Anemia of chronic disease (ACD), also known as anemia of inflammation, represents the second most prevalent cause of anemia after iron deficiency anemia (IDA)[1]. While both conditions can lead to hemoglobin reduction, they differ significantly in pathophysiology, laboratory parameters, and treatment approaches [2]. ACD occurs in patients with chronic inflammatory, infectious, or malignant conditions that elicit an active immune response, leading to altered iron metabolism despite normal iron stores [3].

The prevalence of ACD increases significantly with age, affecting up to 77% of elderly individuals in whom no clear cause of anemia has been established1. Research indicates that ACD accounts for approximately 30.7% of all anemia cases, with prevalence four times higher in individuals aged 80 years and above (56.5%) compared to those between 18-39 years (13.9%)4. Common underlying conditions associated with ACD include diabetes mellitus (44%), hypertension (39%), chronic kidney disease (25%), and various inflammatory disorders [4].

Laboratory differentiation between IDA and ACD presents significant clinical challenges but remains crucial for appropriate management [5]. Typically, ACD manifests with normal red blood cell indices (MCV 80-100 fL, MCHC 32-36 g/dL) and reduced total iron binding capacity (TIBC), while IDA presents with reduced indices except for elevated RDW[6]. Serum ferritin levels are often reduced in IDA but normal to increased in ACD[7]. Recent studies suggest serum hepcidin levels represent a significant distinguishing marker between these conditions [6].

The hemoglobin concentration in ACD typically ranges between 8-9.5 g/dL (mild to moderate anemia) and rarely drops below 6 g/dL1. Most patients with ACD (66%) present with mild anemia, while only 16-17% develop severe anemia with hemoglobin levels below 10 g/dL4[8]. In contrast, severe anemia is more commonly observed in IDA patients[7].

This study aims to investigate the prevalence and distinguishing characteristics of IDA and ACD in patients with hemoglobin levels below 10 g/dL. By delineating the clinical and laboratory profiles of these conditions in this specific population, we seek to facilitate a deeper understanding of their pathophysiology and improve differential diagnosis, ultimately enhancing management strategies for severe anemia associated with chronic diseases.

Study Design

This was a cross-sectional study conducted to investigate the prevalence and distinguishing characteristics of Iron Deficiency Anemia (IDA) and Anemia of Chronic Disease (ACD), with the aim of delineating their clinical and laboratory profiles for better understanding of their pathophysiology and aiding in differential diagnosis.

Study Setting and Duration

The study was carried out at the Department of Pathology, R.D. Gardi Medical College, Ujjain, Madhya Pradesh, India. Sample collection was also performed at Civil Hospital, Mandsaur, M.P. The study was conducted over a period of two months.

Study Population

The study involved 100 patients admitted with a medical condition, presenting with hemoglobin (Hb) levels less than 10 g/dL. Patients who provided informed consent were included.

Inclusion Criteria

• Patients admitted with a medical condition or diagnosis.
• Patients with hemoglobin concentration less than 10 g/dL.
• Patients who provided informed written consent.

Exclusion Criteria

• Patients who did not provide consent.

Sampling Technique

Simple random sampling was employed to select the study participants.

Data Collection Procedure

Data was collected through personal interviews using a pretested questionnaire. A detailed history was obtained, and clinical examinations were performed on each patient. Comprehensive laboratory investigations were conducted, including:

• Serum Ferritin
• Liver function tests: SGOT (AST) and SGPT (ALT)
• Renal function tests: Urea and Creatinine
• C-Reactive Protein (CRP)
• Rheumatoid Arthritis (RA) Factor
• Thyroid Stimulating Hormone (TSH) levels (for suspected hypothyroidism)

These parameters were chosen to explore the underlying causes and assist in the differential diagnosis between IDA and ACD.

Data Analysis

Data was compiled and analyzed using Microsoft Excel (Microsoft Corporation, Redmond, WA, USA). Descriptive statistics, primarily percentages, were used to summarize the findings.

Ethical Considerations

The study was conducted following ethical standards. Written informed consent was obtained from all participants before their enrollment in the study.

Table 1: Age-wise Distribution of Patients

This table presents the distribution of study participants based on age groups. The majority of the patients (87%) were within the 30–45 years age range, indicating a higher prevalence of anemia in this working-age population. Only 13% of the patients fell outside this age bracket. This age distribution may reflect higher exposure to risk factors or comorbid conditions contributing to anemia in this age group.

Table 2: Gender-wise Distribution of Patients

This table shows the gender distribution among the study population. Females accounted for a significant majority (80%), while males comprised only 20%. The female-to-male ratio was 4:1, indicating a notable gender disparity. This trend may be due to factors such as menstrual blood loss, nutritional deficiencies, or chronic illnesses more prevalent in females.

Table 3: Prevalence of Types of Anemia

This table outlines the distribution of anemia types among the patients. Anemia of Chronic Disease (ACD) was more prevalent, affecting 58% of the participants, compared to Iron Deficiency Anemia (IDA), which accounted for 42%. This finding suggests that chronic underlying conditions play a major role in the development of anemia in this population.

Table 4: Types of Anemia of Chronic Disease (ACD)

This table breaks down the types of ACD observed in the study. The most common cause was chronic infection (40%), followed by cancer (28%) and autoimmune diseases (10%). Chronic kidney disease (7%) and other chronic conditions (15%) were also contributing factors. These results highlight the diverse etiologies of ACD and emphasize the importance of comprehensive diagnostic evaluation.

The study reports that 87% of anemic patients were aged 30–45 years, highlighting anemia’s burden in the working-age population. This contrasts with other Indian studies, which show varying age-specific trends. For instance, Ratre et al. (2019) in central India found the highest anemia prevalence (40%) in the 21–30 age group[9]. Similarly, a tertiary care study in North India observed that anemia of chronic disease (ACD) prevalence increased with age, peaking at 56.5% in individuals aged ≥80 years[10]. These discrepancies suggest regional or cohort-specific differences, potentially linked to variations in occupational stress, dietary habits, or access to healthcare. The National Family Health Survey-5 (NFHS-5) further highlights that anemia rates are elevated in children (67.1%) and women (57%), emphasizing age and gender as critical determinants [11].

The study reports a female-to-male ratio of 4:1, with 80% of anemic patients being women. This aligns with broader Indian trends but exceeds figures from some regional studies. For example, a Telangana-based study found 44.04% anemia prevalence in women versus 5.72% in men[12], while NFHS-5 notes 57% of women aged 15–49 are anemic compared to 25% of men[11]. Gender norms exacerbating anemia in women-such as intra-household food allocation biases, limited healthcare access, and menstrual blood loss-are well-documented in rural Odisha[13]. However, the higher female prevalence in this study (80%) may reflect sampling bias or intensified socioeconomic vulnerabilities in the cohort, such as lower education or income levels.

The study identifies ACD (58%) as more prevalent than IDA (42%), diverging from national patterns where IDA dominates. For instance, a North Indian hospital study reported IDA as the leading cause (42.2%) versus ACD (30.7%)[10]. Similarly, Weiss & Goodnough (2005) note that ACD is globally the second-most common anemia after IDA[14]. The high ACD prevalence in this study may reflect regional burdens of chronic infections (40%) and comorbidities like diabetes (44%)[10], underscoring the role of inflammation-driven anemia. Conversely, NFHS-5 attributes most anemia to iron deficiency, particularly in women and children[11], suggesting that the study’s cohort may represent a population with higher chronic disease prevalence.

Chronic infections (40%) and cancer (28%) were the primary ACD drivers in the study, contrasting with national data where chronic kidney disease (25%) and diabetes (44%) are prominent[10]. This discrepancy may reflect regional disease burdens, such as higher infectious disease rates in rural areas. Singh et al. (2024) emphasize multifactorial anemia etiology in India, with vitamin B12/folate deficiency contributing significantly in older adults[15]. The study’s focus on infections aligns with findings from Odisha, where gender norms limit women’s healthcare access, perpetuating untreated chronic condition[13].

The study’s findings highlight regional variations in anemia epidemiology, emphasizing the need for context-specific interventions. While IDA remains a national priority, the high ACD prevalence in this cohort underscores the growing burden of chronic diseases in India. Gender-sensitive programs and improved diagnostic protocols for distinguishing anemia types are critical for reducing disparities.

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