Anemia remains a major global public health concern, affecting over 1.6 billion individuals and contributing significantly to morbidity, mortality, and reduced quality of life.¹ South Asia, particularly India, bears one of the heaviest burdens, where nutritional deficiencies, infections, and socioeconomic disparities exacerbate the condition.¹ In India, the National Family Health Survey-5 (NFHS-5, 2019–21) reported a national prevalence of anemia at 57% among women and 25% among men aged 15–49 years.² Chhattisgarh, a centrally located state with a substantial tribal population and rural economy, exhibits even higher rates: approximately 61% among women aged 15–49 years (a sharp rise from 47% in NFHS-4) and 27% among men in the comparable age group.² These figures highlight Chhattisgarh as one of the states with persistently elevated anemia prevalence, driven by factors such as limited access to fortified foods, high reliance on cereal-based diets low in bioavailable iron, repeated pregnancies, parasitic infections, and socioeconomic challenges.³,⁴ Tertiary care centers in Chhattisgarh, such as those affiliated with government medical colleges, serve as referral hubs for complex cases from urban, rural, and tribal areas. Patients often present with advanced or multifactorial anemia compounded by comorbidities like chronic diseases, malnutrition, hemoglobinopathies (prevalent in tribal communities), and poor dietary intake.⁵,⁶ While community-based surveys like NFHS provide valuable population-level insights, they may underestimate the burden in hospital settings due to referral bias and selection of sicker individuals. Hospital-based studies offer a unique opportunity to examine anemia in a clinical context, where nutritional status—assessed through anthropometric measures (e.g., BMI, MUAC) and dietary patterns—can be directly correlated with hemoglobin levels and anemia severity. Despite the high community prevalence in Chhattisgarh, hospital-based research specifically linking anemia to nutritional indicators among adult patients remains scarce. Existing studies predominantly focus on antenatal women, children, or adolescents, with limited data on broader adult populations attending tertiary facilities.⁷,⁸ This gap hinders the development of targeted inpatient/outpatient interventions aligned with national programs like Anemia Mukt Bharat. The present study addresses this limitation by investigating the prevalence of anemia and its correlation with nutritional status among adult patients at a prominent tertiary care center in Raipur, Chhattisgarh. By integrating standardized hemoglobin estimation, anthropometric assessments, and dietary recall, the research aims to provide evidence for integrating nutritional screening into routine tertiary care protocols in resource-constrained, high-burden settings.

Study design and setting : Cross-sectional observational study Medical college, Raipur, a major 700+ bed tertiary facility serving urban, rural, and tribal populations across Chhattisgarh. Study population: Adults ≥18 years attending Medicine OPD/IPD from January–December 2024. Exclusions: Known hematological disorders, recent transfusion (<3 months), pregnancy, or non-consent. Sample size: 384 (50% prevalence, 95% CI, 5% margin); 500 recruited consecutively. Data collection: • Socio-demographic details (age, sex, SES via modified Kuppuswamy). • Hemoglobin (Sysmex analyzer, cyanmethemoglobin; anemia: Hb <13 g/dL men, <12 g/dL women). Severity: mild (10–12.9/11–11.9), moderate (7–9.9), severe (<7). • Nutritional parameters: BMI (kg/m²), MUAC (<23 cm men/<22 cm women = undernourished), 24-hour recall for iron/protein/folate (vs. ICMR RDA). • Peripheral smear review. Statistical analysis: Descriptive stats, chi-square, Pearson/Spearman correlations, multivariate logistic regression. p<0.05 significant. Funding: None Conflict of interest: None declared.

Socio-demographic profile (n=500) provides a concise summary of key characteristics of the 500 adult patients enrolled in the study conducted at a tertiary care center in Raipur, Chhattisgarh. The study population had a mean age of 42.1 years (standard deviation ±13.8 years), indicating a predominantly middle-aged group with reasonable variability. Females constituted 54% (n=270) of the participants, slightly outnumbering males (46%, n=230). A high proportion—68%—resided in rural or tribal areas, reflecting the catchment population of the hospital, which serves both urban Raipur and surrounding remote/tribal regions of Chhattisgarh. Additionally, 55% belonged to low socioeconomic status (SES), as classified by the modified Kuppuswamy scale, highlighting the socioeconomic vulnerability prevalent among attendees. Overall, anemia was detected in 52.4% of participants (262 out of 500). The prevalence was markedly higher among females at 63.1% (170/270) compared to males at 40.8% (92/230), with the difference being statistically highly significant (p<0.001). This gender disparity aligns with national and regional patterns, where women experience greater risk due to menstrual blood loss, higher parity, and often poorer nutritional access in resource-constrained settings like Chhattisgarh. These baseline characteristics underscore the influence of gender, rural/tribal residence, and low SES as potential contributors to the elevated anemia burden observed in this hospital-based cohort. Table 1: Socio-demographic profile (n=500). • Age (mean ± SD): 42.1 ± 13.8 years • Female: 54% (n=270) • Rural/tribal residence: 68% • Low SES: 55% Severity and type of anemia presents the distribution of anemia severity and morphological type among the 262 anemic patients (out of 500 total). Mild anemia was the most common, affecting 148 patients (29.6% of total sample), followed by moderate anemia in 88 patients (17.6%). Severe anemia was least frequent, seen in 26 patients (5.2%). Among the anemic cases, 72% exhibited microcytic hypochromic morphology on peripheral smear, indicating iron deficiency as the predominant etiology. This pattern aligns with nutritional anemia patterns prevalent in Chhattisgarh, where inadequate dietary iron intake and absorption issues are common contributors. Table 2: Severity and type of anemia. • Mild: 148 (29.6%) • Moderate: 88 (17.6%) • Severe: 26 (5.2%) • Microcytic hypochromic (iron deficiency predominant): 72% of anemic Correlation with nutritional status highlights the strong link between anemia and poor nutritional indicators among the 500 study participants. Anemia prevalence was highest (74.2%) in underweight patients (BMI <18.5 kg/m²), dropping to 35.6% in those with normal BMI (18.5–24.9) and further to 22.1% in overweight/obese individuals (χ² = 82.7, p < 0.001), showing a clear inverse relationship between body mass and anemia risk. Hemoglobin levels positively correlated with BMI (Pearson r = +0.38, p < 0.001), confirming that better nutritional status (higher BMI) is associated with higher hemoglobin. Low mid-upper arm circumference (MUAC), another marker of undernutrition, was linked to 70% anemia prevalence compared to 34% in those with normal MUAC (odds ratio 4.6). Inadequate daily dietary iron intake (<10 mg/day) was reported by 78% of anemic patients versus only 35% of non-anemic (p < 0.001), underscoring iron deficiency as a major contributor. Multivariate logistic regression identified independent predictors of anemia: female sex (adjusted OR 3.1), low socioeconomic status (AOR 3.4), underweight status (AOR 6.1), and vegetarian/tribal dietary patterns (AOR 2.7) (Table 3). These findings demonstrate that undernutrition—particularly low BMI, low MUAC, and poor iron intake—strongly drives anemia in this Chhattisgarh tertiary care setting. Table 3: Correlation with nutritional status • Underweight (BMI <18.5): 74.2% anemic • Normal (18.5–24.9): 35.6% anemic • Overweight/obese: 22.1% anemic (χ²=82.7, p<0.001) • Mean Hb vs. BMI: r = +0.38, p<0.001 • Low MUAC: 70% anemia vs. 34% normal MUAC (OR 4.6) • Inadequate dietary iron (<10 mg/day): 78% anemic vs. 35% non-anemic (p<0.001) Multivariate analysis: Key predictors – female sex (AOR 3.1), low SES (AOR 3.4), underweight (AOR 6.1), vegetarian/tribal diet (AOR 2.7)

The 52.4% prevalence exceeds national averages and aligns with Chhattisgarh's high community burden (NFHS-5: ~61% women), amplified in tertiary settings by referral bias.⁶⁻⁸ Female predominance reflects menstrual/reproductive factors prevalent in the state.⁹ Hb-BMI correlation (r=0.38) and elevated anemia in underweight echo regional patterns in tribal and low-resource areas.¹⁰ Nutritional etiology prevailed (72% microcytic), consistent with iron deficiency in Chhattisgarh.¹¹,¹² LIMITATIONS Single-site, absence of full iron studies (resource constraints), cross-sectional design. Strengths: Adequate sample, standardized methods, multi-faceted nutrition assessment. Compared to earlier central India data, hospital rates here are higher, underscoring need for intensified efforts under Anemia Mukt Bharat in Chhattisgarh.¹³,¹⁴

Anemia affects over half of adult patients at this tertiary center, closely tied to undernutrition. Incorporate BMI/dietary screening and iron interventions in routine care. Multicenter studies with biomarkers recommended. Acknowledgments Funding: No external funding. Conflicts of interest: None declared. Data availability: From corresponding author on request

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