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 regardi...

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Bibliographic Details
Published in:Frontiers in public health 2024-07, Vol.12, p.1392111
Main Authors: Terefe, Bewuketu, Muluneh, Begosew, Sisay Seretew, Wullo, Misganaw Geremew, Bisrat
Format: Article
Language:English
Subjects:
Adolescent
Adult
cash and food reception
Cluster Analysis
Ethiopia
Family Characteristics
Female
Food Assistance - statistics & numerical data
Food Insecurity
Food Supply - statistics & numerical data
Health Surveys
households
Humans
Logistic Models
Male
Middle Aged
Multilevel Analysis
productive safety net program
Public Health
Socioeconomic Factors
Spatial Analysis
spatial variation
Young Adult
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Summary: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 -value was
ISSN:2296-2565
2296-2565
DOI:10.3389/fpubh.2024.1392111