Iron deficiency anemia (IDA) is the most prevalent nutritional deficiency worldwide, affecting nearly 2 billion people globally and contributing significantly to morbidity. It is characterized by reduced hemoglobin synthesis due to inadequate iron availability, resulting in microcytic hypochromic anemia. Hematological indices such as MCV, MCH, MCHC, and RDW are widely used for diagnosis and classification. Serum ferritin is considered the most reliable indicator of iron stores; however, it may not always be feasible in low-resource settings. Therefore, correlating hematological parameters with disease severity is essential for early and cost-effective diagnosis. This study aims to evaluate the relationship between hematological parameters and severity of iron deficiency anemia in a tertiary care setting.

Study Design and Setting A hospital-based cross-sectional observational study conducted in a tertiary care hospital. Study Population • Total sample size: 150 patients • Age: ≥18 years • Inclusion: Confirmed cases of iron deficiency anemia • Exclusion: Chronic disease anemia, hemoglobinopathies, recent transfusion Data Collection Blood samples were collected under aseptic conditions. Laboratory Analysis • Hemoglobin (Hb) • MCV, MCH, MCHC • RDW • Serum ferritin (ELISA method) Classification of Anemia (WHO criteria) • Mild: Hb 10–11.9 g/dL • Moderate: Hb 7–9.9 g/dL • Severe: Hb <7 g/dL Statistical Analysis • SPSS version 25 • Pearson correlation coefficient • p-value <0.05 considered significant.

A total of 150 patients diagnosed with iron deficiency anemia (IDA) were included in the present study. The demographic profile revealed a mean age of 34.5 ± 12 years, indicating that the majority of participants belonged to the young and middle-aged adult population. A clear female predominance was observed, with females constituting 65% of the study population, while males accounted for 35%. This gender distribution is consistent with the known higher prevalence of iron deficiency anemia among women, particularly due to factors such as menstrual blood loss, pregnancy, and nutritional deficiencies. Based on the severity of anemia as per WHO classification, 30% of the patients were categorized as having mild anemia, 50% as moderate anemia, and 20% as severe anemia. The higher proportion of moderate anemia cases suggests delayed healthcare-seeking behavior or underdiagnosis in early stages, which is commonly observed in resource-limited settings. The analysis of hematological parameters demonstrated findings characteristic of microcytic hypochromic anemia. The mean hemoglobin level was 8.9 ± 1.6 g/dL, reflecting an overall moderate degree of anemia in the study population. Red cell indices showed a reduced mean corpuscular volume (MCV) of 70.2 ± 6.8 fL and mean corpuscular hemoglobin (MCH) of 22.1 ± 2.5 pg, both indicative of microcytosis and hypochromia. The mean corpuscular hemoglobin concentration (MCHC) was also decreased (29.5 ± 2.2 g/dL), further supporting the diagnosis of hypochromic anemia. In contrast, red cell distribution width (RDW) was elevated (17.8 ± 3.1%), indicating increased anisocytosis, which is a typical feature of iron deficiency anemia. The mean serum ferritin level was found to be 18.2 ± 7.5 ng/mL, confirming depleted iron stores in the majority of patients. Correlation analysis was performed to assess the relationship between serum ferritin levels and hematological parameters. A strong positive correlation was observed between ferritin and hemoglobin levels (r = +0.78, p < 0.001), suggesting that lower iron stores are significantly associated with reduced hemoglobin concentration. Similarly, MCV showed a significant positive correlation with ferritin (r = +0.65, p < 0.001), indicating that iron deficiency contributes to decreased red cell size. MCH also demonstrated a positive correlation (r = +0.60, p < 0.01), reflecting reduced hemoglobin content within red blood cells in iron-deficient states. MCHC exhibited a moderate positive correlation with ferritin (r = +0.48, p < 0.05), suggesting that hemoglobin concentration within red cells decreases as iron stores decline. In contrast, RDW showed a significant negative correlation with ferritin levels (r = -0.62, p < 0.001). This inverse relationship indicates that as iron stores diminish, there is increased variability in red blood cell size due to the presence of both normal and microcytic cells. Overall, the findings demonstrate that hematological parameters are closely associated with iron status and severity of anemia. The strong correlations observed reinforce the utility of routine hematological indices as reliable indicators for assessing iron deficiency anemia, particularly in settings where advanced biochemical tests may not be readily available.

The present study demonstrated a statistically significant correlation between hematological parameters and the severity of iron deficiency anemia (IDA), reaffirming the critical role of routine hematological indices in both diagnosis and assessment of disease severity. A progressive decline in hemoglobin levels and red cell indices, including mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC), was observed with decreasing serum ferritin levels. This trend clearly indicates that depletion of iron stores is directly associated with worsening anemia, as reflected in both quantitative and morphological red blood cell changes. The strong positive correlation between serum ferritin and hemoglobin (r = +0.78) observed in this study is consistent with the fundamental pathophysiology of IDA, where inadequate iron availability leads to impaired hemoglobin synthesis. Similarly, the significant positive correlation between ferritin and MCV (r = +0.65) highlights the development of microcytosis as iron deficiency progresses. These findings are in agreement with previously published studies, which have reported comparable correlations between ferritin levels and red cell indices, thereby validating the reliability of these parameters in assessing iron status. In addition to red cell indices, red cell distribution width (RDW) emerged as an important parameter in the present study. A significant inverse correlation between RDW and ferritin (r = -0.62) was observed, indicating that RDW increases as iron stores decrease. Elevated RDW reflects increased heterogeneity in red blood cell size (anisocytosis), which is a hallmark feature of iron deficiency anemia. This occurs due to the coexistence of newly produced microcytic cells and older normocytic cells in circulation. The findings of this study are supported by existing literature that identifies RDW as an early and sensitive indicator of iron deficiency, often rising before significant changes in hemoglobin or MCV become apparent. The study further emphasizes that routine hematological parameters can serve as practical and cost-effective surrogate markers for assessing iron deficiency anemia, especially in resource-constrained settings where advanced biochemical tests such as serum ferritin may not be readily available. Given the widespread availability and affordability of complete blood count (CBC) testing, reliance on red cell indices can facilitate early detection, prompt intervention, and improved patient outcomes. Overall, the results underscore the clinical utility of hematological parameters not only in diagnosing iron deficiency anemia but also in gauging its severity. Integrating these indices into routine clinical practice can enhance diagnostic efficiency and support evidence-based decision-making, particularly in settings with limited access to specialized investigations.

Hematological parameters such as hemoglobin, MCV, MCH, and RDW show a significant correlation with the severity of iron deficiency anemia. These parameters can serve as reliable, cost-effective diagnostic tools in resource-limited settings. LIMITATIONS The present study has certain limitations that should be considered while interpreting the findings. The relatively small sample size may limit the statistical power and generalizability of the results. Being a single-center study, the observations may not fully represent the broader population. Additionally, the absence of longitudinal follow-up restricts the ability to assess changes in hematological parameters over time or response to treatment. Furthermore, the study relied on limited biochemical markers, primarily serum ferritin, without incorporating additional iron profile parameters such as serum iron, total iron-binding capacity, or transferrin saturation, which could have provided a more comprehensive evaluation of iron status.

1. Jogu P, Kamran MT. Iron deficiency anemia. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2016. Available from: https://www.ncbi.nlm.nih.gov/books 2. Yasmeen N, Khan S, Ali R, et al. Correlation between serum ferritin and hematological parameters in patients with iron deficiency anemia. Pak J Med Health Sci. 2016;17(2):345–349. 3. Sharanya Raj NL, Sreelatha M, Kumar S, et al. Correlation of red cell indices with serum ferritin in iron deficiency anemia. Biomedicine. 2016;39(4):587–592. 4. Sharma JB, Suri V, Sikka P, et al. Hematological indices and iron status in patients with iron deficiency anemia. Eur J Obstet Gynecol Reprod Biol. 2016;200:125–129. 5. World Health Organization. Iron deficiency anemia: assessment, prevention and control. Geneva: WHO; 2016. 6. DeLoughery TG. Iron deficiency anemia. Med Clin North Am. 2016;101(2):319–332. 7. Camaschella C. Iron-deficiency anemia. N Engl J Med. 2015;372(19):1832–1843. 8. Killip S, Bennett JM, Chambers MD. Iron deficiency anemia. Am Fam Physician. 2007;75(5):671–678. 9. Weiss G, Goodnough LT. Anemia of chronic disease. N Engl J Med. 2005;352(10):1011–1023. 10. Bessman JD, Gilmer PR, Gardner FH. Improved classification of anemias by MCV and RDW. Blood Cells. 1983;9(1):153–160. 11. Hoffbrand AV, Moss PAH. Essential Haematology. 7th ed. Oxford: Wiley-Blackwell; 2016. 12. Bain BJ, Bates I, Laffan MA. Dacie and Lewis Practical Haematology. 12th ed. Philadelphia: Elsevier; 2016. 13. Hall JE, Guyton AC. Guyton and Hall Textbook of Medical Physiology. 14th ed. Philadelphia: Elsevier; 2016. 14. Bain BJ. Blood Cells: A Practical Guide. 5th ed. Oxford: Wiley-Blackwell; 2015. 15. World Health Organization. Global prevalence of anemia in 2011. Geneva: WHO; 2015. 16. Centers for Disease Control and Prevention (CDC). Iron deficiency anemia guidelines. Atlanta: CDC; 2016. 17. Cook JD. Diagnosis and management of iron-deficiency anemia. Blood. 1999;93(1):1–9. 18. Mast AE, Blinder MA, Gronowski AM, et al. Clinical utility of serum ferritin in diagnosing iron deficiency anemia. Blood. 1998;92(2):771–776. 19. Thomas C, Thomas L. Biochemical markers and hematologic indices in the diagnosis of functional iron deficiency. Clin Chem. 2002;48(7):1066–1076. 20. Aapro M, Österborg A, Gascón P, et al. Prevalence and management of iron deficiency in clinical practice. Ann Oncol. 2012;23(8):1953–1962. 21. Pasricha SR, Tye-Din J, Muckenthaler MU, et al. Iron deficiency. Lancet Haematol. 2016;8(7):e510–e521. 22. Oustamanolakis P, Koutroubakis IE. Pathophysiology and clinical implications of iron deficiency. Eur J Intern Med. 2011;22(1):17–21. 23. Andrews NC. Disorders of iron metabolism. N Engl J Med. 1999;341(26):1986–1995. 24. McLean E, Cogswell M, Egli I, et al. Worldwide prevalence of anemia. Public Health Nutr. 2009;12(4):444–454. 25. World Health Organization. Nutritional anaemias: tools for effective prevention and control. Geneva: WHO; 2016.