Anaemia is a disorder characterized by a deficiency in the quantity of red blood cells or a reduced concentration of haemoglobin inside them. Red blood cells are essential for carrying oxygen throughout the body, and when hemoglobin levels are low, aberrant, or absent, the blood's ability to deliver oxygen to tissues is impaired.1 This causes a variety of symptoms, including, but not limited to, weakness, dizziness, weariness, and difficulty breathing. A person's ideal hemoglobin concentration to fulfill physiological demands changes with age, sex, altitude of habitation, smoking habits, and pregnant status.2 A hemoglobin concentration below a certain cut-off point is considered anaemia; the cut-off point varies with the age, gender, physiological status, smoking habits, and altitude of the group being evaluated. According to WHO, anaemia is defined as a hemoglobin concentration below 11 g/dL at sea level in children under 5 years old and pregnant women, and as a hemoglobin concentration below 12 g/dL and 13 g/dL in non-pregnant women and males, respectively.3 Factors that can lead to anemia include nutrient deficiencies caused by poor diet or absorption of nutrients, infections (such as HIV, tuberculosis, parasitic infections, or malaria), inflammation, chronic diseases, gynaecological and obstetric conditions, and disorders of the red blood cells that are passed down through families. Anaemia can be caused by a lack of iron, folate, vitamins B12, or A, although iron insufficiency is the most prevalent dietary cause.4

Young children, teenage girls and women who experience menstruation, and women who are pregnant or recently gave birth are at increased risk of anaemia, which is a major public health concern worldwide. According to the World Health Organization, anaemia affects 40% of children aged 6–59 months, 37% of pregnant women, and 30% of women aged 15–49 globally. The Indian National Family Health Survey NFHS-5 (2019-21) found that 25% of men aged 15–49, 67.1% of children under 5 years old, 57.2% of non-pregnant women aged 15–48, and 52.2% of pregnant women aged 15–48 had anemia. Compared to urban areas, rural areas had a higher prevalence.5

Accurate blood count findings and a probable diagnosis of anemia depend on the manual blood smear examination, RBC histogram, and red cell indices. Factors such as hemoglobin, hematocrit, mean corpuscular volume, red cell distribution width, mean corpuscular hemoglobin concentration, and mean corpuscular volume are used to classify anemia.6 An RBC histogram is a graphical representation of the values acquired by an automated haematology analyzer. Histograms of red blood cells show the frequency of cells relative to their size. The RBC histogram provides diagnostic clues for anemia by revealing distinct patterns in different types of the condition. An essential component of automated haematology analysis, the RBC histogram has enhanced precision and accuracy.7 Conditions including red cell inclusions and membrane abnormalities cannot be detected by red cell indices and RBC histograms. Peripheral smear testing can reveal the RBC population's heterogeneity, however mean value red cell indices like MCV cannot. Therefore, it is vital to do a peripheral smear examination in addition to an RBC histogram and red cell indices in order to make a correct diagnosis of anemia. In order to address the gaps in the current literature, this study set out to investigate this issue in rural Uttar Pradesh.

Two hundred patients with anemia were included in the study; non-pregnant ladies had hemoglobin levels below 12 gm/dl, while males had levels below 13 gm/dl. The current investigation spanned the months of March 2024 through March 2025 and took place in the central diagnostic laboratory of F H Medical College and Hospital, Etmadpur. Participants who were pregnant or had leukemia were not included in the study. This research was conducted using a cross-sectional observational design. The Mindray BC 5300 automated analyzer was used to get a full blood count, which includes hemoglobin, total and differential counts, a haematocrit number, RBC indices, and a histogram. At the same time, each patient had a peripheral blood smear stained with Leishman's solution, as per standard operating procedures. Using pearson's chi-square test, we compared RBC histogram and indices with peripheral smears for diagnosis.

The peripheral smear, red cell indices, and RBC histogram of two hundred anemic patients were examined.There were 158 females (or 79%) and 42 males (or 21%) in our study population. The average age of the patients was 41.28±12.35 years, and their ages varied from 3 to 74 years.

Table 1. Age & Sex Distribution

Anaemia was classified as mild (≥9gm/dl), moderate (7–9gm/dl), or severe (<7gm/dl) based on the hemoglobin value, in accordance with the World Health Organization's guidelines. Haemoglobin levels in our study ranged from 7-9gm/dl in 61.5% of cases, from 9gm/dl in 25.5%, and from 7gm/dl in 13% of individuals with severe anemia. The average hemoglobin level was 8.4±2.7 gm/dl.

Table 2. Severity of Anemia

The results showed that microcytic anemia was present in 56% of cases (MCV<83fl), normocytic anemia in 34% (MCV between 83-101fl), and macrocytic anemia in 10% (MCV>101fl). There was a statistically significant difference (p<0.001) in the diagnosis of anemia based on MCV levels and manual evaluation of peripheral smear. This occurred because dimorphic anemia was present, with some cases falling below the normal range of MCV.

The results showed that 72% of the participants had hypochromic anemia (MCH<27 pg), 23% had normochromic anemia (MCH 27-31 pg), and 5% had MCH > 32 pg. There was a statistically significant difference (p<0.001) in the diagnosis of anemia based on MCH values and manual evaluation of peripheral smear. A total of 85% of the cases demonstrated MCHC levels below 315 g/l. There was a statistically significant difference (p<0.001) in the diagnosis of anemia based on MCHC values and manual evaluation of peripheral smear.

While in dimorphic anemia 36.36% displayed a bimodal curve, 30.30% a normal curve, 18.18% a broad base curve, and 15.15% a left shifting of curve, the histogram for microcytic hypochromic anemia showed a left shift and for macrocytic anemia a right side curve.

In a study involving 120 cases of microcytic hypochromic anemia, 60% were found to have an RDW CV>14%. Among those patients, 86.67% demonstrated this finding. There was a statistically significant difference (p<0.001) in the diagnosis of anemia based on histogram and manual assessment of peripheral smear. With the exception of dimorphic anemia, which displayed a different sort of histogram curve, the histogram pattern was well-correlated with all other forms of anemia.

Table 3. Correlation of MCV and Peripheral Smear

Table 4. Correlation of Peripheral Smear and Histogram

Despite the fact that it can have devastating long-term consequences, anemia is nevertheless rather common in India, particularly among women and those living in rural regions.8 This study examined 200 individuals with anemia using peripheral blood smear examinations, histograms, and red blood cell indices. The majority of instances, out of 100, occur in adults aged 31–45. One way to look at this is as a time of rapid maturation between the ages of 10 and 19. Because of its role in the production of haemoglobin and other essential physiological processes, iron is in great demand. Findings agreed with those of the studies by Mukaya JE et al.9, Kumar A et al.10, and Cook JD et al.11 The gender breakdown of the participants in this study was as follows: 158 (or 79%) were female and 42 (or 21%) were male. The vast majority of the 158 females were in childbearing age. The fast growth and frequent blood loss during menstruation put women in the reproductive age range at a significant risk of getting anemia.

According to the World Health Organization's standards, we included all cases where the hemoglobin level was less than 12 gm/dl for females and less than 13 gm/dl for males. Haemoglobin levels averaged 8.4±2.7 gm/dl. Haemoglobin levels ranging from 7 to 9 grams per deciliter indicated significant anemia in 61.5% of the patients. The average hemoglobin level was 7.2% in the study by Patel et al. and 5.85% in the study by Kumar et al. Microcytic hypochromic anemia was the most common morphological kind of anemia (60%), while the next most common types were normocytic normochromic (16.5%), dimorphic (16.5%), and macrocytic (7%). Among the world's nations with the highest rates of anemia, India ranks top. Iron deficiency anemia and other nutritional problems, as well as infections, are the leading causes of anemia in poor nations among at-risk populations. In a study involving 200 patients, microcytic anemia was discovered in 56% of cases (MCV<83fl), normocytic anemia in 34% (MCV between 83-101fl), and macrocytic anemia in 10% (MCV>101fl). The findings are consistent with what Patel et al.12 found. Similar to the study by Patel S et al., the majority of patients in the present study (72%), have MCH<27pg.12

A high RDW was seen in the majority of instances of microcytic hypochromic anemia. Cell counters, a disregarded piece of information by hematopathologists, graphically represent different population cell types and generate histograms. There are a number of haematological conditions that manifest with abnormalities in the histogram, red blood cell indices, and peripheral blood smear. Using the results of 200 anemia patients and the RBC indices and histograms acquired from the Mindray BC5300 automated analyzer, this study compares the two. A dotted line representing a reference normal curve was drawn against each red cell histogram to help better comprehend the histogram and how it varies in different illness conditions. Diamorphic anemia (16.5%), microcytic hypochromic anemia (60%), normocytic normochromic anemia (16.5%), and macrocytic anemia (7.5%) were the types of anemia that were identified on peripheral smears in this study.

The small size of RBCs caused 68.33% of the histograms to display a left shift in smears described as microcytic hypochromic anemia. Smears with macrocytic blood samples showed a rightward shift in the histogram pattern, while those with normocytic normochromic anemia showed an 84.85% normal curve. The findings of our investigation were consistent with those of Constantino BT et al.13 For the diagnosis of normocytic normochromic anemia, microcytic hypochromic anemia, and macrocytic anemia, this comparison histogram is a helpful tool. A histogram with a basic to complex curve was seen in cases of dimorphic anemia. A bimodal curve was shown by 36.36 percent of the participants, a broad base curve by 18.18%, a left shift curve by 15.15%, and a normal curve by 30.3%. It has been noted that dimorphic anemia can be classified using various histogram patterns.Cases of dimorphic anemia were the primary cause of the statistically significant difference.

The existence of three distinct cell populations—normogytic, microcytic, and macrocytic—can account for the bimodal curve. In addition to therapeutic transfusion and hematinic agent response in microcytic and macrocytic anemia, a bimodal histogram can reveal additional hematological disorders including microcytic populations developing early iron deficiency, macrocytic populations developing folate and vitamin B12 deficiency, anemia following iron deficiency treatment, and megaloblastic anemia following iron deficiency treatment. Dimorphic anemia histograms reveal RBC variability in the center and width. Automated values alone can mislead in the diagnosis of dimorphic blood pictures, which consist of a mixed population of microcytic and normocytic or normocytic and macrocytic red cells, or a combination of microscopic, normal, or big cells of varying sizes and shapes. All patients with anemia should have a peripheral blood smear, RBC indices, and a histogram checked.14

We also used red blood cell indices (MCV, MCH, MCHC) to categorize 200 cases of anemia in this examination. In order to establish a benchmark, these results were compared to peripheral smear examination. In 56% of cases, MCV<83fl was deemed microcytic; in 34% of cases, it was deemed normocytic; and in 10% of cases, it was deemed macrocytic. A MCH count below 27 pg was regarded as microcytic, a count between 27 and 32 pg as normocytic or dimorphic, and a count over 32 pg as macrocytic. Microcytes and macrocytes have little impact on MCV because it merely represents the mean of the distribution curve. The fact that MCV is a mean value and doesn't account for variations in the red cell population is probably to blame. Consequently, a peripheral smear test is essential for the early detection of red blood cell alterations in all anemia patients.

The low MCHC value in anemic individuals indicates that their red blood cells are lacking in haemoglobin, which is why 85% of the cases in our study had this condition. Without MCV, MCH and MCHC don't tell you much. Our results confirm that RDW is a sensitive indicator of anisocytosis, since we found that high RDW is observed in the majority of microcytic hypochromic anemia cases (86.67%). As an indication of anisocytosis, RDW also shows greater correlation when MCV is in the low normal range, as it may be in the event of developing iron deficiency. Iron deficiency anemia patients' red cell histograms indicate a leftward shift before therapy, but afterward, the histograms broaden as a result of an increase in RDW. In nutritional deficiencies, there is an increase in red cell heterogeneity, leading to more aberrant cells in the peripheral blood (iron, folate, vitamin B12). Despite the importance of the white blood cell histogram, very few studies have concentrated on the red blood cell histogram.15

In order to diagnose microcytic hypochromic anemia, normocytic normochromic anemia, and macrocytic anemia, our study found a significant association between RBC histogram and peripheral smear examination. Nevertheless, there were concerns about the validity of the RBC histogram for diagnosing dimorphic anemia due to the link between the histogram pattern, red cell indices, and peripheral smear test. Our study concludes that, even in the era of automation and molecular analysis, a patient's clinical history and a peripheral smear screening are crucial diagnostic tools when dealing with anemia. Red blood cell indices and RBC histograms alone cannot identify all forms of anemia. The only way to use them is to look at the peripheral smear visually.

In order to diagnose microcytic hypochromic anemia, normocytic normochromic anemia, and macrocytic anemia, our study found a significant association between RBC histogram and peripheral smear examination. Nevertheless, there were concerns about the validity of the RBC histogram for diagnosing dimorphic anemia due to the link between the histogram pattern, red cell indices, and peripheral smear test. Our study concludes that, even in the era of automation and molecular analysis, a patient's clinical history and a peripheral smear screening are crucial diagnostic tools when dealing with anemia. Red blood cell indices and RBC histograms alone cannot identify all forms of anemia. The only way to use them is to look at the peripheral smear visually.

1. Cappellini MD, Motta I. Anemia in clinical practice—definition and classification: does hemoglobin change with aging?. InSeminars in hematology 2015 Oct 1 (Vol. 52, No. 4, pp. 261-269). WB Saunders.
2. Garcia‐Casal MN, Pasricha SR, Sharma AJ, Peña‐Rosas JP. Use and interpretation of hemoglobin concentrations for assessing anemia status in individuals and populations: results from a WHO technical meeting. Annals of the New York Academy of Sciences. 2019 Aug;1450(1):5-14.
3. Pasricha SR, Rogers L, Branca F, Garcia-Casal MN. Measuring haemoglobin concentration to define anaemia: WHO guidelines. The Lancet. 2024 May 18;403(10440):1963-6.
4. Sharourou AS, Hassan MA, Teclebrhan MB, Alsharif HM, Alhamad SA, Alsinani TS. Anemia: Its prevalence, causes, and management. The Egyptian Journal of Hospital Medicine. 2018 Jan 1;70(10):1877-9.
5. Belwal E, Pandey S, Sarkar S. Anemia prevalence in India over two decades: evidence from National Family Health Survey (NFHS). Int J Sci Healthcare Res. 2021;6(4):335-40.
6. Buttarello M. Laboratory diagnosis of anemia: are the old and new red cell parameters useful in classification and treatment, how?. International journal of laboratory hematology. 2016 May;38:123-32.
7. Sandhya I, Muhasin T. Study of RBC histogram in various anemias. Journal of Evolution of Medical and Dental sciences. 2014 Dec 29;3(74):15521-35.
8. Natekar P, Deshmukh C, Limaye D, Ramanathan V, Pawar A. A micro review of a nutritional public health challenge: iron deficiency anemia in India. Clinical Epidemiology and Global Health. 2022 Mar 1;14:100992.
9. Mukaya JE, Ddungu H, Ssali F, O'Shea T, Crowther MA. Prevalence and morphological types of anaemia and hookworm infestation in the medical emergency ward, Mulago Hospital, Uganda. South African Medical Journal. 2009 Dec 1;99(12):881-6.
10. Kumar A, Kushwaha R, Gupta C, Singh US. An analytical study on peripheral blood smears in anemia and correlation with cell counter generated red cell parameters. Journal of applied hematology. 2013 Oct 1;4(4):137-44.
11. Cook JD, Finch CA, Smith NJ. Evaluation of the IronStatus of a Population. Blood 1976; 48(3):449-455.
12. Patel S, Shah M, Patel J, Kumar N. Iron DeficiencyAnemia in Moderate to Severely Anaemia Patients. GujMed J 2009; 64(2): 15-17.
13. Constantino BT. The red cell histogram and thedimorphic red cell population. Lab Med 2011; 42:300-308.
14. Rao BS, Santhi V, Rao NM, Grandhi B, Reddy VL, Siresala P. RBC Histogram as Supplementary Diagnostic Tool with Peripheral Smear Examination in Evaluating Anaemia. Ann Pathol Lab Med. 2017 Dec 19;4:668-72.
15. Sandhya V, Rashmi GS. Correlation of peripheral smear with RBC indices and RBC histograms in the diagnosis of anemia. Indian Journal of Pathology and Oncology. 2017 Apr;4(2):242-6.