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Record W4408808759 · doi:10.1016/j.ecoenv.2025.118076

Skin conditions associated with dermal exposure to oil spill chemicals among Deepwater Horizon disaster response and cleanup workers

2025· article· en· W4408808759 on OpenAlexaff
Dazhe Chen, Kaitlyn G. Lawrence, Patricia A. Stewart, Melanie Gorman Ng, Mark Stenzel, John W. Cherrie, Kate Christenbury, William B. Jackson, Lawrence S. Engel, Dale P. Sandler

Bibliographic record

VenueEcotoxicology and Environmental Safety · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Environmental Health SciencesNational Institutes of Health
KeywordsDeepwater horizonOil spillEnvironmental scienceEnvironmental healthEnvironmental chemistryToxicologyEnvironmental engineeringChemistryMedicineBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Previous studies have associated oil spill response and cleanup (OSRC) work with skin symptoms, but evidence is lacking on the specific exposure agents that contributed to these skin effects. OBJECTIVES: We investigated OSRC-related exposures, including dermal exposure to specific chemical agents, in relation to acute and longer-term skin conditions among the 2010 Deepwater Horizon (DWH) OSRC workers. METHODS: At GuLF Study enrollment, workers reported duration of work, jobs performed, and skin contact with crude oil/tar, dispersants, and decontamination chemicals. Cumulative dermal exposure to polycyclic aromatic hydrocarbons (PAHs) from oil/tar was estimated based on the "GuLF DREAM model". We used Poisson regression with robust standard errors to evaluate associations of exposures with prevalent skin conditions during spill cleanup and at enrollment (1-3 years later) and incident eczema diagnoses after the start of OSRC work. We examined modification of associations between exposures and prevalent conditions by use of rubber/synthetic gloves. RESULTS: Duration of OSRC work was positively associated with skin conditions and eczema diagnoses (p-trend<0.01). Workers in operations, response, and decontamination jobs had higher skin condition prevalence (during cleanup: PR range=3.13-4.51; at enrollment: PR range=2.20-2.94) and eczema risk (RR range=1.44-1.89) compared to support workers. After adjusting for co-exposures, we saw associations of skin conditions during cleanup with dermal exposure to oil/tar (PR=3.41, 95 %CI: 3.14, 3.69), decontamination chemicals (PR=1.55, 95 %CI: 1.46, 1.64), dispersants (PR=1.44, 95 %CI: 1.33, 1.57), and PAHs (p-trend<0.01). These associations remained apparent at enrollment. Eczema diagnosis was associated with exposure to oil/tar (RR=1.56, 95 %CI: 1.20, 2.04) and PAHs (Tertile 3 vs. 1: PR=1.33, 95 %CI: 0.86, 2.07). Effect estimates were on average 21 % lower among workers who used rubber/synthetic gloves. CONCLUSIONS: Duration of work, working in non-support jobs, and dermal exposure to oil/tar, dispersants, decontamination chemicals, and PAHs were associated with acute and longer-term skin effects among the DWH OSRC workers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.002
GPT teacher head0.191
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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