Socioeconomic and Gender Inequalities in Urban Water, Sanitation, and Hygiene Access: Evidence from Dhaka, Bangladesh

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Although Bangladesh has achieved notable national progress, substantial intra-urban disparities persist within Dhaka, particularly among socio-economically marginalized populations. This study examines the extent, determinants, and gendered dimensions of urban WASH inequality to inform equitable policy and infrastructure interventions. A two-stage stratified random household survey was conducted across the Dhaka City Corporation, yielding a weighted sample of 1,000 households. Key WASH indicators, including drinking water sources, water availability on premises, treatment practices, sanitation facilities, sharing behavior, and child feces management, were analyzed against socio-economic and gender variables. Analytical methods included chi-square tests, multivariate logistic regression, and machine-learning-based relationship matrices validated using SHAP sensitivity analysis. Results reveal stark disparities between privileged and underprivileged households. Improved drinking water access was reported by 98.1% of privileged households compared to 82.8% of underprivileged households, while improved sanitation coverage was universal among privileged groups but limited to 68.8% among underprivileged ones. Only 9.4% of underprivileged households treated drinking water, compared to 75% of privileged households. Water collection burdens were highly gendered, with 32.8% of female children and 26.6% of male children in underprivileged households responsible for fetching water, often exceeding 30 minutes per trip. Underprivileged households were also disproportionately dependent on shared sanitation facilities (93.8%) and unsafe child feces disposal practices (87.4%). All major WASH indicators were significantly associated with socio-economic status (p < 0.001), demonstrating that economic disadvantage systematically amplifies health, gender, and infrastructural vulnerabilities. These findings provide actionable evidence for policymakers, urban planners, water utilities, public health agencies, and development partners working to advance SDG 6 and reduce urban inequality. Urban WASH inequality Socio-economic disparities Gendered water access Sanitation and hygiene Public health risk Sustainable Development Goal 6 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Access to WASH, which includes adequate sanitary facilities, safe drinking water, and hygiene practices, is widely recognized as a global public health priority and an essential element of sustainable development (World Health Organization, 2022 ), (World Health Organization, 2017). Sufficient WASH services are essential for safeguarding human health and improving quality of life; research indicates that better WASH practices might avert over 2.4 million fatalities a year, or roughly 4.2% of all deaths worldwide (Prüss-Üstün et al., 2008 ), (Husain and Das, 2023 ). Despite notable global progress, WASH conditions are still insufficient in many areas, endangering social well-being, environmental sustainability, and public health. Currently, more than half a billion people lack access to sufficient water sources, and about 2.3 billion people globally still lack access to basic sanitation (World Health Organization and United Nations Children’s Fund, n.d.). Some evidences show that inadequate WASH conditions are closely related to the spread of infectious illnesses like diarrhoea and considerably raise the global disease burden (Bick et al., 2025 ) (C.J. Murray, et al., 2019), (Prüss-Ustün et al., 2019 ). Poor hygiene habits, insufficient sanitation, and drinking tainted water are responsible for about 88% of diarrheal illnesses (Ahmed et al., 2021 ). The WASH crisis is more acute in low- and middle-income countries (LMICs), where resource constraints, growing urbanization, and institutional problems hinder service delivery (United Nations, 2019 ). Bangladesh, a densely populated lower-middle-income (LMIC) country, has made great strides in enhancing basic WASH services by encouraging handwashing, eliminating open defecation, and ensuring access to clean drinking water. However, the nation still has significant urban WASH issues, especially given the country's high rate of urban migration—an estimated 1.4 million people relocate into cities annually (Rahman et al., 2014 ). According to the World Bank, around 55% of people in Dhaka reside in informal settlements with appallingly subpar WASH facilities. Although more than 90% of metropolitan regions have access to basic sanitation services, with more than 55% meeting the updated criteria, only 12% to 30% of slum people benefit from improved or sanitary sanitation facilities (Rahman et al., 2014 ). Water contamination from fecal germs and heavy metals (such as manganese and arsenic) poses major health problems in these areas. As the city's sole unregulated water supplier, DWASA operates a compromised distribution system, potentially making it the primary source of microbiological contamination (Zubaer, 2023 ). There are still significant gaps, even though the Multiple Indicator Cluster Survey (MICS) 2019 indicates general increases in access to better water sources and sanitation. Marginalized and underprivileged groups continue to face systemic barriers that deny them access to clean water and sanitary amenities. Notwithstanding general advancements, an estimated 100,000 Bangladeshi youngsters lost their lives to diarrheal diseases in 2019 (Sin et al., 2023 ), underscoring ongoing public health issues linked to subpar WASH conditions in disadvantaged populations. The accomplishment of Sustainable Development Goal (SDG) 6, which calls for the eradication of open defecation, the prioritization of vulnerable people, and universal and equitable access to good water and sanitation, is directly impacted by these problems (Alam and Sheoti, 2024a ). It is also tangentially related to other goals, such as Goal 3: Good Health and Well-Being and Goal 10: Reduced Inequalities, both among and within countries (Ezbakhe et al., 2019 ). Given the complex effects of insufficient WASH services, it is imperative to have a better understanding of Bangladesh's urban WASH practices as they are today. Therefore, the purpose of this study is to comprehend the state of WASH practices in the Dhaka Metropolitan Area in Bangladesh. The findings are intended to inform stakeholders and policymakers to support evidence-based actions that improve service delivery and achieve national and international development goals (Dickin et al., 2025 ) (Gaspari and Giuliani, 2025 ). Literature Review Bangladesh has seen economic growth in the past decade, resulting in rapid urbanization (World Health Organization, 2022 ). Due to the job crisis and wage gap on the rural side the Bangladesh migrants from around the country come to the cities and reside mostly in the slums (World Health Organization, 2017). It is observed that the discussed migrated households/ people are exposed to the public health hazard due to their limited access to basic amenities of WASH (Prüss-Üstün et al., 2008 ). Studies revealed that due to the lack of social awareness and lack of literacy rate, those households/people are unaware of their basic right to consume safe potable water and have sanitation amenities (Marphatia et al., 2025 ) (Husain and Das, 2023 ). It is identified from the previous studies that till now, most of the households in the urban locality fetch water from their nearest source of potable water stations. The methods of practice to purify the water before consumption also differ from one household to another because of the financial and social status (World Health Organization and United Nations Children’s Fund, n.d.). Moreover, it can be seen that most of the urban population lives in apartments nowadays, and the apartments usually have a direct connection to the water supply. However, due to the infrequent cleaning of the water reservoir, the safe water supplied becomes contaminated for the users (World Health Organization and United Nations Children’s Fund, n.d.). Hand hygiene is another very important part of the basic amenities that needs to be incorporated with the sanitation. However, it is found from the previous studies that due to the lack of awareness within the underprivileged community, the awareness regarding hand hygiene is very low (C.J. Murray, et al., 2019). It is seen that the affluent and middle class have the necessary amenities to maintain improved WASH habits; communities that are impoverished often lack safe water sources, proper sanitation, and hygiene facilities. Discrimination in terms of gender, social status, and financial status is clearly visible in the deprivation of the WASH amenities (Prüss-Ustün et al., 2019 ). The informal slum settlements, locally known as ‘bostis’, along with the people living in these communities, portray the actual scenario where the residents live in an unhygienic environment with poor WASH, drainage, and waste disposal systems. Participatory assessment studies in regions such as Bauniabadh in Mirpur demonstrate that community mapping and transect walks can reveal significant deficiencies in resource availability and WASH service management (Farzana et al., 2024 ). In slums like Shahidbug, only 38.64% of inhabitants have access to properly managed drinking water, while a mere 1.18% have access to adequate sanitation facilities, underscoring a substantial deficiency in achieving Sustainable Development Goal (SDG) goals 6.1 and 6.2 (Rahaman et al., 2021 ). Residents of slums who are well aware that they are paying 7 to 14 times more for water than those with legal connections, and they are prepared to pay additional amounts for a reliable water supply (Bangladesh Bureau of Statistics (BBS) and UNICEF Bangladesh, n.d.). A significant portion of these communities use direct tap water as drinking water, which is supplied by DWASA, the city’s unchaperoned water supplier. The distribution framework of DWASA is mostly compromised, while studies suggest that tap water in Dhaka, Bangladesh, is a source of multi-drug resistant and pathogenic E. coli, posing mass health risks (Talukdar et al., 2013 ). Moreover, research suggests that diarrheal complications are responsible for the deaths of 100,000 infants under five annually (Hasan et al., 2019 ), while other water-borne diseases such as cholera, typhoid, dysentery, and salmonellosis aren’t far behind. Furthermore, only 8.1% of slum dwellers have a direct piped water connection to their homes, while paying 7–14 times more than other residents, with many using communal or public standpipes, increasing contamination risk (Rahaman and Ahmed, 2016 ) (Haque et al., 2020 ). It is further exacerbated by the influence of corrupt officials and poor governance (Haque, 2019 ). Bangladesh’s WASH-related policies portray high inequality towards the ethnic minority population. After analyzing eight policies and plans in the country, a study found only two policies of the country mentioning the ‘ethnic minority’ or ‘Indigenous’ group, and only one of them mentions such action that is specified for their access to WASH (Alam and Sheoti, 2024b ), indicating structural inequality towards the group as structural or institutional racism or inequality. The study also suggests that policymakers of Bangladesh to focus on finding inequalities, cultural patterns, and behavior changes, and embrace a collaborative approach along with participatory research programs to ensure equitable access to WASH services (Zubaer, 2023 ). Research Methodology Sample Design and Sample Size Household-level data were collected exclusively from Dhaka, Bangladesh (Fig. 2 ), using a two-stage stratified random sampling procedure. Urban areas within the district served as the primary sampling strata. Within each stratum, a predetermined number of census Enumeration Areas (EAs) were systematically selected using Probability Proportional to Size (PPS) sampling. After excluding missing cases, the final weighted sample size was 1,000. All research methods and procedures were conducted in strict accordance with the relevant ethical standards and guidelines. Informed consent was secured from all participants involved, ensuring they were fully aware of the study’s objectives, procedures, and any potential risks. Throughout the data collection, handling, and reporting processes, the rights, dignity, and confidentiality of all participants were respected and upheld. WASH Variables This study utilizes a fixed set of household-level WASH variables to assess disparities in access and usage across socio-economic and gender groups. The variables include the main source of drinking water; sources used for handwashing and cooking; presence of a water source within the premises; time required to fetch water; the household member responsible for water collection; whether water is treated before consumption and the type of treatment used; the type of toilet facility available; whether the toilet is shared; the number of households sharing a single toilet; and practices for handling children’s stool. These indicators provide a comprehensive understanding of water accessibility, sanitation adequacy, and hygiene behavior, allowing the study to explore distinctions between privileged and underprivileged households and highlight the gendered dimensions of WASH responsibilities. Socio-economic Variables This study aims to explore and establish the relationship between social, economic, and gender-based distinctions in the consumption of basic Water, Sanitation, and Hygiene (WASH) amenities. By examining household-level data, the research investigates how access to these essential services varies across different socio-economic segments, with a particular focus on gender roles in water collection and hygiene practices. To better understand the disparities, households are categorized into two primary income groups: privileged and underprivileged. These classifications serve as key variables to assess how income status influences access to and utilization of WASH facilities. The study highlights the intersectionality of economic conditions and gender norms, which often dictate responsibilities related to water fetching, sanitation practices, and hygiene maintenance within households. Statistical Analysis Chi-square tests were conducted to assess the associations between WASH indicators and socio-economic variables. Variables that showed significant associations in the bivariate analysis were included in the final multivariate logistic regression models to estimate adjusted odds ratios (AORs) with 95% confidence intervals. All statistical tests were two-sided, and results were considered statistically significant at a p-value of less than 0.05. Data analysis was performed using JASP software. Relationship Matrix The relationship matrix was generated using machine learning models to explore the disparities in WASH access across socio-economic groups in Dhaka, Bangladesh. An MLM, specifically a supervised regression model, was employed to assess the relationships between the independent variables (WASH variables) and the dependent variable (economic condition categorized by P and UP). This model was selected due to its ability to capture complex nonlinear relationships between the variables. The relationship matrix was then created by mapping these feature importance scores, with higher values indicating stronger correlations between socio-economic factors and WASH variables. The matrix was visualized using a heatmap, offering insights into how socio-economic and gendered factors influenced WASH access. Sensitivity analysis and SHAP values were used to validate the robustness of the model and interpret the individual feature contributions. The results highlighted significant disparities, particularly between privileged and underprivileged households, and underscored the importance of targeted interventions and infrastructure upgrades to reduce these inequities and improve public health outcomes. Results Table 1 highlights significant inequalities in WASH conditions between privileged and underprivileged households. Privileged groups generally have better access to safe water, sanitation, and hygiene practices, while underprivileged groups face systemic barriers, such as longer fetching times, reliance on children for water collection, lower treatment of drinking water, shared sanitation, and unsafe disposal of children’s stool. These disparities call for targeted interventions and inclusive WASH policies (Nabi et al., 2025 ). Table 1 Comparative WASH Indicators Between Privileged and Underprivileged Households. Variables Improved Unimproved Main source of drinking water Privileged 471 29 Underprivileged 414 86 Source of water for handwashing and cooking Privileged 500 0 Underprivileged 430 70 Presence of a source of water at the premises or not It takes time 106 414 Water on premises 394 86 Duration to fetch water 10 to 20 min 30 + min 5 to 10 min Water on premises Privileged 48 10 48 394 Underprivileged 336 39 117 8 A member of the household fetches water from Adult man Adult woman Female child Male Child Water on Premises Privileged 42 52 0 0 406 Underprivileged 86 117 164 133 0 Treatment before consumption No Yes Privileged 67 433 Underprivileged 453 47 Treatment process Improved Unimproved Privileged 490 10 Underprivileged 0 500 Toilet Facility Privileged 500 0 Underprivileged 344 156 Shared toilet facility or not No Yes Privileged 365 135 Underprivileged 31 469 The number of households that use a single toilet facility Improved Unimproved Privileged 365 135 Underprivileged 31 469 Handling of children’s stool Improved Unimproved Privileged 423 77 Underprivileged 63 437 The parallel set diagram Fig. 2 illustrates the disparities in WASH indicators between privileged and underprivileged households, emphasizing the extent of inequity in access to safe water and sanitation facilities. It is evident that privileged households predominantly rely on improved sources of drinking water and water for handwashing and cooking, whereas underprivileged households show a significant share in unimproved categories (Jahan et al., 2025 ). Table 2 shows that compared to 414 of underprivileged households, 471 of privileged households used upgraded sources of drinking water. On the other hand, underprivileged households were far more likely to rely on unimproved sources (86) than privileged households (29). The results of a chi-square test showed a strong correlation between drinking water source and socioeconomic position, suggesting that underprivileged households are more likely to rely on unimproved sources. Table 2 Chi-Squared Tests (T. Rahman et al., 2025 a). Variables No. Variables Value df p V1 Main source of drinking water χ² 31.923 1 < 0.001 V2 Source of water for handwashing and cooking χ² 75.269 1 < 0.001 V3 Presence of a source of water at the premises or not χ² 380.064 1 < 0.001 V3.1 Duration to fetch water χ² 632.655 3 < 0.001 V3.2 A member of the household fetches water from χ² 743.125 4 < 0.001 V4 Treatment before consumption χ² 596.939 1 < 0.001 V4.1 Treatment process χ² 960.784 1 < 0.001 V5 Toilet Facility χ² 897.290 4 < 0.001 V6 Shared toilet facility or not χ² 466.402 1 < 0.001 V7 The number of households that use a single toilet facility χ² 466.402 1 < 0.001 V8 Handling of children’s stool χ² 518.807 1 < 0.001 N 1000 According to Table 2 , all privileged homes utilized improved water systems, while 430 out of 500 underprivileged houses did so; the remaining 70 used unimproved water sources. The chi-square test further confirmed that there is a statistically significant relationship between socioeconomic status and access to improved water sources (Alam et al., 2025 ). The chi-square tests reveal a significant association between socio-economic status and water access. According to the first test, privileged households typically have water in their houses, whereas underprivileged households spend more time getting water. It is also confirmed by the second test that, whereas many disadvantaged people spend 30 minutes or more gathering water, privileged people often spend less time. These findings demonstrate a glaring difference in the availability of water between privileged and underprivileged populations. The chi-square analysis reveals a statistically significant association between household socio-economic status and responsibility for water collection. 406 out of 500 houses in privileged households reported having water on-site and not depending on kids to fetch it. On the other hand, all underprivileged households did not have access to on-site water, and they heavily relied on child labor, especially for male (133 cases) and female (164 cases) children. The statistics show a glaring discrepancy, with underprivileged homes experiencing both a lack of infrastructure and a disproportionate amount of work for children fetching water. This reflects larger concerns about gender roles, socioeconomic inequality, and access to basic services. The chi-square test demonstrates a highly significant association in the relationship between socioeconomic status and water treatment techniques. The observed data reveal that 433 out of 500 privileged respondents reported treating their drinking water, compared to 47 out of 500 underprivileged respondents. In contrast, 67 privileged respondents did not treat their water, whereas 453 underprivileged respondents did not. These results demonstrate the stark differences in water treatment between rich and poor populations. The results point to possible disparities in access to clean drinking water and the necessity of focused public health initiatives by indicating that socioeconomic status has a substantial impact on the likelihood of treating drinking water. The results of the chi-square test show a highly significant correlation between the type of water treatment method used to make water safer to drink and socioeconomic status. According to the observed counts, all privileged people utilize better methods for water treatment in the majority of cases (490 out of 500), but all underprivileged people only use unimproved methods (500 out of 500). With privileged groups having much better access to or preference for better water treatment choices than disadvantaged groups, this considerable difference shows that privilege status is closely correlated with the choice of water treatment methods. According to the chi-square test, the type of toilet facility used and household socioeconomic status are significantly correlated. With 471 households utilizing upgraded toilets and very few using unimproved facilities, the observed counts demonstrate that privileged households are the ones that use improved toilet facilities the most. On the other hand, a significant portion of members of underprivileged households use improved toilets (344), while a significant portion use unimproved toilets (156). The distribution of toilet facility types is not independent of household socioeconomic position, as confirmed by the incredibly small p-value and the incredibly big chi-square value. This shows a high correlation between the type of toilet facilities utilized and household privilege. The chi-square test showed a statistically significant correlation between the practice of facility sharing and household socioeconomic status. According to the data, the majority of underprivileged houses (469 out of 500) share the facility with other households, while the majority of privileged households (365 out of 500) do not. With underprivileged households being more inclined to share facilities than their wealthier counterparts, these data show a glaring difference in facility-sharing behavior. The findings of the chi-square test show a significant correlation between household socioeconomic class and the type of toilet facility used, suggesting that access to improved versus unimproved sanitation facilities varies significantly between privileged and underprivileged populations. In particular, just 31 of the 500 underprivileged families have improved toilets, while 469 of the 500 underprivileged households have unimproved toilets. In contrast, 365 of the privileged houses have improved toilets, while 135 have unimproved toilets. There is a high correlation between the chance of utilizing an improved toilet and the privilege level of the households. According to the results of the chi-square test, socioeconomic status and feces disposal habits have a strong and statistically significant link and suggesting that privileged and underprivileged populations use very different disposal techniques. According to the counts that were observed, underprivileged families mostly employed unimproved disposal methods (437 out of 500), whereas privileged households used improved methods 423 out of 500. The data unequivocally demonstrate that in this sample population, the disposal of the youngest child's excrement is closely related to socioeconomic class. Discussions Table 3 reveals sharp disparities in WASH access between privileged and underprivileged households. Privileged groups have far higher access to improved drinking water (98.08% vs. 82.82%) and sanitation (100% vs. 68.75%), with most having water on premises and practicing safe treatment. In contrast, underprivileged households face longer collection times, greater reliance on women and children for fetching water, widespread sharing of sanitation facilities, and limited safe disposal of child feces. These gaps highlight heightened health risks for underprivileged communities. Table 3 Disparities in Access to Safe Water Between the Privileged and the Underprivileged Groups (Zubaer, 2023 ). Indicators Privileged (%) Underprivileged (%) Population Using Improved Drinking Water Sources 98.08 82.82 Population Using Improved Water Sources for Household Chores 100 85.93 Duration to Collect Drinking Water Water on Premises 78.85 1.56 30 mins 1.92 7.81 Gender Perspective on Collecting Water Adult Woman 9.62 23.44 Adult Man 7.69 17.19 Female Child 0 32.81 Male Child 0 26.56 Water on premises 0 26.56 Population Treating Their Drinking Water 75 0 Population Using Improved Sanitation Services 100 68.75 Population Sharing Their Sanitation Facilities 26.92 93.75 Safe Disposal of Child’s Feces 84.61 12.5 Table 4 and Fig. 2 present a comparative assessment of the current scenario and quality of water supplied by DWASA in the study area against both national and international drinking water standards. This comparison provides a critical evaluation of the performance of the existing water supply system, identifying potential risks to public health and highlighting the need for improved treatment, monitoring, and distribution practices. Such analysis is essential for ensuring compliance with regulatory frameworks and guiding future infrastructure development in the water supply sector. Table 4 Quality of potable water supplied by DWASA (Zubaer, 2023 ). Parameter pH Turbidity (NTU) TDS (mg/L) Conductivity (µs/cm) Ammonia-N (mg/L) Total Hardness (mg/L) Residual Chlorine (mg/L) Total Coliforms (N/100 ml) WHO Standard 6.5–8.5 5 1000 - 1.5 - 0.6-1 0 ECR 2023 6.5–8.5 10 1000 - 0.5 200–500 0.2–0.5 0 DWASA Supplied Water 6.8–7.45 1.04–3.01 104–148 192.2–307 0 72–120 0-0.4 0–10 This study sought to explore the views and behaviors related to hygiene in both privileged and disadvantaged households within the Dhaka City Corporation region. There are notable differences in the accessibility, caliber, and practicality of services between privileged and underprivileged homes in the Dhaka City Corporation region when comparing Water, Sanitation, and Hygiene (WASH). Upon analysis, it has been observed that a bigger proportion of privileged households (94.2%) rely on better sources of drinking water compared to underprivileged households (82.8%). In contrast to earlier national data, such as MICS 2019, which reported 78.3% household access to upgraded water sources, and BBS 2022, which indicated 86.51% nationwide coverage, these numbers show an overall improvement. However, the underprivileged group continues to show a significant reliance (17.2%) on unimproved sources, suggesting a greater risk of waterborne illnesses and other health issues in these areas. In the DCC area, the gap between privileged and underprivileged households is noticeable when it comes to access to better water sources. In order to cook and wash their hands, 14% of underprivileged households still utilize outdated methods, which makes them more susceptible to diarrheal illnesses. Severe socioeconomic gaps are revealed by analyzing the availability of residential water sources. Compared to 78.8% of privileged families, just 17.2% of households in lower socioeconomic categories had improved water sources on their households. According to MICS 2019, the national urban average of 87.5% improved on-premises water sources is significantly higher than this number, highlighting long-standing structural disparities in access to convenient and safe water. Additionally, 19.2% of privileged households have to wait for 10 to 20 minutes, while 67.2% of underprivileged households have to do so. Furthermore, it was also seen that only 8 underprivileged households have water on premises compared to 394 privileged households. Unfair gender and age dynamics are also reflected in the task of fetching water: in privileged households, 18.8% adult men and women perform this duty, while in underprivileged households, 23.4% of adult women, 32.8% of female children, and 26.6% of male children are responsible for fetching water for 10 to 20 minutes each day. This number shows a glaring disparity in infrastructure accessibility, which hurts the physical health and productivity of marginalized communities. It worsens gender disparities in the division of everyday labor in addition to endangering children's education and safety. Water treatment techniques also show a gap: 86.6% of privileged households treat their drinking water, whereas only 9.4% of underprivileged households do so. The MICS 2019 urban "no water treatment" percentage, on the other hand, was 68.6%. These results underline the critical need for fair access to water purifying facilities and awareness-raising campaigns. In the study area, 98% of privileged households reported using improved drinking water treatment methods, whereas all the underprivileged households relied on unimproved practices, indicating a substantial disparity between socio-economic groups. Sanitation conditions also revealed marked inequalities. All privileged households (100%) had access to upgraded toilet facilities, reflecting complete coverage of improved sanitation. In contrast, 31.2% of underprivileged households used unimproved toilets, and only 68.8% (344 out of 500) had access to improved facilities. These findings highlight systemic inequities in basic sanitation, with unimproved facilities concentrated exclusively among the underprivileged population. There is a significant gap in socioeconomic categories in the research area, as 98% of privileged homes reported using improved drinking water treatment procedures while the rest households depended on unimproved practices. Significant disparities were also found in the state of sanitation. All the privileged households (100%) have access to improved toilet facilities, demonstrating full coverage of improved sanitation (Nachaiwieng et al., 2024 ). However, only 68.8% of underprivileged households had access to upgraded facilities, and 31.2% of them utilized unimproved toilets. With unimproved facilities concentrated solely among the poor, these data demonstrate systematic disparities in basic sanitation (Dibaba et al., 2024 ). Inequality is also evident in the sharing of toilets, as 93.8% of underprivileged homes use shared unimproved facilities, compared to 27% of privileged households. This exposes underprivileged groups to poor upkeep, insufficient cleanliness, and restricted privacy in crowded urban environments. In Bangladesh and other LMICs, diarrhea continues to be a serious public health issue (Abdulhadi et al., 2024 ). According to data from the Bangladesh Demographic Health Survey (BDHS), the prevalence of diarrhea in children under five was 5.7% in 2014, 4.7% in 2017, and 4.8% in 2022 (Rahman et al., 2025 ). In order to protect children's health and stop the spread of diarrheal illnesses, it is imperative that children's stool be disposed of safely. Compared to just 12.6% of underprivileged households with improved handling techniques, 84.6% of privileged households reported better methods for handling their children's feces. A major public health risk is indicated by the startling finding that 87.4% of underprivileged households report unimproved handling behaviors. This disparity raises severe public health concerns since it most likely results from either a lack of awareness or poor facilities, or both (Nadal et al., 2025 ). Overall, the results show that Dhaka City Corporation's WASH service landscape is extremely stratified. While underprivileged households deal with long water-fetching periods, reliance on contaminated sources, gendered labor constraints, and inadequate purification procedures, privileged households enjoy simpler access to safe water (Arnold and Ante-Testard, 2024 ). Targeted WASH interventions, infrastructure upgrades, behavioral change initiatives, and fair resource distribution are all necessary to address these disparities. The study exclusively focuses on households in the Dhaka City Corporation, which limits its applicability to other Dhaka metropolitan areas or Bangladeshi urban locations where WASH circumstances can vary. Figure 4 presents a heatmap illustrating the correlation between various variables, as detailed in Table 2 , and economic conditions in the context of WASH (Water, Sanitation, and Hygiene) amenities. The heatmap compares two categories, labeled "P" (privileged) and "UP" (underprivileged), across each variable. The variables are organized in rows, with the first column identifying the variables under the conditions of improved WASH (IWA) and unimproved WASH (UIWA). The correlation values range from 0 to 1, with the color gradient representing varying degrees of correlation, from lighter to darker shades of blue. Variables such as V1, V2, and V5 exhibit stronger correlations with economic conditions, particularly in the "P" category. In contrast, variables like V4 and V7 show divergent patterns across the "P" and "UP" categories, with lower correlations observed in some instances. The color scale on the right denotes the strength of these correlations, where darker blue shades correspond to stronger correlations closer to 1, and lighter shades indicate weaker correlations closer to 0. Conclusions The study quantifies significant disparities in WASH access between privileged and underprivileged households in Dhaka, revealing stark inequalities in drinking water, sanitation, and hygiene facilities. Specifically, 98.08% of privileged households have access to improved drinking water sources, whereas only 82.82% of underprivileged households enjoy the same. In terms of sanitation, 100% of privileged households have access to improved facilities, compared to 68.75% of underprivileged households. Water treatment practices also differ significantly, with 75% of privileged households treating their drinking water, in contrast to just 9.4% of underprivileged households. Additionally, the study reveals that 32.8% of female children and 26.6% of male children in underprivileged households are tasked with fetching water, significantly increasing their daily workload. Furthermore, the relationship matrix in this study highlights the correlations between WASH access and economic conditions across both privileged (P) and underprivileged (UP) groups. Key variables such as access to improved drinking water, sanitation facilities, and water treatment practices show stronger correlations with economic conditions, particularly in the privileged group. The matrix reveals that variables like the source of drinking water, the presence of water at the premises, and the treatment of drinking water demonstrate significant disparities between the two groups, where privileged households exhibit a higher degree of access to improved WASH amenities. The results presented in Table 2 further reinforce these disparities by showcasing statistically significant associations between socio-economic status and WASH access. The chi-square tests for variables such as the source of drinking water, the time required to fetch water, the presence of water on premises, and the use of improved sanitation facilities all demonstrate strong associations with socio-economic conditions. For example, 471 privileged households used improved drinking water sources compared to just 414 underprivileged households, and 394 privileged households had water on-premises, compared to only 8 underprivileged households. Additionally, the duration to fetch water varied significantly between the two groups, with 67.2% of underprivileged households spending over 30 minutes fetching water, compared to just 1.92% of privileged households. These findings highlight the intersectionality of socio-economic status and access to essential services, particularly emphasizing that underprivileged groups face compounded barriers that exacerbate their vulnerabilities to waterborne diseases and poor sanitation. The disparities in WASH access, as captured in both the relationship matrix and Table 2 , underscore the urgent need for targeted interventions, infrastructure upgrades, and gender-sensitive policies to address the systemic inequalities in Dhaka's urban WASH landscape. Addressing these gaps is critical to improving public health outcomes, particularly in marginalized communities, and achieving the targets of SDG 6. It is essential for policymakers and stakeholders to prioritize equitable access to WASH services, with a focus on reducing the time burden on underprivileged households, improving sanitation infrastructure, and ensuring safe water treatment practices across all socio-economic strata. Declarations Acknowledgements The authors wish to acknowledge Taimur Rahman (Department of Civil Engineering, World University of Bangladesh) for his assistance in reviewing the manuscript, comments, suggestions, and English proofreading. Authors Contributions Conceptualization: Abdur Razzak Zubaer Data curation: Maisha Maliyat Aronna and Shakib Hossain Khan Methodology: Abdur Razzak Zubaer Investigation: Maliha Farheen Formal Analysis: Abdur Razzak Zubaer, Rahmot Al Jamy, and Tasnim Era Project administration: Abdur Razzak Zubaer Visualization: Ikramul Islam Writing- original draft: Abdur Razzak Zubaer Writing- review & editing: Maliyat Aronna, Ikramul Islam, and Shakib Hossain Khan Funding This study is not supported financially by any institutions or organizations. Data Availability Statement The dataset supporting this study is not publicly available due to its use in ongoing research, but may be obtained from the corresponding author upon reasonable request, subject to confidentiality considerations. Clinical Trial Number Not Applicable Ethics Statement and Accordance Not applicable. All data collection procedures and the collected data were reviewed by the Review Board of the Department of Civil Engineering, World University of Bangladesh, which decided to waive ethical approval, as the study did not involve experiments on human participants or live vertebrates, and no human biological material was used. Data (monthly income, sources of usable water, and sanitation facilities) were collected at the household level without recording any personally identifiable information, and participation was voluntary, in accordance with ethical principles and the Declaration of Helsinki. Consent to Participate Informed consent was obtained from all individual participants included in the study prior to their participation. Participants were adequately informed about the study objectives, procedures, and the voluntary nature of their involvement. Consent to Publish Verbal consent to participate and consent to publish were obtained from all participants prior to participation. No participants under the age of 18 were involved in the study. All participants agreed to the publication of the study results in accordance with applicable ethical standards. References Abdulhadi, R., Bailey, A., Van Noorloos, F., 2024. Access inequalities to WASH and housing in slums in low- and middle-income countries (LMICs): A scoping review. Global Public Health 19, 2369099. https://doi.org/10.1080/17441692.2024.2369099 Ahmed, M.S., Islam, M.I., Das, M.C., Khan, A., Yunus, F.M., 2021. Mapping and situation analysis of basic WASH facilities at households in Bangladesh: Evidence from a nationally representative survey. PLOS ONE 16, e0259635. https://doi.org/10.1371/journal.pone.0259635 Alam, A., Prodhan, Md.E., Islam, F., Hasan, M.N., Chowdhury, M.A.B., Uddin, M.J., 2025. The effects of household water, sanitation, and hygiene on early childhood education enrollment: evidence from the 2022 Bangladesh demographic and health survey. BMC Public Health 25, 2732. https://doi.org/10.1186/s12889-025-23968-7 Alam, Md.Z., Sheoti, I.H., 2024a. Ethnicity and access to water, sanitation, and hygiene in Bangladesh: a study using MICS data and policy reviews. BMC Public Health 24, 2726. https://doi.org/10.1186/s12889-024-20250-0 Alam, Md.Z., Sheoti, I.H., 2024b. Ethnicity and access to water, sanitation, and hygiene in Bangladesh: a study using MICS data and policy reviews. BMC Public Health 24, 2726. https://doi.org/10.1186/s12889-024-20250-0 Arnold, B., Ante-Testard, P.A., 2024. WASH interventions and child diarrhea at the interface of climate and socioeconomic position in Bangladesh. https://doi.org/10.17605/OSF.IO/XWNDG Bangladesh Bureau of Statistics (BBS), UNICEF Bangladesh, n.d. Progotir Pathey, Bangladesh Multiple Indicator Cluster Survey 2019, Survey Findings Report. Bick, S., Davies, K., Mwenge, M., MacLeod, C., Braun, L., Chipungu, J., Chidziwisano, K., Dreibelbis, R., 2025. WASH and learn: a scoping review of health, education and gender equity outcomes of school-based water, sanitation and hygiene in low-income and middle-income countries. BMJ Glob Health 10, e018059. https://doi.org/10.1136/bmjgh-2024-018059 C.J. Murray, A.Y. Aravkin, P. Zheng, C. Abbafati, K.M. Abbas, M. Abbasi-Kangevari, F. Abd-Allah, A. Abdelalim, M. Abdollahi, I. Abdollahpour, K.H. Abegaz, n.d. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Dibaba, D.B., Alemu, B.M., Debela, S.A., 2024. Impact of water, sanitation, and hygiene (WASH) interventions on gender-specific school attendance and learning outcomes: A systematic review and meta-analysis protocol. PLoS ONE 19, e0308144. https://doi.org/10.1371/journal.pone.0308144 Dickin, S., Siddique, S., Liera, C., Dupont, G., Bisung, E., 2025. Assessing the importance of gender transformative WASH: evidence from a gender-mainstreamed WASH programme in Bangladesh. International Journal of Water Resources Development 41, 789–811. https://doi.org/10.1080/07900627.2025.2505867 Ezbakhe, F., Giné-Garriga, R., Pérez-Foguet, A., 2019. Leaving no one behind: Evaluating access to water, sanitation and hygiene for vulnerable and marginalized groups. Science of The Total Environment 683, 537–546. https://doi.org/10.1016/j.scitotenv.2019.05.207 Farzana, F.D., Hossain, D., Rahman, M., Nahar, Q., Arifeen, S.E., Ahmed, T., Mahfuz, M., 2024. Understanding water, sanitation, and hygiene situation through participatory appraisal in urban slum of Dhaka City. EUR J ENV PUBLIC HLT 8, em0165. https://doi.org/10.29333/ejeph/15585 Gaspari, L., Giuliani, M., 2025. The Co‐Optation of Gender Equity Issues in Empirical Business Research: A Systematic Literature Review. Business Ethics Env & Resp beer.12844. https://doi.org/10.1111/beer.12844 Haque, M., 2019. Urban Water Governance: Pricing of Water for the Slum Dwellers of Dhaka Metropolis: Methods, Approaches and Practices. pp. 385–397. https://doi.org/10.1007/978-981-10-8947-3_22 Haque, S.S., Yanez-Pagans, M., Arias-Granada, Y., Joseph, G., 2020. Water and sanitation in Dhaka slums: access, quality, and informality in service provision. Water International 45, 791–811. https://doi.org/10.1080/02508060.2020.1786878 Hasan, Md.K., Shahriar, A., Jim, K.U., 2019. Water pollution in Bangladesh and its impact on public health. Heliyon 5, e02145. https://doi.org/10.1016/j.heliyon.2019.e02145 Husain, Z., Das, P., 2023. Reducing child diarrhoea in India: Shifting policy focus from source of water to quality. Water Resources and Economics 42, 100221. https://doi.org/10.1016/j.wre.2023.100221 Jahan, F., Shuchi, N.S., Yeamin, A., Sen, T., Shoab, A.K., Alam, M.-U., Sarker, S., Mahfuz, M.T., Hasan, M., Jahan, H., Islam, K., Alam, Md.M., Rahman, M., 2025. Improving WASH facilities and practices in Bangladeshi schools: progress and challenges from 2014 to 2018. Global Health Action 18, 2466896. https://doi.org/10.1080/16549716.2025.2466896 Marphatia, A.A., Simiyu, S., Flint O’Kane, M., Alexander, K.T., Nascimento De Castro, A.C.A., Azcona, G., Boni-Morkla, P.E., Bukachi, S.A., Busienei, P., Caruso, B.A., Chase, C., Chipungu, J., Dwivedi, A., Johnston, R., Khurana, I., Kome, A., Kuria, W., Labadia, J., Makoni, F., Mberu, B., Mojumdar, S., Mule, J., Namatende Sakwa, L., Njeri, N., Oliveira De Souza, F.A., Pandolfelli, L., Ramunenyiwa, P., Ray, I., Reddy, M., Saha, P.K., Sinha, U., Sinharoy, S.S., Slaymaker, T., Uguru, E., Uhl, K., Young, S.L., Ross, I., Cumming, O., 2025. Gender equality and quality of life must be central to the design and delivery of sanitation. BMJ Glob Health 10, e018238. https://doi.org/10.1136/bmjgh-2024-018238 Nabi, M.H., Rupa, F.H., Jahan, I., Hasan, A.B.M.N., Naz, F., Masud, I., Hawlader, M.D.H., Hossian, M., 2025. Water, sanitation, and hygiene (WASH) factors and the incidence of communicable diseases in Urban Bangladesh: Evidence from municipal areas. PLoS Negl Trop Dis 19, e0013329. https://doi.org/10.1371/journal.pntd.0013329 Nachaiwieng, W., Sanit, S., Kongta, N., Saingamsook, J., Duangmano, S., Pornprasert, S., Somboon, P., Yanola, J., 2024. The impact of an integrated intervention program combining drug therapy with water, sanitation, and hygiene (WASH) education on reinfection with intestinal parasitic infections among the Karen hill tribe in northern Thailand. Parasites Vectors 17, 544. https://doi.org/10.1186/s13071-024-06611-z Nadal, L., Delaire, C., Yachori, B., Khush, R., Bauza, V., 2025. Gender disparities in water-related knowledge, perceptions, and governance in rural Ghana: insights from a qualitative study augmented by Natural Language Processing. Social Science & Medicine 382, 118338. https://doi.org/10.1016/j.socscimed.2025.118338 Prüss-Üstün, A., Bos, R., Gore, F., Bartram, J., 2008. Safer water, better health: costs, benefits and sustainability of interventions to protect and promote health. WHO. Prüss-Ustün, A., Wolf, J., Bartram, J., Clasen, T., Cumming, O., Freeman, M.C., Gordon, B., Hunter, P.R., Medlicott, K., Johnston, R., 2019. Burden of disease from inadequate water, sanitation and hygiene for selected adverse health outcomes: An updated analysis with a focus on low- and middle-income countries. Int J Hyg Environ Health 222, 765–777. https://doi.org/10.1016/j.ijheh.2019.05.004 Rahaman, M., Ahmed, T., 2016. Affordable Water Pricing for Slums Dwellers in Dhaka Metropolitan Area: The Case of Three Slums. Journal of Water Resource Engineering and Management 3, 15–33. Rahaman, M.M., Galib, A.I., Azmi, F., 2021. Achieving drinking water and sanitation related targets of SDG 6 at Shahidbug slum, Dhaka. Water International 46, 462–476. https://doi.org/10.1080/02508060.2021.1901189 Rahman, A.M.R., Islam, M.R., Bashar, S.J., Al Fidah, M.F., Amin, R., Rahman, M.M., Faruque, A., Chisti, M.J., Ahmed, T., Nuzhat, S., 2025. Trends in preventive practices against diarrhoeal disease among under-five children: experience from the largest diarrhoeal disease hospital in Bangladesh. bmjpo 9, e003259. https://doi.org/10.1136/bmjpo-2024-003259 Rahman, M., Ali, M., Choudhury, M., Rahman, M., Ahmed, A., Soneji, S.V., Akhter, M.B., Syafitri, S., Das, S., 2014. WASH Challenges in Slum Areas of Dhaka City. Rahman, T., Momin, Md.F., Provasha, A.A., 2025a. Comprehensive analysis of structural parameters influencing the fundamental period of steel-braced RC buildings using machine learning interpretability. AI Civ. Eng. 4, 7. https://doi.org/10.1007/s43503-025-00051-z Rahman, T., Momin, Md.F., Provasha, A.A., 2025b. Comprehensive analysis of structural parameters influencing the fundamental period of steel-braced RC buildings using machine learning interpretability. AI Civ. Eng. 4, 7. https://doi.org/10.1007/s43503-025-00051-z Sin, M.P., Hasan, M.Z., Forsberg, B.C., 2023. Change in economic burden of diarrhoea in children under-five in Bangladesh: 2007 vs. 2018. J Glob Health 13, 04089. https://doi.org/10.7189/jogh.13.04089 Talukdar, P.K., Rahman, Mizanur, Rahman, Mahdia, Nabi, A., Islam, Z., Hoque, M.M., Endtz, H.P., Islam, M.A., 2013. Antimicrobial resistance, virulence factors and genetic diversity of Escherichia coli isolates from household water supply in Dhaka, Bangladesh. PLoS One 8, e61090. https://doi.org/10.1371/journal.pone.0061090 United Nations, 2019. UN-Water Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS) 2019 report. World Health Organization, 2022. WHO Global Water, Sanitation and Hygiene: Annual Report 2021. World Health Organization. World Health Organization (Ed.), 2017. Financing universal water, sanitation and hygiene under the sustainable development goals: UN-water global analysis and assessment of sanitation and drinking-water, GLAAS ... Report. Geneva. World Health Organization and United Nations Children’s Fund, n.d. Progress on household drinking water, sanitation and hygiene 2000‒2017: Special focus on inequalities. Zubaer, A., 2023. Evaluation of Bangladesh’s SDG6 achievement: A review 6, 7–15. https://doi.org/10.5281/zenodo.7627649 Zubaer, A.R., 2023. An Analysis of the Quality of Dhaka’s Potable Water and Sanitation Services. Journal of Environmental Issues and Climate Change 2, 12–19. https://doi.org/10.59110/jeicc.v2i1.134 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8515390","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594133885,"identity":"e2a532e5-ccfc-49f0-8e88-8a91b675a398","order_by":0,"name":"Abdur Razzak 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2","display":"","copyAsset":false,"role":"figure","size":482930,"visible":true,"origin":"","legend":"\u003cp\u003eStudy Area (Dhaka, Bangladesh).\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8515390/v1/22ea65ab3582020151d7d6cb.jpeg"},{"id":103259463,"identity":"3b3b8d73-2a5d-4301-ab52-da5c023ec8eb","added_by":"auto","created_at":"2026-02-23 17:38:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":34862,"visible":true,"origin":"","legend":"\u003cp\u003eDisparities in WASH Indicators Among Privileged and Underprivileged Households.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8515390/v1/5834d5d7d6c13ed09dab52e1.png"},{"id":103259688,"identity":"07a807d7-dc10-4844-8204-76aa70b50bb2","added_by":"auto","created_at":"2026-02-23 17:39:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":35307,"visible":true,"origin":"","legend":"\u003cp\u003eAssessment of DWASA’s Potable Water Quality in Comparison with National and International Standards.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8515390/v1/21bcf6225948d0aa61678e30.png"},{"id":103259431,"identity":"c8893bb1-f1b7-49d3-a672-5ff44cc69072","added_by":"auto","created_at":"2026-02-23 17:38:17","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":53411,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship Matrix between the Economic Status and the Improved/Unimproved sources of WASH amenities (T. Rahman et al., 2025).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8515390/v1/88296eba3255f11f9d022d12.png"},{"id":103259764,"identity":"9798e5a9-1be0-4fbf-9d1b-f77e56d92340","added_by":"auto","created_at":"2026-02-23 17:40:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2137753,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8515390/v1/170fc9b4-91a2-4571-b763-224fec52477c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Socioeconomic and Gender Inequalities in Urban Water, Sanitation, and Hygiene Access: Evidence from Dhaka, Bangladesh","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccess to WASH, which includes adequate sanitary facilities, safe drinking water, and hygiene practices, is widely recognized as a global public health priority and an essential element of sustainable development (World Health Organization, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), (World Health Organization, 2017). Sufficient WASH services are essential for safeguarding human health and improving quality of life; research indicates that better WASH practices might avert over 2.4\u0026nbsp;million fatalities a year, or roughly 4.2% of all deaths worldwide (Pr\u0026uuml;ss-\u0026Uuml;st\u0026uuml;n et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), (Husain and Das, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite notable global progress, WASH conditions are still insufficient in many areas, endangering social well-being, environmental sustainability, and public health. Currently, more than half a billion people lack access to sufficient water sources, and about 2.3\u0026nbsp;billion people globally still lack access to basic sanitation (World Health Organization and United Nations Children\u0026rsquo;s Fund, n.d.). Some evidences show that inadequate WASH conditions are closely related to the spread of infectious illnesses like diarrhoea and considerably raise the global disease burden (Bick et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) (C.J. Murray, et al., 2019), (Pr\u0026uuml;ss-Ust\u0026uuml;n et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Poor hygiene habits, insufficient sanitation, and drinking tainted water are responsible for about 88% of diarrheal illnesses (Ahmed et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe WASH crisis is more acute in low- and middle-income countries (LMICs), where resource constraints, growing urbanization, and institutional problems hinder service delivery (United Nations, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Bangladesh, a densely populated lower-middle-income (LMIC) country, has made great strides in enhancing basic WASH services by encouraging handwashing, eliminating open defecation, and ensuring access to clean drinking water. However, the nation still has significant urban WASH issues, especially given the country's high rate of urban migration\u0026mdash;an estimated 1.4\u0026nbsp;million people relocate into cities annually (Rahman et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the World Bank, around 55% of people in Dhaka reside in informal settlements with appallingly subpar WASH facilities. Although more than 90% of metropolitan regions have access to basic sanitation services, with more than 55% meeting the updated criteria, only 12% to 30% of slum people benefit from improved or sanitary sanitation facilities (Rahman et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Water contamination from fecal germs and heavy metals (such as manganese and arsenic) poses major health problems in these areas. As the city's sole unregulated water supplier, DWASA operates a compromised distribution system, potentially making it the primary source of microbiological contamination (Zubaer, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere are still significant gaps, even though the Multiple Indicator Cluster Survey (MICS) 2019 indicates general increases in access to better water sources and sanitation. Marginalized and underprivileged groups continue to face systemic barriers that deny them access to clean water and sanitary amenities. Notwithstanding general advancements, an estimated 100,000 Bangladeshi youngsters lost their lives to diarrheal diseases in 2019 (Sin et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), underscoring ongoing public health issues linked to subpar WASH conditions in disadvantaged populations. The accomplishment of Sustainable Development Goal (SDG) 6, which calls for the eradication of open defecation, the prioritization of vulnerable people, and universal and equitable access to good water and sanitation, is directly impacted by these problems (Alam and Sheoti, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e). It is also tangentially related to other goals, such as Goal 3: Good Health and Well-Being and Goal 10: Reduced Inequalities, both among and within countries (Ezbakhe et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the complex effects of insufficient WASH services, it is imperative to have a better understanding of Bangladesh's urban WASH practices as they are today. Therefore, the purpose of this study is to comprehend the state of WASH practices in the Dhaka Metropolitan Area in Bangladesh. The findings are intended to inform stakeholders and policymakers to support evidence-based actions that improve service delivery and achieve national and international development goals (Dickin et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) (Gaspari and Giuliani, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e"},{"header":"Literature Review","content":"\u003cp\u003eBangladesh has seen economic growth in the past decade, resulting in rapid urbanization (World Health Organization, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Due to the job crisis and wage gap on the rural side the Bangladesh migrants from around the country come to the cities and reside mostly in the slums (World Health Organization, 2017). It is observed that the discussed migrated households/ people are exposed to the public health hazard due to their limited access to basic amenities of WASH (Prüss-Üstün et al., \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e). Studies revealed that due to the lack of social awareness and lack of literacy rate, those households/people are unaware of their basic right to consume safe potable water and have sanitation amenities (Marphatia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) (Husain and Das, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is identified from the previous studies that till now, most of the households in the urban locality fetch water from their nearest source of potable water stations. The methods of practice to purify the water before consumption also differ from one household to another because of the financial and social status (World Health Organization and United Nations Children’s Fund, n.d.).\u003c/p\u003e \u003cp\u003eMoreover, it can be seen that most of the urban population lives in apartments nowadays, and the apartments usually have a direct connection to the water supply. However, due to the infrequent cleaning of the water reservoir, the safe water supplied becomes contaminated for the users (World Health Organization and United Nations Children’s Fund, n.d.).\u003c/p\u003e \u003cp\u003eHand hygiene is another very important part of the basic amenities that needs to be incorporated with the sanitation. However, it is found from the previous studies that due to the lack of awareness within the underprivileged community, the awareness regarding hand hygiene is very low (C.J. Murray, et al., 2019).\u003c/p\u003e \u003cp\u003eIt is seen that the affluent and middle class have the necessary amenities to maintain improved WASH habits; communities that are impoverished often lack safe water sources, proper sanitation, and hygiene facilities. Discrimination in terms of gender, social status, and financial status is clearly visible in the deprivation of the WASH amenities (Prüss-Ustün et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). The informal slum settlements, locally known as ‘bostis’, along with the people living in these communities, portray the actual scenario where the residents live in an unhygienic environment with poor WASH, drainage, and waste disposal systems. Participatory assessment studies in regions such as Bauniabadh in Mirpur demonstrate that community mapping and transect walks can reveal significant deficiencies in resource availability and WASH service management (Farzana et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). In slums like Shahidbug, only 38.64% of inhabitants have access to properly managed drinking water, while a mere 1.18% have access to adequate sanitation facilities, underscoring a substantial deficiency in achieving Sustainable Development Goal (SDG) goals 6.1 and 6.2 (Rahaman et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Residents of slums who are well aware that they are paying 7 to 14 times more for water than those with legal connections, and they are prepared to pay additional amounts for a reliable water supply (Bangladesh Bureau of Statistics (BBS) and UNICEF Bangladesh, n.d.).\u003c/p\u003e \u003cp\u003eA significant portion of these communities use direct tap water as drinking water, which is supplied by DWASA, the city’s unchaperoned water supplier. The distribution framework of DWASA is mostly compromised, while studies suggest that tap water in Dhaka, Bangladesh, is a source of multi-drug resistant and pathogenic E. coli, posing mass health risks (Talukdar et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Moreover, research suggests that diarrheal complications are responsible for the deaths of 100,000 infants under five annually (Hasan et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), while other water-borne diseases such as cholera, typhoid, dysentery, and salmonellosis aren’t far behind. Furthermore, only 8.1% of slum dwellers have a direct piped water connection to their homes, while paying 7–14 times more than other residents, with many using communal or public standpipes, increasing contamination risk (Rahaman and Ahmed, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) (Haque et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). It is further exacerbated by the influence of corrupt officials and poor governance (Haque, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBangladesh’s WASH-related policies portray high inequality towards the ethnic minority population. After analyzing eight policies and plans in the country, a study found only two policies of the country mentioning the ‘ethnic minority’ or ‘Indigenous’ group, and only one of them mentions such action that is specified for their access to WASH (Alam and Sheoti, \u003cspan class=\"CitationRef\"\u003e2024b\u003c/span\u003e), indicating structural inequality towards the group as structural or institutional racism or inequality. The study also suggests that policymakers of Bangladesh to focus on finding inequalities, cultural patterns, and behavior changes, and embrace a collaborative approach along with participatory research programs to ensure equitable access to WASH services (Zubaer, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\n\n\n "},{"header":"Research Methodology","content":"\u003ch2\u003eSample Design and Sample Size\u003c/h2\u003e\u003cp\u003eHousehold-level data were collected exclusively from Dhaka, Bangladesh (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), using a two-stage stratified random sampling procedure. Urban areas within the district served as the primary sampling strata. Within each stratum, a predetermined number of census Enumeration Areas (EAs) were systematically selected using Probability Proportional to Size (PPS) sampling. After excluding missing cases, the final weighted sample size was 1,000. All research methods and procedures were conducted in strict accordance with the relevant ethical standards and guidelines. Informed consent was secured from all participants involved, ensuring they were fully aware of the study’s objectives, procedures, and any potential risks. Throughout the data collection, handling, and reporting processes, the rights, dignity, and confidentiality of all participants were respected and upheld.\u003c/p\u003e\u003ch3\u003eWASH Variables\u003c/h3\u003e\u003cp\u003eThis study utilizes a fixed set of household-level WASH variables to assess disparities in access and usage across socio-economic and gender groups. The variables include the main source of drinking water; sources used for handwashing and cooking; presence of a water source within the premises; time required to fetch water; the household member responsible for water collection; whether water is treated before consumption and the type of treatment used; the type of toilet facility available; whether the toilet is shared; the number of households sharing a single toilet; and practices for handling children’s stool. These indicators provide a comprehensive understanding of water accessibility, sanitation adequacy, and hygiene behavior, allowing the study to explore distinctions between privileged and underprivileged households and highlight the gendered dimensions of WASH responsibilities.\u003c/p\u003e\u003ch3\u003eSocio-economic Variables\u003c/h3\u003e\u003cp\u003eThis study aims to explore and establish the relationship between social, economic, and gender-based distinctions in the consumption of basic Water, Sanitation, and Hygiene (WASH) amenities. By examining household-level data, the research investigates how access to these essential services varies across different socio-economic segments, with a particular focus on gender roles in water collection and hygiene practices.\u003c/p\u003e\u003cp\u003eTo better understand the disparities, households are categorized into two primary income groups: privileged and underprivileged. These classifications serve as key variables to assess how income status influences access to and utilization of WASH facilities. The study highlights the intersectionality of economic conditions and gender norms, which often dictate responsibilities related to water fetching, sanitation practices, and hygiene maintenance within households.\u003c/p\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eChi-square tests were conducted to assess the associations between WASH indicators and socio-economic variables. Variables that showed significant associations in the bivariate analysis were included in the final multivariate logistic regression models to estimate adjusted odds ratios (AORs) with 95% confidence intervals. All statistical tests were two-sided, and results were considered statistically significant at a p-value of less than 0.05. Data analysis was performed using JASP software.\u003c/p\u003e\u003ch2\u003eRelationship Matrix\u003c/h2\u003e\u003cp\u003eThe relationship matrix was generated using machine learning models to explore the disparities in WASH access across socio-economic groups in Dhaka, Bangladesh. An MLM, specifically a supervised regression model, was employed to assess the relationships between the independent variables (WASH variables) and the dependent variable (economic condition categorized by P and UP). This model was selected due to its ability to capture complex nonlinear relationships between the variables.\u003c/p\u003e\u003cp\u003eThe relationship matrix was then created by mapping these feature importance scores, with higher values indicating stronger correlations between socio-economic factors and WASH variables. The matrix was visualized using a heatmap, offering insights into how socio-economic and gendered factors influenced WASH access. Sensitivity analysis and SHAP values were used to validate the robustness of the model and interpret the individual feature contributions. The results highlighted significant disparities, particularly between privileged and underprivileged households, and underscored the importance of targeted interventions and infrastructure upgrades to reduce these inequities and improve public health outcomes.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e highlights significant inequalities in WASH conditions between privileged and underprivileged households. Privileged groups generally have better access to safe water, sanitation, and hygiene practices, while underprivileged groups face systemic barriers, such as longer fetching times, reliance on children for water collection, lower treatment of drinking water, shared sanitation, and unsafe disposal of children\u0026rsquo;s stool. These disparities call for targeted interventions and inclusive WASH policies (Nabi et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparative WASH Indicators Between Privileged and Underprivileged Households.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnimproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMain source of drinking water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSource of water for handwashing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of a source of water at the premises or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIt takes time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWater on premises\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDuration to fetch water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 to 20 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u0026thinsp;+\u0026thinsp;min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 to 10 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWater on premises\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e394\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eA member of the household fetches water from\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdult man\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdult woman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFemale child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale Child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWater on Premises\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTreatment before consumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTreatment process\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnimproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eToilet Facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eShared toilet facility or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eThe number of households that use a single toilet facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnimproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHandling of children\u0026rsquo;s stool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnimproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderprivileged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe parallel set diagram Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the disparities in WASH indicators between privileged and underprivileged households, emphasizing the extent of inequity in access to safe water and sanitation facilities. It is evident that privileged households predominantly rely on improved sources of drinking water and water for handwashing and cooking, whereas underprivileged households show a significant share in unimproved categories (Jahan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that compared to 414 of underprivileged households, 471 of privileged households used upgraded sources of drinking water. On the other hand, underprivileged households were far more likely to rely on unimproved sources (86) than privileged households (29). The results of a chi-square test showed a strong correlation between drinking water source and socioeconomic position, suggesting that underprivileged households are more likely to rely on unimproved sources.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChi-Squared Tests (T. Rahman et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003ea).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain source of drinking water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSource of water for handwashing and cooking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePresence of a source of water at the premises or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e380.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration to fetch water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e632.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA member of the household fetches water from\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e743.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment before consumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e596.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment process\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e960.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToilet Facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e897.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShared toilet facility or not\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e466.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number of households that use a single toilet facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e466.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHandling of children\u0026rsquo;s stool\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e518.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, all privileged homes utilized improved water systems, while 430 out of 500 underprivileged houses did so; the remaining 70 used unimproved water sources. The chi-square test further confirmed that there is a statistically significant relationship between socioeconomic status and access to improved water sources (Alam et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe chi-square tests reveal a significant association between socio-economic status and water access. According to the first test, privileged households typically have water in their houses, whereas underprivileged households spend more time getting water. It is also confirmed by the second test that, whereas many disadvantaged people spend 30 minutes or more gathering water, privileged people often spend less time. These findings demonstrate a glaring difference in the availability of water between privileged and underprivileged populations.\u003c/p\u003e \u003cp\u003eThe chi-square analysis reveals a statistically significant association between household socio-economic status and responsibility for water collection. 406 out of 500 houses in privileged households reported having water on-site and not depending on kids to fetch it. On the other hand, all underprivileged households did not have access to on-site water, and they heavily relied on child labor, especially for male (133 cases) and female (164 cases) children. The statistics show a glaring discrepancy, with underprivileged homes experiencing both a lack of infrastructure and a disproportionate amount of work for children fetching water. This reflects larger concerns about gender roles, socioeconomic inequality, and access to basic services.\u003c/p\u003e \u003cp\u003eThe chi-square test demonstrates a highly significant association in the relationship between socioeconomic status and water treatment techniques. The observed data reveal that 433 out of 500 privileged respondents reported treating their drinking water, compared to 47 out of 500 underprivileged respondents. In contrast, 67 privileged respondents did not treat their water, whereas 453 underprivileged respondents did not. These results demonstrate the stark differences in water treatment between rich and poor populations. The results point to possible disparities in access to clean drinking water and the necessity of focused public health initiatives by indicating that socioeconomic status has a substantial impact on the likelihood of treating drinking water.\u003c/p\u003e \u003cp\u003eThe results of the chi-square test show a highly significant correlation between the type of water treatment method used to make water safer to drink and socioeconomic status. According to the observed counts, all privileged people utilize better methods for water treatment in the majority of cases (490 out of 500), but all underprivileged people only use unimproved methods (500 out of 500). With privileged groups having much better access to or preference for better water treatment choices than disadvantaged groups, this considerable difference shows that privilege status is closely correlated with the choice of water treatment methods.\u003c/p\u003e \u003cp\u003eAccording to the chi-square test, the type of toilet facility used and household socioeconomic status are significantly correlated. With 471 households utilizing upgraded toilets and very few using unimproved facilities, the observed counts demonstrate that privileged households are the ones that use improved toilet facilities the most. On the other hand, a significant portion of members of underprivileged households use improved toilets (344), while a significant portion use unimproved toilets (156). The distribution of toilet facility types is not independent of household socioeconomic position, as confirmed by the incredibly small p-value and the incredibly big chi-square value. This shows a high correlation between the type of toilet facilities utilized and household privilege.\u003c/p\u003e \u003cp\u003eThe chi-square test showed a statistically significant correlation between the practice of facility sharing and household socioeconomic status. According to the data, the majority of underprivileged houses (469 out of 500) share the facility with other households, while the majority of privileged households (365 out of 500) do not. With underprivileged households being more inclined to share facilities than their wealthier counterparts, these data show a glaring difference in facility-sharing behavior.\u003c/p\u003e \u003cp\u003eThe findings of the chi-square test show a significant correlation between household socioeconomic class and the type of toilet facility used, suggesting that access to improved versus unimproved sanitation facilities varies significantly between privileged and underprivileged populations. In particular, just 31 of the 500 underprivileged families have improved toilets, while 469 of the 500 underprivileged households have unimproved toilets. In contrast, 365 of the privileged houses have improved toilets, while 135 have unimproved toilets. There is a high correlation between the chance of utilizing an improved toilet and the privilege level of the households.\u003c/p\u003e \u003cp\u003eAccording to the results of the chi-square test, socioeconomic status and feces disposal habits have a strong and statistically significant link and suggesting that privileged and underprivileged populations use very different disposal techniques. According to the counts that were observed, underprivileged families mostly employed unimproved disposal methods (437 out of 500), whereas privileged households used improved methods 423 out of 500. The data unequivocally demonstrate that in this sample population, the disposal of the youngest child's excrement is closely related to socioeconomic class.\u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reveals sharp disparities in WASH access between privileged and underprivileged households. Privileged groups have far higher access to improved drinking water (98.08% vs. 82.82%) and sanitation (100% vs. 68.75%), with most having water on premises and practicing safe treatment. In contrast, underprivileged households face longer collection times, greater reliance on women and children for fetching water, widespread sharing of sanitation facilities, and limited safe disposal of child feces. These gaps highlight heightened health risks for underprivileged communities.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDisparities in Access to Safe Water Between the Privileged and the Underprivileged Groups (Zubaer, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivileged (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnderprivileged (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation Using Improved Drinking Water Sources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation Using Improved Water Sources for Household Chores\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration to Collect Drinking Water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater on Premises\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 mins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30 mins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender Perspective on Collecting Water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdult Woman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdult Man\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale Child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale Child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater on premises\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation Treating Their Drinking Water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation Using Improved Sanitation Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation Sharing Their Sanitation Facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSafe Disposal of Child\u0026rsquo;s Feces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e present a comparative assessment of the current scenario and quality of water supplied by DWASA in the study area against both national and international drinking water standards. This comparison provides a critical evaluation of the performance of the existing water supply system, identifying potential risks to public health and highlighting the need for improved treatment, monitoring, and distribution practices. Such analysis is essential for ensuring compliance with regulatory frameworks and guiding future infrastructure development in the water supply sector.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuality of potable water supplied by DWASA (Zubaer, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTurbidity (NTU)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTDS (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConductivity (\u0026micro;s/cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAmmonia-N (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal Hardness (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eResidual Chlorine (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTotal Coliforms\u003c/p\u003e \u003cp\u003e(N/100 ml)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHO Standard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.5\u0026ndash;8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECR 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.5\u0026ndash;8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e200\u0026ndash;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2\u0026ndash;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDWASA Supplied Water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.8\u0026ndash;7.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04\u0026ndash;3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104\u0026ndash;148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e192.2\u0026ndash;307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72\u0026ndash;120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0-0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis study sought to explore the views and behaviors related to hygiene in both privileged and disadvantaged households within the Dhaka City Corporation region. There are notable differences in the accessibility, caliber, and practicality of services between privileged and underprivileged homes in the Dhaka City Corporation region when comparing Water, Sanitation, and Hygiene (WASH). Upon analysis, it has been observed that a bigger proportion of privileged households (94.2%) rely on better sources of drinking water compared to underprivileged households (82.8%). In contrast to earlier national data, such as MICS 2019, which reported 78.3% household access to upgraded water sources, and BBS 2022, which indicated 86.51% nationwide coverage, these numbers show an overall improvement. However, the underprivileged group continues to show a significant reliance (17.2%) on unimproved sources, suggesting a greater risk of waterborne illnesses and other health issues in these areas.\u003c/p\u003e \u003cp\u003eIn the DCC area, the gap between privileged and underprivileged households is noticeable when it comes to access to better water sources. In order to cook and wash their hands, 14% of underprivileged households still utilize outdated methods, which makes them more susceptible to diarrheal illnesses. Severe socioeconomic gaps are revealed by analyzing the availability of residential water sources. Compared to 78.8% of privileged families, just 17.2% of households in lower socioeconomic categories had improved water sources on their households. According to MICS 2019, the national urban average of 87.5% improved on-premises water sources is significantly higher than this number, highlighting long-standing structural disparities in access to convenient and safe water. Additionally, 19.2% of privileged households have to wait for 10 to 20 minutes, while 67.2% of underprivileged households have to do so. Furthermore, it was also seen that only 8 underprivileged households have water on premises compared to 394 privileged households.\u003c/p\u003e \u003cp\u003eUnfair gender and age dynamics are also reflected in the task of fetching water: in privileged households, 18.8% adult men and women perform this duty, while in underprivileged households, 23.4% of adult women, 32.8% of female children, and 26.6% of male children are responsible for fetching water for 10 to 20 minutes each day. This number shows a glaring disparity in infrastructure accessibility, which hurts the physical health and productivity of marginalized communities. It worsens gender disparities in the division of everyday labor in addition to endangering children's education and safety. Water treatment techniques also show a gap: 86.6% of privileged households treat their drinking water, whereas only 9.4% of underprivileged households do so. The MICS 2019 urban \"no water treatment\" percentage, on the other hand, was 68.6%. These results underline the critical need for fair access to water purifying facilities and awareness-raising campaigns.\u003c/p\u003e \u003cp\u003eIn the study area, 98% of privileged households reported using improved drinking water treatment methods, whereas all the underprivileged households relied on unimproved practices, indicating a substantial disparity between socio-economic groups. Sanitation conditions also revealed marked inequalities. All privileged households (100%) had access to upgraded toilet facilities, reflecting complete coverage of improved sanitation. In contrast, 31.2% of underprivileged households used unimproved toilets, and only 68.8% (344 out of 500) had access to improved facilities. These findings highlight systemic inequities in basic sanitation, with unimproved facilities concentrated exclusively among the underprivileged population.\u003c/p\u003e \u003cp\u003eThere is a significant gap in socioeconomic categories in the research area, as 98% of privileged homes reported using improved drinking water treatment procedures while the rest households depended on unimproved practices. Significant disparities were also found in the state of sanitation. All the privileged households (100%) have access to improved toilet facilities, demonstrating full coverage of improved sanitation (Nachaiwieng et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, only 68.8% of underprivileged households had access to upgraded facilities, and 31.2% of them utilized unimproved toilets. With unimproved facilities concentrated solely among the poor, these data demonstrate systematic disparities in basic sanitation (Dibaba et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInequality is also evident in the sharing of toilets, as 93.8% of underprivileged homes use shared unimproved facilities, compared to 27% of privileged households. This exposes underprivileged groups to poor upkeep, insufficient cleanliness, and restricted privacy in crowded urban environments. In Bangladesh and other LMICs, diarrhea continues to be a serious public health issue (Abdulhadi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). According to data from the Bangladesh Demographic Health Survey (BDHS), the prevalence of diarrhea in children under five was 5.7% in 2014, 4.7% in 2017, and 4.8% in 2022 (Rahman et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn order to protect children's health and stop the spread of diarrheal illnesses, it is imperative that children's stool be disposed of safely. Compared to just 12.6% of underprivileged households with improved handling techniques, 84.6% of privileged households reported better methods for handling their children's feces. A major public health risk is indicated by the startling finding that 87.4% of underprivileged households report unimproved handling behaviors. This disparity raises severe public health concerns since it most likely results from either a lack of awareness or poor facilities, or both (Nadal et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, the results show that Dhaka City Corporation's WASH service landscape is extremely stratified. While underprivileged households deal with long water-fetching periods, reliance on contaminated sources, gendered labor constraints, and inadequate purification procedures, privileged households enjoy simpler access to safe water (Arnold and Ante-Testard, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Targeted WASH interventions, infrastructure upgrades, behavioral change initiatives, and fair resource distribution are all necessary to address these disparities.\u003c/p\u003e \u003cp\u003eThe study exclusively focuses on households in the Dhaka City Corporation, which limits its applicability to other Dhaka metropolitan areas or Bangladeshi urban locations where WASH circumstances can vary.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents a heatmap illustrating the correlation between various variables, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and economic conditions in the context of WASH (Water, Sanitation, and Hygiene) amenities. The heatmap compares two categories, labeled \"P\" (privileged) and \"UP\" (underprivileged), across each variable. The variables are organized in rows, with the first column identifying the variables under the conditions of improved WASH (IWA) and unimproved WASH (UIWA). The correlation values range from 0 to 1, with the color gradient representing varying degrees of correlation, from lighter to darker shades of blue.\u003c/p\u003e \u003cp\u003eVariables such as V1, V2, and V5 exhibit stronger correlations with economic conditions, particularly in the \"P\" category. In contrast, variables like V4 and V7 show divergent patterns across the \"P\" and \"UP\" categories, with lower correlations observed in some instances. The color scale on the right denotes the strength of these correlations, where darker blue shades correspond to stronger correlations closer to 1, and lighter shades indicate weaker correlations closer to 0.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe study quantifies significant disparities in WASH access between privileged and underprivileged households in Dhaka, revealing stark inequalities in drinking water, sanitation, and hygiene facilities. Specifically, 98.08% of privileged households have access to improved drinking water sources, whereas only 82.82% of underprivileged households enjoy the same. In terms of sanitation, 100% of privileged households have access to improved facilities, compared to 68.75% of underprivileged households. Water treatment practices also differ significantly, with 75% of privileged households treating their drinking water, in contrast to just 9.4% of underprivileged households. Additionally, the study reveals that 32.8% of female children and 26.6% of male children in underprivileged households are tasked with fetching water, significantly increasing their daily workload.\u003c/p\u003e \u003cp\u003eFurthermore, the relationship matrix in this study highlights the correlations between WASH access and economic conditions across both privileged (P) and underprivileged (UP) groups. Key variables such as access to improved drinking water, sanitation facilities, and water treatment practices show stronger correlations with economic conditions, particularly in the privileged group. The matrix reveals that variables like the source of drinking water, the presence of water at the premises, and the treatment of drinking water demonstrate significant disparities between the two groups, where privileged households exhibit a higher degree of access to improved WASH amenities.\u003c/p\u003e \u003cp\u003eThe results presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e further reinforce these disparities by showcasing statistically significant associations between socio-economic status and WASH access. The chi-square tests for variables such as the source of drinking water, the time required to fetch water, the presence of water on premises, and the use of improved sanitation facilities all demonstrate strong associations with socio-economic conditions. For example, 471 privileged households used improved drinking water sources compared to just 414 underprivileged households, and 394 privileged households had water on-premises, compared to only 8 underprivileged households. Additionally, the duration to fetch water varied significantly between the two groups, with 67.2% of underprivileged households spending over 30 minutes fetching water, compared to just 1.92% of privileged households.\u003c/p\u003e \u003cp\u003eThese findings highlight the intersectionality of socio-economic status and access to essential services, particularly emphasizing that underprivileged groups face compounded barriers that exacerbate their vulnerabilities to waterborne diseases and poor sanitation. The disparities in WASH access, as captured in both the relationship matrix and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, underscore the urgent need for targeted interventions, infrastructure upgrades, and gender-sensitive policies to address the systemic inequalities in Dhaka's urban WASH landscape.\u003c/p\u003e \u003cp\u003eAddressing these gaps is critical to improving public health outcomes, particularly in marginalized communities, and achieving the targets of SDG 6. It is essential for policymakers and stakeholders to prioritize equitable access to WASH services, with a focus on reducing the time burden on underprivileged households, improving sanitation infrastructure, and ensuring safe water treatment practices across all socio-economic strata.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors wish to acknowledge Taimur Rahman (Department of Civil Engineering, World University of Bangladesh) for his assistance in reviewing the manuscript, comments, suggestions, and English proofreading.\u003c/p\u003e\n\u003cp\u003eAuthors Contributions\u003c/p\u003e\n\u003cp\u003eConceptualization: Abdur Razzak Zubaer\u003c/p\u003e\n\u003cp\u003eData curation: Maisha Maliyat Aronna and Shakib Hossain Khan\u003c/p\u003e\n\u003cp\u003eMethodology: Abdur Razzak Zubaer\u003c/p\u003e\n\u003cp\u003eInvestigation: Maliha Farheen\u003c/p\u003e\n\u003cp\u003eFormal Analysis: Abdur Razzak Zubaer, Rahmot Al Jamy, and Tasnim Era\u003c/p\u003e\n\u003cp\u003eProject administration: Abdur Razzak Zubaer\u003c/p\u003e\n\u003cp\u003eVisualization: Ikramul Islam\u003c/p\u003e\n\u003cp\u003eWriting- original draft: Abdur Razzak Zubaer\u003c/p\u003e\n\u003cp\u003eWriting- review \u0026amp; editing: Maliyat Aronna, Ikramul Islam, and Shakib Hossain Khan\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study is not supported financially by any institutions or organizations.\u003c/p\u003e\n\u003cp\u003eData Availability Statement\u003c/p\u003e\n\u003cp\u003eThe dataset supporting this study is not publicly available due to its use in ongoing research, but may be obtained from the corresponding author upon reasonable request, subject to confidentiality considerations.\u003c/p\u003e\n\u003cp\u003eClinical Trial Number\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003eEthics Statement and Accordance\u003c/p\u003e\n\u003cp\u003eNot applicable. All data collection procedures and the collected data were reviewed by the Review Board of the Department of Civil Engineering, World University of Bangladesh, which decided to waive ethical approval, as the study did not involve experiments on human participants or live vertebrates, and no human biological material was used. Data (monthly income, sources of usable water, and sanitation facilities) were collected at the household level without recording any personally identifiable information, and participation was voluntary, in accordance with ethical principles and the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eConsent to Participate\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study prior to their participation. Participants were adequately informed about the study objectives, procedures, and the voluntary nature of their involvement.\u003c/p\u003e\n\u003cp\u003eConsent to Publish\u003c/p\u003e\n\u003cp\u003eVerbal consent to participate and consent to publish were obtained from all participants prior to participation. No participants under the age of 18 were involved in the study. All participants agreed to the publication of the study results in accordance with applicable ethical standards.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbdulhadi, R., Bailey, A., Van Noorloos, F., 2024. Access inequalities to WASH and housing in slums in low- and middle-income countries (LMICs): A scoping review. Global Public Health 19, 2369099. https://doi.org/10.1080/17441692.2024.2369099\u003c/li\u003e\n \u003cli\u003eAhmed, M.S., Islam, M.I., Das, M.C., Khan, A., Yunus, F.M., 2021. Mapping and situation analysis of basic WASH facilities at households in Bangladesh: Evidence from a nationally representative survey. PLOS ONE 16, e0259635. https://doi.org/10.1371/journal.pone.0259635\u003c/li\u003e\n \u003cli\u003eAlam, A., Prodhan, Md.E., Islam, F., Hasan, M.N., Chowdhury, M.A.B., Uddin, M.J., 2025. The effects of household water, sanitation, and hygiene on early childhood education enrollment: evidence from the 2022 Bangladesh demographic and health survey. BMC Public Health 25, 2732. https://doi.org/10.1186/s12889-025-23968-7\u003c/li\u003e\n \u003cli\u003eAlam, Md.Z., Sheoti, I.H., 2024a. Ethnicity and access to water, sanitation, and hygiene in Bangladesh: a study using MICS data and policy reviews. BMC Public Health 24, 2726. https://doi.org/10.1186/s12889-024-20250-0\u003c/li\u003e\n \u003cli\u003eAlam, Md.Z., Sheoti, I.H., 2024b. Ethnicity and access to water, sanitation, and hygiene in Bangladesh: a study using MICS data and policy reviews. BMC Public Health 24, 2726. https://doi.org/10.1186/s12889-024-20250-0\u003c/li\u003e\n \u003cli\u003eArnold, B., Ante-Testard, P.A., 2024. WASH interventions and child diarrhea at the interface of climate and socioeconomic position in Bangladesh. https://doi.org/10.17605/OSF.IO/XWNDG\u003c/li\u003e\n \u003cli\u003eBangladesh Bureau of Statistics (BBS), UNICEF Bangladesh, n.d. Progotir Pathey, Bangladesh Multiple Indicator Cluster Survey 2019, Survey Findings Report.\u003c/li\u003e\n \u003cli\u003eBick, S., Davies, K., Mwenge, M., MacLeod, C., Braun, L., Chipungu, J., Chidziwisano, K., Dreibelbis, R., 2025. WASH and learn: a scoping review of health, education and gender equity outcomes of school-based water, sanitation and hygiene in low-income and middle-income countries. BMJ Glob Health 10, e018059. https://doi.org/10.1136/bmjgh-2024-018059\u003c/li\u003e\n \u003cli\u003eC.J. Murray, A.Y. Aravkin, P. Zheng, C. Abbafati, K.M. Abbas, M. Abbasi-Kangevari, F. Abd-Allah, A. Abdelalim, M. Abdollahi, I. Abdollahpour, K.H. Abegaz, n.d. Global burden of 87 risk factors in 204 countries and territories, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019.\u003c/li\u003e\n \u003cli\u003eDibaba, D.B., Alemu, B.M., Debela, S.A., 2024. Impact of water, sanitation, and hygiene (WASH) interventions on gender-specific school attendance and learning outcomes: A systematic review and meta-analysis protocol. PLoS ONE 19, e0308144. https://doi.org/10.1371/journal.pone.0308144\u003c/li\u003e\n \u003cli\u003eDickin, S., Siddique, S., Liera, C., Dupont, G., Bisung, E., 2025. Assessing the importance of gender transformative WASH: evidence from a gender-mainstreamed WASH programme in Bangladesh. International Journal of Water Resources Development 41, 789\u0026ndash;811. https://doi.org/10.1080/07900627.2025.2505867\u003c/li\u003e\n \u003cli\u003eEzbakhe, F., Gin\u0026eacute;-Garriga, R., P\u0026eacute;rez-Foguet, A., 2019. Leaving no one behind: Evaluating access to water, sanitation and hygiene for vulnerable and marginalized groups. Science of The Total Environment 683, 537\u0026ndash;546. https://doi.org/10.1016/j.scitotenv.2019.05.207\u003c/li\u003e\n \u003cli\u003eFarzana, F.D., Hossain, D., Rahman, M., Nahar, Q., Arifeen, S.E., Ahmed, T., Mahfuz, M., 2024. Understanding water, sanitation, and hygiene situation through participatory appraisal in urban slum of Dhaka City. EUR J ENV PUBLIC HLT 8, em0165. https://doi.org/10.29333/ejeph/15585\u003c/li\u003e\n \u003cli\u003eGaspari, L., Giuliani, M., 2025. The Co‐Optation of Gender Equity Issues in Empirical Business Research: A Systematic Literature Review. Business Ethics Env \u0026amp; Resp beer.12844. https://doi.org/10.1111/beer.12844\u003c/li\u003e\n \u003cli\u003eHaque, M., 2019. Urban Water Governance: Pricing of Water for the Slum Dwellers of Dhaka Metropolis: Methods, Approaches and Practices. pp. 385\u0026ndash;397. https://doi.org/10.1007/978-981-10-8947-3_22\u003c/li\u003e\n \u003cli\u003eHaque, S.S., Yanez-Pagans, M., Arias-Granada, Y., Joseph, G., 2020. Water and sanitation in Dhaka slums: access, quality, and informality in service provision. Water International 45, 791\u0026ndash;811. https://doi.org/10.1080/02508060.2020.1786878\u003c/li\u003e\n \u003cli\u003eHasan, Md.K., Shahriar, A., Jim, K.U., 2019. Water pollution in Bangladesh and its impact on public health. Heliyon 5, e02145. https://doi.org/10.1016/j.heliyon.2019.e02145\u003c/li\u003e\n \u003cli\u003eHusain, Z., Das, P., 2023. Reducing child diarrhoea in India: Shifting policy focus from source of water to quality. Water Resources and Economics 42, 100221. https://doi.org/10.1016/j.wre.2023.100221\u003c/li\u003e\n \u003cli\u003eJahan, F., Shuchi, N.S., Yeamin, A., Sen, T., Shoab, A.K., Alam, M.-U., Sarker, S., Mahfuz, M.T., Hasan, M., Jahan, H., Islam, K., Alam, Md.M., Rahman, M., 2025. Improving WASH facilities and practices in Bangladeshi schools: progress and challenges from 2014 to 2018. Global Health Action 18, 2466896. https://doi.org/10.1080/16549716.2025.2466896\u003c/li\u003e\n \u003cli\u003eMarphatia, A.A., Simiyu, S., Flint O\u0026rsquo;Kane, M., Alexander, K.T., Nascimento De Castro, A.C.A., Azcona, G., Boni-Morkla, P.E., Bukachi, S.A., Busienei, P., Caruso, B.A., Chase, C., Chipungu, J., Dwivedi, A., Johnston, R., Khurana, I., Kome, A., Kuria, W., Labadia, J., Makoni, F., Mberu, B., Mojumdar, S., Mule, J., Namatende Sakwa, L., Njeri, N., Oliveira De Souza, F.A., Pandolfelli, L., Ramunenyiwa, P., Ray, I., Reddy, M., Saha, P.K., Sinha, U., Sinharoy, S.S., Slaymaker, T., Uguru, E., Uhl, K., Young, S.L., Ross, I., Cumming, O., 2025. Gender equality and quality of life must be central to the design and delivery of sanitation. BMJ Glob Health 10, e018238. https://doi.org/10.1136/bmjgh-2024-018238\u003c/li\u003e\n \u003cli\u003eNabi, M.H., Rupa, F.H., Jahan, I., Hasan, A.B.M.N., Naz, F., Masud, I., Hawlader, M.D.H., Hossian, M., 2025. Water, sanitation, and hygiene (WASH) factors and the incidence of communicable diseases in Urban Bangladesh: Evidence from municipal areas. PLoS Negl Trop Dis 19, e0013329. https://doi.org/10.1371/journal.pntd.0013329\u003c/li\u003e\n \u003cli\u003eNachaiwieng, W., Sanit, S., Kongta, N., Saingamsook, J., Duangmano, S., Pornprasert, S., Somboon, P., Yanola, J., 2024. The impact of an integrated intervention program combining drug therapy with water, sanitation, and hygiene (WASH) education on reinfection with intestinal parasitic infections among the Karen hill tribe in northern Thailand. Parasites Vectors 17, 544. https://doi.org/10.1186/s13071-024-06611-z\u003c/li\u003e\n \u003cli\u003eNadal, L., Delaire, C., Yachori, B., Khush, R., Bauza, V., 2025. Gender disparities in water-related knowledge, perceptions, and governance in rural Ghana: insights from a qualitative study augmented by Natural Language Processing. Social Science \u0026amp; Medicine 382, 118338. https://doi.org/10.1016/j.socscimed.2025.118338\u003c/li\u003e\n \u003cli\u003ePr\u0026uuml;ss-\u0026Uuml;st\u0026uuml;n, A., Bos, R., Gore, F., Bartram, J., 2008. Safer water, better health: costs, benefits and sustainability of interventions to protect and promote health. WHO.\u003c/li\u003e\n \u003cli\u003ePr\u0026uuml;ss-Ust\u0026uuml;n, A., Wolf, J., Bartram, J., Clasen, T., Cumming, O., Freeman, M.C., Gordon, B., Hunter, P.R., Medlicott, K., Johnston, R., 2019. Burden of disease from inadequate water, sanitation and hygiene for selected adverse health outcomes: An updated analysis with a focus on low- and middle-income countries. Int J Hyg Environ Health 222, 765\u0026ndash;777. https://doi.org/10.1016/j.ijheh.2019.05.004\u003c/li\u003e\n \u003cli\u003eRahaman, M., Ahmed, T., 2016. Affordable Water Pricing for Slums Dwellers in Dhaka Metropolitan Area: The Case of Three Slums. Journal of Water Resource Engineering and Management 3, 15\u0026ndash;33.\u003c/li\u003e\n \u003cli\u003eRahaman, M.M., Galib, A.I., Azmi, F., 2021. Achieving drinking water and sanitation related targets of SDG 6 at Shahidbug slum, Dhaka. Water International 46, 462\u0026ndash;476. https://doi.org/10.1080/02508060.2021.1901189\u003c/li\u003e\n \u003cli\u003eRahman, A.M.R., Islam, M.R., Bashar, S.J., Al Fidah, M.F., Amin, R., Rahman, M.M., Faruque, A., Chisti, M.J., Ahmed, T., Nuzhat, S., 2025. Trends in preventive practices against diarrhoeal disease among under-five children: experience from the largest diarrhoeal disease hospital in Bangladesh. bmjpo 9, e003259. https://doi.org/10.1136/bmjpo-2024-003259\u003c/li\u003e\n \u003cli\u003eRahman, M., Ali, M., Choudhury, M., Rahman, M., Ahmed, A., Soneji, S.V., Akhter, M.B., Syafitri, S., Das, S., 2014. WASH Challenges in Slum Areas of Dhaka City.\u003c/li\u003e\n \u003cli\u003eRahman, T., Momin, Md.F., Provasha, A.A., 2025a. Comprehensive analysis of structural parameters influencing the fundamental period of steel-braced RC buildings using machine learning interpretability. AI Civ. Eng. 4, 7. https://doi.org/10.1007/s43503-025-00051-z\u003c/li\u003e\n \u003cli\u003eRahman, T., Momin, Md.F., Provasha, A.A., 2025b. Comprehensive analysis of structural parameters influencing the fundamental period of steel-braced RC buildings using machine learning interpretability. AI Civ. \u0026nbsp;Eng. 4, 7. https://doi.org/10.1007/s43503-025-00051-z\u003c/li\u003e\n \u003cli\u003eSin, M.P., Hasan, M.Z., Forsberg, B.C., 2023. Change in economic burden of diarrhoea in children under-five in Bangladesh: 2007 vs. 2018. J Glob Health 13, 04089. https://doi.org/10.7189/jogh.13.04089\u003c/li\u003e\n \u003cli\u003eTalukdar, P.K., Rahman, Mizanur, Rahman, Mahdia, Nabi, A., Islam, Z., Hoque, M.M., Endtz, H.P., Islam, M.A., 2013. Antimicrobial resistance, virulence factors and genetic diversity of Escherichia coli isolates from household water supply in Dhaka, Bangladesh. PLoS One 8, e61090. https://doi.org/10.1371/journal.pone.0061090\u003c/li\u003e\n \u003cli\u003eUnited Nations, 2019. UN-Water Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS) 2019 report.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization, 2022. WHO Global Water, Sanitation and Hygiene: Annual Report 2021. World Health Organization.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization (Ed.), 2017. Financing universal water, sanitation and hygiene under the sustainable development goals: UN-water global analysis and assessment of sanitation and drinking-water, GLAAS ... Report. Geneva.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization and United Nations Children\u0026rsquo;s Fund, n.d. Progress on household drinking water, sanitation and hygiene 2000‒2017: Special focus on inequalities.\u003c/li\u003e\n \u003cli\u003eZubaer, A., 2023. Evaluation of Bangladesh\u0026rsquo;s SDG6 achievement: A review 6, 7\u0026ndash;15. https://doi.org/10.5281/zenodo.7627649\u003c/li\u003e\n \u003cli\u003eZubaer, A.R., 2023. An Analysis of the Quality of Dhaka\u0026rsquo;s Potable Water and Sanitation Services. Journal of Environmental Issues and Climate Change 2, 12\u0026ndash;19. https://doi.org/10.59110/jeicc.v2i1.134\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Urban WASH inequality, Socio-economic disparities, Gendered water access, Sanitation and hygiene, Public health risk, Sustainable Development Goal 6","lastPublishedDoi":"10.21203/rs.3.rs-8515390/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8515390/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRapid urbanization in low- and middle-income countries has intensified inequities in access to safe water, sanitation, and hygiene (WASH), posing persistent public health and social justice challenges. Although Bangladesh has achieved notable national progress, substantial intra-urban disparities persist within Dhaka, particularly among socio-economically marginalized populations. This study examines the extent, determinants, and gendered dimensions of urban WASH inequality to inform equitable policy and infrastructure interventions.\u003c/p\u003e \u003cp\u003eA two-stage stratified random household survey was conducted across the Dhaka City Corporation, yielding a weighted sample of 1,000 households. Key WASH indicators, including drinking water sources, water availability on premises, treatment practices, sanitation facilities, sharing behavior, and child feces management, were analyzed against socio-economic and gender variables. Analytical methods included chi-square tests, multivariate logistic regression, and machine-learning-based relationship matrices validated using SHAP sensitivity analysis.\u003c/p\u003e \u003cp\u003eResults reveal stark disparities between privileged and underprivileged households. Improved drinking water access was reported by 98.1% of privileged households compared to 82.8% of underprivileged households, while improved sanitation coverage was universal among privileged groups but limited to 68.8% among underprivileged ones. Only 9.4% of underprivileged households treated drinking water, compared to 75% of privileged households. Water collection burdens were highly gendered, with 32.8% of female children and 26.6% of male children in underprivileged households responsible for fetching water, often exceeding 30 minutes per trip. Underprivileged households were also disproportionately dependent on shared sanitation facilities (93.8%) and unsafe child feces disposal practices (87.4%).\u003c/p\u003e \u003cp\u003eAll major WASH indicators were significantly associated with socio-economic status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), demonstrating that economic disadvantage systematically amplifies health, gender, and infrastructural vulnerabilities. These findings provide actionable evidence for policymakers, urban planners, water utilities, public health agencies, and development partners working to advance SDG 6 and reduce urban inequality.\u003c/p\u003e","manuscriptTitle":"Socioeconomic and Gender Inequalities in Urban Water, Sanitation, and Hygiene Access: Evidence from Dhaka, Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 17:37:59","doi":"10.21203/rs.3.rs-8515390/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-14T17:11:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-04T06:19:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-02T16:25:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T03:37:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255876253400238271879353340621007055133","date":"2026-02-23T03:27:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-19T22:21:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"249638950126948231610915992335293441996","date":"2026-02-19T18:02:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197226201599542501290508506037945202011","date":"2026-02-19T16:10:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"304135849820078144078015681132671512324","date":"2026-02-17T23:46:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"151706520797468796252739301138856071246","date":"2026-02-17T11:59:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-17T11:44:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-08T16:27:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-05T10:55:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-02-05T10:12:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5b1dcd26-991c-4167-b414-a98253489ac3","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T11:53:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 17:37:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8515390","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8515390","identity":"rs-8515390","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}