Diabetes mellitus (DM) is a metabolic disorder caused by absolute or relative insulin deficiency, with increasing prevalence and associated complications worldwide (1). In India, about 10% of the population is affected. HbA1c is the gold standard for assessing glycemic control and predicting diabetic complications (2). It is recommended as a diagnostic tool by the American College of Endocrinology (ACE) and the American Diabetes Association (ADA) (3), reflecting average blood glucose over three months due to the lifespan of erythrocytes (4). ADA guidelines advise maintaining HbA1c below 7% to prevent complications, with levels above 7% indicating increased risk, especially for microvascular issues (5).

HbA1c testing offers advantages over glucose tests, including stability and reduced variation(6), though factors such as anemia, age, race, hemoglobinopathies, and certain conditions can affect HbA1c independent of glucose (7-10). Iron deficiency anemia (IDA) is a common condition affecting HbA1c reliability. It is prevalent in India and globally, contributing significantly to health burdens(11), with IDA seen as a sequence from iron depletion to anemia (11).

Studies indicate that IDA can alter HbA1c levels due to effects on erythrocyte turnover, either lowering or raising HbA1c values (12,13). Some studies report higher HbA1c in IDA patients, with levels decreasing after anemia correction (14-16), though findings are mixed (17,18). Given these inconsistencies, this study aims to explore the effects of IDA on HbA1c, highlighting the need for alternative glycemic markers in anemic populations.

Research indicates that IDA can artificially raise HbA1c levels, potentially leading to misleading interpretations of glycemic control:

• Rajendra Prasad et al. observed that HbA1c levels were significantly elevated in patients with IDA compared to controls, with mean HbA1c at 6.13% versus 5.12%, respectively. (2)
• Balasubramanian Shanthi et al. found higher HbA1c levels in IDA patients (7.6 ± 0.5%) than in controls (5.5 ± 0.8%), with no significant difference in fasting or postprandial glucose, concluding that IDA can elevate HbA1c independently of blood glucose levels.(19)
• Veeramalla & Madas found that HbA1c levels in IDA patients tended to normalize following iron supplementation, suggesting that iron deficiency may independently influence HbA1c readings.(20)
• Ford et al. noted that HbA1c readings were generally higher in individuals with anemia, emphasizing caution in diagnosing diabetes in patients with HbA1c levels around 6.5%.(21)
• Kumar S et al. reported a positive correlation between severe IDA and elevated HbA1c values, reinforcing the need for careful interpretation of HbA1c in the presence of anemia.(22)
• Singh et al. (2017) noted that iron deficiency could increase HbA1c, affecting the accuracy of diabetes diagnosis. (23)
• Adeoye et al. (2014) identified a significant 0.4% increase in HbA1c among anemic individuals but observed minimal change post-anemia correction, suggesting that anemia reference ranges for HbA1c may be necessary. (3)
• Kumar et al. (2017) and Maheshwari et al. (2017) both observed that increased anemia severity correlates with elevated HbA1c values, especially among reproductive-age women. (22,24)
• Other studies, such as Faldu et al. (2016) and Kim et al. (2010), emphasized the importance of ruling out IDA before relying solely on HbA1c for diabetes diagnosis.(5,25)
• Conversely, Vishal Kalasker et al. found lower HbA1c levels in anemic patients, indicating the impact of varying assay methods. (26)
• However, Coban et al. (2004) demonstrated that HbA1c levels in IDA patients dropped after iron supplementation, reinforcing the need to consider iron status in diabetes management. (27)
• Overall, the research highlights that HbA1c accuracy may be compromised in IDA patients, necessitating careful interpretation, especially in populations with high anemia prevalence.

Implications

HbA1c’s limitations in anemia and conditions that alter red blood cell turnover necessitate cautious interpretation, potentially requiring alternative markers in these cases. HbA1c remains a valuable tool, but factors like iron status must be considered for accurate diabetes classification and management.

AIM

• To study the effect of iron deficiency anaemia on glycosylated haemoglobin levels.
• To study association and correlation of various iron deficiency parameters and levels of HbA1C.

Ethics-approved recruitment of patients with anemia symptoms from the General Medicine Department of SNMC and HSK Hospital were considered considered for this study. Age and sex-matched healthy individuals served as controls. Informed consent was obtained.

Inclusion and Exclusion Criteria

·        Study Group (Anemic Participants):

• Age >18 years, with anemia as per WHO (Hb <13.0 g/dL in males; <12 g/dL in non- pregnant females).
• Microcytic, hypochromic blood smear, low serum ferritin (<9 ng/mL for females; <15 ng/mL for males), and normal fasting/postprandial glucose levels.

Control Group (Non-Anemic Healthy Participants)

• Age and sex-matched with WHO-defined normal Hb levels and serum ferritin above IDA thresholds.
• Excluded conditions (both groups): Diabetes mellitus, hemolytic anemia, chronic renal failure, amenorrhea, chronic alcohol use, recent blood transfusion, and other anemia types.

Data Collection

Comprehensive history, clinical examination, and diagnostic confirmation of anemia via laboratory investigations.

Laboratory Investigations

1. Complete Haemogram: Hemoglobin, MCV, MCH, and MCHC.
2. Peripheral Blood Smear
3. Blood Urea and Serum Creatinine
4. Blood Glucose: Fasting and postprandial.
5. HbA1c
6. Serum Ferritin (via CLIA).
7. HbA1c (via HPLC).
8. Additional tests (e.g., ECG, chest X-ray, ultrasound) when necessary.

Data Assessment and Statistical Analysis

Data was entered in Excel and analyzed using SPSS (v20). Quantitative data was reported using mean and standard deviation; qualitative data with frequencies and percentages. Pearson’s chi-square test was used to compare clinical parameters and assess diagnostic accuracy. Sample size was estimated based on a correlation coefficient of 0.593 (Sinha et al., 2012) with MedCalc Software, aiming for 99% confidence and 80% power.

Patient characteristics

The study and control groups had comparable age and sex distributions, as well as similar mean fasting blood sugar (FBS) and postprandial blood sugar (PPBS) levels.

As anticipated, patients in the study group exhibited anemia, with significantly lower hemoglobin (Hb), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and serum ferritin levels, all of which were statistically significant.

HbA1c Distribution

• Mean HbA1c: 5.78% (study) vs. 5.47% (control).
• P-value: <0.001, significant, suggesting elevated HbA1c in the anemia group.

The study group had a higher mean HbA1c (5.78%) compared to the control group (5.46%), which was statistically significant (p < 0.001).

Correlation Analysis (Hb and HbA1c)

●       Control Group:

• Pearson correlation coefficient: -0.043, P-value: 0.76 (not significant).

·        Study Group:

• Pearson correlation coefficient: -0.871, P-value: <0.001, indicating a significant negative correlation.
• Regression equation: HbA1c = -0.4679 x Hb + 8.7882, suggesting a 0.92% decrease in HbA1c for every 2 g/dL increase in Hb.

HbA1c levels showed a strong inverse correlation with hemoglobin levels in the IDA group (r = - 0.871, p = 0.001).

HbA1c, comprising approximately 5% of total hemoglobin in healthy individuals, is a reliable indicator of a patient’s average glycemic status over the past three months. It has gained recognition as a diagnostic tool for diabetes mellitus (DM) due to its high reproducibility and convenience, prompting recommendations for its use from organizations like the American Diabetes Association (ADA) and American College of Endocrinology (ACE). However, it is essential to recognize that HbA1c provides an indirect measure of blood glucose, and various factors beyond chronic hyperglycemia, including iron deficiency anemia (IDA), can influence Hb glycation. Studies suggest that iron deficiency may affect HbA1c levels independently of blood glucose, which has important implications for the clinical management of diabetic patients who also suffer from anemia.

IDA and Its Global Impact

IDA is one of the most common types of anemia worldwide, affecting approximately 2.1 billion people globally, with prevalence rising in both developed and developing countries. High-risk groups include children, adolescents, and women. In India, where about 50% of anemia cases are attributed to iron deficiency, this condition coexists with high DM prevalence. Understanding the relationship between IDA and HbA1c is crucial to avoid misleading glycemic assessments in anemic patients.

Study Objectives and Demographics

This study aimed to examine the effects of IDA on HbA1c levels. The study involved 50 patients with IDA, with an equal number of age- and sex-matched controls. The mean age of the study population was 41.46 years, and the majority (52%) were between 31-50 years old, with a higher prevalence of IDA in the 3rd and 4th decades of life. Women represented 68% of the study population, aligning with the fact that women are more prone to iron deficiency than men.

Key Findings and Statistical Analysis

• Hemoglobin Levels: The mean hemoglobin in the study group was 6.41 g/dL, with severe anemia (<8 g/dL) observed in 80% of the participants. Statistical analysis revealed significantly lower hemoglobin levels in the study group than in the control group (p < 0.001).
• Red Cell Indices: Both mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) were significantly lower in the study group compared to controls, reinforcing IDA diagnosis (p < 0.001).
• Iron Status: Serum ferritin levels were markedly lower in the study group (mean of 5.72 µg/L) compared to the control group (239.29 µg/L), confirming iron deficiency (p < 0.001).
• HbA1c Levels: The study group had a higher mean HbA1c (5.78%) compared to the control group (5.46%), which was statistically significant (p < 0.001). Notably, HbA1c levels showed a strong inverse correlation with hemoglobin levels in the IDA group (r = -0.871, p = 0.001).

Comparative Studies and Theories

Our findings are consistent with studies by Kairavi Bhardwaj et al., who observed an inverse relationship between Hb and HbA1c in patients with IDA. Other studies, such as those by Abdullah Mahal Ghareep Alenazi et al(28)., also support the hypothesis that IDA is associated with increased HbA1c values, suggesting that factors beyond blood glucose levels can influence HbA1c readings in anemic patients. Shailendra Kumar Manjhvar et al(22). and Koga et al(29). further corroborate that IDA can lead to elevated HbA1c levels, which could mislead DM diagnoses if HbA1c alone is used.

In contrast, Vishal Kalasker et al. (26)reported a positive correlation between Hb and HbA1c in non- diabetic Indian adults with IDA, concluding that IDA may not significantly affect DM diagnosis using HbA1c based on ADA guidelines. However, the variance in study findings is often attributed to differences in laboratory methods for HbA1c measurement, as highlighted by Van Heyningen et al. and Rai et al.(18)

Iron deficiency is the most common nutritional disorder globally, affecting an estimated 2.1 billion people, or roughly 30% of the world population. HbA1c, considered the "gold standard" for monitoring glycemic control, is also used to predict diabetic complications. However, HbA1c levels are influenced by several non-glycemic factors, including iron deficiency anemia (IDA), which can lead to skewed interpretations of glycemic status.

This study aimed to explore the impact of IDA on HbA1c levels. The results confirmed that IDA is notably prevalent among women in the third and fourth decades of life. The study group showed significantly higher mean HbA1c levels (5.78%) compared to the control group (5.46%), with a highly significant p-value of <0.001. This indicates a strong association between IDA and elevated HbA1c levels.

Additionally, a significant negative correlation (r = -0.871, p < 0.001) was found between hemoglobin and HbA1c levels in the IDA group, suggesting that as hemoglobin levels decrease, HbA1c levels tend to increase, highlighting the inverse relationship between IDA and HbA1c levels.

The findings underscore the need to account for iron deficiency status when interpreting HbA1c levels in diabetic patients to avoid overestimating poor glycemic control. Iron replacement therapy in diabetic individuals with IDA is crucial for improving the accuracy of HbA1c determinations.

LIMITATIONS

• Small sample size.
• Short study duration.
• Lack of post-anemia correction analysis for hemoglobin and HbA1c correlation.

These limitations suggest the need for further longitudinal studies to comprehensively understand the effects of IDA correction on HbA1c levels.

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