Determinants of Anemia in Pediatric Populations

Anemia in children arises from a complex interplay of nutritional, infectious, genetic and socio-environmental factors. Inadequate dietary intake of iron and other micronutrients such as vitamin A, folate and zinc remains the primary driver, often exacerbated by poor dietary diversity and early cessation of breastfeeding. Recurrent infections – notably malaria, helminthiasis and chronic inflammation – further impair hemoglobin synthesis and iron absorption. Socio-economic determinants including household poverty, maternal education, access to potable water and sanitation influence both feeding practices and exposure to pathogens. Genetic haemoglobinopathies and maternal anaemia contribute to early-life vulnerability, while community-level factors such as healthcare access, vaccination coverage and geographic disparities modulate overall risk. Together, these determinants underscore the need for integrated public health strategies that combine nutrition, infection control, education and environmental improvements to reduce the global burden of childhood anaemia.

Research from Nature Portfolio

Recent studies have employed high-resolution spatial modelling and machine-learning to advance understanding of paediatric anaemia risk. One approach integrated demographic health surveys with climate, land-use and remote-sensing data, applying Bayesian distributional regression to generate age-specific, subnational maps of haemoglobin levels and identify socio-economic and environmental hotspots. This methodology reveals persistent disparities within and between regions, informing targeted interventions. In parallel, a machine-learning analysis of national survey data used feature-selection algorithms to rank predictors of anaemia among under-five children. This work highlighted household size, distance to health facilities, maternal wealth and education, type of cooking fuel and sanitation practices as the most influential factors shaping paediatric haemoglobin status, offering policy-relevant insights for resource allocation and programme design.

Determinants of Anemia in Pediatric Populations publication trend

The graph below shows the total number of articles in determinants of anemia in pediatric populations across all publications each year (not limited to Nature Index journals).

Technical terms

Hemoglobin concentration: The amount of haemoglobin per unit of blood, reflecting oxygen-carrying capacity and used to define anaemia severity.

Stunting: A measure of chronic malnutrition expressed as low height-for-age, indicating long-term nutritional deprivation.

Ferritin: A blood protein that stores iron; low ferritin levels indicate depleted iron reserves and risk of iron-deficiency anaemia.

Bayesian distributional regression: A statistical framework that estimates the full probability distribution of an outcome (e.g. haemoglobin levels) across space and time, accounting for uncertainty and multiple predictors.

Boruta algorithm: A feature-selection method in machine learning that iteratively identifies the most relevant variables for predicting an outcome by comparing their importance to that of randomized features.

References

1. High-resolution spatial prediction of anemia risk among children aged 6 to 59 months in low- and middle-income countries. Communications Medicine (2025).
2. The application of machine learning approaches to determine the predictors of anemia among under five children in Ethiopia. Scientific Reports (2023).
3. Prevalence and Determinants of Stunting-Anemia and Wasting-Anemia Comorbidities and Micronutrient Deficiencies in Children Under 5 in the Least-Developed Countries: A Systematic Review and Meta-analysis. Nutrition Reviews (2024).
4. Association between Child Nutritional Anthropometric Indices and Iron Deficiencies among Children Aged 6–59 Months in Nepal. Nutrients (2024).