Household Food Safety, WASH and Environmental Health Practices in the Context of Nutrition-Sensitive Agriculture: A Comparative Study in Northwest Ethiopia

Household Food Safety, WASH and Environmental Health Practices in the Context of Nutrition-Sensitive Agriculture: A Comparative Study in Northwest Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Household Food Safety, WASH and Environmental Health Practices in the Context of Nutrition-Sensitive Agriculture: A Comparative Study in Northwest Ethiopia Zenaw Merie, Nigatu Regassa, Mogessie Ashenafi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8831449/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Background Household food safety and Water, Sanitation, and Hygiene (WASH) are critical determinants of nutritional status and the prevention of infectious diseases. This study provides an integrated assessment of food safety, WASH, and environmental health practices among beneficiaries of the Productive Safety Net Programme (PSNP) and Nutrition-Sensitive Agriculture (NSA) interventions in rural Ethiopia. Methods A cross-sectional survey was conducted among 586 households in the Ebinat and Farta woredas of Northwest Ethiopia, stratified by intervention status. Data were collected using structured questionnaires. Composite indices were constructed using mean values and Bloom’s cut‑off criteria to classify knowledge and practices related to food safety, hygiene, and sanitation; WASH adequacy; and environmental health. Binary logistic regression identified predictors of food safety, WASH adequacy, and environmental health conditions. Results Food safety was the weakest domain; 74.2% of households engaged in poor practices, and only 9.0% achieved a “good” rating. A notable knowledge–practice gap was observed in hygiene, where 26.6% had good knowledge but only 12.5% practiced well. In contrast, 59.2% reported adequate WASH conditions, with a peak of 73.5% among PSNP + NSA participants. Regression analysis showed that food safety was primarily influenced by paternal literacy, prior awareness, and socioeconomic status, while program participation and wealth were the strongest predictors of WASH adequacy. Maternal literacy and program support significantly improved environmental health practices. Conclusion Integrated programs have strengthened WASH infrastructure but remain less effective at shifting entrenched food‑handling behaviors. Achieving sustainable health outcomes will require culturally tailored interventions, greater investment in parental literacy, and the integration of practical hygiene demonstrations into multisectoral platforms. Together, these strategies can bridge the knowledge–practice gap and enhance the long‑term effectiveness of nutrition‑sensitive initiatives. Food safety WASH Environmental health Productive Safety Net Programme Nutrition‑Sensitive Agriculture Ethiopia Figures Figure 1 Background Food safety and Water, Sanitation, and Hygiene (WASH) are foundational pillars of public health and nutritional security. In low-resource settings, the convergence of contaminated food and inadequate hygiene creates a self-reinforcing cycle of enteric disease and malnutrition. This cycle disproportionately affects vulnerable populations, particularly infants and the elderly. Globally, the World Health Organization (2022) estimates that foodborne pathogens cause 600 million illnesses and 420,000 deaths annually, resulting in 33 million disability-adjusted life years (DALYs) lost ( 1 ). Children under five bear 40% of this burden, accounting for approximately 125,000 deaths per year. Consequently, food safety is a prerequisite for food security; as noted by the FAO, compromised safety undermines nutrient absorption, stalls socioeconomic development, and overburdens national healthcare systems ( 2 ). Regionally, Sub-Saharan Africa faces acute challenges in accessing potable water and sanitation. Estimates suggest that over two-thirds of households in the region lack improved sanitation, a primary driver of diarrheal diseases, cholera, typhoid, and parasitic infections ( 3 ). In Ethiopia, diarrheal diseases remain among the leading five causes of disability‑adjusted life years (DALYs), primarily driven by unsafe water, inadequate sanitation, and child undernutrition ( 4 ). Despite sustained policy attention, critical infrastructure gaps persist: only about 30% of rural households have access to safe drinking water, and fewer than 7% use improved sanitation facilities ( 5 ). National Joint Monitoring Programme (JMP) data further underscore these deficits, indicating that just 13% of households benefit from safely managed drinking water and only 8% have access to handwashing facilities with soap and water ( 6 ). To address these multifaceted challenges, the Ethiopian government has prioritized multisectoral frameworks. The Productive Safety Net Programme (PSNP) has evolved from a purely social protection mechanism into a nutrition-sensitive model that integrates asset transfers with WASH infrastructure ( 7 ). In parallel, the National Nutrition-Sensitive Agriculture (NSA) strategy emphasizes diversifying production and improving post-harvest handling to mitigate contamination risks. These initiatives are anchored by the Seqota Declaration (SD), Ethiopia’s flagship commitment to eradicating child undernutrition by 2030 through the integration of the health, agriculture, and WASH sectors. While implementation sites such as Ebinat Woreda demonstrate the potential of these coordinated efforts ( 8 ), emerging evidence suggests that aligning WASH infrastructure with nutrition programming is essential for improving child growth outcomes ( 9 , 10 ). Despite Ethiopia’s robust policy landscape, a significant gap remains in the literature. Existing research has largely evaluated the PSNP, NSA, and SD in isolation, typically focusing on either food security or WASH indicators while neglecting their synergistic effects at the household level. Furthermore, empirical data on the practical barriers to integrated delivery—such as institutional capacity constraints and climate variability—remain scarce. This study addresses these deficiencies by systematically examining the intersection of these three frameworks in rural Ethiopia. By evaluating their collective efficacy, this research provides novel insights into the potential of multisectoral approaches to simultaneously enhance food security and WASH outcomes, ultimately informing more coherent national policy and implementation strategies. Methods Study Setting The study was conducted in two neighboring woredas in the Amhara Region of Northwest Ethiopia, both characterized by subsistence farming and recurrent food insecurity. Ebinat, the intervention site, is one of forty woredas selected for the Seqota Declaration Innovation Phase. Located approximately 714 km northwest of Addis Ababa at elevations of 1,730 to 2,500 meters, Ebinat benefits from the integrated Productive Safety Net Program and the Seqota Declaration’s Nutrition-Sensitive Agriculture interventions. Farta woreda, located 660 km from the capital at elevations of 1,920 to 4,135 meters, served as the control site because of its comparable socioeconomic and environmental profile, despite lacking the specific integrated intervention package. Data Source and Study Design A cross-sectional mixed-methods design was used to evaluate the impact of these integrated interventions. Data collection took place over a two-week period from late November to early December 2022. The study used a concurrent design, triangulating quantitative household surveys with qualitative key-informant interviews to provide a comprehensive assessment of the intervention landscape. The target population consisted of mothers or primary caregivers and their children aged 6 to 23 months. Sampling Strategy A two-stage cluster sampling design ensured representativeness across the study area. Initially, 30% of kebeles in each woreda were selected, followed by a proportional draw of eligible households from each selected sub-district. The required sample size was determined using a standard cluster sampling formula with a 95% confidence level, a conservative prevalence estimate of 50%, a 5% margin of error, and a 10% non-response adjustment. To account for the clustered study design, the calculation incorporated a design effect of 1.45, yielding a total sample of 586 respondents, evenly distributed between the two woredas. The final cohort included 184 households receiving nutrition-sensitive agriculture support, 109 non-beneficiary households within the intervention woreda, and 293 households from the non-supported woreda. $$\:n=\frac{{z}^{2}p\left(1-p\right)fk}{{e}^{2}}=\:\frac{{z}^{2}p\left(1-p\right)[1+\rho\:\left(m-1\right)]k}{{e}^{2}}$$ Where Z is the standard normal deviate at 95% confidence (1.96), e is the margin of error (0.05), k is the non-response adjustment factor (1.1), and the design effect (1.45) is derived from an intra-class correlation coefficient (ρ) of 0.05 and an average cluster size (m) of 10. This calculation yielded a total required sample of 586 respondents, evenly divided between the two woredas (n = 293 each). The final sample included 184 households receiving NSA support (49 of whom also received PSNP), 109 non-beneficiary households within the intervention woreda (negative control), and 293 households from the non-supported woreda (positive control). Data Collection and Variables Data were collected using structured interviewer-administered questionnaires with child care takers and semi-structured interview guides with key informants. The quantitative instruments were adapted from standardized global frameworks to ensure validity and comparability. Water, sanitation, and hygiene (WASH) indicators were derived from the WHO/UNICEF Joint Monitoring Programme (JMP) core questions ( 6 ), and food safety practices were assessed using the FAO guideline ( 12 ). To ensure cultural and programmatic relevance, specific items were contextualized using instruments from the Ethiopia Demographic and Health Survey ( 13 ). Qualitative data were collected through key informant interviews with community leaders, health extension workers, and agricultural agents to triangulate quantitative findings and explore perceptions of intervention effectiveness. Ten trained data collectors and one supervisor conducted interviews. Data quality was ensured through pretesting, intensive training, daily supervision, and consistency checks. Reliability testing showed acceptable internal consistency (Cronbach’s alpha > 0.70) and good test–retest stability, with intraclass correlation coefficients above 0.75. For categorical items, Cohen’s kappa values indicated substantial agreement. These measures collectively enhanced the reliability and validity of the study findings. Measurement of Variables Outcome variables Food Safety Practices. Household food safety knowledge and practices were evaluated using a composite index developed in accordance with FAO guidelines. The index aggregated nine binary-coded items (0 = not practiced, 1 = practiced) across domains such as food storage, preparation, cooking, and contamination prevention, yielding a cumulative score ranging from 0 to 9. For regression analysis, this composite score was dichotomized into two categories: households with adequate food safety practices (scores ≥ 5) were coded as 1, and those with inadequate practices (scores < 5) were coded as 0. This binary variable served as the dependent outcome in logistic regression models to examine associations with household characteristics and WASH conditions. Because no universally established threshold exists for food safety practices, we applied a mean-score cutoff, consistent with methodological recommendations in food safety KAP research. Households scoring at or above the sample mean were classified as having good practices, while those scoring below the mean were classified as poor. For descriptive reporting, both mean-based cut‑offs and continuous scores were used to capture context-specific variability in behaviors, whereas for inferential analyses, the dichotomized variable was retained to assess associations with socio-demographic and program-related factors ( 14 ). Household WASH Practices . WASH status was assessed using the Joint Monitoring Programme (JMP) service ladder approach, which classifies households by access to basic drinking water, sanitation, and hygiene services. Composite KAP indices for WASH were constructed using indicators of access to water supply, sanitation facilities, and hygiene practices. Access to water supply was coded as improved ( 1 ) or unimproved (0), and sanitation facilities were coded similarly as improved ( 1 ) or unimproved (0). Hygiene was assessed through knowledge of handwashing at critical times (yes = 1, no = 0) and the availability of a functional handwashing facility (yes = 1, no = 0). Attitudinal measures captured perceptions of the importance of hygiene and sanitation, and practice indicators included actual use of improved water sources and safe waste disposal methods. Each indicator was dichotomized, with correct/positive responses coded as 1 and incorrect/negative responses coded as 0. Composite scores were generated by summing across indicators within each domain. Final classifications followed Bloom’s cutoff criteria: ≥80% of the maximum score was categorized as “good,” 60–79% as “moderate,” and < 60% as “poor” for descriptive reporting, consistent with recent applications in WASH and nutrition KAP studies ( 15 ). For inferential analyses, mean-based scores were used to explore associations with socio-demographic and program-related factors. Household Environment Indicators . Food contamination risk was proxied by environmental conditions, including the presence of animals in food preparation areas and household waste disposal methods ( 16 ). Explanatory variables were stratified into four categories: ( 1 ) socioeconomic factors (wealth status, land size, parental education, occupation, and program participation); ( 2 ) individual characteristics (caregiver age, education, and health literacy); and ( 3 ) household factors (number of children, household size, and household headship). These variables were selected based on prior literature on food security, nutrition-sensitive agriculture, and WASH outcomes in Ethiopia and sub-Saharan Africa, which consistently identifies socioeconomic status, caregiver education, household composition, and child demographics as key determinants of food safety and nutrition ( 9 , 6 ). In addition, program participation variables were included to reflect Ethiopia’s policy context and capture the influence of large-scale interventions such as PSNP and the SD. The wealth index was constructed using Principal Component Analysis (PCA) of asset ownership and housing characteristics, with households categorized into poor, middle, and rich tertiles. Statistical Analysis Data were analyzed using multivariable binary logistic regression to identify predictors of three primary outcomes: household food safety, WASH, and environmental health conditions. Variables associated with the outcome at a p-value less than 0.25 in bivariate analysis were included in the final models. Model robustness was assessed using the Hosmer–Lemeshow test for goodness-of-fit and Variance Inflation Factors to assess multicollinearity. Statistical significance was defined as a p-value less than 0.05, and results were reported as Adjusted Odds Ratios. Qualitative data from key informant interviews with community leaders and health extension workers were analyzed thematically to complement and provide contextual depth to the quantitative results. Results Socio-Demographic Characteristics and Study Stratification The socio-demographic profile of the 586 households across Ebinat and Farta woredas highlights a predominantly male-headed, agrarian community with distinct variations in family structure and literacy across program beneficiary groups (Table 1 ). To evaluate the impact of multisectoral programming, the study used a stratified sampling design. In Ebinat Woreda—the primary intervention site—184 households received Nutrition-Sensitive Agriculture (NSA) support under the Seqota Declaration, and a subgroup of 49 households was identified as dual beneficiaries of both NSA and the Productive Safety Net Program (PSNP). This dual-beneficiary group represents the most vulnerable segment of the sample, characterized by chronic food insecurity and high dependence on social protection mechanisms. Localized and external control groups were established by including 109 non-beneficiary households from Ebinat and 293 households from Farta Woreda, the latter serving as a comparison site because of its higher agricultural productivity and proximity to administrative centers. The demographic disparities observed across these groups confirm that national programs effectively target the most vulnerable populations. Male-headed households constitute 90.8% of the total population, while female-headed households are most prevalent among the dual PSNP + NSA-supported group (14.3%). Maternal age is concentrated in the 20–30 age range, though the PSNP + NSA cohort includes a higher proportion of mothers aged 31–45. Household density is notably high; while 44.2% of households have 2–4 members, the majority (55.8%) have five or more members. This trend toward large household size is most pronounced in the PSNP + NSA group, where 71.4% of households exceed four members (p = 0.015), underscoring the concentrated nature of vulnerability among dual-support beneficiaries. Child demographics and educational status further illustrate these socioeconomic barriers. Index children are fairly evenly distributed by sex, with over half aged 11–23 months. However, the PSNP + NSA group shows a distinct pattern, with 55.1% of children aged 0–5 months, suggesting high engagement with infant-targeted health and nutrition services. Regarding educational attainment, a clear "literacy gap" exists, particularly among mothers; 55.5% of the total maternal population cannot read or write, a figure that rises sharply to over 83% in the PSNP + NSA group. While fathers generally exhibit higher literacy, with 64.3% having at least a primary education, the overall low level of maternal education remains a critical factor, as it is a primary predictor of household food safety and environmental health practices. Table 1 Socio-Demographic Characteristics in Ebinat and Farta Woredas, 2023, n = 586 Variable Household No (%) Total (586) Ebinat (293) Farta (293) Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) NSA supported (n = 135) Non-supported (n = 293) Household Headship 100 (91.7) 9 (8.3) 42 (85.7) 7 (14.3) 123 (91.1) 12 (8.9) 267 (91.1) 26(8.9) 532 (90.8) 54 (9.2) Male-headed Female-headed Mother’s Age (Years) 17(15.6) 68(62.4) 24(22.0) 2(4.1) 25(51.0) 22(44.9) 11(8.1) 82(30.7) 42(31.3) 31(10.6) 162(55.4) 100(34.2) 61(10.4) 337(57.5) 188(32.1) < 20 20–30 31–45 Sex of the index Child 49 (45.0) 60 (55.0) 30 (61.2) 19 (38.8) 59 (43.7) 76 (56.3) 128 (43.7) 165 (56.3) 266 (45.4) 320 (54.6) Male Female Age of the Child (Mo) 32 (29.4) 35 (32.1) 42 (38.5) 27 (55.1) 5 (10.2) 17 (34.7) 30 (22.2) 23 (17.0) 82 (60.7) 70 (23.9) 64 (21.8) 159 (54.3) 159 (27.1) 127 (21.7) 300 (51.2) 0–5 6–11 11–23 Number of Children 89 (81.7) 20 (18.3) 31 (63.3) 18 (36.7) 95 (70.4) 40 (29.6) 249 (84.9) 44 (15.1) 464 (79.2) 122 (20.8) 1–4 > 5 Household Size 50 (45.87) 59 (54.13) 14 (28.57) 35 (71.43) 48 (35.55) 87 (64.45) 147 (50.17) 146 (49.83) 259 (44.20) 327 (55.80) 2–4 > 5 Education (Mother) 59 (54.1) 29 (26.6) 21 (19.3) 42 (85.7) 7 (14.3) 0 (0.0) 85 (62.9) 29 (21.5) 21 (15.6) 139 (47.4) 109 (37.2) 48 (16.4) 325 (55.5) 178 (30.4) 90 (15.4) Cannot read/write Primary Secondary & above Education (Father) 43 (39.5) 48 (44.0) 18 (16.5) 34 (69.4) 3 (6.1) 12 (24.5) 44 (32.6) 57 (42.2) 34 (25.2) 88 (30.0) 142 (48.5) 63 (21.5) 209 (35.7) 261 (44.5) 116 (19.8) Cannot read/write Primary Secondary & above Economic Status of Study Households The economic profile of the sampled households underscores a landscape of agrarian subsistence, where a critical paradox exists between near-universal land ownership and actual productive capacity. Agriculture is the primary economic pillar, with 60.4% of mothers engaged in farming and 30.4% supplementing income through petty trading or daily labor. Land ownership is nearly universal (97.6%), yet the majority of households (60.8%) manage holdings of less than one hectare. This land scarcity is most acute in the Farta control group, where 80.4% of households cultivate less than a hectare. The composite wealth index further highlights a high degree of economic precariousness, with 42.8% of the study population classified as poor. Notably, the distribution of wealth does not align uniformly with land size. While Farta households have smaller landholdings and represent a larger share of the "poor" category (54.3%), Ebinat households—particularly those receiving NSA support—report larger landholdings, with 23% managing more than two hectares. Furthermore, dual PSNP + NSA-supported households are concentrated in the rich tertile (55.1%) (Table 2 ). These economic determinants are essential to understanding behavioral outcomes. The prevalence of small-scale farming indicates that even for those with access to land, the ability to generate a surplus for investment in WASH or food safety infrastructure remains constrained. Table 2 Socio-Economic Status in Ebinat and Farta Woredas, 2023, n = 586 Variable Household No (%) Total (586) Ebinat (293) Farta (293) Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) NSA supported (n = 135) Non-supported (n = 293) Occupation (mother) Farming 58 (52.7) 31 (62.0) 67 (60.0) 199 (63.0) 354 (60.4) Petty trader/Daily laborer 41 (38.3) 18 (36.0) 37(33.3) 71 (25.0) 168 (30.4) Other(Brewing local beer- Tella ) 8 (7.3) 1 (2.0) 7 (6.4) 13(4.4) 30 (5.1) Land ownership Yes 103(94.5) 46(93.9) 132(97.8) 291(99.3) 572(97.6) No 6(5.5) 3(2.1) 3(2.2) 2(0.7) 14(2.4) Cultivable land size (ha) 2 hectares 9 (8.3) 4 (8.2) 31 (23.0) 23 (7.8) 67 (11.4) Wealth Index Poor 24(22.0) 11 (22.4) 57(42.2) 159(54.3) 251(42.8) Medium 38(34.9) 11 (22.4) 22(16.3) 78 (26.6) 149(25.4) Rich 47(43.1) 27 (55.1) 56(41.5) 56 (19.1) 186(31.7) Household Food Safety Awareness, Knowledge, and Practices The assessment of food safety reveals a complex interplay among programmatic outreach, structural constraints, and entrenched cultural habits (Table 3 ). Awareness and training are strongly influenced by program participation; although fewer than half of all households (48.0%) have received food safety information, engagement is significantly higher among intervention groups. Dual beneficiaries of the PSNP + NSA reported the highest levels of awareness (61.2%) and formal training attendance (51.0%), contrasting sharply with non-supported households in Farta, where training reached only 10.9%. Practical cooking demonstrations followed this trend, reaching over half of NSA-supported households but only a quarter of the non-supported group, suggesting that multisectoral platforms are effective vehicles for disseminating information. In contrast to these knowledge-based indicators, physical infrastructure for food safety shows a reverse trend that highlights a persistent vulnerability. Households without support are significantly more likely to have a dedicated kitchen (84.3%) than the most vulnerable PSNP + NSA beneficiaries (49.0%). This infrastructure gap is critical because shared living and cooking spaces increase cross-contamination risks regardless of a caregiver's knowledge. Despite these structural deficits, adherence to fundamental storage hygiene is nearly universal; over 99% of households use storage raised at least 20 cm above the floor, and 100% of the study population reports separating raw and cooked items. Self-reported food-handling behaviors remain robust for basic tasks but variable for more intensive safety measures. While 95.9% of respondents wash raw produce with clean water, only about half (50.9%) report boiling milk or water—a practice more common among non-supported households, potentially reflecting fuel access rather than technical knowledge. Cultural dietary preferences often override safety awareness; only 10.8% of the total sample avoids raw food entirely, and even among the highly trained PSNP + NSA group, nearly 78% continue to consume raw items despite known pathogenic risks. Food preservation remains almost exclusively reliant on low-technology, traditional methods. Meat drying is the predominant strategy (83.6%), followed by salting (54.6%) and smoking (23.7%). Modern preservation technologies are virtually non-existent, with refrigeration used by only 6.0% of households—primarily within the non-supported Farta group. This technological gap constrains long-term storage capacity and underscores the need for future interventions to move beyond knowledge dissemination to improve physical infrastructure and preservation technology. Table 3 Food safety awareness, knowledge and practices by program participation status in the study Woredas, 2023, n = 586 Parameters Household No (%) Total (n = 586) Ebinat(293) Farta(293) Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) Only NSA supported (n = 135) Non-supported (n = 293) Awareness on food safety : Ever heard about food safety(yes) Ever attended food safety training(yes) Ever attended a cooking demonstration(yes) 60 (55.0) 20 (18.3) 39 (35.8) 30 (61.2) 25 (51.0) 27 (55.1) 76 (56.3) 50 (37.0) 68 (50.4) 115 (39.2) 32 (10.9) 76 (25.9) 281 (48.0) 127 (21.7) 210 (35.8) Household food hygiene and storage practices : Shelf/food storage for cooked food & utensils Storage raised ≥ 20 cm above floor Cooked food stored in sealed/covered containers Cooked and raw food kept separately Separate kitchen available 89 (81.7) 89 (100.0) 105 (96.3) 109 (100.0) 67 (61.5) 32 (65.3) 30 (93.8) 49 (100.0) 49 (100.0) 24 (49.0) 106 (78.5) 106 (100.0) 130 (96.3) 135 (100.0) 88 (65.2) 259 (88.4) 259 (100.0) 289 (98.6) 293 (100.0) 247 (84.3) 486 (82.9) 484 (99.6) 573 (97.8) 586 (100.0) 426 (72.7) Actions to make raw food safe : Wash with clean water (vegetables/fruits) Boil (milk and water) Ferment (milk for yogurt) Do not consume raw foods 98 (89.9) 38 (34.9) 22 (20.2) 2 (1.8) 49 (100.0) 23 (46.9) 6 (12.2) 11 (22.4) 131 (97.0) 62 (45.9) 30 (22.2) 16 (11.9) 284 (96.9) 175 (59.7) 71 (24.2) 34 (11.6) 562 (95.9) 298 (50.9) 129 (22.0) 63 (10.8) Local food preservation methods : Meat drying Meat salting Smoking Refrigeration Other methods(Drying Injera /local bread in the sun) 93 (85.3) 47 (43.1) 36 (33.0) 1 (0.9) 7 (6.4) 44 (89.8) 19 (38.8) 16 (32.7) 1 (2.0) 8 (16.3) 116 (85.9) 79 (58.5) 27 (20.0) 8 (5.9) 15 (11.1) 237 (80.9) 175 (54.7) 60 (20.5) 25 (8.5) 34 (11.6) 490 (83.6) 320 (54.6) 139 (23.7) 35 (6.0) 64 (10.9) Water, Sanitation, and Hygiene (WASH) The assessment of water supply and handling highlights a strong reliance on improved water sources, yet significant challenges persist regarding collection burdens and point-of-use treatment. Overall, 81.7% of the 586 households use improved sources, with shallow wells equipped with hand pumps serving as the primary supply for half of the study population (Table 4 ). Access and Supply Adequacy Access quality varies markedly by program status. Households receiving NSA-only support reported the highest use of improved sources (90.4%), whereas non-beneficiaries in Ebinat relied most on unimproved sources (29.4%), such as rivers and unprotected springs. Despite the high prevalence of "safe" sources, only 67.9% of households described their supply as adequate for daily needs, suggesting that physical presence does not guarantee sufficient quantity. Collection Burdens and Storage The logistical burden of water collection remains a substantial barrier to household hygiene and a primary driver of "time poverty." Only 22.4% of households reach their water source in under 30 minutes, while nearly 30% of the population spends more than 90 minutes per trip. This burden is particularly acute for dual PSNP + NSA beneficiaries, nearly 40% of whom travel more than an hour and a half for water. Once collected, water is almost exclusively stored in plastic jerry cans (87.2%). While these are easier to transport than traditional clay pots, they are prone to biofilm accumulation and require consistent cleaning to maintain water quality. Treatment Practices and Safety Gaps : A critical vulnerability in the WASH chain is the low rate of point-of-use water treatment. Despite the high risks of contamination during transport and storage, only a small fraction of households adopt safety measures. Chemical treatment with household brands of ‘Waterguard’ (sodium hypochlorite) or ‘Aquatabs’ (sodium dichloro-isocyanurate), is the most common method for water disinfection, used by 15.9% of households, whereas boiling water is exceptionally rare at 3.4%. This discrepancy underscores a major gap: while programs have successfully increased physical hardware, such as hand pumps, the behavioral component of ensuring that water remains safe until consumption remains unaddressed. Table 4 Water supply sources, access, collection time, storage, and treatment practices among households in the study Woredas, 2023, n = 586 Parameters Household No (%) Total (n = 586) Ebinat (n = 293) Farta (n = 293) Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) Only NSA supported (n = 135) Non-supported (n = 293) Water Supply Condition : Unimproved 32 (29.4) 9 (18.4) 13 (9.6) 53 (18.1) 107 (18.3) Improved 77 (70.6) 40 (81.6) 122 (90.4) 240 (81.9) 479 (81.7) Main source of water : Shallow wells with hand pump 55 (50.5) 23 (46.9) 92 (68.1) 125 (42.7) 295 (50.3) Unprotected spring 24 (22.0) 9 (18.4) 9 (6.7) 51 (17.4) 93 (15.9) Piped water & public tap 7 (6.4) 8 (16.7) 22 (16.3) 83 (28.3) 120 (20.5) Hand dug well in the village 7 (6.4) 7 (14.3) 5 (3.7) 3 (1.0) 22 (3.8) Spring water (capped) 8 (7.3) 2 (4.1) 3 (2.2) 29 (9.9) 42 (7.2) River 6 (5.5) 0 (0.0) 4 (2.9) 2 (0.7) 12 (2.1) Unprotected well 2 (1.8) 0 (0.0) 0 (0.0) 0 (0.0) 2 (0.3) Perception on Water Safety and Adequacy : Safe drinking water 75 (68.8) 39 (79.6) 125 (92.6) 243 (82.9) 482 (82.3) Adequate water supply 63 (57.8) 40 (81.6) 93 (68.9) 202 (68.9) 398 (67.9) Time taken to collect water : < 30 minutes 17 (15.6) 14 (28.6) 25 (18.5) 75 (25.6) 131 (22.4) 30–60 minutes 53 (48.6) 16 (32.7) 49 (36.3) 136 (46.4) 254 (43.3) 61–90 minutes 7 (6.4) 0 (0.0) 7 (5.2) 14 (4.8) 28 (4.8) 91–120 minutes 14 (12.8) 14 (28.6) 33 (24.4) 49 (16.7) 110 (18.8) > 120 minutes 18 (16.5) 5 (10.2) 21 (15.6) 19 (6.5) 63 (10.8) Type of storage : Plastic jerry can 88 (80.7) 43 (87.8) 115 (85.2) 265 (90.4) 511 (87.2) Clay pot ( Insira ) 3 (2.8) 2 (4.1) 1 (0.7) 0 (0.0) 6 (1.0) Both Jerry can and Clay pot 18 (16.5) 4 (8.2) 19 (14.1) 28 (9.6) 69 (11.8) Water treatment methods : Water-guard/Aquatabs 19 (20.4) 8 (16.3) 26 (19.2) 40 (13.6) 93 (15.9) Boil 5 (4.6) 1 (2.0) 3 (2.2) 11 (3.7) 20 (3.4) Strain through cloth 3 (2.7) 2 (4.1) 4 (3.0) 1 (0.4) 10 (1.7) Sanitation Conditions and Latrine Coverage Sanitation in the study area reveals a landscape of high utilization but low-quality infrastructure. Overall, 66.9% of households reported having a latrine, though access was unevenly distributed across geographic areas. Coverage peaked in Farta (85.3%) but dropped to 38.5% among non-beneficiaries in Ebinat. Despite these disparities, latrine utilization among those with facilities was nearly universal at 97.4%, suggesting that behavioral intent is well established (Table 5 ). However, facility quality remains a critical concern. The vast majority (86.7%) relied on unimproved traditional latrines, while only 11.5% used improved facilities. Although PSNP + NSA beneficiaries reported the highest prevalence of improved latrines (21.1%), overall structural integrity was poor; only 41.2% had well-covered floors. This limits the effectiveness of latrines in breaking the cycle of disease transmission. Furthermore, only 39.0% of households maintained a handwashing facility near their latrine, and the hardware consisted mostly of low-cost solutions such as jugs or tippy taps. For the third of the population without latrine access, open defecation remains the primary alternative. A striking 90.3% of these households reported that all members defecated in the bush or near the homestead. These patterns reveal a gendered dimension to environmental exposure, with women and girls often restricted to areas closer to the home, underscoring persistent gaps among the most vulnerable. Table 5 Household sanitation situation, latrine coverage, and associated hygiene practices in the study Woredas, 2023, n = 586 Indicator/Parameter Household No (%) Total (n = 586) Ebinat Woreda (n = 293) Farta (293) Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) Only NSA supported (n = 135) Non- supported (n = 293) Latrine facility : Latrine coverage 42 (38.5) 19 (38.8) 81 (60.0) 250 (85.3) 392 (66.9) Unimproved (Traditional) 35 (83.3) 15 (78.9) 71 (87.7) 219 (87.6) 340 (86.7) Improved latrine 7 (16.7) 4 (21.1) 8 (9.9) 26 (10.4) 45 (11.5) Floor well covered 25 (59.5) 4 (21.1) 46 (56.8) 86 (34.5) 161 (41.2) All family members are using latrine 40 (95.2) 19 (100.0) 78 (96.3) 245 (98.0) 382 (97.4) Handwashing facility near to the latrine 13 (31.0) 6 (31.6) 39 (48.1) 95 (38.0) 153 (39.0) Soap/ash used for hand cleansing 10 (76.9) 4 (66.7) 27 (69.2) 58 (61.1) 99 (64.7) Type of handwashing facility : Sink with running water 6 (46.2) 1 (16.7) 9 (23.1) 17 (17.9) 33 (21.6) Jug 2 (15.4) 1 (16.7) 10 (25.6) 48 (50.5) 61 (39.9) Tippy tap 2 (15.4) 1 (16.7) 10 (25.6) 48 (50.5) 61 (39.9) Pace of defecation, if no latrine : Men and women defecate in the bush/near the house 62 (93.9) 24 (80.0) 49 (92.2) 43 (91.5) 178 (90.3) Women and girls defecate near the house 3 (4.5) 5 (16.7) 1 (1.9) 1 (2.1) 10 (5.1) Men/boys defecate in the bush 1 (1.5) 1 (3.3) 4 (7.4) 3 (6.4) 9 (4.6) Handwashing Knowledge and Practices Analysis of handwashing behaviors reveals a moderate level of theoretical awareness, tempered by significant gaps in critical hygiene stages, particularly those related to food preparation. Maternal knowledge is strongest regarding childcare; 68.9% of mothers identified the importance of washing hands after changing a baby’s nappy, and 56.3% recognized the need after toilet use. However, literacy declines regarding dietary milestones; only 53.1% were aware of the need to wash hands before preparing food. The most significant deficit involves post-contamination awareness, with only 27.3% identifying handwashing after handling raw food as a requirement. Despite this knowledge base, a "knowledge-practice gap" persists regarding consistent soap use. Although 60.9% reported using soap after using the toilet, 5.8% admitted not using soap at all, relying solely on water. Adherence remains lowest among non-beneficiaries, suggesting that economic or physical barriers to soap access may undermine even the best-informed households. These findings indicate that while multisectoral programs improve hygiene literacy, they have yet to bridge the gap in specific food-safety behaviors, such as washing hands after handling raw ingredients (Table 6 ). Table 6 Household knowledge and practice of handwashing at critical times in the study Woredas, 2023, n = 586 Indicator Household No (%) Total (n = 586) Ebinat Woreda (n = 293) Farta (n = 293) Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) Only NSA supported (n = 135) Non- supported (n = 293) Critical times for handwashing(Knowledge) : After going to the toilet 54 (49.5) 30 (61.2) 77 (57.0) 169 (57.7) 330 (56.3) After changing a baby's nappy 55 (50.5) 31 (63.3) 106 (78.5) 212 (72.4) 404 (68.9) Before preparing/handling food 34 (31.2) 23 (46.9) 69 (51.1) 185 (63.1) 311 (53.1) Before feeding a child/ eating 29 (26.6) 23 (46.9) 78 (57.8) 164 (56.0) 294 (50.2) After handling raw food 17 (15.6) 15 (30.6) 44 (32.6) 84 (28.7) 160 (27.3) After handling garbage 42 (38.5) 26 (53.1) 44 (32.6) 211 (72.0) 323 (55.1) Don’t Know 20(18.3) 6 (12.3) 6 (4.4) 22 (7.5) 54 (9.2) Critical times for handwashing with soap(Practice) : After going to toilet 68 (62.4) 33 (67.3) 84 (62.2) 172 (58.7) 357 (60.9) After cleaning 39 (35.8) 18 (36.7) 62 (45.9) 137 (46.8) 256 (43.7) Before preparing/handling food 54 (49.5) 30 (61.2) 90 (66.7) 151 (51.5) 325 (55.5) Before feeding a child/ eating 45 (41.3) 26 (53.1) 83 (61.5) 160 (54.6) 314 (53.6) After handling raw food 29 (26.6) 14 (28.6) 39 (28.9) 85 (29.0) 167 (28.5) After handling garbage 35 (32.1) 20 (40.8) 48 (35.6) 189 (64.5) 292 (49.8) Others(did not use soap at all) 7 (6.4) 3 (6.1) 3 (2.2) 21 (7.2) 34 (5.8) Soap used before feeding child (last time)_proving for specific 59 (54.1) 29 (59.2) 79 (58.5) 179 (61.1) 346 (59.0) Environmental Health Practices The assessment reveals a significant disconnect between high hygiene awareness and the persistence of hazardous disposal methods (Table 7 ). While most participants recognized basic hygiene as a primary defense against pathogens, with 83.1% identifying handwashing and 79.5% citing safe fecal removal, prioritization varied. Handwashing awareness was highest among non-supported households in Farta (90.1%), whereas dual PSNP + NSA beneficiaries had the highest fecal management adherence (89.8%), likely reflecting targeted sanitation messaging. However, only 1.4% of households identified drinking safe water as a preventive action. Solid waste management practices reflect a tension between traditional agricultural utility and environmental risk. Composting was used by 37.0% of the sample, while 38.9% disposed of waste directly onto farmland, a practice particularly common among non-beneficiaries in Ebinat (56.9%). More hazardous practices remain prevalent; 39.8% of households burned their waste, and nearly 10% reported indiscriminate disposal on public roads. Liquid waste management further highlights infrastructure constraints. Although draining into boreholes was the predominant method (62.3%), especially in Farta (74.1%), nearly half of the population (48.1%) still flushes liquid waste directly into their compounds. This practice was most pronounced among non-beneficiaries in Ebinat (67.9%) and among PSNP + NSA households (73.5%), creating significant localized contamination risks. This indicates that behavioral knowledge is currently outpacing the development of physical infrastructure. Table 7 Household environmental health knowledge and waste management practices in the study Woredas, 2023, n = 586 Indicator / Parameter Household No (%) Total (n = 586) (Multiple responses) Ebinat (n = 293) Farta (n = 293) Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) Only NSA supported (n = 135) Non- supported (n = 293) Knowledge-Actions to avoid sickness from germs : Wash hands 75 (68.8) 36 (73.5) 112 (83.0) 264 (90.1) 487 (83.1) Remove faeces 75 (68.8) 44 (89.8) 106 (78.5) 241 (82.3) 466 (79.5) Other (drink safe water) 0(0.0) 3 (6.1) 3 (2.2) 2 (0.7) 8 (1.4) Household solid waste disposal : Composting 28 (25.7) 16 (32.7) 46 (34.1) 127 (43.3) 217 (37.0) Burn 19 (17.4) 17 (34.7) 45 (33.3) 152 (51.9) 233 (39.8) Disposing on farm 62 (56.9) 26 (53.1) 70 (51.9) 70 (23.9) 228 (38.9) Throwing on road 18 (16.5) 8 (16.3) 11 (8.1) 21 (7.2) 58 (9.9) Household liquid waste disposal : Flush in the compound 74 (67.9) 36 (73.5) 66 (48.9) 106 (36.2) 282 (48.1) Drain in bore whole 41 (37.6) 20 (5.5) 87 (64.5) 217 (74.1) 365 (62.3) Synthesis of Household Food Safety, WASH, and Environmental Health The composite analysis reveals a bifurcated public health landscape, with gains in physical infrastructure coexisting with stagnation in behavioral safety. Integrated program participation (PSNP and NSA) has improved WASH outcomes, yet a substantial deficit persists in food safety behaviors (Table 8 ). The Food Safety Bottleneck Food safety is the primary behavioral weakness across the population. According to Bloom’s criteria, 74.2% of households exhibited poor food safety practices. Even among dual PSNP + NSA beneficiaries, the "good" practice threshold remained low, suggesting that economic advancement and agricultural support do not automatically translate into safer food-handling practices. Bridging the Knowledge-Practice Gap A compelling divergence exists between theoretical knowledge and practical application. Households in Farta had the highest levels of hygiene literacy (56.0% "good" knowledge), yet a critical reversal in practice emerged: PSNP + NSA households had the highest prevalence of "good" hygiene practices (44.9%). This indicates that targeted programmatic support serves as a vital bridge, translating even modest health literacy into safer behaviors. Responsive Infrastructure vs. Stagnant Environments Physical WASH conditions appear highly responsive to multisectoral interventions. Overall, 59.2% of households reported adequate WASH conditions, with significantly higher rates among PSNP + NSA (73.5%) and NSA-only (68.9%) beneficiaries. However, broader environmental health conditions remain mixed. More than half of the population lived in poor environmental conditions, underscoring that a clean domestic environment requires more than infrastructure; it also necessitates integrating maternal literacy and targeted institutional support. Table 8 Composite index of household food safety, hygiene and sanitation knowledge and practices, WASH, and environmental health condition in study Woredas, 2023, n = 586 Parameters (Transformed Variables) Household No (%) Total (n = 586) Ebinat(n = 293) Farta(n = 293 Non-beneficiary (n = 109) PSNP + NSA supported (n = 49) Only NSA supported (n = 135) Non- supported (n = 293) Food Safety practice _Mean cut-off point : Poor 84(77.1) 35(71.4) 98(72.6) 218(74.4) 435(74.2) Good 25(22.9 14(28.6) 37(27.4) 75(25.6) 151(25.8) Food Safety practice _Bloom’s cut-off point : Poor 84 (77.1) 35 (71.4) 98 (72.6) 218 (74.4) 435 (74.2) Moderate 15 (13.8) 6 (12.2) 27 (20.0) 50 (17.1) 98 (16.7) Good 10 (9.2) 8 (16.3) 10 (7.4) 25 (8.5) 53 (9.0) Hygiene & Sanitation Knowledge _Mean cut-off point : Poor 81(74.3) 28(57.1) 75(55.6) 129(44.0) 313(53.4) Good 28(25.7) 21(42.9) 60(44.4) 164(56.0) 273(46.6) Hygiene & Sanitation Knowledge _Bloom’s cut-off point : Poor 81 (74.3) 28 (57.1) 75 (55.6) 129 (44.0) 313 (53.4) Moderate 17 (15.6) 8 (16.3) 31 (23.0) 61 (20.8) 117 (20.0) Good 11 (10.1) 13 (26.5) 29 (21.5) 103 (35.2) 156 (26.6) Hygiene & Sanitation Practice _Mean cut-off point : Poor 76(69.7) 27(55.1) 87(64.4) 173(59.0) 363(61.9) Good 33(30.3) 22(44.9) 48(35.6) 120(41.0) 223(38.1) Hygiene & Sanitation practice _Bloom’s cut-off point : Poor 90 (82.6) 33 (67.3) 100 (74.1) 216 (73.7) 439 (74.9) Moderate 15 (13.8) 8 (16.3) 21 (15.6) 30 (10.2) 74 (12.6) Good 4 (3.7) 8 (16.3) 14 (10.4) 47 (16.0) 73 (12.5) Household WASH Condition : Inadequate 29 (26.6) 13 (26.5) 42 (31.1) 155 (52.9) 239 (40.8) Adequate 80 (73.4) 36 (73.5) 93 (68.9) 138 (47.1) 347 (59.2) Household Environment Condition : Poor 80 (73.4) 39 (79.6) 74 (54.8) 129 (44.0) 322 (54.9) Good 29 (26.6) 10 (20.4) 61 (45.2) 164 (56.0) 264 (45.1) Predictors of Household Food Safety Practices The binary logistic regression analysis identifies several factors that are significantly associated with household food safety practices in the study woredas (Table 9 ). Program participation status did not show a statistically significant effect. Households in PSNP + NSA, NSA-only, or non-supported woredas had lower odds ratios than non-beneficiaries in supported woredas, but none reached statistical significance. Household headship was an important predictor, with female-headed households less likely to report poor food safety practices than male-headed households (AOR = 0.444, p = 0.038). This suggests that women’s leadership may positively influence household hygiene. Parental literacy showed mixed effects: mothers’ literacy was not significant, whereas households in which fathers could not read or write had significantly lower odds of poor practices (AOR = 0.558, p = 0.021), indicating a possible protective role of paternal literacy. Awareness emerged as a strong determinant, as households that had never heard of food safety were more than twice as likely to report poor practices (AOR = 2.360, p = 0.013). Training and cooking demonstrations showed inconsistent results; not attending training increased the odds (AOR = 1.225), but the reported p-value (0.000) conflicted with the confidence interval, and cooking demonstrations were not significant. Socioeconomic status was a clear predictor, with medium- and high-income households significantly less likely to report poor practices than low-income households (AOR = 0.445 and 0.415, both p = 0.001), highlighting the role of economic capacity in enabling safer food handling. Most notably, the frequency of Health Extension Worker (HEW) visits was consistently associated with protection. Households visited every six months, quarterly, monthly, or biweekly all showed substantially reduced odds of poor practices (AORs ranging from 0.200 to 0.269, all p < 0.05). These findings emphasize that awareness creation, socioeconomic empowerment, and strengthening HEW outreach are pivotal strategies for improving household food safety practices; however, program participation alone may be insufficient without complementary interventions. Table 9 Results of Binary Logistic Regression Analysis for factors affecting Food Safety Practices in Study Woredas(n = 586) Variable / Parameter AOR (Exp (B)) 95% C.I. for EXP(B) P-Value Lower Upper Program Participation Status Non-beneficiary in Supported Woreda 1 - - - PSNP + NSA Supported 0.645 0.360 1.155 0.395 NSA Supported 0.729 0.335 1.588 0.140 Non-supported Woreda 0.705 0.421 1.180 0.426 Household Headship Men 1 - - - Women .444 0.206 0.957 0.038 Literacy status of mothers Read or write a simple sentence 1 - - - Cannot read or write a simple sentence 1.297 0.859 1.960 0.216 Literacy status of husbands Read or write a simple sentence 1 - - - Cannot read or write a simple sentence .558 0.340 0.917 0.021 Ever heard about food safety Yes 1 - - - No 2.360 1.536 3.624 0.013 Attended food safety training Yes 1 - - - No 1.225 0.720 2.084 0.000 Attended cooking demonstration Yes 1 - - - No 1.623 1.048 2.515 0.454 Member in mothers group/ association Yes 1 - - - No .995 0.588 1.684 0.001 Frequency of HEWs visit No visit 1 - - .- Every six month 0.268 0.091 0.786 0.017 Quarterly 0.200 0.065 0.622 0.005 Every month 0.231 0.082 0.651 0.006 Every two weeks 0.269 0.101 0.716 0.009 Wealth Index Poor 1 - - - Medium 0.445 0.278 0.714 0.001 Rich 0.415 0.242 0.711 0.001 Predictors of Household WASH Condition The regression analysis identifies program participation and economic status as the primary determinants of WASH adequacy (Table 10 ). Dual support from PSNP and NSA made households nearly three times more likely to report adequate WASH conditions (AOR = 2.948), while NSA support alone had even higher odds (AOR = 3.356). Wealth status was a definitive determinant, with medium (AOR = 0.136) and rich (AOR = 0.333) households significantly more likely to maintain adequate WASH conditions. Interestingly, parental literacy and household headship did not significantly predict WASH adequacy, suggesting that the physical "adequate" status of WASH is driven more by material resources and large-scale infrastructure than by individual counseling or health literacy. Table 10 Results of Binary Logistic Regression Analysis for Factors Affecting Household WASH Status in the study Woreda, 2023, n = 586 Parameters AOR (Exp (B)) 95% C.I.for EXP(B) P-Value Lower Upper Participation in programs Non-beneficiary HHs in supported Woreda 1 PSNP + NSA supported HHs 2.948 1.635 5.313 0.000 NSA supported HHs 3.356 1.295 8.699 0.013 Non-supported HHs 1.780 1.037 3.055 0.037 Household headship Yes 1 No 1.328 0.569 3.100 0.512 Literacy status of mothers Read or write a simple sentence 1 Cannot read or write a simple sentence 0.713 0.451 1.126 0.147 Literacy status of husbands Read or write a simple sentence 1 Cannot read or write a simple sentence 1.391 0.860 2.247 0.178 Land ownership Yes 1 No 5.040 0.992 25.612 0.051 Accessed credit Yes 1 No 0.714 0.419 1.219 0.217 Member in mothers group/ association Yes 1 No 0.948 0.570 1.578 0.838 Frequency of HEWs visits No visit 1 Every six month 0.616 0.038 9.998 0.733 Quarterly 0.423 0.026 6.999 0.548 Every month 0.616 0.039 9.791 0.731 Every two weeks 0.879 0.056 13.785 0.927 Wealth Index Poor 1 Medium 0.136 0.075 0.247 0.000 Rich 0.333 0.174 0.636 0.001 Predictors of Household Environment Condition The regression analysis identified program participation, maternal literacy, wealth status, HEW visits, and community engagement as the strongest predictors of household environmental health (Table 11 ). Households supported by PSNP + NSA or NSA-only programs had significantly lower odds of poor practices, while medium- and rich households reported better outcomes than poor households, underscoring the role of socioeconomic empowerment. Maternal literacy emerged as a critical determinant, with mothers who cannot read or write a simple sentence more than twice as likely to report poor practices (AOR = 2.543), highlighting women’s central role in managing the domestic environment. Practical education also mattered: households that attended cooking demonstrations were nearly three times more likely to report favorable outcomes (AOR = 2.684), emphasizing the importance of experiential learning. This underscores that environmental management is a specialized skill set driven by maternal education and experiential learning rather than by general agricultural assets. Table 11 Household Environmental Health Situation in the study Woredas, n = 586. Parameter AOR (Exp(B)) 95% C.I.for EXP(B) P-Value Lower Upper Program participation status Non-beneficiary in Supported Woreda 1 PSNP + NSA supported HHs 0.239 0.131 0.436 0.000 NSA supported HHs 0.186 0.061 0.570 0.003 Non-supported HHs 0.722 0.434 1.199 0.208 Household headship 1.180 0.529 2.631 0.686 Yes No 1.180 0.529 2.631 0.686 Land ownership Yes 1 No 0.311 0.057 1.696 0.177 Wealth Index 1 Poor 1 Medium 2.184 1.294 3.686 0.003 Rich 2.137 1.180 3.869 0.012 Literacy status of mothers Read or write a simple sentence 1 Cannot read or write a simple sentence 2.543 1.641 3.941 0.000 Literacy status of husbands Read or write a simple sentence 1 Cannot read or write a simple sentence 1.288 0.807 2.056 0.288 Household received extension service Yes 1 No 0.569 0.351 0.922 0.022 Frequency of HEWs visits No visit 1 Every six month .268 .091 .786 .017 Quarterly .200 .065 .622 .005 Every month .231 .082 .651 .006 Every two weeks .269 .101 .716 .009 Member in mothers' group Yes 1 No 2.176 1.303 3.632 0.003 Attended food safety training Yes 1 No 0.380 0.192 0.752 0.005 Attended a cooking demonstration Yes 1 No 2.684 1.565 4.604 0.000 Accessed credit Yes 1 No .982 0.583 1.654 0.946 Discussion This study evaluated the determinants of household food safety, WASH, and environmental health across Ebinat and Farta woredas, revealing distinct drivers and a persistent knowledge–practice gap. A consistent theme was the gap between knowledge and practice: while households demonstrated moderate awareness of hygiene, this awareness did not consistently translate into risk‑reducing behaviors. Beneficiary households participating in PSNP and NSA interventions reported higher levels of training participation, yet the overall prevalence of good food safety practices remained low. This suggests that current educational models are insufficient without concurrent structural support. These findings echo FAO’s (2020) conclusion that food safety education alone rarely achieves sustainable behavioral change unless paired with systemic reinforcement, and align with evidence that literacy and awareness are stronger predictors of food safety behaviors than program participation alone ( 2 , 17 ). Food Safety: The Literacy-Behavior Gap Food safety emerged as the weakest behavioral domain, with nearly three‑quarters of households demonstrating poor practices. Socioeconomic and informational factors, particularly paternal literacy and prior exposure to food safety information, were the strongest protective influences, confirming the importance of education and awareness campaigns. This finding aligns with UNICEF (2021), which emphasizes that basic literacy enhances uptake of health and nutrition messages. Programmatic interventions such as food safety training, HEW visits, and mothers’ group participation showed limited impact, consistent with evidence from community‑based nutrition programs, where technical training alone has a limited effect unless reinforced by broader literacy ( 2 , 6 ). Structural constraints further compounded risks: only half of PSNP + NSA households had separate kitchens, and reliance on traditional preservation methods such as meat drying and salting posed contamination risks. These structural constraints further compounded contamination risks. These findings align with regional data showing significantly lower food safety compliance in less-resourced areas compared to urban centers ( 17 , 18 ). WASH Outcomes: The Role of Institutional Support Unlike food safety, WASH outcomes were primarily driven by institutional support and socioeconomic empowerment. Participation in PSNP and NSA interventions made households nearly three times more likely to report adequate WASH, confirming that integrated nutrition-sensitive models effectively enhance access to infrastructure ( 2 , 19 ). Although most households used improved water sources, significant challenges remain, including long collection times and low use of point-of-use treatment. Wealthier households maintained superior conditions, reflecting the need for economic resources to invest in latrines and soap. However, the lack of association between literacy and WASH adequacy suggests that infrastructure is the primary limiting factor ( 6 , 20 ). Even with high awareness, persistent gaps, such as the scarcity of handwashing stations near latrines, undermine health gains. These results emphasize the need to upgrade traditional facilities and integrate food safety into WASH curricula to break the cycle of enteric infections ( 21 ). Household Environmental Health: A Hybrid Determinant Environmental health followed a hybrid pattern, shaped by program participation, wealth, and maternal literacy. Households receiving integrated support were significantly less likely to report poor conditions, consistent with findings that WASH education improves sanitation behaviors in rural Ethiopia ( 22 ). Notably, maternal literacy was a critical predictor, with literate mothers twice as likely to maintain favorable conditions. This underscores the central role of women’s education in household health management ( 6 , 23 ). While socioeconomic status enables investment in sanitation, reliance on borehole drainage and the coexistence of composting and burning reflect ongoing resource constraints. Ethiopia’s National WASH and Environmental Health Strategy advocates combining community education with infrastructure provision to mitigate these risks ( 24 ). Cross-Cutting Implications The evidence suggests that food safety is predominantly knowledge-driven, whereas WASH and environmental health are infrastructure-driven. Three cross-cutting implications emerge for public health policy. First, education acts as a catalyst; paternal literacy promotes safer food handling, while maternal literacy strengthens domestic environmental management. Second, an economic–infrastructural nexus exists in which households require both knowledge and resources to overcome structural barriers such as shared kitchens or unimproved latrines. Third, nutrition-sensitive agriculture serves as a viable multisectoral platform for delivering integrated interventions that can effectively reduce childhood growth faltering. Strengths, Limitations, and Future Research A major strength of this study is its simultaneous examination of three critical domains, food safety, WASH, and environmental health, within a single population, providing a holistic view of household health determinants. However, the cross-sectional design precludes causal inference, and self-reported data may be subject to social desirability bias. Future research should use longitudinal and observational methods to capture seasonal dynamics and reduce self-report bias. Expanding geographic coverage and examining the role of market systems and regulatory frameworks will be essential. Ultimately, intervention trials that integrate literacy promotion with infrastructure investment will provide the most robust evidence for improving health outcomes in rural Ethiopia. Conclusions This study underscores the complex and interrelated determinants of household food safety, WASH, and environmental health in rural Ethiopia. While integrated, multisectoral interventions such as the PSNP and NSA have successfully improved hygiene and sanitation behaviors, food safety practices remain persistently poor and structurally constrained. Distinct behavioral drivers emerged across domains: hygiene outcomes were primarily shaped by institutional support and program participation; food safety behaviors were strongly influenced by paternal literacy and household wealth; and environmental health reflected a hybrid pattern driven by maternal literacy, program engagement, and socioeconomic status. These findings highlight a persistent “knowledge–practice gap,” in which awareness of hygiene and food safety does not consistently translate into risk-reducing behaviors because of infrastructure deficits, including unimproved latrines, long water-collection times, and the lack of separate kitchens. Addressing these gaps requires moving beyond knowledge dissemination to address structural inequities and empower households through education, institutional support, and economic strengthening. Recommendations/ Implications To translate these findings into actionable strategies, several priorities emerge: Integrate food safety into agricultural extension: Food safety curricula, particularly those addressing cross‑contamination and pathogen control, should be embedded within NSA platforms, leveraging their proven success in improving hygiene. Invest in infrastructure: Expanding access to protected water sources, improving latrine quality, and promoting separate kitchen facilities are essential to enabling households to adopt safe practices. Strengthen literacy and education initiatives: Adult literacy programs should be paired with health interventions, recognizing the pivotal role of paternal literacy in food safety and maternal literacy in environmental health. Enhance regulatory oversight and consumer education: Stronger food safety regulations, expanded inspection capacity, and culturally tailored consumer education are needed to mitigate risks associated with dietary preferences, including the consumption of raw meat. Leverage multisectoral platforms: Nutrition‑sensitive agriculture, social protection programs, and maternal counseling should be scaled up as effective vehicles for delivering integrated interventions across food safety, hygiene, and environmental health. Adopt equity‑focused strategies: Interventions must ensure that vulnerable households benefit alongside wealthier groups by pairing behavioral communication with economic strengthening, thereby enabling equitable adoption of safer technologies. Abbreviations NSA Nutrition Sensitive Agriculture PSNP Productive Safety Net Program SD Seqota Declaration WASH Water, Sanitation and Hygiene Declarations Consent for publication Not applicable. Ethics approval and consent to participate: The study adhered to the principles outlined in the Declaration of Helsinki. The proposal was approved by the Institutional Review Board of the College of Development Studies at Addis Ababa University (CoDS/IRB/0003/2022) before the study began. Official support letters were obtained from AAU, and permission to conduct the study in the area was granted by the Amhara Health Research Institute. All study participants were informed about the study's objectives and purpose, as well as the voluntary nature of their participation. Informed oral consent was obtained from each participating household prior to interview-based data collection. Respondents’ right to refuse to answer any question or to withdraw at any point during data collection was assured. The information provided by each respondent was collected anonymously and kept confidential. Conflicts of interest : The authors declare no conflicts of interest Funding: Not applicable. Author Contribution Z.T., Conceptualization, Methodology, Data Collection, Investigation, Analysis, Writing original draft. N.R., Conceptualization, Methodology, Analysis, Supervision, Review & Editing. M.A., Conceptualization, Methodology, Analysis, Supervision, Review & Editing. Acknowledgements: None Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References World Health Organization. WHO estimates of the global burden of foodborne diseases. World Health Organization; 2022. FAO, IFAD, UNICEF, WFP, & WHO. The state of food security and nutrition in the world 2020: Transforming food systems for affordable healthy diets. Rome: FAO; 2020. https://doi.org/10.4060/ca9692en . Mara D, Lane J, Scott B, Trouba D. Sanitation and health. PLoS Med. 2010;7(11):e1000363. https://doi.org/10.1371/journal.pmed.1000363 . Institute for Health Metrics and Evaluation (IHME). Global Burden of Disease 2023: Findings from the GBD 2023 Study. Seattle, WA: IHME, University of Washington; 2025. Andualem Z, Abebe L, Gizaw Z. Rural water supply and sanitation coverage in Ethiopia: A systematic review and meta-analysis. Environ Health Prev Med. 2021;26(1):1–14. https://doi.org/10.1186/s12199-021-00943-3 . UNICEF & WHO. (2021). Progress on household drinking water, sanitation and hygiene 2000–2020: Five years into the SDGs. Joint Monit Programme. https://www.who.int/publications/i/item/9789240030848 Abay KA, Abay MH, Berhane G, Chamberlin J. Social protection and resilience: The case of the Productive Safety Net Program in Ethiopia. Food Policy. 2022;112:102367. https://doi.org/10.1016/j.foodpol.2022.102367 . UNICEF. (2022). Safeguarding food and nutrition security in Ethiopia: The Seqota Declaration story. Addis Ababa: UNICEF Ethiopia. Retrieved from https://www.unicef.org/ethiopia Abuye C, Abbott D, Berhanu L, Bailes A, Holtzman R. An evaluation of interventions within a Growth Through Nutrition project aimed at enhancing optimal nutrition and water, sanitation and hygiene (WASH) and nutrition practices among nutritionally most vulnerable households (MVHHs) in Ethiopia. PLoS ONE. 2024;19(10):e0309426. 10.1371/journal.pone.0309426 . PMID: 39480822; PMCID: PMC11527315. Federal Ministry of Health [Ethiopia]. Seqota Declaration roadmap for expansion and scale–up phases 2021–2030. Addis Ababa: Government of Ethiopia; 2021. Ethiopia. Administrative map - Amhara Region (as of October 2020) | OCHA. Macías Y, Glasauer P. Guidelines for assessing nutrition-related Knowledge, Attitudes and Practices. Guidelines for assessing nutrition-related Knowledge, Attitudes and Practices. Rome: Food and Agriculture Organization of the United Nations; 2014. CSA & ICF. (2016). Ethiopia Demographic and Health Survey 2016. Central Statistical Agency, Addis Ababa, Ethiopia, and ICF, Rockville, MD, USA. https://www.dhsprogram.com/publications/publication-fr328-dhs-final-reports.cfm Wallace CA, Sperber WH, Mortimore SE. Origin and evolution of the modern system of food safety management: HACCP and prerequisite programmes. Food safety for the 21st century: Managing HACCP and food safety systems. Hoboken, NJ: Wiley; 2018. pp. 1–13. https://doi.org/10.1002/9781119053569.ch1 . Ayanaw Eyayu R, Zeleke G, Chekol T, Melesse WBY, D., Ashagrie E, H. Assessment of level of knowledge, attitude, and associated factors toward delirium among health professionals working in intensive care unit multicenter, cross-sectional study, Amhara region comprehensive specialized hospitals. Northwest Ethiopia 2023 Front Public Health. 2024;12. https://doi.org/10.3389/fpubh.2024.1338760 . Article 1338760. World Health Organization. (2010, March 25). Food safety: Report by the Secretariat (A63/11). Sixty Third World Health Assembly, Provisional agenda item 11.8. Geneva: WHO. Retrieved from https://apps.who.int/gb/ebwha/pdf_files/WHA63/A63_11-en.pdf Ayelign A, Moges A, Adugna B. Determinants of food safety knowledge and practices among rural households in Ethiopia: A cross-sectional study. Food Control. 2023;145:109431. https://doi.org/10.1016/j.foodcont.2023.109431 . Dagne H, Abdisa G, Shiferaw S. Food safety practice and its associated factors among food handlers in public food establishments in Debre Markos town, Northwest Ethiopia. BMC Res Notes. 2019;12(1):1–6. https://doi.org/10.1186/s13104-019-4471-y . Berhane G, Gilligan DO, Hoddinott J, Kumar N, Taffesse AS. Can social protection work in Africa? The impact of Ethiopia’s Productive Safety Net Programme. Econ Dev Cult Change. 2014;63(1):1–26. https://doi.org/10.1086/677753 . Freeman, M. C., Delea, M., Snyder, J. S., Garn, J. V., Belew, M., Caruso, B. A., …Gobezayehu, A. G. (2022). The impact of a demand-side sanitation and hygiene promotion intervention on sustained behavior change and health in Amhara, Ethiopia: A cluster-randomized trial. PLOS Global Public Health, 2(1), e0000056. https://doi.org/10.1371/journal.pgph.0000056. Soboka NE, Gari SR, Hailu AB. The impact of integrated WASH-food safety interventions on enteric infections in children. Public Health Front. 2025;3(1):77–89. Gizaw Z, Addisu A. Evidence of households’ water, sanitation, and hygiene (WASH) performance improvement following a WASH education program in rural Dembiya, Northwest Ethiopia. Environ Health Insights. 2020;14:1–9. https://doi.org/10.1177/1178630220903100 . Bhutta ZA, Akseer N, Keats EC, Vaivada T, Black RE. How countries can reduce child stunting at scale: Lessons from exemplar countries. Am J Clin Nutr. 2020;112(Supplement2):S894–904. https://doi.org/10.1093/ajcn/nqaa153 . Federal Ministry of Health. (2022). National WASH and Environmental Health Strategy (2021–2025) . Government of Ethiopia. https://www.scribd.com/document/852269236/National-WASH-and-Enviromental-Health-Stratagy Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 22 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviews received at journal 30 Mar, 2026 Reviewers agreed at journal 30 Mar, 2026 Reviewers agreed at journal 26 Mar, 2026 Reviewers agreed at journal 26 Mar, 2026 Reviewers agreed at journal 23 Feb, 2026 Reviewers agreed at journal 22 Feb, 2026 Reviews received at journal 20 Feb, 2026 Reviewers agreed at journal 20 Feb, 2026 Reviewers invited by journal 20 Feb, 2026 Editor assigned by journal 20 Feb, 2026 Editor invited by journal 12 Feb, 2026 Submission checks completed at journal 11 Feb, 2026 First submitted to journal 11 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-8831449","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595739689,"identity":"b648ab26-bde1-4d0a-ac71-aeb98f3601d4","order_by":0,"name":"Zenaw Merie","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Zenaw","middleName":"","lastName":"Merie","suffix":""},{"id":595739690,"identity":"362e2468-e306-4138-bc29-435675d56f49","order_by":1,"name":"Nigatu Regassa","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Nigatu","middleName":"","lastName":"Regassa","suffix":""},{"id":595739691,"identity":"f49e8d94-466f-4946-870a-8f447e4a4042","order_by":2,"name":"Mogessie Ashenafi","email":"data:image/png;base64,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","orcid":"","institution":"Addis Ababa University","correspondingAuthor":true,"prefix":"","firstName":"Mogessie","middleName":"","lastName":"Ashenafi","suffix":""}],"badges":[],"createdAt":"2026-02-09 14:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8831449/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8831449/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103400578,"identity":"7641fa62-c90c-4fbe-b506-4d378a9ee009","added_by":"auto","created_at":"2026-02-25 09:23:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":355742,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area. Source: Administrative map - Amhara Region (2020) |OCHA (11).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8831449/v1/9778dcd7a1ab659d82753ec1.png"},{"id":103400607,"identity":"339388e9-3221-4205-848f-4284d3351f53","added_by":"auto","created_at":"2026-02-25 09:23:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3527031,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8831449/v1/da34d97a-3c70-43c5-9c38-8a053feef59c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Household Food Safety, WASH and Environmental Health Practices in the Context of Nutrition-Sensitive Agriculture: A Comparative Study in Northwest Ethiopia","fulltext":[{"header":"Background","content":"\u003cp\u003eFood safety and Water, Sanitation, and Hygiene (WASH) are foundational pillars of public health and nutritional security. In low-resource settings, the convergence of contaminated food and inadequate hygiene creates a self-reinforcing cycle of enteric disease and malnutrition. This cycle disproportionately affects vulnerable populations, particularly infants and the elderly. Globally, the World Health Organization (2022) estimates that foodborne pathogens cause 600\u0026nbsp;million illnesses and 420,000 deaths annually, resulting in 33\u0026nbsp;million disability-adjusted life years (DALYs) lost (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Children under five bear 40% of this burden, accounting for approximately 125,000 deaths per year. Consequently, food safety is a prerequisite for food security; as noted by the FAO, compromised safety undermines nutrient absorption, stalls socioeconomic development, and overburdens national healthcare systems (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegionally, Sub-Saharan Africa faces acute challenges in accessing potable water and sanitation. Estimates suggest that over two-thirds of households in the region lack improved sanitation, a primary driver of diarrheal diseases, cholera, typhoid, and parasitic infections (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In Ethiopia, diarrheal diseases remain among the leading five causes of disability‑adjusted life years (DALYs), primarily driven by unsafe water, inadequate sanitation, and child undernutrition (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Despite sustained policy attention, critical infrastructure gaps persist: only about 30% of rural households have access to safe drinking water, and fewer than 7% use improved sanitation facilities (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). National Joint Monitoring Programme (JMP) data further underscore these deficits, indicating that just 13% of households benefit from safely managed drinking water and only 8% have access to handwashing facilities with soap and water (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo address these multifaceted challenges, the Ethiopian government has prioritized multisectoral frameworks. The Productive Safety Net Programme (PSNP) has evolved from a purely social protection mechanism into a nutrition-sensitive model that integrates asset transfers with WASH infrastructure (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In parallel, the National Nutrition-Sensitive Agriculture (NSA) strategy emphasizes diversifying production and improving post-harvest handling to mitigate contamination risks. These initiatives are anchored by the Seqota Declaration (SD), Ethiopia\u0026rsquo;s flagship commitment to eradicating child undernutrition by 2030 through the integration of the health, agriculture, and WASH sectors. While implementation sites such as Ebinat Woreda demonstrate the potential of these coordinated efforts (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), emerging evidence suggests that aligning WASH infrastructure with nutrition programming is essential for improving child growth outcomes (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite Ethiopia\u0026rsquo;s robust policy landscape, a significant gap remains in the literature. Existing research has largely evaluated the PSNP, NSA, and SD in isolation, typically focusing on either food security or WASH indicators while neglecting their synergistic effects at the household level. Furthermore, empirical data on the practical barriers to integrated delivery\u0026mdash;such as institutional capacity constraints and climate variability\u0026mdash;remain scarce. This study addresses these deficiencies by systematically examining the intersection of these three frameworks in rural Ethiopia. By evaluating their collective efficacy, this research provides novel insights into the potential of multisectoral approaches to simultaneously enhance food security and WASH outcomes, ultimately informing more coherent national policy and implementation strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eStudy Setting\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in two neighboring woredas in the Amhara Region of Northwest Ethiopia, both characterized by subsistence farming and recurrent food insecurity. Ebinat, the intervention site, is one of forty woredas selected for the Seqota Declaration Innovation Phase. Located approximately 714 km northwest of Addis Ababa at elevations of 1,730 to 2,500 meters, Ebinat benefits from the integrated Productive Safety Net Program and the Seqota Declaration\u0026rsquo;s Nutrition-Sensitive Agriculture interventions. Farta woreda, located 660 km from the capital at elevations of 1,920 to 4,135 meters, served as the control site because of its comparable socioeconomic and environmental profile, despite lacking the specific integrated intervention package.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source and Study Design\u003c/h2\u003e \u003cp\u003eA cross-sectional mixed-methods design was used to evaluate the impact of these integrated interventions. Data collection took place over a two-week period from late November to early December 2022. The study used a concurrent design, triangulating quantitative household surveys with qualitative key-informant interviews to provide a comprehensive assessment of the intervention landscape. The target population consisted of mothers or primary caregivers and their children aged 6 to 23 months.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSampling Strategy\u003c/h3\u003e\n\u003cp\u003eA two-stage cluster sampling design ensured representativeness across the study area. Initially, 30% of kebeles in each woreda were selected, followed by a proportional draw of eligible households from each selected sub-district. The required sample size was determined using a standard cluster sampling formula with a 95% confidence level, a conservative prevalence estimate of 50%, a 5% margin of error, and a 10% non-response adjustment. To account for the clustered study design, the calculation incorporated a design effect of 1.45, yielding a total sample of 586 respondents, evenly distributed between the two woredas. The final cohort included 184 households receiving nutrition-sensitive agriculture support, 109 non-beneficiary households within the intervention woreda, and 293 households from the non-supported woreda.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:n=\\frac{{z}^{2}p\\left(1-p\\right)fk}{{e}^{2}}=\\:\\frac{{z}^{2}p\\left(1-p\\right)[1+\\rho\\:\\left(m-1\\right)]k}{{e}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere Z is the standard normal deviate at 95% confidence (1.96), e is the margin of error (0.05), k is the non-response adjustment factor (1.1), and the design effect (1.45) is derived from an intra-class correlation coefficient (ρ) of 0.05 and an average cluster size (m) of 10. This calculation yielded a total required sample of 586 respondents, evenly divided between the two woredas (n\u0026thinsp;=\u0026thinsp;293 each). The final sample included 184 households receiving NSA support (49 of whom also received PSNP), 109 non-beneficiary households within the intervention woreda (negative control), and 293 households from the non-supported woreda (positive control).\u003c/p\u003e\n\u003ch3\u003eData Collection and Variables\u003c/h3\u003e\n\u003cp\u003eData were collected using structured interviewer-administered questionnaires with child care takers and semi-structured interview guides with key informants. The quantitative instruments were adapted from standardized global frameworks to ensure validity and comparability. Water, sanitation, and hygiene (WASH) indicators were derived from the WHO/UNICEF Joint Monitoring Programme (JMP) core questions (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), and food safety practices were assessed using the FAO guideline (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). To ensure cultural and programmatic relevance, specific items were contextualized using instruments from the Ethiopia Demographic and Health Survey (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Qualitative data were collected through key informant interviews with community leaders, health extension workers, and agricultural agents to triangulate quantitative findings and explore perceptions of intervention effectiveness. Ten trained data collectors and one supervisor conducted interviews. Data quality was ensured through pretesting, intensive training, daily supervision, and consistency checks. Reliability testing showed acceptable internal consistency (Cronbach\u0026rsquo;s alpha\u0026thinsp;\u0026gt;\u0026thinsp;0.70) and good test\u0026ndash;retest stability, with intraclass correlation coefficients above 0.75. For categorical items, Cohen\u0026rsquo;s kappa values indicated substantial agreement. These measures collectively enhanced the reliability and validity of the study findings.\u003c/p\u003e\n\u003ch3\u003eMeasurement of Variables\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutcome variables\u003c/h2\u003e \u003cp\u003e \u003cem\u003eFood Safety Practices.\u003c/em\u003e Household food safety knowledge and practices were evaluated using a composite index developed in accordance with FAO guidelines. The index aggregated nine binary-coded items (0\u0026thinsp;=\u0026thinsp;not practiced, 1\u0026thinsp;=\u0026thinsp;practiced) across domains such as food storage, preparation, cooking, and contamination prevention, yielding a cumulative score ranging from 0 to 9. For regression analysis, this composite score was dichotomized into two categories: households with adequate food safety practices (scores\u0026thinsp;\u0026ge;\u0026thinsp;5) were coded as 1, and those with inadequate practices (scores\u0026thinsp;\u0026lt;\u0026thinsp;5) were coded as 0. This binary variable served as the dependent outcome in logistic regression models to examine associations with household characteristics and WASH conditions. Because no universally established threshold exists for food safety practices, we applied a mean-score cutoff, consistent with methodological recommendations in food safety KAP research. Households scoring at or above the sample mean were classified as having good practices, while those scoring below the mean were classified as poor. For descriptive reporting, both mean-based cut‑offs and continuous scores were used to capture context-specific variability in behaviors, whereas for inferential analyses, the dichotomized variable was retained to assess associations with socio-demographic and program-related factors (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eHousehold WASH Practices\u003c/em\u003e. WASH status was assessed using the Joint Monitoring Programme (JMP) service ladder approach, which classifies households by access to basic drinking water, sanitation, and hygiene services. Composite KAP indices for WASH were constructed using indicators of access to water supply, sanitation facilities, and hygiene practices. Access to water supply was coded as improved (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) or unimproved (0), and sanitation facilities were coded similarly as improved (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) or unimproved (0). Hygiene was assessed through knowledge of handwashing at critical times (yes\u0026thinsp;=\u0026thinsp;1, no\u0026thinsp;=\u0026thinsp;0) and the availability of a functional handwashing facility (yes\u0026thinsp;=\u0026thinsp;1, no\u0026thinsp;=\u0026thinsp;0). Attitudinal measures captured perceptions of the importance of hygiene and sanitation, and practice indicators included actual use of improved water sources and safe waste disposal methods. Each indicator was dichotomized, with correct/positive responses coded as 1 and incorrect/negative responses coded as 0. Composite scores were generated by summing across indicators within each domain. Final classifications followed Bloom\u0026rsquo;s cutoff criteria: \u0026ge;80% of the maximum score was categorized as \u0026ldquo;good,\u0026rdquo; 60\u0026ndash;79% as \u0026ldquo;moderate,\u0026rdquo; and \u0026lt;\u0026thinsp;60% as \u0026ldquo;poor\u0026rdquo; for descriptive reporting, consistent with recent applications in WASH and nutrition KAP studies (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). For inferential analyses, mean-based scores were used to explore associations with socio-demographic and program-related factors.\u003c/p\u003e \u003cp\u003e \u003cem\u003eHousehold Environment Indicators\u003c/em\u003e. Food contamination risk was proxied by environmental conditions, including the presence of animals in food preparation areas and household waste disposal methods (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExplanatory variables were stratified into four categories: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) socioeconomic factors (wealth status, land size, parental education, occupation, and program participation); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) individual characteristics (caregiver age, education, and health literacy); and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) household factors (number of children, household size, and household headship). These variables were selected based on prior literature on food security, nutrition-sensitive agriculture, and WASH outcomes in Ethiopia and sub-Saharan Africa, which consistently identifies socioeconomic status, caregiver education, household composition, and child demographics as key determinants of food safety and nutrition (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In addition, program participation variables were included to reflect Ethiopia\u0026rsquo;s policy context and capture the influence of large-scale interventions such as PSNP and the SD. The wealth index was constructed using Principal Component Analysis (PCA) of asset ownership and housing characteristics, with households categorized into poor, middle, and rich tertiles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using multivariable binary logistic regression to identify predictors of three primary outcomes: household food safety, WASH, and environmental health conditions. Variables associated with the outcome at a p-value less than 0.25 in bivariate analysis were included in the final models. Model robustness was assessed using the Hosmer\u0026ndash;Lemeshow test for goodness-of-fit and Variance Inflation Factors to assess multicollinearity. Statistical significance was defined as a p-value less than 0.05, and results were reported as Adjusted Odds Ratios. Qualitative data from key informant interviews with community leaders and health extension workers were analyzed thematically to complement and provide contextual depth to the quantitative results.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSocio-Demographic Characteristics and Study Stratification\u003c/h2\u003e \u003cp\u003eThe socio-demographic profile of the 586 households across Ebinat and Farta woredas highlights a predominantly male-headed, agrarian community with distinct variations in family structure and literacy across program beneficiary groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To evaluate the impact of multisectoral programming, the study used a stratified sampling design. In Ebinat Woreda\u0026mdash;the primary intervention site\u0026mdash;184 households received Nutrition-Sensitive Agriculture (NSA) support under the Seqota Declaration, and a subgroup of 49 households was identified as dual beneficiaries of both NSA and the Productive Safety Net Program (PSNP). This dual-beneficiary group represents the most vulnerable segment of the sample, characterized by chronic food insecurity and high dependence on social protection mechanisms. Localized and external control groups were established by including 109 non-beneficiary households from Ebinat and 293 households from Farta Woreda, the latter serving as a comparison site because of its higher agricultural productivity and proximity to administrative centers.\u003c/p\u003e \u003cp\u003eThe demographic disparities observed across these groups confirm that national programs effectively target the most vulnerable populations. Male-headed households constitute 90.8% of the total population, while female-headed households are most prevalent among the dual PSNP\u0026thinsp;+\u0026thinsp;NSA-supported group (14.3%). Maternal age is concentrated in the 20\u0026ndash;30 age range, though the PSNP\u0026thinsp;+\u0026thinsp;NSA cohort includes a higher proportion of mothers aged 31\u0026ndash;45. Household density is notably high; while 44.2% of households have 2\u0026ndash;4 members, the majority (55.8%) have five or more members. This trend toward large household size is most pronounced in the PSNP\u0026thinsp;+\u0026thinsp;NSA group, where 71.4% of households exceed four members (p\u0026thinsp;=\u0026thinsp;0.015), underscoring the concentrated nature of vulnerability among dual-support beneficiaries.\u003c/p\u003e \u003cp\u003eChild demographics and educational status further illustrate these socioeconomic barriers. Index children are fairly evenly distributed by sex, with over half aged 11\u0026ndash;23 months. However, the PSNP\u0026thinsp;+\u0026thinsp;NSA group shows a distinct pattern, with 55.1% of children aged 0\u0026ndash;5 months, suggesting high engagement with infant-targeted health and nutrition services. Regarding educational attainment, a clear \"literacy gap\" exists, particularly among mothers; 55.5% of the total maternal population cannot read or write, a figure that rises sharply to over 83% in the PSNP\u0026thinsp;+\u0026thinsp;NSA group. While fathers generally exhibit higher literacy, with 64.3% having at least a primary education, the overall low level of maternal education remains a critical factor, as it is a primary predictor of household food safety and environmental health practices.\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\u003eSocio-Demographic Characteristics in \u003cem\u003eEbinat\u003c/em\u003e and \u003cem\u003eFarta\u003c/em\u003e Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal (586)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEbinat\u003c/em\u003e (293)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eFarta\u003c/em\u003e (293)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold Headship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e100 (91.7)\u003c/p\u003e \u003cp\u003e9 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e42 (85.7)\u003c/p\u003e \u003cp\u003e7 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e123 (91.1)\u003c/p\u003e \u003cp\u003e12 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e267 (91.1)\u003c/p\u003e \u003cp\u003e26(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e532 (90.8)\u003c/p\u003e \u003cp\u003e54 (9.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale-headed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale-headed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother\u0026rsquo;s Age (Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e17(15.6)\u003c/p\u003e \u003cp\u003e68(62.4)\u003c/p\u003e \u003cp\u003e24(22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2(4.1)\u003c/p\u003e \u003cp\u003e25(51.0)\u003c/p\u003e \u003cp\u003e22(44.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e11(8.1)\u003c/p\u003e \u003cp\u003e82(30.7)\u003c/p\u003e \u003cp\u003e42(31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e31(10.6)\u003c/p\u003e \u003cp\u003e162(55.4)\u003c/p\u003e \u003cp\u003e100(34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e61(10.4)\u003c/p\u003e \u003cp\u003e337(57.5)\u003c/p\u003e \u003cp\u003e188(32.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex of the index Child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e49 (45.0)\u003c/p\u003e \u003cp\u003e60 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e30 (61.2)\u003c/p\u003e \u003cp\u003e19 (38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e59 (43.7)\u003c/p\u003e \u003cp\u003e76 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e128 (43.7)\u003c/p\u003e \u003cp\u003e165 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e266 (45.4)\u003c/p\u003e \u003cp\u003e320 (54.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of the Child (Mo)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e32 (29.4)\u003c/p\u003e \u003cp\u003e35 (32.1)\u003c/p\u003e \u003cp\u003e42 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e27 (55.1)\u003c/p\u003e \u003cp\u003e5 (10.2)\u003c/p\u003e \u003cp\u003e17 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e30 (22.2)\u003c/p\u003e \u003cp\u003e23 (17.0)\u003c/p\u003e \u003cp\u003e82 (60.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e70 (23.9)\u003c/p\u003e \u003cp\u003e64 (21.8)\u003c/p\u003e \u003cp\u003e159 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e159 (27.1)\u003c/p\u003e \u003cp\u003e127 (21.7) 300 (51.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e89 (81.7)\u003c/p\u003e \u003cp\u003e20 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e31 (63.3)\u003c/p\u003e \u003cp\u003e18 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e95 (70.4)\u003c/p\u003e \u003cp\u003e40 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e249 (84.9)\u003c/p\u003e \u003cp\u003e44 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e464 (79.2)\u003c/p\u003e \u003cp\u003e122 (20.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e50 (45.87)\u003c/p\u003e \u003cp\u003e59 (54.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e14 (28.57)\u003c/p\u003e \u003cp\u003e35 (71.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e48 (35.55)\u003c/p\u003e \u003cp\u003e87 (64.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e147 (50.17)\u003c/p\u003e \u003cp\u003e146 (49.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e259 (44.20)\u003c/p\u003e \u003cp\u003e327 (55.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (Mother)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e59 (54.1)\u003c/p\u003e \u003cp\u003e29 (26.6)\u003c/p\u003e \u003cp\u003e21 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e42 (85.7)\u003c/p\u003e \u003cp\u003e7 (14.3)\u003c/p\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e85 (62.9)\u003c/p\u003e \u003cp\u003e29 (21.5)\u003c/p\u003e \u003cp\u003e21 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e139 (47.4)\u003c/p\u003e \u003cp\u003e109 (37.2)\u003c/p\u003e \u003cp\u003e48 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e325 (55.5)\u003c/p\u003e \u003cp\u003e178 (30.4)\u003c/p\u003e \u003cp\u003e90 (15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read/write\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (Father)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e43 (39.5)\u003c/p\u003e \u003cp\u003e48 (44.0)\u003c/p\u003e \u003cp\u003e18 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e34 (69.4)\u003c/p\u003e \u003cp\u003e3 (6.1)\u003c/p\u003e \u003cp\u003e12 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e44 (32.6)\u003c/p\u003e \u003cp\u003e57 (42.2)\u003c/p\u003e \u003cp\u003e34 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e88 (30.0)\u003c/p\u003e \u003cp\u003e142 (48.5)\u003c/p\u003e \u003cp\u003e63 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e209 (35.7)\u003c/p\u003e \u003cp\u003e261 (44.5)\u003c/p\u003e \u003cp\u003e116 (19.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read/write\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary \u0026amp; above\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEconomic Status of Study Households\u003c/h2\u003e \u003cp\u003eThe economic profile of the sampled households underscores a landscape of agrarian subsistence, where a critical paradox exists between near-universal land ownership and actual productive capacity. Agriculture is the primary economic pillar, with 60.4% of mothers engaged in farming and 30.4% supplementing income through petty trading or daily labor. Land ownership is nearly universal (97.6%), yet the majority of households (60.8%) manage holdings of less than one hectare. This land scarcity is most acute in the Farta control group, where 80.4% of households cultivate less than a hectare.\u003c/p\u003e \u003cp\u003eThe composite wealth index further highlights a high degree of economic precariousness, with 42.8% of the study population classified as poor. Notably, the distribution of wealth does not align uniformly with land size. While Farta households have smaller landholdings and represent a larger share of the \"poor\" category (54.3%), Ebinat households\u0026mdash;particularly those receiving NSA support\u0026mdash;report larger landholdings, with 23% managing more than two hectares. Furthermore, dual PSNP\u0026thinsp;+\u0026thinsp;NSA-supported households are concentrated in the rich tertile (55.1%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese economic determinants are essential to understanding behavioral outcomes. The prevalence of small-scale farming indicates that even for those with access to land, the ability to generate a surplus for investment in WASH or food safety infrastructure remains constrained.\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\u003eSocio-Economic Status in \u003cem\u003eEbinat\u003c/em\u003e and \u003cem\u003eFarta\u003c/em\u003e Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal (586)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEbinat\u003c/em\u003e (293)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eFarta\u003c/em\u003e (293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation (mother)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e199 (63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e354 (60.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePetty trader/Daily laborer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e168 (30.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther(Brewing local beer- \u003cem\u003eTella\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e30 (5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLand ownership\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103(94.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46(93.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e132(97.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e291(99.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e572(97.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6(5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3(2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3(2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2(0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14(2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCultivable land size (ha)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; a hectare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56 (51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (51.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66 (48.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e209 (80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e356 (60.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 to 2 hectares\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44 (40.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e163 (27.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;2 hectares\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e67 (11.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth Index\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24(22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57(42.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e159(54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e251(42.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38(34.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22(16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e149(25.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47(43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56(41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e186(31.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHousehold Food Safety Awareness, Knowledge, and Practices\u003c/h2\u003e \u003cp\u003eThe assessment of food safety reveals a complex interplay among programmatic outreach, structural constraints, and entrenched cultural habits (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Awareness and training are strongly influenced by program participation; although fewer than half of all households (48.0%) have received food safety information, engagement is significantly higher among intervention groups. Dual beneficiaries of the PSNP\u0026thinsp;+\u0026thinsp;NSA reported the highest levels of awareness (61.2%) and formal training attendance (51.0%), contrasting sharply with non-supported households in Farta, where training reached only 10.9%. Practical cooking demonstrations followed this trend, reaching over half of NSA-supported households but only a quarter of the non-supported group, suggesting that multisectoral platforms are effective vehicles for disseminating information.\u003c/p\u003e \u003cp\u003eIn contrast to these knowledge-based indicators, physical infrastructure for food safety shows a reverse trend that highlights a persistent vulnerability. Households without support are significantly more likely to have a dedicated kitchen (84.3%) than the most vulnerable PSNP\u0026thinsp;+\u0026thinsp;NSA beneficiaries (49.0%). This infrastructure gap is critical because shared living and cooking spaces increase cross-contamination risks regardless of a caregiver's knowledge. Despite these structural deficits, adherence to fundamental storage hygiene is nearly universal; over 99% of households use storage raised at least 20 cm above the floor, and 100% of the study population reports separating raw and cooked items.\u003c/p\u003e \u003cp\u003eSelf-reported food-handling behaviors remain robust for basic tasks but variable for more intensive safety measures. While 95.9% of respondents wash raw produce with clean water, only about half (50.9%) report boiling milk or water\u0026mdash;a practice more common among non-supported households, potentially reflecting fuel access rather than technical knowledge. Cultural dietary preferences often override safety awareness; only 10.8% of the total sample avoids raw food entirely, and even among the highly trained PSNP\u0026thinsp;+\u0026thinsp;NSA group, nearly 78% continue to consume raw items despite known pathogenic risks.\u003c/p\u003e \u003cp\u003eFood preservation remains almost exclusively reliant on low-technology, traditional methods. Meat drying is the predominant strategy (83.6%), followed by salting (54.6%) and smoking (23.7%). Modern preservation technologies are virtually non-existent, with refrigeration used by only 6.0% of households\u0026mdash;primarily within the non-supported Farta group. This technological gap constrains long-term storage capacity and underscores the need for future interventions to move beyond knowledge dissemination to improve physical infrastructure and preservation technology.\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\u003eFood safety awareness, knowledge and practices by program participation status in the study Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;586)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eEbinat(293)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eFarta(293)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOnly NSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eNon-supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAwareness on food safety\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver heard about food safety(yes)\u003c/p\u003e \u003cp\u003eEver attended food safety training(yes)\u003c/p\u003e \u003cp\u003eEver attended a cooking demonstration(yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (55.0)\u003c/p\u003e \u003cp\u003e20 (18.3)\u003c/p\u003e \u003cp\u003e39 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (61.2)\u003c/p\u003e \u003cp\u003e25 (51.0)\u003c/p\u003e \u003cp\u003e27 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76 (56.3)\u003c/p\u003e \u003cp\u003e50 (37.0)\u003c/p\u003e \u003cp\u003e68 (50.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115 (39.2)\u003c/p\u003e \u003cp\u003e32 (10.9)\u003c/p\u003e \u003cp\u003e76 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e281 (48.0)\u003c/p\u003e \u003cp\u003e127 (21.7)\u003c/p\u003e \u003cp\u003e210 (35.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold food hygiene and storage practices\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShelf/food storage for cooked food \u0026amp; utensils\u003c/p\u003e \u003cp\u003eStorage raised\u0026thinsp;\u0026ge;\u0026thinsp;20 cm above floor\u003c/p\u003e \u003cp\u003eCooked food stored in sealed/covered containers\u003c/p\u003e \u003cp\u003eCooked and raw food kept separately\u003c/p\u003e \u003cp\u003eSeparate kitchen available\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (81.7)\u003c/p\u003e \u003cp\u003e89 (100.0)\u003c/p\u003e \u003cp\u003e105 (96.3)\u003c/p\u003e \u003cp\u003e109 (100.0)\u003c/p\u003e \u003cp\u003e67 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (65.3)\u003c/p\u003e \u003cp\u003e30 (93.8)\u003c/p\u003e \u003cp\u003e49 (100.0)\u003c/p\u003e \u003cp\u003e49 (100.0)\u003c/p\u003e \u003cp\u003e24 (49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106 (78.5)\u003c/p\u003e \u003cp\u003e106 (100.0)\u003c/p\u003e \u003cp\u003e130 (96.3)\u003c/p\u003e \u003cp\u003e135 (100.0)\u003c/p\u003e \u003cp\u003e88 (65.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e259 (88.4)\u003c/p\u003e \u003cp\u003e259 (100.0)\u003c/p\u003e \u003cp\u003e289 (98.6)\u003c/p\u003e \u003cp\u003e293 (100.0)\u003c/p\u003e \u003cp\u003e247 (84.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e486 (82.9)\u003c/p\u003e \u003cp\u003e484 (99.6)\u003c/p\u003e \u003cp\u003e573 (97.8)\u003c/p\u003e \u003cp\u003e586 (100.0)\u003c/p\u003e \u003cp\u003e426 (72.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eActions to make raw food safe\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWash with clean water (vegetables/fruits)\u003c/p\u003e \u003cp\u003eBoil (milk and water)\u003c/p\u003e \u003cp\u003eFerment (milk for yogurt)\u003c/p\u003e \u003cp\u003eDo not consume raw foods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (89.9)\u003c/p\u003e \u003cp\u003e38 (34.9)\u003c/p\u003e \u003cp\u003e22 (20.2)\u003c/p\u003e \u003cp\u003e2 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (100.0)\u003c/p\u003e \u003cp\u003e23 (46.9)\u003c/p\u003e \u003cp\u003e6 (12.2)\u003c/p\u003e \u003cp\u003e11 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (97.0)\u003c/p\u003e \u003cp\u003e62 (45.9)\u003c/p\u003e \u003cp\u003e30 (22.2)\u003c/p\u003e \u003cp\u003e16 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e284 (96.9)\u003c/p\u003e \u003cp\u003e175 (59.7)\u003c/p\u003e \u003cp\u003e71 (24.2)\u003c/p\u003e \u003cp\u003e34 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e562 (95.9)\u003c/p\u003e \u003cp\u003e298 (50.9)\u003c/p\u003e \u003cp\u003e129 (22.0)\u003c/p\u003e \u003cp\u003e63 (10.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocal food preservation methods\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeat drying\u003c/p\u003e \u003cp\u003eMeat salting\u003c/p\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003cp\u003eRefrigeration\u003c/p\u003e \u003cp\u003eOther methods(Drying \u003cem\u003eInjera\u003c/em\u003e/local bread in the sun)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (85.3)\u003c/p\u003e \u003cp\u003e47 (43.1)\u003c/p\u003e \u003cp\u003e36 (33.0)\u003c/p\u003e \u003cp\u003e1 (0.9)\u003c/p\u003e \u003cp\u003e7 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (89.8)\u003c/p\u003e \u003cp\u003e19 (38.8)\u003c/p\u003e \u003cp\u003e16 (32.7)\u003c/p\u003e \u003cp\u003e1 (2.0)\u003c/p\u003e \u003cp\u003e8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116 (85.9)\u003c/p\u003e \u003cp\u003e79 (58.5)\u003c/p\u003e \u003cp\u003e27 (20.0)\u003c/p\u003e \u003cp\u003e8 (5.9)\u003c/p\u003e \u003cp\u003e15 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e237 (80.9)\u003c/p\u003e \u003cp\u003e175 (54.7)\u003c/p\u003e \u003cp\u003e60 (20.5)\u003c/p\u003e \u003cp\u003e25 (8.5)\u003c/p\u003e \u003cp\u003e34 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e490 (83.6)\u003c/p\u003e \u003cp\u003e320 (54.6)\u003c/p\u003e \u003cp\u003e139 (23.7)\u003c/p\u003e \u003cp\u003e35 (6.0)\u003c/p\u003e \u003cp\u003e64 (10.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eWater, Sanitation, and Hygiene (WASH)\u003c/h2\u003e \u003cp\u003eThe assessment of water supply and handling highlights a strong reliance on improved water sources, yet significant challenges persist regarding collection burdens and point-of-use treatment. Overall, 81.7% of the 586 households use improved sources, with shallow wells equipped with hand pumps serving as the primary supply for half of the study population (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAccess and Supply Adequacy\u003c/strong\u003e \u003cp\u003e \u003cem\u003eAccess quality varies markedly by program status. Households receiving NSA-only support reported the highest use of improved sources (90.4%), whereas non-beneficiaries in Ebinat relied most on unimproved sources (29.4%), such as rivers and unprotected springs. Despite the high prevalence of \"safe\" sources, only 67.9% of households described their supply as adequate for daily needs, suggesting that physical presence does not guarantee sufficient quantity.\u003c/em\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCollection Burdens and Storage\u003c/strong\u003e \u003cp\u003eThe logistical burden of water collection remains a substantial barrier to household hygiene and a primary driver of \"time poverty.\" Only 22.4% of households reach their water source in under 30 minutes, while nearly 30% of the population spends more than 90 minutes per trip. This burden is particularly acute for dual PSNP\u0026thinsp;+\u0026thinsp;NSA beneficiaries, nearly 40% of whom travel more than an hour and a half for water. Once collected, water is almost exclusively stored in plastic jerry cans (87.2%). While these are easier to transport than traditional clay pots, they are prone to biofilm accumulation and require consistent cleaning to maintain water quality.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTreatment Practices and Safety Gaps\u003c/b\u003e: A critical vulnerability in the WASH chain is the low rate of point-of-use water treatment. Despite the high risks of contamination during transport and storage, only a small fraction of households adopt safety measures. Chemical treatment with household brands of \u0026lsquo;Waterguard\u0026rsquo; (sodium hypochlorite) or \u0026lsquo;Aquatabs\u0026rsquo; (sodium dichloro-isocyanurate), is the most common method for water disinfection, used by 15.9% of households, whereas boiling water is exceptionally rare at 3.4%. This discrepancy underscores a major gap: while programs have successfully increased physical hardware, such as hand pumps, the behavioral component of ensuring that water remains safe until consumption remains unaddressed.\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\u003eWater supply sources, access, collection time, storage, and treatment practices among households in the study Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;586)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEbinat (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFarta (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnly NSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon-supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWater Supply Condition\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnimproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e107 (18.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImproved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (70.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122 (90.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e240 (81.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e479 (81.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMain source of water\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShallow wells with hand pump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (50.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92 (68.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e295 (50.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnprotected spring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93 (15.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePiped water \u0026amp; public tap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e120 (20.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHand dug well in the village\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 (3.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpring water (capped)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42 (7.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnprotected well\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (0.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerception on Water Safety and Adequacy\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSafe drinking water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (79.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125 (92.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e243 (82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e482 (82.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate water supply\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (68.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e202 (68.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e398 (67.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime taken to collect water\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e131 (22.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;60 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e254 (43.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e61\u0026ndash;90 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e91\u0026ndash;120 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110 (18.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;120 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63 (10.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of storage\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlastic jerry can\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (80.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (87.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115 (85.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e265 (90.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e511 (87.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClay pot (\u003cem\u003eInsira\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoth Jerry can and Clay pot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69 (11.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWater treatment methods\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater-guard/Aquatabs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93 (15.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrain through cloth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (1.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSanitation Conditions and Latrine Coverage\u003c/h2\u003e \u003cp\u003eSanitation in the study area reveals a landscape of high utilization but low-quality infrastructure. Overall, 66.9% of households reported having a latrine, though access was unevenly distributed across geographic areas. Coverage peaked in Farta (85.3%) but dropped to 38.5% among non-beneficiaries in Ebinat. Despite these disparities, latrine utilization among those with facilities was nearly universal at 97.4%, suggesting that behavioral intent is well established (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, facility quality remains a critical concern. The vast majority (86.7%) relied on unimproved traditional latrines, while only 11.5% used improved facilities. Although PSNP\u0026thinsp;+\u0026thinsp;NSA beneficiaries reported the highest prevalence of improved latrines (21.1%), overall structural integrity was poor; only 41.2% had well-covered floors. This limits the effectiveness of latrines in breaking the cycle of disease transmission. Furthermore, only 39.0% of households maintained a handwashing facility near their latrine, and the hardware consisted mostly of low-cost solutions such as jugs or tippy taps.\u003c/p\u003e \u003cp\u003eFor the third of the population without latrine access, open defecation remains the primary alternative. A striking 90.3% of these households reported that all members defecated in the bush or near the homestead. These patterns reveal a gendered dimension to environmental exposure, with women and girls often restricted to areas closer to the home, underscoring persistent gaps among the most vulnerable.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHousehold sanitation situation, latrine coverage, and associated hygiene practices in the study Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndicator/Parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;586)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEbinat Woreda (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFarta (293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnly NSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon- supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLatrine facility\u003c/b\u003e:\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLatrine coverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e250 (85.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e392 (66.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnimproved (Traditional)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35 (83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (78.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e71 (87.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e219 (87.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e340 (86.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImproved latrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45 (11.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFloor well covered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (59.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e161 (41.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll family members are using latrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40 (95.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78 (96.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e245 (98.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e382 (97.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHandwashing facility near to the latrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95 (38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e153 (39.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoap/ash used for hand cleansing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27 (69.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58 (61.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99 (64.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of handwashing facility\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSink with running water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33 (21.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJug\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48 (50.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61 (39.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTippy tap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48 (50.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61 (39.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePace of defecation, if no latrine\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\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 \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen and women defecate in the bush/near the house\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62 (93.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (80.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49 (92.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43 (91.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178 (90.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen and girls defecate near the house\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen/boys defecate in the bush\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (4.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eHandwashing Knowledge and Practices\u003c/h2\u003e \u003cp\u003eAnalysis of handwashing behaviors reveals a moderate level of theoretical awareness, tempered by significant gaps in critical hygiene stages, particularly those related to food preparation. Maternal knowledge is strongest regarding childcare; 68.9% of mothers identified the importance of washing hands after changing a baby\u0026rsquo;s nappy, and 56.3% recognized the need after toilet use. However, literacy declines regarding dietary milestones; only 53.1% were aware of the need to wash hands before preparing food. The most significant deficit involves post-contamination awareness, with only 27.3% identifying handwashing after handling raw food as a requirement.\u003c/p\u003e \u003cp\u003eDespite this knowledge base, a \"knowledge-practice gap\" persists regarding consistent soap use. Although 60.9% reported using soap after using the toilet, 5.8% admitted not using soap at all, relying solely on water. Adherence remains lowest among non-beneficiaries, suggesting that economic or physical barriers to soap access may undermine even the best-informed households. These findings indicate that while multisectoral programs improve hygiene literacy, they have yet to bridge the gap in specific food-safety behaviors, such as washing hands after handling raw ingredients (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHousehold knowledge and practice of handwashing at critical times in the study Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;586)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEbinat Woreda (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFarta (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnly NSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon- supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCritical times for handwashing(Knowledge)\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter going to the toilet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (61.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77 (57.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e169 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e330 (56.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter changing a baby's nappy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (50.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (63.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106 (78.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e212 (72.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e404 (68.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBefore preparing/handling food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e185 (63.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e311 (53.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBefore feeding a child/ eating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164 (56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e294 (50.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter handling raw food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84 (28.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e160 (27.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter handling garbage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e211 (72.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e323 (55.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDon\u0026rsquo;t Know\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54 (9.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCritical times for handwashing with soap(Practice)\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter going to toilet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (62.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (67.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84 (62.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e172 (58.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e357 (60.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter cleaning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e137 (46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e256 (43.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBefore preparing/handling food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (61.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151 (51.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e325 (55.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBefore feeding a child/ eating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (41.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e314 (53.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter handling raw food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e167 (28.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter handling garbage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (35.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189 (64.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e292 (49.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers(did not use soap at all)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34 (5.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoap used before feeding child (last time)_proving for specific\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (59.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 (58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e179 (61.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e346 (59.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEnvironmental Health Practices\u003c/h2\u003e \u003cp\u003eThe assessment reveals a significant disconnect between high hygiene awareness and the persistence of hazardous disposal methods (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). While most participants recognized basic hygiene as a primary defense against pathogens, with 83.1% identifying handwashing and 79.5% citing safe fecal removal, prioritization varied. Handwashing awareness was highest among non-supported households in Farta (90.1%), whereas dual PSNP\u0026thinsp;+\u0026thinsp;NSA beneficiaries had the highest fecal management adherence (89.8%), likely reflecting targeted sanitation messaging. However, only 1.4% of households identified drinking safe water as a preventive action.\u003c/p\u003e \u003cp\u003eSolid waste management practices reflect a tension between traditional agricultural utility and environmental risk. Composting was used by 37.0% of the sample, while 38.9% disposed of waste directly onto farmland, a practice particularly common among non-beneficiaries in Ebinat (56.9%). More hazardous practices remain prevalent; 39.8% of households burned their waste, and nearly 10% reported indiscriminate disposal on public roads.\u003c/p\u003e \u003cp\u003eLiquid waste management further highlights infrastructure constraints. Although draining into boreholes was the predominant method (62.3%), especially in Farta (74.1%), nearly half of the population (48.1%) still flushes liquid waste directly into their compounds. This practice was most pronounced among non-beneficiaries in Ebinat (67.9%) and among PSNP\u0026thinsp;+\u0026thinsp;NSA households (73.5%), creating significant localized contamination risks. This indicates that behavioral knowledge is currently outpacing the development of physical infrastructure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHousehold environmental health knowledge and waste management practices in the study Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndicator / Parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;586)\u003c/p\u003e \u003cp\u003e(Multiple responses)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEbinat (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFarta (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnly NSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNon- supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKnowledge-Actions to avoid sickness from germs\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWash hands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112 (83.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e264 (90.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e487 (83.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemove faeces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (89.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106 (78.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e241 (82.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e466 (79.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (drink safe water)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold solid waste disposal\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComposting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e217 (37.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBurn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e152 (51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e233 (39.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisposing on farm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70 (51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70 (23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e228 (38.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrowing on road\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58 (9.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold liquid waste disposal\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlush in the compound\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (67.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (48.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106 (36.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e282 (48.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrain in bore whole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87 (64.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e217 (74.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e365 (62.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis of Household Food Safety, WASH, and Environmental Health\u003c/h2\u003e \u003cp\u003eThe composite analysis reveals a bifurcated public health landscape, with gains in physical infrastructure coexisting with stagnation in behavioral safety. Integrated program participation (PSNP and NSA) has improved WASH outcomes, yet a substantial deficit persists in food safety behaviors (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eThe Food Safety Bottleneck\u003c/h2\u003e \u003cp\u003eFood safety is the primary behavioral weakness across the population. According to Bloom\u0026rsquo;s criteria, 74.2% of households exhibited poor food safety practices. Even among dual PSNP\u0026thinsp;+\u0026thinsp;NSA beneficiaries, the \"good\" practice threshold remained low, suggesting that economic advancement and agricultural support do not automatically translate into safer food-handling practices.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eBridging the Knowledge-Practice Gap\u003c/h2\u003e \u003cp\u003eA compelling divergence exists between theoretical knowledge and practical application. Households in Farta had the highest levels of hygiene literacy (56.0% \"good\" knowledge), yet a critical reversal in practice emerged: PSNP\u0026thinsp;+\u0026thinsp;NSA households had the highest prevalence of \"good\" hygiene practices (44.9%). This indicates that targeted programmatic support serves as a vital bridge, translating even modest health literacy into safer behaviors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eResponsive Infrastructure vs. Stagnant Environments\u003c/h2\u003e \u003cp\u003ePhysical WASH conditions appear highly responsive to multisectoral interventions. Overall, 59.2% of households reported adequate WASH conditions, with significantly higher rates among PSNP\u0026thinsp;+\u0026thinsp;NSA (73.5%) and NSA-only (68.9%) beneficiaries. However, broader environmental health conditions remain mixed. More than half of the population lived in poor environmental conditions, underscoring that a clean domestic environment requires more than infrastructure; it also necessitates integrating maternal literacy and targeted institutional support.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComposite index of household food safety, hygiene and sanitation knowledge and practices, WASH, and environmental health condition in study Woredas, 2023, n\u0026thinsp;=\u0026thinsp;586\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\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003cp\u003e(Transformed Variables)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eHousehold No (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;586)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eEbinat(n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eFarta(n\u0026thinsp;=\u0026thinsp;293\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-beneficiary (n\u0026thinsp;=\u0026thinsp;109)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported (n\u0026thinsp;=\u0026thinsp;49)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOnly NSA supported (n\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eNon- supported (n\u0026thinsp;=\u0026thinsp;293)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood Safety practice _Mean cut-off point\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84(77.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98(72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e218(74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e435(74.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25(22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37(27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e75(25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e151(25.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood Safety practice _Bloom\u0026rsquo;s cut-off point\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (77.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (71.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e218 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e435 (74.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e50 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98 (16.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e25 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e53 (9.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHygiene \u0026amp; Sanitation Knowledge _Mean cut-off point\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81(74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75(55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e129(44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e313(53.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28(25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60(44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e164(56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e273(46.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHygiene \u0026amp; Sanitation Knowledge _Bloom\u0026rsquo;s cut-off point\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e129 (44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e313 (53.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e61 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e117 (20.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e103 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e156 (26.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHygiene \u0026amp; Sanitation Practice _Mean cut-off point\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76(69.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87(64.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e173(59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e363(61.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33(30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(44.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48(35.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e120(41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e223(38.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHygiene \u0026amp; Sanitation practice _Bloom\u0026rsquo;s cut-off point\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (67.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 (74.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e216 (73.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e439 (74.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e74 (12.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e73 (12.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold WASH Condition\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInadequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (31.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e155 (52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e239 (40.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (73.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (68.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e138 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e347 (59.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold Environment Condition\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (73.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (79.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129 (44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e322 (54.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164 (56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e264 (45.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of Household Food Safety Practices\u003c/h2\u003e \u003cp\u003eThe binary logistic regression analysis identifies several factors that are significantly associated with household food safety practices in the study woredas (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Program participation status did not show a statistically significant effect. Households in PSNP\u0026thinsp;+\u0026thinsp;NSA, NSA-only, or non-supported woredas had lower odds ratios than non-beneficiaries in supported woredas, but none reached statistical significance.\u003c/p\u003e \u003cp\u003eHousehold headship was an important predictor, with female-headed households less likely to report poor food safety practices than male-headed households (AOR\u0026thinsp;=\u0026thinsp;0.444, p\u0026thinsp;=\u0026thinsp;0.038). This suggests that women\u0026rsquo;s leadership may positively influence household hygiene. Parental literacy showed mixed effects: mothers\u0026rsquo; literacy was not significant, whereas households in which fathers could not read or write had significantly lower odds of poor practices (AOR\u0026thinsp;=\u0026thinsp;0.558, p\u0026thinsp;=\u0026thinsp;0.021), indicating a possible protective role of paternal literacy.\u003c/p\u003e \u003cp\u003eAwareness emerged as a strong determinant, as households that had never heard of food safety were more than twice as likely to report poor practices (AOR\u0026thinsp;=\u0026thinsp;2.360, p\u0026thinsp;=\u0026thinsp;0.013). Training and cooking demonstrations showed inconsistent results; not attending training increased the odds (AOR\u0026thinsp;=\u0026thinsp;1.225), but the reported p-value (0.000) conflicted with the confidence interval, and cooking demonstrations were not significant.\u003c/p\u003e \u003cp\u003eSocioeconomic status was a clear predictor, with medium- and high-income households significantly less likely to report poor practices than low-income households (AOR\u0026thinsp;=\u0026thinsp;0.445 and 0.415, both p\u0026thinsp;=\u0026thinsp;0.001), highlighting the role of economic capacity in enabling safer food handling.\u003c/p\u003e \u003cp\u003eMost notably, the frequency of Health Extension Worker (HEW) visits was consistently associated with protection. Households visited every six months, quarterly, monthly, or biweekly all showed substantially reduced odds of poor practices (AORs ranging from 0.200 to 0.269, all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings emphasize that awareness creation, socioeconomic empowerment, and strengthening HEW outreach are pivotal strategies for improving household food safety practices; however, program participation alone may be insufficient without complementary interventions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of Binary Logistic Regression Analysis for factors affecting Food Safety Practices in Study Woredas(n\u0026thinsp;=\u0026thinsp;586)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable / Parameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003cp\u003e(Exp (B))\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e95% C.I. for EXP(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgram Participation Status\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-beneficiary in Supported Woreda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA Supported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSA Supported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-supported Woreda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold Headship\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.957\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiteracy status of mothers\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRead or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiteracy status of husbands\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRead or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEver heard about food safety\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttended food safety training\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttended cooking demonstration\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMember in mothers group/ association\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of HEWs visit\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo visit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery six month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery two weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth Index\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePredictors of Household WASH Condition\u003c/h2\u003e \u003cp\u003eThe regression analysis identifies program participation and economic status as the primary determinants of WASH adequacy (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Dual support from PSNP and NSA made households nearly three times more likely to report adequate WASH conditions (AOR\u0026thinsp;=\u0026thinsp;2.948), while NSA support alone had even higher odds (AOR\u0026thinsp;=\u0026thinsp;3.356).\u003c/p\u003e \u003cp\u003eWealth status was a definitive determinant, with medium (AOR\u0026thinsp;=\u0026thinsp;0.136) and rich (AOR\u0026thinsp;=\u0026thinsp;0.333) households significantly more likely to maintain adequate WASH conditions. Interestingly, parental literacy and household headship did not significantly predict WASH adequacy, suggesting that the physical \"adequate\" status of WASH is driven more by material resources and large-scale infrastructure than by individual counseling or health literacy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of Binary Logistic Regression Analysis for Factors Affecting Household WASH Status in the study Woreda, 2023, n\u0026thinsp;=\u0026thinsp;586\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003cp\u003e(Exp (B))\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e95% C.I.for EXP(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipation in programs\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-beneficiary HHs in supported Woreda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported HHs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSA supported HHs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-supported HHs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold headship\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiteracy status of mothers\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRead or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiteracy status of husbands\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRead or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLand ownership\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessed credit\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMember in mothers group/ association\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of HEWs visits\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo visit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery six month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery two weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth Index\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003ePredictors of Household Environment Condition\u003c/h2\u003e \u003cp\u003eThe regression analysis identified program participation, maternal literacy, wealth status, HEW visits, and community engagement as the strongest predictors of household environmental health (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). Households supported by PSNP\u0026thinsp;+\u0026thinsp;NSA or NSA-only programs had significantly lower odds of poor practices, while medium- and rich households reported better outcomes than poor households, underscoring the role of socioeconomic empowerment. Maternal literacy emerged as a critical determinant, with mothers who cannot read or write a simple sentence more than twice as likely to report poor practices (AOR\u0026thinsp;=\u0026thinsp;2.543), highlighting women\u0026rsquo;s central role in managing the domestic environment. Practical education also mattered: households that attended cooking demonstrations were nearly three times more likely to report favorable outcomes (AOR\u0026thinsp;=\u0026thinsp;2.684), emphasizing the importance of experiential learning. This underscores that environmental management is a specialized skill set driven by maternal education and experiential learning rather than by general agricultural assets.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHousehold Environmental Health Situation in the study Woredas, n\u0026thinsp;=\u0026thinsp;586.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003cp\u003e(Exp(B))\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e95% C.I.for EXP(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgram participation status\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-beneficiary in Supported Woreda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSNP\u0026thinsp;+\u0026thinsp;NSA supported HHs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSA supported HHs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-supported HHs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold headship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLand ownership\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiteracy status of mothers\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRead or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiteracy status of husbands\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRead or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot read or write a simple sentence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.288\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold received extension service\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of HEWs visits\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo visit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery six month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuarterly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvery two weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMember in mothers' group\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttended food safety training\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttended a cooking demonstration\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccessed credit\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated the determinants of household food safety, WASH, and environmental health across Ebinat and Farta woredas, revealing distinct drivers and a persistent knowledge\u0026ndash;practice gap. A consistent theme was the gap between knowledge and practice: while households demonstrated moderate awareness of hygiene, this awareness did not consistently translate into risk‑reducing behaviors. Beneficiary households participating in PSNP and NSA interventions reported higher levels of training participation, yet the overall prevalence of good food safety practices remained low. This suggests that current educational models are insufficient without concurrent structural support. These findings echo FAO\u0026rsquo;s (2020) conclusion that food safety education alone rarely achieves sustainable behavioral change unless paired with systemic reinforcement, and align with evidence that literacy and awareness are stronger predictors of food safety behaviors than program participation alone (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eFood Safety: The Literacy-Behavior Gap\u003c/h2\u003e \u003cp\u003eFood safety emerged as the weakest behavioral domain, with nearly three‑quarters of households demonstrating poor practices. Socioeconomic and informational factors, particularly paternal literacy and prior exposure to food safety information, were the strongest protective influences, confirming the importance of education and awareness campaigns. This finding aligns with UNICEF (2021), which emphasizes that basic literacy enhances uptake of health and nutrition messages. Programmatic interventions such as food safety training, HEW visits, and mothers\u0026rsquo; group participation showed limited impact, consistent with evidence from community‑based nutrition programs, where technical training alone has a limited effect unless reinforced by broader literacy (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Structural constraints further compounded risks: only half of PSNP\u0026thinsp;+\u0026thinsp;NSA households had separate kitchens, and reliance on traditional preservation methods such as meat drying and salting posed contamination risks. These structural constraints further compounded contamination risks. These findings align with regional data showing significantly lower food safety compliance in less-resourced areas compared to urban centers (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eWASH Outcomes: The Role of Institutional Support\u003c/h2\u003e \u003cp\u003eUnlike food safety, WASH outcomes were primarily driven by institutional support and socioeconomic empowerment. Participation in PSNP and NSA interventions made households nearly three times more likely to report adequate WASH, confirming that integrated nutrition-sensitive models effectively enhance access to infrastructure (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Although most households used improved water sources, significant challenges remain, including long collection times and low use of point-of-use treatment. Wealthier households maintained superior conditions, reflecting the need for economic resources to invest in latrines and soap. However, the lack of association between literacy and WASH adequacy suggests that infrastructure is the primary limiting factor (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Even with high awareness, persistent gaps, such as the scarcity of handwashing stations near latrines, undermine health gains. These results emphasize the need to upgrade traditional facilities and integrate food safety into WASH curricula to break the cycle of enteric infections (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003eHousehold Environmental Health: A Hybrid Determinant\u003c/h2\u003e \u003cp\u003eEnvironmental health followed a hybrid pattern, shaped by program participation, wealth, and maternal literacy. Households receiving integrated support were significantly less likely to report poor conditions, consistent with findings that WASH education improves sanitation behaviors in rural Ethiopia (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Notably, maternal literacy was a critical predictor, with literate mothers twice as likely to maintain favorable conditions. This underscores the central role of women\u0026rsquo;s education in household health management (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). While socioeconomic status enables investment in sanitation, reliance on borehole drainage and the coexistence of composting and burning reflect ongoing resource constraints. Ethiopia\u0026rsquo;s National WASH and Environmental Health Strategy advocates combining community education with infrastructure provision to mitigate these risks (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eCross-Cutting Implications\u003c/h2\u003e \u003cp\u003eThe evidence suggests that food safety is predominantly knowledge-driven, whereas WASH and environmental health are infrastructure-driven. Three cross-cutting implications emerge for public health policy. First, education acts as a catalyst; paternal literacy promotes safer food handling, while maternal literacy strengthens domestic environmental management. Second, an economic\u0026ndash;infrastructural nexus exists in which households require both knowledge and resources to overcome structural barriers such as shared kitchens or unimproved latrines. Third, nutrition-sensitive agriculture serves as a viable multisectoral platform for delivering integrated interventions that can effectively reduce childhood growth faltering.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eStrengths, Limitations, and Future Research\u003c/h2\u003e \u003cp\u003eA major strength of this study is its simultaneous examination of three critical domains, food safety, WASH, and environmental health, within a single population, providing a holistic view of household health determinants. However, the cross-sectional design precludes causal inference, and self-reported data may be subject to social desirability bias. Future research should use longitudinal and observational methods to capture seasonal dynamics and reduce self-report bias. Expanding geographic coverage and examining the role of market systems and regulatory frameworks will be essential. Ultimately, intervention trials that integrate literacy promotion with infrastructure investment will provide the most robust evidence for improving health outcomes in rural Ethiopia.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study underscores the complex and interrelated determinants of household food safety, WASH, and environmental health in rural Ethiopia. While integrated, multisectoral interventions such as the PSNP and NSA have successfully improved hygiene and sanitation behaviors, food safety practices remain persistently poor and structurally constrained.\u003c/p\u003e \u003cp\u003eDistinct behavioral drivers emerged across domains: hygiene outcomes were primarily shaped by institutional support and program participation; food safety behaviors were strongly influenced by paternal literacy and household wealth; and environmental health reflected a hybrid pattern driven by maternal literacy, program engagement, and socioeconomic status.\u003c/p\u003e \u003cp\u003eThese findings highlight a persistent \u0026ldquo;knowledge\u0026ndash;practice gap,\u0026rdquo; in which awareness of hygiene and food safety does not consistently translate into risk-reducing behaviors because of infrastructure deficits, including unimproved latrines, long water-collection times, and the lack of separate kitchens.\u003c/p\u003e \u003cp\u003eAddressing these gaps requires moving beyond knowledge dissemination to address structural inequities and empower households through education, institutional support, and economic strengthening.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eRecommendations/ Implications\u003c/h2\u003e \u003cp\u003eTo translate these findings into actionable strategies, several priorities emerge:\u003c/p\u003e \u003cp\u003eIntegrate food safety into agricultural extension: Food safety curricula, particularly those addressing cross‑contamination and pathogen control, should be embedded within NSA platforms, leveraging their proven success in improving hygiene.\u003c/p\u003e \u003cp\u003eInvest in infrastructure: Expanding access to protected water sources, improving latrine quality, and promoting separate kitchen facilities are essential to enabling households to adopt safe practices.\u003c/p\u003e \u003cp\u003eStrengthen literacy and education initiatives: Adult literacy programs should be paired with health interventions, recognizing the pivotal role of paternal literacy in food safety and maternal literacy in environmental health.\u003c/p\u003e \u003cp\u003eEnhance regulatory oversight and consumer education: Stronger food safety regulations, expanded inspection capacity, and culturally tailored consumer education are needed to mitigate risks associated with dietary preferences, including the consumption of raw meat.\u003c/p\u003e \u003cp\u003eLeverage multisectoral platforms: Nutrition‑sensitive agriculture, social protection programs, and maternal counseling should be scaled up as effective vehicles for delivering integrated interventions across food safety, hygiene, and environmental health.\u003c/p\u003e \u003cp\u003eAdopt equity‑focused strategies: Interventions must ensure that vulnerable households benefit alongside wealthier groups by pairing behavioral communication with economic strengthening, thereby enabling equitable adoption of safer technologies.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNutrition Sensitive Agriculture\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSNP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProductive Safety Net Program\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSeqota Declaration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWASH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWater, Sanitation and Hygiene\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e \u003cp\u003eThe study adhered to the principles outlined in the Declaration of Helsinki. The proposal was approved by the Institutional Review Board of the College of Development Studies at Addis Ababa University (CoDS/IRB/0003/2022) before the study began. Official support letters were obtained from AAU, and permission to conduct the study in the area was granted by the Amhara Health Research Institute. All study participants were informed about the study's objectives and purpose, as well as the voluntary nature of their participation. Informed oral consent was obtained from each participating household prior to interview-based data collection. Respondents\u0026rsquo; right to refuse to answer any question or to withdraw at any point during data collection was assured. The information provided by each respondent was collected anonymously and kept confidential.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003e \u003cb\u003eConflicts of interest\u003c/b\u003e:\u003c/strong\u003e \u003cp\u003eThe authors declare no conflicts of interest\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZ.T., Conceptualization, Methodology, Data Collection, Investigation, Analysis, Writing original draft. N.R., Conceptualization, Methodology, Analysis, Supervision, Review \u0026amp; Editing. M.A., Conceptualization, Methodology, Analysis, Supervision, Review \u0026amp; Editing.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e \u003cp\u003eNone\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. WHO estimates of the global burden of foodborne diseases. World Health Organization; 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFAO, IFAD, UNICEF, WFP, \u0026amp; WHO. The state of food security and nutrition in the world 2020: Transforming food systems for affordable healthy diets. 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Government of Ethiopia. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.scribd.com/document/852269236/National-WASH-and-Enviromental-Health-Stratagy\u003c/span\u003e\u003cspan address=\"https://www.scribd.com/document/852269236/National-WASH-and-Enviromental-Health-Stratagy\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Food safety, WASH, Environmental health, Productive Safety Net Programme, Nutrition‑Sensitive Agriculture, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-8831449/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8831449/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHousehold food safety and Water, Sanitation, and Hygiene (WASH) are critical determinants of nutritional status and the prevention of infectious diseases. This study provides an integrated assessment of food safety, WASH, and environmental health practices among beneficiaries of the Productive Safety Net Programme (PSNP) and Nutrition-Sensitive Agriculture (NSA) interventions in rural Ethiopia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional survey was conducted among 586 households in the Ebinat and Farta woredas of Northwest Ethiopia, stratified by intervention status. Data were collected using structured questionnaires. Composite indices were constructed using mean values and Bloom\u0026rsquo;s cut‑off criteria to classify knowledge and practices related to food safety, hygiene, and sanitation; WASH adequacy; and environmental health. Binary logistic regression identified predictors of food safety, WASH adequacy, and environmental health conditions.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFood safety was the weakest domain; 74.2% of households engaged in poor practices, and only 9.0% achieved a \u0026ldquo;good\u0026rdquo; rating. A notable knowledge\u0026ndash;practice gap was observed in hygiene, where 26.6% had good knowledge but only 12.5% practiced well. In contrast, 59.2% reported adequate WASH conditions, with a peak of 73.5% among PSNP\u0026thinsp;+\u0026thinsp;NSA participants. Regression analysis showed that food safety was primarily influenced by paternal literacy, prior awareness, and socioeconomic status, while program participation and wealth were the strongest predictors of WASH adequacy. Maternal literacy and program support significantly improved environmental health practices.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIntegrated programs have strengthened WASH infrastructure but remain less effective at shifting entrenched food‑handling behaviors. Achieving sustainable health outcomes will require culturally tailored interventions, greater investment in parental literacy, and the integration of practical hygiene demonstrations into multisectoral platforms. Together, these strategies can bridge the knowledge\u0026ndash;practice gap and enhance the long‑term effectiveness of nutrition‑sensitive initiatives.\u003c/p\u003e","manuscriptTitle":"Household Food Safety, WASH and Environmental Health Practices in the Context of Nutrition-Sensitive Agriculture: A Comparative Study in Northwest Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-25 09:22:50","doi":"10.21203/rs.3.rs-8831449/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-22T06:14:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T19:45:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-30T22:33:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149309209311246401364510042448937434196","date":"2026-03-30T12:01:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201732947063645076002715093577175714893","date":"2026-03-27T03:25:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295495462324428134824123004304391624387","date":"2026-03-26T13:14:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65794230942043887851285613688177296445","date":"2026-02-23T14:58:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"302999064121009051873699750318301659256","date":"2026-02-22T18:49:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-20T08:44:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37887070680408282232007644009716038099","date":"2026-02-20T08:37:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-20T06:23:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T06:21:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-12T05:56:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-11T14:44:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-11T14:22:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"79ea055a-7caf-4619-b042-c013ee35b591","owner":[],"postedDate":"February 25th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T07:55:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-25 09:22:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8831449","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8831449","identity":"rs-8831449","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}