Evidence map›Paper›PMID 38136128›Full record

ArticleChildren (Basel, Switzerland)2023

Modeling the Risk Factors of Undernutrition among Children below Five Years of Age in Uganda Using Generalized Structural Equation Models.

Vallence Ngabo Maniragaba, Leonard K Atuhaire, Pierre Claver Rutayisire

Open access · goldAbstract read
In one paragraph

Article in Children (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 2 institutions in 2 countries.

Vallence Ngabo ManiragabaAfrican Center of Excellence in Data Science, College of Business and Economic, University of Rwanda, Kigali P.O. Box 3248, Rwanda.
Leonard K AtuhaireSchool of Statistical Methods, College of Management Sciences, Makerere University, Kampala P.O. Box 7072, Uganda.
Pierre Claver RutayisireAfrican Center of Excellence in Data Science, College of Business and Economic, University of Rwanda, Kigali P.O. Box 3248, Rwanda.
University of Rwanda · RWMakerere University · UG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe prevalence of undernutrition among children below five years of age, in Uganda and the world over, remains very high. About 45% of all global deaths among children below five years of age are attributed to undernutrition. A number of studies using different statistical approaches affirm this effect, yet some factors indicate the influence of other factors within the system. This study, therefore, uses a method that demonstrates how different variables feed into each other.

aimThe aim of this study was to establish the major factors associated with an increased likelihood of undernutrition and the paths showing how these risk factors influence undernutrition.

methodsData from the Uganda Demographic and Health Survey (UDHS, 2016) were used for this study. A sample of 4530 children, whose age, height, and weight measurements were recorded, was considered for this study. Additionally, the study used generalized structural equation models to identify the multifaceted natures and paths of the risk factors that influence undernutrition among children below five years of age. The study relied on the UNICEF 2020 conceptual framework to identify and analyze the direct and indirect effects of these risk factors of undernutrition.

resultsFrom the perspective of a male child, having a perceived small size at birth, a low birth weight, being breastfed for less than 6 months, having no formal education from mothers, limited income-generating opportunities, a low wealth status, and notable episodes of diarrhea were among the key factors associated with an increased likelihood of undernutrition. The identified paths were as follows: (i) Having no education, as this was associated with limited working opportunities and a low income, which increases the likelihood of low household wealth status, hence increasing the chances of undernutrition. (ii) Exposure to a rural setting was associated with an increased likelihood of undernutrition through association with poor and or low employment levels within the rural areas. (iii) A shorter duration of breastfeeding was associated with children in urban areas, resulting in an increased likelihood of undernutrition. (iv) Children aged between 6 and 47 months had a higher likelihood of undernutrition.

conclusionsAn approach that addresses and recognizes all these factors at different levels, along the established paths, should be implemented to effectively reduce undernutrition among children below five years of age.

Indexed as

GSEMpaths analysisUgandaunder-fivesundernutrition

Identifiers

PMID38136128
PMCPMC10742231
OpenAlexW4389815128

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.