Anemia, a condition marked by low red blood cell count or hemoglobin concentration, impairs oxygen delivery to tissues and is a major public health issue in India. It predominantly affects young children, adolescent girls, and pregnant or postpartum women. Globally, it impacts around 269 million children and 500 million women, with the highest burden in Africa and South-East Asia¹. The condition is most prevalent in rural, low-income, and less-educated populations².According to the National Family Health Survey-5 (2019–21), anemia remains highly prevalent in India, affecting 67.1% of children (6–59 months), 57.2% of non-pregnant women, and 52.2% of pregnant women aged 15–49 years³. Anemia rates are consistently higher in rural populations across all groups. Multiple factors contribute to anemia, including nutrient deficiencies (especially iron), infections, chronic diseases, and blood loss. Iron deficiency anemia, the most common type, often results from poor dietary intake or impaired absorption⁴. Deficiencies in vitamins A, B12, and riboflavin also impair hemoglobin synthesis and increase anemia risk. Iron deficiency is the most prevalent form of malnutrition globally and is the leading cause of anemia, accounting for about 50% of all cases⁵. Ferritin, the body’s iron storage protein, serves as a reliable indicator of iron status. According to WHO, approximately 2.1 billion people worldwide suffer from iron deficiency anemia, affecting both high- and low-income countries. Simultaneously, diabetes is emerging as a major health challenge in these regions. In diabetic individuals, glycation of the NH2-terminal valine of the hemoglobin β-chain leads to the formation of HbA1c^6,7, the major glycated hemoglobin. HbA1c serves as the gold standard for evaluating glycemic control and reflects blood glucose levels over the preceding three months. Since 2010, HbA1c has been used not only to diagnose diabetes but also to screen individuals at high risk of developing the disease. As per the American Diabetes Association⁸, an HbA1c level ≥6.5% is diagnostic for diabetes, while maintaining levels below this threshold is recommended to prevent complications. However, HbA1c levels can be influenced by factors beyond blood glucose, such as age, hemoglobin variants, and conditions affecting red cell turnover like anemia. In iron deficiency anemia (IDA), alterations in hemoglobin structure and prolonged red cell lifespan may lead to falsely elevated HbA1c levels. Iron supplementation corrects anemia⁹, shortens RBC lifespan, and typically lowers HbA1c, suggesting a complex interplay between iron status and glycemic indicators. Several studies have shown that iron deficiency anemia can falsely elevate HbA1c levels, even in non-diabetic individuals, with levels often decreasing after iron therapy¹⁰. However, due to inconsistent findings and unclear mechanisms, this study was conducted to evaluate whether anemia should be considered before using HbA1c for clinical decisions¹¹.

AIM:

Study of association of HbA1C with iron deficiency anemia

This hospital-based observational descriptive study with a cross-sectional design was conducted in the Department of General Medicine, Mahatma Gandhi Medical College & Hospital, from March 2023 to August 2024. The study population included all patients diagnosed with iron deficiency anemia attending the outpatient and inpatient departments. Inclusion criteria were age above 18 years, written informed consent, hemoglobin levels <12 g% in males and <11 g% in females, MCV <76 fl, MCH <27 pg/cell, serum iron levels <50 µg/dl, and low serum ferritin levels. Exclusion criteria included pregnant and lactating females, known cases of diabetes mellitus, and patients unwilling to participate. Institutional Ethics Committee approval was obtained prior to the commencement of the study, and informed written consent was collected from all participants before enrolment.

Table 1. Distribution of study subject according to Age (N=120)

In this study 34 (28.3%) belonged to age group 21-30 yrs., 32 (26.7%) belonged to age group 31-40 yrs., 28 (23.3%) belonged to age group 41-50 yrs. and 26(21.7%) belonged to age group 51-60 yrs. The mean age of the study subject was 38.88 + 11.59 yrs.

Table 2: Distribution of study subject according to mean Glycemic Profile

In this study the mean fasting blood sugar of the study subject was 85.75 + 6.27 mg/dl with minimum 75 and maximum 96 mg/dl. The mean post prandial blood sugar of the study subject was 118.63 + 9.64 with minimum 102 and maximum 136 mg/dl. The mean

HbA1c of the study subject was 5.45 + 0.67 with minimum 4.20 and maximum 6.70.

Table 3: Distribution of study subject according to mean Anemic Profile

In this study, the mean hemoglobin level was 7.71 ± 1.38 g/dl, with corresponding averages for MCV (64.28 ± 5.41 fl), MCH (20.86 ± 2.94 pg/cell), serum ferritin (7.15 ± 1.73 mcg/L), serum iron (23.35 ± 3.65 mcg/dl), and transferrin saturation (8.29 ± 0.63%). All parameters showed relatively narrow ranges, indicating overall uniformity within the study population.

Table 4. Gender wise distribution of Anemic Profile (N=120)

In this study, male subjects had significantly higher mean levels of hemoglobin, MCV, MCH, serum ferritin, serum iron, and transferrin saturation compared to females, with all differences being statistically significant (p < 0.05 to p < 0.001). These findings highlight notable gender-based disparities in hematological and iron parameters among the study population.

Table 5: Correlation analysis of HbA1C with Hemoglobin, MCV, MCH, Serum Ferritin, Serum Iron, Transferrin Saturation

All studied parameters—hemoglobin, MCV, MCH, serum ferritin, serum iron, and transferrin saturation—showed a strong, statistically significant negative correlation with HbA1c (r values ranging from -0.938 to -0.987; p < 0.001). This indicates that as the levels of these hematological and iron indices fall, HbA1c levels rise significantly.

Table 6. Correlation analysis of FBS with Anemia Profile

All evaluated parameters—hemoglobin, MCV, MCH, serum ferritin, serum iron, and transferrin saturation—showed a negative but statistically non-significant correlation with FBS levels (p > 0.05), indicating a trend of rising FBS with declining parameter values. However, these associations were not statistically meaningful, suggesting no significant impact on fasting glucose.

Table 7. Correlation analysis of PPBS with Anemia Profile

All studied hematological and iron parameters—hemoglobin, MCV, MCH, serum ferritin, serum iron, and transferrin saturation—showed a negative but statistically non-significant correlation with PPBS levels (p > 0.05), indicating a trend of rising PPBS with declining parameter values. However, unlike HbA1c, which showed significant negative correlations with these parameters, the fasting and post-prandial blood sugar levels did not change significantly.

In this study mean age of the study subject was 38.88 + 11.59 yrs with 34 (28.3%) belonged to age group 21-30 yrs, 32 (26.7%) belonged to age group 31-40 yrs, 28 (23.3%) belonged to the age group 41-50 yrs and 26(21.7%) belonged to age group 51-60 yrs. So, most of the study subjects belonged to the age group 21 to 30 yrs and study subjects of age group 51 to 60 years were the least.

In our study the mean fasting blood sugar of the study subject was 85.75 + 6.27 mg/dl with minimum 75 and maximum 96mg/dl. Mean post prandial blood sugar of study subject was 118.63 + 9.64 with minimum 102 and maximum 136 mg/dl. The mean HbA1c of the study subject was 5.45 + 0.67 with minimum 4.20 and maximum 6.70. Christy et all¹² (2014) found the mean HbA1c value to be 6.87 ± 1.4% which corroborated with our findings.

In our study, the subject’s mean hemoglobin was 7.71 + 1.38 gm/dl (5.5 - 10.4). The mean MCV was 64.28 + 5.41 fl (54.97 - 75.89 fl). The mean MCH was 20.86 + 2.94 pg/cell (16.05 - 26.83). The mean serum ferritin of the study subject was 7.15 + 1.73 mcg/L (4.38 - 10.93). The mean serum iron level of the study subject was 23.35 + 3.65 mcg/dl (17.14 -30.87). The mean transferrin saturation was 8.29% + 0.63 % (7.20 - 9.40). Aydin et all¹³ (2022) who evaluated 146 patients of diabetes and iron deficiency anemia and they were provided ferrous sulphate 270 mg/day (80 mg elemental iron) orally for 3 months for IDA treatment. Hb baseline median had been ―10.4 (mg/dL) (9.5–11.1), MCV had been 74 (fL) (70.8–77), ferritin was 4 (ug/L) which after intervention at 3 months Hb had been computed at 12.6 (mg/dL) (12.1–13.2), MCV was measured at 82 (fL) (80–86), ferritin was measured at 15 (ug/L) (9–21.2) moreover had been significantly larger then baseline values‖ (p < 0.001). Christy et all¹² (2014) in a similar study found mean ferritin levels in female alongside male cases as 8.92 ± 5.72 & 14.88 ± 8.62ng/ml, correspondingly, mean hemoglobin levels in female alongside male cases as 9.37 ± 1.33 & 9.54 ± 1.4 g/dl, correspondingly. Mean MCV had been 53.2 ± 8.16 fL & mean MCH had been 17 ± 3.7 pg/cell for each case (females and males). These findings also corroborated with our findings.

In this study, male subjects had significantly higher mean values of hemoglobin, MCV, MCH, serum ferritin, serum iron, and transferrin saturation compared to females, with all differences statistically significant (p < 0.05 to p < 0.001). These findings reflect a consistent gender-related disparity in hematological and iron parameters.

In this study, while FBS and PPBS levels showed no significant difference between males and females (p > 0.05), females had significantly higher HbA1c levels (p < 0.05), likely due to greater anemia. Correspondingly, females exhibited significantly lower hemoglobin, MCV, MCH, serum iron, ferritin, and transferrin saturation levels compared to males (p < 0.05). Christy et all¹² (2014) in a similar study found that mean ferritin levels in female & male cases had been 8.92 ± 5.72 & 14.88 ± 8.62ng/ml, correspondingly. Moreover, ―mean FPG concentration had been 99.66±14.73 mg/dl in complete cases. Hemoglobin levels in female & male cases‖ had been 9.37 ± 1.33 & 9.54 ± 1.4 g/dl, correspondingly. Mean MCH had been 17 ± 3.7 pg/cell & Mean MCV had been 53.2 ± 8.16 fL for each case (females & males). So in our study too mean ferritin and hemoglobin level was less in female compared to males. In that study HbA1c had been significantly greater in females moreover in subjects >50 yrs age than males moreover subjects <50 yrs age. Even the odds ratio for HbA1c >6.5% for subjects having fasting glucose levels among 100-126 had been 5 times greater in females & 4 times greater in total population, however it had been non-significant in males. In our study too the HbA1c was significantly higher in females.

In our study, HbA1c levels showed a strong and statistically significant negative correlation with all anemia-related parameters—hemoglobin (r = -0.963), MCV (r = -0.987), MCH (r = -0.938), serum ferritin (r = -0.969), serum iron (r = -0.986), and transferrin saturation (r = -0.985), all with p < 0.001. This indicates that as the levels of these hematological and iron markers decline, HbA1c levels significantly increase. Overall, the findings suggest that anemia may lead to an overestimation of HbA1c, underscoring the need for cautious interpretation in anemic patients. Alzahrani et all (2023)¹⁴ also in their case control study found that the mean HbA1c levels were significantly higher in IDA at 5.75%(95%CI=5.68–5.82) with respect to control grp at 5.31%(95%CI=5.22–5.41). Even after giving treatment there was significant drop in HbA1c from 5.75-5.44% which had been highly significant (p-value of < 0.001).

In our study, correlation analysis revealed that both FBS and PPBS levels were negatively correlated with hemoglobin, MCV, MCH, serum ferritin, serum iron, and transferrin saturation, indicating a trend where glycemic levels rose as anemia-related parameters declined. However, none of these correlations reached statistical significance (p > 0.05). This suggests that although a consistent inverse relationship was observed, the associations were not strong enough to be deemed statistically meaningful.

HbA1c and anemia are related and we must be careful in diagnosing diabetic and pre-diabetic in anemic subjects. In this study females were more anemic than males with all parameters like MCV, hemoglobin, MCH, serum iron, serum ferritin along with transferrin saturation were lower in females compared to females. But the

HbA1c level was significantly higher in females compared to males. Hemoglobin, MCV, MCH, serum ferritin, serum iron and transferrin saturation were negatively correlated with HbA1c which means as their level falls HbA1c level increases, even though they had no relationship with fasting and post prandial blood sugar. So while screening for diabetes hemoglobin level must be measured as severe anemia may spuriously elevate the HbA1c and wrongly tag a non-diabetic as diabetic.

1. " American Society of Hematology, www.hematology.org/education/patients/anemia. Accessed 16 Oct. 2024.
2. "Anaemia." World Health Organization, www.who.int/news-room/fact-sheets/detail/anaemia. Accessed 15 Oct. 2024.
3. "Global Health Metrics: Anaemia–Level 1 Impairment." The Lancet, vol. 393, 2019.
4. "NFHS-5 Phase-II." Ministry of Health and Family Welfare, Government of India, https://mohfw.gov.in/sites/default/files/NFHS-5_Phase-II_0.pdf. Accessed 3 Dec. 2024.
5. Georgieff, Michael K. "Iron Deficiency in Pregnancy." American Journal of Obstetrics and Gynecology, vol. 223, no. 4, 14 Mar. 2020, p. 516.
6. John, A. "Iron Deficiency and Other Hypoproliferative Anemias." Principles of Internal Medicine by Harrison’s, edited by Dennis L. Kasper et al., 17th ed., McGraw-Hill, 2008, pp. 628–35.
7. DeMaeyer, E. M., and M. Adiels-Tegman. "The Prevalence of Anaemia in the World." World Health Statistics Quarterly, vol. 38, no. 3, 1985, pp. 302–16.
8. McLean, E., et al. "Worldwide Prevalence of Anaemia, WHO Vitamin and Mineral Nutrition Information System, 1993–2005." Public Health Nutrition, vol. 12, no. 4, 2009, pp. 54.
9. Stevens, Gretchen A., et al. "Global, Regional, and National Trends in Haemoglobin Concentration and Prevalence of Total and Severe Anaemia in Children and Pregnant and Non-Pregnant Women for 1995–2011: A Systematic Analysis of Population Representative Data." The Lancet Global Health, vol. 1, no. 1, 2013, pp. 16–25.