Mapping the spatial distribution and identifying local determinants of childhood anemia in Ghana: a geographically weighted regression analysis

Anemia remains a public health concern in Ghana. Mapping high-risk areas will help assess the effectiveness of existing health programs, guide resource allocation, and prioritize regions that require urgent attention. Therefore, this study aims to identify the geographic pattern and determinants of anemia among children aged 6 to 59 months in Ghana. The study utilized a weighted sample of 3577 children aged 6–59 months from the 2022 Ghana Demographic and Health Survey. Data were analyzed using Stata version 17 and ArcGIS version 10.7.1. Global Moran’s I statistic was used to assess the spatial autocorrelation of childhood anemia. A global Ordinary Least Squares regression model was used to estimate overall associations between childhood anemia and predictor variables. Furthermore, Geographically Weighted Regression was employed to capture spatial heterogeneity in these relationships across different geographic locations. The prevalence of anemia among children was 49.04% (95% CI 47.40–50.68%), with substantial regional variation. A higher prevalence was observed in the Northern, Upper East, and Northeast regions, while a lower prevalence was found in the Greater Accra, Ahafo, and Bono regions. Spatial analysis revealed significant clustering of anemia (Global Moran’s I = 0.22, p < 0.0001), indicating a non-random distribution and the presence of spatial heterogeneity. Hotspot areas were identified in Upper East, North East, Northern, Upper West, northeastern Oti, southeastern Savannah, and southeastern Upper West regions. Maternal anemia, lack of formal maternal education, household poverty, and childhood fever were identified as significant spatial predictors of childhood anemia. Childhood anemia in Ghana shows substantial spatial heterogeneity. In the high-burden regions, targeted scale-up of routine iron and micronutrient supplementation for children and pregnant women is recommended, alongside strengthened antenatal and postnatal nutrition counseling delivered through health facilities and community-based outreach services. In addition, household poverty reduction efforts should be linked with social protection programs in the most affected regions. Furthermore, integrating routine spatial monitoring and geospatial mapping of anemia cases into Ghana Health Service child health and nutrition programs would support continuous identification of hotspots.

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Journal
Scientific Reports
Published
2026-08-20
DOI
https://doi.org/10.1038/s41598-026-66877-4
Primary Topic
Iron Metabolism and Disorders
Type
article
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article

Mapping the spatial distribution and identifying local determinants of childhood anemia in Ghana: a geographically weighted regression analysis

Beminate Lemma Seifu, Yohannes Mekuria Negussie, Sintayehu Simie Tsega, Mamaru Melkam et al.
Scientific Reports
Iron Metabolism and Disorders
article

Mapping the spatial distribution and identifying local determinants of childhood anemia in Ghana: a geographically weighted regression analysis

Beminate Lemma Seifu, Yohannes Mekuria Negussie, Sintayehu Simie Tsega, Mamaru Melkam, Zufan Alamrie Asmare, Bezawit Melak Fente, Hiwot Altaye Asebe, Meklit Melaku Bezie, Angwach Abrham Asnake, Alemayehu Kasu Gebrehana
article en

Abstract

Anemia remains a public health concern in Ghana. Mapping high-risk areas will help assess the effectiveness of existing health programs, guide resource allocation, and prioritize regions that require urgent attention. Therefore, this study aims to identify the geographic pattern and determinants of anemia among children aged 6 to 59 months in Ghana. The study utilized a weighted sample of 3577 children aged 6–59 months from the 2022 Ghana Demographic and Health Survey. Data were analyzed using Stata version 17 and ArcGIS version 10.7.1. Global Moran’s I statistic was used to assess the spatial autocorrelation of childhood anemia. A global Ordinary Least Squares regression model was used to estimate overall associations between childhood anemia and predictor variables. Furthermore, Geographically Weighted Regression was employed to capture spatial heterogeneity in these relationships across different geographic locations. The prevalence of anemia among children was 49.04% (95% CI 47.40–50.68%), with substantial regional variation. A higher prevalence was observed in the Northern, Upper East, and Northeast regions, while a lower prevalence was found in the Greater Accra, Ahafo, and Bono regions. Spatial analysis revealed significant clustering of anemia (Global Moran’s I = 0.22, p < 0.0001), indicating a non-random distribution and the presence of spatial heterogeneity. Hotspot areas were identified in Upper East, North East, Northern, Upper West, northeastern Oti, southeastern Savannah, and southeastern Upper West regions. Maternal anemia, lack of formal maternal education, household poverty, and childhood fever were identified as significant spatial predictors of childhood anemia. Childhood anemia in Ghana shows substantial spatial heterogeneity. In the high-burden regions, targeted scale-up of routine iron and micronutrient supplementation for children and pregnant women is recommended, alongside strengthened antenatal and postnatal nutrition counseling delivered through health facilities and community-based outreach services. In addition, household poverty reduction efforts should be linked with social protection programs in the most affected regions. Furthermore, integrating routine spatial monitoring and geospatial mapping of anemia cases into Ghana Health Service child health and nutrition programs would support continuous identification of hotspots.

Scientific Reports
Samara University (ET), Wolaita Sodo University (ET), Debre Tabor University (ET), Salale University, Adama Science and Technology University (ET), University of Gondar (ET)
No poverty
Openalex Percentile: Top 10%
Iron Metabolism and Disorders
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