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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 programmers

BACKGROUND: 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 pr...

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Autores principales: Demsash, Addisalem Workie, Emanu, Milkias Dugassa, Walle, Agmasie Damtew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265788/
https://www.ncbi.nlm.nih.gov/pubmed/37312083
http://dx.doi.org/10.1186/s12889-023-16001-2
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author Demsash, Addisalem Workie
Emanu, Milkias Dugassa
Walle, Agmasie Damtew
author_facet Demsash, Addisalem Workie
Emanu, Milkias Dugassa
Walle, Agmasie Damtew
author_sort Demsash, Addisalem Workie
collection PubMed
description BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
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spelling pubmed-102657882023-06-15 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 programmers Demsash, Addisalem Workie Emanu, Milkias Dugassa Walle, Agmasie Damtew BMC Public Health Research BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. BioMed Central 2023-06-14 /pmc/articles/PMC10265788/ /pubmed/37312083 http://dx.doi.org/10.1186/s12889-023-16001-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Demsash, Addisalem Workie
Emanu, Milkias Dugassa
Walle, Agmasie Damtew
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 programmers
title 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 programmers
title_full 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 programmers
title_fullStr 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 programmers
title_full_unstemmed 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 programmers
title_short 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 programmers
title_sort 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 programmers
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265788/
https://www.ncbi.nlm.nih.gov/pubmed/37312083
http://dx.doi.org/10.1186/s12889-023-16001-2
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