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Background Malaria remains a leading cause of morbidity and mortality among children under five in Uganda.
Despite national control efforts, significant disparities and inequalities in prevalence persist across regions, residences,
and mean socio-economic status. This study examines the socio-demographic factors and wealth-related inequalities
associated with malaria among children under five in Uganda.
Methodology A secondary analysis of data from the Uganda Malaria Indicator Survey (UMIS) 2018–2019 was con-
ducted. A sample of 4,600 children with malaria test results was included in the study. The distribution of malaria
prevalence across socio-demographic factors was analysed using cross-tabulations and a chi-squared test. Malaria-
related inequalities were measured using equity plots and the concentration index (CIX). A multilevel logistic regres-
sion model was used to examine the relationship between malaria prevalence and associated factors. The results are
presented as adjusted odds ratios (aORs) with 95% confidence intervals (CI).
Results Almost twenty-three in every 100 children under five had malaria infection (95% CI: 19.2–27.0). Regional vari-
ations in malaria prevalence and wealth-related inequalities were observed. The multilevel model identified several
significant independent factors: older child age (aOR = 2.12, 95% CI: 1.51–2.96, P < 0.001), child’s anemia (aOR = 3.16,
95% CI: 2.33–4.29, P < 0.001), and larger household size (aOR = 1.98, 95% CI: 1.13–3.45, P < 0.05) were positively associ-
ated with malaria in children under five years in Uganda. A negative concentration index (CIX = − 0.334, P < 0.001)
was also observed, indicating that higher malaria prevalence is concentrated among children in the poorest wealth
quintile.
Conclusion Malaria prevalence in Uganda is associated with a complex interplay of socioeconomic and geographic
factors. The substantial disparities observed highlight the need for tailored public health strategies designed for high-
burden regions and vulnerable communities to reduce disease burden effectively |
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