Evidence map›Paper›PMID 39984916›Full record

ArticleMalaria journal2025

Assessing the influence of socioeconomic and environmental variables on malaria risk in Nigerian children under 5 years: a GLMM approach.

Talani Mhelembe, Shaun Ramroop, Faustin Habyarimana

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Article in Malaria journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 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.

Talani MhelembeSchool of Mathematics, Statistics, and Computer Science, University of Kwazulu-Natal, Private Bag X01, PietermaritzburgScottsville, 3209, South Africa. mhelembehht@gmail.com.
Shaun RamroopSchool of Mathematics, Statistics, and Computer Science, University of Kwazulu-Natal, Private Bag X01, PietermaritzburgScottsville, 3209, South Africa.
Faustin HabyarimanaSchool of Mathematics, Statistics, and Computer Science, University of Kwazulu-Natal, Private Bag X01, PietermaritzburgScottsville, 3209, South Africa.

Funding

Research Training on Harnessing Data Science for Global Health Priorities in AfricaU2RTW012140 · FIC · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI BARNIGHAUSEN, TILL, FAWZI, WAFAIE W · 2021 to 2025
$1.7M
FIC NIH HHS U2R TW012140
6 · The paper itself

Abstract

backgroundThe study focused on the full population of children from Nigeria, where the dataset was obtained from the demographic and health surveys (DHS). About 10245 children were selected for the current study and based on the rapid diagnostic test (RDT) results, there is about 37% prevalence of malaria in children under 5 years old in Nigeria. Malaria is the leading public health concern, that contributes to child mortality in the African region.

methodsThe Nigeria Malaria Indicator Survey (NMIS) 2021 was utilized in this investigation. For the 2021 NMIS, a two-stage sampling technique was used. According to the NIMS study, the children chosen for anaemia and RDT testing were under 5 years of age.

resultsA generalized linear mixed model (GLMM) was used to examine malaria RDT findings in conjunction with demographic, geographic, and socioeconomic characteristics. The following underlying risk factors for malaria in children were discovered in the study: altitude, anaemia level, age in months, fever status in the past 2 weeks, toilet facility, main wall material, main roof material, household wealth index, type of place of residence, sex of the child, mother's education level, and knowledge of the preventative measures that can be used to prevent malaria.

conclusionMissing data were not deleted in this investigation; instead, multiple imputations utilizing chained equations were used to approximate the missing observation. Based on the results found by using the GLMM, the findings of this study may influence how the government combats malaria in Nigeria. The novelty of this study is that the missing values were not dropped. However, imputation techniques were explored, and multiple imputation by chained equations was used.

Indexed as

EnvironmentMalariaSocioeconomic FactorsChild, PreschoolFemaleHumansInfantInfant, NewbornLinear ModelsMaleNigeriaPrevalenceRisk FactorsAnaemiaChildrenGLMMMalariaMultiple imputation by chained equationsNigeria

Identifiers

PMID39984916
PMCPMC11846331

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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.