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February 5, 2026PeerJ1 citationsOpen Access

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

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SHSara C. HowardLRLouis RocconiAOAgricola Odoi

Key Points

  • The study aims to identify comorbidity clusters among DOE workers with COPD and assess their impact on lung function changes.
  • Clinical and demographic data were collected from the National Supplemental Screening Program.
  • Missing data were addressed using multiple imputation by chained equations.
  • Comorbidity clusters were identified through hierarchical clustering.
  • Predictors of lung function changes were assessed using regression and random forest models.
  • 17,448 DOE former workers participated, with 20.9% diagnosed with COPD.
  • Four comorbidity clusters were found, varying in the prevalence of cardiovascular diseases and lung cancer.
  • Age at hire, welding fume exposure, and silica exposure were significant predictors of lung function changes.
  • Smoking had a minimal impact on lung function changes in this cohort compared to the general population.

Abstract

Background 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. Methods 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 (FEV 1 ) and FEV 1 decline. Variable importance scores were used to assess the predictive importance of the predictors. Results 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 FEV 1 change or decline. Age at hire, welding fume exposure, and silica exposure were significant predictors of both FEV 1 changes and decline. Age at initial exam and baseline FEV 1, 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 FEV 1 change and decline in this cohort. Conclusion Clusters of COPD related comorbidities were identified. The most important predictors of lung function changes and decline were FEV 1 , 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.

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Cite This Study

Howard et al. (2026) studied this question.

synapsesocial.com/papers/698435e5f1d9ada3c1fb540ahttps://doi.org/10.7717/peerj.20696
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