Experimental study investigates excess dietary iron impacts on hematocrit and glycemia, indicating nuanced health risks.
Objective To examine the systemic biological effects of excess dietary iron and elevated hemoglobin in the context of the 2024 World Health Organization revision of anemia thresholds. This study integrates experimental evidence from BALB/c mice with previously proposed diagnostic indices (SF/TSAT and SF×TSAT) to distinguish iron overload from inflammation. Methods This study is based on an experimental murine model, with human evidence incorporated to provide contextual interpretation. BALB/c mice were exposed to graded oral iron supplementation, and hematocrit and glycemia were evaluated across different metabolic conditions. The findings were interpreted in the context of established human diagnostic criteria and recognized modulators of iron absorption. Results Iron supplementation induced a dose-dependent increase in hematocrit, with higher values observed in operationally defined obese mice. Hematocrit–glycemia coupling strengthened following supplementation (overall r = 0.62; p < 0.01), with stronger correlations in operationally defined obese mice (r = 0.74) and in females (r = 0.72), suggesting that both metabolic status and sex may modulate this relationship. The 2024 WHO revised hemoglobin thresholds are expected to reduce global anemia prevalence estimates, potentially modifying population-level interpretations. Dietary ascorbic acid intake and circadian hepcidin rhythms emerged as relevant determinants of iron absorption and systemic iron dynamics. Conclusions Both iron deficiency and iron excess are associated with adverse outcomes, reflecting a U-shaped relationship between iron status and risk. These findings support precision-based iron supplementation strategies that incorporate validated diagnostic markers, while considering metabolic context and chronobiological regulation. Such approaches may improve anemia management while minimizing unintended iron excess in non-deficient populations.
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Rivera-Manhualaya et al. (2026) studied this question.
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