# Chronic obstructive pulmonary disease among former United States Department of Energy workers: comorbidities and lung function changes

## TL;DR

This study examines COPD comorbidities and lung function changes in former U.S. Department of Energy workers, identifying distinct comorbidity clusters and key predictors of lung function decline.

## Contribution

The study identifies COPD comorbidity clusters and unique predictors of lung function decline in an occupational cohort, differing from general population findings.

## Key findings

- Four COPD comorbidity clusters were identified, including clusters with cardiovascular diseases and lung cancer.
- Age at hire, welding fume exposure, and silica exposure were significant predictors of FEV1 changes and decline.
- Smoking was a weak predictor of lung function decline in this occupational cohort.

## Abstract

Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in the United States and is frequently associated with multiple comorbidities which lead to poor COPD outcomes in the general population. However, little is known regarding COPD comorbidities in occupational cohorts whose exposure experiences could result in differences in comorbidities compared to the general population. These differences may also be important for assessing COPD outcomes such as lung function changes or decline. Therefore, the objectives of this study were to: (1) identify and describe clusters of COPD comorbidities among Department of Energy (DOE) former workers; (2) assess if the attributes of the identified clusters differ from those identified among the general population based on the published literature, and (3) identify predictors of lung function changes and decline among DOE former workers.

Clinical, occupational, and sociodemographic data were obtained from the National Supplemental Screening Program. Imputation for missing values was performed using multiple imputation by chained equation. Comorbidity clusters were identified using hierarchical clustering. Regression and classification random forest models were used to identify predictors of changes in forced expiratory volume in one second (FEV1) and FEV1 decline. Variable importance scores were used to assess the predictive importance of the predictors.

A total of 17,448 DOE former workers were included in this study, 20.9% of whom had COPD at their initial exam. Four comorbidity clusters were identified among those with COPD. Cluster 1 was composed of individuals with low prevalence of comorbidities, cluster 2 contained individuals with high prevalence of cardiovascular diseases, cluster 3 had those with high lung cancer prevalence, while cluster 4 had individuals with high prevalence of multiple comorbidities. There was no significant association between the clusters and either FEV1 change or decline. Age at hire, welding fume exposure, and silica exposure were significant predictors of both FEV1 changes and decline. Age at initial exam and baseline FEV1, which have been identified as significant predictors of these outcomes in the general population, were also significantly associated with the outcomes in the current study. By contrast, smoking, which is a common risk factor in the general population, was a weak predictor of FEV1 change and decline in this cohort.

Clusters of COPD related comorbidities were identified. The most important predictors of lung function changes and decline were FEV1, age, age at hire, and sex. The findings suggest that the important predictors of lung function changes and decline in this occupational cohort are different from those reported in the general population. Study findings may be useful for guiding enhanced monitoring efforts and control programs.