Evidence map›Paper›PMID 36942244›Full record

ArticleHeliyon2023

Covid-19 related factors to food security and dietary diversity among urban households in western Oromia, Ethiopia.

Tamiru Yazew, Agama Daba, Lelisa Hordofa, Girma Garedew, Abdi Negash, Gizachew Merga, Tasama Bakala

Open access · goldFull text read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Tamiru YazewDepartment of Public Health, College of Health Sciences, Salale University, Fitche, 245, Ethiopia.
Agama DabaDepartment of Food and Nutritional Sciences, Faculty of Agriculture, Wollega University, Nekemte, 395, Ethiopia.
Lelisa HordofaDepartment of Natural Resource Management, Faculty of Resource Management and Economics, Wollega University, Nekemte, 395, Ethiopia.
Girma GaredewDepartment of Public Health, College of Health Sciences, Salale University, Fitche, 245, Ethiopia.
Abdi NegashDepartment of Medical Laboratory Sciences, College of Health Sciences, Salale University, Fitche, 245, Ethiopia.
Gizachew MergaDepartment of Horticulture, College of Agriculture and Natural Resources, Salale University, Fitche, 245, Ethiopia.
Tasama BakalaDepartment of Food and Nutritional Sciences, Faculty of Agriculture, Wollega University, Nekemte, 395, Ethiopia.
Salale UniversityWollega University · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aims to assess factors associated with food security and dietary diversity among poor urban households of western Oromia, Ethiopia, after the outbreak of the Covid-19 pandemic. Method: A cross-sectional, community-based study was conducted in May to June 2021 with 361 poor urban households in the Horo Guduru Wollega zone, western Oromia, Ethiopia. A pre-tested structured questionnaire was used to collect primary data. Twenty-four hour reminder points were used to assess household dietary diversity, and household food security was assessed using the Household Food Insecurity Access Scale tool. Data were evaluated using the statistical software SPSS version 25.0. Results: This study showed a prevalence of food insecurity in households of 59.6%. The mean and standard deviation of household dietary diversity values were 4.19 ± 1.844. Family size (AOR = 8.5; 95% CI:3.295-21.92), monthly income (AOR = 3.52; 95% CI; 1.771-6.986), dietary diversity (AOR = 8.5; 95% CI; 3.92-18.59), knowledge (AOR = 3.0, 95% CI = 1.08-)8.347), attitude (AOR = 8.35, 95% CI:3.112-22.39) and practices against Covid-19 (AOR = 2.12; 95% CI:1.299-11.4) were factors significantly associated with food insecurity. Variables like educational status (AOR = 3.46; 95% CI:1.44-8.312), increased family size after the Covid-19 pandemic (AOR = 2.26; 95% CI:1.02-5.04), food security (AOR = 6.7; 95% CI:4.01-19.01), knowledge (AOR = 3.96; 95% CI:1.57-10.0), attitude (AOR = 3.9; 95% CI:1.75-8.82) and practices toward coronavirus (AOR = 2.23; 95% CI:2.18-23.95) were predictors significantly associated with dietary diversity. Conclusion: This study concluded that family size, monthly income, and dietary diversity were factors contributed to household food security. On the other hand, variables such as educational status, family size, and food security were highly relevant factors for dietary diversity after the outbreak of the Covid-19 pandemic. Knowledge, attitudes, and practices were also variables related to both household food security and dietary diversity. Therefore, immediate interventions such as nutrition-specific interventions can be suggested to address food insecurity and problems of inadequate food intake in poor urban households. In addition, governmental and non-governmental organizations should raise awareness and policies to support those at higher risk by developing affordable, sustainable and targeted social protection systems that ensure food security and adequate dietary intake at the household level.

Indexed as

AOR, Adjusted Odd RatioAssociated factorsCI, Confidence LevelCOR, Crude Odd RatioCovid-19Dietary diversityEthiopiaEU, European UnionFood securityHFIAS, Household Food Insecurity Access ScaleNPC, National Planning CommissionSPSS, Statistical Package for Social SciencesUN, United NationsUrbanUSDA, United States Department of AgricultureUSD, United states Dollar

Identifiers

PMID36942244
PMCPMC10008806
OpenAlexW4324032794

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read77
Read underepoch 390

Registered trials

None linked

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.