Exploring spatial patterns, and identifying factors associated with insufficient cash or food received from a productive safety net program among eligible households in Ethiopia: a spatial and multilevel analysis as an input for international food aid pro

In low-income countries, households' food insecurity and the undernutrition of children are the main health problems. Ethiopia is vulnerable to food insecurity and undernutrition among children because its agricultural production system is traditional. Hence, the productive safety net program (PSNP) is implemented as a social protection system to combat food insecurity and enhance agricultural productivity by providing cash or food assistance to eligible households. So, this study aimed to explore spatial patterns of households' insufficient cash or food receiving from PSNP, and identify its associated factors in Ethiopia. The 2019 Ethiopian Mini Demographic and Health Survey dataset was used. A total of 8595 households were included in this study. Data management and descriptive analysis were done using STATA version 15 software and Microsoft Office Excel. ArcMap version 10.7 software was used for spatial exploration and visualization. SaTScan version 9.5 software was used for spatial scan statistics reports. In the multilevel mixed effect logistic regression analysis, explanatory variables with a p-value of less than 0.05 were considered significant factors. Overall, 13.5% (95% CI: 12.81-14.27%) of the households' level beneficiaries received cash or food from PSNP. The spatial distribution of households' benficiaries received cash or food from PSNP was not random, and good access to cash or food from PSNP was detected in Addis Ababa, SNNPR, Amhara, and Oromia regions. Households' heads aged 25-34 (AOR:1.43, 95% CI: 1.02, 2.00), 35-44 (AOR: 2.41, 95% CI: 1.72, 3.37), and > 34 (AOR: 2.54, 95% CI: 1.83, 3.51) years, being female (AOR: 1.51, 95% CI: 1.27,1.79), poor households (AOR: 1.91, 95% CI:1.52, 2.39), Amhara (AOR:.14, 95% CI: .06, .39) and Oromia (AOR:.36, 95% CI:.12, 0.91) regions, being rural residents (AOR:2.18, 95% CI: 1.21,3.94), and enrollment in CBHS (AOR: 3.34, 95% CI:2.69,4.16) are statistically significant factors. Households have limited access to cash or food from the PSNP. Households in Addis Ababa, SNNPR, Amhara, and Oromia regions are more likely to receive benefits from PSNP. Encouraging poor and rural households to receive benefits from the PSNP and raise awareness among beneficiaries to use the benefits they received for productivity purposes. Stakeholders would ensure the eligibility criteria and pay close attention to the hotspot areas.

Demsash AW ，Emanu MD ，Walle AD 《BMC PUBLIC HEALTH》

Spatial variations and determinants of receiving cash and food from the productive safety net program among households in Ethiopia: spatial clustering and multilevel analyses.

There is a global struggle with food insecurity and undernutrition among women, and Ethiopia has been particularly impacted by these issues. To address this challenge, Ethiopia has implemented a cash and food safety net program over many years. However, there is limited information available regarding the program's factors and spatial distributions, with no recent national evidence from Ethiopia. Consequently, the objective of this study is to investigate the spatial clustering and determinants of the Productive Safety Net Program (PSNP) in Ethiopia. This study utilized data from the Ethiopian Demographic and Health Survey. The sample included 8,570 weighted households. Given the hierarchical nature of the data, a multilevel logistic regression model was employed to identify factors influencing the outcome variable. Geographical clusters of individuals receiving assistance from the PSNP were examined using SaTScan software and the Bernoulli model, along with the Kulldorff methods. The nationwide distribution of the program beneficiaries was visualized using ArcGIS version 10.8. Variables were considered statistically significant if their p-value was <0.05. The overall coverage of the PSNP was 13.54% [95% confidence interval (CI): 12.84-14.29] among households in Ethiopia. The study revealed that people from richer households adjusted odds ratio [AOR = 0.46 (95% CI: (0.33, 0.64))], those from the richest households [AOR = 0.26 (95% CI:(0.17,0.41))], and those with educated household heads [AOR = 0.45 (95% CI:(0.28, 0.71))] have a lower likelihood of utilizing the PSNP compared to their counterparts. Conversely, a unit increase in household heads' age [AOR = 1.02 (95% CI:(1.01, 1.02))] and family size [AOR = 1.05 (95% CI:1.021.10)] showed a higher likelihood of joining the PSNP, respectively. Household heads who have joined community health insurance [AOR = 3.21 (95% CI:(2.58, 4.01))] had significantly higher odds of being included in the PSNP than their counterparts. Heads who belong to a community with a high poverty level [AOR = 2.68 (95% CI:(1.51, 4.79))] and community health insurance [AOR = 2.49 (95% CI:(1.51, 4.11))] showed more inclination to utilize the PSNP compared to their counterparts. PSNP was judged to have a low implementation status based on the findings gathered regarding it. We found factors such as age, sex, region, wealth, education, family size, regions, and health insurance to be statistically significant. Therefore, encouraging women empowerment, community-based awareness creation, and coordination with regional states is advisable.

Terefe B ，Muluneh B ，Sisay Seretew W ，Misganaw Geremew B ... -  《-》

Spatial distribution and geographical heterogeneity factors associated with households' enrollment level in community-based health insurance.

Healthcare service utilization is unequal among different subpopulations in low-income countries. For healthcare access and utilization of healthcare services with partial or full support, households are recommended to be enrolled in a community-based health insurance system (CBHIS). However, many households in low-income countries incur catastrophic health expenditure. This study aimed to assess the spatial distribution and factors associated with households' enrollment level in CBHIS in Ethiopia. A cross-sectional study design with two-stage sampling techniques was used. The 2019 Ethiopian Mini Demographic and Health Survey (EMDHS) data were used. STATA 15 software and Microsoft Office Excel were used for data management. ArcMap 10.7 and SaTScan 9.5 software were used for geographically weighted regression analysis and mapping the results. A multilevel fixed-effect regression was used to assess the association of variables. A variable with a p < 0.05 was considered significant with a 95% confidence interval. Nearly three out of 10 (28.6%) households were enrolled in a CBHIS. The spatial distribution of households' enrollment in the health insurance system was not random, and households in the Amhara and Tigray regions had good enrollment in community-based health insurance. A total of 126 significant clusters were detected, and households in the primary clusters were more likely to be enrolled in CBHIS. Primary education (AOR: 1.21, 95% CI: 1.05, 1.31), age of the head of the household >35 years (AOR: 2.47, 95% CI: 2.04, 3.02), poor wealth status (AOR: 0.31, 95% CI: 0.21, 1.31), media exposure (AOR: 1.35, 95% CI: 1.02, 2.27), and residing in Afar (AOR: 0.01, 95% CI: 0.003, 0.03), Gambela (AOR: 0.03, 95% CI: 0.01, 0.08), Harari (AOR: 0.06, 95% CI: 0.02, 0.18), and Dire Dawa (AOR: 0.02, 95% CI: 0.01, 0.06) regions were significant factors for households' enrollment in CBHIS. The secondary education status of household heads, poor wealth status, and media exposure had stationary significant positive and negative effects on the enrollment of households in CBHIS across the geographical areas of the country. The majority of households did not enroll in the CBHIS. Effective CBHIS frameworks and packages are required to improve the households' enrollment level. Financial support and subsidizing the premiums are also critical to enhancing households' enrollment in CBHIS.

Demsash AW 《Frontiers in Public Health》

Unimproved source of drinking water and its associated factors: a spatial and multilevel analysis of Ethiopian demographic and health survey.

Drinking water quality has been a major public health concern in lower and middle income countries where access to improved water supplies is limited. Ethiopia is thought to have one of the worst drinking water infrastructures in the world. This study aimed to assess the spatial variation and determinants of using unimproved sources of drinking water in Ethiopia using recent nationally representative data. A population-based cross-sectional study was employed with the recent EDHS data of 2019. A total of 8663 households were sampled using a stratified two-stage cluster sampling method. Kuldorff's SaTScan version 9.6 software was used to generate spatial scan statistics. ArcGIS version 10.7 software was used to visualize the spatial patterns of unimproved drinking water sources. A multilevel multivariable mixed-effect logistic regression was used to identify factors associated with the use of an unimproved drinking water source. In the multivariable multilevel analysis, those variables with a p-value < 0.05 were considered to be significant predictors of using an unimproved source of drinking water. Around 31% (95% CI: 30%, 32%) of the population in Ethiopia uses unimproved sources of drinking water with significant spatial variation across the country. Households aged 41-60 [AOR = 0.69; 95%CI; 0.53, 0.89] as compared to the households aged 10-25, households having middle wealth index [AOR = 0.48; 95%CI; 0.40, 0.59], and households having a rich wealth index [AOR = 0.31; 95%CI; 0.25, 0.39] as compared to the poor households, living in high community literacy level [AOR = 0.36; 95%CI; 0.16, 0.80], living in high-level community poverty [AOR = 3.03; 95%CI; 1.32, 6.98], rural residence [AOR = 7.88; 95%CI; 2.74, 22.67] were significant predictors of use of unimproved source of drinking water. Hot spot areas of use of unimproved drinking water sources were observed in Amhara, Afar, and Somalia regions and some parts of SNNPR and Oromia regions in Ethiopia. The primary clusters were found in Ethiopia's Somalia and Oromia regions. Around one third of the Ethiopian population utilizes unimproved source of drinking water and it was distributed non-randomly across regions of Ethiopia. The age of the household head, wealth status of the household, residence, community poverty level, and community literacy level were found to be significantly associated with utilizing unimproved drinking water source. State authorities, non-governmental organizations and local health administrators should work to improve the quality of drinking water particularly for high risk groups such as communities living in high poverty and low literacy, poor households, rural residents, and hot spot areas to decrease the adverse consequences of using unimproved drinking water source.

Aragaw FM ，Merid MW ，Tebeje TM ，Erkihun MG ，Tesfaye AH ... -  《BMC PUBLIC HEALTH》

Multilevel and geographically weighted regression analysis of factors associated with full immunization among children aged 12-23 months in Ethiopia.

Immunization is the process of building immunity or resistance to an infectious disease, typically through administering a vaccine. It is one of the most effective strategies for lowering child morbidity and death. It protects against more than 20 potentially fatal diseases, increasing longevity and health. Despite progress, Ethiopia failed to meet its vaccination coverage target. The magnitude of full immunization is different across areas. Therefore, conducting geographically weighted regression to identify the local factors and multilevel analysis to investigate and identify factors associated with full immunization coverage among children aged 12-23 months is necessary. The study was conducted using the 2019 Ethiopian Mini Demographic Health Survey dataset. A sample of 1028 weighted children aged 12-23 months were included in the analysis. Descriptive statistics were used to describe variables. For the spatial analysis, Arc-GIS version 10.8 statistical software was used. Spatial regression (geographically weighted regression) was done to identify factors associated with the proportion of full immunization, and model comparison was based on adjusted R2 and Akaike Information Criteria (AICc). Multilevel mixed-effect binary logistic regression models were fitted to identify factors associated with full immunization. The fitted models were compared based on log-likelihood, deviance, median odds ratio, and Proportional Change in Variance. Finally, statistically significant factors were reported using an adjusted odd ratio (AOR) with a 95% Confidence Interval for fixed effect. All variables with a p-value less than 0.05 in the final model were considered statistically significant factors. In Ethiopia, the overall full immunization coverage among children aged 12-23 months was 40.58%, with spatial variation across regions in Ethiopia. The significant spatial distribution of full immunization coverage among children aged 12-23 months was detected in northern Tigray, Addis Ababa, central Oromia, and southeastern Amhara regions. The proportion of rural residents,the proportion of women aged 35-44 years,  the proportion of women who had ANC 4 and above andthe proportion of women who had PNC were local factors associated with the proportion of full immunization among children aged 12-23 months. Rural residence [AOR 0.27 (95% CI 0.10, 0.70)], family size 4 and above[AOR 0.41 (95% CI 0.17, 0.96)], never breastfeed [AOR 0.026(95% CI 0.003, 0.21)], 1-3 times ANC visit [AOR 0.45 (95% CI 0.23, 0.86)], being from Oromia region [AOR 0.23 (95% CI 0.05, 0.97)], Eastern pastoralist region [AOR 0.09 (95% CI 0.023, 0.35)], age 35-44 years [(AOR 6 (95% CI 1.57, 22.9)], and PNC [AOR 2.40 (95% CI 1.24, 4.8)] were significant factors associated with fully immunization in multilevel mixed effect analysis. Full immunization coverage in Ethiopia is below the global target with significant geographical variation. The high proportion of rural residents, the high proportion of women who had ANC 4 and above, mothers who had a high proportion of PNC, and the high proportion women age 35-44 years were local geographical factors for the proportion of full immunization among children age 12-23 months in Ethiopia. Women who had PNC, ANC visits four or more times, and increased maternal age were positively associated, whereas larger family size, no breastfeeding, rural residence, and being from Oromia and eastern pastoralist region were negatively associated with full immunization. Strengthening maternal and child health services, focusing on rural areas and low-coverage regions, is essential to increase immunization coverage in Ethiopia.

Diress F ，Negesse Y ，Worede DT ，Bekele Ketema D ，Geitaneh W ，Temesgen H ... -  《Scientific Reports》