Exposure patterns among coast guard responders to the Deepwater Horizon Oil Spill: A latent class analysis

Matthew O. Gribble*, Taj Keshav, Hristina Denic-Roberts, Lawrence S. Engel, Jennifer A. Rusiecki

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The Deepwater Horizon Oil Spill was an environmental crisis for which multiple groups, including the United States Coast Guard (USCG), provided emergency response services. A cohort of 5,665 USCG oil spill responders completed postdeployment surveys eliciting information on a variety of topics, including oil spill-related exposures and experiences. Our objective was to determine the most common exposure patterns among USCG responders. Methods: We used latent class analysis based on six indicator variables reflecting different aspects of the responders' experiences: exposure to oil, exposure to engine exhaust fumes or carbon monoxide, hand sanitizer use, sunblock use, mosquito bites, and level of anxiety. We validated our interpretation of these latent classes using ancillary variables. Results: The model distinguished four distinct exposure profiles, which we interpreted as "low overall exposure" (prevalence estimate = 0.18), "low crude oil/exhaust and moderate time outdoors/anxiety (prevalence estimate = 0.18), "high crude oil/exhaust and moderate time outdoors/anxiety" (prevalence estimate = 0.25), and "high overall exposure" (prevalence estimate = 0.38). The validation analysis was consistent with our interpretation of the latent classes. Conclusions: The exposure patterns identified in this analysis can help inform future studies of the health impacts of exposure mixtures among USCG oil spill responders.

Original languageEnglish
Pages (from-to)E211
JournalEnvironmental Epidemiology
Volume6
Issue number3
DOIs
StatePublished - 2 Jun 2022
Externally publishedYes

Keywords

  • Disaster response
  • Exposure science
  • Latent variables
  • Occupational health
  • Structural equation modeling

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