Multilevel modelling of the risk of malaria among children aged under five years in Nigeria

Victor M Oguoma, Anayochukwu E Anyasodor, Adeniyi O Adeleye, Obiora A Eneanya, Evaristus C Mbanefo

Research output: Contribution to journalArticle

Abstract

Background Malaria is still a major cause of morbidity and mortality among children aged <5 y (U5s). This study assessed individual, household and community risk factors for malaria in Nigerian U5s. Methods Data from the Nigerian Malaria Health Indicator Survey 2015 were pooled for analyses. This comprised a national survey of 329 clusters. Children aged 6–59 mo who were tested for malaria using microscopy were retained. Multilevel logit model accounting for sampling design was used to assess individual, household and community factors associated with malaria parasitaemia. Results A total of 5742 children were assessed for malaria parasitaemia with an overall prevalence of 27% (95% CI 26 to 28%). Plasmodium falciparum constituted 98% of the Plasmodium species. There was no significant difference in parasitaemia between older children and those aged ≤12 mo. In adjusted analyses, rural living, northwest region, a household size of >7, dependence on river and rainwater as primary water source were associated with higher odds of parasitaemia, while higher wealth index, all U5s who slept under a bed net and dependence on packaged water were associated with lower odds of parasitaemia. Conclusion Despite sustained investment in malaria control and prevention, a quarter of the overall study population of U5s have malaria. Across the six geopolitical zones, the highest burden was in children living in the poorest rural households.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalTransactions of the Royal Society of Tropical Medicine and Hygiene
DOIs
Publication statusE-pub ahead of print - 18 Sep 2020

Fingerprint Dive into the research topics of 'Multilevel modelling of the risk of malaria among children aged under five years in Nigeria'. Together they form a unique fingerprint.

Cite this