Examining households’ expenditure patterns on water, sanitation, and hygiene services in urban slums in Southeast Nigeria

Abstract

Objectives:

Access to safe water, sanitation, and hygiene (WASH) is essential for human health and wellbeing. However, many households in slum settlements lack access to WASH and are exposed to adverse health effects. Understanding household expenditure and equality in access to WASH is crucial for developing effective policies and interventions to improve access to such services. This paper offers new insights into household expenditures and equality in access to WASH services in urban slums in Nigeria.

Methods:

A cross-sectional study was conducted in two urban slums in Anambra State, Nigeria. An interviewer-administered questionnaire was used to collect data on household expenditures on WASH services from 421 purposively selected households. Household expenditures on WASH were computed. Multiple regression was used to investigate associations between WASH expenditures and socioeconomic characteristics. Principal component analysis was used to create wealth quintiles. Concentration indices were used to assess equality in expenditures.

Results:

The average monthly and yearly household expenditure on WASH were US$19.9 and US$168.6, respectively. WASH spending accounts for 11.3% of the household expenditure. The mean annual expenditure on hygiene accounted for 57.9% of total expenditures on WASH services, followed by water (36.9%) and sanitation (5.6%). Expenditure on water (CI: −0.019, p-value: 0.637) and sanitation services (CI: −0.011, p-value: 0.800) was slightly concentrated among the poorer population, while expenditure on hygiene services (CI: −0.012, p-value: 0.561) was slightly concentrated among the wealthier population. Expenditures on WASH services were equitable across wealth quintiles (CI: −0.001, p-value: 0.946). Larger household size (mean difference: 80,874; 95% CI: 50,621; 111,127) and respondents older than 38 years (mean difference: 37,679; 95% CI: 7,137–68,220) were associated with higher expenditures.

Conclusion:

This study highlights the significant financial burden that households in urban slums face in accessing WASH, which can lead to a decrease in their use. Decision-makers should consider targeted subsidies for water and sanitation services, promote hygiene awareness in low-income households, and invest in affordable WASH infrastructure.

Introduction

About 2.2 billion people worldwide lack access to safe drinking water, while approximately 4.2 and 3 billion lack access to safe sanitation and basic hygiene, respectively (WHO and UNICEF, 2019). Access to appropriate water, sanitation, and hygiene (WASH) services is essential for human health, dignity, and wellbeing (WHO and UNICEF, 2019). The severe consequences of inadequate access to WASH services include increased morbidity and mortality, reduced economic productivity, and diminished quality of life (WHO, 2018). The scenario in urban slums in developing countries, including Nigeria, is even worse, as many households lack access to high-quality WASH services (UN-Habitat, 2016). Only 11% of the Nigerian population has access to basic WASH services, representing a significant gap between access to various WASH components (FMWR, NBS, and UNICEF, 2021). About 87% of households lack access to safe drinking water services, while only 13% of the population use improved sanitation facilities with a proper handwashing station that has running water and soap (FMWR, NBS, and UNICEF, 2021). The country also records a high prevalence of open defecation, with 23% of households practising open defecation (FMWR, NBS, and UNICEF, 2021). In addition, 11% of households spend more than 30 min to fetch water, indicating a significant burden of water collection on households (UNICEF, 2019).

The provision of appropriate WASH services in Nigeria is bedevilled with significant challenges that include high household expenditures on WASH services, inadequate funding, poor infrastructure, and weak institutions (Federal Ministry of Water Resources, 2021). Hence, many residents of urban slums rely on informal and substandard WASH services (National Bureau of Statistics, 2021). Consequently, poor access to appropriate WASH services is a major contributing factor to high morbidity and mortality rates among children under five (CU5) as a result of increased vulnerability to water-borne diseases, including diarrhoea, which leads to deaths of more than 70,000 CU5 in Nigeria (UNICEF, 2018).

Household expenditure on WASH services is a critical indicator of financial access, as it reflects the economic burden of securing these essential services. Many households in urban slums face significant financial constraints in access to WASH services, making it difficult for them to afford appropriate services (Abdulhadi et al., 2024; Acheampong et al., 2024). Also, there is inequality in the distribution of household expenditure on WASH services, with the poorest households paying the highest proportional prices for services compared to their income (Acheampong et al., 2024; Azeez et al., 2023).

However, the level of household expenditures and effects on access to WASH remain understudied in urban slums in Nigeria. There is also limited research on household expenditure on WASH at the micro-level. Current research has primarily focused on evidence around access, infrastructure, and the impact of poor access on health outcomes (WHO and UNICEF, 2019; UNESCO, 2019). While these studies have contributed significantly to our understanding of WASH challenges, they have largely overlooked the critical issue of household expenditure on WASH services.

Consequently, there is a need for evidence on household expenditure and equitable access to WASH services within urban slums in Nigeria. Such information is essential for informing policy and investment decisions aimed at promoting equitable access to improved WASH services. Evidence on WASH expenditures and access also contributes to the discussion surrounding the achievement of Sustainable Development Goal (SDG) 6 (Ensure access to water and sanitation for all), particularly targets 6.1 (Achieving universal and equitable access to safe and affordable drinking water for all) and 6.2 (End open defecation and provide access to sanitation and hygiene). This paper offers new insights into household expenditures and equality in access to WASH services in urban slums in Nigeria.

Methods

Conceptual framework

This study was guided by the principles of the Distributional Impact Analysis (DIA) framework (Bedoya et al., 2017) to investigate how water, sanitation, and hygiene (WASH) expenditures affect various income groups in urban slums. DIA is grounded in the principles of equality, which emphasize the need to ensure that all households, regardless of socio-economic status, have access to safe and affordable WASH services. The framework posits that household WASH expenditures are a critical factor in determining access to these essential services, particularly for low-income households.

It assesses the distribution of WASH resources and services across different SES groups, focusing on factors like expenditure proportions, access to WASH services, and service quality while highlighting potential inequalities. The DIA framework, therefore, provides a lens to understand the relationships between WASH expenditures, SES groups, and access to services in urban slums. Exploring these dynamics to identify the most vulnerable income groups and inform policies that promote equitable access to WASH services, and ultimately enhancing the wellbeing of urban slum residents.

Study design and setting

A cross-sectional study was conducted in two urban slums in Okpoko, situated in the Ogbaru Local Government Area (LGA), Anambra State, South-eastern Nigeria. The State is one of the most densely populated in the country, with an estimated population of 6.1 million (National Population Commission, 2016). The urban slums in Anambra face significant WASH challenges, including inadequate access to clean water, poor sanitation, and limited hygiene facilities (Anambra State Ministry of Public Utilities, 2019).

Study population

The overall target population consisted of households containing at least one woman of reproductive age and/or at least one child aged 5 years or younger. Participants were eligible if they were community members living in an eligible household within the study sites. Within eligible households, we primarily sought the main female caregiver as the eligible respondent, but if such an individual was not available, we allowed the male head of the household to be the eligible respondent if they had sufficient knowledge of household WASH expenditures.

Sampling and sample size

Two out of six slums were randomly selected in Okpoko. Within each selected slum, data collection began with a random walk from the household closest to the public primary health centre, and continued to the next-nearest household. The next succeeding household was then selected from the recruited ones until the desired sample size was reached. We conveniently selected the households in line with the eligibility criteria. Households not willing to participate were excluded. In each household, the head or primary caregiver was identified for the interview. A revisit was made to each household to recruit primary caregivers who were absent during the initial visit.

To determine the required sample size for exploring household expenditures on WASH services in slums in Nigeria, we conducted a power analysis using standard statistical methods. Assuming a 95% confidence level (α = 0.05) and 80% power (1-β = 0.80), the minimum required sample size was estimated based on the assumption of a proportion of households incurring WASH expenditures (p = 0.5) to maximize variability, as well as an effect size of d = 0.1. Using the standard formula for sample size estimation for proportions:

Where:

• Z = 1.96 (Z-score for 95% confidence level)

• p = 0.5 (assumed proportion)

• d = 0.05 (margin of error)

The minimum required sample size was calculated as 385 households. Given that the two slums under study are similar in size, the sample was divided equally, resulting in approximately 193 households per slum. However, the sample size was increased to 420 (210 households per slum) to enhance the precision, reliability, and generalizability of the research findings, as well as to ensure sufficient statistical power and account for missing data.

Data collection

Data was collected using a pre-tested interviewer-administered questionnaire that elicited information on socio-demographic characteristics, household expenditure on WASH services, and attributes of WASH facilities. The questionnaire was administered using both hard copies and tablets with Open Data Kit (ODK) software installed. Trained enumerators with a minimum of secondary education completed and administered the questionnaire. Data was collected in April 2024.

The study achieved a response rate of 98%, with 421 households participating out of 428 approached. The response rate is considered high, likely due to strong community mobilization and engagement of community leaders before the survey’s commencement, as well as the study’s relevance to the setting. No attrition was observed during data collection.

Data on various expenditure categories, including food and non-food items such as clothing, housing rent, durable household goods, healthcare, cooking fuel, recreation and entertainment, education, food, and WASH, were collected from the households. Data was also collected separately on households’ monthly and annual expenditure on WASH services: water household spending with storage facilities (e.g., tank and its stand, containers, bucket), bills/levies/payments for water supply or purchase and water treatment (e.g., water guard, chlorine, purification tablets, cooking fuel for boiling water), sanitation facilities such as toilet maintenance or repair (e.g., doors, roof, seat, floor), waste bin container (e.g., Sulo or basket), bills/levies/payments for toilet use, bills/levies/payments for sanitation exercise (e.g., Anambra State Waste Management Authority (ASWAMA), community sanitation exercise, waste service provider pick-ups), waste bin and bags, toilet emptying (e.g., soak away, or pit toilet), and hygiene products (e.g., purchase of hand washing equipment such as buckets, stand, tap), washing/laundry soap or detergent and bathing soap, toothpaste and brush/chewing stick, sanitary pads, tissue paper/wipes, and other washing materials (e.g., hypo/bleach/Jik, dettol/izal sponge).

Data analysis

The data were cleaned and analyzed using Stata version 17. Descriptive statistics were used to describe the socio-economic characteristics of the study respondents by calculating frequencies for each slum and overall. We also applied this approach to characterize household WASH practices and facilities. Monthly and yearly household expenditures on WASH services and components were calculated as mean (95% CI) and median (IQR). The expenditure data were collected in Nigerian Naira (₦) and converted to United States Dollars (US$) using the exchange rate (₦1,450 = US$1) (OANDA currency converter) at the time of data collection.

Key variables:

• Outcome or dependent variable – Total expenditure on WASH, which was measured as the amount of money spent by the household while purchasing WASH services.

• Explanatory or independent variables – Socio-economic variables: age of the respondent in the household, gender, educational level, occupation or major source of income, household size, and wealth quintiles where the household falls.

Gamma regression analysis was also conducted to investigate the relationship between WASH annual expenditures and socioeconomic characteristics (age, household size, occupation, education, and wealth quintile). WASH spending as a percentage of household expenditure was calculated by dividing the total WASH expenditure by the total household expenditure and multiplying by 100. The principal component analysis (PCA) was used to create the wealth index of the respondents using household living assets and living conditions. The concentration index (CI) was used to measure the degree of inequality in the distribution of WASH expenditures according to wealth quintiles (O'Donnell et al., 2008; Wagstaff et al., 1991). The index varies from −1 and +1, with (−) denoting the concentration of expenditures amongst the poorest (regressivity) and (+) the concentration amongst the richest (progressivity). We applied the concentration index to measure socioeconomic inequalities in WASH expenditure, allowing us to quantify the distribution of WASH spending across different wealth quintiles. It quantifies the degree to which a variable is concentrated among the poor or the rich, providing a summary measure of inequality. This approach enables us to identify potential disparities in WASH expenditure and inform targeted interventions that promote more equitable access to WASH services. Our analytical focus is on examining inequality rather than inequity, as we aim to measure the distribution of WASH expenditure without making normative judgments about fairness (Figure 1).

Figure 1

Ethical considerations

The study was approved by the Ethics Committee of the University of Nigeria Teaching Hospital, Ituku Ozalla, Enugu (UNTH/HREC/2023/10/639) and the University of Leeds (MREC 23–013). Informed consent was obtained from all respondents before administering the questionnaire. Respondents were assured of confidentiality and anonymity.

Results

Demographics, socioeconomic profile, and WASH facilities

Table 1 shows the socioeconomic characteristics of the respondents and households. Most respondents were female (99.3%). The majority had secondary education (67.5%) and were employed (93.6%). The mean household size was six, while the mean age of the respondents was 38 years.

Table 2 shows the WASH practices and facilities of the households disaggregated by the study communities. The source of drinking water for the majority (83%) was boreholes. Almost all the respondents purchased their water (96.9%). The most common toilet facility was a flush or pour/flush toilet (77%). Only 4% of the respondents had handwashing facilities in their households.

Household expenditure on WASH services

The mean (95% CI) and median (IQR) monthly and yearly household expenditure on WASH services are presented in Table 3. The median expenditure on WASH services varied across different categories, with the highest median expenditure being reported on hygiene (monthly: US$6.95; yearly: US$82.76), followed by water (monthly: US$4.63; yearly: US$46.69) and then sanitation (monthly: US$3.17; yearly: US$6.07). The monthly and yearly WASH median expenditures were US$15.79 and US$142.21, respectively. The annual mean expenditures on hygiene accounted for 57.9% of total WASH spending, while water (36.9%) and sanitation (5.6%) expenditures were lower.

Table 4 presents a snapshot of household expenditure and WASH spending among the households. On average, households spend US$168.61 on WASH services, which accounts for approximately 11.27% of their total household expenditure. The total WASH spending for the households surveyed amounts to US$70,983.54, while the average household expenditure is US$1,496.23, totaling US$629,772.64.

Expenditure pattern on WASH services

Table 5 presents the relationship between yearly expenditures on WASH and various socio-economic characteristics. There was a statistically significant difference in terms of household size and respondents’ age. Respondents from larger households (mean difference: US$55.77; 95% CI: US$34.91-US$76.64) and older than 38 years (mean difference: US$25.98; 95% CI: US$4.92 - US$47.05) reported higher yearly expenditures on WASH. No other socio-economic characteristics demonstrated statistically significant differences (Table 6).

Equality in access to WASH services

The concentration index of −0.019 indicates that expenditure on water services was slightly concentrated among the poorer population. For sanitation services, the concentration index of −0.011 shows that expenditure was also slightly concentrated among the poorer population, while the concentration index of 0.012 indicates that expenditure on hygiene services is slightly concentrated among the wealthier population. Overall, the concentration index for WASH was −0.001. However, the p-values were not statistically significant. Figures 2–5 show the concentration index of WASH expenditure by wealth quintiles.

Figure 2

Figure 3

Figure 4

Figure 5

Discussion

The study provides valuable insights into household expenditure patterns and inequalities in accessing WASH services in urban slums in Nigeria. There were varying estimates of household expenditure on different components of WASH services. The findings of this study highlight the significant expenditure on WASH services by households in urban slums, with hygiene services accounting for the largest proportion of total WASH spending. The higher percentage of expenditure on hygiene services may indicate that households in urban slums prioritize personal hygiene practices, potentially due to awareness of its importance in preventing illnesses and maintaining personal cleanliness. This finding suggests that households are investing in hygiene products and practices to protect their health. However, this prioritization of hygiene over sanitation services may also highlight the need for a more balanced approach to WASH investments, ensuring that both hygiene and sanitation services are adequately addressed to promote overall health and wellbeing. The relatively low expenditure on sanitation services is concerning and may reflect the filthy nature of many slum environments, where inadequate sanitation infrastructure and poor waste management practices are common. This low expenditure on sanitation services may perpetuate the cycle of poor health outcomes and environmental degradation in these settings.

The substantial financial burden of WASH services on households in urban slums, accounting for 11.3% of household expenditure, may also have broader implications for household welfare, potentially diverting resources away from other essential expenses such as healthcare and education. Chronic challenges, including underinvestment, fragmented institutional responsibilities, and inadequate regulations, exacerbate the issue (FMWR, NBS, and UNICEF, 2021). These findings are consistent with research highlighting access inequities in WASH services in LMICs (Abdulhadi et al., 2024). The findings underscore the need for increased investments in WASH infrastructure and targeted support (FMWR, NBS, and UNICEF, 2021; WHO and UNICEF, 2019) for the underserved areas to achieve SDG 6, particularly since household spending on WASH may not necessarily translate to access to quality, safe, and sustainable services and practices. This requires a multifaceted approach that prioritizes the needs of underserved areas and populations.

The result for households with larger members spending more on WASH services is expected. This is probably due to comparatively increased demands for water, sanitation, and hygiene-related services, which translates into higher expenditures (UNICEF, 2019). Also, older household heads, often with more experience and awareness of the importance of WASH services, may prioritise it, which can lead to comparatively increased expenditure. Our findings are consistent with studies showing that household size and/or age were significant predictors of WASH expenditure (Gaffan et al., 2022; WHO and UNICEF, 2019; Tanzania National Bureau of Statistics, 2019; India National Sample Survey Office, 2019). Other studies have also reported mixed findings in terms of the demographic factors influencing WASH expenditure. For example, a study in Nairobi found that household size was not a significant predictor of WASH expenditure (Sarkar, 2020). On the other hand, a study in Uganda found that the age of the household head was a significant predictor of WASH expenditure (Whittington et al., 2012), which is consistent with the current finding. The difference in findings may be due to differences in methodology or sampling frames.

Our study reveals interesting patterns in WASH expenditures concerning socio-economic characteristics. Notably, households with secondary education had higher mean WASH expenditures compared to those with primary education. This may suggest that households with secondary education are more aware of the importance of WASH services or have better access to resources to invest in these services. However, households with tertiary education did not exhibit significantly higher expenditures, which may indicate that other factors, such as income or occupation, play a more significant role in determining WASH expenditures. Furthermore, our study shows that employed households had higher mean WASH expenditures compared to unemployed households. This finding highlights the importance of economic stability in accessing WASH services. Households with stable employment may have more financial resources to invest in WASH services, which can have positive impacts on their health and wellbeing.

These findings have important implications for policy and practice. They suggest that WASH interventions should consider the socio-economic context of households and target those who are most vulnerable. For example, households with lower levels of education or unemployment may require additional support to access WASH services. Additionally, policymakers should explore ways to make WASH services more affordable and accessible to all households, regardless of their socio-economic status. These also highlight the importance of considering intersectional vulnerabilities when designing WASH interventions. Households with multiple disadvantages, such as low education and unemployment, may face compounded challenges in accessing WASH services.

Our analysis of equality revealed that expenditures on the water and sanitation components were slightly more concentrated among the poorer population, while expenditures on the hygiene component were slightly more concentrated among the wealthier population. One possible explanation is that poorer households may prioritise spending on basic WASH services such as water and sanitation. In comparison, wealthier households may have more disposable income to spend on hygiene services and materials such as soap, toothpaste, and other personal hygiene products (World Bank, 2020). Our findings also suggest that poorer households are disproportionately burdened with expenditure on water and sanitation services. This is consistent with previous studies showing that poorer households often pay more for water and sanitation services due to poor access to affordable and reliable services (WHO and UNICEF, 2019; Hutton, 2012; Andres et al., 2020). Secondly, wealthier households often prioritise hygiene practices due to greater awareness and knowledge of the importance of hygiene for health (Acheampong et al., 2024) and the associated costs.

Despite these variations, the overall distribution of expenditure on WASH services is relatively equitable, suggesting that households across different income levels are spending similar proportions of their income on WASH services. Our finding is consistent with studies that reported that WASH expenditure was not disproportionately concentrated among wealthy or poor households (RMH, 2015; GON, 2019). Nevertheless, a study reported less equitable distributions of WASH expenditure, with the wealthiest households spending more than twice as much on WASH services as the poorest households (UNICEF, 2021). However, the equal distribution of WASH expenditure could imply vertical inequity in access to WASH services among households. This is because households with lower SES are disproportionately disadvantaged in terms of their WASH expenditure and needs. Hence, future research could build upon this analysis by examining the equity implications of WASH expenditure, going beyond equality measures to assess fairness and justice in the distribution of WASH services. This will inform policymakers and practitioners to consider the implications of WASH expenditure patterns while designing more targeted and effective interventions to improve access to WASH services.

The findings of this study highlight the need for further research on the economics of WASH services in Nigerian urban slums. While the study provides valuable insights into the expenditure patterns of households on WASH services, further research is needed to understand the drivers of expenditure and the impact of improved WASH services on household health and wellbeing. In addition, future studies should investigate the value for money, reliability, and quality of WASH services to provide a more comprehensive understanding of these services in urban slums. This would enable policymakers to make informed decisions and improve the effectiveness of WASH interventions.

It is crucial to highlight that availability of water plays a vital role in maintaining proper sanitation and hygiene. Without reliable water supply, achieving and sustaining proper hygiene and sanitation practices becomes significantly challenging, impacting overall health and wellbeing. Hence, availability of water is tied to expenditure on water infrastructure and services. Inadequate water supply system can limit access to hygiene and sanitation. Studies has shown that availability of safe drinking water improves health outcomes, reducing diarrheal diseases and improving maternal and child health (Okesanya et al., 2024; Okesanya et al., 2024; Osisiogu et al., 2024). Water availability has been reported to have to positive impacts on health, hygiene, time-saving, productivity, food supply and nutrition, school performance and reduced stress on people especially women (Abnyie2023 et al., 2021).

This study has some strengths. First, the study focused on vulnerable urban slums, usually neglected or underrepresented in national surveys and statistics. The study’s focus on household expenditure on WASH services provides valuable insights into the economic burden of accessing these services. In addition, using a structured, interviewer-administered questionnaire allowed for the collection of quantitative data, which can be easily analysed and compared. Last, the selection of two urban slums from a larger pool of six slums allows for some generalisability of the findings to other urban slum settings. Finally, the study is part of CHORUS, a large consortium focusing on urban health, which allowed for interdisciplinary support for the study design and implementation.

We noted some limitations of the study. As the study relied on self-reported cost data, recall bias could be a concern, especially for a long-term time horizon such as one year. Respondents may have difficulty accurately recalling their expenditures on WASH services, particularly if they do not keep track of their expenses. However, it is worth noting that recall bias can be difficult to eliminate. To mitigate this, the researchers attempted to minimise the bias by asking respondents to report their expenditures over a shorter period of a month, rather than a longer one. In addition, the study only collected quantitative data, which may not provide a complete understanding of the drivers and complexities surrounding household expenditure on WASH services. The high percentage of female respondents may limit the generalizability of our findings to male heads of households. However, this skewness in representation is largely since females were more available and likely to recall household expenditures accurately, given their role in managing household finances. While this approach ensured the collection of reliable data, future research should aim to capture a more balanced representation of male and female household heads to provide a more nuanced understanding of WASH expenditure patterns in households. Finally, the study only focused on household expenditure on WASH services and did not consider other important factors, such as the quality of WASH services or the impact of WASH services on health outcomes.

Policy implications and recommendations

Policymakers should prioritise the development of affordable and sustainable WASH services for the urban slums in Nigeria. This can be achieved by developing targeted subsidies or other forms of support to help households with larger sizes access WASH services. In addition, the development of affordable and sustainable WASH services that cater to the needs of households in urban slums, regardless of demographic and socio-economic groups, should be implemented to address disparities in access to WASH in Nigeria. This can help improve access to these essential services, promoting health, wellbeing, and economic development.

Conclusion

This study has provided valuable insights into the household’s expenditure patterns and inequality in access to WASH services in urban slums in Nigeria. Our findings reveal a significant economic burden associated with WASH access. Also, while expenditure on water and sanitation is pro-poor, and hygiene services are skewed toward wealthier households, the overall distribution of WASH expenditure remains relatively equitable across income groups. This study revealed vertical inequities in access to WASH services, with poorer households facing a disproportionate burden. To address these issues, decision-makers should consider chronic barriers to improve WASH access in urban slums. Targeted subsidies for water and sanitation services, promoting hygiene awareness among low-income households, and investments in WASH infrastructure in urban slum settlements should be prioritised. These efforts are crucial for improving access to affordable and equitable WASH services for vulnerable populations in urban slums.

References

• 1

  Abdulhadi R. Bailey A. Van Noorloos F. (2024). Access inequalities to WASH and housing in slums in low- and middle-income countries (LMICs): a scoping review. Glob. Public Health19:69099. doi: 10.1080/17441692.2024.2369099,

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 2

  Acheampong A. O. Opoku E. E. O. Tetteh G. K. (2024). Unveiling the effect of income inequality on safe drinking water, sanitation, and hygiene (WASH): does financial inclusion matter?World Dev.178:106573. doi: 10.1016/j.worlddev.2024.106573

  • CrossRef
  • Google Scholar

• 3

  Anambra State Ministry of Public Utilities (2019). Anambra state water and sanitation sector policy. Awka, Anambra State, Nigeria: Anambra State Ministry of Public Utilities.

  • Google Scholar

• 4

  Andres L. Brocklehurst C. Grabinsky J. Joseph G. Thibert M. (2020). Measuring the affordability of water supply, sanitation, and hygiene services: a new approac. Water Economics and Policy6:2050002.

  • Google Scholar

• 5

  Azeez O. Henderson-Mitchell R. J. LaFevor M. C. Gregg A. (2023). Socioeconomic predictors of access to improved water sources, sanitation facilities, and household water treatment in Nigeria. J. Water Sanit. Hyg. Dev.13, 875–884. doi: 10.2166/washdev.2023.169

  • CrossRef
  • Google Scholar

• 6

  Bedoya G. Bittarello L. Davis J. Mittag N. (2017). Distributional Impact Analysis (DIA) framework: Toolkit and Illustrations of Impacts Beyond the Average Treatment Effect. World Bank Policy Research Working Paper No. 8139.

  • Google Scholar

• 7

  Federal Ministry of Water Resources (2021). National Water and sanitation policy. Abuja, Nigeria: Federal Ministry of Water Resources.

  • Google Scholar

• 8

  FMWR, NBS, and UNICEF (2021). Water, sanitation and hygiene: National Outcome Routine Mapping (WASHNORM) 2021: A report of findings. Nigeria: FCT Abuja.

  • Google Scholar

• 9

  Gaffan N. Kpozèhouen A. Dégbey C. Glèlè Ahanhanzo Y. Glèlè Kakaï R. Salamon R. (2022). Household access to basic drinking water, sanitation, and hygiene facilities: secondary analysis of data from the demographic and health survey V, 2017–2018. BMC Public Health22:1345. doi: 10.1186/s12889-022-13665-0,

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 10

  GON (2019). Nepal water, sanitation, and hygiene (WASH) sector review. Kathmandu, Nepal: Government of Nepal, Ministry of Foreign Affairs.

  • Google Scholar

• 11

  Hutton G. (2012). Monitoring “Affordability” of water and sanitation services after 2015: Review of global indicator options. A paper submitted to the UN Office of the High Commissioner for Human Rights, 20.

  • Google Scholar

• 12

  India National Sample Survey Office (2019). India household consumption expenditure survey report. New Delhi, India: National Sample Survey Office, Ministry of Statistics and Programme Implementation, Government of India.

  • Google Scholar

• 13

  National Bureau of Statistics (2021). Nigerian Living Standards Survey

  • Google Scholar

• 14

  National Population Commission (2016). 2016 population and housing census. Abuja, Nigeria: National Population Commission.

  • Google Scholar

• 15

  O'Donnell O. van Doorslaer E. Wagstaff A. Lindelow M. (2008). Analyzing health equity using household survey data: A guide to techniques and their implementation. London: World Bank.

  • Google Scholar

• 16

  Okesanya O. J. Eshun G. Ukoaka B. M. Manirambona E. Olabode O. N. Adesola R. O. et al . (2024). Water, sanitation, and hygiene (WASH) practices in Africa: exploring the effects on public health and sustainable development plans. Tropical Med Health52:68. doi: 10.1186/s41182-024-00614-3,

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 17

  Osisiogu E. U. Akinrotoye K. P. Banini A. E. Amemo R. E. (2024). A systematic scoping review of access to safe drinking water in sub-Saharan Africa: mapping literature on determinants, interventions, and policy implications over the past decade and the path forward. Ethiop. J. Health Sci.34, 413–420. doi: 10.4314/ejhs.v34i5.10,

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 18

  RMH (2015). Rwanda water, sanitation, and hygiene (WASH) sector review. Kigali, Rwanda: Rwandan Ministry of Health.

  • Google Scholar

• 19

  Sarkar A. (2020). Informal water vendors and the urban poor: evidence from a Nairobi slum. Water Int.45, 443–457. doi: 10.1080/02508060.2020.1768022

  • CrossRef
  • Google Scholar

• 20

  Tanzania National Bureau of Statistics (2019). Tanzania household budget survey report. Dar es Salaam, Tanzania: Tanzania National Bureau of Statistics.

  • Google Scholar

• 21

  UNESCO (2019). The United Nations world water development report 2019: Leaving no one behind. Paris: UNESCO Publishing.

  • Google Scholar

• 22

  UN-Habitat . (2016). Urbanization and development: Emerging futures. Nairobi, Kenya: UN-Habitat.

  • Google Scholar

• 23

  UNICEF (2018). Available online at: https://www.unicef.org/nigeria/water-sanitation-and-hygiene

  • Google Scholar

• 24

  UNICEF (2019). Water, sanitation and hygiene (WASH) in Nigeria: Situation analysis and recommendations. Paris: UNICEF.

  • Google Scholar

• 25

  UNICEF (2021). WHO. Assessing the Affordability of Water, Sanitation, and Hygiene: Ghana Country Case Study. Available online at: https://www.efaidnbmnnnibpcajpcglclefindmkaj/https://www.unicef.org/media/97476/file/WASH%20affordability%20case%20study-Ghana.pdf (Accessed November 2025).

  • Google Scholar

• 26

  Wagstaff A. Paci P. van Doorslaer E. (1991). On the measurement of inequalities in health. Soc. Sci. Med.33, 545–557. doi: 10.1016/0277-9536(91)90212-U,

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 27

  Whittington D. Davis J. Kunreuther H. Comfort L. Bermúdez M. D. Hughes J. et al . (2012). How best to invest in developing countries’ water sector? BMJ,344:e835. doi: 10.1136/bmj.e835

  • CrossRef
  • Google Scholar

• 28

  WHO (2018). Water, sanitation, and hygiene. Geneva: WHO.

  • Google Scholar

• 29

  WHO and UNICEF (2019). Progress on household drinking water, sanitation, and hygiene 2000–2017. Special focus on inequalities. Joint monitoring program report. Geneva: United Nations Children’s Fund (UNICEF) and World Health Organization.

  • Google Scholar

• 30

  World Bank (2020). Nigeria: Water, sanitation, and hygiene (WASH) sector review. London: World Bank.

  • Google Scholar