Rationale: Normal values for FEV₁ and FVC are currently calculated using cross-sectional reference equations that include terms for race/ethnicity, an approach that may reinforce disparities and is of unclear clinical benefit. Objectives: To determine whether race/ethnicity–based spirometry reference equations improve the prediction of incident chronic lower respiratory disease (CLRD) events and mortality compared with race/ethnicity–neutral equations. Methods: The MESA Lung Study, a population-based, prospective cohort study of White, Black, Hispanic, and Asian adults, performed standardized spirometry from 2004 to 2006. Predicted values for spirometry were calculated using race/ethnicity–based equations following guidelines and, alternatively, race/ethnicity–neutral equations without terms for race/ethnicity. Participants were followed for events through 2019. Measurements and Main Results: The mean age of 3,344 participants was 65 years, and self-reported race/ethnicity was 36% White, 25% Black, 23% Hispanic, and 17% Asian. There were 181 incident CLRD-related events and 547 deaths over a median of 11.6 years. There was no evidence that percentage predicted FEV₁ or FVC calculated using race/ethnicity–based equations improved the prediction of CLRD-related events compared with those calculated using race/ethnicity–neutral equations (difference in C statistics for FEV₁, −0.005; 95% confidence interval [CI], −0.013 to 0.003; difference in C statistic for FVC, −0.008; 95% CI, −0.016 to −0.0006). Findings were similar for mortality (difference in C statistics for FEV₁, −0.002; 95% CI, −0.008 to 0.003; difference in C statistics for FVC, −0.004; 95% CI, −0.009 to 0.001). Conclusions: There was no evidence that race/ethnicity–based spirometry reference equations improved the prediction of clinical events compared with race/ethnicity–neutral equations. The inclusion of race/ethnicity in spirometry reference equations should be reconsidered.

Rationale: African American individuals have worse outcomes in chronic obstructive pulmonary disease (COPD). Objectives: To assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognize pathological decrements and considering them normal. Methods: In a cohort with and at risk for COPD, we assessed whether lung function prediction equations applied in a race-specific versus universal manner better modeled the relationship between FEV₁, FVC, and other COPD outcomes, including the COPD Assessment Test, St. George’s Respiratory Questionnaire, computed tomography percent emphysema, airway wall thickness, and 6-minute-walk test. We related these outcomes to differences in FEV₁ using multiple linear regression and compared predictive performance between fitted models using root mean squared error and Alpaydin’s paired F test. Measurements and Main Results: Using race-specific equations, African American individuals were calculated to have better lung function than non-Hispanic White individuals (FEV₁, 76.8% vs. 71.8% predicted; P = 0.02). Using universally applied equations, African American individuals were calculated to have worse lung function. Using Hankinson’s Non-Hispanic White equation, FEV₁ was 64.7% versus 71.8% (P < 0.001). Using the Global Lung Initiative’s Other race equation, FEV₁ was 70.0% versus 77.9% (P < 0.001). Prediction errors from linear regression were less for universally applied equations compared with race-specific equations when examining FEV₁% predicted with the COPD Assessment Test (P < 0.01), St. George’s Respiratory Questionnaire (P < 0.01), and airway wall thickness (P < 0.01). Although African American participants had greater adversity (P < 0.001), less adversity was only associated with better FEV₁ in non-Hispanic White participants (P for interaction = 0.041). Conclusions: Race-specific equations may underestimate COPD severity in African American individuals.Clinical trial registered with www.clinicaltrials.gov (NCT01969344).

Sleep is an important dimension in the care of chronic obstructive pulmonary disease (COPD), but its relevance to exacerbations is unclear. We wanted to assess whether sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) is associated with an increased risk of COPD exacerbations and does this differ by socio-environmental exposures. We included 1647 current and former smokers with spirometrically confirmed COPD from the SPIROMICS cohort. We assessed incidence rate ratios for exacerbation using zero-inflated negative binomial regression adjusting for demographics, medical comorbidities, and multiple metrics of disease severity, including respiratory medications, airflow obstruction, and symptom burden. Our final model adjusted for socio-environmental exposures using the Area Deprivation Index, a composite measure of contemporary neighborhood quality, and Adversity–Opportunity Index, a composite measure of individual-level historic and current socioeconomic indicators. We used a pre-determined threshold of 20% missingness to undertake multiple imputation by chained equations. As sensitivity analyses, we repeated models in those with complete data and after controlling for prior exacerbations. As an exploratory analysis, we considered an interaction between socio-environmental condition and sleep quality. After adjustment for all co-variates, increasing PSQI scores (range 0–21) were associated with a 5% increased risk for exacerbation per point (p = .001) in the imputed dataset. Sensitivity analyses using complete cases and after controlling for prior exacerbation history were similar. Exploratory analysis suggested less effect among those who lived in poor-quality neighborhoods (p-for-interaction = .035). Poor sleep quality may contribute to future exacerbations among patients with COPD. This represents one target for improving disease control. Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS). ClinicalTrials.gov Identifier# NCT01969344. Registry URL: https://clinicaltrials.gov/ct2/show/.

Rationale: United States veterans represent an important population to study sarcoidosis. Their unique history of environmental exposures, wide geographic distribution, and long-term enrollment in a single integrated healthcare system provides an unparalleled opportunity to understand the incidence, prevalence, and risk factors for sarcoidosis. Objectives: To determine the epidemiology, patient characteristics, geographic distribution, and associated risk factors of sarcoidosis among U.S. veterans. Methods: We used data from the Veterans Health Administration (VHA) electronic health record system between 2003 and 2019 to evaluate the annual incidence, prevalence, and geographic distribution of sarcoidosis (defined using the International Classification of Diseases codes). We used multivariate logistic regression to examine patient characteristics associated with sarcoidosis incidence. Results: Among more than 13 million veterans who received care through or paid for by the VHA, 23,747 (0.20%) incident diagnoses of sarcoidosis were identified. Compared with selected VHA control subjects using propensity score matching, veterans with sarcoidosis were more likely to be female (13.5% vs. 9.0%), of Black race (52.2% vs. 17.0%), and ever–tobacco users (74.2% vs. 64.5%). There was an increase in the annual incidence of sarcoidosis between 2004 and 2019 (from 38 to 52 cases/100,000 person-years) and the annual prevalence between 2003 and 2019 (from 79 to 141 cases/100,000 persons). In a multivariate logistic regression model, Black race (odds ratio [OR], 4.49; 95% confidence interval [CI], 4.33–4.65), female sex (OR, 1.64; 95% CI, 1.56–1.73), living in the Northeast compared with the western region (OR, 1.57; 95% CI, 1.48–1.67), history of tobacco use (OR, 1.36; 95% CI, 1.31–1.41), and serving in the Army, Air Force, or multiple branches compared with the Navy (OR, 1.08; 95% CI, 1.03–1.13; OR, 1.10; 95% CI, 1.04–1.17; OR, 1.27; 95% CI, 1.16–1.39, respectively) were significantly associated with incident sarcoidosis (P < 0.0001). Conclusions: The incidence and prevalence of sarcoidosis are higher among veterans than in the general population. Alongside traditionally recognized risk factors such as Black race and female sex, we found that a history of tobacco use within the Veterans Affairs population and serving in the Army, Air Force, or multiple service branches were associated with increased sarcoidosis risk.