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A Scoping Review of Selected Studies on Predictor Variables Associated with the Malaria Status among Children under Five Years in Sub-Saharan Africa
Article

Individual and Contextual Factors Associated with Malaria among Children 6–59 Months in Nigeria: A Multilevel Mixed Effect Logistic Model Approach

1
School of Health and Related Research (ScHARR), University of Sheffield, Sheffield S1 4DA, UK
2
Department of Liberal Studies, College of Administrative and Business Studies, Niger State Polytechnic, Bida Campus, Bida 912231, Nigeria
3
Faculty of Health and Wellbeing, Sheffield Hallam University, Sheffield S10 2BP, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2021, 18(21), 11234; https://doi.org/10.3390/ijerph182111234
Received: 5 August 2021 / Revised: 17 October 2021 / Accepted: 23 October 2021 / Published: 26 October 2021
Background/Purpose: Over the last two decades, malaria has remained a major public health concern worldwide, especially in developing countries leading to high morbidity and mortality among children. Nigeria is the world most burdened malaria endemic nation, contributing more than a quarter of global malaria cases. This study determined the prevalence of malaria among children at 6–59 months in Nigeria, and the effects of individual and contextual factors. Methods: This study utilized data from 2018 Nigeria Demographic and Health Survey (NDHS) involving a weighted sample size of 10,185 children who were tested for malaria using rapid diagnostic test (RDT). Given the hierarchical structure of the data set, such that children at Level-1 were nested in communities at Level-2, and nested in states and Federal Capital Territory (FCT) at Level-3, multilevel mixed effect logistic regression models were used for the analysis. Results: The proportion of children 6–59 months of age in Nigeria that had malaria fever positive as assessed by RDTs was 35.5% (3418/10,185), (CI: 33.9–37.1). Kebbi State had 77.7%, (CI: 70.2–83.5), which was the highest proportion of 6–59 months who were malaria positive, next in line was Katsina State with 55.5%, (CI: 47.7–63.1). The Federal Capital Territory (FCT), Abuja had the proportion of 29.6%, (CI: 21.6–39.0), malaria positive children of 6–59 months of age. Children between the age of 48 and 59 months were 2.68 times more likely to have malaria fever than children of ages 6–11 months (AOR = 2.68, 95% CI: 2.03–3.54). In addition, children from the rural area (AOR = 2.12, 95% CI: 1.75–2.57), were more likely to suffer from malaria infection compared to children from urban area. Conclusion: The study identified some individual and contextual predictors of malaria among children in Nigeria. These factors identified in this study are potential areas that need to be considered for policy designs and implementations toward control and total elimination of malaria-related morbidity and mortality among children in Nigeria. View Full-Text
Keywords: malaria; fever; Plasmodium falciparum; Falciparum vivax; under-five; determinants; risk factors malaria; fever; Plasmodium falciparum; Falciparum vivax; under-five; determinants; risk factors
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MDPI and ACS Style

Obasohan, P.E.; Walters, S.J.; Jacques, R.; Khatab, K. Individual and Contextual Factors Associated with Malaria among Children 6–59 Months in Nigeria: A Multilevel Mixed Effect Logistic Model Approach. Int. J. Environ. Res. Public Health 2021, 18, 11234. https://doi.org/10.3390/ijerph182111234

AMA Style

Obasohan PE, Walters SJ, Jacques R, Khatab K. Individual and Contextual Factors Associated with Malaria among Children 6–59 Months in Nigeria: A Multilevel Mixed Effect Logistic Model Approach. International Journal of Environmental Research and Public Health. 2021; 18(21):11234. https://doi.org/10.3390/ijerph182111234

Chicago/Turabian Style

Obasohan, Phillips E., Stephen J. Walters, Richard Jacques, and Khaled Khatab. 2021. "Individual and Contextual Factors Associated with Malaria among Children 6–59 Months in Nigeria: A Multilevel Mixed Effect Logistic Model Approach" International Journal of Environmental Research and Public Health 18, no. 21: 11234. https://doi.org/10.3390/ijerph182111234

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