ORIGINAL RESEARCH article
Front. Pediatr.
Sec. General Pediatrics and Pediatric Emergency Care
Volume 13 - 2025 | doi: 10.3389/fped.2025.1559140
Mapping the covariate-adjusted spatial effects of childhood anemia in Ethiopia using a semi-parametric additive model
Provisionally accepted
- 1Department of Statistics, College of Natural and Computational Sciences, Debre Tabor, Ethiopia
- 2Department of Statistics, University of Pretoria, Pretoria, South Africa
- 3Department of Statistics, Faculty of Science, University of Johannesburg, Johannesburg, South Africa
- 4College of Health Solution, Arizona State University,, Phoenix, 85004,, United States
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Background: Globally, anemia poses a serious health challenge for children under the age of five, and Ethiopia is one of the countries significantly affected by this issue. The 2016 Ethiopian Demographic and Health Survey (DHS) data sets were employed to evaluate anemia risk among children aged 6 to 59 months. Due to limited research has been conducted on childhood anemia spatial disparities at the Ethiopian zonal level, and it is essential for developing zonallevel interventions for inform policy recommendations.Methods: This study was examined the geospatial disparities in anemia prevalence among children aged 6 to 59 months. We used a semi-parametric additive model with spatial smoothing to assess zone-level variation in anemia risk while adjusting for key covariates.Results: A regularized random forest techniques was employed to identify the most influential predictors of childhood anemia and enhance the model predictive performance. Our findings revealed that the regional states of Somalia, Afar, and Dire Dawa exhibit the highest risk levels for childhood anemia. Furthermore, the risk of anemia in children varies spatially across different zones in Ethiopia. The most prominent hotspots for childhood anemia were in the country's Northeastern, Eastern, and Southeastern regions. In contrast, the areas with the lowest risk were in Northwestern, Western, and Southwestern zones of Ethiopia.The significant spatial disparities in anemia risk across the administrative zones of Ethiopia, indicating that the distribution of each predictor variable is not uniform. These findings provide valuable insights for policymakers, enabling the development of geographically targeted interventions to mitigate anemia risk at the zonal level.
Keywords: Geolocations, semi-parametric, spatial, Anemia, Ethiopia
Received: 11 Jan 2025; Accepted: 31 Jul 2025.
Copyright: © 2025 Yilema, Shiferaw, Nakhaeirad and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Seyifemickael Amare Yilema, Department of Statistics, College of Natural and Computational Sciences, Debre Tabor, Ethiopia
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