Association of Sociodemographic and Clinicopathological Characteristics with Severity of COVID-19 Disease: A Cross-Sectional Study

Background: COVID-19 exhibits variable clinical severity influenced by host-related factors, including sociodemographic characteristics and metabolic status. Identifying these determinants is essential for early risk stratification and improved patient management.

Objective: To evaluate the association of sociodemographic and clinicopathological characteristics, particularly insulin and glucose levels, with the severity of COVID-19 disease.

Methods: This hospital-based cross-sectional observational study included 122 RT-PCR confirmed COVID-19 patients admitted to Government Medical College Srinagar associated Chest Disease Hospital. Sociodemographic data, clinical characteristics, and biochemical parameters were collected. Fasting blood glucose was measured by the GOD-POD method, and insulin levels were estimated using chemiluminescent microparticle immunoassay (CMIA). Statistical analysis was performed using SPSS version 25. Associations were assessed using the chi-square test, with p<0.05 considered statistically significant.

Results: Among the 122 patients, 55.7% had severe disease. Age ≥50 years was significantly associated with severity (p<0.001; OR=7.6). Rural residence (p=0.003), unknown source of infection (p=0.007), and absence of travel history (p=0.021) were also significantly associated with increased severity. A significant association was observed between insulin levels and disease severity (p=0.004), with the highest severity seen in patients with low insulin levels (78.5%). However, gender (p=0.097), comorbidities (p=0.204), glucose levels (p=0.445), and HOMA-IR (p=0.691) were not significantly associated with severity.

Conclusion: Advanced age, sociodemographic factors, and altered insulin levels are significantly associated with increased severity of COVID-19. These findings highlight the importance of early identification of high-risk patients and emphasize the role of metabolic assessment in clinical management.