High-Res­o­lu­tion Esti­mates of Ane­mia in Chil­dren in Low- and Mid­dle-income Coun­tries

In 2019, the Nobel Memorial Prize in Economic Sciences was awarded to three development economists who have used experimental approaches in their research on global poverty alleviation. Their research aims to identify which types of aid actually help improve living conditions in low-income countries — and which do not. This drew political attention to the importance of targeted and effective measures, particularly in relation to the UN’s Sustainable Development Goals. One major challenge is "hidden hunger" — a deficiency in essential micronutrients such as iron or vitamin A —common in low- and middle-income countries. Anemia, which can result from this, occurs in various forms.

Although anemia in children is associated with stunted growth, impaired physical and cognitive development, and a higher risk of mortality, it has received less attention than other health issues. “To establish effective monitoring, it’s crucial to understand how anemia is distributed over time and space, and which age groups are most affected,” says Kenneth Harttgen, co-author of the study from ETH Zurich. Until now, such information has only been available for selected countries or regions. A study published in early March in Communications Medicine (Nature) now provides model-based estimates of anemia prevalence in children aged 6 to 59 months in sub-Saharan Africa and South Asia between 2005 and 2020.

The study is the result of a long-standing collaboration between statistical researchers Johannes Seiler, Nikolaus Umlauf, and Mattias Wetscher from the University of Innsbruck, development economist Kenneth Harttgen from ETH Zurich, and epidemiologist Jürg Utzinger, Director of the Swiss Tropical and Public Health Institute at the University of Basel. First author Johannes Seiler, who conducted the research while at the University of Innsbruck, is now based at the Technical University of Munich.

Complex and Computationally Intensive Modeling

The team at the University of Innsbruck’s Department of Statistics used Bayesian distributional regression models to estimate the risk of anemia based on factors such as place of residence, age and climatic conditions, and to assess how the disease has changed over time. The method relies on assumptions about possible associations, which are then refined using data. “Bayesian models are particularly well suited to drawing inferences about populations based on sample data, but they require significant computational power,” explains Nikolaus Umlauf.

“Distributional regression allows us to make fully probabilistic predictions and to examine how specific variables are related—for example: What’s the probability that a child with certain characteristics has a particular hemoglobin level?” adds first author Johannes Seiler, who conducted the study as part of an FWF-funded research project at the University of Innsbruck.

To perform the calculations, the team used the University’s high-performance computing cluster LEO 4. The models were trained on observational data from the Demographic and Health Surveys program—one of the key data sources for analyzing education, health, and nutrition in low- and middle-income countries—as well as on climate, population, environmental, and geospatial data, which first had to be combined in an efficient way.

Anemia Remains a Major Issue in Parts of Africa

The following picture emerges from the model-based estimates: In 2020, approximately 98.7 million children aged 6 to 59 months in sub-Saharan Africa and 95.1 million children in South Asia were affected by anemia. Based on a 20-kilometer grid, the maps produced in the study show how anemia prevalence evolved between 2010 and 2020—highlighting substantial regional disparities within and between countries. In sub-Saharan Africa, prevalence decreased slightly from 65.0 percent in 2010 to 63.4 percent in 2020. In South Asia, the rate declined from 63.1 percent to 58.8 percent over the same period.
Despite this modest progress, anemia remains a widespread health concern, particularly in many parts of Africa. In West African countries such as Burkina Faso and Mali, the prevalence has declined slightly but remains very high—dropping from 87 percent in 2010 to 77 percent in 2020 in Burkina Faso, with similar figures in Mali. However, there are also positive examples. In Madagascar, for instance, the predicted prevalence in 2020 was 47.3 percent—remarkably low given the country’s high rates of chronic and acute malnutrition.
The models also provide detailed insights, such as how different age groups are affected by mild, moderate, or severe anemia, and how prevalence varies by gender.

The study contributes to achieving the following Sustainable Development Goals (SDGs): SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-being), SDG 10 (Reduced inequalities).