Age and Comorbidity in COVID-19 Mortality: A Single-Center Retrospective Study Using Multivariable Regression and Interaction Analysis

Abstract Background COVID-19 has caused a major mortality wave across the globe signifying that age and comorbidity are major risk factors. The elderly, as well as with multiple chronic illnesses, are at a distinct risk of severe outcomes. This study examines the relative influence of age and comorbidity burden on mortality due to COVID-19 through a retrospective observational investigation. Method A retrospective observational analysis was carried out at tertiary care hospital, Belgaum, Karnataka, India. There was a total of 642 laboratory-confirmed COVID-19 (RT-PCR or rapid antigen test). Bivariate, Multivariable logistic regression, and Interaction Analysis were used in this study. Result Overall, the study showed that age above or equal to 50 years is associated with significantly greater odds of dying (OR = 2.37, 95% CI: 1.41–3.97, p < 0.001), while patients with polymorbidity experienced high mortality (35.37%) compared those with mono-morbidity (19.66%). Kidney diseases (OR = 6.41 with 95% CI: 2.32–17.70, p < 0.001) and dyspnea (OR = 2.89, 95% CI: 1.86–4.49, p < 0.001) as key comorbidities increased risk further. Interaction analyses for these two factors showed no synergistic effect (p = 0.563), indicating that the risks are additive rather than multiplicative. Significantly increased blood glucose and pulse rate levels are also predictors of mortality. Conclusion All these disorders highlight the role of age, comorbidity burden, and some clinical markers in risk stratification for COVID-19 patients, pointing to the necessity for a management strategy for high-risk subgroups.