Understanding the Influence of Social Determinants of Health on Pulmonary Function in COVID-19 Recovery

Introduction: Pulmonary function tests are interpreted using population-specific normative values that may not adequately reflect individual patient contexts. Following SARS-CoV-2 infection, respiratory symptoms persist in many patients. The relationship between social determinants of health, built environments, and pulmonary physiology remains poorly understood. This study examines how social/environmental factors influence lung function trajectories and symptom development in the post-acute sequelae of SARS-CoV-2 infection.

Objective: To develop predictive models integrating social and environmental determinants of lung health with pulmonary function parameters to predict cardiopulmonary symptoms and exercise capacity following SARS-CoV-2 infection.

Methods: This secondary analysis of the RECOVER Adult cohort (n=14,480) examines relationships between social determinants of health, built environments, and longitudinal pulmonary function outcomes. Primary measures include forced expiratory volume (FEV₁), forced vital capacity (FVC), and diffusing capacity for carbon monoxide (DLCO), analyzed using multiple reference equations. Social determinants are assessed through validated survey instruments measuring economic stability, educational attainment, healthcare access, and neighborhood characteristics. Built environment factors are evaluated using the HOUSES socioeconomic index. Primary outcomes include self-reported dyspnea, fatigue, post-exertional malaise, six-minute walk distance, and maximum oxygen consumption. Machine learning methodologies including penalized regression, gradient boosting, and random forest algorithms will develop predictive models. Cross-validation techniques ensure model performance. The Mayo Clinic validation cohort (n≈10,000) with complementary pulmonary function and socioeconomic data will validate developed models. Time-to-event analyses will assess symptom development patterns.

Results: Pending.

Conclusion/Discussion: This research will enhance understanding of how social and environmental factors affect pulmonary recovery following SARS-CoV-2 infection. Validated predictive models integrating social determinants with physiologic measurements will improve clinical assessment and patient care. Findings may inform more personalized approaches to respiratory evaluation and guide treatment decisions for patients with persistent post-viral symptoms.

Key Topics:

• Intersectionality of social determinants of health, built environments and/or pre-existing conditions and the risk for development or severity of Long COVID