|---|---|
% | % | |||
No flush toilet | 28.3 | 0.4 | 86.4 | 0.8 |
Flush toilet | 71.7 |
0.4 | 13.6 |
0.8 |
Notes: Data have been weighted to be nationally representative. Standard errors are in parentheses.
Significantly different at the 5% level compared to the ‘no piped water’.
Households with access to flush shared versus non-shared toilets.
More than two-thirds of these households with access to flush toilets have a toilet inside their dwelling, whilst just under a third of the households have a facility outside the dwelling but within their yard (
Households with access to flush toilets by location
A number of socio-economic status indicators in relation to household access to either piped water or a flushing toilet were analysed (
Household socio-economic indicators.
Socio-economic variable | Piped |
Not piped |
Total | Flush |
No flush |
Total | ||||
---|---|---|---|---|---|---|---|---|---|---|
% | % | % | % | |||||||
Formal housing | 91.9 |
0.2 | 8.1 | 0.2 | 100 | 72.6 |
0.4 | 27.4 | 0.4 | 100 |
Informal housing | 81.2 |
0.7 | 18.8 | 0.7 | 100 | 35.0 |
1.0 | 65.0 | 1.0 | 100 |
Urban area | 98.4 |
0.1 | 1.6 | 0.1 | 100 | 89.1 |
0.3 | 10.9 | 0.3 | 100 |
Rural area | 71.4 |
0.5 | 28.6 | 0.5 | 100 | 12.5 |
0.5 | 87.5 | 0.5 | 100 |
African | 87.9 |
0.3 | 12.1 | 0.3 | 100 | 57.1 |
0.5 | 42.9 | 0.5 | 100 |
Mixed race | 98.6 |
0.3 | 1.4 | 0.3 | 100 | 96.3 |
0.5 | 3.7 | 0.5 | 100 |
Indian | 99.3 |
0.3 | 0.7 | 0.3 | 100 | 99.2 |
0.3 | 0.8 | 0.3 | 100 |
White | 96.3 |
0.4 | 3.7 | 0.4 | 100 | 99.9 |
0.1 | 0.1 | 0.1 | 100 |
Household head is male | 91.3 |
0.3 | 8.7 | 0.3 | 100 | 71.6 |
0.5 | 28.4 | 0.5 | 100 |
Household head is female | 87.8 |
0.3 | 12.2 | 0.3 | 100 | 57.8 |
0.6 | 42.2 | 0.6 | 100 |
Connected to electricity mains | 91.5 |
0.2 | 8.5 | 0.2 | 100 | 69.5 |
0.4 | 30.5 | 0.4 | 100 |
Not connected to electricity mains | 91.7 |
1.1 | 8.3 | 1.1 | 100 | 75.1 |
1.8 | 24.9 | 1.8 | 100 |
Notes: Data have been weighted to be nationally representative. Standard errors are in parentheses.
Significantly different at the 5% level compared to the ‘not piped’ or ‘no flush’ category, respectively.
It is important to note that for the African subset of the population,
Geographical differences of piped water against a flush toilet access are shown using two maps.
Access to piped water or flush toilets by education, employment status and household size.
This is now contrasted with access to flush toilet on the property in
Average monthly household income (incl. grants).
Only the Western Cape and Gauteng maintain their 90% or more status. Comparing the two maps, it can be clearly seen that all the other provinces drop considerably in how many households have access to a flush toilet on the property. This is consistent with
Household socio-economic drivers of access to piped water and flushing toilet.
Socio-economic variable | Piped water |
Flush toilets |
||||
---|---|---|---|---|---|---|
I | II | III | I | II | III | |
Flush toilet | 0.16 |
0.04 |
- | - | - | - |
Piped water | - | - | - | 0.62 |
0.14 |
- |
Household size | - | -0.00 (0.00) | -0.00 |
- | -0.02 |
-0.02 |
Number of household members employed | - | 0.00 (0.00) | 0.00 |
- | 0.08 |
0.08 |
Connected to electricity mains | - | 0.03 |
0.03 |
- | -0.05 (0.03) | -0.04 (0.03) |
Urban | - | 0.17 |
0.24 |
- | 0.75 |
0.77 |
Male | - | -0.01 |
-0.00 (0.00) | - | 0.05 |
0.05 |
Educational attainment of household head (years) | - | -0.00 (0.00) | 0.00 (0.00) | - | 0.03 |
0.03 |
Formal housing | - | 0.02 |
0.03 |
- | 0.47 |
0.48 |
Notes: Data have been weighted to be nationally representative. The marginal effects of the probit estimations are presented. Standard errors are in parentheses. Figures marked with
are significant at the 1% level and
at the 5% level.
African household socio-economic drivers of access to piped water and flushing toilet.
Variable | Piped water |
Flushing toilet |
||
---|---|---|---|---|
% | % | |||
Household size | −0.00 |
0.00 | −0.02 |
0.00 |
Number of household members employed | 0.00 |
0.00 | 0.06 |
0.01 |
Connected to electricity mains | 0.04 |
0.01 | −0.05 | 0.03 |
Urban | 0.24 |
0.01 | 0.75 |
0.01 |
Male | −0.00 | 0.00 | 0.03 |
0.01 |
Educational attainment of household head (years) | 0.00 | 0.00 | 0.02 |
0.00 |
Formal housing | 0.04 |
0.00 | 0.42 |
0.02 |
Notes: Data have been weighted to be nationally representative. The sample consists of African households only. The marginal effects of the probit estimations are presented. Standard errors are in parentheses. Figures marked with
are significant at the 1% level,
at the 5% level and
at the 10% level.
In addition to the above, other socio-economic variables were examined. Those households with piped water tend to be smaller as larger households are typically associated with higher levels of poverty (Dungumaro
Geographic distribution of households with piped water on the property.
These descriptive results therefore indicate that sanitation services are still lacking in comparison to piped water provision. It is clear that Africans, female-headed households and those in rural areas are mostly affected by this lack of service provision. This article will hence examine these relationships more closely by estimating a probit model to determine the extent to which socio-economic indicators can predict access to these services. Whilst it is clear that the main concern is sanitation, this article will conduct a similar analysis for both piped water and sanitation to enable comparison.
The multivariate analysis aims to determine whether certain socio-economic indicators affect household access to piped water and to a flushing toilet. In both cases, as the dependent variable is binary, a probit model was used:
In this case, Y represents a dummy variable for piped water (as mentioned above) and X is a vector of household-level socio-economic indicators which includes dwelling type, household size, gender, race and educational attainment of the household head, the number of household members employed, electricity connection and geographical (urban/rural) location. Given that 71.7% of households with piped water were identified as having a flushing toilet (
The probit model (Eqn 1) was estimated three times, varying the explanatory variables each time so as to ensure the robustness of the results. In addition, we expect that access to piped water is a likely predictor of sanitation given that sanitation services may require piped water infrastructure; thus, these two variables may actually be collinear. The first probit (I) simply estimates the probability of accessing piped water if a household has a flush toilet. The second (II) includes the additional household-level indicators mentioned above and the third (III) excludes the variable for flush toilets.
The marginal effects of the probit estimations are presented in
With reference to the same
Once again the marginal effects of the probit estimations are presented in
Household income (including government grants) was not included in the regressions owing to its insignificance in all models; however, the differences in income between access and no access are wider for flush toilet than piped water (
Geographic distribution of households with flush toilets on the property.
Results suggest that poverty issues (informal households located in rural areas) drive access to flush toilets more so than piped water. The 2014 GHS data show that 38% of households in rural areas are headed by Africans. Given that Africans appear to be the worst affected population group in terms of flush toilet access, the probit model (III) was re-estimated for African households only (
Being able to access piped drinking water and a flushing toilet is taken for granted by many. In reality, this is a luxury which many households in South Africa do not experience even after more than 20 years of democracy in Africa’s largest economy. Inadequate provision of WSS is at best undignified but is potentially costly in terms of lost productivity and a health sector burden. Whilst, of course, there has been considerable progress since 1994 in achieving WSS development, consistent with previous studies, results show that progress in the domain of piped drinking water is more advanced than sanitation. As such the socio-economic variables examined here are not significant predicators of household access to piped water, whereas access to flush sanitation still appears to depend on household socio-economic status.
Relative to piped water access, having access to a flush toilet is more dependent upon many of the socio-economic variables, as they act as poverty signals, including household size, the number of people employed in the household, connection to the electricity mains, geographical location (urban/rural), gender of the household head, educational attainment of the household head and dwelling type. A plausible explanation could be that piped water relative to flush sanitation has been largely addressed as a supply-side issue, with government expanding infrastructure to accommodate households countrywide. However, the same practice does not seem to have been applied to flush sanitation services, indicating that poorer households are significantly worse off. This could be indicative of a lack of infrastructure and service delivery in poor rural areas. Such a premise is supported by the National Planning Commission which identifies that the rural municipalities have little of the technical expertise to manage the whole supply chain of WSS projects from source to tap. Such infrastructure is a prerequisite for flush toilets which will also require additional technical support over the more basic VIP latrines.
An important aspect of water provision and motivations for improvement is health. The social health dimension of better access to quality drinking water and sanitation facilities was not enabled by the data. The only waterborne disease that is reported on in the GHS is that of very recent diarrhoea problems. The sample reporting these issues is too small to make useful inferences with regard to piped water or flush toilet ownership. This remains an interesting area for future research as adequate volumes of water and sanitation facilities are needed to support a basic level of hygiene. Increasing the quality of water access and sanitation is arguably a necessary condition for associated incremental health improvements although perhaps not sufficient. Health education may be needed to ensure appropriate behavioural changes.
Identifying and understanding the importance of the different household socio-economic characteristics remains an important part of WSS-based policy design. Despite progress, the calls for service delivery in WSS continue to get louder as expectations grow and the disparity of provision by geography, race group or otherwise widens. This article serves to highlight those important socio-economic factors that identify water impoverished households, especially in the domain of sanitation. Policymakers would be well advised to focus attention in this area and ensure that the required level of technical ability is in place in areas of WSS scarcity. Whilst this is beyond the scope of this article, it is acknowledged that providing universal WSS has to be achieved within the limits of environmental capacities. Flush toilets are water-intensive and alternative technologies may be more appropriate as environmental constraints get tighter.
The authors wish to thank Warren Botes for his invaluable assistance in creating the GIS maps. The authors would like to thank ERSA for their input and comments in earlier drafts.
The authors declare that they have no financial or personal relationships which may have inappropriately influenced them in writing this article.
Both authors conceptualised the article and designed the research questions. B.R. wrote the literature review and the main results section. T.M. ran the regressions and generated the charts and tables. Both authors wrote the discussion and concluding sections
Significant at the 5% level, with respect to the categories for no piped water and no flush toilet, respectively.
As determined by the race identified by the household head.