Spatial distribution and determinants of improved shared sanitation facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health Survey

Baye Tsegaye Amlak; Daniel Gashaneh Belay

doi:10.1371/journal.pone.0315860

. 2025 Jan 13;20(1):e0315860. doi: 10.1371/journal.pone.0315860

Spatial distribution and determinants of improved shared sanitation facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health Survey

Baye Tsegaye Amlak ^1,^*, Daniel Gashaneh Belay ^2,³

Editor: Alison Parker⁴

PMCID: PMC11730421 PMID: 39804838

Abstract

Introduction

Limited or shared sanitation services are considered improved sanitation facilities, but they are shared between two or more households. Globally, 600 million people use shared toilet facilities. Although shared facilities are not classified as improved sanitation due to potential infection risks, inaccessibility, and safety concerns, this is a significant issue in developing countries like Ethiopia. Evidence on the distribution of shared sanitation services and their determinants in Ethiopia is limited. Therefore, this study aimed to assess the extent of shared toilet facilities and their determinants among households in Ethiopia.

Methods

The 2019 Ethiopian Demographic and Health Survey (EDHS) served as the basis for the cross-sectional secondary data analysis. The analysis included a total of 7,770 households from the weighted sample. STATA 14 software was used to clean, weigh, and analyze the data. To explore the distribution and determine the factors associated with shared toilet facilities in Ethiopia, both spatial and mixed-effect analyses were utilized. A p-value of less than 0.05 was used to display the relationships between the dependent and independent variables, employing adjusted odds ratios and 95% confidence intervals.

Results

The magnitude of improved shared sanitation facilities among households in Ethiopia, according to the EDHS 2019, was 10.5% (95% CI: 9.88, 11.24). The prevalence was highest in Addis Ababa at 70.2% and lowest in the Southern Nations, Nationalities, and Peoples’ Region at 2.4%. Individual-level variables significantly associated with the use of improved shared toilet facilities included being a household head aged 55 years or older [AOR = 0.48; 95% CI: 0.33, 0.71], having secondary education or higher [AOR = 2.43; 95% CI: 1.80, 3.28], and belonging to middle or rich wealth status [middle: AOR = 2.32; 95% CI: 1.35, 3.96; rich: AOR = 6.23; 95% CI: 3.84, 10.11]. Community-level characteristics such as residing in urban areas [AOR = 7.60; 95% CI: 3.47, 16.67], the metropolitan region [AOR = 25.83; 95% CI: 10.1, 66.3], and periphery regions [AOR = 5.01; 95% CI: 2.40, 10.48] were also associated with the use of shared toilet facilities.

Conclusion

The usage of improved shared toilet facilities among households in Ethiopia is relatively low. Significant factors related to the use of shared toilet facilities were being 55 years of age or older, possessing secondary or higher education, having a middle or rich wealth status, living in urban areas, and residing in metropolitan or peripheral regions. To improve access to and utilization of shared sanitation facilities, Ethiopian policy should emphasize user education and awareness.

Introduction

The World Health Organization (WHO) and the United Nations Joint Monitoring Programme (JMP) define limited sanitation services as improved sanitation facilities that are shared between two or more households [1, 2]. Globally, 2.3 billion people lack access to improved sanitation facilities [2]. From these, 600 million people use shared toilet facilities [2].

Safely managed sanitation is the only option available to millions of people living in densely packed urban areas, especially in informal settlements. This is preferable to open defecation, which has far more severe negative impacts on health, safety, and dignity [1]. However, while shared toilets are designed to be an improved type of sanitation facility, they are considered unimproved because they are shared among multiple users [3].

A meta-analysis of global studies on shared sanitation in informal settlements estimated that the overall prevalence of shared sanitation was 67%. Users’ preferences for using shared facilities were influenced by factors such as cleanliness, affordability, safety, privacy, structural quality, and accessibility [4]. However, informal settlements are widespread and often characterized by substandard housing, poverty, and a lack of basic sanitation facilities. This is especially true in developing nations like Ethiopia, where conflict and internal displacement are prevalent [5]. Therefore, sharing toilets provides residents who lack private toilets in their homes with access to sanitation facilities [5].

In Sub-Saharan African countries, the number of households using shared toilet facilities increased from 0.64 million to 0.96 million, representing 0.08% of all households [2, 6]. Similarly, in Ethiopia, the use of shared toilet facilities rose from 4% to 7% between 2000 and 2015 [7]. Shared facilities are not regarded as an improvement in sanitation because they frequently encounter maintenance issues. Furthermore, their accessibility can lead to the spread of infections due to poor hygiene, limited accessibility, and unsafe conditions [8]. These are frequently not well kept, creating unclean conditions that discourage frequent use [1]. Global research has shown a connection between the use of shared toilets and adverse health outcomes such as helminth infections, diarrhea, enteric fevers, and fecal-oral diseases [9]. It aids the transmission of microorganisms that cause diarrheal diseases [10], with children being the most vulnerable [11]. Diarrheal disease is the second leading cause of death for children under five worldwide, accounting for 760,000 deaths and 1.7 million morbidities annually [12]. In Africa, diarrhea is one of the main causes of death in under-five children [13], It causes the deaths of half a million children under the age of five annually in Ethiopia alone [14]. Moreover, using shared toilets puts hundreds of millions of women and children at greater risk of sexual exploitation and a lack of privacy during their menstrual cycles [5, 15]. Poor sanitation is also associated with infections and eye diseases, such as trachoma [5].

Sustainable Development Goal (SDG) target 6.2 aims to ensure that by 2030, all children will have access to universal sanitation facilities [8] and that no child should suffer from disease or die due to contaminated water or contact with human waste [16]. Therefore, providing shared sanitation services could be a crucial initial step toward achieving the universal sanitation coverage goal set out in the Sustainable Development Goals [8]. Since 1995, Ethiopia has prioritized its sanitation program, following the inclusion of public health in the country’s National Constitution. Subsequently, in 2005 and 2006, the Ministry of Health developed the National Hygiene and Sanitation Strategy and the National Hygiene and On-Site Sanitation Protocol, respectively [17, 18]. However, the magnitude and contributing factors to using shared toilet facilities in Ethiopia are little known [19]. Therefore, this study aims to address the following research questions: What is the magnitude and spatial distribution of improved shared sanitation facilities in Ethiopia? What factors are associated with improved shared sanitation facilities? Answering these questions will provide valuable insights for policymakers and program planners, helping them allocate resources more effectively, design targeted interventions, and develop relevant policies.

Methodology

Study design, setting, and data source

This study utilized data from the recent Ethiopian Demographic and Health Survey (EDHS 2019), which was collected using a community-based cross-sectional study design. Since 1984, the DHS has gathered a broad range of objective and self-reported data across more than 99 countries. Key advantages of the DHS include high response rates, national coverage, rigorous interviewer training, standardized data collection procedures across countries, and consistent content over time [20].

With 1.1 million square kilometers under its belt and an expected 132,059,767 inhabitants in 2024, Ethiopia is the second most populated country in Africa next to Nigeria [21]. Ethiopia has two city administrations (Addis Ababa and Dire Dawa) and nine regions (Tigray, Afar, Amhara, Oromia, Benishangul Gumuz, Somalia, South Nation Nationalities and Peoples of Ethiopia (SNNP), Gambelia, and Harari) with a federal decentralized administrative structure. To ensure survey precision was comparable across regions, the sample allocation was carried out through equal distribution, with 35 enumeration areas (EAs) selected from each of the three larger regions: Amhara, Oromia, and the Southern Nations, Nationalities, and Peoples’ Region (SNNPR). Additionally, 25 EAs were selected from each of eight other regions. In the first stage, a total of 305 EAs (93 in urban areas and 212 in rural areas) were chosen with probability proportional to EA size. In the second stage, an average of 25–30 households were carefully selected from each EA based on the 2019 Ethiopian Population and Housing Census (EPHC) frame [22].

Study population

The study population consisted of all houses that had unimproved sanitation services evaluated during the 2019 mini EDHS survey (7,561). This includes, shared improved sanitation services (1,276), unimproved sanitation facilities (3,442), and open defecation (OD) (2,843).

Out of the 8,663 households included in the 2019 mini EDHS survey, 1,102 households had improved but not shared sanitation facilities and were excluded from the analysis. Ultimately, a sample of 7,561 households (weighted to 7,770) was included in the analysis.

Study variables

The outcome variable of the study was shared/ limited sanitation service which means households with either one type of improved sanitation facility but shared with other households [23] (Table 1).

Table 1. Questions to measure improved but shared/ limited sanitation service.

Outcome variable (Shared/ limited sanitation service)	Control group/comparators
Did the toilet have flush/pour flush to the piped sewer system?	✓ Unimproved sanitation services such as ⚬ Pit latrine without slab/open pit ⚬ Bucket toilet ⚬ Hanging toilet/latrine ⚬ Other ✓ Open defecation: no facility/bush/field
Did the toilet have flush/pour flush to the septic tank?
Did the toilet have a flush to somewhere else?
Did the toilet have flush/pour flush to the pit latrine?
Did the toilet have a flush, don’t know where.
Was the toilet Ventilated Improved Pit (VIP) latrine?
Was the toilet pit latrine with a slab?
Was the toilet composting toilet?
If a household uses any of the listed above-improved sanitation facilities but shares them with other households.

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The study’s predictor variables were categorized into individual-level variables, which included the age, sex, and educational attainment of household heads, as well as factors such as the household wealth index, family size, and household size. Additionally, community-level characteristics such as residence location, region, and community poverty were examined. After assessing the normal distribution of the aggregated community components using a histogram and the Shapiro-Wilk test, the data were recorded using the appropriate measures of central tendency (Table 2).

Table 2. A list of the study’s variables along with an explanation of each measurement.

Level	Variables	Measurements
Individual level variables	Age	The age of the participants was categorized as 15–24, 25–40, 41–54, >55
	Sex	Sex of the household head as male and female
	Education level	Educational attainment is categorized as uneducated, primary, secondary, and above
	Family size	Categorized as 1–3, 4–6, and 7 and above.
	Wealth index	A wealth index categorized as poorest, intermediate, richest, and wealthiest in the DHS data collection was developed using principal components analysis and included in the datasets. We classified it into three categories for this study: middle class, rich (including wealthier), and poor (including poorer and poorest).
Community level variables	Residency	Urban or rural based on where the household lives in the dataset was used without change.
	Region	Ethiopia’s eleven regions are divided into three groups according to their level of development and need for government assistance: the "three metropolises" (Addis Ababa, Harari, and Diredewa); the "large central" (Tigray, Amhara, Oromia, SNNPR); and the "small peripherals" (Afar, Benshangul-Gumuz, Gambelia, and Somali) [24].
	Community level poverty	The percentage of households in the lowest and poorest quintiles found in the wealth index data was used to calculate the community’s level of poverty. classified as high if the percentage of households falling into the poor categories exceeded 50% and as low if the percentage was less than 50%.

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Data management and analysis

This study utilized data from the EDHS 2019 provided by the DHS program. The results and independent variables were extracted using the household data (HR) set, and STATA version 14 was employed for recording, extracting, and analyzing the data. To ensure the representativeness of the survey and obtain reliable estimates and standard errors, the data were weighted for sampling probabilities using the weighting factor before performing any statistical analysis.

Multilevel analysis was used to account for both individual and community levels due to the hierarchical structure of the EDHS data, where households are nested within enumeration areas (EAs). This approach addresses the violation of the assumption of independence of observations and equal variance across clusters. The Interclass Correlation Coefficient (ICC), Median Odds Ratio (MOR), and Proportional Change in Variance (PCV) were utilized to measure variance through random effects.

The ICC reveals the variation of shared toilet facilities usage between clusters is calculated as; $I C C = \frac{V C}{V C + 3.29} * 100 %$ , where; VC = cluster level variance.

The MOR is defined as the median value of the odds ratio between the area at the lowest risk and the highest risk of shared toilet facilities usage when randomly picking out two clusters.

$MOR = e^{{0.95}^{\sqrt{V C}}}$ Where; VC is the cluster-level variance.

The PCV shows the variation in shared toilet facilities usage among households explained by both individual and community level factors. $P C V = \frac{V n u l l - V C}{V n u l l} * 100 %$ Where; Vnull = variance of the initial model, and VC = cluster level variance of the next model [25–27].

Generally, four models were fitted in multi-level analysis. The first model was the null model, which simply included the outcome variable and was meant to examine the cluster’s variability in shared toilet facility utilization. Household and community-level factors are included in the second and third multilevel models, respectively, while shared toilet facility usage was simultaneously fitted to both household and community-level variables in the fourth model. The deviation test was used to compare the models, and the model that suited the data the best was the one with the lowest deviance [25–27]. In the multivariable analysis, the associations between dependent and independent variables were presented using adjusted odds ratios and 95% confidence intervals with a p-value of <0.05.

Spatial analysis

The Global Moran’s I statistic was used to assess spatial autocorrelation [28]. The Global Moran’s I value ranges from −1 to +1, where a value below 0 indicates negative spatial autocorrelation, and values above 0 indicate positive spatial autocorrelation [28, 29]. Based on sampled clusters, we employed a spherical semivariogram ordinary Kriging-type spatial interpolation technique to forecast the extent of shared toilet facilities in Ethiopia for unsampled areas. The input for spatial prediction was the percentage of shared restrooms in each cluster. To determine the locations of shared restroom clusters, Bernoulli-based model spatial scan statistics were applied [30]. To suit the Bernoulli model, the houses without shared toilets were taken as controls, and the scanning window that moves over the research region with shared toilet facilities was taken as a case.

Ethical approval statement

The study doesn’t involve the collection of information from subjects, secondary data analysis was done. Ethical approval and consent to participate are not applicable. Since the study is a secondary data analysis based on DHS data.

Results

Sociodemographic characteristics of the study participants

This study included a total of 7,770 households. Among them, males constituted more than three-fourths (6,046 or 77.81%) of the household heads. The majority of participants (72.19%) lived in rural areas, and nearly half (3,785 or 48.71%) of the household heads had no formal education.

As the age of household heads increased from 13–30 years to above 57 years, the use of shared toilet facilities decreased from 20.35% to 6.9%, respectively. More than two-thirds (69.09%) of households in metropolitan regions and about one-fourth (28.95%) of household heads in urban residences used shared toilet facilities [Table 3].

Table 3. Socio-demographic characteristics and improved shared toilet usage in Ethiopia, mini 2019 EDHS.

Variables	Categories	Shared toilet facilities		Total weighted frequency (%)
		Yes (%)	No (%)
		n = 819 (10.5)	n = 6,951 (89.5)
Age of household head (years)	15–24	184 (20.35)	722 (79.65)	906 (11.66)
	25–40	370 (11.40)	2875 (88.60	3245 (41.75)
	41–54	136 (7.74)	1616 (92.26)	1751 (22.53)
	>55	129 (6.92)	1739 (93.08)	1868 (24.05)
Sex of household head	Male	501 (8.28)	5545 (91.72)	6,046 (77.81)
Sex of household head	Female	318 (18.470	1406 (81.53)	1,724 (22.19)
Educational attainment of household head	No education	228 (6.01)	3,556 (93.99)	3,785 (48.71)
	Primary education	244(8.79)	2,530 (92.21)	2,775(35.71)
	Secondary & above	348 (28.71)	863 (71.29)	1,211 (15.58)
Household family size	1–3	49 8 (17.96)	2141 (82.04)	2,610 (33.59)
	4–6	249 (7.35)	3140 (92.65)	3,889 (43.61)
	7 & above	101 (5.72)	1670 (94.28)	1,771 (22.80)
Wealth index	Poor	60 (2.01)	2,929 (97.99)	2,989 (38.47)
	Middle	36 (2.35)	1,516 (97.65)	1,553 (19.98)
	Rich	723 (22.39)	2,506 (77.61)	3,229 (41.55)
Community level variables
Residence	Urban	625 (28.95)	1,535 (71.05)	2,161 (27.81)
Residence	Rural	193 (3.45)	5,415 (96.55)	5,609 (72.19)
Region	Metropolis	173 (69.09)	77 (30.91)	250 (3.22)
	Large centrals	530 (7.68)	6,373 (92.32)	6,904 (88.85)
	Small periphery	116 (18.82)	500 (81.18)	615 (7.93)
Community poverty level	Low	711 (15.43)	3,898 (84.57)	4,610 (59.33)
Community poverty level	High	108 (3.41)	3,052 (96.59)	3,160 (40.67)

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The magnitude of shared sanitation facilities in Ethiopia

In the EDHS 2019, the magnitude of improved shared sanitation facilities among households in Ethiopia was 10.5% (95% CI: 9.88, 11.24). Of these, more than two-thirds (69.5%) used shared pit latrines with slabs, while only 0.6% used shared sanitation facilities connected to a flush-piped sewer system. The highest prevalence of shared toilet facilities was observed in Addis Ababa (70.2%), whereas the lowest was in the Southern Nations, Nationalities, and Peoples’ Region (2.4%) (Fig 1).

Factors associated with shared or limited access to improved sanitation service in Ethiopia

Since the models were nested, log-likelihood and deviance tests were performed for model comparison. The III-level binary logistic regression model was chosen because it had the largest LR (-1438) and the smallest deviance test result (2,876). The random effects of ICC, PCV, and MOR were evaluated.

The difference at the cluster level was responsible for almost 79% of the variability in improved shared sanitation facilities among sample families, according to the ICC in the null model. According to the MOR value in the null model (28.75), a household from a high-risk cluster had 28.75 times higher odds of having shared toilet facilities compared to a household from a low-risk cluster. Additionally, the PCV value in the final model demonstrated that characteristics at both the individual and community levels simultaneously explained nearly 76% of the variation in improved shared toilet facilities among study families [Table 4].

Table 4. Multilevel analysis of factors associated with improved shared toilet facilities usage among households in Ethiopia.

Variables	Categories	Null model	Model I	Model II	Model III
Variables	Categories	Null model	AOR [95% CI]	AOR [95% CI]	AOR [95% CI]
Age of household head (years)	15–24		1.00	‐‐‐‐‐‐‐‐‐‐‐‐	1.00
	25–40		0.67 [0.50, 0.91]^*	‐‐‐‐‐‐‐‐‐‐‐‐	0.66 [0.50, 0.89]^*
	41–54		0.56 [0.38, 0.81]^**	‐‐‐‐‐‐‐‐‐‐‐‐	0.54 [0.37, 0.79]^*
	>55		0.49 [0.34, 0.72]^***	‐‐‐‐‐‐‐‐‐‐‐‐	0.48 [0.33, 0.71]^***
Sex of household head	Male		1.00	‐‐‐‐‐‐‐‐‐‐‐‐	1.00
Sex of household head	Female		1.17 [0.86, 1.37]	‐‐‐‐‐‐‐‐‐‐‐‐	1.23 [0.92, 1.47]
Educational attainment of household head	No education		1.00	‐‐‐‐‐‐‐‐‐‐‐‐	1.00
	Primary education		1.36 [0.99,1.78]	‐‐‐‐‐‐‐‐‐‐‐‐	1.31 [0.98, 1.73]
	Secondary& above		2.54 [1.88, 3.44]^**	‐‐‐‐‐‐‐‐‐‐‐‐	2.43 [1.80, 3.28]^*
Household family size	1–3		1.00	‐‐‐‐‐‐‐‐‐‐‐‐	1.00
	4–6		0.75 [0.61, 1.03]	‐‐‐‐‐‐‐‐‐‐‐‐	0.76 [0.60, 1.01]
	7 & above		0.88 [0.62, 1.26]	‐‐‐‐‐‐‐‐‐‐‐‐	0.97 [68, 1.38]
Wealth index	Poor		1.00	‐‐‐‐‐‐‐‐‐‐‐‐	1.00
	Middle		2.66 [1.55, 4.56]^**	‐‐‐‐‐‐‐‐‐‐‐‐	2.32 [1.35, 3.96]^*
	Rich		10. 25 [6.39, 16.41]^**	‐‐‐‐‐‐‐‐‐‐‐‐	6.23 [3.84, 10.11]^***
Community level variables
Residence	Urban		‐‐‐‐‐‐‐‐‐‐‐‐	14.6 [6.61, 32.21] ^***	7.60 [3.47, 16.67]^***
Residence	Rural		‐‐‐‐‐‐‐‐‐‐‐‐	1.00	1.00
Region	Metropolis		‐‐‐‐‐‐‐‐‐‐‐‐	28.97 [11.21, 74.87]^***	25.83 [10.1, 66.3] ^***
	Small periphery		‐‐‐‐‐‐‐‐‐‐‐‐	4.51 [2.14, 9.49]^***	5.01 [2.40, 10.48] ^***
	Large central		‐‐‐‐‐‐‐‐‐‐‐‐	1.00	1.00
Community poverty usage	Low		‐‐‐‐‐‐‐‐‐‐‐‐	1.00	1.00
Community poverty usage	High		‐‐‐‐‐‐‐‐‐‐‐‐	0.23 [0.11, 0.49]	0.65 [0.29, 1.39]
Random effect
	Variance	12.5 [8.99, 17.46]	6.75 [4.84, 9.41]	3.27 (2.34, 4.55)	3.05 [2.17, 4.29]
	ICC	0.79 [0.73, 0.84]	0.67 [0.59, 0.74]	0.50 [0.42, 0.58]	0.48 [0.40, 0.57]
	MOR	28.75	11.80	5.57	5.25
	PCV	Reff	0.46	0.74	0.76
Model comparison
	Log-likelihood	-1654	-1515	-1544	-1438
	Deviance	3.308	3,030	3,088	2,876
	Mean VIF	‐‐‐	1.59	2.18	1.96

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* = P-value < 0.05

** = Pvalue < 0.01

*** = Pvalue < 0.001

ICC = Inter cluster correlation coefficient, MOR = Median odds ratio, PCV = proportional change in variance. AOR = adjusted odds ratio; CI = confidence intervale, VIF = Variance Inflation Factors

Based on the results from Model III, there was a positive association between improved shared sanitation facilities and several factors such as individuals with higher educational attainment and from greater household wealth, those living in urban areas and metropolitan regions.

As the age of household heads increased to 15–24 years, 25–40 years, and over 55 years, the odds of using improved shared toilet facilities decreased by 33%, 46%, and 52%, respectively [AOR = 0.66; 95% CI: 0.50, 0.89], [AOR = 0.54; 95% CI: 0.37, 0.79], and [AOR = 0.48; 95% CI: 0.33, 0.71]. The odds of using improved shared toilet facilities were doubled among household heads with above-primary education [AOR = 2.43; 95% CI: 1.80, 3.28].

Households with a middle or rich wealth index were 2 and 6 times more likely to use improved shared toilet facilities compared to poor households [AOR = 2.32; 95% CI: 1.35, 3.96] and [AOR = 6.23; 95% CI: 3.84, 10.11], respectively. Individuals living in urban areas were 7.6 times more likely to use improved shared toilet facilities compared to those in rural areas [AOR = 7.60; 95% CI: 3.47, 16.67]. Residents of metropolitan regions were 26 times more likely, and those in small periphery regions were 5 times more likely to use improved shared toilet facilities compared to those in large central regions [AOR = 25.83; 95% CI: 10.1, 66.3] and [AOR = 5.01; 95% CI: 2.40, 10.48], respectively [Table 4].

Spatial analysis of improved shared toilet facilities utilization among households in Ethiopia

Spatial autocorrelation analysis of improved shared toilet facilities

Ethiopia’s improved shared sanitation services spatial autocorrelation data revealed a strong positive spatial autocorrelation throughout the nation’s regions. It was discovered to be grouped with the value of the Global Moran’s Index: 1.78 with (p< 0.001) (Fig 2).

Fig 2 — The base map for the shapefile was sourced from: https://gadm.org/.

Hotspot analysis of improved shared toilet facilities among household in Ethiopia

The Getis-Ord Gi* hotspot analysis showed that improved shared toilet facilities were more practised in Addis Ababa, and Dire Dawa, whereas the SNNPR (South Nations Nationalities and People’s Region), and Beneshangul Gumuz regions were the cold spot areas (Fig 3).

Fig 3 — The base map for the shapefile was sourced from: https://gadm.org/.

Significant windows and SaTscan analysis of improved shared toilet facilities among households in Ethiopia

The SaTScan analysis of improved shared toilet facilities among households in Ethiopia identified 86 primary clusters and 29 secondary clusters. The primary clusters were centered at coordinates 8.771915 N, 40.335915 E, with a radius of 206.97 km, and were located in Addis Ababa, northern parts of Oromia, southern parts of Amhara and Afar, and Dire Dawa. Households within these primary clusters were 5 times more likely to use improved shared toilet facilities compared to those outside these clusters (RR = 5.0, P-value < 0.001) (Table 5 and Fig 4).

Table 5. Significant spatial clusters of improved shared toilet facilities among households in Ethiopia using 2019 mini-EDHS.

Clusters	Enumeration areas (clusters) detected	Coordinate/radius	Population	Cases	RR	LLR	P-value
1^ry (86)	105, 88, 28, 41, 102, 106, 42, 127, 40, 104, 69, 90, 101, 43, 103, 108, 272, 269, 268, 271, 110, 280, 278, 273, 279, 270, 267, 264, 266, 277, 305, 275, 276, 265, 263, 256, 274, 304, 258, 257, 261, 260, 262, 50, 259, 303, 281, 296, 287, 68, 282, 302, 286, 284, 288, 283, 111, 294, 285, 291, 292, 293, 295, 297, 290, 289, 175, 231, 233, 246, 244, 232, 243, 237, 234, 236, 301, 298, 235, 242, 247, 241, 240, 253, 238, 239	8.771915 N, 40.335915 E / 206.97 km	2447	851	5.04	181.4–489.78	<0.001
2^nd (29)	281, 282, 284, 283, 287, 285, 286, 288, 296, 291, 297, 292, 294, 290, 289, 295, 302, 264, 273, 267, 263, 270, 276, 265, 275, 266, 258, 271,	10.589922 N, 34.352539 E / 88.60 km	505	245	2.28	7.0–181.3	<0.001

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Fig 4 — The base map for the shapefile was sourced from: https://gadm.org/.

Kiringing interpolation of improved shared toilet facilities among households in Ethiopia

The Kriging interpolation method for improved shared toilet facilities among households in Ethiopia indicated that high-risk areas, such as Addis Ababa and Dire Dawa, had predicted usage rates ranging from 50% to 61%. Conversely, the lowest predicted usage rates were observed in the SNNPR, Gambela, Beneshangul Gumuz, and Oromia regions, ranging from 0% to 12% (Fig 5).

Fig 5 — The base map for the shapefile was sourced from: https://gadm.org/.

Discussion

This study was conducted to assess the magnitude of improved shared toilet facilities and their determinants among households in Ethiopia. Based on this, the prevalence of improved shared toilet facilities in Ethiopia was 10.5% (95% CI: 9.88, 11.24). This is higher than a study by the WHO and UNICEF Joint Monitoring Program in Ethiopia (7%) [7]. It is also higher than in Yemen (4%) and Eritrea (5%), but lower than the global estimate reported in meta-analyses (67%) [4], in Kenya (21%), Ghana (57%), and Uganda (14%) [7]. This variation may be attributed to the different community initiative programs that employ more effective approaches to reducing unimproved sanitation practices and achieving desired sanitation outcomes [18, 31].

In this study, as the age of household heads increases, the usage of improved shared toilet facilities among households decreases. This is consistent with a study conducted in India, which found that unimproved sanitation practices decrease among older household members [32]. This trend may reflect that as individuals age, they may experience disabilities or incontinence, making it more challenging to use outdoor or shared sanitation facilities [32]. Another factor could be that older individuals, on average, may have reduced mobility and greater difficulty moving freely outside their homes to access sanitation facilities.

In this study, as the educational status of household heads increased, the odds of using shared toilet facilities also increased. This is because one-third (32.23%) of households in Ethiopia use open defecation which is more prevalent in less socioeconomic regions [33]. Individuals with at least a formal education are more likely to use improved shared toilet facilities, which generally have fewer severe consequences for health, safety, and dignity compared to open defecation [1]. Furthermore, educated household heads are more likely to recognize the importance of having sanitation facilities, even if they are limited or shared [34, 35]. According to the World Health Organization report, education can raise the community’s demand for better sanitation facilities [36]. Moreover, a higher level of education enhances awareness and fosters positive attitudes toward choosing relatively more upgraded sanitation facilities [37]. Specifically, educated women are more likely to prefer safe and sanitary facilities that offer privacy and maintain good quality during their menstrual cycle [38]. Moreover, well-educated households with higher incomes had better access to upgraded sanitation facilities [39].

Households that have a rich wealth index are more likely to use the improved shared toilet as compared to poor households. This is in line with Ethiopia [4], Nigeria [40], and Ghana [41]. This might be because the majority of improved shared toilet facilities are found in urban areas with a good income-earning population group as compared to open defecation practices that have been taking place in rural areas of low-income countries [42]. In addition, poor households may not have enough place and capacity to construct private and improved shared toilets and their only option is open defecation. Furthermore, poor households found in developing countries are mainly housed in slums that lack essential infrastructure [38].

The study also found that individuals living in rural households were less likely to use improved shared toilet facilities compared to those in urban areas. This finding is consistent with other research indicating that shared toilet facilities are less common in rural areas, where open defecation remains prevalent, affecting 37% of the rural population in Ethiopia [43]. This may be because many governments do not prioritize rural sanitation in their national agendas, often lacking progressive budgetary support as well as essential legislative and institutional reforms [44]. Besides, the previous study findings suggested that rural households’ willingness to pay for ’improved’ latrines is minimal [45]. Moreover, rural households are uneducated, and they believe that open defecation is a routine sanitation service [35]. On the other side, sanitation is an investment, and peri-urban inhabitants made the effort to get improved toilet facilities because they had relatively consistent income to support their planning.

The other finding showed that households who live in large central regions were less likely to use improved shared toilet facilities as compared to metropolitan cities. The spatial analysis result also showed that improved shared toilet facilities were more commonly practiced in Addis Ababa and Dire Dawa, whereas the SNNPR (South Nations Nationalities and People’s Region) and Beneshangul Gumuz regions were the cold spots. This is in line with a study in Mozambique that shows that shared toilet facilities are increasingly common in low-income countries in rapidly growing urban areas [1]. Moreover, in Ethiopia, as a result of internal conflict and drought, informal settlements and refugee camps that use shared toilet facilities are more common in metropolitan cities. The other possible explanation is that those large Centrals contained rural households that practiced open defecation rather than shared and improved sanitation.

The strengths of this study lie in the use of nationally representative, high-quality standardized data, which allows for generalization at the country level. However, a limitation of the study is that being cross-sectional, it cannot establish cause-and-effect relationships.

Conclusion and recommendation

The prevalence of improved shared sanitation services usage among households in Ethiopia is relatively low. Age, educational attainment of the household head, wealth status, residence, and region were found to be significantly associated factors with improved shared sanitation facilities in Ethiopia. Moreover, there was a non-random spatial distribution of improved shared sanitation services in Ethiopia mainly found in Addis Ababa and Dire Dawa.

Based on the findings presented, it is advisable for Ethiopia to execute focused interventions aimed at rectifying the inequities in access to improved shared sanitation services, with particular emphasis on rural households and among marginalized demographics, including individuals with diminished educational and economic standing. It is essential that particular attention is directed towards regions beyond Addis Ababa and Dire Dawa, where the availability of improved sanitation services is disproportionately higher. Policymakers ought to prioritize the development of infrastructure in inadequately served regions and seamlessly integrate sanitation initiatives with comprehensive socio-economic development programs.

Ethiopia stands to gain from the adoption of analogous strategies, ensuring that interventions are characterized not only by infrastructure development but also by cultural sensitivity and community leadership. Additionally, sustained collaboration among governmental entities, non-governmental organizations, and local authorities will prove indispensable for the amplification of these initiatives. Lastly, the continuous collection of data and spatial analysis should inform decision-making processes, thereby facilitating targeted resource allocation to areas of greatest need. Further qualitative studies are needed to explore the behavioral and socio-cultural factors that may prevent individuals from utilizing improved shared sanitation facilities.

By assimilating these lessons, Ethiopia can enhance access to sanitation and improve health outcomes, drawing on the successes observed in other nations, like Nigeria and Ghana, which have higher sanitation standards.

Abbreviations

AOR: Adjusted Odds Ratio
CI: Confidence Interval
CSA: Central Statistical Agency
EDHS: Ethiopian Demographic and Health Survey
HR: Household Record
MOH: Ministry Of Health
OD: Open Defecation
SDG: Sustainable Development Goal

Data Availability

The data utilized in this study were accessed from the Demographic and Health Surveys (DHS) Program database following a formal registration process. Interested researchers can obtain the data by registering and submitting a request via the DHS Program’s website at https://dhsprogram.com/data/new-user-registration.cfm.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0315860.r001

Decision Letter 0

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6 Aug 2024

PONE-D-24-20290Spatial distribution and determinants of shared toilet facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health SurveyPLOS ONE

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Reviewer #1: NB - on quations 1 and 3 above, I don't know the answer, as I am not a statistician. There is much I cannot comment on in the statistical aspects of this work. I can only comment on the discussion of the data analysis, and whether the arguments make sense.

Thank you for the opportunity of reviewing this paper.

Overall:

1. This paper addresses a critical issue of shared sanitation and its role in reaching the goal of safely managed sanitation by 2030. Understanding the extent of shared sanitation use in Ethiopia may support strategies for realising SDG6 and for understanding what the barriers to achieving this might be.

2. I think that there is a useful paper in here, but there needs to be a bit more clarity

about what is arising from the study, what is new in the study, and what is a confirmation of other studies on the issue of shared sanitation. It also needs to be clearer when the other literature is arising from a case study in a particular country, and so may not be generalisable (will clarify below in the line by line review when this comes up). I think that there are times that other studies are used to illustrate something that does NOT arise out of this study (for example on domestic violence) and this is confusing to the reader.

3. The study could benefit from more clarity on the definitions used, particularly given the move from MDGs to SDGs and the greater focus on whether a service is safely managed rather than on the technologies used.

4. One important clarification would be whether this study assumes that people who are not using SS are practicing OD – is that correct? If so, that needs to be spelled out – that SS is the better option. Because at the moment we just read, those who use SS and those who do not, but without the clarity of what the options are of those who do not use SS. This could be my lack of statistical knowledge, but even so, it would be good to clarify in the text. To the same end, it would be useful to have a graphic of the overall breakdown of sanitation used in Ethiopia – from SMS, to SS, to OD.

5. For the results / discussion / conclusion, you could provide recommendations that arise from this study – what does the data tell you that will help planners etc. to increase access to shared sanitation, or more specifically to move people from OD to shared sanitation?

Abstract

Lns 29 -33 This starts as a good argument for including shared toilets in statistics but lines 33-34 does not clarify how understanding the prevalence of shared sanitation (SS) further supports this argument

Lns 35-50 – I am not a statistician so cannot comment

Lns 51-54 It would be useful to have a few headline results – what age or education means for the prevalence of shared sanitation

Introduction

I recommend that the discussion on the move from MDGs to SDGs happens here, and what that means for the indicators etc., as the data is from the SDG era.

e.g. lines 70-78 – are these MDG definitions, or SDG definitions?

Line 79 – check the numbers, something is not right – an increase of 3-6 million is not worth mentioning if the total using SS is 600 million

Line 80-82 – check the numbers 0.96 is not 18% of the population of SSA.

Line86 – is a word missing after ‘easy’

Lines 103-104 – what is the source of this statement (it is not SDG 6.2 as suggested by the reference)

Line 110 – they may be superior to OD – but what are the criteria?

Lines 115-117 – are you drawing a link between using , or not using SS and child mortality? Are you drawing that from your data?

Lines 118-119 – what is the relevance for planners – so that they can target particular households?

Lines 138-143 – I am confused by these numbers – there are 8663 households across 645 EAs? That doesn’t make 20-30 households per EA – please clarify here

I regret that the rest of the methods section doesn’t mean anything to me!

Results

Line 212 – can you define what a male head of household denotes and what a female head of household denotes? Is a head of household only female if there is no adult male in the house? Or how is it defined?

Line 215 I think here you could summarise up front that an increase in age, and decrease in education, wealth etc. leads to a household being more likely to use SS. Then you can go into the detail

Lines 235 – 239 Where is the risk of DV data coming from? And is SS a DV risk or a GBV risk? What is the correlation?

does this suggest a corellation? A causation? Or just two random connected indicators of increased vulnerability?

Line 244 – 247 – write this as clearly as possible also for a non-statistician audience – as I understand it, this is your main finding.

From line 306 onwards I cannot comment! Sorry!

Discussion

Again – I think it needs to be clarified what the non-SS households are using, to be clear that it is worse than SS.

Line 329 - this is not a strong reference, as it is a webpage without links to the claims it references.

Lines 331-332 Did you get this from the data in the study? Or from somewhere else (if so reference) Also add “Studies in Zambia and Ethiopia show…..” I think that the context is critical.

Line 334 – is this an assumption? |Or does education lead to households using SS (which is what your data says, I think)

Line 341 – the reference you use for the tragedy of the commons is rather old-fashioned, and the tragedy of the commons itself may not be relevant to sanitation usage. More work has been done on this more recently, e.g. by Ostrom, or by McGranahan.

Line 344 – 346 – is this speculation or from the data?

Line 346-348 it would be better to say “a study in Kenya shows….” Because otherwise it can be taken as a general truth and it may not be.

Line 347 – is ‘consistent income’ one of the indicators in the data, it’s the first time I see the qualifier ‘consistent’?

Lines 358 – 361 – this seems to be a circular argument – rewrite for clarity?

Line 361 – does ‘governments’ here refer to local governments in Ethiopia or other national governments?

Line 365 – blanket statement not support by the reference as far as I can see

Conclusion

The conclusion could usefully contain some recommendations arising from the study – how can planners / government used this data analysis to make changes to how they promote SS? What are the lessons that can be acted upon?

What still remains to be researched and analysed. What is new from this study, and what confirms previous studies?

Also – be careful what assumptions are embedded in the analysis – for example if women care so much about sanitation, why do households with a male head of household have increased access to SS?

Another still to be resolved quesiton, critical for acceptance of SS as safely managed sanitaiton is what types of shared toilet facility people are using, and whether they are properly maintained? I believe that the main issue with shared sanitation is that it is difficult to judge if they are indeed improved, or safely managed or barely better than OD.

Reviewer #2: Summary and overall impression.

The paper addresses important issue of shared sanitation facilities and puts it in the individual household and community perspective. As it uses well recognised and reliable EDHS survey data, the analysis should yield dependable results that could support policy decision makers and other stakeholders when developing interventions at local and country level. It should also provide reference points for researchers and sanitation experts alike.

From a reader point of view there is a confusion related to the definition of shared sanitation and improved sanitation. I find it difficult to see how shared sanitation is assessed in the context of the type of primary toilet type available to the household. In terms of proportions, methodology and modelling sections are broad and detailed but the outcome of the analysis that is supposed to address research questions is incomplete. Although the discussion section provides many valid points, the paper in my opinion requires major revisions to communicate its points clearly and develop more substantial recommendations that should be developed in closing (conclusions) section. Grammar, spelling mistakes and clarity of writing style must be addressed as well.

Evidence and examples

Major issues

The introduction that is to include an overview of previous research is narrow and lacks currency. It should have a clearer structure and include more recent research-based evidence. Indeed, the most recent reference cited is from 2022 (only one position). I recommend Shared sanitation in informal settlements: A systematic review and meta-analysis of prevalence, preferences, and quality. https://doi.org/10.1016/j.ijheh.2024.114392. to provide broader perspective for this paper in the context of previously published research.

Definition of shared sanitation is unclear – contradicting statements 78 vs 75.

Research question 2 (118, 119) is unclear – contributing factors (contributing to what?).

Results section needs to be re-written to address gaps (e.g. explanation of how cluster with high risk of domestic violence was identified/taken from original data set?) and improve readability by providing more detailed interpretations (see e.g. 257, 258).

Minor issues

More recent population figures are available for Ethiopia now; 2023 as opposed to cited value for 2021 (131).

Table 1 (149) does not present the logic of questions well.

Miscellaneous comments

Formatting of references requires attention – there are issues with numbers and completeness of the records.

**********

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Reviewer #2: No

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PLoS One. 2025 Jan 13;20(1):e0315860. doi: 10.1371/journal.pone.0315860.r002

Author response to Decision Letter 0

9 Sep 2024

Date: September 1, 2024

Alison Parker

Academic Editor of Plos One Journal

Re: Spatial distribution and determinants of improved shared toilet facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health Survey (Submission ID: PONE-D-24-20290)

Dear Editor,

We are grateful for the opportunity to revise our manuscript for further consideration for publication in Plos One Journal.

We have addressed the reviewer's comments and suggestions. Our point-by-point response describes all changes in the manuscript text. We have indicated the changes in track changes in the revised manuscript. We hope that you will find the revised manuscript acceptable for publication.

Yours sincerely,

Baye Tsegaye Amlak

Corresponding Author

A point-by-point response to the reviewer’s comment

We thank the editor and reviewer for their time and effort in reviewing our manuscript and for highlighting its importance. We have addressed the comments provided and revised the manuscript accordingly.

Reviewer 1

Overall: This paper addresses a critical issue of shared sanitation and its role in reaching the goal of safely managed sanitation by 2030. Understanding the extent of shared sanitation use in Ethiopia may support strategies for realising SDG6 and for understanding what the barriers to achieving this might be.

Response: Certainly, Thank you for your critical feedback and for recognizing the importance of this manuscript. We have addressed the comments provided and revised the manuscript accordingly.

Comment #1. I think that there is a useful paper in here, but there needs to be a bit more clarity about what is arising from the study, what is new in the study, and what is a confirmation of other studies on the issue of shared sanitation. It also needs to be clearer when the other literature is arising from a case study in a particular country, and so may not be generalisable (will clarify below in the line by line review when this comes up). I think that there are times that other studies are used to illustrate something that does NOT arise out of this study (for example on domestic violence) and this is confusing to the reader.

Response: Thank you for noting this. This study focused only on improved shared sanitation and its spatial distribution in Ethiopia. Providing shared sanitation services where improved sanitation services are limited could be a crucial first step in achieving the universal sanitation coverage aim outlined in the Sustainable Development Goals. We use only variables which have been associated with the previous studies on sanitation services.

Comment #2. The study could benefit from more clarity on the definitions used, particularly given the move from MDGs to SDGs and the greater focus on whether a service is safely managed rather than on the technologies used.

Response: Thank you for noting this. The definition of the outcome variable is clearly stated in the "Study Variables" section. We have revised it based on the DHS recode manual to read: "If a household uses any of the listed improved sanitation facilities and shares them with other households it is considered as improved shared sanitation services" (see page 7, lines 153-155).

Comment #3. One important clarification would be whether this study assumes that people who are not using SS are practising OD – is that correct? If so, that needs to be spelled out – that SS is the better option. Because at the moment we just read, those who use SS and those who do not, but without the clarity of what the options are of those who do not use SS. This could be my lack of statistical knowledge, but even so, it would be good to clarify in the text. To the same end, it would be useful to have a graphic of the overall breakdown of sanitation used in Ethiopia – from SMS, to SS, to OD.

Response: Thank you for noting this. We have corrected it; accordingly, the following sentences clearly shows the outcome and controls. The outcome of this study is improved shared sanitation facilities whereas the control group are all unimproved sanitation facilities which includes OD, and all unimproved sanitation services such as Pit latrines without slab/open pits, Bucket toilets, hanging toilet/latrines and others. We modified and revised the title and all sections of the manuscript accordingly. “Spatial distribution and determinants of improved shared sanitation facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health Survey”

The study population consisted of all houses that had unimproved sanitation services evaluated during the 2019 mini-EDHS survey (7,561). This includes, shared improved sanitation services (1,276), unimproved sanitation facilities (3,442), and open defecation (OD) (2,843). From the total 8,663, households included in the 2019 mini-EDHS survey, 1,102 households did have improved but not shared sanitation facilities and were excluded from the analysis. Ultimately, a sample of 7,561 (weighted 7,770) households was included in the analysis. (see Page 6 line no 146-151).

Comment #4. For the results/discussion/conclusion, you could provide recommendations that arise from this study – what does the data tell you that will help planners etc. to increase access to shared sanitation, or more specifically to move people from OD to shared sanitation?

Response: Thank you for noting this. We have added a recommendations section and incorporated the issues that need to be addressed by the concerned bodies and stakeholders. Revised according to the following “The government of Ethiopia and other stakeholders should provide economic support to low-income households to construct shared sanitation facilities. Additionally, policy should emphasize user awareness and practices through education to enhance access to and usage of improved shared sanitation facilities, particularly in rural residences and large central regions. Further qualitative studies are needed to explore the behavioural and socio-cultural factors that may prevent individuals from utilizing improved shared sanitation facilities” (see page 20, lines 385-391).

Abstract

Comment #5. Line 29 -33 This starts as a good argument for including shared toilets in statistics but lines 33-34 do not clarify how understanding the prevalence of shared sanitation (SS) further supports this argument.

Response: Thank you for highlighting this important point. We have addressed the identified gap and incorporated it to support the argument. Corrected as follows: “Evidences are limited on the distribution of shared sanitation services and its determinants in Ethiopia. Therefore, this study aimed to assess the magnitude of shared toilet facilities and their determinants among households in Ethiopia.” (see Abstract page 2, lines 30-31 And page 5 line number line number 118-119 in the introduction section).

Comment #6. Lines 35-50 – I am not a statistician so cannot comment

Response: Thank you for your honest feedback, we double-checked it.

Comment #7. Lines 51-54, It would be useful to have a few headline results – what age or education means for the prevalence of shared sanitation

Response: Thank you for your valuable comment. We have corrected it as follows: “Being 55 years or older, having secondary or higher education, having middle or rich wealth status, living in urban areas, and residing in metropolitan or peripheral regions were significantly associated with the usage of shared toilet facilities.” (see page 3, lines 51-53).

Introduction

Comment #8.

I recommend that the discussion on the move from MDGs to SDGs happens here, and what that means for the indicators etc., as the data is from the SDG era.

e.g. lines 70-78 – are these MDG definitions, or SDG definitions

Response: Thank you for your response The SDG definition states that “The Sustainable Development Goals target 6.2 calls for universal access to sanitation by 2030 and no child should die or get sick as a result of drinking contaminated drinking water, and/or being exposed to other people's excreta”

Comment #9. Line 79 – check the numbers, something is not right – an increase of 3-6 million is not worth mentioning if the total using SS is 600 million. Line 80-82 – check the numbers 0.96 is not 18% of the population of SSA

Response: Revised accordingly as “Whereas in Sub-Saharan African countries households who used shared toilet facilities climbed from 0.64 million to 0.96 million, which was 0.08% of all households” (see page 2, lines 93-94).

Comment #10. Line86 – is a word missing after ‘easy’

Response: We thank you. It was a grammatical and typing error. Modification has been made throughout the document.

Comment #11. Lines 103-104 – what is the source of this statement (it is not SDG 6.2 as suggested by the reference)

Response: We thank you and revised the source. https://iris.who.int/bitstream/handle/10665/258617/9789241512893-eng.pdf?sequence=1

Comment #12: Line 110 – they may be superior to OD – but what are the criteria?

Response: Thank you for raising this point: improved shared sanitation facilities are superior to open defecation for several reasons:

They reduce the incidence of open defecation, lowering exposure to harmful pathogens and disease spread.

They offer more privacy and dignity than open defecation, which occurs in public spaces.

They generally cause less environmental pollution compared to open defecation, which contaminates soil and water sources.

They provide a more structured and accessible option, especially in urban or densely populated areas.

Comment #12: Lines 115-117 – are you drawing a link between using, or not using SS and child mortality? Are you drawing that from your data?

Response: Thank you for your interesting question, it is not from our data. It is based on the reference since it is an introduction, we want to show its burden. However, we revised the child mortality section.

Comment #13: Lines 118-119 – what is the relevance for planners – so that they can target particular households?

Response: Thank you for your interesting question. Knowing the magnitude of improved shared toilet facilities and their contributing factors in Ethiopia helps program planners allocate resources more effectively, design targeted interventions, and develop relevant policies. This understanding enables better planning and decision-making, leading to improved sanitation outcomes, enhanced public health, and more efficient use of resources by addressing the specific needs and challenges faced by different communities (see page 5, lines 121-123).

Comment #14: Lines 138-143 – I am confused by these numbers – there are 8663 households across 645 EAs? That doesn’t make 20-30 households per EA – please clarify here.

Response: Thank you very much for showing the mistake we made; Now we revised accordingly, as the following “In the first stage, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size. The second stage was the careful selection of, on average, 25–30 homes (based on the 2019 EPHC frame)” (see page 6, lines 141-143).Though the revised sample size is 7,561, in the 2019 mini-EDHS 8663 households were included. Then 8,863/305=29 households on average.

Comment #15. I regret that the rest of the methods section doesn’t mean anything to me!

Response: No worries; thank you very much for focusing on your experts.

Results

Comment #16. Line 212 – can you define what a male head of household denotes and what a female head of household denotes? Is a head of household only female if there is no adult male in the house? Or how is it defined?

Response: Thank you for seeking clarification. Yes, as you mentioned, the sociodemographic variables of the household data/record (HR) in DHS are collected for the head of households only. Then in the Ethiopian context, mostly if both male (father) and female (mother) are present in the household, the male is considered the household head. However, if the female is leading the household alone, she is recognized as the household head. (See Table 2)

Comment #17: Line 215 I think here you could summarise up front that an increase in age, and decrease in education, wealth etc. leads to a household being more likely to use SS. Then you can go into the detail

Response: Thank you for this important comment. Revised in the manuscript as the following: “Based on the results from Model III, there was a positive association between improved shared sanitation facilities and several factors such as individuals with higher educational attainment and from greater household wealth, those living in urban areas and metropolitan regions”. (see page 13, lines 244-246).

Comment #18: Lines 235 – 239 Where is the risk of DV data coming from? And is SS a DV risk or a GBV risk? What is the correlation? does this suggest a correlation? A causation? Or just two random connected indicators of increased vulnerability?

Response: Thank you for your comments, and we apologize for any confusion. We are not entirely sure about the abbreviations "DV" and "GBV" you used. However, if "DV" refers to the dependent variable, it implies that improved shared sanitation facilities in our context. The risk associated with the dependent variable is influenced by the cluster in which individuals reside. Since we used Enumeration Area (EA) or cluster as a random variable, the variations observed in the null model (e.g., ICC, MOR) were not due to random chance but rather to the variability of the random variable, which was the cluster or enumeration area. This indicates there was a correlation or association between the random variable (cluster) and the dependent variable. This is accounted for by our multilevel analysis.

Comment #19: Line 244 – 247 – write this as clearly as possible also for a non-statistician audience – as I understand it, this is your main finding.

Response: Thank you for your suggestion: Modifications and clarification have been made in the manuscript as follows: “Based on the results from Model III, there was a positive association between improved shared sanitation facilities and several factors such as individuals with higher educational attainment and from greater household wealth, those living in urban areas and metropolitan regions”. (see page 13, lines 244-246).

Comment #20: From line 306 onwards I cannot comment! Sorry!

Response: No worries; thank you very much for focusing on your experts.

Discussion

Comment #21: Again – I think it needs to be clarified what the non-SS households are using, to be clear that it is worse than SS.

Response: Thank you for your suggestion: We have corrected it; accordingly, the following sentences show the outcome and controls. The outcome of this study is improved shared sanitation facilities whereas the control group are all unimproved sanitation facilities which includes OD, and all unimproved sanitation services such as Pit latrines without slab/open pits, Bucket toilets, hanging toilet/latrines and others. (see table 1).

Comment #22: Line 329 - this is not a strong reference, as it is a webpage without links to the claims it references.

Response: Thank you for your suggestion: revised it accordingly.

Comment #23: Lines 331-332 Did you get this from the data in the study? Or from somewhere else (if so reference) Also add “Studies in Zambia and Ethiopia show…..” I think that the context is critical.

Response: We have got it from previous studies, and we cited references accordingly as the following. “Moreover, a higher level of education enhances awareness and fosters positive attitudes towards choosing relatively more upgraded sanitation facilities [36]. Specifically, educated women are more likely to prefer safe and sanitary facilities that offer privacy and maintain good quality during their menstrual cycle [37]. Moreover, well-educated households with higher incomes had better access to upgraded sanitation facilities [38]. ” (see page 18, lines 330-335).

Comment #24: Line 334 – is this an assumption? |Or does education lead to households using SS (which is what your data says, I think).

Response: Thank you for your valuable comments. Revised accordingly and removed the OD from the revised manuscript. Our data says

Attachment

Submitted filename: point by point response to Reviewers shared toilet_BD.docx

pone.0315860.s001.docx^{(44.6KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0315860.r003

Decision Letter 1

Alison Parker

13 Dec 2024

PONE-D-24-20290R1Spatial distribution and determinants of improved shared sanitation facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health SurveyPLOS ONE

Dear Dr. Amlak,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Apologies for the delay in getting this back to you, one of the reviewers was not available for a while. Both reviewers have some minor comments that still need to be addressed before we can accept the manuscript.

Please submit your revised manuscript by Jan 27 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #3: No

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

Reviewer #3: Most of the comments were addressed correctly. Here are additional comments with regards to revision1:

1) In the response to reviewers' comments you gave 3 research questions: " 1. What was the

magnitude of improved shared sanitation facilities in Ethiopia? 2. What do the spatial

distributions of improved shared sanitation facilities in Ethiopia look like? 3. What are

the associated factors with improved shared sanitation facilities?" In the text you have only 2 questions 119-121.

2) In your Multilevel model results you state:

"A household

236 from a cluster with a high risk of domestic violence had 28.75 times higher odds of having shared

237 toilet facilities than a household from a cluster with a lower risk of shared toilet facilities, according

238 to the MOR value in the null model (28.75), on the other hand, if you randomly selected two

239 households from two different clusters."

You can see you are referring to a cluster with high risk of domestic violence. How this cluster characteristics has been arrived to? Is it one of the characteristics of EA? This needs to be clarified before you report your results.

3) There is a need for further proof reading of the text. See e.g. the paragraph copied above for style and clarity and 241 (valve - should be value?).

4) Referencing - also requires additional check to make sure all statements made are link to this study results or specific source(s) see e.g. 322.

5) Recommendations are basic and could have been developed better taking into account findings and discussion. (E.g. if other countries mentioned have higher standards of sanitation are there any lessons to be learned from their experiences?

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #3: No

**********

Attachment

Submitted filename: PONE-D-24-20290_R1.pdf

pone.0315860.s002.pdf^{(4.6MB, pdf)}

PLoS One. 2025 Jan 13;20(1):e0315860. doi: 10.1371/journal.pone.0315860.r004

Author response to Decision Letter 1

15 Dec 2024

Date: December 14, 2024

Alison Parker

Academic Editor of Plos One Journal

Re: Spatial distribution and determinants of improved shared toilet facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health Survey (Submission ID: PONE-D-24-20290)

Dear Editor,

We are grateful for the opportunity to revise our manuscript for further consideration for publication in Plos One Journal.

Yours sincerely,

Baye Tsegaye Amlak

Corresponding Author

A point-by-point response to the reviewer’s comment

Reviewer #3:

Most of the comments were addressed correctly. Here are additional comments with regards to revision1:

Thank you for your feedback and for recognizing the importance of this manuscript. We have addressed the comments provided and revised the manuscript accordingly.

Comment #1. In the response to reviewers' comments, you gave 3 research questions: " 1. What was the magnitude of improved shared sanitation facilities in Ethiopia? 2. What do the spatial distributions of improved shared sanitation facilities in Ethiopia look like? 3. What are

the associated factors with improved shared sanitation facilities?" In the text you have only 2 questions 119-121.

Response: Thank you for noting this. In the revised manuscript, we have included three research questions? 1. To determine magnitude, 2. Spatial distribution, 3. determinants or factors. We have revised it as a short description as the following. “This study aims to address the following research questions: What is the magnitude and spatial distribution of improved shared sanitation facilities in Ethiopia? What factors are associated with improved shared sanitation facilities? See page 5 line number 119. Furthermore, those research questions were clearly answered and indicated in the manuscript (Magnitude of improved shared sanitation(Page 12 line number 239), factors associated with it(page 15 table 4), spatial distribution page 16 line number 302).

Comment #2. In your Multilevel model results you state: "A household from a cluster with a high risk of domestic violence had 28.75 times higher odds of having shared toilet facilities than a household from a cluster with a lower risk of shared toilet facilities, according to the MOR value in the null model (28.75), on the other hand, if you randomly selected two households from two different clusters. "You can see you are referring to a cluster with high risk of domestic violence. How these cluster characteristics has been arrived to? Is it one of the characteristics of EA? This needs to be clarified before you report your results.

Response: We thank the reviewer. “Domestic violence” was the wrong word incorporated in the document. We have revised the document accordingly. Here is the comment. “According to the MOR value in the null model (28.75), a household from a high-risk cluster had 28.75 times higher odds of having shared toilet facilities compared to a household from a low-risk cluster”. Please, see line numbers 238-240.

Comment #3. There is a need for further proofreading of the text. See e.g. the paragraph copied above for style and clarity and 241 (valve - should be value?).

Response: Thank you for noting this. We have corrected the specified spelling. Moreover, we have proofread all sections of the documents.

Comment #4. Referencing - also requires additional check to make sure all statements made are linked to this study results or specific source(s) see e.g. 322.

Response: Thank you for your comment. Even though the EDHS report reported the magnitude of open defecation, we have revised and changed it with the updated articles.

“Spatiotemporal distribution and determinants of open defecation among households in Ethiopia: A Mixed effect and spatial analysis”

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0268342

Comment #5. Recommendations are basic and could have been developed better taking into account findings and discussion. (E.g. if other countries mentioned have higher standards of sanitation are there any lessons to be learned from their experiences?

Response: Thank you for your comment.

We have addressed and revised based on your comments

Attachment

Submitted filename: Response to Reviewers.docx

pone.0315860.s003.docx^{(26.2KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0315860.r005

Decision Letter 2

Alison Parker

18 Dec 2024

Spatial distribution and determinants of improved shared sanitation facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health Survey

PONE-D-24-20290R2

Dear Dr. Amlak,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Alison Parker

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0315860.r006

Acceptance letter

Alison Parker

2 Jan 2025

PONE-D-24-20290R2

PLOS ONE

Dear Dr. Amlak,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: point by point response to Reviewers shared toilet_BD.docx

pone.0315860.s001.docx^{(44.6KB, docx)}

Attachment

Submitted filename: PONE-D-24-20290_R1.pdf

pone.0315860.s002.pdf^{(4.6MB, pdf)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0315860.s003.docx^{(26.2KB, docx)}

Data Availability Statement

[pone.0315860.ref001] 1.Shiras T., et al., Shared Sanitation Management and the Role of Social Capital: Findings from an Urban Sanitation Intervention in Maputo, Mozambique. Int J Environ Res Public Health, 2018. 15(10). doi: 10.3390/ijerph15102222 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0315860.ref002] 2.World Health Organization and UNICEF, Progress on Drinking Water, Sanitation and Hygiene Update and SDG Baselines 2017. 2017, WHO, Geneva.

[pone.0315860.ref003] 3.Central Statistical Agency (CSA) [Ethiopia] and ICF. 2016, Ethiopia Demographic and Health Survey 2016. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: CSA and ICF.

[pone.0315860.ref004] 4.Sprouse L., et al., Shared sanitation in informal settlements: A systematic review and meta-analysis of prevalence, preferences, and quality. International Journal of Hygiene and Environmental Health, 2024. 260: p. 114392. doi: 10.1016/j.ijheh.2024.114392 [DOI] [PubMed] [Google Scholar]

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PERMALINK

Spatial distribution and determinants of improved shared sanitation facilities among households in Ethiopia: Using 2019 mini-Ethiopian Demographic and Health Survey

Baye Tsegaye Amlak

Daniel Gashaneh Belay

Roles

Abstract

Introduction

Methods

Results

Conclusion

Introduction

Methodology

Study design, setting, and data source

Study population

Study variables

Table 1. Questions to measure improved but shared/ limited sanitation service.

Table 2. A list of the study’s variables along with an explanation of each measurement.

Data management and analysis

Spatial analysis

Ethical approval statement

Results

Sociodemographic characteristics of the study participants

Table 3. Socio-demographic characteristics and improved shared toilet usage in Ethiopia, mini 2019 EDHS.

The magnitude of shared sanitation facilities in Ethiopia

Fig 1. Magnitude of improved shared toilet facilities among households in Ethiopia, using the 2019 EDHS.

Factors associated with shared or limited access to improved sanitation service in Ethiopia

Table 4. Multilevel analysis of factors associated with improved shared toilet facilities usage among households in Ethiopia.

Spatial analysis of improved shared toilet facilities utilization among households in Ethiopia

Spatial autocorrelation analysis of improved shared toilet facilities

Fig 2. Spatial autocorrelation analysis of improved shared toilet facilities among households in Ethiopia using 2019 mini-EDHS.

Hotspot analysis of improved shared toilet facilities among household in Ethiopia

Fig 3. Hotspot analysis of improved shared toilet facilities among households in Ethiopia using 2019 mini-EDHS.

Significant windows and SaTscan analysis of improved shared toilet facilities among households in Ethiopia

Table 5. Significant spatial clusters of improved shared toilet facilities among households in Ethiopia using 2019 mini-EDHS.

Fig 4. SaTscan analysis of improved shared toilet facilities among households in Ethiopia using 2019 mini-EDHS.

Kiringing interpolation of improved shared toilet facilities among households in Ethiopia

Fig 5. Kiringing interpolation of improved shared toilet facilities among households in Ethiopia using 2019 mini-EDHS.

Discussion

Conclusion and recommendation

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Alison Parker

Roles

Author response to Decision Letter 0

Decision Letter 1

Alison Parker

Roles

Author response to Decision Letter 1

Decision Letter 2

Alison Parker

Roles

Acceptance letter

Alison Parker

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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