Evidence map›Paper›PMID 40918663›Full record

ArticleFrontiers in pediatrics2025

Mapping the covariate-adjusted spatial effects of childhood anemia in Ethiopia using a semi-parametric additive model.

Seyifemickael Amare Yilema, Yegnanew A Shiferaw, Najmeh Nakhaeirad, Ding-Geng Chen

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Article in Frontiers in pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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4 authors.

Seyifemickael Amare YilemaDepartment of Statistics, College of Natural and Computational Science, Debre Tabor University, Debre Tabor, Ethiopia.
Yegnanew A ShiferawDepartment of Statistics, University of Johannesburg, Johannesburg, South Africa.
Najmeh NakhaeiradDepartment of Statistics, University of Pretoria, Pretoria, South Africa.
Ding-Geng ChenDepartment of Statistics, University of Pretoria, Pretoria, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 6-59 months. Due to limited research has been conducted on childhood anemia spatial disparities at the Ethiopian zonal level, and it is essential for developing zonal-level interventions for inform policy recommendations. Methods: This study was examined the geospatial disparities in anemia prevalence among children aged 6-59 months. We used a semi-parametric additive model with spatial smoothing to assess zone-level variation in anemia risk while adjusting for key covariates. Each predictor variable was spatially adjusted using non-parametric smoothing techniques based on geolocation parameters, and corresponding maps for each predictor. 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. Conclusion: 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.

Indexed as

anemiaEthiopiageolocationssemi-parametricspatial

Identifiers

PMID40918663
PMCPMC12408295

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