Hematological and Socioeconomic Determinants of Tuberculosis Diagnosis: A Cross-Sectional Analysis in Tertiary Care Hospital in Northern India

Abstract

Background:Poverty significantly amplifies the risk of Tuberculosis (TB) due to undernutrition and cramped, poorly ventilated living conditions. More than 90% of TB cases occur in people with weaker socioeconomic statuses. In low-income communities, undernutrition increases the risk of active TB. Lack of awareness among these populations exacerbates their susceptibility to various risk factors such as smoking, alcoholism, and HIV infections. Hematological indicators of systemic inflammation can aid in the early detection of Tuberculosis in environments with limited resources.

Objectives: This study aims to investigate the correlation between socioeconomic status (SES)and Tuberculosis positivity and evaluate the clinical relevance of hematological parameters as potential predictors of TB.

Methodology: A cross-sectional study was carried out with 282 individuals to evaluate the variables affecting the results of TB diagnosis. Patient information sheets were used to gather demographic, socioeconomic, and clinical data after getting consent from individual patients. GeneXpert and culture tests were used to confirm the TB diagnosis. Treatment failure predictors were found using logistic regression, and p-values and odds ratios (OR) were shown. Chi-square and Mann-Whitney U tests were used to evaluate correlations between TB status and important factors. ROC analysis was utilized to assess diagnostic accuracy, and Spearman correlation was employed to investigate the connections among biomarkers.

RESULTS: Among the 282 individuals, 190 (67.6%) were male. While 61.4% were culture-positive, 87.6% had TB identified by GeneXpert. Most patients were from the higher lower (26.9%) and lower medium (39.3%) socioeconomic groups. Gender (p = 0.006) and isoniazid resistance (p < 0.01) were substantially associated with TB. Hemoglobin (p < 0.05), WBC count, NLR, and ESR were key predictors. ESR (AUC = 0.776) exhibited the highest diagnostic accuracy, followed by hemoglobin, WBC count, and NLR. A mild negative correlation (r = -0.191) between NLR and hemoglobin and a significant positive correlation (r = 0.278) between ESR and NLR in TB patients were observed.

CONCLUSION: The findings highlight the dual impact of SES and inflammation markers on TB risk, emphasizing the need to incorporate these factors into routine screening and early detection strategies. Public health policies should address socioeconomic barriers while integrating hematological assessments as supplementary diagnostic tools to improve TB management, particularly in resource-constrained settings.