ArticleBMC public health2025
Determinants of childhood anaemia in Nigeria: a public health perspective using quantile regression analysis.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundIn Nigeria, anaemia is still a major public health issue for children under five, and its high prevalence is caused by a variety of risk factors. Conventional regression techniques frequently ignore the ways in which these risk factors affect various population segments. The distributional effects of environmental and sociodemographic factors on childhood haemoglobin levels are investigated in this study using quantile regression.
methodData from the 2021 Nigeria Integrated Malaria Survey (NIMS) and the Demographic and Health Survey (DHS) household dataset were combined to produce a pooled sample. Using SPSS, a quantile regression analysis was performed to evaluate the relationship between haemoglobin levels in children aged 6–59 months and a number of risk factors, such as altitude, child age, region, housing materials, household wealth index, mosquito net usage, sex, recent fever, and malaria status. Quantile regression has an advantage over binary logistic regression in that it makes it possible to ascertain how the independent factors affect the full distribution of the dependent variable.
resultsThe results of the investigation showed that risk factors had different effects on haemoglobin levels depending on the distribution. Children with substandard housing materials, those from the poorest households, and those from certain locations (north-east, north-west, and south-east) had considerably lower haemoglobin levels, especially at the lower quantiles. Higher haemoglobin levels were linked to protective factors such as growing older, being a woman, sleeping beneath mosquito nets, not having had a recent illness, and having a negative malaria status; these effects were frequently more noticeable at quantiles. These results demonstrate how the most vulnerable children bear a disproportionate amount of the anaemia burden.
conclusionQuantile regression provided a nuanced understanding of the determinants of childhood anaemia, revealing that socio-economic disadvantage, regional disparities, and malaria infection exert the greatest impact among children with the lowest haemoglobin levels. Universal and targeted interventions addressing poverty, housing quality, malaria prevention, and equitable access to health resources are essential to reduce the burden of anaemia and promote health equity. RECOMMENDATIONS: Interventions for the most vulnerable children should be given top priority by policymakers and medical professionals, especially for those living in high-burden areas and the quintiles with the lowest incomes. Improving socioeconomic conditions, expanding access to high-quality healthcare and nutrition, and improving malaria control measures (such universal mosquito net coverage) are all important strategies. It is advised that more studies employ quantile regression to track the reduction of childhood anaemia and inform focused public health initiatives.
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