Spatial variations and determinants of receiving cash and food from the productive safety net program among households in Ethiopia: spatial clustering and multilevel analyses - Terefe, Bewuketu; Muluneh, Begosew; Sisay Seretew, Wullo; Misganaw Geremew, Bisrat (Frontiers in Public Health, 2024)
Background: Despite the global struggle with food insecurity and undernutrition among women, 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 available information 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. Method: 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 the SaTScan software and the Bernoulli model with Kulldorff methods. The nationwide distribution of program beneficiaries was visualized using ArcGIS version 10.8. Variables were considered statistically significant if their p-value was <0.05Results: The overall coverage of PSNP was 13.54% (95%, CI, 12.84-14.29) among households in Ethiopia. Being from the richer, richest household, and educated heads have (AOR=0.46, (CI 95%: (0.33,0.64)), (AOR= 0.26, (CI 95%:(0.17,0.41)), and (AOR=0.45(CI 95%:(0.28,0.71)) revealed less likely odds of utilizing the PSNP compared to their counterparts respectively.Conversely, a unit increase of household head age and family size have shown a higher (AOR=1.02(CI 95%:1.01,1.02)), and (AOR=1.05(CI 95%:1.021.10)) odds of joining PSNP respectively. Those household heads have joined community health insurance had shown more odds of being included in the PSNP (AOR=3.21(CI 95%:2.58,4.01)) compared to their counterparts. Heads who are from community with high poverty level and community health insurance have shown (AOR=2.68, (CI 95%:1.51,4.79)), and (AOR=2.49(CI 95%:1.51,4.11)) more inclination to utilize PSNP compared to their counterparts.The findings of the PSNP was judged as low implementation status. We found statistically significant factors such as age, sex, regions, wealth, education, family size, regions, and health insurances. Therefore, encouraging women empowerment, community-based awareness creation, coordination with regional states is advisable.