Mother’s Socioeconomic Status and Under-Five Malaria Infection in Nasarawa State

The main objective of this paper is to contribute to understanding the relationship between a mother’s socioeconomic status and child malaria infection in Nasarawa State. This is because Nasarawa State is one of the states with the highest malaria cases in Nigeria, and previous finding from other malaria endemic areas shows different factors influencing child malaria. This study aimed to research the regional determining factors in Nasarawa State, seeing that less of this study is undertaken in the state. During the survey, a multi-stage sampling technique was used to collect data from 477 women with children between 0 and 5. Binary logistic regression was used to analyse this relationship. The results from binary logistic regression without control variables indicated a negative relationship between the mother’s socioeconomic status and child malaria infection. Including necessary control variables in the binary logistic regression shows that the mother’s level of education is the only mother’s socioeconomic variable that is a consistent determinant of child malaria infection in Nasarawa State. Lafia and Keffi were the best-performing communities in the state for children with malaria-free infection. At the same time, Agyaragu had the highest number of malaria-infected children. The study recommends that Government and community leaders encourage girl child education, especially among rural dwellers of Nasarawa State, through a sensitisation campaign.

Authors

Institutions

Publication Details

Journal
Futurity of Social Sciences.
Published
2025-02-05
DOI
https://doi.org/10.57125/fs.2025.03.20.02
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mother’s Socioeconomic Status and Under-Five Malaria Infection in Nasarawa State

Joseph Paul
Futurity of Social Sciences.
COVID-19 epidemiological studies
article

Mother’s Socioeconomic Status and Under-Five Malaria Infection in Nasarawa State

Joseph Paul
article en

Abstract

The main objective of this paper is to contribute to understanding the relationship between a mother’s socioeconomic status and child malaria infection in Nasarawa State. This is because Nasarawa State is one of the states with the highest malaria cases in Nigeria, and previous finding from other malaria endemic areas shows different factors influencing child malaria. This study aimed to research the regional determining factors in Nasarawa State, seeing that less of this study is undertaken in the state. During the survey, a multi-stage sampling technique was used to collect data from 477 women with children between 0 and 5. Binary logistic regression was used to analyse this relationship. The results from binary logistic regression without control variables indicated a negative relationship between the mother’s socioeconomic status and child malaria infection. Including necessary control variables in the binary logistic regression shows that the mother’s level of education is the only mother’s socioeconomic variable that is a consistent determinant of child malaria infection in Nasarawa State. Lafia and Keffi were the best-performing communities in the state for children with malaria-free infection. At the same time, Agyaragu had the highest number of malaria-infected children. The study recommends that Government and community leaders encourage girl child education, especially among rural dwellers of Nasarawa State, through a sensitisation campaign.

Futurity of Social Sciences.Vol. 3(1)
Federal University Lafia (NG)
Openalex Percentile: Top 95%
COVID-19 epidemiological studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.