Mapping Hemoglobin Levels Among Women and Children Across Ethiopian Administrative Zones: A Geospatial Small Area Estimation Approach

Abstract Hemoglobin, an iron-rich protein in red blood cells, enables oxygen delivery to all body tissues. The hemoglobin records in most countries are collected through surveys. Surveys often provide reliable estimates of target variables for the population at both national and regional administration levels. This study investigates the spatial distribution of hemoglobin levels among women and children across Ethiopian administrative zones. Because survey sample sizes are often insufficient to produce reliable direct estimates at the zonal level, small area estimation methods are used to improve the precision of estimates. Small area estimation provides reliable estimates at the local zones by combining survey, census, and spatial datasets. Therefore, we focus on geospatial small area estimation to provide reliable and precise hemoglobin estimates for women and children. Therefore, our prime objective is to provide reliable and precise estimates of hemoglobin levels for women and children using geospatial small area estimation by integrating the survey and census datasets. An area-level Fay-Herriot modeling framework was implemented to estimate hemoglobin levels across the studied zones. The results show that for both children and women, the Spatial Empirical Best Linear Unbiased Predictor (SEBLUP) consistently produces the lowest coefficients of variation (CVs), followed by the standard Empirical Best Linear Unbiased Predictor (EBLUP), while direct survey estimates display the highest variability. The comparison of CVs for hemoglobin estimates demonstrates that children’s mean CVs decrease from 13.64 (Direct survey estimates) to 11.29 (EBLUP) and then to 6.06 (SEBLUP). Similarly, women’s mean CVs decline from 13.48 (Direct survey estimates) to 10.71 (EBLUP) and then 6.37 (SEBLUP), confirming that SEBLUP provides the highest precision for both children and women, consistently producing the lowest CVs across all statistical measures. The results in the maps indicate the spatial disparities in hemoglobin levels for both women and children among the Ethiopian administrative zones. Policymakers will significantly benefit from these local area-level estimates, and researchers will gain methodological insights into the application of geospatial small-area estimation.

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Publication Details

Journal
Applied Spatial Analysis and Policy
Published
2026-07-22
DOI
https://doi.org/10.1007/s12061-026-09949-2
Primary Topic
Iron Metabolism and Disorders
Type
article
Field-Weighted Citation Impact
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article

Mapping Hemoglobin Levels Among Women and Children Across Ethiopian Administrative Zones: A Geospatial Small Area Estimation Approach

Najmeh Nakhaei Rad, Seyifemickael Amare Yilema, Ding-Geng Chen
Applied Spatial Analysis and Policy
Iron Metabolism and Disorders
article

Mapping Hemoglobin Levels Among Women and Children Across Ethiopian Administrative Zones: A Geospatial Small Area Estimation Approach

Najmeh Nakhaei Rad, Seyifemickael Amare Yilema, Ding-Geng Chen
article en

Abstract

Abstract Hemoglobin, an iron-rich protein in red blood cells, enables oxygen delivery to all body tissues. The hemoglobin records in most countries are collected through surveys. Surveys often provide reliable estimates of target variables for the population at both national and regional administration levels. This study investigates the spatial distribution of hemoglobin levels among women and children across Ethiopian administrative zones. Because survey sample sizes are often insufficient to produce reliable direct estimates at the zonal level, small area estimation methods are used to improve the precision of estimates. Small area estimation provides reliable estimates at the local zones by combining survey, census, and spatial datasets. Therefore, we focus on geospatial small area estimation to provide reliable and precise hemoglobin estimates for women and children. Therefore, our prime objective is to provide reliable and precise estimates of hemoglobin levels for women and children using geospatial small area estimation by integrating the survey and census datasets. An area-level Fay-Herriot modeling framework was implemented to estimate hemoglobin levels across the studied zones. The results show that for both children and women, the Spatial Empirical Best Linear Unbiased Predictor (SEBLUP) consistently produces the lowest coefficients of variation (CVs), followed by the standard Empirical Best Linear Unbiased Predictor (EBLUP), while direct survey estimates display the highest variability. The comparison of CVs for hemoglobin estimates demonstrates that children’s mean CVs decrease from 13.64 (Direct survey estimates) to 11.29 (EBLUP) and then to 6.06 (SEBLUP). Similarly, women’s mean CVs decline from 13.48 (Direct survey estimates) to 10.71 (EBLUP) and then 6.37 (SEBLUP), confirming that SEBLUP provides the highest precision for both children and women, consistently producing the lowest CVs across all statistical measures. The results in the maps indicate the spatial disparities in hemoglobin levels for both women and children among the Ethiopian administrative zones. Policymakers will significantly benefit from these local area-level estimates, and researchers will gain methodological insights into the application of geospatial small-area estimation.

Applied Spatial Analysis and PolicyVol. 19(3)
Debre Tabor University (ET), Arizona State University (US), University of Pretoria (ZA)
Gender equality
Openalex Percentile: Top 9%
Iron Metabolism and Disorders
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