ABSTRACT
This study aimed to assess the trends in water, sanitation, and hygiene (WASH) services over time and analyze associated factors influencing these services through a cross-sectional approach. The authors used a structured questionnaire to evaluate WASH indicators. They applied descriptive statistics for trend analysis and multivariate logistic regression analysis to identify associated factors. The findings revealed that basic drinking water services coverage in Arm 1 (WASH intervention area) increased by 238% or three times (from 8% in 2021 to 27% in 2023), while Arm 2 (WASH nonintervention) showed a 109% increase (from 11 to 23%) over the same period. Improved sanitation services were accessible to 8.6% of Arm 1 households (HHs) and 8.5% of Arm 2 HHs in 2023. Furthermore, awareness creation sessions on WASH practices conducted in the past 12 months were significantly correlated with WASH service improvements. The study indicated a slight improvement in basic drinking water service coverage; however, many HHs still lack adequate sanitation and hygiene facilities. Immediate action is necessary to achieve Sustainable Development Goal 6 regarding clean water and sanitation. Effective interventions should consider sociodemographic factors. Collaboration among government, NGOs, and communities is essential for sustainable WASH development in Ethiopia's Wolayita Zone and similar regions.
HIGHLIGHTS
In 2023, 27 and 82% of households (HHs) had access to basic and improved water services, respectively.
Around 2.3 and 7.1% of HHs in 2021 and 2023, respectively, utilized safely managed sanitation services.
The majority of HHs had no adequate safe water, sanitation, and hygiene services.
Awareness creation sessions on WASH practices conducted in the past 12 months were significantly correlated with WASH services.
INTRODUCTION
Access to clean water, improved sanitation facilities, and proper hygiene practices are essential to human health, economic development, and overall quality of life for developing countries. They help prevent waterborne disease, reduce health costs, and support societal well-being (UN 2015; Prüss-Üstün et al. 2016; Hope & Ballon 2019; Dorea et al. 2020; WHO 2020; Girmay et al. 2020b, 2021, 2022). Despite their importance, the world is not on track to achieve SDG targets 6.1 and 6.2 (WHO & UNICEF 2023). The Sustainable Development Goal 6 (SDG 6) of the United Nations specifically intends to provide everyone with access to safe water and sanitation by the year 2030 (WHO & UNICEF 2021). For the health and well-being of individuals as well as communities, access to basic sanitary facilities is essential (Akpakli et al. 2018). The Joint Monitoring Program (JMP), an initiative of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF), provides a framework for monitoring and reporting on water, sanitation, and hygiene (WASH) services globally, making it easier to monitor progress toward achieving SDG 6 (WHO 2019).
Water scarcity and pollution are persistent issues in arid regions, affecting growth and prosperity. Throughout the 21st century, infrastructure like dams and reservoirs has helped meet the increasing water demands (Eslamian 2016). A significant public health issue has been epidemics associated with insufficient and poor use of sanitary and water supply systems (Bbaale 2011; Hutton & Chase 2017; Wolf et al. 2023), as well as extreme water-related weather events (Cann et al. 2013). Disease is a global problem that is mostly attributed to the availability of clean water, proper sanitation, and adequate hygiene (Ekong 2015). The most common reason for death related to WASH is diarrhea. Worldwide, diarrhea is responsible for 4% of all diseases and 5% of health losses to disability (Girmay et al. 2020a). In sub-Saharan Africa, 7% of people used surface water in 2020, which is a significant source of waterborne diseases (WHO & UNICEF 2021). Diarrheal diseases are the main cause of death in children, killing close to 1.37 million children (0–14 years) annually (Pruss-Ustun & World Health Organization 2008). These illnesses are brought on by polluted water and poor sanitation.
The provision of WASH services is essential for preserving human health and promoting a country's rapid development (WHO/UNICEF 2014; UNICEF 2016; Belay & Andualem 2022). Despite Ethiopia's improvement, approximately 40% of the population lacks access to an improved water source (Beyene et al. 2015), and 17% still defecate in the open (WHO & UNICEF 2021). A major health concern in many nations is the increase in the practice of open defecation, which has been linked to many significant health effects (Brown et al. 2013; Schmidlin et al. 2013; Spears et al. 2013; Adesogan 2018). Likewise, many people have suffered from water and sanitation-related health problems. Clean water and sanitation-related health issues have been explored in reputable scientific literature, with a focus on the relevance and significance of WASH assessment (Biplob et al. 2011; Hulland et al. 2013; Johnson et al. 2015; Orimoloye et al. 2015; Girsha et al. 2016; Dearden et al. 2017; Ohwo & Agusomu 2018; Mushota et al. 2021; Gaffan et al. 2022; Satriani et al. 2022; Alemu et al. 2023). More than 88% of diarrhea-associated deaths in underdeveloped nations, including Ethiopia, are caused by inadequate access to improved water and sanitation (WHO 2009; Merid et al. 2023). Over the past decade, Ethiopia, one of the most populated countries in Africa, has significantly improved WASH services (Terry 2023). However, many people still face difficulties in obtaining safe drinking water, proper sanitation, and appropriate hygiene practices, especially in rural and marginalized communities. Hence, there is a high-estimated disease burden associated with inadequate WASH (Kwami et al. 2019; Abebe & Tucho 2021; Girma et al. 2021; WHO 2023). The Wolayita Zone, which is located in the Southern Nations, Nationalities, and Peoples' Region (SNNPR) of Ethiopia, is no exception to these challenges.
The Geshiyaro project is an impactful initiative aimed to address the prevalence of schistosome and soil-transmitted helminth infections in the Wolayita Zone. It focuses on implementing high-coverage community-wide mass drug administration (MDA) in combination with improved WASH services, as well as behavior change communication (BCC) (Phillips et al. 2023). This approach recognizes that poor sanitation coverage contributes to the high burden of disease in the area and aims to reduce environmental exposure and the transmission of these parasitic infections through WASH-based interventions (Campbell et al. 2018). Overall, the Geshiyaro project aims to support global efforts to control and eliminate neglected tropical diseases while improving access to clean water and sanitation. It seeks to provide a holistic and sustainable solution for improving community health and well-being in the Wolayita Zone. Understanding trends and factors affecting the JMP service ladders for WASH in this region is essential for developing targeted interventions and policies to accelerate progress toward universal access to safe and sustainable WASH services. Region-specific studies are needed to identify challenges and opportunities influencing households' (HHs) access to WASH services. Therefore, this study focuses on exploring these trends and factors impacting the JMP service ladders for WASH services.
MATERIALS AND METHODS
Study design and setting
A cross-sectional survey was used to examine key HH WASH indicators in the Wolayita Zone, focusing on sites of the Geshiyaro project. A standardized questionnaire aligned with WHO/UNICEF JMP definitions (JMP 2018) was used to evaluate these indicators. The study, conducted in 2021, 2022, and 2023, took place in the Wolayita Zone, which is located 330 km from Addis Ababa, Ethiopia. The administration units in the Wolayita Zone consist of woredas and kebeles. The zone is administratively divided into 17 rural districts and three municipal administrations (Alemayehu et al. 2023).
HH sampling size estimation
Thus, adding a 10% non-response rate, the estimated total sample size for this study was 6,675.
Arm classification
According to the Children's Investment Fund Foundation (CIFF) categorization, Arm 1 includes WASH intervention woredas, while Arm 2 consists of nonintervention woredas. Arm 1 comprises five woredas: Boloso Sore, Boloso Bombe, Damot Sore, Damot Gale, and Damot Pulasa. In these areas, water utilities have been established, sanitation facilities provided, and regular educational BCC conducted to promote hygiene and sanitation practices. World Vision Ethiopia took the lead and conducted the intervention works. Conversely, Arm 2 includes seven woredas: Duguna Fango, Abala Abaya, Damot Weyde, Humbo, Kindo Didaye, Ofa, and Sodo Zuria, which were not part of the WASH intervention for this study. However, the types of water systems commonly used in Wolayita include hand pumps, boreholes, shallow wells, piped water systems, rainwater harvesting, protected springs, and water kiosks.
Operational definition of key terms
Enumeration areas (EAs) are specific geographic areas designed to speed up the collection of data in surveys and censuses. As they are smaller units within larger regions, they make population surveys more effective by targeting specific HHs, thereby simplifying the processes of data collection and analysis.
Woreda is an administrative division in Ethiopia responsible for local governance and the delivery of services, comparable to a district or county.
Kebele is the smallest administrative unit within a woreda, similar to a village or neighborhood.
Definition of SDG/JMP ladders for WASH services in HHs: The WASH indicator definition is sourced from the WHO/UNICEF JMP for SDG ladders for WASH services (WHO/UNICEF 2018) as indicated in Table 1.
Definition of the SDG/JMP ladders for assessing WASH services in household
Service level . | Definition . |
---|---|
Drinking-water service ladders | |
Safely managed | Obtaining drinking water from an improved source that is available when needed, accessible on-premises, and free from fecal and priority chemical contamination |
Basic | Drinking water from an improved source requires a round-trip collection time of 30 min or less, including queuing |
Limited | Drinking water from an improved source requires a collection time omore than 30 min for a round trip, including queuing |
Unimproved | Drinking water from an unprotected spring or unprotected dug well |
Surface water | Drinking water is directly obtained from a river, lake, pond, dam, stream, or irrigation canal |
Sanitation service ladders | |
Safely managed | Use improved sanitation facilities that are not shared with other HHs, where excreta is safely disposed of in situ or removed and treated offsite |
Basic | Use of improved sanitation facilities that are not shared with other HHs |
Limited | Use of improved sanitation facilities that are shared with other HHs |
Unimproved | Use of pit latrines without a slab or platform, bucket latrines, or hanging toilets |
Open defecation | Disposal of human feces in fields, forests, bushes, open bodies of water, beaches, or other available places, as well as solid wastes |
Hygiene service ladders | |
Basic | Presence of a hand-washing facility with soap and water at home |
Limited | Presence of a hand-washing facility lacking soap and/or water at home |
No services | There is no hand-washing facility at home |
Note: Improved water sources (basic + limited) include piped water, boreholes or tube wells, protected dug wells, protected springs, rainwater, and packaged or delivered water | |
Unimproved sources of drinking water | |
Unprotected well | It is a dug well that lacks any of the following: a lining or casing raised above ground level to form a headwall; an apron to divert spilled water away from the well; a cover to prevent contaminated materials (including bird droppings and small animals) from entering the well; or a pump or manual lifting device |
Unprotected spring | It is a natural spring that lacks a ‘spring box’ to protect against runoffs and other sources of contamination (including bird droppings and animals) |
Surface water | It refers to open water sources located above the ground including rivers, reservoirs, lakes, ponds, streams, canals, and irrigation channels |
Note. Unimproved drinking water sources are those that, due to their design and construction, are unlikely to deliver safe water |
Service level . | Definition . |
---|---|
Drinking-water service ladders | |
Safely managed | Obtaining drinking water from an improved source that is available when needed, accessible on-premises, and free from fecal and priority chemical contamination |
Basic | Drinking water from an improved source requires a round-trip collection time of 30 min or less, including queuing |
Limited | Drinking water from an improved source requires a collection time omore than 30 min for a round trip, including queuing |
Unimproved | Drinking water from an unprotected spring or unprotected dug well |
Surface water | Drinking water is directly obtained from a river, lake, pond, dam, stream, or irrigation canal |
Sanitation service ladders | |
Safely managed | Use improved sanitation facilities that are not shared with other HHs, where excreta is safely disposed of in situ or removed and treated offsite |
Basic | Use of improved sanitation facilities that are not shared with other HHs |
Limited | Use of improved sanitation facilities that are shared with other HHs |
Unimproved | Use of pit latrines without a slab or platform, bucket latrines, or hanging toilets |
Open defecation | Disposal of human feces in fields, forests, bushes, open bodies of water, beaches, or other available places, as well as solid wastes |
Hygiene service ladders | |
Basic | Presence of a hand-washing facility with soap and water at home |
Limited | Presence of a hand-washing facility lacking soap and/or water at home |
No services | There is no hand-washing facility at home |
Note: Improved water sources (basic + limited) include piped water, boreholes or tube wells, protected dug wells, protected springs, rainwater, and packaged or delivered water | |
Unimproved sources of drinking water | |
Unprotected well | It is a dug well that lacks any of the following: a lining or casing raised above ground level to form a headwall; an apron to divert spilled water away from the well; a cover to prevent contaminated materials (including bird droppings and small animals) from entering the well; or a pump or manual lifting device |
Unprotected spring | It is a natural spring that lacks a ‘spring box’ to protect against runoffs and other sources of contamination (including bird droppings and animals) |
Surface water | It refers to open water sources located above the ground including rivers, reservoirs, lakes, ponds, streams, canals, and irrigation channels |
Note. Unimproved drinking water sources are those that, due to their design and construction, are unlikely to deliver safe water |
Data quality control, data collection, and analysis
Both statistical and visual techniques were used to evaluate data quality. Visual inspection was used to identify errors in data entry and compilation, while goodness-of-fit tests assessed the statistical appropriateness of the model. Additionally, the respondent selection criteria specified that HHs must include respondents aged 18 and above, excluding those with mental disorders and those who had lived in the HHs for less than six months.
Forty-five data collectors and 15 supervisors were recruited based on their educational background and technical experience related to data collection using the Open Data kit. Five days of training were given, followed by a pilot. Actual data were then collected immediately after the pilot test using a structured questionnaire in face-to-face interviews with the heads of the HHs. Socio-demographic indicators related to safe water storage and handling at the HH level, the prevalence of environmental health-related diseases, exposure to sanitation, and environmental health information, along with the core questions on WASH, were incorporated into the questionnaire.
The socio-demographic details of the HHs in the research population were ascertained by the application of descriptive statistics. To find the parameters related to basic drinking WASH while accounting for potential confounders, we employed binary and multivariate logistic regression analyses were used. A p-value of 0.05 or less was deemed statistically significant in the multivariate logistic regression analysis. The Origin 2022 software was used to create graphs, while STATA Version 16 was used for data analysis.

Likewise, the author tested four assumptions for the logistic regression analysis: a suitable sample size, no extremely significant outliers, no multicollinearity, and independent observations (Ambrosius 2007; Stoltzfus 2011; Hosmer et al. 2013). They examined and confirmed the adequacy of the model using the Pearson goodness-of-fit test (Pearson 1900). The authors found the drinking WASH ladder models suitable for the data and validated their use.
Ethical considerations
The study received ethical approval from the Scientific and Ethical Review Board of the Ethiopian Public Health Institute (reference number: EPHI-IRB-321-2020). The research adhered to the 1964 Helsinki Declaration, its subsequent revisions, and other relevant ethical standards. Informed consent was obtained in writing from all participants. Data collection tools (ODK) were password-protected to ensure respondent privacy and confidentiality throughout the investigation.
RESULTS AND DISCUSSION
The study was carried out for three years. The study included sample size and response rate, which is a total of 6,543 HHs with a 98.0% response rate in 2021, 6,567 HHs with a 98.4% response rate in 2022, and 6,574 HHs with a 98.5% response rate in 2023. Data on drinking WASH service ladders were analyzed using a time-trend analysis, incorporating information from Arm 1 (WASH intervention area) and Arm 2 (non-WASH intervention area). To identify associated factors, multivariate logistic regression analysis was employed (Tables 3–5).
Socio-demographic characteristics of HHs, 2023 (n = 6,574)
Characteristics . | Frequency . | Percentage . |
---|---|---|
Sex | ||
Male-headed | 4,843 | 73.7 |
Female-headed | 1,731 | 26.3 |
Residence | ||
Rural | 5,850 | 89 |
Urban | 724 | 11 |
Annual income | ||
< 18,000 (median) | 3,217 | 48.9 |
≥ 18,000 (median) | 3,357 | 51.1 |
Family size | ||
< 5 (median) | 2,716 | 41.3 |
≥ 5 (median) | 3,858 | 58.7 |
HH head education | ||
No education | 4,757 | 72.4 |
Primary | 460 | 7 |
Secondary and above | 1,357 | 20.6 |
Occupation | ||
Farmer | 5,392 | 82 |
Merchant | 374 | 5.7 |
Government worker | 374 | 5.7 |
No occupation | 416 | 6.3 |
Age-headed | ||
18–28 | 246 | 3.7 |
29–39 | 1,606 | 24.4 |
40–50 | 3,030 | 46.1 |
51–61 | 977 | 14.9 |
62–72 | 474 | 7.2 |
≥ 73 | 241 | 3.7 |
Marital status | ||
Married | 5,450 | 82.9 |
Single | 1,124 | 17.1 |
Arm classification | ||
Intervention woreda (Arm 1) | 2,840 | 43.2 |
Nonintervention woreda (Arm 2) | 3,734 | 56.8 |
Characteristics . | Frequency . | Percentage . |
---|---|---|
Sex | ||
Male-headed | 4,843 | 73.7 |
Female-headed | 1,731 | 26.3 |
Residence | ||
Rural | 5,850 | 89 |
Urban | 724 | 11 |
Annual income | ||
< 18,000 (median) | 3,217 | 48.9 |
≥ 18,000 (median) | 3,357 | 51.1 |
Family size | ||
< 5 (median) | 2,716 | 41.3 |
≥ 5 (median) | 3,858 | 58.7 |
HH head education | ||
No education | 4,757 | 72.4 |
Primary | 460 | 7 |
Secondary and above | 1,357 | 20.6 |
Occupation | ||
Farmer | 5,392 | 82 |
Merchant | 374 | 5.7 |
Government worker | 374 | 5.7 |
No occupation | 416 | 6.3 |
Age-headed | ||
18–28 | 246 | 3.7 |
29–39 | 1,606 | 24.4 |
40–50 | 3,030 | 46.1 |
51–61 | 977 | 14.9 |
62–72 | 474 | 7.2 |
≥ 73 | 241 | 3.7 |
Marital status | ||
Married | 5,450 | 82.9 |
Single | 1,124 | 17.1 |
Arm classification | ||
Intervention woreda (Arm 1) | 2,840 | 43.2 |
Nonintervention woreda (Arm 2) | 3,734 | 56.8 |
Multivariate logistic regression analysis of respondents' basic drinking water service ladders, 2023 (n = 6,574)
Description . | Basic drinking water service . | P-value . | AOR with 95% CI . | |
---|---|---|---|---|
Yes (%) . | No (%) . | |||
Residence | ||||
Urban | 42.7 | 57.3 | Reference | |
Rural | 22.6 | 77.4 | 0.00*** | 0.47 [0.39, 0.56] |
Education of HH head | ||||
No education | 24.2 | 75.8 | Reference | |
Primary | 23.5 | 76.5 | 0.53 | 0.93 [0.74, 1.17] |
Secondary and above | 27.3 | 72.7 | 0.25 | 0.91 [0.78, 1.07] |
Occupation of HH head | ||||
Government | 37.2 | 62.8 | Reference | |
Farmer | 22.8 | 77.2 | 0.00*** | 0.66 [0.51, 0.85] |
Merchant | 37.2 | 62.8 | 0.78 | 0.96 [0.70, 1.31] |
Not working | 28.1 | 71.9 | 0.06* | 0.73 [0.53, 1.01] |
Family size | ||||
<5 HH members | 26.0 | 74.0 | Reference | |
≥5 HH members | 24.0 | 76.1 | 0.06* | 0.90 [0.80, 1.01] |
Income of HH head | ||||
≥18,000 | 27.2 | 72.8 | Reference | |
<18,000 | 22.3 | 77.7 | 0.09* | 0.90 [0.80, 1.01] |
HH head attended awareness creation sessions about WASH practices in the past 12 months | ||||
Yes | 28.0 | 72.0 | Reference | |
No | 22.5 | 77.5 | 0.00*** | 0.78 [0.70, 0.88] |
Arm classification | ||||
Intervention woreda (Arm 1) | 27.3 | 72.7 | Reference | |
Nonintervention woreda (Arm 2) | 22.9 | 77.1 | 0.00*** | 0.78 [0.70, 0.88] |
Description . | Basic drinking water service . | P-value . | AOR with 95% CI . | |
---|---|---|---|---|
Yes (%) . | No (%) . | |||
Residence | ||||
Urban | 42.7 | 57.3 | Reference | |
Rural | 22.6 | 77.4 | 0.00*** | 0.47 [0.39, 0.56] |
Education of HH head | ||||
No education | 24.2 | 75.8 | Reference | |
Primary | 23.5 | 76.5 | 0.53 | 0.93 [0.74, 1.17] |
Secondary and above | 27.3 | 72.7 | 0.25 | 0.91 [0.78, 1.07] |
Occupation of HH head | ||||
Government | 37.2 | 62.8 | Reference | |
Farmer | 22.8 | 77.2 | 0.00*** | 0.66 [0.51, 0.85] |
Merchant | 37.2 | 62.8 | 0.78 | 0.96 [0.70, 1.31] |
Not working | 28.1 | 71.9 | 0.06* | 0.73 [0.53, 1.01] |
Family size | ||||
<5 HH members | 26.0 | 74.0 | Reference | |
≥5 HH members | 24.0 | 76.1 | 0.06* | 0.90 [0.80, 1.01] |
Income of HH head | ||||
≥18,000 | 27.2 | 72.8 | Reference | |
<18,000 | 22.3 | 77.7 | 0.09* | 0.90 [0.80, 1.01] |
HH head attended awareness creation sessions about WASH practices in the past 12 months | ||||
Yes | 28.0 | 72.0 | Reference | |
No | 22.5 | 77.5 | 0.00*** | 0.78 [0.70, 0.88] |
Arm classification | ||||
Intervention woreda (Arm 1) | 27.3 | 72.7 | Reference | |
Nonintervention woreda (Arm 2) | 22.9 | 77.1 | 0.00*** | 0.78 [0.70, 0.88] |
***p < 0.01, **p < 0.05, *p < 0.1.
Multivariate logistic regression analysis of respondents' basic sanitation service ladders, 2023 (n = 6,574)
Description . | At least a basic sanitation service . | P-value . | AOR with 95% CI . | |
---|---|---|---|---|
Yes (%) . | No (%) . | |||
Residence | ||||
Urban | 20.0 | 80.0 | Reference | |
Rural | 4.7 | 95.3 | 0.00*** | 0.33 [0.25, 0.42] |
Education of HH head | ||||
No education | 4.9 | 95.1 | Reference | |
Primary | 6.7 | 93.3 | 0.25 | 1.26 [0.85, 1.88] |
Secondary and above | 11.6 | 88.4 | 0.00*** | 1.52 [1.18, 1.95] |
Occupation of HH head | ||||
Government | 18.5 | 81.5 | Reference | |
Farmer | 4.6 | 95.4 | 0.00*** | 0.51 [0.35, 0.73] |
Merchant | 16.8 | 83.2 | 0.67 | 1.09 [0.73, 1.64] |
Not working | 9.1 | 90.9 | 0.18 | 0.73 [0.46, 1.15] |
Income of HH head | ||||
≥ 18,000 | 4.4 | 95.6 | Reference | |
< 18,000 | 8.4 | 91.6 | 0.03** | 0.77 [0.62, 0.97] |
HH head attended awareness creation sessions about WASH practices in the past 12 months | ||||
Yes | 8.5 | 91.5 | Reference | |
No | 4.9 | 95.1 | 0.00*** | 0.61 [0.49, 0.74] |
Arm classification | ||||
Intervention woreda (Arm 1) | 7.1 | 92.9 | Reference | |
Nonintervention woreda (Arm 2) | 5.9 | 94.1 | 0.01*** | 0.76 [0.62, 0.94] |
Description . | At least a basic sanitation service . | P-value . | AOR with 95% CI . | |
---|---|---|---|---|
Yes (%) . | No (%) . | |||
Residence | ||||
Urban | 20.0 | 80.0 | Reference | |
Rural | 4.7 | 95.3 | 0.00*** | 0.33 [0.25, 0.42] |
Education of HH head | ||||
No education | 4.9 | 95.1 | Reference | |
Primary | 6.7 | 93.3 | 0.25 | 1.26 [0.85, 1.88] |
Secondary and above | 11.6 | 88.4 | 0.00*** | 1.52 [1.18, 1.95] |
Occupation of HH head | ||||
Government | 18.5 | 81.5 | Reference | |
Farmer | 4.6 | 95.4 | 0.00*** | 0.51 [0.35, 0.73] |
Merchant | 16.8 | 83.2 | 0.67 | 1.09 [0.73, 1.64] |
Not working | 9.1 | 90.9 | 0.18 | 0.73 [0.46, 1.15] |
Income of HH head | ||||
≥ 18,000 | 4.4 | 95.6 | Reference | |
< 18,000 | 8.4 | 91.6 | 0.03** | 0.77 [0.62, 0.97] |
HH head attended awareness creation sessions about WASH practices in the past 12 months | ||||
Yes | 8.5 | 91.5 | Reference | |
No | 4.9 | 95.1 | 0.00*** | 0.61 [0.49, 0.74] |
Arm classification | ||||
Intervention woreda (Arm 1) | 7.1 | 92.9 | Reference | |
Nonintervention woreda (Arm 2) | 5.9 | 94.1 | 0.01*** | 0.76 [0.62, 0.94] |
***p < 0.01, **p < 0.05, *p < 0.1.
Multivariate logistic regression analysis of respondents' basic hygiene service ladders, 2023 (n = 6,574)
Description . | Basic hygiene service . | P-value . | AOR with 95% CI . | |
---|---|---|---|---|
Yes (%) . | No (%) . | |||
Residence | ||||
Urban | 7.2 | 92.8 | Reference | |
Rural | 3.4 | 96.6 | 0.10* | 0.74 [0.52, 1.06] |
Education of HH head | ||||
No education | 3.3 | 96.7 | Reference | |
Primary | 2.4 | 97.6 | 0.20 | 0.67 [0.36, 1.24] |
Secondary and above | 6.1 | 93.9 | 0.12 | 1.29 [0.94, 1.78] |
Occupation of HH head | ||||
Government | 9.1 | 90.9 | Reference | |
Farmer | 3.2 | 96.8 | 0.05* | 0.63 [0.39, 1.01] |
Merchant | 6.9 | 93.1 | 0.93 | 0.98 [0.56, 1.70] |
Not working | 4.3 | 95.7 | 0.31* | 0.73 [0.39, 1.35] |
Income of HH head | ||||
≥ 18,000 | 2.1 | 97.8 | Reference | |
< 18,000 | 5.5 | 94.5 | 0.00*** | 0.47 [0.35, 0.63] |
HH head attended awareness creation sessions about WASH practices in the past 12 months | ||||
Yes | 5.3 | 94.7 | Reference | |
No | 2.8 | 97.2 | 0.00*** | 0.57 [0.44, 0.74] |
Description . | Basic hygiene service . | P-value . | AOR with 95% CI . | |
---|---|---|---|---|
Yes (%) . | No (%) . | |||
Residence | ||||
Urban | 7.2 | 92.8 | Reference | |
Rural | 3.4 | 96.6 | 0.10* | 0.74 [0.52, 1.06] |
Education of HH head | ||||
No education | 3.3 | 96.7 | Reference | |
Primary | 2.4 | 97.6 | 0.20 | 0.67 [0.36, 1.24] |
Secondary and above | 6.1 | 93.9 | 0.12 | 1.29 [0.94, 1.78] |
Occupation of HH head | ||||
Government | 9.1 | 90.9 | Reference | |
Farmer | 3.2 | 96.8 | 0.05* | 0.63 [0.39, 1.01] |
Merchant | 6.9 | 93.1 | 0.93 | 0.98 [0.56, 1.70] |
Not working | 4.3 | 95.7 | 0.31* | 0.73 [0.39, 1.35] |
Income of HH head | ||||
≥ 18,000 | 2.1 | 97.8 | Reference | |
< 18,000 | 5.5 | 94.5 | 0.00*** | 0.47 [0.35, 0.63] |
HH head attended awareness creation sessions about WASH practices in the past 12 months | ||||
Yes | 5.3 | 94.7 | Reference | |
No | 2.8 | 97.2 | 0.00*** | 0.57 [0.44, 0.74] |
***p < 0.01, **p < 0.05, *p < 0.1.
Socio-demographic characteristics of HHs
The majority (89%) of study participants live in rural areas, 73.7% of HH heads were males, and 82.9% of participants were married. Nearly half (48.9%) of the participants had less than 18,000 birr annual income. Table 2 also includes information on HH head education, family size, and other factors.
Trends of WASH services based on JMP ladders in three different survey years
In this study, improved drinking water service is defined as the sum of basic and limited improved water sources. In 2023, access to improved drinking water was 82% for Arm 1 woredas and 76% for Arm 2 woredas, both of which are lower than the 88% access reported in a study from Ghana (Agbadi et al. 2019) and higher than the 68.7% reported in the EDHS (Desye et al. 2023). The proportion of unimproved drinking water services in Arm 2 increased by 50%, rising from 10% in 2021 to 15% in 2023. In contrast, Arm 1 showed a decrease in unimproved drinking water services, dropping from 17% in 2021 to 15% in 2023, which reflects a decrease of 12%. Similarly, in 2023, Arm 1 reported a surface water usage of 3%, while Arm 2 used 9%. Notably, the surface water usage in Arm 1's research areas was below the WHO's national estimate of 5% in 2020, whereas Arm 2's usage exceeded this estimate (WHO & UNICEF 2021). This decline in unimproved drinking water services and surface water consumption in Arm 1 may be attributed to the ongoing interventions of the Geshiyaro WASH project. Likewise, the 2023 Arm 1 survey data showed that 27 and 55% of the HHs used basic and limited drinking water services, respectively (Figure 1).
Trends in HH-headed WASH services and health information exposure, 2021 (n = 6,543), 2022 (n = 6,567), and 2023 (n = 6,574).
Trends in HH-headed WASH services and health information exposure, 2021 (n = 6,543), 2022 (n = 6,567), and 2023 (n = 6,574).
Demographic factors associated with WASH services in 2023
The study aimed to identify the demographic factors influencing drinking WASH indicators, which are important for evaluating and tracking global progress toward achieving universal access to safe and sustainable WASH services. Evaluating water supply, sanitation, and hygiene services, as well as related demographic aspects, is crucial to improving public health concerns. The impact of demographic factors on the provision of basic drinking WASH services was studied (Tables 3–5).
As shown in Table 3, HHs with rural residents were 0.47 times less likely to use basic drinking water services than HHs with an urban population (adjusted odds ratio (AOR) = 0.47 with 95% CI [0.39–0.56]). This result aligns with that of Alemu et al. (2023), who found that HHs in rural areas were 0.64 times less likely to use basic drinking-water services than those in urban areas (AOR = 0.64 with 95% CI [0.22–1.89]) (Alemu et al. 2023). Moreover, the likelihood that HHs headed by a farmer would use basic drinking water services was 0.66 times lower than that of HHs headed by a government worker (AOR = 0.66 with 95% CI [0.51–0.85]). According to the current study, the majority of HH heads were farmers from rural areas (Table 2). These farmers may not have access to higher education, and as a result, there may be a knowledge gap regarding the use of drinking water services.
HH heads with annual incomes less than 18,000 birr were 0.90 times less likely to use basic drinking water services (AOR = 0.90 with 95% CI [0.80–1.01]) than those with annual incomes more than 18,000 birr. The computed p-value (0.09) is greater than the significant level (α = 0.05); hence, the change is insignificant at the 5% significance level. The result may be due to economic differences to influence the basic drinking water services.
Furthermore, HHs in the nonintervention areas (Arm 2) were 0.78 times less likely to use basic drinking-water services (AOR = 0.78 with 95% CI [0.70–0.88]) than those in the intervention areas (Arm 1) than those in the intervention areas (Arm 1). This may be due to better drinking water coverage for HH heads in Arm 1 compared to those in Arm 2. HH respondents with a family size of more than five members were 0.90 times less likely to use basic drinking water services (AOR = 0.90 with 95% CI [0.80–1.01]) than those HH respondents with less than five members. The computed p-value (0.09) is greater than the significant level (α = 0.05); hence, the change is insignificant at the 5% significance level. This result showed that access to basic drinking water services could also be dependent on family size (Table 3).
The study defines at least basic sanitation services as the sum of safely managed sanitation service ladders and basic sanitation services. Accordingly, the findings showed that HHs in rural areas were 0.33 times less likely to use basic sanitation services (AOR = 0.33 with 95% CI [0.25–0.42]) than those in urban areas. This result also aligned with the findings of the WHO report, which showed that a greater proportion of rural HHs lacked access to basic sanitation than urban residents (WHO 2014). Also, HH heads who completed secondary school or higher were 1.52 times more likely to use basic sanitation services than those with no education (AOR = 1.52 with 95% CI [1.18–1.95]). HH heads who had an annual income less than 18,000 birr used basic sanitation services 0.77 times less frequently (AOR = 0.77 with 95% CI [0.62–0.97) than those who had an annual income greater than 18,000 birr. Other research (Donacho et al. 2022; Girmay et al. 2022) also supports the findings of this investigation.
Furthermore, HH heads who attended awareness creation sessions about WASH practices in the past 12 months were strongly correlated with access to basic sanitation facilities. HH heads who did not attend awareness creation sessions about WASH practices in the past 12 months were 0.61 times less likely to use basic sanitation services than HH heads who attended awareness creation sessions about WASH practices (AOR = 0.61 with 95% CI [0.49–0.74]). This suggests that attending these sessions likely increased HHs' willingness to construct or invest in their sanitation infrastructure. Similarly, HH heads in the nonintervention areas (Arm 2) were 0.76 times less likely to use basic sanitation services (AOR = 0.76 with 95% CI [0.62–0.94]) than those in the intervention areas (Arm 1) (Table 4). Very certainly, this positive outcome has to be expected, as the Geshiyaro project is very much involved in awareness creation regarding sanitation service practices of HHs in the intervention areas (Arm 1) compared to Arm 2 HHs (nonintervention); beyond awareness creation, the community (Arm 1) has also been provided with sanitary services.
In this study, basic hygiene service is defined as having a handwashing facility with soap and water at home. The binary logistic regression analysis revealed that five predictor variables, such as residence type, education, occupation, income, and attendance at awareness sessions about WASH practices in the past 12 months, were significantly associated (p-value <0.05) with access to basic hygiene service. However, only two explanatory variables including income and awareness creation sessions about WASH practices in the past 12 months were significantly associated in the multivariable logistic regression model with a p-value <0.05 (Table 4). Hence, HH heads with an annual income of less than 18,000 birr were 0.47 times less likely to use basic drinking water services (AOR = 0.47 with 95% CI [0.35–0.63]) than HH heads with an annual income of more than 18,000 birr. Therefore, it can be concluded that access to basic hygiene services is impacted by economic inequality, and HH heads with better annual incomes may probably construct hygiene facilities to positively impact the services. The findings of this work concur with those of Gaffan et al. (2022), who found that wealthier HHs had a higher likelihood of having basic handwashing facilities than the poorest HHs (Gaffan et al. 2022).
Likewise, HH heads who attended awareness creation sessions about WASH practices in the past year strongly correlated with access to basic hygiene facilities in the current study. Heads who did not attend awareness creation sessions about WASH practices in the past year were 0.57 times less likely to use basic hygiene services than those who attended awareness creation (AOR = 0.57 with 95% CI [0.44–0.74]) (Table 5). In a different study by Girmay et al. (2023b), children whose mothers did not engage in community and school WASH discussions were 2.39 times more likely (AOR = 2.39; 95% CI 1.10 to 5.23) to develop diarrheal disease than those whose mothers did participate (Girmay et al. 2023b). The current study highlights the need to promote behavioral change through mass media and community engagement to encourage the utilization of sanitation facilities and proper hygiene practices. The study's strengths include the use of a representative sample and international assessment tool from the JMP core questions (WHO/UNICEF 2018) to track WASH services and enable cross-national comparisons. However, its focus on specific sites of Ethiopia's Geshiyaro project may limit the generalizability of its findings to other regions. Furthermore, although cross-sectional surveys provide valuable insights, they are limited in their ability to establish cause-and-effect relationships between WASH conditions and health outcomes.
CONCLUSIONS
The study revealed a slight increase in basic drinking water service coverage; however, many HHs still lack improved sanitation and hygiene facilities. A concerning decline in WASH education attendance and an increase in open defecation were noted, even as reliance on surface and unimproved water sources decreased. Intervention areas (Arm 1) demonstrated better WASH coverage compared to nonintervention areas (Arm 2), underscoring the importance of targeted efforts. To address these challenges, the authors recommended prioritizing underserved rural and semi-urban areas by investing in localized water infrastructure projects, such as boreholes, rainwater harvesting, and community water kiosks. The study advocates for a multi-faceted approach to enhance WASH services, emphasizing community-led sanitation, behavior change, and targeted hygiene promotion efforts.
In planning these interventions, socio-demographic factors should be considered to ensure effectiveness and equity. These factors include income levels, gender roles, education, cultural practices, and population density, all of which play a critical role in shaping the success of WASH initiatives. Collaborative efforts among governments, NGOs, and local communities should focus on capacity building, with particular attention to establish sustainable maintenance management systems. These actions are vital for sustainable WASH services within the Wolayita Zone and across Ethiopia, aligning with the country's SDGs for health and sanitation improvements. Furthermore, expanding access to safe drinking water and enhancing sanitation and hygiene facilities are essential for sustainable development and public health advancement.
ACKNOWLEDGEMENTS
The authors express their gratitude to the funder, project teams, and the financial and logistics sections of the Ethiopian Public Health Institute.
FUNDING
This study was funded by the CIFF with grant number R-1805-02741. The opinions stated here are those of the authors and do not necessarily represent the views of the CIFF and the CIFF's staff.
AUTHORS’ CONTRIBUTIONS
Z.A.A. managed the project, conceptualized the paper, interpreted the data, and wrote it. A.M.G., B.C., A.W.K., M.G.W., and K.F. wrote and edited a review. E.A.A. performed data quality control and statistical analysis. All authors have made critical revisions and made a major contribution to writing the manuscript. All authors read and approved of the final manuscript.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
The study proposal was approved by the Ethiopian Public Health Institute (EPHI) scientific and ethical review board, with reference number EPHI-IRB-321-2020. Written consent was obtained from the participants. Those who did not want to be a part of the study were not compelled to do so. The participants' confidentiality and privacy were ensured through the investigation.
DATA AVAILABILITY STATEMENT
Data cannot be made publicly available; readers should contact the corresponding author for details.
CONFLICT OF INTEREST
The authors declare there is no conflict.