ABSTRACT This F32 fellowship award will provide Dr. Aaron Baugh with the support necessary to accomplish the following goals: (1) to become an expert in population-oriented clinical research in chronic obstructive pulmonary disease (COPD) (2) to gain advanced skills in epidemiology, biostatistics, and data science methods to conduct clinical research (3) to further the study of health disparities in pulmonary disease and (4) to advance scientific understanding of COPD by establishing the optimal means of reporting objective metrics of pulmonary function across different racial groups. To accomplish these goals, Dr. Baugh will conduct investigations comparing the predictive power of FEV1 on important COPD outcomes as calculated by different methodologies across several national cohorts of patients with COPD. There are large, unexplained differences in pulmonary function by race. Genetic, anthropometric, and socio- cultural explanations have all been hypothesized but incompletely investigated. At the same time, large disparities exist in COPD outcomes, where for the same level of percent predicted lung function and co-morbidity, African Americans have higher symptom burdens and more exacerbations. The current practice is to report pulmonary function as the percent of a value predicted by equations derived from large, race-specific cohorts. However, both COPD and race are highly correlated with socioeconomic disparities within the United States. It is therefore unclear whether current reporting standards highlight essential differences in population groups or obscure socioeconomic ones. The fundamental aim of the NRSA proposal is to leverage data from large national cohorts of COPD patients to determine whether use of a race-specific prediction equation inappropriately adjusts for clinically important lung injury such that it has poorer correlation to symptom burden, radiographic disease, and exacerbations than alternative models. Solving this problem will both help define the normal biologic function of the lung by identifying the most reliable reference equations and help characterize the underlying cause of differences in lung function between different races. Using data from SPIROMICS, MESA Lung, CAPTURE, FLOW, SUMMIT, IMPACT, STATCOPE, MACRO, BLOCK COPD, and PuSHCon, we will consider scores on the St George's Respiratory Questionnaire, COPD Assessment Test, as well as quantitative airway thickness and percent emphysema, two radiographic markers of disease. For each selected outcome we will assess whether the race-specific equation for FEV1 or an alternative equation that does not include race better predicted the actual outcome. Finally, we will perform exploratory analysis of the extent to which the observed association between race and lung function is mediated by socio-economic status.