Evidence map›Paper›PMID 37312083›Full record

ArticleBMC public health2023

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.

Addisalem Workie Demsash, Milkias Dugassa Emanu, Agmasie Damtew Walle

Abstract read
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Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Addisalem Workie DemsashMattu University, College of Health Science, Health Informatics Department, Mettu, Ethiopia. addisalemworkie599@gmail.com.
Milkias Dugassa EmanuMattu University, College of Health Science, Nursing department, Mettu, Ethiopia.
Agmasie Damtew WalleMattu University, College of Health Science, Health Informatics Department, Mettu, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 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.

methodsThe 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.

resultsOverall, 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.

conclusionsHouseholds 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.

Indexed as

FoodMalnutritionAgricultureChildEthiopiaFemaleHumansMaleMultilevel AnalysisAnd spatial patternsCashFoodHouseholdsSafety net program

Identifiers

PMID37312083
PMCPMC10265788

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.