Investigating the Determinants of COVID-19 Outcomes in West Bengal Through Sociodemographic, Behavioral and Clinical Predictors of Survival and Mortality

Abstract

This study investigates the sociodemographic, clinical, and lifestyle factors associated with disease outcomes in a cohort of 455 patients, with a focus on distinguishing between survival and mortality. Using a retrospective design, data were collected on demographic characteristics, lifestyle behaviors, comorbidities, clinical parameters, and laboratory findingsThe researchers used descriptive statistics together with chi-square tests and Cox proportional hazards models to process data and detect adverse outcome risk factors.

Old age (P < 0.001), obesity (HR = 5.833, P = 0.006), hypertension (HR = 3.245, P = 0.005), elevated inflammatory markers D-dimer (HR = 5.073, P = 0.001) and IL-6 (HR = 4.938, P < 0.001) significantly contributed to higher mortality rates among patients. A creatinine level above 1 mg/dL proved to be the most important risk factor for negative health outcomes (HR = 10.159, P < 0.001). Patients with higher BMI presented a decreased risk for mortality according to statistical data (HR = 0.805, P = 0.032).

The disease's ultimate outcomes heavily depended on sociodemographic characteristics of patients. Individuals who were married along with those with lower education achievements and lower incomes demonstrated higher death rates among the sample (P = 0.002, P < 0.001, and P = 0.011). The combination of unhealthy habits including alcohol drinking and non-wearing of masks elevated the mortality risk (P = 0.001 and P = 0.021 respectively) yet proper hand hygiene habits demonstrated an interconnected relationship between positive practices and survival (P = 0.025).

The presence of cough symptoms related to COVID-19 along with shortness of breath and nasopharyngeal sensory impairment proved fatal for infected individuals (P < 0.001). Patient outcomes were highly correlated with lower RT-qPCR Ct values and positive initial chest X-ray infection results (P = 0.004 and P < 0.001 respectively). The research demonstrates the necessity of early risk assessment and surveillance methods for determining high-risk populations that include older adults alongside obese and sick patients with elevated markers of inflammation. The study reveals why public health needs specific interventions which include support for healthy lifestyle habits together with healthcare system improvements for low-income communities and early biomarker tracking in clinical settings. Further investigation should involve prospective research designs for validating discovered correlations while investigating extra risk indicators linked to severe disease progression and mortality outcomes.