ArticleBMC public health2025
Reducing acute respiratory infections in under-five children in Nigeria through the mirror of risk factors: a cross-sectional study.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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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.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
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2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGlobally, acute respiratory infections (ARIs) account for nearly 20% of all deaths among children under five years old. In low- and middle-income countries, the prevalence of ARIs ranges from 1.9 to 60.2%, with socioeconomic conditions significantly increasing the risk. Despite advancements in the management of ARIs in Nigeria, the country has not yet met global control targets.
methodsThis cross-sectional study investigated the spatial heterogeneity of identified ARI risk factors in under-five children in Nigeria with the goal of determining which to address in each location, utilizing data from the 2021 Multiple Indicator Cluster Survey (MICS) and the 2018 Nigeria Demographic and Health Survey. The study employed multiple linear regression (MLR) and geographically weighted regression (GWR) analyses, taking the percentage of children aged 0-59 months for whom the mother/caretaker reported symptoms of ARI during the 2021 MICS as the dependent variable and the identified risk factors as independent variables, at 0.05 significance level.
resultsA north-south divide was noted in the reported ARIs cases, with higher number of cases in the northern region. The fitted MLR model was significant, with multiple R
conclusionWhile the study highlights the spatial heterogeneity of ARI risk factors, it provides information on the factors to prioritize per state for effective control interventions.
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