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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

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  • Phillips Edomwonyi Obasohan

    (School of Health and Related Research (ScHARR), University of Sheffield, Sheffield S1 4AD, UK
    Department of Liberal Studies, College of Business and Administrative Studies, Niger State Polytechnic, Bida Campus, Bida 912231, Nigeria)

  • Stephen J. Walters

    (School of Health and Related Research (ScHARR), University of Sheffield, Sheffield S1 4AD, UK)

  • Richard Jacques

    (School of Health and Related Research (ScHARR), University of Sheffield, Sheffield S1 4AD, UK)

  • Khaled Khatab

    (Faculty of Health and Wellbeing, Sheffield Hallam University, Sheffield S10 2BP, UK)

Abstract

Background/Purpose: In recent times, Sub-Saharan Africa (SSA) had been rated by the World Health Organization (WHO) as the most malaria-endemic region in the world. Evidence synthesis of the factors associated with malaria among children aged under-five in SSA is urgently needed. This would help to inform decisions that policymakers and executors in the region need to make for the effective distribution of scarce palliative resources to curb the spread of the illness. This scoping review is aimed at identifying studies that have used multivariate classical regression analysis to determine the predictors associated with malaria among children under five years old in SSA. Methods/Design: The search terms followed population, intervention, comparator, outcome, timing, setting (PICOTS), and were used in searching through the following databases: PubMed, MEDLINE, Web of Science, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Scopus, and Measure DHS. The databases were searched for published articles from January 1990 to December 2020. Results: Among the 1154 studies identified, only thirteen (13) studies met the study’s inclusion criteria. Narrative syntheses were performed on the selected papers to synchronize the various predictors identified. Factors ranging from child-related (age, birth order and use of a bed net), parental/household-related (maternal age and education status, household wealth index) and community-related variables (community wealth status, free bed net distribution) were some of the identified significant predictors. Conclusions: It is timely to have a synthesis of predictors that influence the malaria status of children under-five in SSA. The outcome of the review will increase the knowledge of the epidemiology of morbidity that will form the basis for designing efficient and cost-effective distribution of palliatives and control of malaria in SSA.

Suggested Citation

  • Phillips Edomwonyi Obasohan & Stephen J. Walters & Richard Jacques & Khaled Khatab, 2021. "A Scoping Review of Selected Studies on Predictor Variables Associated with the Malaria Status among Children under Five Years in Sub-Saharan Africa," IJERPH, MDPI, vol. 18(4), pages 1-21, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:2119-:d:503578
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    References listed on IDEAS

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    1. Mbalenhle Mkhize & Melusi Sibanda, 2020. "A Review of Selected Studies on the Factors Associated with the Nutrition Status of Children Under the Age of Five Years in South Africa," IJERPH, MDPI, vol. 17(21), pages 1-26, October.
    2. Samuel Manda & Ndamonaonghenda Haushona & Robert Bergquist, 2020. "A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa," IJERPH, MDPI, vol. 17(9), pages 1-20, April.
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    Cited by:

    1. Phillips Edomwonyi Obasohan & Stephen J. Walters & Richard M. Jacques & Khaled Khatab, 2024. "The Risk Factors Associated with the Prevalence of Multimorbidity of Anaemia, Malaria, and Malnutrition among Children Aged 6–59 Months in Nigeria," IJERPH, MDPI, vol. 21(6), pages 1-22, June.
    2. Phillips Edomwonyi Obasohan & Stephen J. Walters & Richard Jacques & Khaled Khatab, 2021. "Individual and Contextual Factors Associated with Malaria among Children 6–59 Months in Nigeria: A Multilevel Mixed Effect Logistic Model Approach," IJERPH, MDPI, vol. 18(21), pages 1-25, October.

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