Evidence map›Paper›PMID 35953835›Full record

ArticleBMC nutrition2022

Spatial distribution of vitamin A rich foods intake and associated factors among children aged 6-23 months in Ethiopia: spatial and multilevel analysis of 2019 Ethiopian mini demographic and health survey.

Addisalem Workie Demsash, Alex Ayenew Chereka, Sisay Yitayih Kassie, Dereje Oljira Donacho, Habtamu Setegn Ngusie, Masresha Derese Tegegne, Mequannent Sharew Melaku, Sisay Maru Wubante, Mekonnen Kenate Hunde

Open access · goldAbstract read
In one paragraph

Article in BMC nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

27 citing papers in PubMed, 27 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

Addisalem Workie DemsashHealth Informatics Department, College of Health Science, Mattu University, Mettu, Ethiopia. addisalemworkie599@gmail.com.
Alex Ayenew CherekaHealth Informatics Department, College of Health Science, Mattu University, Mettu, Ethiopia.
Sisay Yitayih KassieHealth Informatics Department, College of Health Science, Mattu University, Mettu, Ethiopia.
Dereje Oljira DonachoHealth Informatics Department, College of Health Science, Mattu University, Mettu, Ethiopia.
Habtamu Setegn NgusieHealth Informatics Department, College of Health Science, Mattu University, Mettu, Ethiopia.
Masresha Derese TegegneHealth Informatics Department, Institute of Public Health, University of Gondar, Gondar, Ethiopia.
Mequannent Sharew MelakuHealth Informatics Department, Institute of Public Health, University of Gondar, Gondar, Ethiopia.
Sisay Maru WubanteHealth Informatics Department, Institute of Public Health, University of Gondar, Gondar, Ethiopia.
Mekonnen Kenate HundeLifelong Learning and Community Development Department, College of Education and Behavioral Scieence , Mattu University, Mettu, Ethiopia.
Ethiopian Civil Service University · ETMattu UniversityUniversity of Gondar · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInadequate micronutrients in the diet and vitamin A deficiency are worldwide public health problems. In developing regions, many preschool children are undernourished, become blind every year and died before the age of 23 months. This study was aimed to explore the spatial distribution of vitamin A rich foods intake among children aged 6-23 months and identify associated factors in Ethiopia.

methodsEthiopian Mini Demographic and Health Survey 2019 dataset with a total 1407 children aged 6-23 months was used. Data management and processing were done using STATA version 15 software and Microsoft Office Excel. ArcMap version 10.7 software was used for mapping and spatial visualization of the distribution. Spatial scan statistics was performed using SaTScan version 9.5 software for Bernoulli-based model. Multilevel mixed effect logistic regression model was employed to identify associated factors.

resultsOverall, 38.99% (95% CI: 36.46-41.62) of children aged 6- 23 months took vitamin A rich foods. Poor intake of vitamin A rich foods was significantly clustered Dire Dawa city, Somali and Harari regions of Ethiopia. Children aged 6-23 months lived in the primary cluster were 70% (RR = 1.70, P-value < 0.001) more likely to intake vitamin A rich foods than children lived outside the window. In the multilevel mixed effect logistic regression analysis, Primary educational status (AOR:1.42, 95% CI: 1.05, 1.93) and higher educational status (AOR:3.0, 95% CI: 1.59, 5.65) of mother, Dire Dawa (AOR:0.49, 95% CI: 0.22, 1.12) city, Afar (AOR: 0.16, 95% CI: 0.07, 0.36), Amhara (AOR: 0.37, 95% CI: 0.19, 0.71) and Somali (AOR: 0.02, 95% CI: 0.003, 0.08) regions of Ethiopia, children aged 13-23 months (AOR: 1.80, 95% CI: 1.28, 2.36), Mothers' exposure to media (AOR: 1.41, 95% CI: 1.04, 1.92) were statistically significant factors for vitamin A rich foods intake among children aged 6-23 months.

conclusionsOnly 4 out of ten children took vitamin A rich foods which is too low compared to the national target and significantly clustered in Ethiopia. Mother's educational status, Region, Child age and Mother's media exposure are significant factors vitamin A rich foods intake. Stakeholders should strengthen mothers' education status, creating awareness for mothers on child feeding and using locally available natural resource to produce vitamin A rich foods.

Indexed as

ChildrenEthiopiaIntakeMultilevelSpatial distributionVitamin A rich foods

Identifiers

PMID35953835
PMCPMC9367059
OpenAlexW4291004231

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.